Comprehensive effects of traditional Chinese medicine treatment on heart failure and changes in B-type natriuretic peptide levels: A meta-analysis

BACKGROUND Heart failure(HF),a common cardiovascular condition,is characterized by significant morbidity and mortality.While traditional Chinese medicine(TCM)is often used as a complementary approach in HF management,systematic evalua-tions of its impact on clinical outcomes,TCM syndrome scores,and B-type natriuretic peptide(BNP)levels are lacking.This study fills this gap through a comprehensive analysis of randomized controlled trials(RCTs)focusing on TCM for HF treatment.It encompasses an assessment of methodological quality,a meta-analysis,and an evaluation of evidence quality based on established standards.The results offer crucial insights into the potential advantages and constraints of TCM in HF management.RCTs on TCM for HF treatment published since the establishment of the database were searched in four Chinese and English databases,including China National Knowledge Infrastructure,Wanfang,VIP Information Chinese Science and Technology Journal,and PubMed.Methodological quality was assessed for the included studies with the Cochrane risk-of-bias assessment tool,and the meta-analysis and publication bias assessment was performed with the RevMan5.3 software.Finally,the quality of evidence was rated according to the GRADE criteria.RESULTS A total of 1098 RCTs were initially retrieved.After screening,16 RCTs were finally included in our study,which were published between 2020 and 2023.These RCTs involved 1660 HF patients,including 832 in the TCM group[TCM combined with conventional Western medicine(CMW)treatment]and 828 in the CWM group(CWM treatment).The course of treatments varied from 1 wk to 3 months.TCM syndrome differentiation was analyzed in 11 of the included RCTs.In all included RCTs,outcome indicators included comprehensive clinical outcomes,TCM syndrome scores,and BNP levels.The meta-analysis results showed significant differences between the TCM and CWM groups in terms of comprehensive clinical outcomes[risk ratio=-0.54;95%confidence interval(CI)=-0.61,-0.47;P<0.00001],TCM syndrome scores[weighted mean difference(WMD)=-142.07;95%CI=-147.56,-136.57;P<0.00001],and BNP levels(WMD=-142.07;95%CI=-147.56,-136.57;P<0.00001).According to the GRADE criteria,RCTs where"TCM improves clinical comprehensive outcomes"were rated as low-quality evidence,and RCTs where"TCM reduces TCM syndrome scores"or"TCM decreases BNP levels"were rated as medium-quality evidence.CONCLUSION TCM combined with CWM treatment effectively improves comprehensive clinical outcomes and diminishes TCM syndrome scores and BNP levels in HF patients.Given the low and medium quality of the included RCTs,the application of these results should be cautious.

A Framework for Exploring the Dynamics of Autonomous Work Groups in Manufacturing Organizations

Nowadays, new paradigm of enterprise organization i s constantly changing due to the emergence of the global marketplace, the rise of information technology, and the emphasis of the social developments. This re quires a more flexible form of organization that are more adaptable to rapid cha nges in business environment such as autonomous work groups (AWGs) in order to achieve higher productivity and effectiveness. AWGs are work units responsib le for the production of goods and the provision of services. They involve team members in making decisions that are traditionally the responsibility of the sup ervisors and managers (Cohen & Bailey, 1997). Team members of AWGs are allowed t o self-regulate their behavior on jobs such as task assignments, methods for ca rrying out the work, and scheduling of activities etc. (Cohen & Ledford, 1994). For example, Motorola achieved a high organizational performance due to the succ essful implementation of AWGs in quality management (Piczak & Hauser, 1996). Xer ox also reported their operational successes based on the team-oriented work gr oups (Wageman, 1997). In recent years many organizations have replaced the traditional layers of manag ement with autonomous team-based work arrangements. Surveys indicated that the adoption of AWGs has soared in responding to the competitive business challenges . Many enterprises are making a deliberate effort to use AWGs to carry out work and operational processes as an alternative for hierarchical approaches (Lawler et al., 1995). There is a growing body of evidence that AWGs are more effective than traditionally managed groups and they contributes to organizational perform ance, such as improvement in operational performance, productivity, quality, cos t savings, employee attitude and behavior, and employee satisfaction (e.g. Pears on, 1992; Cohen & Ledford, 1994; Seers et al. 1995). Given the complexity and cognitive nature of team-based organizations, the mech anisms that the enterprises use in the development of the increasingly sophistic ated models, which can contribute to the effective functioning of AWGs, are extr emely important. The process of developing effective AWGs enables enterprises to inherent built-in intelligence of the organizations so that they will be more able to accommodate to external pressures and changes. The context of this paper is the construction of a dynamics framework and a stra tegic path for autonomous work groups in the technology-oriented manufacturing organization re-design. The framework is a conceptual one drawn from the litera ture survey. The importance of studying autonomous work groups for today’s manuf acturing organizations is claimed. Based on the General System Theory (GST), the characterization of AWGs is addressed. Three-dimensional domains such as t echnical content, service content, and relationship content are identified. A st rategic path is proposed to guide the organizations how the development of AWGs progresses at different levels of maturity that are associated with organization al effectiveness and performance. The utility of the model for AWGs is expected to provide technology-oriented organizations with a strategic path to achieve h igher organizational performance.

