In this article, we present two topics related to mathematical economics. We offer an intriguing proposal for securing cost and production functions in the face of uncertainty and risk. We discuss the relationship between individual and social preferences. This is important because traditional revealed preference theory does not account for such factors.

After brings about a brief review of the theoretical explanations and researches on the reasons for being a victim, this article is organized into two sections. The first presents a comparative analysis of the data for 1999 and 2016 in terms of perceptions, profiles and most significant sociodemographic and socioeconomic variables. The second one shows an explanatory analysis based on a multivariate logistical regression model using as an independent variable lifestyle of the population and socioeconomic variables, and as dependent variables individual’s susceptibility to becoming a victim of certain crimes. The results points towards an explanatory model of victimization in which sociodemographic variables play an increasingly less important role while variables related to lifestyle and subjective perceptions make a significant contribution to greater understanding of the nature of being the victim of a crime.

Underreporting is the main limitation of the spontaneous reporting systems. This study aims to reduce underreporting enhancing public participation in vaccinovigilance through an SMS-based reporting system integrated with electronic immunization registries (IRs). Using the VigiVax software, parents of vaccinated children aged 2 years or younger received a single SMS inquiry about adverse events following immunization (AEFI). Responses were collected, validated by health operators and integrated with the information on IRs. AEFI reports were automatically submitted to the Italian Pharmacovigilance system. Among 254,160 SMS messages sent, corre-sponding to 451,656 administered doses (AD), 71,643 responses were collected (28.2% response rate), 21,231of them (8.3%) reporting an AEFI. After seriousness assessment based on clinical criteria, 50 reports (0,24%) were classified as serious. Among these, causality assessment identi-fied 31 reports at least potentially related to the vaccination (RR: 6.86/100,000 AD). Febrile seizures following MMRV vaccination accounted for 11 of these 31 cases, with an incidence of 32 per 100,000 AD. No fatal outcomes were reported. Our findings support the highly favorable risk profile of pediatric vaccinations and the possibility to improve spontaneous reporting through the integration of digital technologies.

Over the past decade, Knowledge bases (KB) have been increasingly utilized to complete and enrich the representation of queries and documents in order to improve the document retrieval task. Although many approaches have used KB for such purpose, understanding how effectively lev-erage entity-based representation still needs to be resolved. This paper proposes a Purely Enti-ty-based Semantic Search Approach for Information Retrieval (PESS4IR) as a novel solution. The approach includes (i) its own entity linking method, (ii) an inverted indexing method, and for document retrieval and ranking, (iii) an appropriate ranking method is designed to take advantage of all the strengths of the approach. We report the findings on the performance of our approach tested by queries annotated by two known entity linking tools, REL and DBpedia-Spotlight. The experiments are performed on the standard TREC 2004 Robust and MSMARCO collections. By using the REL method, for queries whose all terms are annotated and whose average annotation scores are greater than or equal to 0.75, our approach achieves the maximum nDCG@5 score (1.000). Thus, using our approach with any other document retrieval method would be an added value, unless that method achieves the maximum nDCG@5 score for those highly annotated queries.

Nature-based Solutions (NbS) have rapidly been gaining traction across the research, policy, and practice spheres, touted as transformative actions to jointly address biodiversity loss and climate change. However, there are multiple, alternative ways to imagine NbS in those three spheres. To inform the NbS discourses across these three spheres, we critically reflect on the prevailing framing of NbS and consider the potential of a different framing of NbS to support transformations towards regenerative relationships between humans and nature. Such reflection is urgently needed to ensure that research, policy, and practice delivers on the transformative ambitions of NbS. We propose a novel “core framing” of NbS, charting two pathways for how such a framing can support a human value-based transformation – first through influencing individual beliefs and values, and second through the communication and application of the NbS concept in research, policy, and practice. We argue that for NbS to support transformation, it must support a reframing of human-nature relationships, one where the interdependencies between people and nature are recognized as essential for social and environmental well-being. We elaborate on how such a framing is key to support inclusivity and collaboration between diverse research perspectives, policy objectives across scales, and implementation practices, to deliver successful NbS.

Abstract: The trend of fasting until noon (omission or delayed breakfast) is increasingly prevalent in modern society. This eating pattern triggers discordance between endogenous circadian clock rhythms and the feeding/fasting cycle and is associated with an increased incidence of obesity and T2D. Although the underlying mechanism of this association is not well understood, growing evidence suggests that fasting until noon, also known as an “extended postabsorptive state,” has the potential to cause a deleterious effect on clock gene expression and disrupted regulation of body weight, postprandial and overall glycemia, skeletal muscle protein synthesis, appetite and may also lead to lower energy expenditure. This manuscript overviews the clock gene-controlled glucose metabolism during the active and resting phases. The consequences of postponing until noon the transition from postabsorptive to fed state on glucose metabolism, weight control, and energy expenditure. Finally, we will discuss the metabolic advantage of shifting more energy, carbohydrates (CH), and proteins to the early hours of the day.

The purpose of this research is to understand the relationship between green business ethics, green finance, and sustainable business performance, and to evaluate the role of corporate social responsibility (CSR) in this relationship. The impact of the damage inflicted on nature's functioning order is being felt much more strongly today. In light of these realities, companies are required to place greater emphasis on sustainability principles not just out of financial concerns but as a result of corporate social responsibility. In this context, focusing on the role of corporate social responsibility in sustainable business performance is the main goal of this research. Quantitative research methods, specifically the cross-sectional survey method, were employed for data collection and analysis. For this purpose, a convenience sampling method was used to select 427 white-collar employees working in industries operating in Türkiye as the sample for this study. The data collected through surveys were analyzed using the AMOS 24 statistical program. The findings underscore that green business ethics and green finance have a significant impact on corporate social responsibility and sustainable business performance. Additionally, it was determined that corporate social responsibility plays an intermediary role in shaping sustainable business performance. These findings are expected to provide an important foundation that can guide both employees and managers in developing awareness about green policies and sustainability, emphasizing the importance of green policies in the working life.

As practiced in Africa, urban agriculture (UA) has been examined in the literature and by architecture and urban planning experts, revealing both advantages and disadvantages for health. While the recognized disadvantages are not negligible, the literature focuses mainly on the positive outcomes about food security and improved socio-economic conditions for farmers. However, little research has focused on farmers' perceptions of the effect of this practice on their psychological well-being. This study seeks to delve into this aspect by surveying 733 farmers in Dar es Salaam and Greater Lomé to map UA's distribution, assess its benefits and challenges, study its psychosocial associations, and demonstrate how architectural design and urban planning can enhance its spatial distribution and overall benefits. The standardized Mental Health Continuum-Short Form (MHC-SF) and non-standardized questionnaires are used to evaluate their responses. Using logistic regression and spatial analysis techniques with Python and QGIS 3.32.2-Lima, the analysis uncovers that farmers attribute improved psychological well-being to their involvement in UA. The study found that farmers' happiness due to UA varies by location within a city, with those on the outskirts generally more satisfied than those in urban centers. Additionally, women farmers reported greater happiness than men farmers, highlighting UA's role in empowering women. The research underscores UA's positive association with practitioners' psychological health in Africa and advocates for its integration into urban planning to promote equitable and beneficial urban spaces.

Given the extreme importance of improving the accountability of Private Social Solidarity Institutions (IPSS), both for reasons of legal compliance (hard law) and for reasons of improving legitimacy and notoriety among their stakeholders (soft law), this paper aims to present a framework designed under a more comprehensive research project, for the assessment of IPSS accountability and, consequently, its improvement. This study also present results of the indicators conceived, identifying the main trends of the framework dimensions and sub-dimensions from a pilot test for the years 2018, 2019 and 2020 in Portugal. Given the results, we believe that the framework designed answers the research question: How to promote accountability (social, financial and economic) in the social economy sector, in particular: the case of the IPSS?, however, as this is an exploratory article, it incorporates the limitation that this is a pilot test with only 7 entities.

Poor social skills in autism spectrum disorder (ASD) are associated with reduced independence in daily life. Current interventions for improving the social skills of individuals with ASD fail to represent the complexity of real-life social settings and situations. Virtual reality (VR) may facilitate social skills training in social environments and situations proximal to real life, however, more research is needed for elucidating aspects such as the acceptability, usability, and user experience of VR systems in ASD. Twenty-five participants with ASD attended a neuropsychological evaluation and three sessions of VR social skills training, incorporating 5 social scenarios with three difficulty levels for each. Participants reported high acceptability, system usability, and user experience. Significant correlations were observed between performance in social scenarios, self-reports, and executive functions. Working memory and planning ability were significant predictors of functionality level in ASD and the VR system’s perceived usability respectively. Yet, performance in social scenarios was the best predictor of usability, acceptability, and functionality level in ASD. Planning ability substantially predicted performance in social scenarios, postulating an implication in social skills. Immersive VR social skills training appears effective in individuals with ASD, yet an error-less approach, which is adaptive to the individual’s needs, should be preferred.

Vitronectin is a glycoprotein, present in plasma and extracellular matrix, implicated in cell migration. The high amount of vitronectin found in neuroblastoma biopsies was associated with poor prognosis. However, there are almost no studies of vitronectin levels in neuroblastoma cell culture media nor in plasma of neuroblastoma patients. Vitronectin concentration in culture media of four neuroblastoma cell lines grown in monolayer and in 3D-models, and in plasma of 114 neuroblastoma patients, was quantified using ELISA. Three of the neuroblastoma cell lines secreted vitronectin to culture media when cultured in monolayer and 3D-models. Vitronectin release was higher by neuroblastoma cells cultured in 3D-models than in monolayer, and was still great when cells grown in 3D-scaffolds with cross-linked vitronectin. Vitronectin secretion occurred independently of cell numbers in cultures. Its concentration in plasma of neuroblastoma patients ranged between 52.4 and 870µg/mL (median, 218µg/mL). A ROC curve was used to establish a cutoff of 361µg/mL, above which patients over 18-months-old had worse prognosis (p=0.0018). Vitronectin could be considered a new plasma prognostic biomarker in neuroblastoma, and warrants confirmation in collaborative studies. Drugs inhibiting vitronectin interaction with cells and/or extracellular matrix could represent a significant improvement in survival for neuroblastoma patients.

Background: The incidences of COVID-19 related suicide among adolescents and youths have been reported across the world. There is no cumulative study focusing on nature, patterns, and causative factors that lead to the present investigation. Methods: A purposive sampling of google news between 15 February to 6 July was performed. After excluding duplicate reports, the final list comprised a total of 37-suicide cases across 11 countries. Results: More male suicides were reported (21-cases, i.e., 56.76%), and the mean age of the total victims was 16.6±2.7 years (out of a total of 29-cases). About two-thirds of the suicides were from three countries named India (11-cases), United Kingdom (8-cases), and the USA (6-cases). Out of 23-student victims, 14 were school-going students. Hanging was the most common suicide method accounting in 51.4% of cases. The most common suicide causalities were related to mental sufferings such as depression, loneliness, psychological distress, etc., whereas either online schooling or overwhelming academic distress was placed as the second most risk factors followed by TikTok addiction-related psychological distress, and tested with COVID-19. Conclusion: The finding of the temporal distribution of suicides concerning lockdowns may help in exploring and evolving public measures to prevent/decrease pandemic-related suicides in young people.

