How to warp a tablet loom (/neolithic digital computing device)

Tablet looms have some interesting properties. Firstly, they are very
very old – our neolithic ancestors invented them. Secondly they
are quite straightforward to make and weave but form an extremely
complex structure that incorporates both weaving and braiding (and one I
haven’t managed to simulate correctly yet) – they are also the only form
of weaving that has never been mechanised.

I’ve learned to warp tablets very much by trial and error, so I expect
there are many improvements possible (please let me know), but as I had
to warp a load of tablet looms for the weavecoding workshop in Düsseldorf last
week, I thought I’d document the process here.

The first thing you need to do is make the tablets themselves from
fairly stiff card. You need squares of about 5cm, and holes punched out
from the corners. Beer mats or playing cards are good, I’m just using recycled card here. It saves a bit of time later if you can get the holes lined up when
the tablets are stacked together – but I’ve never managed to do this
very well. A good number of cards to start with are 8 or 10, fewer in
number are easier to manipulate and use less yarn – if you don’t have
much to spare.

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The second step is to prepare the warp yarn. You need four separate
balls or cones of wool – it’s easiest to start with four different
colours, although you can make more patterns with double faced weave
(two colours opposite each other on the cards). Fluffy knitting wool
works fine but can catch and be annoying sometimes, cotton is better. In
order to help prevent the yarn getting tangled together which is
probably the biggest problem with this job – it’s a good idea to set
this up so the yarn passes through the back of a chair with the yarn on
the floor like this – it restricts the distance the balls roll as you
pull the yarn.

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You need two sticks you can easily loop the warp over, I’m using a cut
broom stick clamped to the chair here. The distance between them determines
how long the final woven band will be, a metre or so is good.

Next you need to thread each of the four warp threads through the
corners of the tablets – each thread needs it’s own corner so be careful
not to mix them up. If the holes line up you can do them all at once,
otherwise it’s one by one.

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Here are the tablets with all the corners threaded.

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Now we tie the threads together looped over the warp stick furthest from
the yarn, this knot is temporary.

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Hook the other end of the warp over the stick on the other side, and
leave one of the tablets half way along. Loop it back again leaving
another tablet – go backwards and forwards repeating.

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I can never manage to keep the tablets in order, and usually end up with a mess like this – don’t panic if you get a similar result!

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When you have done all of the tablets, quickly check that every warp
pass has a card associated with it and then cut the first knot and tie
the last warp threads to the first.

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This gives you a continuous warp, which is good for adjusting the
tension. Group all the cards together and arrange them so the colours
are aligned – rotate them until the same colours are at the top and the bottom.

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This is also a good point to check the twist of the tablets so they alternate in
terms of the direction the threads are coming from. This is quite
difficult to explain with text but these images may help. It’s basically a bit easier if they are consistent when you start weaving, then you can see how changing this alters the patterns as you go.

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You can actually reorder and flip the tablets at any time, even after
starting weaving – so none of this is critical. It’s handy to equalise
the tension between the warp threads at this point though, so grab all
the cards in alignment, put some tension on the warp and drag them up
and down the warp – if the loops at either end are not too close this
should get the lengths about the same.

Once this is done, tie all the tablets together to preserve their order
and alignment.

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Then tie loops of strong cord around both ends of the warp.

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Then you’re done – you can pull the ends off the sticks and start tablet
weaving!

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As I needed to transport the tablet looms I wrapped the warps (keeping the upper/lower threads separated) around cardboard tubes to keep the setup from getting tangled up. This seemed to work well:

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If you find one of the warp threads is too long and is causing
a tablet to droop when the warp is under tension, you can pull it tight
and tie it back temporarily, after weaving a few wefts it will hold in
place.

The two most important things I’ve learned about weaving – the older the
technique the more forgiving it is to mistakes, and you can never have
too many sticks.

Red King – listening to coevolution

Scientific models are used by researchers in order to understand interactions that are going on around us all the time. They are like microscopes – but rather than observing objects and structures, they focus on specific processes. Models are built from the ground up from mathematical rules that we infer from studying ecosystems, and they allow us to run and re-run experiments to gain understanding, in a way which is not possible using other methods.

