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ScienceDaily

Single photons from a silicon chip

Quantum technology holds great promise: Just a few years from now, quantum computers are expected to revolutionize database searches, AI systems, and computational simulations. Today already, quantum cryptography can guarantee absolutely secure data transfer, albeit with limitations. The greatest possible compatibility with our current silicon-based electronics will be a key advantage. And that is precisely where physicists from the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) and TU Dresden have made remarkable progress: The team has designed a silicon-based light source to generate single photons that propagate well in glass fibers.

Quantum technology relies on the ability to control the behavior of quantum particles as precisely as possible, for example by locking individual atoms in magnetic traps or by sending individual light particles — called photons — through glass fibers. The latter is the basis of quantum cryptography, a communication method that is, in principle, tap-proof: Any would-be data thief intercepting the photons unavoidably destroys their quantum properties. The senders and receivers of the message will notice that and can stop the compromised transmission in time.

This requires light sources that deliver single photons. Such systems already exist, especially based on diamonds, but they have one flaw: “These diamond sources can only generate photons at frequencies that are not suitable for fiber optic transmission,” explains HZDR physicist Dr. Georgy Astakhov. “Which is a significant limitation for practical use.” So Astakhov and his team decided to use a different material — the tried and tested electronic base material silicon.

100,000 single photons per second

To make the material generate the infrared photons required for fiber optic communication, the experts subjected it to a special treatment, selectively shooting carbon into the silicon with an accelerator at the HZDR Ion Beam Center. This created what is called G-centers in the material — two adjacent carbon atoms coupled to a silicon atom forming a sort of artificial atom.

When radiated with red laser light, this artificial atom emits the desired infrared photons at a wavelength of 1.3 micrometers, a frequency excellently suited for fiber optic transmission. “Our prototype can produce 100,000 single photons per second,” Astakhov reports. “And it is stable. Even after several days of continuous operation, we haven’t observed any deterioration.” However, the system only works in extremely cold conditions — the physicists use liquid helium to cool it down to a temperature of minus 268 degrees Celsius.

“We were able to show for the first time that a silicon-based single-photon source is possible,” Astakhov’s colleague Dr. Yonder Berencén is happy to report. “This basically makes it possible to integrate such sources with other optical components on a chip.” Among other things, it would be of interest to couple the new light source with a resonator to solve the problem that infrared photons largely emerge from the source randomly. For use in quantum communication, however, it would be necessary to generate photons on demand.

Light source on a chip

This resonator could be tuned to exactly hit the wavelength of the light source, which would make it possible to increase the number of generated photons to the point that they are available at any given time. “It has already been proven that such resonators can be built in silicon,” reports Berencén. “The missing link was a silicon-based source for single photons. And that’s exactly what we’ve now been able to create.”

But before they can consider practical applications, the HZDR researchers still have to solve some problems — such as a more systematic production of the new telecom single-photon sources. “We will try to implant the carbon into silicon with greater precision,” explains Georgy Astakhov. “HZDR with its Ion Beam Center provides an ideal infrastructure for realizing ideas like this.”

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ScienceDaily

Infinite chains of hydrogen atoms have surprising properties, including a metallic phase

An infinite chain of hydrogen atoms is just about the simplest bulk material imaginable — a never-ending single-file line of protons surrounded by electrons. Yet a new computational study combining four cutting-edge methods finds that the modest material boasts fantastic and surprising quantum properties.

By computing the consequences of changing the spacing between the atoms, an international team of researchers from the Flatiron Institute and the Simons Collaboration on the Many Electron Problem found that the hydrogen chain’s properties can be varied in unexpected and drastic ways. That includes the chain transforming from a magnetic insulator into a metal, the researchers report September 14 in Physical Review X.

The computational methods used in the study present a significant step toward custom-designing materials with sought-after properties, such as the possibility of high-temperature superconductivity in which electrons flow freely through a material without losing energy, says the study’s senior author Shiwei Zhang. Zhang is a senior research scientist at the Center for Computational Quantum Physics (CCQ) at the Simons Foundation’s Flatiron Institute in New York City.

“The main purpose was to apply our tools to a realistic situation,” Zhang says. “Almost as a side product, we discovered all of this interesting physics of the hydrogen chain. We didn’t think that it would be as rich as it turned out to be.”

