Socialization Development of ESG Business Models in Representative Asia-Pacific Countries:A State-of-the-Art Review and Recommendation

The integration of environmental,social,and governance(ESG)principles has become a pivotal factor in shaping sustainable and responsible corporate practices.The present study investigates the integration of ESG principles within corporate governance models in Asia-Pacific countries,focusing on socialization.By examining the governance culture,legal frameworks,and corporate practices in these representative countries,the paper delineates a strategic framework for embedding social governance into corporate strategies.The study introduces a Cultural,Economic,Legal,and Political(CELP)framework to assess corporate social governance,investigating the correlation between business practices and social changes.Through a systematic literature review and detailed thematic analysis,this paper aims to offer actionable insights and recommendations,guiding corporations in their transition towards more sustainable and socially responsible business practices.

Brain region-specific roles of brain-derived neurotrophic factor in social stress-induced depressive-like behavior

Brain-derived neurotrophic factor is a key factor in stress adaptation and avoidance of a social stress behavioral response.Recent studies have shown that brain-derived neurotrophic factor expression in stressed mice is brain region–specific,particularly involving the corticolimbic system,including the ventral tegmental area,nucleus accumbens,prefrontal cortex,amygdala,and hippocampus.Determining how brain-derived neurotrophic factor participates in stress processing in different brain regions will deepen our understanding of social stress psychopathology.In this review,we discuss the expression and regulation of brain-derived neurotrophic factor in stress-sensitive brain regions closely related to the pathophysiology of depression.We focused on associated molecular pathways and neural circuits,with special attention to the brain-derived neurotrophic factor–tropomyosin receptor kinase B signaling pathway and the ventral tegmental area–nucleus accumbens dopamine circuit.We determined that stress-induced alterations in brain-derived neurotrophic factor levels are likely related to the nature,severity,and duration of stress,especially in the above-mentioned brain regions of the corticolimbic system.Therefore,BDNF might be a biological indicator regulating stress-related processes in various brain regions.

Integrated ribosome and proteome analyses reveal insights into sevoflurane-induced long-term social behavior and cognitive dysfunctions through ADNP inhibition in neonatal mice

A growing number of studies have demonstrated that repeated exposure to sevoflurane during development results in persistent social abnormalities and cognitive impairment.Davunetide,an active fragment of the activity-dependent neuroprotective protein(ADNP),has been implicated in social and cognitive protection.However,the potential of davunetide to attenuate social deficits following sevoflurane exposure and the underlying developmental mechanisms remain poorly understood.In this study,ribosome and proteome profiles were analyzed to investigate the molecular basis of sevoflurane-induced social deficits in neonatal mice.The neuropathological basis was also explored using Golgi staining,morphological analysis,western blotting,electrophysiological analysis,and behavioral analysis.Results indicated that ADNP was significantly down-regulated following developmental exposure to sevoflurane.In adulthood,anterior cingulate cortex(ACC)neurons exposed to sevoflurane exhibited a decrease in dendrite number,total dendrite length,and spine density.Furthermore,the expression levels of Homer,PSD95,synaptophysin,and vglut2 were significantly reduced in the sevoflurane group.Patch-clamp recordings indicated reductions in both the frequency and amplitude of miniature excitatory postsynaptic currents(mEPSCs).Notably,davunetide significantly ameliorated the synaptic defects,social behavior deficits,and cognitive impairments induced by sevoflurane.Mechanistic analysis revealed that loss of ADNP led to dysregulation of Ca^(2+)activity via the Wnt/β-catenin signaling,resulting in decreased expression of synaptic proteins.Suppression of Wnt signaling was restored in the davunetide-treated group.Thus,ADNP was identified as a promising therapeutic target for the prevention and treatment of neurodevelopmental toxicity caused by general anesthetics.This study provides important insights into the mechanisms underlying social and cognitive disturbances caused by sevoflurane exposure in neonatal mice and elucidates the regulatory pathways involved.