This pilot study of Streptococcus mutans ATCC 35668 grown in media with and without polyols (erythritol) measured the resultant metabolites, including the short chain fatty acids by using head space analysis. Brain Heart Infusion Broth (BHI2 or BHI10) supplemented with 2% or 10% sucrose containing no polyols or either erythritol or xylitol and Streptococcus mutans (ATCC 35668) was grown aerobically. After 48 hours of growth the supernatant were harvested and centrifuged to pellet bacteria. Supernatants were removed from bacterial pellets then submitted for Short Chain Fatty Acid (SCFA) analysis with an Agilent Technologies (Santa Clara, CA 95051) system configured from three components, a 5973 mass selective detector, a 6890N gas chromatographer, and a 7697A headspace sampler. Streptococcus mutans growing in Brain Heart Infusion Broth (BHI2 or BHI10) supplemented with 2% or 10% sucrose but containing no polyols produced the following short chain fatty acids: methyl isovalerate, acetic acid, propionic acid, butanoic acid, pentanoic acid, ethyl butaric acid, 4-methylvaleric acid, hexanoic acid. When the Brain Heart Infusion Broth (BHI2 or BHI10) supplemented with 2% or 10% sucrose containing erythritol was used as media for this Streptococcus mutans strain, the following were produced: ethanol, acetoin, and acetic acid. Our results would suggest that constituents of the media may affect the bacterial metabolite production.

Job characteristics shape organizational sustainability, conferring tangible benefits to employees. Job characteristics shape attitudes toward work, such as satisfaction and engagement, and are related to the well-being and health of employees. The aim of the study was to determine and describe the role of work engagement and support at work in the relation between selected job characteristics (organizational justice, job control, and role clarity) and self-rated health. The study was conducted on a sample of 368 employees representing various industries. The study used: Utrecht Work Engagement Scale (UWES), Organizational Justice Survey, Coworker Support Scale, Supervisor Support Scale, Role Clarity Scale, Job Control Scale. Cantril ladder was used to measure self-rated health. The presented study established the importance of lower scores on the UWES subscale: dedication as a significant moderator of the examined correlations. In relation to the correlation: justice and its dimensions, and self-rated health, support from supervisors showed a greater effect than that from coworkers. The conducted study expands knowledge on the formation of employees' self-rated health through the sense of justice experienced within the organization. The results obtained are applicable to organizational practice. This finding highlights the importance of supporting organizational justice, which contributes to employee well-being (particularly when combined with high levels of work engagement and supervisor support) and ultimately increases organizational sustainability. Further research can be continued taking into account the limitations of the previous procedure of selecting people for the study and the measurement tools used.

This qualitative research investigates sustainable procurement practices, focusing on the integration of environmental and social criteria in supplier evaluation processes. The study explores how organizations, ranging from large multinational corporations to smaller enterprises, navigate sustainability challenges and opportunities within their procurement strategies. Data were gathered through semi-structured interviews with procurement professionals and sustainability managers across diverse industries. Themes identified include varying organizational commitments to sustainability, from structured policies and resource allocation in larger firms to reactive approaches constrained by resource limitations in smaller entities. Effective supplier relationship management emerged as crucial, facilitating collaborative partnerships aimed at improving environmental and social performance across supply chains. Motivations for sustainable procurement practices encompass regulatory compliance and responding to consumer demands for eco-friendly products, shaping procurement decisions to enhance market competitiveness and stakeholder satisfaction. Environmental and social criteria integration in supplier evaluations highlighted strategies such as lifecycle assessments and sustainable sourcing practices, aimed at minimizing environmental footprints and promoting ethical labor practices. Benefits included cost savings and enhanced brand reputation, tempered by challenges such as higher procurement costs and supplier resistance. Leadership commitment and organizational culture were identified as critical enablers of sustainable procurement, influencing strategic alignment and fostering a culture of sustainability within organizations. The study underscores the transformative potential of sustainable procurement in achieving organizational resilience and contributing to global sustainability goals.

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

Purpose: Social responsibility has been accepted as a core value of nursing profession, particularly in the area of health disparity, but it seems to be difficult to understand for what is meant by social responsibility. The purpose of this study was to explore ways to define the concept of social responsibility of nursing in order to understand the meaning of social responsibility in the field of nursing profession. Methods: The concept analysis process by Walker and Avant was used to clarify the meaning of social responsibility of nursing. Results: Defining attributes of social responsibility of nursing included praxis, as approach to strategizing for social and structural change of inequity, care for an oppressed group which is under social suffering caused by the privilege and power, and action for health policy change in social and political unequal contexts. The antecedents of social responsibility of nursing included reflectivities in identifying personal characteristics, taking seriously the perspective of other vulnerable population, recognizing social environmental status quo (‘fair or unfair’), developing competences in ethical and moral reasoning with social issues. Consequences of social responsibility of nursing were achieving social justice, as equal access to basic human health need in societal level, equal access to effective nursing practice delivery system and development of health promotion policy for world health administrative practices (“health for all”) in nursing. Conclusion: This study provides a guidance to direct future studies through the procedure of identifying conceptual attributes in the context of social responsibility of nursing. Future studies are suggested to develop instruments for social responsibility as well as development of educational programs to promote social responsibility competences in nursing students and nurses.

Postpartum depression (PPD) can predispose to physical and mental health problems in women. However, PPD is associated with health and perceived social support but their causal relationship is unclear. Therefore, this study intended to evaluate the association of PPD with insomnia, mental health, and physical health. Convenience sampling technique was used to collect data from 320 (52.8 %) young and middle aged postpartum women, in the outpatient departments of obstetrics and gynecology in Government Maula Bakhsh Hospital, District Head Quarter in Sargodha, Pakistan. The Edinburgh Postnatal depression scale, Pittsburg sleep quality index, Warwick-Edinburgh mental wellbeing scale, Patient health questionnaire, and Multidimensional scale of perceived social support were used to measure study variables. Results revealed a significant positive relationship of PPD with physical health (r= .45, p=.001), while a negative relationship with insomnia (r= -.24, p<.001), and perceived social support (r= -.38, p=.001). Results further confirmed that perceived social support played a moderating role (β = .97, p=.01) in the relationship between PPD and mental health among females. This study concluded that perceived social support has an important role in PPD and women’s health. The study also concluded that poor health is a risk indicator for identifying aid in the early stages of postpartum among women.

The possibilities and reach of social networks are increasing, the designs are becoming more diverse, and the ideas more visionary. Most recently, the former company “Facebook” announced the creation of a metaverse. With these technical possibilities, however, the danger of fraudsters is also growing. Using social bots, consumers are increasingly influenced on such platforms and business transactions are brought about through communication, i.e. conversational commerce. Minors or the elderly are particularly susceptible. This technical development is accompanied by a legal one: it is permitted by the Digital Services Directive and the Sale of Goods Directive to demand the provision of data as consideration for the sale of digital products. This raises legal problems at the level of the law of obligations and data protection law, whose regulations are intended to protect the aforementioned groups of individuals. This protection becomes even more important the more manipulative consumers are influenced by communicative bots. We show that there is a lack of knowledge about what objective data value can have in business transactions. Sufficient transparency of an objective data value can maintain legal protection, especially of vulnerable groups, and ensure the purpose of the laws.

Mental health and social resilience play a significant role in refugees’ adaptation during the resettlement process in the host country. Maintaining good mental wellbeing helps the refugees to respond to stressful experiences with healthy life choices. This study aimed to explore the mental wellbeing and social resilience of Eritrean refugees living in Germany and to identify social conditions and enablers to foster adaptation. This study employs a qualitative approach with a semi-structured, in-depth interview data collection method. Informants were identified among mostly young adult refugees living in Heidelberg, Germany, with a migration history of 3-6 years. In total, 15 informants were recruited through snowball sampling. Data were sorted and analyzed using the five pillars of the Adaptation and Development after Persecution and Trauma (ADAPT) model. The findings suggest that Eritrean refugees experience psychological distress after resettlement in Germany, however with time, their mental health has improved. The study revealed conditions that were experienced as hindrances, as well as ones that were considered to be resources of positive mental wellbeing and social resilience for resettled refugees. Challenges described were the language barrier, discrimination, unemployment, insecure residence status, loss of family and friends, conflict within the diaspora community, and isolation. The main sources of mental wellbeing and social resilience include the feeling of being welcomed by local communities, access to social services, adopting new relationships, and educational opportunities. These experiences encouraged refugees to have a favorable view of their lives and futures as well as also found to facilitate better integration and adaptation. Understanding refugee mental wellbeing and social resilience require a multidimensional perspective. Eritrean refugees living in Germany have experienced and still are experiencing resettlement challenges, as for example loss of family and friends, negative perception of the German system, loss of past achievements, or unemployment. But they have developed adaptive and resilience mechanisms, too, such as seeing an opportunity for a better life, adopting new roles, and accepting Germany as a “second home”. In addressing those by the refugees as hindrances reported issues, these could be turned into sources of mental well-being and resilience.

An increasing number of studies have proposed that corporate social responsibility (CSR) performance depends on how companies apply their resources and capabilities to implement CSR. A firm’s ability to integrate, build, and reconfigure internal and external competencies to respond to environmental changes is its dynamic capability. Implementation of CSR at the strategic level will contribute to a firm’s sustainability. However, the research on strategic CSR is incipient. This study explores possible mechanisms to investigate how dynamic capability influences the performance of strategic CSR in China. By analyzing 134 Chinese listed companies in the period 2017–2019, in this study, we found that firms with a high level of dynamic capability were less likely to adopt strategic CSR practices, and had a low strategic CSR adoption performance. The results confirmed the loss aversion channel, indicating that firms with a high dynamic capability level were loss averse and that managers had a decreasing sensibility in decision-making and allocated fewer company resources in CSR projects. These results can help companies to better understand the dynamic capability and how dynamic capability contributes to the adoption of strategic CSR and performance over time. The policy implications of the study are also discussed.

The COVID-19 pandemic of 2020 changed the way we interact and engage in commerce at a fundamental level. Social distancing and stay-at-home orders leave businesses and cities wondering what economic activity will look like in the future. Given a likely reduction in face-to-face interactions, it is important to better understand how social interactivity influences economic outcomes. Here we measure the effect of social interactions in the workforce on patent production and economic efficiency. We decompose U.S. occupations into individual work activities, determine which of those activities are associated with face-to-face interactions, and reaggregate the labor force of each U.S. metropolitan statistical area (MSA) into a metric of social interactiveness. We then calculate each MSA’s density of social work activities and find that this measure is more highly correlated with an MSA’s per capita patent production than simple population density. This suggests that density of face-to-face interactions is the important driver of a city’s rate of invention. We close by exploring analogies between the development of cities and the development of stars, suggesting ways these analogies may help frame future research on cities.

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.

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.

This paper presents the results of aerodynamical performance research focused on maintaining the thermal comfort and increasing the energy efficiency of a typical social housing unit located in a high-density urban area. Bioclimatic design strategies are used to develop a sustainable and economic technology in existing housing clusters in Mexico City. A full-scale prototype, built on campus facilities, was used to study the flow conditions around the design. All scaled prototypes implement similar criterion. Furthermore, a scaled prototype is evaluated within a low speed wind tunnel installation. Additionally, numerical simulations were performed at transient state based on previous physical measurements and historical local climatic conditions to determine preferable modifications.

