COVID-19, caused by SARS-CoV-2, is responsible for widespread mortality and economic loss across almost 212 countries. The distribution of disease prevalence is, however, uneven and likely dependent on the range of human behavior and/or the pathogen and environmental variables. Here in this research we examined the correlation between daily and total COVID-19 case reports from Bangladesh and meteorological variables (average temperature, average humidity, and average wind speed) against one another using Spearman rank and Kendall correlation tests to highlight significant meteorological variables in relation to COVID-19. The tests revealed that both temperature and humidity had a non-significant correlation with COVID-19 transmission amid epicenter (EC) and non-epicenter (NEC) areas. However, a weak (KCC: 0.168, p < 0.05; SCC: 0.271, p < 0.05) correlation was found for temperature in ECs. Wind speed showed moderate to strong correlation in ECs with a very high statistical significance to both daily new cases [(KCC: 0.494, p < 0.01); (SCC: 0.689, p < 0.01)] and total cases [(KCC: 0.426, p < 0.01); (SCC: 0.617, p < 0.01)]. The COVID-19 transmission was found to have a weak (KCC: 0.354, p < 0.01) to moderate (SCC: 0.465, p < 0.01) correlation with daily new cases; however, a moderate (KCC: 0.497, p < 0.01) to strong (SCC: 0.712, p < 0.01) correlation with total cases was found in NECs. The results suggest that temperature and humidity have little influence on COVID-19 transmission, but wind speed may have some influence. Countries should prioritize social engineering to modify human behavior in order to combat the spread of COVID-19 and future pandemics.

In Iran, fake news has been refined to weapon due to the popularity of new media and the growing social media-based assault on Afghan refugees. The recent geopolitical tensions and migrations, of course, have brought with them an increased number of false information reports and with them the rapid spread of negative stereotypes and the fueling of anti-Afghan sentiment. The article examines disinformation dispersion and its exacerbation in the digital space. It discusses in specifics ways in which misleading and hate speech against Afghan refugees pass through Iranian social media, in a thorough study of the psychological factors behind these narratives, that favors or fights such disinformation. The study screens the virtual screening areas that distribution of toxicity and disinformation by and engagement with social media. The disinformation technologies as well as the socio-political and historical contexts they derive from. Based on a detailed overview of the cyber-world, this study exposes the myriad challenges of suppressing false narratives and hate speech, focusing particularly on Afghan refugees in Iran. Besides, it points out to methods for both disallowing it to be distributed and curing the disease itself, basically, by redesigning digital agendas to present only the truth. The paper is aimed at unveiling the subversive forms of disinformation, armory with the data concerning digital tools and platforms, as well as input by external societies into the tapestry of the web that will construct a more inclusive digital discourse through critical engagement. Setting apart the genuine and not so wrong investigative procedures show great progress in society through these demanded efforts. Besides, the study impinges on more general issues such as media ethics and fact-checking, in what may be called the development of reliable information systems. This paper impinges on disinformation and humanizing toxic information, a vital aspect that currently has been managed only to a limited extend through the top-down disapproving or regulatory method and it creates strong ecosystem.

The aim of the study is to explore how sharing status updated and receiving Likes on Facebook, as a form of positive social feedback, correlates with current and perceived changes in Quality of Life (QoL) Sample consisted of 1577 adult Facebook users (76.3% females; 65.9% aged 18-24, 21.9% aged 25-30, 12.3% aged &gt; 30 years old). The study employed a longitudinal approach, collecting Facebook data from adult users over a 12-month period using the Graph API. Data were divided into 12 monthly segments. Two monthly indicators were calculated: the percentage of textual status updates and the average number of Likes per post. Current and perceived changes in Quality of Life (QoL) were administered as self-report measures. The findings indicated a positive correlation between the frequency of textual Facebook posts and the average received Likes. Furthermore, receivign more Likes was positively associated with a higher current QoL, and perceived improvements in QoL correlated with an increase in Likes over time. The study suggests that online positive social feedback, measured through Likes on Facebook, is associated with both current QoL and perceived improvements in QoL among adult Facebook users. This highlights the potential impact of online social interactions on individual well-being.

The objective of this article is to determine as conclusively as possible if the implementation of a UBI (universal basic income) would lead to a significant reduction in the working age population labour supply. If this were true, implementation of a UBI would be unsustainable. To do this, we will compile empirical evidence from studies over the last few decades on the effects of implementation of a UBI on employment. We apply the PRISMA methodology to better judge their validity, which ensures maximum reliability of the results by avoiding biases and making the work reproducible. Given that the methodologies used in these studies are diverse, they are reviewed to contextualize the results taking into account the possible limitations detected in these methodologies. While many authors have been writing about this issue citing experiences or experiments, the added value of this article is that it performs a systematic review following a widely tested scientific methodology. Over 1,200 documents that discuss the UBI/employment relationship have been reviewed. We found a total of 50 empirical cases, of which 18 were selected, and 38 studies with contrasted empirical evidence on this relationship. The results speak for themselves: despite a detailed search, we have not found any evidence of a significant reduction in labour supply; instead we found evidence that labour supply increases globally among adults, men and women, young and old; and the existence of some insignificant and functional reductions to the system such as a decrease in workers from the following categories: children, the elderly, the sick, those with disabilities, women with young children to look after, or young people who continued studying. These reductions do not reduce overall supply because it is largely offset by increased supply from other members of the community.

This research aims to determine the similarities in groups of people to build a film recommender system for users. Users often have difficulty in finding suitable movies due to the increasing amount of movie information. The recommender system is very useful for helping customers choose a preferred movie with the existing features. In this study, the recommender system development is established by using several algorithms to obtain groupings, such as the K-Means algorithm, birch algorithm, mini-batch K-Means algorithm, mean-shift algorithm, affinity propagation algorithm, agglomerative clustering algorithm, and spectral clustering algorithm. We propose methods optimizing K so that each cluster may not significantly increase variance. We are limited to using groupings based on Genre and, Tags for movies. This research can discover better methods for evaluating clustering algorithms. To verify the quality of the recommender system, we adopted the mean square error (MSE), such as the Dunn Matrix and Cluster Validity Indices, and social network analysis (SNA), such as Degree Centrality, Closeness Centrality, and Betweenness Centrality. We also used Average Similarity, Computational Time, Association Rule with Apriori algorithm, and Clustering Performance Evaluation as evaluation measures to compare method performance of recommender systems using Silhouette Coefficient, Calinski-Harabaz Index, and Davies-Bouldin Index.

This study explores the impact of mobile technologies on consumer behavior in retail marketing, examining how advancements in mobile platforms have transformed shopping habits and interactions with brands. Mobile technologies have revolutionized the retail experience by providing unprecedented convenience, allowing consumers to shop at any time and from any location. This shift has led to a marked preference for mobile shopping over traditional methods, fundamentally altering consumer behavior. Key findings reveal that personalization plays a crucial role in enhancing consumer engagement and satisfaction, with mobile technologies enabling tailored recommendations and offers based on individual preferences. Access to real-time information, such as product details and price comparisons, empowers consumers to make more informed purchasing decisions, reflecting a shift towards deliberate and confident buying choices. Social media and social commerce have also become significant factors, with consumers discovering new products and brands through these platforms and benefiting from integrated shopping features. Impulse buying behavior has increased due to the convenience of mobile shopping, with promotional alerts and simplified payment processes contributing to spontaneous purchases. The integration of mobile technologies with physical store experiences has created a more seamless shopping journey, bridging the gap between online and offline interactions. However, challenges such as privacy concerns, data security, and information overload remain significant. Consumers are increasingly aware of data collection risks and may experience fatigue from excessive marketing messages. To navigate this evolving landscape, retailers must balance the advantages of mobile technologies with addressing these challenges to effectively meet consumer needs and expectations.

Social media HPV vaccination interventions show promise for increasing HPV vaccination rates. An important consideration for the implementation of effective interventions into real-world practice in the translation potential, or external validity, of the intervention. To this end, we conducted a systematic literature review to describe the current body of evidence regarding the external validity of social media HPV vaccination-related interventions. Constructs related to external validity were based on the RE-AIM (reach, effectiveness, adoption, implementation, maintenance) framework. Seventeen articles published between 2006 and 2020 met inclusion criteria. Three researchers independently coded each article using a validated RE-AIM (reach, effectiveness/efficacy, adoption, implementation, maintenance) framework. Discrepant codes were discussed with a fourth reviewer to gain consensus. Of these 17 studies, three were pilot efficacy studies, 10 were RCTs to evaluate effectiveness, one was a population-based study, and three did not explicitly state which type of study was conducted. Reflecting this distribution of study types, across all studies the mean level of reporting RE-AIM dimensions varied with reach recording 90.8%, effectiveness (72.1%), adoption (40.3%), implementation (45.6%), and maintenance (26.5%). This review suggests that while the current HPV vaccination social media-driven interventions provide sufficient information on internal validity (reach and effectiveness), few have aimed to gather data on external validity needed to translate the interventions into real world implementation. Our data suggest that implementation research is needed to move HPV vaccination-related interventions into practice. Included in this review are recommendations for enhancing the design and reporting of these HPV vaccination social media-related interventions.

A regional organisation (RO) is a group of states that, through the formation of mutual relationships, work together for shared regional goals such as economic growth, social welfare, security, and democracy. The Association of South East Asian Nations (ASEAN) is one such organisation, of interest because of its operative paradoxes. However, current theory to study ROs is both fragmented across the field of study, and inadequate. Taking ROs to be complex adaptive systems, diagnosing ROs requires theory that can to explore their hidden aspects. The metacybernetics framework enables the creation of a critical realism configurative a-priori inquiry approach to theory building, the configurations providing coordinative schemas able to respond to predefined complex modelling needs. To analyse ROs using metacybernetics, we offer a derivative schema, Cultural Agency Theory (CAT). Currently this is limited to exploring modes of information acquisition processes through cognitive style, and until now has had no inherent mechanism to explore social relationships as is required to explore ROs. To enable CAT to explore such relationships, we configure the Tönnies social organisation paradigm for CAT. Mindset Agency Theory (MAT) is a specific elaboration of CAT, and creates an empirical setting for the set of formative traits that de-fine an RO character. A related derivative of CAT is that of Multiple Identity Theory (MIT) which enables organisational pathologies to be explored in terms of identity conflicts. This multifaceted paradigm provides a relatively simple approach to the RO diagnosis, in particular in terms of stability/coherence. This paper is in two parts. In this part 1, the CAT theory will be further developed through the joint configuration of Tönnies social organisation paradigm allowing its pathologies to be diagnosed. In part 2 of the paper, the theory will be applied to ASEAN and the diagnosis will show that it is an inherently incoherent organisation.

A regional organisation (RO) is a group of states that, through the formation of mutual relation-ships, work together for shared regional goals such as economic growth, social welfare, security, and democracy. The Association of South East Asian Nations (ASEAN) is one such organisation, of interest because of its operative paradoxes. However, current theory to study ROs is both fragmented across the field of study, and inadequate. Taking ROs to be complex adaptive systems, diagnosing ROs requires theory that can to explore their hidden aspects. The metacybernetics framework enables the creation of a critical realism configurative a-priori inquiry approach to theory building, the configurations providing coordinative schemas able to respond to predefined complex modelling needs. To analyse ROs using metacybernetics, we offer a derivative schema, Cultural Agency Theory (CAT). Currently this is limited to exploring modes of information acquisition processes through cognitive style, and until now has had no inherent mechanism to explore social relationships as is required to explore ROs. To enable CAT to explore such relationships, we configure the Tönnies social organisation paradigm for CAT. Mindset Agency Theory (MAT) is a specific elaboration of CAT, and creates an empirical setting for the set of formative traits that de-fine an RO character. A related derivative of CAT is that of Multiple Identity Theory (MIT) which enables organisational pathologies to be explored in terms of identity conflicts. Thes multifaceted paradigm provides a relatively simple approach to the RO diagnosis, in particular in terms of stability/coherence. This paper is in two parts. In this part 1, the CAT theory will be further developed through the joint configuration of Tönnies social organisation paradigm allowing its pathologies to be diagnosed. In part 2 of the paper, the theory will be applied to ASEAN and the diagnosis will show that it is an inherently incoherent organisation

We present a model of infection dynamics that might explain slower approaching the herd immunity during the covid-19 epidemy in Sweden than it was predicted by a variety of other models; see graphs Fig. \ref{GROWTH2}. The new model takes into account the hierarchic structure of social clusters in the human society. We apply the well developed theory of random walk on the energy landscapes represented mathematically with ultrametric spaces. This theory was created for applications to spin glasses and protein dynamics. To move from one social cluster (valley) to another, the virus should cross a social barrier between them. The magnitude of a barrier depends on the number of social hierarchy's levels composing this barrier. As the most appropriate for the recent situation in Sweden, we consider linearly increasing (with respect to hierarchy's levels) barriers. This structure of barriers matches with a rather soft regulations imposed in Sweden in March 2020. In this model, the infection spreads rather easily inside a social cluster (say working collective), but jumps to other clusters are constrained by social barriers. This model's feature matches with the real situation during the covid-19 epidemy, with its cluster spreading structure. Clusters need not be determined solely geographically, they are based on a number of hierarchically ordered social coordinates. The model differs crucially from the standard models of spread of disease, such as the SIR-model. Our model describes such a specialty of spread of covid-19 virus as the presence of ``super-infectors'' who by performing a kind of random walk on a hierarchic landscape of social clusters spreads infection. In future, this model will be completed by adding the SIR-type counterpart. But, the latter is not a specialty of covid-19 spreading.

