We investigate the relationship between social isolation and subjective health, considering that this relationship is potentially affected by endogeneity due to the presence of self-reported measures. Thus, if an increase in social isolation may impact the perception on health, alternative paths of causality may also be hypothesized. Using data from round 7 of the European Social Survey, we estimate an instrumental variable model in which isolation is explained as being a member of an ethnic minority and having experienced some serious family conflicts in the past. Our results confirm that changes in social isolation influence subjective general health. In particular, greater isolation produces a strong and significant deterioration of the perceived health status. With respect to the literature on social isolation and health, we try to advance it by supporting a path of causality running from social isolation to subjective health.

Social distancing is a recommended solution by the World Health Organisation (WHO) to minimise the spread of COVID-19 in public places. The majority of governments and national health authorities have set the 2-meter physical distancing as a mandatory safety measure in shopping centres, schools and other covered areas. In this research, we develop a Deep Neural Network-based Model for automated people detection, tracking, and inter-people distances estimation in the crowd, using common CCTV security cameras. The proposed DNN model along with an inverse perspective mapping technique leads to a very accurate people detection and social distancing monitoring in challenging conditions, including people occlusion, partial visibility, and lighting variations. We also provide an online infection risk assessment scheme by statistical analysis of the Spatio-temporal data from the moving trajectories and the rate of social distancing violations. We identify high-risk zones with the highest possibility of virus spread and infection. This may help authorities to redesign the layout of a public place or to take precaution actions to mitigate high-risk zones. The efficiency of the proposed methodology is evaluated on the Oxford Town Centre dataset, with superior performance in terms of accuracy and speed compared to three state-of-the-art methods.

In recent years, online social networks have received important consideration in spatial modelling fields given the critical information that can be extracted from them for events in real time; one of the most latent issues is that regarding various natural disasters such as earthquakes. Although it is possible to retrieve data from these social networks with embedded geographic information provided by GPS, in many cases this is not possible. An alternative solution is to reconstruct specific locations using probabilistic language models, more specifically those based on Name Entity Recognition (NER), which extracts names from a user’s description about an event occurring in a specific place (e.g., a collapsed building on a specific avenue). In this work, we present a methodology to use twitter as a social sensor system for disasters. The methodology scores NER locations with a kernel density estimation function for different subtopics originating from a natural disaster and that maps them into a geographic space is proposed. The proposed methodology is evaluated with tweets related to the 2017 earthquake in Mexico.

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.

The capabilities of autonomous mobile robotic systems have been steadily improving due to recent advancements in computer science, engineering, and related disciplines such as cognitive science. In controlled environments, autonomous robots have been able to achieve relatively high levels of autonomy. In more unstructured environments, however, the realisation of autonomous mobile robots remains challenging due to limitations in the robots’ external environment understanding. Many autonomous mobile robots use classical, learning-based or hybrid approaches for navigation. The classical navigation approach typically includes robot perception, localisation, environmental mapping, path planning and motion control stages. More recent learning-based methods may replace the complete navigation pipeline or selected stages of the classical approach. For effective deployment, autonomous robots need to be able to understand their external environments at a sophisticated level according to their intended applications. Therefore, in addition to robot perception, scene analysis and higher-level scene understanding (e.g., traversable/non-traversable, and rough or smooth terrain) are required for autonomous robot navigation in unstructured outdoor environments. A wide number of alternative approaches have been proposed in recent years to attempt to address these scene understanding requirements. This paper provides a comprehensive review and critical analysis of these methods in the context of their applications to the problems of robot perception and scene understanding in unstructured environments, and the related problems of localisation, environment mapping and path planning. State-of-the-art sensor fusion methods and multimodal scene understanding approaches are also discussed and evaluated within this context. The paper concludes with an in-depth discussion regarding the current state of the autonomous ground robot navigation challenge in unstructured outdoor environments and the most promising future research directions to overcome these challenges.

Background: The primary objective worldwide during the COVID-19 pandemic has been controlling disease transmission. However, lockdown measures used to mitigate transmission have affected human behavior and altered lifestyles, with a likely impact on chronic non-communicable diseases. More than a year into the pandemic, substantial peer-reviewed literature has emerged on altered lifestyles following the varying lockdown measures imposed globally to control the virus spread. Objective: To explore the impact of lockdown measures on the six lifestyle factors, namely diet, physical activity, sleep, stress, social connectedness, and the use of tobacco, alcohol, or other harmful substances.Methods: We comprehensively searched PubMed and the World Health Organization’s global literature database on COVID-19 and retrieved 649 relevant articles for the narrative review. A critical interpretative synthesis of the articles was performed.Results: Most of the articles included in the review identified the negative effect of lockdown measures on each of the lifestyle factors in many parts of the world. Interestingly, encouraging lifestyle trends were also highlighted in a few articles. Such trends can positively influence the outcome of lifestyle-related chronic diseases, such as obesity and diabetes.Conclusions: The COVID-19 pandemic provides an opportunity to better understand the negative impact of strict lockdown measures on lifestyles. At the same time, it helps us identify and initiate positive behavioral changes, which, if consolidated, could improve chronic disease outcomes. It is up to governments, communities, and healthcare/academic entities to derive benefit from lessons learned from the pandemic, with the ultimate objective of better educating and promoting healthy lifestyles among communities.

The COVID-19 pandemic situation, disease intensity, weak healthcare facilities, unawareness, and misinformation led people to fear and anxiety in Bangladesh. This study intended to get peoples’ perception on psychosocial, socio-economic and environmental crisis amidst the pandemi. An online questionnaire was surveyed nationwide (respondents no.1066). Datasets were analyzed through the Principal Component Analysis (PCA), hierarchical Cluster Analysis (CA), Pearson’s correlation matrix (PCM), Linear regression analysis (LRA), and psychometric characteristics were included in the Classical Test Theory (CTT) analysis. There were good associations among the psychosocial, socio-economic and environmental parameters. A significant association between fear of COVID-19 with struggling healthcare system (p<0.05) was found. Also, negative association between fragile health system and government’s ability to deal with the pandemic (p<0.05) revealing poor governance. Again, a positive association of shutdown and social distancing with fear of losing life, and due to lack of health treatment (p<0.05) reveals that shut down hampers normal activities which may lead to mental and economic stress. However, a positive association of socio-economic impact of the shutdown with poor people’s suffering, the price hike of basic need, hamper of formal education (p<0.05) may lead to severe socio-economic and health crisis. There is a possibility of climate-induced disaster during/after the pandemic, which will create severe food insecurity (p<0.01). Daily wage earners and poors will suffer most by food and nutritional deficiency, and the country may face huge economic burden. Proper risk assessment and communications is needed to alleviate fear and anxiety. Thus, financial support and mental boosting is required.

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.

Artificial Intelligence (AI) experienced significant advancements in recent years, and its impact is already recognized across various industries. Yet, the rise of AI has led to a growing concern about its impact on meeting the Sustainable Development Goals (SDGs). The aim of this paper was to evaluate contributions and the potential impact of AI to sustainable development in the society domain. Furthermore, the study analyzed GPT-3 responses, as one of the largest language models developed by OpenAI, descriptively. We conducted a set of queries on the SDGs to gather infor-mation on GPT-3`s perceptions of AI impact on sustainable development. Analysis of GPT-3’s contribution potential towards the SDGs showcased its broad range of capabilities for contributing to the SDGs in areas such as education, health, and communication. The study findings provide valuable insights into the contributions of AI to sustainable development in the society domain and highlight the importance of proper regulations to promote the responsible use of AI for sustainable development. We plan subsequent research for effects on ecologic and economic domains of SDGs. We highlighted the potential for improvement in neural language processing skills of GPT-3 by avoiding imitating weak human writing styles with more mistakes in longer texts.

As professionals, social workers have a special position in relation to considering the needs of children with cancer and their families. Hence, it is important to recognize the experiences and challenges of social workers to improve care of their clients. This study was a qualitative content analysis that aimed to determine a comprehensive understanding of 19 pediatric oncology social workers’ experiences in Iran. Data were collected using semi structured interviews and field observations, analyzed through face content analysis. Concepts extracted from social workers’ experiences consisted of the nature of oncology work, lack of professional competence, low organizational support and professional inferiority that were related to main concept of "exhausting and stressful service". The results indicated that social workers' involvement in stressful and emotionally demanding situations and professional and organizational challenges caused personal exhaustion. In addition to explaining the social workers’ experiences and related factors, the results emphasize the importance of taking care of service providers to prevent them becoming stressed and exhausted. It is also important to protect patients from the consequences of stressed and exhausted care providers so further research is recommended to develop specific intervention.

Urban development and planning are increasingly centered on matters of sustainability, balancing economic development with ecosystem services and biotic structures within urban environments. In addition to these institutional and structural factors, the decision-making process within individual households must be understood to address rising concerns about water use. Therefore, individual characteristics and preferences that influence the use of water also warrant examination. In response to a survey of occupants of single-family residences in the Fresno Clovis Metropolitan Area of California, contextual interviews and focus group interviews with a homeowner sub-sample, we find evidence of an interplay of social-structural, institutional, and cultural factors involved in influencing individual water use behaviors and landscape decision making. The complexity of residential behaviors and decision-making poses some potential issues with regards to the interactions between individual households and institutional actors in matters of water usage and landscaping, as survey respondents indicate relatively little confidence in institutions and groups to make wise water policy decisions. We conclude that the promotion and implementation of sustainable water use practices will require not only environmental education for the citizenry, but also a tailoring of information for environmental educational initiatives that address the particularities of individual neighborhoods and communities.

Motivated by the #Metoo movement, we explore in this paper people’s perception of female bullying at workplace. We looked at #workplacebullying and found that 1) people were split between identifying the prevalence of workplace bullying against female and the view that such bullying simply does not exist and is a nuisance, 2) The tweets also showed the existence of psychological effects of cyberbullying, and 3) the tweets showed many intervention techniques that can minimize the effects of such bullying. We further explored the top three recurring hashtags mentioned under the #workplacebullying and found that the three top hashtags were #sexism, #feminism and #equality. Our results showed that the above hashtags represent the positive and negative approach to workplace bullying i.e. #feminism hashtag was mostly used by people who denied that workplace bullying against females exist while # sexism was mentioned as the prime cause by people who agree that such bullying exist. #equality overwhelmingly comprises of techniques to minimize workplace bullying against females.

