Search Results (4,954)

This paper applied an adapted design sprint approach, called a design summit, to educational prototyping. Design sprints provide a structure for applying design thinking and capturing user requirements that can be adapted to the needs of varied design contexts. However, finding a format that meets project requirements and brings in diverse stakeholders while also considering their availability can be difficult to construct using a traditional design sprint approach. Through four adapted stages of understanding, defining, iterating and prototyping towards a problem space, this paper presents a case study of a design summit applied to education/instructional design, specifically towards the problem of designing teacher professional development on the topic of the high ability (HA) student. A key feature in our applied approach is using concurrent prototyping, over many months, to achieve project outcomes. The case study presents the process and challenges of developing educational resources suited to the professional development of teachers and school leaders that need to support HA students. Through iteration, the results show how diverse stakeholders engaged and provided feedback to inform prototyping outcomes. Our design summit case study demonstrates how careful planning, focused elicitation of user requirements and an elongated and concurrent prototyping process results in outcomes that meet education stakeholder expectations and align with project requirements. Full article

The problem of geolocating Reddit users without access to the author information API is tackled in this study. Using subreddit data, we analyzed and identified user location based on their interactions within location-specific subreddits. Using unsupervised learning methods such as Latent Dirichlet Allocation (LDA) and Non-Negative Matrix Factorization (NMF) algorithms, we examined conversations about COVID-19 and immunization across the U.S., focusing on COVID-19 vaccination. Our topic modeling identifies four themes: humor and sarcasm (e.g., jokes about microchips), conspiracy theories (e.g., tracking devices and microchips in the COVID-19 vaccine), public skepticism (e.g., debates over vaccine safety and freedom), and vaccine brand concerns (e.g., Pfizer, Moderna, and booster shots). Our geolocation analysis shows that regions with lower vaccination rates often exhibit a higher prevalence of misinformation-labeled comments. For example, counties such as Ada County (Idaho), Newton County (Missouri), and Flathead County (Montana) showed both a low vaccine uptake and a high rate of false information. This study provides useful information on the many different examples of misinformation that are disseminated online. It gives us a better understanding of how people in different parts of the U.S. think about getting a COVID-19 vaccine. Full article

Background: As the social-emotional well-being of children as a whole and specifically during the transition to kindergarten is of paramount importance, it is important to continuously research this topic using a multi-informant approach. Moreover, a further contribution of this study lies in addressing the substantial gap in the existing literature within this important field. Objectives: Starting from the Ecological-Dynamic Transition Model and the Positive Development and Resilience in Kindergarten (PERIK) Model, the main aim of this research was to analyze parents’ and teachers’ perceptions of children’s social-emotional well-being during the transition and adjustment, and the quality of transition and adjustment. Methods: The study was conducted on a sample of parents (N = 154; 147 mothers) and teachers from 4 kindergartens (N = 12, all female) as raters of children’s (N = 202; 82 girls) social-emotional well-being, using PERIK scale and four questions on the quality of transition. Results: All PERIK-dimensions were rated as elevated based on parents’ ratings and moderate based on teachers’ ratings. Ratings of difficulties during transition decreased, and satisfaction with transition and adjustment and cooperation between parents and caregivers during transition increased (teachers’ ratings were lower than parents’ ratings). The average duration of adjustment in kindergarten was three weeks. Correlation analyses showed the expected significant correlations between the PERIK dimensions and the quality of transitions and adjustment of children. Inter-rater agreement analyses showed the effect sizes were predominantly large and poor to medium agreement between parent and teacher ratings was determined. Conclusions: Although the study found that there are significant differences in perceptions of the relationship between PERIK-dimensions and satisfaction with children’s transition between teachers and parents, which was expected due to the assessment of children in different contexts, it is important to consider them both in future research. Full article

In recent years, generative AI and autonomous driving have been highly popular topics. Additionally, with the increasing global emphasis on carbon emissions and carbon trading, integrating autonomous driving technologies that can instantly perceive environ-mental changes with vehicle-based generative AI would enable vehicles to better under-stand their surroundings and provide drivers with recommendations for more energy-efficient and comfortable driving. This study employed You Only Look Once version11 (YOLOv11) for visual detection of the driving environment, integrating it with vehicle speed data received from the OBD-II system. All information is integrated and processed using the embedded Nvidia Jetson AGX Orin platform. For visual detection validation, part of the test set includes standard Taiwanese road signs. Experimental results show that incorporating Squeeze-and-Excitation Attention (SEAttention), into YOLOv11 improves the mAP50–95 accuracy by 10.1 percentage points. Generative AI processed this information in real time and provided the driver with appropriate driving recommendations, such as gently braking, detecting a pedestrian ahead, or warning of excessive speed. These recommendations are delivered through voice output to prevent driver distraction caused by looking at an interface. When a red light or pedestrian is detected, early deceleration is suggested, effectively reducing fuel consumption while also enhancing driving comfort, ultimately achieving the goal of energy-efficient driving. Full article