I’ve managed to reproduce many of the patterns of co-evolution between the hosts and parasites in the red king model by tweaking the parameters, but the points at which certain patterns emerge is very difficult to pin down. I thought a good way to start building an understanding of this would be to pick random parameter settings (within viable limits) and ‘sweep’ paths between them – looking for any sudden points of change, for example:

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This is a row of simulations which are each run for 600 timesteps, with time running downwards. The parasite is red and the host is blue, and both organism types are overlayed so you can see them reacting to each other through time. Each run has a slightly different parameter setting, gradually changing between two settings as endpoints. Halfway through there is a sudden state change – from being unstable it suddenly locks into a stable situation on the right hand side.

I’ve actually mainly been exploring this through sound so far – I’ve built a setup where the trait values are fed into additive synthesis (adding sine waves together). It seems appropriate to keep the audio technique as direct as possible at this stage so any underlying signals are not lost. Here is another parameter sweep image (100 simulations) and the sonified version, which comprises 2500 simulations, overlapped to increase sound density.

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You can hear quite a few shifts and discontinuities between different branching patterns that emerge at different points – writing this I realise an animated version might be a good idea to try too.

Stereo is done by slightly changing one parameter (the host tradeoff curve) across the left and right channels – so it gives the changes a sense of direction, and you are actually hearing 5000 simulations being run in total, in both ears. All the code so far (very experimental at present) is here. The next thing to do is to take a step back and think about the best way to invite people in to experience this strange world.

Here are some more tests:

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Red King: Host/Parasite co-evolution citizen science

A new project begins, on the subject of ecology and evolution of infectious disease. This one is a little different from a lot of Foam Kernow’s citizen science projects in that the subject is theoretical research – and involves mathematical simulations of populations of co-evolving organisms, rather than the direct study of real ones in field sites etc.

The simulation, or model, we are working with is concerned with the co-evolution of parasites and their hosts. Just as in more commonly known simulations of predators and prey, there are complex relationships between hosts and parasites – for example if parasites become too successful and aggressive the hosts start to die out, in turn reducing the parasite populations. Hosts can evolve to resist infection, but this has an overhead that starts to become a disadvantage when most of a population is free of parasites again.

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Example evolution processes with different host/parasite trade-offs.

Over time these relationships shift and change, and this happens in different patterns depending on the starting conditions. Little is known about the categorisation of these patterns, or even the range of relationships possible. The models used to simulate them are still a research topic in their own right, so in this project we are hoping to explore different ways people can both control a simulation (perhaps with an element of visual live programming), and also experience the results in a number of ways – via a sonifications, or game world. The eventual, ambitious aim – is to provide a way for people to feedback their discoveries into the research.

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A cryptoweaving experiment

Archaeologists can read a woven artifact created thousands of years ago, and from its structure determine the actions performed in the right order by the weaver who created it. They can then recreate the weaving, following in their ancestor’s ‘footsteps’ exactly.

This is possible because a woven artifact encodes time digitally, weft by weft. In most other forms of human endeavor, reverse engineering is still possible (e.g. in a car or a cake) but instructions are not encoded in the object’s fundamental structure – they need to be inferred by experiment or indirect means. Similarly, a text does not quite represent its writing process in a time encoded manner, but the end result. Interestingly, one possible self describing artifact could be a musical performance.

Looked at this way, any woven pattern can be seen as a digital record of movement performed by the weaver. We can create the pattern with a notation that describes this series of actions (a handweaver following a lift plan), or move in the other direction like the archaeologist, recording a given notation from an existing weave.

example
A weaving and its executable code equivalent.

One of the potentials of weaving I’m most interested in is being able to demonstrate fundamentals of software in threads – partly to make the physical nature of computation self evident, but also as a way of designing new ways of learning and understanding what computers are.

If we take the code required to make the pattern in the weaving above:

(twist 3 4 5 14 15 16)
(weave-forward 3)
(twist 4 15)
(weave-forward 1)
(twist 4 8 11 15)

(repeat 2
 (weave-back 4)
 (twist 8 11)
 (weave-forward 2)
 (twist 9 10)
 (weave-forward 2)
 (twist 9 10)
 (weave-back 2)
 (twist 9 10)
 (weave-back 2)
 (twist 8 11)
 (weave-forward 4))

We can “compile” it into a binary form which describes each instruction – the exact process for this is irrelevant, but here it is anyway – an 8 bit encoding, packing instructions and data together:

8bit instruction encoding:

Action  Direction  Count/Tablet ID (5 bit number)
0 1         2              3 4 5 6 7 

Action types
weave:    01 (1)
rotate:   10 (2)
twist:    11 (3)

