Specific Context Research Articles

Learning about science topics of social relevance using lower and higher autonomy-supportive scaffolds

Evaluation of plausible alternative explanations of scientific phenomena is an authentic scientific activity. Instructional scaffolding can facilitate students’ engagement in such evaluations by facilitating their reflections on how well various lines of scientific evidence support alternative explanations. In the present study, we examined two forms of such scaffolding, with one form providing more autonomy support than the other, to determine whether any differential effects existed between the two. Nearly 300 adolescent students in middle school, high school, and university courses completed two activities on scientific topics of social relevance (e.g., the climate crisis, fossils and fossil fuel use, water resources, and astronomical origins), with the less autonomy-supportive form being completed prior to the more autonomy-supportive form. In line with prior pilot studies, both scaffold types demonstrated significant pre- to post-instructional shifts in plausibility judgments toward the scientific model and gains in knowledge with small to medium effect sizes. A mediation model provided a robust replication of previous findings showing that the indirect path meaningfully linked greater levels of evaluation to more scientific plausibility judgments and topic knowledge, above and beyond the direct relational path linking greater levels of evaluation to topic knowledge. However, we found no difference in relations between the two scaffold types, counter to our hypothesis that the more autonomy-supportive version would lead to better outcomes. This suggests that the implementation of more autonomy-supportive learning environments may be conditional, opening up a promising avenue for additional research, such as looking at specific contexts and how activities could be sequenced to optimize learning.

Knowledge mobilization between the food industry and public health nutrition scientists: findings from a case study

BackgroundImproving the nutritional quality of the food supply increases access to nutritious foods, which improves dietary habits and population health. Yet, knowledge mobilization initiatives between public health nutrition researchers and food industries are often not adequately considered and understood. This study explored what elements related to this specific context need to be recognized so that researchers can better mobilize nutrition science knowledge with the food industry to promote the nutritional improvement of food products.MethodA case study qualitative approach was selected to answer the research question, using semi-structured interviews as the data collection technique. Québec baking industry actors were shown a mock-up of an online mobilization platform sharing the results of the Food Quality Observatory that describes the nutritional quality of breads offered in Québec, Canada. They were asked to think aloud as they explored the web platform and were interviewed. Two coders analyzed the data using an inductive approach and thematic content analysis, starting with individual open coding, and then put forward their analyses and drafted the final themes.ResultsThe final data consisted of 10 semi-structured interviews conducted between October 2019 and August 2020. Four main themes were identified: the industry’s context, the knowledge mobilization initiative, the product-related matters stemming from the information shared and the motivation within the industry. Within each theme, sub-themes were highlighted and related to the industries’ motivation to improve their products’ nutritional quality. This study also specified key considerations for changes to the sodium and fiber content in bread.ConclusionOther steps beyond using simple language and a website format could be taken to better mobilize scientific knowledge with food industries, such as providing more consumer information, using an integrated knowledge mobilization approach that includes a consideration of ethics, working with communication professionals, collaborating with food science experts, and providing resources to act on shared information. Legislation such as the front-of-pack regulations could accelerate the pace of collaboration between researchers and industry. Overall, establishing a prior relationship with industries could help gain a better understanding of the themes highlighted in this study. Future research could build on this case study to provide more insights and solidify these findings.Classification codesPublic Health, Public Private, Policy Making, Research Institutions, Use of Knowledge.

Team resilience in high-performance women’s football: Contextual stressors and opportunities for development

