一种高效率MCU芯片Multi-Sites测试技术

介绍了使用Multi-Sites工程测试技术提高MCU芯片测试效率的方案。针对MCU芯片Multi-Sites测试难点,阐述了在MCU芯片Multi-Sites测试中电性能测试、功能测试的影响因素和解决方案,并对MCU芯片Multi-Sites测试过程中经常遇到的干扰因素进行分析,保证MCU芯片Multi-Sites测试获得稳定可靠的性能参数,有效提高测试效率。

基于Multi-Site并行测试的效率分析与研究

在晶圆芯片测试时,提高单位时间内的效率能够实现低投入、高产出的效果。在采用Multi-site方式的并行测试中,需要先解决选择何种产品进行并行测试,如何确定并行site数等问题,然后再用最高效率的方法设计确定Multi-site并行测试方案。从软件和硬件方面,分析当前流行的Multi-site并行测试的效率,研究了影响Multi-site并行测试效率的各种因素,并对其影响深度和范围进行分析,给出相应的对策和提高效率的解决方法,同时还提出了溢出die计算方法,通过选择适当的site数,减少无用touchdown次数,提高测试效率。

Nuclephilic ring opening of epoxides promoted by multi-site phase-transfer catalyst:An efficient and eco-friendly route to synthesis of β-hydroxythiocyanate

A highly effective and mild protocol for ring opening of epoxides with NH4SCN in the presence of catalytic amount of a multi- site phase-transfer catalyst, α,α＇,α＂-N-hexakis（triethylammoniummethylene chloride）-melamine, is developed. A variety of ^-hydroxy thiocyanates as important intermediates in agricultural and pharmaceutical chemistry were obtained in high yields with excellent regioselectivity and in short reaction times. 2009 Ali Reza Kiasat. Published by Elsevier B.V. on behalf of Chinese Chemical Society. All rights reserved.

Current climate overrides past climate change in explaining multi-site beta diversity of Lauraceae species in China

Background:We aimed to characterise the geographical distribution of Sørensen-based multi-site dissimilarity(β_(sor))and its underlying true turnover(β_(sim))and nestedness(βsne)components for Chinese Lauraceae and to analyse their relationships to current climate and past climate change.Methods:We used ensembles of small models(ESMs)to map the current distributions of 353 Lauraceae species in China and calculated β_(sor) and its β_(sim) and β_(sne) components.We tested the relationship between β_(sor),β_(sne) and β_(sim) with current climate and past climate change related predictors using a series of simultaneous autoregressive(SAR_(err))models.Results:Spatial distribution of β_(sor)of Lauraceae is positively correlated with latitude,showing an inverse rela-tionship to the latitudinalα-diversity(species richness)gradient.High β_(sor) occurs at the boundaries of the warm temperate and subtropical zones and at the Qinghai-Tibet Plateau due to high β_(sne).The optimized SAR_(err) model explainsβ_(sor) andβ_(sne) well,but notβ_(sim).Current mean annual temperature determinesβ_(sor) and β_(sne) of Lauraceae more than anomalies and velocities of temperature or precipitation since the Last Glacial Maximum.Conclusions:Current low temperatures and high climatic heterogeneity are the main factors explaining the high multi-siteβ-diversity of Lauraceae.In contrast to analyses of the β-diversity of entire species assemblages,studies of single plant families can provide complementary insights into the drivers of β-diversity of evolutionarily more narrowly defined entities.

Multi-site spinal stimulation strategies to enhance locomotion after paralysis

With the advent of spinal cord epidural stimulation techniques,i.e.,electrically enabled motor control（e Emc）in combination with activity dependent locomotor training,humans with traumatic complete sensori-motor paralysis are able to initiate voluntary leg movements and achieve gains in postural control,and bladder and sexual function（Angeli et al.,2014）.

基于ATE的电源芯片Multi-Site测试设计与实现

介绍了电源芯片的多Site测试设计与实现。基于CTA8280测试系统,通过对芯片CP(晶圆测试)要求进行分析,设计了8 Site测试电路外围,能够实现对晶圆进行8 Die并行测试。测试结果显示,该方案能够有效提升该电源芯片的测试效率,降低测试成本。

Accurate Multi-Site Daily-Ahead Multi-Step PM_(2.5)Concentrations Forecasting Using Space-Shared CNN-LSTM