Mapping and measuring urban-rural inequalities in accessibility to social infrastructures

Equal access to social infrastructures is a fundamental prerequisite for sustainable development,but has long been a great challenge worldwide.Previous studies have primarily focused on the accessibility to social infras-tructures in urban areas across various scales,with less attention to rural areas,where inequality can be more severe.Particularly,few have investigated the disparities of accessibility to social infrastructures between urban and rural areas.Here,using the Changsha-Zhuzhou-Xiangtan urban agglomeration,China,as an example,we investigated the inequality of accessibility in both urban and rural areas,and further compared the urban-rural difference.Accessibility was measured by travel time of residents to infrastructures.We selected four types of social infrastructures including supermarkets,bus stops,primary schools,and health care,which were funda-mentally important to both urban and rural residents.We found large disparities in accessibility between urban and rural areas,ranging from 20 min to 2 h.Rural residents had to spend one to two more hours to bus stops than urban residents,and 20 min more to the other three types of infrastructures.Furthermore,accessibility to multiple infrastructures showed greater urban-rural differences.Rural residents in more than half of the towns had no access to any infrastructure within 15 min,while more than 60%of the urban residents could access to all infrastructures within 15 min.Our results revealed quantitative accessibility gap between urban and rural areas and underscored the necessity of social infrastructures planning to address such disparities.

Adolescent suicide risk factors and the integration of socialemotional skills in school-based prevention programs

Adolescents are considered one of the most vulnerable groups affected by suicide.Rapid changes in adolescents’physical and mental states,as well as in their lives,significantly and undeniably increase the risk of suicide.Psychological,social,family,individual,and environmental factors are important risk factors for suicidal behavior among teenagers and may contribute to suicide risk through various direct,indirect,or combined pathways.Social-emotional learning is considered a powerful intervention measure for addressing the crisis of adolescent suicide.When deliberately cultivated,fostered,and enhanced,selfawareness,self-management,social awareness,interpersonal skills,and responsible decision-making,as the five core competencies of social-emotional learning,can be used to effectively target various risk factors for adolescent suicide and provide necessary mental and interpersonal support.Among numerous suicide intervention methods,school-based interventions based on social-emotional competence have shown great potential in preventing and addressing suicide risk factors in adolescents.The characteristics of school-based interventions based on social-emotional competence,including their appropriateness,necessity,cost-effectiveness,comprehensiveness,and effectiveness,make these interventions an important means of addressing the crisis of adolescent suicide.To further determine the potential of school-based interventions based on social-emotional competence and better address the issue of adolescent suicide,additional financial support should be provided,the combination of socialemotional learning and other suicide prevention programs within schools should be fully leveraged,and cooperation between schools and families,society,and other environments should be maximized.These efforts should be considered future research directions.

Making the case for the evolving role of social media in health professions education and a literature review on the application of some in ophthalmology

Background and Objective:Social media(SoMe)has emerged as a tool in health professions education(HPE),particularly amidst the challenges posed by the coronavirus disease 2019(COVID-19)pandemic.Despite the academia’s initial skepticism SoMe has been gaining traction in supporting learning communities,and offering opportunities for innovation in HPE.Our study aims to explore the integration of SoMe in HPE.Four key components were outlined as necessary for a successful integration,and include designing learning experiences,defining educator roles,selecting appropriate platforms,and establishing educational objectives.Methods:This article stemmed from the online Teaching Skills Series module on SoMe in education from the Ophthalmology Foundation,and drew upon evidence supporting learning theories relevant to SoMe integration and models of education.Additionally,we conducted a literature review considering Englishlanguage articles on the application of SoMe in ophthalmology from PubMed over the past decade.Key Content and Findings:Early adopters of SoMe platforms in HPE have leveraged these tools to enhance learning experiences through interaction,dialogue,content sharing,and active learning strategies.By integrating SoMe into educational programs,both online and in-person,educators can overcome time and geographical constraints,fostering more diverse and inclusive learning communities.Careful consideration is,however,necessary to address potential limitations within HPE.Conclusions:This article lays groundwork for expanding SoMe integration in HPE design,emphasizing the supportive scaffold of various learning theories,and the need of furthering robust research on examining its advantages over traditional educational formats.Our literature review underscores an ongoing multifaceted,random application of SoMe platforms in ophthalmology education.We advocate for an effective incorporation of SoMe in HPE education,with the need to comply with good educational practice.