The purpose of this study was to conduct a pre-intervention team resilience needs assessment in the context of high-performance women’s football. The needs assessment included a review of the literature, focus group discussions, and input from an expert steering group. Following scoping meetings with senior personnel from the National Governing Body, teams in the top two tiers of a professional women’s football league and within the academy structure were contacted. Five focus groups made up of football players were conducted. Altogether, 27 participants (Mage = 23.96, SD = 4.49) took part. The focus groups were analyzed using reflexive thematic analysis from a critical realist standpoint. The study identified the contextual stressors that high-performance women’s football teams encounter (i.e., organizational stressors arising from a newly professionalized environment and on-pitch stressors arising from low social resources), effective team resilience practices currently employed by group members (i.e., establishing a strong foundation for high quality relationships; unity in managing pressure; and learning from setbacks to inform future preparation for adversity) and the perceived gaps for team resilience development (i.e., limited effectiveness and inconsistent use of deliberate pressure training; inadequate psycho-social resources; and lack of effective proactive group level strategies during pressure). The study highlighted the importance of a systematic needs assessment within an Intervention Mapping Framework prior to undertaking an intervention as several nuances to the specific context of high-performance women’s football were identified.

Differential impacts of health systems and sociocultural environment on vulnerable populations during the COVID-19 pandemic: lessons from four Asia-Pacific countries

BackgroundThis study aims to evaluate healthcare systems and pandemic responses in relation to marginalized and vulnerable groups, identify populations requiring urgent care, and assess the differential impacts on their health during the pandemic.MethodsData were collected by the Asia-Pacific Observatory on Health Systems and Policies (APO)–National University of Singapore and APO–International Health Policy Program consortium members: Korea, Indonesia, Philippines, and Singapore. Data were collected through a combination of semi-structured interviews, policy document reviews, and analysis of secondary data.ResultsOur findings reveal that the pandemic exacerbated existing health disparities, particularly affecting older adults, women, and children. Additionally, the study identified LGBTI individuals, healthcare workers, slum dwellers, and migrant workers as groups that faced particularly severe challenges during the pandemic. LGBTI individuals encountered heightened discrimination and limited access to health services tailored to their needs. Healthcare workers suffered from immense stress and risk due to prolonged exposure to the virus and critical working conditions. Slum dwellers struggled with healthcare access and social distancing due to high population density and inadequate sanitation. Migrant workers were particularly hard hit by high risks of virus transmission and stringent, often discriminatory, isolation measures that compounded their vulnerability. The study highlights the variation in the extent and nature of vulnerabilities, which were influenced by each country’s specific social environment and healthcare infrastructure. It was observed that public health interventions often lacked the specificity required to effectively address the needs of all vulnerable groups, suggesting a gap in policy and implementation.ConclusionsThe study underscores that vulnerabilities vary greatly depending on the social environment and context of each country, affecting the degree and types of vulnerable groups. It is critical that measures to ensure universal health coverage and equal accessibility to healthcare are specifically designed to address the needs of the most vulnerable. Despite commonalities among groups across different societies, these interventions must be adapted to reflect the unique characteristics of each group within their specific social contexts to effectively mitigate the impact of health disparities.

Constructing a resilience measurement model for small and medium-sized enterprises in Vietnam: A PLS-SEM approach

Small and medium-sized enterprises (SMEs) constitute around 97% of the total number of businesses in Vietnam, which contributes to 60% of the national growth. In a dynamic and uncertain business environment, both domestically and internationally, the resilience of SMEs has become a topic of significant interest among researchers and practitioners. Resilience, however, is a multifaceted concept that depends on the specific context in which it is applied. Therefore, this study aims to construct a measurement model for assessing the resilience of SMEs in Vietnam. Drawing from a dataset collected from 500 SMEs and employing the PLS-SEM technique. the findings of this research indicate that the resilience index is a combination of reflective and formative models. Resilience at level three is a formative construct comprising four prioritized components: agility, anticipatory capability, flexibility, and adaptability. The reflective measurement model of agility, anticipation, flexibility, and adaptability confirms its reliability and validity. These findings form the basis for the effective allocation of resources to enhance resilience within SMEs. Understanding the nuanced aspects of resilience can benefit in developing targeted strategies to bolster SMEs against the challenges posed by an ever-changing business landscape.

