: This study aims at examining how B Corporations advance Sustainable Development Goals (SDGs) in their practices by analyzing the socioenvironmental problems they address and the solutions they provide to those problems. All Argentinian B corporations, certified by early 2023 (135 companies), were investigated using a mixed approach, combining social network analysis with textual data analysis. The results showed that the environmental practices are primarily linked to waste, water, energy and chemical management, as well as product innovation. In turn, the social practices address the training, education, and well-being of employees and other stakeholders, diversity, equity and inclusion management, and the creation of an inclusive and fair environment, integrating local communities. Thus, in the flow of their sustainability practices, Argentinian B Corporations contribute to SDGs 8, 12, 13, 9, 6, 7, 5, 10, 11, 4, and 17, in line with the SDGs declared by these companies. Our findings contribute to the theoretical knowledge of the B Corp movement and have practical implications by providing inputs to improve the management of B Corporations and to guide public policies encouraging these companies to advance sustainable development dimensions lacking attention.

This article presents the development and validation of a new instrument measuring social, cultural, and behavioral factors influencing exposure to occupational zoonoses in agricultural settings. The Social Ecological Model (SEM) and the Standards for Educational and Psychological Testing were used as guiding frameworks to ensure the instrument's validity. The instrument's content was compiled by combining the results of a scoping literature review and an expert qualitative study. The instrument items were drafted, organized, and underwent a meticulous process of revision and adjustment. It was translated into Spanish and tested in one-to-one cognitive interviews with five volunteer agricultural workers. Exploratory factor analysis was conducted for construct discrimination, and bivariate regression analyses were conducted to explore the association with exposure indicators. Evidence of validity was obtained from four out of five sources of validity evidence according to the AERA/APA’s Standards of Educational and Psychological Testing. The Social Ecology of Occupational Zoonoses (SEOZ) was successfully used to determine social and behavioral factors associated with a higher risk of exposure to occupational zoonoses. Further use of the SEOZ can provide valuable insights into developing effective interventions to improve the health and well-being of agricultural workers.

Since the outbreak of COVID-19, social media platforms, such as Twitter, have experienced a tremendous increase in conversations related to Long COVID. The term “Long COVID” describes the persistence of symptoms of COVID-19 for several weeks or even months following the initial infection. Recent works in this field have focused on sentiment analysis of Tweets related to COVID-19 to unveil the multifaceted spectrum of emotions, viewpoints, and perspectives held by the Twitter community. However, most of these works did not focus on Long COVID, and the few works that focused on Long COVID have limitations. Furthermore, no prior work in this field has investigated Tweets where individuals self-reported experiencing Long COVID on Twitter. The work presented in this paper aims to address these research challenges by presenting multiple novel findings from a comprehensive analysis of a dataset comprising 1,244,051 Tweets about Long COVID, posted on Twitter between May 25, 2020, and January 31, 2023. First, the analysis shows that the average number of Tweets per month where individuals self-reported Long COVID on Twitter, has been considerably high in 2022 as compared to the average number of Tweets per month in 2021. Second, findings of sentiment analysis using VADER show that the percentage of Tweets with positive, negative, and neutral sentiment were 43.12%, 42.65%, and 14.22%, respectively. Third, the analysis of sentiments associated with these Tweets also shows that the emotion of sadness was expressed in most of these Tweets. It was followed by the emotions of fear, neutral, surprise, anger, joy, and disgust, respectively.

The exoskeleton technology has been rapidly advancing in the recent past due to its multitude of applications and diverse use-cases in assisted living, military, healthcare, firefighting, and industry 4.0. The exoskeleton market is projected to increase by multiple times of its current value within the next two years. Therefore, it is crucial to study the degree and trends of user interest, views, opinions, perspectives, attitudes, acceptance, feedback, engagement, buying behavior, and satisfaction, towards exoskeletons, for which the availability of Big Data of conversations about exoskeletons is necessary. The Internet of Everything style of today's living, characterized by people spending more time on the internet than ever before, with a specific focus on social media platforms, holds the potential for the development of such a dataset, by the mining of relevant social media conversations. Twitter, one such social media platform, is highly popular amongst all age groups, where the topics found in the conversation paradigms include emerging technologies such as exoskeletons. To address this research challenge, this work makes two scientific contributions to this field. First, it presents an open-access dataset of about 140,000 tweets about exoskeletons that were posted in a 5-year period from May 21, 2017, to May 21, 2022. Second, based on a comprehensive review of the recent works in the fields of Big Data, Natural Language Processing, Information Retrieval, Data Mining, Pattern Recognition, and Artificial Intelligence that may be applied to relevant Twitter data for advancing research, innovation, and discovery in the field of exoskeleton research, a total of 100 Research Questions are presented for researchers to study, analyze, evaluate, ideate, and investigate based on this dataset.

The present article aims at investigating the role of social support in the emotional well-being of young offenders. We hypothesized that perceived social support would be positively related to the emotional well-being of juvenile offenders. The methods were worked out to study perceived and received social support, psychological well-being and emotional state of the juvenile offenders. The entire sample consisted of 56 males aged from 15 to 18 years old (M = 16.5; SD = 0.8). 32 subjects (57%) were in pretrial detention and 24 participants (43%) were in a correctional camp located in the central region of Russia. The study detected that the level of psychological well-being of the respondents from the camp was correlated neither with perceived social support nor with the frequency of seeking assistance from the different sources of support. For the respondents in the pretrial detention, the level of psychological well-being was directly connected to the degree of the perceived support from the friends. The obtained differences might be associated with the influence of social environment in the pretrial detention and in the camps.

Nigeria's upstream oil and gas sector is extensively contributing to the economic growth of the country, but the sector is plagued with challenges around corporate social responsibility (CSR) and taxation practices. Petroleum Industry Act (PIA) is introduced to tackle these challenges towards promoting sustainable development in Nigeria. The aim of this study is to explore the PIA’s provisions on CSR and taxation, identify the Act’s implementation challenges and improvement opportunities, propose an integrated framework for monitoring and evaluating the PIA’s impact on CSR and taxation over time, and recommend measures for enhancing PIA’s impact on CSR and taxation support for sustainable development in Nigeria's upstream oil and gas sector. This study adopts the qualitative desk review method to analyze existent literature, reports, and documents regarding PIA’s provisions on CSR and taxation. Findings reveal that the PIA’s provisions greatly emphasize CSR initiatives and taxation transparency in improving responsible ethical business behaviour. An integrated framework for monitoring and evaluating PIA’s impact over time is developed. This study concludes that the PIA's provisions can balance CSR and taxation practices for sustainable development. The study’s recommendations include using the integrated framework as a structured strategy for monitoring and evaluating the PIA’s impact. This study contributes to the discussion on the imperatives of ethical business practices and regulatory frameworks for sustainable development drive in the oil and gas sector.

Man-made shallow fishponds in the Czech Republic have been facing a high eutrophication since 1950s. Anthropogenic eutrophication and feeding of fish have strongly affected the physico-chemical properties of water and its aquatic community composition leading to harmful algal bloom formation. In our current study, we have characterised the phytoplankton community across three hypertrophic ponds to assess the phytoplankton dynamics during the vegetation season. We microscopically identified and quantified 29 cyanobacterial taxa comprised of non-toxigenic and toxigenic species. Further, a detailed cyanopeptides (CNPs) profiling was performed using molecular networking analysis of liquid chromatography tandem mass spectrometry (LC–MS/MS) data coupled with dereplication strategy. This MS networking approach coupled with dereplication on online global natural product social networking (GNPS) web platform led us to putatively identify forty CNPs: fourteen anabaenopeptins, ten microcystins, five cyanopeptolins, six microginins, two cyanobactins, a dipeptide radiosumin, a cyclooctapeptide planktocyclin and epidolastatin12. We have applied the binary logistic regression to estimate the CNPs producer by correlating the GNPS data with the species abundance. Usage of The combination of molecular networking and dereplication on online global natural product social networking (GNPS) web platform has proved as a valuable approach for rapid and simultaneous detection of high number of peptides, and rapidly assessing the risk for harmful bloom.

This article delves into the psychological dimensions of peace as articulated in the Srimad Bhagavad-Gita, an ancient Indian scripture. Through its dialogue between Lord Krishna and the warrior Arjuna, the Bhagavad-Gita presents profound insights into achieving inner peace, managing conflict, and fostering a peaceful society. The text aligns with contemporary psychological constructs such as self-realization, mindfulness, emotional regulation, and prosocial behavior. Additionally, it addresses how the teachings enhance social engagement and disengagement, as well as cognitive, affective, mental, and physical regulation. The Bhagavad- Gita's bidirectional question-answering approach motivates, reasoning, and rationality, decision- making and goal-directed behavior. This analysis demonstrates the relevance of these ancient principles in addressing modern psychological challenges, providing a holistic framework for understanding and cultivating peace. Ultimately, the treatise portrays peace as a reflection of safety, security, and social well-being, making its teachings profoundly relevant today.

(1) Background: Nursing homes’ preparedness in managing a public health crisis has been fragile, with effects on safety culture. The objective of this study was to assess nursing homes’ COVID-19 preparedness in Southern Portugal, including personnel’s work experiences during the pandemic. (2) Methods: We used a COVID-19 preparedness checklist to be completed by management teams, followed by follow-up calls to nursing homes. Thereafter, a survey to personnel was applied. Data analysis included descriptive statistics, exploratory factor analysis, and thematic analysis of open-end questions. (3) Results: In total, 71% (138/195) of eligible nursing homes returned the preparedness checklist. We conducted 83 follow-up calls and received 720 replies to the personnel survey. On average, 25% of nursing homes did not have an adequate decision-making structure to respond to the pandemic. Outbreak capacity and training were fragile areas among nursing homes’ contingency plans. We identified compliance with procedures and nonpunitive response to mistakes as fragile areas of safety culture, and teamwork as a strong safety area. (4) Conclusions: To strengthen how nursing homes cope with upcoming phases of the COVID-19 pandemic or future public health emergencies, nursing homes’ preparedness and safety culture should be fostered and closely monitored.

Respiratory viral infections (RVI) are common reasons for healthcare consultations. The inpatient management of RVI consumes significant resources. From 2009-2014, we assessed the costs of RVI management in 4776 hospitalized chil-dren aged 0-18 years participating in a quality improvement program, where all ILI patients underwent virologic testing at the National Reference Centre followed by de-tailed recording of their clinical course. The direct (medical or non-medical) and indirect costs of inpatient management outside the ICU (“non-ICU”) versus management requiring ICU-care (“ICU”) added up to 2,767.14€ (non-ICU) vs. 29,941.71€ (ICU) for Influenza, 2,713.14€ (non-ICU) vs. 16,951.06€ (ICU) for RSV infections, and 2,767.33€ (non-ICU) vs. 14,394.02€ (ICU) for human rhinovirus (hRV) infections, respectively. Non-ICU inpatient costs were similar for all 8 RVI studied: Influenza, RSV, hRV, ade-novirus (hAdV), metapneumovirus (hMPV), parainfluenzavirus (hPIV), bocavirus (hBoV) and seasonal coronavirus (hCoV) infections. ICU-costs for Influenza however, ex-ceeded all other RVI. At the time of the study, Influenza was the only RVI with antivi-ral treatment options available for children, but only 9.8% of Influenza patients (non-ICU) and 1.5% of ICU-patients with Influenza received antivirals; only 2.9% were vac-cinated. Future studies should investigate the economic impact of treatment and pre-vention of Influenza-, COVID-19-, and RSV post vaccine introduction.