Language-socialization-based Analysis of Putonghua Promotion’s Influences on Tujia Cultural Identity-A Case Study of Enshi Tujia and Miao Autonomous Prefecture

Language functions as a carrier of culture,playing a crucial role in individual socialization into his cultural community,thus it is inextricably interconnected with individual cultural identity.Language acquisition and language ability development require necessary sociocultural interactions and practices.China boasts 55 ethnic minorities which have their own distinctive cultures and language varieties.But some of them are experiencing loss of languages and cultural identity.This paper is dedicated to examining the influences of Putonghua Promotion on Tujia cultural identity from the perspectives of Language Socialization.

Spatiotemporal dynamics of the social structure of Indo-Pacific humpback dolphins(Sousa chinensis)in Xiamen waters from 2007 to 2019

As highly social animals,Indo-Pacific humpback dolphins(Sousa chinensis)exhibit community differentiation.Nevertheless,our understanding of the external and internal factors influencing these dynamics,as well as their spatiotemporal variations,is still limited.In the present study,variations in the social structure of an endangered Indo-Pacific humpback dolphin population in Xiamen Bay,China,were monitored over two distinct periods(2007–2010 and 2017–2019)to analyze the effects of habitat utilization and the composition of individuals within the population.In both periods,the population demonstrated a strikingly similar pattern of social differentiation,characterized by the division of individuals into two main clusters and one small cluster.Spatially,the two primary clusters occupied the eastern and western waters,respectively,although the core distribution area of the eastern cluster shifted further eastward between the two periods.Despite this distribution shift,the temporal stability of the social structure and inter-associations within the eastern cluster remained unaffected.A subset of 16individuals observed in both periods,comprising 51.6%and 43.2%of the population in each respective period,emerged as a foundational element of the social structure and may be responsible for sustaining social structure stability,especially during the 2007–2010 period.These observations suggest that the composition of dominant individuals,an internal factor,had a more substantial influence on the formation of the social network than changes in habitat use,an external factor.Consequently,the study proposes distinct conservation measures tailored to each of the two main clusters.

Enhancing Data Forwarding Efficiency in SIoT with Multidimensional Social Relations

Effective data communication is a crucial aspect of the Social Internet of Things(SIoT)and continues to be a significant research focus.This paper proposes a data forwarding algorithm based on Multidimensional Social Relations(MSRR)in SIoT to solve this problem.The proposed algorithm separates message forwarding into intra-and cross-community forwarding by analyzing interest traits and social connections among nodes.Three new metrics are defined:the intensity of node social relationships,node activity,and community connectivity.Within the community,messages are sent by determining which node is most similar to the sender by weighing the strength of social connections and node activity.When a node performs cross-community forwarding,the message is forwarded to the most reasonable relay community by measuring the node activity and the connection between communities.The proposed algorithm was compared to three existing routing algorithms in simulation experiments.Results indicate that the proposed algorithmsubstantially improves message delivery efficiency while lessening network overhead and enhancing connectivity and coordination in the SIoT context.

A Retrodirective Array Enabled by CMOS Chips for Two-Way Wireless Communication with Automatic Beam Tracking