In this study we were interested in the behaviors of individuals who preserve the social and organizational environment by ensuring sustainability. More specifically we are interested in allegiants behaviors. Numerous studies have highlighted the normative character of allegiance. To confer an object the status of social norm means to assign value (in terms of desirability and utility) to that object. Therefore we questioned the value attributed to allegiance. 170 employees were questioned on the desirability and utility they attribute to a future work colleague (future peer or future subordinate) starting from the answers the latter was supposed to have given to a questionnaire on allegiance. It was observed that desirability and utility make reference to two independent dimensions, utility being often more important. It was also noted there is greater severity assigned to endo-group targets (future peers) than to exo-group targets (future subordinates). Finally, it was noted there was not so much a valuation of allegiant targets, but rather a rejection of rebel targets, which raises the question of the bi-dimensionality of the valuation-devaluation process.

Critical realism emerged from the philosophical writings of Roy Bhaskar, and has evolved into a philosophy of social science research using the model of “dialectical critical realism” (DCR) which begins with the researcher’s assumptions that the structures being researched have a real, ontological grounding which is independent of the researcher. This approach has proved fruitful in British and European social science research, but has had less influence in North America. We outline DCR’s four level model for understanding society and its changing social structures through “the pulse of freedom”. DCR has been used by Marxists, Muslims, Catholics and secular scholars who engage fruitfully in morphogenic dialogues leading to a critical realist understanding of society and social research, which transcends positivist and social constructionist models. Examples of DCR’s application in the fields of childhood research, child abuse, education, and research on organisations are outlined to illustrate the working of this new research paradigm. We are enthusiastic in our advocacy of DCR as a model of qualitative research, and for constructing models of positive social change, and are particularly impressed by the substantive and theoretical expositions of DCR by Priscilla Anderson, Matthew Wilkinson and Margaret Archer, whose work we document and review.

Total-body PET/CT scanners provide increased sensitivity, enabling the adjustment of imaging parameters by reducing injected activity or shortening acquisition time. This study aimed to evaluate the limitations of reduced [18F]FDG activity doses on image quality, lesion detectabil-ity, and quantification of lesion uptake in the Biograph Vision Quadra, as well as to assess the benefits of the recently introduced ultra-high sensitivity mode in a clinical setting. A number of 26 patients who underwent [18F]FDG-PET/CT (3.0 MBq/kg, 5 min. scan time) were included in this analysis. PET raw data was rebinned for shorter frame durations to simulate 5 min. scans with lower activities in high sensitivity (HS) and ultra-high sensitivity (UHS) modes. Image quality, noise, and lesion detectability (n=82) were assessed using a 5-point Likert scale. The co-efficient of variation (CoV), signal-to-noise ratio (SNR), tumor-to-background ratio (TBR), and standardized uptake values (SUV) including SUVmean, SUVmax, and SUVpeak were evaluated. Sub-jective image ratings were generally superior in UHS compared to HS mode. At 0.5 MBq/kg, le-sion detectability decreased to 95% (HS) and 98% (UHS). SNR was comparable at 1.0 MBq/kg in HS (5.7±0.6) and 0.5 MBq/kg in UHS (5.5±0.5). With lower doses, there were negligible reductions in SUVmean and SUVpeak, whereas SUVmax increased steadily. Reducing [18F]FDG activity to 1.0 MBq/kg (HS/UHS) in a total-body PET/CT provides diagnostic image quality without statistical-ly significant changes in uptake parameters. UHS mode improves image quality, noise, and le-sion detectability compared to HS mode.

Empowering women and promoting gender equality is crucial for accelerating sustainable development in fragile countries, including the Democratic Republic of Congo (DRC). However, there is scarce existing knowledge or understanding of the factors determining women’s empowerment in these contexts. We aimed to assess women's empowerment and determine its associated factors in Kinshasa, DRC. We analyzed data from the 2021 Performance Monitoring Assessment (PMA) survey. A sample of 1,365 women of childbearing age was retained for this study. Twenty empowerment items related to household decision-making, contraception use, and husband/partner influence were considered. We calculated the average women’s empowerment index (aWEI), identified the women empowerment variables using principal component analysis (PCA), and determined the associated factors for the first three principal components through the performance of multivariate binary logistic regression. In Kinshasa, the overall aWEI was estimated at 0.65. It was low for household decision-making (0.34) and high for husband/partner influence domains (0.93), respectively. Three principal components were identified and named, including the absence of threats, control of sexuality, and participation in decision-making. The factors associated with these components were having internet access, being in free union with a partner, being aged 40-49 years, and residing in a non-slum area. Increasing access to information would enable women in Kinshasa to make strategic decisions about their lives, benefiting themselves and others.

Studies show that although female soccer players often have shorter change of direction (COD) deficits than males, indicating different biomechanical profiles, there is lack of research on the impact of physical metrics on COD performance in females. The aim of this study was to analyze whether performance metrics based on speed, and jumping could explain the variation in %CODD in young female soccer players. Thirty-three highly trained adolescent female soccer players (age: 16. ± 0.95 years; height: 160.4 ± 5.22 cm; body mass: 55.7 ± 7.22 kg) performed COD180 tests, 10-m and 30-m sprint test and single leg countermovement and horizontal jumps. Acceleration in the first 10 meters of a sprint was identified as a significant predictor of COD180 performance (R2 = 28%), (R2 = 50%), (p

Liver cancer is the fourth leading cause of cancer-related death worldwide. In Mexico, there is a high burden of liver cancer mortality in rural states, which affects both women and men equally. Thus, we aimed to describe the demographic and clinical characteristics of hepatocellular cancer (HCC) by sex in Mexico. Demographic and clinical information were extracted retrospectively from the medical records of patients with HCC initially treated (2015-2022) at participating institutions of a national survey across the country. The male-to-female ratio was calculated at the national and regional levels and the results were stratified by sex. Among 697 HCC patients, the age at diagnosis was 65.4±11.9y and 20% were diagnosed at ≥75y. The male-to-female ratio was 1.4:1, ranging from 1:1 in the northwestern and southwestern regions to 2.1:1 in the western region. The proportion of cirrhosis was similar between sexes; however, the etiologies for cirrhosis differed: cryptogenic cirrhosis was higher in women and alcohol consumption was higher in men. Men had a higher proportion of advanced HCC, poor/undifferentiated tumors, and ≥4 nodules than women. HCC in the Mexican population affects men and women at a 1.4:1 male-to-female ratio. This unique proportion by sex could be explained by the differences in the prevalence of risk factors across our heterogeneous country.

Electronic waste (e-waste), characterized by the widespread disposal of electronic devices, shows a growing environmental challenge. In this study, we explore the electrocatalytic potential of gold nanoparticles supported on Vulcan obtained from e-waste for their application as electrocatalysts for the methanol oxidation reaction in alkaline media. Gold nanoparticles are synthesized from gold coatings recovered from Intel Pentium 4 processor pins, highlighting their sustainability as electrocatalyst precursors. Comprehensive characterization, including UV-Vis spectroscopy, transmission electron microscopy (TEM), scanning electron microscopy (SEM) and X-ray dif-fraction, is performed to assess the electrocatalyst's structural properties. Electrochemical evalu-ation is carried out in 0.5 M KOH electrolyte employing the rotating disk electrode technique, us-ing cyclic voltammetry for the study of methanol oxidation. Remarkably, the gold nanoparticles show electrocatalytic activity on par with commercially synthesized counterparts, demonstrating the feasibility of this approach for sustainable electrocatalyst production. Thus, this research opens new routes for utilizing e-waste as a source of valuable catalyst materials, addressing en-vironmental and technological challenges in the field of alkaline fuel cells.

We experimentally study the supercontinuum (SC) induced by femtosecond filament in different liquid media, and determine the relative measurement value of filamentation threshold Pth for these media by using a Mach-Zehnder interferometer (MZI). It is found that the value of Pth is higher than the critical power for self-focusing Pcr, which can be attributed to the strong dispersion effect. Changing the focal length of the focusing lens affect the measured results of the filamentation threshold: In the case of shorter focal length, linear focusing (i.e., geometrical focusing) regime dominates, and the measured values of Pth for different media are almost the same; as the focal length becomes larger, self-focusing starts to play a role, making the values of Pth for different media different from each other. This work provides an effective approach to study the femtosecond filamentation process in liquid media, and helpful to further understand the physical process of supercontinuum induced by femtosecond filament in liquid media.

The South African government introduced a nationwide lockdown in March 2020 to mitigate the spread of Covid-19. Among other restrictions, the government banned the sale of tobacco products, which lasted for nearly five months. We performed a Google search using the keywords smok*, puff*, lockdown, tobacco, and cigarette*, for articles published in English from 23 March 2020to 18 December 2020 and analysed 441 online media articles. We identified the main arguments made by proponents and opponents of the tobacco sales ban, which were categorised into themes. Three themes were prominent: medical, legal, and economic/financial. Legal aspects were covered in 48% of articles, followed by economic (34%), and medical aspects (18%). The media was generally ambivalent about the tobacco sales ban during the first five weeks of lockdown. Sentiment then turned against the ban. because the medical rationale was not well communicated by the government, there was limited empirical evidence of a link between smoking and contracting Covid-19, and the sales ban was ineffective, since most smokers still purchased cigarettes. Policy framing in the media plays an important role in how the public receives the policy. Any future tobacco control policy intervention should be well-considered and appropriate cessation support services offered.

Dielectric spectroscopy (DS) is a promising cell screening method that can be used for diagnostic and drug discovery purposes. The primary challenge of using DS in physiological buffers is the electrode polarization (EP) that overwhelms the impedance signal within a large frequency range. These effects further amplify with miniaturization of the measurement electrodes. In this study, we present a microfluidic system and the associated equivalent circuit models for real-time measurements of cell membrane capacitance and cytoplasm resistance in physiological buffers with 10s increments. The current device captures several hundreds of biological cells in individual microwells through gravitational settling and measures the system’s impedance using microelectrodes covered with dendritic gold nanostructures. Using PC-3 cells (a highly metastatic prostate cancer cell line) suspended in cell growth media (CGM), we demonstrate stable measurements of cell membrane capacitance and cytoplasm resistance in the device for over 15 minutes. We also describe a consistent application of the equivalent circuit model, starting from the reference measurements used to determine the system parameters. The circuit model is tested using devices with varying dimensions, and the obtained cell parameters between different devices are nearly identical. Further analyses of the impedance data have shown that accurate cell membrane capacitance and cytoplasm resistance can be extracted using a limited number of measurements in the 5 MHz to 10 MHz range. This will potentially reduce the timescale required for real-time DS measurements below 1s. Overall the new microfluidic device can be used for dielectric characterization of biological cells in physiological buffers for various cell screening applications.

Introduction: Otitis media with effusion (OME) is common in pediatric primary care consultations. Its etiology is multifactorial, although it has been proven that inflammation factors mediate and that immunity is in a phase of relative immaturity. The objective of this study was to assess the effects of the Traditional Mediterranean Diet (TMD) modulating inflammation and immunity in patients diagnosed with OME.

In an attempt to improve the quality of the agricultural drain in Egypt for its reuse again in the irrigation, low cost solution such as sand filter along with/ without other filtration media have been used in this research, As a result of that, pilot plant of sand filter mixed with other filtration media was tested for its ability to improve the sand performance in removing the suspended solids and organic matters from agricultural drain water of the Belbeis drain (in Sharkia governorate in Egypt). Only sand compared with sand with sponge and sand with Liyan Nanfang activated carbon (L.N.A.C) have been tested to find the optimum mixing sand/ medium ratio &optimum infiltration rate. The work has been done on four runs. It was found that sand mixed with sponge gave the best removal efficiency compared to that of the sand only and the sand mixed with L.N.A.C. The results presented that the concentration of CODt, CODsol and TSS was reduced from 125, 47 and 162 mg/l to 44, 34 and 28 mg/l respectively at optimum infiltration rate of 2 m³/m²/d for sand mixed with sponge.

