Energy imports and the transition to renewable energy sources are of critical importance in the current geopolitical context, which necessitates concrete actions to tackle the energy crisis at the European Union level. The study aims to explore the impact of imported non-renewable energy resources on the EU-27 economy. It examines the correlations and causal relationships between GDP, GVA, R&D investments, and energy imports from 2000 to 2021. Data normality was assessed using the Shapiro-Wilk test, while Pearson's test identified correlations between variables. Linear and multiple regression analyses were conducted to determine the effects of changes in independent variables on dependent variables. The study found a strong association between natural gas imports and GDP, with increases in GDP leading to a more than fourfold rise in imports. Furthermore, multiple regression analysis indicated that a 1% increase in R&D investments results in a 2.21% decrease in fossil fuel imports in 91.7% of cases. This suggests that R&D investments contribute to improved efficiency and the use of renewable energy sources.

Background: Sexualized substance use (SSU) is the practice of psychotropic substance usage, before or during sexual intercourse in order to increase sexual pleasure and arousal. It has a strong association with sexually transmitted infections (STIs). The present study aimed to assess the knowledge gaps regarding SSUs among the community health mobilizers by interviewing them regarding their knowledge, attitudes, and practices through qualitative approach. Methodology: In-depth interviews (IDIs) were conducted with a total of nineteen community health mobilizers engaged in counselling of sexualized substance users. A semi-structured open-ended questionnaire with socio-demographic information and probes related to SSU was administered. Informed consent was taken from each participant prior to data collection. Results: Gender-wise distribution indicated that 47% of the community mobilizers are men, followed by transgender persons (32%), and women (21%). Responses of participants highlighted that alcohol consumption was the most observed form of SSU. The findings indicated that drug administration through injection was most common, followed by sniffing and swallowing. Sources of drug pro-curement enlisted by participants included peddlers, peer groups, sexual parties, medical and liquor stores. Only 63% of participants had fair knowledge about STIs such as HIV, viral hepatitis, syphilis, and gonorrhoea. All were familiar with the administration of naloxone injections and the locations of nearby hospitals where patients could be transported in the event of an overdose. Conclusions: The in-depth interviews among the study participants reflected substantial know-ledge gaps related to various areas associated with SSU, which highlights the need for periodic workshops and training for upgradation of existing knowledge and practices among community health mobilizers. This will help to broaden their knowledge of different types of SSUs, the latest substances of abuse, the diseases caused by high-risk sexual practices, and additional health and psychological issues associated with SSUs, which would ultimately help in better counseling and management of sexualized substance users. It may also play a crucial role in the strengthening of capacity-building systems and engagements at the community level. This study may be used as formative research by researchers and policy makers to develop study protocols for multi-centric community-based studies among community health mobilizers and sexualized substance users across the country for further validation and exploration.

The current availability of electronic health records represents an excellent research opportunity on multimorbidity, one of the most relevant public health problems nowadays. However, it also poses a methodological challenge due to the current lack of tools to access, harmonize and reuse research datasets. In FAIR4Health, a European Horizon 2020 project, a workflow to implement the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles on health datasets was developed, as well as two tools aimed at facilitating the transformation of raw datasets into FAIR ones and the preservation of data privacy. As part of this project, we conducted a multicentric retrospective observational study to apply the aforementioned FAIR implementation workflow and tools to five European health datasets for research on multimorbidity. We applied a federated frequent pattern growth association algorithm to identify the most frequent combinations of chronic diseases and their association with mortality risk. We identified several multimorbidity patterns clinically plausible and consistent with the bibliography, some of which were strongly associated with mortality. Our results show the usefulness of the solution developed in FAIR4Health to overcome the difficulties in data management and highlight the importance of implementing a FAIR data policy to accelerate responsible health research.

Biological diversity (BD) explored by the biological systematics is a complexly organized natural phenomenon and can be partitioned in several aspects defined with references to various causal factors structuring biota. These BD aspects are studied by particular research programs based on specific taxonomic theories (TT). They provide in total a framework for comprehending the structure of the biological systematics and its multi-aspect relations to other fields of biology. General principles of individualizing BD aspects and construing TT as quasi-axiomatics are briefly considered. It stressed that each TT is characterized by a specific combination of interrelated ontological and epistemological premises most adequate to the BD aspect a TT deals with. The following contemporary research programs in systematics are recognized and characterized in brief: phenetic, rational (with several subprograms), numerical, typological (with several subprograms), biosystematic, biomorphic, phylogenetic (with several subprograms), evo-devo. From a scientific pluralism perspective, all these research programs related to particular naturally defined BD aspects are of the same biological and scientific significance and no one of them can pretend to take a privileged position. They elaborate “locally” natural classifications that can be united by a kind of generalized faceted classification.

A significant part of the literature on innovative practice in medicine relates to seizing opportunities and curbing harms for patients in desperate situations. Unfortunately, the term innovation has multiple meanings and a rich rhetorical flourish that adds confusion and misunderstanding to an already difficult debate. This paper aims to enhance the current definition of innovative practice for medicine. First, we replace the term innovation with the more literal of new non-validated practice. To identify this meaning, we analyse the traditional research ethics’ distinction between research, validated practice, and innovation in the Belmont Report. Second, we propose the following explicit definition of new non-validated practice: the first or recent use of diagnostic, therapeutic or preventive interventions that introduce a significant change, with an insufficient level of evidence of safety or efficacy for regular healthcare, and with the main aim to benefit individual patients. This definition is a promising conceptual tool to inform empirical research, ethicists, and the harmonization of its regulation and legislation (e.g. right-to-try laws).

The effective dissemination and implementation of health service interventions into practice requires a range of strategic and systematic approaches. This paper applies a conceptual implementation framework to the evaluation of a hospital-wide clinical pharmacy initiative, a redesign of the discharge medication prescription pathway. The influencing factors and strategies used to overcome potential negative influences are described and assessed.

Suicidal behaviour remains difficult to predict and prevent, even for experienced mental health care professionals. The known distal risk factors for suicidal behaviour are not sufficiently specific to fully understand the complex dynamic processes that precede a suicide attempt. Real-time mobile monitoring data can be used to analyse proximal risk mechanisms within the suicidal process. At the same time smartphone-based safety planning and self-monitoring may enhance a patient’s self-management skills thereby increasing their capacity to respond to a suicidal crisis and to become more aware of crisis symptoms. The current paper describes the theoretical and conceptual rationale for the CASPAR study which applies an innovative approach to the study of suicidal processes. It uses basic science approaches to inform the implementation of an innovative suicide prevention intervention. We aim to develop and implement mobile safety plan in conjunction with real-time monitoring in order to both directly implement suicide prevention interventions and to study the ongoing dynamics of individual suicidal behaviour by applying network analysis.

Variability is the predisposition of phenomena to assume different values over time. Variability is higher when the differences of cases from each other are larger or diverge from a specific value, such as arithmetic mean. This study focuses on the variability of research topics within and between research fields to explain, whenever possible, how the variability shapes the structure and dynamics of technological trajectories. Analysis of variability here applies the entropy and variance decomposition on main research fields in quantum technologies. Empirical evidence shows that variability in research topics is inversely proportional to the age of research fields. Inductive implications are that higher variability in research topics of recent scientific fields is due to uncertain dynamics that generates a heterogeneity of different technological trajectories some of them can growth and develop towards fruitful directions others can be dismissed. Hence the variability seems to be one of the drivers that shapes technological evolution and can provide policy and managerial implications to improve the scientific and technological forecasting that may support appropriate decisions of R&D investments towards promising research fields and technologies.

A capacity to reflect on experience and learn through it (reflective and reflexive practice) is deemed an essential part of ethical practice and research. Challenging traditional research approaches this arts-based, inter-disciplinary, Ph.D. project explores artistic practice as a research methodology, and how learning through experiences of ‘making’ things may enhance and amplify our understanding of the more affective aspects of human situations and experience. Grounded in the author’s artistic practice and learning through experiences of ‘making’, the author assembles and adapts frames from psychoanalysis, art (psycho)therapy, and the arts with/through which to observe and document their experience of an organisational situation. Describing the development of their method in three phases, analysis takes place through returning to revisit and rework artistic material produced, and engaging in conversation with the emergent material and others in response. Results take the form of artworks and artistic projects, including documentation of process. Emergent threads draw attention to the speculative, entangled, and affective nature of the research process, the reflexivity generated through moving and handling material, and the reflexive work of undergoing, foregrounding an ethics of responsibility, attention, and care for/of the body. As a space for imaginative encounter and performative enactment, and a site for reflexivity through which one may be pressed to notice and feel more acutely, the author argues that the research value resides in the capacity of this method to embrace complex relationalities, and engage our affective, ethical sensibilities in ways that may not emerge through more traditional approaches to reflective/reflexive practice(s). This has implications for both art therapy practice and research, amplifying the learning opportunities afforded by moving, modifying, and assembling things differently, the embodied ‘work’ of art as a method of enquiry, the cultural sensitivity of documentary fragments captured in/through various media and voices, and the value of collaborative endeavours where meaning is co-constructed in conversation.

Coronavirus disease 2019 (COVID-19) affected not only individuals but also families. The purpose of this study was to clarify the temporal changes in the impact of the COVID-19 pandemic on entire families with older adults susceptible to infection living on small islands in Japan over the duration of the pandemic. Family ethnographic research was conducted from 2021 to 2023, using the Concentric Sphere Family Environment Theory as the theoretical framework. Formal interviews were conducted with 20 families. In addition, data from informal interviews, participant observation and other sources were compiled into field notes. All data on the impact on the entire family were extracted and content analysis was conducted. Five categories and a total of 85 subcategories were extracted. The results show that COVID-19 exerted not only negative but also positive impacts on the entire family, and their temporal changes are clarified. The impact on families is believed to have been influenced by the family external environment, such as increases and decreases of infection cases or events that occurred outside the family. The knowledge acquired from these studies will help healthcare professionals in providing appropriate family support.

Revealing the underlying pathomechanisms of neurological and psychiatric disorders, searching for new biomarkers, and developing novel therapeutics all require translational research. In vivo and in vitro disease models have been instrumental in casting light on complex polygenic, multifactorial, and heterogeneous disease mechanisms. In the most recent years, advanced preclinical models have revealed the intriguing interaction of sex/gender and aging with the pathogenesis and clinical manifestations of psychiatric and neurological diseases. However, despite these advancements, there is still a great deal of work to be done to fully comprehend the underlying mechanisms of these diseases and to develop treatments that can significantly improve the lives of those who suffer from them. The current challenge in the field of neurological and psychiatric diseases is to develop disease-modifying, effective treatments for these complex and long-lasting debilitating conditions with a high burden of disease.The first edition of the research topic ‘Emerging Translational Research in Neurological and Psychiatric Diseases: From In Vitro to In Vivo Models’ reinforces translational research playing a critical role in bridging the gap between basic research and clinical applications. Also, it provides a platform for researchers to share their findings and advancements in translational research in this field. This new collection gathers 25 papers offering insights into the latest advancements in translational research and potential new avenues for treatments. These papers cover various topics, including the development of new preclinical models, the use of in vitro and in vivo methods, and the application of qualitative and quantitative research methods.

The purpose of this work is to describe and explain the characteristics of pedagogy as a science of education, as an object, concepts and research method. The methodology assumed was the review of the history of pedagogy, especially the classics of pedagogy, those who built it with their experiences in laboratory schools. Here are listed the main concepts of pedagogy, its laws and principles; she establishes the opposition that exists between teaching-learning and education as formation of the personality; she also delimits the fields of the pedagogical method, of didactics or teaching-learning, and the methodology of educational labor that organizes the process and the educational context, the regime and the lifestyle, such as those experienced in the "colonies" or "communes" of children and adolescents, organized and directed by Neill and Makarenko. Since the present article does not derive from a primary source or from field work, as an empirical or experimental research, the results constitute the content of the article, as conclusions.

Underpinned by the new world Kirkpatrick model and in the context of a community-based, sport psychology program (My Strengths Training for Life™) for young people experiencing homelessness, this process evaluation investigated: (1) young peoples’ reactions (program and facilitator evaluation, enjoyment, attendance, and engagement) to and learning (mental skills and transfer intention), (2) the relationship between reaction and learning variables, and (3) the mediators underpinning this relationship. 301 young people living in a West Midlands housing service completed questionnaires on demographics, reaction and learning variables. Higher levels of program engagement were positively associated with more favorable reactions to the program. Enjoyment positively predicted learning outcomes, which was mediated by transfer intention. Recommendations are made for: (1) a balance between rigor and flexibility for evaluation methods with disadvantaged youth, (2) including engagement as well as attendance for indicators of meaningful program participation, (3) measuring program experiences (e.g., enjoyment) to understand program effectiveness, and (4) providing opportunities for skill transfer during and after program participation. Findings have implications for researchers, program commissioners, and policy makers working designing and evaluating programs in community-based settings.

