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Purpose An investigational drug services (IDS) pharmacy plays a vital role in supporting clinical trial research by ensuring the safe and efficient management of investigational products. This article describes the implementation of an electronic project management software to improve an IDS pharmacy's study protocol work. The article describes the implementation of the software and how this approach addressed specific challenges, including project oversight, process standardization, documentation, reporting, accountability, and intrateam communication. Summary We describe an electronic project management software system used to streamline and standardize the work associated with study protocols. This software provides an organized and customizable workspace to manage tasks associated with each study protocol. The software automates task creation, tracks progress, and ensures comprehensive record keeping. Additionally, the software fosters effective communication within the team and offers real-time reporting to assess team productivity and progress. We have observed improved consistency, enhanced revenue, including approximately $18,000 in additional fee capture, and increased collaboration among pharmacy team members. Conclusion Implementing an electronic project management software has proven highly beneficial in the IDS pharmacy. The software has significantly improved workflow efficiency by addressing challenges in study protocol management. While initial setup and training required time and resources, the long-term benefits in project oversight, collaboration, and revenue capture justify the investment. An electronic project management software is a valuable tool in managing the complexity of study protocol activities and supports the pharmacy's crucial role in advancing clinical research. [ABSTRACT FROM AUTHOR]

Mortality surveillance systems can have limitations, including reporting delays, incomplete reporting, missing data, and insufficient detail on important risk or sociodemographic factors that can impact the accuracy of estimates of current trends, disease severity, and related disparities across subpopulations. The Centers for Disease Control and Prevention used multiple data systems during the COVID-19 emergency response—line-level case‒death surveillance, aggregate death surveillance, and the National Vital Statistics System—to collectively provide more comprehensive and timely information on COVID-19‒associated mortality necessary for informed decisions. This article will review in detail the line-level, aggregate, and National Vital Statistics System surveillance systems and the purpose and use of each. This retrospective review of the hybrid surveillance systems strategy may serve as an example for adaptive informational approaches needed over the course of future public health emergencies. (Am J Public Health. 2024;114(10):1071–1080. https://doi.org/10.2105/AJPH.2024.307743) [ABSTRACT FROM AUTHOR]

Educational dashboards are increasingly prevalent visualising technologies that display data from educational processes to help learners and educators track learning pathways, alert for deviations, and make interventions. This study contributes to critical studies on data visualisations in education by examining dashboards in higher distance education. Inspired by science and technology studies (STS), it investigates several modes of relating to educational dashboards at one distance university, focusing on their production and deployment. Ethnographic findings show how dashboards are produced through public-private, interdisciplinary collaboration and (made to) align with predominant techno-pedagogical ideas, often by persuading university students to use technologies correctly. When deployed, students learn to filter relevant information, practice self-monitoring, and (re)examine dashboard usage. The case exemplifies a ‘dashboarding of learning’ and ‘learning to dashboard’, indicating that dashboards not only enter educational practices but also encourage actors – sometimes unsuccessfully – to understand and realise their education in line with specific techno-pedagogical ideas. [ABSTRACT FROM AUTHOR]

Ongoing seismic events in global society have increased demands on organizations to change their focus on profit maximization alone to becoming a social enterprise that follows humanistic management (serving the common good) principles. Coincidentally, business schools are under pressure to teach humanistic management principles in their curriculum to enable the future work force to become agents of world benefit. Data analytics offers a means to introduce these principles to undergraduate business students. The analytics module described in this paper introduces undergraduates in an introductory Information Systems course to humanistic management. It discusses the use of humanistic management analytics (HMA), and describes an assignment to design, develop and use a HMA dashboard. Through video, lecture, case study and assignments, students learn the value of incorporating humanistic management principles to analytics and human resource functions that embody concepts of data analytics for social good. [ABSTRACT FROM AUTHOR]