Vulvar viral infections such as condyloma acuminata, genital herpes, molluscum contagiosum, and Lipschütz ulcers span both sexually and non-sexually transmitted diseases and affect patients across all age groups. Lesions may present as papules, verrucous growths, or painful ulcers, often causing functional impairment and significant psychosocial distress. A multidisciplinary strategy that integrates epidemiology, precise diagnostics, individualized therapy, and psychological support is essential to optimize outcomes. We performed a structured literature search in PubMed, Scopus, and Web of Science using terms “vulvar viral infection,” “HPV,” “HSV,” “molluscum contagiosum,” and “Lipschütz ulcers.” International guidelines from the UK, Europe, and Australia were reviewed, alongside reference lists of key articles. Particular attention was given to paradoxical presentations, pediatric considerations, and cost-effectiveness analyses. HPV vaccination programs have markedly reduced anogenital warts, while early PCR/NAAT for HSV accelerates targeted antiviral therapy. First-line treatments like oral acyclovir/famciclovir for HSV and topical imiquimod or podophyllotoxin (±cryotherapy) for HPV are supported by adjunctive measures for self-limiting conditions. Host factors (hormonal cycles, immune status) and local irritants modulate recurrence risk, informing anticipatory suppressive regimens and barrier-reinforcing care. Validated patient-reported outcome measures (VPAQ, DLQI, FSFI) capture pain, sexual function, and quality-of-life impacts. Health–economic evaluations underscore the long-term value of rapid diagnostics and broad vaccination. Personalized, multidisciplinary management that combines prevention, precision diagnostics, tailored therapy, psychosocial support, and economic considerations offers the greatest promise for improving clinical and quality-of-life outcomes in patients with vulvar viral infections. We aim to outline best practices for the diagnosis and management of common vulvar viral infections, providing practical guidance for clinicians to improve recognition and therapeutic decision-making. Full article

Background: Scientific evidence plays a critical role in informing public health decision-making processes. However, the extent, nature, and effectiveness of its use remain uneven across contexts. Despite the increasing volume of literature on the subject, previous syntheses have often suffered from narrow thematic, temporal, or geographic scopes. Objectives: This study undertook a comprehensive systematic literature review spanning 50 years to (i) synthesise current knowledge on the use of scientific evidence in public health decisions, (ii) identify key determinants, barriers, and enablers, (iii) evaluate implementation patterns, and (iv) propose future directions for research and practice. Methods: We adopted the PRISMA model (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Moreover, we researched three large databases (Web of Science, Embase, and PubMed), and this study focused on articles published in the English and French languages between January 1974 and December 2024. Studies were analysed thematically and descriptively to identify trends, patterns, and knowledge gaps. Results: This review reveals a growing corpus of scholarship with a predominance of qualitative studies mainly published in public health journals. Evidence use is most frequently analysed at the national policy level. Analyses of the evolution of scientific production over time revealed significant shifts beginning as early as 2005. Critical impediments included limited access to reliable and timely data, a lack of institutional capacity, and insufficient training among policy-makers. In contrast, enablers encompass cross-sector collaboration, data transparency, and alignment between researchers and decision-makers. Conclusions: Addressing persistent gaps necessitates a more nuanced appreciation of interdisciplinary and contextual factors. Our findings call for proactive policies aimed at promoting the use of scientific evidence by improving the accessibility of health data (addressing the absence or lack of data, as well as its reliability, timeliness, and accessibility), and by training decision-makers in the use of scientific evidence for decision making. Furthermore, our findings advocate for better alignment between the agendas of healthcare professionals (e.g., data collection), researchers (e.g., the selection of research topics), and decision-makers (e.g., expectations and needs) in order to develop and implement public health policies that are grounded in and informed by scientific evidence. Full article

The gut microbiota of red deer is a topic of growing interest, particularly with regard to its ecological and physiological importance. The diversity and composition of these microbial communities is influenced by environmental variables, diet and interactions with other organisms in their habitat. Fecal samples were collected in 10 hunting reserves in the Friuli-Venezia Giulia region, Italy. In each hunting reserve, five individual samples were taken from the ground for a total of 50 samples. After DNA extraction, the V3–V4 16s rRNA regions were sequenced. The raw data were uploaded to QIIME2 and taxonomic annotation was performed. Significant differences between the deer sampled in the hunting reserves (p < 0.05) were calculated for the phyla Firmicutes and Cyanobacteriota and for the ratio of Firmicutes to Bacteroidota, especially for the mountain reserves in the north and northeast compared to the reserves in the hills in the west. Shannon and Chao1 alpha diversity indices varied between reserves (p < 0.01) and the Bray–Curtis beta diversity index also indicated differences in microbiota between hunting reserves. The different habitats and vegetation of the reserves could explain the differences observed. Understanding the dynamics of the microbiota of red deer provides important information about their health and feeding behavior and also has far-reaching implications for species conservation. Full article

