Spotlight has been able to find text extracted from images using Live Text, and the names of objects recognised using Visual Look Up, for some years now. This article considers how you can and cannot search for those. Although this might seem obvious, it’s more confusing than it appears and could mislead you into thinking that Spotlight indexing or search isn’t working.

As detailed in yesterday’s account of Live Text, text recognition in images uses a lexicon to match words rather than proceeding in single characters. Terms assigned to recognised objects are also words. Thus, when searching for either type you should use words as much as possible to increase the chances of success.

Global Spotlight

Type a word like cattle into Spotlight’s search window and you can expect to see a full selection of documents and images containing the term or cattle objects. Those include images containing the word, and images containing objects identified as cattle, but don’t include images in PDF files, as they’re not analysed by mediaanalysisd, so don’t undergo character or object recognition in the same way that regular images like JPEGs do.

The Finder’s Find

Open a new window in the Finder and turn it into a Spotlight search using the Finder’s File menu Find command. In its search box at the top right, type in a word like cattle and in the popup menu select the lower option, Content contains. Press Return and the search box will now display ANY cattle. Then set the Kind to Image in the toolbar above search results, to narrow results down to image files. You should then see a full listing of image files that either contain the word cattle, or contain objects identified by image analysis as being cattle. Note how many of those appear.

Reconfigure the search so the search box is empty, and there are two rows of search settings: the first can remain the same as Kind is Image, but set the second to Contents contains cattle. Those images containing objects identified as cattle will now vanish, leaving images containing the word cattle still listed.

To understand the difference between these, you can save those two Find windows and read the underlying terms used for each search. The search that returned text obtained by both Live Text and Visual Look Up used
(((** = "cattle*"cdw)) && (_kMDItemGroupId = 13))
while the one excluding Visual Look Up used
(((kMDItemTextContent = "cattle*"cdw)) && (_kMDItemGroupId = 13))
instead. We can transfer those to the mdfind command tool to explore further.

mdfind

To use those as search predicates with mdfind we’ll translate them into more general form,
mdfind "(** == 'cattle*'cdw) && (kMDItemContentTypeTree == 'public.image'cd)"
should return both Live Text and Visual Look Up, while
mdfind "(kMDItemTextContent == "cattle*"cdw) && (kMDItemContentTypeTree == 'public.image'cd)"
only returns Live Text results.

The term (** == 'cattle*'cdw) has a special meaning because of its wild card **, and will return any match found in the metadata and contents of files. kMDItemTextContent is similar, but confined to text content, which doesn’t include the names of objects recognised in an image, and Apple doesn’t reveal whether there’s an equivalent that does.

Code search

Although apps can call mdfind to perform searches, they normally use NSMetadataQuery with an NSPredicate instead. That isn’t allowed to use a predicate like
** ==[cdw] "cattle"
so can’t search for objects identified using Visual Look Up. When it uses the substitute of
kMDItemTextContent ==[cdw] "cattle"
it also fails to find text obtained using Live Text. So the only way to search for recovered text in a compiled app is to call mdfind.

Timing

Searching for text obtained using Live Text, or object labels obtained using Visual Look Up, depends entirely on those being added to the Spotlight indexes on the volume. Observations of the log demonstrate just how quickly normal indexing by mdworker processes takes place. Here’s an example for a screenshot:
06.148292 com.apple.screencapture Write screenshot to temporary location
06.151242 [0x6000009bc4b0] activating connection: mach=true listener=false peer=false name=com.apple.metadata.mds
06.162302 com.apple.screencapture Moving screenshot to final location
06.169565 user/501/com.apple.mdworker.shared.1E000000-0600-0000-0000-000000000000 internal event: WILL_SPAWN, code = 0
06.198868 com.apple.DiskArbitration.diskarbitrationd mdworker_shared [7266]:118071 -> diskarbitrationd [380]
06.226997 kernel Sandbox apply: mdworker_shared[7266]

In less than 0.1 second an mdworker process has been launched and granted the sandbox it uses to generate metadata and content for Spotlight’s indexes. Unfortunately, that doesn’t include any Live Text or Visual Look Up content, which are generated separately by mediaanalysisd later. It’s hard to estimate how much later, although you shouldn’t expect to find such recovered text for several hours or days, depending on the opportunities for mediaanalysisd to perform background image analysis for this purpose.

Summary

• Words recovered from images (not those in PDF files, though) and objects recognised in them can be found by Spotlight search. For best results, choose words rather than letter fragments for search terms.
• Global Spotlight gives full access to both types.
• The Finder’s Find gives full access to both only when the search term is entered in the search box as Content contains, otherwise it may exclude objects recognised.
• mdfind can give full access to both types only when using a wildcard term such as (** == 'cattle*'cdw).
• NSMetadataQuery currently appears unable to access either type. Call mdfind instead.
• The delay before either type is added to the volume Spotlight indexes can be hours or days.

Apple has just released an update to XProtect for all supported versions of macOS, bringing it to version 5310. As usual, Apple doesn’t release information about what security issues this update might add or change.

This version adds a single new detection rule for MACOS.SOMA.AUENA, further extending its coverage of Soma/Amos.

You can check whether this update has been installed by opening System Information via About This Mac, and selecting the Installations item under Software.

A full listing of security data file versions is given by SilentKnight and SystHist for El Capitan to Tahoe available from their product page. If your Mac hasn’t yet installed this update, you can force it using SilentKnight or at the command line.

If you want to install this as a named update in SilentKnight, its label is XProtectPlistConfigData_10_15-5310

Sequoia systems only

This update has already been released for Sequoia via iCloud. If you want to check it manually, use the Terminal command
sudo xprotect check
then enter your admin password. If that returns version 5310 but your Mac still reports an older version is installed, you may be able to force the update using
sudo xprotect update

On the face of it, watercolour painting should be the simplest of all the more popular painting media. The paper is both support and ground, the paint layer is thin, with a little binder of gum arabic and a diluent of plain water. Although some have tried using varnish and other protective layers, in the great majority of watercolour paintings, that’s all there is.

In practice, though, as anyone who has taken watercolour painting seriously knows, there’s a great deal more to it. Much of that is hard to see and can only be inferred from images of watercolour paintings.

Raphael’s The Miraculous Draft of Fishes (c 1515-16) is among the earliest large paintings made using opaque watercolour. Because of limitations in the manufacture of paper at the time, it was made on many sheets that have been mounted on canvas. At around 3 x 4 metres (10.5 x 13 feet), it’s huge by any standards, and even today would probably need to be painted on multiple sheets and mounted on added support.

Over three centuries later, the Pre-Raphaelite artist Marie Spartali Stillman painted her watercolours in layers, using a combination of transparent and opaque watercolour on paper that had been hot-pressed to give it a satin-smooth finish. When re-wetted with another layer of wet paint, watercolour usually becomes liquid again, resulting in the layers mixing. Great care and skill is required to apply wet watercolour on dry paint in the way that she did. Even then some paintings simply don’t work, the layers mix and that attempt has to be discarded. When successful, the end result can resemble layered oil paints, which don’t suffer the same problem when dry paint is overpainted.

The Childhood of Saint Cecily (1883) was one of the last paintings Stillman composed when she lived in Florence, as reflected in its idealised Tuscan background. As with so many paintings of saints, it departs from even the most inventive of hagiographies, here for the patron saint of music, Cecilia. The saint is shown playing a harp-like psaltery, while an angel adjusts the garland on her head. She has worked subtle patterns into the blue fabric on the arm of the angel, and in the side of the instrument. Flowers and hair have fine detail with sharp highlights, just as might be seen with oils.

Love’s Messenger (1885) is probably the finest of her single-figure paintings, and was her most successful ‘problem picture’. The woman stands by her embroidery at an outside window. On her right hand is a messenger dove/pigeon, to which a letter is attached. She clutches that letter to her breast with her left hand, implying that its contents relate to matters of the heart. The dove is being fed corn, which could either be its reward for having reached its destination (thus the woman is the recipient of the message), or preparation for its departure (she is the sender). Despite being exhibited at the Grosvenor Gallery in 1885, and elsewhere, this painting didn’t sell until after she had reworked the background in the 1890s, which must have been a feat in itself.

A detail view of Love’s Messenger shows how her watercolour technique results in a facture more closely resembling that of oils, although this painting is an extreme example with its use of tempera too. This was accomplished by using transparent watercolours more like oil glazes, and gouache (opaque watercolour) for details.

Her portrait of Beatrice (1896) refers to Dante’s Vita Nuova, through Dante Gabriel Rossetti’s popular translation into English. In this her first version, she shows Dante’s beloved Beatrice lost in contemplation while reading, an intimate insight set firmly in the Pre-Raphaelite mediaeval. This was exhibited at the New Gallery later that year.

This detail view of Beatrice provides more insight into her exacting technique.

Over the same period, other artists were developing techniques for use on cold-pressed paper with its coarser texture.

At a time when most watercolour painting was still disparagingly considered to be ‘drawing’ for routine topographic views, Alexander Cozens developed specialist techniques, such as keeping ‘reserved space’ to let his white paper ground show through, wet on wet as well as wet on dry application of paint, and scratching out. He also employed both transparent and opaque paints for different effects.

JMW Turner did a great deal to advance both technique and the critical reception of large watercolour works painted in the studio, although even today his oils are much better known, with a few exceptions such as his sublime paintings of the Rigi.

Towards the end of the nineteenth century, Winslow Homer earned his place as one of the greatest watercolour painters of America during a period spent in a fishing community in north-east England. The advanced techniques which he used are shown well in The Watcher, Tynemouth (1882), and include both transparent and opaque paints, rewetting and blotting to remove paint for highlights, scraping, application of wax to resist the adherence of paint, and the use of pure gum solution as a glaze. In this case, his paper is only lightly textured, though.

Perhaps the greatest exponent of these techniques was another American, John Singer Sargent.

Sargent’s most radical watercolours were painted when he stayed with various friends in the Bellevue Hotel, at the top of the Simplon Pass, in the summers before the First World War. While his family and friends whiled away their days in leisure, Sargent got them to pose for a unique series of informal portraits. They may have been reclining at leisure, but Sargent took those watercolours very seriously, and deployed an amazing array of techniques. Among the finest is his Simplon Pass: The Tease from the summer of 1911.

One of his most unusual techniques, used extensively here, is wax resist. Before applying paint, Sargent scribbled over areas intended to be vegetation, using a soft wax crayon, probably made from beeswax. On fairly rough paper, that wax is deposited unevenly, and when painted over using watercolour it shows the white paper through. This creates disruptive patterns of near-white in the midst of the greens, and a superb textural effect, as shown in this detail.

In complete contrast, Edward Robert Hughes’ Night with her Train of Stars of the following year has been painted in a controlled and meticulous manner, although it too uses advanced techniques, particularly in the sky and background. I suspect that some of the latter may have relied on the scattering of salt grains to impart its fine texture. In other passages he has allowed different colours to rewet and blur what would otherwise be sharp edges.

Of course, AI can now mimic these when provided with suitable original material to plagiarise. But there’s still nothing like an original painted by a master.

Live Text and Visual Look Up are recent features in macOS, first appearing in Monterey nearly four years ago. As that immediately followed Apple’s short debacle over its now-abandoned intention to scan images for CSAM, most concerns have been over whether these features send details of images to Apple.

Although recent Intel Macs also support both these features, they don’t have the special hardware to accelerate them, so are far slower. For this walkthrough, I’ll only present information from Apple silicon Macs, in particular for the M4 Pro chip in a Mac mini.

Initiation

When an image is opened from disk, the VisionKit system starts up early, often within 0.1 second of it starting to open. Its initial goal is to segment the image according to its content, and identify whether there’s any part of it that could provide text. If there is, then Live Text is run first so you can select and use that as quickly as possible.

In the log, first mention of this comes from com.apple.VisionKit announcing
Setting DDTypes: All, [private]
Cancelling all requests: [private]
Signpost Begin: "VKImageAnalyzerProcessRequestEvent"

It then adds a request to Mad Interface, that’s the mediaanalysisd service, with a total method return time, and that’s processed with another signpost (a regular log entry rather than a Signpost):
Signpost Begin: "VisionKit MAD Parse Request"

com.apple.mediaanalysis receives that request
[MADServicePublic] Received on-demand image processing request (CVPixelBuffer) with MADRequestID
then runs that
Running task VCPMADServiceImageProcessingTask

This is run at a high Quality of Service of 25, termed userInitiated, for tasks the user needs to complete to be able to use an app, and is scheduled to run in the foreground. Next Espresso creates a plan for a neural network to perform segmentation analysis, and the Apple Neural Engine, ANE, is prepared to load and run that model. There’s then a long series of log entries posted for the ANE detailing its preparations. As this proceeds, segmentation may be adjusted and the model run repeatedly. This can involve CoreML, TextRecognition, Espresso and the ANE, which can appear in long series of log entries.

