Pressure stimulated current in progressive failure process of combined coal-rock under uniaxial compression:Response and mechanism

Effective monitoring of the structural health of combined coal-rock under complex geological conditions by pressure stimulated currents(PSCs)has great potential for the understanding of dynamic disasters in underground engineering.To reveal the effect of this way,the uniaxial compression experiments with PSC monitoring were conducted on three types of coal-rock combination samples with different strength combinations.The mechanism explanation of PSCs are investigated by resistivity test,atomic force microscopy(AFM)and computed tomography(CT)methods,and a PSC flow model based on progressive failure process is proposed.The influence of strength combinations on PSCs in the progressive failure process are emphasized.The results show the PSC responses between rock part,coal part and the two components are different,which are affected by multi-scale fracture characteristics and electrical properties.As the rock strength decreases,the progressive failure process changes obviously with the influence range of interface constraint effect decreasing,resulting in the different responses of PSC strength and direction in different parts to fracture behaviors.The PSC flow model is initially validated by the relationship between the accumulated charges of different parts.The results are expected to provide a new reference and method for mining design and roadway quality assessment.

Coal-rock gas:Concept,connotation and classification criteria

In recent years,great breakthroughs have been made in the exploration and development of natural gas in deep coal-rock reservoirs in Junggar,Ordos and other basins in China.In view of the inconsistency between the industrial and academic circles on this new type of unconventional natural gas,this paper defines the concept of"coal-rock gas"on the basis of previous studies,and systematically analyzes its characteristics of occurrence state,transport and storage form,differential accumulation,and development law.Coal-rock gas,geologically unlike coalbed methane in the traditional sense,occurs in both free and adsorbed states,with free state in abundance.It is generated and stored in the same set of rocks through short distance migration,occasionally with the accumulation from other sources.Moreover,coal rock develops cleat fractures,and the free gas accumulates differentially.The coal-rock gas reservoirs deeper than 2000 m are high in pressure,temperature,gas content,gas saturation,and free-gas content.In terms of development,similar to shale gas and tight gas,coal-rock gas can be exploited by natural formation energy after the reservoirs connectivity is improved artificially,that is,the adsorbed gas is desorbed due to pressure drop after the high-potential free gas is recovered,so that the free gas and adsorbed gas are produced in succession for a long term without water drainage for pressure drop.According to buried depth,coal rank,pressure coefficient,reserves scale,reserves abundance and gas well production,the classification criteria and reserves/resources estimation method of coal-rock gas are presented.It is preliminarily estimated that the coal-rock gas in place deeper than 2000 m in China exceeds 30×10^(12)m^(3),indicating an important strategic resource for the country.The Ordos,Sichuan,Junggar and Bohai Bay basins are favorable areas for large-scale enrichment of coal-rock gas.The paper summarizes the technical and management challenges and points out the research directions,laying a foundation for the management,exploration,and development of coal-rock gas in China.

基于改进AdvSemiSeg的半监督遥感影像作物制图方法

作物精准遥感制图对于农业资源调查与管理具有重要意义。深度学习为实现精准高效作物制图提供了技术支持。为了缓解深度学习对标记样本的依赖,本文提出了一种改进AdvSemiSeg的半监督遥感影像作物制图方法。所提方法引入STMF-DeepLabv3+作为对抗学习中的生成网络,通过Swin Transformer(ST)和多尺度特征融合(Multi-scale fusion, MF)模块提高生成网络特征编码能力和语义表达能力,改善遥感影像作物分割效果;此外,在判别网络中引入通道注意力(Efficient channel attention, ECA)模块,对不同通道特征图的表征信息进行自适应学习,增强判别网络对不同通道特征的感知能力。模型训练过程中,判别网络为生成网络提供高质量的伪标签和对抗损失,有效提高生成网络的泛化能力。采用所提方法与几种先进的半监督语义分割方法对内蒙古河套灌区遥感影像种植信息进行提取,本文方法性能最优。