The implementation of management systems has become a strategic advantage in achieving business goals, especially in industrial organizations, but the implementation of social responsibility requirements is especially ethical. Large multinational companies have long been developing and, in particular, implementing their own codes of conduct, which include their suppliers, to demonstrate their commitment to Corporate Social Responsibility (CSR). The compliance with CSR requirements from stakeholders is thus extended or intertwined with requirements in established management systems (MSs). The objectives of the study were to (1) analyze the different approaches to CSR in internationally recognized cross-industry and industry-specific standards and codes in different industries; (2) select the most appropriate framework for assessing the degree of applicability of CSR in the selected management systems and develop a methodology for its assessment; (3) apply the proposed methodology (referred to as SRIMS) in the selected areas: automotive industry, research organization, and metallurgical industry; (4) through ANOVA, validate its use for assessing the overall level of CSR applicability in an organization's established management systems. The application of the Bonferroni method confirmed the hypotheses that the developed SRIMS model is a sufficiently appropriate tool for assessing the overall level of applicability of CSR requirements to established MSs.

Informal caregivers are essential in supporting stroke survivors' recovery, but it is unclear whether community interventions can promote healthy eating behaviors and social participation among stroke survivors and their caregivers. The Train-Your-Brain (TYB) program's impact on adherence to national dietary guidelines and social participation among informal caregivers and stroke survivors were assessed in a quasi-experimental study. The TYB program had nine sessions, with one focusing on healthy lifestyle. Participants were prompted to discuss the topics covered, leading to social participation. Dietary habits were assessed using fruits and vegetables consumption questions, while social participation was measured using the Social Impact Measurement Framework. Mann-Whitney U-test and Wilcoxon Signed Rank Test were utilized to analyze the data. Eighteen informal caregivers and 27 stroke survivors participated in the program. Results showed a significant increase in fruit and vegetable intake and social participation in informal caregivers after the program, but there were no significant changes in stroke survivors. Informal caregivers play a crucial role in stroke survivors' lifestyle habits and in encouraging social connections with other stroke survivors. Thus, healthcare professionals should prioritize caregiver support and education to facilitate long-term dietary and social changes that can positively impact stroke survivor's recovery and quality of life.

We aimed to assess the prevalence, content structure and psychological comorbidity of PIU in Russian adolescents. In addition, the design of our research provided an opportunity to compare demographic and psychological patterns of different forms of PIU: generalised (PIUgen) and specific – problematic video game use (PUgame) as well as problematic social media use (PUsocial). Methods: This is a one-stage cross-sectional observational study of school sampling in three major Siberian cities. A total of 4514 schoolchildren aged 12-18 (mean age 14.52±1.52 years) were surveyed. Chen Internet Addiction Scale, Game Addiction Scale for Adolescents”, and The Social Media Disorder Scale were used to identify PIU and its types. Results: The prevalence of PIUgen among adolescents in Central Siberia was 7.2%; the prevalence of PUgame was 10.4%; the prevalence of PUsocial was 8.0%. The results of structural equation modelling, as well as the correlation analysis data, suggest two possible patterns of psychosocial problems with PIU – the first one characteristic of both PIUgen and PUsocial, the second one, significantly different, – of PUgame. Conclusions: Urban adolescents in Central Siberia do not differ significantly from their Asian and European peers. Our findings support the concept of rejecting the term “generalised PIU” as a single psychological construct.

This study examines the influence of digital marketing on brand awareness within the multinational Fast-Moving Consumer Goods (FMCG) sector, focusing on how various digital strategies contribute to overall marketing effectiveness. Utilizing a sample of 277 respondents, the research employs descriptive statistics, correlation, and regression analyses to explore the relationships between digital marketing strategies, brand awareness outcomes, and perceived digital marketing effectiveness. The findings reveal that digital marketing strategies significantly enhance brand awareness and overall marketing effectiveness, underscoring the pivotal role of activities such as social media engagement, content marketing, and search engine optimization. Specifically, the regression analysis shows that digital marketing strategies have a positive and statistically significant impact on overall effectiveness, indicating that companies investing in these areas are better positioned to achieve higher levels of brand recognition and marketing success. However, the study also uncovers a complex relationship between brand awareness outcomes and overall effectiveness, where increased brand awareness does not directly correlate with enhanced digital marketing effectiveness. This suggests that while brand awareness is critical, its influence on marketing success is nuanced and may involve diminishing returns or additional mediating factors. The regression model explains a modest portion of the variance in marketing effectiveness, highlighting the need for a holistic evaluation approach that incorporates a broader set of performance metrics and contextual factors. The high reliability of the measures used affirms the robustness of the findings, which emphasize the importance of a strategic and integrated approach to digital marketing in the FMCG sector. Companies must continuously adapt and optimize their digital marketing strategies to align with dynamic market conditions and achieve sustainable success.

This paper aims to argue the fundamental significance of education in addressing notable gaps in the constitutive, performance, and evaluation criteria for corporate social responsibility (CSR) and endeavours to showcase the complementarity between education, human security, sustainable human development, and the pursuit of CSR as an ideal normative paradigm. An abstractive approach to studying CSR engages with corporate philanthropy, which has not been helpful outside traditional CSR paradigms without looking at key dynamics that can robustly underpin successful CSR. It relies on the systematic analysis of written data sources to theoretically explore the central significance, and complementarity between human security, education, and human dignity and how they can orchestrate a holistic CSR paradigm. In 1994, the UNDP in formulating the human security doctrine recognised the syncretic correlation between human security, education, and sustainable human development as fundamental elements that should underpin CSR. This paper contends that these are necessary intrinsic components of human dignity as the central factor that justifies a multi-dimensional and proactive approach to CSR. Despite the criticisms against human security, this paper identifies it as an important concept that could instrumentally orchestrate a model of CSR that uniformly mainstreams sustainable human development and human dignity that leverages education which has routinely and traditionally been seen as a constitutive component of CSR. It reveals how a holistic path to CSR can reinvigorate the central pillars of human security and human dignity using education as a springboard and makes a compelling case for supporting explicit references to education in company law with appropriate human security informed constitutive, performance, and evaluation criteria which are absent in existing legally orchestrated CSR.

Suicidal behaviour is a public health problem whose magnitude is both substantial and increasing. Since many individuals seek medical treatment following a suicide attempt, strategies aimed at reducing further attempts in this population are a valid and feasible secondary prevention approach. An evaluation of the available evidence suggests that existing treatment approaches have limited efficacy in this setting, highlighting the need for innovative approaches to suicide prevention. Existing research on the neurobiology of social pain has highlighted the importance of this phenomenon as a risk factor for suicide, and has also yielded several attractive targets for pharmacological preventive strategies. In this paper, the available evidence related to these targets is synthesized and critically evaluated. The way in which social pain is related to the “anti-suicidal” properties of recently approved treatments, such as ketamine and psilocybin, is also examined. Such strategies may be effective for the short-term reduction of suicidal ideation and behaviour in individuals who have made a suicide attempt suicide prevention, particularly in cases where social pain is identified as a contributory factor. These pharmacological approaches may be effective regardless of the presence or absence of a specific psychiatric diagnosis.

In the second decade of the 21st century, social media changed the nature of communication and cooperation between participants of the culture services market. They became, among other things, an important marketing instrument in the area of contact with the customers of the cultural offer. However, despite their growing importance in various areas of activity of organisations in the cultural sector, the issue of building the cultural institution's brand equity by social media users is relatively seldom raised. Research on the impact of online consumer activity on brand equity is at an early stage of development. Therefore, this article is an attempt to fill the research gap in this area. The article presents the results of a survey conducted in 2018 on a group of 1021 consumers of cultural services, who at the same time regularly used social media. The statistical analysis carried out and the research results obtained prove that the 3C sustainable system developed by the authors, concerning the activity of consumers of cultural services in social media, stimulates the consumer-based brand equity (CBBE). Statistically significant relations have been observed in particular for CBBE components related to the awareness of a cultural institution's brand and for the relationship related to the perception of its quality. The study opens a review of literature on social media and consumer-based brand equity (CBBE). Next, based on the COBRA model (consumer's online brand-related activities), a proposal of the 3C sustainable system, concerning the activity of consumers of cultural services in social media, has been presented. The further part of the article presents research hypotheses, a conceptual model, research methodology as well as results and conclusions. The last part of the article discusses the results obtained and indicates the existing management implications.

This paper investigates if Corporate Social Responsibility (CSR) reports published by a selected group of Nordic companies are aligned with the Global Reporting Initiative (GRI) standards. To achieve this goal, several natural language processing, and text mining techniques were implemented and tested. We extracted strings, corpus, and hybrid semantic similarities from the reports and evaluated the models through the intrinsic assessment methodology. A quantitative ranking score based on index matching was developed to complement the semantic valuation. The final results show that Latent Semantic Analysis (LSA) and Global Vectors for Word Representation (GloVE) are the best methods for our study. Our findings will open the door to the automatic evaluation of sustainability reports which could have a strong impact on the environment.

To explore the spatial network structure characteristics and driving effects of carbon emission intensity in China's construction industry, the investigation combined the modified gravity model and social network analysis method to deeply analyze the spatially associated network structure characteristics and driving effects of carbon emission intensity in China's construction industry, based on the measurement of carbon emission data of China's construction industry from 2006 to 2017. The results show that the regional differences of carbon emission of construction industry are significant, and the carbon emission intensity of construction industry show a fluctuation trend. The overall network of carbon emission intensity shows an obvious “core-edge” state, the hierarchical network structure is gradually broken. Economically developed provinces generally play a leading role in the network, and play an intermediary role to guide other provinces to develop together with them. Among the network blocks, most of the blocks play the role of “brokers”. The block with the leading economic development has a strong influence on the other blocks. The increase of network density, the decrease of network hierarchy and network efficiency will reduce the construction carbon emission intensity.

The research examines the relationship between self-rated health situation and personal percep-tion of heat waves, and how social linkage of communities would be a moderator variable in residents’ perception of heat waves in Taiwan. This study uses the questionnaire conducted by Sinica “Responsive Capacity under Heat Wave: The Perspectives of the Locals”(2019), using OLS method for estimating the unknown parameters in multiple regression model. The author finds that the correlation of self-rated health situation and perception toward heat is significantly posi-tive. Also, social linkage in communities affects strongly as a moderator variable: While the sat-isfaction to with their community could reduce negative reaction to heat, contacts with neighbors could increase possibility people feel uncomfortable in high-temperature situation. This study ex-hibits the effects of social environment on community, and expects further related researches or practices to strengthen capability to resist heat wavesƒ for Taiwanese residents.

Social safety, security, and comfort of school-going children during the travel time to school becomes a subject of anxiety to the parents and is a crucial issue in recent times. In this regard, community-based transport can be a significant way to address social security issues in travel at a reasonable cost and reduce the burden on private mode. In Dhaka city, school van service already exists but due to some sort of problems the service has not been proved an efficient and formal mode of transport for solving mobility problems. This study seeks to identify the existing problems and prospects of the school van service and provide a unique, healthy, safe, and reliable transport mode for children. Applying different tools of the Participatory Rural Appraisal (PRA) method, the problems and solutions have been drawn from the community. The recommendations of this study will help the school van services (a community-managed para-transit system) to be more functional in playing a vital role in solving the problems of short-distance travel. This service has great potentialities to be adopted in other trips such as trips to and from offices which will lessen the road congestion at the peak periods.

The use of social media is increasing worldwide, and thus, some new problems that negatively affect life are coming to the fore. The “White Bear Thought Suppression” problem, which was put forward in previous years, has re-emerged in the digital environment as psychological disorders accompanying excessive social media use. The reason for this study was that people constantly think about what is happening on social media, cannot distinguish between digital and reality, and cannot manage their mental process. The aim of this study is to examine the relationship between social media addiction and White Bear Thought Suppression and the factors affecting it from the perspective of White Bear Suppression on social media. The sample of the research consists of 356 volunteer participants in Turkey between the ages of 18-71. The research was conducted by analyzing the data collected with the Social Media Addiction Scale (SMAS) and White Bear Suppression Inventory (WBSI) scales in accordance with the quantitative method. Some of the results obtained in the research are as follows: (a) Women’s social media addiction and White Bear Suppression were found to be high, (b) Generation Z is the generation in which social media addiction and White Bear Suppression are seen at the highest level, (c) As daily social media use increases, the level of social media addiction and White Bear Suppression increases; (d) The frequency of opening live chats and having more than one profile increases social media addiction and White Bear Suppression. (e) The frequency of sleep disorders and perceived loneliness affect both phenomena. At the end of the research, it was emphasized that social media impacted White Bear Suppression and that new clinical studies were needed, especially with young people.