Text recognition

With segmentation analysis looking promising for the successful recognition of text in the image, LanguageModeling prepares its model by loading linguistic data, marked by com.apple.LanguageModeling reporting
Creating CompositeLanguageModel ([private]) for locale(s) ([private]): [private]
NgramModel: Loaded language model: [private]
and the appearance of com.apple.Lexicon. An n-gram is an ordered sequence of symbols, that could range from letters to whole words, and the lexicon depends on the language locales. In my case, two locales are used, en (generic English) and en_US (US English).

At this point, mediaanalysisd declares the VCPMADVIDocumentRecognitionTask is complete, and runs a VCPMADVIVisualSearchGatingTask, involving com.apple.triald, TRIClient, PegasusKit and Espresso again. Another neural network is loaded into the ANE, and is run until the VCPMADVIVisualSearchGatingTask is complete and text returned.

The next task is for the translationd service to perform any translations required. If that’s not needed, VisionKit reports
Translation Check completed with result: NO, [private]
These may be repeated with other image segments until all probable text has been discovered and recognised. At that stage, recognised text is fully accessible to the user.

Object recognition

Further image analysis is then undertaken on segments of interest, to support Visual Look Up. Successful completion of that phase is signalled in Preview by the addition of two small stars at the upper left of its ⓘ Info tool. That indicates objects of interest can be identified by clicking on that tool, and isn’t offered when only Live Text has been successful. VisionKit terms those small buttons Visual Search Hints, and remains paused until the user clicks on one.

Visual Search Hints

Clicking on a Visual Search Hint then engages the LookupViewService, and changes the state from Configured to Searching. VisionKit records another
Signpost Begin: "VisionKit MAD VisualSearch Request"
and submits a request to MAD for image processing to be performed. If necessary, the kernel then brings all P cores online in preparation, and the ANE is put to work with a new model.

PegasusKit then makes the first off-device connection for assistance in visual search:
Querying https: // api-glb-aeus2a.smoot.apple.com/apple.parsec.visualsearch.v2.VisualSearch/VisualSearch with request (requestId: [UUID]) : (headers: ["grpc-message-type": "apple.parsec.visualsearch.v2.VisualSearchRequest", "Content-Type": "application/grpc+proto", "grpc-encoding": "gzip", "grpc-accept-encoding": "gzip", "X-Apple-RequestId": "[UUID]", "grpc-timeout": "10S", "User-Agent": "PegasusKit/1 (Mac16,11; macOS 15.6 24G84) visualintelligence/1"]) [private]

When the visual search task completes, information is displayed about the object of interest in a floating window. Visual Look Up is then complete, and in the absence of any further demands, the ANE may be shut down to conserve energy, and any inactive CPU cluster likewise:
ANE0: power_off_hardware: Powering off... done
PE_cpu_power_disable>turning off power to cluster 2

Key points

• Image analysis starts shortly after the image is loaded.
• Central components are VisionKit and mediaanalysisd, MAD.
• In Apple silicon Macs, extensive use is made of the Apple Neural Engine throughout, for neural network modelling.
• Most if not all is run at high QoS of 25 and in the foreground, for performance.
• Segmentation analysis identifies areas that might contain recoverable text.
• Segments are then analysed, using language modelling for appropriate locales and languages, and lexicons, to return words rather than fragmented characters.
• When Live Text is ready, segments are then analysed for recognisable objects. When that’s complete, each is marked by a Visual Search Hint.
• Clicking on a Visual Search Hint initiates a network connection to provide information about that object, displayed in a floating window.

Dante lost consciousness just before he was expecting to be ferried across the River Acheron in Charon’s boat, from Hell’s Gate to its First Circle.

Botticelli’s Map of Hell from 1480-90 shows these stages of their descent at the very top: highest are the woods through which Dante was wandering when he encountered the three wild beasts. At the left, Virgil led Dante down to the area in which the cowards are trapped, neither being allowed admittance to Heaven, nor to Hell. Charon’s boat then crosses the River Acheron, shown in blue, taking Dante and his guide Virgil to the First Circle of Limbo.

Dante is woken by thunder, and realises that he’s on the edge of the abyss that is Hell. Virgil leads him down into darkness, where there is no grief or pain, and explains that the multitude there never sinned at all, but none was baptised in faith as they had lived before the Christian era. This is where Virgil’s ghost now inhabits, for despite his merit and attainments, he never revered the Christian God.

Dante asks whether any of those in Limbo, as this circle is known, have ever been blessed and been able to leave. This allows Virgil to explain the Harrowing of Hell by Christ after his crucifixion. This occurred not long after Virgil’s death: following his crucifixion, Jesus Christ descended into Hell, where he reached the First Circle, blessed and liberated from it the many Old Testament figures who had been faithful to the God of the Jews, also known as Anastasis.

The descent of Christ into Limbo and his Harrowing of Hell was a popular theme in religious painting until the end of the Renaissance, and would have been familiar to Dante’s readers. Here is a small selection of some of the finest paintings of this, from 1530 to 1600.

Virgil then introduces the great classical writers: Homer, Horace the satirist, Ovid and Lucan. Together with Virgil, these five invite Dante to join them as the sixth among the ranks of great writers, in an ambitious piece of self-promotion.

The group walk on to the Dome of Light, and further to a castle surrounded by seven curtain walls and a moat. When they enter that they see many ancient heroes, including Electra, Hector, Aeneas, and other figures from classical history and legend. Next Dante notices a group of philosophers, including Socrates, Plato and others. Finally, he sees other learned figures from the past, including Euclid, Ptolemy and Hippocrates.

Here Dante and Virgil bid farewell to the spirits of those great figures as they move onward to the next circle.

The artists

Domenico di Pace Beccafumi (1486–1551) was one of the last of the Sienese School of Painting, which contrasted with the better-known Renaissance painting of Florence. He has been aptly summarised as “a mediaeval believer of miracles awaking in Renaissance reality.”

William Blake (1757–1827) was a British visionary painter and illustrator whose last and incomplete work was an illustrated edition of the Divine Comedy for the painter John Linnell. Most of his works shown in this series were created for that, although he did draw and paint scenes during his earlier career. I have a major series on his work here.

Sandro Botticelli (1445–1510) was one of the leading painters of the early Southern Renaissance, working in his native city of Florence. In addition to his huge egg tempera masterpieces of Primavera (c 1482) and The Birth of Venus (c 1485), he was a lifelong fan of Dante’s writings. He produced drawings that were engraved for the first printed edition of the Divine Comedy in 1481, but those weren’t successful, most copies only having two or three of the 19 that were engraved. He later began a manuscript illustrated edition on parchment, but few pages were ever fully illuminated.

Jan Brueghel the Elder (1568–1625) was the son of Pieter Brueghel the Elder, who specialised in floral still lifes. The painting shown above was made in collaboration with the figure painter Hans Rottenhammer, a relationship that lasted between 1595-1610. At the time of this painting, Brueghel had returned to Antwerp, and Rottenhammer was in Venice.

Pablo de Céspedes (1538–1608) was a Spanish polymath from Córdoba, who was an accomplished painter, poet and architect who worked for twenty years in Italy, largely because he fell foul of the Inquisition of Valladolid in Spain. He was also a linguist and theologian.

Gustave Doré (1832–1883) was the leading French illustrator of the nineteenth century, whose paintings are still relatively unknown. Early in his career, he produced a complete set of seventy illustrations for translations of the Inferno, that were first published in 1857 and continue to be used. These were followed in 1867 by more illustrations for Purgatorio and Paradiso. This article looks at his paintings.

Hans Rottenhammer (1564–1625) was a German figure painter who worked in Italy from 1593-1606. Later during that period, when he was in Venice, he collaborated with Jan Brueghel the Elder on the work shown above. He was probably responsible for the early training of Adam Elsheimer, and for introducing him to the technique of painting on a small scale using oil on copper plate.

Jacopo Tintoretto (c 1518-1594) was one of the three grand masters working in Venice in the middle and late sixteenth century, alongside the more senior figure of Titian, and Paolo Veronese. Primarily a religious painter, I have looked in detail at his major works and biography. His painting shown above was made to accompany his Crucifixion for the church of San Cassiano in Venice.

References

Wikipedia
Danteworlds

Robin Kirkpatrick (trans) (2012) Dante, The Divine Comedy, Inferno, Purgatorio, Paradiso, Penguin Classics. ISBN 978 0 141 19749 4.
Richard Lansing (ed) (2000) The Dante Encyclopedia, Routledge. ISBN 978 0 415 87611 7.
Guy P Raffa (2009) The Complete Danteworlds, A Reader’s Guide to the Divine Comedy, Chicago UP. ISBN 978 0 2267 0270 4.
Prue Shaw (2014) Reading Dante, From Here to Eternity, Liveright. ISBN 978 1 63149 006 4.

I hope that you enjoyed Saturday’s Mac Riddles, episode 320. Here are my solutions to them.

1: What ET wants is a call coming to the Mac.

2: A glass to enlarge among the liquid.

3: Daybook you might already have started elsewhere.

The common factor

I look forward to your putting alternative cases.

Six years ago, in July 2019, Macs came closer to disaster than at any time before or since. Millions of Mac users around the world had, at some time or other, installed Zoom conferencing software, and in doing so had unknowingly put their Macs at risk. For their convenience, the old Zoom installers of that time also installed a hidden web server that was left running. That was capable of reinstalling the Zoom client, and had been discovered to contain an easily exploitable vulnerability that exposed all those Macs to remote attacks.

The only solution was for Apple to harness its old Malware Removal Tool, MRT, to remove that web server from all Macs before they came under attack. Although MRT had been widely criticised for what others considered to be weakness, on this occasion it proved its value. MRT version 1.45 was released by Apple on 10 July 2019, and averted that potential catastrophe.

Three years later, in the summer of 2022, Apple replaced MRT with its successor, XProtect Remediator or XPR, which has been vastly improved, and still contains the remnants of MRT in its MRTv3 scanning module. As Apple documents almost nothing about XPR, it has been up to others to dive deep inside it, among them Koh M Nakagawa, @tsunek0h, of FFRI Security. While others have merely scratched the surface, he has just presented a superb and deep account of XPR at Black Hat USA. You can download the slides for his presentation from here.

Status_code 30 PlugInCanceled

If you check XPR scans using SilentKnight or XProCheck, you’ll be aware that for many months some of them are terminated prematurely with a status_code of 30 and the message PlugInCanceled. This most commonly affects Adload scans, and still occurs in beta-releases of macOS 26 Tahoe. According to Koh’s research, the Adload scanning module alone contains over 1,000 Yara detection rules, accounting for the long time it takes whenever XPR runs a set of scans.

Before XPR started terminating its scans as it does now, a full set could take an hour or more, so XPR has started using a timer. If the scan exceeds the time allowed, then it will be abruptly terminated, resulting in this status_code and message. There’s nothing the user can do to avoid it, and we’re surprised that XPR continues to exhibit this behaviour.

Laptop Macs

The other significant limitation in XPR affects those using MacBook Pro, MacBook Air and MacBook models. Because XPR scans take a substantial amount of energy, even when run almost entirely on the E cores of Apple silicon Macs, daily full scans will only be run when those laptops are using mains power, and won’t be run at all on battery.

As XPR scans are also normally run when a Mac is awake but only under a light load, it’s possible for a laptop to go several days without running an XPR scan. The only solution is to leave it connected to mains power, awake and doing little else for an hour or so, when it should seize the opportunity to catch up with that and other important background tasks with similar requirements.

Unfortunately, XPR won’t warn you that it hasn’t run any scans for several days, but SilentKnight and XProCheck will.

In the first of these two articles showing masterly landscape paintings of summer storms, I had reached John Constable in the early 1830s.

Of Constant Troyon’s early paintings the most outstanding must be The Approaching Storm from 1849. Set on a river worthy of Constable, two anglers appear to be readying themselves for the torrential rain heading towards them, while others still wander in the last patch of sunshine on the far bank.

Jules Noel’s Panorama of the Town of Dieppe (c 1865) shows a large picnic party on the cliffs overlooking the town of Dieppe on the coast of northern France. These families seem blissfully unaware of the dark clouds and heavy rain already over the land to the right.