Zhang, who is also a chancellor professor of physics at the College of William and Mary, co-led the research with Mario Motta of IBM Quantum. Motta serves as first author of the paper alongside Claudio Genovese of the International School for Advanced Studies (SISSA) in Italy, Fengjie Ma of Beijing Normal University, Zhi-Hao Cui of the California Institute of Technology, and Randy Sawaya of the University of California, Irvine. Additional co-authors include CCQ co-director Andrew Millis, CCQ Flatiron Research Fellow Hao Shi and CCQ research scientist Miles Stoudenmire.

The paper’s long author list — 17 co-authors in total — is uncommon for the field, Zhang says. Methods are often developed within individual research groups. The new study brings many methods and research groups together to combine forces and tackle a particularly thorny problem. “The next step in the field is to move toward more realistic problems,” says Zhang, “and there is no shortage of these problems that require collaboration.”

While conventional methods can explain the properties of some materials, other materials, such as infinite hydrogen chains, pose a more daunting computational hurdle. That’s because the behavior of the electrons in those materials is heavily influenced by interactions between electrons. As electrons interact, they become quantum-mechanically entangled with one another. Once entangled, the electrons can no longer be treated individually, even when they are physically separate.

The sheer number of electrons in a bulk material — roughly 100 billion trillion per gram — means that conventional brute force methods can’t even come close to providing a solution. The number of electrons is so large that it’s practically infinite when thinking at the quantum scale.

Thankfully, quantum physicists have developed clever methods of tackling this many-electron problem. The new study combines four such methods: variational Monte Carlo, lattice-regularized diffusion Monte Carlo, auxiliary-field quantum Monte Carlo, and standard and sliced-basis density-matrix renormalization group. Each of these cutting-edge methods has its strengths and weaknesses. Using them in parallel and in concert provides a fuller picture, Zhang says.

Researchers, including authors of the new study, previously used those methods in 2017 to compute the amount of energy each atom in a hydrogen chain has as a function of the chain’s spacing. This computation, known as the equation of state, doesn’t provide a complete picture of the chain’s properties. By further honing their methods, the researchers did just that.

At large separations, the researchers found that the electrons remain confined to their respective protons. Even at such large distances, the electrons still ‘know’ about each other and become entangled. Because the electrons can’t hop from atom to atom as easily, the chain acts as an electrical insulator.

As the atoms move closer together, the electrons try to form molecules of two hydrogen atoms each. Because the protons are fixed in place, these molecules can’t form. Instead, the electrons ‘wave’ to one another, as Zhang puts it. Electrons will lean toward an adjacent atom. In this phase, if you find an electron leaning toward one of its neighbors, you’ll find that neighboring electron responding in return. This pattern of pairs of electrons leaning toward each other will continue in both directions.

Moving the hydrogen atoms even closer together, the researchers discovered that the hydrogen chain transformed from an insulator into a metal with electrons moving freely between atoms. Under a simple model of interacting particles known as the one-dimensional Hubbard model, this transition shouldn’t happen, as electrons should electrically repel each other enough to restrict movement. In the 1960s, British physicist Nevill Mott predicted the existence of an insulator-to-metal transition based on a mechanism involving so-called excitons, each consisting of an electron trying to break free of its atom and the hole it leaves behind. Mott proposed an abrupt transition driven by the breakup of these excitons — something the new hydrogen chain study didn’t see.

Instead, the researchers discovered a more nuanced insulator-to-metal transition. As the atoms move closer together, electrons gradually get peeled off the tightly bound inner core around the proton line and become a thin `vapor’ only loosely bound to the line and displaying interesting magnetic structures.

The infinite hydrogen chain will be a key benchmark in the future in the development of computational methods, Zhang says. Scientists can model the chain using their methods and check their results for accuracy and efficiency against the new study.

The new work is a leap forward in the quest to utilize computational methods to model realistic materials, the researchers say. In the 1960s, British physicist Neil Ashcroft proposed that metallic hydrogen, for instance, might be a high-temperature superconductor. While the one-dimensional hydrogen chain doesn’t exist in nature (it would crumple into a three-dimensional structure), the researchers say that the lessons they learned are a crucial step forward in the development of the methods and physical understanding needed to tackle even more realistic materials.

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Cascades with carbon dioxide: Making substances out of CO2

Carbon dioxide (CO2) is not just an undesirable greenhouse gas, it is also an interesting source of raw materials that are valuable and can be recycled sustainably. In the journal Angewandte Chemie, Spanish researchers have now introduced a novel catalytic process for converting CO2 into valuable chemical intermediates in the form of cyclic carbonates.