基于事件触发的奇异semi-Markov跳变系统的有限时间控制

为减少不必要的网络资源传输,解决实际复杂系统的有限时间问题,提出一种基于事件触发方案的奇异semi-Markov跳变系统的有限时间控制器设计方法。在事件触发方案下,用系统的时滞表示网络诱导时延,闭环系统可以建模为一个时滞系统。首先,通过构造合适的Lyapunov-Krasovskii泛函,以严格矩阵不等式的形式给出充分条件,以使事件触发方案下的闭环系统正则、无脉冲、随机有限时间有界;然后,通过求解矩阵不等式,得到状态反馈控制器的参数;最后,给出一个数值示例,通过仿真证明所提方法的有效性。

Estimating the Drought-Induced Yield Loss for Winter Wheat in a Semi-Arid Region of the Southern United States Using a Drought Index

The economy of most rural locations in the semi-arid region of Llano Estacado in the southern United States is predominantly based on agriculture, primarily beef and wheat (Triticum aestivum L.) production. This region is prone to drought and is projected to experience a drier climate. Droughts that coincide with the critical phenological phases of a crop can be remarkably costly. Although drought cannot be prevented, its losses can be minimized through mitigation measures if it is predicted in advance. Predicting yield loss from an imminent drought is an important need of stakeholders. One way to fulfill this need is using an agricultural drought index, such as the Agricultural Reference Index for Drought (ARID). Being plant physiology-based, ARID can represent drought-yield relationships accurately. This study developed an ARID-based yield model for predicting the drought-induced yield loss for winter wheat in this region by accounting for its phenological phase-specific sensitivity to water stress. The reasonable values of the drought sensitivity coefficients of the yield model indicated that it could reflect the phenomenon of water stress decreasing the winter wheat yields in this region reasonably. The values of the various metrics used to evaluate the model, including Willmott Index (0.86), Nash-Sutcliffe Index (0.61), and percentage error (26), indicated that the yield model performed fairly well at predicting the drought-induced yield loss for winter wheat. The yield model may be useful for predicting the drought-induced yield loss for winter wheat in the study region and scheduling irrigation allocation based on phenological phase-specific drought sensitivity.

Reversible Semi-Fragile Watermarking Technique for Integrity Control of Relational Database

Reversible watermarking schemes for relational database are usually classified into two groups: robust schemes and fragile schemes. The main limitation of existing reversible fragile methods is that they cannot differentiate between legal and malicious modifications. In this paper, we introduce a novel lossless semi-fragile scheme based on prediction-error expansion for content protection of relational database. In the proposed method, all attributes in a database relation are first classified according to their sensitivity to legitimate updates. Then, the watermark is embedded by expanding the prediction error of the two least significant digits of securely selected attributes. At watermark extraction, the proposed method has the ability to fully restore the original data while detecting and localizing tampering. The applicability of our method is demonstrated theoretically and experimentally.

Decentralized Semi-Supervised Learning for Stochastic Configuration Networks Based on the Mean Teacher Method

The aim of this paper is to broaden the application of Stochastic Configuration Network (SCN) in the semi-supervised domain by utilizing common unlabeled data in daily life. It can enhance the classification accuracy of decentralized SCN algorithms while effectively protecting user privacy. To this end, we propose a decentralized semi-supervised learning algorithm for SCN, called DMT-SCN, which introduces teacher and student models by combining the idea of consistency regularization to improve the response speed of model iterations. In order to reduce the possible negative impact of unsupervised data on the model, we purposely change the way of adding noise to the unlabeled data. Simulation results show that the algorithm can effectively utilize unlabeled data to improve the classification accuracy of SCN training and is robust under different ground simulation environments.

Pseudo-Semi-Overlap Functions-Based Fuzzy Rough Sets Applied to Image Edge Extraction

As an extension of overlap functions, pseudo-semi-overlap functions are a crucial class of aggregation functions. Therefore, (I, PSO)-fuzzy rough sets are introduced, utilizing pseudo-semi-overlap functions, and further extended for applications in image edge extraction. Firstly, a new clustering function, the pseudo-semi-overlap function, is introduced by eliminating the symmetry and right continuity present in the overlap function. The relaxed nature of this function enhances its applicability in image edge extraction. Secondly, the definitions of (I, PSO)-fuzzy rough sets are provided, using (I, PSO)-fuzzy rough sets, a pair of new fuzzy mathematical morphological operators (IPSOFMM operators) is proposed. Finally, by combining the fuzzy C-means algorithm and IPSOFMM operators, a novel image edge extraction algorithm (FCM-IPSO algorithm) is proposed and implemented. Compared to existing algorithms, the FCM-IPSO algorithm exhibits more image edges and a 73.81% decrease in the noise introduction rate. The outstanding performance of (I, PSO)-fuzzy rough sets in image edge extraction demonstrates their practical application value.