In this study, we identified the factors that affect the frequency of receiving nonmarket fruit and vegetables (FV). For Survey 1, we conducted a cross-sectional survey using a self-administered questionnaire for men aged 50–74 living in city (A) in Gunma, Japan. Participants were asked questions on FV receiving frequency, FV gardening, social cohesion (4–20 points), and basic characteristics. For Survey 2, a similar survey was conducted for residents aged 20–74 in three areas in city (B) in Gunma, but we included more variables. Ordinal logistic regression models were used for the analysis. In Survey 1, the responses of 243 participants were analyzed. The results showed that the FV receiving frequency was positively associated with non-gardeners and social cohesion. In Survey 2, the responses of 791 participants were analyzed. Vegetable receiving frequency was positively associated with rural and suburban areas, family structure, employment status, and non-farmers. The relationship between receiving frequency and social cohesion was similar to that found in Survey 1. In conclusion, in areas with flourishing FV cultivation, it seems to be easy to obtain FV through the social networks of reception, even for individuals who are not cultivating FV themselves.

he paper presents an innovative method for tourist route planning inside a destination. The necessity of reorganizing the tourist routes within a destination comes as an immediate response to the Covid-19 crisis. The implementation of the method inside tourist destinations can bring an important advantage in transforming a destination into a safer destination in times of Covid-19 and post-Covid-19. The existing trend of shortening the tourist stay length has been accelerated while the epidemic became a pandemic. Moreover, the wariness for future pandemics has brought into spotlight the issue of overcrowded attractions inside a destination at certain moments. The method presented in this paper proposes a backtracking algorithm, more precisely an adaptation of the travelling salesman problem. The method presented is aimed to facilitate the navigation inside a destination and to revive certain less-visited sightseeing spots inside a destination while facilitating conformation with the social distancing measures imposed for Covid-19 control.

The NOSTR is a communication protocol for the social web, based on the w3c websockets standard. Although it is still in its infancy, it is well known as a social media protocol, thousands of trusted users and multiple user interfaces, offering a unique experience and enormous capabilities. To name a few, the NOSTR applications include but are not limited to direct messaging, file sharing, audio/video streaming, collaborative writing, blogging and data processing through distributed AI directories. In this work, we propose an approach that builds upon the existing protocol structure with end goal a decentralized marketplace for federated learning and LLM training. In this proposed design there are two parties: on one side there are customers who provide a dataset that they want to use for training an AI model. On the other side, there are service providers, who receive (parts of) the dataset, train the AI model, and for a payment as an exchange, they return the optimized AI model. The decentralized and censorship resistant features of the NOSTR enable the possibility of designing a fair and open marketplace for training AI models and LLMs.

This review article explores the convergence of virtual reality (VR) and architectural design from an inclusive lens. It underscores the crucial role of virtual reality (VR) in serving as a catalyst for the incorporation of social and cultural sustainability principles in architectural projects. The exploration is guided by inclusive design principles, which encompass several aspects such as accessibility, cultural sensitivity, diversity and inclusivity, user-centered design, and empathy. These concepts serve as the basis for further investigation into the potential of virtual reality (VR) technology to enhance and heighten these features within architectural design, therefore promoting the progress of social and cultural sustainability. The review article highlights the profound impact that virtual reality (VR) may have, going beyond mere visualisation to generate architectural experiences that are immersive, interactive, and empathetic. These experiences are designed to take into account diverse perspectives and needs.

Emotion recognition and social inference impairments are well-documented post-traumatic brain injury (TBI) yet the mechanisms underpinning these are not fully understood. We examined dynamic emotion recognition, social inference abilities, and eye fixation patterns between adults with and without TBI. Eighteen individuals with TBI and 18 matched non-TBI participants were recruited and underwent all three components of The Assessment of Social Inference Test (TASIT). The TBI group were less accurate in identifying emotions compared to the non-TBI group. Individuals with TBI also scored lower when distinguishing sincere and sarcastic conversations but scored similarly to those without TBI during lie vignettes. Finally, those with TBI also had difficulty understanding the actor’s intentions, feelings, and beliefs compared to participants without TBI. No group differences were found for eye fixation patterns and there were no associations between fixations and behavioural accuracy scores. This conflicts with previous studies and might be related to an important distinction between static and dynamic stimuli. Visual strategies appeared goal- and stimulus-driven, with attention being distributed to the most diagnostic area of the face for each emotion. These findings suggest that low-level visual deficits may not be modulating emotion recognition and social inference disturbances post-TBI.

Digital technologies are becoming increasingly relevant in the processes of documenting, surveying, enhancing and preserving Cultural Heritage, also through applications that are increasingly optimized and oriented towards new data management and accessibility processes. This great potential can find significant levels of application in the tourism sector, seeking new strategies to access, discover, understand cultural assets. In this direction, many digital applications have already found interesting outcomes in the tourism sector, but there is large room for improvement in the applications for “minor”, small or neglected cultural sites, not included in conventional tourism routes, which play a key-role in social inclusion and territorial cohesion, and for the development of social, economic and environmental sustainability. The paper presents a conceptual framework or possible outline to foster the use of digital technologies through a set of integrated bottom-up and top-down actions, to facilitate connections of minor sites into larger networks, contributing to search for new forms of active fruition and social participation.

As the digital era advances, many industries continue to expand their use of digital technologies to support company operations, notably at the customer interface, bringing new commercial opportunities and increased efficiencies. However, there are new sets of responsibilities associated with the deployment of these technologies, encompassed within the emerging concept of corporate digital responsibility (CDR), which to date has received little attention in the academic literature. This exploratory paper thus looks to make a small contribution to addressing this gap in the literature. The paper adopts a qualitative, inductive research method, employing an initial scoping literature review followed by two case studies. Based on the research findings, a simple model of CDR parameters is put forward, and the article concludes with a discussion of a number of emergent issues - fair and equitable access, personal and social well-being, environmental implications, and cross-supply chain complexities - that suggest possible directions for future research.

The purpose of this study was to examine the problem of violent extremism among young people. Additionally, a youth violent extremism scale (YVES) was developed that takes into account the differences between and within Arab cultures. The goal was to produce a scale that could be used and tested within an Arab country or between Arab countries. The scale was developed in three stages: generation, refinement, and validation. A literature review and nomological network were utilized to show the scale's dimensions, correlations to those dimensions, and other relevant variables (such as the LSC, LSE, and criminality scale). A sample of 6726 young students from fifteen Arab countries and the authorities involved were selected. Findings showed that six factors were obtained through principal component factor analysis using Varimax and Kaiser normalization (29 items). A significant positive association was found (r=.651, p = 0.000), supporting the scale's validity. Using Cronbach's alpha, the scale reliability was strong and assessed at 0.98. The scale's construct validity was estimated by assessing the correlation between the Youth Violent Extremism scale and low self-control. A significant positive correlation (r=.651, p = 0.000) indicates the scale's validity. Findings showed significant differences between males and females in youth violent extremism (F = 13.678, α ≤0.000). Descriptive results showed, however, that females have a slightly higher mean of violent extremism than males (M =85.2 vs. 87.6), with a close variation (26 vs. 27) for males and females, respectively. In this study, a measurement tool was provided that can be used as a knowledge base for security strategies. The scale can be applied to identify legal, social, and educational policies and applications of violent extremism. Future research is needed to test the scale on different professions like teachers, police officers, and parents. Also, a need to test the scale on different age groups, settings, and cultures. A need for atheoretical and empirical framework for understanding and preventing youth violent extremism through promoting a more cohesive and resilient youth society.

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.

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.

The real challenge in Human Robot Interaction (HRI) is to build machines capable of perceiving human emotions so that robots can interact with humans in a proper manner. It is well known from the literature that emotion varies accordingly to many factors. Among these, gender represents one of the most influencing one, and so an appropriate gender-dependent emotion recognition system is recommended. In this paper, a two-level hierarchical Speech Emotion Recognition (SER) system is proposed: the first level is represented by the Gender Recognition (GR) module for the speaker’s gender identification; the second is a gender-specific SER block. Specifically for this work, the attention was focused on the optimisation of the first level of the proposed architecture. The system was designed to be installed on social robots for hospitalised and living at home elderly patients monitoring. Hence, the importance of reducing the software computational effort of the architecture also minimizing the hardware bulkiness, in order for the system to be suitable for social robots. The algorithm was executed on the Raspberry Pi hardware. For the training, the Italian emotional database EMOVO was used. Results show a GR accuracy value of 97.8%, comparable with the ones found in literature.

The social confinement resulting from the COVID-19 crisis temporarily reduced greenhouse gas emissions. Although experts consider that the decrease in pollution rates was not drastic, some surveys detect a growth in social concern about the climate. In this environment, institutions, city councils and companies have promoted sustainable tourism as a necessary option, even before world society regains freedom of movement. This work analyzes and geolocates the sustainable tourism and ecotourism proposals on Twitter, quantitatively and qualitatively, using the Twitonomy Premium tool, with data extracted at the end of December 2020. The results show an arduous activity in Ireland, Kenya, Sri Lanka, India, Croatia, Spain, Finland, France, Mexico and Pakistan, among others. The accounts that achieve the most impact and engagement are both from public institutions and influencers specialized in travel, writers and chefs, who act as eco-influencers. Ecotourism is promoted as the necessary option for the conservation of cities and landscapes, which will be visited by tourists supposedly more aware after the virus.

The COVID-19 outbreaks have caused universities all across the globe to close their campuses and forced them to initiate online teaching. This article reviews the pedagogical foundations for developing effective distance education practices, starting from the assumption that promoting autonomous thinking is an essential element to guarantee full citizenship in a democracy and for moral decision making in situations of rapid change, which has become a pressing need in the context of a pandemic. In addition, the main obstacles related to this new context are identified, and solutions are proposed according to the existing bibliography in learning sciences.

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.

In relation to organizational performance measurement, there is a growing concern about the creation of value for people, society and the environment. The traditional corporate reporting does not adequately satisfy the information needs of stakeholders for assessing an organization’s past and future potential performance. Practitioners and scholars have developed new non-financial reporting frameworks from a social and environmental perspective, giving birth to the field of Integrated Reporting (IR). The Economy for the Common Good (ECG) model and its tools to facilitate sustainability management and reporting can provide a framework to do it. The present study is the first one that empirically validates such metrics on a sample of 206 European firms. Consequently, it allows knowledge to advance as it checks their statistical validity and reliability.

In the U.S. 44% of low-income households struggle to pay their utility bills, affecting their ability to afford necessities such as food and health expenses. Several government and utility funded energy efficiency programs exist to assist those experiencing energy insecurity. In Salt Lake City, Utah, there is a high demand for, but low availability of, energy efficiency services in underserved neighborhoods creating an opportunity for creative community-based programs to fill this inherent gap. This pilot project, involving the exchanging of LED bulbs in Salt Lake City, highlights the development of a community-based energy efficiency program that aims to bring energy savings to a uniquely targeted portion of the city and determines its feasibility in addressing energy insecurity at a larger scale. Through the 8-month project duration, 1,432 bulbs were exchanged at 23 events reaching 181 households in low-income areas. Through a year of use, these bulbs are estimated to save residents approximately 18,219 USD in electricity bills and reduce CO2 emissions from power plants by 122.23 metric tons, in addition to a savings of 4,400 USD in social cost of carbon as defined by the U.S. Environmental Protection Agency. Since this pilot reached less than 1% of households, we extrapolated a reach of 2%, 5%, and 7.5% and found substantial potential decreases in power plant emissions and financial savings. As this project is ongoing and being expanded, we discuss relevant findings that will help shape future community-based models so that they are appropriately deployed and more effective in alleviating local energy insecurity.

Polarization in online social networks has gathered a significant amount of attention in the research community and in the public sphere due to stark disagreements with millions of participants in topics surrounding politics, climate, the economy and other areas where an agreement is required. There are multiple approaches to investigating the scenarios in which polarization occurs and given that polarization is not a new phenomenon but that its virality may be supported by the low cost and latency messaging offered by online social media platforms; an investigation into the intrinsic dynamics of online opinion evolution is presented for complete networks. Extending a model which utilizes the Binary Voter Model (BVM) to examine the effect of the degree of freedom for selecting contacts based upon homophily, simulations show that different opinions are reinforced for a period of time when users have a greater range of choice for association. The facility of discussion threads and groups formed upon common views further delays the rate in which a consensus can form between all members of the network. This can temporarily incubate members from interacting with those who can present an alternative opinion where a voter model would then proceed to produce a homogeneous opinion based upon pairwise interactions.