Design and Psychometric Properties of the Student Perception of Teacher Care Scale in University Students

Teacher care in the university setting is crucial for the academic, emotional, and social development of students, encompassing moral virtues such as compassion and professional competence. The students’ perception of teacher care directly relates to their well-being and active participation in learning. Despite the recognized importance of teacher care, there is a lack of adequate instruments to measure it, especially in specific cultural and educational contexts like Peru. The aim of this research is to develop and assess the psychometric properties of a scale measuring student perception of teacher care in the Peruvian university context, to provide a valid and reliable tool for future research and educational practices. An instrumental study was conducted with 910 university students aged between 18 and 50 years (M = 20.2, SD = 3.45). The Student Perception of Teacher Care Scale (SPTCS) was used, divided into five dimensions (Compassion, Competence, Confidentiality, Trust, and Awareness). Exploratory (EFA) and confirmatory (CFA) factor analyses were conducted to evaluate the scale’s internal structure, along with reliability analyses and measurement invariance across genders. The EFA identified a four-factor structure reflecting the dimensions of Confidentiality and Trust, Competence, Awareness, and Compassion. The CFA confirmed this structure with good fit indices for four-factor models, which was then adjusted to a five-factor model, one of which is a second-order factor (χ2 = 720.727, df = 369, CFI = 0.951, TLI = 0.946, RMSEA = 0.046, and SRMR = 0.032). Internal reliability was high (α and ω > 0.9 for all factors). Measurement invariance was established across genders, allowing for valid comparisons between men and women. It is concluded that the Student Perception of Teacher Care Scale proves to be a valid and reliable instrument for measuring teacher care in the Peruvian university context. The results emphasize the multidimensionality of teacher care and its significance for the educational environment and student experience. This study contributes to educational research and teaching practice, offering a means to assess and improve caring relationships in higher education.

Strategies for Mitigating Risks of Government-Led Energy Retrofitting Projects in China

Residential energy retrofitting projects in the hot summer and cold winter (HSCW) zone of China face various risks related to project activities, which incur transaction costs (TCs), such as search, negotiation, and monitoring costs. As the leader in project implementation, the Chinese government is responsible for project planning, organisation, and coordination. However, TCs impede the government’s ability to execute risk-related project activities effectively, subsequently increasing the probability of the occurrence of risk. Drawing on transaction cost economics (TCE), this study proposes a theoretical framework to understand the barriers—such as asset specificity, uncertainty, and frequency—that prevent the government from performing project activities and mitigating risks effectively. An artificial neural network (ANN) is applied to verify the hypotheses. The results underscore experience and operational maturity in project activities, cost and time constraints, and the immature retrofitting market as significant impediments to the government’s execution of risk-related activities. Considering the varying roles of the government in reducing different risks, this study concludes by offering policy recommendations to alleviate these activity barriers and mitigate risks. By employing a TCs perspective, this study not only identifies key barriers but also deepens our understanding of risk mitigation mechanisms, providing robust policy insights tailored to the specific regional context of China, thereby enhancing both the execution and the framework of government-led retrofitting projects.

Introducing a Scale for Measuring Attachment to Urban Green

Urban green contributes to enhanced well-being and overall quality of life in urban populations. The concept of place attachment provides an established avenue for exploring the intricate connections between urban environments and personal experiences. Building on the notion of place attachment, we investigated the perceptions of horizontal and vertical urban green by introducing a novel Urban Green Attachment (UGA) scale. A cross-sectional study using an online survey in German, measuring emotional, cognitive, and behavioral relations to urban vegetation, was conducted among 164 adult inhabitants of the Volkert quarter in Vienna, Austria. Using principal component analysis, we found that the UGA scale was a reliable measure of attachment to urban green, with ten items within the “attachment” factor. Study participants highly valued vertical green, but did not differentiate their attachment to it from horizontal greenery within the specific local context and by design of the measures we used. Thus, further studies and ethnographic investigations, preferentially accompanied by methods such as walking interviews, are needed to test the scale for other populations and settings. The UGA scale emerges as a valuable tool for advancing understanding in this critical area, given the current climate change-driven transformations of cities, building on the creation of green infrastructure.

