Psychiatrists’occupational stigma conceptualization,measurement,and intervention:A literature review

Psychiatrists require frequent contact with and treatment of patients with mental illnesses.Due to the influence of associative stigma,psychiatrists may also be targets of stigma.Occupational stigma warrants special consideration because it significantly affects psychiatrists'career advancement,well-being,and their patients’health.Given that there is no complete summary of this issue,this study reviewed the existing literature on psychiatrists'occupational stigma to clearly synthesize its concepts,measurement tools,and intervention strategies.Herein,we emphasize that psychiatrists’occupational stigma is a multifaceted concept that simultaneously encompasses physically,socially,and morally tainted aspects.Currently,standardized methods to specifically measure psychiatrists’occupational stigma are lacking.Interventions for psychiatrists’occupational stigma may consider the use of protest,contact,education,comprehensive and systematic methods,as well as the use of psychotherapeutic approaches.This review provides a theoretical basis for the development of relevant measurement tools and intervention practices.Overall,this review seeks to raise public awareness of psychiatrists'occupational stigma,thereby promoting psychiatric professionalism and reducing its stigma.

Resilience, the 6th Vital Sign: Conceptualizing, Contextualizing, and Operationalizing All Six Vital Signs

There are five vital signs that healthcare providers assess: temperature, pulse, respiration, blood pressure, and pain. Normal levels for the five vital signs are published by the American Heart Association, and other specialty organizations, however, the sixth vital sign (resilience) which adopts the measure of immune resilience is suggested in this paper. Resilience is the ability of the immune system to respond to attacks and defend effectively against infections and inflammatory stressors, and psychological resilience is the capacity to resist, adapt, recover, thrive, and grow from a challenge or a stressor. Individuals with better optimal immune resilience had better health outcomes than those with minimal immune resilience. The purpose of this paper is to conceptualize, contextualize, and operationalize all six vital signs. We suggest measuring resilience subjectively and objectively. Subjectively, use a 5-item guided interview revised from the Connor-Davidson Resilience Scale (CDRC), a scale of 10 items. The revised CDRC scale is a 5-item scale. The scale is rated on a 5-point Likert scale from 0 (not true) to 4 (true all the time). The total score ranges from 0 to 20, with higher total scores indicating greater resilience. The scale demonstrated good construct validity and internal consistency (α = 0.85) during the development of the scale. The CD-RISC had a good Cronbach’s alpha level of 0.85. The Revised CD-RISC can be completed in 2 - 4 minutes. To measure resilience objectively, we suggest using Immune Resilience (IR) levels, the level of resilience to preserve and/or rapidly restore immune resilience functions that promote disease resistance and control inflammation and other inflammatory stress. IR levels are gauged with two peripheral blood metrics that quantify the balance between CD8 and CD4 T-cell levels and gene expression signatures tracking longevity-associated immunocompetence and mortality- or entropy-associated inflammation. IR deregulation is potentially reversible by decreasing inflammatory stress. IR metrics and mechanisms have utility as vital signs and biomarkers for measuring immune health and improving health outcomes.

Combining Deep Learning with Knowledge Graph for Design Knowledge Acquisition in Conceptual Product Design

The acquisition of valuable design knowledge from massive fragmentary data is challenging for designers in conceptual product design.This study proposes a novel method for acquiring design knowledge by combining deep learning with knowledge graph.Specifically,the design knowledge acquisition method utilises the knowledge extraction model to extract design-related entities and relations from fragmentary data,and further constructs the knowledge graph to support design knowledge acquisition for conceptual product design.Moreover,the knowledge extraction model introduces ALBERT to solve memory limitation and communication overhead in the entity extraction module,and uses multi-granularity information to overcome segmentation errors and polysemy ambiguity in the relation extraction module.Experimental comparison verified the effectiveness and accuracy of the proposed knowledge extraction model.The case study demonstrated the feasibility of the knowledge graph construction with real fragmentary porcelain data and showed the capability to provide designers with interconnected and visualised design knowledge.

