Abstract With the goal of “double carbon,” wind power and PV are connected to grid on a large scale, which poses great challenge safe operation grid. The synergistic optimization “hydro-wind-PV hybrid systems” can bring into play ability coordination mutual assistance between different types sources, is one important measures increase reduce abandoned photovoltaic power. Based analysis characte...

The presence of muscle redundancy and co-activation of agonist-antagonist pairs in vivo makes the optimization of the load distribution between muscles in physiologic joint simulators vital. This optimization is usually achieved by employing different control strategies based on position and/or force feedback. A muscle activated physiologic wrist simulator was developed to test and iteratively ...

BACKGROUND Whether for cell culture studies of protein function, construction of mouse models to enable in vivo analysis of disease epidemiology, or ultimately gene therapy of human diseases, a critical enabling step is the ability to achieve finely controlled regulation of gene expression. Previous efforts to achieve this goal have explored inducible drug regulation of gene expression, and con...

The main precondition for applications such as face recognition and face de-identification for privacy protection is efficient face detection in real scenes. In this paper, we propose a hybrid cascade model for face detection in the wild. The cascaded two-stage model is based on the fast normalized pixel difference (NPD) detector at the first stage, and a deep convolutional neural network (CNN)...

The process of human blood clotting involves a complex interaction of continuous-time/continuous-state processes and discrete-event/discrete-state phenomena, where the former comprise the various chemical rate equations (which can be written as differential equations) and the latter comprise both threshold-limited behaviors and qualitative facets of the coagulation cascade. We model this proces...

Background: The generalized space-time autoregressive (GSTAR) model is one of the most widely used models for modeling and forecasting time series location data. Methods: In GSTAR model, there an assumption that research locations are heterogeneous. addition, differences between these shown in form a weighting matrix. novelty this paper we propose hybrid time-series uses cascade neural network ...

Charged particle production is calculated in a hybrid framework consisting of the IP-Glasma initial state, MUSIC viscous relativistic fluid dynamics, and UrQMD microscopic hadronic cascade. Using one set parameters, we compute observables for large variety collision systems. We compare to experimental data p+p, p+Pb, Xe+Xe, Au+Au Pb+Pb collisions at various energies, make predictions potential ...

The safe and stable operation of the energy system is top priority world in industrial field. integrated optimizes through multiple channels cascade utilization energy, which greatly improves rate provides a convenient way for development low-carbon society. In this paper, composite model constructed analysis structure system. On basis, coordinated optimal scheduling method with stations propos...

a simple semi-phenomenological model, which accurately predicts the dependence of thresholdcurrent for temperature of resonant-phonon three well quantum cascade laser based on verticaltransitions is offered. we found that, the longitude optical phonon scattering of thermally excitedelectrons is the most important limiting factor for thermal performance of high frequency thz qcls.in low frequenc...