The COVID-19 pandemic in Indonesia makes a significant impact both physically and psychologically. One month after the President of the Republic of Indonesia announced about the COVID-19 patient cases, the Indonesian Child Protection Commission data during April 2020, depicted that 76.7% of children were not happy to participate in distance learning because 81.8% were only given assignments by the teacher and 73.2% felt they had a heavy task and had a short period of time to complete. This reaction is an indicator of the children’s anxiety about distance learning. The anxiety that occurs in these students is assumed to depend on their social support and emotional maturity. When students get optimal family support and are able to control their emotions in the face of a pandemic, they can reduce anxiety in facing online learning. The subjects of this study were 202 junior high and high school students. The results showed that social support and emotional maturity simultaneously affect anxiety in online learning (Freg = 45.066, p = 0.00 <0.01). These results can be used as a basis for providing psycho-education to increase family support and emotional maturity to reduce anxiety in online learning.

In the design of educational robots, it seems undecided whether robots should show social behaviors and look human-like or that such cues are indifferent to learning. We conducted an experiment with different designs of social robots, rehearsing the multiplication tables with primary school children in Hong Kong. Results show that affective bonding tendencies may occur but did not significantly contribute to the learning progress of these children, perhaps due to the short interaction period. Nonetheless, 5 minutes of robot tutoring improved their scores with about 30% and only for a few challenged children, performance dropped. We discuss that topics such as teaching language skills may be fostered by human likeness in appearance and behaviors but that for STEM-related subjects, the social aspects of robots hardly matter.

Underpinned by the research works on private returns on education in developing nations that have found a positive correlation between earning and subsequent level of schooling, this paper presents a concept of an investment policy which will help the impoverished children in becoming economically successful through systematic funding of their educational needs with an obligation of interest adjusted returns.

This study takes as a starting point the importance and dependence of the media (Ball-Rokeach & DeFleur, 1976) to obtain information about the pandemic. The dependency theory of the media system was developed in the 1970s when mass media were the dominant source of information. Today, at a time when media choices have become abundant, studies are needed to understand the phenomenon of media dependence in light of new dimensions made important by the transformations that have taken place in the social and media fields - where the coexistence of mass media with social media platforms stands out. As large-scale crises rarely occur and the media environment changes rapidly, it is important to analyze how media dependence relates to choose and trust in different media (traditional media vs. social media) in times of crisis. Several questions arise. What is the trust attributed by individuals to social media as sources of information about the COVID-19? How well informed are the individuals who choose these sources as the main sources of information? From a questionnaire administered to 240 individuals in Portugal, during the first week of the state of emergency (March 2020), this research seeks to identify how people gained access to information about the COVID-19, how they acted critically towards the various sources and how they assess the reliability of different media. Finally, it analyzes the association between the type of medium chosen and adherence to misinformation content about the virus. The results reveal the existence of a phenomenon of dependence on the media, with a strong exposure (both active and accidental) to informative content, with conventional media being privileged as the main source, and positively distinguished in terms of confidence. Finally, a statistically significant association of a positive sign was identified between the use of social media as the main source and the acceptance of misinformation.

The Corona Virus (COVID-19) pandemic situation has posed significant effect on tourism industry. Tourism destinations have embraced emergency health care measures and restrictions imposed on human movement around the world. Beaches and resorts are empty, peoples’ movements are stopped and travelling between territories is strictly controlled. The COVID-19 lockdown around the world has imposed negative impact on the livelihood of people and world economy as well. The present study attempts to find out the scopes for sustainable tourism development in near future from the consequences of social, economic, and environment in COVID-19 pandemic situation.

This study empirically investigates the complex interplay between the severity of the coronavirus pandemic, mobility changes in retail and recreation, transit stations, workplaces, and residential areas, and lockdown measures in 88 countries of the word. To conduct the study, data on mobility patterns, socioeconomic and demographic characteristics of people, lockdown measures, and coronavirus pandemic were collected from multiple sources (e.g., Google, UNDP, UN, BBC, Oxford University, Worldometer). A Structural Equation Modeling (SEM) technique is used to investigate the direct and indirect effects of independent variables on dependent variables considering the intervening effects of mediators. Results show that lockdown measures have significant effects to encourage people to maintain social distancing. However, pandemic severity and socioeconomic and institutional factors have limited effects to sustain social distancing practice. The results also explain that socioeconomic and institutional factors of urbanity and modernity have significant effects on pandemic severity. Countries with a higher number of elderly people, employment in the service sector, and higher globalization trend are the worst victims of the coronavirus pandemic (e.g., USA, UK, Italy, and Spain). Social distancing measures are reasonably effective at tempering the severity of the pandemic.

The assessment of positive emotional states in animals has been advanced considerably through the use of judgement bias testing. JBT methods have now been reported in a range of species. Generally, these tests show good validity as ascertained through use of corroborating methods of affective state determination. However, published reports of judgement bias task findings can be counter-intuitive and show high inter-individual variability. It is proposed that these outcomes may arise as a result of inherent inter- and intra-individual differences as a result of biology. This review discusses the potential impact of sex and reproductive cycles, social status, genetics, early life experience and personality on judgement bias test outcomes. We also discuss some aspects of test design that may interact with these factors to further confound test interpretation. There is some evidence that a range of biological factors affect judgement bias test outcomes, but in many cases this evidence is limited and needs further characterisation to reproduce the findings and confirm directions of effect. It is our proposition that researchers should consider dedicated study on these factors and their impact on judgement biasing. This is needed to confirm effect and investigate mechanisms. Alternately, consideration and reporting of these factors in JBT studies through incorporation in statistical analyses will provide much needed additional data on their impact. These actions will enhance the validity and practical applicability of the JBT for welfare assessment.

Registry and survey data gave an opportunity to compare possible roles of social attitudes and social values in control and limit the COVID-19 pandemic. We analysed social values and time series of daily R0 (reproduction rate) estimates for 27 European countries. Embedded and affective autonomy are significantly negatively associated (p-Value<0.05) with controlled R0. It could mean that well interconnected societies with high attention to maximize utilities are more likely to couple with COVID-19. Hierarchy is significantly positively associated (p-Value<0.05) with controlled R0. Thus, hierarchical structures could inhibits control of COVID-19. The results emphasize the need to pay more attention to social values context in evaluating the effectiveness of mitigation strategies internationally.

In late February 2020, Coronavirus disease-2019 (COVID-19) has aggressively spread around many bordering provinces of the three most productive regions of northern Italy (Lombardy, Veneto and Emilia Romagna). The first outbreak exploded in the municipality of Codogno (Lombardy). The province of Ferrara (Emilia Romagna) has been indicated as an anomaly due to the lower number of confirmed cases (1·065 cases per 1000 population). We argue that the spread of the virus throughout Emilia Romagna has a possible explanation in the geographical location of most of its provinces along the Via Emilia, an ancient Roman road that runs throughout the region, which we consider as a proxy for citizens’ movement, number of contacts, and social interactions. In order to test this hypothesis, we used a non-linear multiple regression analysis on aggregate province data to investigate the association between the rates of confirmed cases and the distance from the Via Emilia. The results indicate that the infection rate decreases proportionally to the distance from Via Emilia (-14% every 10 km, p<0·001). Further studies are needed, but Ferrara’s “peculiarity” might have a geographical/behavioral explanation, due to its isolation from the regional main connection routes, which are still revolving around a road built by the ancient Romans 2,000 years ago.

The social distancing as a response to COVID 19 pandemic has led to the exceptional reductions of daily routine people activities and vehicle uses mainly in city. This same situation was also experienced by several busy, large, and populous cities in Southeast Asia (SA) countries. Correspondingly, this study aimed to test the hypothesis that the social distancing implementation period has increased the air quality in the term of carbon monoxide (CO) emission reduction as drawn from Jakarta city as an example of the one of populated cities in SA region. The CO was measured in parts per billions (ppb) and monitored on the daily basis employing remote sensor platform. The monitor periods were started from January, February, March, and April 2020 with 10 measurement days for each month. The social distancing was implemented from mid of March to the recent April. The CO measurement data were statistically tested to justify the significant effects of social distancing on the CO levels. Based on the CO data analysis, the order of CO mean by months is February > January > March > April. The CO levels for January, February, March, and April were 87.46 ppb (95%CI: 83.54-91.37), 88.20 ppb (95%CI: 81.65-94.74), 86.38 (95%CI: 81.06-91.69), and 78.68 (95%CI: 74.03-83.32) respectively. This study also find significant difference (p<0.05) of CO levels especially in April when social distancing has been implemented. Hence, these findings illustrate the potential air pollutant reduction gained from implementing social distancing as can be seen in April.

Ninety percent of the people added to the planet over the next 30 years will live in African and Asian cities, and a large portion of these populations will reside in deprived neighborhoods defined by slum conditions, informal settlement, or inadequate housing. The four current approaches to neighborhood deprivation mapping are largely silo-ed, and each fall short of producing accurate, timely, comparable maps that reflect local contexts. The first approach, classifying “slum households” in census and survey data and aggregating to administrative areas, reflects household-level rather than neighborhood-level deprivation. The second approach, field-based mapping, can produce the most accurate and context-relevant maps for a given neighborhood, however it requires substantial resources, preventing up-scaling. The third and fourth approaches, human interpretation and machine classification of satellite, aerial, or drone imagery, both overemphasize informal settlements, and fail to represent key social characteristics of deprived areas such as lack of tenure, exposure to pollution, and lack of basic public services. The latter, machine classification of imagery, can be automated and extended to incorporate new and multiple sources of data. This diverse collection of authors represent experts from these four approaches to neighborhood deprivation mapping. We summarize common areas of understanding, and present a set of requirements to produce maps of deprived urban areas that can be used by local-to-international stakeholders for advocacy, planning, and decision-making.

This article aims to understand the domains and conceptual uses of contagion, its modalities and its effects, in its different historical contexts and meanings, as an expression of the process of interdependence between the positions and the different points of view of different actors involved in multiple scientific, moral, social and political challenges. Another objective focuses on understanding the process of collective management of contagion, disease and health, where prevention is an essential element of its objectives and justifications, its discursive order, as well as its practical activities.

Tuberculosis (TB) associated stigma is well-documented phenomenon that may contribute to sub-optimal TB care in Pakistan. The objective of study was to assess TB related knowledge and perceived stigma among community members. This was cross-sectional survey using convenience sample of 183 individuals recruited between October and December 2017. A validated stigma measurement tool developed by Van Rie et al. was adapted. Data was analyzed using SPSS version 20.0. 183 individuals (73% males; n = 134) participated in survey. Eighty-seven percent were aware that TB is curable disease (n = 159) and 91% thought that it could be transmitted by coughing (n = 167). However, respondents also thought that TB was spread through contaminated food (73%; n = 134), sharing meals (55%; n = 100), sharing utensils (53%; n = 96) and by having sexual intercourse with a TB patient (51%; n = 93). Fifty-seven percent (n = 104) associated TB with high levels of stigma. Persons who had less than six years of education (crude OR = 1.2; 95% CI: 0.89, 1.72) and lacked knowledge that TB is curable (crude OR = 3.42; 95% CI: 1.20, 9.70) were more likely to associate TB with stigma. In addition, females (crude OR = 1.33; 95% CI: 0.87, 2.04) and those who were unemployed (crude OR = 1.06; 95% CI: 0.65, 1.74) were also more likely to associate TB with stigma. We found an association between lack of knowledge about TB and perceived stigma. This highlights need for improved education and awareness about TB.

Despite numerous interventions to promote gender equality, sub-Saharan Africa has one of the highest prevalence rates of non-partner sexual assault in the world, thus constituting a major social and public health issue in the region. As social workers frequently provide services to this population, an exploratory cross-sectional study was conducted to explore rape myth acceptance among undergraduate social work students studying in Namibia. Findings revealed the positive influence of social work education in reducing rape myth acceptance as well as highlighted the influence of age, gender, country of origin, self-identification as a feminist, and religiosity on rape myth acceptance among this population.