SEMI标准在半导体制造设备中的应用

SEMI标准是一项国际通用的半导体行业标准,为研究SEMI标准在半导体制造设备中的应用情况,介绍了SEMI S2半导体设备安全准则、SEMI F47半导体设备电压暂降抗扰度标准并说明了标准的实际应用。分析了SEMI S23半导体设备能源、电力和原料的使用效率标准、SECS/GEM通讯标准及其研究应用现状;提出了我国半导体产业的快速发展需要加大SEMI标准的普及应用。

基于多核CPU的无锁并行Semi-naive算法

Datalog系统被广泛应用于很多领域,如图数据库、网络和静态程序分析等。在处理海量数据时,基于串行的Datalog求解策略无法充分发挥现有多核处理器的计算性能。针对上述问题,提出一种基于多核CPU的无锁并行Semi-naive算法(Parallel Semi-naive, PSN)用于支持Datalog的高效求解。PSN使用B+树索引进行数据划分,将数据分配给不同的线程执行计算,每个分区产生的中间结果元组互不相同,有利于实现计算时无锁的并行。同时提出一种双层哈希表结构来索引中间结果以提高查重的效率,每个线程只在特定的区域执行相关的计算,无需使用锁来防止写冲突。PSN使用任务队列-线程池为空闲线程分配任务,来实现多线程的负载均衡。在KONECT(Koblenz Network Collection)及斯坦福SNAP(Stanford Network Analysis Platform)的公开数据集上的实验结果表明,PSN算法可以优化Datalog规则的查询性能。

The Delivery of Grand Multiparas in a Semi-Rural Setting: A Cross-Sectional Descriptive Study at the Ayos Locality of Cameroon

Introduction: Grand multiparity is a known risk factor for maternal and fetal complications. Materials and Methods: We carried out a cross-sectional descriptive study on the delivery of grand multiparas at the maternity of the regional hospital annex of Ayos, a semi-rural locality in the Center region of Cameroon. The study covered the period from January 2012 through December 2020, and the objective was to assess the frequency, the determinants and the outcome of delivery in grand multiparas. Results: We recorded 1384 deliveries and enrolled 137 cases of delivery of grand multiparas. This gives a frequency of grand multipara delivery of 9.89%. The mean age of the women was 34.96 ± 4.45 years. Married parturients accounted for 65% of the cases and 16.8% were HIV positive. Delivery occurred at term in 89.9%. In 35.8%, no antenatal consultation was done. The use of the partograph during labor was reported in 11.7%. Per vaginal delivery was noted in 88.3%, emergency cesarean in 10.2% and elective cesarean in 1.5%. The most frequent maternal complications included post-partum hemorrhage (19.9%), genital tract tears (12.4%), endometritis (9.5%) and surgical wound infection (8.7%). No maternal death was recorded. The mean birth weight of the newborns was 3336.8 ± 550 g. Fetal complications were mostly represented by neonatal infection (20.1%), perinatal death (7.9%) and neonatal asphyxia (9.5%). Conclusion: The frequency of grand multiparous delivery in the semi-rural locality of Ayos, Cameroon, was 9.89%. The mean age of parturients was 38.96 years and the proportion of vaginal delivery was 88.3%.

Radar emitter signal recognition method based on improved collaborative semi-supervised learning

Rare labeled data are difficult to recognize by using conventional methods in the process of radar emitter recogni-tion.To solve this problem,an optimized cooperative semi-supervised learning radar emitter recognition method based on a small amount of labeled data is developed.First,a small amount of labeled data are randomly sampled by using the bootstrap method,loss functions for three common deep learning net-works are improved,the uniform distribution and cross-entropy function are combined to reduce the overconfidence of softmax classification.Subsequently,the dataset obtained after sam-pling is adopted to train three improved networks so as to build the initial model.In addition,the unlabeled data are preliminarily screened through dynamic time warping(DTW)and then input into the initial model trained previously for judgment.If the judg-ment results of two or more networks are consistent,the unla-beled data are labeled and put into the labeled data set.Lastly,the three network models are input into the labeled dataset for training,and the final model is built.As revealed by the simula-tion results,the semi-supervised learning method adopted in this paper is capable of exploiting a small amount of labeled data and basically achieving the accuracy of labeled data recognition.

