Effectiveness of structured teaching program on knowledge and attitude toward foot care

Objective:The study was aimed to assess the knowledge and attitude toward foot care and evaluate the effectiveness of structured teaching program(STP)on the knowledge and attitude of patients with diabetes mellitus regarding foot care.Materials and Methods:A preexperimental research design was used in this study,which was conducted in medical-surgical wards of a secondary hospital in Northeast India,Nagaland.A total of 30 subjects were recruited by consecutive sampling technique.A closed-ended structured questionnaire and 5-point Likert scale was used to assess knowledge and attitude toward foot care.A STP was administered after which posttest was done after 24 h.Results:The majority(86.6%)of the participants in the pretest had inadequate knowledge and 80%had negative attitudes toward foot care.After STP,70%had moderately adequate knowledge and 53.3%had a positive attitude regarding foot care.The structured teaching program was effective in improving the knowledge and attitude at P<0.01 which is highly significant and there was a significant association between the pretest level knowledge and duration of diabetes at P<0.01.Conclusion:STP was effective in enhancing the level of knowledge and attitude toward foot care among diabetic inpatients.This type of interaction can be organized at regular intervals to reinforce knowledge and attitude toward foot care among inpatients.

IndRT-GCNets: Knowledge Reasoning with Independent Recurrent Temporal Graph Convolutional Representations

Due to the structural dependencies among concurrent events in the knowledge graph and the substantial amount of sequential correlation information carried by temporally adjacent events,we propose an Independent Recurrent Temporal Graph Convolution Networks(IndRT-GCNets)framework to efficiently and accurately capture event attribute information.The framework models the knowledge graph sequences to learn the evolutionary represen-tations of entities and relations within each period.Firstly,by utilizing the temporal graph convolution module in the evolutionary representation unit,the framework captures the structural dependency relationships within the knowledge graph in each period.Meanwhile,to achieve better event representation and establish effective correlations,an independent recurrent neural network is employed to implement auto-regressive modeling.Furthermore,static attributes of entities in the entity-relation events are constrained andmerged using a static graph constraint to obtain optimal entity representations.Finally,the evolution of entity and relation representations is utilized to predict events in the next subsequent step.On multiple real-world datasets such as Freebase13(FB13),Freebase 15k(FB15K),WordNet11(WN11),WordNet18(WN18),FB15K-237,WN18RR,YAGO3-10,and Nell-995,the results of multiple evaluation indicators show that our proposed IndRT-GCNets framework outperforms most existing models on knowledge reasoning tasks,which validates the effectiveness and robustness.

A Practical Study of Knowledge Mapping Empowering the Construction of Engineering Costing Software Application Courses in Undergraduate Colleges and Universities

Relying on the talent cultivation program of Chongqing Institute of Engineering,this paper combines the characteristics of the Engineering Costing Software Application course with its current status quo,analyzes the existing problems and teaching pain points,and introduces knowledge mapping.The course construction is carried out in terms of the combing of knowledge points,the optimization of the course structure,the innovation of the teaching method,and the evaluation and feedback of the teaching in order to improve the systematicity and structural nature of the teaching content,enhance students’learning experience,and enhance their learning effect.It is conducive to the formation of students’knowledge systems and provides a basis for discussion and reference for improving the quality of teaching and cultivating application-oriented talents who meet the market demand.

Mapping theme trends and knowledge structures for human neural stem cells:a quantitative and co-word biclustering analysis for the 2013-2018 period

