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MaxDIA -- taking proteomics to the next level

The new MaxDIA software provides a computational workflow for data-independent acquisition proteomics, combining library-based and library-free approaches. This enables highly sensitive and accurate data analysis for thousands of proteins, opening up new possibilities for medical applications in personalized medicine.

SourceMax-Planck-Gesellschaft·JournalNature Biotechnology·DateJul 12, 2021

Obscuring the truth can promote cooperation

A study by University of Pennsylvania researchers found that overstating the level of cooperation in a society can increase cooperative behavior overall. The study used a mathematical model to simulate the creation and maintenance of a community, finding that a degree of deceit or obfuscation can promote the formation of a cooperative ...

SourceUniversity of Pennsylvania·JournalEvolutionary Human Sciences·DateJul 8, 2021

Gold digger: Neural networks at the nexus of data science and electron microscopy

Researchers at Max Planck Florida Institute for Neuroscience used machine learning to develop Gold Digger software that can accurately identify gold particles bound to specific proteins of interest. The software uses a deep learning approach to distinguish gold particles from shadow artifacts with near-human level accuracy.

SourceMax Planck Florida Institute for Neuroscience·JournalScientific Reports·DateApr 20, 2021

Merging technologies with color to avoid design failures

A team of Penn State researchers used machine learning algorithms to improve the efficiency of design evaluations for porous materials. By leveraging image colorization techniques, they reduced computational load while maintaining accuracy. The findings provide a framework for designers to create more structurally responsible parts wit...

AI reduces computational time required to study fate of molecules exposed to light

Scientists from the University of Groningen developed a machine learning-based algorithm, PySurf, which reduces electronic structure calculations significantly. The software requires several orders of magnitude less computational time than existing direct dynamics software and is available as an open-source free download.

SourceUniversity of Groningen·JournalJournal of Chemical Theory and Computation·DateDec 1, 2020

The accident preventers

Researchers at TUM have developed a software module that analyzes and predicts events while driving, ensuring the vehicle will not cause accidents. The system determines movement options and emergency maneuvers to prevent collisions, using simplified dynamic models for swift calculations.

SourceTechnical University of Munich (TUM)·JournalNature Machine Intelligence·DateSep 16, 2020

Autonomous robot plays with NanoLEGO

Scientists have developed an artificial intelligence system that autonomously learns how to grip and move individual molecules, overcoming the complexity of nanoscale manipulation. The system uses reinforcement learning to find optimal movement patterns, enabling targeted assembly and separation of molecules.

SourceForschungszentrum Juelich·JournalScience Advances·DateSep 3, 2020

Revealing destructive cracks in rock

Researchers at Texas A&M University are using advanced machine-learning analysis to reveal the evolution of cracks in rock and concrete. By combining data from multiple sources, including sound waves, electromagnetics, and pressure measurements, they aim to improve our understanding of crack damage and development.

Clever computing puts millions into charities' hands

A new model called Swiftaid has been developed to automate the process of claiming Gift Aid on donations, allowing charities to claim up to £2.50 for every £10 donated. This system uses formal methods to improve design and security, streamlining the process and unlocking millions in extra funding.

SourceUniversity of Surrey·JournalFormal Aspects of Computing·DateJun 1, 2020

Speak math, not code

Using Euclid's algorithm as an example, Dr. Lamport showed how a precise mathematical formula can be used to specify an algorithm, making it more efficient and easier to debug. By using math instead of code, developers can reduce the size of their programs by up to ten times and make debugging easier.

Best of both worlds: Asteroids and massive mergers

University of Arizona researchers are using the Catalina Sky Survey's near-Earth object telescopes to find optical counterparts to gravitational waves triggered by massive mergers. The team found several supernovae and a near-Earth object during their ongoing campaign, which began in April.

SourceUniversity of Arizona·JournalThe Astrophysical Journal Letters·DateAug 15, 2019

A new level of smart industrial robots control and management reached at FEFU

Scientists developed a command-and-control plugin for intelligent industrial robots, allowing for high-quality 3D computer models to be built quickly and precisely. The software helps solve the issue of hard programming of industrial robots and can fix in-process workpieces on universal positioning devices.

SourceFar Eastern Federal University·JournalInternational Journal of Mechanical Engineering and Robotics Research·DateJul 17, 2019