Colombia has initiated the process of participating in the environmental projects of the United Nations global agenda for the mitigation of climate change and the protection of biodiversity. Consequently, organizations within the solidarity sector have devised projects with the objective of aligning themselves with regional programs and of promoting leadership in the rural development through solidarity-based environmental initiatives. These include the organizations Canapro Ambiental, Cooperación Verde and Cootregua, which have participated in and accompanied local environmental projects. This study has identified the common elements related to the principles of organizational design proposed by Elinor Ostrom as a result of the adoption of Corporate Social Responsibility (CSR) for the purpose of a sustainable growth. The above findings serve to corroborate the relevance of the principles of organizational design as a qualitative assessment methodology for environmental solidarity initiatives. In particular, the methodology demonstrates the value of supporting the objectives of environmental sustainability and governance in the long term, by means of the strengthening of Corporate Social Responsibility (CSR) for the purposes of the solidarity ecosystem.

Curriculum teaching is the basic unit to realize the cultivation and achievement of students’ ability in undergraduate colleges, and it is very important to investigate the influence mechanism of the curriculum system on the achievement states of students' ability. This paper first puts forward the theoretical system and framework of curriculum chains, and constructs a “double-energy and double-space” (DEDS) which consist of the curriculum energy efficiency space and student ability space respectively. Investigating the space-time transformation relationship of curriculum chains in the DEDS, the forward transformation model, inverse transformation model and the rheological model of the achievement states in the curriculum energy efficiency space and student ability space are established. Studying the dynamic evolution mechanism of curriculum chains within the DEDS, the dynamic evolution model, which presents the relationship between achievement states of curriculum energy efficiency/students' ability and curriculum/students' dynamic potential, are established; the control methods of courses/students' dynamic potential based on the proposed dynamic evolution model are developed to ensure the achievements of the graduates’ social ability; the evaluation and detection methods of achievement states of curriculum chains in DEDS are proposed to obtain the actual achievement states of curriculum energy efficiency and students’ ability, and this will provide effective input for the control of curriculums/students’ dynamic potential; the planning and design methods of curriculum chains facing social needs are presented, which can provide theoretical basis for the formulation of the talent training scheme and curriculum system in colleges and universities.

Eco-agricultural technology is crucial to alleviating agricultural resource scarcity and environ-mental pressures. However, financial constraint affects its successful promotion. Digital finance has a significant impact on farmers, but existing research lacks an exploration of the impact of digital finance on farmers' adoption of eco-agricultural technology. This study focuses on Rice–Crayfish Co-cultivation Technology as an example. It utilizes survey data from 1,063 households in China. An Endogenous Switching Probit model is employed to solve self-selection bias. The results reveal several key findings. First, the average treatment effect on the treated is 51.5%. This indicates that if farmers who use digital finance were to stop using it, the probability of adopting rice–crayfish co-cultivation technology would decrease by 51.5%. Therefore, digital finance is beneficial for farmers in adopting this technology. Second, heterogeneity analysis reveals that digital finance has a greater promoting effect on older farmers, those with lower education levels, and higher proportions of agricultural income. This suggests a greater reliance on digital financial services among vulnerable groups. Third, digital finance promotes farmers' adoption of rice–crayfish co-cultivation technology by alleviating financial constraints, expanding information channels, and increasing social capital accumulation. Overall, the findings offer valuable insights for for-mulating supportive policies.

The Directive 2014/95, in force in 2017, is the first European step that requires mandatory non-financial information to undertakings (all “public interest entities” with more than 500 employees). The regulation is concerning sustainability information as environmental, social and employee, human rights and anti-corruption and bribery matters and disclosure of diversity policy for board members. The study, in the strand of the regulation of accounting, part of the broader field of research into accounting regulation, contributes to the debate on the quality of regulation, in this specific case referred to sustainability disclosure. The regulation of sustainability matters is studied in literature broadly in a post-implementation phase and at national level. This research, instead, aims to analyse, through the causal chain of regulatory policy, in the ex-ante stage, the quality of the regulation and, at least, the usefulness of the normative pressure. The Oil & Gas sector is chosen as sample of the study, because it is one of the most advanced sectors in sustainability disclosure. The examination of the law, in terms of content requirements (what) and location of information (where), is the basis to apply the disclosure-scoring system, a partial form of content analysis, to the reports of the sample. The findings reveal a good level of completeness of non-financial information, however, there are some areas that have to be improved to reach the requests of the Directive. Results show also the presence of overlap between financial reports and sustainability ones. In conclusion, the regulation is useful to prompt undertakings to reflect on their reporting and so doing improve their sustainability approach.

Leisure education has the potential to improve quality of life and prepares students for social par-ticipation after graduation. This study aimed to elucidate the perspectives of special education teachers regarding leisure instruction. This study surveyed 538 teachers from 10 special needs schools for students with intellectual disabilities in Prefecture A, a rural area of Japan. An online survey was conducted from October 21 to November 17, 2023. The survey items were based on 13 aspects of leisure instruction identified from a literature review related to leisure instruction in Japan and a qualitative analysis of interviews with high school teachers in special needs schools for stu-dents with intellectual disabilities. The results showed that “The ability to pass time during brief periods of free time,” “Various activity experiences that lead to leisure,” and “Knowing one’s strengths and weaknesses in activities” were significantly more important during school. Con-versely, “understanding the psychological importance of leisure,” “connecting with organizations that support leisure activities,” and “finding places to engage in leisure activities” were significantly more important after graduation. The results of this study will be used to identify gaps in percep-tions between special education teachers and vocational rehabilitation practitioners responsible for post-social participation support.

Will human societies accommodate social robots, given the current development rate? Are we under a novelty effect? Can (and should) social robots compete with intelligent agents (e.g., software robots) for the attention of humans? Will the current development of machine learning be the motor of social robotics? What kind of robotics products and culture can we expect that will emerge? These are relevant questions to assess the sustainability of social robots and how they will change business practices and lifestyle. Speculative/exploratory arguments on these topics are possible and have been mostly left out of research papers. This, however, results in an unconventional structure where the novelty comes from the questioning of the role of Social Robotics that has not been duly addressed in the literature. The paper raises questions and (i) presents arguments supporting sustainability grounded on experiments in real-world scenarios, and (ii) identifies challenges according to multiple viewpoints. These are questions for which assertive answers are not found in the literature. Besides the answers to the above questions, the conclusions point to pathways we believe social robotics can evolve, e.g., incorporating maximal knowledge on how humans work.

The transition to renewable energy sources is critical for sustainable development, particularly in rural regions with limited access to electricity. Solar-powered microgrids offer a promising solution for rural electrification by providing reliable, clean energy that can enhance economic opportunities and improve quality of life. This paper presents a techno-economic analysis of solar-powered microgrids for rural areas, evaluating their feasibility, costs, and benefits. The analysis encompasses technological aspects, such as solar panel efficiency, battery storage, and grid management, alongside economic factors including initial investment, maintenance costs, and potential returns. Additionally, the study assesses the social impact of solar-powered microgrids, exploring their effects on local communities, including improvements in education, health, and economic activities. The findings indicate that solar microgrids can be a viable and impactful solution for rural electrification, with significant long-term benefits for both economic development and social well-being.

This study analyzes the relationship between economic policy uncertainty (hereinafter EPU) and corporate value, and verifies the differential effects of EPU on corporate value according to corporate social responsibility (hereinafter CSR) activities. The study period was from 2010 to 2020, and the EPU indexes measured by Baker et al. (2016)'s method and Hexun's CSR scores for companies listed on the Chinese stock market were used. Hexun is one of the three major evaluation agencies in China, and the CSR scores evaluated by this agency have been widely used in previous studies as a representative indicator of Chinese companies' CSR performance. The results of this study are as follows. First, EPU and corporate value were found to have a negative (-) relationship. Second, active CSR activities relieved the negative (-) relationship between EPU and corporate value. Finally, companies were divided into groups according to CSR activity scores to analyze the relationship and according to the result, the negative (-) relationship between EPU and corporate value was greater in the groups with low CSR activity scores than in the groups with high CSR activity scores. A lag model was applied to control endogeneity, and the results were consistent with the main results above. Previous studies have mainly focused on microscopic factors to investigate factors affecting corporate value. This study focused on macroeconomic policies and paid attention to the effects of changes in the macroenvironment caused by economic policy uncertainty on corporate value. In addition, this study is meaningful in that it expanded previous studies related to CSR activities by confirming that active CSR activities can be an advantageous tool for overcoming EPU.

The rapid expansion of social media and instant messaging applications, such as WhatsApp, has transformed how individuals and organizations communicate and engage. This think piece explores the potential of integrating WhatsApp as a customer relationship management (w-CRM) tool within the education sector to foster and sustain long-term relationships among students, teaching staff, and non-teaching staff. By leveraging real-time features and the widespread use of WhatsApp, educational institutions can create a more interactive and dynamic learning environment, benefiting all stakeholders involved. The literature highlights the importance of establishing clear frameworks for mutual engagement and interaction and the potential of w-CRM to improve communication between students' families and educational institutions. There are potential risks associated with the pervasive use of WhatsApp, and call for future research to explore strategies for mitigating these risks while maximizing the benefits of w-CRM in the education sector. Longitudinal studies are recommended to evaluate the long-term impact of w-CRM on stakeholder relationships, student outcomes, and overall institutional performance.

Traditional Corporate Social Responsibility (CSR)-programs rarely include participatory components that connect CSR-activities of private companies with their local communities. However, there is an increasing demand to include citizens as well as the resources and expertise of the private sector in the design and implementation of local community planning processes. To assess the potential, opportunities, and challenges of including private companies into participatory community planning at a local level, we analyzed the experiences that we collected during the piloting phase and the commercial roll-out of the ‘Bürgercockpit’-application for citizen participation, as well as the results of a digital CSR-questionnaire that we shared with different companies in Austria. Our research indicates that most of the participating companies are interested in including local communities into their CSR-projects using a digital tool, if this tool is easy-to-use, easy-to-access, and provides a flexible structure to address specific project requirements as well as properly designed features for stakeholder communication and user feedback. The findings of both, the ‘Bürgercockpit’-pilot study and the CSR-questionnaire provided us valuable input for designing a prototype solution of a digital CSR-tool for participatory community planning at a local level as well as recommendations for future research in this topic of growing interest.

The well-being in the people is a key aspect of the field of psychology. Hence, it is important to an-alyse the variables that are related to life satisfaction and happiness as perceived by individuals and that, therefore, increase their overall well-being. The main objective of this study was to ana-lyse the predictive capacity of emotional intelligence and perceived social support on both the level of life satisfaction and perceived happiness. A total of 380 psychology students completed the Trait Meta Mood Scale, the Multidimensional Scale of Perceived Social Support, the Satisfaction With Life Scale, and the Subjective Happiness Scale. The results show that both emotional intelligence and social support are related to and predictive of subjective happiness and life satisfaction. The importance of developing the components of emotional intelligence and promoting an adequate social network in young people is highlighted.

The spatial and temporal changes in social vulnerability to natural hazards in Mexico are analyzed. To this end, using census data from 2000, 2010, and 2020 and a statistical method, different indices were computed, and with a GIS-based approach, patterns of social vulnerability are examined. In addition, a risk assessment test for severe weather (thunderstorms, hailstorms, and tornadoes) is made out. The results show different common social vulnerability driving factors in the three analyzed years, with root causes that have not been addressed since the beginning of the century. Likewise, a wider gap between Mexico's most and least vulnerable populations is identified. The changes in spatial patterns respond to different historical situations, such as migration, urbanization, and increased population. Also, poverty, ethnicity, and marginalization factors located in very particular regions in Mexico have remained relatively the same in the last few years. These situations have strongly influenced the spatial-temporal distribution of vulnerability in the country. The role of social vulnerability in the disaster risk to extreme events such as thunderstorms, hailstorms, and tornadoes in Mexico is fundamental to understanding changes in disaster distribution at the national level, and it is the first step to generating improvements in integrated risk management.

Landscape restoration activities must be conducted through a transdisciplinary process, integrating social, economic, environmental, and governance aspects. Combining visions from the natural and social sciences is a challenge in highly complex territories, where unique ecosystem characteristics, economic processes, stakeholders of diverse nature, and different normativity converge. The harmonization of multiple techniques, such as multicriteria spatial analysis, expert knowledge elicitation, and social mapping, allows for an approach to defining landscape restoration areas in complex regions. This paper employs multiple techniques to define ecosystem restoration areas in a complex Colombian Andes landscape, integrating ecological and social components for sustainable development. We observed that areas of high and very high feasibility for ecological restoration, encompassing 179.5 hectares (4.84% of the study area), are predominantly located near primary forests. Although some areas have low feasibility for conservation processes, they should not be disregarded as they still require protection. Landowners prioritize watershed and soil restoration as the most important landscape restoration activity due to their interest in improving water-related ecosystem services. This proposal enables the identification of areas with higher restoration potential at the property level, facilitating prioritization and investment allocation for future implementation.