On the co-optation of according to as an evidential in English

Abstract The use of according to + NP has rarely been the topic of any specialized research in relation to English evidentiality, although it would probably figure among the most frequent types of reportative evidentials found in written texts. One of the problems often associated with reportatives has related to the existence of the Reportative Exception (see, e.g. AnderBois 2014), referring to the fact that the speaker may not always subjectively endorse the proposition conveyed with the support of the evidential phrase. The present study reviews the history of according to + NP from Middle English onwards, after which it began to develop evidential functions, and shows how the tendency to reject the truth of the content of the proposition marked by according to + NP arose in specific contexts containing alternative information sources, comparison, or adversative clauses. It was shortly after the diachronic appearance of according to + NP in such contexts that the more periphrastic form, in accordance with + NP, began to renovate/renew the earlier, non-evidential meanings of according to + NP. The present study also attributes the development of according to + NP to a process of co-optation (e.g. Heine 2013) rather than grammaticalization.

Untangling the Tongues: Exploring Pronunciation Development Strategies for Learners of English at High Schools in Oromia Region of Ethiopia

One of the most important aspects of learning a new language is mastering the pronunciation of that language. It is crucial in helping second language learners improve their communication skills and overall performance. Mastering proper pronunciation is a difficult and subtle part of teaching English as a foreign or second language. The focus of this study is to assess the contributing factors affecting ESL students' pronunciation. The study used a quantitative research approach. A total of 189 students from Burayu High School were chosen at random sampling technique for this study. The researchers collected data through a questionnaire. SPSS version 26 was used to analyze the data obtained from the respondents of the survey. Factors influencing pronunciation that were identified in this study include poor motivation, lack of confidence, exposure, practice, interest, an unfriendly atmosphere, one's native language interference, age, personal traits of the learners, instructional approach, and feedback deficiency. The findings also provide valuable insights into preferred pronunciation learning strategies among students of English in the Oromia region of Ethiopia and explore the impact of individual and environmental factors, including first language influence, strengths, and weaknesses of current teaching methodologies in fostering pronunciation development in this specific context. This study will contribute to the development of more effective and learner-centered pedagogical approaches for pronunciation instructions in English language programs designed for English learners in the Oromia region of Ethiopia.

STYLISTIC ROLE OF DETERMINED VOCABULARY IN PUBLICISTIC STYLE (Based on the material of Lina Kostenko’s article “The Humanitarian Aura of a Nation, or The Defect of the Main Mirror”)

This research aims to analyze the stylistic possibilities of deterministic vocabulary in a journalistic style based on the material of Lina Kostenko’s article “The Humanitarian Aura of the Nation, or the Defect of the Main Mirror”. To achieve this goal, we have carried out a continuous selection of quotes from the analyzed article using lexical units that have undergone determination; described the thematic classes of deterministic lexemes, distinguished the decisions of the functional, lexical-semantic, and traced semantic-stylistic levels, the semantic modifications of the deterministic vocabulary; revealed the stylistic role of determinations for achieving a communicative goal. The article uses several linguistic and general scientific research methods: the continuous selection method that we used to single out quotes in which the author used deterministic lexemes; based on semantic analysis, we have carried out a thematic classification of the studied material; statistical methods made it possible to reveal quantitative parameters of thematic groups of deterministic vocabulary; with the help of structural-thematic and semantic analysis, we have classified selected lexemes according to the levels of determination; we have also applied the interpretive method to reveal the semantics of deterministic lexical units in specific contexts, of analysis. We have also used descriptive, comparative, component, and deductive research methods to accomplish the article’s aim. We have singled out 167 quotations with lexical units that underwent determination and were used for different stylistic or content purposes. We have identified 146 terms of twenty-one thematic groups. The most frequently presented general scientific terms (19.2%), political science (13.8%), psychological (9.6%), and historical (8.9%) terms, the dominance of which can be explained primarily by the content features of the analyzed work. Considering the degree of loss of the signs of the term by the lexeme, 67% of determined lexemes are functional determinations that belong mainly to the groups of general scientific terms and terms of the socio-political sphere. We have established that the functional determinations reflect the features of the modern communicative space, testify to the high intellectual level of the author, and are aimed at the same educated readers. Determinations of the lexical-semantic level arise due to the modification of term semantics and the emergence of a new, universal meaning of the lexeme, usually recorded in explanatory dictionaries. Thanks to the combination of language units from different thematic fields, seven intentions are actualized, additional common language connotations are superimposed, and original imagery arises – all this contributes to the emergence of a specific expression inherent in the journalistic style of literary language. We have revealed that the term gets the semantic-stylistic level of determination when it undergoes certain semantic modifications and becomes an element of an artistic device (trope, stylistic figure). The specificity of Lina Kostenko’s creative style determines the presence of complex artistic images in the analyzed work, which combine semantic transformations and stylistic means – figures, and tropes. Usually, artistic metaphors with antitheses, oxymorons, epithets, phraseology, etc., are intertwined in one quote. Determinations contribute to the semantic accuracy, exactness, and imagery of speech and reflect the author’s subjective perception of the corresponding subject or phenomenon, strengthen the author’s assessment of what was said, and contribute to the statement’s expression.