This paper introduces both a hardware and a software system designed to allow low-cost electronic monitoring of social insects using RFID tags. Data formats for individual insect identification and their associated experiment are proposed to facilitate data sharing from experiments conducted with this system. The antenna's configuration and their duty cycle ensure a high degree of detection rates. Other advantages and limitations of this system are discussed in detail in the paper.

The purpose of this study is to explore the intensity of emotions and social skills in a physical education teaching unit (PE). Two instruments of analysis are used: the GES (Games and Emotion Scale) to evaluate emotions and an ad-hoc questionnaire to measure the social skills of 21 students in the sixth year of primary education. The data analysis was carried out using a generalised estimating equation model (GEE), taking into account the correlation between the different scores of the same subject and the asymmetry of the data. The results show positive emotions to be significantly more intense than negative ones and ambiguous emotions are revealed throughout all the PE sessions.

Introduction Headache is a common public health problem, but its burden could be avoided by raising headache awareness and the appropriate use of acute medication and prophylactic medication. Few reports on raising headache awareness in the general public have been reported, and there are no reports on headache awareness campaigns through social networking services (SNS), or social media, in Japan. We prospectively performed a headache awareness campaign from March 2022 through 2 SNS, targeting nurse and wind instrumental musicians, because they are with high headache prevalence. Methods Through the 2 SNS, the article and video were distributed, respectively. The article and video described the 6 important topics for the general public about headaches, which were described in the Clinical Practice Guideline for Headache Disorders 2021. Just after reading or watching them as e-learning, we performed online questionnaire sheets to investigate the awareness of the 6 topics through the 2 SNS. The awareness of the 6 topics before and after the campaign was evaluated. Results In the SNS nurse-senka, we obtained 1191 responses. Women comprised 94.4%, and the median (range) age was 45 (20 to 71) years old. Headache sufferers were 63.8%, but only 35.1% had consulted doctors. In the SNS Creatone, we got the response from 134 professional musicians, with 77.3% of women. The largest number of respondents were in their 20s (range 18-60 years old). Headache sufferers were 87.9%. Of them, 36.4% had consulted doctors, 24.2% were medication-overuse headache. The ratios of individuals who were aware of the 6 topics significantly increased from 15.2%-47.0% to 80.4-98.7% after the online questionnaire in both SNS (p < 0.001, all). Conclusions We conducted this headache awareness campaign through e-learning and an online survey via 2 SNS. The ratios of individuals who were aware of the 6 topics about headaches significantly increased 1 month after e-learning. Our results suggest that e-learning and online survey can improve headache awareness. The materials in this campaign can be installed into smartphone applications and further spread on SNS, leading to strong influence. With rapid digital transformations such as online telemedicine and artificial intelligence diagnosis, raising awareness will be more efficient and effective and should be important.

In spite of numerous predictions, the natural herd immunity for covid-19 visru had not been approahed anywhere in the world. Thus, the traditional mathematical models of disease spread demonstrated their inability to describe adequately the covid-19 pandemic. In author's works, the novel model of the disease spread was developed. This model reflects the basic features of the covid-19 pandemic: a) the social clustering character of virus spread, b) . Social clustering is mathematically modelled with ultrametric spaces having the treelike geometry encoding hierarchy of the regulation constraints. The virus spread is described by ultrametric diffusion or random walk on the hierarchic energy landscape. In contrast to the standard models which are characterized by the exponential decrease of the probability to become infected - at the stage of approaching of the herd immunity, the ultrametric model is characterized by the power law. Moreover, the model gives the possibility to quantify the influence of restriction measures up to the lockdown. Our main result is that the play with restrictions, including lockdowns, is counterproductive and leads to the essential slowdown of approaching the herd immunity or even makes this impossible.

We aimed to explore university students’ perceptions and experiences of SARS-CoV-2 mass asymptomatic testing, social distancing and self-isolation during the COVID-19 pandemic. This qualitative study comprised of four rapid online focus groups conducted at a higher education institution in England during high alert (tier 2) national COVID-19 restrictions. Data were analysed thematically. Participants were purposively sampled university students (n = 25) representing a range of gender, age, living circumstances (on/off campus) and SARS-CoV-2 testing/self-isolation experiences. Six themes with 16 sub-themes emerged from the analysis of the qualitative data: ‘Term-time Experiences’, ‘Risk Perception and Worry’, ‘Engagement in Protective Behaviours’, ‘Openness to Testing’, ‘Barriers to Testing’ and ‘General Wellbeing’. Students described feeling safe on campus, believed most of their peers are adherent to protective behaviours and were positive towards asymptomatic testing in university settings. University communications about COVID-19 testing and social behaviours need to be timely and presented in a more inclusive way to reach groups of students who currently feel marginalised. Barriers to engagement with SARS-CoV-2 testing, social distancing and self-isolation were primarily associated with fear of the mental health impacts of self-isolation, including worry about how they will cope, high anxiety, low mood, guilt relating to impact on others and loneliness. Loneliness in students could be mitigated through increased intra-university communications and a focus on establishment of low COVID-risk social activities to help students build and enhance their social support networks. These findings are particularly pertinent in the context of mass asymptomatic testing programmes being implemented in educational settings and high numbers of students being required to self-isolate. Universities need to determine the support needs of students during self-isolation and prepare for the long-term impacts of the pandemic on student mental health and welfare support services.

The first two decades of the 21st-century have seen the emergence of the modern citizen science movement, increased demand for niche eco and wildlife tourism experiences, and the willingness of people to voluntarily share information and photographs online. To varying extents, the rapid growth of these three phenomena has been driven by the availability of portable smart devices, access to the Web 2.0 internet from almost anywhere on the planet, and the development of applications and services, including social media/networking sites (SNSs). In addition, the number of peer-reviewed publications that explore how text and images shared on SNSs can be data-mined for academic research has surged in recent years. This systematic quantitative review has two goals. The first goal is to provide an oversight of how the photographs that ecotourists share online are contributing to wildlife tourism research. The second goal is to promote the emerging photovoice technique as a theoretical context for social research based on the photographs and comments that ecotourists share on SNSs. From the perspectives of community benefits, conservation behaviours, and environmental education, there are many similarities between authentic ecotourism experiences and quality ecological citizen science programs. Much of the literature regarding the theory and practice of citizen science reports on the difficulties of attracting, training, motivating and retaining community members. The synthesis of this review is that crowdsourcing wildlife and tourism data from comments and photographs that ecotourists share on SNSs is a credible method of research that provides a self-replenishing pool of citizen scientists.

In this paper we present a review of recent developments in AI towards the possibility of an artificial intelligence equals that of human intelligence. AI technology has always shown a stepwise increase in its capacity and complexity. The last step took place several years ago, with the increased progress in deep neural network technology. Each such step goes hand in hand with our understanding of ourselves and our understanding of human cognition. Indeed, AI was always about the question of understanding human nature. AI percolates into our lives, changing our environment. We believe that the next few steps in AI technology, and in our understanding of human behavior, will bring about much more powerful machines, flexible enough to resemble human behavior. In this context, there are two research fields: Artificial Social Intelligence (ASI) and General Artificial Intelligence (AGI). The authors also allude to one of the main challenges for AI, embodied cognition, and explain how it can viewed as an opportunity for further progress in AI research.

This qualitative research explores the influence of Corporate Social Responsibility (CSR) on supply chain sustainability within the renewable energy sector. Through a comprehensive review of existing literature, key themes and patterns are identified, shedding light on the complex dynamics and interrelationships inherent in CSR practices and their impact on supply chain sustainability. The findings highlight the critical role of CSR in driving environmental sustainability, social equity, economic viability, governance mechanisms, and technological innovation across renewable energy supply chains. Environmental sustainability emerges as a priority, with CSR initiatives focusing on reducing carbon emissions, promoting clean energy technologies, and adopting sustainable sourcing strategies. Social equity is emphasized through stakeholder consultation, transparent decision-making, and investments in community development. Economic viability is addressed through considerations of brand reputation, financial performance, and regulatory compliance. Governance mechanisms and regulatory frameworks play a crucial role in shaping CSR practices, with collaborative partnerships and policy advocacy driving industry-wide change. Technological innovation, particularly the integration of blockchain, IoT, and AI, enhances transparency, traceability, and accountability in supply chains. The study concludes by discussing theoretical implications, practical insights, limitations, and avenues for future research, highlighting the importance of CSR in promoting sustainable development in the renewable energy sector.

Promoting organic foods production and consumption contributes to accomplishing United Nations sustainable development goals. Social commerce provides a promising opportunity to develop the organic food industry. However, there is limited knowledge regarding customer behaviors in relation to purchasing organic foods via social commerce platforms. Therefore, this study expanded upon the unified theory of acceptance and use of technology (UTAUT-2) to develop a comprehensive model that explains how customers' social commerce trust and behavioral intentions to purchase organic foods using Instagram social commerce affect their purchasing behaviors. The research model was analyzed by employing partial least squares structural equation modeling (PLS-SEM) for the data collected from a quantitative survey of 410 customers who used Instagram to purchase organic foods in Iran. The results revealed that facilitated purchasing conditions, hedonic motivations, social influence, rating and reviews, and influencers’ endorsements increase customers' purchase intentions. Moreover, Instagram’s recommendations and referrals, influencers’ endorsements, as well as social influence boost customers' trust in the social commerce platform. Eventually, it was determined that influencers’ endorsements, social commerce trust, and purchase intention determine a customer’s organic foods purchasing behaviors. This research provides valuable insights for organic food marketers to optimize their social commerce strategies.

This paper proposes a concise literature review aimed at identifying the current body of knowledge on the adoption of Social Networks in Crisis Management. The major input is a structured research question based on the initial reading around the topic. Before the recent pan-demic, most literature has focused on local crises, with a relatively low number of exceptions. Additionally, self-organizing system are spontaneous established between people who are af-fected by a crisis. Among the identified challenges, there is the need to integrate official commu-nication by emergency agencies with citizen-generated contents in a contest of credibility and trustworthiness. In certain cases, it has been reported a lack of specific competence, knowledge, and expertise, as well as a lack of sufficient policies and guidelines in the use of Social Networks. Those challenges need to be framed by considering the classic difficulties to provide timely and accurate information, to deal with fake news, unverified or misleading information, and infor-mation overload. Bridging major gaps though advanced analytics and AI-based technology is expected to provide a key contribution to establish and safely enable in practice an effective and efficient communication, to contrast dissonant mental models, which are often fostered by Social Networks, and to enable a shared situational awareness.

Background: Heat waves are correlated with increased mortality in the aged population. Social isolation is known as a vulnerability factor. This study aims at evaluating the correlation between an intervention to reduce social isolation and the increase in mortality in the population over 80 during heat waves. Methods: The study adopts a retrospective ecologic design. We compared the excess mortality rate (EMR) in the over 80 population during heat waves in urban areas of Rome (Italy), where a program to reduce social isolation was implemented compared to others where it was not implemented. We measured mortality of the summer periods from 2015 to 2019 compared with 2014 (a year without heat waves). Winter mortality, cadastral income and proportion of over 90 were included in the multivariate Poisson regression. Results: The EMR in the intervention and controls was 2.70% and 3.81%, respectively. Rate ratio 0.70 (c.i. 0.54 - 0.92, p-value 0.01). The Incidence Rate Ratio (IRR) of the interventions with respect to the controls is 0.76 (c.i. 0.59 - 0.98). After adjusting for other variables, the IRR was 0.44 (c.i. 0.32 - 0.60). Conclusions: Reducing social isolation could limit the impact of heat waves on the mortality of the elderly population.