This paper explores the relationships between marketing strategies, social media platforms, the adoption and diffusion of products and services, and organizational resilience to gain an understanding of the ability of organizations to cope with disruptive events (e.g., COVID-19). This can be achieved through effective marketing strategies and the efficient use of social media platforms. In fact, resilience thinking can help organizations maintain their operations by increasing the adoption and diffusion of their products and services through the use of effective marketing strategies. To achieve this article’s objectives, a literature review is conducted to help develop a conceptual framework that highlights a clear relationship between the previously discussed concepts. In addition, the novel nature of the relationship between marketing strategies and organizational resilience is dissected and its significance for organizations is demonstrated. In fact, the findings of this study suggest that effective marketing strategies that consider the "what," "who," and "how" dichotomies and the efficient use of social media to promote the adoption and diffusion of products and services can significantly enhance the resilience of organizations. These relationships can serve as a starting point for further studies examining and empirically analyzing marketing strategies and their positive effect on strengthening organizational resilience.

The role of chemical communication in social relationships of birds is receiving growing attention but our knowledge is still scarce compared to other taxa. Previous evidence suggests that chemical cues emitted by birds may carry information about their characteristics that may be useful in a sexual selection context. However, experimental studies are needed to investigate the role of bird chemical cues in signalling quality of potential partners. We performed an experimental study aimed to disentangle whether female zebra finches, Taeniopygia guttata, use chemical cues to assess the body condition and body size of potential partners. We offered focal females the scent of two males differing in body condition and body size. Our results show that females can assess the body condition of potential partners using olfaction. However, contrary to expected in a mate choice context, our results show that females avoided the scent of the male with greater body condition and body size. Our results therefore suggest that, despite performing the study during breeding period, social interactions may be mediating the avoidance of the scent of the conspecific of the opposite sex with better body condition and body size in this gregarious species.

This empirical research is part of a larger project beginning in 2020 and ongoing until 2023 exploring the impact of the COVID-19 pandemic on young caregivers aged 5-25 years and their families in Canada. Utilizing the social determinants of health as a conceptual framework, this case study emphasizes the voices of professionals offering services to young caregiver clients during the pandemic, and explores their perspectives on the impact of the pandemic on young caregivers and their families. Across three (3) different organizations offering programs and services to young caregiver clients in Ontario, six (6) individual interviews were conducted with directors/program managers and four (4) group interviews were conducted with thirteen (13) staff members who worked directly with young caregivers and their families. Nineteen (19) service providers participated in total. The results of this study highlight five (5) primary themes that emerged through data analysis: i) the role of service providers, ii) the impact of the COVID-19 pandemic on organizations and service providers supporting young caregivers and their families, iii) barriers for service users, iv) helpful resources for service providers and organizations, and v) resources needed/preferred by service providers and organization. The pandemic significantly impacted young caregivers and their families, as reported by professionals, and organizations working with young caregivers and their families were tasked with addressing increased service demands and adapting service delivery to follow public health guidelines.

Fake news detection has become a significant topic based on the fast-spreading and detrimental effects of such news. Many methods based on deep neural networks learn clues from claim content and message propagation structure or temporal information, which have been widely recognized. However, such models (i) ignore the fact that information quality is uneven in propagation, which makes semantic representations unreliable. (ii) Most models do not fully leverage spatial and temporal structure in combination. (iii) Finally, internal decision-making processes and results are non-transparent and unexplained. In this study, we develop a trust-aware evidence reasoning and spatiotemporal feature aggregation model for more interpretable and accurate fake news detection. Specifically, we first design a trust-aware evidence reasoning module to calculate the credibility of posts based on a random walk model to discover high-quality evidence. Next, from the perspective of spatiotemporal structure, we design an evidence-representation module to capture the semantic interactions granularly and enhance the reliable representation of evidence. Finally, a two-layer capsule network is designed to aggregate the implicit bias in evidence while capturing the false portions of source information in a transparent and interpretable manner. Extensive experiments on two benchmark datasets indicate that the proposed model can provide explanations for fake news detection results, as well as can achieve better performance, boosting 3.5% in F1-score on average.

Children’s right to participation in child protection decision-making is supported by moral imperatives and international conventions. The fragmented implementation of this right reflects an already-conflicted discursive terrain that attempts to incorporate both children’s agency and their need for protection. This article uses two key theoretical lenses to further examine this terrain: child welfare inequalities and cultural capital. These theories draw attention to how social inequities and cultural capital relating to culture and class affect how participation plays out. An unintended consequence of constructing children within a traditional liberal account of rights, within neoliberal and ‘child focussed’ policy paradigms, is the reduction of an acknowledgment of the culturally contested nature of an individualistic construction of children, excising children from their social backgrounds and promoting the notion of a ‘universal child’. With a particular focus on class, culture and professional paradigms, I argue that the ways children’s views are elicited, the content of those views and how they are interpreted, become subject to a set of professional assumptions that tend to take little cognisance of the social backround of children, including norms relating to class, ethinicity and the oppressive structural relations relating to those two factors. This process is shored up with concepts such as attachment theory, the ‘adultification’ of children of colour, the diminishing of Indigenous concepts of children and childhood, and the pre-eminence of the ‘concerted cultivation’ middle class parenting style. The child’s cultural worldview and manner of expressing it may clash with professional cultures that emphasise an ability for verbal expression, independence, and entitlement when negotiating preferences with representatives of powerful social institutions such as child protection systems. Many children may not comply with this expectation due to both cultural and class socialisation processes, and the histories of the oppressive functions of child protection systems. The unspoken power of child protection organisations that must engage in constant translation of children’s cultural capital to ensure participation, may instead better serve children’s participation aims by devolving authority to affected communities. Communities reflecting children’s own, may be better able to offer recognition to children and enable their participation more effectively.

Within the field of movement sensing and sound interaction research, multi-user systems have gradually gained interest as a means to facilitate an expressive non-verbal dialogue. When tied with studies grounded in psychology and choreographic theory, we consider the qualities of interaction that foster an elevated sense of social connectedness, non-contingent to occupying one’s personal space. In reflection of the newly adopted social distancing concept, we orchestrate a technological intervention, starting with interpersonal distance and sound at the core of interaction. Materialised as a set of sensory face-masks, a novel wearable system was developed and tested in the context of a live public performance from which we obtain the user’s individual perspectives and correlate this with patterns identified in the recorded data. We identify and discuss traits of the user’s behaviour that were accredited to the system’s influence and construct 4 fundamental design considerations for physically distanced sound interaction. The study concludes with essential technical reflections, accompanied by an adaptation for a pervasive sensory intervention that’s finally deployed in an open public space.

Users on the social networking platform have the freedom to express themselves freely. Towards the same time, this has created a forum for disagreement and hate directed at someone, society, racism, sexual orientation, and so on. Identifying hate online is a challenging task. Researchers from all around the world have contributed major methods for detecting hate speech, but owing to the issue's complexity, there are still many unresolved issues. In this research, we offer a multi-model learning strategy for detecting hate speech on Twitter. We utilised the Kaggle TwitterHate dataset, which had 31962 tweets categorised as binary hate or non-hate, to evaluate our technique. The suggested method is tested using commonly used machine learning classifiers with multi-model technique. Using TF-IDF features, we acquired detection results of 96.29 %, precision of 96%, recall of 96%, and f1-score of 96%.

At the end of 2018, a high school student asked a question in Zhihu community, claiming that he had proved Goldbach's conjecture. The problem caused an explosive reaction and a large number of users participated in the discussion. And has caused the widespread influence. On January 1, 2019, the questioner issued his "proof". His proof was soon proved wrong. The heated discussion caused by the incident contains a lot of information of social science analysis value. Therefore, we follow up the event in the first time and build a time series dataset for the event. Taking the questioner's "proof" as the dividing line, all the answers, comments, sub comments and user information of writing these texts before and after two days were recorded. This series of temporal information can reflect the dynamic features of the interaction between user opinions, and the impact of exogenous shocks (proof release) on community opinions. The dataset can be used not only for the demonstration of various social network analysis algorithms, but also for a series of natural language processing tasks such as fine-grained sentiment analysis for long texts, as well as multimodal tasks combining natural language processing and social network analysis. This paper introduces the characteristics and structure of the dataset, shows the visualization effect of social network, and uses the dataset train the benchmark model of emotion analysis.

The present study aims to examine the role the social and digital infrastructures might have during the building process of the Smart Regions in the Italian context. Within this framework, it is possible to identify some essential research questions, such as why the same regions are growing faster than the other and which type of effects could be generated from the different connectivity between the regions. Since the Smart Region concept is still composed of technical reports, pilot projects and experiences from a limited number of cities on the international stage, this work it is tried to use a new approach, applying either a neuronal model, the Self-Organizing Maps, and the multivariate regression approach, to extrapolate the existence of possible future conditions for the rising of Smart Regions in Italy, studying the evolution of the used database during the period 2005 – 2016. From the analysis what emerged is that the only bridging social capital dimension, empirically speaking, feed the regional innovation growth because the structure of social relationship facilitates interactions across social, political and economic agents; but there are institutional deficits, most pronounced in Italy and other European countries.

Social enterprises are very common in Birmingham having the largest concentrations of social enterprises in the United Kingdom. With the emergence of the Covid-19 pandemic, the operations and management of social enterprises in Birmingham has been greatly affected. This study seeks to analyse the impact of the Covid-19 pandemic on the operations and funding of social enterprises in Birmingham UK. In order to achieve this, the study is going to carry out a qualitative methodology in order to analyse the impact Covid-19 has had on social enterprises. The research is going to select relevant stakeholders through a non-purposive sampling criteria identifying individuals who have direct interest in the functioning of social enterprises. The relevant stakeholders will be expected to respond to semi structured interviews that are structured to evoke responses relevant to this area of research. The research realized that Social enterprises in Birmingham are a critical player in the economy of UK with many individuals depending on the social enterprise industry. In addition to that, the study realised that the Covid-19 pandemic exposed social enterprises to various financial and market risks. Moreover, social enterprises were forced to make a change in their organizational structure through cost management changes and offering alternative services. However, the government came in support through provision of grants and funding to boost the social enterprise economy.

This study aimed to examine trust in information provided by public authorities and financial measures put in place to address the impact of COVID-19. Using a cross-national approach among four Western countries; the United States of America, Norway, Australia, and the United Kingdom provides an analysis of responses related to trust and how they were associated with age group, gender, education level, employment status, size of place of residence, infection sta-tus, and social media use. When controlling for all included variables in logistic regression analyses, the likelihood of having trust in the public authorities’ information was higher for women, those with higher levels of education, and those living in urban areas. Being infected with the coronavirus, and spending more time daily on social media was associated with lower likelihood reporting trust in information. Although policies implemented to respond to eco-nomic concerns varied cross-nationally, higher age, identifying as female, being employed, liv-ing in a city, and lower levels of social media usage were associated with higher likelihood of trusting in the financial measures put in place to counteract the economic effects of COVID-19.

Studies showed that introversion is the strongest personality trait related to perceived social isolation (loneliness), which can predict various complications beyond objective isolation such as living alone. Lonely individuals are more likely resort to social media for instantaneous comfort, but it is not a perpetual solution. Largely negative implications including poorer interpersonal relationship and depression were reported due to excessive social media usage. Conversational task is an established intervention to improve verbal communication, cognitive and behavioral adaptation among lonely individuals. Despite that behavioral benefits have been reported, it is unclear if they are accompanied by objective benefits underlying physiological changes. Here, we investigate the physiological signals from 28 healthy individuals during a conversational task. Participants were ranked by trait extraversion, where greater introversion is associated with increased susceptibility to perceived social isolation as compared to participants with greater extraversion as controls. We found that introverts had a greater tendency to be neurotic, and these participants also exhibited significant differences in task-related electrodermal activity (EDA), heart rate (HR) and HR variability (HRV) as compared to controls. Notably, resting state HRV among individuals susceptible to perceived loneliness was below the healthy thresholds established in literature. Conversational task with a stranger significantly increased HRV among individuals susceptible to isolation up to levels as seen in controls. Since HRV is also elevated by physical exercise and administration of oxytocin hormone (one form of therapy for behavioral isolation), conversational therapy among introverts could potentially confer physiological benefits to ameliorate social isolation and loneliness. Our findings also suggest that although the recent pandemic have changed how people are interacting typically, we should maintain a healthy dose of social interaction innovatively.

Background: Few studies examined the contributions of childhood adversities, intimate partner violence and social support to antenatal depression (AD). This study aims to 1) evaluate association of these psychosocial factors with AD symptoms in early pregnancy; and 2) examine the mediating effect of social support on the relationship between psychosocial stressors and AD symptoms.Methods: Participants were 120 pregnant women aged from 18 to 49 in less than 16 gestational weeks and attending at Antenatal Care Center at Khon Kaen hospital, Thailand. AD symptoms were assessed by the Edinburgh Postnatal Depression Scale (EPDS). Childhood adversities, intimate partner violence and social support were measured using the Adverse Childhood Experiences Questionnaire (ACE questionnaire), Abuse Assessment Screen (AAS), and Multidimensional Scale of Perceived Social Support (MSPSS). Results: We found that the EPDS score was significantly and positively associated with adverse childhood experiences (ACEs) and negatively with social support. Partial Least Square analysis showed that 49.1% of the variance in the depressive subdomain of the EPDS score was predicted by ACEs, namely psychological and physical abuse and neglect, emotional or physical abuse by the partner, unplanned pregnancy, and no satisfaction with their relationship. The effects of adverse childhood experience due to neglect on the EDPS score was mediated by social support by friends. Limitations: ACEs were assessed retrospectively and, therefore, may be susceptible to recall bias.Conclusion: Prenatal depression scores are to a large extent predicted by psychological distress as indicated by early lifetime trauma, abuse by partner, relation satisfaction, and implications of unintended pregnancy.