Misinformation can amplify humanity's most significant challenges. As the novel coronavirus spreads across the world, concerns regarding the spreading of misinformation about it and also people downplaying the severity of it are also growing. This article investigates social media activity in May 2020, specifically Twitter, with respect to COVID-19, the themes of tweets, where the discussion is emerging from, disinformation shared about the virus, and its relationship with COVID-19 incidence rate at the state and county level. A geodatabase of all geotagged COVID-19 related tweets was compiled. Multiscale Geographically Weighted Regression was employed to examine the association between social media activity, population, and the spatial variability of disease incidence; our results suggest that MGWR could explain 96.7% of the variations. Moreover, Covid-19 related twitter dataset content analysis reveals a meaningful strong spatial relationship that exists between social media activity and known cases of COVID-19. Discourses analysis was conducted on tweets to index tweets downplaying the Pandemic or disseminating disinformation; the discourses analysis findings suggest that states in where twitter users spread more misinformation and showed more resistance to pandemic management measures in May are experiencing a surge in the number of cases in July.

In today's digital landscape, the use of smartphones is almost inevitable, and so is the pervasive use of social media (SM), a constantly evolving system that has become an integral part of the daily lives of adolescents. Over the past seven years, the usage of social media platforms such as Instagram, Twitter, and TikTok has seen exponential growth among younger audiences. Excess SM use has raised concerns. This paper examines the possible negative consequences of the escalating trend in social media usage, and the implications of social media addiction (SMA), especially platforms featuring short-form video content, among teenagers. The paper also addresses the debate surrounding the validity of the term "addiction" concerning social media overuse and highlights the neurobiological processes associated with addiction, including the activation of dopamine-related brain structures. Furthermore, it discusses the researched structural and functional changes to the adolescent brain, including drawing parallels with substance addictions based on neuroimaging studies. Finally, this review advocates for exploring avenues of regulation to ensure a safer digital future, emphasizing the importance of policy to mitigate unforeseen long-term consequences of SMA and provides recommendations for reasonable and efficient future policy directions, guided by scientific and health concerns rather than political motives.

COVID-19 has created anxiety not only in individuals but also in health organizations, and countries worldwide. Not a single industry is left un-influenced and loss is being estimated in billions of dollars. The widespread of this pandemic disease has challenged researchers all over the world. Some of the researchers are working to invent its cure while, others are applying computing technologies to stop its spread, by analyzing and identifying patterns for prediction and forecasting. This is by no doubt the hottest area of research for the last 100 years. This survey has targeted the research published in computing sub-domains to combat the pandemic. The survey has clustered the scientific efforts into logical groups: surveillance, metrological effects, social media analytics, image processing and business and economy, analysis and modeling. It will serve as a leading source for the followings: researchers who want to identify what has been achieved in different computing sub-domains, those who need fresh authenticated datasets openly accessible for different research contexts and what are future directions in this area of research. The findings of analysis and modeling can be also useful for government agencies who want to set priorities and formulate policies.

Investors are currently obliged to take ESG (Environment, Social, Governance) issues into consideration as part of their fiduciary duty. As such, it becomes increasingly important to identify sustainable investments that hold financial value as well. A sector where this is especially underdeveloped is real estate. This has a lot to do with the obfuscated conceptualization of ESG. The article identifies key gaps in literature and practice, and provides a framework to further the understanding of how ESG factors can add societal and financial value in the real estate sector. A key premise of the article is that the user in the building is grossly overlooked. Drawing on insights from behavioral social science and environmental psychology, the paper explains the role of the user in improving buildings’ ESG, also taking into account the investment value. To conclude, the article makes the case that the transition to user-centered smart real estate is the solution to improving both the environmental (E) and social (S) sustainability of buildings, as well as their investment value. Therefore, practitioners and academics are encouraged to critically evaluate and contextualize the ESG framework they are using, as well as the extent to which users are considered and smart technology is employed.

The access to agricultural information in Sudan continues to be challenging to farmers due to use of inadequate sources and traditional extension approaches. The rapid growth of smart-mobile phones usage in developing countries resulted in several advantages compared to other alternatives in term of costs, geographic coverage and ease of use. This research was conducted in North Kordofan Sate to explore the role of smart-mobile phone in accessing agricultural information. Primary data were obtained by structured questionnaires and focus group discussion through participatory rural appraisal and observation while secondary data were collected from scientific journals, books and authenticated web sources. A number of 230 respondents (10% from total farmers) were interviewed and five focus group discussions were done. Statistical Packages for Social Science (SPSS) version 22 was used to analyze the data with aid of descriptive statistics and Chi-squire Test. The result indicated that most of the respondents fall in age group between 21-40 years, and they depend on farm activity. There was 90% of farmers processed mobile phone since more than three years ago, 90.8%continuedto use smart mobile phone to access agricultural information and showed positive contribution towards income generation. The results also revealed that there was positive perception towards using mobile phones which showed more efficient in use than radio and TVs. The results showed great advantages of using smart mobile phone where 75.2 % of respondents preferred to get agricultural information, logistics and other needs through successful communication in the mid of agricultural season. Results of Chi-squire test showed significant differences between the parameters tested. The study recommended that farmers should be connected with mobile phones to admit ease communication with agricultural extension offices and quick access to their needs and logistics.

Since the late 1980s the idea of sustainable development has been gaining widespread recognition as a guiding framework for policies on development and the environment. However, the concept of sustainable development has received a number of criticisms, including its over-emphasis on meeting human needs through economic growth, as well as its failure to recognize dynamic human-environment interactions. In response to these shortfalls, the concepts of resilience and adaptive governance have emerged as alternative perspectives for pursuing sustainable development. Resilience in social-ecological systems emphasizes the capacity of coupled human-environment systems to deal with change while continuing to develop. Adaptive governance relies on diverse and nested institutional mechanisms for connecting actors across multiple scales to manage conflicts and uncertainties in ecosystem management processes. However, the ethical dimensions of resilience and adaptive governance have not received enough attention. A promising ethical perspective for guiding policies on human-environment interactions is the philosophy of deep ecology which highlights the need for recognition of the intrinsic values of all living things, as well as the nurturing of ecological and cultural diversity. We argue that an integration of the principles of deep ecology and adaptive governance provides a complementary set of ethical principles and institutional attributes that offers better prospects for pursuing sustainable development in the era of the Anthropocene. The implications of this integrative agenda include: adoption of a holistic conception of dynamic human-environment interactions; recognition of diverse knowledge systems through an anti-reductionist approach to knowledge; promotion of long term sustainability through respect for ecological and cultural diversity; and embracing decentralization and local autonomy. We further illustrate this integrative agenda using the management of protected areas as a case study.

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

Smartphone devices, particularly android devices used by billions of people everywhere in the world. Similarly, this increasing rate attracts mobile botnet attackers that is a network of interconnected nodes operated by command and control (C&C) method to expand malicious activities. At present, mobile botnet attacks carried Distributed denial of services (DDoS) that causes to steal sensitive data, remote access, spam generation, etc. Consequently, various approaches are defined in the literature to detect mobile botnet using static or dynamic analysis. In this paper, we have proposed a novel hybrid model, which is a combination of static and dynamic method that relies on machine learning to identify android botnet applications having C&C capability. The results evaluated through machine learning classifiers in which Random forest classifier outperform other ML techniques, i.e. Naïve Bayes, Support Vector Machine, and Simple logistics. Our proposed framework can achieve 97.48% accuracy in detecting such harmful applications. Furthermore, we highlight some research directions and possible solutions regarding botnet attacks for the entire community.

Autism spectrum disorder (ASD) is a heterogeneous neuropsychiatric problem with a few core symptoms: weaknesses in social behavior, verbal impairments, repetitive behavior and restricted interests. Beyond the core symptoms, autism has strong association with other disorders such as intellectual disability, epilepsy, schizophrenia among many others. This paper outlines a theory of ASD with capacity to connect heterogeneous ‘core’ symptoms, medical and psychiatric comorbidities as well as other etiological theories of autism in a unifying cognitive framework rooted in neuroscience and genetics. Cognition is embedded into an ever-developing structure modified by experiences, including the outcomes of environment influencing behaviors. We introduce the hypothesis that autism is caused by deficits in component-based cognition and the internal learning reinforcing machinery. Specifically, we outline our Cartesian Factor forming autoencoder like model that supports cognition by breaking combinatorial explosion and discuss the cognitive and neural processes behind our model. The high dimensionality of sensory information poses serious problems, since the brain can handle only 7±2 relevant variables at a time making processes, such as the extraction and encoding of the relevant variables and their efficient manipulation critical. These processes are influenced by previous experiences and the internal reward system. In addition, large delays of distributed information processing should be counteracted by learned predictive models to synchronize sensory, proprioceptive, and cognitive signals and have timely and accurate model-based actions. Impairments in any of these aspects may disrupt learning and execution. Combinations of small impairments may allow the solving of low complexity tasks but may become visible if learned variables and the related metric are improper and imprecise, respectively, especially if their number is large. We claim that social interactions are amongst the most challenging cognitive tasks in terms of the number of variables involved. In turn, they are highly susceptible to combinations of small impairments. We consider impairments as the basic colors of autism, whereas the combinations of diverse impairments make the palette of autism. In turn, social processes can be spoiled in many ways and can lead to diverse comorbidities.

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

Leaders are failing to respond to the climate and environmental urgency the world is facing. A growing action gap, clearly visible during the recent CoP25, has been fueled by leaders' inability to respond efficiently to the mounting threats scientists—and increasingly society—are concerned about. Bridging this gap and tackling the growing polarization within society calls for leaders to accept the full complexity of the issues the world is facing. This will require them to question their understanding of these geopolitical affairs and embrace the dynamics at play, and avoid falling back on simplistic cognitive models. We propose a heuristic to convey the pathways available to decision-makers to make their way out of the current inaction impasse. By breaking free of this deadlock, a social transition will have the potential to take place, helping us to avoid crossing the climate system tipping points.

