The laparoscopic rating scale for the evaluation of working conditions for surgical treatment of super-obesity

In this technical note,a novel rating scale(abdominal integral index)was introduced for assessing the conditions of the working laparoscopic space based on linear measurements to select the optimal one or two-stage surgical treatment for super-obesity.Patients with the same height and similar BMI values had different rating scale scores,reflecting different conditions of laparoscopic bariatric surgery.The rating scale helps surgeons and patients make a safe option for surgery,depending on the experience of the surgeon and technical laparoscopic conditions.

The dynamical complexity of work-hardening:a large-scale molecular dynamics simulation

We analyze a large-scale molecular dynamics simulation of work hardening in a model system of a ductile solid. With tensile loading, we observe emission of thousands of dislocations from two sharp cracks. The dislocations interact in a complex way, revealing three fundamental mechanisms of work-hardening in this ductile material. These are (1) dislocation cutting processes, jog formation and generation of trails of point defects; (2) activation of secondary slip systems by Frank-Read and cross-slip mechanisms; and (3) formation of sessile dislocations such as Lomer-Cottrell locks. We report the discovery of a new class of point defects referred to as trail of partial point defects, which could play an important role in situations when partial dislocations dominate plasticity. Another important result of the present work is the rediscovery of the Fleischer-mechanism of cross-slip of partial dislocations that was theoretically proposed more than 50 years ago, and is now, for the first time, confirmed by atomistic simulation. On the typical time scale of molecular dynamics simulations, the dislocations self-organize into a complex sessile defect topology. Our analysis illustrates numerous mechanisms formerly only conjectured in textbooks and observed indirectly in experiments. It is the first time that such a rich set of fundamental phenomena have been revealed in a single computer simulation, and its dynamical evolution has been studied. The present study exemplifies the simulation and analysis of the complex nonlinear dynamics of a many-particle system during failure using ultra-large scale computing.

Environment and Personal Well-being in Urban China

The aim of this study is to examine the relationship between environment and personal well-being using a sample of 562 urban employees from three cities in Liaoning province in the People's Republic of China.In contrast to previous studies,this study controlled positive affectivity (PA),negative affectivity (NA),job satisfaction and Big Five personality traits.In addition,the research variables of personal well-being index (PWI),positive affectivity,negative affectivity,job satisfaction,Big Five,and environmental satisfaction are measured with multi-item scales.The research finds that environmental satisfaction is positively related to personal well-being,suggesting that improvement of the natural surroundings in the cities can improve people's well-being.

Subjective well-being of Sichuan adolescents from Han, Qiang and Yi nationalities

Using subjective well-being scale for adolescents, this article studies the subjective well-being of 900 adolescents from Han, Qiang and Yi nationalities in mainland of China. Results: In general, the SWB of the adolescents from the three nationalities is at the level of more than medium. Their SWB is significant difference in the aspects of nationality, grade and academic records. In view of interaction, their SWB is also of differ- rent dimensions because the interrelated effects are significant between genders and grades, between genders and academic records, between grades and academic records, and even between grades and their parental educational levels and parental occupations.

Mobile user forecast and power-law acceleration invariance of scale-free networks

This paper studies and predicts the number growth of China＇s mobile users by using the power-law regression. We find that the number growth of the mobile users follows a power law. Motivated by the data on the evolution of the mobile users, we consider scenarios of self-organization of accelerating growth networks into scale-free structures and propose a directed network model, in which the nodes grow following a power-law acceleration. The expressions for the transient and the stationary average degree distributions are obtained by using the Poisson process. This result shows that the model generates appropriate power-law connectivity distributions. Therefore, we find a power-law acceleration invariance of the scale-free networks. The numerical simulations of the models agree with the analytical results well.

A Study of Nurses＇ Well-being Prediction Model in a General Hospital

The study is to explore the well-being of nurses in Eastern Taiwan and significant predictive factors. Clinical nurses are responsible for improving patient well-being; whereas nurse＇s perceived well-being and which factors affect the well-being of nurses has not explored. A cross-sectional related survey is on nurses at a teaching hospital in Eastern Taiwan. There were 375 nurses completed surveys. The instruments include Well-Being Scale, Work Environment Perception Scale, Health-Promoting Lifestyle Scale and Leisure Coping Strategy Scale. Data were analyzed using descriptive statistic, Spearman＇s correlation and stepwise regression. Joy and comfort were two major components of nurses＇ well-being; seven significant predictors explained 63.9% of the variance in the well-being distribution. The findings supported ways to promote the nurses＇ well-being with the seven significant predictors. These results from the clinical nurses＇ perspective and provide an evidence for policy development, improve nurses work environment and to promote nurse healthy life and well-being.

