A High-Precision Time Handling Library

An appropriate assessment of end-to-end network performance presumes highly efficient time tracking and measurement with precise time control of the stopping and resuming of program operation. In this paper, a novel approach to solving the problems of highly efficient and precise time measurements on PC-platforms and on ARM-architectures is proposed. A new unified High Performance Timer and a corresponding software library offer a unified interface to the known time counters and automatically identify the fastest and most reliable time source, available in the user space of a computing system. The research is focused on developing an approach of unified time acquisition from the PC hardware and accordingly substituting the common way of getting the time value through Linux system calls. The presented approach provides a much faster means of obtaining the time values with a nanosecond precision than by using conventional means. Moreover, it is capable of handling the sequential time value, precise sleep functions and process resuming. This ability means the reduction of wasting computer resources during the execution of a sleeping process from 100% （busy-wait） to 1-1.5%, whereas the benefits of very accurate process resuming times on long waits are maintained.     

An empirical molecular docking study of a di-iron binding protein with iron ions

Various molecular docking software packages are available for modeling interactions between small molecules and proteins.However,there have been few reports of modeling the interactions between metal ions and metalloproteins.In this study,the AutoDock package was employed to example docking into a di-iron binding protein,bacterioferritin.Each binding site of this protein was tested for docking with iron ions.Blind docking experiments showed that all docking conformations converged into two clusters,one for internal iron binding in sites within the metalloprotein and the other for external iron binding on the protein surface.Local docking experiments showed that there were significant differences between two internal iron binding sites.Docking at one site gave a reasonable root-mean-square deviation(RMSD) distribution with relatively low binding energy.Analysis of the binding mode quality for this site revealed that more than half of the docking conformations were categorized as having good binding geometry,while no good conformations were found for the other site.Further investigations indicated that coordinating water molecules contributed to the stability of binding geometries.This study provides an empirical approach towards the study of molecular docking in metalloproteins.     

高集成RDS调频收音模块设计

主要介绍基于便携式设备的RDS调频收音模块的设计,着重讲述了有关FM接收、RDS数据接收与音频处理等方面的应用电路。     

In Situ Polymerizing Internal Encapsulation Strategy Enables Stable Perovskite Solar Cells toward Lead Leakage Suppression

Despite the outstanding power conversion efficiency (PCE) of perovskite solar cells (PSCs) achieved over the years, unsatisfactory stability and lead toxicity remain obstacles that limit their competitiveness and large-scale practical deployment. In this study, in situ polymerizing internal encapsulation (IPIE) is developed as a holistic approach to overcome these challenges. The uniform polymer internal package layer constructed by thermally triggered cross-linkable monomers not only solidifies the ionic perovskite crystalline by strong electron-withdrawing/donating chemical sites, but also acts as a water penetration and ion migration barrier to prolong shelf life under harsh environments. The optimized MAPbI₃ and FAPbI₃ devices with IPIE treatment yield impressive efficiencies of 22.29% and 24.12%, respectively, accompanied by remarkably enhanced environmental and mechanical stabilities. In addition, toxic water-soluble lead leakage is minimized by the synergetic effect of the physical encapsulation wall and chemical chelation conferred by the IPIE. Hence, this strategy provides a feasible route for preparing efficient, stable, and eco-friendly PSCs.     

Lightweight deep learning methods for panoramic dental X-ray image segmentation

Neural Computing and Applications - Dental X-ray image segmentation is helpful for assisting clinicians to examine tooth conditions and identify dental diseases. Fast and lightweight segmentation...     

Semi-supervised transformable architecture search for feature distillation

Pattern Analysis and Applications - The designed method aims to perform image classification tasks efficiently and accurately. Different from the traditional CNN-based image classification methods,...     

Graph-based fine-grained model selection for multi-source domain

Pattern Analysis and Applications - The prosperity of datasets and model architectures has led to the development of pretrained source models, which simplified the learning process in multi-domain...