Background: Media coverage of Lyme disease (LD) has led to an increase in consultations for presumed LD in Europe. However, LD is confirmed in only 10-20% of patients, with a significant number remaining in a diagnostic dead-end. Objectives: To reach a deeper understanding of how patients themselves contribute to the diagnostic process. To describe the genesis of the LD hypothesis in care pathways. Methods: In 2019, 30 patients from a prospective cohort consulting in the infectious diseases department at University Hospital in Marseille for presumed LD were recruited for semi-structured interviews. The inclusion criteria were : suffering from subjective symptoms for 6 months, no clinical or paraclinical argument suggesting current LD. The patients’ medical trajectories were collected using a biographical approach. Results: The diagnosis of Lyme disease was primarily triggered by identification with personal testimonies found on the internet. Most of patients were leading their own diagnostic investigation. The majority of participants were convinced they had LD despite the lack of medical evidence and the scepticism of their referring GP. Conclusion: GPs should first systematically explore patients’ etiologic representations in order to improve adherence to the diagnosis especially in the management of medically unexplained symptoms. Long COVID-19 syndrome challenge offers an opportunity to promote active patient involvement in diagnosis.

The ability to self-direct a research program determines graduate degree completion. Yet, research on incompletion of graduate physics programs assume students’ present level of self-direction adequate and neglects to recognize a lack of self-directed learning as key. One theoretical mathematical physicist focused on changing this challenge of physics graduate education by promoting self-directed learning through the type research flow that has been found to bring the greatest satisfaction to researchers with respect to their insights. This he provided through his space, time, open mindedness and theoretical contributions with his students and in collaboration with his colleagues. A self-directed learner himself, David J. Rowe developed methods of mentoring for encouraging physics graduate students to recognize symmetry as valuable in identifying solutions to problems quickly—helping these students take the lead in finding insightful resolutions to complex, multidimensional, mathematical physics uncertainties. How Rowe set about supporting self-directed learning in his graduate physics education interactions will be examined with the use of narrative research to interpret the texts and conversations with the author he made available. His techniques will be presented and recommendations made regarding how Rowe’s work in this regard can be modeled to improve self-direction in STEM graduate education.

This article identifies promising research areas on the PETROLEUM SCIENCE topic via bibliometric analysis of the 2018-2021 publications in the highly cited Journal of Petroleum Science and Engineering, which is included in the Journal Citation Reports Section: ENERGY & FUELS — Q2 Quartile, ENGINEERING, PETROLEUM — Q1 Quartile. Bibliometric metadata from Web of Science were used for 866 articles in 2018, 1,142 — in 2019, 1,138 — in 2020, and 1,832 in 2021. The clustering of articles was performed using the texts of the Title, Abstract, Keywords, and Keywords Plus fields. The demo version of the Lingo3G algorithm was used. For the two major clusters, the most promising research topics were determined by comparing the titles of the 350 most cited and 350 least cited articles for each year. The hypothesis that low-cited papers often have the same subject matter as high-cited papers of previous years is discussed.

Given the increasing public interest in how ingredients are processed and the growing demand for organic food products, it is critical to understand consumers’ expectations about the process-related quality of organic products. Consumers perceive organic food to be nutritious, healthy and either natural or less processed, as they are afraid of the loss of nutrients and other natural properties of the food products. However, emerging food processing technologies might generate healthy and safe food options with nutritional quality properties. Simplified communication schemes might help to overcome this barrier. The main objective of this paper is to propose a working definition of "careful processing" for organic products and test its consistency while being used in scoring different processing methods by consumers. Results show that the proposed definition allows to consistently rate alternative processing methods. Consumers tend to score novel processing methods such as pulsed electric fields and microwave as less careful, supporting the idea that organic consumers want the least man-made interference with their food products. Results show that a simple but effective definition of careful processing may help consumers to distinguish further organic food products from conventional ones, no matter which communication scheme is used.

Abstract Traditional plants are known to contain a wide array of secondary metabolites with important biological activity, including anticancer activity. One of such metabolites is saponin; a steroidal or triterpenoid glycoside that is distinguished by its soap forming nature. Different saponins have been characterized and purified so far, and are gaining attention in cancer chemotherapy. Saponins possess incredible structural diversity which has been linked to their activity. They have been implicated in cancer chemoprevention and chemotherapy. Several studies have reported the role of saponins in cancer and their mechanism of actions including cell cycle arrest, antioxidant, cellular invasion inhibition, induction of apoptosis and autophagy. Despite the extensive research and significant anticancer effect of saponins there are no known FDA approved saponin based anticancer drugs due to a number of limitations including toxicities and drug likeness properties. Recent studies have explored options such as structural optimization, combination therapy and drug delivery systems to design saponins with increased efficacy and decreased toxicities. This review discussed the current knowledge on different saponins, their anticancer activity, mechanism of action as well as the current promising research on saponins within the last two decades and recommendations for future studies.

Tourism is the main economic sector in the Balearic Islands (Spain) and hotel housekeepers (HHs) are a large occupational group, in which stress is becoming a major issue. This study aims at exploring in-depth factors perceived as stressors by HHs and key-informants, and their effects on work-life balance (WLB). A qualitative design with phenomenological approach was used, conducting six focus groups with 34 HHs and 10 individual interviews with key-informants. Results were analyzed adopting the job demands-resources model and a gender perspective. High demands –e.g work overload, time pressure, physical burden...-, lack of enough resources and little control –derived from role conflict, unexpected events...- were the most important factors explaining HHs’ stress. Additionally, this imbalance was perceived as leading to health problems –mainly musculoskeletal disorders-. Working schedule was mentioned as a facilitator to WLB, whereas an imbalance between job demands and resources led to work-home conflict –preventing them from enjoying leisure time-. Multiple roles at work and at home increased their stress. HHs experienced their job as invisible and unrecognised. Regarding practical implications, our recommendations for hotel organization include reducing workload and increasing resources, which would improve the job demands-resource balance, diminish negative mental and physical outcomes and improve WLB.

This paper summarizes over a decade of collaborative eco-archaeological research along the central coast of California involving researchers from the University of California, Berkeley, tribal citizens from the Amah Mutsun Tribal Band, and California Department of Parks and Recreation archaeologists. Our research employs remote sensing methods to document and assess cultural resources threatened by coastal erosion and geophysical methods to identify archaeological deposits, minimize impacts on sensitive cultural resources, and provide tribal and state collaborators with a suite of data to consider before proceeding with any form of invasive archaeological excavation. Our case study of recent eco-archaeological research developed to define the historical biogeography of threatened and endangered anadromous salmonids demonstrates how remote sensing technologies help identify dense archaeological deposits, remove barriers, and create bridges through equitable and inclusive research practices between archaeologists and the Amah Mutsun Tribal Band. These experiences have resulted in the incorporation of remote sensing techniques as a central approach of the Amah Mutsun Tribal Band when conducting archaeology in their traditional territories.

During the last years, significant initiatives have been launched for the dissemination of Open Access as part of the Open Science movement. Nevertheless, the other major pillars of Open Science such as Open Research Data (ORD) and Open Peer Review (OPR) are still in an early stage of development among the communities of researchers and stakeholders. The present study sought to unveil the perceptions of a medical and health sciences community about these issues. Through the investigation of researchers’ attitude, valuable conclusions can be drawn, especially in the field of medicine and health sciences, where an explosive growth of scientific publishing exists. A quantitative survey was conducted based on a structured questionnaire, with 51.8% response rate (215 responses out of 415 electronic invitations). The participants in the survey agreed with the ORD principles However they ignored basic terms like FAIR (Findable, Accessible, Interoperable and Reusable) and appeared incentive to permit the exploitation of their data. Regarding OPR, participants expressed their agreement, implying their interest for a trustworthy evaluation system. Conclusively, researchers urge to receive proper training for both ORD principles and OPR processes which combined with a reformed evaluation system will enable them to take full advantage of the opportunities that arise from the new scholar publishing and communication landscape.

Acknowledging the diverse perceptions about science-religion relationships among learners who come from various religious environments may increase learners’ willingness to learn about evolution. This study is based on a zoology course designed for in-service teachers, which aimed to provide basic scientific knowledge about evolution using the Religious Cultural Competence in Evolution Education framework. The study explores whether learners who were resistant to evolution modify their attitudes and willingness to learn about it, and whether they develop respect toward learners who hold contradicting views. Using qualitative methods, the findings indicate that using the Religious Cultural Competence in Evolution Education framework increased some formerly "resistant" learners’ willingness to learn about evolution and include it in their own teaching, albeit in varying degrees and with various reservations. The learners appreciated the freedom to express their challenges concerning evolution learning or teaching and became more willing to respect opposing perspectives, even though not all the religious learners accepted evolution as an explanation for the development of organisms. This study has international implications for bridging the gap between science and religion, thus reducing resistance to learning and teaching about evolution.

The IRRESISTIBLE Project (FP7, Grant 612367) had the aim of involving teachers, students and the public in the discussion on Responsible Research and Innovation (RRI), promoting both the construction of knowledge on cutting-edge (and controversial) research topics and the discussion about the criteria that these research/innovation processes should respect in order to be considered as responsible. These criteria also represent a strong contribution to a more sustainable future for all. This quantitative research evaluates the impact of IRRESISTIBLE’s student-curated exhibitions – about the RRI dimensions of cutting-edge research topics (socio-scientific issues) – on students’ perceptions regarding their scientific competences and the science classes. A pre and post-questionnaire was developed, validated and applied to students from 10 countries. The overall results of the statistical analysis indicate that students improved their perceptions regarding their competences for developing exhibitions in science classes as a way of creating awareness on topics relating science-technology-society. This activity reinforced students’ perceptions that in science classes they: a) discuss current issues and how they impact their lives; b) develop socially and relevant projects; and c) learn how to influence other citizens’ decisions about social issues related to science, technology and environment with the aim of assuring a more sustainable future.

Postgraduate research is a massive stumbling block to students who had never had an opportunity of exposure to research methods. A study conducted by the researcher (Costa, 2018) revealed challenges in postgraduate supervision—one of these challenges was lack of exposure to research language by students. Qualitative research and its complexities due to a variety of approaches including rigour determination pose a plethora of challenges to novice researchers. This document presents C.O.S.T.A model as a tool suitable for use by academics and students, with a panoramic view of steps to be taken first to understand foundational concepts and the language of research and secondly to make informed choices on the research methods and design strategy options available for the prospective researcher. Conclusions drawn on the reliability of the model are based on empirical evidence of application of the model observed over a period of 12 months, with some students testifying to have passed their research projects satisfactorily at their respective leading universities in South Africa. Secondary research also provides voluminous sources of success of similar research supervision programmes both in South Africa and abroad.

The Automatic Dependent Surveillance-Broadcast (ADS-B) protocol stands as a cornerstone in modern aviation surveillance and Aircraft Traffic Control systems, integral to the NextGen project initiated by the US Department of Federal Aviation Administration (FAA) in 2005. ADS-B utilizes data links to autonomously broadcast Aircraft navigational and identification information to augment air transportation system capacity and safety. However, concerns regarding the protocol's security persist, particularly as its adoption expands. The unencrypted nature of transmitted aircraft data and the absence of robust authentication mechanisms render the protocol susceptible to exploitation by malicious actors. In this study, we comprehensively reviewed existing research in the field, identifying a crucial gap necessitating a holistic survey. Prior surveys have predominantly focused on specific aspects, such as vulnerabilities, attacks, or critiques of existing solutions. Our survey addresses this gap by thoroughly exploring the aviation system, providing readers with a nuanced understanding of ADS-B security. Utilizing a detailed SWOT analysis diagram, our paper delves into the vulnerabilities inherent in the ADS-B protocol outlines potential threats and scrutinizes various attack scenarios. We systematically categorize and analyze existing security solutions, considering cost-effectiveness, scalability, implementation complexity, and coverage against diverse attack vectors. Furthermore, we critically evaluate these solutions, elucidate ADS-B security requirements, discuss current challenges, and propose future research directions. This survey serves as a comprehensive resource for researchers and practitioners alike, shedding light on the multifaceted landscape of ADS-B security and paving the way for enhanced aviation system resilience in the face of evolving cybersecurity threats.

This study examines the practicality and limitations of using a FANUC CRX-10 iA/l collaborative robot to assemble a product component, highlighting the trade-offs between increased roboisation and reduced manual intervention. Through a detailed case study in the i-Labs laboratory, critical factors affecting precision assembly such as station layout, tooling design and robot programming are discussed. The findings highlight the benefits of robots for non-stop operation, freeing up human operators for higher value tasks despite longer cycle times. In addition, the paper advocates further research into reliable gripping of small components, a current challenge for robotics. The work contributes to open science by sharing partial results and methods that could inform future problem solving in robotic assembly.