Scope Management in Industry 4.0 Projects

This study investigates the implementation of marketing innovations within the framework of Industry 4.0, focusing on Asian corporate culture. Companies must innovate in the rapid globalization and digital transformation era to stay competitive and meet evolving client demands. The research identifies 15 critical attributes essential for marketing innovation in Industry 4.0, including augmented reality, virtual cryptocurrencies, and the Internet of Things (IoT). These innovations represent a blend of technological and non-technological advancements companies use to enhance their marketing strategies. The study examines the impacts of these innovations through a survey of 50 companies utilizing Industry 4.0 technologies. Key findings indicate significant impacts such as increased competitiveness, improved customer communication, and enhanced work efficiency. Larger companies and those in the automotive sector rate these impacts more highly, reflecting their greater reliance on technological advancements. Additionally, the study reveals that cultural factors influence the perception of these impacts, with companies in Asian cultures exhibiting varied responses compared to those with a global business culture. The pilot study utilized qualitative and quantitative methods, including structured surveys and descriptive statistical analysis. The results underscore the importance of effective scope management in successfully implementing Industry 4.0 projects, emphasizing the need for clear goal-setting, resource allocation, and change control. The research highlights the necessity for organizations to adapt their corporate culture and develop innovative marketing strategies tailored to their specific contexts. These insights offer practical recommendations for optimizing project outcomes and maintaining competitiveness in the digital age.

INTEGRATING MACHINE LEARNING AND BIG DATA ANALYTICS FOR REAL-TIME DISEASE DETECTION IN SMART HEALTHCARE SYSTEMS

The integration of machine learning (ML) and big data analytics within smart healthcare systems represents a transformative advancement in medical services, emphasizing efficiency, accuracy, and patient-centered care. This paper investigates the application of these advanced technologies in real-time disease detection, showcasing their potential to revolutionize healthcare delivery. Smart healthcare systems leverage a multitude of technological components, including Internet of Things (IoT) devices, sensors, and artificial intelligence (AI), to enable continuous monitoring and diagnostics. This real-time monitoring facilitates prompt interventions and treatment adjustments, which is particularly advantageous for managing chronic conditions and acute illnesses where timely responses are critical to improving patient outcomes. Despite the evident benefits, traditional healthcare infrastructures face significant challenges such as delays in diagnosis due to manual processes, inefficient data handling resulting in data silos, and limited interoperability between different healthcare providers, leading to worsened health outcomes and increased healthcare costs. The integration of ML and big data analytics offers promising solutions to these challenges. ML algorithms can process vast amounts of healthcare data to identify patterns and predict outcomes with high accuracy, such as recognizing early signs of diseases like cancer or diabetes from medical images or electronic health records (EHRs). Big data analytics complements ML by providing the necessary infrastructure to handle and process large volumes of health data, enabling the collection, storage, and analysis of structured data from EHRs, unstructured data from clinical notes, and real-time data from wearable devices. By integrating these technologies, healthcare providers can gain deeper insights into patient health trends and outcomes, leading to more informed decision-making and better patient management. This study employs a qualitative research design, focusing on five genuine case studies: the Mayo Clinic's predictive analytics for heart disease, Cleveland Clinic's use of ML for cancer diagnosis, Kaiser Permanente's diabetes management program, Johns Hopkins Hospital's sepsis detection system, and Mount Sinai Health System's genomic data analysis. Each case study is chosen for its relevance and comprehensive data, detailing the specific healthcare environment and context. This paper interprets these findings in the broader context of smart healthcare systems and existing literature, emphasizing the importance of these technologies in modernizing healthcare and addressing inefficiencies. The challenges encountered during integration, such as data privacy concerns and interoperability issues, are examined along with implemented solutions.