Background: Hospital-acquired pressure injuries (HAPIs) have a major impact on patient outcomes in intensive care units (ICUs). Effective prevention relies on early and accurate risk assessment. Traditional risk-assessment tools, such as the Braden Scale, often fail to capture ICU-specific factors, limiting their predictive accuracy. Although artificial intelligence models offer improved accuracy, their "black box" nature poses a barrier to clinical adoption. Objective: To develop an artificial intelligence–based HAPI risk-assessment model enhanced with an explainable artificial intelligence dashboard to improve interpretability at both the global and individual patient levels. Methods: An explainable artificial intelligence approach was used to analyze ICU patient data from the Medical Information Mart for Intensive Care. Predictor variables were restricted to the first 48 hours after ICU admission. Various machine-learning algorithms were evaluated, culminating in an ensemble "super learner" model. The model's performance was quantified using the area under the receiver operating characteristic curve through 5-fold cross-validation. An explainer dashboard was developed (using synthetic data for patient privacy), featuring interactive visualizations for in-depth model interpretation at the global and local levels. Results: The final sample comprised 28 395 patients with a 4.9% incidence of HAPIs. The ensemble super learner model performed well (area under curve = 0.80). The explainer dashboard provided global and patient-level interactive visualizations of model predictions, showing each variable's influence on the risk-assessment outcome. Conclusion: The model and its dashboard provide clinicians with a transparent, interpretable artificial intelligence–based risk-assessment system for HAPIs that may enable more effective and timely preventive interventions. [ABSTRACT FROM AUTHOR]

Research Summary: We conducted a group randomized‐controlled trial of an internal dashboard system deployed by the Michigan State Police to determine its effectiveness in reducing traffic stop racial disparities. Informed by a difference‐in‐differences design, analyses of traffic stop data from 2019–2022 indicated that the dashboard had no impact on traffic stop racial disparities. Additional analyses of traffic stops, crashes, and crime revealed that the dashboard had no "de‐policing" effect on traffic patrols, nor were there any significant changes in traffic safety or crime in treatment patrol areas relative to control patrol areas. Qualitative analyses of interview data from more than 40 troopers in the agency revealed unique barriers to program implementation and opportunities for future improvement. Policy Implications: In an era of policing where the capacity and demand for data‐driven decision‐making is on the rise, evidence‐based policy and practice can provide police agencies with informed solutions for addressing traffic stop racial disparities. Yet, the increased demand for evidence‐based reform is fueled by a relatively low supply of evidence‐based research. This study adds to this evidence base by providing unique insights into the effectiveness of a program built specifically to reduce racial disparities in traffic stops, while also highlighting implementation challenges. [ABSTRACT FROM AUTHOR]

Background: Provision of a Medication Action Plan (MAP) on admission and a Discharge Medication Record (DMR) are associated with reduced medication‐related harm. Aim: To report factors associated with the provision of MAPs and DMRs in rural and regional hospitals in Queensland, Australia. Method: A literature search, environmental scan and department consultations were conducted to develop Clinical Pharmacy Key Performance Indicators (cpKPIs) and design a cpKPI dashboard. Two of the five KPIs included in the dashboard, relating to medication action plans on admission and medication records on discharge, were reported for all the hospitals and were included in the study. A retrospective, period‐prevalence study was conducted to evaluate the coverage and equity of clinical pharmacy service provision for patients admitted for longer than 24 h. The proportions of patients who received MAPs and DMRs were stratified by age, gender, Indigeneity and hospital type. Statistical analysis used chi‐squared tests and logistic regression in R. This project was exempt due to the local policy requirements that constitute research by the Far North Queensland Human Research Ethics Committee (Reference no: EX/2023/QCH/94383‐1684QA). The justification for this exemption is as follows: the project was determined to be negligible risk research and involved the use of existing collection of data or records that contain only non‐identifiable data about human beings. Results: In total, 13 818 patients (37.9% of admissions) received a MAP and 11 631 patients (32.7% of discharges) received a DMR. The proportion of MAPs and DMRs was significantly higher in rural hospitals than in regional hospitals (MAP 50.6% vs 34.6%, DMR 33.1% vs 31.3%) and for male patients than female patients (MAP 42.2% vs 33.7%, DMR 36.4% vs 29.2%). When stratified by age, First Nations patients received a higher proportion of MAPs and DMRs in each age group, except for age 85 years and over. The proportion of First Nations patients aged 50 years and over who received MAP was lower compared to that for non‐Indigenous patients aged 65 years and over (56.3% vs 59.8%), whilst the proportion for DMRs was similar (50.4% vs 49.3%). Conclusion: The study defined the clinical pharmacy key performance indicators for measuring equity of clinical pharmacy service provision in Australia. When adjusted for a difference in life expectancy, the proportion of MAPs for First Nations patients was lower compared to the proportion of MAPs for non‐Indigenous patients. Further improvements are required to achieve equity of service provision for First Nations patients and female patients. [ABSTRACT FROM AUTHOR]