Abstract Background: Cluster randomized controlled trials are increasingly becoming popular in public health research interventions and health services research in primary health care design and use in low and middle-income countries. However, the majority of researchers in these trials did not account correctly for the effect of confounders and clustering in the design and analysis stages. Objectives: This article aimed to review the main implications of implementing a cluster randomized controlled trials design in public health research and emphasize the practical application of proper analytical methods and the performance of different statistical models. Methods: The practical application of various analytical methods is validated via the utilization of experimental data from a public health research case study. This article also demonstrated the performance of hierarchical models and made comparisons in terms of empirically precise effect size estimates. Results: Three hierarchical statistical models were provided with highly varied effect sizes during the analysis of the intervention effect on outcome, such as model 1 (AOR: 14.32; 95% CI: 3.75–54.68), model 2 (ARR: 3.52; 95% CI: 2.16–5.77), and model 3 (ARR: 4.79; 95% CI: 2.69–5.52).Conclusion: Inaccurate results and potentially misleading conclusions can arise from improper cluster randomized controlled trial designs and analyses. This article has shown that real-world data can be adjusted for the effects of confounders and clustering, and we advocate for the routine use of suitable design and analytical methods. This article concludes that researchers should be careful when selecting hierarchical models to analyze cluster randomized controlled trials.

The Food Boost Challenge (FBC) was developed using a participatory action research approach to enhance healthy eating behaviors, here vegetable and fruit products (V&F-products) among adolescents, particularly those with lower education levels. FBC is a quadruple helix innovation process, involving adolescents, (peer)researchers, and food system partners of non-governmental and commercial organizations. In 2021-2022, 34 partners provided both cash and in-kind contributions to join the FBC-community. Phase 1 involved 200 students identifying barriers and drivers for consumption of F&V-products among 1000 pre-vocational adolescents, aged 12-20 years. In phase 2, student teams submitted innovative ideas, resulting in 25 concepts fitting into ≥1 of 4 routes: I) innovative technology for a healthy diet, II) new food products/concepts for adolescents, III) hotspots improving F&V-product experience, and IV) new routes to market. In phase 3 consortia of adolescents, students and partners were formed to develop 10 selected concepts into prototypes, and phase 4 offered teams a national platform. Results show FBC resonates with all stakeholders, generating valuable insights to increase F&V-intake. Prototypes in all 4 routes have been developed, with some already in the implementation stage. Additionally, other regions in the Netherlands have adopted the FBC approach. Overall, FBC is an approach that transforms ideas into actionable measures and shows potential to be adapted to promote various healthy eating behaviors among school students.

Blood gas analysis plays a central role in modern medicine. Advances in technology have expanded the range of available parameters and increased the complexity of their interpretation. By applying user-centered design principles, it is possible to reduce the cognitive load associated with interpreting blood gas analysis. In this international, multicenter study, we explored anesthesiologists' perspectives on Visual Blood, a novel visualization technique for presenting blood gas analysis results. We conducted interviews with participants following two computer-based simulation studies: the first utilizing Virtual Reality (VR) (50 participants) and the second without VR (70 participants). Employing the template approach, we identified key themes in the interview responses and formulated six statements, which were rated using Likert scales: from 1 (strongly disagree) to 5 (strongly agree) in an online questionnaire. The most frequently mentioned theme was the positive usability features of Visual Blood. The online survey revealed that participants found Visual Blood to be an intuitive method for interpreting blood gas analysis (median 4, IQR 4-4, p<0.001). Participants noted that minimal training was required to effectively learn how to interpret Visual Blood (median 4, IQR 4-4, p<0.001). However, adjustments are necessary to reduce visual overload (median 4, IQR 2-4, p<0.001). Overall, Visual Blood received a favorable response. The strengths and weaknesses derived from these data will help optimize future versions of Visual Blood to improve the presentation of blood gas analysis results.

This paper focuses on quantifying the economic and financial viability of NB-IoT and LoRaWAN technologies, two low-power wide-area network (LPWAN) technologies with unique characteristics that make them suitable for IoT applications. The purpose of the study is to propose an artefact for performing life cycle cost analysis and demonstrate its application to these technologies. The methodology uses pragmatic computational tools to facilitate the analysis and considers all relevant economic and financial factors, such as operating costs, equipment costs, and revenue potential. The main finding of the study is that NB-IoT and LoRaWAN technologies have different cost structures and revenue potentials, which may affect their economic and financial viability for different IoT applications. Ultimately, the study concludes that a comprehensive life cycle cost analysis is critical to making informed decisions about technology adoption, and that the proposed methodology can be applied to other IoT technologies to gain insight into their economic and financial viability.

(1) Background: Artificial intelligence (AI) has existed in some form for decades, but recent rapid advances in a subset called machine learning (ML) — and more specifically deep learning (DL), a neural network-based approach — have made headlines for the potential to revolutionize and automate multiple large sectors of society, including scientific research and the healthcare field. Furthermore, large language models (LLMs) — which are built on DL — could lead to a more seamless, natural interaction between humans and computers. (2) Methods: We reviewed numerous publications on this subject from recent years. (3) Results: We found these studies collectively show that AI is positively disrupting both biomedical research and medical practice, such as optical imaging in surgery guidance. (4) Conclusions: However, we recommend caution in over-reliance on AI in the laboratory or the clinic due to anticipated risks and current limitations.

Accurately predicting the power of solar power generation can greatly reduce the impact of the randomness and volatility of power generation on the stability of the power grid system, which is beneficial for the balanced operation and optimized dispatch of the power grid system, and reduces operating costs. Solar PV power generation depends on weather conditions, which are prone to large fluctuations under different weather conditions. Its power generation is characterized by randomness, volatility and intermittency. Recently, the demand for further investigation and effective use on the uncertainty of short-term solar PV power generation prediction has been getting increasing attention in many application of renewable energy sources. In order to improve the predictive accuracy of output power of solar PV power generation and develop a precise predictive model, the authors worked predictive algorithms for the output power of a solar PV power generation system. Moreover, since short-term solar PV power forecasting is one of the important aspects for optimizing the operation and control of renewable energy systems and electricity markets, this review focuses on the predictive models of solar PV power generation, which can be verified in the daily planning and operation of a smart grid system. In addition, the predictive methods in the reviewed literature are classified according to the input data source used for accurate predictive models, and the case studies and examples proposed are analyzed in detail. The contributions, advantages and disadvantages of the predictive probabilistic methods are compared. Finally, the future studies of short-term solar PV power forecasting is proposed.

Analysing and understanding donor behaviour in Non-profit Organisations (NPOs) is challenging due to the lack of human and technical resources. Machine learning (ML) techniques can analyse and understand donor behaviour at a certain level; however, it remains to be seen how to build and design an Artificial Intelligence enabled Decision Support System (AI-enabled DSS) to analyse donor behaviour. Thus, this paper proposes an AI-enabled DSS conceptual design to analyse donor behaviour in NPOs. A conceptual design is created following a Design Science Research approach to evaluate an AI-enabled DSS's initial DPs and features to analyse donor behaviour in NPOs. The evaluation process of the conceptual design applied formative assessment through conducting interviews with stakeholders from NPOs. The interviews were conducted using the Appreciative Inquiry framework to facilitate the process of interviews. The results of analysis based on the interviews provide insightful information not only about the proposed conceptual design for an AI-enabled DSS, but also about what is required to analyse donor behaviour NPOs using DSS. Evaluating the conceptual design results recommend efficiency, effectiveness, flexibility, and useability in the requirements of the AI-enabled DSS. This research contributes to the design knowledge base of AI-enabled DSS for analysing donor behaviour in NPOs. Future research will combine theoretical components to introduce a practical AI-enabled DSS for analysing donor behaviour in NPOs. This research is limited to such analysis on donors who donate money or volunteer time for NPOs.

Education is one of the most important tools available to policymakers and non-governmental bodies to promote a change in the behavior of society and to address the climate crisis, in line with the 4^th and 13^th Sustainable Development Goals of the United Nations 2030 Agenda. Project-based learning (PBL) addresses real and global challenges and allows the academic and professional formation of students. As part of the reflection stage of the educational action research method using the Business Canvas Model (BMC), pedagogic deficiencies were identified in the PBL and a didactic proposal was elaborated to emulate the interaction of students with the ecosystems of society. A prototype for improving the management of organic manures as soil amendments was initially developed, to provide the students with a quick start on the first steps of the proposed project. In the 10 sessions designed for the PBL (Make it happen!), the students elaborate a more sophisticated artifact in response to the demands of potential clients, as per the outcomes of the primary market research (5^th session). Active teaching methods and tools, such as a modified template of the BMC with the Rumsfeld’s matrix, aid the metacognition of students and their competences development. In a double session of the PBL, the primary market research is organized with key stakeholders of the agroindustry to enquire about the feasibility of the implementation of the technological solution and the logistics at farm level. Finally, the evaluation relies on the suitability of the upgraded prototype to respond customers’ demands.

Background: Monitoring of antibiotic prescription practices in hospitals is essential to assess and facilitate appropriate use. This is relevant to halt the progression of antimicrobial resistance. Methods: Assessment of antibiotic prescribing patterns and completeness of antibiotic prescriptions among out-patients in 2021 was conducted at the University Hospital of Kwame Nkrumah University of Science and Technology in the Ashanti region of Ghana. We reviewed electronic medical records (EMR) of 49,660 patients who had 110,280 encounters in the year. Results: The patient encounters yielded 350,149 prescriptions. Every month, 33-36% of patient encounters resulted in antibiotic prescription, higher than the World Health Organization’s (WHO) recommended optimum of 27%. Almost half of the antibiotics prescribed belonged to WHO’s Watch group. Amoxicillin-clavulanic acid (50%), azithromycin (29%), ciprofloxacin (28%), metronidazole (21%), and cefuroxime (20%) were the most prescribed antibiotics. Antibiotic prescribing parameters (indication, name of drug, duration, dose, route and frequency) were documented in almost all prescriptions. Conclusions: Extending antimicrobial stewardship to the out-patient settings by developing standard treatment guidelines, an out-patient specific drug formulary and antibiograms can promote rational antibiotic use at the hospital. The EMR system of the hospital is a valuable tool for monitoring prescriptions that can be leveraged for future audits.

In this review, the potential of an emerging field of interdisciplinary climate research, that is the Coastal Boulder Deposits (CBDs) as natural archives for intense storms, is explored with particular reference to the Mediterranean region. First, the identification of the pertinent scientific articles was performed by using Web of Science (WoS) engine. Thus, the selected studies have been analysed to feature CBDs produced and/or activated during the last half century. Then, the meteorological events responsible to the literature reported cases were analysed in some details using the web archives of the Globo-Bolam-Moloch model cascade. The study of synoptical and local characteristics of the storms involved in the documented cases of boulder production/activation proved useful to assess the suitability of selected sites as geomorphological storm proxies. It is argued that a close and fruitful collaboration involving several scientific disciplines is required to develop this climate research field.

We live in a complex world characterised by complex people, complex times, and complex social, technological, and ecological environments. There is clear evidence that governments are failing at most public matters. The recent COVID-19 pandemic is a high example of global governance failure both at preventing such pandemics and managing the COVID-19 pandemic. It is time that all of us take responsibility and look into ways of collaboratively improving the governance of public matters, our matters. While there are many reasons for government failures, we believe the lack of information availability is a fundamental reason that limits the government’s ability to act smartly and allows the lack of transparency to creep into policy and action leading to corruption and failure. To this end, this paper introduces the concept of deep journalism, a data-driven deep learning-based approach for discovering multi-perspective parameters related to a topic of interest. We build three datasets (a newspaper, a technology magazine, and a Web of Science dataset) and discover the academic, industrial, public, governance, and political parameters for the transportation sector as a case study to introduce deep journalism and our tool DeepJournal (Version 1.0) that implements our proposed approach. We elaborate on 89 transportation parameters and hundreds of dimensions reviewing 400 technical, academic, and news articles. The findings related to the multi-perspective view of transportation reported in this paper show that there are many important problems seen by the public that industry and academia seem to not place their focus on. On the other hand, academia produces much broader and deeper knowledge on the subject such as a wide range of pollutions affecting the people and planet do not get to reach the public eye. Our deep journalism approach could find the gaps and highlight them to the public and other stakeholders.