Accurate multi-step PM_(2.5)(particulate matter with diameters≤2.5 um)concentration prediction is critical for humankinds’health and air populationmanagement because it could provide strong evidence for decisionmaking.However,it is very challenging due to its randomness and variability.This paper proposed a novel method based on convolutional neural network(CNN)and long-short-term memory(LSTM)with a space-shared mechanism,named space-shared CNN-LSTM(SCNN-LSTM)for multi-site dailyahead multi-step PM_(2.5)forecasting with self-historical series.The proposed SCNN-LSTM contains multi-channel inputs,each channel corresponding to one-site historical PM_(2.5)concentration series.In which,CNN and LSTM are used to extract each site’s rich hidden feature representations in a stack mode.Especially,CNN is to extract the hidden short-time gap PM_(2.5)concentration patterns;LSTM is to mine the hidden features with long-time dependency.Each channel extracted features aremerged as the comprehensive features for future multi-step PM_(2.5)concentration forecasting.Besides,the space-shared mechanism is implemented by multi-loss functions to achieve space information sharing.Therefore,the final features are the fusion of short-time gap,long-time dependency,and space information,which enables forecasting more accurately.To validate the proposed method’s effectiveness,the authors designed,trained,and compared it with various leading methods in terms of RMSE,MAE,MAPE,and R^(2)on four real-word PM_(2.5)data sets in Seoul,South Korea.The massive experiments proved that the proposed method could accurately forecast multi-site multi-step PM_(2.5)concentration only using self-historical PM_(2.5)concentration time series and running once.Specifically,the proposed method obtained averaged RMSE of 8.05,MAE of 5.04,MAPE of 23.96%,and R^(2)of 0.7 for four-site daily ahead 10-hourPM_(2.5)concentration forecasting.

Preparation of Cellulose Nanofibrils by Multi-Site Regioselective Oxidation

Cellulose nanofibrils(CNFs)are promising sustainable materials that can be applied to nanocomposites,as well as medical and life-sciences devices.However,methods for the preparation of these important materials are energy intensive because heating and mechanical disintegration are required to produce cellulose fibers below 100 nm in size.In this study,CNFs were prepared through the multi-site regioselective oxidation of cellulose with 2,2,6,6-tetramethylpiperidine-1-oxyl(TEMPO)and periodate at room temperature(20–25°C),without any mechanical-disintegration treatment.Transmission electron microscopy(TEM)revealed that the CNFs had the average widths of 14.1,55.4,and 81.9 nm for three different treatments.Fourier-transform infrared spectroscopy revealed that carboxyl groups were created on the surfaces of the microfibrils,while X-ray diffraction studies showed that the cellulose I structure was maintained after oxidation,and that the cellulose nanofibril crystallinity index exceeded 70%.These results demonstrate that CNFs can be prepared by multi-site regioselective oxidation at room temperature in the absence of mechanical disintegration.In addition,a model was developed to calculate the total content of carboxylate and aldehyde groups of CNFs prepared by the TEMPO mediate oxidation,the periodate oxidation,and the multi-site regioselective oxidation methods based on the particle width determined by TEM.The calculated values of the model were in good agreement with the total content(experimental value)of carboxylate and aldehyde groups of CNFs prepared by the TEMPO-mediated oxidation and the multi-site regioselective oxidation methods.However,the model was not valid for CNFs prepared by the periodate oxidation method.

Regulated multi-sited practice for physicians in China: incentives and barriers

The multi-sited practices (MSP) policy in China is expected to exert found implications upon uneven distribution of high-quality medical resources,coupled with the widespread phenomenon of physician's informal practices on multiple sites.Since 2009,the Chinese government has upheld a policy that allows medical doctors to take on secondary jobs for the purpose of encouraging talented physicians to work in medical institutions and underdeveloped areas where their expertise is badly needed.This paper focuses on the MSP policy in China by examining how it has been implemented at the national and provincial levels through a review of government documents,statistical information,academic papers,and newspaper accounts.Despite the MSP policy is to offer incentive to physicians at first-tier public hospitals to work in primary care centers or areas where their expertise,the evidence is hard to find.This paper identifies several outstanding challenges to the MSP policy:(1) The importance of the MSP policy which is made by the central government is perceived differently at the provincial level by health officials and hospital administrators;(2) Interest in implementing the policy varies among physicians and hospitals;(3) Concerns about quality control and legal responsibilities for medical doctors to take on secondary jobs are widespread.China's MSP policy differs from the 'dual practice' policy in many countries because of its top-down approach,with its emphasis on government's role and administrative intervention.This paper's findings may be useful for other developing countries where medical expertise is unevenly distributed due to market forces.On the special occasion of the Alma Ata Declaration's 40th anniversary and for the sake of promoting Universal Health Coverage,this paper also aims at sharing with other countries China's experience in trying to develop an adequate force of primary care professionals.At the end of this paper,a four-point proposal is made for policy makers in China.