Learning analytics dashboards (LADs) are emerging tools that convert abstract, complex information with visualizations to facilitate teachers' data-driven pedagogical decision-making. While many LADs have been designed, teachers' capacities for using such LADs are not well articulated in the literature. To fill the gap, this study provided a conceptual definition highlighting data visualization literacy and integrating abilities as two critical components in LAD capacities. Moreover, this study assessed teachers' LAD capacities through a knowledge test and examined the combined effect of teachers' self-regulation, emotions, perceptions of LAD usefulness and ease of use, and online teaching experience on teachers' achievements of the LAD capacity knowledge test. The results of a Bayesian path analysis based on the sample of 150 teachers show that (1) teachers' self-regulation and perceived LAD usefulness were the two main factors that made significant impacts on their LAD capacities, (2) the factors of negative emotions and perceived ease of use had effects on teachers' LAD capacities, but such effects were mediated by self-regulation and perceived usefulness, and (3) online teaching experience had little effect on LAD capacities. This is the first study that conceptually researches teachers' capacities for LAD uses. The findings offer novel perspectives into the complexity of LAD using process and demonstrate the importance of teachers' self-regulation, emotions, and perceptions of usefulness in enhancing teachers' abilities to use LADs for pedagogical decisions and actions. [ABSTRACT FROM AUTHOR]

Designing a Web-based Employee Task Management Information System on CV. Achai Berkat Sejahtera is a plan made to assist business owners in employee management and help employees communicate an obstacle in an organized manner so that communication misses do not occur. Designing CV Employee Task Management Information System. Achai Berkat Sejahtera has features such as Employee Task Management Systems and a dashboard for admins to see employee performance. The design of this Information System uses the Waterfall System Development Life Cycle (SDLC) development methodology. The database that this application uses uses a MySQL database. The programming languages used are HTML, CSS, JS, and PHP with the Bootstrap Framework and CodeIgniter which produce attractive and dynamic web applications. With a dynamic web application, it will be able to help admins and employees in accessing and processing data. [ABSTRACT FROM AUTHOR]

Supply chain decision making can cause exaggerated fluctuations in inventory levels in spite of small changes in customer demand. While previous research has recognized the positive impact of information sharing on supply chain decision making, little attention has been given to how information is presented, such as through dashboards or information displays. This study applies bounded rationality theory, intrinsic motivation, and the knowledge-based view to address this gap, exploring the effects of providing information to supply chain managers, emphasizing how the information is presented rather than merely its availability. Via an experiment using a version of the beer game supply chain simulation, we find that the display of information about inventory and upstream incoming orders significantly impacted overall performance. Psychometric modeling indicates that knowledge acquisition and shared meaning are crucial in decision-makers' perceived performance. Moreover, information distribution among supply chain participants will likely contribute to cognitive overload and reduce motivation to improve decision-making. [ABSTRACT FROM AUTHOR]

Research so far has overlooked the contribution of students' noncognitive factors to their performance in introductory programming in the context of personalized learning support. This study uses learning analytics to design and implement a Dashboard to understand the contribution of introductory programming students' learning motivation, personality, and class participation factors to their programming performance and provide adaptive support to improve their motivation and persistence. Moreover, this study evaluates the effectiveness and usefulness of the dashboard in two phases: committee evaluation and laypersons evaluation. The evaluation results indicate dashboard's effectiveness in students' better-informed decision-making related to their learning approach. In both phases, the dashboard has been perceived as useful and easy-to-use tool. These findings indicate that the dashboard is perceived as a useful tool for providing timely feedback about non-cognitive factors contributing to students' programming performance. The study provides insights into the noncognitive side of novice programmers and encourages further exploration of other aspects influencing their performance. [ABSTRACT FROM AUTHOR]