This article proposes and demonstrates a retrodirective array(RDA)for two-way wireless communication with automatic beam tracking.The proposed RDA is enabled by specifically designed chips made using a domestic complementary metal-oxide semiconductor(CMOS)process.The highly integrated CMOS chip includes a receiving(Rx)chain,a transmitting(Tx)chain,and a unique tracking phaselocked loop(PLL)for the crucial conjugated phase recovery in the RDA.This article also proposes a method to reduce the beam pointing error(BPE)in a conventional RDA.To validate the above ideas simply yet without loss of generality,a 2.4 GHz RDA is demonstrated through two-way communication links between the Rx and Tx chains,and an on-chip quadrature coupler is designed to achieve a nonretrodirective signal suppression of 23 dBc.The experimental results demonstrate that the proposed RDA,which incorporates domestically manufactured low-cost 0.18 lm CMOS chips,is capable of automatically tracking beams covering±40with a reduced BPE.Each CMOS chip in the RDA has a compact size of 4.62 mm^(2) and a low power consumption of 0.15 W.To the best of the authors’knowledge,this is the first research to demonstrate an RDA with a fully customized CMOS chip for wireless communication with automatic beam tracking。

基于Social Transformer的井下多人轨迹预测方法

目前煤矿井下人员轨迹预测方法中,Transformer与循环神经网络(RNN)、长短期记忆(LSTM)网络相比,在处理数据时不仅计算量小,同时还有效解决了梯度消失导致的长时依赖问题。但当环境中涉及多人同时运动时,Transformer对于场景中所有人员未来轨迹的预测会出现较大偏差。并且目前在井下多人轨迹预测领域尚未出现一种同时采用Transformer并考虑个体之间相互影响的模型。针对上述问题,提出一种基于Social Transformer的井下多人轨迹预测方法。首先对井下每一个人员独立建模,获取人员历史轨迹信息,通过Transformer编码器进行特征提取,接着由全连接层对特征进行表示,然后通过基于图卷积的交互层相互连接,该交互层允许空间上接近的网络彼此共享信息,计算预测对象在受到周围邻居影响时对周围邻居分配的注意力,从而提取其邻居的运动模式,继而更新特征矩阵,最后新的特征矩阵由Transformer解码器进行解码,输出对于未来时刻的人员位置信息预测。实验结果表明,Social Transformer的平均位移误差相较于Transformer降低了45.8%,且与其他主流轨迹预测方法LSTM,S−GAN,Trajectron++和Social−STGCNN相比分别降低了67.1%,35.9%,30.1%和10.9%,有效克服了煤矿井下多人场景中由于人员间互相影响导致预测轨迹失准的问题,提升了预测精度。

Reference-frame-independent quantum key distribution with two-way classical communication

The data post-processing scheme based on two-way classical communication(TWCC)can improve the tolerable bit error rate and extend the maximal transmission distance when used in a quantum key distribution(QKD)system.In this study,we apply the TWCC method to improve the performance of reference-frame-independent quantum key distribution(RFI-QKD),and analyze the influence of the TWCC method on the performance of decoy-state RFI-QKD in both asymptotic and non-asymptotic cases.Our numerical simulation results show that the TWCC method is able to extend the maximal transmission distance from 175 km to 198 km and improve the tolerable bit error rate from 10.48%to 16.75%.At the same time,the performance of RFI-QKD in terms of the secret key rate and maximum transmission distance are still greatly improved when statistical fluctuations are considered.We conclude that RFI-QKD with the TWCC method is of practical interest.

The Influence of Watching TV Talent Show on Teenagers Socialization From Marcuse’s Thought of“One Dimensional Person”

Based on Marcuse’s thought of“one-dimensional person”,this paper discusses the influence of TV talent show on teenagers’socialization.By analyzing the characteristics of TV talent shows that emphasize individual competition and success,appearance and image,and instant satisfaction,it is pointed out that these characteristics are easy for teenagers to produce the mentality of pursuing fame and fortune,appearance,and instant satisfaction,ignoring the development of other important values and qualities.Therefore,we need to guide teenagers to maintain a critical attitude toward TV talent shows,and pay attention to cultivating their independent thinking and all-round development.