Socioeconomic Factors Influencing Levels of Knowledge in Soil Fertility Management in the Central Highlands of Kenya

This study aimed to first assess knowledge levels of the farmers in the use of manure, fertilizer and combinations of manure and fertilizer and secondly to identify the socioeconomic factors influencing the levels of knowledge in the use of animal manure, inorganic fertilizers and combination of animal manure and inorganic fertilizers in Meru South, Maara and Mbeere South districts of the central highlands of Kenya. Data were collected from a random sample of 300 households through face to face interviews using an interview schedule. The data was analyzed using descriptive statistics and binary logistic regression model. Results showed that 75% and 73% of the respondents had high levels of knowledge in use of manure and fertilizers, respectively, while 43% of the respondents had moderate levels of knowledge in the use of manure ＋ fertilizers. Age of the household head （HHH） training in the use of animal manure and group membership significantly influenced household levels of knowledge in use of animal manure. In regard to levels of knowledge on fertilizer use, group membership, age of the HHH and total farm size were important explanatory variables while gender of the HHH, household size, training on manure ＋ fertilizers, group membership and total farm size were important in influencing the levels of knowledge in use of manure ＋ fertilizers. The implication of these results is that training and belonging to a group enhances level of knowledge on soil fertility management and development, so workers should focus on these two aspects.

Hyperspectral remote sensing identification of marine oil spills and emulsions using feature bands and double-branch dual-attention mechanism network

The accurate identification of marine oil spills and their emulsions is of great significance for emergency response to oil spill pollution.The selection of characteristic bands with strong separability helps to realize the rapid calculation of data on aircraft or in orbit,which will improve the timeliness of oil spill emergency monitoring.At the same time,the combination of spectral and spatial features can improve the accuracy of oil spill monitoring.Two ground-based experiments were designed to collect measured airborne hyperspectral data of crude oil and its emulsions,for which the multiscale superpixel level group clustering framework(MSGCF)was used to select spectral feature bands with strong separability.In addition,the double-branch dual-attention(DBDA)model was applied to identify crude oil and its emulsions.Compared with the recognition results based on original hyperspectral images,using the feature bands determined by MSGCF improved the recognition accuracy,and greatly shortened the running time.Moreover,the characteristic bands for quantifying the volume concentration of water-in-oil emulsions were determined,and a quantitative inversion model was constructed and applied to the AVIRIS image of the deepwater horizon oil spill event in 2010.This study verified the effectiveness of feature bands in identifying oil spill pollution types and quantifying concentration,laying foundation for rapid identification and quantification of marine oil spills and their emulsions on aircraft or in orbit.

