Systematically coarse grained models for complex fluids usually lack chemical and thermodynamic transferability. Efforts to improve transferability require the development of effective potentials with unequivocal physical significance. In this paper, we introduce conditional reversible work (CRW) potentials that describe nonbonded interactions in coarse grained models at the pair level. The met...

Deep neural networks are susceptible to interference from deliberately crafted noise, which can lead incorrect classification results. Existing approaches make less use of latent space information and conduct pixel-domain modification in the input instead, increases computational cost decreases transferability. In this work, we propose an effective adversarial distribution searching-driven atta...

For further development of electronic commerce, electronic payment systems play an essential role. Many payment schemes have been proposed, but none of them have been accepted as a standard payment system for a variety of reasons. In this paper, we evaluate payment schemes in terms of the three requirements: offline operability, anonymity and transferability. We think these three requirements a...

The vast majority of genome-wide association studies (GWASs) are performed in Europeans, and their transferability to other populations is dependent on many factors (e.g., linkage disequilibrium, allele frequencies, genetic architecture). As medical genomics studies become increasingly large and diverse, gaining insights into population history and consequently the transferability of disease ri...

The context in which public health programmes operate can play an important role in influencing their implementation and effectiveness. An intervention that has been shown to be effective in one setting may turn out to be ineffective somewhere else, even supposing it can be implemented there. Therefore, systematic reviews of public health interventions should appraise the applicability of the i...

Convolutional Neural Networks (CNNs) models are one of the most frequently used deep learning networks, and extensively in both academia industry. Recent studies demonstrated that adversarial attacks against such can maintain their effectiveness even when on other than targeted by attacker. This major property is known as transferability, makes CNNs ill-suited for security applications. In this...

OBJECTIVES To estimate the transferability of processes of care from general practitioners (GPs) to allied healthcare professionals and the determinants of such transferability. DESIGN French national cross-sectional multicentre study SETTING: 128 family practices providing supervised training for residents in general practice. PARTICIPANTS All patients consulting with their GP over a total...

Soft Sensors (SSs) are inferential dynamical models employed in industries to perform prediction of process hard-to-measure variables based on their relation with easily accessible ones. They allow implementation real-time control and monitoring the plants present other advantages terms costs efforts. Given complexity industrial processes, these generally designed data-driven black-box machine ...