Being a combination of the conference call, talkback radio, audio podcast, and an online video chat, Clubhouse is a new social networking app that gained over 10 million users and over $100 in valuation in just 8 months. Unlike other social networks, it offers a real-time streaming audio chat that does not ask users to share any unnecessary information like exchanging text messages, conducting video calls, or sharing photos. Instead, Clubhouse users can listen to real-time conversations, contribute to these conversations and create their own conversations for the others to listen and to interact with. Often nicknamed a “Silicon Valley’s hottest start-up”, Clubhouse positions itself as an “exclusive” and “alternative” social network that attracts various celebrities and people who just want to talk to each other. Launched in March 2020, amidst the COVID-19 pandemic with its social distancing and lockdowns, Clubhouse offered its users a space for the digital group psychotherapy where people could solve their problems by talking them through with strangers. However, it is unclear what is going to happen to this new social network in the post-pandemic world after all of its hype eventually evaporates. This paper discusses the possible underlying motives for the Clubhouse creation and its real purposes. Moreover, it looks at the three possible scenarios of its further development.

Contact tracing is one of the oldest social network health interventions used to reduce the diffusion of various infectious diseases. However, some infectious diseases like COVID-19 amass at such a great scope that traditional methods of conducting contact tracing (e.g., face-to-face interviews) remain difficult to implement, pointing the need to develop reliable and valid survey approaches. The purpose of this research is to test the effectiveness of three different egocentric survey methods for extracting contact tracing data: (1) a baseline approach, (2) a retrieval cue approach, and (3) a context-based approach. A sample of 397 college students were randomized into one of each condition and were prompted to anonymously provide contacts and populated places visited from the past four days. After controlling for various demographic, social identity, psychological, and physiological variables, participants in the context-based condition were significantly more likely recall more contacts (medium effect size) and places (large effect size) than the other two conditions. Theoretically, the research supports suggestions by field theory that assume network recall can be significantly improved by activating relevant activity foci. Practically, the research contributes to developing innovative social network data collection methods for contract tracing survey instruments.

This paper aimed to use social media impact on student studies in higher education. Apart from enjoyment and academic purposes, many educational practices and processes have been influenced by social networks. This paper highlighted the use of media tools in higher education as well as indicates out some of the factors. Moreover, through a literature review of related articles, we aim to provide insights into the impacts of a social network on educational quality, actual use of social media, and performance impact in higher education. A questionnaire survey on constructivism was circulated among a total of 206 university students as the key method for collecting data. This research hypothesizes educational quality and actual social media use indicates a positive effect in education, all of which also hypothesizes constructivism for educational quality and actual social media that in turn improve students’ satisfaction, and performance impact. Moreover, all research findings were attained through a quantitative method using the Structural Equation Modeling (SEM-AMOS). Findings of this research to indicate a positive effects students on their academic through behavioral intention to utilize social media to actual social media use for teaching and learning on higher education. Moreover, the results mention the use of social media for learning purpose, as well as social media to enables the sharing of knowledge, discussions, and information to enhance students' learning activities, Further studies are recommended which universities educators should take this into consideration when planning their curricula; it comes to the inclusion of technology in the teaching process.

Tracking information diffusion is a non-trivial task and it has been widely studied across different domains and platforms. The advent of social media has led to even more challenges, given the higher speed of information propagation and the growing impact of social bots and anomalous accounts. Nevertheless, it is crucial to derive a trustworthy information diffusion graph, which is capable of highlighting the importance of specific nodes in spreading the original message. The paper introduces the interaction strength, a novel metric to model retweet cascade graphs by exploring users’ interactions. Initial findings show the soundness of the approaches based on this new metric with respect to the state-of-the-art model, and its ability to generate a denser graph, revealing crucial nodes that participated in the retweet propagation. Reliable retweet graph generation will enable a better understanding of the diffusion path of a specific tweet.

Many governments particularly in Europe are designing social interventions for the first post COVID-19 emergency phase. Definition of a ‘best practice’ for restriction release is urgent. Although data uncertainty generate difficulties, we believe near term analysis must shift from attempting to understand the numerous ‘unknowns’ to the clarification and interpretation of the few ‘knowns’, to create stepping stones towards rapid evidence-based decision making.Here, open access data on COVID-19 severity in three European countries were analyzed. Spain’s data were more comprehensive than those from Italy and Germany. Overall, COVID-19 severity shows a remarkable nonlinear growth with age that is significantly higher in adult males. Hence, age-adaptive and gender-balanced social interventions might represent efficient repopulation options for public health policymakers. Furthermore, we urge wider governmental effort for open access to relevant data. Their analysis will allow consolidation of existing trends, validation of key observations and thus facilitation of timely decisions.

The paper is devoted to fundamental issues concerning to the ideology of the future sustainable development. Its implementation has available in the first place basing on the recognized framework concept of sustainable development (SD). At the same time, this concept requires serious improvement. As follows from the argumentation, a realistic design of institutional changes in connection with resource and organizational/behavioral changes needed for SD is called for to realize in the line of overall social system transformation. Its adequate understanding presupposes an exhaustive study of interconnected transformations in the main social fields as system processes taking into account the influence of relatively exogenous factors (technological, demographic and climate changes).According to the author, the transition to global sustainable social transformation is achievable. Main attention focuses on a number of possible fundamental shifts, the synergetic implementation of which will make such a transition possible.Proceeding from the arguments, the sustainable reproduction of the economy of a mature post-industrial type, including the green sectors, implies its stable and quiet growth, although the rapid growth of individual markets, especially innovative ones, may take place. The main findings also include the substantiation in favor of the choice of the national middle way model as the most appropriate for the corresponding sustainable system transformation of society.

State legitimacy and effectiveness could be seen by the way to deliver welfare to citizens to mitigate social grievances, that could eventually lead to conflicts (Kivimäki, 2021). Social security systems in Maghreb countries are quite similar in their architecture and aims to provide social insurance to all the workers in the labor market. However, they suffer from the same main problem: the low rate of enrollment of workers. Many workers (employees and self-employed) work informally without any social security coverage. The issue of whether informal jobs are chosen voluntarily by workers or as a strategy of last resort is controversial. Many authors recognize that the informal sector is heterogeneous and it is made up of workers who voluntary choose it and others who are pushed inside because of entry barriers to the formal sector (Günther & Launov, 2012). Using the SAHWA survey and discrete choice models, this article confirms the heterogeneity of the informal labor market in three Maghreb countries: Algeria, Morocco, and Tunisia. Furthermore, this article highlights the profiles of workers who voluntarily choose informality, which is missing from previous studies. Finally, this article proposes policy recommendations in order to extend social security to informal workers and to include them in the formal labour market.

The notion of hierarchy is a key characteristic of any complex system. This paper explores which notions of hierarchy are being used in the field of management and organization studies. Four distinct types of hierarchy are identified: a ladder of formal decision-making authority, a ladder of achieved status, a self-organized ladder of responsibility, and an ideology-based ladder. A social mechanism-based perspective serves to define and distinguish these four types. Subsequently, the typology is further developed by comparing the four hierarchy types in terms of their tacit/explicitness, (in)transitivity, and behavior- versus cognition-centeredness. This review article contributes to the literature by dissecting the general metaphor of hierarchy into four different constructs and their social mechanisms, which serves to create a typology of the various ways in which complex systems can be characterized as being hierarchical. This typology can inform future research drawing on any type of hierarchy.

The development of dispersed urbanism in Spain ran parallel to the real estate boom and consolidated a new model of city sprawl based on the expansion of suburban areas. This process, which started in the mid 1980s, came to a halt with the onset of the economic crisis in 2007. With it, construction stopped, mobility fell and urban growth came to a standstill. The purpose of this article is to carry out an analysis of the recent evolution and chronology of the expansion of dispersed urbanism in the Barcelona Metropolitan Region (BMR) in order to gain an insight into some of the explanatory factors of such expansion and to deal with the future prospects of middle-term development of dispersed urbanism in the BMR and in Spain. To do this, we examine the trends in the housing market, in residential mobility and we take stock of the impact of business cycles. The conclusion is that dispersed areas retain their appeal in the stages of creation and expansion of households. For this reason, an effective economic recovery and a renewed rise in the price of housing in denser cities may contribute to an upturn in the popularity of the dispersed residential model, which nowadays could be considered to be in a ‘lethargic’ stage, waiting for certain factors to coincide and re-activate its expansion.

This cross-sectional study was aimed to investigate the relationship between gratitude and life satisfaction, and the mediation role of social support and enjoyment of life among older individuals. The Gratitude Resentment and Appreciation Test, the Enjoyment of Life Scale, the Satisfaction with Life Scale, and the Multidimensional Scale of Perceived Social Support Scale were administered to a sample of 260 older individuals aged between 60 and 80. The main findings revealed a positive association between gratitude and life satisfaction, and social support was a partial mediator in this relationship. Although enjoyment of life was not a direct mediator in the relationship between gratitude and life satisfaction, the final model indicated a significant serial pathway from gratitude to social support and then through enjoyment of life-to-life satisfaction. In conclusion, enhancing gratitude, promoting enjoyment of life, and social support in older individuals might increase their life satisfaction, which in turn might contribute to their successful aging

Mobile phones have become an integral part of our lives in the last two decades, leaving a digital trace of our activities and communication. This study aims to develop a data processing framework to evaluate human mobility and socioeconomic status based on call detail records. The methodology proposed first calculates radius of gyration and entropy for each user, then estimates the socioeconomic status by the price and age of the subscribers' phones. Finally, an unsupervised machine learning algorithm was used to group the cells into clusters based on their mobility and socioeconomic metrics. The research showed differences between Buda and Pest during a large scale social event using mobile phone ages and prices. Additionally, the clustering results revealed homogenous groups of cells around Budapest, with similar mobility and socioeconomic metrics. The main conclusion is that mobile network data combined with mobile phone properties offer a useful tool for characterising urban mobility and socioeconomic status.

The emergence of the Covid-19 pandemic has created both negative and positive changes, including implementing the circular economy across the globe. This Systematic Review follows the PRISMA statement and employs the Text Mining (Voyant Tools) technique to visualize and analyze the impacts of the Covid-19 on three aspects of the circular economy: economic, social, and environmental. The research employs Latent Dirichlet Allocation (LDA) to identify five major topics: (1) Shortage of medical equipment but high medical waste during Covid-19 due to the high demand in healthcare; (2) The long term negative impacts of lockdown on economic and social activities because of Covid-19 pandemic; (3) The reports on impacts of Covid-19 pandemic on the manufacturing globally, and their coping strategies and new opportunities; (4) The impacts of international restriction on the tourism, trade, shipping, and aviation industry, causing billion-dollar losses; (5) The reduction of pollution with health environment improvements with example cases from China and EU. The research identifies current literature gaps in the circular economy and Covid- 19 topics and encourages the application of text mining tools into researching to stimulate the research process and assist in communicating with the public.

Background: In schizophrenia (SZ), social cognition mediates the relationship between neurocognition and social functioning. Although people with major depressive disorder (MDD) also exhibit cognitive impairments, which are often prolonged, little is known about the role of social cognition in MDD. Methods: Using data obtained through an internet survey, 210 patients with SZ or MDD were selected using propensity score matching based on their demographic information and illness duration. Social cognition, neurocognition, and social functioning were evaluated using the Self-Assessment of Social Cognition Impairments, Perceived Deficits Questionnaire, and Social Functioning Scale, respectively. The mediation effects of social cognition on the relationship between neurocognition and social functioning were examined in each disease group. Invariances of the mediation model across the two groups were then analyzed. Results: The SZ and MDD groups had mean ages of 44.49 and 45.35 years, contained 42.0% and 42.8% women, and had mean illness durations of 10.76 and 10.45 years, respectively. In both groups, social cognition had significant mediation effects. Configural, measurement, and structural invariances across the groups were established. Conclusion: The role of social cognition in patients with chronic depression was similar to that in schizophrenia. Social cognition could be a common endophenotype for various psychiatric disorders.

The term “risk” is connoted with divergent meanings in natural hazard risk research and the practice of risk management. Whilst the technical definition is accurately defined, in practice, the term “risk” is often synonymously used with “danger”. Considering this divergence as a deficiency, risk communication often aims to correct laypersons’ understanding. We suggest in reference to Breakwell (2001) to treat the variety of meanings as a resource for risk communication strategies instead. However, there is no investigation so far, of what laypersons’ meanings of risk actually comprise. To address this gap, we examine the meanings of risk applying a social representations approach (Moscovici, 2001) in a qualitative case study design. Results of the study among inhabitants of Swiss mountain villages show that differences in meanings were found according to hazard experience and community size. We found commonly shared core representations, and single peripheral ones. We conclude with suggestions on how to make usage of the knowledge on SR in risk communication.