Correlation between the avian community and habitat at different water levels during spring migration in Zhalong National Nature Reserve,China

Zhalong National Nature Reserve （Zhalong） is an important stopover for migratory birds. In recent decades, Zhalong has become the focus of researchers and public discussion in relation to irrigation. We studied relationships between birds and habitats at different water levels to guide development of more effective habitat management measures. We used line transects to survey bird numbers and distribution during April-May from 2005-2009 at Zhalong, and used cluster analysis and Chi-Square tests to analyze data. We recorded 139 bird species of 39 families and 13 orders during spring migration, including Anseriformes, Charadriiformes, Ciconiiformes, Columbiformes, Coraciiformes, Cucu- liformes, Falconiformes, Galliformes, Gruiformes, Passeriformes, Pici- formes, Podicipediformes, Strigiformes. Dominant vegetation and geo- graphic region were the main influence factors of avian distribution. Different ecological groups preferred different water levels （p〈0.01） and different habitat types （p〈0.01）. Grallatores, Natatores and Passeres were the main ecological groups in different wetland habitats, and reed marsh and lake are the main habitats for management. Grallatores preferred reed marsh and lake with water levels 〉30 cm and 5-15 cm. Natatores preferred lakes with deep water （〉30 cm）. Passeres preferred open forest and reed marsh with no surface water. Different avian ecological groups occupied specific habitats depending on water level and we recorded some overlaps in bird distribution.

General Relativity as the Classical Limit of the Renormalizable Gauge Theory of Volume Preserving Diffeomorphisms

The different roles and natures of spacetime appearing in a quantum field theory and in classical physics are analyzed implying that a quantum theory of gravitation is not necessarily a quantum theory of curved spacetime. Developing an alternative approach to quantum gravity starts with the postulate that inertial energy-momentum and gravitational energy-momentum need not be the same for virtual quantum states. Separating their roles naturally leads to the quantum gauge field theory of volume-preserving diffeomorphisms of an inner four-dimensional space. The classical limit of this theory coupled to a quantized scalar field is derived for an on-shell particle where inertial energy-momentum and gravitational energy-momentum coincide. In that process the symmetry under volume-preserving diffeomorphisms disappears and a new symmetry group emerges: the group of coordinate transformations of four-dimensional spacetime and with it General Relativity coupled to a classical relativistic point particle.

Popularity Prediction of Social Media Post Using Tensor Factorization

The traditional method of doing business has been disrupted by socialmedia. In order to develop the enterprise, it is essential to forecast the level ofinteraction that a new post would receive from social media users. It is possiblefor the user’s interest in any one social media post to be impacted by external factors or to dwindle as a result of changes in his behaviour. The popularity detectionstrategies that are user-based or population-based are unable to keep up with theseshifts, which leads to inaccurate forecasts. This work makes a prediction abouthow popular the post will be and addresses any anomalies caused by factors outside of the study. A novel improved PARAFAC (A-PARAFAC) method that istensor factorization-based has been presented in order to cope with the user criteria that will be used in the future to rate any project. We consolidated the information on the historically popular content, and we accelerated the computation bychoosing the top contents that were most like each other. The tensor is factorisedwith the application of the Adam optimization. It has been modified such that thebias is now included in the gradient function of A-PARAFAC, and the value ofthe bias is updated after each iteration. The prediction accuracy is improved by32.25% with this strategy compared to other state of the art methods.

The breaking point between fast-and slow-light in a degenerate two-level atomic system

This paper investigates the breaking point between fast- and slow-light in a degenerate two-level atomic system, where fast-light can be converted to slow-light arbitrarily on a single transition line by adjusting the strength of the pumping field. An equivalent incoherent pumping rate is introduced in this simplified theoretical model which exploits the dependence of this feature. The experimental observation is presented as evidence of the breaking point where the injected power is about 0.08 mW.