Neural stem cells,which are capable of multi-potential differentiation and self-renewal,have recently been shown to have clinical potential for repairing central nervous system tissue damage.However,the theme trends and knowledge structures for human neural stem cells have not yet been studied bibliometrically.In this study,we retrieved 2742 articles from the PubMed database from 2013 to 2018 using "Neural Stem Cells" as the retrieval word.Co-word analysis was conducted to statistically quantify the characteristics and popular themes of human neural stem cell-related studies.Bibliographic data matrices were generated with the Bibliographic Item Co-Occurrence Matrix Builder.We identified 78 high-frequency Medical Subject Heading(MeSH)terms.A visual matrix was built with the repeated bisection method in gCLUTO software.A social network analysis network was generated with Ucinet 6.0 software and GraphPad Prism 5 software.The analyses demonstrated that in the 6-year period,hot topics were clustered into five categories.As suggested by the constructed strategic diagram,studies related to cytology and physiology were well-developed,whereas those related to neural stem cell applications,tissue engineering,metabolism and cell signaling,and neural stem cell pathology and virology remained immature.Neural stem cell therapy for stroke and Parkinson’s disease,the genetics of microRNAs and brain neoplasms,as well as neuroprotective agents,Zika virus,Notch receptor,neural crest and embryonic stem cells were identified as emerging hot spots.These undeveloped themes and popular topics are potential points of focus for new studies on human neural stem cells.

Structure of Chinese City Network as Driven by Technological Knowledge Flows

Based on patent cooperation data,this study used a range of city network analysis approaches in order to explore the structure of the Chinese city network which is driven by technological knowledge flows.The results revealed the spatial structure,composition structure,hierarchical structure,group structure,and control structure of Chinese city network,as well as its dynamic factors.The major findings are:1) the spatial pattern presents a diamond structure,in which Wuhan is the central city;2) although the invention patent knowledge network is the main part of the broader inter-city innovative cooperation network,it is weaker than the utility model patent;3) as the senior level cities,Beijing,Shanghai and the cities in the Zhujiang(Pearl) River Delta Region show a strong capability of both spreading and controlling technological knowledge;4) whilst a national technology alliance has preliminarily formed,regional alliances have not been adequately established;5) even though the cooperation level amongst weak connection cities is not high,such cities still play an important role in the network as a result of their location within ′structural holes′ in the network;and 6) the major driving forces facilitating inter-city technological cooperation are geographical proximity,hierarchical proximity and technological proximity.

Safety evaluation system for hydraulic metal structures based on knowledge engineering

A comprehensive safety evaluation system taking the most influential factors into account has been developed to evaluate the reliability of hydraulic metal structures. Applying the techniques of AI and DB, the idea of a one-machine and three-base system is proposed. The framework of the three-base system has been designed and the structural framework constructed in turn. A practical example is given to illustrate the process of using this system and it can be used for comparison and analysis purposes. The key technology of the system is its ability to reorganize and improve the expert system＇s knowledge base by establishing the expert system. This system utilizes the computer technology inference process, making safety evaluation conclusions more reasonable and applicable to the actual situation. The system is not only advanced, but also feasible, reliable, artificially intelligent, and has the capacity to constantly grow.

Evolution of the Socio-cognitive Structure of Knowledge Management(1986–2015): An Author Co-citation Analysis

Purpose: The evolution of the socio-cognitive structure of the field of knowledge management(KM) during the period 1986–2015 is described. Design/methodology/approach: Records retrieved from Web of Science were submitted to author co-citation analysis(ACA) following a longitudinal perspective as of the following time slices: 1986–1996, 1997–2006, and 2007–2015. The top 10% of most cited first authors by sub-periods were mapped in bibliometric networks in order to interpret the communities formed and their relationships.Findings: KM is a homogeneous field as indicated by networks results. Nine classical authors are identified since they are highly co-cited in each sub-period, highlighting Ikujiro Nonaka as the most influential authors in the field. The most significant communities in KM are devoted to strategic management, KM foundations, organisational learning and behaviour, and organisational theories. Major trends in the evolution of the intellectual structure of KM evidence a technological influence in 1986–1996, a strategic influence in 1997–2006, and finally a sociological influence in 2007–2015.Research limitations: Describing a field from a single database can offer biases in terms of output coverage. Likewise, the conference proceedings and books were not used and the analysis was only based on first authors. However, the results obtained can be very useful to understand the evolution of KM research.Practical implications: These results might be useful for managers and academicians to understand the evolution of KM field and to(re)define research activities and organisational projects.Originality/value: The novelty of this paper lies in considering ACA as a bibliometric technique to study KM research. In addition, our investigation has a wider time coverage than earlier articles.