The Impact of Outpatient Parenteral Antimicrobial Therapy (OPAT) in Al Hada Armed Forces Hospital, Taif, Saudi Arabia

Background In the realm of healthcare quality, outpatient parenteral antimicrobial therapy (OPAT) has emerged as the gold standard for managing patients who have transitioned from inpatient care but still require extended intravenous antimicrobial treatment. The adoption of OPAT at Al Hada Armed Forces Hospital in Taif, Saudi Arabia, not only bolsters patient satisfaction but also serves as a catalyst for reduced hospitalization durations, lower rates of emergency department readmissions, and an overall reduction in healthcare expenditures. The main objective of this study was to evaluate the effectiveness of OPAT in a tertiary center facility in Saudi Arabia. Methods In this retrospective investigation, we conducted a thorough review of patient records spanning from November 2020 to October 2021. Our study encompassed all patients who had intravenous antibiotics and were participants in the hospital’s OPAT program during this specific timeframe. Our primary goal was to achieve a 20% reduction in the total number of hospital bed days related to long-term antibiotic therapy. Results The incorporation of OPAT has yielded a multifaceted transformation within the hospital. Over the span of one year, from November 2020 to October 2021, there was a notable decrease in the proportion of patients requiring intravenous antibiotics. This percentage initially dropped from 23% to 12% with the implementation of the OPAT quality improvement project, and later, it reached an even lower 8%. This positive transformation not only had a positive impact on patient care but also led to significant cost savings, exceeding 2 million riyals. These savings were primarily driven by the reduction in hospitalization duration and the more efficient allocation of resources. Moreover, this improvement contributed to the avoidance of 673 patient days of hospitalization, thereby creating additional resources for more critical cases. Conclusion OPAT has emerged as a pivotal component of Al Hada Armed Forces Hospital’s commitment to elevating healthcare quality. This abstract offers a concise insight into the quality-driven impact of OPAT within a specific healthcare context, underlining its capacity to optimize patient care, enhance healthcare efficiency, and elevate resource allocation. Ongoing research and continuous evaluation will play a critical role in refining and expanding the OPAT program while preserving its quality-oriented perspective.

The InterModel Vigorish as a Lens for Understanding (and Quantifying) the Value of Item Response Models for Dichotomously Coded Items.

The deployment of statistical models-such as those used in item response theory-necessitates the use of indices that are informative about the degree to which a given model is appropriate for a specific data context. We introduce the InterModel Vigorish (IMV) as an index that can be used to quantify accuracy for models of dichotomous item responses based on the improvement across two sets of predictions (i.e., predictions from two item response models or predictions from a single such model relative to prediction based on the mean). This index has a range of desirable features: It can be used for the comparison of non-nested models and its values are highly portable and generalizable. We use this fact to compare predictive performance across a variety of simulated data contexts and also demonstrate qualitative differences in behavior between the IMV and other common indices (e.g., the AIC and RMSEA). We also illustrate the utility of the IMV in empirical applications with data from 89 dichotomous item response datasets. These empirical applications help illustrate how the IMV can be used in practice and substantiate our claims regarding various aspects of model performance. These findings indicate that the IMV may be a useful indicator in psychometrics, especially as it allows for easy comparison of predictions across a variety of contexts.

