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Computers & Math

Reviving the Old, Saving the Sea: How Upcycled Phones Can Power Sustainable Cities

In a world where over a billion smartphones are produced yearly, a team of researchers is flipping the script on electronic waste. Instead of tossing out older phones, they ve demonstrated a groundbreaking approach: turning outdated smartphones into micro data centers. This low-cost innovation (just 8 euros per phone) offers practical applications from tracking bus passengers to monitoring marine life without needing new tech.

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The world is facing an environmental crisis, with the production and disposal of electronic devices contributing significantly to greenhouse gas emissions and pollution. Each year, over 1.2 billion smartphones are produced globally, but these devices have a relatively short lifespan – users replace them every 2-3 years on average. This has led to a staggering amount of waste, with many devices ending up in landfills or incinerators.

However, researchers from the University of Tartu’s Institute of Computer Science and their international colleagues have discovered an innovative solution to this problem. They’ve found that old smartphones can be repurposed into tiny data centers capable of efficiently processing and storing data. This is made possible by replacing the phone’s battery with an external power source, reducing the risk of chemical leakage.

These tiny data centers have a wide range of applications, including urban environments like bus stops. By collecting real-time data on passenger numbers, cities can optimize public transportation networks, making them more efficient and environmentally friendly.

The researchers have also successfully tested these underwater data centers in marine life monitoring projects. Normally, such tasks require scuba divers to record video and bring it back to the surface for analysis. However, with this technology, the process is done automatically underwater, reducing the need for human intervention and minimizing the risk of disturbance to sea life.

The team’s results show that outdated technology doesn’t have to end up as waste. With minimal resources, these devices can be given a new purpose, contributing to the development of more environmentally friendly and sustainable digital solutions.

As Associate Professor of Pervasive Computing Huber Flores puts it, “Innovation often begins not with something new, but with a new way of thinking about the old, re-imagining its role in shaping the future.” This project demonstrates that sustainability is not just about preserving the future – it’s about reimagining the present, where yesterday’s devices become tomorrow’s opportunities.

Artificial Intelligence

The Quantum Drumhead Revolution: A Breakthrough in Signal Transmission with Near-Perfect Efficiency

Researchers have developed an ultra-thin drumhead-like membrane that lets sound signals, or phonons, travel through it with astonishingly low loss, better than even electronic circuits. These near-lossless vibrations open the door to new ways of transferring information in systems like quantum computers or ultra-sensitive biological sensors.

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The Niels Bohr Institute at the University of Copenhagen has made a groundbreaking discovery that could revolutionize the way we transmit information. Researchers, in collaboration with the University of Konstanz and ETH Zurich, have successfully sent vibrations through an ultra-thin drumhead, measuring only 10 mm wide, with astonishingly low loss – just one phonon out of a million. This achievement is even more impressive than electronic circuit signal handling.

The drumhead, perforated with many triangular holes, utilizes the concept of phonons to transmit signals. Phonons are essentially sound waves that travel through solid materials by vibrating atoms and pushing each other. This phenomenon is not unlike encoding a message and sending it through a material, where signal loss can occur due to various factors like heat or incorrect vibrations.

The researchers’ success lies in achieving almost lossless transmission of signals through the membrane. The reliability of this platform for sending information is incredibly high, making it a promising candidate for future applications. To measure the loss, researchers directed the signal through the material and around the holes, observing that the amplitude decreased by only about one phonon out of a million.

This achievement has significant implications for quantum research. Building a quantum computer requires super-precise transfer of signals between its different parts. The development of sensors capable of measuring the smallest biological fluctuations in our own body also relies heavily on signal transfer. As Assistant Professor Xiang Xi and Professor Albert Schliesser explain, their current focus is on exploring further possibilities with this method.

“We want to experiment with more complex structures and see how phonons move around them or collide like cars at an intersection,” says Albert Schliesser. “This will give us a better understanding of what’s ultimately possible and what new applications there are.” The pursuit of basic research is about producing new knowledge, and this discovery is a testament to the power of scientific inquiry.