Since the 1970s, the application of microprocessor in industrial machinery and the development of computer systems have transformed the manufacturing landscape. The rapid integration and automation of production systems have outpaced the development of suitable human design criteria, creating a deepening gap where human factor was seen as an important source of errors and disruptions. Today the situation seems different: the scientific and public debate about the concept of Industry 4.0 has raised the awareness about the central role humans have to play in manufacturing systems, to the design of which they must be considered from the very beginning. The future of industrial systems, as represented by Industry 4.0, will rely on the convergence of several research fields such as Intelligent Manufacturing Systems (IMS), Cyber-Physical Systems (CPS), Internet of things (IoT), but also socio-technical fields such as social approaches within technical systems. This article deals with different Human dimensions associated with CPS and IoT and focuses on their conceptual evolution of automatization to improve the sociability of such automated production systems and consequently puts again the human in the loop. Hereby, our aim is to take stock of current research trends, and to show the importance of integrating human operators as a part of a socio-technical system based autonomous and intelligent products or resources. As results, different models of sociability as way to integrate human into the broad sense and/or the development of future automated production systems, were identified from the literature and analysed.

The sustainability of social security is increasingly important to countries worldwide, yet the impact of regulation on social security remains controversial. Most scholars and policymakers focus primarily on the influence of social regulation on social security, while to varying degrees neglecting the effects of market regulation. This study employs data on the relaxation of market regulation (RMR) from the Marketization Index of China’s Report (MICR) and balanced panel data for 31 provinces in China from 2008 to 2019. Using instrumental variable methods to address endogeneity issues in the model, we empirically evaluate the impact of China's RMR on the level of social security (SSL) and its underlying mechanisms. The conclusion indicates that for every standard deviation increase in the intensity of RMR by local governments, there is a 2.25% increase in SSL. The study also found that social security expenditure and efficiency serve as mediating variables for the impact of RMR on SSL, but it did not support the mediating role of social security fairness. These findings offer valuable insights for optimizing regulation and social security reform in China, as well as useful references for other emerging market economies in identifying priorities for their coordinated regulatory and social security reform.

Global biodiversity loss and climate change highlight the importance of environmental knowledge and behavior in the population at large. Americans gain environmental knowledge almost exclusively from sources outside of formal schooling, and increasingly, the internet and social networking sites (SNS) are the preferred sources of that specific, just-in-time learning. The North Carolina Native Plant Forum is a regionally specific Facebook group focused on environmental education with over 80,000 members. This case study used 14 forum member interviews and analysis of the Facebook site itself to explore the Native Plant Forum and its users through the lens of the Technologies for Pro-Environmental Actions Model (TPAM). These data revealed a process of information seeking, sharing experiences, obsession, and pro-environmental intentions leading to the planting of native plant species that host and support pollinators and wildlife. Users of the forum expressed how much they learned from the Facebook group and particularly valued the photographs shared daily by other forum members of their native planting projects. The ability of social networking sites to support and incentivize pro-environmental knowledge and behaviors is a critical area of research for adapting environmental education to a new information age and for combating multiple overlapping environmental crises.

Amidst the Covid-19 pandemic, open spaces provided solace for people during social isolation but also heighten risks, particularly in areas lacking proper management. This was especially critical in regions already facing challenges like low human development, extreme poverty, limited healthcare access, as seen in Pará Coastal Zone (NE Brazil). To address this, this study introduced the Pandemic Risk Index (PRI), evaluating Covid-19 risk using demographic, social, economic, and epidemiological indicators. Applied to municipalities in the area, PRI highlighted preexisting vulnerabilities shaping the region’s pandemic response and overall risk. PRI analysis revealed temporal and spatial variations in risk levels, identifying areas where the use of open spaces like beaches, presented a higher transmission risk. The results emphasized the significance of effective governance, improved healthcare, and containment measures, lowers risk levels. affect risk levels, and becomes one of the most important challenges, especially in remote areas with limited services and access.

The current study examined the relationship between creative potential, estimated with tests of divergent thinking (DT) and emotional intelligence (EI). Two DT tests were used, one commonly used to estimate creative potential (Titles Game) and the other focusing on social problems (Social Games). The youth version of the Bar-On Emotional Quotient Inventory ( EQ-i: YV) was used to measure EI. The sample comprised 244 male and female gifted (N = 125) and nongifted (N = 119) high school students in Saudi Arabia. The first objective was to examine whether the EI-DT relationship differs based on the nature of the task of the two DT tests used in the current study (Social Games vs Titles Game). The second objective was to test whether the Interpersonal and Intrapersonal subscales of EI are more associated with DT than the Adaptability and Stress Management EI subscales. Canonical correlation analysis showed that the relationship between the Social Games test and EI was stronger than the relationship between the Titles Game test and EI. Two path analyses were run: one for the total sample and the second for the gifted sample. The likelihood ratio test showed that the Social Games test was more strongly associated with EQ-i subscales than the Titles Game test for both samples. As expected, the Inter and the Intrapersonal subscales of the EQ-i were highly related to Social Games fluency and originality scores compared with Stress Management and Adaptability subscales. Limitations and future directions are discussed.

Yoga promotes acceptance, compassion, physicality, active postures, mental and emotional awareness, and spiritual benefits. It involves breath techniques, postures, and body locks, maintaining balance and strength. It's based on ethical principles. Beyond simple performance, swimming is a catalyst for overall well-being. Complementarily, yoga serves as an invaluable adjunct for swimmers, enhancing flexibility, strength, and body awareness - a triad essential to aquatic excellence. The confluence of yoga and swimming, particularly through the practice of aqua yoga asanas, presents a new paradigm for both athletes and non-performers alike. Athletes who embrace the harmonious fusion of swimming and yoga unearth the potential for achieving not just athletic mastery but also a more balanced and fulfilling lifestyle. This blend provides a route not only to enhance performance in the water but also to elevate the overall quality of life. We examined the feasibility of incorporating yoga and swimming practice into Romanian subjects' lifestyles, designing a factor analysis in SmartPLS software, based on an online survey. The study assesses the participants' knowledge of yoga's theory and philosophy, as well as their perceptions of the swimming practice's benefits for social and health issues. According to our study, Romanian participants practice yoga and swimming as often as possible to reduce stress, improve concentration for work-related tasks, and improve joint elasticity, balance, and muscular tone. Thus, Yoga and swimming are substitutes for other approaches in prevention and therapy.

This study discusses the belonging, position, livelihood sustainability and vulnerabilities of fishery dependent nomadic community of Bangladesh. Nomads in Bangladesh are called as bede. With the technological advancements, infrastructural developments and advancements in medical science, ancient tradition and culture of the nomad’s community are in the verge of extinction. Fishing is found to be the most sustainable livelihood approach for nomadic community than any other professions. The average daily income is up to BDT 700±100 (mean ± standard deviation) during fishing season. Nomad community is a part of Bengali culture, but they are considered as socially backward community. They have faced numerous natural and anthropogenic threats and stressors affecting their traditional occupations and livelihoods which make their life more vulnerable. Natural drivers include climatic catastrophe, storms, winds, cyclone and tides. Anthropogenic drivers included ban period, dependency on single profession (fishing), lack of effective alternative income generating options, economic, social and cultural exclusion in the society. Proper measures should be taken to design the livelihood interventions of nomad fishers. The Government and responsible NGOs should take a holistic approach to livelihood intervention including financial support during the ban period and other unavoidable crises to continue their profession smoothly.

Social isolation and loneliness are major public health concerns and are associated with morbidity and mortality. As this is an increasing issue in older adults, guidance for healthcare providers is a priority. The Canadian Coalition for Senior’s Mental Health (CCSMH) has de-veloped the first Canadian social isolation and loneliness guidelines to help providers recog-nize, assess, and manage social isolation and loneliness among older adults. We review and summarize these guidelines to support healthcare to apply best practices and evidence based care for older adults experiencing social isolation and loneliness.

The growing interest in fair AI development is evident. The ''Leave No One Behind'' initiative urges us to address multiple and intersecting forms of inequality in accessing services, resources, and opportunities, emphasising the significance of fairness in AI. This is particularly relevant as an increasing number of AI tools are applied to decision-making processes, such as resource allocation and service scheme development, across various sectors such as health, energy, and housing. Therefore, exploring joint inequalities in these sectors is significant and valuable for thoroughly understanding overall inequality and unfairness. This research introduces an innovative approach to quantify cross-sectoral intersecting discrepancies among user-defined groups using latent class analysis. These discrepancies can be used to approximate inequality and provide valuable insights to fairness issues. We validate our approach using both proprietary and public datasets, including EVENS and Census 2021 (England \& Wales) datasets, to examine cross-sectoral intersecting discrepancies among different ethnic groups. We also verify the reliability of the quantified discrepancy by conducting a correlation analysis with a government public metric. Our findings reveal significant discrepancies between minority ethnic groups, highlighting the need for targeted interventions in real-world AI applications. Additionally, we demonstrate how the proposed approach can be used to provide insights into the fairness of machine learning.

To identify the effect of frailty on loneliness of older adults receiving home care, considering their socioeconomic and homebound status. This cross-sectional study enrolled 218 individuals aged ≥65 years receiving home-based health services “Help at Home” in the Region of Evrytania, Greece, after an open invitation by Municipality authorities from March to June 2022. Tilburg Frailty Indicator (TFI) was used for the evaluation of frailty, UCLA Loneliness Scale version 3 for loneliness and social isolation was accessed through five questions (living alone, frequency of interaction with children, relatives, friends, and participation in social organizations). The mean age of the participants was 81.48 ± 9.06, 61.9% were female, 54.1% experienced high levels of loneliness (UCLA-3 mean 45.76 ±11.10 [range 20-68]), and 46.3% of the participants identified as socially isolated. Also, 58.3% of the individuals were classified as frail (TFI mean 5.95 ± 3.07, [TFI range 0-13], with 57.3% experiencing physical frailty, 43.6% psychological frailty, and 27.1% social frailty. An analysis of covariance (ANCOVA) placing UCLA-3 as the dependent variable revealed that loneliness and across all domains of TFI were significantly higher in participants with frailty (total frailty [yes] 49.27 vs. [no] 40,87 p &lt;0.001) particularly, (physical frailty [Yes]=48.99 vs. [No]=41.42, p &lt;0.001, psychological: 48.60 vs. 43.57 p &lt;0.001 and social: 53.38 vs. 42.94 p &lt;0.001) compared to non-frail individuals, even after adjusting for potential confounding effects (covariates: gender, age, marital status, family status, living status, educational level, annual income, chronic diseases, homebound status, and social isolation). Our data analysis confirmed that frailty is a significant risk factor for higher levels of loneliness among older adults who received home-based healthcare.

Poverty has long been associated intricately with neurological disorders. Majority of the previous studies designed to describe the effects of poverty on neurological ailments have mostly linked the association of hypoxic ischemic encephalopathy and nutritional deficiency disorders with poverty. Authors herein try to delve deeper into this issue. The association of begging with neuropsychiatric disorders is robust. The burden of probable autosomal dominant neurological ailments is very common among beggars; followed by neurological disorders with social stigma like abnormal movements, facial dysmorphism and gait unsteadiness. Dearth of support from family members in autosomal dominant neurological disorders (as family members are likely to be suffering from similar neurodegenerative disorder ) and poor perception about neurological diseases, misconceptions, myths and low educational attainment at large in the society can be implicated as the often overlooked but important factors underneath this association of begging and neurological disorders.

Businesses use technological and social media marketing to respond to the Covid-19 pandemic. This study aims to understand better the factors that impact the spread of new technologies, the effectiveness of social media advertising, and the longevity of businesses. The study used a quantitative strategy based on partial least squares structural equation modeling to learn about the phenomenon of interest as much as possible. Dhaka, Bangladesh, small and medium-sized businesses participated in the survey. According to the findings, the popularity of internet and e-business technologies may be attributed to their apparent usefulness and ease of use. It is connecting internet/e-business technology, social media marketing, and the long-term success of small and medium-sized enterprises. Still, the expense factor was insufficient to prove that SMEs engage in social media advertising. Mediating effects between components may be better understood via internet/e-business technology and social media marketing, as shown by this study. This study is the first of its kind in Bangladesh and sheds light on the resilience of SMEs in the face of the Covivirus-19 pandemic, notwithstanding its focus on the capital city of Dhaka.