Due to the limitations on the capabilities of current robots regarding task learning and performance, imitation is an efficient social learning approach that endows a robot with the ability to transmit and reproduce human postures, actions, behaviors, etc., as a human does. Stable whole-body imitation and task-oriented teleoperation via imitation are challenging issues. In this paper, a novel comprehensive and unrestricted real-time whole-body imitation system for humanoid robots is designed and developed. To map human motions to a robot, an analytical method called geometrical analysis based on link vectors and virtual joints (GA-LVVJ) is proposed. In addition, a real-time locomotion method is employed to realize a natural mode of operation. To achieve safe mode switching, a filter strategy is proposed. Then, two quantitative vector-set-based methods of similarity evaluation focusing on the whole body and local links, called the Whole-Body-Focused (WBF) method and the Local-Link-Focused (LLF) method, respectively, are proposed and compared. Two experiments conducted to verify the effectiveness of the proposed methods and system are reported. Specifically, the first experiment validates the good stability and similarity features of our system, and the second experiment verifies the effectiveness with which complicated tasks can be executed. At last, an imitation learning mechanism in which the joint angles of demonstrators are mapped by GA-LVVJ is presented and developed to extend the proposed system.

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.

Fall prediction using machine learning has become one of the most fruitful and socially relevant applications of computer vision in gerontological research. Since its inception in the early 2000s, this subfield has proliferated into a robust body of research underpinned by various machine learning algorithms (including neural networks, support vector machines, and decision trees) as well as statistical modeling approaches (Markov chains, Gaussian mixture models, and hidden Markov models). Furthermore, some advancements have been translated into commercial and clinical practice, with companies in various stages of development capitalizing on the aging population to develop new commercially available products. Yet despite the marvel of modern machine learning-enabled fall prediction, little research has been conducted to shed light on the security and privacy concerns that such systems pose for older adults. The present study employs an interdisciplinary lens in examining privacy issues associated with machine learning fall prediction and exploring the implications of these models in elderly care and the Internet of Medical Things (IoMT). Ultimately, a justice-informed set of best practices rooted in social geroscience is suggested to help fall prediction researchers and companies continue to advance the field while preserving elderly privacy and autonomy.

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 response of building elements during earthquakes has been an area of concern for different researchers around the world. The NSEs are the first elements to attain failure, the buildings after damages in safety priority are classified as in “Life Safety” mode, but in reality, they are in “Collapse Safety” mode and the occupants inside the buildings are in a state of “Non-Life Safety” as a result of falling of the hazardous NSE’s like cladding's, partitions, hanging objects. In addition to the Life Cycle Cost Assessment (LCCA), the Social Life Cycle Assessment (SLCA) is overlooked by the majority of the researchers, the community must be prepared to respond to an event more efficiently without any major casualties or loss of life. It is expected that by the end of 2050, almost double the construction will take place, the embodied energy during the pre-construction, post-construction and demolition generates a lot of CO2s into the environment, hence sustainability should be given due importance, helping in the achievement of Sustainable Developmental Goals (SDGs).

The analysis of the human movement patterns based on the mobile network data makes it possible to examine a very large population cost-effectively, and led to several discoveries about human dynamics. However, the application of this data source is still not common practice. The goal of this study was to analyze the commuting tendencies of the Budapest Metropolitan Area using mobile network data and propose an automatized alternative to the current, questionnaire-based method. Commuting is predominantly analyzed by the census, but that is performed only once in a decade in Hungary. To analyze commuting, the home and the work locations of the subscribers are determined based on their appearances during and outside the working hours. The home locations were compared to census data at a settlement level. Then, the settlement and district level commuting tendencies were identified and compared to the findings of census-based sociological studies. It has been found that commuting analysis based on mobile network data strongly correlates with the census-based findings, even though home and work locations have been estimated by statistical methods. All the examined aspects, including commuting from sectors of the agglomeration to the districts of Budapest and demographic distribution of the commuters, show that mobile network data can be an automatized, fast, cost-effective, and relatively accurate way of commuting analysis, that could provide a powerful tool to the sociologists interested in commuting.

Unmanned aerial vehicles (UAVs) represent a new model of social robots for home care of dependent persons. In this regard, this article introduces a study on people’s feeling of safety and comfort while watching the monitoring trajectory of a quadrotor dedicated to determining their condition. Three main parameters are evaluated: the relative monitoring altitude, the monitoring velocity and the shape of the monitoring path around the person (ellipsoidal or circular). For this purpose, a new trajectory generator based on a state machine, which is successfully implemented and simulated in MATLAB/Simulink®, is described. The study is carried out with 37 participants using a virtual reality (VR) platform based on two modules, UAV Simulator and VR Visualiser, both communicating through the MQTT protocol. The participants’ preferences have been a high relative monitoring altitude, a high monitoring velocity and a circular path. These choices are a starting point for the design of trustworthy socially assistive UAVs flying in real homes.

In the increasingly competitive SVOD market, platforms face high churn rates and substantial revenue losses from SVOD content piracy, all of which limit their ability to invest in acquir-ing/creating content compelling enough to win and retain subscribers. Based on social exchange theory, this study argues that platforms can improve relationships with SVOD content users by offering tiered discounts in exchange for advertising/loyalty and by promoting anti-piracy messages with a prosocial (threatening) approach that emphasizes harm to filmmakers (punishment for pi-rates). We hypothesize that these incentives enhance subscription intention when the incentive specifications (advertising levels, loyalty levels, message approach, and message credibility) match the public’s heterogeneous dispositions (advertising attitude, loyalty attitude, justice sensitivity, and fear of punishment). In a survey on the intention to subscribe to a hypothetical new platform, we confirmed the hypothesized interactions for advertising-based discounts, loyalty-based discounts, and prosocial messages, but did not find support for threatening messages. Further exploration showed that the evaluation of platform content was much more influential than any other incentive and that tiered loyalty discounts had a remarkable capacity to enhance subscription intention. This study’s findings may help shape incentives that are more satisfying to users and ultimately more profitable for platforms.

In contrast to global AIDS data, which show a higher number of diagnosed HIV cases in women, the Indonesian National AIDS report reveals that the percentage of HIV cases in the country is significantly higher in men. Using a conceptual model of how social networks impact health, this paper describes how structural conditions, such as poverty, lack of job opportunities, and lack of income determined the engagement of Indonesian male labour migrants and motorbike taxi (also known as ojek) drivers in their respective professions and shaped their social networks. It also describes how these social networks created opportunities for various psychosocial mechanisms, including social influence, peer pressure, and intimate contact, that facilitated HIV infection through different behavioural pathways, such as unprotected sex with multiple partners and injecting drug use (IDU) practices. A qualitative design using face-to-face in-depth interviews was employed to collect data from participants in Yogyakarta municipality and Belu district, Indonesia. Participants were recruited using the snowball sampling technique, starting from two HIV clinics in the study settings. Data analysis was guided by a qualitative data analysis framework. The findings highlight the significance of structural conditions, such as poverty, poor family conditions, precarious employment, and lack of income, in determining the participants' engagement in labour migration and motorbike taxi driving. Involvement in these occupations allowed them to become acquainted with fellow labour migrants and ojek drivers, leading to cohabitation in the same shelters or areas and daily interactions, which fostered the development of social networks among them. These social networks then provided opportunities for various psychosocial mechanisms, including social influence through peer pressure and person-to-person contact. The influence and pressure experienced by the participants were reflected in their behaviours related to sex, condom use, and IDU, ultimately contributing to the transmission of HIV among them. The findings underscore the importance of public health interventions, such as HIV information and education, that take into account the dynamics of social networks in order to develop effective strategies for increasing understanding of HIV transmission and prevention, reducing vulnerability, and promoting safer behaviours among male labour migrants and ojek drivers.

This paper explores the views of a group of young men aged 16–18, studying towards a Level 1 diploma in music in the North East area of England. It uses the conceptualization of “social haunting” to focus our discussions about how Level 1 learners articulated their experiences in the context of their learning journeys and perceived marginalization. The research took place at a large Further Education (FE) college and included a series of five “research encounters” with the group of Level 1 learners. These encounters included a range of activities, resulting in a variety of data being collected, including several activity worksheets, structured and unstructured focus group interviews, and questionnaires. This paper focusses on the outcomes of a single research activity that focused on exploring the topic of marginalization. We present a discussion on social haunting as one of the emerging findings from this research encounter, outlining how the reality of the social and cultural legacy of the UK’s industrial past can shape today’s youth and their futures. We will talk about the young men’s views of marginalization, their school-to-work transitions, the formation of masculinity in post-industrial communities and the role of Further Education in it. The paper concludes by discussing some insights for practice and future research.

There are strong indications that the built environment intertwines consistently with the advent of Covid-19 and the need for post-disaster recovery. The advent of the Covid-19 pandemic has exerted adverse effects on both human and global developments; while the efforts to combat this menace call for an integrated human social capital index. This research seeks to adequately enhance the comprehension of how the built environment can be enhanced through resilience in the backdrop of the Covid-19 pandemic. The study's goal is to investigate the impact of a resilient built environment on increasing resilience in the aftermath of the Covid-19 pandemic in Nigeria. Overall, the quantitative study test the impact of four built environments resilience indices (Built Environment capitals; Disaster management indices, Awareness of the Covid-19 Pandemic, and Built Environment adaptive strategies) on Human social capital and Covid-19 pandemic Indices. This study reveals the role of human social capital in achieving a resilient built environment in the wake of Covid 19 pandemic in Nigeria. Also, built environment capitals, disaster management indices, and awareness on the Covid-19 have indirect effects on Covid-19 pandemic indices through the human social capital. The implication of the study is useful for Post-Covid 19 recovery; which is important for future planning of the built environment in Nigeria.

Companion animals play a central role in many families and are especially valued by those who are socially isolated. Crisis situations such as acute hospitalizations, homelessness and natural disasters can make it difficult to preserve the human-animal bond and can result in animals being surrendered or euthanized. Social support programs like the RSPCA NSW Emergency Boarding and Homelessness program support people experiencing crisis situations with emergency pet boarding, access veterinary treatment and individualized case management. This study aimed to estimate the social return on investment (SROI) for this program using standard SROI methodology. In-depth interviews were conducted with 13 program stakeholders and questionnaire responses were received from 29 program clients. Outcomes were quantified for four stakeholder groups: program clients, client’s animals, RSPCA Inspectors, animal pounds and shelters. Clients and their animals experienced the bulk of the benefit from the program, estimated to have a combined value of over $5 million AUD for the 2020-21 financial year. The estimated social return on investment was $8.21 for each $1 invested. The study demonstrates that keeping people together with their companion animals, or ensuring they are reunited as soon as possible, can reduce stressors, and improve outcomes for people and animals.

The sustainable metabolic engineering (SME) concept was defined by Stalidzans and Dace as an approach for the selection of most sustainable metabolic engineering designs taking the economic, environmental and social components of sustainability into account. In the centre of sustainability calculations is a genome scale metabolic model that provides full balance of all incoming and outgoing metabolic fluxes at steady state. Therefore, sustainability indicators are assigned for each exchange reaction enabling calculation of sustainability features of consumption or production of each metabolite. The further development of the SME concept depends on its implementation at the computational level to acquire applicable results – sustainable production strain designs. This study proposes for the first time a workflow and tools of SME implementation using constraint based stoichiometric modelling, genome scale metabolic models and growth coupled product synthesis approach. For SME application demonstration purposes, a relatively simple engineering task has been carried out. The most sustainable designs have been identified using Escherichia coli as chassis organism, glucose as a substrate and gene deletions as metabolic engineering tool. A growth coupled production design tool has been used to reduce the variability of sustainability. The 10 000 most sustainable designs were producing succinate as the main product with the number of deleted genes ranging from two to ten. A big number of similar designs has been identified due to the combinatorial explosion of different alternative combinations of gene deletion sets that result in interruption of the same metabolic pathways with the same impact on the metabolism.