Sensors available on mobile devices allow the automatic identification of Activities of Daily Living (ADL). This paper describes an approach for the creation of a framework for the identification of ADL, taking in account several concepts, including data acquisition, data processing, data fusion, pattern recognition, and machine learning. These concepts can be mapped in a module of the framework, including the use and creation of several algorithms. For the development of a framework that works in several conditions, e.g., without Internet connection, these algorithms should take in account the hardware and software limitations of the mobile devices to run all main tasks locally. The main purpose of this paper is related to the presentation the sensors, algorithms, and architecture of the proposed approach.

The segmentation of urban scene mobile laser scanning (MLS) data into meaningful street objects is a great challenge due to the scene complexity of street environments, especially in the vicinity of street objects such as poles and trees. This paper proposes a three-stage method for the segmentation of urban MLS data at the object level. The original unorganized point cloud is first voxelized, and all information needed is stored in the voxels. These voxels are then classified as ground and non-ground voxels. In the second stage, the whole scene is segmented into clusters by applying a density-based clustering method based on two key parameters: local density and minimum distance. In the third stage, a merging step and a re-assignment processing step are applied to address the over-segmentation problem and noise points, respectively. We tested the effectiveness of the proposed methods on two urban MLS datasets. The overall accuracies of the segmentation results for the two test sites are 98.3% and 97%, thereby validating the effectiveness of the proposed method.

Social plasticity, defined as the ability to adaptively change the expression of social behavior according to previous experience and to social context, is a key ecological performance trait that should be viewed as crucial for Darwinian fitness. The neural mechanisms for social plasticity are poorly understood, in part due to skewed reliance on rodent models. Fish model organisms are relevant in the field of social plasticity for at least two reasons: first, the diversity of social organization among fish species is staggering, increasing the breadth of evolutionary relevant questions that can be asked. Second, that diversity also suggests translational relevance, since it is more likely that “core” mechanisms of social plasticity are discovered by analyzing a wider variety of social arrangements than relying on a single species. We analyze examples of social plasticity across fish species with different social organizations, concluding that a “core” mechanism is the initiation of behavioral shifts through the modulation of a conserved “social decision-making network”, along with other relevant brain regions, by monoamines, neuropeptides, and steroid hormones. The consolidation of these shifts may be mediated via neurogenomic adjustments and regulation of the expression of plasticity-related molecules (transcription factors, cell cycle regulators, and plasticity products).

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.

Some management practices, such as maintaining birds under high group density, used in the poultry industry may cause birds stress, leading to injurious behaviors, such as injurious pecking, aggression, and cannibalism. In addition, some management practices used to prevent severe injuries in birds may cause pain. Beak trimming (BT), removal of 1/3 to 1/2 of a beak, is a routine husbandry procedure practiced in laying hens to prevent or reduce injurious behaviors. However, BT causes tissue damage, which may increase somatosensory sensitization of the damaged nerve tissues, resulting in pain (acute, chronic or both) in the treated birds because the beak is a complex, functional organ with an extensive nerve supply. BT has already been heavily regulated or prohibited in several European countries and, in time, this trend will impact the practice used in the United States poultry industry. With the growing public concern for poultry welfare there is a pressing need to identify and develop alternatives to BT. Probiotics defined “as a source of live (viable) naturally occurring microorganisms (direct-fed microbials)” have been used as dietary supplements or functional foods to target gut microbiota (microbiome) for prevention or therapeutic treatment of mental diseases including social stress-induced psychiatric disorders in humans and various experimental animals. In our studies, chickens were used as an animal model to assess if dietary supplementation of probiotic, Bacillus subtilis, reduces injurious behaviors following social challenge. Hens of Dekalb XL strain, an aggressive line, were used in the studies. Our results indicate that dietary supplementation of the Bacillus subtilis based probiotic reduces aggressive behaviors in chickens. These results suggest dietary probiotics could be a suitable strategy for increasing hosts’ health status and welfare conditions.

Electrification coverage in Sarawak is the lowest at 78.74%, compared to Peninsular Malaysia at 99.62% and Sabah at 82.51%. Kapit, Sarawak with its 88.4% populations located in rural areas and mostly situated along the main riverbanks has great potential to generate electrical energy by hydrokinetic system. Yearly water velocity data is the most significant parameter to perform hydrokinetic analysis study. Nevertheless, the data retrieved from local river databases are inadequate for river energy analysis, thus hindering its progression. Instead, flow rates and rainfall data had been utilised to estimate the water velocity data. This signifies no estimation of water velocity in an unregulated river by using water level data had been made. Therefore, a novel technique of estimating the daily average water velocity data in unregulated rivers is proposed. The modelling of regression equation for water velocity estimation was performed and two regression model equations were generated to estimate both water level and water velocity on-site and proven to be valid as the coefficient of determination values had been R² = 87.4% and R²=87.9%, respectively. The combination of both regression model equations can be used to estimate long-term time series water velocity data for type-C unregulated river in remote areas.

Background (1) In the time of the 4th Industrial Revolution or Industry 4.0, a conglomerate of technical and social inventions, political contexts, socio-cultural circumstances, environmental policies, business models, and economic policies has emerged. Sustainability policy in theory and practice aims to deal with the effects of all these factors and to try to make decisions that ensure both social and economic development sustainably. The question is how to familiarize oneself with the current knowledge about the relationship between Industry 4.0 and sustainability?; (2) Methods: This research utilizes an automated content analysis method to analyses scientific journals, newspapers and magazines. The comparison of results of both research group shows that the scientific literature focuses more on changes in business models, production processes and technologies that enable sustainable development; (3) We found that the scientific literature focuses more on changes in business models, production processes and technologies that enable sustainable development. Newspapers and magazines articles write more about sustainable or green investment, sustainable standards and sustainable reporting. Newspapers and magazines articles write more about sustainable or green investment, sustainable standards and sustainable reporting. Newspapers, as well as some latest research journals, include articles of the COVID-19 outbreak and its effect on the economy and the environment. Indeed, the outbreak of the virus brings a new thought to the reorganization of the complex relationships between consumers, businesses and the state; (4) Conclusions: According to the comparison of the analyses of the results, it can is that the analyses of both types of literature, both scientific and professional, shows that there are common topics they write about, which are related to the field of clean production, emissions, renewable energy, climate change, sustainable investments and corporate sustainability. An urgent global issue that extends all over the world is the promotion of energy-saving technologies and reduction of carbon dioxide emissions.

This theoretical article reviews the model describing processes in social systems based on the analysis of their resource base. Application of the system theory can help to explain why some systems are aimed at prevention of type I errors, while other seek to decrease quantity of type II errors. Such differences are manifested in investment of resources either into deep interaction or into wide coverage. Some examples of such strategies in economic, market and production systems are provided in the article. The article introduces some provisions of the system theory in the context of the resource flows. The main indicators that are considered in this article are the characteristics of the sources of the exchanging flows of resources. Their relative frequency and quality are investigated, on the basis of which the most effective strategy of the system is derived, as a mechanism for redistributing resources. The rigor of the system's strategy depends on the magnitude of the difference in characteristics. It is explained how exactly it influences the exchange processes, that in reality systems do not interact simultaneously, and one of the opposite resource flows is always delayed. It is shown how the system strategy depends on the risks linked with interactions. Also, there are grounds for the need to accumulate resources, including in the situation of their surplus. The model helps also explain shift of economic centers throughout history. Additionally, there is an analogy between systems strategies and the competitive strategies described by M. Porter, and outsourcing versus integration.

Objective: The goal of this study was to analyse the attitudes and perceptions of emergency and mental health nurses through the validation of the SM-GIBED scale in specialised care in Spain on alcoholics and other drug-dependent patients. Design and Setting: This cross-sectional study was developed using the Spanish hospital version of the Seaman-Mannello scale to denominate the SM-GIBED scale. Participants: 170 Emergency and Mental Health Nursing from five Spanish Hospitals. Intervention: Self-administered questionnaire to analiyse the perceptions and attitudes about the drug addict and the alcoholic. Primary and Secondary Outcome Measures: A descriptive and inferential analysis of the study variables was carried out. A psychometric analysis was performed to validate the scale. Results: A total of 170 questionnaires were collected from 257 healthcare workers. Overall, 99.1% of the participants had contact with drug-dependent patients during their professional experience. Nearly 75% had difficulties in treating them. The psychometric analysis of the SM-GIBED scale in the Spanish context obtained values of KMO = 0.655 and Bartlett's test p < 0.000. Cronbach's alpha of 0.738 was obtained from the reliability analysis. A reliability analysis of each of the SM-GIBED questions found no case with an alpha lower than 0.71. In conclusion, positive aspects include an ingratiating attitude and subject-to-subject communication when nurses self-define as empathic and non-paternalistic. Among the negative aspects, there is a lack of communication skills and assertiveness with these patients. This highlights a certain degree of resignation and dissatisfaction when working with drug addicts.

Animal-focused research has been crucial for scientific advancement however, in this matter, rodents are still taking a starring role. Coming out from merely being supportive of evidence found in rodents, the use of fish models has slowly taken a more central role and expanded its overall contributions in areas such as social sciences, evolution, physiology, and recently in translational medical research. In neurosciences, zebrafish has been widely adopted, contributing to our understanding of the genetic control of brain processes, and the effects of pharmacological manipulations. However, discussion continues regarding the paradox of function versus structure, when fish and mammals are compared, and on the potentially evolutionarily conserved nature of behaviour across fish species. From the behavioural stand point we explored aversive/stress and social behaviour in selected fish models, and refer to the extensive contributions of stress and monoaminergic systems. We suggest that, in spite of marked neuroanatomical differences between fish and mammals, stress and sociality are conserved at the behavioural and molecular levels. We also suggest that stress and sociality are mediated by monoamines in predictable and non-trivial ways, and that monoamines could “bridge” the relationship between stress and social behaviour. To reconcile the level of divergence with the level of similarity, we need neuroanatomical, pharmacological, behavioural, and ecological studies conducted in the laboratory and in nature. These areas need to add to each other to enhance our understanding of fish behaviour and ultimately how this all may translate to better model systems for translational studies.