For most people, using social media to research products has become common. Despite previous research, there is a gap in understanding reviewers' product-related comments and how they lead to purchase intentions. In terms of contributions, this study analyses people's dependence on social media for product information in purchase intention while considering the moderating impact of risk and trust on the link between purchase intention and social media. The data were collected quantitatively using surveys. The sample consisted of 384 students. The study hypotheses were tested using the PROCESS macro after exploratory factor analysis and correlation analysis were conducted. Among those surveyed, it was confirmed that most people sought product-related comments on social media when seeking information about a product they might be interested in purchasing. It was also observed that the risk factor reduced the impact of other variables in the model presented in this study. In conclusion, this investigation is more reliable, and its outcomes benefit scholars, supervisors, merchants, and webmasters, for instance, in establishing a study for future research efforts and providing practical guidance that could boost promotional efforts and marketing activities, especially in this era of artificial intelligence.

Public housing stock, called Social Housing, in Italy developed between the 1950s and the 1980s. As of today, the first residential developments are almost nearing their end-of-life age, in need of urgent and intensive renovation. The European Commission, with the Renovation Wave, has set a goal of doubling the rate of building renovation over the next 10 years, reducing emissions, improving energy performance, and promoting decarburization. Renovation interventions, including structural, functional, energy, plant upgrading, etc., are to be preferred over integral demolition and reconstruction interventions, which have significant repercussions in terms of managerial and social discomfort. The case studies examined concern renovation interventions aimed at energy efficiency, functional adaptation of housing as well as facade restyling. The design variants analyzed were evaluated in terms of CO2e emissions, according to LCI (Life Cycle Inventory) and EPD (Environmental Product Declaration) approaches. This approach has a twofold purpose: to propose design guidelines, with low CO2e emissions, through hypotheses of variants to the case studies, and to propose, to the Economic Operators, economically advantageous bidding scenarios, in the procurement process.

This study examines the effectiveness of a comprehensive psychomotor development program combined with adapted football training for adolescents diagnosed with intellectual disabilities in Romania. Twelve participants, with a mean age of 17.42 years underwent a carefully designed intervention program spanning 36 weeks. The program aimed to enhance fundamental movement skills, integrate these skills into specialized football training, and culminate in a Unified 7-a-side Football Match. Results indicate significant improvements in psychomotor skills, including static and dynamic balance, pulse processing speed, and identified stimuli. Moreover, the intervention positively impacted social interaction among participants. Statistical analysis, employing Pearson Correlation Analysis and Paired Samples t-Test (One-Sample), compared assessments. Results revealed significant differences between pre- and post-intervention measurements, providing robust evidence of the program's efficacy. The positive correlations between physical parameters and social interaction highlight the interconnectedness between physical fitness and social engagement. Our findings suggest that improvements in physical abilities may contribute to increased social interaction among children with intellectual disabilities, underscoring the holistic nature of our intervention, which addresses multiple dimensions of development simultaneously. The findings underscore the holistic benefits of integrating psychomotor development and adapted football programs for adolescents with intellectual disabilities, emphasizing the importance of promoting inclusive physical activities for their overall well-being.

In order to achieve the elimination of the negative impacts of transport on road safety, the European Union is taking various measures resulting from its commitment to improve road safety. One of the instruments for achieving the objectives set is social legislation for the work of drivers in road freight and passenger transport. In line with the objective of improving the quality of working conditions for road transport drivers and road safety, the European Union applies Regulation (EC) No 561/2006 on the harmonisation of certain social legislation relating to road transport, which lays down rules on driving times, breaks and rest periods for drivers operating in road freight and passenger transport. The main objective of the paper is to assess the impact of social legislation on road transport safety by means of real research and to identify the factors influencing the violation of the legislation depending on the type of transports carried out in domestic or international road freight transport.

Nurses have experienced several psychological and work-related issues during the COVID-19 pandemic including pandemic burnout and job burnout. The aim of the study was to examine the impact of social support and resilience on COVID-19 pandemic burnout and job burnout among nurses. We conducted a cross-sectional study in Greece. Study population included 963 nurses. We measured social support, resilience, COVID-19 pandemic burnout, and job burnout with the Multidimensional Scale of Perceived Social Support, Brief Resilience Scale, COVID-19 burnout scale, and single item burnout measure respectively. Nurses received high levels of social support, while their resilience was moderate. Additionally, nurses experienced moderate levels of COVID-19 burnout and job burnout. Increased social support (adjusted beta = -0.075, 95% CI = -0.125 to -0.024) and increased resilience (adjusted beta = -0.399, 95% CI = -0.491 to -0.308) were associated with reduced COVID-19 pandemic burnout. We found a negative relationship between social support and job burnout (adjusted beta = -0.263, 95% CI = -0.405 to -0.121). A similar negative relationship was found between resilience and job burnout (adjusted beta = -0.529, 95% CI = -0.785 to -0.272). Social support and resilience can act as protective factors against COVID-19 pandemic burnout and job burnout among nurses. Policy makers should develop and implement appropriate strategies to improve nurses’ social support and resilience since they are the backbone of healthcare systems worldwide.

This paper presents how social media platforms and their components could be integrated into the KMS for the purpose of managing and sustaining Somali Indigenous knowledge (IK). The discovery of knowledge and its utilization is now fuelled by the advancement of technology, which connects users to external sources through using different platforms. The rapidly increasing use of SM and mobile technologies create opportunities to form knowledge networks that can facilitate the process of creating, preserving, and sharing knowledge and skills that are unique to communities in the Somali context. Somali society being an oral society with rich IK and other cultural practices lacked a framework in place to organize the existing knowledge in various methods. The paper refers to existing methodology E-learning and KM functions. This method first identifies functional similarities between SM, E-Learning, and KM systems and their interactions if they are properly integrated. The proposed framework consists of two functional parts; KM and SM. The KM part involves knowledge capturing, validation, formatting, storing, and distribution. SM part of the framework involves knowledge presentation, sharing, and application. Since the Somalis are said to be an oral society, this framework helps to capture and disseminate IK residing in knowledge holders.

On February 28, 2023, the Facebook page of the United Nations Children's Fund (UNICEF) South Africa, announced the beginning of the HPV vaccination campaign for 2023. The aim of this study was to examine the attitudes of Facebook users, who commented on the UNICEF South Africa post, towards HPV vaccination to inform the development and implementation of interventions that can increase HPV vaccine acceptance and uptake. Several comments were questions regarding the eligible criteria for vaccination, side effects, consent form, and vaccination strategies. Many Facebook users were hesitant towards HPV vaccination due to various reasons including concerns around side effects, religious beliefs, vaccine stock outs, and their distrust in the institutions or systems involved in vaccination programmes. Few users accepted HPV vaccination because they believed that it was very important thing to do, beneficial for the children’s health, and they have vaccinated they children before. Our findings of the current study contribute to the promotion of acceptance and uptake of HPV vaccination by developing and implementing interventions tailored to address identified barriers that are associated with hesitant to HPV vaccination.

The high demands of caring for and raising a child with autism spectrum disorder on a daily basis fatally lead parents to the appearance of physical and mental fatigue. This study aimed to assess the effect of social support and spirituality on the fatigue of parents with children with autistic spectrum disorder. A cross-sectional study with a convenience sample was conducted in Schools of Special Education in Attica (Greece). The sample consisted of 123 parents who completed The Fatigue Assessment Scale (FAS), the Multidimensional Scale of Perceived Social Support (MSPSS), and the Functional Assessment of Chronic Illness Therapy Spiritual Well-Being Scale (FACIT Sp-12) to measure the levels of fatigue, social support, and spirituality, respectively. Demographic data were, also, recorded. Data analysis was applied using IBM SPSS 21.0. The mean age was 47.3 years old, 81.3% were women, and 38.9% stated much / very much religious. The mean of total FAS was 28.4 (SD±7.5), of total FACIT Sp-12 was 31.5 (SD±8.7), and of total MSPSS 5.1 (SD±1.1). Higher levels of total MSPSS and FACIT Sp-12 were associated with lower total FAS (r= -0.50, p &lt;0.001 and r= -0.49, p&lt;0.001 respectively). Social support and spirituality are significant predictors of fatigue.

The essay focuses, from a sociological perspective, on the phenomenon of depopulation of Inner Areas in Italy. In this areas, younger generations, live a great inequality that exposed them to risk of social vulnerability. So, on the one hand, the desire to leave their community is growing among younger, on the other hand, the desire to deal with extreme adverse conditions is falling down. The research aims to explore the depopulation phenomenon in the context of Southern Italy, considering it as an emerging social vulnerability that impacts very deeply onto the sustainability of a social, economic and community systems such as the Molise region one. The following paper therefore presents an empirical web-survey conducted in the Molise region. The methodology used is Quantitative, and the research design is Exploratory. The essay underlines how proximity welfare can act as a flywheel to counter the depopulation Inner Areas of Italy enacted by the younger generations.

Oxytocin is well known for its role in relationships and social cognition and has more recently been implicated in pain relief and pain perception. Connections between prosocial feelings and pain relief are also well documented, however, effects of exogenous oxytocin on social cognition and pain have not been explored. The current study tested whether intranasally-delivered oxytocin affects pain perception through prosocial behaviors. Additionally, moderation of the effects of oxytocin by life history or genetic polymorphisms are examined. Young adults (n=43; 65% female) were administered intranasal oxytocin (24 IU) or placebo in a crossover design on two visits separated by a one-week washout period. Pain was delivered via cold-pressor. Baseline measures for decision-making and social cognition were collected, as well as pain sensitivity and medication history. Saliva samples were collected for analysis of genetic markers, and urine samples were collected to assess oxytocin saturation. Following oxytocin administration, participants reported increased prosocial cognition and decision-making. Pain perception appeared to be adaptive, with procedural order and expectation affecting perception. Finally, behavioral trust and cooperation responses were significantly predicted by genetic markers. Oxytocin may increase a patient’s trust and cooperation and reduce pain sensitivity while having fewer physiological side effects than current pharmaceutical options.

This study applies several natural language processing techniques for characterizing social groups by analyzing published text in social media. The resulting computed values are proposed as features for modeling social groups and measure distances or similarities among them, along further data that could help understanding group behavior according to language usage. In this study, we have analyzed the messages published on Twitter regarding patriotism by the main political parties in Spain. The results show that lexical resources and topic modelling algorithms are useful to model different groups and serve as comparison tools to better understand the topics these groups are talking about.

This article belongs in the emerging area of research seeking ways to depolarize societies in the short run (around events such elections) as well as in a sustainable fashion. We approach the depolarization process with a model of three homophilic groups (US Democrats, Republicans and Independents interacting in the context of upcoming federal elections). We expand a previous polarization model, which assumed that each individual interacts with all other individuals in its group with mean-field interactions. We add a depolarization field which is analogous to the Blume-Capel model’s crystal field. There are currently numerous depolarization efforts around the world, some of which act in ways similar to this depolarization field. We find that for low values of the depolarization field, the system continues to be polarized. When the depolarization field increases, the polarization decreases.

With the changing relationship between urban and rural areas in China, the rural areas are experiencing rapid social transformation. To ensure successful implementation of the rural revitalization strategy, land consolidation has become a major measure of rural economic reform. Existing research focuses on quantitative studies exploring the relationship between land consolidation and rural economic development, but there is a lack of studies on the relationship between land consolidation and social change. In this study, Jin’an Village is selected as the research area, using semi-structured interviews and semi-participatory observation to obtain original materials, aiming to make a detailed description of the specific practice of land consolidation, and to analyze the impact of land consolidation on the transformation of rural social consciousness. The study found that rural land consolidation involves villagers in the land consolidation process, which can effectively stimulate villagers’ participation in public affairs. Concurrently, the interaction between villagers and outside investors disrupts the conventional socialization model in rural areas and motivates villagers to act in accordance with contractual agreements. The conclusion is that land consolidation in rural areas can enhance the political democracy and legal consciousness of local villagers, which can lead to a change in local social consciousness. Our findings also emphasize the crucial necessity to grant rural villagers with improved accessibility to professional services and information, coupled with the continued promotion of land consolidation to advance modernization in these areas.

