Catastrophic temperature: Based on the catastrophe theory [38,39], by closely linking the influencing factors of CSC differences caused by different uniaxial stresses, a novel mathematical model is obtained to predict the temperature when the CSC development stage changes under different uniaxial ...
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Multiple Kernel Learning (MKL) is a machine learning approach that allows for the integration of multiple features, such as genes, proteins, and metabolites, by combining them as different kernel matrices. These matrices are then used as input for various inference tasks, such as classification and...
The native mobile app for iOS and Android allows users to learn on the go, even offline, and fit learning into their busy schedules. The built-in Knowledge Base simplifies knowledge sharing and allows trainees to find relevant training resources and documents quickly. The Development Plans module...
Children's outdoor play and access to nature are important for their health and development of environmental agency but there is a global decline of gr
📖 Professional software development: pretty complete and a good companion to this page. The free chapters are mostly focused on software development processes: design, testing, code writing, etc. - and not so much about tech itself. 🧰 vhf/free-programming-books 🧰 EbookFoundation/free-progr...
as well as the platforms in which the ROLE technological framework has been integrated are presented. In addition, the experiences and lessons learned from the design and development of the ROLE technological framework are discussed, together with the lessons learned from the collaboration both internal...
Most current Alzheimer’s disease (AD) and mild cognitive disorders (MCI) studies use single data modality to make predictions such as AD stages. The fusion of multiple data modalities can provide a holistic view of AD staging analysis. Thus, we use deep
Human Cell Atlas [9] is a prominent example: an effort to sequence the various cell types and cellular states that make up a human being. Encouraged by the great potential of single-cell investigation of DNA and RNA, there has been substantial growth in the development of related experimental...
Breast cancer (BC) is a multifactorial disease and the most common cancer in women worldwide. We describe a machine learning approach to identify a combination of interacting genetic variants (SNPs) and demographic risk factors for BC, especially factors