利益群体视角下江西省国家区域医疗中心建设探讨

建设国家区域医疗中心是促进优质医疗资源均衡布局的重大举措。江西省国家区域医疗中心建设数量多,且病种选择准、会商调度勤、思想统一快。但从政府、输出医院、依托医院等利益群体视角看,仍存在顶层设计不清晰、参与医院动力不足等问题,需要加快健全协调机制、明晰三方权责、完善考评和专班制度、优化绿色通道,强化输出医院动力,支持依托医院错位发展,打造可持续的双方合作与项目医院自我发展模式。

高水平专业群建设产出绩效评价指标体系构建研究

高水平专业群建设绩效评价既是衡量“双高”建设成效的必然要求,也是促进高职院校内涵式发展的迫切需要,还是下一轮双高计划建设单位遴选的重要举措。依据教育部和财政部相关文件,提出了高水平专业群建设绩效评价体系框架。在对产出指标选用原则分析的基础上,选出了9个二级指标下的备选三级指标;运用DEMATEL分析法,对备选三级指标进行优化,确定了产出指标下的评价体系和权重。通过高水平专业群建设绩效评价体系的构建,引导专业群建设方向始终指向“双高计划”总体目标,有效提升专业群的人才培养质量与服务能力。

“双高计划”背景下高职院校专业群建设的政策演进与内涵特质

高水平专业群建设是高职院校治理体系和治理能力现代化的集中体现。纵观我国高职教育发展进程,专业(群)建设作为高职院校发展水平的核心要素和显著标识始终贯穿其中。从政策演进透析专业群建设的历史脉动和演进逻辑,有助于从政策制度层面理解高水平专业群建设在“双高计划”背景下所具有的功能定位和价值旨向,从专业理论层面理解高水平专业群所体现出的“群”“高”“才”诸方面的内涵特质,从而为高水平专业群建设的实现路径和行动方略等提供制度依据和理论支撑。

产教融合视阈下高职院校高水平专业群治理研究——基于56份“双高计划”学校中期绩效自评报告的文本分析

产教融合视阈下高职院校高水平专业群治理的逻辑框架必须遵循产业发展需求的逻辑、知识关联的逻辑和组织治理的逻辑。以56份“双高计划”学校中期绩效自评报告为研究对象,运用NVIVO12.0软件对专业群治理逻辑归纳而建构的要素指标进行数据挖掘和分析,结果表明专业群产教融合形态由“单一虚体”向“多元实体”蜕变有待突破,专业间知识关联由“弱关联”向“强关联”演变有待强化,组织管理形态由“科层治理”向“多元治理”转变有待革新。产教融合视域下高职院校高水平专业群治理应坚持“以产定群”,搭建区域产业集群与专业知识关联耦合的专业群;坚持“以群治院”,打造治理结构与治理效能相匹配的组织体系;坚持多元共治,搭建产教协同与利益共享的实体育人平台。

中国县级领导班子群体特征研究——基于东西部比较分析

面对东西部发展存在的巨大差距,西部地区必须全面提升发展质量,而这离不开作为地区发展“领头羊”的领导班子的引领和推动。现有文献对于领导干部群体特征以及配置结构进行了深入的归纳和探讨,但也有必要比较区域间领导干部整体水平的差异并分析其潜在原因,据此对症下药。比较东西部领导班子的群体特征,对于西部地区领导干部的培养、选拔有一定参考价值。论文运用高层梯队理论,采用分层抽样的方法,在广东省、天津市、陕西省、重庆市获得562名县级党政领导班子的履历信息,从人口统计学特征、教育背景、职业发展经历三个维度进行分析,对比研究东西部地区县级党政领导班子群体特征的共性和差异。本研究利用EXCEL对县级领导班子特征各个指标的变量进行统计分析,通过均值、标准差等数据展示变量的分布结构和特征;利用SPSS21.0对东西部县级领导班子的差异性特征进行分组,通过t检验、卡方检验等呈现数据间的差异性。研究表明,东西部党政领导班子在性别、民族、政治面貌、教育背景等方面呈现出相似的特征,但在籍贯来源、年龄、任职经历、晋升路径等方面呈现出显著差异,西部地区县级领导班子年龄分布呈现“两头多,中间少”、籍贯结构“本地多,外地少”、教育背景“偏人文,轻理工”、“任职经历单一,工作经验同质性高”、自下而上晋升比例更低等明显特征。针对分析结果,建议西部县级党政领导班子要着重加强领导班子协同效能建设、优化领导班子干部队伍结构、完善现代干部任用选拔机制,以及进一步强化领导干部的交流制度。