This article addresses the socioeconomic gradient in immigrant health by exploring immigration status and social capital as key considerations in measurement and development of health-promoting research and practice. This paper also seeks to draw attention to the importance of understanding how researchers approach the study of health disparities affecting minoritized and immigrant populations. A critical examination of the measures used in comparative health research challenges scholars to consider the different pathways through which socio-economic factors impact health and underscores the ethical commitment of health disparities researchers to consider the relevance and implications of their work. Given the reliance on existing data from national population health surveys to test the assumptions of the immigrant paradox, any immigrant-specific measure of SES with limited application to a large, representative sample of immigrants would likely hold little appeal to both researchers and practitioners. Understanding the mechanisms through which socioeconomic status influences immigrant health can allow scholars to address the needs of immigrant populations and advocate more effectively for programs and policies that seek to advance the health of all people.

This paper examines the condition of the Scheduled Castes in India and recognizes the factors that are causing dismal performance of the Scheduled Castes despite reservation policies. The paper first discusses the condition of Scheduled Castes based on the parameters of social, economic, education, and political representation. It then provides a brief overview of the current reservation percentages allocated to Scheduled Castes in various sectors. Moreover, the paper explores the causes for the dismal performance of Scheduled Castes despite the existence of reservation policies. In order to improve the condition of Scheduled Castes, the paper proposes a multifaceted approach, including the consideration of socio-economic criteria for recognizing castes in the list of Scheduled Castes, dis reservation of affluent Scheduled Caste families, preferential appointment of Scheduled Castes in administrative positions within Scheduled Areas, and reforms within the National Commission for Scheduled Castes. The paper also emphasizes the importance of periodic evaluations of socioeconomic conditions, talent identification, and grassroots awareness campaigns as strategies to uplift the Scheduled Castes.Keywords

Healthcare workers have atypical working schedule and are exposed to experienced stress that led to poor sleep health and frequent mental complaints, particularly since the Covid-19 crisis. We conducted a cross-sectional study to determine the prevalence of poor sleep hygiene and mental complaints and their associations among healthcare workers. Usual sleep-wake timings were ex-plored during workdays and free days and used to compute sleep duration, sleep efficiency and social jetlag. Insomnia, sleepiness, anxiety and depressive symptoms, and fatigue were calculated using validated scales. A total of 1,562 participants were included (80.5% of women and mean age of 40.0). Among them, 25.9% slept less than 6 hours, 24.3% had a poor sleep efficiency, and 11.5% reported a social jetlag. A total of 33.9% of participants reported insomnia, 45.1% reported EDS, 13.1% reported fatigue, 16.5% reported depression and 35.7% reported anxiety. After ad-justment, sleep duration and sleep efficiency were associated with mental complaints. Social jetlag was associated with significant insomnia but not with anxiety or depression symptoms. Healthcare workers have a high prevalence of poor sleep hygiene and mental complaints. The promotion of sleep health through behavioral sleep strategies should be encouraged to ensure good health for these professionals.

Abstract—Annually, approximately 500,000 Merger and Ac- quisition (M&A) transactions are disclosed globally, each trans- action inciting substantial perturbations to the associated com- panies’ equity prices. The probability of an M&A transaction’s closure, as perceived by the public, inherently influences the stock price of the target company leading up to the proposed date of the deal. Given the recent advancements in the realm of Natural Language Processing (NLP), we propose an empirical investigation into the correlation between digital dialogue sur- rounding M&A transactions and consequent movements in the stock prices of involved companies. Utilizing transformer-based encoder-only architectures, we fine tune a stance detection model on an extensive dataset, amassed from digital communication platforms, featuring public discourse related to five historical M&A transactions. Ultimately, we achieved 70% accuracy on deal-completion stance detection using the Roberta-base model. We subsequently employ the aggregated the public sentiment towards the completion or termination of a proposed M&A transaction to model stock price movement. Utilizing a multitude of time-series based approaches, we achieve a mean absolute error of 2.29 USD for next-day price prediction and 3.40 USD for next-week price prediction. Ultimately, we find an existing but tenuous relationship between online discourse and the price trajectory of target companies, ultimately highlighting the complex social and economic phenomena behind M&A deals.Index Terms—Mergers and Acquisitions, Stock prediction, su- pervised learning, neural networks, Recurrent Neural Network, LSTM, stance detection, transformers

Type I contextuality or inconsistent connectedness is a fundamental feature of both the classical as well as the quantum realms. Type II contextuality (true contextuality or CHSH type contextuality) is frequently asserted to be specific to the quantum realm. Nevertheless, evidence for Type II contextuality in classical settings is slowly emerging (at least in the psychological realm). An example is given here of Type II contextuality involving a simple cooperative game. This arises due to the cooperative nature of the game which results in sign intransitivity for expectation values while individual random variables remain consistently connected. This shows that the conditions attributed uniquely to quantum systems may occur in classical settings as well. Sign intransitivity can be observed in preference relations in the setting of decision making and so intransitivity in decision making may also yield examples of Type II contextuality. Previously it was suggested that a fruitful setting in which to search for such contextuality is that of decision making by collective intelligence systems. An experiment was conducted using a detailed simulation of nest emigration by workers of the ant Temnothorax albipennis. In spite of intransitivity, these simulated colonies came close to but failed to violate Dzhafarov’s inequality for a 4-cyclic system. Further research using more sophisticated simulations and experimental paradigms is required

Repeated fires cause peatlands to degrade. Fire management has been carried out, but fires continue to occur, especially during the dry season. Through social capital that applies in the community based on the local wisdom of the Banjar people in environmental management, it is hoped that peatland fires can be overcome in this area. This research aims to analyze the social capital of the Banjar people in mitigating land fires based on local wisdom and the environment. The sample in this study was 250 people who live in an area prone to fires on peatlands in Banjarbaru, South Kalimantan, Indonesia. There are three variables in this study, namely Trust (T), Network (N) and Norm (N). There are 33 Likert scale questions (1-4, strongly agree-strongly disagree). We also conducted interviews with 20 members of the Fire Care Community (MPA) to obtain information about the social capital of the Banjar community in mitigating land fires. The analysis used is Structural Equation Modeling (SEM). The study results show norms have the greatest influence on disaster mitigation of peatland fires compared to trust and social networks. Norms in the community in the form of values from peatlands, rules, norms and sanctions regulate the community more to deal with the problem of peatland fires than trust and social networks

This research objective was to develop a promoting vegetable and fruit consumption behaviors program among preschool children based on 4 aspects of House’s social support framework to increase fruit and vegetable consumption in preschool the program. This study was quasi-experimental. The sample consisted of preschool children and their caregivers who were randomly selected based on the inclusion criteria. The experimental and control groups had 96 pairs of preschool-aged children and their caregivers. The experimental group was given the program, while the control group was to resume normal activities. The program development was based on the caring lifestyle of caregivers in Muang District, Nakhon Si Thammarat Province. The tools consisted of a preschool care eating behavior assessment and a caregiver knowledge test about the child's fruit and vegetable intake and how to modify the child's fruit and vegetable intake. In addition, fruit and vegetable eating behaviors in preschoolers and a handbook for nurses and primary caregivers were approved by five experts and deemed suitable for the caregiver support framework. The results of the development indicated that a 10-week program was appropriate and tended to increase preschoolers' consumption of fruits and vegetables. In especially experimental group both caregivers increasingly gained knowledge and behavior of caregivers to promote fruit and vegetable eating behavior and preschool increasing the fruit and vegetable consumption.

The relationship between child psychology and the widespread usage of mobile devices in the modern day is examined in "The Mobile Dilemma: Child Psychology and the Era of Technological Dependence." The abstract serves as a brief synopsis of the work, highlighting its important ideas and arguments. Concerns concerning the effects of excessive time spent on mobile devices on children's mental health and development have arisen in this age of technology dependency. The essay opens by pointing out the importance of investigating the psychological effects of kids' exposure to mobile gadgets. The effects of mobile phone addiction on learning, memory, and social and emotional health are investigated. The neurodevelopmental implications are explored further in the abstract, with a focus on the impact of mobile technology on brain plasticity and the formation of the developing brain. It offers advice on how to establish appropriate limits for children's screen time, encourages the development of digital literacy, and promotes responsible behavior.The pros and cons of using mobile devices in the classroom are also examined, along with their effects on students' ability to study and the risks and difficulties that could arise from implementing such a strategy. The emotional and social impacts of mobile device addiction are discussed in the abstract. This includes the impact on one's social life, empathy, ability to communicate, and sense of self-worth. The abstract also stresses the importance of interdisciplinary efforts involving parents, teachers, psychologists, and legislators to combat mobile device addiction through intervention and preventative techniques. Future directions are highlighted, with a focus on topics such as mobile technology development, digital well-being, privacy protection, mental health implications, screen time limits, digital literacy, and the impact of cultural and socioeconomic variables.

Community co-creation is increasingly crucial to the building of sustainable societies. Communities must proactively and independently create value chains in the face of many wicked problems. However, practical frameworks and tools for facilitating community co-creation require further development. As such, for this paper, we propose a theoretical framework for analyzing community co-creation value chain mechanisms based on a narrative review of literature on Collective Impact, social impact assessment, and Community Capital from the perspective of collective impact, a framework with a fair amount of previous research. We argue for the importance of applying knowledge of social impact assessment, particularly for the collective impact conditions of common agenda and shared measurement system. We discuss its relationship with the Theory of Change and the use of systems thinking to mitigate the subjectivity and arbitrariness of design thinking. Furthermore, we emphasize the value of employing the community capital concept as a framework for analyzing interrelationships among elements. By integrating multiple concepts, we enhance the collective impact framework and outline potential avenues for future research on analyzing and effectively implementing co-creation value chain mechanism in a community-based approach.

This systematic review seeks to position online radicalisation within whole system frameworks incorporating individual, family, community and wider structural influences, whilst reporting evidence of public mental health approaches for individuals engaging in radical online content. Methods: Authors searched Medline (via Ovid), PsycInfo (via Ebscohost) and Web of Science (Core Collection), with the use of Boolean operators across ‘extremism’, ‘online content’, and ‘intervention’. Results: Following assessment of full text, all retrieved papers had to be excluded. Results from six excluded articles which did not fit inclusion criteria but identified theoretical relationships between all three elements of online extremism, psychological outcomes, and intervention strategy, were discussed. Authors found no articles outlining public mental health approaches to specifically online radicalisation. Conclusions: There is an immediate need for further research in this field given the increase in different factions of radicalised beliefs resulting from online, particularly social media, usage.

This article investigates the impact of the foreign background of women directors on a firm’s corporate social responsibility (CSR) disclosure and performance. Using a dataset on listed firms on Shanghai and Shenzhen stock exchange from 2010 to 2019, we find that corporate boards with a higher proportion of women directors with foreign education experience tend to disclose more CSR information. CSR performance is also improved when there is a greater proportion of women directors with foreign education and work experience on a board. This study provides new insights into integrating stakeholder, social role, and neo-institutional theories to advance the understanding of CSR engagement in emerging economies.

This research aims to produce a network structure in the Integrated Urban Farming Program in Bandung City to map the policy actors involved in it as an effort to support food security in the city. This research uses a mixed method with an exploratory sequential strategy involving policy actors from the government, private sector, academia, community, and mass media. To obtain the network structure in integrated urban farming to determine the most important actors, this research uses a social network analysis approach by utilizing the Gephi application. The network structure is based on four dimensions, namely centrality. The results of this study confirm that the actor who has the most connections (degree centrality), as well as the one who holds the best communication control (betweenness centrality), is Parahyangan Catholic University (Academic). While the actor who plays the most important role (eigenvector) is at the lower level of the government Sub-District and Urban Village. This research is useful for explaining the importance of the position of actors in the urban agriculture policy network which is the key to the success of a program.