Kinect is a device that has been widely used in many areas since it was released in 2010. Kinect SDK was announced in 2011 and used in many other areas than its original purpose, which was a controller for gaming. In particular, it has been used by a number of artists in digital media art since it is inexpensive and has a fast recognition rate. However, there is a problem. Kinect create 3D coordinates with a single 2D RGB image for x, y value - single depth image for z value. And this creates a significant limitation on the installation for interactivity of media art. Because the Cartesian XY coordinate and the spherical Z coordinate system are used in combination, depth error depending on the distance is generated, which makes real-time rotation recognition and coordinate correction difficult above coordinate system. This paper proposes a real-time calibration method of Kinect recognition range expansion for useful application in the digital media art area. The proposed method can recognize the viewer accurately by calibrating a coordinate in any direction in front of the viewer. 3,400 datasets witch acquire from experiment were measured as five stances: the 1m attention stance, 1m hands-up stance, 2m attention stance, 2m hands-up stance, and 2m hands-half-up stance, which were taken and recorded every 0.5 sec. The experimental results showed that the accuracy rate was improved about 11.5% compared with front measurement data according to Kinect reference installation method.

A new and easy-to-make polymer film sensor was prepared by dip-coating technique and this film used as fluorescent chemosensor for the detection of metal ions in aqueous solution. The proposed film sensor exhibited dual emissions at 540 and 582 nm under a single excitation wavelength. The fluorescence behavior of this film sensor toward metal ions has been investigated using these two wavelengths. The proposed sensor was found to show selectivity and sensitive to Fe³⁺ ion when compared the other metal ions in deionized water with excellent photostability. Detection limit of the polymeric film sensor was calculated as 86.15 and 28.90 μM. The results showed that the sensor can be successfully applied to the determination of Fe³⁺ ions in aqueous media. Contact angle measurement of PAZU film probe was also investigated and the result showed that the proposed film probe has hydrophobic property.

A review of literature, supporting the view on the psychophysical origins of some acceptance effects of cyber-physical systems (CPSs), is presented and discussed in the paper. Psychological effects like the reactance to a robot or the uncanny valley phenomenon suggest that CPSs are perceived as a special type of ‘being’, a phylogenetically emergent category, or a novel ontology in a philosophical sense, culturally developing as a function of the social brain. Justification of this view is provided by the psychophysically-relevant human responses to technologically and socially ambiguous stimuli on the one hand, and the probabilistic independence of the proposed ontology to similar ontologies, subjectively experienced by the human, on the other. The results of the presented in the paper analysis demonstrate the feasibility of the proposed hypothesis of ontological ‘near independence’ of the distribution of the probabilistic psychophysical processes in response to the cyber-physical stimulus as a socially evolving phenomenon.

Individuals are pupils of society, and students represent individuals within the societal context. It is the noble aspiration of every educator to cultivate students with well-rounded personalities for the benefit of society. School curricula are instrumental in shaping the children who will, in turn, shape the future of society, and it is posited that students with well-rounded personalities are invariably those who embody love. The challenge lies in how to enable children to possess, retain, extend, refine, and be filled with love—a task necessitating the collaborative and synergetic efforts of both the educational and social systems to achieve a societal milestone. Pedagogy of love focuses on nurturing the capacity for love within students, who, through self-awareness of their indoctrination in love, transform techniques of self-love into capabilities of love for others. This process continuously generates the energy of love within social relations, thereby fostering social production, improving the relations of production, and enhancing the creative capacities, vitality, and welfare of a socialist society's wealth and capital accumulation.

With the fast development of the mobile Internet, the online platforms of social networks have rapidly been developing for the purpose of making friends, sharing information, etc. In these online platforms, users being related to each other forms social networks. Literature reviews have shown that social networks have community structure. Through the studies of community structure, the characteristics and functions of networks structure and the dynamical evolution mechanism of networks can be used for predicting user behaviours and controlling information dissemination. Therefore, this study proposes a deep community detection method which includes (1) matrix reconstruction method, (2) spatial feature extraction method and (3) community detection method. The original adjacency matrix in social network is reconstructed based on the opinion leader and nearer neighbors for obtaining spatial proximity matrix. The spatial eigenvector of reconstructed adjacency matrix can be extracted by an auto-encoder based on convolution neural network for the improvement of modularity. In experiments, four open datasets of practical social networks were selected to evaluate the proposed method, and the experimental results show that the proposed deep community detection method obtained higher modularity than other methods. Therefore, the proposed deep community detection method can effectively detect high quality communities in social networks.

The article analyses the main aspects of upstream social marketing for implementing of mobile government (MGov). The methodology of current research is based on the systematic literature review in the fields of MGov and social marketing. According to our findings, most researchers investigated MGov from the side of citizens (consumers) and emphasised the benefits to them while changing their attitudes and behaviours in employing mobile applications. However, as there is a lack of the researches from the side of governmental bodies, in this paper, we were contrary looking for new meanings, attitudes and values from their perspective. Limitations of employment of MGov occur due knowledge gap among decision makers and public policy formers (upstream audience). Therefore, we argue that upstream social marketing for the upstream audience would bring the success in faster MGov implementation. Specific social marketing would be mostly valuable on the municipal level that is the closest substance to the society. Thus, in our paper we emphasise the benefit of the MGov for the local upstream audience and propose possible external marketers as well as the motivating theses based on these 7P of marketing mix for the successful MGov on municipal level.

Sustainable agriculture is essential to provide food security for a growing world population without further sacrificing the integrity of the environment. To make progress towards agricultural sustainability we must consider ecological and socioeconomic processes within the agricultural socio-ecosystem and involve stakeholders in the research process. We propose an innovative experimental approach for examining how natural regulation of ecosystems may provide an alternative to increasing external inputs in agriculture while improving the socio-economic welfare of farmers. These “social-ecological experiments” go further to participatory action research by not only involving stakeholders in the research process but also by manipulating simultaneously socioeconomic and ecological processes under real field conditions to give a faster route to sustainability. Social-ecological experiments are undertaken in real field conditions, explicitly involving stakeholders, and help untangle the drivers of social-ecological dynamics under various land management and farming practices. Social-ecological experiments are distinct from adaptive management and scenario-planning approaches as they highlight the interactions between ecological and social processes, manipulate the social and ecological processes shaping the system and show causal links between patterns and processes. As an example, we describe a social-ecological experiment for reducing herbicide use. Social-ecological experiments offer great opportunities for increasing stakeholders’ acceptance of environmental policies implemented through adaptive management. These experiments may help to identify management practices that optimize multiple objectives, deliver a portfolio of ecosystem services and satisfy key stakeholders.

Background: The financial austerity policy imposed to Portugal by Troika - the European Commission, European Central Bank and International Monetary Fund in 2011, led to a tremendously social crisis. Under these dominant trends in Europe, which were felt especially in certain countries, such as Portugal, we feel ourselves forced into an analysis and reflection on the impact of this conjuncture in social workers, especially analyzing the role played by social workers and its critical consciousness relative to this neoliberal model and imposed austerity policies. Methods: This article results from an analysis of empirical data collected after the entry of Troika in Portugal, during 2013. Were conducted 26 in-depth interviews to front line social workers, with the purpose of obtaining a narrative of their daily work practice and with the concern of encouraging reflection on them. Results: Analysis shows the predominance of a maintenance role at the expense of more emancipatory approaches and thus, this results point to the relationship of this maintenance role with the sociological paradigm of social regulation and shows also, how social work is still attached to a conservative agenda. Secondly, one finds a weak critical reflection among social workers, being very afraid to speak out against the system, taking on a submissive attitude and subservient to the policies of social cuts imposed. The analysis then raises the challenge for social workers to develop a critical reflexivity Conclusion: The results highlight several important observations in terms of social woker role and that a critical activity is urgently required to social workers.

Social Business Intelligence (SBI) enables companies to capture strategic information from public social networks. Contrary to traditional Business Intelligence (BI), SBI has to face the high dynamicity of both the social network contents and the company analytical requests, as well as the enormous amount of noisy data. Effective exploitation of these continuous sources of data requires efficient processing of the streamed data to be semantically shaped into insightful facts. In this paper, we propose a multidimensional formalism to represent and evaluate social indicators directly from fact streams derived in turn from social network data. This formalism relies on two main aspects: the semantic representation of facts via Linked Open Data and the support of OLAP-like multidimensional analysis models. Contrary to traditional BI formalisms, we start the process by modeling the required social indicators according to the strategic goals of the company. From these specifications, all the required fact streams are modeled and deployed to trace the indicators. The main advantages of this approach are the easy definition of on-demand social indicators, and the treatment of changing dimensions and metrics through streamed facts. We demonstrate its usefulness by introducing a real scenario user case in the automotive sector.

The challenge of this work is to re-define the concept of intelligent agent as a building block of social networks by presenting it as a physical particle with additional non-Newtonian properties. The proposed model of an intelligent agent described by a system of ODE coupled with their Liouville equation has been introduced and discussed. Following the Madelung equation that belongs to this class, non-Newtonian properties such as superposition, entanglement, and probability interference typical for quantum systems have been described. Special attention was paid to the capability to violate the second law of thermodynamics, which makes these systems neither Newtonian, nor quantum. It has been shown that the proposed model can be linked to mathematical models of livings as well as to models of AI. The model is presented in two modifications. The first one is illustrated by the discovery of a stochastic attractor approached by the social network; as an application, it was demonstrated that any statistics can be represented by an attractor of the solution to the corresponding system of ODE coupled with its Liouville equation. It was emphasized that evolution to the attractor reveals possible micro-mechanisms driving random events to the final distribution of the corresponding statistical law. Special attention is concentrated upon the power law and its dynamical interpretation: it is demonstrated that the underlying micro- dynamics supports a “violent reputation” of the power-law statistics. The second modification of the model of social network associated with a decision-making process and applied to solution of NP-complete problems known as being unsolvable neither by classical nor by quantum algorithms. The approach is illustrated by solving a search in unsorted database in polynomial time by resonance between external force representing the address of a required item and the response representing the location of this item.

Autism spectrum disorder (ASD) is characterized by diverse patterns of social interaction, communication, and behavior. This study explores the application of clustering and stochastic migration models to visualize and understand the social and neural connectivity patterns associated with autism. The clustering model, with its strong internal connections and limited external connections, mirrors the tight-knit social groups and communication barriers often observed in individuals with autism. In contrast, the stochastic model, characterized by more dispersed connections and greater adaptability, represents the variability and flexibility seen in social interactions across typical individuals. By comparing these models, we can gain deeper insights into the unique challenges and strengths of individuals with autism, highlighting the importance of personalized interventions. Additionally, these models provide a visual framework for understanding the differences in brain connectivity patterns observed in autism, with implications for both behavioral and neural correlates. This study underscores the value of computational models in advancing our understanding of autism and guiding effective support strategies.