Effect of Green HRM and Green Self-efficacy on Pro-environment Behavior-Mediating Role of Environmental Commitment

The basic aim of sustainability is to promise a good future for our planet and the upcoming generations. This can be achieved by raising awareness regarding sustainable development among people. The present research explores the relationship between green human resource management, green self-efficacy, and pro-environment behavior with the mediating role of environmental commitment. The research was based on a structured questionnaire on employees working in the universities of Pakistan. The data was collected from 600 employees working in the universities of Pakistan through convenience sampling. Smart PLS-SEM was used in the analysis. The study found that the relationship between green human resource management and green self-efficacy with pro-environment behavior is significant in the presence of environmental commitment. The mediating role of environmental commitment is tested using bootstrapping techniques. The research makes contributions to theoretical and practical fields. Convenience sampling might have introduced a bias in the data, limiting the generalizability of the findings beyond the specific sample of employees from universities in Pakistan. Since the research was conducted in the specific context of Pakistan, cultural factors might have influenced the responses and relationships, thereby limiting the generalizability of the findings to other cultural contexts.Future reserachers might conduct longitudinal studies to investigate the long-term effects of green human resource management and green self-efficacy on pro-environment behavior, thus providing a deeper understanding of the causal relationships over time.In addition future researchers might supplement the quantitative findings with qualitative studies to gain a deeper insight into the underlying mechanisms and to capture the nuances and complexities of individuals' experiences and perceptions related to green human resource management and pro-environment behavior.

Automatized self-supervised learning for skin lesion screening

Melanoma, the deadliest form of skin cancer, has seen a steady increase in incidence rates worldwide, posing a significant challenge to dermatologists. Early detection is crucial for improving patient survival rates. However, performing total body screening (TBS), i.e., identifying suspicious lesions or ugly ducklings (UDs) by visual inspection, can be challenging and often requires sound expertise in pigmented lesions. To assist users of varying expertise levels, an artificial intelligence (AI) decision support tool was developed. Our solution identifies and characterizes UDs from real-world wide-field patient images. It employs a state-of-the-art object detection algorithm to locate and isolate all skin lesions present in a patient’s total body images. These lesions are then sorted based on their level of suspiciousness using a self-supervised AI approach, tailored to the specific context of the patient under examination. A clinical validation study was conducted to evaluate the tool’s performance. The results demonstrated an average sensitivity of 95% for the top-10 AI-identified UDs on skin lesions selected by the majority of experts in pigmented skin lesions. The study also found that the tool increased dermatologists’ confidence when formulating a diagnosis, and the average majority agreement with the top-10 AI-identified UDs reached 100% when assisted by our tool. With the development of this AI-based decision support tool, we aim to address the shortage of specialists, enable faster consultation times for patients, and demonstrate the impact and usability of AI-assisted screening. Future developments will include expanding the dataset to include histologically confirmed melanoma and validating the tool for additional body regions.

Enhanced Indoor Air Quality Dashboard Framework and Index for Higher Educational Institutions

This research proposes a 10-step methodology for developing an enhanced IAQ dashboard and classroom index (CI) in higher educational facilities located in arid environments. The identified parameters of the enhanced IAQ dashboard–inspired by the pandemic experience, result from the literature review and the outcome of two electronic surveys of (52) respondents, including health professionals and facility management experts. On the other hand, the indicators included in the CI are based on (80) occupant survey responses, including parameters related to IAQ, Indoor Environmental Quality (IEQ), and thermal comfort, amongst other classroom operative considerations. The CI is further tested in four learning spaces at the American University in Cairo, Egypt. The main contribution of this research is to suggest a conceptual visualization of the dashboard and a practical classroom index that integrates a representative number of contextual indicators to recommend optimal IAQ scenarios for a given educational facility. This study concludes by highlighting several key findings: (1) both qualitative and quantitative metrics are necessary to capture indoor air quality-related parameters accurately; (2) tailoring the dashboard as well as the CI to specific contexts enhances its applicability across diverse locations; and finally, (3) the IAQ dashboard and CI offer flexibility for ad-hoc applications.