One of the finest and most dramatic of Albert Bierstadt’s paintings from his second expedition to the West in 1863 is this of A Storm in the Rocky Mountains, Mt. Rosalie from 1866. Its foreground shows a pastoral valley floor with a native American camp, in mottled light. Some people and their animals are seen making haste to return from the pastures to the shelter of the camp. A small rocky outcrop has trees straggling over it, which are silhouetted against the brilliant sunlight on the lake behind, in the middle distance.

Behind the lake the land rises sharply, with rock crags also bright in the sunshine. In the background the land is blanketed by indigo and black storm-clouds. Those are piled high, obscuring much of Mount Rosalie, but its ice-clad peaks show proud, high up above the storm, with patches of blue sky above and beyond them. A single large bird, an eagle perhaps, is seen in silhouette, high above the lake.

It was Volodymyr Orlovsky’s painting of Harvest on the steppe in Ukraine, in 1882, that apparently earned the artist’s promotion to Professor in the Imperial Academy.

Few artists ever get to witness tropical storms, but after his time painting winter storms at Cullercoats in England, Winslow Homer witnessed and painted this Hurricane, Bahamas in 1898.

In 1903, Gustav Klimt spent his summer holiday at Attersee with his partner’s family, where he painted this landscape of an Approaching Thunderstorm. Many of his other landscape paintings made during his summers away show no sky at all, but this is an exception.

Thunderstorm at Vernouillet is an atmospheric landscape painted by Pierre Bonnard in 1908, or the following year. Vernouillet is on the southern bank of the river Seine, midway between the centre of Paris and Monet’s property at Giverny.

The young Canadian artist and canoeist Tom Thomson excelled in rapid sketching in oils, with several witnessed accounts of him dashing off a painting in little more than fifteen minutes. As a result he was able to capture many transient effects, such as the passing thunderstorm in Thunderhead from 1912-13.

If you’re fortunate, the storm is soon gone, its humid air blows away, and summer returns.

Arkhyp Kuindzhi specialised in painting in spectacular light. After a Thunderstorm from 1879 is one of his oil sketches capturing the brilliant colour and light following heavy summer rain on the steppe.

According to scientific tradition, we first observe then experiment. If you proceed to the latter before you understand how a system behaves, then you’re likely to labour under misapprehensions and your trials can become tribulations. Only when a system is thoroughly opaque and mysterious can we risk attempting both together.

That’s the case for Spotlight, which despite its name does everything but shine any light on its mechanisms. It presents itself in several guises, as a combination of web and local search (), as local search using terms limited in their logical operators (Finder’s Find), as full-blown predicate-based local search (mdfind), as in-app file search (Core Spotlight), and the coder’s NSMetadataQuery and predicates. It relies on indexes scattered across hundreds of binary files, and runs multiple processes, while writing next to nothing in the log.

Last week’s code-doodling has been devoted to turning the Spotlight features in Mints into a separate app, SpotTest, so I can extend them to allow testing of different volumes, and search for text that has been derived from images. Those are proving thorny because of Spotlight’s unpredictable behaviour across different Macs running Sequoia.

Every week I search for screenshots to illustrate another article on Mac history. When using my old iMac Pro where most of them are stored, Spotlight will find many images containing search terms from the text shown within them, even from ancient QuickDraw PICT images, demonstrating that text is being recovered using Live Text’s optical character recognition. When I try to repeat this using test images on an Apple silicon Mac, Spotlight seems unable to recognise any such recovered text.

Image analysis on Macs has a stormy history. In a well-intentioned gaffe four years ago, Apple shocked us when it declared it was intending to check our images for CSAM content. Although it eventually dropped that idea, there have been rumours ever since about our Macs secretly looking through our images and reporting back to Apple. It didn’t help that at the same time Apple announced Live Text as one of the new features of macOS Monterey, and brought further image analysis in Visual Look Up.

Although I looked at this in detail, it’s hard to prove a negative, and every so often I’m confronted by someone who remains convinced that Apple is monitoring the images on their Mac. I was thus dragged back to reconsider it in macOS Sonoma. What I didn’t consider at that time was how text derived from Live Text and image analysis found its way into Spotlight’s indexes, which forms part of my quest in SpotTest.

This doesn’t of course apply to images in PDF documents. When I looked at those, I concluded: “If you have PDF documents that have been assembled from scans or other images without undergoing any form of text recognition, then macOS currently can’t index any text that you may still be able to extract using Live Text. If you want to make the text content of a PDF document searchable, then you must ensure that it contains its own text content.” I reiterated that in a later overview.

My old images aren’t PDFs but QuickDraw PICTs, TIFFs, PNGs and JPEGs, many from more than 20 years ago. When the circumstances are right, macOS quietly runs Live Text over them and stores any text it recovers in Spotlight’s indexes. It also analyses each image for recognisable objects, and adds those too. These happen more slowly than regular content indexing by mdworker, some considerable time after the image has been created, and have nothing whatsoever to do with our viewing those images in QuickLook or the Finder, or even using Live Text or Visual Look Up ourselves.

There are deeper problems to come. Among them is discovering the results of image recognition as can be revealed in the command line using a search such as
mdfind "(** == 'cattle*'cdw) && (kMDItemContentTypeTree == 'public.image'cd)"
to discover all images that have been recognised as containing cattle. There’s no equivalent of the first part of that when calling NSMetadataQuery from Swift code, and a predicate of
kMDItemTextContent CONTAINS[cd] \"cattle\"
will only discover text recovered by Live Text, not the names of objects recognised within an image.

What started as a quick doodle is now bogged down in the quirks of Spotlight, which defies the scientific method. Perhaps it’s time for a little sorcery.

As we near the grain harvest in the northern hemisphere, so come the summer storms. Just as the farmworkers have ventured out into the fields of dry, ripe wheat, the heavens above become inky black as towering clouds bring torrential rain and rolling thunder. This weekend we’re in for more than our fair share, in the company of many of the great landscape artists.

At the dawn of modern landscape painting, Giorgione’s The Tempest from about 1504-8 centres on an approaching storm. The sky is filled with inky dark clouds, and there’s a bolt of lightning in the distance. The figures here imply an underlying narrative, but today that can only be speculated.

Nicolas Poussin’s setting of a Landscape during a Thunderstorm with Pyramus and Thisbe (1651) shows the city of Babylon in the distance, along a picturesque and pastoral valley. But the peacefulness of this landscape has been transformed by the sudden arrival of a thunderstorm: the gusty wind is already bending the trees, and near the centre of the view a large branch has broken with its force. Two bolts of lightning make their way to the hills below.

There’s frantic activity in response not only to the storm, but to a lioness attacking a horse, whose rider has fallen. An adjacent horseman is about to thrust his spear into the back of the lioness, while another, further ahead, is driving cattle away from the scene. Others on foot, and a fourth horseman, are scurrying away, driven by the combination of the lioness and the imminent storm.

In the foreground, Pyramus lies dying, his sword at his side, and his blood flowing freely on the ground, down to a small pond. Thisbe has just emerged from sheltering in the cave, has run past the bloodied shawl at the right, and is about to reach the body of her lover.

Still attributed to Poussin’s pupil and brother-in-law Gaspard Dughet, this Landscape with Lightning from 1667-69 lacks the subtlety and finesse of the master himself, but shows a bolt of lightning striking ground and setting a fire in the countryside. In the foreground, a couple flee from among trees being shattered by the strong gusts brought by the storm.

The founding fathers of landscape painting in the Northern Renaissance weren’t to be outdone by those of the south: Aelbert Cuyp’s Thunderstorm over Dordrecht from about 1645 is amazingly effective and accurate, considering it was painted more than two centuries before anyone saw high-speed photographic images of lightning.

In Claude-Joseph Vernet’s series The Four Times of Day from 1757, by Midday the clouds of early morning have built into squally showers. While two people are fishing with nets, a couple with an infant and a dog, in the left foreground, are hurrying for shelter before heavy rain starts. Behind them a shepherd has brought their flock under a grove of trees. Seagulls are wheeling and soaring in the strengthening wind.

George Morland’s Before a Thunderstorm (1791) shows well the rising wind and threatening sky just before a summer storm strikes.

When he was only sixteen, in 1821, Samuel Palmer painted this watercolour sketch At Hailsham, Sussex: a Storm Approaching, a faithful representation of Cumulus congestus building in the distance.

Palmer’s watercolour Summer Storm near Pulborough, Sussex from about 1851 refers to Dutch landscape painting, but set in a very Kentish context. A storm is seen approaching the rolling countryside near Pulborough, now in West Sussex, in the south-east of England. On the left, in the middle distance, a small bridge leads across to a hamlet set around a prominent windmill, whose blades are blurred as they’re driven by the wind. Beyond that mill are fields of ripening cereal.

John Constable’s half-size and well-developed study for Salisbury Cathedral from the Meadows places an angler in the foreground, as a thunderstorm builds over the Wiltshire countryside behind. Sadly, the fisherman didn’t survive into Constable’s finished painting.

Here are this weekend’s Mac riddles to entertain you through family time, shopping and recreation.

1: What ET wants is a call coming to the Mac.

2: A glass to enlarge among the liquid.

3: Daybook you might already have started elsewhere.

To help you cross-check your solutions, or confuse you further, there’s a common factor between them.

I’ll post my solutions first thing on Monday morning.

Please don’t post your solutions as comments here: it spoils it for others.

To make its graphical interface work, the Mac needed a high-performance graphics system, for which the late Bill Atkinson (1951-2025) and Andy Hertzfeld designed and implemented QuickDraw. When it came to driving printers, though, Steve Jobs licensed the new page description language PostScript from Adobe, where it had just been developed by John Warnock (1940-2023), Charles Geschke (1939-2021) and others. PostScript is a stack-based interpreted language that could take many seconds or even minutes to image a page for printing, so wasn’t practical for doing much else at that time.

In the early 1990s, as desktop publishing became dominant among Mac users and we were all sending one another faxes, several companies recognised the need for a universal document format that could display laid-out text and graphics. Among them was Adobe, where Warnock formulated the aims of what he then referred to as Interchange PostScript or IPS, and so led the development of Portable Document Format. It’s telling that the final sentence of his proposal reads: “In any event corporations should be interested in site-licensing arrangements.”

When the first version of PDF was released in 1993, with its Carousel reader app, it faced competition from other similar ideas, and Adobe found itself competing against products including Farallon’s Replica, and Tumbleweed’s Envoy that gained the support of WordPerfect, then a popular cross-platform word processor. PDF didn’t become dominant until Adobe distributed its reader app free, rather than charging $50 for it as it had initially.

For many years, the only way to create really good PDFs was using Adobe’s Acrobat Distiller app, costing $695 for a single-user licence. That ingested PostScript files, created on the Mac by printing to a file, and transformed them into PDFs that could in turn only be read using Adobe’s software. Although PostScript was by then a prerequisite for all publishing work on Macs, it wasn’t until 1996, when PDF reached version 1.2 in Acrobat 3.0, that it captured the prepress market, which it consolidated in 1998 with the PDF/X-1 standard.

This is Acrobat Distiller 4.0 running on Mac OS 9.1 in early 2001, showing a few of its bewildering array of options for turning PostScript files into PDF.

At the same time, John Warnock’s aspirations for success in enterprise markets were being realised, and PDF steadily became the standard for fixed-format electronic documents, with the support of the US Internal Revenue Service and Adobe’s free cross-platform Acrobat Reader.

When Steve Jobs established NeXT in 1985 he must have become the only person to have licensed PostScript from Adobe twice, as NeXTSTEP adopted Display PostScript as the centrepiece of its graphics, developed collaboratively between NeXT and Adobe. At the time many thought this to be a mistake, as PostScript isn’t as efficient a graphics language as QuickDraw, despite Adobe’s efforts to accelerate it.

When NeXT and Mac merged to form the beginnings of Mac OS X in 1997, Display PostScript was replaced with PDF as the central graphics standard for both display and printing, in what was dubbed Quartz 2D. This was first demonstrated at WWDC in 1999 and lives on today in macOS. At the time, Apple’s in-house PDF engine in Quartz was one of few, alongside Adobe’s.

Prior to Mac OS X, Adobe Acrobat, both in its free viewer form and a paid-for Pro version, had been the de facto standard for reading, printing and working with PDF documents on the Mac. The Preview app had originated in NeXTSTEP in 1989 as its image and PDF viewer, and was brought across to early versions of Mac OS X, where it has remained ever since.

This PDF shows Apple’s original iPod promotional literature from late 2001.

Adobe continued providing its free Acrobat Reader for Mac OS X, here seen in 10.0 Cheetah.

The full paid-for version of Adobe Acrobat provided an extensive suite of editing tools, here in Mac OS X 10.1 Puma in early 2002.