This scholarly article provides an overview of the present and future issues and trends in social work on a global scale. Drawing upon recent bibliographic references and a review of the literature, this article explores the challenges faced by social workers in various regions and highlights emerging trends that are reshaping the field. The analysis incorporates insights from renowned authors and researchers to provide a comprehensive understanding of the current state and anticipated future of social work practice, education, and research worldwide.

The aim of the article is to present a snapshot in time, of the current state in cryptocurrencies, the values and risks associated to blockchains. With emergence of over 20,000 crypto projects, the first objective of this article is to present the stage as it is in 2023, with historical overview since Satoshi presented the first paper on decentralised blockchains, until today. Second objective of the article is to review the values and risks associated to cryptocurrencies, and to clarify the differences between cryptocurrencies from blockchain technologies. The research questions that drive this article are related determining if the blockchain technology an innovation or its already obsolete technology? Are there any significant risks from cryptocurrencies? And are the potential values to society and economy worth pursuing? Would developed or developing countries benefit more from these technologies? And which blockchain projects will survive in the long run? In other words, where is the money and is there money or just hype. The review discusses the high probability that some crypto projects will fail, and given the vast number of cryptos, the article acknowledges that many of these projects are nothing more than ponzies. These are discussed and acknowledged, then the focus is shifted to the real-world use cases of blockchain projects.

This study aims to unravel the paradox of perceptions and knowledge of the flood victims towards the causes of the disaster in both internal and external context. Internal context comprises of a comparison of perceptions and knowledge based on individual characteristics (age, gender, education and income). Whereas, the external context includes the factors of the awareness of the victims towards the amount of rainfall, the impact of land use changes as well as the negligence of the responsible parties. The main objective of this study is to determine the differences of perception and knowledge of December 2014 flood victims in Kelantan towards the factors that lead to the flood. This disaster had resulted in huge amount of money loss as well as traumatize the victims in which can be felt to this day. Since that incident, there were various points of view and different perceptions in finding the cause of the disaster occurred. Besides that, the study found that the level of perception and knowledge as to the cause of the disaster is different in the internal context (individual characteristics). This difference has a significant influence on the awareness of the causes of the floods that occurred in the external context. Significant relationships at the level of p <0.05 has existed between perception and knowledge of the causes of the disaster victims affected by environmental changes in the last 10 years. This indicates that although the victim is aware of the physical environment changes happening around them, but all that is seen as not a major contributing factor to the cause of the floods in Kelantan in 2014.

Biocultural heritage-based products, including regional specialty foods, are increasingly part of sustainable rural development strategies. While export-oriented biocultural products are often the most visible, we examine the role of campesino gastronomic heritage in the Central Valley of Tarija, Bolivia, as a case study of a local market-centered biocultural resource-based development strategy reflected in an alternative agri-food network. We develop a biocultural sustainability framework to examine this network from ecological, economic and sociocultural perspectives. Data are drawn from interviews (n=77), surveys (n=89) and participant observation, with primary and secondary producers of traditional and new products, as well as restaurant owners, market vendors and local consumers. We find that campesino biocultural heritage and the alternative agri-food network surrounding it represent an influential territorial project that underpins many household economies, particularly for women. We conclude that the relatively small investments by local governments to promote campesino gastronomic heritage are having positive ripple effects on small-scale producer livelihoods and on biocultural sustainability. We suggest that further support to increase market access and reduce other barriers to participation in alternative food networks will likely increase the options and benefits available to small-scale producers mobilising campesino gastronomic heritage within the local economy.

Rosavin, a phenylpropanoid in Rhodiola rosea's rhizome, an adaptogen, is known for enhancing the body's response to environmental stress. It significantly affects cellular metabolism in health and many diseases, particularly influencing bone tissue metabolism. In vitro, rosavin inhibits osteoclastogenesis, disrupts F-actin rings formation, and lowers osteoclastogenesis-related gene expression (cathepsin K, CTR, TRAF6, TRAP, MMP-9). It also impedes NFATc1, c-Fos, NF-κB, and MAPK signaling pathways, and blocks phosphorylation processes crucial for bone resorption. Moreover, rosavin promotes osteogenesis, osteoblast differentiation and increases Runx2 and OCN expression. In vivo studies show its effectiveness in enhancing BMD in PMOP mice, re-straining osteoclast maturation, and increasing active osteoblast percentage in bone tissue. It modulates mRNA expressions (increasing EEF2 and decreasing HDAC1, thereby activating os-teoprotective epigenetic mechanisms) and alters various serum markers, including decrease of CTX-1, TRAcp5b, RANKL, M-CSF, TRAP, and increase of ALP and OCN. Additionally, when combined with zinc and probiotics, it reduces pro-osteoporotic MMP-3, IL-6, TNF-α, and en-hances anti-osteoporotic IL-10 and TIMP3 expressions. This paper aims to systematically review rosavin's impact on bone tissue metabolism, exploring its potential in osteoporosis prevention and treatment, and suggesting future research directions.

This review explores the transformative impact of sensor technologies in early disease detection. It highlights recent advancements in nanotechnology-based sensors, particularly focusing on their applications in identifying disease biomarkers at early stages. The integration of these sensors with artificial intelligence for predictive analytics in healthcare is also discussed. Applications in cancer, infectious diseases, and chronic disease management underscore their diverse utility. Challenges in sensor technology adoption and future directions, including multiplexed sensors and wearable devices, are examined. This review underscores sensors' potential in enhancing disease management and patient outcomes.

Herpesvirus is a prevalent pathogen that primarily infects human epithelial cells and has the ability to reside in neurons. In the field of otolaryngology, herpesvirus infection primarily leads to hearing loss and vestibular neuritis, and is considered the primary hypothesis regarding the pathogenesis of vestibular neuritis. In this review, we provide a summary of the effects of herpes virus on cellular processes in both host cells and immune cells, with a focus on HSV-1 as illus-trative examples.

Energy demand has exponentially increased with the increase in the world population and ur-banization. Renewable energy is clean, renewable, and environmentally friendly. Hydrogen production through Proton Exchange Membrane (PEM) electrolyzer is an efficient way to produce renewable energy. The efficiency and energy consumption of the PEM electrolyzer depends on the feed water quality. In this report, we study the effect of pH, TDS, and conductivity on hydrogen production as well as energy consumption during the process. pH values (3, 7, 9), TDS values (300ppm, 600ppm, 900ppm), and conductivity values (30mS/cm, 70mS/cm, 100mS/cm) were studied to understand and optimize the hydrogen production using PEM electrolyzer. The in-vestigations showed that hydrogen production is significantly affected by pH, total dissolved solids, and conductivity, and the best levels of each variable were identified by extensive testing. The findings show both the scientific significance of proton exchange electrolysis in meeting the growing energy demands of society as well as the importance of knowing the influence that di-verse conditions have on the creation of hydrogen. Our research, in general, contributes to the expanding body of scientific knowledge on the topic of the effective production of hydrogen and offers useful insights for the continuation of investigation in this field.

The article is aimed at a brief comparison and analysis of the results of queries to IEEE Xplore and the leading abstract databases Scopus and Web of Science to identify research trends. Some errors in the Author Keywords in Web of Science have been revealed. Therefore, a more detailed analysis was conducted by comparing different types of key terms for IEEE Xplore and Scopus platforms only. I used IEEE Access journal metadata as indexed on both platforms. The sample match for IEEE Xplore and Scopus was achieved by comparing DOI. The IEEE Xplore metadata contains more types of key terms, which provides an advantage in analyzing research trends. Using NSPEC Controlled Terms from expert-compiled vocabulary provides a more stable data, which gives an advantage when considering the change of terms over time. Apriori, an algorithm for finding association rules, has been used to compare co-occurrence of terms for a more detailed description of sample subjects on both platforms. VOSviewer was used to analyze trends in scientific research based on IEEE Xplore data. The 2011-2021 ten-year period was divided into two sub-intervals for comparing the occurrence of Author Keywords, IEEE Terms, and NSPEC Controlled Terms. Using the IEEE conference proceedings bibliometric data, I illustrated the importance of context in estimating the rate of growth of publishing activity on a topic of interest.

Intravitreal injection is the gold standard therapeutic option for posterior segment pathologies, and long-lasting release is necessary to avoid reinjections. There is no effective intravitreal treatment for glaucoma or other optic neuropathies in daily practice, nor is there a non-invasive method to monitor drug levels in the vitreous. Here we show that a glaucoma treatment combining a hypotensive and neuroprotective intravitreal formulation (IF) of brimonidine-Laponite (BRI/LAP) can be monitored non-invasively using vitreous imaging captured with optical coherence tomography (OCT) over 24 weeks of follow-up. Qualitative and quantitative characterization was achieved by analysing the changes in vitreous (VIT) signal intensity, expressed as a ratio of retinal pigment epithelium (RPE) intensity. Vitreous hyperreflective aggregates mixed in the vitreous and tended to settle on the retinal surface. Relative intensity and aggregate size progressively decreased over 24 weeks in treated rat eyes as the BRI/LAP IF degraded. VIT/RPE relative intensity and total aggregate area correlated with brimonidine levels measured in the eye. The OCT-derived VIT/RPE relative intensity may be a useful and objective marker for non-invasive monitoring of BRI/LAP IF.

Besides the increase in global energy demand, access to clean energy, reduction in greenhouse gas emissions caused by conventional power generation sources, energy security, and availability of electricity in remote villages in emerging nations are some of the factors that foster the use of renewable energy sources (RESs) in generating electricity. One of the aims of initiating microgrids (MGs) is to maximize the benefits of RES and alleviate the associated grid integration issues. Microgrids are made up of RES connected to electrical loads within clearly delineated electrical limits that operate as individual controllable units on the electrical network. It can operate in-dependently as well as in connection with the grid. The paper presents an overview of microgrids and investigates the system's performance when connected to and disconnected from the grid. Furthermore, in both modes of operation, the functioning and behavior of system components such as the bidirectional DC-DC converter and energy storage system (ESS) were evaluated. The architecture of the proposed microgrid consists of a small hydropower plant, a wind farm, and a battery energy storage system (BESS). The microgrid under investigation is modeled and simu-lated using MATLAB and Simulink.

We aimed to determine if infection-associated urine biomarkers can differentiate true urinary tract infection (UTI) from non-UTI controls. Midstream clean-catch urine samples were collected from asymptomatic volunteers and symptomatic subjects > 60 years old diagnosed with presumptive UTI in a specialty setting. Microbial identification and density were assessed using multiplex PCR/pooled antibiotic susceptibility test (M-PCR/P-AST) and standard urine culture (SUC). Three biomarkers (NGAL, IL-8, and IL-1β) were measured in the same urine specimens. Definitive UTI cases were symptomatic and had positive microorganism detection by SUC and M-PCR, while definitive non-UTI cases were asymptomatic volunteers regardless of microbial detection. We observed a strong positive correlation (R2 ≈ 1) between microbial density and the biomarkers NGAL, IL-8, and IL-1β. Biomarker consensus criteria of two or more positive biomarkers had sensitivity 90.2%, specificity 91.2%, positive predictive value (PPV) 91.7%, negative predictive value (NPV) 89.7%, accuracy 90.7%, positive likelihood ratio of 10.28, and negative likelihood ratio of 0.11 in differentiating definitive UTI from non-UTI cases, regardless of microbial density. NGAL, IL-8, and IL-1β showed a significant elevation in symptomatic cases with positive microbe identification compared to asymptomatic cases with or without microbe identification. Biomarker consensus exhibited high accuracy in distinguishing UTI from non-UTI cases.