Every day around 93% of children under the age of 15 (1.8 billion children) breathe outdoor air that is so polluted it puts their health and development at serious risk. Due to the pandemic, however, ventilation of buildings using outdoor air has become an important safety technique to prevent the spread of COVID-19. With the mounting ev-idence suggesting that air pollution is impactful to human health and educational out-comes, this contradictory guidance may be problematic in schools with higher air pol-lution levels, but keeping kids COVID-19 free and in school to receive their education is now more pressing than ever. To understand if all schools in an urban area are ex-posed to similar outdoor air quality and if school infrastructure protects children equally indoors, we installed research grade sensors to observe PM2.5 concentrations in indoor and outdoor settings to understand how unequal exposure to indoor and out-door air pollution impacts indoor air quality among high- and low-income schools in Salt Lake City, Utah. Based on this approach, we found that during atmospheric inver-sions and dust events, there was a lag ranging between 35 to 73 minutes for the out-door PM2.5 concentrations to follow a similar temporal pattern as the indoor PM2.5. This lag has policy and health implications and may help to explain the rising concerns re-garding reduced educational outcomes related to air pollution in urban areas. These data and resulting analysis show that poor air quality may impact school settings, and the potential implications with respect to environmental inequality.

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.

Leishmania parasites are a group of kinetoplastid pathogens that cause a variety of clinical forms while maintaining cell communication by secreting extracellular vesicles. Emerging technologies have been adapted for the studies of Leishmania-host-cell interactions to enable broad scale analysis of parasite extracellular vesicles. Leishmania extracellular vesicles (LEVS) are naturally released spheroidal nanoparticles of polydispersed suspensions surrounded by a lipid layer of membrane. Although LEVs have increasingly gained in importance, much is still unexplained, including bioavailability and function in the complex molecular mechanisms of pathogenesis. Considering the importance of LEVs in the parasite-host interaction and in the parasite-parasite relationships emerged during evolution, the current review aims at giving an overview of Leishmania summarizing knowledge and formulating guidelines for LEVs research. In the end, we report, direct methods for specific isolation of LEVs from promastigotes and amastigotes culture supernatant suitable for a range of different downstream applications increasing the compatibility and reproducibility to establish optimal and comparable isolation conditions and full LEVs characterization, and crucial immunomodulatory events triggered by this important group of parasites.

The digital transformation of healthcare is advancing, leading to an increasing availability of clinical data for research. Perioperative big data initiatives were established to monitor treatment quality and benchmark outcomes. However, big data analyzes have long exceeded the status of pure quality surveillance instruments. Large retrospective studies nowadays often represent the first approach to new questions in clinical research and pave the way for more expensive and resource intensive prospective trials. As a consequence, utilization of big data in acute pain and regional anesthesia research considerably increased over the last decade. Multicentric clinical registries and administrative databases (e.g., healthcare claims databases) have collected millions of cases until today, on which basis several important research questions were approached. In acute pain research, big data was used to assess postoperative pain outcomes, opioid utilization, and the efficiency of multimodal pain management strategies. In regional anesthesia, adverse events and potential benefits of regional anesthesia on postoperative morbidity and mortality were evaluated. This article provides a narrative review on the growing importance of big data for research in acute postoperative pain and regional anesthesia.

Cities’ delineation remains a hot topic of debate in a time where comparisons between cities are becoming increasingly based on different issues that address various scales of interventions and thus different concepts of cities. Aiming to compare cities and their insertion into globalization, we suggest that the “urban field of influence” is the best way to approach cities for this specific perspective. However, after reviewing the different existing possible concepts, we replace this concept with four different approaches proposed by Pumain et al. (1992): political entities, morphological agglomerations, functional urban areas and conurbations/Mega city regions. We discuss the top-down and bottom-up existing initiatives launched at the world scale and then use a mixed top-down and bottom-up approach to propose a new delineation of a large urban region (LUR), denoting a concept close to the conurbation or Mega city-region concept. The compositions of these LURs are published as an initial incomplete framework, suggesting the need for further critical comments and contributions to improve them.

Combined awareness about the power and limitations of bioinformatics and molecular biology enables advanced research based on high-throughput data. Despite an increasing demand for scientists with a combined background in both fields, the education in dry lab and wet lab is often separated. This work describes an example of integrated education with focus on genomics and transcriptomics. Participants learn computational and molecular biology methods in the same practical course. Peer-review is applied as a teaching method to foster cooperative learning of students with heterogeneous backgrounds. Evaluation results indicate acceptance and appreciation of this approach.

Full-scale/model test comparison studies to validate the traditional ABL wind tunnel simulation technique are reviewed. According to the literature review, notable discrepancies between full-scale measurement results and model test results were observed by most performed comparison studies, but the causes of the observed discrepancies were not revealed in a scientific way by those studies. In this regard, a new research scheme for future full-scale/model test comparison studies is proposed in this article, which utilizes the multiple-fan actively controlled wind tunnel simulation technique. With the new research scheme, future full-scale/model test comparison studies are expected to reasonably disclose the main problems with the traditional ABL wind tunnel simulation technique, and the technique can be improved correspondingly.

The emission of sulphur dioxide (SO2) from mining activities presents a substantial risk to public health, especially in populations located near mine industrial regions. This study investigated the potential correlation between exposure to sulphur dioxide (SO2) and its effects on respiratory health in Kankoyo Township, Zambia. A variety of methodologies were employed in this study, encompassing community participation, expert interviews, spatial analysis, and a retrospective examination of health and SO2 data for Kankoyo spanning 15 years. The results of our research indicated a worrisome correlation between the community and the presence of SO2, which has had a significant impact on their lives. The expert interviews also emphasized the effects of SO2, with respiratory cases accounting for approximately 75% of the reported cases. Additionally, the clinic officer observed that asthma cases have decreased following the implementation of a monitoring station in the community. Furthermore, overall emissions of SO2 have decreased since the upgrade of the smelter operation. A probable association was identified in the retrospective analysis between exposure to SO2 and the occurrence of asthma, respiratory non-pneumonia, and pneumonia infections. The findings of the retrospective research revealed a substantial association between SO2 concentrations and the susceptibility of individuals aged 5 years and older to asthma, respiratory non-pneumonia, and pneumonia infections. The results of the spatial study indicated that Kankoyo exhibited a significant level of SO2 pollution, above the established limitations set by the Zambian Environmental Management Agency (ZEMA) by an alarming margin of 1713%. In response to the challenges identified, this study proposed several measures. These measures encompassed the implementation of a requirement for regulators such as ZEMA and local communities to have access to real-time pollution data from mines, to enhance transparency. Additionally, the deployment of affordable air quality sensors, the resolution of medication shortages, the establishment of specialized respiratory health clinics, the initiation of IT-driven public awareness campaigns, and the expansion of research to investigate additional pollutants and confounding factors were also recommended.

Distribution System Operators (DSOs) are adapting to changing energy demands and the shift toward renewable and decentralized energy. Circularity is increasingly relevant for DSOs as their distribution systems age and need replacing. Taking circular action, however, is generally regarded as challenging as the current circular economy (CE) landscape is highly fragmented and rarely touches the implementation level. A longitudinal case study at Dutch DSO Liander on the circu-larity of distribution transformers was used to understand empirical success factors for taking circular action and to generate prescriptive knowledge on the operationalization of circularity. Six design propositions for circular action were formulated that suggest to 1) initiate small-scale cir-cularity experiments, 2) involve technical and strategic experts, 3) synergize circularity with more urgent, primary goals 4) translate circular initiatives bottom-up and top-down, 5) collaborate with other DSOs, and 6) create multidisciplinary teams. At DSO Liander, selecting the right interventions depending on the changing context contributed to operationalizing circularity for distribution transformers and achieving circularity targets. The generalizable design propositions could assist other DSOs in optimizing their strategy toward circular action.

The purpose of this study is to analyze how global research cooperation patterns in the secondary battery industry have changed over recent years and to identify the evolution in the focus of research. To this end, network analysis was performed using the nationality information of the authors of a 10-year multinational joint research paper related to lithium-ion batteries. Furthermore, keyword analysis and topic modeling were performed using the abstract data from the study. The results of this study confirm that some countries that are not well-known in the field, such as Australia, Spain, and France, showed high centrality, compared with the level of cooperation scale. Additionally, six research topics were identified. According to a comparison over the first half of the decade, no difference was observed in the appearance of keywords indicating high energy density and conductivity with lithium, a key mineral. Keyword distribution was high for topics like battery charging and discharging in the first half of the decade, and for next-generation battery materials, such as solid electrolytes, lithium metal anodes, and lithium-sulfur batteries in the second. These results provide insights into the establishment of R&D cooperation strategies by countries and pre-planning by companies in the battery industry.

In the evolving landscape of vibration analysis, the integration of machine learning technologies for semi-automated analytical processes presents challenges in establishing clear cause-and-effect relationships in decision-making formulas. This research addresses this gap by exploring analytical diagnosis through residual signals, enabling the identification of anomalies and underperformance in machinery. Vibration signature analysis, focusing on distinctive vibration patterns, proves instrumental in detecting bearing defects and optimizing maintenance for enhanced operational efficiency and safety. Mathematical modeling, particularly worst-case analysis, provides a structured framework for decision-making under uncertainty. The research employs descriptive methods to analyze bearing wear data, transforming it into quantitative data for multiple regression equations. The derived equations reveal the dominance of harmonics in determining bearing wear stages, with PeakVue and overall vibration further indicating damage progression. The findings emphasize the significance of harmonic detection and high-frequency vibration analysis in predicting bearing health, offering a comprehensive approach to enhance machinery reliability. The study concludes with practical recommendations for bearing damage diagnosis based on the developed mathematical models, providing valuable insights for predictive maintenance strategies.

This research paper examines the effects, advantages, challenges, and economic aspects of a research town. The study concludes that inclusion and diversity not only constitute fundamental values but also serve as crucial drivers of business success and sustained competitiveness. Universities play a central role in shaping the prosperity of the research town by functioning as knowledge hubs, fostering collaboration, nurturing talent, and contributing to the broader innovation ecosystem. The symbiotic relationship between universities and industries within the cluster establishes a dynamic and resilient environment for research and development. The presence of startups within the research cluster introduces novel ideas, enhancing the overall vibrancy and competitiveness of the local economy. In an era where social media algorithms increasingly influence people's choices, the potential for foreign interference emerges as a significant threat.

: One of the challenges facing operations management is the design, choice and imple-mentation of action plans adapted to the magnitude of the deviations of the variables of an industrial process. Making conscious and quick decisions is crucial to achieving im-provements in productivity. This will be achieved if the organization's internal and external communication model is strategically designed, considering specific cultural factors and the symmetry or asymmetry required in the communication model. However, how do we organize ourselves and through what channels do we communicate within a production process to generate Big Data that combines data from technologies and the perception, comprehension and projection of experienced humans? Our purpose is to create an operations management model that facilitates the incorporation of technology, allows a prompt response to failures, and promotes the sustainability of processes, without losing sight of its alignment with the organizational strategy. The developed model was implemented in an operations management team, following the guidelines of an action researcher methodology. This resulted in the design of an operations management model and a detailed methodology for its implementation, achieving sig-nificant improvements in the metrics of the current process, making it a success story.

We introduce the Open Research Knowledge Graph Agriculture Named Entity Recognition (the ORKG Agri-NER) corpus and service for contribution-centric scientific entity extraction and classification. The ORKG Agri-NER corpus is a seminal benchmark for the evaluation of contribution-centric scientific entity extraction and classification in the agricultural domain. It comprises titles of scholarly papers that are available as Open Access articles on a major publishing platform. We describe the creation of this corpus and highlight the obtained findings in terms of the following features: 1) a generic conceptual formalism focused on capturing scientific entities in agriculture that reflect the direct contribution of a work; 2) a performance benchmark for named entity recognition of scientific entities in the agricultural domain by empirically evaluating various state-of-the-art sequence labeling neural architectures and transformer models; and 3) a delineated 3-step automatic entity resolution procedure for the resolution of the scientific entities to an authoritative ontology, specifically AGROVOC that is released in the Linked Open Vocabularies cloud. With this work we aim to provide a strong foundation for future work on the automatic discovery of scientific entities in the scholarly literature of the agricultural domain.

(1) Background: Rational use of medicines (RUM) and their assessment is important to ensure optimal use of resources and patient care in hospitals. These assessments are essential to identifying practice gaps for quality improvement. (2) Methods: Assessment of adherence to WHO/ International Network for Rational Use of Drugs core prescribing indicators among out-patients in 2021 was conducted at the University Hospital of the Kwame Nkrumah University of Science and Technology in the Ashanti region of Ghana. We reviewed electronic medical records (EMR) of 110,280 patient encounters in the year which resulted in 336,087 medicines prescribed. (3) Results: The average number of medicines prescribed per encounter was 3 with generics being prescribed in 76% of prescriptions. Injections were prescribed in 7% of encounters while 90% of medicines were from Ghana’s Essential Medicines List 2017. (4) Conclusions: With the exception of patient encounters with injections, all prescribing indicators assessed in this study did not meet WHO optimum levels providing targets for quality improvement in RUM. Implementing prescribing guides and policies, regular audits and feedback as well as continuous professional development training may help to improve prescribing practices in the hospital.

