ADDRESSING BARRIERS TO HEALTHCARE ACCESS FOR ROMA: A COMMUNITY DEVELOPMENT APPROACH


R&D of the EM Calorimeter Energy Calibration with Machine Learning based on the low-level features of the Cluster

We have developed an energy calibration method using machine learning Apparel for the ILC electromagnetic (EM) calorimeter (ECAL), a sampling calorimeter consisting of Silicon-Tungsten layers.In this method, we use a deep neural network (DNN) for a regression to determine the energy of incident EM particles, improving the energy calibration resolut

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Genetic basis of the early heading of high-latitude weedy rice

Japonica rice (Oryza sativa L.) is an important staple food in high-latitude regions and is widely distributed in northern China, Japan, Korea, and Europe.However, the genetic diversity of japonica rice is relatively narrow and poorly adapted.Weedy rice (Oryza sativa f.spontanea) is a semi-domesticated rice.Its headings are earlier than the accompa

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Computerized Cognitive Behavioral Therapy Intervention for Depression Among Veterans: Acceptability and Feasibility Study

BackgroundComputerized cognitive behavioral therapies (cCBTs) have been developed to deliver efficient, evidence-based treatment for depression and other mental health conditions.Beating the Blues (BtB) is one of the most empirically supported cCBTs for depression.The previous trial of BtB with veterans included regular guidance by health care pers

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