MCU芯片Multi-Sites测试中几个值得关注的问题

介绍了MCU芯片Multi-Sites测试方法,针对MCU芯片Multi-Sites测试的难点,阐述了在MCU芯片Multi-Sites测试过程中经常影响测试系统和测试效率的问题。主要提出了MCU芯片MultiSites测试过程中的直流参数测试、功能测试的影响因素和解决方案,并对MCU芯片Multi-Sites测试过程中经常遇到的干扰因素进行分析,尽可能保证MCU芯片Multi-Sites测试过程中获得的各项性能参数稳定可靠。

ON ANALYSIS METHOD FOR INFRARED MULTI-SITES SYSTEM PERFORMANCE

The calculation method about infrared multi-sites passive system location is introduced based on the principle of the weighted least square method, and the variance matrix of estimated error is offered. Through deduction, it can be found out that treated appraise precision can be directly analyzed and deduced without carrying out real measure and reaching estimation value. The simulation result shows that the system performance based on the weighted least square method is much better than the traditional passive location method, and it can be also used for reference to the research of the location algorithm of similar system.

Controllable construction of ionic frameworks for multi-site synergetic enhancement of CO_(2) capture

CO_(2) capture is one of the key technologies for dealing with the global warming and implementing lowcarbon development strategy.The emergence of ionic metal-organic frameworks(I-MOFs)has diversified the field of porous materials,which have been extensively applied for gas adsorption and separation.In this work,amino-functionalized imidazolium ionic liquid as organic monodentate ligand was used for one step synthesis microporous Cu based I-MOFs.Precise tuning of the adsorption properties was obtained by incorporating aromatic anions,such as phenoxy,benzene carboxyl,and benzene sulfonic acid group into the I-MOFs via a facile ion exchange method.The new I-MOFs showed high thermal stability and high capacity of 5.4 mmol·g^(-1) under atmospheric conditions for selective adsorption of CO_(2).The active sites of microporous Cu-MOF are the ion basic center and unsaturated metal,and electrostatic attraction and hydroxyl bonding between CO_(2) and modified functional sulfonic groups are responsible for the adsorption.This work provides a feasible strategy for the design of I-MOF for functional gas capture.

Generative adversarial networks for detecting contamination events in water distribution systems using multi-parameter,multi-site water quality monitoring

Contamination events in water distribution networks(WDNs)can have a huge impact on water supply and public health;increasingly,online water quality sensors are deployed for real-time detection of contamination events.Machine learning has been used to integrate multivariate time series water quality data at multiple stations for contamination detection;however,accurate extraction of spatial features in water quality signals remains challenging.This study proposed a contamination detection method based on generative adversarial networks(GANs).The GAN model was constructed to simultaneously consider the spatial correlation between sensor locations and temporal information of water quality indicators.The model consists of two networksda generator and a discriminatordthe outputs of which are used to measure the degree of abnormality of water quality data at each time step,referred to as the anomaly score.Bayesian sequential analysis is used to update the likelihood of event occurrence based on the anomaly scores.Alarms are then generated from the fusion of single-site and multi-site models.The proposed method was tested on a WDN for various contamination events with different characteristics.Results showed high detection performance by the proposed GAN method compared with the minimum volume ellipsoid benchmark method for various contamination amplitudes.Additionally,the GAN method achieved high accuracy for various contamination events with different amplitudes and numbers of anomalous water quality parameters,and water quality data from different sensor stations,highlighting its robustness and potential for practical application to real-time contamination events.

D3Targets-2019-nCoV: a webserver for predicting drug targets and for multi-target and multi-site based virtual screening against COVID-19

A highly effective medicine is urgently required to cure coronavirus disease 2019(COVID-19).For the purpose,we developed a molecular docking based webserver,namely D3 Targets-2019-nCoV,with two functions,one is for predicting drug targets for drugs or active compounds observed from clinic or in vitro/in vivo studies,the other is for identifying lead compounds against potential drug targets via docking.This server has its unique features,(1)the potential target proteins and their different conformations involving in the whole process from virus infection to replication and release were included as many as possible;(2)all the potential ligand-binding sites with volume larger than 200 A^3 on a protein structure were identified for docking;(3)correlation information among some conformations or binding sites was annotated;(4)it is easy to be updated,and is accessible freely to public(https://www.d3 pharma.com/D3 Targets-2019-nCoV/index.php).Currently,the webserver contains 42 proteins[20 severe acute respiratory syndrome-related coronavirus 2(SARS-CoV-2)encoded proteins and 22 human proteins involved in virus infection,replication and release]with 69 different conformations/structures and 557 potential ligand-binding pockets in total.With 6 examples,we demonstrated that the webserver should be useful to medicinal chemists,pharmacologists and clinicians for efficiently discovering or developing effective drugs against the SARS-CoV-2 to cure COVID-19.