Humanizing the Culture of Technology Teams: Strategies for Creating Healthier and More Productive Work Environments

With the advancement of technology, companies are increasingly dependent on technology teams to stay competitive. However, members of these teams often work in stressful and unhealthy environments, which can undermine their productivity and well-being. The humanization of the culture of technology teams is an approach that aims to create healthier and more productive work environments for team members, promoting balance between personal and professional life. Despite the importance of a healthy and productive work environment, many companies do not invest in strategies to humanize the culture of their technology teams. This can lead to high levels of stress, staff turnover and low productivity. The objective of this project is to identify effective strategies to humanize the culture of technology teams and create healthier and more productive work environments in digital companies. For this, factors such as management styles, psychological safety, human-centered development, individual beliefs and time and energy management will be analyzed. The project’s methodology will include a literature review on the subject and qualitative data analysis will be performed using a content analysis approach. This project will contribute to the advancement of knowledge about the humanization of the culture of technology teams in digital companies. The results can be applied to companies that want to create healthier and more productive work environments for their team members.

考虑谐波严重程度的长时间尺度谐波责任划分方法

针对现有谐波责任划分方法未考虑不同谐波严重程度下责任所造成的实际影响差异,提出一种考虑谐波严重程度的长时间尺度谐波责任划分方法。考虑谐波数值分布与变化趋势两方面因素划分工况,并计算各工况综合权重量化谐波严重程度;基于典型相关性分析原理筛选长时间尺度数据,并根据谐波责任定义式估算谐波责任;结合上述综合权重获取长时间尺度综合谐波责任划分指标;采用仿真算例与实测数据进行验证,与传统方法相比,所提方法可反映各谐波源在长时间尺度下不同次数谐波造成的累计影响,更适用于谐波精准治理与公平奖惩工作。

基于GAN和MS-ResNet的房颤自动检测模型

房颤是一种常见的心律失常疾病,针对现有研究工作大多依赖于单尺度信号段而忽略了不同尺度下潜在的互补信息和数据不平衡问题导致诊断性能下降的问题,提出了一种新颖的基于生成对抗网络(generative adversarial network, GAN)和多尺度残差网络(multiscale residual net, MS-ResNet)的房颤自动检测模型,该网络使用GAN合成具有高形态相似性的单导联心电数据来解决数据的隐私和不平衡问题。同时,设计了MS-ResNet特征提取策略,从不同尺度提取不同大小信号段的特征,从而有效地捕捉P波消失和RR间期不规则特征。该模型联合这两种策略不仅为房颤自动检测生成高质量心电图(electrocardiogram,ECG)数据,还可以利用多尺度网格提取不同波之间的时序特征。在PhysioNet Challenge2017公开ECG数据集上以及平衡后的数据集上评估了MS-ResNet的性能,并将其与现有的房颤分类模型进行了比较。实验结果表明,MS-ResNet在平衡后的数据集上平均F1值和精确率分别达到0.914 1和91.56%,与不平衡数据集相比,F1提高了4.5%,精确率提高了3.5%。

基于边缘辅助和多尺度Transformer的无参考屏幕内容图像质量评估

与从现实场景中拍摄的自然图像不同,屏幕内容图像是一种合成图像,通常由计算机生成的文本、图形和动画等各种多媒体形式组合而成.现有评估方法通常未能充分考虑图像边缘结构信息和全局上下文信息对屏幕内容图像质量感知的影响.为解决上述问题,本文提出一种基于边缘辅助和多尺度Transformer的无参考屏幕内容图像质量评估模型.首先,使用高斯拉普拉斯算子构造由失真屏幕内容图像高频信息组成的边缘结构图,然后通过卷积神经网络(Convolutional Neural Network,CNN)对输入的失真屏幕内容图像和相应的边缘结构图进行多尺度的特征提取与融合,以图像的边缘结构信息为模型训练提供额外的信息增益.此外,本文进一步构建了基于Transformer的多尺度特征编码模块,从而在CNN获得的局部特征基础上更好地建模不同尺度图像和边缘特征的全局上下文信息.实验结果表明,本文提出的方法在指标上优于其他现有的无参考和全参考屏幕内容图像质量评估方法,能够取得更高的主客观视觉感知一致性.