In conclusion, the quantum drumhead revolution has brought us one step closer to achieving near-perfect signal transmission. As researchers continue to explore the possibilities of this method, we can expect exciting breakthroughs in various fields, ultimately leading to innovative applications that will transform our understanding of the world.

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Computer Programming

AI Revolutionizes Heart Risk Prediction, Saving Lives and Reducing Unnecessary Interventions

An advanced Johns Hopkins AI model called MAARS combs through underused heart MRI scans and complete medical records to spot hidden scar patterns that signal sudden cardiac death, dramatically outperforming current dice-roll clinical guidelines and promising to save lives while sparing patients unnecessary defibrillators.

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The AI model significantly outperformed traditional clinical guidelines, achieving an accuracy rate of 89% across all patients, with a remarkable 93% accuracy for individuals between 40-60 years old – the population most at-risk for sudden cardiac death. By accurately predicting patient risk, doctors can tailor medical plans to suit individual needs, reducing unnecessary interventions and saving lives.

Led by researcher Natalia Trayanova, the team’s findings were published in Nature Cardiovascular Research. The study demonstrates the potential of AI to transform clinical care, particularly in high-risk areas such as sudden cardiac death prediction. With further testing and expansion to other heart diseases, this technology has the potential to save many lives and improve patient outcomes.

In an interview, Trayanova noted that current clinical guidelines for identifying patients at risk have about a 50% chance of success – “not much better than throwing dice.” The AI model’s accuracy is a significant improvement, with Trayanova stating that it can predict with high accuracy whether a patient is at very high risk for sudden cardiac death or not.

The team tested the MAARS model against real patients treated with traditional clinical guidelines at Johns Hopkins Hospital and Sanger Heart & Vascular Institute in North Carolina. The results showed that the AI model was more accurate than human clinicians, with an impressive 93% accuracy rate for individuals between 40-60 years old.

The study’s co-author, Jonathan Crispin, a Johns Hopkins cardiologist, stated that the research demonstrates the potential of AI to transform clinical care and enhance patient outcomes. The team plans to further test the MAARS model on more patients and expand its use to other heart diseases, including cardiac sarcoidosis and arrhythmogenic right ventricular cardiomyopathy.

The development of this AI model offers a glimmer of hope for those affected by hypertrophic cardiomyopathy and sudden cardiac death, providing a new tool for doctors to accurately predict patient risk and tailor medical plans accordingly. As the research continues to evolve, it has the potential to save many lives and improve patient outcomes worldwide.

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Computer Modeling

Scientists Crack Code to Simulate Quantum Computations, Paving Way for Robust Quantum Computers

A multinational team has cracked a long-standing barrier to reliable quantum computing by inventing an algorithm that lets ordinary computers faithfully mimic a fault-tolerant quantum circuit built on the notoriously tricky GKP bosonic code, promising a crucial test-bed for future quantum hardware.

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The researchers have successfully simulated quantum computations with an error correction code known as the Gottesman-Kitaev-Preskill (GKP) code. This code is commonly used in leading implementations of quantum computers and allows for the correction of errors without destroying the quantum information.

The method developed by the researchers consists of an algorithm capable of simulating quantum computations using a bosonic code, specifically the GKP code. This achievement has been deemed impossible until now due to the immense complexity of quantum computations.

“We have discovered a way to simulate a specific type of quantum computation where previous methods have not been effective,” says Cameron Calcluth, PhD in Applied Quantum Physics at Chalmers and first author of the study published in Physical Review Letters. “This means that we can now simulate quantum computations with an error correction code used for fault tolerance, which is crucial for being able to build better and more robust quantum computers in the future.”

The researchers’ breakthrough has far-reaching implications for the development of stable and scalable quantum computers, which are essential for solving complex problems in various fields. The new method will enable researchers to test and validate a quantum computer’s calculations more reliably, paving the way for the creation of truly reliable quantum computers.

The article Classical simulation of circuits with realistic odd-dimensional Gottesman-Kitaev-Preskill states has been published in Physical Review Letters. The authors are Cameron Calcluth, Giulia Ferrini, Oliver Hahn, Juani Bermejo-Vega, and Alessandro Ferraro.

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