By Mac OS X 10.3 Panther in 2003, Apple was claiming that Preview was “the fastest PDF viewer on the planet”, capable of navigating and searching text within PDF documents “at lightning speed”. This worked with the Mac’s new built-in support for faxing, which rendered received faxes in PDF to make them easier and clearer to access.

This is an early Keynote Quick Reference guide from 2003, viewed in Preview.

At that time, Preview was also able to convert Encapsulated PostScript (EPS) files and raw PostScript to PDF, so they could be saved in the more accessible format, and printed easily.

This page from the 9/11 Commission Report of 22 July 2004 is being viewed in Preview.

Acrobat Distiller remained an important component in Adobe’s paid-for product, even though Mac OS X was capable of generating its own PDFs. It’s seen here in Mac OS X 10.4 Tiger in 2005.

This is Acrobat Pro in 10.4 Tiger in early 2006, showing its long list of supported export formats.

Since those heady days, Preview has been relatively neglected. Revision of both the Quartz PDF engine and its API brought a spate of bugs that only abated with macOS Sierra. Preview has adopted an uncommon model for PDF annotations that often doesn’t work well with other PDF products, but it has remained very popular for completing electronic forms. Then, in macOS Ventura, Apple removed all support for converting EPS and PostScript to PDF, most probably as a result of security concerns, and their progressive disuse.

Although rumours of the death of Preview continue to prove unfounded, it’s unlikely to feature again as one of the strengths of macOS.

References

John Warnock (1991) The Camelot Project, on the Internet Archive’s Wayback machine.
Laurens Leurs’ The history of PDF.

In the first of these two articles I showed paintings of Hercules (Heracles) brandishing a large olive-wood club and wearing a lion-skin, as a stereotype of the ultimate high-testosterone uncouth hero. That association was strong enough to make its way into some more Christian images.

In Frans Francken the Younger’s composite painting of Mankind’s Eternal Dilemma – The Choice Between Virtue and Vice from 1633, the upper section of Paradise sets heroes including Hercules, to the left of centre with his trademark club and lion-skin, in an idealised landscape. Above them is an angelic musical ensemble serenading the figures below. This clearly was a Paradise for the artist’s patron, not the common person.

Clubs also appeared in other examples of hand-to-hand combat drawn from classical mythology.

In Peter Paul Rubens’ finished painting of The Rape of Hippodame (Lapiths and Centaurs) (1636-38) the figure at the upper right is just about to bring his club down on this wedding feast that turned into a pitched battle.

Sebastiano Ricci’s Battle of the Lapiths and Centaurs from about 1705 uses multiplex narrative to tell the same story. In the left background, Hippodame is seen being carried away by Eurytus, and a centaur in the centre foreground is swinging his club at one of the Lapiths.

Although the original story of the death of Orpheus at the hands of Bacchantes has them club him with their thyrsi, more modern interpretations are content with ordinary clubs.

Louis Bouquet’s The Death of Orpheus (1925-39) transports this scene to a beach, where the naked Bacchantes are armed with clubs, and just starting to tear the body of Orpheus with their bare hands and teeth.

Some earlier paintings of Christian devils show them with clubs.

Painted in 1430-32, Stefano di Giovanni’s St Anthony Beaten by the Devils identifies the saint by his Tau crucifix. Three devils, clearly fallen angels by their wings, are beating him with clubs. Those devils are fairly conventional figures, part animal and part man, with horns.

In contrast, Hercules’ lion-skin developed different associations, and involved other species.

Jean-Louis-Ernest Meissonier’s romanticised view of The Siege of Paris from 1870 combines almost every symbol relevant to the city’s distress, and dresses the symbolic figure of Marianne in a lion-skin against a battle-worn flag.

By the end of the nineteenth century, animal skins had gone from the uncouth to the mildly erotic, as seen in several of John William Godward’s paintings of doing nothing, or Dolce Far Niente.

This first from 1897 returns to a classical Roman setting, and adds a brilliant green parakeet to accompany this woman on a tiger-skin, in her diaphonous dress.

Seven years later (in 1904), Godward painted his more complex version, also known as Sweet Idleness, or A Pompeian Fishpond. More modestly clad, his lone woman rests with her knees drawn up into a sleeping (near-foetal) position on another animal skin, with a peacock-feather fan in the foreground.

A couple of years after that (in 1906), Godward’s beautiful woman is stretched out on an animal skin on marble, a colour-co-ordinated garden and distant Mediterranean waterscape beyond: a far cry from the uncouth Hercules.

With the next scheduled update to macOS Sequoia likely to be released in September or October, macOS 15.6 officially marks the end of its year-long cycle of full support. This article looks at its updates and how it has changed.

Updates

It took Sequoia a total of 11 updates to reach version 15.6 at the end of July, including five unscheduled patch updates, which is close to average. Prominent through those updates has been the number of security vulnerabilities addressed, peaking at 81 in 15.6.

In terms of cumulative size of updates, Sequoia was close to average at a total of 27.5 GB for Apple silicon Macs and 19.3 GB for Intel models. Although not as bad as Big Sur which took over 50 GB for Apple silicon Macs, it wasn’t as good as Sonoma at just over 21 GB. Update size was relatively small up to 15.3, but added over 9 GB in the three updates it took to reach 15.4. Apple doesn’t appear to have made progress in reducing the size of updates for Apple silicon Macs, and that may not be achieved until macOS 27 next year, when Intel support is finally dropped.

Bundled apps

The total number of bundled apps has increased slightly, from 60 in Sonoma to 62 in 15.0, and 64 in 15.6. That’s set to rise again in Tahoe, with the addition of Journal and Phone.

/System/Library

The total number of bundles in /System/Library has risen further to reach 9,304, almost double the number in 10.14.5 six years ago, and up from 8,392 a year ago in 14.6. Unusually, this has risen by nearly 300 through Sequoia’s cycle. Previously it has been more common for only small rises to occur during a cycle, and in macOS 13 the total fell slightly.

Over that period, the main growth has been in the number of Private Frameworks, which have risen from about 1,760 in 10.14 to over 4,400 in 15.6. Public Frameworks have risen less, from less than 520 to 806. Despite Apple’s campaign for third-parties to move away from kernel extensions, those in macOS also continue to grow, rising from a minimum of 515 in 10.15.0 to 939 in 15.6. Sequoia has added 39 of those in going from 15.0 to 15.6.

This is a more detailed breakdown by category of bundles in /System/Library, comparing 10.15.6 with 15.6:

• Accessibility, a small increase from 125 to 161
• Automator, a small reduction from 266 to 252
• Templates, a marked reduction from 383 to 252
• CoreServices, a small reduction from 390 to 363
• AssetsV2, a substantial growth from 188 to 806
• Public Frameworks, a modest increase from 600 to 806
• Kernel extensions, a substantial increase from 534 to 939
• Private Frameworks, a huge increase from 2,055 to 4,407.

Five years ago in 10.15.6, public Frameworks were almost a quarter of all Frameworks. In 15.6, they are less than 18%. macOS continues to become an increasingly private operating system supporting Apple’s apps, not those of third party developers.

If you see a well-muscled man brandishing a large olive-wood club and wearing a lion-skin, you can be fairly certain he is Hercules, or Heracles if you prefer the original Greek. He’s the ultimate high-testosterone uncouth hero, who doesn’t understand why others wear fabrics, and relies on his club to settle all disputes. In this and tomorrow’s article I explore how reliably paintings meet that expectation, and who else wielded clubs and liked animal hide next to their skin.

One of the most unusual summaries of Hercules’ career is this mosaic from Llíria, Valencia, showing each of his twelve labours around its central panel. His club goes with him in every one except that in the centre, seen in the detail below.

There, in the midst of all his swashbuckling masculinity, Hercules is seen holding a distaff and spindle for spinning, and is dressed as a woman, while Queen Omphale sits on his Nemean lion-skin on her throne, clutching his club. This comes from a curious myth of role reversal and cross-dressing, in which Hercules served as a slave to the Queen of Lydia for a year as penalty for murdering Iphitus.

Bartholomeus Spranger’s Hercules and Omphale (c 1585) uses the same exchange of attributes, and plays openly with the eroticism of Omphale’s position. Note also the colour-coding of their skin.

Luigi Garzi’s Hercules and Omphale (c 1700-10) lets Hercules put his spinning gear behind him, as he entertains the court with a song and the tambourine. Omphale seems to be enjoying her new position on the lion-skin, while fondling his club in her left hand.

Byam Shaw ignores the figure of Hercules altogether, showing a triumphant and erotically-charged Omphale (1914) against a background of the twelve labours, in a remarkable reconfiguration of that ancient Roman mosaic.

Elsewhere, there are many depictions that identify the uncouth hero with his attributes.

In Hans Thoma’s Hercules Delivering Hesione (1890) Hercules stands on the beach in front of the early city of Troy, his trademark club in his right hand. A naked Telamon is busy keeping the sea monster at bay by throwing boulders at it, while Hercules is bargaining with the fair Hesione.

In about 1706, Sebastiano Ricci embroidered the story of Hercules Fighting with the Centaur Nessus showing the hero wearing his lion-skin, and his left hand grasping Nessus’ mouth, about to club the centaur to death, while a slightly bedraggled Deianeira watches in the background.

Noël Coypel, the father of the better-known history painter Antoine Coypel, painted Hercules Fighting Achelous in about 1667-69. This opts to show the pair during the first phase of their fight. In addition to wearing his lion-skin, Hercules wields his fearsome club.

Francisco de Zurbarán’s powerful Death of Hercules (1634) uses chiaroscuro as stark as any of Caravaggio’s to show a Christian martyrdom, with its victim staring up to heaven, commending his soul to God. He is wearing the poisoned shirt inadvertently given him by Deianeira, rather than his lion-skin, and his club rests at his feet.

If RunningBoard’s copious log entries record the life cycle of apps, can we use them to our advantage? To test this out, I’ve analysed a section of log using waypoints and information provided in RunningBoard’s entries.

Waypoints, or landmarks if you prefer, are essential for navigating the log. In an ideal world we would always know when any significant event occurred, timed to the millisecond. In practice we may only be able to estimate to the nearest few seconds or minutes. Without some means of discovering exactly when to obtain log extracts, you can waste many hours trying to pin down when something happened, and in many cases will be forced to abandon the hunt.

Methods

My aim was to separate RunningBoard log entries into those handling its assertions, which should represent life-cycle events, and job descriptions giving details of apps launched. To try this yourself, open LogUI and set the Start date and time to the start of the period of interest. Set the Period to at least 100 seconds, and Max entries to 2,000 or more. Then set the Predicate popup menu to read subsystem, and type in com.apple.runningboard so that LogUI only gets entries from that subsystem. Click on the Get Log tool in the toolbar, and check you get at least 1,000 entries.

Click on the Save JSON tool to save the whole of this excerpt. To view all the RunningBoard assertions acquired over that excerpt, type acquiring assertion in the search box at the top right, and press Enter.

The window name then changes to append the text from the search box.

To save this limited selection of entries, first click on the Reduce tool to discard all the others, then click on the Save JSON tool again and save the entries using a different filename. Repeat that using each of three search terms:

• acquiring assertion to see RunningBoard’s outline of life cycle events,
• constructed job to see job descriptions for newly launched apps,
• extension overlay to see similar information for appexes and similar extensions.

In my case, I analysed a period of 4 minutes of user activity on a Mac mini M4 Pro running macOS 15.6, during which there were 6,580 RunningBoard entries, suggesting that the whole log would have had well over 50,000 entries in that time, far too many to attempt any more detailed analysis. My search terms found 305 assertions acquired, 3 job descriptions constructed, and 20 extension overlays submitted.

Job descriptions

The three captured represented the three apps I had launched over those four minutes, Cormorant, DelightEd and Consolation 3. Each of them has a platform ID of 1, as notarized macOS apps. I also noticed that one was run in app translocation, although this was long after its first run. Recent versions of macOS, Sequoia in particular, appear prone to this, when an app that should have cleared quarantine gets stuck in perpetual app translocation.

Extension overlays

While I had expected to find those three app launches, I didn’t expect to see any appexes being run over this period. Those encountered consisted of three widgets, none of which had ever been opened, and five QuickLook thumbnail extensions. Most of these were run multiple times, with ScappleThumbnail appearing on six occasions. All were platform 1, except for the widgets, all three of which are bundled in macOS, for the FindMy widget and NewsToday2. They were platform 6, and subject to RunningBoard’s resource controls.

RunningBoard’s log entries here give potentially valuable insights that might otherwise be missed.

Assertions

It’s straightforward to construct a narrative of the key events that took place over that period of 4 minutes using a selection of assertions acquired. Rather than reproduce the whole of each of those waypoints, here they are laid out in more readable form.

