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Polymer-derived carbon as metal-free,


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Catalysts are key materials in modern society, enabling selective conversion of raw materials into valuable products while reducing waste and saving energy. In case of industrially relevant oxidative dehydrogenation reactions, most known catalyst systems are based on transition metals such as Iron, Vanadium, Molybdenum or Silver. Due to intrinsic drawbacks associated with the use of transition metals, such as rare occurrence, environmentally harmful mining processes, and toxicity, the fact that pure carbon exhibits catalytic activity in this type of reaction and thus has high potential as a sustainable substitution material is of high interest.
To date, the development of carbon-based catalysts for oxidative dehydrogenation reactions may be divided into two generations. The first generation of carbon catalysts was inspired by the discovery of the catalytic activity of coke deposits on metal-based catalysts for oxidative dehydrogenation. Subsequently, mainly amor ....

Felix Herold , Jan Philipp Hofmann , Wei Qi , Bastianjm Etzold , Surface Science Laboratory , Shenyang National Laboratory Of Material Science , Professor Bastian , Shenyang National Laboratory , Material Science , Professor Jan Philipp Hofmann , Graphitic Carbon , ஃபெலிக்ஸ் ஹீரோல்ட் , ஜான் பிலிப் ஹாஃப்மேன் , வெய் குய் , மேற்பரப்பு அறிவியல் ஆய்வகம் , ஷேனிாங் தேசிய ஆய்வகம் ஆஃப் பொருள் அறிவியல் , ப்ரொஃபெஸர் பாஸ்டியன் , ஷேனிாங் தேசிய ஆய்வகம் , பொருள் அறிவியல் , ப்ரொஃபெஸர் ஜான் பிலிப் ஹாஃப்மேன் ,

New statistical method exponentially increases ability to discover genetic insights


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Pleiotropy analysis, which provides insight on how individual genes result in multiple characteristics, has become increasingly valuable as medicine continues to lean into mining genetics to inform disease treatments. Privacy stipulations, though, make it difficult to perform comprehensive pleiotropy analysis because individual patient data often can t be easily and regularly shared between sites. However, a statistical method called Sum-Share, developed at Penn Medicine, can pull summary information from many different sites to generate significant insights. In a test of the method, published in
Nature Communications, Sum-Share s developers were able to detect more than 1,700 DNA-level variations that could be associated with five different cardiovascular conditions. If patient-specific information from just one site had been used, as is the norm now, only one variation would have been determined. ....

Rui Duan , Hakon Hakonarson , Marylynd Ritchie , Yong Chen , Robert Carroll , Sarah Pendergrass , Christopher Bauer , Joshc Denny , Ruowang Li , Jonathand Mosley , Patrick Sleiman , Wei Qi , Jason Moore , Thomas Lumley , Davids Carrell , Dignar Velez Edwards , Xinyuan Zhang , Institute For Biomedical Informatics , Nature Communications , National Institutes Of Health , Consortium For Clinical Characterization , Penn Medicine , Biomedical Informatics , Clinical Characterization , National Institutes , Georgia Wiesner ,