This article aims to provide a comprehensive understanding of vaping from various perspectives that contributes to the origin, development, achievement, and consequences of the greed of e-cigarette manufacturers. In our analysis, multiple elements of the social landscape, including economic, cultural, moral, psychological, and philosophical dimensions, contributed to the origin and development of the vaping greed and shaped people’s behaviors. Further discussion was made on how the specific characteristics of e-cigarette products and the marketing strategies of the companies, especially social media marketing, fostered the growth of such greed. Through interviews, we have also discussed the unfolding of this greed within the community of teenage vapers. The growth of the vaping greed was manifested in the large market share taken by the companies, but these all significantly harm people’s health and the communities. Nicotine and other chemicals in e-liquids promote each other’s negative effects in the mechanism leading to pulmonary symptoms and addiction, which are not limited to the physical level. We described that addiction could be transgenerational and can induce trauma both at an individual level and a community level. Overall, the greed of the vaping industry is a very complex system. The treatment of the greed shall be complicated as well: Besides the public health measures taken to treat the symptoms of the greed, we should educate individuals to be aware of their unfulfilled needs to regain authenticity and establish an infallible authority to enforce universal morality, which eradicates the complications of addiction and the root of the capitalists’ greed, respectively.

Social media has revolutionized the way we communicate and interact with each other. While it has brought many benefits, it has also presented many ethical challenges. Social media platforms have access to an enormous amount of personal data, and there are concerns about how this data is being stored, collected, and used. Users often need to fully understand the risks of sharing sensitive information. Social media platforms have made it easy for fake news to spread rapidly, which can be dangerous and have serious consequences. Misinformation and propaganda can influence people's decisions and beliefs. In this paper, we will analyze the issues and challenges that may arise, and it will be necessary for individuals and society to address these challenges ethically and responsibly.

The territory of Serbia is vulnerable to various types of natural and man-made disasters. The risk is not equal across the entire territory, depending on the type of hazard and the expected potential for damage. So far, the level of community disaster resilience has not been determined in Serbia. There are no scientific preconditions for its improvement to reduce the future material and intangible consequences of disasters. Regarding that, the project’s main objective is to develop and validate a predictive model of community disaster resilience based on social identity influences through an investigation impact of social identity indicators on the level of community disaster resilience in Serbia. The project is based on the upcoming research on whether the level of community disaster resilience can be predicted based on social identity indicators, how social identity indicators affect different dimensions of community disaster resilience, and how disasters shape social identity. The project is based on multimethod research in which quantitative (face-to-face interviews in 40 of the 191 municipalities), and qualitative (semi-structured interviews) research methodology will be applied. A developed predictive model with an index of community disaster resilience in Serbia will empower the creation of preconditions for designing public policies, strategies and procedures for improving resilience and reducing the consequences of disasters on people and their property and enhancing citizens’ security. The project will encourage the prediction of community disaster resilience based on social identity indicators, improving disaster foresight and preparing to limit disaster losses. Based on the development of analytical frameworks for understanding community disaster resilience and social identity in disasters, essential preconditions for designing innovative information systems will be created to enable local communities to increase their level of resilience.

Social media informs the public about the most important events and conveys important information. Before, during and after disasters, social media are used to disseminate information about disasters and to collect data relevant to the implementation of preparedness, response and recovery activities and measures. Social networks are effective in disseminating information and warnings, as well as in educating the public. The subject of the research is examining the influence of demographic factors on the effectiveness of social media in informing the public about the risks of disasters. Using an online survey questionnaire, and according to the snowball principle, a survey of 247 respondents was conducted in 2022. The research results show no statistically significant relationship between the level of education of the respondents and the assessment of the effectiveness of social media reporting on disasters. The use of social media can improve communication between stakeholders in disaster management and facilitate coordination of efforts, fostering communication and allocation of resources. To effectively use social media in disaster management, decision-makers in the disaster management system must be aware of new technologies, their disadvantages and advantages, as well as ways in which data from social networks can be collected and analyzed.

Introduction: The application of the concept of self-regulation that has an impact on the psychological well-being of adolescent social media users as self-regulation in a core aspect of human functioning that helps facilitate the successful pursuit of personal goals and adaptability to changes in the environment. This literature aims to determine the study of the psychological well-being philosophy of adolescent social media users based on self-regulation.Methods: This literature study was conducted through a search for scientific publications ranging from 2018-2022. The databases used are PubMed, Science Direct, and ProQuest. The literature search was carried out according to topics with four groups of keywords based on Medical Subject Heading (MeSH) and combined with Boolean operators AND, OR and NOT, keywords Self-regulation AND mental wellbeing AND social media AND adolescence.Results: A study of the psychological well-being of adolescent social media users based on self-regulation based on ontology, epistemology, and axiology studies. Self-regulation is a philosophy that emphasizes the dynamic process that directs the behavior of a teenager towards the desired final state and adapts to changes that occur in the surrounding environment. The adaptation process is carried out as a form of self-regulation of the positive and negative impacts of using social media on adolescents with a motivational approach and avoidance system. The approach motivation system is carried out if it provides positive aspects in social media. While avoidance motivation is carried out if it has a negative impact in the form of low self-esteem, depression, and body image disturbances as a result of social comparisons made by teenagers when they see other people's posts.Conclusion: The concept of psychological well-being of adolescent social media users based on self-regulation is beneficial for parents to improve the parenting pattern of adolescent children. Good parenting is needed in understanding the positive and negative impacts of using social media and reducing externalization problems in adolescents.

Social sustainability is the major concern of planners and local officials when urban renewal projects are being conducted. Extreme individualism can potentially cause conflicts of interest, making urban renewal in Western cities fraught with various types of social risks. As a country with deep-rooted socialist tradition, urban renewal projects in China are influenced by collectivist culture and show different features from those of the West. The objective of this research is to investigate how different stakeholders in urban redevelopment projects, including local residents, social organizations, the local state, and developers, interact with each other and how the associated social risks are hedged against. Using a recent well-known project in the city of Guangzhou, the authors attempt to present the latest progress in social risk management in China. With the support from a government-sponsored project, the authors have conducted a questionnaire-based survey and year-long follow-up fieldwork. Using ATLAS.ti software, we found that that “residents’ demand”, “status of collaboration”, and “degree of trust” are the keys to risk management. The results of an ordered probit model show that residents are worried about the overall planning, the relocation timetable, and whether their personal needs are taken into account. It is also indicated that the timely disclosure of project information, high-quality public participation, and a reasonable compensation plan can possibly boost the support rate. The authors suggest that utilizing China’s collectivist culture could be an effective way to mitigate social risks, and residents’ personal interests should also be respected.

This research paper describes the social engineering concepts, techniques, and security countermeasures. This research aims to study various social engineering techniques to find the best countermeasures that would help to reduce social engineering attacks.

The potential of social networks for the circulation of disinformation as a strategy of diplomacy has been of great interest to the academic community, but the way in which it is propagated and modelled is still in its beginnings. This article aimed to simulate the propagation of disinformation in social networks derived from the diplomacy strategy, based on the elements of the system. For the design of the simulation model, system dynamics was used as the main technique in the research methodology in conjunction with statistical analysis. Five computational simulations were run for the adoption methods of susceptible and uninformed population, misinformation techniques and echo chamber. The developed model found that the diplomacy disinformation agent is able to spread its message efficiently through the bot outreach mechanism and only a part of the susceptible population unsubscribes to the disinformation agent's account. Significant differences were identified in the absence of paid outreach, bots and trolls in the propagation of information, and in the variation in the timing of disinformation propagation. Consequently, the developed model allows the understanding of the problem of disinformation as a strategy of diplomacy from international rather than local dynamics, as well as the effects of the use of each element in the system.

Automated software bots infiltrate online surveys and corrupt data integrity, not to mention waste researcher time and budgets. Although resources exist to help keep bots out and identify bots when they do evade survey barriers, bot attacks may be a persistent problem for online surveys for a long time to come. Bots are evolving -- even as survey designers try ever more sophisticated methods to fend them off and weed their answers out. Vigilance needs to be high and the bot generators should not be under-estimated. We recount here some bot features we encountered after our own survey was attacked that helped to identify them, and that have not been detailed elsewhere. We also discuss reasons why commonly recommended strategies for how to keep bots out may not be feasible for many scientific researchers.

Based on the data of A-share listed companies in Shanghai and Shenzhen of China from 2011 to 2018 and the digital inclusive finance index of Peking University (2011-2018), this paper empirically tests the impact of digital finance development on corporate social responsibility in various provinces of China and its impact mechanism. The results show that: (1) the development of digital finance helps to promote the fulfillment of corporate social responsibility; (2) the influence mechanism of the development of digital finance to promote the fulfillment of corporate social responsibility lies in that it reduces the cost of debt financing and leads to the improvement of corporate social responsibility.(3) Further research shows that the positive relationship between digital finance and corporate social responsibility is more significant in private enterprises. At the same time, the impact is more significant in areas with poor market environment. The above research shows that the development of digital finance has a significant positive effect, which will improve the level of corporate social responsibility.

After the first weeks of vaccination against the SARS-CoV-2, several cases of acute thrombosis were reported. These news reports began to be shared frequently across social media platforms. The aim of this study was to conduct an analysis of Twitter data related to the overall discussion. Data was retrieved from 14th March to 14th April using the keyword ‘blood clots’. A dataset with n=266,677 tweets was retrieved, and a systematic random sample of 5% of tweets (n=13,334) were entered into NodeXL for further analysis. Social network analysis was used to analyse the data by drawing upon the Clauset-Newman-Moore algorithm. Influential users were identified by drawing upon the betweenness centrality metric. Text analysis was applied to identify the key hashtags and websites used at this time. More than half of the network was comprised of retweets and the largest groups within the network were broadcast clusters where a number of key users were retweeted. The most popular narratives were around highlighting the low risk of obtaining a blood clot from a vaccine and highlighting higher blood clot risks in medicines commonly consumed. A wide-variety of actors drove the discussion on Twitter ranging from writers, physicians, the general public academics, celebrities, and journalists. Twitter was used to highlight the low potential of obtaining a blood clot from a vaccine and encouraged vaccinations among the public.

This study analyses the papers published by Spanish social psychologists to determine whether they address topics related with the Sustainable Development Goals (SDGs). Publications by Spanish institutions indexed by the Web of Science in the thematic category of “Social Psychology” were subjected to bibliometric analysis. The publications were classified by their relationship with the SDGs using OSDG, an open-source labelling tool, and an in-depth content analysis was performed to validate the results. A corpus of 1632 papers published by Spanish institutions between 1980 and 2020 was identified. Thirty-four percent of the papers address matters related with the SDGs; 23 % concern matters related with Goal 3 (good health and well-being), and 5 %, with Goal 5 (gender equality). Only 3 % are interventions to modify behaviour or change social environments. Conclusions: The review of these papers allows detecting to what extent the research conducted in Social Psychology contributes to achieving the goals proposed in each of the SDGs. Also, the content analysis of this publications identifies several factors (cognitive, emotional, social or cultural) which should be investigated to improve knowledge on how to achieve the Sustainable Development Goals.

The spread of ideas is a fundamental concern of today’s news ecology. Understanding the dynamics of the spread of information and its co-option by interested parties is of critical importance. Research on this topic has shown that individuals tend to cluster in echo-chambers and are driven by confirmation bias. In this paper, we leverage the active inference framework to provide an in silico model of confirmation bias and its effect on echo-chamber formation. We build a model based on active inference, where agents tend to sample information in order to justify their own view of reality, which eventually leads to them to have a high degree of certainty about their own beliefs. We show that, once agents have reached a certain level of certainty about their beliefs, it becomes very difficult to get them to change their views. This system of self-confirming beliefs is upheld and reinforced by the evolving relationship between agent's beliefs and its observations, which over time will continue to provide evidence for their ingrained ideas about the world. The epistemic communities that are consolidated by these shared beliefs, in turn, tend to produce perceptions of reality that reinforce those shared beliefs. We provide an active inference account of this community formation mechanism. We postulate that agents are driven by the epistemic value that they obtain from sampling or observing the behaviors of other agents. Inspired by digital social networks like Twitter, we build a generative model in which agents generate observable social claims or posts (e.g. `tweets') while reading the socially-observable claims of other agents, that lend support towards one of two mutually-exclusive abstract topics. Agents can choose which other agent they pay attention to at each timestep, and crucially who they attend to and what they choose to read influences their beliefs about the world. Agents also assess their local network’s perspective, influencing which kinds of posts they expect to see other agents making. The model was built and simulated simulated using the freely-available Python package pymdp. The proposed active inference model can reproduce the formation of echo-chambers over social networks, and gives us insight into the cognitive processes that lead to this phenomenon.