The COVID-19 pandemic has had devastating consequences for health, social, and economic domains, but what has received far less focus is the effect on people’s relationship to vital ecological supports, including access to greenspace. We assessed patterns of greenspace use in relation to individual and environmental factors and their relationship with experiencing psychological symptoms under the pandemic. We conducted an online survey recruiting participants from social media for adults in Korea for September–December 2020. The survey collected data on demographics, patterns of using greenspace during the pandemic, and major depression (MD) and generalized anxiety disorder (GAD) symptoms. The Patient Health Questionnaire (PHQ-9) and the Generalized Anxiety Disorder 2-item (GAD-2) were applied to identify probable cases of MD and GAD. A logistic regression model assessed the association decreased visits to greenspace after the outbreak compared to 2019 and probable MD and GAD. Among the 322 survey participants, prevalence of probable MD and GAD were 19.3% and 14.9%, respectively. High rates of probable MD (23.3%) and GAD (19.4%) were found among persons currently having job-related and financial issues. Of the total participants, 64.9% reported decreased visits to greenspace after the COVID-19 outbreak. Persons with decreased visits to greenspace had 2.06 higher odds (95% CI: 0.91, 4.67) of probable MD at the time of the survey than persons whose visits to greenspace increased or did not change. Findings suggest that barriers to greenspace use could deprive people of mental health benefits and affect mental health during pandemic; an alternative explanation is that those experiencing poor mental health may be less likely to visit greenspaces during pandemic. This implies the need of adequate interventions on greenspace uses under an outbreak especially focusing on how low-income populations may be more adversely affected by a pandemic and its policy responses.

The current practices of the technology transfer profession seem to reflect the belief that the chances for success are greatly improved when faculty inventors employ their social capital to facilitate the process. However, there is a gap in the university technology transfer literature regarding our understanding of faculty inventor social capital in the technology transfer process. The aim of this study was to understand whether the use of faculty inventor social capital is a causal condition for successful university technology transfer. This question was examined using a multiple case study approach and the qualitative comparative analysis (QCA) method. The results of the study suggest that the use of faculty inventor social capital is not a necessary, sufficient, or INUS condition for the occurrence of university technology transfer.

Media coverage of Lyme disease (LD) has led to an increase in consultations for presumed LD in Europe. However, LD is confirmed in only 10-20% of patients, with a significant number remaining in a diagnostic dead-end. The objective of our study was to understand the genesis of the LD hypothesis in care pathways. In 2019, 30 patients from a prospective cohort consulting in the infectious diseases department at University Hospital in Marseille for presumed LD were recruited for semi-structured interviews. The inclusion criteria were: suffering from subjective symptoms for 6 months, no clinical or paraclinical argument suggesting current LD. The patients’ medical trajectories were collected using a biographical approach. A majority of participants were convinced they had LD despite the lack of medical evidence and the scepticism of their referring GP. The diagnosis of Lyme disease was primarily triggered by identification with clinical stories circulating in the media. Most of participants had conducted the diagnostic investigation themselves. Diagnostic wandering in the diagnostic process suggests a failure of modern medicine to propose solutions for medically unexplained symptoms. Clinicians should systematically explore patients’ etiologic representations in a patient-centred care approach.

Wide-scale commercialization of cultured meat, produced from in vitro-grown animal stem cells, is still a long way off because of technical, regulatory and, above all, social acceptability constraints. As a result, despite the advancement of knowledge, it is difficult to predict whether this innovation will be commonly accepted. The concept of media framing is key to better understanding individuals’ decision-making and mental interpretative patterns in relation to cultured meat adoption. This research therefore analyzes the role of media framing (namely the social media platform Twitter) on the components of consumer attitudes (cognitive, affective, and conative) in relation to cultured meat. A total of 23 020 publications and 38 531 comments were analyzed qualitatively (content analysis) and quantitatively (MANOVA). This study showed that media-framed posts influenced consumer attitudes more than did non-media-framed posts. Although the results indicate that the different types of media framing (ethical, intrinsic, informational, and belief) do not exert the same influence on each attitude component, they suggest that posts combining the ethical, intrinsic, and informational media frames have a greater impact on the acceptability of cultured meat and that the belief frame is equally important, particularly for the behavioral component. Relevant implications can be drawn for authorities and businesses on the use of differentiated education and marketing strategies

This article provides a comprehensive historical analysis of Brazil's industrialization, tracing its evolution from the 19th century to the present day. It examines key periods and policies that have shaped the nation's economic landscape, beginning with early industrial efforts during the Imperial era and the Old Republic. The analysis delves into the Vargas regime's Import Substitution Industrialization policies, post-war industrial expansion under developmentalism, the military regime's economic strategies during the "Economic Miracle," and the challenges posed by the 1980s debt crisis. The discussion highlights contemporary issues faced in the 21st century, including premature deindustrialization and the complexities during the administrations of Presidents Lula da Silva and Dilma Rousseff. It explores the impact of Operation Lava Jato on industrial development and assesses the ramifications of President Jair Bolsonaro's policies during the COVID-19 pandemic. Central to this exploration is the critical examination of regional disparities, social inclusion efforts, and environmental sustainability initiatives. The article emphasizes that Brazil's most significant challenges lie in persistent inequality and structural racism, which serve as fundamental barriers to economic progress and industrial advancement. It argues that addressing these issues through comprehensive policies focused on education reform, economic inclusion, healthcare access, legal and institutional changes, community development, and cultural recognition is essential. By integrating social justice into economic strategies, Brazil can achieve sustainable and inclusive industrial development, fostering a more equitable and prosperous society.

The fusion of "innovation theory" and "ecology" gave birth to a large number of studies on "innovation ecology", which mainly studies how to build an industrial ecological chain at the regional level, focusing on self-evolution, achieving ecological balance, and enabling the regional economy to take the path of sustainable innovation. This type of research borrows a lot of concepts from ecology, and very vividly describes the competition and cooperation relationships formed by various agents in the innovation system, laying a good foundation for qualitative analysis of the inherent dynamics of innovation development. However, many studies focus on the analogous description of ecosystems and economic systems, lacking scientifically and rigorously quantitative empirical research as a support. This paper uses network-based indicators such as degree, cluster coefficient, and betweenness centrality to measure the function and position of high-tech enterprises in the Z-Park in a business environment, so as to clarify the socio-economic meaning of the topological structure of the regional innovation system. On this basis, it provides theoretical references for regional innovation development and sustainable development policy formulation.

1) Background: It has been more than a decade since the concern about addictive use of the Internet and mobile phones was first expressed and its possible inclusion into the lists of mental disorders has been a popular topic of discussion recently, thus it seems to be a fitting moment to investigate the evolution of this issue over time. The aim of the present study was to analyze the evolution of the perception of problematic Internet and smartphone use in young people over the period 2006–2017; 2) Methods: To this end, a questionnaire on Internet use habits and the CERI and CERM questionnaires on negative consequences of Internet and smartphone use were administered to a sample of 792 university students and compared with data from former studies over the period 2006–2017; 3) Results: The perception of problematic Internet and mobile phone use has increased over the last decade, social networks are considered responsible for this increase, and females are the ones perceived to be more affected than males. The degree to which participants agree with the statement “I am addicted to the Internet” can be used as a screening item for problematic use.

Motivation: there is a paradox at the heart of informatics where practical implementation generally fails to understand the socio-technical impact of novel technologies and disruptive innovation when adopted in `real-world’ systems. This phenomenon, termed technological determinism, is manifested in a time-lag between the adoption of novel technologies and an understanding of the underlying theory which develops following research into their adoption. Methods: we consider informatics theory as it relates to: social informatics and how humans’ function in society, the relationship between society and technology, information systems, information systems design, and human-computer interactions. The challenges posed by novel technologies and disruptive innovation are considered as they relate to information systems and information systems design. Open research questions with directions for future research are discussed with an introduction to and our proposed approach to socio-technical information system design. Significance: we conclude that the adoption of disruptive innovation presents both opportunities and threats for all stakeholders in computerised systems. However, determinism is a topic requiring research to generate a suitable level of understanding and technological determinism remains a significant challenge.

At the beginning of 2019, the petroleum crisis impacted many economies dependent on this industry. The Mexican government started programs to identify points and government officials involved in the gasoline stealing from PEMEX (Petróleos Mexicanos), the country’s leading government petroleum company. The programs consisted of supervising and monitoring the Mexican country network of gasoline ducts to detect points where gasoline was being stolen. Consequently, large urban regions faced a lack and shortage of gasoline. This situation generated several reactions in social media and many open data in news media. Although the government provided open data about stealing gasoline locations related to crimes, it did not analyze the collected data to identify patterns, insights, and the spatio-temporal characterization of this phenomenon. This paper presents a study to deal with the regional semantics described in the social media locations of gasoline stealing. Thus, a framework to discover the trends that emerge from social media and how it is correlated with the government’s open data is also presented—the proposed methodology used machine learning techniques based on linguistic and semantic technologies. The analysis was applied to a dataset of 24,317 geo-referenced tweets. The obtained results reflected the Mexican thinking opinion regarding discovered social topics, polarization maps, and regional insights. According to discovered trends, there were long fuel lines between 1.5 and 5 kilometers (on average) at fuel stations in different Mexican states.

This research investigates the economic resilience of small and medium enterprises (SMEs) during financial crises, focusing on the factors that enable these businesses to survive and recover from economic downturns. Employing a qualitative methodology, the study examines various aspects of SME operations, including financial management, innovation, leadership, government support, geographical location, social capital, and contingency planning. The findings reveal that effective financial management—encompassing cash flow management, debt restructuring, and diversified funding sources—is crucial for maintaining stability during financial crises. Innovation and adaptability also play significant roles, with SMEs that embraced new technologies and market strategies demonstrating greater resilience. Leadership emerged as a critical factor, with leaders who communicated effectively and managed stress contributing to their organization's ability to navigate crises. Government support provided essential relief, although its impact varied depending on accessibility and timeliness. Geographical location influenced resilience, with urban SMEs having better access to resources, while rural SMEs benefited from strong community networks. Social capital, including relationships with suppliers and customers, was vital for providing stability and support. Contingency planning and risk management were identified as essential for preparing for and responding to disruptions. The research highlights that resilience is a multifaceted attribute resulting from the interplay of financial prudence, adaptability, effective leadership, supportive policies, geographic factors, and strong social networks. These insights offer valuable lessons for SME owners, policymakers, and support organizations, emphasizing the need for a comprehensive approach to building and sustaining resilience in the face of economic challenges.

This paper aims at addressing the exploitation of solid-state carriers for hydrogen storage, with attention paid both to the technical aspects, through a wide review of the available integrated systems, and to the social aspects, through a preliminary overview of the connected impacts from a gender perspective. As for the technical perspective, carriers to be used for solid-state hydrogen storage for various applications can be classified into two classes: metal and complex hydrides. Related crystal structures and corresponding hydrogen sorption properties are reviewed and discussed. Fundamentals of thermodynamics of hydrogen sorption evidences the key role of the enthalpy of reaction, which determines the operating conditions (i.e. temperatures and pressures). In addition, it rules the heat to be removed from the tank during hydrogen absorption and to be delivered to the tank during hydrogen desorption. Suitable values for the enthalpy of hydrogen sorption reaction for operating conditions close to ambient (i.e. room temperature and 1-10 bar of hydrogen) are close to 30 kJ·molH2 1. The kinetics of hydrogen sorption reaction is strongly related to the microstructure and to the morphology (i.e. loose powder or pellets) of the carriers. Usually, kinetics of hydrogen sorption reaction is rather fast, and the thermal management of the tank is the rate determining step of the processes. As for the social perspective, various scenarios for the applications in different socio-economic contexts of solid-state hydrogen storage technologies are described. As it occurs with the exploitation of other renewables innovative technologies, a wide consideration of the social factors connected to these processes is needed to assess the extent to which a specific innovation might produce positive or negative impacts in the recipient socio-economic system and to explore the potential role of the social components and dynamics in fostering the diffusion of the innovation itself. Attention has been addressed to the gender perspective, in view of the enhancement of hydrogen-related energy storage systems, intended both in terms of the role of women in triggering the exploitation of hydrogen-based storage as well as to the impact of this innovation in their current conditions, at work and in daily life.

Pre-Western contact Hawaiʻi stands as a quintessential sustainability example of a large human population that practiced intensive agriculture, yet minimally displaced native habitats that comprised the foundation of its vitality. An explicit geospatial footprint of human-transformed areas across the pre-contact Hawaiian archipelago comprised less than 15% of total land area, yet provided 100% of human needs, supporting a thriving Polynesian society. A post-contact history of disruption of traditional Hawaiian land-use and its supplanting by Western land tenure and agriculture based on ranching, sugarcane, and pineapple, culminated in a landscape, in which over 50% of native habitats have been lost, while self-sufficiency has plummeted to 15% or less. Recapturing the ʻāina momona (productive lands) of ancient times can be accomplished through study of pre-contact agriculture, assessment of biological and ecological changes imposed on Hawaiian social-ecological systems, and conscious planned efforts to increase self-sufficiency and reduce importation. Impediments include the current tourism-based economy, competition from habitat-modifying introduced species, a suite of agricultural pests severely limiting traditional agriculture, and changes in climate rendering some pre-contact agricultural centers suboptimal. Modified agricultural methods will be required to counteract these limitations, and diversified agriculture to broaden the production base, without contributing to further degradation of native habitats.