Getting CO2 to react is unfortunately not easy. Currently, most research is focused on the conversion of CO2 into methanol, which can be used as an alternative fuel as well as a feedstock for the chemical industry. Innovative catalytic processes could allow CO2 to be converted into valuable chemical compounds without taking a detour through methanol, perhaps for the production of biodegradable plastics or pharmaceutical intermediates.

One highly promising approach is the conversion of CO2 into organic carbonates, which are compounds that contain a building block derived from carbonic acid, comprising carbon atom attached to three oxygen atoms. Researchers working with Arjan W. Kleij at the Barcelona Institute of Science and Technology (Barcelona), the Institute of Chemical Research of Catalonia (Tarragona), and the Catalan Institute of Research and Advanced Studies (Barcelona), have developed a conceptually new process to produce carbonates in the form of six-membered rings, starting from CO2 and basic, easily accessible building blocks. These cyclic carbonates have great potential for the creation of new CO2-based polycarbonates.

The starting materials are compounds with a carbon-carbon double bond and an alcohol group (-OH) on a neighboring carbon atom (homoallylic alcohols). In the first step of the reaction, the double bond is converted into an epoxide, a three-membered ring with one oxygen and two carbon atoms. The epoxide is able to react with CO2 in the presence of a specific catalyst. The product is a cyclic carbonate in the form of a five-membered ring with three carbon and two oxygen atoms. The carbon atom at the “tip” of the five-membered ring is attached to an additional oxygen atom. In the next step, an organic catalyst (N-heterocyclic base) activates the OH group and causes the five-membered ring to rearrange into a six-membered ring. The oxygen atom from the OH group is integrated into the new ring, while one of the oxygen atoms from the original five-membered ring forms a new OH group. However, the reverse reaction also takes place because the original five-membered ring is significantly more energetically favorable, and only a vanishingly small amount of the six-membered ring is present at equilibrium. The trick is to trap the six-membered ring. The new OH group binds to a reagent (acylation) because its different position makes it considerably more reactive than the original OH group.

This newly developed process gives access to a broad palette of novel, six-membered carbonate rings in excellent yields, with high selectivity and under mild reaction conditions. This widens the repertoire of CO2-based heterocycles and polymers, which are difficult to produce by conventional methods.

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Civilization may need to ‘forget the flame’ to reduce CO2 emissions

Just as a living organism continually needs food to maintain itself, an economy consumes energy to do work and keep things going. That consumption comes with the cost of greenhouse gas emissions and climate change, though. So, how can we use energy to keep the economy alive without burning out the planet in the process?

In a paper in PLOS ONE, University of Utah professor of atmospheric sciences Tim Garrett, with mathematician Matheus Grasselli of McMaster University and economist Stephen Keen of University College London, report that current world energy consumption is tied to unchangeable past economic production. And the way out of an ever-increasing rate of carbon emissions may not necessarily be ever-increasing energy efficiency — in fact it may be the opposite.

“How do we achieve a steady-state economy where economic production exists, but does not continually increase our size and add to our energy demands?” Garrett says. “Can we survive only by repairing decay, simultaneously switching existing fossil infrastructure to a non-fossil appetite? Can we forget the flame?”

Thermoeconomics

Garrett is an atmospheric scientist. But he recognizes that atmospheric phenomena, including rising carbon dioxide levels and climate change, are tied to human economic activity. “Since we model the earth system as a physical system,” he says, “I wondered whether we could model economic systems in a similar way.”

He’s not alone in thinking of economic systems in terms of physical laws. There’s a field of study, in fact, called thermoeconomics. Just as thermodynamics describe how heat and entropy (disorder) flow through physical systems, thermoeconomics explores how matter, energy, entropy and information flow through human systems.

Many of these studies looked at correlations between energy consumption and current production, or gross domestic product. Garrett took a different approach; his concept of an economic system begins with the centuries-old idea of a heat engine. A heat engine consumes energy at high temperatures to do work and emits waste heat. But it only consumes. It doesn’t grow.

Now envision a heat engine that, like an organism, uses energy to do work not just to sustain itself but also to grow. Due to past growth, it requires an ever-increasing amount of energy to maintain itself. For humans, the energy comes from food. Most goes to sustenance and a little to growth. And from childhood to adulthood our appetite grows. We eat more and exhale an ever-increasing amount of carbon dioxide.