Objective To explore the feasibility of building a primary care performance dashboard using DHIS2 data from Ethiopia's largest urban (Addis Ababa), agrarian (Oromia) and pastoral (Somali) regions. Methods We extracted 26 data elements reported by 12 062 health facilities to DHIS2 for the period 1 July 2022 to 30 June 2023. Focusing on indicators of effectiveness, safety and user experience, we built 14 indicators of primary care performance covering reproductive, maternal and child health, human immunodeficiency virus, tuberculosis, noncommunicable disease care and antibiotic prescription. We assessed data completeness by calculating the proportion of facilities reporting each month, and examined the presence of extreme outliers and assessed external validity. Findings At the regional level, average completeness across all data elements was highest in Addis Ababa (82.9%), followed by Oromia (66.2%) and Somali (52.6%). Private clinics across regions had low completeness, ranging from 38.6% in Somali to 58.7% in Addis Ababa. We found only a few outliers (334 of 816 578 observations) and noted that external validity was high for 11 of 14 indicators of primary care performance. However, the 12-month antiretroviral treatment retention rate and proportions of patients with controlled diabetes or hypertension exhibited poor external validity. Conclusion The Ethiopian DHIS2 contains information for measuring primary care performance, using simple analytical methods, at national and regional levels and by facility type. Despite remaining data quality issues, the health management information system is an important data source for generating health system performance assessment measures on a national scale. [ABSTRACT FROM AUTHOR]

In the web application development process, selecting the right method is crucial to achieving goals effectively and efficiently. Previously, applications at PLN UP3 Yogyakarta were developed using the waterfall development method. Some projects that were developed without a structured method progressed slowly and were not well organized. Therefore, for the PLN UP3 data visualization dashboard project, the Scrum method was chosen. The Scrum method was selected for its flexibility, rapid development capabilities, and ease of implementation by all team members. The implementation of Scrum follows these stages: setting product goals, creating a product backlog, sprint planning, conducting sprints, producing increments, holding sprint reviews, conducting sprint retrospectives, and daily stand-ups. By using the Scrum development method, the SIBER project at PLN has been able to progress according to the specified timeline and successfully deliver all required features. [ABSTRACT FROM AUTHOR]

Purpose To describe the development and implementation of clinical dashboards to standardize data capturing and reporting across multiple partner health systems. Summary Between July and September 2020, clinical dashboards were developed and implemented across multiple partner health-system specialty pharmacies (HSSPs) located throughout the United States. The dashboards were developed via collaboration between personnel involved in clinical subcommittees, clinical outcomes, data analytics, information technology, and clinical and central operations. Utilizing a cloud-scale business intelligence service, patient clinical data documented in a shared patient management system was utilized to create customizable dashboards that displayed patient-reported outcome measures, collected laboratory or test results, and completed pharmacist interventions. Separate dashboards were developed for several disease states and/or medication classes. Based on specialty pharmacy recommendations, medical literature, and clinical guidelines, internally developed disease-specific protocols defined data included in the dashboards and ensured consistent data collection amongst partner health systems. Having access to real-time clinical information allows health systems to closely monitor performance metrics, track patient outcomes, and identify operational gaps. Conclusion Accurately capturing and reporting clinical metrics using clinical dashboards can assist HSSPs in delivering high-quality care. Having access to clinical outcome measures allows HSSPs to better understand the impact of their services on patients' health and quality of life. Health systems can utilize this data to analyze trends and recognize areas of opportunity so that measures can be taken to improve patient care. [ABSTRACT FROM AUTHOR]