Predicting Users’ Latent Suicidal Risk in Social Media: An Ensemble Model Based on Social Network Relationships

Suicide has become a critical concern,necessitating the development of effective preventative strategies.Social media platforms offer a valuable resource for identifying signs of suicidal ideation.Despite progress in detecting suicidal ideation on social media,accurately identifying individuals who express suicidal thoughts less openly or infrequently poses a significant challenge.To tackle this,we have developed a dataset focused on Chinese suicide narratives from Weibo’s Tree Hole feature and introduced an ensemble model named Text Convolutional Neural Network based on Social Network relationships(TCNN-SN).This model enhances predictive performance by leveraging social network relationship features and applying correction factors within a weighted linear fusion framework.It is specifically designed to identify key individuals who can help uncover hidden suicidal users and clusters.Our model,assessed using the bespoke dataset and benchmarked against alternative classification approaches,demonstrates superior accuracy,F1-score and AUC metrics,achieving 88.57%,88.75%and 94.25%,respectively,outperforming traditional TextCNN models by 12.18%,10.84%and 10.85%.We assert that our methodology offers a significant advancement in the predictive identification of individuals at risk,thereby contributing to the prevention and reduction of suicide incidences.

Exploring Global Demands for Integrating Social Aspects into Community Healthcare: A Literature Review

Aging and crises like pandemics and climate change are global concerns that affect community environments. These social and natural changes influence people’s health worldwide. Aging impacts human health, including physical and mental aspects, and increases the need for care. Recent crises have affected not only the elderly but also younger populations, necessitating further efforts to develop a systematic community strategy. The goal of such a strategy is to maintain or enhance people’s well-being. As we face aging and crises like pandemics and climate change, it becomes essential to consider health holistically and globally, taking into account the community environment and social determinants without boundaries. The present study aimed to explore the necessary aspects of incorporating social determinants into clinical practice, enabling healthcare providers to view health from a holistic and planetary perspective. This approach facilitates the development of integrated community strategies. The study reviewed literature from PubMed, MEDLINE, and CINAHL databases, focusing on medicine, health, and welfare. An electronic search for English-language articles in peer-reviewed journals was conducted up to July 2024, using search terms such as “holistic health,” “planetary health,” and “social determinants.” Eight articles were identified through the search. After excluding three based on their titles, abstracts, and full texts, five articles were selected. The research focused on three areas: perceiving health in ecosystems, considering health-related policy in clinical situations, and addressing health in primary care settings. This study emphasizes the need for further research on innovative, integrated community strategies in the context of a globally aging society, focusing on non-medical aspects like pandemics, climate change, and social determinants to achieve a holistic and planetary understanding of people’s health. It suggests that understanding the social aspects of ecosystems in clinical settings, through interdisciplinary collaboration, is crucial for developing systematic community strategies for people’s well-being life in medical, health, and welfare contexts.

Social prescribing in the metaverse:a new frontier for primary care practice

The advent of immersive technologies such as the metaverse,extended reality,artificial intelligence,and blockchain offers novel possibilities to transform healthcare services.These innovations coincide with clinicians'aspirations to deliver more comprehensive,patient-centered care tailored to individuals singular needs and preferences.Integration of these emerging tools may confer opportunities for providers to engage patients through new modalities and expand their role.However,responsible implementation necessitates deliberation of ethical implications and steadfast adherence to foundational principles of compassion and interpersonal connection underpinning the profession.While the metaverse introduces new channels for social prescribing,this perspective advocates that its ultimate purpose should be strengthening,not supplanting,human relationships.We propose an ethical framework centered on respect for patients'dignity to guide integration of metaverse platforms into medical practice.This framework serves both to harness their potential benefits and mitigate risks of dehumanization or uncompassionate care.Our analysis maps the developing topology of metaverse-enabled care while upholding moral imperatives for medicine to promote healing relationships and human flourishing.

