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While advancements in healthcare have come in leaps and bounds since the 20th century, there is perhaps none more exciting than what digital twin technology could offer. The healthcare industry has the potential to be revolutionized by this application of new advancements, which will ultimately lead to improved research capabilities and patient outcomes.

Defined as the virtual representation of a physical object or system across its life cycle, a digital twin is a computer program that uses real world data to create simulations that can predict the outcomes of a product or process. A concept initially utilized by NASA in the 1960s, this technology has grown exponentially in the last decade, now further expanding into the world of healthcare.

Beginning in 2014 with The Living Heart Project headed by Dassault Systémes, healthcare research with digital twins has broadened to include organs such as the brain and lungs, as well as projects for virtual parts of the body. With these models, doctors have the potential to discover undeveloped illnesses, experiment with treatments, and improve surgical outcomes. They allow clinicians to test multiple treatments across a vast range of therapies, equipment, and interventions by comparing possible outcomes without taking any risks in terms of patient safety. Ultimately, care can become more precise, targeted, and based on the most accurate data available when digital twins are utilized.

We all know Linux is written in C. What you may not know is that it’s written in a long-outdated C dialect: The 1989 version of the C language standard, C89. This is also known as ANSI X3.159‑1989, or ANSI C. Linus Torvalds has decided that enough is enough and will move Linux’s official C to 2011’s C11 standard.


The Linux kernel’s foundation is the ancient C89 standard of C. Now, Torvalds has decided to upgrade to 2011’s more modern C11 standard.

Often, reprogramming a microcontroller involves placing it in reset, flashing the code, and letting it fire back up. It usually involves shutting the chip down entirely. However, [bor0] has built a virtual machine that runs on the ESP32, allowing for dynamic program updates to happen.

The code is inspired by the CHIP-8, a relatively ancient interpreter that had some gaming applications. [bor0] had already created a VM simulating the CHIP-8, and repurposed it here, taking out the gaming-related drawing instructions and replacing them with those that control IO pins. Registers have also been changed to 16 bits for added flexibility and headroom.

It’s probably not something with immediate ground-breaking applications for most people, but it’s a different way of working with and programming the ESP32, and that’s pretty neat.

A silicon wasteland.


In a sign that the United States government’s export restrictions on semiconductor sales to Russia due to its war against Ukraine have been enacted swiftly, multiple reports have emerged today that both Intel and AMD have suspended chip sales to Russia. In addition, reports have also emerged that TSMC’s decision to participate in the sanctions will thwart Russia’s supply of homegrown chips. We have reached out to Intel, AMD, and Nvidia for comment.

The Russian media outlets also claim that the suspensions have been confirmed by the Association of Russian Developers and Electronics Manufacturers (ARPE). Additionally, Chinese IT companies are said to have been notified by Intel that sales to Russia have been banned.

The extent of the halted sales is currently unclear. The new export restrictions are primarily aimed at chips for military purposes or dual-use chips that could be used for both civilian and military purposes. That means sales of most consumer-focused chips, like AMD’s Ryzen and Intel’s Core chips, likely won’t be impacted. However, it is widely expected that there will be a temporary halt for all semiconductor sales to Russia as companies work to decide which products are impacted. Additionally, the US DoC has added 49 Russian companies to the Entity List, and those companies aren’t eligible to purchase any type of chip.

The late 90s and early 2000s were a breakout time for mobile phones, with cheap GSM handsets ushering in the era in which pretty much everybody had a phone. Back then, a popular way to customize one’s phone was to install a sticker that would flash when the phone rang. These required no batteries or any other connection to the phone, and [Big Clive] has dived in to explain how they worked.

It’s an old-fashioned teardown that requires a bit of cutting to get inside the sticker itself. A typical example had three LEDs in series for a total voltage drop of around 7V, hooked up to two diodes and a PCB trace antenna. A later evolution used raw unpackaged components bonded to the PCB. Future versions went down to a single diode, using the LEDs to serve as the second. The basic theory was that the PCB traces would pick up RF transmitted by the phone when a call was coming in, lighting the LEDs.

In the 2G era, the freuqencies used were on the order of 300 MHz to 1.9GHz. A combination of the change in frequencies used by modern phone technology and the lower transmit powers used by handsets means that the stickers don’t work properly with modern phones according to [Big Clive].

The joint development team of Professor Shibata (the University of Tokyo), JEOL Ltd. and Monash University succeeded in directly observing an atomic magnetic field, the origin of magnets (magnetic force), for the first time in the world. The observation was conducted using the newly developed Magnetic-field-free Atomic-Resolution STEM (MARS). This team had already succeeded in observing the electric field inside atoms for the first time in 2012. However, since the magnetic fields in atoms are extremely weak compared with electric fields, the technology to observe the magnetic fields had been unexplored since the development of electron microscopes. This is an epoch-making achievement that will rewrite the history of microscope development.