The diversity and inclusion discussion permeates many sectors of society. Within this dialogue, science and scientists are acutely aware of the value of diversity and the need for inclusion. While demographic diversity in science has received considerable recent attention, very little research and understanding exists on inclusion. Our study presents empirical data on the meaning of inclusion using a crowdsourcing approach that sought responses to the question “What does inclusion mean to you?”. The most prominent concepts were those of empathy, warmth, support, love, acceptance and curiosity; diverse perspectives; and participation. We clustered conceptual elements of inclusion into four themes: access and participation, embracing diverse perspectives, a welcome environment, and team belonging. On the basis of these data, we theorize a conceptual framework model from which inclusion may be put into practice. Our model suggests a dynamic process of inclusion operating from principal structural elements of 1) a foundation that involves place, access and participation, and space; 2) reciprocal engagement as an engine for inclusion; and 3) expression of inclusion as culture. The framework model demonstrates a means by which the practice of diversity can be more than shifts in demographic statistics, and instead promote the full expression of benefits derived when the many dimensions of diversity are truly included.

(1) This study aimed to examine the prevalence of depression and its correlation with acculturative Stress and Social Connectedness among domestic and overseas students in Japan International University. (2) Methods: A Web-based survey was distributed among students of International University, which resulted in 263 responses. On the survey together with socio-demographic data, a nine-item tool from the Patient Health Questionnaire (PHQ-9), was used to measure the prevalence of Depression and its relationship with socio-demographic data, Social Connectedness Scale was used to measure Social Connectedness, and Acculturative Stress Scale for International Students (ASSIS) was used to measured acculturative stress. (3) Results: Depression was significantly high in international and domestic students (37.81% and 29.85% respectively). English language proficiency and students age (20 years old) showed a significant correlation with depression among domestic students (β=-1.63, p=0.038 and β=2.24, p=0.048). Stay length (third year) also displayed a significant correlation with depression among international students (β=1.08, p=0.032). Among international and domestic students statistically significant positive correlation between depression and acculturative stress, negative associations of social connectedness with depression and acculturative stress were also found. Suicidal or self-hurting ideation thoughts are found among around 20% of all students. (4) Conclusions: These findings indicate a relatively high prevalence of depression among students of International University, and overseas students are more affected. Depression, Acculturation stress and Social Connectedness show statistically strong intercorrelation, which highlights the need of host University to recognise the role of Acculturation and Social Connectedness in the development of Depression among students.

Excessive cell phone use contributes to distracted driving, may increase risk for automobile accidents, and a minority of mobile phone users exhibit behaviors consistent with technological addiction. The purpose of this study was to determine whether cell phone beliefs and behaviors could be changed by a brief educational encounter. The Theory of Reasoned Action provided a lens for viewing attitudes and behavior. A one-week pre-post design with a thirty-day follow-up was used with participants (N = 215, 67.0% female, age = 20.0 + 1.6) assigned to a peer led intervention or comparison groups. The intervention included cell-phone educational materials. A short index of cell phone behavior was developed which showed good internal consistency with a Cronbach’s alpha of .81. The intervention group “agreed” or “strongly-agreed” more than the comparison group on five of the seven areas of cell phone beliefs and behaviors ( p < 0.05, item Cohen’s d = .32 to .47, total d = .50) at one-week following receipt of informational materials. We conclude that attitudes and behaviors regarding cell phones are malleable and susceptible to change in young-adults following a brief psychoeducational intervention.

This article assumes that collaborators who adopt a positive-sum, prosocial perspective can build trust-based relationships, which is equivalent to collaborative ability (CA). To improve a collaborator’s CA, we anticipated that content based upon a model of positive-sum collaboration, founded upon ancestral behaviours presented as social norms, might alter a zero-sum, proself, collaborator’s perspective. However, we also postulated that learner’s willingness to engage in positive-sum content may rely on pre-existing prosociality. Intervention participant’s prosociality was assessed via self-assessment of their emotional intelligence (EQ), quality of life (QoL), and goal orientation (GO). Learner’s engagement in online content was assessed by the three stage reached: examine website front matter; examine website content; learn website content. Tukey’s multiple comparison showed a statistically significant difference between stages one and three, in the mean of respondent’s self-assessed QoL. This suggests that participants who wished to learn content had, on average, higher quality of life, and potentially therefore greater prosociality. In general, these findings support a claim that any intervention designed to increase individual prosociality may need to consider the target population’s reticence to engage.

Bacterial conjugation, also referred to as bacterial sex, is a major horizontal gene transfer mechanism where the DNA is transferred from a donor to a recipient bacterium by direct contact. Conjugation is universally conserved among bacteria and occurs in a wide range of environments (soil, plant surfaces, water, sewage, biofilms and host-associated bacterial communities). Within these habitats, conjugation drives the rapid evolution and adaptation of bacterial strains by mediating the propagation of various metabolic properties, including symbiotic life-style, virulence, biofilm formation, or resistance to heavy metals and, most importantly, resistance to antibiotics. These properties make of conjugation a fundamentally important process at the center of extensive study. Here, we review the key steps of conjugation by following the life-cycle of the F plasmid during transfer from the donor to the recipient cell. We also discuss our current knowledge of the extent and impact of conjugation within an environmentally and clinically relevant bacterial habitat, bacterial biofilms.

This article describes the use of the PI ProcessBook software tool for visualization and indirect monitoring of occupancy of SHC rooms from the measured operational and technical quantities for monitoring of daily living activities for support of independent life of elderly persons. The proposed method for data processing (predicting the CO₂ course using neural networks from the measured temperature indoor T_i (°C), temperature outdoor T_o (°C) and the relative humidity indoor rHi (%)) was implemented, verified and compared in MATLAB SW tool and IBM SPSS SW tool with IoT platform connectivity. Within the proposed method, the Stationary Wavelet Transform de noising algorithm was used to remove the noise of the resulting predicted course. In order to verify the method, two long-term experiments were performed, (specifically from February 8 to February 15, 2015, from June 8 to June 15, 2015) and two short-term experiments (from February 8, 2015 and from June 8, 2015). For the best results of the trained ANN BRM within the prediction of CO₂, the correlation coefficient R for the proposed method was up to 90%. The verification of the proposed method confirmed the possibility to use the presence of persons of the monitored SHC premises for rooms ADL monitoring.

Currently, companies and SMEs (small and medium enterprises) are looking to be more competitive. In order to achieve this, they are adopting new business models and strategies that allow them to move towards sustainability. Strategies such as CSR (Corporate social responsibility) and supply chain management have become essential for ensuring a company’s permanence and financial consolidation. The literature has stated that the theories of Stakeholders and Sustainability are fundamental pillars for the development and sustained growth of business. The purpose of this article is to examine the effects of CSR and the SC (supply chain) on innovation, image and reputation, and in turn, their influences on profitability in SMEs. This research is based on a sample of 143 companies in the city of Guaymas Sonora, in Mexico. For the analysis and validation of the results, we used the SEM (Structural Equation Modeling) statistical technique based on the variance, through PLS (Partial Least Squares) (using SmartPLS version 3.2.6 Professional). The findings show that SMEs that develop social and sustainable practices increase their level of innovation, and improve their image, their reputation, and their financial profitability. This work contributes mainly to the development of Stakeholders and Sustainability.

The use of mobile phones has increased dramatically among drivers in multiple countries in the past few years. The primary objective of this study was to measure the prevalence of cell phone use while driving in Saudi Arabia and to find whether there is a relationship between car accidents and the use of mobile phones while driving. The secondary objective was to explore general knowledge and attitudes toward traffic regulations related to cell phone usage while driving. This is a cross-sectional study conducted among 585 drivers in Saudi Arabia using a self-reported online survey distributed through social media channels. Our results showed that 78.6% of the participants acknowledged that they use the phone while driving. The percentage who reported car accidents involving them or their friends or relatives while using the phone while driving was 43.8%, along with 71.8% mentioning near misses. The percentage of respondents who thought that using a mobile phone while driving had a strong impact on the driver’s ability to drive was 31.5%. This study highlights the importance of raising awareness about risks of using Mobile phones during driving in Saudi Arabia and it recommends harsher penalties to reduce the use of mobile phones while driving.

As a result of extensive research in the field of mobile robots (rovers) and swarms, a number of algorithms exist to assist them for executing a mission in the three levels of software architecture: strategic (interaction loop level), tactic (planning) and operational (sensing, control and actuation). They allow them to achieve their goals while adapting to their environment through a multitude of methods designed for each situation. For this reason, a literature review of the latest research conducted in previous years is required to identify new research trends in human-swarm interaction applied to help humans in hazardous environment such as militarized zone. In this paper, we will present some interesting algorithms for interactive and autonomous mobile robots acting in swarms in an open and crowded environment. A discussion will focus on comparing different algorithms and their advantages and disadvantages.

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%.

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.

Hand gestures may play an important role in medical applications for health care of elderly people, where providing a natural interaction for different requests can be executed by making specific gestures. In this study we explored three different scenarios using a Microsoft Kinect V2 depth sensor then evaluated the effectiveness of the outcomes. The first scenario utilized the default system embedded in the Kinect V2 sensor, which depth metadata gives 11 parameters related to the tracked body with five gestures for each hand. The second scenario used joint tracking provided by Kinect depth metadata and depth threshold together to enhance hand segmentation and efficiently recognize the number of fingers extended. The third scenario used a simple convolutional neural network with joint tracking by depth metadata to recognize five categories of gestures. In this study, deaf-mute elderly people execute five different hand gestures to indicate a specific request, such as needing water, meal, toilet, help and medicine. Then, the requests were sent to the care provider’s smartphone because elderly people could not execute any activity independently. The system transferred these requests as a message through the global system for mobile communication (GSM) using a microcontroller.

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.

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

With a low rate of new building construction and insufficient rate of existing building renovation, there is the need for stepping up the pace of building renovation with ambitious performance targets to achieve EU climate change policies. However, effective technologies alone cannot solve the low renovation rate of existing buildings in Europe that is hindering the reaching of EU-wide targets. A workshop was held at the Sustainable Place Conference 2018 to present successful experiences with an integrative approach from H2020 innovation actions (4RinEU, P2ENDURE, Pro-GET-OnE, MORE-CONNECT) aiming at improving building energy performance through deep renovation. This article presents the outcomes of the joint workshop and interactive discussion, by focusing on the different technical, financial and social added values, barriers and challenges in building renovation as well as on the identification of open questions to address future innovation opportunities.