In standard investigative interviews, follow-up questioning from a free recall is typically based on the core topics of the free recall that are relevant to the event under investigation. We suggest the Segmented Interview as an alternative in which each free recall topic is partitioned into segments, and focused questioning occurs for each topic and segment separately, regardless of their relevance to the event under investigation. We expected the focused questioning of the Segmented Interview to elicit more details and Veracity cues than a Structured Interview. All participants (N = 80) completed three activities, of which only the second was different: Truth tellers visited a store, whereas lie tellers stole an envelope with money. Participants were then interviewed and provided a free recall, followed by open questions based on the Segmented or Structured Interview protocol. The Segmented Interview elicited more information and Veracity cues than the Structured Interview. These results suggest that the Segmented Interview may be a promising interview technique for eliciting information and detecting lies. Full article

The construction industry is recognized as high-risk due to frequent accidents and injuries, prompting extensive research and bibliometric analysis of construction safety. However, little attention has been given to the evolution and interconnections of key research topics in this field. This study applies semantic network analysis (SNA) to examine relationships and trends in construction safety research over the past 30 years. SNA enables quantitative exploration of topic interrelationships that is difficult to achieve with other approaches. Chronological network graphs are evaluated using the number of nodes, edges, density, average clustering coefficient, and average path length. Prominent topics are identified through degree, betweenness, and eigenvector centrality measures. The analysis combines a global overview of the main network, a chronological perspective, and local examination of clusters based on five macro keywords: accident, safety management, worker behavior, machine learning, and safety training. Results show a shift from traditional concerns with mortality and injuries to contemporary issues, such as safety climate, worker behavior, and technological innovations, including building information modeling, machine learning, and real-time monitoring. Topics with lower centrality scores are identified as under-researched. Overall, SNA offers a comprehensive view of the construction safety knowledge system, guiding researchers toward emerging topics and helping practitioners prioritize resources and design integrated safety risk strategies. Full article

Background/Objectives: Adapalene is a synthetic retinoid used as a treatment for acne vulgaris. In this study, we attempted to evaluate the dermal pharmacokinetics of adapalene utilizing experimental and in silico tools. Methods: We utilized three over the counter (OTC) adapalene gels to evaluate local dermal pharmacokinetics. A data-driven, robust, mechanistic dermal physiologically based pharmacokinetic (PBPK) model was developed by integrating the physicochemical properties of adapalene, the formulation attributes of the gels, and the biophysical aspects of dermal absorption. The dermal PBPK model was validated against experimental data using in vitro release studies and in vitro permeation studies with human cadaver skin. A clinical study was performed to evaluate the effects of adapalene from the three gel formulations. The impact of adapalene delivery from three gels on the stratum corneum (SC) thickness, pilosebaceous unit area, keratinocyte number, and epidermal thickness was captured using a non-invasive technique, line-field confocal optical coherence tomography (LC–OCT). These responses were evaluated using an Emax model. Results: The dermal PBPK model has successfully predicted adapalene penetration profiles across different gel formulations. The model accuracy, in predicting drug release and permeation characteristics, was confirmed using the experimental data. Clinical evaluation revealed formulation-dependent differences in adapalene’s effects on measured skin parameters, with distinct pharmacodynamic profiles observed for each gel formulation. Conclusions: The overall study gave us a detailed insight into potential effects of formulation on the dermal pharmacokinetics and pharmacodynamics of adapalene using three marketed gels. Full article

Image captioning is an important task in cross-modal research in numerous applications. Image captioning aims to capture the semantic content of an image and express it in a linguistically and contextually appropriate sentence. However, existing models mostly trend to focus on a topic generated by the most conspicuous foreground objects. Thus, other topics in the image are often ignored. To address these limitations, we propose a model that can generate richer semantic content and more diverse captions. The proposed model can capture not only main topics using coarse-grained objects but also finds fine-grained visual information from background or minor foreground objects. Our image captioning system combines the ResNet, LSTM, and topic feature models. The ResNet model extracts fine-grained image features and enriches the description of objects. The LSTM model provides a longer context for semantics, increasing the fluency and semantic completeness of the generated sentences. The topic model determines multiple topics based on the image and text content. The topics provide directions for the model to generate different sentences. We evaluate our model on the MSCOCO dataset. The results show that compared with other models, our model achieves a certain improvement in higher-order BLEU scores and a significant improvement in CIDEr score. Full article