11:40:50.424950 Acquiring assertion targeting app application.co.eclecticlight.Cormorant.10809046.10809052(501)
description "LS launch co.eclecticlight.Cormorant" ID:424-620-716
target: application.co.eclecticlight.Cormorant.10809046.10809052(501)
attributes: domain:"com.apple.launchservicesd" name:"LaunchRoleUserInteractive" sourceEnvironment:"(null)"

This marks the start of the launch process for Cormorant, handled in the normal way through LaunchServices and RunningBoard.

11:41:18.304367 Acquiring assertion targeting app application.co.eclecticlight.DelightEd.10206240.10206246(501)
description "LS launch co.eclecticlight.DelightEd" ID:424-620-756
target: application.co.eclecticlight.DelightEd.10206240.10206246(501)
attributes: domain:"com.apple.launchservicesd" name:"LaunchRoleUserInteractive" sourceEnvironment:"(null)"

This is the same for DelightEd.

11:41:20.050166 Acquiring assertion targeting [xpcservice com.apple.appkit.xpc.openAndSavePanelService([app application.co.eclecticlight.DelightEd.10206240.10206246(501) :1553])(501) 1576:1576]
description "viewBridge:1576" ID:424-391-769
target: 1576
attributes: domain:"com.apple.launchservicesd" name:"RoleViewBridge" sourceEnvironment:"(null)"

DelightEd is here being used to open a document using the openAndSavePanelService, a separate process.

11:41:44.171636 Acquiring assertion targeting app application.co.eclecticlight.Consolation3.430650.430692(501)
description "LS launch co.eclecticlight.Consolation3" ID:424-620-788
target: application.co.eclecticlight.Consolation3.430650.430692(501)
attributes: domain:"com.apple.launchservicesd" name:"LaunchRoleUserInteractive" sourceEnvironment:"(null)"

This is the launch of Consolation 3, a user error on this occasion!

Two long runs of assertions were discovered, both involving syncing the address book for Contacts.

11:41:57.462118 Acquiring assertion targeting [osservice com.apple.AddressBook.SourceSync(501):1610]
description "App is holding power assertion" ID:424-362-811
target: 1610
attributes: domain:"com.apple.appnap" name:"PowerAssertion" sourceEnvironment:"(null)", RBSAcquisitionCompletionAttribute policy:AfterApplication

The first of these was to sync the Address Book with its source in iCloud, and lasted 12.181 seconds.

11:42:11.840349 Acquiring assertion targeting [osservice com.apple.AddressBook.abd(501):1625]
description "Contacts shared filesystem lock" ID:424-1625-857
target: 1625
attributes: domain:"com.apple.common" name:"FinishTaskUninterruptable" sourceEnvironment:"(null)", RBSAcquisitionCompletionAttribute policy:AfterApplication

Shortly after that completed, synced data was updated by a service abd (Address Book Daemon?) that I had been unaware of. This only lasted 2.238 seconds.

RunningBoard’s assertions seldom appear for single-shot shell commands, and most commonly handle executable bundles rather than bare Mach-O binaries. They also don’t appear to provide clear information recording when apps are quit normally.

Conclusions

• RunningBoard entries can readily provide accurate waypoints for many events in the log.
• Establishing waypoints on the strength of RunningBoard log entries is straightforward in LogUI.
• Job descriptions are readily found, and provide useful information on apps launched.
• Extension overlays provide details of appexes that might otherwise be overlooked.
• Acquisition of assertions identify various events in the app life cycle.
• Once RunningBoard entries have provided precise times of events, attention can be focussed on obtaining more detail using short log extracts.

The Renaissance modernised the art of the late Middle Ages with realistic images that strived to resemble what we actually see, rather than presenting a world of stereotypes and symbols. This is best seen by comparing paintings of a common theme spanning the period, here those of the Madonna and Child.

Cimabué’s Maestà was painted in egg tempera for the main altar of the church of Santa Trinita in Florence, between 1280-90. Little attempt is made to distinguish surface textures, although some use is made of lightness and pattern in fabrics to depict their folds. Faces are uniform and devoid of expression or emotion, most turned in directions determined by its structured composition. There’s no sign of any landscape or other background, and no impression of reality.

While Ghirlandaio’s Madonna and Child from about 1470-75 was still painted in egg tempera, it’s much more realistic in its approach to the figures and the folds in fabrics. Modelling of the figures is still restrained, and there’s no natural background, but its intent is clearly to resemble a real mother and her infant.

Raphael’s Madonna della Sedia (Madonna of the Chair) from 1513-14 shows a thoroughly real and natural mother with two infants, every surface texture rendered as in life, with wisps of hair, differentiation between types of fabric, and convincing expressions and postures.

Many of the changes seen here in the Renaissance can be elaborated as follows:

• surface texture of skin, hair and fabrics;
• individual faces expressing emotions;
• telling stories using body language;
• individual natural posture;
• realistic landscape backgrounds;
• three-dimensional perspective projection with controlled vanishing points;
• varied composition;
• the air of reality;
• use of oil paints;
• increasing production of easel paintings;
• references to both secular and classical literature;
• introduction of new genres such as landscapes and secular paintings;
• direct patronage;
• independent and secular masters.

Technically the Renaissance provided the painter with all the tools for painting anything that might be seen in life. However, the great majority of paintings were commissioned for religious use, so depicted motifs drawn from the Bible and other Christian writing.

One of the early and most skilled practitioners of oil painting was the brilliant but short-lived Venetian master Giorgione, who has the added distinction of painting what was probably the first landscape painting of the southern Renaissance.

Giorgione’s revolutionary landscape The Tempest from just after 1500 remains enigmatic today, and may have religious references, but it marked the start of a new and wholly secular genre.

Late in the Italian Renaissance, emphasis shifted from its birthplace Florence to other centres such as Bologna and, most of all, Venice, where the effects of colour (Italian colore) came to dominate form and design (Italian disegno).

Jacopo Tintoretto’s Crucifixion from 1565 is over 5 metres (17 feet) high, and 12 metres (40 feet) across, larger than many frescoes of the Renaissance. He makes use of this space with a narrative technique based on the popular ‘multiplex’ form: its single image shows events at more than a single point in time, in an ingenious and modern manner.

Naturally, the painting centres on Christ crucified, but the two thieves executed beside him are not shown, as would be traditional, already hanging from their crosses. Instead, to the right of Christ, the ‘bad’ thief is still being attached to his cross, which rests on the ground. To the left of Christ, the ‘good’ thief is just being raised to the upright position.

Tintoretto’s Annunciation is thought to have been painted even later, in about 1582. Its composition is unusual by any contemporary standards, with natural rendering of brickwork, a wicker chair, and a splendidly realistic carpenter’s yard at the left. This is coupled with an aerial swarm of infants, at the head of which is the dove of the Holy Ghost in a small mandorla. Christ’s origins are here very real, tangible, and contemporary, in stark contrast to most traditional depictions of this scene.

If any single workshop brought the Renaissance to a close and moved on to what has become termed the Baroque it’s that of the Carraccis, initially in Bologna, then in Rome.

Annibale Carracci’s Latona and the Lycian Peasants, probably from 1590-1620, is the first truly masterly painting of this myth told in Ovid’s Metamorphoses, and for once an easel painting on canvas rather than a fresco. Although not a religious theme, this drew on the other acceptable source of narratives at the time, classical myth.

If there’s one artist who clearly defined the start of a new era it was Caravaggio, who began his career in Milan, but transformed art when he was painting in Rome.

His portrait of Narcissus from 1594-96 demonstrates how the tools of realism could be used in thoroughly secular paintings, but still of classical myth.

Caravaggio wasn’t alone. Among those who adopted and developed his style, the Caravaggists, was Lavinia Fontana, who came from Bologna and worked at the height of her career in Rome. Her Judith with the Head of Holofernes from 1600 also contrasts completely with the tondo Madonna by Raphael at the start of this article.

There was, of course, much more to the Baroque than Caravaggism. In 1604-06, Annibale Carracci and Domenichino (also from Bologna) joined forces in the Palazzo Farnese in Rome to paint this fresco of Perseus and Phineas. As Perseus stands in the centre brandishing the Gorgon’s face towards his attackers, Andromeda and her parents shelter behind, shielding their eyes for safety. The Renaissance was in the past, and Florence was no longer the beacon that it had been.

Signs of change occurred earlier in the north, where the first tentative steps were made towards a broadening of genres.

It was probably Hans Memling (c 1340-1494) who painted one of the first still lifes, on the back of a panel bearing a portrait of a young man praying, in about 1485. It has been proposed that this was part of a diptych or triptych, and could have formed its back cover when folded.

His choice of jug and flowers confirms its religious nature: Christ’s monogram is prominent on the body of the jug, and each of the flowers has specific references. Lilies refer to the purity of the Virgin Mary, the irises to her roles as Queen of Heaven and in the Passion, and the small aquilegia flowers have associations with the Holy Spirit. The eastern pattern on the rug is so distinctive of the artist that these became referred to as Memling rugs.

Coming closer to what was soon to become the Dutch Republic, Pieter Bruegel the Elder founded a dynasty of Flemish artists who broke from the Renaissance mould and started depicting the everyday.

Two of his major paintings from 1565 were formative influences on what was to come in the Dutch Golden Age. The Harvesters is a complete account of the grain harvest in the Low Countries, and Winter Landscape with Skaters and Bird Trap below is a pure landscape.

There are no figures particularly close by, and those on the ice are not demonstrating the many different activities they could be undertaking. It also happens that this was one of the first paintings to show Netherlandish people on the ice in the winter, a theme that shortly became very popular, and whose influence extended throughout Europe, across centuries and styles.

By 1600 the techniques of depicting the real world were well understood, and all it required was an abundant trade in art materials including drying oils and pigments, an increasingly wealthy population, seemingly insatiable demand for paintings, and an army of painters. Those all came in the Dutch Republic.

By now your Mac should have the latest macOS update installed, and be running the current firmware. This article takes stock of where EFI, T2 and Apple silicon firmware are now, and where they’re heading with the forthcoming release of macOS 26 Tahoe in a month or two.

For many years, the only way your Mac will have its firmware updated is when macOS or one of its updates is installed on it. There is one significant exception to that, in Apple silicon Macs, whose firmware will be completely replaced when it’s put into DFU mode and restored from an IPSW file.

Each macOS update or full installer comes with the firmware current at the time Apple built it. So if your Mac is still running macOS 12.7.6 Monterey and has never installed any later version, it will have the firmware that came with that, such as iBoot 10151.140.19, or T2 version 2022.140.5.0.0 with iBridge 21.16.6074.0.0,0.

Note that firmware is updated whether macOS is installed or updated on the internal storage, or on an external disk. So if your Mac’s internal SSD is still running 12.7.6, but it has been used to update Ventura to 13.7.7 on an external SSD, then it will have the firmware brought in that version of Ventura, rather than that for Monterey. That doesn’t of course apply to macOS installed in any virtual machines, as they can’t update the host firmware.

Intel Macs without T2 chips

All these models appear to have reached the end of their EFI firmware updates, with the versions shown.
iMac:

• iMac18,1 529.140.2.0.0
• iMac18,3 529.140.2.0.0
• iMac19,1 2075.100.3.0.3

MacBook:

• MacBook10,1 529.140.2.0.0

MacBook Pro:

• MacBookPro14,1 529.140.2.0.0
• MacBookPro14,2 529.140.2.0.0
• MacBookPro14,3 529.140.2.0.0

All those date from 23 June 2024, apart from that for the iMac19,1, whose latest firmware is from March 2025. Although the latter could still be updated in a security update to Sonoma or Sequoia, that now looks increasingly unlikely.

Intel Macs with T2 chips

The current EFI version is 2075.140.4.0.0 and iBridge is 22.16.16083.0.0,0, and those are likely to continue to be updated over the coming year. However, T2 models still running macOS Ventura are likely to stay there, unless Apple releases one final extra update. To ensure that your T2 Mac continues to get firmware updates, it now needs to be running Sonoma or later.

Apple silicon Macs

The current iBoot version is 11881.140.96, and that is sure to see a substantial update with the release of macOS 26.0, and in the simultaneous security updates for Sequoia and Sonoma. However, any Apple silicon Mac still running Ventura or earlier will be running an older version of iBoot that it can’t update, unless it installs or updates a more recent macOS in another boot volume group, such as on an external disk.

Apple Studio Display

Display firmware remains at version 17.0 (build 21A329) as it was when updated with macOS Sonoma nearly two years ago in September 2023. Although there’s no sign of any update with the beta-test versions of Tahoe, maybe it’s likely that this will be updated with macOS 26.0 and its associated security updates.