The fear of missing out (FoMO) is characterized in the literature as a fear that others are having rewarding experiences while one is missing out, and a constant need to keep connected with one’s social network. Driven by Social Determination Theory (SDT) FoMO has been linked with Problematic Social Networking Sites use (PSNSU), negative affectivity (NA), self-esteem (SE) and sleep disturbances. The present study reports findings from 512 individuals (79.1% women, mean age 30.5 years, SD= 8.61). Structural equation modelling (SEM) suggests that the duration of SNSs use and the numbers of SNSs platforms actively used partially mediated the relationship between FoMO and PSNSU. In turns, PSNSU partially mediated the relationship between FoMO and NA. Furthermore, the present study has extended the literature by incorporating the Vulnerability Model in the FoMO concept, identifying that SE partially mediated the relationship between FoMO and NA, while NA fully mediated the relationship between FoMO and sleeping disturbances. Accordingly, the present has extended previous research findings in showing exercise as a potential protective factor to prevent against FoMO. Practical and theoretical implications are discussed.

Although floods, as well as other natural disasters, can be considered relevant causes of intra-generational inequalities, the frequent catastrophes and the resulting damages to territory reflect the generalized indifference about inter-generational justice. Societal concerns, such as land protection, typically involve the administrative system performing proactive policies in the perspective of inter-generational solidarity, but subsidiarity has made more and more independent the local communities. As a consequence, the attention toward the long run effects – typically concerning the territorial system, as a whole, at the geographical scale – has been dispersed, and the proactive policies coming from the central government has became more ineffective. Regarding the case of the flood happened in 2009 in the Fiumedinisi-Capo Peloro hydraulic basin, in the northeastern part of Sicily, Italy, we propose an economic valuation – carried out by performing the method of the imputed preferences – in order to compare the expenses incurred by the public authorities responsible for protecting the territory to the costs of the rehabilitation of the damaged areas. Some considerations about the economic significance of the proactive policies for the arrangement of territory are addressed according to the role played by the social discount rate in the inter-temporal economic calculation.

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

Despite the considerable focus on job characteristics and individual differences in job crafting research, the influence of social factors on job crafting has not been well-acknowledged. This meta-analysis estimates the associations between social factors and job crafting, and how social factors contribute to employee outcomes through their job crafting. Based on a sample of 51 empirical studies that included 54 independent effect sizes (N = 17,863), we found that social factors of positive leadership styles (e.g., empowering and transformational) and coworker support were positively related to employee job crafting. Further, our study showed that employee job crafting positively mediate the relationships between social factors and work outcomes (e.g., job performance and well-being). Our study contributes to job crafting literature by integrating social factors into the job crafting model and demonstrating that the social context of work (in particular organizational-insiders) play a crucial role in shaping employees’ job crafting behavior. We also emphasize the critical role that job crafting plays in transmitting valuable social resources into improved work outcomes. Building on our results, we provide future direction for job crafting research and discuss how our results can imply practice in terms of job crafting training.

The exponential increase in the use of the Internet and social media over the last two decades has changed human interaction. This has led to many positive outcomes, but at the same time it has brought risks and harms. While the volume of harmful content online, such as hate speech, is not manageable by humans, interest in the academic community to investigate automated means for hate speech detection has increased. In this study, we analyse six publicly available datasets by combining them into a single homogeneous dataset and classify them into three classes, abusive, hateful or neither. We create a baseline model and we improve model performance scores using various optimisation techniques. After attaining a competitive performance score, we create a tool which identifies and scores a page with effective metric in near-real time and uses the same as feedback to re-train our model. We prove the competitive performance of our multilingual model on two langauges, English and Hindi, leading to comparable or superior performance to most monolingual models.

Sleep disorders (SD) have a complex aetiology, and socioeconomic status (SES) as determined by social class, household income, ethnicity and education plays an important role in their development. As SD are associated with cognitive impairment and mood disorders, they in turn impact SES. Socioeconomic status also influences allostatic load caused by chronic accumulation of stress throughout life. Environmental and psychological stressors have a direct effect on SD, and they are modulated by SES, in combination with comorbidities like obesity and cardiovascular disease. This review explores the recent theories about the influence of SES on the development of SD in the general population, whether or not occurring with comorbidities, and also focusses on the interplay between socioeconomic status, circadian rhythms, aging and clinical outcomes like metabolic diseases and cancer.

This paper extends previous research on the influence of social media and digital channels on customer purchase behaviour by presenting a new omnichannel purchasing model. We characterise that model as a “virtuous circle” as it centres around customer use of social media and has potential to benefit both customers and companies. We illustrate that model with a worked example, discuss approaches to its implementation and evaluate its use in the context of a business case study. The model creates a framework that combines elements of digital marketing, social CRM, omnichannel CRM, and customer experience and engagement. This paper bridges academic and industry practitioner communities across those fields.

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

A more sustainable society and economy also implies a more sustainable behavior in the consumption of financial products. A possible change in focus can come from the demand side, so that more sustainable consumption of financial products have to go hand to hand with financial literacy. However, financial literacy, potential favoring of this sustainable behavior, is far from reaching an international consensus about its definition, object and scope. Two objectives are analyzed; the different interpretations of financial literacy in the academic literature, as well as its evolution and how, in what context and with what other concepts the term is used in social networks. Scientometric techniques and content analysis have been used to carry out a systematic review of literature and also NLP to analyze the comments on Social Networks. Critical moments are identified in the definition of financial literacy. Also ten sentiments are analyzed in social networks in wich positivity, trust, and anticipation predominate. Greater attention to this issue is necessary both from the private initiative and from public policies, so that financial literacy is an effective tool for a more sustainable behavior by consumers. Finally, a new definition is proposed based on our findings.

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

The present research endeavours to examine the impact of customers' perceptions regarding a firm's dedication to corporate social responsibility (CSR) on their allegiance to particular banking brands. The mediating factors of brand credibility and image help to facilitate the indirect relationship between corporate social responsibility (CSR) and brand equity, which is the focus of this study. The objective of the research is to investigate the plausible causal association among perceived corporate social responsibility, brand image, brand credibility, and brand equity. The study's data was obtained by conducting a survey among a sample of 320 banking customers in Ethiopia. In order to perform a thorough examination of the data, AMOS version 24.0 and structural equation modelling (SEM) methodologies were employed. The present research endeavours to broaden the conventional comprehension of the advantages that corporate social responsibility (CSR) offers to customers. It aims to address a void in the current literature by scrutinising the impacts of customers' perceptions of CSR, brand credibility, and brand image on their allegiance towards particular banking service brands. The findings of this study carry substantial implications for financial institutions, and the conclusions derived from the results are of considerable significance.

This study examines the relationship of fear of missing out (FOMO) with heavy social networking among Turkish university students (aged 17 - 55). The perception of the possible role of parental supervision on online activities is also investigated. Factor analysis of FOMO scale led us to evaluate the construct under two dimensions as (1) fear of missing experience and (2) fear of missing activity. The results revealed that fear of missing activity increases social media intrusion while fear of missing experience is found to have no significant effect. The reverse relationship is also valid: an urge to use social media predicts fear of missing out (activity and experience). Fear of missing experience is associated with problematic social media use (PSMU) and a high desire to use social media. The results additionally demonstrate that students aged 30 and older believe more in the requirement of parental control than those aged 17-22.

Estimation and planning play a vital role in the construction of an autonomous navigation framework. However, these problems are often considered separately, while planning gives robot a free-collision path towards the desired goal, estimation algorithm presents the executed trajectory in the sense that it has to be closed to the ground truth path as much as possible. Recently, a unified probabilistic framework, which supports solving these problems simultaneously, dubbed STEAP has been proposed. Nevertheless, its current version is only designated for an omni wheels robot, which allows robot to move and turn in vertical direction. Differential drive robot, on the other hand, though limited to move along only one direction, has been used in various situations due to its flexibility and lower cost in hardware designing. Thus, in this extension, our aim is to control a differential drive robot via STEAP. Moreover, in a more complicated environment such as labyrinth or maze, the original STEAP sometimes fails to find a path. Indeed, this problem is mainly caused by the poor initialization and the non-linearity in optimizer constraints. In our implementation, instead of dealing with these constraints, we employ a global planner algorithm such as Dijkstra or RRT to treat STEAP as an effective local planner module that focus on following the global path. Consequently, the experimental results show that the extended STEAP not only able to navigate a differential drive robot but also in a more complicated and unstructured environment.

COVID-19 severity is heterogeneously distributed over age strata, but current mitigation strategies are homogeneously applied to all population. Social-distancing and stay-home are effective conservative approaches but lack economic sustainability on long term. Conversely, herd-immunity is a nonrestrictive strategy which can cost remarkable number of human lives and can melt the healthcare system down. Here I propose an Age Adaptive Social Distancing (AASD) engineering strategy to mitigate COVID-19 outbreak. AASD is based on the scientific evidence that the fatality rate grows nonlinearly with age, hence also the containing strategy should adapt nonlinearly. Essentially, AASD suggests that ‘silent spreaders’ (age 0-39) should avoid/minimize direct and indirect contacts with individuals in ‘dangerous zone’ (age 40+). The rationale is: 0-19 should follow parents strategy, healthy 20-39 (low fatality rate) might conduct screened life under active surveillance, to sustain economy and acquire rational immunity; 40-59 should respect social distancing (waiting a therapy); 60+ should stay at home (waiting a vaccine). This might save human lives, reduce healthcare demand and improve economic sustainability. The final take-home message is that future studies should design precision and personalized strategies for specific contagious diseases that integrate different social constrains, active surveillance and contact tracing.

Online Social Networks (OSNs), such as Facebook and Twitter, have become a very important part of many people’s daily lives. Unfortunately, the high popularity of these platforms makes them very attractive to spammers. Machine-learning (ML) techniques have been widely used as a tool to address many cybersecurity application problems (such as spam and malware detection). However, most of the proposed approaches do not consider the presence of adversaries that target the defense mechanism itself. Adversaries can launch sophisticated attacks to undermine deployed spam detectors either during training or the prediction (test) phase. Not considering these adversarial activities at the design stage makes OSNs’ spam detectors prone to a range of adversarial attacks. This paper thus surveys the attacks against Twitter spam detectors in an adversarial environment. In addition, a general taxonomy of potential adversarial attacks is proposed by applying common frameworks from the literature. Examples of adversarial activities on Twitter were provided after observing Arabic trending hashtags. A new type of spam tweet (Adversarial spam tweet), which can be used to undermine deployed classifier, were found. In addition, possible countermeasures that could increase the robustness of Twitter spam detectors against such attacks are investigated.