A Study on Internet Buzzwords in the Last Four Years Based on Conceptual Integration Theory

Internet buzzwords,as distinct forms of language,consist of short sentences yet carry rich meanings and spread rapidly.To better study this intriguing and unique linguistic phenomenon,this paper employed conceptual integration theory for its powerful explanatory capabilities to analyze the origins,composition,and emergence of meanings of internet buzzwords over the past four years.These 40 internet buzzwords can be categorized into five types:semantic derivation,generalization,abbreviation,metonymy,and compounding.Furthermore,this paper conducted cognitive analysis from different conceptual integration network perspectives,elucidating specific cognitive operations involved in the construction of meanings and revealing the emergence process of layered meanings in recent internet buzzwords over the past four years.

Conceptual Metaphor Analysis in Advertising Slogans about Coffee Brands

This paper delves into the strategic use of conceptual metaphors in advertising slogans for coffee brands,exploring how these linguistic devices influence consumer perception and brand appeal.By employing cognitive linguistic theories,this study categorizes eight global coffee brand slogans into five distinct metaphorical patterns,revealing the underlying conceptual mappings that enhance brand messaging.The analysis underscores the importance of metaphorical language in simplifying complex ideas,evoking emotional responses,and establishing a connection between the product and the consumer’s everyday experiences.This paper concludes that the judicious application of conceptual metaphors in advertising is a powerful tool for creating memorable and impactful slogans that resonate with the target audience.

Contribution of the MERISE-Type Conceptual Data Model to the Construction of Monitoring and Evaluation Indicators of the Effectiveness of Training in Relation to the Needs of the Labor Market in the Republic of Congo

This study proposes the use of the MERISE conceptual data model to create indicators for monitoring and evaluating the effectiveness of vocational training in the Republic of Congo. The importance of MERISE for structuring and analyzing data is underlined, as it enables the measurement of the adequacy between training and the needs of the labor market. The innovation of the study lies in the adaptation of the MERISE model to the local context, the development of innovative indicators, and the integration of a participatory approach including all relevant stakeholders. Contextual adaptation and local innovation: The study suggests adapting MERISE to the specific context of the Republic of Congo, considering the local particularities of the labor market. Development of innovative indicators and new measurement tools: It proposes creating indicators to assess skills matching and employer satisfaction, which are crucial for evaluating the effectiveness of vocational training. Participatory approach and inclusion of stakeholders: The study emphasizes actively involving training centers, employers, and recruitment agencies in the evaluation process. This participatory approach ensures that the perspectives of all stakeholders are considered, leading to more relevant and practical outcomes. Using the MERISE model allows for: • Rigorous data structuring, organization, and standardization: Clearly defining entities and relationships facilitates data organization and standardization, crucial for effective data analysis. • Facilitation of monitoring, analysis, and relevant indicators: Developing both quantitative and qualitative indicators helps measure the effectiveness of training in relation to the labor market, allowing for a comprehensive evaluation. • Improved communication and common language: By providing a common language for different stakeholders, MERISE enhances communication and collaboration, ensuring that all parties have a shared understanding. The study’s approach and contribution to existing research lie in: • Structured theoretical and practical framework and holistic approach: The study offers a structured framework for data collection and analysis, covering both quantitative and qualitative aspects, thus providing a comprehensive view of the training system. • Reproducible methodology and international comparison: The proposed methodology can be replicated in other contexts, facilitating international comparison and the adoption of best practices. • Extension of knowledge and new perspective: By integrating a participatory approach and developing indicators adapted to local needs, the study extends existing research and offers new perspectives on vocational training evaluation.

NeuroBiometric:An Eye Blink Based Biometric Authentication System Using an Event-Based Neuromorphic Vision Sensor

The rise of the Internet and identity authentication systems has brought convenience to people's lives but has also introduced the potential risk of privacy leaks.Existing biometric authentication systems based on explicit and static features bear the risk of being attacked by mimicked data.This work proposes a highly efficient biometric authentication system based on transient eye blink signals that are precisely captured by a neuromorphic vision sensor with microsecond-level temporal resolution.The neuromorphic vision sensor only transmits the local pixel-level changes induced by the eye blinks when they occur,which leads to advantageous characteristics such as an ultra-low latency response.We first propose a set of effective biometric features describing the motion,speed,energy and frequency signal of eye blinks based on the microsecond temporal resolution of event densities.We then train the ensemble model and non-ensemble model with our Neuro Biometric dataset for biometrics authentication.The experiments show that our system is able to identify and verify the subjects with the ensemble model at an accuracy of 0.948 and with the non-ensemble model at an accuracy of 0.925.The low false positive rates(about 0.002)and the highly dynamic features are not only hard to reproduce but also avoid recording visible characteristics of a user's appearance.The proposed system sheds light on a new path towards safer authentication using neuromorphic vision sensors.