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 rise of Asian and the stagnation of Western middle classes over the last thirty years have resulted in gradual convergence of income of large parts of the world’s population. Recent global crises ‐ the Great Recession and the COVID-19 pandemic ‐ have led to a decline in income and increase in income uncertainty. Rise in consumption of lower quality goods of shorter durability and an overall decline in demand and economic activity resulted as challenges to the global economy. In this paper, we argue that generational responsibility in consumption can be an environmentally sustainable response to crises which enables the economies to overcome the crisis of confidence and reaffirms community ties. As an element of long‐term orientation in consumption, generational responsibility is a cultural phenomenon dependent on solidarity within family and the wider community. It is characterized by consideration of consequences of consumption choices on the environment, and the abundance of savings and the usability of goods to be inherited by future generations. For companies, willing to revisit their traditional business models and incorporate principles of sustainability in their competitive strategies, promotion of generational responsibility can become a new source of competitive advantage and a driver of economic recovery.

Research focused on understanding wider systemic factors driving behavioral change is limited with a dominant focus on the role of individual farmer and psychosocial factors for farming practice change, including reducing fertilizer application in agriculture. Adopting a wider systems perspective, the current study examines change and the role that supporting services have on fertilizer application rate change. A total of 238 sugarcane growers completed surveys reporting on changes in fertilizer application along with factors that may explain behavior change. Logistic regressions and negative binomial count-data regressions were used to examine whether farmers had changed fertilizer application rates and if they had, how long ago they made the change, and to explore the impact of individual and system factors in influencing change. Approximately one in three sugarcane growers surveyed (37%) had changed the method they used to calculate fertilizer application rates for the cane land they owned/managed at some point. Logistic regression results indicated growers were less likely to change the basis for their fertilizer calculation if they regarded maintaining good relationships with other local growers as being extremely important, they had another source of off-farm income, and if they had not attended a government-funded fertilizer management workshop in the five years preceding the survey. Similar drivers promoted early adoption of fertilizer practice change; namely, regarding family traditions and heritage as being unimportant, having sole decision-making authority on farming activities and having attended up to 5 workshops in the five years prior to completing the survey. Results demonstrated the influence of government-funded services to support practice change.

Many microbes live in habitats below their optimum temperature. Retention of metabolic heat by aggregation or insulation would boost growth. Generation of excess metabolic heat may also provide benefit. A cell that makes excess metabolic heat pays the cost of production, whereas the benefit may be shared by neighbors within a zone of local heat capture. Metabolic heat as a shareable public good raises interesting questions about conflict and cooperation of heat production and capture. Metabolic heat may also be deployed as a weapon. Species with greater thermotolerance gain by raising local temperature to outcompete less thermotolerant taxa. Metabolic heat may provide defense against bacteriophage attack, by analogy with fever in vertebrates. This article outlines the theory of metabolic heat in microbial conflict and cooperation, presenting several predictions for future study.

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 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.

Limited observational studies have described the relationship between sleep duration and overall diet. The present study investigated the association between sleep duration at weekdays and empirically derived dietary patterns in a nationally representative sample of UK adults, aged 19-64 years old, participating in the 2008-2012 UK National Diet and Nutrition Survey Rolling Programme. Survey members completed between three to four days of dietary records. Sleep duration at weekdays was categorised into tertiles to reflect short, normal and long sleep duration. Social jetlag was calculated as the difference between sleep duration at weekends and weekdays. The association between sleep duration/ social jetlag and dietary patterns, derived by principal components analysis, was assessed regressing diet on sleep whilst accounting for the complex survey design and adjusting for relevant confounders. Survey members in the highest tertile of sleep duration had on average 0.45 (95% CI -0.78, -0.12) lower healthy dietary pattern score compared to middle tertile (p =0.007). There was an inverted u-shaped association between social jetlag and a healthy dietary pattern, such that when sleep at weekends exceeded weekday sleep by 1h 45min, scores for indicating a healthy dietary pattern declined (p =0.005). In conclusion, long sleep duration at weekdays and an increased social jetlag are associated with a lower healthy dietary pattern score. Further research is required to address factors influencing dietary patterns in long sleepers.

Chatbots are intelligent conversational computer systems designed to mimic human conversation to enable automated online guidance and support. The increased benefits of chatbots led to their wide adoption by many industries in order to provide virtual assistance to customers. Chatbots utilise methods and algorithms from two Artificial Intelligence domains: Natural Language Processing and Machine Learning. However, there are many challenges and limitations in their application. In this survey we review recent advances on chatbots, where Artificial Intelligence and Natural Language processing are used. We highlight the main challenges and limitations of current work and make recommendations for future research investigation

Rats, including those of the Sprague Dawley strain, may kill mice. Because of this muridical behavior, it is standard practice in many research animal housing facilities to separate mice from rats (i.e., the predators) to minimize stress for the mice. We therefore tested the effect of cohousing on the stress levels of mice from either the C57BL/6J (BL6) or the CD1 strain and Sprague Dawley (SD rat) by determining their fecal corticosterone or cortisol metabolites (FCM) concentration and investigated how cohousing impacts a behavioral assay, i.e., conditioned place preference for intragenus (i.e., mouse-mouse or rat-rat) dyadic social interaction (DSI CPP) that had been shown be sensitive to social factors, especially to handling by humans. We found that the two delivery batches of BL6 mice or SD rats, respectively, had different stress levels at delivery that were statistically significant for the BL6 mice. Even so, the BL6 mice cohoused with rats had significantly increased FCM concentrations, indicative of higher stress levels, as compared to (1) BL6 mice housed alone or (2) BL6 mice at delivery. In contrast to their elevated stress levels, the attractiveness for contextual cues associated with mouse-mouse social interaction (DSI CPP) even increased in rat-cohoused BL6 mice, albeit nonsignificantly. Thus, cohousing BL6 mice and rats did not impair a behavioral assay in BL6 mice that had proved to be sensitive to handling stress by humans in our laboratory. SD rats cohoused with BL6- or CD1 mice and CD1 mice cohoused with SD rats showed DSI CPP that was not different from our previously published data on SD rats and BL6 mice of the Jackson- or NIH substrain obtained in the absence of cohousing. Our findings suggest that the effect of cohousing rats and mice under the conditions described above on their stress levels as opposed to their behavior might be less clearcut than generally assumed and might be overriden by conditions that cannot be controlled, i.e., different deliveries. Our findings can help to use research animal housing resources, which usually are limited, more efficiently.

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.

Aymaraism, as a socio-cultural phenomenon, has given rise to components and elements of representativeness in the population of the Andes. However, the dialectic component of the Aymara as a nation is annulled by fundamental historiographical elements that underlie this process of identification. The empirical analysis of the historical data leads us to conclude that the Aymara language and culture contain ambiguous elements that cannot be defined according to the dialectical interpretation and the current narrative. Thus, the analysis of the cultural, linguistic and social elements of this population from the Early Horizon period to the present confirms the historical distortion towards a narrative component of origin and presence in the territory of the Qullasuyu, in the current geographical area of the Collao. In order to understand this phenomenon, this work promotes the complementarity of the analysis through the use of ethnoarchaeological and documentary elements in order to clarify the origin, synthesis and development of the Aymara from a historical perspective, leaving aside the dialectical component of the present.

This study addresses the influence of working conditions on Work-Related Quality of Life (WRQOL) among Spanish healthcare professionals. The research seeks to elucidate the mediating roles of job engagement and burnout, and the moderating effects of resilience and self-efficacy, in this relationship. Methods: The study included 374 healthcare workers from Spain, encompassing physicians, nurses, and nursing assistants. It employed a methodological approach using validated instruments to assess psychosocial risks, work-life quality, job engagement, burnout, and resilience. Data were gathered through self-reported questionnaires. Results: Key findings indicate a negative association between working conditions and WRQOL. Job engagement and burnout significantly mediated this relationship, accounting for 19% to 33% of the variance in WRQOL. Notably, lack of support emerged as a strong negative factor for work-related quality of life. Additionally, resilience moderated the relationship between lack of support and burnout. Conclusions: The study concludes that improving working conditions could increase WRQOL. Interventions aimed at enhancing engagement and addressing burnout may be effective. The moderating role of resilience suggests that strategies to enhance resilience could also be beneficial. These findings hold significant implications for policy formulation and human resources planning in healthcare, emphasizing the need for enhanced workplace support and the development of resilience among health workers.

Harbor porpoise are typically seen in small groups of 1-3 individuals, with aggregations of 20+ individuals treated as rare events. Since the 1990s, the harbor porpoise population in the Salish Sea has seen a significant recovery, which has led to an increased number of observed aggregations that exceed the more usual small group sizes. By combining the observational data of United States and Canadian research organizations, community scientists, and whale watch captains or naturalists, we demonstrate that harbor porpoise aggregations appear to be more common than previously known, with 160 aggregations documented in 2022 alone. Behavioral data also indicated that foraging behaviors were common and social behaviors, like mating, were seen more often during these encounters compared to small groups. Other behaviors that are considered to be rare or unknown, were also observed during these encounters, including cooperative foraging and vessel approach. These aggregations are likely important foraging and social gatherings for harbor porpoises. This holistic approach integrating data from two countries and multiple sources provides an ecosystem level assessment that more effectively reflects the habitat use of harbor porpoise in this region that do not recognize the socio-political boundaries imposed upon the natural world.

The textile and clothing (T&C) industry is not usually viewed as an exemplar of sustainable de-velopment and the circular economy, as the industry has hitherto made its products in linear fashion, with relatively little recycling of the finished goods. This article examines the industry’s approach to the core sustainability concept and the circular economy in particular, through a re-view of the available academic literature, evidence from corporate sustainability reports and websites, and feedback from an online survey of industry professionals. The role of digital technology deployment in engendering sustainability and the circular economy in the industry is also explored. The study finds that whilst sustainability is now firmly embedded at the strategic level in the vast majority of companies studied, attitudes towards the circular economy remain fickle. The use of digital technologies in support of sustainability objectives is also limited at present, but the article concludes that the need to meet compliance requirements and new cus-tomer perceptions of sustainability will speed the transition to circular economy activities, facili-tated by greater exploitation of digital technologies. Building upon the research findings, existing models and an initial conceptual framework, a simple operational model for initiating such a transition for small-to-medium sized enterprises in the T&C industry is put forward.

Social media has become the most influential battleground for political and societal debate. The reach, the speed, and the fact that everybody can participate make this medium very popular but also highly manipulative, subject to biases and extremely precious to control. Misinformation spreads in an unforeseeable way. Sometimes it just follows usual non-malicious social interaction patterns, but often a targeted and designed-for-purpose manner. In this paper, we propose a novel method to identify the most effective opportunities to moderate the social media debate at a large scale using the properties of social signed graphs, such as structural balance. After building the topic universe for a particular political debate in a given time frame, we extract the most active and influential users and mine their position regarding the topic based on their interactions with other users. The result is a signed graph where each edge represents either support or challenge between a pair of users in the context of the topic. This graph can be modelled as an Ising model, with the goal of minimizing its energy state by using the advantages of Adiabatic Quantum Computing. Applying this principle, we use a Quantum Annealing implementation to solve the problem of finding the edges violating the structural balance of this graph, which in classic computing is known to be an NP-hard problem. We then provide a non-intrusive moderation technique for those violations to mitigate or increase the structural imbalance, depending on the desired strategy. The methodology is shown in the context of the COVID-19 skeptics’ debate in Twitter and implemented using a D-Wave 2000Q-6 quantum annealer.