Structure, Evolution and Hot Spots of Cooperation Innovation Knowledge Network

Based on the statistics analysis of cooperation innovation articles, the paper analyses the distributing characteristics of cooperation innovation research papers. The distribution, structure and evolution of cooperation innovation research are studied through the social network and co-word method, combined with the information visualization technology. This study is based on the papers in the SSCI database during 2000-2014. The analysis and statistics of papers reveal distribution characteristics of the subject, time, institutions, countries and areas. The statistics shows that the research perspective of cooperation innovation from business and economics. The time distribution presents that research of cooperation innovation attracts enormous attention and the research achievement is increasing. From the distribution of organizations, countries and areas, North America and Europe countries maintain the leading position in this research field. But institutions and universities of China and other Asian countries or areas are witnessed their outstanding achievements in cooperation innovation research. Combining the co-word network analysis method, the paper studies the structure and content of cooperation innovation knowledge network in five stages and makes the net spectrum, visually showing the hot spots at various periods. The top highly cited papers in all five stages are reviewed simultaneously;their research hot spots and evolution process are concluded. The study shows 11 subjects including strategic alliances, social networks, R&D cooperation, R&D, technology transfer, alliances, knowledge management, social capital, entrepreneurship, trust, biotechnology are always the central issues in last 15 years. The focus of research is from the relationship between alliance and technology innovation to networking and knowledge innovation and then to open innovation.

A Systemic Functional Linguistics Approach to Knowledge Structure in Educational Discourse

This paper makes a literature review of Bernstein＇s knowledge structure theory and its influence on systemic functional linguistics. Then it explores systemic functional linguists＇ research on knowledge building and discusses Martin＇s theory of field as a powerful tool to analyze the knowledge structure in educational discourse.

Effectiveness of structured teaching programme on knowledge regarding therapeutic nurse- patient communication among the staff nurses

Introduction:The therapeutic nurse patient relationship is viewed as central or foundational to the practice of nursing.Such relationship not only improve patients’physical and emotional state but also facilitate their adjustments to their illness,ease pain and can ultimately lead to a good health experience.Methodology:The pre experimental one group pre test post test study was undertaken to assess the effectiveness of structured teaching programme on knowledge regarding therapeutic nurse-patient communication among the staff nurses working in SGT Hospital,Haryana.Total 30 study participants were selected by convenient sampling technique and Data were collected by using a structured knowledge questionnaire.Result:The findings of the study revealed that half of the participants 50%had average and poor knowledge regarding therapeutic nurse patient communication in the pre test.Similarly,the post test scores depicted that majority(63%)had average knowledge and 37%had good knowledge regarding therapeutic nurse patient communication.Most of the demographic variable was not significantly associated with level of pre knowledge of staff nurses regarding therapeutic nurse patient communication.Only staff nurses years of experience P=0.021 were found to statistically significant at 0.05 level of significance.There was significant difference between the knowledge of staff nurses before and after the implementation of structured teaching programme(t=11.844,P=0.0001).Conclusion:It was concluded that structured teaching programme was effective strategy which can help to increase their knowledge regarding therapeutic nurse patient communication.

Study on the Interior Market Network Structure and Its Efficiency in a Knowledge Based Company

A knowledge based company is the microcosmic foundation of the knowledge economy, the design of its organization structure should amplify the company competence to be agile to the knowledge elements. This paper expounds an interior market network structure which is fit for the company intellectual capital operation, and analyses this organization pattern about the reasons of existence, the effectiveness of growing up in scale, the economies of knowledge distribution and the efficiency of operation, and it will provide some beneficial theoretical guidance about how can a company improve its competition competence in the knowledge environment through organization innovation.