Using Event-Based Method to Estimate Cybersecurity Equilibrium

Estimating the global state of a networked system is an important problem in many application domains.The classical approach to tackling this problem is the periodic(observation)method,which is inefficient because it often observes states at a very high frequency.This inefficiency has motivated the idea of event-based method,which leverages the evolution dynamics in question and makes observations only when some rules are triggered(i.e.,only when certain conditions hold).This paper initiates the investigation of using the event-based method to estimate the equilibrium in the new application domain of cybersecurity,where equilibrium is an important metric that has no closed-form solutions.More specifically,the paper presents an event-based method for estimating cybersecurity equilibrium in the preventive and reactive cyber defense dynamics,which has been proven globally convergent.The presented study proves that the estimated equilibrium from our trigger rule i)indeed converges to the equilibrium of the dynamics and ii)is Zeno-free,which assures the usefulness of the event-based method.Numerical examples show that the event-based method can reduce 98%of the observation cost incurred by the periodic method.In order to use the event-based method in practice,this paper investigates how to bridge the gap between i)the continuous state in the dynamics model,which is dubbed probability-state because it measures the probability that a node is in the secure or compromised state,and ii)the discrete state that is often encountered in practice,dubbed sample-state because it is sampled from some nodes.This bridge may be of independent value because probability-state models have been widely used to approximate exponentially-many discrete state systems.

基于Conceptual Play Spaces理论的初中语文教育游戏设计

在真实的情境中教学可以促进学生的理解,对于初中生来说,他们需要一些具体形象的支撑,3D体验游戏可以将抽象的事物具体化,让学生感受到真实的世界。本文以Conceptual Play Spaces理论为基础,根据初中生的学习特征,设计教育游戏桃花源记,激发学习者的学习兴趣,使学生沉浸在教育游戏情境中,提高学习者核心素养。

A Conceptual Model of Our Universe Derived from the Fine Structure Constant (α)

The Fine Structure Constant (α) is a dimensionless value that guides much of quantum physics but with no scientific insight into why this specific number. The number defines the coupling constant for the strength of the electromagnetic force and is precisely tuned to make our universe functional. This study introduces a novel approach to understanding a conceptual model for how this critical number is part of a larger design rather than a random accident of nature. The Fine Structure Constant (FSC) model employs a Python program to calculate n-dimensional property sets for prime number universes where α equals the whole number values 137 and 139, representing twin prime universes without a fractional constant. Each property is defined by theoretical prime number sets that represent focal points of matter and wave energy in their respective universes. This work aims to determine if these prime number sets can reproduce the observed α value, giving it a definable structure. The result of the FSC model produces a α value equal to 137.036, an almost exact match. Furthermore, the model indicates that other twin prime pairs also have a role in our functional universe, providing a hierarchy for atomic orbital energy levels and alignment with the principal and azimuthal quantum numbers. In addition, it construes stable matter as property sets with the highest ratio of twin prime elements. These results provide a new perspective on a mathematical structure that shapes our universe and, if valid, has the structural complexity to guide future research.

A Conceptualist Survey of Physical Theories

The main thesis intended in this paper consists in that scientific knowledge of the physical world entails a conceptualization of it in a certain mode which is relative to,and dependent on,the theory assumed or constructed.Physical theories embody conceptual systems that at once make possible and limit our conceptualization of how the world is and our cognitive access to what happens in it.From a conceptual holism(Brown,2007),we try to maintain that since we think of the world and understand what occurs in it by systems of concepts,they acquire major relevance to a philosophical stance about scientific knowledge.In a holistic sense,delimited,at least,by the system of concepts of a given theory,concepts have both a theoretical laden to scientific experience,according to the thesis of Hanson(1958),and an ontological laden to the world,which consists in that the statements that one can assert about the physical world,the entities,and systems that one can describe as well as the claims that one holds about the processes undergone by the physical systems are dependent on and relative to such conceptual system of such theory.Thus,the framework displayed here contrasts with the epistemological realist thesis in the sense that we cannot claim how the world is really but rather how we conceptualize it relative to our theory.In addition,we expose an epistemic concept of valid statement,relative to a theory,which becomes consistent and even complementary to the framework provided.