Background: A large percentage of deaths in an epidemic or pandemic can be due to overshoot of population (herd) immunity, either from the initial peak or from planned or unplanned exit from lockdown or social distancing conditions. Objectives: We study partial unlock or reopening interaction with seasonal effects in a managed epidemic to quantify overshoot effects on small and large unlock steps and discover robust strategies for reducing overshoot. Methods: We simulate partial unlock of social distancing for epidemics over a range of replication factor, immunity duration and seasonality factor for strategies targeting immunity thresholds using overshoot optimization. Results: Seasonality change must be taken into account as one of the steps in an easing sequence, and a two step unlock, including seasonal effects, minimizes overshoot and deaths. It may cause undershoot, which causes rebounds and assists survival of the pathogen. Conclusions: Partial easing levels, even low levels for economic relief while waiting on a vaccine, have population immunity thresholds based on the reduced replication rates and may experience overshoot as well. We further find a two step strategy remains highly sensitive to variations in case ratio, replication factor, seasonality and timing. We demonstrate a three or more step strategy is more robust, and conclude that the best possible approach minimizes deaths under a range of likely actual conditions which include public response.

Less aligned emphasis has been given to the COVID-19 infodemic coordinating with the COVID-19 outbreak. Global profusion of tangled monikers and hashtags has found their ways in daily communication and contributed to backlash against Chinese. Official naming efforts against infodemic should be meet with a fair share of identification. Based on brief critical reviews on previous multifarious naming practices, we punctuate heuristic introspection in scientific conventions and sociocultural paradigms. Infodemiological analysis promises to articulate that people around the globe are divided in their favor stigmatized monikers in the public and scientific communities because of perceptual bias. There is no positive correlation between the degree of infection in their territories and collective perceptual bias to COVID-19. The official portfolio “COVID-19” and “SARS-CoV-2” has not become de facto standard usages, but full-fledged official names are excepted to duly contribute to the resilience of negative perceptual bias and collective behavioral propensities.

Social recommendation is almost as the integration of the business platform and social platform, and gradually become a top in recommendation system. Social recommendation algorithm solves the problem of cold start and data sparseness for traditional commodity, while the internal structure of the relationship graph in social relations has not been fully excavated. This paper proposes two models of Micro Relation Transfer Model and Macro Relation Transfer Model of social relations, and applies the social relations transfer models into the social recommendation system. A relationship graph is built from the relationship between customers on the Internet. Micro Relation Transfer Model establishes the transfer activation function by calculating the relationship between the two customers using the similarity of interests set. Micro Relation Transfer Model spreads the relationship of friends by calculating the proportion of common neighbors held by the customer's social relations. In order to effectively control the transmission range and effect of social relations graph, we introduce pruning algorithm based on Monte Carlo Decision Tree convergence algorithm. The experimental results show that SRRTC algorithm enhances the success rate and stability significantly.

This work is part of an ongoing research project to develop an unmanned flying social robot to monitor dependants at home in order to detect the person’s state and bring the necessary assistance. In this sense, this paper focuses on the description of a virtual reality (VR) simulation platform for the monitoring process of an avatar in a virtual home by a rotatory-wing autonomous unmanned aerial vehicle (UAV). This platform is based on a distributed architecture composed of three modules communicated through the Message Queue Telemetry Transport (MQTT) protocol: the UAV Simulator implemented in MATLAB/Simulink, the VR Visualiser developed in Unity, and the new emotion recognition (ER) System developed in Python. Using a face detection algorithm and a convolutional neural network (CNN), the ER System is able to detect the person’s face in the image captured by the UAV’s on-board camera and classify the emotion among seven possible ones (surprise, fear, happiness, sadness, disgust, anger or neutral expression). The experimental results demonstrate the correct integration of this new computer vision module within the VR platform, as well as the good performance of the designed CNN, with around 85% in the F1-score, a mean of the precision and recall of the model. The developed emotion detection system can be used in the future implementation of the assistance UAV that monitors dependent people in a real environment, since the methodology used is valid for images of real people.

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.

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.

We introduce the Transformation Flower Approach (TFA), a Theory of Change that attends to multiple value creation and institutional change as a dual design challenge. We highlight how the TFA integrates social scientific theories and models relevant for transformative change (in particular focusing on pathways, leverage points, governance, power, and values) and demonstrate its practical value by an application to the ongoing transformation of the Dutch food system. By providing a holistic, transdisciplinary and practically relevant approach that aims to support new social contract formation, the TFA goes beyond other transformative change approaches. Based on the notion of pathways, it offers a toolbox that aids in working towards desired futures, involving both incumbents and challengers in an effort to harness untapped yet proximal potentials in a forward-looking way. By embracing an innovation approach, it not only promises to circumvent resistance to change, but also serves as a step-by-step approach to identify options for multiple value creation and effective cooperation. We demonstrate the analytical and practical value of the TFA by discussing action perspectives at various levels and scales in the context of the Dutch food system transition, including (1) area-oriented approaches, (2) acceleration agendas for specific transformation pathways, and (3) actor-specific transformation flowers. In developing these, we emphasize the importance of interdependencies between leverage points. Our approach helps to identify opportunities to link transformative options (the what), actors (the who) and levers (the how) in dynamic interaction to embark on transformative pathways.

The American Civil War has been commemorated with a great variety of monuments, memorials, and markers. These monuments were erected for a variety of reasons, beginning with memorialization of the fallen and later to honor aging veterans, commemoration of significant anniversaries associated with the conflict, memorialization sites of conflict, and celebration of the actions of military leaders. Sources reveal that during both the Jim Crow and Civil Rights eras, many were erected as part of an organized propaganda campaign to terrorize African American communities and distort the past by promoting a ‘Lost Cause’ narrative. Through subsequent decades, to this day, complex and emotional narratives have surrounded interpretive legacies of the Civil War. Instruments of commemoration, through both physical and digital intervention approaches, can be provocative and instructive, as the country deals with a slavery legacy and the commemorated objects and spaces surrounding Confederate inheritances. Today, all of these potential factors and outcomes, with internationally relevance, are surrounded by swirls of social and political contention and controversy, including the remembering/forgetting dichotomies of cultural heritage. The modern dilemma turns on the question: In today’s new era of social justice, are these monuments primarily symbols of oppression, or can we see them, in select cases, alternatively as sites of conscience and reflection encompassing more inclusive conversations about commemoration? What we save or destroy and assign as the ultimate public value of these monuments rests with how we answer this question. In this essay, drawing from the testimony of scholars and artists, I address the conceptual landscape of approaches to the presentation and evolving participatory narratives of Confederate monuments that range from absolute expungement and removal to more restrained ideas such as in situ re-contextualization, removal to museums, and preservation-in-place.

Abstract: Background: chronotype is generally defined as the variability of the phase angle of en-trainment, while the latter reflects the relationship between the timing of a certain rhythm (e.g., sleep-wake cycle) and the timing of an external temporal cue. Individuals can be placed on a spectrum from "morning types" (M types), to "evening types" (E types). E-chronotype has been proposed as a transdiagnostic risk factor for psychiatric conditions and associated with psycho-pathological dimensions. Eveningness seems correlated with both suicidal ideation (SI) and suicidal behavioral (SB), through several possible mediating factors. Immunological alterations also have been linked to later chronotypes and SI/SB. Objective: This narrative review aims to summarize the evidence supporting the possible association between chronotypes and suicide, with the eventual mediating role of neuroinflammation and several psychopathological dimensions. Material and methods: A search of literature (2003-2023) was conducted, using various databases: PUBMED, EMBASE, Scopus, UpToDate, PsycINFO, Cochrane Library. English-language articles were col-lected and screened for eligibility. Results: Despite the apparent absence of a direct correlation between E-chronotype and suicidality, E-chronotype promotes a chain of effects that could be in-volved in an increased risk of SB, in which with neuroinflammation possibly play an intriguing role and some psychopathological dimensions may stand out.

Highly-skilled migrants and refugees finding employment in low-skill vocations, despite professional qualifications and educational background, has become a global tendency, mainly due to the language barrier. Employment prospects for displaced communities are mostly decided by their knowledge of the sublanguage of the vocational domain they are interested in working. Common vocational domains include agriculture, cooking, crafting, construction, and hospitality. The increasing amount of user-generated content in wikis and social networks provides a valuable source of data for data mining, Natural Language Processing and machine learning applications. This paper extends the contribution of the authors’ previous research on automatic vocational domain identification by further analyzing the results of the machine learning experiments with the domain-specific textual data set, considering 2 research directions: a. predictions analysis and b. data balancing. Wrong predictions analysis and the features that contributed to misclassification, along with correct predictions analysis and the features that were the most dominant, contributed to the identification of a primary set of terms for the vocational domains. Data balancing techniques were applied on the data set to observe their impact on the performance of the classification model. A novel 4-step methodology is proposed in this paper for the first time, consisting of successive applications of SMOTE oversampling on imbalanced data. Data oversampling obtains better results than data undersampling in imbalanced data sets, while hybrid approaches perform reasonably well.

The BRFSS is an annual survey conducted by each state and designed to identify trends in a representative sample of the resident population. In its 2019 field survey, the U.S. state of Georgia tested a new 3 – item module to measure the numbers of bereaved, resident adults. Bereavement means that participants answered, ‘Yes’ to the item ‘Have you experi-enced the death of a family member or close friend in the years 2018 or 2019?’. This analysis addresses two questions. Can estimates for bereavement prevalence be derived without large sampling errors, low precision, and small subsamples? Can multiple imputation techniques be applied to overcome non-response and missing data to support multivari-ate modeling? Analyses in this study were conducted under two scenarios. Scenario 1 ap-plies the complex sample weights created by the Centers for Disease Control and imputes values for missing responses. Scenario 2 treats the data as a panel – no weighting com-bined with removal of persons with missing data. Scenario 1 reflects the use of BRFSS data for public health and policy, while Scenario 2 reflects data as it is commonly used in so-cial science research. The bereavement item has a response rate (RR) of 70.8% (5206 of 7534 persons). Subgroups have RR of 55% or more. Under Scenario 1, the prevalence of bereavement is 45.38%, meaning that 3,739,120 adults reported bereaved in 2018 or 2019. The prevalence is 46.02% with Scenario 2 which removes persons with any missing data (4,289 persons). Scenario 2 overestimates the bereavement prevalence by 1.39%. An il-lustrative logistic model is included to show the performance of exposure to bereavement under each scenario. Recent bereavement can be ascertained in a surveillance survey without biases in response. This survey is limited to one US state in a single year and ex-cludes persons aged 17 years and younger.

Urban forests are critical infrastructure for mitigating environmental and social challenges cities face. Municipalities and non-governmental entities, among others, often set goals (e.g., tree planting or canopy targets) to support urban forests and their benefits. We focus on canopy goals and develop conceptual underpinnings for an analysis of where additional canopy, as one important dimension of the urban forest, can fit within the landscape, while considering factors that influence where trees can be planted and where canopy can grow – ‘practical canopy.’ We apply this in New York City (NYC) to inform the setting of a canopy goal by the NYC Urban Forest Task Force (UFTF) for the NYC Urban Forest Agenda, which may trigger a virtuous cycle that supports the urban forest there. We further develop framing for a ‘priority canopy’ analysis to understand where urban forest expansion should be prioritized given more context (e.g., environmental hazards, local preferences), which can inform how expansion of the urban forest is achieved. We estimate an opportunity for 15,899 ha of new canopy in NYC given existing opportunities and constraints (practical canopy), which, if leveraged, could result in nearly doubling the canopy as of 2017 (17,253 ha). However, like existing canopy, practical canopy is not evenly distributed, in general, or across jurisdictions and land uses. Relying solely on areas identified as practical canopy to expand the urban forest would exacerbate inequities in its distribution. We discuss how the NYC UFTF established an aspirational but achievable goal of 30% canopy cover by 2035, which was informed by this analysis and guided by priorities of equity, health, and resilience. Achievement of this goal will ultimately require a combination of protecting and stewarding the existing resource, and leveraging opportunities for tree planting. Achieving a more equitable urban forest will also require identification of priority canopy, and, in cases, creation of new opportunities for tree planting and canopy expansion. Overall, the collaborative establishment of such goals based on local context can be instrumental in creating a virtuous cycle, moving conservation actors toward exercising influence and agency within the social ecological system.