高地应力缓斜半煤岩巷道断面形状优化研究

为了优化高地应力缓斜半煤岩巷道的断面形状,以东欢坨矿3018工作面运道为工程背景展开研究。通过复变函数理论推导得出了倾斜煤层中不同断面形状的应力解析解,然后运用FLAC3D数值模拟求解了不同断面形状巷道的应力集中和塑性区情况,并以此为基础确定了巷道最优断面形状,最后结合现场工业性试验对研究结果的可靠性进行了验证。研究结果表明:高地应力作用下缓斜半煤岩巷道破坏呈现非对称形式;不管断面形状如何,巷道均在左、右两底角处呈现高应力集中,且应力集中程度矩形>梯形>直墙拱形;直墙拱形巷道稳定性最佳,梯形巷道次之,矩形稳定性最差,确定直墙拱形为最终巷道断面形状;现场巷道表面位移量监测结果表明,直墙拱形巷道更能满足现场安全生产要求。

基于PI的Semi-Markovian电力系统事件触发控制设计分析

基于PI控制器设计理论,本文对电力系统负荷频率的稳定性问题进行分析,提出改进的事件触发机制,对带有不确定性半马尔可夫跳变参数的电力系统进行数学均值期望处理,整理构建成随采样信号状态变化而自适应调整的闭环系统。考虑随机跳变多模态下系统中的干扰影响和时滞虚拟延迟,设计模态依赖控制器,结合矩阵叉积不等式和Schur补定理等,对泛函导数积分项进行放缩,将最优值问题转化为解线性矩阵不等式,最终利用Matlab工具箱求解,求出控制增益和事件触发矩阵,给出系统随机稳定性判据,对系统H∞性能指标进行分析。本文所设计方案可以提高通信网络中控制信号的传输率,有效减轻电网信息输送负担,在节约能源的同时还能提高系统的动态性能。

中青年缓解期精神分裂症患者社会疏离体验的质性研究

背景精神分裂症患者在整个生存期常感知到的较为严重的社会歧视,出现自我疏离或者社会性疏离。目前针对中青年缓解期精神分裂症患者社会疏离方面的研究较少。目的描述中青年缓解期精神分裂症患者社会疏离的体验,旨在为缓解该人群社会疏离体验制订支持干预方案提供一定的借鉴和参考。方法采用目的抽样法选取18~59岁,曾在新乡医学院第二附属医院住院且出院后愿意继续接受随访的中青年缓解期精神分裂症患者为研究对象,于2022年5—12月通过对受访者进行面对面半结构式深入访谈,并以内容分析法归纳和提炼主题。结果共纳入18名中青年缓解期精神分裂症患者。通过对访谈资料进行分析,共提炼出3个主题和8个亚主题:中青年缓解期精神分裂症患者社会疏离的表现(包括2个亚主题:负性情感体验、期待与行为之间的退缩);中青年缓解期精神分裂症患者社会疏离的主观原因(包括2个亚主题:自我疏离、自我歧视)、中青年缓解期精神分裂症患者社会疏离的客观原因(包括4个亚主题:社会歧视和被动疏离、药物不良反应的影响、精神疾病引起的生活和照护负担加重、缺乏社会支持)。结论中青年缓解期精神分裂症患者由于生理健康受损、心理状况不良、社会支持不足等存在社会疏离,医护人员应加强对该人群的症状管理和心理疏导,政府及社会各界应积极引导对精神疾病的正向认知并给予一定的社会支持;同时强化家庭内部支持,以帮助其重返和适应社会。

专注晶圆及封测高端设备厂商达仕科技隆重亮相SEMICON CHINA 2023

根据SEMI报告,2022年全球半导体制造设备出货金额相较2021的1026亿美元增长5%,创下1076亿美元的历史新高,中国内地连续第三年成为全球最大的半导体设备市场。今年一季度全球半导体设备出货金额达到268亿美元,比去年同期增长9%,是不可多得的亮点。SEMI预计,2024年半导体设备市场会重新恢复增长,预计将以15%的增速重新恢复到1000亿美元以上。