Conceptual Blending and Meme Humor on the Internet:The Example of COVID-19 Publicity Posters in Chinese Microblogging

Internet memes,as multimodal cultural products disseminated through the Internet,usually take the form of short videos or images that express humor or satire.The creation and dissemination of humor in memes are both creative and complex,and the successful perception of meme humor reflects humans’universal thinking capacity.Based on the theoretical framework of conceptual blending,this paper selects a set of COVID-19 publicity posters from the official Weibo account of China Guangzhou Fabu(Guangzhou Internet Information Office),analyses the multi-level structure of Internet memes,and explores the dynamic cognitive process in the interpretation of humorous memes to reveal people’s ability to make simultaneous analogies and integration between elements in different mental spaces.

基于系统结构的水利高质量发展内涵与结构解析

准确把握水利高质量发展内涵,是实施新时代水利发展战略的重要前提。通过系统梳理高质量发展和水利发展的研究进展,基于系统观,分析了水利高质量发展的基本概念体系和核心要义;基于系统结构及系统优化视角,构建了由水利高质量发展目标、发展途径、发展条件三要素组成的水利高质量发展系统的关系结构。结果表明:水利高质量发展既是水利系统优化的发展理念,也是实现系统治水的发展措施;将水利高质量发展目标解析为水旱灾害防御安全、水资源供给安全、水生态保护安全和水环境保护安全保障以及高质量水利共享;五大新发展理念内化于水利高质量发展系统的关系结构之中,其中水资源禀赋和绿色发展是前提基础和约束条件,开放是其外在环境条件和内在体现,水利科技创新、水资源优化配置、水资源集约节约利用、水利系统现代化管理、水利基础设施建设和水安全系统功能协调是发展的重要优化途径,高质量水安全保障与满足人民需求的高质量水利共享是发展目标的核心内容。基于系统结构及系统优化问题视角深入剖析水利高质量发展的系统结构及其内在关系,可进一步深化对水利高质量发展的内涵认识,为区域水利高质量发展综合定量评价奠定基础。

Corpus-Driven Analysis of Conceptual Metaphor in Artificial Intelligence Language:A Sample of ChatGPT-Written Speeches

Based on Conceptual Metaphor Theory(CMT),this paper creates a tiny corpus of ChatGPT-written speeches.Through employing a corpus-driven approach,this study analyzes the identification and utilization of conceptual metaphors in artificial intelligence(AI)languages.The AI demonstrated its capacity to utilize metaphors in the metaphoric corpora through the display of diversity,non-arbitrariness,repetition,and intersectionality in the selection of source domains.It often uses vocabulary combinations with clear similarities to establish metaphorical meaning.In the literal sense,the outcomes of metaphor identification by artificial intelligence differ significantly from those of humans.Therefore,there is a need to develop advanced automatic models for identifying metaphors in order to enhance the precision of metaphor identification consistently.

A Study of the English Translation of Positive Emotions from the Perspective of Conceptual Metaphor

experience shared by human beings,but it is often expressed in the form of conceptual metaphor which is pervasive in the concrete language.Drawing upon the theory of conceptual metaphor and emotion metaphors,this paper aims to study the translation of positive emotions in David Hawkes’version of The Story of the Stone and the related daily expressions as the corpus.According to the theories,this paper categorizes the positive emotions metaphors into body metaphors,sensory metaphors,entity metaphors,and orientational metaphors to discuss the process of English translation and the metaphorical mechanism,analyzes the similarities and differences between Chinese and English expressions of positive emotions and their cultural,physiological,and psychological motives,and lastly attempts to summarize the translation strategies of emotional expressions.The analysis of metaphorical mechanisms reveals that the common physiological and psychological experiences of human beings and cultural exchanges give rise to similarities,while the unique cultural environments,antecedents,and historical development of each nation give rise to their distinctiveness.This paper concludes that translators need to make full use of their subjectivity,understand the surface and underlying meaning of the text,and establish a high level of mental compatibility between themselves,the readers,and the author.

