Computational intelligence and neuroscience
Dec 16, 2021
Developing artificial intelligence (AI) agents is challenging for efficient exploration in visually rich and complex environments. In this study, we formulate the exploration question as a reinforcement learning problem and rely on intrinsic motivati...
Computational intelligence and neuroscience
Dec 16, 2021
Generation Z is a data-driven generation. Everyone has the entirety of humanity's knowledge in their hands. The technological possibilities are endless. However, we use and misuse this blessing to face swap using deepfake. Deepfake is an emerging sub...
INTRODUCTION: Cervical cancer remains a major public health challenge in low- and middle-income countries (LMICs) due to financial and logistical issues. WHO recommendation for cervical cancer screening in LMICs includes HPV testing as primary screen...
This work investigates the application of empirical, statistical and machine learning methods to appraise the prediction of transmembrane pressure (TMP) by oscillating slotted pore membrane for the treatment of two kinds of deformable oil drops. Here...
Current opinion in structural biology
Dec 15, 2021
Stability is a key ingredient of protein fitness, and its modification through targeted mutations has applications in various fields, such as protein engineering, drug design, and deleterious variant interpretation. Many studies have been devoted ove...
PURPOSE: Noise power spectrum (NPS) is a commonly used performance metric to evaluate noise-reduction techniques (NRT) in imaging systems. The images reconstructed with and without an NRT can be compared via their NPS to better understand the NRT's e...
Archaea can produce special cellular components such as polyhydroxyalkanoates, carotenoids, rhodopsin, and ether lipids, which have valuable applications in medicine and green energy production. Most of the archaeal species are uncultivated, posing c...
To accelerate cancer research that correlates biomarkers with clinical endpoints, methods are needed to ascertain outcomes from electronic health records at scale. Here, we train deep natural language processing (NLP) models to extract outcomes for p...
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