This study observes, interprets, and analyses the knowledge production in the research field of Human–Robot Interaction (HRI). It intends to foreground the hidden assumptions that are often taken for granted when roboticist design and conduct their research. By doing so, this study demonstrates how these assumptions influence the result of their research. Based on data collected through sociological field observation, this study argues that the current practise in HRI research is highly anthropocentric. In short, the robots are designed to be like human instead of for human. Therefore, the human–robot relationship embodies the existing power relations between human beings. These relations generate inequality, hierarchy, and dominance, which are the opposite of the common imagination of the robotised future among roboticists. For the purpose of enabling the robotised future closer to their ideal, this study suggests that HRI researchers to go beyond the conventional methodology, to allow a human–robot relationship that realises reciprocity.

Supplier selection (SC) product life cycle cost (SCPLCC) is an important consideration among corporations, SCPLCC problem has become associated with deciding how one supplier should be selected from possible alternatives. In this study, we applied two types of goal programming, multiobjective linear programming and revised multichoice goal programming to develop a PLCC-based concept to solve the SCPLCC problem and construct a decision-making tool for application to a case of supply chain management in a Taiwanese light-emitting diode company in the high-tech industry. Our study main contribution Company managers can easily use the two approaches of the SCPLCC model with different parameters to solve SCPLCC model problems. Finally, we comparing five models found RMCGP with weighted linear goal programming had an adequate effect for application to the PLCC concept for high-technology company; this cloud makes company decision–makers focus on low PLCC and select a better supplier in sustainable supply chains goal.

(1) Aims: To analyse the relationship between demographic and clinical characteristics and particular kinds of suicidal behaviour and its relationship with a nurse-led suicide prevention program. (2) Methods: A 5-year cross-sectional study design. Study performed in the region of Osona (Catalonia) during 2013-2017. Suicidal behaviour was classified as suicidal ideation, interrupted self-directed violence, suicide attempt and completed suicide. (3) Results: The sample included 753 patients ─ of whom 53 died by suicide─ and encompassed 931 suicidal behaviour episodes. Men represented 38.4% of the sample but 81.1% of deaths by suicide. Mental disorders were associated with suicidal behaviour in 75.4% of the sample. 66.4% of the individuals were engaged in the nurse-led Suicidal Behaviour Case Management Program, of which 0.8% (n=4) died by suicide. (4) Conclusion: The main risk factors were female sex for suicidal behaviour, and male sex and older age for suicide. Mental disorders, widowhood and retirement were also associated with suicide. A high proportion of patients was engaged to the nurse-led suicide prevention program with a low proportion of suicides.

Multiple social and environmental justice concerns are linked to urban form such as the distribution of socioeconomic class populations, healthcare spending, air pollution exposure, and human mobility. This study used 1m resolved LIDAR data to characterize land use in Salt Lake County, Utah and associate it with sociodemographic and air quality data at the census block group and zip code levels. We found that increasing tree cover was associated with higher per capita income and lower minority populations while increasing built cover was linked to lower per capita income and higher minority populations. Air quality showed less strong correlations, however, decreased non irrigated cover, increased built cover, and higher amounts of households living under poverty was related to higher long-term PM2.5 exposure. Several policy efforts have been undertaken to improve air quality and reduce negative health outcomes in Utah which are being informed by regulatory and research grade air quality sensors.

This paper introduces a theory for the evolution of corporates in which the growth and sustainability strategies are developed simultaneously. Since the introduction of corporate sustainability, it has been an extra cost for risk mitigation and making ‘compensating’ positive impact. The world has reached a tipping point of volatility, mainly due to climate change but also by emergence of COVID-19, so that the applicability of existing corporate structures is under question and these poses high risk to the existence of our planet. On the other hand, the technology cost for sustainable investment has reached a parity in comparison with non-sustainable alternatives. Therefore, our proposed Organic Grow Theory introduces a step-by-step approach so that corporates can grow and be profitable without compromising the ability of future generations to meet their needs. It is concluded that, a new structure for corporate, called Founcorp, would be needed to direct corporates to evolve being a responsible legal entity.

This study addresses the latent construct of attitudes towards environmental conservation based on study participant’s responses. We measured and evaluated the latent scale based on an 18-item scale instrument, over four experimental strata (N=945) in the US Virgin Islands and the Caribbean. We estimated the latent scale reliability and validity. We further fitted multiple alternative two-parameter logistic (2PL) and graded response models (GRM) from Item-Response Theory. We finally constructed and fitted equivalent structural and generalized structural equation models (SEM/GSEM) for the attitudinal latent scale. All scale measures (composite, alpha-based, IRT-based and SEM-based) were consistently and reliably valid measures of the study participants’ latent attitudes toward conservation. We found statistically significant differences among participant’s attributes relating to socio-demographic, physical and core environmental characteristics of participants. We assert that the nature of relationship between cognitive attitudes and individual as well as social behavior related to environmental conservation.

Maintaining a healthy cyber society is a big challenge due to the users’ freedom of expression and behaving. It can be solved by monitoring and analyzing the users’ behavior and taking proper actions towards them. This research aims to present a platform that monitors the public content on Twitter by extracting tweet data. After maintaining the data, the users’ interactions are analyzed using Graph Analysis methods. Then the users’ behavioral patterns are analyzed by applying Metadata Analysis, in which the timeline of each profile is obtained; also, the time-series behavioral features of users are investigated. Then in the Abnormal Behavior Detection Filtering component, the interesting profiles are selected for further examinations. Finally, in the Contextual Analysis component, the contents will be analyzed using natural language processing techniques; A binary text classification model (SVM + TF-IDF with 88.89% accuracy) for detecting if the tweet is related to crime or not. Then, a sentiment analysis method is applied to the crime-related tweets to perform aspect-based sentiment analysis (DistilBERT + FFNN with 80% accuracy); because sharing positive opinions about a crime-related topic can threaten society. This platform aims to provide the end-user (Police) suggestions to control hate speech or terrorist propaganda.

Recent brain imaging findings by using different methods (e.g., fMRI and PET) have suggested that social anxiety disorder (SAD) is correlated with alterations in regional or network-level brain function. However, due to many limitations associated with these methods, such as poor temporal resolution and limited number of samples per second, neuroscientists could not quantify the fast dynamic connectivity of causal information networks in SAD. In this study, SAD-related changes in brain connections within the default mode network (DMN) were investigated using eight electroencephalographic (EEG) regions of interest. Partial directed coherence (PDC) was used to assess the causal influences of DMN regions on each other and indicate the changes in the DMN effective network related to SAD severity. The DMN is a large-scale brain network basically composed of the mesial prefrontal cortex (mPFC), posterior cingulate cortex (PCC)/precuneus, and lateral parietal cortex (LPC). The EEG data were collected from 88 subjects (22 control, 22 mild, 22 moderate, 22 severe) and used to estimate the effective connectivity between DMN regions at different frequency bands: delta (1–3 Hz), theta (4–8 Hz), alpha (8–12 Hz), low beta (13–21 Hz), and high beta (22–30 Hz). Among the healthy control (HC) and the three considered levels of severity of SAD, the results indicated a higher level of causal interactions for the mild and moderate SAD groups than for the severe and HC groups. Between the control and the severe SAD groups, the results indicated a higher level of causal connections for the control throughout all the DMN regions. We found significant increases in the mean PDC in the delta (p = 0.009) and alpha (p = 0.001) bands between the SAD groups. Among the DMN regions, the precuneus exhibited a higher level of causal influence than other regions. Therefore, it was suggested to be a major source hub that contributes to the mental exploration and emotional content of SAD. In contrast to the severe group, HC exhibited higher resting-state connectivity at the mPFC, providing evidence for mPFC dysfunction in the severe SAD group. Furthermore, the total Social Interaction Anxiety Scale (SIAS) was positively correlated with the mean values of the PDC of the severe SAD group, r (22) = 0.576, p = 0.006 and negatively correlated with those of the HC group, r (22) = −0.689, p = 0.001. The reported results may facilitate greater comprehension of the underlying potential SAD neural biomarkers and can be used to characterize possible targets for further medication.

Metabolic Syndrome (MetS) is a serious condition that significantly increases the risk of cardiovascular diseases and the severity of type 2 diabetes, also impacting on the development and evolution of other chronic diseases. Predicting metabolic syndrome is a complex task due to the multifactorial nature of this condition, which involves a combination of various risk factors such as abdominal obesity, insulin resistance, dyslipidemia, and hypertension. The complex interplay of these factors makes it challenging to predict the syndrome. Both genetic predisposition and environmental factors also contribute to the development of metabolic syndrome. Metabolic syndrome affects diverse populations with different ethnicities, lifestyles, and socioeconomic backgrounds. Prediction models, in addition, need to account for population heterogeneity and consider variations in risk factors across different groups. The present study analyzed data from participants in a cohort from Mexico City to identify key risk factors in men and women, addressing the presence of unbalanced data. In order to tackle the issues posed by data imbalance data, SMOTE and ADASYN were applied to assess significant differences in the selection of risk factors for MetS prediction. Random Forest and RPART models using ADASYN and SMOTE demonstrated better performance, achieving a balanced accuracy of approximately 87%. In women, they highlighted sleep quality, anxiety factors, tobacco consumption, and nutritional components. In the case of men, stronger associations were identified with the social development index and factors related to gout in parents.

In the era of digital information consumption, YouTube has emerged as a prominent platform for disseminating knowledge across various domains. One such area that has gathered significant attention is teeth whitening, with a plethora of videos offering insights into professional proce-dures, home remedies, and personal experiences. This study delves into the vast landscape of teeth whitening content on YouTube, meticulously categorizing videos into professional and amateur domains. The aim is to critically analyze the information presented, considering its accuracy, re-liability, and potential impact on public perceptions and oral health choices. A total of 100 videos in Greek (n1= 73) and in English (n2= 27) were studied. The analysis was based on views, likes, publication year, duration, presence of background music, and the presence of a description. The completion date of the search was October 7, 2023. Professional videos predominantly present whitening as a painless, conservative, and economical procedure, emphasizing safety measures. Bleaching mechanisms involving hydrogen peroxide and carbamide are explored, with various application techniques discussed, including whitening strips, splints, and in-office procedures. Contradictory findings on the efficacy of home versus in-office treatments are highlighted. In-ternal and external discoloration factors are delineated, with contraindications specified. Amateur videos, garnering greater public appeal, present personal experiences, product promotions, and homemade remedies, reflecting a concerning trend of misinformation. The analysis incorporates viewer engagement metrics, emphasizing the impact of non-professional content. As social media platforms play an increasingly influential role in shaping healthcare narratives, understanding the nuances of dental discourse on YouTube becomes crucial for both practitioners and the public. This exploration encompasses a spectrum of topics, ranging from the chemical intricacies of bleaching agents to the societal dynamics influencing viewer preferences. By unraveling the complexities of online dental information, this study seeks to contribute valuable insights to the evolving land-scape of oral health education in the digital age. Future research should adopt a multi-platform approach and explore the dynamic interaction between content creators and viewers for a more holistic comprehension of online dental information.

The craft guilds have been at the core of important historiographical debates on the economic, social and political history of medieval cities for twenty years. The aim of this article is to examine the seamen’s guilds in the town ports of Northern Peninsula in the late Middle Ages. This study analyzes fundamental aspects of the social assistance, labour organization and social identity of the town ports, located on the maritime border of the Kingdom of Castile. In contrast to the more classical view of the craft guilds as protectionist institutions, which only served the interests of a privileged group of masters, this analysis highlights the contribution of the seamen craft guilds to the organization of labor at sea, the training of sea workers, the ability to negotiate with merchants and avoid labor exploitation, the provision of social assistance to the most vulnerable population, and the ability to lead the social protest for the guilders’ representation in the urban government. In summary, it is concluded that the seafarers’ guilds were constituted as networks of mutual help between individuals in the labor, welfare and political spheres of the population of the town ports of Northern Iberia in the late Middle Ages.