“We looked at the economy as a whole to see if similar ideas could apply to describe our collective maintenance and growth,” Garrett says. While societies consume energy to maintain day to day living, a small fraction of consumed energy goes to producing more and growing our civilization.

“We’ve been around for a while,” he adds. “So it is an accumulation of this past production that has led to our current size, and our extraordinary collective energy demands and CO2 emissions today.”

Growth as a symptom

To test this hypothesis, Garrett and his colleagues used economic data from 1980 to 2017 to quantify the relationship between past cumulative economic production and the current rate at which we consume energy. Regardless of the year examined, they found that every trillion inflation-adjusted year 2010 U.S. dollars of economic worldwide production corresponded with an enlarged civilization that required an additional 5.9 gigawatts of power production to sustain itself . In a fossil economy, that’s equivalent to around 10 coal-fired power plants, Garrett says, leading to about 1.5 million tons of CO2 emitted to the atmosphere each year. Our current energy usage, then, is the natural consequence of our cumulative previous economic production.

They came to two surprising conclusions. First, although improving efficiency through innovation is a hallmark of efforts to reduce energy use and greenhouse gas emissions, efficiency has the side effect of making it easier for civilization to grow and consume more.

Second, that the current rates of world population growth may not be the cause of rising rates of energy consumption, but a symptom of past efficiency gains.

“Advocates of energy efficiency for climate change mitigation may seem to have a reasonable point,” Garrett says, “but their argument only works if civilization maintains a fixed size, which it doesn’t. Instead, an efficient civilization is able to grow faster. It can more effectively use available energy resources to make more of everything, including people. Expansion of civilization accelerates rather than declines, and so do its energy demands and CO2 emissions.”

A steady-state decarbonized future?

So what do those conclusions mean for the future, particularly in relation to climate change? We can’t just stop consuming energy today any more than we can erase the past, Garrett says. “We have inertia. Pull the plug on energy consumption and civilization stops emitting but it also becomes worthless. I don’t think we could accept such starvation.”

But is it possible to undo the economic and technological progress that have brought civilization to this point? Can we, the species who harnessed the power of fire, now “forget the flame,” in Garrett’s words, and decrease efficient growth?

“It seems unlikely that we will forget our prior innovations, unless collapse is imposed upon us by resource depletion and environmental degradation,” he says, “which, obviously, we hope to avoid.”

So what kind of future, then, does Garrett’s work envision? It’s one in which the economy manages to hold at a steady state — where the energy we use is devoted to maintaining our civilization and not expanding it.

It’s also one where the energy of the future can’t be based on fossil fuels. Those have to stay in the ground, he says.

“At current rates of growth, just to maintain carbon dioxide emissions at their current level will require rapidly constructing renewable and nuclear facilities, about one large power plant a day. And somehow it will have to be done without inadvertently supporting economic production as well, in such a way that fossil fuel demands also increase.”

It’s a “peculiar dance,” he says, between eliminating the prior fossil-based innovations that accelerated civilization expansion, while innovating new non-fossil fuel technologies. Even if this steady-state economy were to be implemented immediately, stabilizing CO2 emissions, the pace of global warming would be slowed — not eliminated. Atmospheric levels of CO2 would still reach double their pre-industrial level before equilibrating, the research found.

By looking at the global economy through a thermodynamic lens, Garrett acknowledges that there are unchangeable realities. Any form of an economy or civilization needs energy to do work and survive. The trick is balancing that with the climate consequences.

“Climate change and resource scarcity are defining challenges of this century,” Garrett says. “We will not have a hope of surviving our predicament by ignoring physical laws.”

Future work

This study marks the beginning of the collaboration between Garrett, Grasselli and Keen. They’re now working to connect the results of this study with a full model for the economy, including a systematic investigation of the role of matter and energy in production.

“Tim made us focus on a pretty remarkable empirical relationship between energy consumption and cumulative economic output,” Grasselli says. “We are now busy trying to understand what this means for models that include notions that are more familiar to economists, such as capital, investment and the always important question of monetary value and inflation.”

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ProgrammableWeb

Google Adds Digital Ink Recognition to ML Kit

Just a month after announcing changes to ML Kit, Google’s machine learning toolkit for mobile application development, that were designed to simplify the developer experience, Google is again adding new features. This week’s announcement is the addition of Digital Ink Recognition. 

Digital Ink Recognition allows app developers to recognize and interpret stylus and touch inputs. This will allow applications to process users writing and drawing using the same technology that powers Google’s own Gboard handwriting recognition technology. 