This study aims to broaden the current understanding of the antecedents and consequences of green purchase intention within the realm of perceived green value (PGV) A mixed-method approach is deployed, integrating PLS-SEM and Necessary Condition Analysis (NCA) to examine the role of influence and interaction as key precursors to perceived responsibility and perceived self-efficacy, and explores how perceived responsibility and perceived self-efficacy impacts green purchasing intention, mainly through the mediation of perceived responsibility (PER) and perceived self-efficacy (PSE) using survey data gathered from consumers participating. The results indicate that PGV positively influences green purchase intention (GPI). Moreover, PER and PSE exhibit significant chain mediation effects, with the mediation effect of perceived environmental responsibility being particularly strong. It is recommended that the government intensify green disseminate and education, promote the establishment of certification and evaluation systems for electric vehicle products, and that electric vehicle factories emphasize the environmental attributes and economic interest of their products to encourage green purchasing behavior.

This study examined the effect of the media usage environment, particularly TV and SNS devices, on advertisement acceptance, lifestyle, and psychological satisfaction. Hypothesis pathways and comparative structural mediating effects were analyzed. Media and Consumer Research public data were used for empirical analysis. A total of 6,640 people who participated in sports activities were included in the study. The results demonstrated that TV and SNS device usage environments had similar effects on advertisement acceptance. While TV did not influence the pursuit of personal life, SNS device use environments affected the pursuit of personal life. SNS device use environments had a greater effect on individual psychological satisfaction than TV. Adoption had a mediating effect on the influence of media usage environments on the pursuit of personal life. The pursuit of a personal life had a significant mediating effect on the influence of media use environments on psychological stability. This study revealed no differences in the effects of new and traditional media on advertisement acceptance, while new media had a greater influence on lifestyle and psychological satisfaction.

The article is devoted to the topical problem of estimating water content in water-oil mixtures and porous media they saturate, according to low-field NMR relaxometry and dielectric spectroscopy. The aim of the research is to theoretically substantiate and experimentally validate the capability of joint interpretation of data from these methods to acquire information on the filtration-volumetric properties of drill cuttings, relaxation characteristics of oil-containing fluids, water/oil ratio in water-oil mixtures and saturated with them drill cuttings in order to control the composition of liquids produced from boreholes. The studies were carried out on samples of cuttings and oils taken from fields in the northern and Arctic regions of the West Siberian oil-and-gas province. Based on the experimental data obtained, we evaluated the water content in the water-oil mixtures, determined the main NMR parameters of the mixtures in terms of properties of the constituent oils, and specified the parameters and shapes of NMR and complex dielectric permittivity spectra. The NMR method was found to be effective in examining high-viscosity and medium-viscosity oils, while the dielectric spectroscopy method – in the study of light oils; their integration allows obtaining reliable data for all the samples under study. We also showed how the shapes of NMR and complex dielectric permittivity spectra depend on the rheological properties of oil belonging to the mixture.

This study contributes to the Sybil nodes detecting algorithm in Online Social Networks (OSNs). As major communication platforms, online social networks get significantly guarded from malicious activity. A thorough literature review identified various detection and prevention Sybil attack algorithms. Additional exploration of distinct reputation systems and their practical application led to the study’s discovery of machine learning algorithms, i.e., the KNN, Support Vector Machines, and Random Forest algorithms. The study details the data cleansing process for the employed dataset in its process for optimizing the computational demands required to train machine learning algorithms, achieved through dataset partitioning. Such a process led to explaining and analysis of conducting experiments and comparing their results. Such experiments demonstrate the algorithm’s ability to detect Sybil nodes in OSNs (100% accuracy in SVM, 99.6% in Random Forest, and 97% in KNN algorithms); thus concluding by proposing future research opportunities.

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

The etiology of Autism Spectrum Disorder (ASD) has been linked to both genetic and epigenetic factors. Among the epigenetic factors, exposure to valproic acid (VPA), an antiepileptic and mood-modulating drug, has been shown to induce characteristic traits of ASD when exposed during embryogenesis. Conversely, in animal models, Enriched Environment (EE) has demonstrated positive behavioral and neural effects, suggesting its potential as a complementary treatment to pharmacological approaches in central nervous system disorders. In this study, we utilized zebrafish to model ASD characteristics induced by VPA and hypothesized that sensory stimulation through EE could ameliorate the behavioral and neuroanatomical features associated with ASD. To test this hypothesis, we assessed social behavior, cerebellar volume, and Purkinje cell populations via histology and immunohistochemistry after exposing the fish to EE. The results revealed that zebrafish exposed to VPA exhibited social deficits, reduced cerebellar cortex volume, and a decrease in c-Fos-positive cells in the Purkinje layer. In contrast, VPA-exposed fish treated with EE showed increased socialization, augmented cerebellar cortex volume, and an elevation in c-Fos-positive Purkinje cells. These findings suggest that alterations induced by VPA may be ameliorated through EE treatment, highlighting the potential therapeutic impact of sensory stimulation in conditions related to ASD.

This paper presents the results of quantitative research examining the impacts of demographic and socioeconomic factors on community resilience to disasters. The survey was carried out utilising a questionnaire distributed and subsequently collected online from 321 participants during January 2024. The study employed an adapted version of the '5S' social resilience framework, encompassing five sub-dimensions – social structure (10 variables), social capital (9 variables), social mechanisms (17 variables), social equity and diversity (13 variables), and social belief (13 variables). This customized framework includes 62 indicators, providing a thorough assessment of community (social) disaster resilience in the research context. To explore the relationship between predictors and community (social) disaster resilience in Serbia, their attitudes towards the mentioned five sub-dimensions, as well as their engagement in preventive measures and their perception of resilience to various disasters with a particular focus on demographic and socio-economic impacts, statistical methods including t-tests, one-way ANOVA, Pearson’s correlation, and multivariate linear regression were employed. The results of the multivariate regressions across various community disaster resilience subscales indicate that age emerged as the most significant predictor for the social structure subscale. At the same time, education stood out as the primary predictor for the social capital subscale. Additionally, employment status proved to be the most influential predictor for both social mechanisms and social equity-diversity subscales, with property ownership being the key predictor for the social beliefs sub-scale. Despite being considered in the analyses, gender, marital status, income level, and number of household members did not emerge as the most significant predictors across the investigated community (social) disaster resilience subscales. The determined mean value of the community (social) disaster resilience index is M = 2.62, and the findings reveal that participants assigned the highest ratings to the social beliefs subscale (M = 2.76), while the lowest values were observed in the social structure subscale (M = 2.46). Findings can be used to create strategies and interventions aimed at enhancing the resilience of communities in Serbia by addressing the intricate interplay between demographic characteristics, socio-economic factors, and their ability to withstand, adapt to, and recover from different disasters.

Numerous researchers acknowledge that occupational pension protects employees. However, the total occupational pension is shared by employees and employers in China, which is a cost. This study aimed to explore the occupational pension on corporate social responsibility (CSR) and organizational resilience. We drew upon insights from cost-stickiness and resource-based theories to develop a model that illuminates how occupational pension affected firms’ stance toward CSR in the context of the COVID-19 pandemic and how this, in turn, has result organizational resilience. This study categorized CSR into strategic and responsive activities based on cost stickiness. We selected a total of 34,145 observations of Chinese listed companies over the period 2010-2023 as a sample to investigate whether occupational pension changes CSR strategies. The results showed that the cost pressure to contribute to occupational pension drove firms to reduce their responsive CSR and boost their strategic CSR. Moreover, strategic CSR improved organizational resilience, but responsive CSR did not. This relationship between occupational pension and CSR was significantly and negatively moderated by the minimum wage and population aging. Whereas, the relationship between CSR and organizational resilience was significantly and positively moderated by digital transformation and marketing capabilities. This study has implications for decision-making regarding high-quality firm development.

Increasingly, firms are expected to implement ESG (Environment, Social, and Governance) mandates to appeal to the global market. However, this requires overcoming practical challenges and capitalizing on emerging opportunities. This paper conducts an in-depth analysis of the ESG practices of leading Korean global firms. The study selects five firms for case studies representing industries such as electronics, automotive, steelmaking, and chemicals. It examines ESG reports, performance indicators, and corporate disclosures of these firms. The analysis reveals the adoption of industry-specific ESG strategies, highlighting how these firms tailor their approaches to address unique industry challenges while aligning with global sustainability trends. Key findings include a strong emphasis on innovative solutions to ESG challenges, the integration of ESG into core business operations, and a balanced approach to economic, social, and environmental responsibilities. This study contributes to a broader understanding of how ESG practices are implemented in various industrial contexts, particularly in the dynamic and evolving landscape of Korean global businesses. It offers valuable insights and benchmarks for global companies, underlining the importance of contextualized and industry-specific ESG strategies in achieving sustainable and ethical business practices

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

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

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

This study uses explainable artificial intelligence to analyze major predictors of poor self-rated health, dementia and their comorbidity, which include various aspects of social support. Data came from the Korean Longitudinal Study of Ageing (2016-2018), with 5527 participants aged 56 or more. The dependent variables were: (1) poor self-rated health (SRH) with 5 categories (very good, good, middle, poor, very poor); (2) dementia (no, yes); and (3) their comorbidity with 4 categories (SRH very good, good or middle, dementia no; SRH very good, good or middle, dementia yes; SRH poor or very poor, dementia no; SRH poor or very poor, dementia yes). The 49 demographic, socioeconomic and health-related predictors were included. The accuracy and area under the receiver operating characteristic curve (AUC) were compared for logistic regression and the random forest. Logistic regression and the random forest registered similar AUCs with the range of 0.80-0.87. Based on random forest variable importance, 18 out of top-20 predictors were identical for SRH, dementia and their comorbidity: previous SRH, life satisfaction - health, age, body mass index, income, chronic diseases, life satisfaction - economic, life satisfaction - overall, grandchildren alive, friendship meeting, brothers/sisters alive, class identity, children alive, social activity - friendship, education, children in weekly contact, religion and drinker. However, some variations were found among the three dependent variables, i.e., previous SRH for comorbidity (1st) and SRH (1st) compared to dementia (11th), grandchildren alive for SRH (6th) and dementia (4th) compared to comorbidity (9th), chronic diseases for comorbidity (6th) compared to SRH (10th) and dementia (10th). In terms of Shapley Additive Explanation (SHAP) values, the probability of dementia is expected to decrease by 5.57% in case a predictor grandchildren alive is included to the model. This study highlights the importance of social support for the prediction of poor self-rated health, dementia and their comorbidity. Specifically, the promotion of family support and friendship activity for elders would be vital for the prevention and management of their self-rated health and dementia.

(1) Background: The social robot interaction design is critical in determining acceptance and user experience. However, few studies have systematically discussed the current focus and future research directions of social robot interaction design from a bibliometric perspective. Therefore, in order to identify the latest research progress and evolution trajectory of research hotspots in social robot interaction design over the last decade. (2) Methods: based on 2416 papers related to social robot interaction design collected in the Web of Science (WOS) database, a comprehensive review was conducted by using bibliometrics to draw a knowledge map using VOSviewer and CiteSpace in an integrated manner. (3) Conclusions: The current research hotspots of social robot interaction design mainly focus on #1the study of human-robot relationships in social robot, #2Research on the Emotional Design of Social Robot, #3research on social robot for children's psychotherapy, #4research on companion robot for elderly rehabilitation, and #5research on educational social robot. The reference co-citation identifies the classic literature that forms the basis of the current research, which provides theoretical guidance and methods for the current research. Finally, we discuss several future research directions and challenges in this field.