Background: Pediatric tracheostomy decisions are challenging for clinicians and parents, especially when a child’s survival/neurodevelopmental outcome is uncertain. Better understanding of parents’ values over the decision period is crucial for clinical decision-making. Objective: To describe parents’ values during tracheostomy decision-making for their critically ill child and to identify opportunities to improve parent–clinician shared decision-making (SDM). Methods: We thematically analyzed 12 semi-structured interviews with parents who recently faced a tracheostomy decision for their critically ill child. Three study team members with qualitative expertise reviewed the transcripts, identifying key topics independently. A codebook was developed, and data were coded. Key research questions guided analysis, with findings iteratively reviewed by the study team. Results: We identified parents’ values at the three time points: when the decision was introduced, during their deliberations of it, and when the ultimate decision was made. Initially, parents resisted tracheostomy because it threatens normalcy. They valued proof of a need for tracheostomy and information with certainty. As certainty for tracheostomy increased over time, parents’ hope focused on reversibility of tracheostomy and improvement in normalcy compared to current status. They concurrently worried about practical issues such as emergencies, home care, and finances. Key considerations driving the final decision included best interest of the child, perceived benefits of tracheostomy compared to its downsides or other options, and potential for better quality of life and longer life. Conclusions: Parents’ dynamic values shifting with clinical uncertainty suggests opportunities to improve SDM by attending to parents’ individualized needs and managing expectations. Full article

With the growing adoption of electric vehicles, optimizing the user experience of charging infrastructure has become critical. However, extracting actionable insights from the vast number of user reviews remains a significant challenge, impeding demand-driven operational planning for charging stations and degrading the user experience. This study leverages three pre-trained language models to perform sentiment classification and multi-level topic identification on 168,129 user reviews from Beijing, facilitating a comprehensive understanding of user feedback. The experimental results reveal significant task-model specialization: RoBERTa-WWM excels in sentiment analysis (accuracy = 0.917) and fine-grained topic identification (Micro-F1 = 0.844), making it ideal for deep semantic extraction. Conversely, ELECTRA, after sufficient training, demonstrates a strong aptitude for coarse-grained topic summarization, highlighting its strength in high-level semantic generalization. Notably, the models offer capabilities beyond simple classification, including autonomous label normalization and the extraction of valuable information from comments with low information density. Furthermore, integrating textual and spatial analyses revealed striking patterns. We identified an urban–rural emotional gap—suburban users are more satisfied despite fewer facilities—and used geographically weighted regression (GWR) to quantify the spatial differences in the factors affecting user satisfaction in Beijing’s districts. We identified three types of areas requiring differentiated strategies, as follows: the northwestern region is highly sensitive to equipment quality, the central urban area has a complex relationship between supporting facilities and satisfaction, and the emerging adoption area is more sensitive to accessibility and price factors. These findings offer a data-driven framework for charging infrastructure planning, enabling operators to base decisions on real-world user feedback and tailor solutions to specific local contexts. Full article

Facial Expression Recognition (FER) is a research topic of great practical significance. However, existing FER methods still face numerous challenges, particularly in the interaction between spatial and global information, the distinction of subtle expression features, and the attention to key facial regions. This paper proposes a lightweight Global-Aware Spatial (GAS) Attention module, designed to improve the accuracy and robustness of FER. This module extracts global semantic information from the image via global average pooling and fuses it with local spatial features extracted by convolution, guiding the model to focus on regions highly relevant to facial expressions (such as the mouth and eyes). This effectively suppresses background noise and enhances the model’s ability to perceive subtle expression variations. In addition, we further introduce a Squeeze-and-Excitation (SE) Attention module into the dual-branch architecture to adaptively adjust the channel-wise weights of features, emphasizing critical region information and enhancing the model’s discriminative capacity. Based on these improvements, we develop the Ada-DF++ network model. Experimental results show that the improved model achieves test accuracies of 89.21%, 66.14%, and 63.75% on the RAF-DB, AffectNet (7cls), and AffectNet (8cls) datasets, respectively, outperforming current state-of-the-art methods across multiple benchmarks and demonstrating the effectiveness of the proposed approach for FER tasks. Full article

In the context of Industry 4.0, technologies such as Digital Twin (DT) and Data Space (DS) have emerged as a revolution in the way physical assets are represented in simulation models and how their information and data are represented in cloud repositories. The aim of this work was to investigate the technologies of DTs and DSs, with a focus on their application in an industrial context, delving into the approaches and difficulties of the integration of both technologies, so that it can be explored and answered the respective challenges. To this end, literature reviews on these topics were explored by reading various sources, as well as analyzing different methodologies for implementing and integrating the two technologies. The result was a description of the main methodologies for integrating DTs with DSs, with the addition of a practical application using AASX Package Explorer, this being a platform enabling the virtual representations of industrial equipment in the molds of DT technologies, containing the association with server tools from other developers and specifications. Full article