Skilled academic/medical writing is critical to research communication. The fundamental sections of a scholarly manuscript are introduction, methods, results and discussion. The introduction of a medical manuscript is aimed at briefing readers on the clinical extent and public health context of the research problem. It must justify the essentialness of the research to the scientific community and reveal any underlying research novelty. Skillfully conceived, designed and performed research protocols that are unskillfully presented can lose scientific credibility and impact. Without research communication skills authors would not be able to display the usefulness of their research for the scientific community. Generally, research communication or medical writing training/skills is underrepresented in curricular systems of medical schools globally. This can challenge publication quality and quantity of early-career authors/researchers. The author presents the academic experience he accumulated through peer review and supervision of vast manuscripts and theses. This article aimed at presenting a comprehensive roadmap for academic writing of the introduction and at identifying its common pitfalls.

Biocultural heritage preservation relies on ethnobotanical knowledge and the paleoethnobotanical data used in (re)constructing histories of human-biota interactions. Biocultural heritage, defined as the knowledge and practices of Indigenous and Local peoples and their biological relatives, is often guarded information, meant for specific audiences and withheld from other social circles. As such, these forms of heritage and knowledge must also be included in the ongoing data sovereignty discussions and movement. In this paper we share the process and design decisions behind creating an online database for ethnobotanical knowledge and associated paleoethnobotanical data, using a content management system designed to foreground Indigenous and local perspectives. Our main purpose is to suggest the Mukurtu content management system, originally designed for physical items of cultural importance, be considered as a potential tool for digitizing and ethically circulating biocultural heritage, including paleoethnobotanical resources. With this database, we aim to create access to biocultural heritage and paleoethnobotanical considerations for a variety of audiences while also respecting the protected and sensitive natures of Indigenous and local knowledges.

Course-based Undergraduate Research Experiences (CUREs) in high-enrollment, introductory classes are a 37 potentially transformative approach to retaining more students in STEM majors. We developed and piloted a CURE 38 in the introductory biology courses at the University of Washington. This CURE focuses on analyzing experimental 39 evolution of antibiotic resistance in Escherichia coli and generates data on two topics relevant to clinical practice: 40 compensatory mutations and cross-drug effects. By studying mutations in central cellular machinery that confer drug 41 resistance, students not only gain insight into fundamental cellular phenomena, but also recognize the molecular 42 basis of a medically important form of evolutionary change, connecting genetics, microbiology, and evolution.

The doctoral defense is an important step in the doctoral journey and an essential requirement for obtaining the doctoral degree. Past research on the doctoral defense has focused solely on national practices. In this work, I investigate the potential link between the doctoral defense format based on its major and minor elements and the perception of the defense by the student. For this purpose, I first reviewed the different defense formats used internationally to extract the different elements of the doctoral defense, as well as the literature on students’ perceptions of the doctoral defense. Then, I carried out an international survey which received 297 responses, of which 204 completed surveys which I used for the analysis in this article. I first analyzed the outcomes of the survey using qualitative and quantitative methods, and then cross-correlated the outcomes of defense format to the outcomes of student perception. From this analysis, I observe that the defense elements that positively impact the students’ perception are: publication of the thesis before the defense, receiving committee feedback before the defense, knowing the recommendation of one or more committee members in advance, having the supervisor present in the audience or as part of the committee, using a dress code, and including a laudatio. The final conclusion of this work is threefold. The first conclusion is that the details of the defense format impact most the students’ perception. The second conclusion is that doctoral students on average value the defense as a positive experience. The third conclusion is that the defense format cannot influence two important aspects of how a student perceives the defense: the student’s inner life and lived experience during the defense, and the behavior of the committee members.

In light of the worldwide spreading requirements related to the disclosure of non-financial information, which are aligning to the Sustainable Development Goals (SDGs) developed by the United Nations (UN) in 2015, the study aims to analyse the influence of sustainability and other non-financial reporting on companies’ engagement in earnings management practices, through a pre-post adoption of European Directive 2014/95/EU comparative analysis for firms listed on the Bucharest Stock Exchange (BSE) in the period 2015-2019. To conduct the investigation, the research involves the assessment and analysis of three earnings management metrics resulted by running multiple linear regression models on a sample of 31 companies listed on BSE. Research findings emphasise a decrease in the use of income smoothing practices by sampled companies in the post-adoption period 2017-2019, compared to the period preceding the implementation of the EU directive related to mandatory disclosure of non-financial information, 2015-2016. Thus, firms characterised by a higher transparency in terms of sustainability reporting are less inclined to engage in earnings management practices. This research complements the literature in the field of sustainability reporting and earnings management, providing empirical evidence on the significance and impact of publishing non-financial information.

This paper presents the current lexical, morphological, syntactic and rule-based machine translation work for Erzya and Moksha that can and should be used in the development of a roadmap for Mordvin linguistic research. We seek to illustrate and outline initial problem types to be encountered in the construction of an Apertium-based shallow-transfer machine translation system for the Mordvin language forms. We indicate reference points within Mordvin Studies and other parts of Uralic studies, as a point of departure for outlining a linguistic studies with a means for measuring its own progress and developing a roadmap for further studies.

In the Brazilian Amazon, rural settlements are increasingly isolated by large-scale production farms, jeopardizing their sustainability and the good living of family farmers. Works were carried out in settlements to measure sustainability. However, the majority does not consider the participation and the collectively of those involved. In this way, we propose to evaluate, in a collective and participatory way, the sustainability and good living of the SDP São Paulo Rural Settlement, of the northern Amazon of Mato Grosso. We used the didactic-pedagogical method Circle of Sustainability, developed from five points: 1st - circle of investigation of generating themes; 2nd - circle of the history of the subject world; 3rd - circle of diagnosis of rural settlements; 4th - circle of exchange of knowledge; and 5th - circle of sustainable perceptions and narratives. The historical, socioeconomic and cultural characterization of the settlement allowed us to understand how sustainability and good living are being built in the settlement history process. Sustainability and good living are dialectical processes, are under construction, in movement.

STUDY QUESTION: Which are the main research interests among patients of assisted reproductive technologies (ART)? SUMMARY ANSWER: Patients identified as research priorities that deserve further investigation: success rates and risks of ART, side-effects of treatments, resources to cope with infertility, effectiveness of alternative therapies, lifestyle habits to protect fertility, oocyte quality and ovarian reserve, and causes of genetic or hereditary infertility. WHAT IS KNOWN ALREADY: The involvement of patients and caregivers in setting research agendas in medicine has gathered significant momentum in the last decade. Patients’ involvement in setting research priorities offers several benefits: improved patient knowledge and awareness of their condition; greater understanding of the medical professionals of the impact of the condition on patients’ quality of life; reduced costs associated with redundant research activities. This is may be also applicable to research in infertility and ART, where patients’ interests have never been explored before. STUDY DESIGN, SIZE, DURATION: This is a cross-sectional study that consists of an anonymous online survey, which was sent up to three times to 2112 patients from 11 fertility centers in 5 countries between January-December 2018. The study design was based on the James Lind Alliance priority setting partnership model, which comprises the identification of patients groups, the exploration of the research agenda, the analysis of collected data and identification of priorities. PARTICIPANTS/MATERIALS, SETTING, METHODS: Overall, 2112 patients were contacted, and 945 surveys were answered (RR: 44.7%). Patients were asked to identify research questions relevant to them in the areas of infertility causes and prevention, fertility treatments (medication and ART), and the emotional aspects of infertility. Answers were categorized in topics and ranked by frequency. A long list of the top-30 research topics was extracted from the aggregate results, from which, a short list of the top-10 research topics was created. At the end, 10 research questions related to each of the 10 research topics were constructed, based on the answers given by patients. MAIN RESULTS AND THE ROLE OF CHANCE: Female (845, 89.4%) and male (100, 10.6%) patients were included. The mean age of patients was 37.8 (SD 1.74). Most of the patients did not have children at the time of the survey (523, 59%), while 51 (5.7%) were pregnant. Sixty (6.3%) patients did not start treatment, 579 (61.3%) were performing a treatment with their own gametes and 304 (32.2%) were treated through gamete donation. Patients were mainly interested in the effectiveness of ART -especially per clinical profile-, side effects of drugs, protection of fertility and prevention of infertility –especially through diet and exercise-, and psychological aspects of the infertility journey. The top-10 research questions (and weight) obtained were: 1) What are the side-effects of ART treatments? (41.6%); 2) What are the most effective methods to cope with infertility from the psychological point of view? (37.2%); 3) What effects could diet have on fertility? (25.9%); 4) What are ART success rates per clinical profile? (25.9%); 5) Are there habits and lifestyle factors that could prevent infertility? (20.0%); 6) What are the long-term risks associated to ART? (18.5%); 7) Are alternative therapies such as acupuncture, yoga, and meditation effective to treat/prevent infertility? (18.5%); 8) What is the impact of exercise on fertility? (15.4%); 9) How does oocytes quantity and quality affect fertility? (9.5%); 10) What are the genetic patterns or hereditary conditions causing/related to infertility? (9.5%). LIMITATIONS, REASONS FOR CAUTION: Although all respondents had attended a fertility center, not all of them were diagnosed as infertile (i.e. single women) and had started treatment at the time of response, while a few were pregnant; their priorities for research might have been influenced by their infertility journey. Also, all participants attended private fertility centers: areas of interest may be different in public settings. WIDER IMPLICATIONS FOR THE FINDINGS: Researchers and clinicians should keep in mind that, in addition to improvement of treatments’ success rates and side-effects, patients greatly value research on causes, prevention and emotional aspects of infertility. As their views might differ from those of medical professionals, patients’ voices should be incorporated in setting infertility research priorities.

The growing adoption of electric propulsion systems in Maritime Autonomous Surface Ships (MASS) necessitates advancements in shipboard electronics for safe, efficient, and reliable operation. These advancements are crucial for tasks like real-time sensor data processing, control algorithms for autonomous navigation, and robust decision-making capabilities. This study investigates research trends in MASS using bibliographic analysis to inform policy and future research directions in this evolving field. We analyze 3,363 MASS-related articles from the Web of Science database, employing co-occurrence word analysis and latent Dirichlet allocation (LDA) topic modeling. Findings reveal a rapidly growing field dominated by image recognition research. Keywords like "datum," "image," and "detection" suggest a focus on collecting and analyzing marine data, particularly with deep learning for synthetic aperture radar imagery. LDA confirms this, with "Image analysis and classification research" as the leading topic. The study also identifies national and organizational leaders in MASS research. However, research on Arctic routes lags behind other areas. This work provides valuable insights for policymakers and researchers, promoting a deeper understanding of MASS and informing future policy and research agendas for the integration of electric propulsion systems in the maritime industry.

Background: Carers (or care partners) of adults in LTC contribute substantially to the health and well-being of their loved ones by providing physical care, emotional support, and companionship. Despite their critical role, little is known about how caregivers have been impacted by the pandemic. The purpose of this study was to explore the lived experiences of caregivers of people living in long-term care (LTC) homes during the initial phases of the COVID-19 pandemic and potential supports and resources needed to improve caregivers’ quality of life.Design: An interpretive descriptive approach that incorporated photovoice method was used. Methods: Using purposive sampling strategy, six family carers in Ontario, Canada were recruited between September and December 2021. Over a four-week period, caregivers took pictures depicting their experience of the pandemic that were shared in a virtual focus group. Visual and text data were analyzed using thematic analysis with an inductive approach.Findings: Caregivers expressed feelings of frustration, confusion, and joy. Emerging themes included: (i) feeling like a “criminal” amidst visitor restrictions and rules; (ii) experiencing uncertainty and disappointment in the quality of care of long-term care homes; (iii) going through burnout; and (iv) focusing on small joys and cherished memories.Conclusions: The combination of visual and textual methods provided unique insight into the mental distress, isolation, and intense emotional burdens experienced by caregivers during the pandemic. Impact: Our findings underscore the need for LTC organizations to work in unison with caregivers to optimize the care of residents and support mental health of caregivers.