Electron microscopes have the highest spatial resolution among all currently used microscopes. However, in order to achieve ultra-high resolution so that atoms can be observed directly, we have to observe the sample by placing it in an extremely strong lens . Therefore, atomic observation of magnetic materials that are strongly affected by the lens magnetic field such as magnets and steels had been impossible for many years. For this , the team succeeded in developing a lens that has a completely new structure in 2019. Using this new lens, the team realized atomic observation of magnetic materials, which is not affected by the lens magnetic field. The team’s next goal was to observe the magnetic fields of atoms, which are the origin of magnets (), and they continued technological to achieve the goal.

This time, the joint development team took on the challenge of observing the magnetic fields of iron (Fe) atoms in a hematite crystal (α-Fe2O3) by loading MARS with a newly developed high-sensitivity high-speed detector, and further using computer image processing technology. To observe the magnetic fields, they used the Differential Phase Contrast (DPC) method at atomic resolution, which is an ultrahigh-resolution local electromagnetic field measurement method using a scanning transmission electron microscope (STEM), developed by Professor Shibata et al. The results directly demonstrated that iron atoms themselves are small magnets (atomic magnet). The results also clarified the origin of (antiferromagnetism) exhibited by hematite at the atomic level.

Nature is a never-ending source of inspiration for scientists, but our artificial devices usually don’t communicate well with the real thing. Now, researchers at Linköping University have created artificial organic neurons and synapses that can integrate with natural biological systems, and demonstrated this by making a Venus flytrap close on demand.

The new artificial neurons build on the team’s earlier versions, which were organic electrochemical circuits printed onto thin plastic film. Since they’re made out of polymers that can conduct either positive or negative ions, these circuits form the basis of transistors. In the new study, the team optimized these transistors and used them to build artificial neurons and synapses, and connect them to biological systems.

When the transistors detect concentrations of ions with certain charges, they switch, producing a signal that can then be picked up by other neurons. Importantly, biological neurons operate on these same ion signals, meaning artificial and natural nerve cells can be connected.

Using a new fabrication technique, NIMS has developed a diamond field-effect transistor (FET) with high hole mobility, which allows reduced conduction loss and higher operational speed. This new FET also exhibits normally off behavior (i.e., electric current flow through the transistor ceases when no gate voltage is applied, a feature that makes electronic devices safer). These results may facilitate the development of low-loss power conversion and high-speed communications devices.

Diamond has excellent wide bandgap semiconductor properties: its bandgap is larger than those of and gallium nitride, which are already in practical use. Diamond therefore could potentially be used to create power electronics and communications devices capable of operating more energy efficiently at higher speeds, voltages and temperatures. A number of R&D projects have previously been carried out with the aim of creating FETs using hydrogen-terminated diamonds (i.e., diamonds with their superficial carbon atoms covalently bonded with hydrogen atoms). However, these efforts have failed to fully exploit diamonds’ excellent wide bandgap semiconductor properties: the (a measure of how quickly holes can move) of these diamond-integrated transistors was only 1–10% that of the diamonds before integration.

The NIMS research team succeeded in developing a high-performance FET by using hexagonal boron nitride (h-BN) as a gate insulator instead of conventionally used oxides (e.g., alumina), and by employing a new fabrication technique capable of preventing the surface of hydrogen-terminated diamond from being exposed to air. At high hole densities, the hole mobility of this FET was five times that of conventional FETs with oxide gate insulators. FETs with high hole mobility can operate with lower electrical resistance, thereby reducing conduction loss, and can be used to develop higher speed and smaller electronic devices. The team also demonstrated normally-off operation of the FET, an important feature for power electronics applications. The new fabrication technique enabled removal of electron acceptors from the surface of the hydrogen-terminated diamond.

Humans have been trying to understand how the brain works and how it acquires information for centuries. While neuroscientists now have a pretty good understanding of how different parts of the brain work and what their function is, many questions remain unanswered; thus, a unified neuroscience theory is still lacking.

In recent years, computer scientists have been trying to create computational tools that artificially recreate the functions and processes of the human . New theories clarifying how the brain makes predictions could help to significantly enhance these tools so that they replicate neural functions in increasingly realistic ways.

Researchers at the Canadian Centre for Behavioural Neuroscience in Lethbridge, Canada have recently carried out a study investigating how individual learn and make predictions about the future. Their findings, published in Nature Machine Intelligence, suggest that the ability of single neurons to predict their future activity could offer a new learning mechanism.