学习任务群视域下知识观转型与教学变革

学科知识、主体经验和学习活动是语文教学不可缺少的要素,不能因强调其一而取代另两者。学习任务群视域下的知识观,是从静态知识到动态运用、从知识点到概括性知识、从“知识—人”到“知识—世界—人”。学习任务群以实践活动内联知识类型、以学习单元建立知识结构、以真实情境促进知识—人—世界三者交融,探索出一条知识生成素养的有效路径。研究认为,依据学习任务群的特征,以初中语文为例,教学实践中宜采用概括性知识统领的单元教学,可分为提炼单元的概括性知识、提出引导性问题融入学科知识、设计知识理解与运用的学习过程三个步骤。

关于风景园林专业学位与知识体系的思考

【目的】中国风景园林教育事业进入新的发展阶段,在专业学位背景下,风景园林知识体系亟待梳理与反思。【方法/过程】基于专业学位教育特点,剖析国家政策、社会需求,重新系统认知风景园林专业学位:从培养目标、知识类型、知识层级与知识结构4个方面探讨风景园林专业学位与知识体系的内涵及发展方向。现代风景园林专业人才培养的核心在于对实践智慧与能力的培养,专业知识类型势必从过去以经验知识为主体转变为以科学知识与规律为主体。科学、艺术与技术3种类型知识的融合是专业发展与人才培养的基础。学士、硕士与博士三级人才培养模式体现出风景园林专业知识的层级属性,据此处理好专业知识体系中内涵与外延的结构关系是推动专业发展的根本问题。【结果/结论】面对风景园林专业乃至思维范式的革新,应按照专业知识生产与组构的特定规律,探索风景园林专业未来可持续发展的有效路径。

知识网络视角下科学、技术、产业间创新驱动关系识别方法研究

开展科学、技术、产业之间创新驱动关系研究,对于实现科学发现、技术创新与产业的深度有效融合与发展具有重要意义。本文从知识网络视角展开科学、技术、产业间创新驱动关系识别方法研究。首先,通过构建时效知识网络,利用社区网络结构熵来表征知识网络结构特征;其次,利用网络结构特征信息间的传递熵探究创新过程中科学、技术、产业三个系统相互驱动的关系;再其次,采用互信息探测主要驱动关系下知识传递路径的变化特点;最后,以再生医学(干细胞)领域作为实证对象,实证研究发现不同时间阶段,科学、技术、产业之间的相互驱动关系会发生转变,三者知识传递路径上知识内容前后继承关系也不同,科学驱动技术过程中的知识传递路径继承性特征持续增强,而技术驱动科学过程中的知识传递路径继承性呈现不稳定、非连续性特征。此外,通过多种方式论证了本文方法的科学有效性,可以用于其他创新领域科学、技术、产业间创新驱动关系的识别。

知识复杂性的测度方法综述与比较

[研究目的]复杂知识是突破关键核心技术的基础支撑,也是企业或区域建立竞争优势的关键要素。该文旨在全面把握知识复杂性测度方法的研究现状与前沿进展,为知识复杂性的深入研究提供测度理论基础。[研究方法]通过梳理国内外知识复杂性研究的相关文献,详细介绍三种主要的知识复杂性测度方法的核心思想、理论基础和计算过程,并进一步对比分析不同方法的适用层次和优缺点,最后提出未来研究方向。[研究结论]反射法主要基于知识的空间分布异质性间接衡量知识复杂性,虽然原理简单且操作相对容易,但无法揭示知识复杂性的本质特征;元素依赖性指数利用知识组合频次衡量知识元素之间的相互依赖程度,进而反映知识复杂性,忽视了其他影响知识组合的因素;结构多样性指数通过知识组合网络拓扑结构的多样性反映知识复杂性,综合考虑多个网络结构指标,并经过大量数值模拟检验,但存在估计结果不稳定、仅适用于二值网络等问题。

知识状态集合准确界定的意义

教育认知诊断基于被试的作答反应估计其知识状态从而进行分类.尽管给定属性及其层级关系,其知识状态集合是唯一的,但对此并未形成共识.如有的软件包认为同一属性层级关系可对应2种不同的知识状态集合;有的研究仅仅给出属性及其层级关系的知识状态集合的真子集.针对这些情况,该文从理论上和应用上进行了分析,并给出修正的建议.