This brief communication intends to develop critical thinking on the development at different levels that could be evaluated in the well-being of humans from the local development towards a global scale or planetary point of view. Therefore it was presented and discussed how Artificial Intelligence tools could provide important contributions and influence in the design of critical thinking to develop ideas and insights within Research as well as funding for technology transfer. In this context it should be highlighted that the generation of funding and economy for sustainability that it should be based on critical thinking and analysis of what is need it from the close surrounding towards longer distances as well as in the inversed direction. In this regard, the main axes that support it are based on the importance of entailment of individuals in their close surrounding as well as to longer physical distances and cultural differences. An in this context it should be highlighted the existence of large diversity and varied Multicultural differences. These factors could affect the developments of technology, education; level, and quality of life. Thus the Economical and development indexes could be largely varied and different between them. For this reason it should highlighted the local development within shortened times by interacting to receive or provide materials with aggregated value or non-tangible values. Therefore, it could be accelerated the process of improvement in a targeted field looking for average homogeneous development everywhere. And there, it is where the link-up and transfer strategies of technology and education by creation of varied strategies in communication media. As for example the communication plays an important role to transfer knowledge within the different social status and imagining the development of thinking that later it will be the basis for the next generation of technology. By this manner, it could be coupled different levels of educations degrees by a factor in common related with curiosity and open minds to learn, work, and live together in the context of developments of new smart manners of living where economy and new encrypted currency are involucred and provide by different manners sustainability. In these perspectives the development and education at the University and higher degrees taking into account the transmission of important factors such as; i) entailment , ii) development of knowledge, and iii) transference, is fundamental. Finally, it should be highlighted the particular need of good human relationships, emotional intelligence, and diplomacy to afford from the simplest challenges to the higher ones.

The prediction of wind power output is part of the basic work of power grid dispatching and energy distribution. At present, the output power prediction is mainly obtained by fitting and regressing the historical data. The medium- and long-term power prediction results exhibit large deviations due to the uncertainty of wind power generation. In order to meet the demand for accessing large-scale wind power into the electricity grid and to further improve the accuracy of short-term wind power prediction, it is necessary to develop models for accurate and precise short-term wind power prediction based on advanced algorithms for studying the output power of a wind power generation system. This paper summarizes the contribution of the current advanced wind power forecasting technology and delineates the key advantages and disadvantages of various wind power forecasting models. These models have different forecasting capabilities, update the weights of each model in real time, improve the comprehensive forecasting capability of the model, and have good application prospects in wind power generation forecasting. Furthermore, the case studies and examples in the literature for accurately predicting ultra-short-term and short-term wind power generation with uncertainty and randomness are reviewed and analyzed. Finally, we present prospects for future studies that can serve as useful directions for other researchers planning to conduct similar experiments and investigations.

Interdisciplinary research into the underlying neural processes of music therapy (MT) and subjective experiences of patients and therapists are largely lacking. The aim of the current study was to assess the feasibility of newly developed procedures (including EEG/ECG hyperscanning, synchronous audio-video monitoring, and qualitative interviews) to study the personal experiences and neuronal dynamics of moments of interest during MT with stroke survivors. The feasibility of our mobile set-up and procedures as well as their clinical implementation in a rehabilitation centre and an acute hospital ward were tested with four phase C patients. Protocols and interviews were used for the documentation and analysis of the feasibility. Recruiting patients for MT sessions was feasible, although data collection on three consecutive weeks was not always possible due to organisational constraints, especially in the hospital with acute ward routines. Research procedures were successfully implemented, and according to interviews, none of the patients reported any burden, tiredness or increased stress due to the research procedures, which lasted approx. 3 hours (ranging from 135min to 209min) for each patient. Implementing the research procedures in a rehabilitation unit with stroke patients was feasible and only small adaptations were made for further research.

The online learning necessitated by COVID-19 social distancing limitations has resulted in the utilization of hybrid online formats focused on maintaining visual contact among learners and teachers. The preferred option of video conferencing for academic meetings has become that of Zoom. The needs of one voluntary, democratic, self-reflective university research group—grounded in responses to writing prompts—differed in learning focus. Demanding a safe space to encourage and record both self-reflection and creative questioning of other participants, the private Facebook group was chosen over video conferencing to maintain the concentration on group members’ written responses rather than how they saw themselves (and thought others saw them) on screen. A narrative research model initiated in 2015, the 2020/21 interaction of the group in the year’s worth of Facebook entries, and the yearend feedback received from group participants, will be compared with previous years when the weekly group met in-person. The results in relation to COVID-19 limitations indicate that an important aspect of self-directed learning related to trust that comes from team mindfulness is lost when face-to-face interaction is eliminated regarding the democratic nature of these meetings. With online meetings the new standard, maintaining trust requires improvements to online virtual meeting spaces.

Research Infrastructures (RIs) are essential to achieve excellence in innovative scientific research. However, because of limited land availability and specific geological requirements, evaluating the viability of a site for a new RI can be a challenging task. Stringent safety construction requirements include developing site-specific architectural and geoengineering solutions, minimizing construction disturbances, and reinforcing rock and soil in a timely fashion. For successful development of the RIs in China, such as the Daya Bay Neutrino Laboratory (DBNL), and the China Spallation Neutron Source (CSNS), an integrated approach of joint geophysical methods including the electrical resistivity tomography (ERT), controlled-source audio-frequency magneto telluric (CSAMT)), gravity and seismic refraction methods, and geological mapping and surveys were carried out. Geophysical parameters, such as electrical resistivity, density, and seismic velocity show inverse proportion to the degree of rock fracturing or weathering. The results show that the low values of geophysical parameters suggest the weathered/fractured rock, while high values reveal the fresh bedrock. The Engineering Geological Suitability Index (EGSI) value can represent the individual EGSI values at a constant and summed over varying depths. EGSI methodology is an improvement on the existing siting process, and has been applied this to CSNS. Our integrated approach provides clearer insight of the subsurface for site suitability of RIs in challenging engineering geological conditions, and removes any ambiguity caused by a single geophysical parameter. The obtained geological knowledge of the area not only provides engineers with much-needed information about the construction conditions of a potential site, but also gives scientists the opportunity to explore the local geology. In this study, we demonstrate our innovative approach for siting RIs, as demonstrated by the synthetic evaluation of the site location and utilization for two established RIs (DBNL and CSNS).

Background: Globally, infections are the third leading cause of neonatal mortality. Predominant risk factors for facility-born newborns are poor hygiene practices that span both the facility and home environments. Current improvement interventions focus on only one environment and tar-get limited caregivers, primarily birth attendants and mothers. To inform the design of a hand hygiene behaviour change intervention in rural Cambodia, a formative mixed-methods research study was conducted to investigate the context specific behaviours and determinants of hand-washing among healthcare workers, maternal and non-maternal caregivers along the early new-born care continuum. Methods: Direct observations of hygiene practices of all individuals providing care to 46 newborns across eight facilities and associated communities were completed and hand hygiene compliance assessed in analysis. Semi structured interactive interviews were subsequently conducted with 35 midwives and household members to explore the corresponding cognitive, emotional, and environmental factors influencing the observed key hand hygiene behaviours. Results: Hand hygiene opportunities during newborn care were frequent in both set-tings (n = 1319) and predominantly performed by mothers, fathers and non-parental caregivers. Compliance to hand hygiene protocol across all caregivers, including midwives, was inadequate (0%). Practices were influenced by the lack of accessible physical infrastructure, time, increased workload, low infection risk perception, nurture-related motives, norms and inadequate knowledge. Conclusion: Our findings indicate that an effective intervention in this context should be multi-modal to address the different key behaviour determinants and target a wide range of caregivers.

Integrating triple bottom line (TBL) goals into supply chains (SCs) is a challenging task which necessitates the careful coordination of numerous stakeholders’ individual interests. Recent technological advancements can impact TBL sustainability by changing the design, structure and management of modern SCs. Blockchain technology enables immutable data records and facilitates a shared data view along the supply chain. The Physical Internet (PI) is an overarching framework that can be applied to create a layered and comprehensive view of the SC. In this conceptual paper I define and combine these technologies and derive several high-level research areas and research questions to investigate adoption, management as well as structural SC issues. I suggest a theory-based research agenda for the years to come that exploits the strengths of rigorous academic research, while remaining relevant for the industry. Furthermore, I suggest various well-established theories to tackle the respective research questions and provide specific directions for future research.

In this paper, we study the effect of decreasing aperture diameter on signal transmission from the scintillator to the PMT. The apertures have been inserted directly between the scintillator and the photomultiplier. Three different aperture diameters have been used over a wide energy range.A newly developed fast digital spectrometer has been utilised for experimental measurement in the radial channel of the VR-1 research reactor. The detector signals with and without inserted apertures have been measured and evaluated. The aim of our research was to determine the effect of the apertures on the spectral quality, energy range and the evaluated physical quantities.

Despite being small and simple structured in comparison to their victims, virus particles have the potential to harm severly and even kill highly developed species such as humans. To face upcoming virus pandemics, detailed quantitative biophysical understanding of intracellular virus replication mechanisms is inevitable. Unveiling the relationship of form and function might allow to determine putative attack points relevant for the systematic development of direct antiviral agents (DAA) and potent vaccines. Biophysical investigations of spatio-temporal dynamics of intracellular virus replication so far are rare. We are developing a framework to allow for fully spatio-temporal resolved virus replication dynamics simulations based on partial differential equations models (PDE) and evaluated with advanced numerical mathematical methods on leading supercomputers. This study presents an advanced highly nonlinear model of the genome replication cycle of a specific RNA virus, the Hepatitis C virus (HCV). The diffusion-reaction model mimics the interplay of the major components of the viral RNA (vRNA) cycle, namely non structural viral proteins (NSP), vRNA and a generic host factor. Technically, we couple surface PDEs (sufPDEs) on the 3D embedded 2D Endoplasmatic Reticulum (ER) manifold with PDEs in the 3D membranous web (MW) and cytosol volume. (The MWs are the replication factories growing on the ER induced by NSPs.) The sufPDE/PDE model is evaluated at realistic reconstructed cell geometries which are based on experimental data. The simulations couple the effects of NSPs which are restricted to the ER surface with effects appearing in the volume. The volume effects include the host factor supply from the cytosol and the MW dynamics. Special emphasis is put to the exchange of components between ER surface, MWs and cytosol volume. As the vRNA spatial properties are not fully understood so far in experiment, the model allows for vRNA both restricted to the ER and moving in the cytosol. The visualization of the simulation resembles a look into some sort of fully 3D resolved “in silico microscopes” to mirror and complement in vitro / in vivo experiments for the intracellular vRNA cycle dynamics. The output data are quantitatively consistent with experimental data and provoke advanced experimental studies to validate the model.

Background: Since 2000, vaccine coverage in Sub-Saharan Africa (SSA) has surpassed multiple milestones. Its contribution to global health, especially in low-middle-income countries is one of the achievements in global governance of modern medicine, averting 2-3 million child deaths every year. However, in Nigeria, vaccine-preventable-diseases still account for one in eight child deaths before their fifth-year birthday and remains one of the ten countries where 4.3 million children under five are without complete immunization. The reasons for declining childhood vaccine demand are unclear. Therefore, the goal of this contribution is to shed light on the reasons to set a foundation for future interventions. Methods: Four focus group discussions were conducted. The primary targets were mothers of children 0 – 12 months old in Nigeria. A simplified quota sampling approach was used to select mothers in four geographical clusters of Nigeria’s Federal Capital Territory. At least six mothers from each cluster were randomly included, giving a total of 24 participants. An interview guide developed from the 5C psychological antecedence model was used (assessing confidence, complacency, calculation, constraints, collective responsibility); two additional variables were included that had proved meaningful in previous work (religion and masculinity). The data were analyzed using meta-aggregation approach such as framework synthesis, which summarized data in a stepwise fashion. Results: The sample was generally relatively positive towards vaccination. Still, mothers reported low trust in vaccine safety and the healthcare system (confidence). Yet, they had great interest in seeking additional information during antenatal visits (calculation), difficulties in prioritizing vaccination over other equally competing priorities (constraints) and were aware that vaccination translates into overall community health and wellbeing (collective responsibility). They had a bias towards God as ultimate giver of good health (religion) and reported that their husbands played a dominant role in vaccination decision-making (masculinity). Mothers perceived their children vulnerable to disease outbreaks, which motivated them to get them vaccinated (complacency). Conclusion: The 5C model and the added determinants provided a useful qualitative tool for understanding mothers’ vaccination decision-making in low resources settings.

University-Business partnership for collaborative curriculum design, development and delivery is possibly the less explored dimension of University Business Collaboration (UBC). Even if some models for curricular design and development might be available, scarce information exists on how the partnership is constructed, the new curricula are designed, developed and how they are implemented. This article intends to present and discuss the experience obtained during a three-year European funded Project, namely Think4Jobs. This project exemplifies the significance and benefits of UBC in the design, development and delivery of curricula that meet the evolving demands of the labour market while promoting Critical Thinking (CT) as a foundational 21st century skill to contribute to graduates' employability. Think4Jobs project brought together a multidisciplinary team of researchers and business organisations from five European countries (Germany, Greece, Lithuania, Portugal and Romania) with interests in promoting and developing CT and mitigating eventual competence gaps. The project's success was attributed to key practices, including defining a common conceptualization of CT, employing participatory co-design, and providing common training for university and business partners. Clear objectives, explicit roles, effective communication, and ongoing evaluation further enhanced the collaboration. Experiential learning, real-work problems, and case studies reinforced the curricula, bridging the gap between academia and the labour market. By embracing these insights, future UBC initiatives can empower graduates with the necessary skills to stand out in an ever-changing labour market, contributing to enhanced education and successful careers.