Artificial Intelligence is increasingly being used by social media platforms to tackle online hate speech. The sheer quantity of content, the speed at which is it developed and the enhanced pressure companies are facing by States to remove hate speech quickly from their platforms have led to a tricky situation. This commentary argues that automated mechanisms, which may have biased datasets and be unable to pick up on the nuances of language, should not be left unattended with hate speech as this can lead to issues of violating freedom of expression and the right to non-discrimination.

Food intake plays a pivotal role of human growth, which necessarily contributes 45% of global economy and wellbeing in general. Consumption of balanced food is elementary for overall good health while a shift of equilibrium can lead to malnutrition, prenatal death, obesity, osteoporosis and bone fractures, coronary heart diseases (CHD), idiopathic hypercalciuria, diabetes and many more. Though CHD, osteoporosis, malnutrition, obesity are being classified thoroughly in the literature, there are fragmented findings in the regime of kidney stone diseases (KSD) and the correlation with food intake therein. KSD associated with hematuria and renal failure poses an increasing threat to the healthcare and global economy while its emergence of Indian populations is being affected with multi-factorial urological disorder resulting from several factors. In this realm, epidemiological, biochemical, macroeconomic situations been portrayed when food intake is also a paramount importance which rarely been forecasted. Hence, in this article we will be reviewing the corollary connotation with diverse food consumption and the efficacy it plays in KSD extrapolating in Indian context.

This research contributes to the development of theories regarding the relationship between Corporate Social Responsibility (CSR) and investment decisions. Acquisition of stock returns that exceed normal predictions depends on the successful implementation of Good Corporate Governance (GCG). This study aims to examine investors' reactions to information on CSR disclosure in several countries that are members of the Association of Southeast Asian Nations (ASEAN). Furthermore, this study also examines the role of implementing GCG in strengthening the impact of CSR disclosure on investor relations as measured by abnormal stock returns. The sampling technique used was purposive Sampling. The research was conducted on Manufacturing Companies in countries that are members of ASEAN during 2017-2019. The estimation model used to analyze data is a multiple regression model. The results showed that CSR information was able to increase investors' positive reactions. Meanwhile, GCG practice is proven to strengthen the impact of CSR information on investment decisions. Other variables involved in this study, namely audit quality, company size, debt level, and sales growth, are not proven to influence abnormal stock returns.

Tinnitus is a complex and heterogeneous psycho-physiological disorder responsible for causing a phantom ringing or buzzing sound albeit the absence of an external sound source. It has a direct influence on affecting the quality of life of its sufferers. Despite being around for a while, there hasn’t been a cure for tinnitus, and the usual course of action for its treatment involves use of tinnitus retaining and sound therapy, or Cognitive Behavioral Therapy (CBT). One positive aspect about these therapies is that they can be administered face-to-face as well as delivered via internet or smartphone. Smartphones are especially helpful as they are highly personalized devices, and offer a well-established ecosystem of apps, accessible via respective marketplaces of differing mobile platforms. Note that current therapeutic treatments such as CBT have shown to be effective in suppressing the tinnitus symptoms when administered face-to-face, their effectiveness when being delivered using smartphones is not known so far. A quick search on the prominent market places of popular mobile platforms (Android and iOS) yielded roughly 250 smartphone apps offering tinnitus-related therapies and tinnitus management. As this number is expected to steadily increase due to high interest in smartphone app development, a contemporary review of such apps is crucial. In this paper, we aim to review scientific studies validating the smartphone apps, particularly to test their effectiveness in tinnitus management and treatment. We use the PRISMA guidelines for systematic identification of studies on major scientific literature sources and delineate the outcomes of identified studies.

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

Since very few empirical endeavors have looked into statue and funerary art that represents social identities, this study aims to fill this gap. The research article aims to portray social status from the funeral arts, traditions and rituals. This longitudinal case study used interviews and a series of observations. The finding reveals that each funerary art represents particular class of noble families. Every funerary art also depicts specific insightful meaning for their noble families. The process of ritual and funeral ceremony is performed according to each status of noble families. This paper also describes the implication of the funerary art in social and cultural interactions.

Aggregative multicellularity occurs when dispersed cells join together to form a highly cooperative unit, in contrast to clonal multicellular organisms formed by cells that remain in contact after descent from a single cell. Because aggregative groups may include non-relatives, aggregative multicellular organisms should be particularly vulnerable to the rise of cheater cells that take advantage of social goods without paying the costs, reducing cooperation, and even threatening extinction. We review the key mechanisms by which aggregative multicellular organisms control cheaters with a focus on the best studied aggregative organisms, Myxococcus xanthus and Dictyostelium discoideum. These include various passive and active mechanisms to maintain high relatedness within aggregates, to enforce cooperation on aggregate members, and the costs of cheating on other key functions. Ultimately, aggregative multicellular organisms are not that different from clonal organisms descended from a single cell.

Despite extensively investigating the impact of social media on fashion products’ marketing, little evidence is available on how the platforms influence sales prediction. Focusing on Lolita fashion, this study investigates the impact of social media marketing on the sales volume prediction of fashion products. Essentially, we analyzed marketing data, including comments, likes, and shares from the Weibo social platform, to forecast future sales, examine how to enhance profit performance, and make production decisions. Using a quantitative approach, we tested three different prediction models, including multiple regression, decision tree, and XGBoost. The results revealed that increasing comments and decreasing the number of likes could significantly improve the sales volumes of Lolita products. In contrast, shares exerted a less significant impact on sales. Regarding prediction models, XGBoost was found to be the best method. In the fashion industry, social media is a useful tool for forecasting market trend. A limitation of this study is that only one social media platform was used to extract data, which might limit the generalization of the findings.

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

The expanding use of devices emitting Pulsed Telecommunication Signals (PTS) has launched a serious debate over the possible effects of electromagnetic radiation (EMR) on living organisms. Our previous work has indicated that PTS exposure alters Amyloid Precursor Protein (APP) and alpha-synuclein (α-syn) metabolism in human cells of neural origin, providing a possible connection between exposure and neurodegeneration. This investigation aimed to reveal, in vitro in human non-neural cells (HEK293), the aftermath of the same exposure on the processing of APP and α-syn. Data presented here, indicate changes in APP metabolism, acquisition of different cellular topologies of the newly generated APP fragments, changes in monomeric α-syn accumulation and multimerization, indicating that APP and α-syn processing is possibly altered in the periphery by EMR. These effects are accompanied by a substantial increase in the levels of Reactive Oxygen Species (ROS). Further investigation is required in order to provide insights into the interaction of PTS with non-neural cells affecting the peripheral systemic functional stability. This is necessary because nowadays whole body human exposure from various EMR sources is a fact in normal life with the valid estimation that they may be increased in view of the forthcoming 5G telecommunications network implementation.

Social media gives researchers an invaluable opportunity to gain insight into different facets of human life.Researchers put a great emphasis on categorizing the socioeconomic status (SES) of individuals to help predict various findings of interest. Forum uses, hashtags and so on are common tools of conversations grouping. On the other hand, crowdsourcing is a concept that involves gathering intelligence to group online user community based on common interest. This paper provides a mechanism to look at writings on social media and group them based on their academic background. We build upon earlier work where we analyzed online forum posts from various geographical regions in the USA and Canada and characterized the readability scores of such users. Specifically, we collected 1000 tweets from the members of the US Senate and computed the Flesch-Kincaid readability score for the Senators. Comparing the Senators’ tweets to the ones from average citizens, we note the following. 1) US Senators’ readability based on their tweets rate is much higher affirming the gap between the academic performance of US Senators and their average citizen, and 2) the immense difference among average citizen’s score compared to those of US Senators is attributed to the wide spectrum of academic attainment.

Background Due to the Covid-19 pandemic and the strict national policies regarding social distancing behavior in Europe, America and Australia, people became reliant on social media as a means for gathering information and a tool for staying connected to family, friends and work. This is the first trans-national study exploring the qualitative experiences and challenges of using social media while in lockdown or shelter in place during the current pandemic. Methods This study was part of a wider cross-sectional online survey conducted in Norway, UK, USA and Australia during April/May 2020. The manuscript reports on the qualitative free text component of the study asking about the challenges of social media users during the Covid-19 pandemic in UK, USA and Australia. 1991 responses were included in the analysis. Thematic analysis was conducted independently by two researchers. Results Three overarching themes identified were: Emotional/Mental Health, Information and Being Connected. Participants experienced that using social media during the pandemic amplified anxiety, depression, fear, panic, anger, frustration and loneliness. They felt that there was information overload and social media was full of misleading or polarized opinions from which was difficult to switch off. Nonetheless, participants also thought that there was an urge for connection and learning which was positive and stressful and the same time. Conclusion Using social media while in shelter in place or lockdown could have a negative impact on the emotional and mental health of some of the population. To support policy and practice in strengthening mental health care in the community, social media could be used to deliver practical advice on coping and stress management. Communication with the public should be strengthened by unambiguous and clear messages and clear communication pathways. We should be looking at alternative ways of staying connected.

VANET networks are a class of peer-to-peer wireless networks that are used to organize communication between cars (V2V), cars and infrastructure (V2I) and between cars and other types of nodes (V2X). These networks are based on the DSRC, 802.11 standards and are mainly intended for organizing the exchange of various types of messages, mainly emergency ones, to prevent road accidents or alert when road accident occur, or control the priority of the driveway. Initially it was assumed that cars would only interact with each other, but later, with the advent of the concept of Internet of things (IoT). Researchers began to analyze connectivity with other devices, which in general will allow to combine various road users and other devices that can used in the creation of intelligent transport infrastructure in a single smart city management system. Infrastructure is necessary for the provision of services, monitoring and management of the VANET network. As infrastructure objects it is proposed to use stationary objects of Roadside unit (RSU). The aim of this paper is to analyze the use of mobile edge computing to decrease the load to the base station and latency between RSU clouds and provide a real experiment using software defined networking and mobile edge computing for RSU.

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.