It is important that both static and dynamic information is efficiently used to create a suitable tourism plan. However, collecting, accumulating and managing dynamic information can cost tourists time, money and energy. The present study developed an original tourism support system was designed and developed with the purpose of reducing the burden of tourists who are unfamiliar with the tourist destinations in particular. An original tourism planning support system and web-geographic information systems (Web-GIS) were integrated into a single system, and two original functions were implemented. The system was operated targeting Osaka City, Japan for a period of one month. The information concerning 529 sightseeing spots was collected from tourism-related web media and then saved to the database of the system beforehand. During the operation period, a cumulative total of 160 users accessed the system. Based on the questionnaire survey results, most of the main functions were highly rated regardless of users’ travel experiences to the operation target area. Additionally, based on the access log analysis results, it was clear that the use of the system was in line with the purpose of the present study, as the number of visits to the page for the main functions were high.

The closure of Black churches raises concerns about the socioeconomic impact on African American communities. This pilot study uses Social Capital theory to highlight the relationship between the Black church and socioeconomic outcomes within the community. Based on survey responses from approximately 60% of African American participants, it was revealed that religious communities have a positive impact on their socioeconomic status. These findings have reinforced the strong connection between faith and success, noting that active involvement in religious services or activities could lead to higher annual incomes. Individuals who earned a higher income also reported more frequent participation in weekly religious services and activities. Furthermore, a chi-square test of independence showed a significant relationship between the frequency of religious participation and the likelihood of receiving a scholarship or grant funding from religious organizations. Therefore, the study provides evidence highlighting the church's critical role in fostering positive economic outcomes and social networks within African American communities. These findings provide a framework for additional research in this field to explore further the impact of religious communities on various aspects of African American life.

Previous studies have shown, in the United States (U.S.), that non-White communities are exposed to significantly higher temperatures in urban environments than complementary White populations. Studies highlighting this disparity have usually been cross-sectional and are therefore “snapshots” in time. Using surface urban heat island (SUHI) intensity data, U.S. Census 2020 population counts, and a measure of residential segregation, this study performs a comparative analysis between census tracts identified as prevalent for White, Black, Hispanic and Asian populations and their thermal exposure from 2003 – 2018. The analysis concentrates on the top 200 most populous U.S. cities. SUHI intensity is shown to be increasing through time for all examined tracts. However, the increase is only statistically significant for White and Black prevalent zones. There is a 1.25K to ~2.00K higher degree of thermal exposure on average for non-White relative to White prevalent areas. When examined on an inter-city basis, White and Black prevalent tracts had the largest disparity, as measured by SUHI intensity, in New Orleans, LA, USA by < 6.00K. Hispanic (>7.00K) and Asian (<6.75K) prevalent tracts were greatest in intensity in San Jose, CA, USA. To further explore temporal patterns, two models were developed using a Bayesian hierarchical spatial temporal framework. One models the effect of varying the percentages of each population group relative to SUHI intensity within all examined tracts. Increases in percentages of Black, Hispanic, and Asian populations contributed to statistically significant increases in SUHI intensity. White increases in population percentage lowered SUHI temperature intensity. Throughout all modeled tracts, there is a statistically significant 0.01K per year average increase in SUHI intensity. A second model tests the effect of residential segregation on thermal inequity across all examined cities. Residential segregation, indeed, has a statistically significant positive association with SUHI intensity from this portion of the analysis. Similarly, there is a statistically significant 0.01K increase in average SUHI intensity per year for all cities. Results from this study can be used to guide and prioritize intervention strategies and furthers urgency related to social, climatic, and environmental justice concerns.

Sustainable and Responsible Design (SRD) harnesses design’s potential to address eco-social problems and in doing so challenge the status quo of design education by reframing the social and ecological consequences, boundaries and agencies of design. This critical and transdisciplinary approach frays the edges of traditional design disciplines with embedded and reflexive modes of learning. We describe characteristics of SRD education and present theories of learning to empower students in this complex terrain. The learning associated with SRD education is ecologically engaged, participative, critical, expansive and designerly. We recount case studies of our own experiences advancing sustainable and responsible undergraduate design education in the UK. We identify path constraints such as disciplinary fragility, appropriation, and power dynamics in the design school. The push for a revision of priorities generates tensions where there is often greenwashing rhetoric of sustainability and inclusivity. We describe strategies and tactics to address these tensions. We highlight the agency we have as educators and designers and argue that design education can only meaningfully participate in response to the challenges presented by climate change, other types of ecocide, and social problems when educators make substantive commitments to supporting sustainability literacies and design approaches that serve the interests of diverse stakeholders.

Research has consistently found that people with mental illness (known as consumers) experience lower levels of participation in meaningful activities, which can limit their opportunities for recovery support. The aim of this study was to describe the outcomes of participation in a group program designed to address all stages of activity participation, known as Pathways to Participation (P2P). A descriptive longitudinal design was utilized, collecting data at three time points. Outcomes were measured by the Camberwell Assessment of Need Short Appraisal (CANSAS), Recovery Assessment Scale – Domains and Stages (RAS-DS), Behaviour and Symptom Identification Scale (BASIS-24), Living in the Community Questionnaire (LCQ) and time use diaries. All data was analysed using descriptive statistics, and Chi square analyses. Seventeen consumers completed baseline data, eleven contributed post program data and eight provided follow up data. Most were female (63.64%) and had been living with mental illness for 11.50 (± 7.74) years on average. Reductions in unmet needs and improvements in self-rated recovery scores were re-ported, but no changes were identified in either time use or psychosocial health. The findings indicate the P2P program may enable consumers to achieve positive activity and participation out-comes as part of their personal recovery.

Cultural ecosystem services has been increasingly influential in both environmental research and policy decision-making, such as for urban green spaces However, its popular definition conflates the concepts of ‘services’ and ‘benefits’ which made it challenging for planners to employ it directly for urban green space management. One the most widely used definition of this non-tangible ecosystem services are “functions of environmental spaces and cultural activities which may then result in the enjoyment of cultural ecosystem benefits”; yet the latter itself have never found its way into official laws and regulations. In this study, via a case study in Singapore, we propose new evidence to re-evaluate and re-position the two of the most important emerging concepts in managing the green spaces in urban areas. Using the transdisciplinary mixed methods of public participation GIS and social media text mining analysis, a wealth of cultural ecosystem services and their associated benefits were reported. This was especially so with regards to recreational and aesthetic services and experiential benefits. Recommendations to improve the park were also suggested, alongside sharing of methodological considerations for future research. Overall, this paper recommends the employment of the redefined cultural ecosystem services conceptual framework to generate relational, data-driven and actionable insights to better support urban green space management, which is not only useful to Singapore governments but also world-wide relevant.

Abstract: Ultrasonic vocalizations (USVs) are one of the evolutionarily oldest forms of animal communication. In order to study the communication architecture in an aversive social situation, we used a behavioral model in which one animal, the observer, is witnessing as his cagemate, the demonstrator, is experiencing a series of mild electrical foot-shocks (aversive stimuli). We studied the effect of foot-shocks experience in the observer and the influence of a warning sound (emit-ted shortly before the shock is applied) on USVs communication. These experiments revealed that such a warning seems to increase the arousal level, which differentiates the responses depending on previous experience. It can be identified by the emission of characteristic, short 22-kHz calls, of a duration below 100 ms. Furthermore, by analyzing temporally overlapping USVs, we found that in ‘Warned’ pairs with a naive observer, 22-kHz were mixed with 50-kHz calls. This fact, combined with a high fraction of very high-pitched 50-kHz calls (over 75-kHz), suggests the presence of the phenomenon of social buffering. On the other hand, in ‘Warned’ pairs with an experienced observer, pure 22-kHz overlaps were mostly found, signifying possible fear contagion with dis-tress sharing. Hence the importance of differentiating 22-kHz calls to long and short.

Decisions affecting the COVID-19 pandemic, by the individual and those with highest authority, are being made on the basis of unreliable data. Data about cases and deaths are collected daily but represent only a sample of reality. Statistics convert sample data into more reliable estimates. However, statistics have no magical powers; reliability requires dependable data. It is futile to rail against this darkness; COVID-19 is not a scientific experiment. However, we must do better both with data collection and data analysis. In this review, I focus on one element of the data, the asymptomatic case of COVID-19. Without reliable information about this number, decision makers are significantly blinded. By its nature, the asymptomatic case is hidden but contaminating to understanding COVID-19. The true case rate and death rate per case are unknowable without knowing the fraction of cases that are asymptomatic. The best estimate of asymptomatic cases is in the CDC document: COVID-19 Pandemic Planning Scenarios. For four different scenarios the estimates range from 10% to 70%, with the best estimate of 40% for asymptomatic cases. However, even the definition of the asymptomatic case is problematic. In simplest terms, two elements are required: an infection and no symptoms. How is “no symptoms” to be usefully defined? It appears to be analogous to pontificating about black swans from studying only white swans. It implies infection, but how is infection defined? Is it presence of the virus, replication of the virus, or presence of antibodies? Is asymptomatic disease an oxymoron? Without extensive, purposeful screening for specifically defined, essential symptoms and appropriate virus and antibody testing over time, the class of asymptomatic cases remains unknown. Current estimates range from <20% to ˃80%. If low, it can be ignored; if high, it dramatically and proportionately lowers the case rate and the death rate per case. Consequentially, the asymptomatic rate dramatically affects our societal and political responses. In this focused review, we assess the limitations of the published estimates, bring attention to the importance of obtaining accurate data, and exhort that high priority be given in the scientific community to understanding the issue, asymptomatic COVID-19 cases.

This article discusses how, in today’s world of disruptive and dramatic social change (DSC), non-sports related coaching, which includes a wide range of services such as life coaching, career coaching, executive coaching, and team coaching, can inadvertently fuel undesirable social dynamics. There is little or no awareness of this risk among coaches and coachees. The global, fast-growing, multi-billion-dollar industry aimed at supporting people and organisations to perform better and increase wellbeing while managing and adapting to change has been developed with limited sociological input. The article is based on 15 years of social constructionist-informed reflective practice by a sociologist-turned-coach, and uses a multi-layered autoethnographic account to argue for a sociologically informed paradigm shift in coaching, as well as relevant sociological knowledge and social and human sciences research methodology in coaches’ education. It presents the rationale and key features of a new coaching approach that places DSC-relevant sociological concepts at the heart of the coaching process, helps people develop psycho-sociological awareness, and uses a learning-to-develop through research design. A new definition of coaching to address DSC is derived. Coaching practitioners will find DSC-relevant sociological concepts, critical reflections, coaching questions, and procedures to expand coaching effectiveness. Interdisciplinary research topics combining coaching sociology and coaching psychology are suggested.

As a pioneering transdisciplinary field, innovationology transcends the traditional boundaries of academic disciplines and development practices to address persistent global challenges. This article provides a comprehensive exploration of innovationology, delving deep into its philosophical foundations, ontological commitments, and ethical imperatives. By unpacking the core tenets of this innovative approach, the paper positions it as a robust and holistic science capable of catalyzing transformative innovation and sustainable development worldwide. Innovationology represents a paradigm shift that moves beyond conventional innovation and development theories, embracing a systems-oriented, community-centric, and decolonial praxis. Drawing on a synthesis of theoretical perspectives and empirical insights, the article examines innovationology's ontological commitment to marginalized communities as active agents of change, its epistemological grounding in pluralistic knowledge systems, and its ethical imperatives of social justice, environmental sustainability, and inclusive innovation. This in-depth analysis strengthens the conceptual and theoretical foundations of innovationology, providing critical guidance for its practical implementation and continued refinement as a cutting-edge transdisciplinary science for global transformation.