Australia’s mental health system is failing young people. Calls for accountability, strategic long-term policy planning, and regional leadership have been identified as solutions to guide mental health reform. Developing system dynamics models using a participatory approach (participatory systems modelling, PSM) is recognised as a useful method that can support decision-making for strategic reform. This paper reports evaluation findings of a youth mental health PSM process conducted in the Australian Capital Territory (ACT). Baseline and follow-up mixed-methods evaluation data were collected in 2022 across diverse stakeholder groups to investigate the feasibility, value, impact, and sustainability of PSM. Though youth mental health system reform was viewed as desirable and a necessity across all stakeholder groups, shared perceptions of disabling powerless was observed regarding their ability to influence current decision-making processes to improve the youth mental health system. This suggests greater accountability is required to support systemic reform in youth mental health. PSM offers promise in improving transparency and accountability of decision-making for youth mental health as exemplified in the ACT. However, more support and time are required to facilitate transformational change. Future research should investigate empowerment strategies to complement the implementation of findings from dynamic models developed through PSM, as well as the effectiveness of regional youth mental health policy decision-making supported by systems modelling.

In real financial markets, the certainty equivalent rate is an important factor for investors to consider. From the value of a specific company’s certainty equivalent rate, investors can judge if this company is worth investing in. In this paper, we will explore how to obtain the value of the certainty equivalent rate so that we can evaluate a given company. First, we will introduce the theoretical support of this paper, which is put-call parity. From put-call parity, we will derive the mathematical expression for the certainty equivalent rate. Second, we will use the mathematical expression for the certainty equivalent rate to perform an empirical study. We will consider some extreme examples, including some of the best- and worst-performing stocks up to this point in 2023. Based on these stocks’ data, we will visualize the performance of these stocks and explain the meaning of the data. Finally, we will apply the results to a very popular industry—the electric vehicle industry—to explore the current electric vehicle market situation in the U.S.A.

We are all similar, but a bit different. These differences are partially due to variations in our genomes and are related to the heterogeneity of symptoms and responses to treatments that patients exhibit. Most animal studies are performed in one single strain with one manipulation. However, due to the lack of variability, therapies are not always reproducible when treatments are translated to humans. Panels of already sequenced organisms are valuable tools for mimicking human phenotypic heterogeneities and gene mapping. This review summarizes the current knowledge of mouse, fly and yeast panels with insightful applications for translational research.

In this paper we explore extending the concept of common cross-study Common Data Element concepts beyond simple demographics to cover disease-specific concepts relevant to imaging. We test interactively linking the resulting database to the associated images in a federated manner. We examine the use of existing standards, not only for terminology, but for interchange of serialized data in forms familiar to imaging and clinical trials specialists and their dedicated systems. Our intent is to perform preliminary work to inform both the upcoming Imaging Data Commons specifically, as well as more general integration projects beyond imaging.

Late January 2020, COVID-19 unexpectedly imposed world-wide limitations on daily life. Deemed a pandemic mid-March 2020, lockdowns were imposed for an indefinite period, including at academic institutions. Consequently, interest in digital literacy—an on-going and increasing concern of academic institutions in the 21^st century—exponentially heightened. Continuing meetings of academic groups now necessitated online communication. In the almost overnight closure of all non-essential services, academic units at one post-secondary institution expeditiously selected Zoom—a popular video conferencing application—as the preferred platform for meetings until social distancing was lifted. In contrast to this widely accepted use of Zoom for scheduled meetings, one unique health-related group at the institution, tailored to the 4Cs of 21^st century learning of critical thought, communication, cooperation and creativity, found social networking through a private Facebook group a more appropriate and satisfying group experience than likely possible with the Zoom app. Pros and cons of both online platforms are presented along with when each choice is warranted. In promoting digital literacy as the primary goal in online communication for academic meetings, private Facebook groups hold promise for collaborative online academic meetings with similar features to this health-related group.

Background: Active case finding for TB was implemented in selected sixty high TB burden wards of Kolkata, India. Community volunteers called TOUCH agents (TAs) identified and referred presumptive TB patients (PTBPs) to health facilities for TB diagnosis and treatment. We aimed to describe the ‘care cascade’ of PTBPs identified during July to December, 2018 and to explore the reasons for attrition as perceived by TAs and PTBPs. Methods: An explanatory mixed methods study with quantitative phase of cohort study using routinely collected data followed by descriptive qualitative study with in-depth interviews was conducted. Results: Of the 3, 86,242 individuals enumerated, 1132 (0.3%) PTBPs were identified. Only 713 (63.0%) PTBPs visited referred facility for TB diagnosis. TB was diagnosed in 177 (24.8%) and the number needed to screen for one TB was 2,183 individuals. The potential reasons for low yield were stigma and apprehension about TB, distrust about TA, wage loss for attending health facilities and substance abuse among PTBPs. Conclusion: The yield of ACF was suboptimal with low PTBP identification rate and high attrition rate. Interviewing each individual for symptoms of TB and supporting PTBPs for diagnosis through sputum collection and transport can be adopted to improve the yield.

This report describes the experience in implementing the FAIR principles for the GoTriple Discovery Platform for the Social Sciences and Humanities (SSH). It shows how adherence to FAIR should be considered as a continuous process throughout the entire lifespan of any information management system, including GoTriple, rather than a static goal with decisions only made at design time. The report presents an introduction highlighting the importance of the FAIR principles, indicating how they can be assessed in data management systems. Then the GoTriple case is presented, with a general overview of this discovery platform before describing some of the implemented practices in support of FAIR. The Discussion section shows on the one hand some virtuous reuse of GoTriple data, together with one major pitfall in the platform’s FAIR implementation. In this sense, this report serves as a case study that can offer insights and actionable advice for those implementing information systems aligned, from the very outset, with the FAIR principles.

Burden of diseases measured as disability-adjusted life years per 100,000 people can be mined from public domain data, when they are made available by population health surveillance systems. This can be analysed to allow insightful comparisons with the national average, and to understand differences in trends between the sexes, age groups, time periods, geographic regions and sub-regions. In this illustrative case study, we have analysed the Scottish burden of disease database to understand what ailed the population of the Grampian region before the COVID-19 pandemic. We have identified selected cancers, ischaemic heart disease, Alzheimer’s disease and other dementias amongst the highest contributors to the burden; that drug use disorders and colorectal cancer are showing worsening trends and require health promotion and disease prevention measures from ages 15 and 25 respectively, especially in Aberdeen City; and that males are more vulnerable to atrial fibrillation and flutter, diabetes mellitus and oesophageal cancer, while females are to cerebrovascular disease. We demonstrate the usefulness of our analysis and methodology for the wider health system, allowing targeted medical research investments and coordinated response from public health and health service delivery. We also show the need for up-to-date surveillance data, forecasts and evidence on the impact of interventions to be made available widely.

Obstructive Sleep Apnea (OSA) is nowadays one of the respiratory pathologies with a higher in-cidence globally in developed countries. This situation led to an increase in the demand for medical appointments and diagnostic studies related to that condition, especially those based on poly-somnographies and cardiorespiratory polygraphies. These studies are limited in resources, causing long waiting lists with the subsequent impact on the patients’ health. Furthermore, it is necessary to mention that OSA’s symptomatology is not very specific, and it is typically present in the general population (excessive sleepiness, snore, etc.). In this regard, this paper proposes a novel intelligent clinical decision support system for the diagnosis of OSA which could be used to help medical teams, both in primary care settings and in units specialized in respiratory pathologies. The aim of the proposed system is to help discriminate the patients suspected of suffering from the pathology from those who are not. To this end, two types of information sets of heterogeneous nature are consid-ered. The first one encompasses objective data, related to the patient's health profile with infor-mation usually available in electronic health records. The second type comprises subjective data, referred to the symptomatology reported by the patient in a previous interview. To process the first group of information, a Machine Learning classification algorithm is used, Bagged Trees in this case. For processing the second information set, related with the symptomatology of the patient, a col-lection of expert systems based on fuzzy inferential systems arranged in cascade are employed. As a result, the system is able to determine two risk indicators related to the patient's risk of suffering from OSA: the Statistical Risk and the Symbolic Risk respectively. Subsequently, by interpreting both risk indicators mentioned it will be possible to determine the severity of the patients’ health, proposing a preliminary evaluation on their condition. For the initial tests of the system, a software artifact has been built using a dataset with 4,978 selected patients, suspected of suffering from OSA, from the Álvaro Cunqueiro Hospital in Vigo. The results obtained are promising, demonstrating the potential usefulness of this type of tools in medical diagnosis. Once the system has been validated with new data from clinical environments, it is considered as possible to obtain a relevant improvement in the quality of the healthcare services, and a reduction in the associated costs.

Artificial Intelligence (AI) has the power to generate scenarios and make predictions through the use of advanced algorithms and machine learning techniques. OpenAI’s GPT-3 AI is a state-of-the-art language model that has been trained on a large dataset of text, which allows it to generate hu-man-like text, and it can generate scenarios for different fields. However, GPT-3 was trained on data available up until June 2021, had no access to more recent data nor was connected to the internet. In this study, we investigated the capability of OpenAI’s GPT-3 AI to predict the Ukrainian war es-calation, which started in 2022 and had massive geopolitical effects. We used GPT-3´s capability to generate future scenarios, to check those scenarios for internal consistency, and to create a proba-bility estimate. The results showed that although GPT-3 described an open war as one of the low probability scenarios, its capability on predicting the future was limited. Furthermore, it became evident that checking internal consistency of the generated scenarios could be improved. We ap-preciated GPT-3 as very useful and powerful for generating future scenarios, but also concluded that its prediction capabilities of real-world events are limited, should be used with caution, and require further development.

How do sensor research and technologies grow over time? This paper applies the network analysis with a new computational approach to map the structure and evolution of sensor research and technologies over a 30-year time frame (1990-2020).The goal of this study is to analyze the evolution of sensor research for forecasting emerging scientific and technological trajectories. Results show that the scientific interaction within ecosystem (represented with networks) of sensor generates a co-evolution of scientific fields supporting the accelerated growth of different technological tra-jectories, such as: wireless sensors, fiber optic and optical sensors, gas sensors and biosensors. These results suggest main theoretical implications that explain the evolution of sensor research with critical aspects of innovation management to support R&D investments towards new technological trajectories having a high potential of growth.

Demographic change is leading to the aging of German society. As long as the baby boom co-horts are still of working age, the working population will also age - and decline as soon as this baby boom generation gradually reaches retirement age. At the same time, there has been a trend towards increasing absenteeism (times of inability to work) in companies since the zero years, with the number of days of absence increasing with age. We present a novel stochastic forecast approach that combines population forecasting with forecasts of labor force participation trends, considering epidemiological aspects. For this, we combine a stochastic Monte Carlo-based cohort-component forecast of the population with projections of labor force participation rates and morbidity rates. This article examines the purely demographic effect on the economic costs associated with such absenteeism due to the inability to work. Under expected future employment patterns and constant morbidity patterns, absenteeism is expected by close to 5 percent by 2050 relative to 2020, associated with increasing economic costs of almost 3 percent. Our results illustrate how strongly the pronounced baby boom/ baby bust phenomenon determines demographic development in Germany in the midterm.

Solar radiation prediction is an important process in ensuring optimal exploitation of solar energy power. Numerous models have been applied to this problem, such as numerical weather prediction models and artificial intelligence models. However, well-designed hybridization approaches that combine numerical models with artificial intelligence models to yield a more powerful model can provide a significant improvement in prediction accuracy. In this paper, we propose novel hybrid machine learning approaches that exploit auxiliary numerical data. The proposed hybrid methods invoke different machine learning paradigms, including feature selection, classification, and regression. Additionally, numerical weather prediction (NWP) models are used in the proposed hybrid models. Feature selection is used for feature space dimension reduction to reduce the large number of recorded parameters that affect estimation and prediction processes. The rough set theory is applied for attribute reduction and the dependency degree is used as a fitness function. We investigate the effect of the attribute reduction process with thirty different classification and prediction models in addition to the proposed hybrid model. Then, different machine learning models are constructed based on classification and regression techniques to predict solar radiation. Moreover, other hybrid prediction models are formulated to use the output of the numerical model of Weather Research and Forecasting (WRF) as learning elements in order to improve the prediction accuracy. The proposed methodologies are evaluated using a data set that is collected from different regions in Saudi Arabia.