Correlation Analysis between Self-Disclosure and Social Support in Patients with Breast Cancer

Objective: Describe the status quo of self-disclosure and social support in breast cancer patients and analyze the correlation between them. Methods: General data questionnaire, distress disclosure Index scale and Chinese version of medical social support scale were used to investigate the correlation between self-disclosure and social support in breast cancer patients by Pearson correlation analysis. Results: 1) The total self-disclosure score was (38.75 ± 9.18);the total score of social support was (70.57 ± 14.04) scores, including emotional information support dimension (28.39 ± 6.06) scores, practical support dimension (15.62 ± 3.31) scores, elastic support dimension (14.85 ± 3.23) scores, and emotional support dimension (11.70 ± 2.56) scores. 2) Self-disclosure was positively correlated with social support (r = 0.433, p Conclusion: Breast cancer patients had a moderate level of self-disclosure, and the higher the level of self-disclosure, the better the social support. It is suggested that improving the self-disclosure level of breast cancer patients can help them obtain more social support.

Social Robot Detection Method with Improved Graph Neural Networks

Social robot accounts controlled by artificial intelligence or humans are active in social networks,bringing negative impacts to network security and social life.Existing social robot detection methods based on graph neural networks suffer from the problem of many social network nodes and complex relationships,which makes it difficult to accurately describe the difference between the topological relations of nodes,resulting in low detection accuracy of social robots.This paper proposes a social robot detection method with the use of an improved neural network.First,social relationship subgraphs are constructed by leveraging the user’s social network to disentangle intricate social relationships effectively.Then,a linear modulated graph attention residual network model is devised to extract the node and network topology features of the social relation subgraph,thereby generating comprehensive social relation subgraph features,and the feature-wise linear modulation module of the model can better learn the differences between the nodes.Next,user text content and behavioral gene sequences are extracted to construct social behavioral features combined with the social relationship subgraph features.Finally,social robots can be more accurately identified by combining user behavioral and relationship features.By carrying out experimental studies based on the publicly available datasets TwiBot-20 and Cresci-15,the suggested method’s detection accuracies can achieve 86.73%and 97.86%,respectively.Compared with the existing mainstream approaches,the accuracy of the proposed method is 2.2%and 1.35%higher on the two datasets.The results show that the method proposed in this paper can effectively detect social robots and maintain a healthy ecological environment of social networks.

Exploring the Reasons for Selfie-Taking and Selfie-Posting on Social Media with Its Effect on Psychological and Social Lives:A Study among Indian Youths

‘Selfie’taking was introduced to the common people by smartphones and has become a common practice across the globe in no time.With technological advancement and the popularity of smartphones,selfie-taking has grown rapidly within a short time.In light of the new trend set by the generation,this study aimed to explore reasons for selfie-taking and selfie-posting on social media and their effects on the social and psychological lives of young adults.A purposive sampling method was adopted to select 20 Indian citizens,between 18 and 24 years.The data were collected through semi-structured interviews and analysed using thematic analysis.Selfie-taking and posting on social media give positive feelings,and it acts as a mood modifier dependent mostly on the favourability and feedback about the post which in turn affects emotions and self-satisfaction.

Beamforming Design for IRS-and-UAV-Aided Two-Way Amplify-and-Forward Relay Networks in Maritime IoT

In this paper,an intelligent reflecting surface(IRS)-and-unmanned aerial vehicle(UAV)-assisted two-way amplify-and-forward(AF)relay network in maritime Internet of Things(IoT)is proposed,where ship1(S1)and ship2(S2)can be viewed as data collecting centers.To enhance the message exchange rate between S1 and S2,a problem of maximizing minimum rate is cast,where the variables,namely AF relay beamforming matrix and IRS phase shifts of two time slots,need to be optimized.To achieve a maximum rate,a low-complexity alternately iterative(AI)scheme based on zero forcing and successive convex approximation(LC-ZF-SCA)algorithm is presented.To obtain a significant rate enhancement,a high-performance AI method based on one step,semidefinite programming and penalty SCA(ONSSDP-PSCA)is proposed.Simulation results show that by the proposed LC-ZF-SCA and ONS-SDP-PSCA methods,the rate of the IRS-and-UAV-assisted AF relay network surpass those of with random phase and only AF relay networks.Moreover,ONS-SDP-PSCA perform better than LC-ZF-SCA in aspect of rate.