面向边缘计算的轻量级母猪分娩识别模型

为实时监测母猪分娩过程并准确分析记录其完整产程的产仔数、产仔间隔和产程等信息,该研究运用知识蒸馏和剪枝,结合了ResNet50高准确率和MobileNetV3高检测效率的优势设计了一种轻量级网络。采用数据增强提高教师模型ResNet50对分娩特征的提取能力,通过掩模生成蒸馏(maskedgenerativedistillation,MGD)提高学生模型MobileNetV3-S对分娩关键区域的表达能力,并通过依赖关系图(dependency graph)显式建模学生网络层间的依赖关系,结合分组耦合参数对学生模型进行剪枝。剪枝得到的MobileNetV3-S(MGD)_Prune参数量为0.74 M,在DELL OptiPlex微型机上检测速度为83.10帧/s,单栏视角测试准确度为91.48%,相比于ResNet50的检测速度提升了67.13帧/s,测试准确度下降0.98个百分点。试验结果表明,单栏视角对监测母猪分娩更为有效,模型对于产仔平均间隔的检测误差为0.31 s,仔猪出生事件的平均持续时长检测误差为0.02 s,能够高效监测母猪分娩全过程。

董事网络位置对企业风险承担的影响研究——来自中国上市公司的经验证据

风险承担是企业实现持续发展的重要因素。基于社会网络视角,本文运用中国A股上市公司2011~2022年的样本数据,实证研究了董事网络位置对企业风险承担的影响及其作用机理。结果表明:董事网络中心度显著提升了企业风险承担水平,结构洞对企业风险承担起到显著的抑制作用。知识溢出在董事网络中心度以及结构洞对企业风险承担的影响中均发挥遮掩效应;进一步研究发现,经济政策不确定性正向调节董事网络位置对企业风险承担水平的影响。基于研究结论,企业应该合理构建董事网络关系;优化董事网络结构,适度获取外部知识,提升决策质量。

数字化转型提升企业创新效率的网络机制——合作和知识双重创新网络结构洞的中介作用

企业数字化转型不仅拓展和优化了创新网络,也使创新网络在创新驱动发展中的作用日益重要。基于网络结构洞理论,从创新合作网络和创新知识网络(双重创新网络)角度分析数字化转型通过增强企业在创新网络中的“桥梁”作用来提升企业创新效率的机制,并采用沪深A股制造业上市公司2013—2021年的数据进行实证检验,结果发现:制造业企业数字化转型能够显著提升其创新效率,该作用在非国有企业中更为显著;双重创新网络结构洞是数字化转型影响企业创新效率的中介变量,即存在“数字化转型水平提高→双重创新网络结构洞增加→创新效率提升”的影响路径;企业组织韧性提高能够强化数字化转型对网络结构洞的正向影响,但对网络结构洞影响创新效率没有显著的调节作用。因此,应积极推进企业数字化转型,通过拓展和优化创新网络来促进企业创新效率提升,并不断提高企业的组织韧性以有效化解转型风险。

“抽取共性–讲透典型–衍生个性”,构建晶体结构知识点图谱

在结构化学教学中,晶体结构的多样性、复杂性和抽象性使教学难度增加,本文介绍了笔者在教学实践中根据晶体结构的对称性,以具体–抽象–具体主线,以“抽取共性–讲透典型–衍生个性”为核心,构建晶体结构知识点图谱的拓展教学方法。具体做法是以等径圆球密堆积及其空隙类型/分布作为共性的出发点,通过填隙模型得到典型晶体的结构,通过取代/添加/去除/衍生等方式建立具有多样性的具体物质的晶体结构,形成直观和有脉络关系的知识图谱。可以加深学生理解晶体结构教学中的共性与个性,达到知识理解与迁移运用的目的。