Online social networks (OSNs) play an integral role in facilitating social interaction; however, these social networks increase antisocial behavior, such as cyberbullying, hate speech, and trolling. Aggression or hate speech that takes place through short message service (SMS) or the Internet (e.g., in social media platforms) is known as cyberbullying. Therefore, automatic detection utilizing natural language processing (NLP) is a necessary first step that helps prevent cyberbullying. This research proposes an automatic cyberbullying method to detect aggressive behavior using a consolidated deep learning model. This technique utilizes multichannel deep learning based on three models, namely, the bidirectional gated recurrent unit (BiGRU), transformer block, and convolutional neural network (CNN), to classify Twitter comments into two categories: aggressive and not aggressive. Three well-known hate speech datasets were combined to evaluate the performance of the proposed method. The proposed method achieved promising results. The accuracy of the proposed method was approximately 88%.

Background: Caregivers often use the internet to access information related to stroke care to improve preparedness, thereby reducing uncertainty and enhancing the quality of care. Method: Social media communities used by caregivers of people affected by stroke were identified using popular keywords searched for using Google. Communities were filtered based on their ability to provide support to caregivers. Data from the included communities were extracted and analysed to determine the content and level of interaction. Results: There was a significant rise in the use of social media by caregivers of people affected by stroke. The most popular social media communities were charitable and governmental organizations with the highest user interaction – this was for topics related to stroke prevention, signs and symptoms, and caregiver self-care delivered through video-based resources. Conclusion: Findings show the ability of social media to support stroke caregiver needs and practices that should be considered to increase their interaction and support.

Early detection that results in early warning of forest fires occurrences in Indonesia, which are strongly related to land management practices (including peatlands), is necessary to mitigate land and forest fires in Indonesia. Riau has been chosen in this study because of its vulnerability to forest fires. The remoteness of this region is one reason for developing alternative warning tools using meteorological and social media information. This study identified tweets related to fires using carefully selected keywords, geoparsed to select messages relevant to fire occurrences, and binned within several Indonesian sub-regions in Riau Province. Content analysis was performed for 31 related online local newspapers. Assessment to study the correlation between meteorological and Twitter information with the forest fires was conducted. Existing approaches that the BMKG and other Indonesian agencies use to detect fire activities are reviewed, and a novel approach based on crowdsourcing of tweets is proposed. The results show a correlation between meteorological information and Twitter activity with satellites derived hotspot information. The policy implications of these results suggest that information should be included in the fire management system in Indonesia to support fire early detection as part of fire disaster mitigation efforts.

Drawing on contextualization literature, this paper seeks to evaluate the impact of contextual theology from a Latin American perspective. Bevans' (2002) Praxis Model of contextual theology sets the conceptual framework used to evaluate the evangelical response to the sociopolitical crisis in Nicaragua. The case study provides an example of how Bevans’ Praxis Model can be applied by looking at the manner with which the evangelical and the catholic church have responded to the sociopolitical upheaval in Nicaragua. The literature on contextualization highlights how theologizing is inextricably tied to culture, that contextual theology is necessary to effectively communicate the truth of the Gospel in varying cultural contexts, and that the issues of syncretism and the plurality of theologies can be effectively addressed.

There are experimental evidences that chronic social defeat stress is accompanied by development of anxiety- and depression-like state as well as downregulation of serotonergic genes in the midbrain raphe nuclei of male mice. The study was aimed at investigating the effect of chronic lithium chloride (LiCl) administrations on anxiety behavior and the expression of serotonergic genes in the midbrain raphe nuclei of affected mice. The pronounced anxiety in male mice was caused by chronic social defeat stress in daily agonistic interactions. After 6 days of social stress, defeated mice were treated with saline or LiCl (100 mg/kg, i.p. two weeks) against the background of continuing agonistic interactions. The level of anxiety was assessed using behavioral tests. The effect of chronic treatment with LiCl on the expression of serotonergic genes in the midbrain rapher nuclei was also studied. Mild anxiolytic effects of LiCl were found on communication in the partition test. Anxiogenic-like effects assessed using the elevated plus-maze and social interaction tests were found. Chronic LiCl treatment induced overexpression of the serotonergic genes in the midbrain raphe nuclei. The effects of chronic LiCl treatment depends on the method of treatment, psychoemotional state, and experimental context (tests).

Clubhouse is an auditory app that allows users to host various rooms surrounding a diverse range of topics from Artificial Intelligence to Philosophy. Along with its educational and serene approach, it is known for its popularity amongst celebrities, including Elon Musk, Mark Zuckerburg, CEO of Shopify, and its elusive invite and ios-only pass into gaining access into Clubhouse. Waiting lists are available in the case of not achieving an invite, but to further speed the process, various sellers on eBay, Reddit, Twitter, etc., charging invites from $10-$200. This research paper covers the phenomenon of Clubhouse and the emergence of audio-only rooms, along with a hypothesis of why Clubhouse and other apps of a similar kind are experiencing a harsh downfall despite its seemingly successful business model.

Objective: To investigate social, economic, and environmental contributors to quit or continue smoking and vaping during the COVID-19 pandemic. Methods: A qualitative study design was adopted to identify smokers’ beliefs in a LMIC, using a small community sample. Results: 276 participants were primarily surveyed. Motivation to continue smoking included temporary pleasurable effects, working remotely, stress or anxiety, whereas a motivator to quit smoking was the overlap with COVID-19 symptomatology. There was a rise in social awareness regarding the potential harm of smoking and vaping during the pandemic yet those participants who were younger felt they were immune from its morbid complications. Conclusions: With paradoxical associations of COVID-19 with cigarette and vape usage, it is important to pay attention to biases in data in favor of educating its users of the increased risk of severe disease.

Social and behavioral rhythms (SBRs) are related to circadian rhythms well known as central points in the pathophysiology of bipolar disorders. The purpose is to verify in elderly people if having functional SBRs correlated with a positive perception of the quality of life (QoL) and health parameters and if there was an association between dysfunctionality of SBRs and Major Depressive Disorder (MDD). Sample: 141 people aged 65 years (58,9%Female). Each subject was submitted to SBRs Scale (in which higher scores show more dysfunctional SRB); SF-12 for QoL; PHQ-9 for depressive symptoms and underwent blood levels essays including cholesterol and triglyceride. The medical documented lifetime diagnosis including Major Depressive Disorder was taken into account. SBRs Scale score correlated inversely with SF-12 score (r=-0.360, p&lt;0.0001) and positively with PHQ9 (r=0.396, p&lt;0.0001). Lifetime MDD medical diagnosis was associated with a higher score at scale on social rhythms (24.811.9 vs 20.18.0, F=15.848, p&lt;0.0001).The study highlighted, for the first time, that SBRs such as sleep, and nutrition have a role in well-being and that dysregulation of SBRs is related to MDD. Further longitudinal studies with a sufficient number of individuals will have to confirm these data and clarify causal links of the association between QoL and SBRs.

Accompanied by increasing population growth and urban sprawl, most coastal cities are unprecedentedly vulnerable to climate change and its impacts, such as sea level rise, increasing extreme storm events, and coastal flooding. Coastal resilience and sustainable development are antidotes to vulnerability; they aim to enhance the adaptive capability of absorbing disturbances and resisting uncertainty. This study explores building a quantitative assessment framework to measure resilience and provide an objective and comparable method to understand the strengths and weaknesses in a given region. The proposed 25 resilience indicators incorporate the aspects of essential livelihood protection, infrastructure and natural resource maintenance, emergency facilities and institutions, floodplain management regulations, and adaptive planning process. Each indicator is assigned the resilience quality that includes robustness, resourcefulness, redundancy, and rapidity. The aggregated resilience quality scoring reflects the systematic performance of the city to cope with the coastal hazards. The innovative part of this framework is combining hazard mitigation measures, climate adaptation strategies, and sustainable development goals together to achieve a comprehensive assessment method. In the case of New Haven, the resilience assessment is taken as a practical monitoring tool and decision-making support.

This paper aims to contribute to the advancement of scientific knowledge about the impact of the COVID-19 pandemic on social workers and the social work profession in Romania. Research has shown that social work is a profession at high risk for developing the burnout syndrome, which has many detrimental effects on both social workers and the clients that they serve. Two conceptual models are used to frame the discussion: the theoretical framework of VUCA (volatility, uncer-tainty, complexity, and ambiguity) to discuss the challenges of the unprecedented context the COVID-19 pandemic has created for social workers; stress and burnout to explain the negative impact of this period of time. Based on convergent mixt methods, the study sample consisted of 83 social workers employed in statutory and private social services in Romania, from different fields of intervention. Results show that 25,3% of respondents suffer from a high level of burnout and 44.6% scored in a range that indicate a medium level of burnout. A group of 31.1% have managed to handle stress factors in a healthy manner. Main stressors found are especially personal (fear of contamination, personal and family) and work-related factors (workload, new legislative rules and decisions, inconsistency, instability, ambiguity of managerial decisions, or even their absence or non-assumption, lack of clarity of working procedures, limited managerial and supervisory support, limited financial resources), less than client related factors (lack of direct contact, risk of contami-nation in two ways, managing beneficiaries fears, difficulties related to technology and digital skills). Study results point to the importance of organizational support and developing a self-care plan that help protect against occupational stress and burnout. Recommendations are made putting forward the voice of fieldworkers and managers fostering initiatives and applications of sustainability-based measures and activities designed to deal with the challenges of the VUCA environment.

Although cooperative social networks are considered key to human evolution, emphasis has usually been placed on the functions of men’s cooperative networks. What do women's networks look like? Do they resemble or differ from men's and what does this suggest about evolutionarily inherited gender differences in reproductive and social strategies? In this paper, we test the ‘universal gender differences’ hypothesis positing gender-specific network structures against the ‘gender reversal’ hypothesis that posits women's networks looking more 'masculine' under matriliny. Specifically, we ask whether men's friendship networks are always larger than women's and we investigate measures of centrality by gender and descent system. To do so, we use tools from social network analysis and data on men’s and women’s friendship ties in matrilineal and patrilineal Mosuo communities. In tentative support of the gender reversal hypothesis, we find that women's friendship networks in matriliny are relatively large. Measures of centrality and generalized linear models otherwise reveal greater differences between communities than between men and women. The data and analyses we present are primarily descriptive given limitations of sample size and sampling strategy. Nonetheless, our results provide support for the flexible application of social relationships across genders and clearly challenge the predominant narrative of universal gender differences across space and time.

The widespread deployment of social media has helped researchers access an enormous amount of data in various domains, including the pandemic caused by the COVID-19 spread. This study presents a heuristic approach to classify Commercial Instagram Posts (CIPs) and explores how the businesses around the Holy Shrine – a sacred complex in Mashhad, Iran, surrounded by numerous shopping centers – were impacted by the pandemic. Two datasets of Instagram posts (one gathered data from March 14th to April 10th, 2020, when Holy Shrine and nearby shops were closed, and one extracted data from the same period in 2019), two word embedding models – aimed at vectorizing associated caption of each post, and two neural networks – multi-layer perceptron and convolutional neural network – were employed to classify CIPs in 2019. Among the scenarios defined for the 2019 CIPs classification, the results revealed that the combination of MLP and CBoW achieved the best performance, which was then used for the 2020 CIPs classification. It is found out that the fraction of CIPs to total Instagram posts has increased from 5.58% in 2019 to 8.08% in 2020, meaning that business owners were using Instagram to increase their sales and continue their commercial activities to compensate for the closure of their stores during the pandemic. Moreover, the portion of non-commercial Instagram posts (NCIPs) in total posts has decreased from 94.42% in 2019 to 91.92% in 2020, implying the fact that since the Holy Shrine was closed, Mashhad citizens and tourists could not visit it and take photos to post on their Instagram accounts.