Caring for an ill or disabled relative can present significant challenges that may exceed the per-sonal resources of the caregiver. Young carers (YCs) often take on this role, providing support to family members or friends, which can have far-reaching effects on various aspects of their lives. This study involved 235 adolescents, 106 YCs and 129 non-carers (NCs), who completed ques-tionnaires assessing life satisfaction, social support, family functioning, academic functioning, and caring activities. Group effects measured with MANOVA and MANCOVA (controlling for age effects), showed YCs to have higher amounts of caregiving activities than NC (as expected) but lower satisfaction with life. Hierarchical regressions also found that, for YCs, academic func-tioning, social support and the negative impact of caregiving predicted satisfaction with life; and that the negative impact of caregiving on YCs is explained by their family functioning and the amount of their caregiving activities. For NCs, only academic functioning, social support and family functioning predicted satisfaction with life. In conclusion, caregiving has a negative im-pact on YC’s life satisfaction, but this effect is determined by their social support, academic func-tioning and negative impact of caring, which in turn depends on their familiar functioning and amount of caring activities.

This paper aims to present the basic assumptions for creation of social Fröhlich condensate and attract attention of other researchers (both from physics and socio-political science) to the problem of modelling of stability and order preservation in highly energetic society coupled with social energy bath of high temperature. The model of social Fröhlich condensation and its analysis are based on the mathematical formalism of quantum thermodynamics and field theory (applied outside of physics). The presented quantum-like model provides the consistent operational model of such complex socio-political phenomenon as Fröhlich condensation. The model of social Fröhlich condensation is heavily based on theory of open quantum systems. Its consistent elaboration needs additional efforts. Evidence of such phenomenon as social Fröhlich condensation is demonstrated by stability of modern informationally open societies Approaching the state of Fröhlich condensation is the powerful source of social stability. Understanding its informational structure and origin may help to stabilize the modern society. Application of the quantum-like model of Frhlich condensation in social and political sciences is really the novel and original approach to mathematical modeling of social stability in society exposed to powerful information radiation from mass-media and internet based sources.

The growth of social media has changed the face of many aspects of marketing such as online, digital, etc. It also has changed the way modern human communicates and connects with others. Moreover, the behavior on this platform could not and should not be justified with strategies of other marketing channels and media. Due to the nature of social media, they are rich in precise and lean data, but processing these data and extracting knowledge and insights from them are problematic. Evaluating the effectiveness of a marketing endeavor is also a task related to these data. The current research attempts to assess the effectiveness of an advertising campaign on Instagram via advertising cost and sentiment classification of audience opinion regarding the campaign. The methodology used in this research is the standard process of data mining, i.e., CRISP-DM. Furthermore, multiple machine learning models and approaches were studied to train a prediction model based on data. In order to find the most accurate algorithm, grid search was used among the trained models and different algorithms with different combinations of hyper-parameters. The obtained results revealed that although the number of not profitable advertising media was higher than the profitable media, the overall status of the campaign was profitable, both in the cost-effectiveness approach and sentiment analysis approach. The other valued outcome of this research was important general and specific insights which can be used to shape a better-performing and effective advertising campaign on Instagram.

The present study investigates the decision-making process of investors on the Pakistan Stock Exchange with regard to portfolio construction, explicitly focusing on the incorporation of ESG concerns. The present study employed SmartPLS and structural equation modeling (SEM) to quantitatively assess data received from a sample of 393 out of 400 respondents. Based on the available data, investors participating in the Pakistan Stock Exchange are notably impacted by ESG aspects. The findings of this study hold significance for emerging economy firms, regulators, and investors, both in terms of theoretical and practical ramifications. The study's findings demonstrate a clear indication of investors' significant emphasis on ESG matters. Furthermore, it provides valuable insights for stakeholders who are involved in the ever-evolving realm of sustainable finance within developing countries

The aim of the paper is to identify the most likely factors that determine the demand for Renewa-ble Energy Consumption (R.E.C.) in European countries. Although in Europe a high environmen-tal awareness is omnipresent, countries differ in scope and share of R.E.C. due to historical ener-getic policies and dependencies, investments into renewable and traditional energetic sectors, R&D development, structural changes required by energetic policy change, and many other fac-tors. The study refers to a set of macroeconomic, institutional, and social factors affecting energetic renewable policy and R.E.C. in selected European countries in two points of time: i.e., before and after the Paris Agreement. The Bayesian Average Classical Estimates (BACE) is applied to indicate the most likely factors affecting R.E.C. in 2015 and 2018. The comparison of the results reveals that the G.D.P. level, nuclear and hydro energy consumption were the determinants significant in both analyzed years. Furthermore, it became clear that in 2015 the R.E.C. depended strongly on the energy consumption structure, while in 2018, the foreign direct investment and trade openness played their role in increasing renewable energy consumption. The direction of changes is positive and complies with sustainable development goals (S.D.G.s).

The aim of this study was to examine the prevalence of self-reported and parent-reported bullying victimization, perpetration, and victimization-perpetration and the associations of autistic social impairment and attention-deficit/hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD) symptoms with bullying involvement in adolescents with high functioning autism spectrum disorder (ASD). A total of 219 adolescents with high functioning ASD participated in this study. The associations of sociodemographic characteristics, parent-reported autistic social impairment on the Chinese Social Responsiveness Scale, and parent-reported ADHD and ODD symptoms on the Short form of the Swanson, Nolan, and Pelham Version IV Scale (SNAP-IV)-Chinese version with self-reported and parent-reported bullying victimization, perpetration, and victimization-perpetration evaluated using the Chinese version of the School Bullying Experience Questionnaire were examined using logistic regression analysis. The agreement between self-reported and parent-reported bullying involvement was low. Compared with bullying involvement experiences reported by adolescents themselves, parents reported higher rates of pure bullying victimization (23.7% vs. 17.8%) and victimization-perpetration (28.8% vs. 9.1%) but a lower rate of pure bullying perpetration (5.9% vs. 9.1%). Deficit in socio-communication increases the risk of being pure victims and victim-perpetrators. Parent-reported victim-perpetrators had more severe ODD symptoms than did parent-reported pure victims. The agreement between self-reported and parent-reported bullying involvement of adolescents with high functioning ASD was low. Deficit in socio-communication and ODD symptoms were significantly associated with a high risk of bullying involvement in adolescents with high functioning ASD.

Machine learning (ML) is increasingly useful as data grows in volume and accessibility as it can perform tasks (e.g. categorisation, decision making, anomaly detection, etc.) through experience and without explicit instruction, even when the data are too vast, complex, highly variable, full of errors to be analysed in other ways , . Thus, ML is great for natural language, images, or other complex and messy data available in large and growing volumes. Selecting a ML algorithm depends on many factors as algorithms vary in supervision needed, tolerable error levels, and ability to account for order or temporal context, among many other things. Importantly, ML methods for explicitly ordered or time-dependent data struggle with errors or data asymmetry. Most data are at least implicitly ordered, potentially allowing a hidden `arrow of time’ to affect non-temporal ML performance. This research explores the interaction of ML and implicit order by training two ML algorithms on Twitter data before performing automatic classification tasks under conditions that balance volume and complexity of data. Results show that performance was affected, suggesting that researchers should carefully consider time when selecting appropriate ML algorithms, even when time is only implicitly included.

Section 25(2) of the Constitution of South Africa protects property rights and the White Paper on Land Reform demonstrate tolerance and wisdom in the application of land reform policies. The central argument to this research was whether amendment of Section 25 (2) of the constitution to allow expropriation of land without compensation redresses redistribution of land for social cohesion and political stability. The researcher argues that, currently, Section 25 of the constitution provides for expropriation without compensation but at the same time protects property rights reducing the pace of redistribution. Hence, an amendment of section 25 (2) may remove the property right clause and accelerate expropriation without compensation. But whether the removal of the property right clause and acceleration of the process of expropriation without compensation will result to equitable and fair distribution of land to the majority of landless South Africans is not certain. The study concludes that, amendment of Section 25(2) is a justifiable process and priorities must be given to equity in redistribution to the majority landless at the margins of communities and not elites. If the amendment of Section 25 (2) cannot guarantee equity in redistribution for all ill respective of race, social cohesion, political stability and economic growth, intra-racial tensions may emerge. Such tensions may further compound the land question and affects investors’ confidence in South Africa.

This study investigates the influence of digital marketing on consumer purchasing decisions, focusing on how various strategies impact consumer behavior. By analyzing data collected from in-depth interviews and thematic analysis, the research highlights several key factors driving consumer engagement and purchases. Personalized content emerged as a significant factor, with tailored recommendations and customized email campaigns creating a sense of individual attention and enhancing consumer involvement. Social media platforms played a pivotal role, with advertisements, influencer endorsements, and user-generated content significantly affecting purchasing decisions. The impact of visual content, including high-quality images and videos, was also notable, as these elements helped consumers better understand products and increased their confidence in making purchases. Email marketing proved effective, particularly when offering exclusive discounts and creating a sense of urgency. Mobile marketing demonstrated its growing influence, with consumers valuing the convenience of mobile-friendly websites and app notifications. The integration of artificial intelligence further improved the shopping experience by providing instant assistance and personalized recommendations. Ethical considerations, such as data privacy and honest advertising, were essential for maintaining consumer trust and loyalty. User-generated content provided authentic insights that influenced purchasing decisions, while omnichannel strategies offered a seamless and flexible shopping experience. Gamification elements, including reward programs and interactive challenges, enhanced consumer engagement and motivation. The study concludes that a multifaceted approach to digital marketing, incorporating these strategies, is crucial for effectively engaging consumers and driving sales. The findings offer valuable insights for marketers aiming to optimize their digital marketing strategies in the evolving digital landscape.

The Coronavirus (COVID-19) pandemic has created big challenges and opportunities in Higher Education (HE). In this situation, several universities worldwide have responded with digital methods and hybrid classes in a short period of time. The aim of this paper is to show how the universities have adapted teaching methods to digital platforms in the academic year 2020–21. This case study is based on the experience of 37 postgraduate communication students in the course Business and Communication from a Communication Programme. The objective of this course was to promote the 17 sustainable development goals (SDGs) in business and following the Principles for Responsible Management Education (PRME) of the United Nations. To do this, the students provided different solutions related to the SDGs and developed a communication strategy to inform and engage the stakeholders in the companies analyzed in a hybrid class. The results show that using this methodology and working in digital platforms, students have learned the importance of SDGs through implementing specific solutions linked to the corporate social responsibility (CSR) strategy. Based on this analysis, they also developed a communication strategy showing how companies can improve society with specific actions through the lens of the SDG perspective.

The main goal of the study is to assess the Decision criteria, and the determining factor for the sustainability of entrepreneurial startups in order to contribute towards social inclusion and capacity building. Both concepts are in the development phase and are the outcome of entrepreneurial ecosystem and individual behavior and traits. The current study observed the research problem as entrepreneurship and the entrepreneurial startups are the continuous phenomena required for every economy. The lack of an efficient ecosystem and incompetent trait of an entrepreneur drags the entrepreneurial startup to a failure. Therefore, an assessment on decision criteria and determining factors categorizing them with their importance may provide requisites to lead a successful entrepreneurial startup contributing to the social inclusion and capacity building. The study solved the research problem by statistical assessment of decision criteria and determining factors and categorizing them with their importance may provide requisites to lead a successful entrepreneurial startup. The research is built on research questions, objectives, conceptual model, and hypothesis which are tested based on the data collected. The collection of data was done through a survey questionnaire on a sample of established entrepreneurs. The study concludes that five components of decision criteria are Region, Competition, Funding Opportunities, Tax System, and Country Economic Situation, whereas the eight components Consciousness and Reliable, Pursuit Results, Flexibility, Stress Resistance, Skills Identification Exploitation Potential Market Opportunities, Leadership, Creativity and Innovation, and Delegation Decision Making of determining factor are required for a successful entrepreneurial startup to be able to work towards social inclusion and capacity building.

This paper considers two types of Protestant ethnic groups of some areas of Urals and Western Siberia. The first type consist of representatives of members of different ethnic groups consisting of well-educated professionals, incorporated into industrial society and associated with the intellectualism of Protestantism. The second type is represented by the indigenous peoples of the Polar Urals and Western Siberia, who use the Protestant religious organizations as tool for restoring life-sustaining elements of the native peoples’ traditional economy. I employed the inductive approach and the comparison method; during the fieldwork I used ethnographic participant observations, sociological structured interviews and closed-ended questionnaires. The empirical data have been collected in the Southern, Middle and Polar Urals and Western Siberia.