Direction
forward: 0
backward: 1

If we compile the code notation above with this binary system, we can then read the binary as a series of tablet weaving card flip rotations (I’m using 20 tablets, so we can fit in two instructions per weft):

0 1 6 7 10 11 15
0 1 5 7 10 11 14 15 16
0 1 4 5 6 7 10 11 13
1 6 7 10 11 15
0 1 5 7 11 17
0 1 5 10 11 14
0 1 4 6 7 10 11 14 15 16 17
0 1 2 3 4 5 6 7 11 12 15
0 1 4 10 11 14 16
1 6 10 11 14 17
0 1 4 6 11 16
0 1 4 7 10 11 14 16
1 2 6 10 11 14 17
0 1 4 6 11 12 16
0 1 4 7 10 11 14 16
1 5

If we actually try weaving this (by advancing two turns forward/backward at a time) we get this mess:

close

The point is that (assuming we’ve made no mistakes) this weave represents *exactly* the same information as the pattern does – you could extract the program from the messy encoded weave, follow it and recreate the original pattern exactly.

The messy pattern represents both an executable, as well as a compressed form of the weave – taking up less space than the original pattern, but looking a lot worse. Possibly this is a clue too, as it contains a higher density of information – higher entropy, and therefore closer to randomness than the pattern.

Pixel Quipu

The graphviz visualisations we’ve been using for quipu have quite a few limitations, as they tend to make very large images, and there is limited control over how they are drawn. It would be better to be able to have more of an overview of the data, also rendering the knots in the right positions with the pendants being the right length.

Meet the pixelquipu!

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These are drawn using a python script which reads the Harvard Quipu Database and renders quipu structure using the correct colours. The knots are shown as a single pixel attached to the pendant, with a colour code of red as single knot, green for a long knot and blue as a figure of eight knot (yellow is unknown or missing). The value of the knot sets the brightness of the pixel. The colour variations for the pendants are working, but no difference between twisted and alternating colours, also no twist direction is visualised yet.

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Another advantage of this form of rendering is that we can draw data entropy within the quipu in order to provide a different view of how the data is structured, as a attempt to uncover hidden complexity. This is done hierarchically so a pendant’s entropy is that of its data plus all the sub-pendants, which seemed most appropriate given the non-linear form that the data takes.

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e-ur037

We can now look at some quipus in more detail – what was the purpose of the red and grey striped pendants in the quipu below? They contain no knots, are they markers of some kind? This also seems to be a quipu where the knots do not follow the decimal coding pattern that we understand, they are mostly long knots of various values.

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There also seems to be data stored in different kinds of structure in the same quipu – the collection of sub-pendants below in the left side presumably group data in a more hierarchical manner than the right side, which seems much more linear – and also a colour change emphasises this.

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Read left to right, this long quipu below seems very much like you’d expect binary data to look – some kind of header information or preamble, followed by a repeating structure with local variation. The twelve groups of eight grey pendants seem redundant – were these meant to be filled in later? Did they represent something important without containing any knots? We will probably never know.

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The original thinking of the pixelquipu was to attempt to fit all the quipus on a single page for viewing, as it represents them with the absolute minimum pixels required. Here are both pendant colour and entropy shown for all 247 quipu we have the data for:

all

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Quipu: further experiments in Düsseldorf

A report on further experimentation with Julian Rohrhuber and his students at the Institute for Music and Media in Düsseldorf during our coding with weaves and knots remote seminar this week.

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As we have so little idea what the Inca are telling us in their Quipu, it seems appropriate to add a cryptanalysis approach to our toolkit of inquiry. One of the first things that a cryptanalyst will do when inspecting an unknown system is to visualise it’s entropy in order to get a handle on any structures or patterns in the underlying information. This concept comes from Claude Shannon’s work on information theory in the 40’s, where he proved that information obeys fundamental laws of physics. The concept that information and “cyberspace” may not be as intangible and otherworldly as we might believe (in fact is grounded in physical reality along with everything else) is one of the recurring themes of the weavingcodes project.

Shannon’s innovation was to separate the concepts of data quantity from information value, and he claims that information is equivalent to surprise – the more surprising a piece of data is, the more information it contains. Conversely a piece of information which we expect to hear by definition doesn’t really tell us very much. The potential for some data to be surprising (or more specifically it’s potential to reduce our uncertainty) can be measured statistically, with a quantity he called entropy, as it is analogous to states in thermodynamic systems.