Data science is facing the following major challenges: (1) developing scalable cross-disciplinary capabilities, (2) dealing with the increasing data volumes and their inherent complexity, (3) building tools that help to build trust, (4) creating mechanisms to efficiently operate in the domain of scientific assertions, (5) turning data into actionable knowledge units and (6) promoting data interoperability. As a way to overcome these challenges, we further develop the proposals by early Internet pioneers for Digital Objects as encapsulations of data and metadata made accessible by persistent identifiers. In the past decade, this concept was revisited by various groups within the Research Data Alliance and put in the context of the FAIR Guiding Principles for findable, accessible, interoperable and reusable data. The basic components of a FAIR Digital Object (FDO) as a self-contained, typed, machine-actionable data package are explained. A survey of use cases has indicated the growing interest of research communities in FDO solutions. We conclude that the FDO concept has the potential to act as the interoperable federative core of a hyperinfrastructure initiative such as the European Open Science Cloud (EOSC).

As most of the current dynamic positioning systems are based on model ships, they cannot accu-rately reflect the motion state, position changes, and mutual influence of each part of the dynamic positioning system of actual ships in complex environments. Other actual ships such as cargo ships cannot add various sensors and auxiliary equipment to verify and analyze the positioning system. This article takes the intelligent research and training dual-use ship of Dalian Maritime University, which integrates scientific research and training, as the object of study. This ship will not be affected by the voyage period and route and can choose a suitable sea area for research. Therefore, in order to improve the accuracy and reliability of the dynamic positioning system, research on the ship’s dynamic positioning system was carried out. Firstly, an accurate mathematical model of ship motion was established, and the hydrodynamic derivatives of ship model motion were obtained by nu-merical calculation, and applied to the three-degree-of-freedom model of the intelligent research and training dual-use ship. Then, the model was used as part of the closed-loop simulation model of the ship’s dynamic positioning system, and the terminal sliding mode controller was used for sim-ulation and emulation, thereby obtaining ideal simulation test results. This research helps to im-prove the accuracy and reliability of the dynamic positioning system and provides new ideas and methods for ship motion control.

Construction Design Management (DM) involves the coordination of design process and activity to ensure quality project design, yet it involves many challenges. This work reports on a collaborative Knowledge Transfer Project (KTP) that tackled several challenges faced by construction design management practitioners. Employing a design science research methodology (DSRM), qualitative analysis of semi-structured interviews with purposively identified design managers first uncovered real world concerns around design coordination, and designer performance monitoring. Then to address these concerns, a web-based design management prototype dashboard was developed which uses typical project data to aid the management of design coordination activity and facilitate design management task prioritization and reporting functionalities. By digitalizing selected design management processes to improve efficiency, and productivity, the visual reporting capability of the dashboard enables design production to be monitored at project and portfolio levels; trends in designer performance to be assessed and focus to be retained on technical queries (TQs) and requests for information (RFIs). By reporting on the development of this web-based Design Management prototype dashboard and illustrating how it can enhance design management productivity in construction firms, this work also provides further evidence of how employing a design science research methodology in construction can produce practical solutions that address real world construction concerns.

The Single Site Order – a policy restricting staff from working at multiple long-term care homes – was mandated by the Public Health Agency of Canada to control the spread of COVID-19 in long-term care homes, where nearly 70% of COVID-19-related deaths in Canada occurred. This mixed methods study assesses the impact of Single Site Order on long-term care residents in British Columbia. Interviews were conducted (residents (n=6), family members (n=9), staff (n=18), and leadership (n=10) from long-term care homes (n=4)) and analyzed using thematic analysis. Administrative data was collected between April 2019 – March 2020 and April 2020 – March 2021 and analyzed using descriptive statistics and data visualization. Qualitative and quantitative data were triangulated and demonstrate staffing challenges became worse during implementation of the SSO resulting in the mental and physical health deterioration of LTC residents. Qualitative data demonstrated decreased time for personalized and proactive care, increased communication challenges, and increased loneliness and isolation. Quantitative data showed a decline in activities of daily living, increased antipsychotic medication use, pressure ulcers, behavioural symptoms, and an increase in falls. Addressing staff workload and staffing shortages during SSO-related policy implementation is essential to avoid resident health deterioration.

This study evaluated the effectiveness of an electronic system for managing drug-sensitive pulmonary tuberculosis patients in the Kyrgyz Republic. This was a cohort study using programmatic data. The study included patients registered on the paper-based system in 2019 and the electronic system between June 2021 and May 2022. Data was taken from 302 individuals from the electronic system for completeness and concordance in comparison with the paper-based system. The study showed that for most variables the completeness and concordance was 85.3%-93.0% and was lowest for non-mandatory fields such as medication side effects (26.8% vs 13.6%). No significant difference was observed in time taken from symptom onset to diagnosis and treatment initiation between the two systems. However, the electronic system had a significantly higher percentage of patients who initiated treatment on the same day of diagnosis (80.3% vs. 57.1%). The proportion with successful outcomes was similar in both groups, but the electronic system had a significantly lower proportion of patients with outcomes that were not evaluated or recorded (4.8% vs. 14.3%, p &lt; 0.001). The study highlights the potential advantages of implementing an electronic TB register system for improving records. We advocate for similar studies in other regions in Kyrgyz Republic.

The world is moving to the next phase of the energy transition with high penetrations of renewable energy. Flexible and scalable redox flow battery (RFB) technology is expected to play an important role in ensuring electricity network security and reliability. Continuous performance improvements will further enhance their value by reducing parasitic losses and maximizing available energy conversion over broader operating conditions. Concentration overpotentials from poor internal reactant distribution at high and low states of charge (SOC) limit power densities and are thus an important area of investigation. However, efforts to address these coupled electrochemical phenomena can compromise mechanical performance. Modelling and simulation of cell design innovations have shown it is possible to reduce losses from pump energy while increasing the availability of active species where required. The combination of wedge-shaped cells with static mixers investigated in this paper can reduce pressure drop and improve energy efficiency. Toroidal vanadium redox flow battery (VRB/VRFB) designs incorporating this innovation are presented for further development to improve community engagement with the technology.

The shift towards Personalized Cancer Medicine (PCM) represents a significant transformation in cancer care, emphasizing tailored treatments based on genetic understanding of cancer at the cellular level. This review draws on recent literature to explore key factors influencing PCM implementation, highlighting the role of innovative leadership, interdisciplinary collaboration, and coordinated funding and regulatory strategies. Success in PCM relies on overcoming challenges such as integrating diverse medical disciplines, securing sustainable investment for shared infrastructures, and navigating complex regulatory landscapes. Effective leadership is crucial for fostering a culture of innovation and teamwork, essential for translating complex biological insights into personalized treatment strategies. The transition to PCM necessitates not only organizational adaptation but also the development of new professional roles and training programs, underscoring the need for a multidisciplinary approach and the importance of team science in overcoming the limitations of traditional medical paradigms. The conclusion underscores that PCM's success hinges on creating collaborative environments that support innovation, adaptability, and shared vision among all stakeholders involved in cancer care.

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

Suicide dynamics form a complex system deeply influenced by interrelated factors, necessitating advanced methodologies for comprehensive analysis. This study pioneers the application of Particle Markov Chain Monte Carlo (PMCMC) methods in suicide research, recognized for their enhanced sampling efficiency over traditional techniques in complex, high-dimensional models. PMCMC is particularly adept at handling non-Gaussian distributions and navigating parameter spaces efficiently, preventing the entrapment in local optima. Utilizing PMCMC, our research simulated a broad spectrum of potential outcomes, clarifying the probable scenarios and their likelihoods, thus enriching the predictive accuracy and understanding of suicide dynamics. These methods facilitated the exploration of dynamic interactions among key risk factors such as mental health issues, trauma, substance use, social isolation, and access to harmful means, whose complex interplays challenge predictive modeling. The study extends previous applications of PMCMC in complex systems like H1N1, opioid crises, and COVID-19 to the domain of suicide, suggesting its potential in enhancing decision-making and intervention strategies. However, limitations due to the model's simplified assumptions and the specificity of the data to certain populations underscore the necessity for broader application to validate findings across varied demographics. In summary, while PMCMC offers robust capabilities for the dynamic modeling of suicide, it requires careful parameter selection and consideration of computational demands. Future research should continue to leverage this approach in more complex settings, enhancing our ability to predict and mitigate suicide risks effectively.

Role identity theory describes the purpose and meaning in life that comes, in part, from occupying social roles. While robustly linked to health and well-being, this may become, however, when an individual is unable to fulfil the perceived requirements of an especially salient role in the way that they believe they should. Amid high rates of mental illness among public safety personnel, we interviewed a purposely selected sample of 21 paramedics from a single service in Ontario, Canada to explore incongruence between an espoused and able-to-enact paramedic role identity. Situated in an interpretivist epistemology, and using successive rounds of thematic analysis, we developed a framework for role identity dissonance wherein chronic, identity-relevant disruptive events cause emotional and psychological distress. While some participants were able to recalibrate their sense of self and understanding of the role, for others, this dissonance was irreconcilable, contributing to disability and lost time from work. In addition to contributing a novel perspective on paramedic mental health and well-being, our work also offers a modest contribution to the theory in using the paramedic context as an example to consider identity disruption through chronic workplace stress.

Thousands of antibodies for diagnostic and other analytical purposes are on the market. However, it is often difficult to identify duplicates, reagent changes, and to assign the correct original publications to an antibody. This slows down scientific progress and might even be a cause of irreproducible research and a waste of resources. Recently, activities were started to suggest the sole use of recombinant antibodies in combination with the open communication of their sequence. In this case, such uncertainties should be eliminated. Unfortunately, this approach seems to be rather a long-term vision since the development and manufacturing of recombinant antibodies remain quite expensive in the foreseeable future. Also, nearly all commercial antibody suppliers may be reluctant to publish the sequence of their antibodies, since they fear counterfeiting. De-novo sequencing of antibodies is also not feasible today for a reagent user without access to the hybridoma clone. Nevertheless, it seems to be crucial for any scientist to have the opportunity to identify an antibody undoubtedly to guarantee the traceability of any research activity using antibodies from a third party as a tool. For this purpose, we developed a method for the identification of antibodies based on a MALDI-TOF-MS fingerprint. To circumvent lengthy denaturation, reduction, alkylation, and enzymatic digestion steps, the fragmentation was performed with a simple formic acid hydrolysis step. Eighty-nine unknown monoclonal antibodies were used for this study to examine the feasibility of this approach. Although the molecular assignment of peaks was rarely possible, antibodies could be easily recognized in a blinded test, simply from their mass-spectral fingerprint. A general protocol is given, which could be used without any optimization to generate fingerprints for a database. We want to propose that in most scientific projects relying critically on antibody reagents, such a fingerprint should be established to prove and document the identity of the used antibodies and to assign a specific reagent to a datasheet of a commercial supplier, a public database record or an antibody ID.

AI is extraordinarily useful technology but it is becoming increasingly powerful with rapidly growing capabilities to disrupt and harm human society. We call on international and national organizations and individuals to join forces in banning the development of superintelligent AI and introducing regulations to prevent and mitigate AI-caused harm.

This research paper aimed to explore the impact of childhood and adolescent experiences on the leadership development of Emirati women in the United Arab Emirates (UAE). Using a qualitative research methodology, the study utilized in-depth narrative semi-structured interviews, document analysis, and diary writing to understand the complex issue of leadership development. Findings indicate that childhood and adolescent experiences, including family upbringing, education, culture, and societal expectations, have significant impacts on the leadership development of Emirati women. Specifically, family upbringing and cultural values shape Emirati women's leadership aspirations and behaviors, while education and societal expectations provide opportunities and barriers for women's leadership development. The implications of these findings for policymakers and practitioners seeking to promote women's leadership development in the UAE are discussed.

The article discusses determinants of living environment in Central and Eastern Europe. As an example, the city of Radzionkow was chosen, with 16 thousand inhabitants, located in the Silesia agglomeration in southern Poland, in the area where hard coal has been mined for almost two hundred years, which largely serves as a source of heating for houses and flats. 360 buildings in 6 groups of 60 buildings were examined in the selected city, which allowed to distinguish 3 different areas in terms of the quality of the living environment depending on the technical condition of buildings, the method of heating and location. To a large extent, determinants are the existing spatial and geophysical conditions of a given location. Many research and reports on the living environment do not take into account the factors mentioned, focusing only on the statistical data of pollution, excluding spatial factors. In the research presented, the author, taking into account location variables, shows differences in the measurements of air pollution in relation to the designated location zones depending on the morphological structure of the building, the degree of its modernization and the types of heating used in buildings.