The ’social amoeba’ Dictyostelium discoideum, where aggregation of genet- ically heterogeneous cells produces functional collective structures, epitomizes social conflicts associated with multicellular organization. ’Cheater’ populations that have a higher chance – quantified by a positive spore bias – of surviving to the next generation are selectively advantaged. Their spread is thus expected to undermine collective functions over evolutionary times. In this review, we discuss the two main approaches adopted to conceptualize social conflicts in Dictyostelium discoideum: describing spore bias as a property of cell popula- tions (strains), or as a result of individual cell choices during the developmental process. These two points of view are often held equivalent and used inter- changeably. While the population-level view allows for more direct evolutionary inference, however, the cell-level interpretation reveals that such evolutionary predictions may be modified if developmental mechanisms, such as dependence on the environment and intrinsic unpredictability of cell fate choices, are taken into account. We conclude by proposing a set of open questions that in our opinion lie at the core of a multi-scale description of aggregative life cycles, where the formulation of predictive evolutionary models would include cell-level mechanisms responsible for spore bias alongside population-level descriptors of multicellular organization.

Sarcasm is a linguistic expression often used to communicate the opposite of what is said, usually something that is very unpleasant with an intention to insult or ridicule. Inherent ambiguity in sarcastic expressions, make sarcasm detection very difficult. In this work, we focus on detecting sarcasm in textual conversations from various social networking platforms and online media. To this end, we develop an interpretable deep learning model using multi-head self-attention and gated recurrent units. Multi-head self-attention module aids in identifying crucial sarcastic cue-words from the input, and the recurrent units learn long-range dependencies between these cue-words to better classify the input text. We show the effectiveness of our approach by achieving state-of-the-art results on multiple datasets from social networking platforms and online media. Models trained using our proposed approach are easily interpretable and enable identifying sarcastic cues in the input text which contribute to the final classification score. We visualize the learned attention weights on few sample input texts to showcase the effectiveness and interpretability of our model.

Circular Economy (CE) is a growing topic among scholars, industry and government aiming at decoupling economic growth and development from the consumption of finite resources. CE incorporates different meanings, from reduce, reuse and recycle activities to environmental degradation or resource scarcity, and supported by specific indicators to attain sustainable development. However, so far, there has been no agreement to measure how effective an industry/product is in making the transition from linear to circular approaches, particularly those affected the society. This research work aims to perform a systematic literature review (n=60) to analyze and discuss how social aspects have been considered and integrated in the CE research so far. Moreover, this review provides and overview of the literature on social impact within CE, that resulted in three main outputs: a knowledge map of the CE, an analysis of social aspects within CE, and the theories/frameworks used to evaluate social impact of CE. Finally, this study brings to light how CE implementation can affect society and highlights the importance of social dimension in the domains of CE and policy-making community, which could help moving CE towards a sustainable development.

Predicting the popularity of posts on social networks has taken on significant importance in recent years, and several social media management tools now offer solutions to improve and optimize the quality of published content and to enhance the attractiveness of companies and organizations. Scientific research has recently moved in this direction, with the aim of exploiting advanced techniques such as machine learning, deep learning, natural language processing, etc., to support such tools. In light of the above, in this work we aim to address the challenge of predicting the popularity of a future post on Instagram, by defining the problem as a classification task and by proposing an original approach based on Gradient Boosting and feature engineering, which led us to promising experimental results. The proposed approach exploits big data technologies for scalability and efficiency and is general enough to be applied to other social media as well.

Introduction: Corona epidemic and quarantine enforcement, various effects on the psychological and social aspects of the population has left. The aim of this study is to investigate the relationship between depression, anxiety and relationship with medical staff and mental health is caused by corona. Methods: For this purpose, samples of 650 health personnel of private hospitals were selected. Inventory DASS, HADS, and selected social cohesion (Keyes) and the Internet and through social media networks were evaluated. To analyze the data, Pearson correlation and regression analysis were used. Results: The results showed that straw anxiety corona) to negative (and social cohesion caused by corona) to positive (mental health correlates. It was also found that anxiety and social cohesion caused by corona, respectively 47 and 26 percent predict changes in mental health. Conclusion: These results show the positive and negative effects of psychosocial interventions in quarantine and it have practical implications in the development of the epidemic crisis is Corona.

The article is of a research nature. The aim of the article is to identify the role of social media in shaping personal brand. To this end, the first part discusses the concept of personal brand, components of brand capital in case of famous people, including consumer-based capital. Attention was also paid to the great importance of social media and the growing role of their users in the process of shaping personal brand. Based on the analysis of the source literature, a research gap was identified, related to the lack of empirical verification of the relationship between users’ online activity and the brand capital of famous people, also known as celebrities, associated with artistic and cultural activities. The article uses the results of direct research carried out in the years 2019-2020. The second (empirical) part of the article presents research hypotheses, methodology, as well as results and conclusions from the research. Based on 26 in-depth individual interviews that were conducted with people famous in Poland (mainly engaged in artistic and cultural activities) and surveys on a group of 324 social media users, it was shown, among others, that online activity of Internet users stimulates the brand capital of famous people. Statistically significant relationships were observed for such components of the personal brand as awareness / associations with the personal brand and for the relationship regarding the perception of the quality of activities carried out by a famous person.

Investments in digital infrastructure in marginalised communities are set to increase in the next decade. These are premised on the potential of digital technologies to contribute towards solving societal problems, including the fragility of food value chains in rural areas. Although there are mixed empirical findings on the impact of these digital infrastructure investments, huge investments are continuing amid changing ICT policies in most developing countries. This paper, using a case study of a local livestock value chain in a rural community in Zimbabwe, argues for the application of non-conventional approaches towards digital infrastructure transformation impact assessment. Using selected theories and frameworks (socio-ecological systems framework, choice framework and technology affordances theory) as well as empirical data from a project in a rural community, the paper shows that real-time impact assessment using context-specific metrics may reveal hidden digital infrastructure transformation impacts, positive and negative, that are often overlooked when traditional impact assessment approaches are employed. The findings of this study contribute towards improving approaches towards ICT impact assessment. Practitioners engaging in impact assessment are challenged to move beyond dependence on traditional metrics (e.g. access) to the adoption of participatory processes to decipher context-appropriate metrics.

The analyses of the socio-economic consequences of the 2000s land redistribution in Zimbabwe have always been biased towards the analyses of the ‘production’ and ‘redistributive’ aspects while other equally important features such as ‘social cohesion’, ‘cooperation’, ‘protection’, and ‘accumulation’ amongst beneficiaries are neglected. Using the Sangwe farm in Chiredzi as a case study, this article departs from the conventional use of the political economy, sustainable livelihoods, human rights-based and neo-patrimonial approaches. It experiments with the transformative social policy approach positing that this approach includes the features which are ignored in dominant analyses. Using both quantitative and qualitative data in an exploratory research design, the article shows that viewed from this social policy perspective, the 2000s land reform was not a mere resounding success nor was it a complete disaster. The programme actually produced mixed results. There is therefore, the need to deploy eclectic approaches in the analysis of its consequences.

In Bangladesh, microcredit program has been in function for almost half a century. Though popularly termed as a tool for poverty alleviation and women empowerment, criticism about microcredit program’s actual effectiveness isn’t new. This study attempts to evaluate the impact of such programs by measuring borrowers’ social mobility. Using a multidimensional approach, indicators like household income, economic susceptibility, living conditions, consumption pattern, children’s education, healthcare facilities, women’s participation in decision-making were taken into account for measurement. Quantitative method was used. Based on a non-probability sampling, 107 microcredit borrowers were selected for conducting interview schedules who live in a rural, a semi-urban and an urban area. Statistical analysis of data reveals that those who have been taking loans for several number of years have all managed to increase their income level to a variety of extent, but only those have gained some sort of mobility who have been taking loans for more than 4-5 years and have taken 5 times or more. Few of them have actually moved from microcredit to become a microfinance client by taking bigger amount of loans and having savings. Positive responses about the indicators being used in the study were found among the handful of those who have mobilized significantly. In true sense, most of the borrowers are stuck at the bottom end of socio-economic ladder and are struggling to manage a better living standard.

All over the world, development of micro blog and other social platform indicate that Social Media is now the focus and trend of the Internet. Daily life, study and work are influenced by news in Social Medias . Micro blog is new emergent type of media and it spreads information rapidly in the crowd in recent years. Suppose an user searches for specific information about one topic on micro blog. He/she found easily plenty of information related to his/her search in social medias. The problem is to find out the correct information. Normally, multi-document summarization method deals with a collection of documents about one topic for extracting the valuable points and discards useless information. Actually, it needs to extract the topic content by adding topic factors and social patterns. Topic factor is the lexical information related to the topic. Social pattern relates to special interactive mode owned by online social network, such as comment and repost. People has been seen the fake news on mobile/internet during lockdown period. It is of no doubt that anyone with a social media account has seen at least one example of this.Humanity’s greatest challenges are to detect false information. Fake news are collected from 150 persons using social media The aim of the paper is to investigate the truthfulness of the news people share on social media using K-nearest Neighbour (KNN) based Classifier method.

COVID-19 has been a major issue in most countries throughout the world with 213 countries being affected till date due to the disease. The pandemic has raised concerns over the healthcare facilities available in various countries and question the government decisions made during this period of outbreak. Despite having the best healthcare facilities several countries across Europe and America have found it difficult to contain the disease outbreak questioning the available solutions to contain an area. This paper focuses on presenting information on solutions available to control outbreaks in order to prevent another pandemic occurring in the future. The paper also highlights the strategies and plans implemented by various governments who have been successful in combatting the disease with minimum damage. By using available resources such as technology, scientific innovation and digitalized healthcare this paper focuses on providing solutions which are already available to be utilized in the right manner.

Cheating prevention in online exams is often hard and costly to tackle with proctoring, and it even sometimes involves privacy issues, especially in social distancing due to the pandemic of COVID-19. Here we propose a low-cost and privacy-preserving anti-cheating scheme by programmatically minimizing the cheating gain. A novel anti-cheating scheme we developed theoretically ensures that the cheating gain of all students can be controlled below a desired level aided by the prior knowledge of students’ abilities and a proper assignment of question sequences. Furthermore, a heuristic greedy algorithm we developed can refine an assignment of questions from a cyclic pool of question sequences to efficiently reduce the cheating gain. Compared to the integer linear programming and min-max matching methods in a small-scale simulation, our heuristic algorithm provides results close to the optimal solutions offered by the two standard discrete optimization methods. Hence, our anti-cheating approach could potentially be a cost-effective solution to the well-known cheating problem even without proctoring.

It has been hypothesized that social distancing as the prevention measures for COVID 19 can affect the air quality including PM_2.5 and PM₁₀ in urban areas. According to this situation, this study aims to compare the PM_2.5 and PM₁₀ before and after the implementation of social distancing. Likewise, this study also forecasts the benefits of social distancing on PM_2.5 and PM₁₀ if social distancing period is continued and extended. To achieve these objectives, an Auto Regressive Integrated Moving Average (ARIMA) model to investigate the daily PM_2.5 and PM₁₀ trends has been developed for social distancing periods (March– May 2020) and after May as well. The model confirms that if social distancing period is extended after May 2020 then the PM_2.5 and PM₁₀ are estimated will be 4% and 9% lower. To confirm that the PM_2.5 and PM₁₀ reductions are only due to social distancing effect, the study has investigated the possible effects of wind speed and rainfall on PM_2.5 and PM₁₀. Nonetheless, the reductions do not correlate with those factors. To conclude social distancing should be considered as an option to control PM_2.5 and PM₁₀ in urban areas.