Disease outbreaks can severely affect populations in the wild. However, their ecological consequences are poorly understood. Here, we used a multi-site capture-recapture model to investigate the impacts of a yellow fever outbreak on the endangered golden lion tamarin Leontopithecus rosalia, in the Atlantic forest, Brazil. We show that the annual adult survival rate severely declined in 2017-2018, coinciding with the outbreak period. Simultaneously, dispersal patterns changed temporarily, with a slight reduction of dispersal between groups of the same forest fragment from 3.6 to 2.8%, and a strong increase of dispersal between forest fragments, from 0.4 to 4.3%. Those results suggest that disease transmission potential was low, especially between forest fragments and advocate for a better integration of host movements and landscape configuration when evaluating species response to vector-borne diseases

This study investigated the capability of vocal-identity-cloning Artificial Intelligence (AI) to encode human-specific confident, doubtful, and neutral-intending emotive states. Linear mixed-effects models and machine learning classification with eXtreme Gradient Boosting were employed to examine the underlying acoustic signatures from 2,700 audio clips, comprising of sentences spoken by human speakers and two sets of equivalences (AI-Geography/AI-Trivia, based on the trained text) generated by voice-cloning models designed to clone human speakers’ identities. Compared with neutral-intending voice, human speakers lengthened their vocal tract, raised the fundamental frequency, and increased Chroma constant-Q transform when they intended to be confident; An opposite pattern was shown when they intended to be doubtful. The two sets of AI sounds displayed a similar pattern to human speech, suggesting a shared mechanism for encoding vocal expression across sources. The 1,000 times training-testing classification models reported an in-group advantage for AI sources. The algorithms, trained on AI-Geography/AI-Trivia, resulted in higher accuracies when tested within these AI sources than when tested on human audio. All between-source classifications reported above-chance-level (1/3) accuracies. These findings highlighted that voice-cloning AI, the widely used conversational agent, can learn and generate human-specific vocally-expressed confidence.

This study assesses the impact of incorporating an adaptive learning mechanism into an agent-based model (ABMS) simulating behavior on a university campus during the course of a pandemic outbreak, with a particular case on the COVID-19 pandemic. The aim is to reduce overcrowding and infections on campus through the use of Reinforcement Learning (RL). Our findings indicate that RL is a viable approach for effectively representing agents’ behavior within this context. The results reveal specific temporal patterns of overcrowding violations. While our study successfully mitigated campus crowding, it had limited influence on altering the course of the epidemic. This highlights the necessity for comprehensive epidemic control strategies that consider the role of individual decision-making influenced by adaptive learning, along with the implementation of targeted interventions. This research significantly contributes to our understanding of adaptive learning within complex systems and offers valuable insights for shaping future public health policies in similar community settings. Future research directions encompass exploring various parameter settings and updating representations of the disease’s natural history.

The article aims to explore social aspects in the area of energy research by using bibliometrics methods and tools. The study is based on the data of Energy Research & Social Science journal publications exported from ScienceDirect database during 2019-2023. Methodologically, the work included clustering of the bibliometric records under consideration. This allowed to identify the main topics of publications and those in which the research of social problems prevails. This stage of the work was carried out using carrot2, an engine for clustering search results. Next, the analysis of publication topics related to social issues research was carried out using VOSviewer — a software tool for visualizing scientific landscapes. The topics of the four clusters obtained at this stage were described by key terms with the maximum total link strength. For the principal ones, a definition was made on the basis of the texts of publications that most fully disclose the meaning of these terms. The 1537 publications in the journal during the period under review deal with many aspects of energy transition research, renewable energy, energy policy, energy justice and energy systems, but only 78 of them are dominated by social issues. The paper reveals the main social issues in the field of energy research: sociology of energy, socio-technical system, community energy, energy democracy, sociology of the future, energy sovereignty, socio-technical imaginary and shows the insufficient attention to this topic, especially to the investment of such research.

Social networks have captured the attention of many people worldwide. However, these services have also attracted a considerable number of malicious users whose purpose is to compromise digital assets of other members by using messages as an attack vector to execute different variants of cyberattacks against them. Therefore, this work presents an approach based on Natural Language Processing tools and a Convolutional Neural Network architecture to detect and classify, on social network messages, four types of cyberattacks, such as malware, phishing, spam, and even one whose purpose is deceiving the user into spreading malicious messages to other users, which in this work is identified as bot attacks. One notable feature of this work is that it analyzes textual content without depending on any characteristics from a specific social network, making its analysis independent from particular data sources. Finally, this work was tested on real data, demonstrating its results in two stages. The first detects the existence of any of the four cyberattacks within the message, obtaining an accuracy value of 0.91. After detecting a message as a cyberattack, the next stage is to classify it into one of the four types of cyberattack, achieving an accuracy value of 0.82.

This paper investigates how agroecology in Africa is researched for two purposes. First, we present evidence of links between agroecology and food and nutrition security in sub-Saharan Africa. Second, we investigate which pathways of influence are dominant in the existing research and which pathways are under-represented. To achieve these objectives we anchor our analysis within feminist economics, thereby making use of the concepts of social reproduction and agency in our analysis of the literature. By employing a systematic literature review of empirical studies from African countries, starting from 1996 to 2020, we consolidate evidence that agroecology has contributed to food and nutrition security by acting toward sustainability at the farm level. However, our review shows in a second step that social and household dimensions of agroecology at the level of households and territories are not well documented in research linking agroecology to food security and nutrition in sub-Saharan Africa. Given that sustainable production practices such as agroecological practices are not mutually exclusive from the social activities of farmers and cultural contexts in which farmers are embedded, it is important to consider social and ecological processes concomitantly when assessing the value of Agroecology programs.

The herd effect is a common phenomenon in social society. The detection of this phenomenon is of great significance in many tasks based on social network analysis such as recommendation. However, the research on social network and natural language processing seldom focuses on this issue. In this paper, we propose an unsupervised data mining method to detect herding in social networks. Taking shopping review as an example, our algorithm can identify other reviews which are affected by some previous reviews and detect a herd effect chain. From the overall perspective, the cross effects of all views form the herd effect graph. This algorithm can be widely used in various social network analysis methods through graph structure, which provides new useful features for many tasks.

The study examines the relationship between corporate social responsibility (CSR) and the corporate life cycle (CLC) of the Chinese pharmaceutical listed companies for the duration of 2010 to 2018. The firm cash flow pattern is used as a proxy for the CLC. The study results indicate that the relationship between CSR and CLC is positive and linear in all the phases of the CLC including, the introduction, growth and maturity stage. Although the relationship is smaller and more significant at the maturity phase. The research further shows that investors incorporating social responsibilities values play a key role in the firm cash flow performance (CFP) across all the firm stages. Whilst, employees espousing social responsibility tenets can only improve CFP in the decline or shakeout stages. Likewise, embedding CSR into the customers group only improves CFP at the maturity stage. Applying the lag effects lead to the same study results. The finding for the bi-directional causality indicates that although CSR can positively influence CFP, CFP is ultimately more associated with the firm unobservable characteristics rather than performance attributed to CSR. On the whole, our study results point to positive causality between CSR and CFP across all the firm life stages and the CSR has a mediating effect on each life cycle.

We transformed the existing learning program Language Shower, which is used in some Norwegian day-care centers in the Grorud district of Oslo municipality, into a digital solution using an app for smartphone or tablet with the option for further enhancement of presentation by a NAO robot. The solution was tested in several iterations and multiple day-care centers over several weeks. Measurements of the children’s progress across learning sessions indicate a positive impact of the program using a robot as compared to the program without robot. In-situ observations and interviews with day care center staff confirmed the solution’s many advantages, but also revealed some important areas for improvement. In particular, the speech recognition needs to be more flexible and robust, and special measures have to be in place to handle children speaking simultaneously.

This paper presents a requirements specification analysis for driving the design of new systems that will allow 3D media creators to further promote and monetize from their work. The provided requirements analysis is based on the IEEE 830 standard for requirements specification. It allows us to elucidate system requirements through existing (AS-IS) and envisioned (TO-BE) scenarios affected by the latest trends on design methodologies and content promotion in social media. A total of 30 tools for content creation, promotion and monetization are reviewed. The target groups, i.e. creator groups, are divided in 10 types according to their role in 3D media production. Based on this division 10 candidate TO-BE scenarios have been identified and out of these 10 scenarios, we have selected 6 scenarios for validation by media creators. The validation was performed through a survey of 24 statements on a 5 Likert scale by 47 individuals from the domains of Media, Fine arts, Architecture, and Informatics. Useful evaluation results and comments have been collected that can be useful for future systems design.

The COVID-19 pandemic and associated restrictive measures implemented may considerably affect people’s lives. This study aimed to assess the well-being of Vietnamese people after COVID-19 lockdown measures were lifted and life gradually returned to normal. An online survey was organized from 21st to 25th April 2020 among Vietnamese residents aged 18 and over. Besides collecting socio-demographic and COVID-19-related data, the WHO-5 Well-Being Index (scored 0–25) was used to score participants’ well-being. A multivariate logistic regression model was used to determine the predictors of well-being. A total of 1922 responses were analyzed (mean age: 31 years; 30.5% male). Mean well-being score was 17.35±4.97. Determinants of high well-being score (≥13) included older age, eating healthy food, practising physical exercise, working from home, and adhering to the COVID-19 preventive measures. Female participants, persons worried about their relatives’ health, and smokers were more likely to have a low well-being score. In conclusion, after the lockdown measures were lifted, the Vietnamese people continued to follow COVID-19 preventive measures and most of them scored high on the well-being scale. Waiting to achieve large scale COVID-19 vaccine coverage, promoting preventive COVID-19 measures remains important, together with strategies to guarantee the well-being of the Vietnamese people.

This paper reports on the changing dynamics of a small town’s social-ecological system (SES) concerning oil and gas industry boom-bust economic cycles and both the vulnerability and resilience of the town over the past 30 years. With the goal to understand how resource-based single industry impact social-ecological systems, we developed indicators of human and environmental well-being and assessed them. Seven indicators include labor force distribution, education, oil price, household income, water quality, air quality, and land cover land use. Over this period, Drayton Valley, Canada quadrupled in size, with more than 20% of the population working in the oil and gas sector. Median income rose to 42% above the national average despite the population lagging national benchmarks for educational attainment. There have also been dramatic fluctuations in levels of fluoride, phosphorus, and other chemicals in water quality samples, implying a correlation with fossil fuel extractive activities over this period. Land cover land use change analysis shows a decreased area of water bodies, wetland, and forests, and increased built capital and agricultural land. While economic boom cycles have led to cash inflows, an exclusive focus on the benefits of the oil and gas industry may leave those dependent on the industry vulnerable to social and environmental risk factors during bust cycles that are beyond their control in the everchanging global oil economy. This phenomenon which has been referred to as the “resource curse” suggests the need to anticipate cyclical (or more sustained) periods of low levels of oil and gas production. These results suggest that single boom-bust economies impact every aspect of social-ecological systems. Therefore, a sustainable development plan that comprehensively considers not only economic growth, but also diversification, environment protection, and strategic land use planning is indispensable to ensure the long-term development of communities that depend upon extractive industries.

Social networking applications such as Twitter have increasingly gained significance in terms of socio-economic, political, and religious as well as entertainment sectors. This in turn, has witnessed a wide gamut of information explosion in the social networking realm that can tend to be both useful as well as misleading at the same point of time. Spam detection is one such solution that caters to this problem through identification of irrelevant users and their data. However, existing research has so far laid primary focus on user profile information through activity detection and relevant techniques that may underperform when these profiles exhibit characteristics of temporal dependency, poor reflection of generated content from the user profile, etc. This is the primary motivation for this paper that addresses the aforementioned problem of user profiles by focusing on both profile information and content-based spam detection. To this end, this work delivers three significant contributions. Firstly, exhaustive use of Natural language processing (NLP) techniques has been rendered towards creation of a new comprehensive dataset with a wide range of content-based features. Secondly, this dataset has been fed into a customized state-of-art hybrid machine learning model that has been exclusively built using a combination of both machine learning and deep learning techniques. Extensive simulation based analysis not only records over 98% accuracy but also establishes the practical applicability of this proposal by proving that modeling based on the mixed profile and content-generated data is more capable of spam detection in contrast to each of these standalone approaches. Finally, a novel methodology based on logistic regression is proposed and supported by analytical formulations. This paves the way for the custom-built dataset to be analyzed and corresponding probabilities to be obtained that differentiate legitimate users from spammers. The obtained mathematical outcome can henceforth be used for future prediction of user categories through appropriate parameter tuning for any given dataset. This makes our method a truly generic one capable of identifying and classifying different user categories.

The success of many viruses depends upon cooperative interactions between viral genomes. For example, viruses that coinfect the same cell can share essential gene products, such as replicase, the enzyme that replicates the viral genome. However, when cooperation occurs, there is the potential for ‘cheats’ to exploit that cooperation. We suggest that: (1) the biology of viruses makes viral cooperation particularly susceptible to cheating; (2) cheats are common across a wide range of viruses, including viral entities that are already well studied, such as defective interfering genomes, and satellite viruses. Consequently, evolutionary theory developed to explain cheating offers a conceptual framework for understanding and manipulating viral dynamics. At the same time, viruses offer unique opportunities to study how cheats evolve, because cheating is relatively common in viruses, compared with taxa where cooperation is more usually studied, such as animals.