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Blog – Page 4789

Vocal biomarkers have become a buzzword during the pandemic, but what does it mean and how could it contribute to diagnostics?

What if a disease could be identified over a phone call?

Vocal biomarkers have amazing potential in reforming diagnostics. As certain diseases, like those affecting the heart, lungs, vocal folds or the brain can alter a person’s voice, artificial intelligence (A.I.)-based voice analyses provide new horizons in medicine.

Using biomarkers for diagnosis and remote monitoring can also be used for COVID-screening. So is it possible to diagnose illnesses from the sound of your voice?

Continue reading “Do I sound ill? — All About Vocal Biomarkers Diagnosing Illnesses” | >

A research group led by Prof. WU Kaifeng from the Dalian Institute of Chemical Physics (DICP) of the Chinese Academy of Sciences (CAS), in collaboration with Dr. Peter C. Sercel from the Center for Hybrid Organic Inorganic Semiconductors for Energy, recently reported the utilization of lattice distortion in lead halide perovskite quantum dots (QDs) to control their exciton fine structure.

The study was published in Nature Materials (“Lattice distortion inducing exciton splitting and coherent quantum beating in CsPbI 3 perovskite quantum dots”).

Lattice distortion of perovskite quantum dots induces coherent quantum beating. (Image: DICP)

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Skin-like electronics could seamlessly integrate with the body for applications in health monitoring, medication therapy, implantable medical devices, and biological studies.

With the help of the Polsky Center for Entrepreneurship and Innovation, Sihong Wang, an assistant professor of molecular engineering at the University of Chicago’s Pritzker School of Molecular Engineering, has secured patents for the building blocks of these novel devices.

Drawing on innovation in the fields of semiconductor physics, solid mechanics, and energy sciences, this work includes the creation of stretchable polymer semiconductors and transistor arrays, which provide exceptional electrical performance, high semiconducting properties, and mechanical stretchability. Additionally, Wang has developed triboelectric nanogenerators as a new technology for harvesting energy from a user’s motion—and designed the associated energy storage process.

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At this year’s Conference on Machine Learning and Systems (MLSys), we and our colleagues presented a new auto-scheduler called DietCode, which handles dynamic-shape workloads much more efficiently than its predecessors. Where existing auto-encoders have to optimize each possible shape individually, DietCode constructs a shape-generic search space that enables it to optimize all possible shapes simultaneously.

We tested our approach on a natural-language-processing (NLP) task that could take inputs ranging in size from 1 to 128 tokens. When we use a random sampling of input sizes that reflects a plausible real-world distribution, we speed up the optimization process almost sixfold relative to the best prior auto-scheduler. That speedup increases to more than 94-fold when we consider all possible shapes.

Despite being much faster, DietCode also improves the performance of the resulting code, by up to 70% relative to prior auto-schedulers and up to 19% relative to hand-optimized code in existing tensor operation libraries. It thus promises to speed up our customers’ dynamic-shaped machine learning workloads.

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Due to their self-assembly function, DNA sensors have gained much attention as next-generation sensors that require an extremely low power supply.

Study: Spin transport properties in DNA & electrically doped iron QD organo-metallic junction. Image Credit: marie_mi/Shutterstock.com.

Scientists have recently used iron (Fe) quantum dots (QD) electrodes to determine the spin transport properties and quantum scattering transmission characteristics of DNA sensors at room temperature. This study is available in Materials Today: Proceedings.

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Explaining the potential of nanotubes further, one of the lead researchers and associate professor at Johns Hopkins University (JHU), Rebecca Schulman told IE, “Tinier plumbing might help us analyze individual molecules, which could help us make better drugs or enzymes, separate toxins, or even create better batteries by designing the conduits that ions flow through rather than using a porous material.”

She believes that although these technologies are still 10+ years away, their foundation is in things like nano-plumbing and being able to precisely measure and control the pipes the plumbing is made of.

Nanotubes are a highly evolved version of nanopores, small DNA structures proposed in some previously published studies. A nanopore is designed to serve as a conduit across a thin barrier between two chambers. Examples of such barriers are cell membranes (nanopores allow things to move in and out of a cell) and across metal or graphene sheets (like in nanopore-enabled DNA sequencing).

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AI image generation is here in a big way. A newly released open source image synthesis model called Stable Diffusion allows anyone with a PC and a decent GPU to conjure up almost any visual reality they can imagine. It can imitate virtually any visual style, and if you feed it a descriptive phrase, the results appear on your screen like magic.

Some artists are delighted by the prospect, others aren’t happy about it, and society at large still seems largely unaware of the rapidly evolving tech revolution taking place through communities on Twitter, Discord, and Github. Image synthesis arguably brings implications as big as the invention of the camera—or perhaps the creation of visual art itself. Even our sense of history might be at stake, depending on how things shake out. Either way, Stable Diffusion is leading a new wave of deep learning creative tools that are poised to revolutionize the creation of visual media.

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