The world is currently facing an outbreak of the monkeypox virus and confirmed cases have been reported from 74 countries. Following a recent “emergency meeting”, the World Health Organization just declared monkeypox a global health emergency. As a result, people from all over the world are using social media platforms, such as Twitter, for information seeking and sharing related to the outbreak, as well as for familiarizing themselves with the guidelines and protocols that are being recommended by various policy-making bodies to reduce the spread of the virus. This is resulting in the generation of tremendous amounts of Big Data related to such paradigms of social media behavior. Mining this Big Data and compiling it in the form of a dataset can serve a wide range of use-cases and applications such as analysis of public opinions, interests, views, perspectives, attitudes, and sentiment towards this outbreak. Therefore, this work presents MonkeyPox2022Tweets, an open-access dataset of more than 255,000 Tweets related to the 2022 monkeypox outbreak that were posted on Twitter since the first detected case of this outbreak on May 7, 2022. The dataset is compliant with the privacy policy, developer agreement, and guidelines for content redistribution of Twitter, as well as with the FAIR principles (Findability, Accessibility, Interoperability, and Reusability) principles for scientific data management.

The aim of this article has been to evaluate the impact of a physical-sport education programme, based on the pedagogical model of Sport Education within the framework of quality Physical Education and approached from the field of social and emotional learning, on a set of psychological variables: subjective well-being (quality of life related to health, positive affect and negative affect); trait emotional intelligence and social anxiety. A total number of 113 Compulsory Secondary Education students were involved, aged 12 to 15 years old, 44 of whom belonged to the control group (CG) and 69 to the experimental group (EG). A quasiexperimental design of repeated pretest and posttest measures with the CG was used. The results obtained in this investigation revealed that the intervention programme caused significant improvements in the subjective well-being and the trait emotional intelligence for the EG. These findings reinforce the pedagogical efficiency of the programme with regards to the aim that has been set. Likewise, the findings also highlight the suitability and appropriateness in terms of innovative teaching proposals. In the same way, the results showed relevant empirical contributions in this given school context due to its psychological benefits and the encouragement of healthy living.

The current urban environment is faced with the potential threat of frequent natural disasters, and the sustainable development of post-disaster community has become a global issue. As an intrinsic motivation influencing the social interaction and capital operation of community, social network is an important mechanism promoting such sustainable development. However, the difference in social network caused by different member structure, spatial arrangement and management mechanism of post-disaster communities in different reconstruction modes has influenced such sustainable development process. Therefore, reasonable selection of reconstruction mode is crucial. This paper applied analytic hierarchy process to comprehensively measure and compare the social network strength in post-disaster communities in the four reconstruction modes adopted by the government of China, i.e. unified planning and unified construction, unified planning and independent construction, in situ reconstruction and relocation resettlement, with communities after the 2008 Sichuan earthquake in Chengdu, China as study objects from the perspective of three social relations (the relations between residents and residents, residents and managers, and residents and servers). The results showed that strong connections are generally presented in the social network of post-disaster communities in unified planning modes, that the strength is significantly higher than that of those in non-unified planning modes, and that the strength of UPIC communities is the highest. Meanwhile, government intervention, residents’ free participation and market operation are positively correlated to government trust, community interaction and community service respectively. The positive impact of government intervention is the most significant, but it has a peak value. No government management and excessive government intervention will exert negative impacts. The coordination of government, society and market is the key contents of post-disaster community reconstruction. The reconstruction modes based on “government leadership, resident participation and market operation” may become a feasible path for such sustainable development.

We present the detailed calculations of social distancing requirement. A comparative study of the growth pattern and death tolls in different communities indicates that the growth pattern of infected patients and death rate follow the similar distribution with different parametrizations. Every distribution follows an exponential growth pattern curve, like other microbes, then reaches the saturation point an d eventually decay s However, the argument for the exponential function depends on several parameters unbeknownst, as of yet. However, the slope varies different ial ly for various epicenter s and seems to have a relationship with parameters such as accessibi lity to healthcare facilities, pre existing medical conditions socio economic conditions and lifestyle. The mismatch of the growth pattern is also linked with the impact of various other factors and a premature interpretation of limit ed data. Novel behavi or of the virus brought many surprises, opened up new venues for medical research, and the need for the more detailed study of pathogens in the light of the interaction of RNA and DNA The adaptability to diverse ecological condition s and the relevant modification in the structure is also worth investigation The genetic modification can be studied using quantum mechanical probabilistic approach.

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

"The wisdom of crowd'' is so often observed in social discourses and activities around us. The manifestations of it are, however, so intrinsically embedded and behaviorally accepted that an elaboration of a social phenomenon evidencing such wisdom is often cheered as a discovery; or at least an astonishing fact. One such scenario is explored here, namely conceptualization and modeling of a food safety system, a system directly related to social cognition. Food safety is an area of concern these days. Models representing the food safety systems are recently published to study the effect of interactions between important entities of the system. For example, Knowles’s model finds conditions leading to a more efficient and dependable system of entities like consumers, regulators and stores with specific focus on regulators behavior and their impact on the food safety. The first contribution of this paper is reevaluation of Knowles’s model towards a more conscious understanding of ``the wisdom of crowd'' effects on inspection and consuming behaviors. The second contribution is augmenting of the model with social networking capabilities, which acts as a medium to spread information about stores and help consumers find stores which are not contaminated. Simulation results reveal that stores’ respecting social cognition improve effectiveness of the food safety system for consumers and stores both. Simulation findings also reveals that an active society has a capability to self-organize effectively even in the absence of any regulatory compulsion.

Mobile elevating work platforms (MEWPs) consist of a work platform, extending structure, and chassis, and are used to move persons to working positions. MEWPs are useful but are composed of pieces of equipment, and accidents do occur owing to equipment defects. Among these defects, accidents caused by the fracture of bolts fixed to the extension structure and swing system are increasing. This paper presents a failure analysis of the fixing bolts of MEWP. Standard procedure for failure analysis was employed in this investigation. Visual inspection, chemical analysis, tensile strength measurement, and finite element analysis (FEA) were used to analyze the failure of the fixing bolts. Using this failure analysis approach, we found the root cause of failure and proposed a means for solving this type of failure in the future. First, the chemical composition of the fixing bolt is obtained by a spectroscopy chemical analysis method, which determined that the chemical composition matched the required standard. The tensile test showed that the tensile and yield strengths were within the required capacity. The stress analysis was carried out at five different boom angles, and it was determined that the fixing bolt of MEWP can withstand the loads at all the boom angles. The outcomes of the fatigue analysis revealed that the fixing bolt fails before reaching the design requirements. The results of the fatigue analysis showed primarily that the failure of the fixing bolt was due to fatigue. A visual inspection of the fractured section of the fixing bolt also confirmed the fatigue failure. We propose a method to prevent failure of the fixing bolt of the MEWP from four different standpoints: the manufacturer, safety certification authority, safety inspection agency, and owner.

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

Financial Payment has evolved into mobile payment for easy access and convenience. Despite the benefits of mobile payment, the adoption rate is unsatisfactory worldwide. Therefore, understanding the customer's adoption intention factors is essential for both researchers and practitioners. This study examines mobile payment intention and actual use by adapting the integrated framework, which combines the Mobile Technology Acceptance Model and the Theory of Planned Behaviour with additional new constructs found to be related. The new model consists of 12 variables moderated by the individual's experience and is examined via a structured PLS equation mixed-mode methodology. Knowing mobile payment influence will shape the industry strategic decision and socially contribute to transforming society into a cashless society. This paper provides an opportunity to prove the relationship between technology variables and human behaviour concerning mobile payment adoption. In contrast, this study novelty adopted an integrated model that combines MTAM with the TPB.

Background: Social Anxiety Disorder (SAD) is among the most common anxiety disorders worldwide with data largely emerging from the Euro-American and Pacific Rim populations. In contrast, there is a dearth of studies among the populations of Arabian Gulf countries including Oman. This study has two interrelated aims: (i) to explore the prevalence of SAD among Omani adults, and (ii) to tease out the links between sociodemographic factors and SAD in Oman. Methods: A cross-sectional study via an online survey was conducted among 1019 adult Omani nationals residing in Oman. The presence of SAD was assessed using the Arabic version of the Liebowitz Social Anxiety Scale (LSAS). Result: Nearly half the participants (45.9%, n=468) endorsed themselves as having features of SAD as defined by LSAS. In the multivariate logistic analysis, participants below 40 years of age were 1.6 times (OR=1.568, p=0.026) more likely to have SAD than those who were 40 and older. Women were 1.3 times (OR=1.348, p=0.038) more likely to endorse SAD than men. Participants who had secondary or undergraduate education were respectively 1.5 times (OR=1.45, p=0.014) and 2.5 times (OR=2.509, p<.001) to have SAD than who were postgraduates. Conclusion: The present data suggest that 45.9% of the participants reached the cut-off for case-ness in LSAS, which is high compared to reports from other populations. As online survey respondents tend to belong to similar demographics, the current results need not be representative of the Omani adult population, which calls for studies that adopt more inclusive survey methods.

This pilot study explores the potential of using a citizen science approach for sourcing volunteered geographic information via social media to research wildlife tourism interactions with endangered Borneo Pygmy Elephants on the lower Kinabatangan River in Sabah, Malaysia. Such information is critical if the lower Kinabatangan region is to achieve the United Nations Sustainable Development Goals through a sustainable tourism industry based around viewing the pygmy elephants. Guests and guides from the Sukau Rainforest Lodge were encouraged to become close-range remote sensors by sharing geotagged photographs of pygmy elephant sightings on Flickr. A ten week on-ground trail generated 247 photographs shared by 17 individual contributors with approximately two-thirds (65%) of photographs being georeferenced for the time and location of the elephant sighting. Plotting those sighting to explore the vegetation matrix (i.e. remnant forest or oil palm plantation) showed almost three-quarter (73%) of the sightings occurred within 1 km of an oil palm plantation. Of greater concern is that one in two sightings (50%) along the river occurred within the 500 m of an oil palm planation, which is inside the riparian buffer that the Sabah Government recommended for conservation of the elephants in their Lower Kinabatangan range. This study therefore demonstrates proof of concept for this research method and its further application at the nexus of wildlife conservation and sustainable ecotourism research.