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Shannon defined a generalised communication system, which is handy to give us a way of reasoning about our situation in relation to the Inca. Our main unknown is the source of the messages they are sending us, are they accounting information, calendars or stories? We know a bit more about the transmitters of the messages, the khipukamayuq – the knot makers and quipu keepers. At the time Shannon was working on information theory, he was part of the start of the movement away from analogue, continuous signals and towards digital signals – with advantages that they are highly resistant to noise and can be carried further and combined together to increase bandwidth. Quipu are also mainly comprised of digital information – the type of a knot, the number of turns it’s comprised of or the twist direction of a thread are all discreet (either one thing or another) and therefore highly robust to material decay or decomposition. We can still ‘read’ them confidently after 500 years or more without the digital signal they represent being degraded too badly, if only we could understand it. At the same time, none of us working on this have access to a real quipu, so our receivers are the archaeologists and historians who study them, and compile archives such as the Harvard Quipu Archive we are using.

Although entropy is a very simplistic approach mathematically, it’s main use is to give us a tool for measuring the comparative information carrying potential of data which we have no idea about. Here are all the quipu in the Harvard database in order of average entropy bits they contain (only listing every other quipu ID):

entropy-per-quipu

This graph is calculated by making lists of all the discreet data of the same type, e.g. knot value, type, tying direction, pendant colours and ply direction (ignoring lengths and knot positions as these are continuous) – then calculating Shannon entropy on histograms for each one and adding them together.

We can also compare different types of information against one another, for example the main data we currently understand has some specific meaning are the knot values, partly derived from the knot type (long, single or figure of eight), which represent a decimal notation. If we compare the entropy of these we can expect them to have roughly similar average amounts of information:

entropy-values-types

The meanings of colours, ply and structure are largely unknown. Here are the knot values compared with the colours:

entropy-values-colours

And this is pendant ply direction compared with knot values for each quipu:

entropy-values-ply

At this point the most useful aspect of this work is to give us some outliers to inspect visually and sonically – more on that soon.

Photos from the machine wilderness workshop

Busy times at Foam Kernow, here are some photos from the Machine Wilderness Workshop weekend before last. This was a project between Foam Amsterdam and us, with 30 participants from all over the place geographically and professionally. My role was as facilitator, so mainly obtaining raw materials (electronic toys, recycled trash and e-waste) as well as a bit of cooking and general running around which I found very enjoyable. The machines invented and prototyped were grounded in the environment of the Penryn river in Cornwall, so common themes were seaweed biomimicry and experiments with estuarine mud, both as a surprisingly rich power source as well as a design medium in it’s own right.

I’ll leave the in-depth write ups to those leading the event, but one of my interests was to see how a workshop involving e-waste would work, practically and as an inspiration – with an eye to doing this with primary school kids and teachers. We managed to locate a good quantity of old toys from various local second hand stores and warehouses, quite a modest outlay in return for some very good mechanics, motors and electronic parts. Resisting the temptation to take them to bits beforehand meant that the participants could open them up and discover what they could use, one of the best items was a bubble machine – inside was a good air pump and lots of mechanics (total cost ~£1.50). This was incorporated into a robot lifeform that was in part augmented by moss growth and LED lights.

See the rest of the photos here.

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The UAV toolkit & appropriate technology

The UAV toolkit’s second project phase is now complete, the first development sprint at the start of the year was a bit of research into what we could use an average phone’s sensors for, resulting in a proof of concept remote sensing android app that allowed you to visually program different scripts which we then tested on some drones, a radio controlled plane and a kite.

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This time we had a specific focus on environmental agencies, working with Katie Threadgill at the Westcountry Rivers Trust has meant we’ve had to think about how this could be used by real people in an actual setting (farm advisors working with local farmers). Making something cheap, open source and easy to use, yet open ended has been the focus – and we are now looking at providing WRT with a complete toolkit which would comprise a drone (for good weather) a kite (for bad weather/no flight licences required) and an android phone so they don’t need to worry about destroying their own if something goes wrong. Katie has produced this excellent guide on how the app works.

The idea of appropriate technology has become an important philosophy for projects we are developing at Foam Kernow, in conjunction with unlikely connections in livecoding and our wider arts practice. For example the Sonic Bike project – where from the start we restricted the technology so that no ‘cloud’ network connections are required and all the data and hardware required has to fit on the bike – with no data “leaking” out.