A comparison of single- and multi-site calibration and validation： a case study of SWAT in the Miyun Reservoir watershed, China

An essential task in evaluating global water resource and pollution problems is to obtain the optimum set of parameters in hydrological models through calibra- tion and validation. For a large-scale watershed, single-site calibration and validation may ignore spatial heterogeneity and may not meet the needs of the entire watershed. The goal of this study is to apply a multi-site calibration and validation of the Soil and Water Assessment Tool （SWAT）, using the observed flow data at three monitoring sites within the Baihe watershed of the Miyun Reservoir watershed, China. Our results indicate that the multi-site calibration parameter values are more reasonable than those obtained from single-site calibrations. These results are mainly due to significant differences in the topographic factors over the large-scale area, human activities and climate variability. The multi-site method involves the division of the large watershed into smaller watersheds, and applying the calibrated parameters of the multi-site calibration to the entire watershed. It was anticipated that this case study could provide experience of multi-site calibration in a large-scale basin, and provide a good foundation for the simulation of other pollutants in follow- up work in the Miyun Reservoir watershed and other similar large areas.

2型糖尿病合并感染患者肺炎克雷伯菌分布及预后影响因素分析

目的:探讨2型糖尿病(T2DM)合并感染患者肺炎克雷伯菌(KP)分布及预后影响因素分析。方法:选择226例T2DM患者为研究对象,根据是否合并KP感染分为未感染组(n=170)和感染组(n=56),分析T2DM患者感染的危险因素。收集T2DM合并感染患者KP标本,记录标本来源并进行菌种鉴定和药敏试验,并对所有菌株进行多位点序列(MLST)分型,记录预后情况。结果:基础疾病、抗生素使用、侵入性操作、血清白蛋白(ALB)、糖化血红蛋白(HbA1c)、空腹血糖(FPG)为影响T2DM发生感染的危险因素(均P<0.05)。T2DM合并感染患者体内分离56株肺炎克雷伯菌,肺炎克雷伯菌在痰液中的占比最高为44.62%,其次为尿液19.64%,血液中占比16.07%,脓液中占比12.5%,其他标本占比7.14%。56株KP总耐药率最高为氨苄西林,最低为亚胺培南,痰液标本中KP对头孢呋辛、头孢哌酮、庆大霉素耐药率高于非痰液标本,非痰液标本中KP对头孢他啶高于痰液标本(均P<0.05)。56株肺炎克雷伯菌MLST分型共发现42个ST型,ST-20型、36型、65型、347型、660型各2株,分别占3.57%,23型4株占7.14%,ST-17、25、29、35、37、45、86、189、208、211、218、322、355、412、490、519、557、595、726、776、1049、1092、1103、1319、1569、1916、2059、3014、3140、3536、4023、4194、4262、4412、4857型各1株,分别占1.78%,其他ST型7株占比12.5%。56例T2DM合并KP感染患者预后良好患者52例,预后不良患者4例,预后良好率为92.86%。结论:T2DM合并感染患者KP主要分布在痰液和尿液中,基础疾病、抗生素使用、侵入性操作、ALB、HbA1c、FPG是影响KP感染发生危险因素,T2DM合并KP感染患者根据药敏结果选择用药,有利于患者预后。

高毒力肺炎克雷伯杆菌致多部位感染的病例分析

肺炎克雷伯杆菌是一种常见的机会性病原体,基于其高毒力性和易发转移性感染的特征,可引起呼吸系统感染、泌尿系统感染以及肝脓肿等,甚至可以发展成脓毒血症。根据其毒力特征,可分为经典和高毒力肺炎克雷伯杆菌,高毒力肺炎克雷伯杆菌感染常发展迅速,累及全身,病情危重,预后极差,死亡率高。本文选取本院近期收治的3例肺炎克雷伯杆菌感染患者,均有多个器官及组织脓肿,伴有严重的多脏器损害,病情进展迅速,其中1例患者死亡,其余2例患者治疗时间长,迁延多个部位感染,本文总结归纳3例患者特点及治疗方案,对其进行回顾性分析,为临床应对此类感染提供参考,望对此病菌得到重视,早期根据药敏结果针对性用药,缩短患者住院时间,提高临床治疗效果,改善预后。