Social capital creates a synergy that brings many benefits to members of a community. Thus, the main objective of this article was to examine whether social capital can improve a society's food security. If yes, how? To answer these questions, a systematic literature review was conducted using the Prisma approach. The output of this method led to finding 39 related articles. Precise studying these articles illustrated that social capital improves food security through two mechanisms of knowledge sharing and product sharing (i.e., sharing food products). It revealed that social capital through improving the food security pillars (i.e., food availability, food accessibility, food utilization, and food system stability) affects food security. In other words, the interaction among the members of the community results in sharing food products and information among community members, and this facilitates food availability and access to food. There are many shreds of evidence in the literature that sharing food and food product among the community member decreases household food security and provides the healthy nutrition to the vulnerable families and improve the food utilization pillar of food security. In addition, it is disclosed that belonging to the social networks increases the resilience of the community members and decreases the vulnerability of the community that subsequently strengthens the stability of a food system. This study contributes to the common literature on food security and social capital by providing a conceptual model based on the literature. In addition to researchers, policymakers can use the finding of this study to provide solutions to address food insecurity problems.

Understanding behavioral factors associated with obesity is of importance in addressing this issue. This study examined the association between cognitive restraint, uncontrolled eating, emotional eating and body mass index (BMI) and amount of food plated, consumed, leftovers, and leftover food thrown into the trash (food wasted) in early adolescent girls nine to 13 years in O’ahu, Hawai’i (n = 93). Food plated, consumed, leftovers, and food wasted were estimated using a three-day mobile food record (mFR). Weight and height were measured to compute BMI (kg/m2). The three-factor eating questionnaire provided a score from 0 to 100 for cognitive restraint, uncontrolled eating, and emotional eating. Higher scores are indicative of greater cognitive restraint, uncontrolled eating, and emotional eating. Pearson’s correlation and general linear models were computed to examine the relationship between three factor eating scores, BMI, and food plated, consumed, leftovers, and food wasted. There was no clinically significant association between cognitive restraint and amount of food wasted. Cognitive restraint was positively correlated with BMI (r=0.36, p<0.001) and with BMI z score (r=0.40, p<0.001). Uncontrolled eating and emotional eating were positively correlated with amount of leftover food at dinner (r=0.30, p=0.006; r=0.33, p=0.003, respectively). Emotional eating was positively associated with percentage of leftover food at dinner (r=0.24, p=0.30). Additional research should examine the specific roles of cognitive restraint, uncontrolled eating, emotional eating and food waste in the development of obesity in adolescents.

The commitment of the EU to Corporate Social Responsibility (CSR) is projected in the EU law about annual reporting by businesses. Since EU member states further develop this framework by their own domestic laws, annual reporting with CSR information is not unified and just partially mandatory in the EU. Do all European businesses report CSR information and what public declaration to society do they provide with it? The main dual purpose of this paper is identifying the parameters of this annual reporting duty and studying the CSR information provided by the ten largest Czech companies in their annual statements for 2013-2017. Based on legislative research and the teleological interpretation, the current EU legislative framework with Czech particularities is presented and, via a case study exploring 50 annual reports, the data about the type, extent and depth of the CSR is dynamically and comparatively assessed. It appears that, at a minimum, large Czech businesses satisfy their legal duty and e-report on CSR in a similar extent, but in dramatically different quality. Employee matters and adherence to international standards are used as a public declaration to society more than the data on environmental protection, while social matters and R&D are played down.

The COVID-19 pandemic has resulted in a wide range of spatial interventions to slow down the spread of the virus. The spatial limitations of narrow public circulation spaces within informal settlements, which house over one billion people around the world, make it impossible for pedestrians to practice physical distancing (or social distancing). In this paper, we propose a flexible mathematical method, named the Cluster Lane Method, for turning a planar circulation network of any size or complexity into a network of unidirectional lanes, making physical distancing possible in narrow circulation spaces by limiting face-to-face interactions. New notions and theorems about oriented graphs in graph theory are introduced. The paper ends with a discussion of the potential implementation of this cost-efficient, low-tech, sustainable solution, and with the introduction of a novel unidirectional tactile paving for the visually impaired.

How can neuroscience help everyone to live and care for our confined brains? Understanding and studying human behaviour allows us to measure the impact of such confinement on each of us and to identify those who need help. The challenges are to understand the psychological repercussions following confinement and to understand how neuroscience and neurotechnology can be very interesting tools for dealing with the health crisis. Neuroscience is changing our traditional philosophical and ethical views by providing information about the biological basis of our moral behaviour. The exception of the brain is at the heart of neuroethical thinking and discourse. Neuroethics is an interdisciplinary discipline placed at the intersection between the human sciences and the neurosciences, and aims to help understand how knowledge and research in neurosciences and neurotechnologies will affect the future of society, their impact on humans, relationships, daily life, the labour market ... but also how they can help and provide solutions and answers to the questions of citizens in a health crisis. But it's a double-edged sword, collecting and analyzing brain data in real time seems to be increasingly simple and within everyone's reach, without having the hindsight of the real meaning of these data, allowing one day to read people's thoughts, control them and manipulate them. It is becoming clear that the boundaries between medical and non-medical uses of neuroscience and neurotechnology are becoming very porous, inviting us to reflect on neuroethical issues in order to put safeguards on these uses.

Place attachment is an emotion that people experience in connection to a specific place and it is needed to maintain sustainable neighborhood community. The emotion is affected by various factors, such as experience, function, environment, and satisfaction. This study focuses on commercial structures, which are one feature that characterize the physical environments of neighborhoods. The aim of this study is to determine the effects of commercial activities in different commercial environments on social bonding and place attachment in residents. Two sites were selected for analysis due to their different commercial environments, and path analysis was used to examine the relationships among factors. The results indicate that the type of commercial environment had effects on commercial activities, including shopping frequency, and that commercial activities affected social bonding and place attachment in residents. Also, commercial activities had indirect effects on place attachment through social bonding between residents. These results suggest that the commercial environment is an important element affecting the community and place attachment of residents in neighborhoods.

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.

Problem gambling among young people is an emerging trend globally. The online environment in particular offers various possibilities for gambling engagement. This is the first cross-national survey study using the social ecological model to analyze problem gambling, especially in the online context. The aim was to analyze how different social ecological spheres explain problem gambling. Participants were young people aged 15–25 in the United States (n = 1,212), South Korea (n = 1,192), Spain (n = 1,212), and Finland (n = 1,200). The South Oaks Gambling Screen (SOGS) instrument was used as a measure for problem gambling. Regression models predicted problem gambling with measures of intrapersonal, interpersonal, organizational, and societal spheres. Spanish participants had the highest SOGS score for problem gambling. Out of the spheres, organizational-sphere measures best explained the variation in problem gambling in all countries (26%) when compared to the societal (3%), interpersonal (5%) and intrapersonal (11%) spheres. In the full model, organizational-sphere measures had strong associations with problem gambling. These included consumer debt, online gambling community participation, online casino participation, and exposure to online pop-up advertisements. Other robust predictors of problem gambling included conformity to group norms in the interpersonal sphere and male gender and impulsivity in the intrapersonal sphere. Cross-national results were similar in different countries. The online context plays a major role in problem gambling behavior. The social ecological model is a useful tool by which to tackle problem gambling and develop preventative measures.

The role of Social Media Marketing (SMM) in marketing strategies is rapidly growing. Because the use of social media is growing, the industry of SMM will grow bigger in the coming years; the pace of this growth is faster than ever. To survive in the modern competitive world, effective use of SMM for a firm is a must; for that, every SMM channel needs to be used to its full potential. For a marketing campaign to be effective, there is a need for some metrics to measure the success of the SMM campaign. These metrics measure if the campaign is successfully implemented or not. This would help firms understand the market, gain a competitive advantage, and ultimately get a positive impact on the overall business. This study categorizes SMM strategy into 4 dimensions and associates 10 broad categories of SMM metrics to these dimensions. The proposed model of this study suggests the application of Social Media Analytics (SMA) ineffective use of metrics to measure SMM campaigns. There are so many SMA Tools available for free and time-efficient data analysis that can lead to faster and better results than manual analysis. Following this model, the importance of SMA tools in devising an effective SMM strategy is highlighted. The implication of this research is towards a better understanding of the application of SMA for any firm to have a solid SMM Strategy, especially small and medium-sized enterprises that have limited resources.

The COVID-19 pandemic caused by the novel coronavirus emerged in Wuhan City, Hubei province of China at the end of 2019, has radically transformed the lives of people around the world. Due to its fast spreading, it is currently considered as a worldwide health, social and economic concern. The lack of knowledge on this area has encouraged academic sphere for extensive research, which is reflected in exponentially growing scientific literature in this area. However, current state of COVID-19 research reveals only early development of knowledge, while a comprehensive and in-depth overview remains neglected. Accordingly, the main aim of this paper is to fill the aforementioned gap in the literature and provide an extensive bibliometric analysis of COVID-19 research across science and social science research landscape, using innovative and sophisticated bibliometric approaches (e.g. Venn diagram, Biblioshiny descriptive statistics, VOSviewer co-occurrence network analysis, Jaccard distance cluster analysis, text mining based on logistic regression). The bibliometric analysis is based on the Scopus database including all relevant and latest information on COVID-19 related publications (n=16,866) in the first half of 2020. The empirical results indicate that there is still a lack of publications of COVID-19 and its implications in less-explored (non-health) sciences, especially in social sciences. Accordingly, the findings emphasize an importance of a comprehensive and in-depth approach considering different scientific disciplines in COVID-19 research. The understanding of the evolution of emerging scientific knowledge on COVID-19 is beneficial not only for scientific community but also for evidence-based policymaking in order to prevent and address the COVID-19 pandemic.

Green public space immensely provides ecological soundness (ES), social resilience, social inclusiveness, mental health, self-esteem, and cultural prosperity from privileged class to lower ones. This research aims at estimating the effect of social services, safety, and infrastructural amenity in green space (parks) on mental health building self-esteem for elderly population. Data were collected from four parks out of 21 in Dhaka selected by systematic random sampling. Two-hundred and three elderly participants were picked up for survey using snowball sampling. The survey was conducted in a pre-structured questionnaire consisted of 40 close-ended questions. Data was analyzed applying ordinal logistic model, multivariate regression analysis, and Partial Least Square (PLS) -Path Modeling. The study explored several key findings-1) Infrastructural amenities impacted social services of parks; 2) Social services contributed positively to mental health boosting up self-esteem for elderly population. 3) Likewise, mental health for elderly population was affected by safety measure of green space. Dhaka requires constructing age-friendly parks to promote elderly mental health.

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