基于实测数据的半潜式平台贝叶斯模型修正方法研究

随着半潜式平台的长期海上服役,平台的基本设计参数会发生变化,如仍基于原始设计参数对平台进行分析将影响结果的准确性。本文以半潜式平台服役中易发生变化的基本参数(平台排水量、重心高度和三个自由度回转半径)作为修正参数,以平台横摇、纵摇和垂荡自由度的方差和波频功率谱密度构建目标函数,建立可依据实测数据的半潜式平台贝叶斯参数修正方法。以我国某半潜式平台实测数据为例,开展平台的参数修正研究,并基于修正后的参数对平台多年一遇环境荷载下的响应进行对比评估。

Features and Patterns of Primipara Delivery in a Cameroon Semi-Rural Area: The Case of Ayos Locality

Introduction: The delivery of a primipara, a woman giving birth for the first time, is challenging and may lead to complications and influence the obstetrical future of a woman. Materials and Methods: We carried out a cross-sectional and analytical study at the maternity of the regional hospital annex of Ayos, a semi-rural locality in Cameroon, for the period between January 2012 and December 2020. The objective was to determine the frequency and the determinants of primipara delivery. Results: We recruited 440 cases. The frequency of primipara delivery was 31.8%. The ages of the participants ranged from 12 to 35 years with a mean age of 18.01 ± 3.52 years. Single women contributed to 95.5% of cases while 97.5% were unemployed. The delivery occurred at term in 90.2% and 98.4% of pregnancies were singleton. The delivery was vaginal in 91.6%, while caesarean delivery was done in 8.4% (8% emergency and 0.4% elective). The most frequent maternal complications were genital tract tears (15.7%), post-partum hemorrhage (12.5%) and endometritis (2.7%). The birth weight of newborns ranged from 1070 to 4500 g with a mean of 3024.5 ± 511.4 g. The single marital status, a gestational age between 37 and 42 weeks and a birth weight between 1500 g and 2499 g were significantly associated with vaginal delivery. Conclusion: The frequency of primiparous delivery was relatively high (31.8%) in the Ayos semi-rural health district of Cameroon. Major complications associated with delivery included genital tract tears, post-partum hemorrhage, cesarean section and neo-natal infection.

Inequalities for Scalar Curvature and Shape Operator of an R-Lightlike Submanifold in Semi-Riemannian Manifold

We establish the links between the lightlike geometry and basics invariants of the associated semi-Riemannian geometry on r-lightlike submanifold and semi-Riemannian constructed from a semi-Riemannian ambient. Then we establish some basic inequalities, involving the scalar curvature and shape operator on r-lightlike coisotropic submanifold in semi-Riemannian manifold. Equality cases are also discussed.

半结构访谈联合德尔菲法用于急诊护生的护理迷你临床演练评估量表的构建

目的利用半结构访谈联合德尔菲法构建符合急诊护理的迷你临床演练评估量表(Mini⁃CEX)指标,为评估急诊护生临床护理能力提供有效工具。方法查阅国内外急诊护理相关文献,对符合纳入标准的文献进行归纳整理后,筛选出用于急诊临床护理能力的评价指标,对江苏省苏北人民医院急诊科的16名医生和护士长进行半结构访谈,将半结构访谈内容作为Mini⁃CEX量表的初步量表;然后利用德尔菲法对初步量表的各个指标条目进行专家咨询,形成最终的Mini⁃CEX量表。结果经2轮函询后形成4个一级指标(人文关怀、护理问诊、实践能力、整体表现)、10个二级指标(正确且合理称呼患者,注重患者隐私保护,能够建立良好的护患关系,有效引导和利用问题询问,采集病史完整,准确掌握护理措施流程与使用技巧,准确掌握各种急救药物位置与用法,准确掌握急救相关仪器的使用方法与注意事项,准确评估患者病情、护理指征及评估时间合理、整体效率高,护理过程简洁、流畅及护理措施实施顺序准确),共10个条目的急诊护理Mini⁃CEX量表评分项目指标体系。结论采取半结构访谈法联合德尔菲法所构建的急诊护理Mini⁃CEX量表评价指标对急诊护理带教具有良好的指导作用,能够作为急诊护生临床护理技能的有效评估工具。