Check

The currently installed firmware version is displayed in System Information, by selecting the Hardware item at the top left. It’s also checked against the current version in SilentKnight. However, in recent Mac models with T2 or Apple silicon chips it’s most unlikely to differ from that brought with the latest version of macOS that Mac has installed or updated. Macs without T2 chips were less reliable, and some older models often failed to update when expected. Thankfully that’s now a problem of the past. If there’s one thing you should be able to trust it’s firmware updating.

Apple has just released updates to XProtect for all supported versions of macOS, bringing it to version 5309, and to XProtect Remediator for all macOS from Catalina onwards, to version 153. As usual, Apple doesn’t release information about what security issues these updates might add or change.

Yara definitions in this version of XProtect add a single new detection rule for MACOS.SOMA.JUENB, part of the Soma/Amos family.

XProtect Remediator doesn’t change the list of scanner modules.

There are extensive changes to the Bastion rules, which add a new definition for common system binaries, extend Rule 1 coverage to include support folders for more browsers, tweak Rules 3 and 14-17, and add new Rules 18-24.

You can check whether these updates have been installed by opening System Information via About This Mac, and selecting the Installations item under Software.

A full listing of security data file versions is given by SilentKnight and SystHist for El Capitan to Tahoe available from their product page. If your Mac hasn’t yet installed this update, you can force it using SilentKnight or at the command line.

If you want to install these as named updates in SilentKnight, their labels are XProtectPayloads_10_15-153 and XProtectPlistConfigData_10_15-5309.

Sequoia and Tahoe systems only

The XProtect update has already been released for Sequoia and Tahoe via iCloud. If you want to check it manually, use the Terminal command
sudo xprotect check
then enter your admin password. If that returns version 5304 but your Mac still reports an older version is installed, you may be able to force the update using
sudo xprotect update

Before I delve into painting media, it’s helpful to establish the terms I’m going to use. Although at their simplest paintings consist of a fairly flat and even surface with a layer of paint on it, in practice most have a more complex anatomy.

Earliest surviving paintings, such as these from around thirty-six millennia ago, in the Chauvet-Pont d’Arc Cave in the Ardèche, were simple applications of pigment to a stone surface. It’s a miracle that any have survived, given the lack of bonding between pigment and stone.

Fast-forward over thirty-five thousand years, and in 1570-72 Giorgio Vasari created something similar in his painting of Perseus and Andromeda consisting of pigment bound in a drying oil, applied to slate. The big difference is in his paint, which was developed over several centuries to form a strong bonded layer adhered to the surface of the rock.

Stone and walls make a robust support for a painting, but aren’t exactly portable unless they’re as small as Vasari’s sheet of slate. Alternatives were constructed from wood in panels, and could be painted on an easel rather than up a scaffold, hence these portable works of art are widely known as easel paintings, and use wood panel supports.

The next step in development was to apply a primer to the wooden panel to form a smooth surface to which the paint layer would bond better, forming the ground.

When Leonardo da Vinci abandoned his Adoration of the Magi as he left Florence in about 1482, he had applied little paint to its ground, on which he had already made extensive underdrawings and prepared tonal modelling for the paint layer he never completed.

Our easel painting now has a physical support, a purely mechanical task, and on that the ground on which the paint is applied. Those roles are distinct, even when a single surface such as a wall or sheet of paper fulfils both. Most traditional paintings by professional painters made in the last few centuries have been on supports of stretched canvas, which have been sized to protect their fibres, then had a white or tinted ground such as chalk bound to them.

Support and ground form the receiver, on which colour in the form of pigments has to be bound. Although it’s possible to get pigment to adhere to a suitably rough ground, part of the principle behind painting in pastels, the result isn’t durable, and clients and patrons are likely to be wary about paying for a painting that literally crumbles into dust in front of their eyes.

Not all paints contain pigments: some prefer soluble dyes instead. Generally dyes, often derived from plants, aren’t as durable. Pigments consist of large insoluble particles, as seen in the cross-section above, to protect them from physical damage, chemical reactions, and most importantly the adverse effects of exposure to light, which can cause their intensity to fade.

The goal of many paint systems is to trap these pigment particles in a solid layer formed by a chemical binder which is liquid when applied but hardens by the chemical process of polymerisation into a solid. In the case of oil paints, the binder is an oil that undergoes slow oxidation to form the polymer, a drying oil such as linseed obtained from the common flax plant.

The final component involved in a painting is one that should vanish during the process of applying the paint: a diluent or solvent used to thin the paint, and clean wet paint from brushes and the other tools used in the process. Diluents are often confused with binders, but they are usually opposites: an ideal diluent should evaporate quickly, leaving no residues and a robust if thin paint layer behind, for the binder to turn it into a strong, enduring and faithful record of what the artist intended.

In traditional oil painting, typical diluents are organic solvents such as turpentine and white spirit, used to spread a thin layer of drying oil binder and pigment particles. Remove most of the drying oil and use largely diluent, though, as in peinture à l’essence, used by Degas, and you can end up without any proper paint layer at all, with powdery pigment trying not to fall off.

Degas’ Danseuse dans sa loge (Dancer in her Dressing Room) (c 1879) is one of his experimental paintings using both pastel and peinture à l’essence applied to canvas.

In this respect, watercolours are strangely named. Oil paints rely on drying oils as their binder, but in watercolours the water is the diluent not the binder, which is gum arabic; many other painting methods also rely on water as diluent, but aren’t called watercolour as a result.

We finally end up with a rigid support, on which is the ground, that provides an adherent base for the paint layer, composed of pigment particles in a binder, that was originally thinned using a diluent. In most older paintings, those are then coated with layers of varnish intended to protect the surface of the paint layer.

Just like Giorgio Vasari with his oil painting on slate, there’s always someone who breaks conventions. This painting of Dandenongs from Heidelberg was made by Charles Conder on a sheet of wood from a cigar box. Conder was a member of a group of Australian artists who held a ‘9 by 5’ exhibition of paintings they had made on wooden cigar-box panels of 9 by 5 inches (23 x 13 cm) in size. Similar panels had been used extensively by Georges Seurat for his oil sketches, for which he had invented the term croquetons. They also resembled the small wood panels used by the Macchiaioli for their plein air oil sketches.

In thirty-six thousand years we have progressed from painting the walls of caves to sketching on a wooden cigar box.

Key terms

• easel painting, on a portable support rather than a wall or ceiling;
• support, a more or less rigid surface for a painting;
• ground, a priming layer applied to the support to form an adherent base for paint;
• paint layer, consisting of pigment particles in a binder, thinned during painting with a diluent;
• varnish, to protect the surface of the paint layer.

macOS comes with no support for the file systems most likely to be used by Linux. This article suggests how you might be able to access them, for example when a NAS system is connected directly to an Apple silicon Mac, or when you need to access external storage that has been used with a Linux system.

extFS

I believe Paragon Software’s extFS is the only generally available commercial solution, and is described here. If you only need access for a short period, it’s free to use for up to ten days, but must be licensed for $39.95, €39.95, or £38.81 if you want to unlock it to use for any longer. Paragon also offers support for accessing APFS from Linux and Windows.

If you need more than simple access to the contents of the file system, you can also combine extFS with an Ubuntu VM running in UTM to access backups made using Duplicity, for example. This is detailed here by Benjamin, to whom I’m very grateful for information about extFS and for inspiring this note.

macFUSE

Benjamin Fleischer’s free fork of Google’s MacFUSE software should be able to implement a fully functional alien file system running in user space. Its latest release 5.0.5 is compatible with current betas of macOS Tahoe as well as older versions back to macOS 12. However, some report that it isn’t able to deliver reliable support for Ext4 and similar. In theory, this should now be simpler, as recent versions of macOS can support macFUSE without requiring a kernel extension, and there’s an alternative backend in recent versions of macFUSE to support that. Project front page.

Jeff Geerling’s walkthrough using macFUSE with ext4fuse.

anylinuxfs

This is based on the libkrun microVM hypervisor, available separately from here. It has the advantage that it doesn’t rely on either kernel or system extensions, and is available from here. I’ve been unable to discover how reliable this is on Apple silicon, if it works at all.

Others

If you know of other ways of doing this with an Apple silicon Mac, please provide details in a comment.

Dante has been rescued from three wild beasts by the ghost of Virgil, who leads him along the only possible route, taking them to the gate of Hell. Inscribed above that gate is a forbidding series of lines leaving the traveller in no doubt that they’re going to a place of everlasting pain and tortured souls. This culminates in the most famous line of the whole of the Divine Comedy:
Lasciate ogne speranza, voi ch’intrate
traditionally translated as Abandon hope all ye who enter here, but perhaps more faithfully as Leave behind all hope, you who enter, and is seen written in William Blake’s own hand below.

Virgil explains its meaning to Dante before the two enter. Dante is then struck by the terrible sounds that he hears, those of tormented sinners in Hell mixed with the noise of the first group of dead: those who have been refused entry to Hell or to Heaven, because of their cowardice in failing to choose between God and the Devil. They form a river of naked bodies drawn by a banner, their faces constantly stung by wasps and hornets, streaking them with blood and tears.

Among them is one who has been identified as Pope Celestine V, who resigned from office in 1294, and another candidate is Pontius Pilate, who refused to pass judgement on Christ.

Then Charon, an irascible old man with white hair and coal-black eyes, appears in his boat. He tells Dante to get away from the dead, as he won’t be carried across by him with those souls, and will have to arrange another crossing. Virgil intercedes to ensure that they too will be ferried across the marshy River Acheron to Hell.

Those souls destined for Hell rush to board the boat, with Charon sweeping them in using his oar to hit those who are slow. The boat then carries them across, as another load gathers on the shore ready for its return.

There is then a violent gust of wind and a red bolt of lightning, and Dante loses consciousness.

Although Dante doesn’t describe his crossing of the Acheron in Charon’s boat, this has been imagined by several painters.

In 1822, the young Eugène Delacroix painted one of his finest narrative works, The Barque of Dante, showing the pair crossing a stormy river Acheron in a very small boat. He painted this quickly, over an intense period of a little over two and a half months, just in time for submission to the Salon. Dante, wearing his distinctive scarlet chaperon (hat), holds his hand up as he leans back onto the shoulder of Virgil his guide. This has been interpreted as showing how, when we encounter challenges from the modern we should look to tradition for support.

This is one of the most remarkable paintings of the Inferno, as an early experiment with colour. In the detail below, water droplets on the bodies of those surrounding the boat contain at least three different colours: their reflected highlights are pure white, the rest of the body of the droplet and its trail are the dark green of the water below, and the droplet itself has a shadow of the same pink that Delacroix uses to shade flesh. Their overall effect is of an unusually three-dimensional and realistic droplet.

The artists

José Benlliure y Gil (1855–1937) was a Spanish painter who was born in Valencia but spent much of his working life in Rome, where he became the director of the Spanish Academy there. After painting small genre works, he turned to classical narratives including the painting shown here.

William Blake (1757–1827) was a British visionary painter and illustrator whose last and incomplete work was an illustrated edition of the Divine Comedy for the painter John Linnell. Most of his works shown in this series were created for that, although he did draw and paint scenes during his earlier career. I have a major series on his work here.

Eugène Delacroix (1798–1863) was a major French painter whose Romantic and painterly style laid the groundwork for the Impressionists. In addition to many fine easel works, he painted murals and was an accomplished lithographer too. Many of his paintings are narrative, and among the most famous is Liberty Leading the People from 1830. This article introduces a series featuring his major works.

Gustave Doré (1832–1883) was the leading French illustrator of the nineteenth century, whose paintings are still relatively unknown. Early in his career, he produced a complete set of seventy illustrations for translations of the Inferno, first published in 1857 and continue to be used. These were followed in 1867 by more illustrations for Purgatorio and Paradiso. This article looks at his paintings.

Alexander Dmitrievich Litovchenko (1835-1890) was born in Kremenchuk, Ukraine, but spent most of his career painting historical events in Russia. His painting of Charon won him a gold medal.

Paolo Vetri (1855–1937) was a precocious Italian painter who was born in Sicily. He was a pupil of the great narrative artist Domenico Morelli, and completed several major murals as well as many easel paintings.

References

Wikipedia
Danteworlds

Robin Kirkpatrick (trans) (2012) Dante, The Divine Comedy, Inferno, Purgatorio, Paradiso, Penguin Classics. ISBN 978 0 141 19749 4.
Richard Lansing (ed) (2000) The Dante Encyclopedia, Routledge. ISBN 978 0 415 87611 7.
Guy P Raffa (2009) The Complete Danteworlds, A Reader’s Guide to the Divine Comedy, Chicago UP. ISBN 978 0 2267 0270 4.
Prue Shaw (2014) Reading Dante, From Here to Eternity, Liveright. ISBN 978 1 63149 006 4.