基于多标签卷积神经网络的结构损伤识别

准确识别结构多位置损伤一直是结构损伤识别的难题。为提升结构多位置损伤识别的准确率,提出一种基于卷积神经网络(CNN)的多标签分类(MLC)方法(CNN-MLC)进行结构损伤识别。该方法将结构多个位置损伤识别转换为多标签分类问题,每个损伤位置均用一个对应的标签表示;利用CNN强大的特征提取能力,深入挖掘不同损伤工况之间公共损伤位置的相关性,实现结构多位置损伤识别。通过四层框架结构和一座铁路连续梁桥多位置损伤识别验证了CNN-MLC方法的识别准确率,并将其识别结果与基于CNN的多类别分类(MCC)方法(CNN-MCC)和基于示例差异化算法(InsDif)的多标签分类方法(InsDif-MLC)进行了对比。结果表明:框架结构在两位置和三位置损伤工况下,CNN-MLC方法比CNN-MCC方法的识别准确率分别提升2.50%和9.64%,比InsDif-MLC方法识别准确率提升17.50%和29.28%;对于铁路连续梁桥的两位置损伤和三位置损伤,CNN-MLC方法比CNN-MCC方法识别准确率提升1.63%和6.85%,比InsDif-MLC方法识别准确率提升4.18%和18.49%;随着损伤位置数量的增加,CNN-MLC方法的识别准确率显著提升。

黄河流域煤炭-煤电-煤化工场地特征精准智能识别方法及应用

黄河流域是“能源流域”,兼具生态环境治理和经济社会发展的重任,涉煤产业场地类型、数量及特征的精准智能识别是流域能源资源-低碳发展-生态保护的关键基础问题。研究融合多源数据与深度学习算法,从流域-基地-场地尺度对黄河流域13个大型煤电基地的煤基场地特征精准解析,获得煤电基地高精度、高质量的本底信息,提出一种实时实景智能识别涉煤产业空间特征的新方法。(1)筛选Google image、GF-6影像、Sentinel-2影像等多源数据,采集13个大型煤电基地煤基场地样本,构建煤炭场地(露天)、煤炭场地(井工)、煤电场地、煤化工场地4类数据集,涵盖21种样本类型。按照每种样本六面体设定6×10个样本,共计1 260个场地样本,分析得出最适样本数量-最高识别效率-最优识别模型的置信区间为80%~86%。(2)建立了煤基场地类型量化模型(Coal-based Site Classification Quantitative Model, CSCQM)和煤基场地范围特征模型(Coalbased Site Range Characteristic Model, CSRCM),模型平均精准度为0.837。明析了黄河流域涉煤产业场地本底信息,提出Google image底图叠加场地智能识别模型解算结果的高精度场地智能识别方法。(3)解析了流域神东煤炭-煤电产业集聚区精准本底数据,依据遥感生态指数(Remote Sensing Based Ecological Index,IRSE)分析,煤基场地分布2 km核心区地表生态质量受煤炭、煤电产业影响明显,5 km缓冲区则影响不明显,而8 km控制区基本不受煤炭、煤电产业影响,从而给出了“动态修复”与分区域、分阶段重点治理等低碳路径。(4)解析了流域宁东煤炭-煤电-煤化工产业集聚区精准本底数据,2022年煤炭场地17.81 km^(2)、占比34.1%,煤化工场地22.3 km^(2)、占比42.6%,煤电场地12.2 km^(2)、占比23.3%,煤化工场地>煤炭场地>煤电场地。进而采用PSR(Pressure-State-Response)模型得到风险管控综合得分53.93分,较2003年提高了27.2%。划分生态维护区、生产监测预警区、损毁修复重建区、其他调控区的分区管控模式。研究为涉煤产业煤基场地潜在污染控制、场地治理及区域生态修复提供技术方法与实践支撑。

基于GA-SA组合算法的山区复杂环境无人机起降点选址

针对山区复杂环境下的物流链前端无人机货运起降点选址和任务分配进行研究。首先以建设成本最小和运输时间满意度最大为目标,综合考虑无人机自身性能和禁飞空域等因素,构建多约束条件下多目标函数的起降点选址和任务分配模型。采用遗传算法(genetic algorithm, GA)和模拟退火算法(simulated annealing algorithm, SA)的组合算法进行求解,首先通过遗传算法得出较优的可行解,再以此解作为退火算法的初始解进行模型求解。仿真结果表明,构建的多约束模型能够实现预期效果,并且采用的算法解决此类问题时具有良好的适用性。