Global and human development and freedoms increasingly thrive on robust and policy-oriented research and related activities. Yet, the African research landscape faces a myriad of challenges, resulting in a very unequal continent in terms of research and research capacity. The prevailing research inequities and challenges in Africa are even more pronounced in the social sciences, humanities, arts, and related fields (SSHA). Here, the strengths and impact of scholarship in SSHA fields are often overshadowed by deficits and apparent preferential investment in research in science, technology, engineering, and mathematics-related fields. In response, the African Academy of Sciences commissioned a study in 2020 to generate evidence on the SSHA research support landscape in Africa. This paper summarizes findings from the literature review, key informant interviews, a bibliometric analysis, a survey with a sample of 670 respondents from SSHA communities in Africa, and a series of focus group discussions. We highlight key messages and make recommendations focussing on lessons learnt opportunities, and priorities for intervention to enhance significant SSHA research leadership capacity strengthening and, ultimately, minimize research inequalities in Africa.

This work presents the results of an experimental socio-economic study conducted in two shanty towns of Messina as part of a systemic urban regeneration and fight against poverty program called Capacity. The study has shown that the development of a positive attitude towards the future and the confidence in others are associated with the development of the riskiest option, which is the one that can give the highest pay-off. The paper also illustrates the expected and unexpected outcomes of projects for individuals and the community, as well as the economic benefits for the public administration and the society of a strategy that reduces the reliance on social welfare measures as well as the local control exercised by organized crime.

Human behaviour was tipped as the mainstay in the control of further SARS-CoV-2 (COVID-19) spread especially after the lifting of restrictions by many countries. Countries in which restrictions were lifted soon after the first wave, had subsequent waves of the COVID-19 infections and it remains to be seen whether there will be more waves. In this paper, we formulate a deterministic model for COVID-19 incorporating dynamic non-pharmaceutical interventions, dubbed social dynamics. The model steady states are determined and their stability analysed. Numerical simulations are carried out to determine the pack of various parameters that influence the social dynamics. In South Africa, the first wave was the only wave in which the only interventions rested solely on human behavior. The model is thus fitted to COVID-19 data on the first wave in South Africa. The results presented in this paper have implications on the trajectory of the pandemic in the presence of changing social processes.

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

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

For personalized recommender systems,matrix factorization and its variants have become mainstream in collaborative filtering.However,the dot product in matrix factorization does not satisfy the triangle inequality and therefore fails to capture fine-grained information. Metric learning-based models have been shown to be better at capturing fine-grained information than matrix factorization. Nevertheless,most of these models only focus on rating data and social information, which are not sufficient for dealing with the challenges of data sparsity. In this paper,we propose a metric learning-based social recommendation model called SRMC.SRMC exploits users' co-occurrence pattern to discover their potentially similar or dissimilar users with symmetric relationships and change their relative positions to achieve better recommendations.Experiments on three public datasets show that our model is more effective than the compared models.

The research is based on the question: Can teaching/learning methodologies help to achieve the objective of Sumak Kawsay in Ecuador? a STEAM work approach was applied in technical high school students and higher education students (technological), in order to determine the level of impact in terms of project generation, following the entire process, from the generation of ideas to the linking of projects with society, The analysis was carried out in students from 15 to 22 years old in two institutions in the city of Cuenca, using the method of intentional sampling and the systematic review of scientific articles in the Scopus and Google academic databases of the last 3 years, to determine the level of impact of the prototypes pub-lished in indexed journals. The most striking aspect of the results is that of the 260 students surveyed, only 19.6% of students consider that there are STEAM teachers in the classroom, and only 56.92% of students manage to link their work with society, one of the recommended strategies being the publication of scientific articles and participation in congresses disseminating the high impact work done by students in the classroom.

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

Possible alterations of maternal immune function due to psychological stress may reflect immunoactive factor levels in breast milk. This study aimed to assess the association between maternal distress and breast milk levels of secretory IgA (SIgA), IgM, IgG, and lactoferrin (LF). We hypothesized this association is moderated by maternal social support achieved from others during lactation. The study group included 103 lactating mothers and their healthy 5-months-old infants. Maternal distress was determined based on the State Anxiety Inventory and the level of salivary cortisol. Social support was assessed using Berlin Social Support Scales. Breast milk samples were collected to test for SIgA, IgM, IgG, and LF using the ELISA method. Milk immunoactive factors were regressed against maternal anxiety, social support, salivary cortisol, and infant gestational age using the general regression model. Maternal anxiety was negatively associated with milk levels of LF (β=-0.22, p<0.05) and SIgA (β=-0.29, p<0.01), while social support was positively associated with milk IgG (β=0.25, p<0.05). Neither anxiety nor social support was related to milk IgM. No association was found between the level of maternal salivary cortisol and immunoactive factors in milk. Our results suggest that maternal psychological well-being and social support may affect milk immune properties.

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.

Globally, humans are struggling with the double threat of communicable and non-communicable diseases, which are presenting new challenges to public health. Public health problems are generally studied and addressed at primary, secondary and tertiary levels. Most effective results are seen with primary interventions. Public health is becoming more aware of the importance of environment-gene interactions in the ontology of health and disease using epigenetics. Epigenetics is the study of altered gene expression without change in base pairs. Be it physical, social, behavioral, or economic factors; they all influence quality of life and health of individuals and populations. That environments are changing the human health phenotype and these changed phenotypes are heritable is of concern for the future of the human race. Knowing the causes of non-communicable human diseases using epigenetics will contribute to the development of new policies to encourage prevention using primary public health initiatives. Research and application of epigenetics shows great promise for improving population health. Continued advances in epigenetics will enhance how we understand and address the way environments are affecting the human health phenotype. For some time, health systems have been and continue to be tertiary in nature. Epigenetic changes can provide information necessary to better understand how social determinants of health can be used to build societies focused on equitable health for all people, rather than continuing to focus on treatment of diseases in the tertiary phase that leads to health disparities. Understanding mechanisms of social determinants of disease, will allow society to evolve in a health-oriented rather than a disease-oriented world. For this reason, we must enhance and apply epigenetics (physical, social, behavioral, economic) research to policy development. We will discuss how bringing social determinants together with biology can be used as new tools for public health policy.

Copper-containing materials are attracting attention as self-desinfecting surfaces, suitable for helping healthcare settings in reducing healthcare associated infections. However, the impact of repeated exposure to disinfectants frequently used in biocleaning protocols on their antibacterial activity remains insufficiently characterized. This study aimed at evaluating the antibacterial effi-ciency of copper (positive control), a brass alloy (AB+®) and stainless steel (negative control) after repeated exposure to a quaternary ammonium compound and/or a mix of peracetic acid/hydrogen peroxide routinely used in healthcare settings. A panel of 6 antibiotic-resistant strains (clinical isolates) was selected for this assessment. After a short (5 min) exposure time, the copper and brass materials retained significantly better antibacterial efficiencies than stainless steel, whatever the bacterial strain or disinfectant treatment considered. Moreover, post-treatment with both disinfectant products, copper-containing materials still reached similar levels of antibacterial efficiency as those obtained before treatment. Antibiotic resistance mechanisms such as efflux pump overexpression did not impair the antibacterial efficiency of copper-containing materials, neither did the presence of one or several genes related to copper homeostasis/resistance. In light of those results, surfaces made out of copper and brass remain interesting tools in the fight against dissemination of antibiotic-resistant strains that might cause healthcare associated infections.

This study aims to construct simple devices to ascertain the concentrations of ammonium (NH4+) and nitrate (NO3-). The device structure comprises a visible and near-infrared absorption meas-urement room, along with an RGB (red, green, and blue) absorption measurement room, con-stituting the two measuring rooms. Both the measurement rooms are equipped with light sources and detectors configured to operate in opposed or thru-beam modes. A tiny processor is utilized for processing the measurements, with an algorithm implemented within its memory. During the algorithm development phase, ranges for measuring the quantity of nutrients were categorized using a discriminant analysis approach. Thirty percent of the soil sample data were utilized as verification data, while the remaining 70 percent served as training data. Nutrient content values from reliable measuring instruments were incorporated into all datasets. Discriminant analysis was employed to classify the amount of NH4+ into five ranges based on the test results. When tested with soil samples, the accuracy was 66.13% compared to the reference value of a reliable measuring device. Similarly, NO3- was classified into four ranges with an accuracy of 81% com-pared to the reference value of a reliable measuring device.

Anxiety in older individuals is understudied despite its prevalence. Investigating its occurrence can be challenging, yet understanding the factors influencing its recurrence is important for improved management. This study aimed to model the recurrence of anxiety symptomatology in an older population within a five-month timeframe. Data included baseline socio-demographic and general health information for older adults aged 60 years or older with at least mild depressive symptoms. A Bayesian network model explored the relationship between baseline data and recurrent anxiety symptomatology. Model evaluation employed the Area Under the Receiver Operating Characteristic Curve (AUC). The Bayesian model was also compared to three machine learning models. The model achieved an AUC of 0.821 on the test data, using a threshold of 0.367. This result surpassed both the Logistic Regression and XGBoost models, but slightly behind SGDClassifier. Key factors associated with recurrence of anxiety symptomatology were: “Not being able to stop or control worrying”; “Becoming easily annoyed or irritable”; “Trouble relaxing”; and “depressive symptomatology severity”. The model demonstrated generalisation abilities and outperformed some machine learning models while being less complex and more explainable. These findings indicate a prioritised sequence of predictors to identify individuals most likely to experience recurrent anxiety symptomatology.

The goal of newborn screening is to improve health outcomes by identifying and treating affected newborns. This manuscript provides an overview of a data tool to facilitate the longitudinal collection of health information on newborns diagnosed with a condition through NBS. The Newborn Screening Translational Research Network (NBSTRN) developed the Longitudinal Pediatric Data Resource (LPDR) to capture, store, analyze, visualize, and share genomic and phenotypic data over the lifespan of NBS identified newborns to facilitate understanding of genetic disease, and to assess the impact of early identification and treatment. NBSTRN developed a consensus-based process using clinical care experts to create, maintain, and evolve question and answer sets organized into common data elements (CDEs). The LPDR contains 24,172 core and disease-specific CDEs for 118 rare genetic diseases, and the CDEs are being made available through the NIH CDE Repository. The number of CDEs for each condition average of 2,200 with a range from 69 to 7,944. The LPDR is used by state NBS programs, clinical researchers, and community-based organizations. Case level, de-identified data sets are available for secondary research and data mining. The development of the LPDR for longitudinal data gathering, sharing, and analysis supports research and facilitates the translation of new discoveries into clinical practice.

This study aimed to determine a nutritionally adequate feeding protocol for Hippocampus hippocampus juveniles. In the experimental trial, seahorses were fed copepods from 0-7 days post-parturition (DPP) and, from 8-28 DPP, four dietary treatments: (copepods (control diet), microalgae-enriched Artemia with a DHA/EPA ratio of 2:1, microalgae-enriched Artemia with a DHA/EPA ratio of 2:1 along with 5% copepods, and with 10% copepods) were tested. Results showed that juvenile seahorses fed on copepods attained a significantly higher (P&lt;0.05) growth performance (5.1 mg d-1) than fish-fed diets with 5% and 10% copepod inclusion, (3.09 and 3.07 mg d-1, respectively), and fish-fed enriched Artemia (1.83 mg d-1) which performed poorly. Data suggests that feeding copepods during the first 7 DPP promotes maturation of the digestive tract of juvenile seahorses, and the addition of a limited amount of copepods to the diet improves H. hippocampus juvenile growth performance when compared to the use of Artemia as a single diet due to the improvement of the essential fatty acid profile in the diets.