新发展理念下高职院校高水平专业群建设研究

专业群建设实质为打造能够精准对接区域职业岗位群的专业群。但当前高职院校在专业群建设中并未形成全新建设思路,不仅缺乏建“群”意识,还存在一定盲目性与随意性。“创新、协调、绿色、开放、共享”的新发展理念正推动着中国经济社会高质量发展。高职院校也应积极应用新发展理念引领专业群建设,瞄准适应产业、支撑发展、中国特色、世界水平等目标,以创新发展精准对接区域产业群、以协调发展强化专业群内部治理、以绿色发展打造高水平师资队伍、以开放发展强化专业群国际交流、以共享发展深化专业群校企合作,推动高职院校高质量发展。

OBE理念下围绕药品生产技术高水平专业群建设推动产教融合人才培养体系构建对策

在推动药品生产技术领域人才培养阶段,需要将OBE理念融入其中,以OBE理念建设药品生产技术高水平专业群,从而推动产教融合人才培养体系构建,从而为药品生产技术领域发展持续性输送高水平人才。所以,在论文中提出了OBE理念下围绕药品生产技术高水平专业群建设推动产教融合人才培养体系构建对策,用以抛砖引玉。

社区团购三级供应链定价与渠道决策

社区团购平台进入理性竞争的稳健发展期,如何整合线下便利店渠道优化团长服务,以应对多渠道博弈是社区团购企业关注的重要内容。针对“社区团购+社区便利店”渠道整合有效性问题,基于消费者效用理论和Stakelberg博弈理论,构建由供应商、社区团购零售商和社区便利店的三级供应链博弈模型,对比分析不同渠道策略下供应商和社区团购零售商分别为渠道结构主导者时,供应链最优定价决策和利润分配,研究供应商和零售商博弈情形下社区团购零售商渠道整合策略获得利润增值的市场条件。研究表明,除了在分散渠道策略下的线下实体渠道产品销售价格会下降,社区团购渠道产品销售价格和批发价格都会随团长运营服务水平的提升而升高;供应商和零售商的权力结构并不影响社区团购渠道整合策略的选择,仅影响整合策略后获得利润增值大小;只有在消费者对线上渠道偏好程度较低且团长运营服务水平不太高时,整合策略才对社区团购渠道有利。研究结论不仅实现社区团购三级供应链最优定价决策和利润分配,同时帮助社区团购零售商有效整合社区便利店,提供可靠的理论依据和重要的政策启示。

区域高职教育核心竞争力的布局落点与发展策略——基于广东省高职院校高水平专业群的分析

立足区域高职教育核心竞争力发展的现实需求,着眼广东省现有国家、省级高水平专业群建设的整体情况与结构,形成对广东省高职教育核心竞争力布局落点的基本描绘。对高水平专业群组群逻辑主线进行归纳提炼,提出技术演进多元化、区域优势产业特色化、院校专业发展类属化三种类型的组群走向,并进行内部细化区分。在此基础上,从专业群聚集化发展、校企协同治理机制建设、特色优势专业群打造等维度提出提升区域高职教育核心竞争力的路径。

基于大数据应用的高职院校高水平专业群建设管理研究

高水平专业群建设是一项复杂的系统性工程,是专业群内部与外部结构要素的深度融合。涉及专业领域众多、数据和资源繁杂,必须采用数字化管理,运用大数据思维构建专业群建设管理体系,以教师发展、学生成长为目标开展专业群的诊改,动态调整专业群组建和优化专业群资源配置,提升专业群建设管理水平和建设质量。

课程教法改革典型案例探索——以机械零件与典型机构数字化设计为例

双高建设是我国职业教育改革发展中实施的重大战略措施,在这个大背景下,国家对高职教育提出了更高的要求。专业群建设需要引领职业教育服务国家战略、融入区域发展、促进产业升级,聚焦高端产业和产业高端,构建高水平人才体系,为中国产业走向全球产业中高端提供高素质技术技能型人才支撑。因此,传统的教学方法已不能满足这个需求,教法改革刻不容缓。在高水平专业群建设背景下探索机械零件与典型机构数字化设计课程教法改革,形成典型案例并应用推广。