信息偏食:概念内涵、主要表征及图书馆治理路径

文章在梳理现有零散文献的基础上,从概念性定义视角出发,系统探讨用户视角和技术视角下信息偏食的概念内涵、主要特征及其相关概念关系,据此探究信息偏食在图书馆这个具象化信息实践场域的表现。研究发现,信息偏食存在主动型偏食和被动型偏食,其在图书馆信息实践场域中可表征为无声的用户偏好,反射出信息选择的单一化;被动的技术接受,映射出服务内容的茧房化;隐匿的资源建设,折射出资源供给的单体化三个方面。最后,提出图书馆角度的治理路径:拓围资源建设,形塑资源内容供给多体性;优化技术平台,促进信息服务内容多样化;提升用户素养,培育用户信息偶遇敏感性。

中国式体育现代化的理念源流、关键势能和适配路径

体育作为中国式现代化建设的重要组成部分,是社会发展和人类进步的重要标志,是国家综合国力的重要体现。在中国式现代化进程中,实现体育的现代化既是加快建设体育强国的内在要求,也是推进中华民族伟大复兴的强大动力。该研究立足于中国式体育现代化的理念源流,深挖推动中国式体育现代化发展的关键势能,进而提出适配于中国式体育现代化道路的发展路径,以助力社会主义现代化体育强国建设。研究认为,中国式体育现代化的理念源流从体育政治化的兴国理念向体育社会化的大国理念、再向体育人民性的强国理念嬗变;关键势能可分为政策势能、人才势能、场地势能、创新势能、金融势能、文化势能和健康势能;适配路径包括以增强民生福祉为中心的体育发展路径、以完善治理体系为核心的体育保障路径、以绿色生态和谐为要义的体育共生路径以及以产业消费双升级为主的体育供需路径。

概念研究为什么重要?--构筑教育学建设与发展的概念基石

概念研究之所以重要,在于它通向“理论”。概念研究的重要性,来自于概念的重要性:“概念”是基础研究的根基或基石,“概念”演变是学科发展的动力源泉,“概念”潜藏了前提假设,“概念”体现了思维方式,“概念”包含了多元复杂关系。要更好地推动概念研究,需要更加关注思维方式、新兴学科或交叉学科、融通转化、贡献能力和概念误区。

心理意象视域下元宇宙教学赋能高校学生的学习效果研究

数字化转型背景下,元宇宙的应用促使教育方式发生了深刻变革。然而,元宇宙教学中仍存在一些共识性问题尚未得到解决,如学生的学习持久性不强、专注度不足、学习效率低下等。对此,文章将元宇宙教学的沉浸性、交互性、构想性作为刺激变量,将表象能力作为调节变量、心理意象作为中介变量、学习效果作为反应变量,构建了元宇宙教学赋能学习效果的假设模型。在此基础上,文章构建了假设模型的结构方程模型,并进行了中介效应检验和调节作用检验,研究结果显示:元宇宙教学的沉浸性、交互性、构想性均正向影响高校学生的学习效果,心理意象在元宇宙教学影响高校学生学习效果的过程中起中介作用,表象能力在元宇宙教学影响心理意象和高校学生学习效果的过程中发挥调节作用。据此,文章提出高校应将心理意象融入数字素养、开发数字化元宇宙教学平台、培养学生的表象能力等启示。文章的研究有助于高校有针对性地提升元宇宙教学中学生的学习效果,并推动元宇宙技术与元宇宙教学的深度融合。

范畴·规律·体系:习近平文化思想的三重诠释

作为马克思主义中国化时代化理论成果的文化图绘,习近平文化思想是党的十八大以来中国特色社会主义文化建设实践的理论凝结,创造性地解答了建设社会主义文化强国、建设中华民族现代文明的“文化之问”。全面把握和深入理解习近平文化思想,要在概念范畴解读中明晰其演进脉络,总结具有原创性、标志性的概念群、范畴群,立足世界文化学术坐标体系以互学互鉴、交流提升,打造融通中外的文化新概念、新范畴、新表达。要在遵循文化建设规律中进一步检视其精髓要义,不断深化对文化及文化建设规律的认识,推动守正创新,强化中华民族自立于世界民族之林的自信自强。要在推进体系化学理化研究阐释中厘清其逻辑理路,在原则与路径、形式与内容、实质与目的、使命与价值的有机统一中昭显其结构明晰、层次分明、观点科学、逻辑严密的特征。这三重诠释整体彰显了习近平文化思想的理论广度、阐释深度、影响力度,为以中国式现代化全面推进中华民族伟大复兴提供了强大精神力量。