I hope that you enjoyed Saturday’s Mac Riddles, episode 319. Here are my solutions to them.

1: Successor to 3 inside a scheme was part of a popular atelier.

2: High speed subatomic particle took the lead in the 1990s.

3: Creator of a squire’s assistant was the first, but died before Mac OS X.

The common factor

I look forward to your putting alternative cases.

With additional information about Spotlight’s volume indexes, this article looks in more detail at how those indexes are updated when new files are created, and how local search is reflected in log entries. To do this I use the Spotlight test feature in my free utility Mints, which is designed to assess its performance.

Mints can create a test folder and populate it with 9 test files, copied from inside the app bundle using File Manager’s copyItem function. Provided the app and that newly created folder in ~/MintsSpotlightTest4syzFiles are in the same volume, this will almost certainly occur by creating APFS clone files. The files are:

• SpotTestA.rtf, RTF, relying on /System/Library/Spotlight/RichText.mdimporter
• SpotTestB.pdf, PDF, relying on /System/Library/Spotlight/PDF.mdimporter
• SpotTestC.txt, plain text, relying on /System/Library/Spotlight/RichText.mdimporter
• SpotTestD.html, HTML, relying on /System/Library/Spotlight/RichText.mdimporter
• SpotTestE.docx, Microsoft Word docx, replying on /System/Library/Spotlight/Office.mdimporter
• SpotTestEXIF.jpg, JPEG image not containing the target string in the image, but in the Make field of its EXIF IDF0 metadata, and relying on /System/Library/Spotlight/Image.mdimporter
• SpotTestF.numbers, Numbers spreadsheet containing the target string in one of its cells, and relying on /System/Library/Spotlight/iWork.mdimporter
• SpotTestG.pages, Pages document, relying on /System/Library/Spotlight/iWork.mdimporter
• SpotTestMD.txt, plain text not containing the target string in its contents, but in an extended attribute of type com.apple.metadata:kMDItemKeywords attached when the file is copied.

The search target they each contain is a string starting with the characters syzygy999 so most likely to be unique to the test files and Mints’ bundle.

This example test was performed on a Mac mini M4 Pro running macOS 15.6 from its internal SSD, with the Home folder located in the boot Data volume in that storage.

Indexing

Folder creation and file copying should take place soon after clicking on the Create Test button, in this example test in just over 0.3 seconds. The first mdworker process responding to this is spawned about 0.9 seconds after file copying starts, and further mdworker processes are added to it, making a total of 11. These are uncorked by launchd in about 0.03-0.05 seconds and are active for a period of about 0.2 seconds before they appear to have finished creating new posting lists to be added to the local indexes.

Shortly after those are complete, spotlightknowledge is active briefly, then 0.2 seconds after file copying mediaanalysisd receives a text processing request and initialises CGPDFService. Just over 0.1 second later CoreSceneUnderstanding is invoked from mediaanalysisd. For the following 5 seconds, a series of MADTextEmbedding (mediaanalysisd text embedding) tasks are performed. Finally, content obtained by mdworker and MADTextEmbedding is compressed by mds_stores, finishing about 6.7 seconds after the new files were created.

These steps are summarised in the diagram above, where those in blue update metadata indexes, and those in yellow and green update content indexes. It’s most likely that each file to be added to the indexes has its own individual mdworker process that works with a separate mdimporter, although in this case at least 11 mdworker processes were spawned for 9 files to be indexed.

Text extraction from files by mediaanalysisd involves a series of steps, and will be covered in more detail separately. In this test, local Spotlight indexes should have been updated within 7-8 seconds of file creation, so waiting at least 10 seconds after clicking the Create Test button should be sufficient to enable the test files to be found by search.

Searching

When the Check Search button in Mints is clicked, an NSMetadataQuery is performed using a search predicate over the search scope of NSMetadataQueryUserHomeScope, the Home folder. This uses the search predicate (kMDItemTextContent CONTAINS[cd] "syzygy999") OR (kMDItemKeywords CONTAINS[cd] "syzygy999") OR (kMDItemAcquisitionMake CONTAINS[cd] "syzygy999") to find all items containing any of:

• kMDItemTextContent CONTAINS[cd] "syzygy999" looks for the target string in a text representation of the content of the document, as in most of the test files used.
• kMDItemKeywords CONTAINS[cd] "syzygy999" looks for keywords in an extended attribute of type com.apple.metadata:kMDItemKeywords as attached to the SpotTestMD.txt file.
• kMDItemAcquisitionMake CONTAINS[cd] "syzygy999" looks for the Make field of an EXIF IDF0 as embedded in the SpotTestEXIF.jpg file.

Each of those is both case- and diacritic-insensitive, although the test cases all use lower case without any diacritics.

Remarkably little is recorded in the log for these test searches. com.apple.metadata starts the query within 0.001 second of clicking the Check Search button, and is interrupted by TCC approving the search to proceed. About 0.03 seconds after the start of the query, a series of entries from mds_stores reports query node counts of 4, and results are fetched and sent as replies between 0.09 and 19.5 seconds after the start of the query. However, Mints typically reports a considerably shorter search time of around 4 seconds.

Better testing

The test currently included in Mints appears useful, in that it assesses the whole of Spotlight local search from file creation to completion of a test search. However, in its current form it doesn’t test LiveText or other in-image text extraction, and only applies to the volume containing the Home folder. Log extracts obtained in its Log Window are basic and don’t capture much of the detail used for this article. There seems scope for a dedicated Spotlight test app that addresses these and more.

Summary

• Spotlight local indexing from the creation of nine new files reliant on macOS bundled mdimporters is initiated promptly, and should be completed within 10 seconds of their creation. It appears to follow the scheme shown in the diagram above.
• Text extraction from images by mediaanalysisd (‘MAD’) is significantly slower than extraction of metadata and other text content.
• NSMetadataQuery search should also be relatively quick when the number of hits is small, but leaves little information in the log.

Until the advent of chemistry in the eighteenth century, early in the Age of Enlightenment, the vast majority of pigments occurred in nature, even if the minerals or plant matter from which they were derived had to be specially processed. The first truly synthetic pigment was so ancient that it had been forgotten completely by the Middle Ages: Egyptian blue was originally made before about 3000 BCE by heating together powdered rocks and sand, but that was an exception. It wasn’t until the early years of the eighteenth century that a hydrated iron hexacyanoferrate complex soon known as Prussian blue was synthesized.

No one knows who first made Prussian blue, nor exactly when it was first synthesized. It seems to have appeared initially around 1704, and its origins have been attributed variously to Diesbach in Berlin, or Mak in Leipzig. For once its name is appropriate, as it was a product of the Prussian Empire. Its potential as a colourant was recognised by 1710 when it went on sale in Berlin, and by about 1724 it was being manufactured across Europe.

Among the earliest surviving oil paintings to use Prussian Blue is that by Adriaen van der Werff and Henrik van Limborch, of Jacob Blessing the Sons of Joseph. This was started by van der Werff before he died in 1722, and the paint containing Prussian blue pigment is thought to have been applied by him to the curtain at the upper left. After van der Werff’s death, his pupil Henrik van Limborch finished the painting between 1727-28.

Another early example of the proven use of Prussian blue is Antoine Watteau’s The Italian Comedians from about 1720.

Canaletto is one of the first Masters to have used the new pigment extensively. Grand Canal from Palazzo Balbi toward the Rialto from 1720-23 has been attributed to him as one of his earliest surviving works, and its blues have been found to contain Prussian blue.

Canaletto was quick to adopt the pigment for use in almost all his paintings, including this view of the Rio dei Mendicanti from 1723-24, above, and his famous The Stonemason’s Yard (c 1725), below.

As experience was gained in using this pigment, it became controversial. Some artists were confident that its colour was stable and didn’t change or fade, but others experienced problems as bad as or even worse than those of the notoriously fugitive indigo blue, which it had generally replaced. It has gradually become understood that adverse results of lightfastness testing (and experience in paintings) have depended on the mixture of Prussian blue with other colours, particularly with white paint, and the presence of impurities in the pigment.

By the middle of the eighteenth century, Prussian blue was widely used with a range of binding media, with the notable exception of fresco and other alkaline media with which it proved incompatible.

William Hogarth’s paintings in his Marriage A-la-Mode series have been found to contain both smalt and Prussian blues. In The Tête à Tête (c 1743), smalt has been found in the ornate carpet, and I suspect that the ornamental pillars behind the woman rely on Prussian blue, at least in part. Hogarth trained as Prussian blue came to the ascendant, and wouldn’t have painted much before it had become widely available.

Jean-Baptiste Perronneau’s A Girl with a Kitten from about 1743 is a fine example of the use of Prussian blue in pastels: the girl’s blue dress and the background have both been found to contain the pigment.

Prussian blue also became popular in water-based media. William Blake’s Lucia Carrying Dante in his Sleep, from his series depicting Dante’s Divine Comedy painted in watercolour between 1824-27, is a good example. In this and several other of his paintings, Blake used the pigment on its own and mixed with gamboge yellow in what was known as Prussian green.

Prussian blue pigment has been found in the blue passages in Whistler’s The Princess from the Land of Porcelain (1863-65), from his Peacock Room, shown above and in the detail below.

The use of different blue pigments varied markedly among the French Impressionists and their successors. Paul Cézanne and Georges Seurat appear to have used Prussian blue seldom if at all, but it’s well known in the work of Edgar Degas, Claude Monet and Vincent van Gogh.

Although Monet’s Bathers at la Grenouillère (1869) contains cobalt blue in the brighter mid-blues of the water surface and details in the boats, darker blues towards the left, and in the clothing of some of the figures and their reflections, are almost certainly Prussian blue.

Vincent van Gogh’s portrait of La Mousmé from 1888 illustrates some of the difficulties of identifying pigment use. Its unusual title is derived from the Japanese word musume, meaning girl; at the time the French word was understood to mean an ‘easy’ girl.

Infra-red images demonstrate van Gogh’s use of at least two different blues, one of which has been identified as Prussian blue. The two (or more) blue pigments aren’t distributed evenly: on the girl’s jacket, the three blue stripes to the left of the row of buttons contain the most Prussian blue, while the three under her right armpit, which look darker, contain little or no Prussian blue. Van Gogh also mixed yellow with Prussian blue to form the green of the flowers she holds in her hand.

Prussian blue remained a popular pigment in oil and watercolour paints well into the twentieth century, and is still offered in commercial ranges. For many artists, though, it has been replaced by much more recent synthetic blue pigments, such as phthalocyanine (‘phthalo’) blue, introduced around 1970, and is seldom used in Prussian green.

Reference

Barbara H Berrie (1997) Artists’ Pigments, vol 3, ed Elisabeth West Fitzhugh, Archetype. ISBN 978 1 904982 76 0.

One thing we humans are good at is searching. It’s a task we engage in from a few moments after birth until the time we slip away in death, we search everything around us. Locating and identifying that bird of prey wheeling high, finding the house keys, and that book we mislaid some time last week, meeting the perfect partner, discovering the right job, choosing the best education, looking through a Where’s Wally? or Where’s Waldo? book, and so on. Searching has transformed some into explorers like Christopher Columbus, and was the purpose of the chivalric quest. It’s what researchers in every field do, and thanks to Douglas Adams can be answered by the number 42.

Last week my searching took two new turns.

Spotlight

The first was more of a meta-search, in trying to discover more about the internals of Spotlight. Following the example of Maynard Handley, who has used them so successfully in understanding how M-series CPUs work, I looked through patents that have been awarded to Apple for the work of its search engineers. Yesterday’s slightly fuller history of Spotlight search is one result, and there are more to come in the future as I digest those patents concerned with performing search.

There’s a tinge of irony here, as many of my searches have been conducted using Google Patents, alongside Google Scholar one of the remaining search engines that doesn’t yet use AI and attempt to provide its own answers.

Logs

The other marks a new phase in my quest to get more information from the Unified log. Looking back to my first comment here, I realise how wildly over-optimistic I was when I wrote that it “should make my life a lot easier”, and that “a new version of Console will provide improved features to help us wade through logs.” Nine years later, I look wistfully at what remains of Console and realise how wrong I was on both counts.

When RunningBoard arrived in macOS Catalina, I soon noticed how “its log entries are profuse, detailed, and largely uncensored for privacy.” Since then it has proved garrulous to the point where its apparently ceaseless log chatter is a distraction, and can overwhelm attempts to read other log entries. I suspect it has contributed significantly to those advanced Mac users who now refuse to even try to make sense of the log.