As global economic integration and rapid technological advancements transform international business, international engineering contracting has become essential for achieving sustainable development goals (SDGs). This paper investigates the significant impact of China’s strategic initiatives, notably the "Going Global" strategy and the Belt and Road Initiative (BRI), on the operational practices of Chinese enterprises involved in overseas investments. Central to this transformation is the Engineering, Procurement, and Construction (EPC) model, which emphasizes the integration of supply chain management and stakeholder collaboration to enhance performance in international EPC projects and underscores the crucial role of these elements in promoting sustainability. Incorporating insights from social network data analysis, this study reveals that contractors collaborating with various stakeholders—such as owners/consulting engineers, domestic and foreign customs departments, and group headquarters/design parties—exhibit a high degree of similarity in personnel profiles. This suggests that the internal organizational structure and personnel allocation of contractors could be optimized to enhance operational efficiency, aligning with the collaborative patterns identified. This study addresses a critical research gap by exploring how effective supply chain management and collaborative stakeholder engagement within multinational EPC projects contribute to sustainable outcomes. Employing advanced social network analysis software, the research examines the complex interactions among stakeholders and their influence on procurement dynamics. Findings indicate that strong relational networks and strategic collaborations significantly enhance procurement efficiency and project success, underscoring the importance of supply chain integration. Ultimately, integrating supply chain management principles into the EPC model not only offers innovative perspectives for advancing sustainability in international projects but also provides actionable insights for improving project outcomes within the BRI framework. This research underscores the pivotal role of supply chain organization and stakeholder cooperation in achieving sustainability objectives, thereby enriching the discourse on sustainable enterprise operation and supply chain management in the context of global initiatives.

Background: Acceleration of mass vaccination strategies is the only pathway to overcome the COVID-19 pandemic. Healthcare professionals and students have a key role in shaping public opinion about vaccines. This study aimed to evaluate the attitudes of dental students globally towards COVID-19 vaccines and explore the potential drivers for students' acceptance levels; Methods: A global cross-sectional study was carried out in February 2021 using an online ques-tionnaire. The study was liaised by the scientific committee of the International Association of Dental Students (IADS), and data was collected through the national and local coordinators of IADS member organizations. The dependent variable was the willingness to take the COVID-19 vaccine, and the independent variables included demographic characteristics, COVID-19-related experi-ence, and the drivers of COVID-19 vaccine-related attitude suggested by the WHO-SAGE; Results: A total of 6639 students from 22 countries representing all world regions responded to the ques-tionnaire properly. Their mean age was 22.06 ± 2.79 (17-40) years, and the majority were females (70.5%), in clinical years (66.8%), and from upper-middle-income economies (45.7%). In general, 22.5% of dental students worldwide were hesitant, and 13.9% rejected COVID-19 vaccines. The students in low- and lower-middle-income (LLMI) economies had significantly higher levels of vaccine hesitancy compared to their peers in upper-middle- and high-income (UMHI) economies (30.4% vs 19.8%; p < 0.001); Conclusions: The global acceptance level of dental students for COVID-19 vaccines was suboptimal, and their worrisome level of vaccine hesitancy was influenced by the socioeconomic context where the dental students live and study. The media and social media, public figures, insufficient knowledge about vaccines, and mistrust of governments and the pharmaceutical industry were barriers to vaccination. The findings of this study call for further implementation of epidemiology (infectious diseases) education within undergraduate dental curricula.

Streptomyces, being one of the most promising genera due to its ability to synthesize a variety of bioactive secondary metabolites of pharmaceutical interest, here studied in relation to its genomic and metabolomic potential. Coinciding with the increase in sequenced data, mining of bacterial genomes for biosynthetic gene clusters (BGCs) has become a routine component of natural product discovery. Herein, we describe the isolation and characterization of a Streptomyces tendae VITAKN with quorum sensing inhibitory activity (QSI) that was isolated from southern coastal parts of India. The nearly complete genome consists of 8,621,231bp with a GC content of 72.2%. Utilizing the BiG-SCAPE-CORASON platform, a sequence similarity network predicted from this strain was evaluated through sequence similarity analysis with the MIBiG database and existing 3,365 BGCs predicted by antiSMASH analysis of publicly available complete Streptomyces genomes. Crude extract analyzed on LC-HRMS/MS and Global Natural Product Social Molecular Networking (GNPS) online workflow using dereplication resulted in the identification of cyclic dipeptides (2,5-diketopiperazines, DKPs) in the extract, which are known to possess QSI activity. Our results highlight the potential use of genomic mining coupled with LC-HRMS/MS and bionformatic tools (GNPS) as a potent approach for metabolome studies in discovering novel QSI lead compounds. This study also provides the biosynthetic diversity of these BGCs and an assessment of the predicted chemical space yet to be discovered.

The textile and clothing (T&amp;C) industry, despite its significant contribution to the European economy, is one of the most polluting industries globally. Therefore, the EU's Green Deal has identified the T&amp;C sector as a strategic area for allocating public funding and transitioning towards a circular economy (CE). In this context, the “Circular Design for Natural Fibers” project, financed by the PNRR MICS “Made in Italy Circolare e Sostenibile” programme, focuses on enhancing the use of natural fibrous material, related by-products and waste from local production chains. In the research, a crucial aspect is the evaluation of the effectiveness of circularity through life cycle approaches, such as LCA, LCC, S-LCA and LCSA, for environmental, economic and social sustainability evaluation, respectively. A systematic review was carried out, to provide a synthesis of the available scientific evidence regarding the life cycle approaches in the international/national context within the production, processing, and post-consumer supply chains of natural fibers. The study identifies gaps in the literature on life cycle evaluation approaches for natural fibers. Specifically, the LCA approach appears preponderant compared to the others. The paper offers insights for researchers and professionals interested in improving the sustainability of natural fiber production processes and the evaluation of their overall sustainability.

The rapid evolution of information and communication technologies, notably the Internet, has yielded substantial benefits while posing challenges to information system security. With an increasing frequency of cyber threats—from unauthorized access to data breaches—the digital landscape's vulnerability is evident. Addressing the financial impact of cybercrime, this study delves into the role of Artificial Intelligence (AI) and Machine Learning (ML) technologies in cybersecurity. Analyzing advancements and outcomes, the research explores practical techniques for anomaly detection, threat prediction, and automated response. By investigating prior research and real-world implementations, the study provides valuable insights into the potential of AI/ML, uncovering current trends, challenges, and prospects in enhancing cybersecurity tactics amid a dynamically changing threat landscape.

1960s Europe saw a large number of residential neighborhoods built to house those migrating from the countryside. Today, more than 50 years later, these neighborhoods suffer high levels of functional, social, and technical obsolescence. In response to this, University of Seville developed the Aura Strategy as an intervention methodology to find global solutions to issues in outdated neighborhoods. To provide visibility to this aspect of the Aura strategy, the retrofit proposal presented in this article provides a solution to improve the roofing of buildings in a case study neighborhood (Polígono de San Pablo, Seville) and an analysis of the results in terms of energy and financial savings for local residents. The results show that for a population of roughly 18,000 (in 2018), net savings, including energy and retrofitting costs, ranging from nearly 6.5 to over 8.6 million can be made over the 20-year life cycle span. Likewise, the results obtained on the reduction of thermal loads indicate a 72% decrease in energy consumption, equivalent to a saving of close to 4,500 tons of greenhouse gas emissions for the district and the entire life cycle time period, with the consequent benefits on the impact on air quality and and the fight against climate change. climate change.

This study explores several global and country cluster sustainable development (herein SD) models. It jointly examines constructs from the “Neoliberal-turn” ((e.g., Institutional Enhancers (e.g., business freedom, property rights, government integrity, and judicial effectiveness), Financial Enhancers (e.g., government spending and monetary, trade, investment, and financial freedoms), Foreign Direct Investment, Global Competitiveness-institutions, and Global Competitiveness-innovation-sophistication)), and the “Social-turn” (five SD pillars (e.g., Planet, People, Peace, Prosperity, and Resources), which synthesize the 17 United Nations SD goals); and Happiness and Life Satisfaction (herein H&amp;LS). The study examines a large and diverse set of relationships encompassing 11 years of data of 108 social, economic, and environmental indicators from 129 countries at the global, country cluster, and country levels. We analyze data using structural equation modeling. Remarkably, Planet, an SD pillar constituted by biophysical variables, is the least of the five SD pillars positively related to the "neoliberal-turn" constructs and H&amp;LS. Results show model configurations and scale effects. Furthermore, findings reveal both synergies between neoliberal and the five SD pillars as well as both negative and non-significant relationships among them. The diversity of results calls for further model integration and specificity. Diverse findings entail caution and difficulties in generalizing knowledge. Similarly, results suggest that it is not advisable, since there may be many different and partly legitimate alternatives, to rely on just one perspective (e.g., giving primacy to economic-based analyses) and or in analyses at only one scale. The perspective effects and the stakes involved in SD urgently call for more collaborative efforts at all levels.

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.

Artificial Intelligence (AI) play an important role in many fields, including medical education, practice, and research. Many medical educators started using ChatGPT at the end of 2022 for many purposes. The aim of this article was to explore the potential uses, benefits and risks of using ChatGPT in integrated pharmacotherapy of infectious disease module education. This study was an experimental study with content analysis of the potential applications of the ChatGPT model for integrated pharmacotherapy of infectious diseases module education was performed. The findings of this study shows that there are many potential uses, benefits and risks associated with the use ChatGPT. In conclusion, medical and health sciences educators can use ChatGPT as a guide in many aspects related to the integrated pharmacotherapy of infectious disease curriculum development, syllabus design, lecture notes preparation and exam preparation with caution.

Community-based case managers in health have been compared to glue which holds the dynamic needs of clients to a disjointed range of health and social services. However, case manager roles are difficult to understand due to poorly defined roles, confusing terminology, and low visibility in New Zealand. This review aims to map the landscape of case management work to advance workforce planning by clarifying the jobs, roles, and relationships of case managers in Aotearoa New Zealand (NZ). Our scoping and mapping review includes peer-reviewed articles, grey literature sources, and interview data from 15 case managers. Data was charted iteratively until convergent patterns emerged and distinctive roles identified. A rich and diverse body of literature describing and evaluating case management work in NZ (n=148) is uncovered with at least 38 different job titles recorded. 18 distinctive roles are further analysed with sufficient data to explore the research question. Social ecology maps highlight diverse interprofessional and intersectoral relationships. Significant innovation and adaptations are evident in this field, particularly in the last five years. Case managers also known as health navigators, play a pivotal but often undervalued role in NZ health care, through their interprofessional and intersectoral relationships. Their work is often unrecognised which impedes workforce development and the promotion of person-centred and integrated health care.

Perinatal mortality is a major issue in laboratory mouse breeding. We compared a counting method using daily checks (DAILY_CHECK) with a method combining daily checks with detailed video analyses to detect cannibalisms (VIDEO_TRACK) for estimating the number of C57BL/6 pups born, died and weaned in 193 litters from trios with (TRIO-OVERLAP) or without (TRIO-NO_OVERLAP) the presence of another litter. Linear mixed models were used at litter level. To understand if cannibalism was associated with active killing (infanticide), we analysed VIDEO_TRACK recordings of 109 litters from TRIO-OVERLAP, TRIO-NO_OVERLAP or SOLO (single dams). We used Kaplan-Meier method and logistic regression at pup level. For DAILY_CHECK, the mean litter size was 35% smaller than for VIDEO_TRACK (P&lt;0.0001) and the number of dead pups was twice lower (P&lt;0.0001). The risk of pup loss was higher for TRIO-OVERLAP than TRIO-NO_OVERLAP (P&lt;0.0001). A high number of pup losses occurred between birth and the first cage checking. Analyses of VIDEO_TRACK data indicated that pups were clearly dead at the start of most of the cannibalism events and infanticide was rare. As most pups die and disappear before the first cage check, many breeding facilities are likely to be unaware of their real rates of mouse pup mortality.

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.