基于胜任力量表的中国工会社会工作自主知识体系构建

在我国社会工作本土化的进程中,工会社会工作以其独特的实践模式和深厚的群众基础,成为最具中国特色的实践领域之一。然而,工会社会工作的本土实践深化面临着诸多挑战,其中工会社会工作者的实践能力是关键因素。本研究通过问卷调查和探索性因子分析,构建了工会社会工作者胜任力量表,萃取了包括价值素养、场景素养与专业素养在内的三个维度胜任力指标。这一量表不仅为评估和提升工会社会工作者的实践能力提供了有效工具,也为深入理解中国工会社会工作的实践要求提供了理论支撑。基于工会社会工作者胜任力量表,本研究从工会社会工作本土实践场景的要求出发,进一步讨论了构建中国工会社会工作“政治—场景—专业”三维自主知识体系的学理构思。

工作-生活平衡量表在护士工作-生活平衡状态中的应用评价

目的探讨工作-生活平衡量表用于测评护士工作-生活平衡状态的信度和效度,为调查护士工作-生活平衡状态提供科学、严谨的测评工具。方法2023年2月1日至3月1日使用工作-生活平衡量表对广西医科大学第一附属医院、广西医科大学第二附属医院、广西医科大学附属武鸣医院3所三甲医院具有临床工作经验1年及以上的526名护士进行测定,并对测评结果进行信效度检验。结果总量表Cronbach′s α系数为0.940,分半信度为0.881;3个因子内部Cronbach′s α系数为0.819~0.930,折半信度为0.796~0.899,量表信度良好。该量表包含3个因子,累积解释方差变异为68.857%。每个条目的因子载荷值为0.468~0.862,而条目的具体归属则与以往的研究结论有所不同。3个分量表间的相关系数为0.515~0.663,总量表的相关系数为0.731~0.949,说明量表结构、内容效度良好。验证性因素分析量表的理论模型剔除2个条目后标准化残差均方根为0.070,比较拟合指数为0.904。结论工作-生活平衡量表测评护士工作-生活平衡状态具有较好的信度和结构效度,模型拟合度稍差,建议扩大样本量进一步验证。

中青年急性心肌梗死患者重返工作障碍量表编制及信度效度检验

目的:编制中青年急性心肌梗死患者重返工作障碍量表并检验其信度、效度,为评估中青年急性心肌梗死患者重返工作障碍程度提供可靠工具。方法:基于Feuerstein模型,通过文献研究、访谈和德尔菲专家函询法,形成初始量表。采用便利抽样法,选取2022年8月—11月浙江省某综合性医院414例中青年急性心肌梗死患者进行正式调查,筛选条目并检验量表的信度、效度。结果:中青年急性心肌梗死患者重返工作障碍量表包含4个维度,20个条目。探索性因子分析最终提取4个公因子,累计方差贡献率为64.437%。量表各条目内容效度指数为0.80~1.00,平均内容效度指数为0.94。量表总的Cronbach’sα系数、重测信度分别为0.915、0.997。结论:中青年急性心肌梗死患者重返工作障碍量表具有良好的信度、效度,可作为中青年急性心肌梗死患者重返工作障碍程度的评估工具。

联合注意力和条件GAN的被遮挡人体姿态和体形估计方法

基于图像的人体姿态和体形估计常常因人体被遮挡而充满挑战.为此,提出一种基于单幅图像的姿态和体形估计方法.首先提出多尺度的注意力模块策略,输出具有丰富上下文信息的多尺度注意力特征,以有效地获得不受遮挡影响的全局的姿态和体形分布;然后提出基于热图的条件生成对抗网络策略,将由关节热图得到的姿态估计作为约束,实现网格精细调整;最后借助这2个策略得到的姿态和体形估计方法实现全局预测和局部细节求精的结合.在Ubuntu环境下,在3DPW,3DOH50K和Human3.6M公开数据集上的实验结果表明,与SMPLify,GraphCMR和SPIN等方法相比,所提方法在身体部分被遮挡时重建效果更好,并在ACK,AVE和PA-MPJPE等定量评价指标上取得了更好的结果.

基于GA-BP神经网络的月生活需水预测——以黄河流域为例

在水利高质量发展的背景下,为了更精准地反映未来需水情势,探索月尺度需水的预测方法十分必要,有利于有效规划和管理供水系统以解决水资源短缺问题。以黄河流域9个省区为例,对月生活用水规律进行分析,通过奇异谱分析(singular spectrum analysis,SSA)法对用水规律进行验证,引入遗传算法对BP神经网络预测模型进行改进,分别建立基于时间序列的单变量模型和基于影响因子的多变量模型,并将预测结果与BP神经网络模型预测结果进行比较。结果表明:改进预测模型对各省区2020年月生活需水量预测的平均相对误差基本在5%以内,精度优于BP神经网络模型,对水资源精细化管理具有一定的参考价值。