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With the UAV toolkit the open endedness of providing a visual programming system that works on a touchscreen results in an application that is flexible enough to be used in ways and places we can’t predict. For example in crisis situations, where power, networking or hardware is not available to set up remote sensing devices when you need them most. With the UAV toolkit we are working towards a self contained system, and what I’ve found interesting is how many interface and programming ‘guidelines’ I have to bend to make this possible – open endedness is very much against the grain of contemporary software design philosophy.

The “app ecosystem” is ultimately concerned with elevator pitches – to do one thing, and boil it down to the least actions possible to achieve it. This is not a problem in itself, but the assumption that this is the only philosophy worth consideration is wrong. One experience that comes to mind recently is having to make and upload banner images of an exact size to the Play Store before it would allow me to release an important fix needed for Mongoose 2000, which is only intended to ever have 5 or 6 users.

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For the UAV toolkit, our future plans include stitching together photos captured on the phone and producing a single large map without the need to use any other software on a laptop. There are also interesting possibilities regarding distributed networking with bluetooth and similar radio systems – for example sending code to different phones is needed, as currently there is no way to distribute scripts amongst users. This could also be a way of creating distributed processing – controlling one phone in a remote location with another via code sent by adhoc wifi or SMS for example.

Procedural weave rendering

We’ve been working on new approaches to 3D rendering ancient weaves, using Alex’s new behavioural language (which describes a weave from the perspective of a single thread) as the description for our modelling. This new approach allows us to build a fabric out of a single geometric shape, where warp and weft are part of the same thread.

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This is mix of tabby and 2:2 twill, created by this code:

warp 12 24 ++ [TurnIn] ++ threadWeftBy'' Odd (rot 3) ([Over,Under]) 12 12 ++ threadWeftBy'' Odd (rot 3) ([Over,Over,Under,Under]) 12 12

I’m still learning this language, but more on that soon. This line produces an large list of instructions the weave renderer uses to build it’s model, turning the thread and shifting it up and down as it crosses itself.

In the video in his last post Alex describes using this to mix two separate weaving techniques together, which is one of our main reasons for developing this language – existing weave simulations cannot replicate the weaving technology of the ancient Greeks who for example, combined tablet and warp weighted weaving in the same fabric.

The second problem with weave simulations is shown by the following screenshot from a popular existing system:

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Fabrics modelled in this way are considered to infinitely repeating sections with chopped off threads. There is no consideration for the selvedge at the edge of the fabric – which as we’ve shown in our past research is almost like a completely separate weave system of it’s own, and rarely considered by notation systems or modelling (and often left to the weaver to ‘livecode’). Here is a different view of the same fabric:

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We can also now introduce other changes to the yarn structure, for example modifying the width using a sine wave.

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I still have a few glitches to fix as you can see above, but here is a video of the development process from the first script, getting the polygons lined up, fixing the turning, adding over/under, reading Alex’s code and finally lining everything up.

Weavecoding performance experiments in Cornwall

Last week the weavecoding group met at Foam Kernow for our Cornish research gathering. As we approach the final stages of the project our discussions turn to publications, and which ideas from the start need revisiting. While they were here, I wanted to give local artists and researchers working with code and textiles a chance to meet Ellen, Emma and Alex. As we are a non-academic research organisation I wanted to avoid the normal powerpoint talks/coffee events and try something more informal and inclusive.

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One of the original ideas we had was to combine weaving and coding in a performance setting, to both provide a way to make livecoding more inclusive with weaving, and at the same time to highlight the digital thought processes involved in weaving. Amber made vegetarian sushi for our audience and we set up the Jubilee Warehouse with a collection of experiments from the project:

  • The newly warped table loom with a live camera/projection from underneath the fabric as it was woven with codes for different weaves on post-it notes for people to try.
  • The tablet/inkle loom to represent ancient weaving techniques.
  • The pattern matrix tangible weavecoding machine and Raspberry Pi.
  • A brand new experiment by Francesca with a dancemat connected to the pattern matrix software for dance code weaving!
  • The slub livecoding setup.

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This provided an opportunity for people to try things out and ask questions/provide discussion starting points. Our audience consisted of craft researchers, anthropological biologists, architects, game designers and technologists – so it all went on quite a lot longer than we anticipated! Alex and I provided some slub livecoded music to weave by, and my favourite part was the live weaving projection – with more projectors we could develop this combination of code and weaving performance more. Thanks to Emma for all the videos and photos!

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