From perception to prediction: A comparative study of thermal comfort assessment techniques in school facilities

Indoor environmental quality (IEQ) significantly affects learning, health, and productivity in educational buildings, particularly classrooms. Thermal comfort is crucial to IEQ in classrooms, and various approaches have been developed to assess it. This study compares subjective evaluation, fieldwork measurement, and simulation methods in naturally ventilated secondary school classroom environments in Abuja, Nigeria. It evaluates their reliability, validity, advantages, and limitations. In achieving this objective, fieldwork measurements, questionnaire surveys, and building simulations were conducted in 83 classrooms with 2758 respondents. The data were subjected to descriptive and inferential statistical analysis using the analytical software programs SPSS version 23 and Microsoft Excel. The study found that the Actual Mean Vote (AMV) comfort operative temperature for classrooms was 28.7 °C. Findings from the comparative analysis of the methods indicate that the PMV generally overestimates students’ thermal sensation and that the fieldwork measurement Predicted Mean Votes (PMVf) undervalues the neutral temperature by 4.2 °C. In contrast, the computer-simulated Predicted Mean Votes (PMVs) undervalues it by 3.9 °C. The study found that all three methods are valid and reliable, with some advantages and limitations, depending on the assessment’s specific context and goals. The findings provide valuable insights into improving indoor environmental quality and occupant satisfaction in educational buildings, contributing to the discourse on assessing thermal comfort in classrooms and informing the development of more effective assessment methods. The systematic comparison of these methods addresses a notable gap in the literature, providing practical insights to optimize thermal conditions in learning environments.

Systemic inflammatory markers in neoadjuvant pembrolizumab therapy for triple-negative breast cancer: Prognostic insights and nomogram construction.

e12649 Background: Systemic inflammatory markers derived from peripheral blood cells, such as the neutrophils and lymphocytes ratio (NLR), derived neutrophil lymphocyte ratio (dNLR), platelet-lymphocyte ratio (PLR), and lymphocyte–monocyte ratio (LMR), have shown promise as prognostic markers. Currently, neoadjuvant treatment (NACT) for early triple-negative breast cancer (eTNBC) involves the addition of an immune therapy, and little is known about the variation of these markers in this specific context. Methods: This study evaluated two groups who received NACT for eTNBC in a single third-level cancer center. The first received NACT with EC X4 and a weekly paclitaxel regimen, the second pembrolizumab and NACT. A total of 70 patients were included, 37 patients in the pembrolizumab group. NLR was defined as the absolute blood neutrophil count (N) divided by the absolute lymphocyte count (L), dNLR was defined as the N divided by the derived L (absolute leukocyte count — N), PLR was defined as the absolute platelet count divided by the L, LMR was defined as the L divided by the absolute monocyte count. Association between systemic inflammatory markers and pathological complete response (pCR) was analyzed using statistical tests. Inflammatory markers were evaluated at the time of diagnosis, at the time of chemotherapy regimen change, and 1 week before surgery. The χ2 test or Fisher’s exact test was used for correlation and Student’s t-test to compare different groups. Results: The pCR rates were 60,6% in the standard therapy and 77,8% in the pembrolizumab. There were no significant differences in clinical characteristics between the two groups. NLR, dNLR, PLR and LMR at 6 months showed significant differences compared to baseline levels. dNLR in the immunotherapy group, at the end of therapy, showed statistical significance with the Welch Two Sample t-test with p-value = 0.001. Variables were weighted with respect to the type of treatment and the outcome was assessed as pCR. On the basis of these data, a nomogram was constructed to predict the likelihood of achieving pCR in patients undergoing neoadjuvant pembrolizumab therapy. Conclusions: This study highlights the potential of systemic inflammatory markers as prognostic indicators in patients with eTNBC undergoing NACT. dNLR is a novel biomarker associated with clinical outcome in solid tumors. In this study, for the first time, a correlation was found between the use of pembrolizumab and the change in dNLR and consequently its impact on pCR. A nomogram was constructed to predict the outcome of pCR. [Table: see text]