新时代健全干部容错工作机制的边界尺度、现实困境和路径选择

新时代健全干部容错工作机制是落实“三个区分开来”重要讲话精神、建设堪当民族复兴重任的高素质干部队伍的重要举措。在健全干部容错工作机制的过程中,一是要明确何错可容的边界尺度是“容为公之失,惩为私之罪”“免创新之责,担逾矩之过”;二是要探究有错难容的现实困境,包括认知困境、实施困境、管理困境、制度困境的成因和表征;三是要完善有错能容机制,通过重塑容错认知、优化容错运转、整合容错主体、完善容错制度等路径,对干部容错工作机制面临的现实困境逐一破解,从而系统构建起干部容错工作机制。

新形势下高校研究生导师工作压力现状与对策

研究生导师是培养高素质创新型人才的重要群体,随着高等教育事业的快速发展,研究生导师面临的工作压力日益增大,这不利于导师身心健康和研究生培养质量。为了全面掌握新形势下我国高校研究生导师的工作压力状况,有针对性缓解研究生导师的工作压力,避免职业倦怠感的产生,在文献研究的基础上从教学压力、科研压力、指导压力、角色压力和制度压力五个维度开发了研究生导师工作压力的测量量表并编制了调查问卷,基于421个样本数据对测量量表的信度和效度进行检验,并对高校研究生导师的工作压力现状进行总体水平分析、单因素分析和回归分析。研究结果表明:所开发的研究生导师工作压力测量量表具有良好的信度和效度;新形势下高校研究生导师总体工作压力水平介于中度压力和较大压力之间,五个压力源的压力水平由高到低分别为制度压力、科研压力、指导压力、教学压力和角色压力;对于不同性别、年龄阶段、身份、职称、工作年限、学科领域和高校类型,研究生导师工作压力在不同维度上存在一定的差异性。在此基础上,从建立缓解研究生导师工作压力的有效机制、提高研究生导师应对工作压力的能力和关注重点研究生导师群体的工作压力三个方面,提出了缓解新形势下高校研究生导师工作压力的对策与建议。

基于MES−YOLOv5s的综采工作面大块煤检测算法

综采工作面的目标具有高速运动、多尺度、遮挡等特点,现有的目标检测算法存在精度低、模型占用的内存大、硬件依赖强等问题。针对上述问题,提出了一种基于MES−YOLOv5s的综采工作面大块煤检测算法。采用轻量化设计,将MobileNetV3作为主干网络,以减小模型占用的内存,提高CPU端的检测速度;在颈部网络添加高效多尺度注意力(EMA)模块,融合不同尺度的上下文信息,并进一步减少计算开销;采用SIoU损失函数代替CIoU损失函数,以提高训练速度和推理准确性。消融实验结果表明:MobileNetV3大幅减少了模型占用的内存和检测时间,但mAP损失严重;EMA模块和SIoU损失函数可在一定程度上恢复损失的精度,同时保证模型在CPU上具有较高的检测速度,满足煤矿井下目标实时检测需求。对比实验结果表明,与DETR,YOLOv5n,YOLOv5s,YOLOv7模型相比,MES−YOLOv5s模型综合性能最好,mAP为84.6%,模型占用的内存为11.2 MiB,在CPU端的检测时间为31.8 ms,在高速运动、多尺度、遮挡和多目标的工况环境下能够保持较高的召回率和精度。

工作面尺度和顶煤厚度影响下的放煤规律研究

结合理论分析、数值模拟和工程测试,对顶煤放出规律进行分析,探究顶煤厚度和工作面尺度对放煤结果的影响规律。研究表明:煤岩模型尺度对顶煤运移状态影响较小,对工作面放煤结果的统计分析会产生明显影响;放煤口数目由40增长到100,工作面顶煤回收效率由68%增长到77%,放出煤量和放煤时间明显减少;采用全尺度煤岩模型的放煤模拟更加符合工程实际。随顶煤层厚度由2 m增大到5 m,顶煤回收率由78%逐渐降低到71.6%;总放煤时间非线性增大,各支架放煤波动性增大。

基于多尺度特征记忆增强的异常行为检测算法

针对传统视频异常行为检测任务中存在目标对象空间尺寸变化差异大和对异常行为预测的泛化能力过强等问题,提出一种基于多尺度特征记忆增强的视频异常行为检测改进方法。通过多分支结构的空洞卷积组成的多尺度特征模块在高级特征图上提取不同尺度的特征信息,级联记忆增强模块存储正常行为特征以削弱泛化能力。在多尺度特征模块和记忆增强模块的协同工作下能够有效收集和记忆正常行为场景中的多尺度特征信息。以实验分析验证该方法的有效性。