Digital Ink Recognition Processing Gboard Data

This new feature is designed to be implemented globally with support for 300+ languages and 25+ writing systems. The drawing recognition functionality is also quite robust, with the power to recognize myriad emojis and shapes. The Digital Ink Recognition API runs locally, so app developers can include the functionality in games that are intended to run offline. 

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Author: <a href="https://www.programmableweb.com/user/%5Buid%5D">KevinSundstrom</a>

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ProgrammableWeb

Facebook Introduces v8.0 of Graph and Marketing APIs

Facebook just announced v8.0 of its GraphTrack this API and MarketingTrack this API APIs. Per usual, the new releases include some breaking changes, feature updates, and deprecations. The company is pointing developers to the Platform Initiatives Hub to stay up to date with all company plans and programs.

Three changes require developer action. By October 24th, developers must leverage a user, app, or client token for querying the Graph API specifically for profile pictures via UID, FB OEmbeds and IG OEmbeds. Second, granular permissions will soon be required for an app to access the business field. By November 2nd, apps need to start requesting granular business_management permissions to the business that owns the ad. Finally, catalog_management and ads_management permissions are being decoupled. By January 31st of next year, developers with access to catalog_management need to prompt users to grant access through the FB Login Dialog.

On the improvements front, business app developers now have better onboarding options and a new reviewable feature called Business Asset User Profile Access. Starting in October, Facebook will move from target cost bidding to cost cap bidding to manage campaign costs.

The Marketing API, versions 5.0 and 6.0 will be removed on September 28th. The Graph API, v3.1 will be removed on October 27th. A number of API endpoints will be deprecated on November 2nd. Check out the Changelog for more details.

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Author: <a href="https://www.programmableweb.com/user/%5Buid%5D">ecarter</a>

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ProgrammableWeb

10 Top APIs for Rentals

These days consumers can rent just about anything. Homes, cars, vacation villas, offices, boats, RVs, furniture, art, solar panels, clothing, garages, sports equipment, garden spaces, party supplies, bikes, scooters, storage, wedding venues, rooms, cameras, smartphones, games and text books are all available to rent for a fee. And for good reason, renting things is generally a more affordable, and sustainable way to get use out of items and property.

Developers wanting to create applications to take advantage of the rental market would need APIs to accomplish the task.

What is a Rentals API?

A Rentals API is an Application Programming Interface that allows developers to connect to data about rental properties or other information normally found in rental marketplaces.

The best place to find these APIs is in the Rentals category of the ProgrammableWeb directory. In this category developers can discover dozens of resources including APIs, SDKs, news and how-to articles, and source code samples for creating applications.

In this article we highlight 10 top Rentals APIs based on ProgrammableWeb readers’ interest.

1. Airbnb API

Airbnb is a vacation rental and room service that allows users to rent out their houses or rooms to travellers. The Airbnb APITrack this API allows developers to access and integrate the functionality of Airbnb with other applications and to create new applications. Recently Airbnb declared TypeScript to be its standard language for Web development. Public documentation is not yet available, and interested developers need to apply for access.

2. MyBuilding API

RealPage’s MyBuilding is an online platform that enables users to manage residential buildings. The MyBuilding APITrack this API provides functions for rental property management and communications. API methods support management of resident accounts and profiles, along with assignment of residents to rental units, reassignment to different units if they move, and terminating tenancy when they move out. Methods also support submission and tracking of maintenance requests. The API also supports community interaction among residents and listings of events on the property.

3. Smoobu API

Smoobu offers tools for vacation rental providers. The Smoobu APITrack this API enables access to reservations, rates, apartment IDs, and listing details. Data is available in JSON format. Smoobu functions as a channel manager, reservation system, and booking system and features automatic synchronization, no commissions on bookings, and customized rental homepages.

4. HousingAnywhere API

HousingAnywhere is a rental accommodation platform with payments services. The HousingAnywhere APITrack this API enables data interoperability between HousingAnywhere and its partners. Developers can use the API to connect an inventory to the HousingAnywhere platform. Bookings take place on the HousingAnywhere platform and the API will ensure that partner systems are updated in real-time.

HousingAnywhere is a home rental marketplace that includes and API for listings data. Screenshot: HousingAnywhere

5. Avis Rental Car Suite API

Avis Budget Group operates mobile solutions for Avis, Budget and Zipcar. The Avis Rental Car Suite APITrack this API allows developers to access rental car product catalogs, reservations, and locations offered by Avis, Budget, and Zipcar. The API enables request flows for car renting on behalf of users.