One answer might be to tweak log preferences to shut out this noise, but given the purpose of RunningBoard in monitoring the life cycle of apps, why not try to use the information it provides? To do that, it’s first necessary to understand RunningBoard’s idiosyncratic language of assertions, and its protocols under which they’re acquired. The only way to do that without documentation is by observation: catalogue over 30 of those assertions for an interesting example like Apple’s Developer app, and see what they reveal.

By far the most informative entries from RunningBoard are those announcing that it’s acquiring an assertion, such as
Acquiring assertion targeting [app<application.developer.apple.wwdc-Release.9312198.9312203(501)>:2946] from originator [osservice<com.apple.uikitsystemapp(501)>:748] with description <RBSAssertionDescriptor| "com.apple.frontboard.after-life.subordinate" ID:424-748-2228 target:2946 attributes:[
<RBSDomainAttribute| domain:"com.apple.frontboard" name:"AfterLife-Subordinate" sourceEnvironment:"(null)">
]>

In a log often censored to the point of being unintelligible, this contains frank and explicit detail. The app is identified clearly, with the user ID of 501 and process ID of 2946. The originator is similarly identified as com.apple.uikitsystemapp with its PID of 748, which is confirmed in the middle digits in the Assertion ID. This is explicitly related to FrontBoard and an attribute named AfterLife-Subordinate. There’s not a single <private> to blight this entry, although further knowledge is needed to decode it fully.

Normally to get such information from a running process would require its source code to be instrumented with calls to write log entries, many of which would be lost to <private>, yet RunningBoard seems happy, for the moment, to provide that information freely. You can see what I mean by applying the predicate
subsystem == "com.apple.runningboard" AND message CONTAINS "Acquiring assertion t"
in LogUI, to obtain a running commentary on active apps and processes. Once you’ve identified a relevant assertion, you can focus attention on other log entries immediately prior to that. I will be following this up in the coming week, with fuller instructions and some demonstrations.

Although neither patents nor assertions have the significance of the number 42, in their own ways they show how the art and science of search aren’t dead yet, nor have they succumbed to AI.

Blue pigments used in painting include some of the oldest used by man, and others that led the change to modern synthetic pigments driven by the arrival of chemistry in the eighteenth century. This weekend I look at two examples, today the queen of pigments, ultramarine, and tomorrow the first synthetic chemical, Prussian blue.

Originally made by crushing and grinding the semi-precious stone lapis lazuli, the cost of ultramarine has exceeded that of gold. Seen in paintings, it produces a rich slightly reddish blue which stands the test of time, as distinctive and effective today as when it was first used. And its use has a history of unmasking fakes and forgeries.

The sole source of lapis lazuli in Europe and the West were quarries in Badakshan, described by Marco Polo and now in Afghanistan. It appears that wall paintings made around 507-554 CE adjacent to the great Buddahs of Bamiyan were the first to have used the mineral as a pigment. It was then used in early Persian miniatures, and in early Chinese and Indian paintings too. Tragically, these wall paintings in Bamiyan, Afghanistan, were damaged by the Taliban in 2001 when the two statues were destroyed, and their restoration has made little progress since.

The powdered pigment had made its way, first along the Silk Road, then by sea, to traders in Venice by about 1300. By the Renaissance, it was established as one of the most important and precious of all the pigments used in European art.

Because of its beauty and high cost, ultramarine blue was used for the robes of Jesus Christ and the Virgin Mary. Duccio’s panels from the Maestà Predella, including this of The Healing of the Man born Blind, show this tradition in its earliest years, around 1307-11. As a pigment, it proved practical in egg tempera as here, and in oils, watercolour, and fresco.

Ultramarine blue has been found in the van Eyck brothers’ Ghent Altarpiece from about 1432 (above), and particularly in its most famous panel, The Mystic Lamb, below.

Sandro Botticelli’s early tempera on panel painting Adoration of the Kings from about 1470, apparently made with Filippino Lippi, shows two different blue colours and purple. He painted the purple with an opaque underpainting of lead white tinted with a red lake derived from madder, to create pink. That was then glazed with quite coarse particles of ultramarine blue, so the pigment was thinly dispersed.

Peter Paul Rubens used ultramarine blue widely in his magnificent triptych now in Antwerp Cathedral. In its centre panel, Descent from the Cross (1612-14), it has been found combined with indigo and other pigments.

In van Dyck’s Charity from 1627-8, its most obvious use is in the blue cape, where ultramarine blue was painted over indigo, applied as both a tint and as a glaze over the top.

Visit any of the larger galleries with substantial collections of paintings made before 1700, and you will see works with drapery that I can only describe as arresting in the brilliance of their ultramarine blue. One stunning example in the National Gallery in London is Sassoferrato’s The Virgin in Prayer from 1640-50. The Virgin’s cloak looks as if it was painted only yesterday, and that colour makes you stop in your tracks and draws you into the painting, like no other pigment can.

Given its importance, and limited supply, considerable effort was devoted to ensuring that natural ultramarine blue was of the highest quality, and alternative sources were sought. Deposits in the Chilean Andes, and near Lake Baikal in Siberia, weren’t developed until the nineteenth century, and attempts to make synthetic ultramarine proved unsuccessful until 1828, when Jean Baptiste Guimet was awarded a prize of six thousand francs for his discovery. Almost simultaneously, C G Gmelin of Tübingen discovered a slightly different method.

Commercial production had started by 1830, and it became known as French ultramarine, to distinguish it from the natural pigment. Although almost identical in colour and performance, there are significant differences between natural and synthetic ultramarine when tested in the laboratory. This has enabled the examination of paintings to determine the source of their pigment, and has brought some surprises. These most often relate to later overpainting during restoration. For example, two areas of much later painting have been discovered in the van Eycks’ Ghent Altarpiece.

Examination of Édouard Manet’s Corner of a Café-Concert, from 1878-80, has shown that he used synthetic ultramarine in its blue passages, for example.

Pierre-Auguste Renoir’s The Umbrellas, from about 1881-86, uses synthetic ultramarine in a methodical fashion. The first stage in its painting used only cobalt blue, but in its second stage synthetic ultramarine was applied extensively.

Vincent van Gogh’s A Wheatfield, with Cypresses (1889) contains synthetic ultramarine in its deepest blues, and in some areas of green, although it’s unusual to find ultramarine mixed to form green. Before synthetic pigment became available, this would have been far too expensive a way of making any significant amount of green, but once much cheaper pigment came onto the market, that became more feasible, if still unusual.

The ability to distinguish synthetic ultramarine, which didn’t exist before about 1828, and the natural pigment has proved important in detecting some forgeries. Only the most ignorant would attempt to pass off a painting made with synthetic ultramarine as being very old, but a few fakes fell at that hurdle.

Han van Meegeren was far too knowledgeable and cunning to be caught so easily. He used natural ultramarine, for example when he sold The Men at Emmaus (1937) to the Museum Boijmans Van Beuningen as a Vermeer. What no one knew at the time was that his ultramarine looked genuine, but had been contaminated with a small amount of cobalt blue, which wasn’t discovered until 1803-04, and was first used as a pigment in 1806.

In 1960, the modern artist Yves Klein worked with the paint supplier Edouard Adam to ‘invent’ a paint he termed International Klein Blue (IKB). Although its formulation is a secret, it’s almost entirely synthetic ultramarine blue pigment in a polyvinyl acetate binder.

Like all the best queens, ultramarine blue has an unnerving habit of revealing the truth.

Reference

Joyce Plesters (1993) Artists’ Pigments, vol 2, ed Ashok Roy, Archetype. ISBN 978 1 904982 75 3.

Here are this weekend’s Mac riddles to entertain you through family time, shopping and recreation.

1: Successor to 3 inside a scheme was part of a popular atelier.

2: High speed subatomic particle took the lead in the 1990s.

3: Creator of a squire’s assistant was the first, but died before Mac OS X.

To help you cross-check your solutions, or confuse you further, there’s a common factor between them.

I’ll post my solutions first thing on Monday morning.

Please don’t post your solutions as comments here: it spoils it for others.

Since writing A brief history of local search, I have come across numerous patents awarded to Apple and its engineers for the innovations that have led to Spotlight. This more detailed account of the origins and history of Spotlight uses those primary sources to reconstruct as much as I can at present.

1990

ON Technology, Inc. released On Location, the first local search utility for Macs, a Desk Accessory anticipating many of the features to come in Spotlight 15 years later. This indexed text found in the data fork of files, using format-specific importer modules to access those written by Microsoft Word, WordPerfect, MacWrite and other apps of the day. Those files and their indexed contents were then fully searchable. This required System Software 6.0 or later, and a Mac with a hard disk and at least 1 MB of RAM. It was developed by Roy Groth, Rob Tsuk, Nancy Benovich, Paul Moody and Bill Woods.

1991

Version 2 of On Location was released. ON Technology was later acquired by Network Corporation, then by Symantec in 2003.

1994

AppleSearch was released, and bundled in Workgroup Servers. This was based on a client-server system running over AppleShare networks. September’s release of System Software 7.5 introduced a local app Find File, written by Bill Monk.

1998

Sherlock was released in Mac OS 8.5. This adopted a similar architecture to AppleSearch, using a local service that maintained indexes of file metadata and content, and a client app that passed queries to it. This included remote search of the web through plug-ins working with web search engines, as they became available.

Early patent applications were filed by Apple’s leading engineers who were working on Sherlock, including US Patent 6,466,901 B1 filed 30 November 1998 by Wayne Loofbourrow and David Cásseres, for a Multi-language document search and retrieval system.

1999

Sherlock 2 was released in Mac OS 9.0. This apparently inspired developers at Karelia Software to produce Watson, ‘envisioned as Sherlock’s “companion” application, focusing on Web “services” rather than being a “search” tool like Sherlock.’

2000

On 5 January, Yan Arrouye and Keith Mortensen filed what became Apple’s US Patent 6,847,959 B1 for a Universal Interface for Retrieval of Information in a Computer System. This describes the use of multiple plug-in modules for different kinds of search, in the way that was already being used in Sherlock. Drawings show that it was intended to be opened using an item on the right of the menu bar, there titled [GO-TO] rather than using the magnifying glass icon of Sherlock or Spotlight. This opened a search dialog resembling a prototype for Spotlight, and appears to have included ‘live’ search conducted as letters were typed in.

2001

Karelia Software released Watson.

2002

Mac OS X Jaguar brought Sherlock 3, which many considered had an uncanny resemblance to Watson. That resulted in acrimonious debate.

2005

In preparation for the first Intel Macs, Mac OS X 10.4 Tiger, released in April 2005, introduced Spotlight as a replacement for Sherlock, which never ran on Intel Macs.

Initially, the Spotlight menu command dropped down a search panel as shown here, rather than opening a window as it does now.

2006

On 4 August, John M Hörnkvist and others filed what became US Patent 7,783,589 B2 for Inverted Index Processing, for Apple. This was one of a series of related patents concerning Spotlight indexing. Just a week later, on 11 August, Matthew G Sachs and Jonathan A Sagotsky filed what became US Patent 7,698,328 B2 for User-Directed search refinement.

A Finder search window, precursor to the modern Find window, is shown in the lower left of this screenshot taken from Tiger in 2006.

2007

Spotlight was improved in Mac OS 10.5 Leopard, in October. This extended its query language, and brought support for networked Macs that were using file sharing.

This shows a rather grander Finder search window from Mac OS X 10.5 Leopard in 2009.

2014

Search attributes available for use in the search window are shown here in OS X 10.9 Mavericks, in 2014.

In OS X 10.10 Yosemite, released in October, web and local search were merged into ‘global’ Spotlight, the search window that opens using the Spotlight icon at the right end of the menu bar, accompanied by Spotlight Suggestions.

2015

John M Hörnkvist and Gaurav Kapoor filed what was to become US Patent 10,885,039 B2 for Machine learning based search improvement, which appears to have been the foundation for Spotlight Suggestions, in turn becoming Siri Suggestions in macOS Sierra. Those were accompanied by remote data collection designed to preserve the relative anonymity of the user.

This shows a search in Global Spotlight in macOS 10.12 Sierra, in 2017.

c 2019

Apple acquired Laserlike, Inc, whose technology (and further patents) has most probably been used to enhance Siri Suggestions. Laserlike had already filed for patents on query pattern matching in 2018.

I’m sure there’s a great deal more detail to add to this outline, and welcome any additional information, please.

4 August 2025: I’m very grateful to Joel for providing me with info and links for On Location, which I have incorporated above.