One of the most important problems, which public health is called to face, is obesity. The World Health Organization (WHO) underlines that worldwide more than 380 million of overweight or obese children and adolescents exist. Although obesity is a multifactorial disease, excessive use of the screen seems to act in a way that affects obesity. The purpose of this systematic literature review is to study of the major problem, obesity in teenagers and its association with the hours of entertainment(referring to excessive hours of television use and viewing, video games and social media).In the present systematic literature review was carried out search for sources, through the scientific databases PubMed, ScienceDirect, and Scopus for the period from 2010 to 2022.This systematic review provides public health evidence regarding the positive association of excessive screen time and of obesity and overweight in adolescents.

Background: Dental avulsion is the most serious dentoalveolar traumas because its management requires immediate reimplantation to maintain the periodontal ligament. The success of the treatment depends largely on the appropriate storage medium that ensures the viability of the periodontal cells. The purpose of this review was to identify the most efficient media to store and transport avulsed permanent teeth, according to the viability of the periodontal ligament cells. Methods: The Scopus, Web of Science and PubMed electronically searched using the keywords “Storage media”; “Avulsed teeth”; and “Periodontal ligament”. The inclusion criteria were in vitro studies and articles published in English. The exclusion criteria were literature reviews, studies in primary teeth, studies in animals, and cell culture studies. Results: Hank’s saline solution and honey were equally effective, maintaining a cell viability rate of 98.89% and 96.43%, respectively, over a period of 3 hours. Ringer’s lactate solution maintained the viability of 906.40 viable cells/mm3 at 1 hour. Propolis maintained the viability of 285,000 cells/mm3 at 45 minutes, and the Neem extract maintained a cell viability rate of 88% at 30 minutes. Conclusions: Hank’s saline solution is the most effective storage medium for maintaining the viability of periodontal cells in avulsed teeth.

The main goal of this work is to develop a novel boundary element method (BEM) model for analyzing ultrasonic wave propaga-tion in three-temperature anisotropic viscoelastic porous media. Because of strong nonlinearity of ultrasonic wave propagation in three-temperature porous media problems, the analytical or numerical solutions to the problems under consideration are always challenging, necessitating the development of new computational techniques. As a result, we use a new BEM model to solve such problems. A time stepping procedure based on the linear multistep method is obtained after solving the discretized boundary in-tegral equation with the quadrature rule. The calculation of a double integral is required to obtain fundamental solutions, but this increases the total BEM computation time. Our proposed BEM technique is used to solve the current problem and improve the formulation efficiency. The numerical results are graphed to demonstrate the effects of viscosity and anisotropy on the nonlinear ultrasonic stress waves in three-temperature porous media. The validity, accuracy, and efficiency in the proposed methodology were demonstrated by comparing obtained results to the corresponding solution obtained from finite difference method (FDM).

Our investigations show that electrochemical corrosion of copper is faster than electrochemical corrosion of aluminium at temperatures below 100oC. Literature data analysis shows that the Al atoms diffuse faster than the Cu atoms at temperatures higher than 475oC, Al rich intermetallic compounds (IMCs) are formed faster in the Cu-Al system, and the Kirkendall plane shifts toward Al side. Electrochemical corrosion occurs due to electric current and due to diffusion. An electronic devise working time, for example, depends on initial copper cover thickness on aluminium wire, connected to the electronic devise, temperature, and volume and dislocation pipe diffusion coefficients, so copper, iron, and aluminium electrochemical corrosion rates are investigated experimentally at room temperature and at temperature 100oC. Intrinsic diffusivities ratios of copper and aluminium at different temperatures and diffusion activation energies in the Cu-Al system are calculated by proposed here methods using literature experimental data. Dislocation pipe and volume diffusion activation energies of pure iron are calculated separately by earlier proposed method using literature experimental data. Aluminium dissolved into NaCl solution as the Al3+ ions at room temperature and at temperature 100oC, iron dissolved into NaCl solution as the Fe2+ (not Fe3+) ions at room temperature and at temperature 100oC, copper dissolved into NaCl solution as the Cu+ ions at room temperature and as the Cu+ and the Cu2+ ions at temperature 100oC. It is founded experimentally that copper corrosion is higher than aluminium corrosion, and ratio of electrochemical corrosion rates, kCu/kAl>1, decreases with temperature increasing, although iron electrochemical corrosion rate doesn’t depend on temperature below 100oC. It is obvious, because melting point of iron is more higher then melting point of copper or aluminium. It is calculated that copper electrochemical corrosion rate is approximately equal to aluminium electrochemical corrosion at temperature about 300oC, so copper can dissolve into NaCl solution mostly as the Cu2+ ions at temperature about 300oC. Ratio of intrinsic diffusivities, DCu/DAl <1, increases with temperature increasing, and intrinsic diffusivity of aluminium could be approximately equal to intrinsic diffusivity of copper at temperature about 460oC.

This comprehensive review has systematically examined the use of heterogeneous solid acid catalysts in the production of biodiesel from wastewater-derived sludge by using the PRISMA methodology. The manuscript highlighted the composition and characteristics of wastewater-derived sludge, presenting both the opportunities and challenges associated with its use as a feedstock for biodiesel production. Various types of catalysts were dis-cussed, with a detailed exploration of heterogeneous solid acid catalysts, including zeolites, hetero-polyacid (HPA), mixed metal oxides, and sulphonic acid group catalysts. The advantages and limitations of these catalysts were critically analyzed, providing a balanced view of their potential in industrial applications. The application section delved into the catalytic transesterification reaction, mechanisms of biodiesel production, and the effects of catalyst loading on yield. Performance metrics such as catalytic activity, stability, recyclability, cost-effectiveness, and environ-mental impact were thoroughly evaluated, offering a clear understanding of the efficacy of these catalysts. Synthesis and characterization techniques were also reviewed, shedding light on the latest preparation methods and characterization techniques. Recent advances in catalyst development were presented, showcasing the innovative strides made in enhancing catalyst performance. The environmental and economic implications of using solid acid catalysts for bio-diesel production were assessed, emphasizing the importance of sustainability and economic viability.

Globally mangrove forests are substantially declining and a globally synthesized database of the drivers of deforestation and drivers’ interaction is scarce. Here we synthesized the key social-ecological drivers of global mangrove deforestation by reviewing about two hundred published scientific studies over the last four decades (from 1980 to 2021). Our focus was on both natural and anthropogenic drivers with gradual and abrupt impacts and their geographic ranges of effects and how these drivers interact. We also summarized the patterns of global mangrove coverage decline between 1990 and 2020 and identified the threatened mangrove species and their geographic ranges. Our consolidated studies reported a 8,600 km2 decline in the global mangrove coverage between 1990 and 2020 with the highest decline occurring in South and Southeast Asia (3870 km2). We could identify 11 threatened mangrove species, two of which are critically endangered (Sonneratia griffithii and Bruguiera hainseii). Our reviewed studies pointed to aquaculture and agriculture as the predominant driver of global mangrove deforestation though the spatial distribution of their impacts varied. Gradual climate variations, i.e. seal-level rise, long-term precipitation and temperature changes and driven coastline erosion, constitute the second major group of drivers. Our findings underline a strong interaction across natural and anthropogenic drivers with the strongest interaction between the driver groups aquaculture and agriculture and industrialization and pollution. Our results suggest prioritizing globally coordinated empirical studies linking drivers and mangrove changes and a global development of policies for mangrove conservation.

Peer-to-peer (P2P) energy trading is a new data-driven business model currently being trialed within the energy sector. Introducing P2P transactions to an essential service such as energy could have far-reaching implications for individuals and the grid. This paper raises considerations and questions from social, economic/markets and regulatory points of view, that should be understood and addressed by societies and policymakers. It does this by considering under what circumstances it is reasonable to conceptualize P2P energy trading as part of the sharing economy, and drawing parallels to the sharing economy experience in other sectors. In order to reap the full societal benefits, while avoiding considerable risks to infrastructure and individuals, a policy approach promoting dialogue and innovation is necessary. We suggest the regulatory sandbox is the most appropriate tool to achieve this and would help avoid the breakdown of trust between policymakers and platform companies observed in other sectors.

The Social-Ecological Systems (SES) framework serves as a valuable framework to explore and understand social and ecological interactions, and pathways in water governance. Yet, it lacks a robust understanding of change. We argue an analytical and methodological approach to engaging global changes in SES is critical to strengthening the scope and relevance of the SES framework. Relying on SES and resilience thinking, we propose an institutional and cognitive model of change that institutions and natural resources systems co-evolve to provide a dynamic understanding of SES that stands on three causal mechanisms: institutional complexity trap, rigidity trap, and learning processes. We illustrate how Data Cube technology could overcome current limitations and offer reliable avenues to test hypothesis about the dynamics of social-ecological systems and water security by offering to combine spatial and time data with no major technical requirements for users.

Within the field of guilt and shame, two competing perspectives have been advanced. The first, the social-adaptive perspective, proposes that guilt is an inherently adaptive emotion and shame is an inherently maladaptive emotion; thus, those interested in moral character development and psychopathology should work to increase an individual’s guilt-proneness and decrease an individual’s shame-proneness. The functionalist perspective, in contrast, argues that both guilt and shame can serve a person adaptively or maladaptively—depending on the situational appropriateness, duration, intensity, and so forth. This paper reviews the research conducted supporting both positions, critiques some issues with the most widely used guilt- and shame-proneness measure in the social-adaptive research (the TOSCA), and discusses the differences in results found when assessing guilt and shame at the state versus trait level. The conclusion drawn is that although there is broad support for the functionalist perspective across a wide variety of state and trait guilt/shame studies, the functionalist perspective does not yet have the wealth of data supporting it that has been generated by the social-adaptive perspective using the TOSCA. Thus, before a dominant perspective can be identified, researchers need to (1) do more research assessing how the social-adaptive perspective compares to the functionalist perspective at the state level, and (2) do more trait research within the functionalist perspective to compare functionalist guilt- and shame-proneness measures with the TOSCA.

For decades, the discoverability and visibility of a paper relied on the readership of the academic journal where the publication was issued. The public's increasing interest in scientific research, particularly in biomedicine, has led news media outlets to play a significant role in disseminating scientific advances. This investigation, which explores the potential impact of news media stories on the citations and altmetrics of a paper, was conducted with thoroughness and rigour. A total of 2020 open access biomedical research papers, all published in the same year, 2015, and in journals with an impact factor between 10 and 14, were investigated. The papers were split into two groups based on the sole criterion of receiving or not receiving news media coverage. Papers with news media coverage accounted for 44% of the total. They received, on average, 60% more citations, 104% more blogs, 150% more X posts, 106% more Facebook reports, 40% more Wikipedia references, 85% more videos, and 51% more Mendeley readers than papers without news media coverage. The correlation between news media outlets and increased citations and altmetrics is evident. However, the broader societal impact of news media coverage, in terms of bringing scientific matters or discoveries to the public eye, appears to be more robust when compared to the reactions of the scientific community.