6. Skyscanner Car Hire API

Skyscanner is a global travel search engine offering a comprehensive and free flight search service, as well as instant comparisons for hotels and car hire. The Skyscanner Car Hire APITrack this API allows developers to retrieve live prices for car hire providers, by making requests to the Car Hire API. With the API developers can allow their application users to retrieve live prices for car hire providers.

7. Chegg Textbook Rental API

Chegg rents out textbooks and distributes etextbooks at subsidized rates through its online library portal. The Chegg Textbook APITrack this API allows access to the book rental portal for users to search textbook titles and pricing details. The API is ideal for Chegg-affiliated developers that run shopping sites that compare rental prices of textbooks and other stationery items. Access to the API’s documentation must be requested through email and is restricted to developers with approved Chegg affiliate accounts.

8. HomeAway API

HomeAway is a service that helps users choose and book a vacation rental and pay securely online. The HomeAway APITrack this API allows developers to get information on vacation home rental listings, access their accounts, and post reviews. Users can search for rentals at their desired location for their anticipated arrival/departure dates from among more than a million listings. Note: HomeAway has recently been consolidated into Expedia’s other rental brand, VRBO, and this API is scheduled for retirement during August, 2020.

9. Knock API

Knock is a CRM for property managers. Knock features channel management, customer reminders, engagement score monitoring, collaboration tools, and goal tracking. The Knock APITrack this API enables prospect management and property details.

10. Vacasa API

Vacasa offers a vacation rental platform that includes community association management, 3D virtual tours of every property, local staff, interior design, and more, and booking. The Vacasa APITrack this API enables developers to integrate rental management and booking functions in applications. API methods are available for available units, unit lists, photos, contacts, addresses, countries and more.

Vacasa API enables vacation rental booking for applications

Vacasa API enables vacation rental booking for applications. Screenshot: Vacasa

Look to the Rentals category on ProgrammableWeb for more than 60 APIs, SDKs, and Source Code Samples.

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Author: <a href="https://www.programmableweb.com/user/%5Buid%5D">joyc</a>

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Hackster.io

Using Soft Potentiometers // Live Demo

For many people, a potentiometer just means a knob. Let’s take a look at another variety – the soft potentiometer, or softpot. We’ll follow SparkFun’s hookup guide, and then branch into more adventurous territory, using the Arduino Nano Every board.

// https://learn.sparkfun.com/tutorials/softpot-hookup-guide/all
// https://www.arduino.cc/en/Guide/NANOEvery

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ScienceDaily

Artificial Intelligence to identify individual birds of same species

Humans have a hard time identifying individual birds just by looking at the patterns on their plumage. An international study involving scientists form the CNRS, Université de Montpellier and the University of Porto in Portugal, among others, has shown how computers can learn to differentiate individual birds of a same species. The results are published on 27 July 2020 in Methods in Ecology and Evolution.

Differentiating between individuals of a same species is essential in the study of wild animals, their processes of adaptation and behaviour. Scientists from the CEFE research centre in Ecology and Evolutionary Ecology (CNRS/ Université de Montpellier/ Université Paul-Valéry-Montpellier/ IRD/ EPHE) and the Research Centre in Biodiversity and Genetic Resources (CIBIO) at Porto University have for the very first time identified individual birds with the help of artificial intelligence technology.

They have developed a technique that enables them to gather a large number of photographs, taken from various angles, of individual birds wearing electronic tags. These images were fed into computers which used deep learning technology to recognise the birds by analysing the photographs. The computers were able to distinguish individual birds according to the patterns on their plumage, something humans can’t do. The technology was able to identify specimens from populations of three different species: sociable weavers, great tits and zebra finches.

This new technique could not only result in a less invasive method of identification but also lead to new insights in ecology, for example, by opening ways of using AI to study animal behaviour in the wild.

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3D Printing Industry

PostProcess Technologies’ 2020 Post-Printing Trends Survey is now live

PostProcess Technologies has just launched the 2020 iteration of its annual Additive Manufacturing Post-Printing Industry Trends Survey. After a successful debut in 2019, the post-printing (aka post-processing) specialist is again looking to share insights into the 3D printing industry’s most common post-printing methods, most frequently faced challenges, and growth plans. This year’s survey is packed […]

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Author: Kubi Sertoglu