Background: Critical nursing shortages have required many health care organizations to restructure nursing care delivery models. At a tertiary health care center, 150 registered practical nurses were integrated into acute inpatient care settings. Problem: A mechanism to continuously monitor the impact of this staffing change was not available. Approach: Leveraging current literature and consultation with external peers, metrics were compiled and categorized according to Donabedian's Structure Process Outcome Framework. Consultation with internal subject matter experts determined the final metrics. Outcomes: The Patient care, Utility, Logistics, Systemic Evaluation (PULSE) electronic dashboard was developed, capturing metrics from multiple internal databases and presenting real-time composites of validated indicators. Conclusion: The PULSE dashboard is a practical means of enabling nursing leadership to evaluate the impact of change and to make evidence-informed decisions about nursing care delivery at our organization. [ABSTRACT FROM AUTHOR]

This collection of articles and documents explores the involvement of external parties in the conflict in Sudan. It discusses the roles of countries such as Egypt, Ethiopia, Chad, Kenya, Libya, Eritrea, Saudi Arabia, the United Arab Emirates (UAE), Russia, and the United States. The articles highlight the strategic importance of Sudan, the historical influences and tensions between these countries and Sudan, and their interests in the conflict. The collection provides a comprehensive understanding of the external dynamics at play in the Sudanese war and their implications for the region. [Extracted from the article]

Purpose: This study addresses the critical role of Life Cycle Assessment (LCA) visualisations in the building industry, focusing on the development and evaluation of an innovative 3D dashboard approach in Microsoft Power BI for enhanced LCA visualisations in building projects. It emphasises the need for effective communication of LCA results among stakeholders to support sustainable decision-making and reduce CO2 emissions in the construction sector. Methods: The research involved defining key goals for LCA visualisation, developing a novel methodology to integrate LCA results with 3D models in an interactive Power BI dashboard and conducting a comparative analysis of traditional and 3D visualisation methods. Two real-world case studies were evaluated, and a survey was conducted among professionals in the architectural and structural engineering fields to assess the effectiveness of the proposed visualisation approach. Results and discussions: The findings demonstrate that the 3D dashboard significantly enhances the ability to meet diverse LCA visualisation goals compared to traditional methods. The interactive nature of the dashboard allows for dynamic representation of LCA data, facilitating better understanding and decision-making. The study underscores the importance of tailoring LCA visualisations to the specific requirements of different building projects. User feedback confirmed the new approach's advantages, particularly in its ability to facilitate informed sustainable decision-making. Conclusions: The introduction of interactive 3D dashboards represents a significant advancement in the field of sustainable building design and analysis. This approach not only improves the clarity and comprehensibility of LCA data, but also fosters collective action and systemic change in the construction industry towards more sustainable practices. By setting a new standard in LCA methodologies, this study contributes to the broader goal of reducing CO2 emissions and addressing the climate crisis in the building sector. [ABSTRACT FROM AUTHOR]

With the rise of health awareness, pharmaceutical and cosmetic products should be verified to protect ourselves from health risks. MyPharmaceutical is a proof-of-concept proposed to provide a mobile application for users to carry out product verification and reporting and a web application for administrative purposes. The data on the registered pharmaceutical and cosmetic products were extracted from national pharmaceutical regulatory agency (NPRA) website. MyPharmaceutical mobile application provides functionalities such as searching the registered product, bookmarking products, reporting products, and tracking report status. The mobile application also implemented a barcode scanner feature to provide ease of product verification. A named entity recognition algorithm is applied with the NLP.js library to provide an improved product search feature for the users, where products can be searched with multiple search criteria in a single input. The web application is proposed to support the mobile application, where the NPRA data admins and officers can manage reported products, publish announcements, verify product data, and utilize the analytic dashboard. The system proposed is expected to provide ease of product verification and reporting to assist the public in choosing safe registered products and a platform for NPRA to manage data and deliver information to the users. [ABSTRACT FROM AUTHOR]

Fertigation system has been widely used by farmers to automate some processes of crops productions. A conventional system requires workers to prepare a fertilizer mixture, before transferring it into a main storage tank to be mixed with water. Then, electrical conductivity (EC) of the mixture will be measured. The existing fertigation system still relies heavily on workers and is manually operated and prone to human error. Therefore, internet of things (IoT) based fertigation system has been developed to deliver the fertilizer mixture with consistent EC value automatically to the plants. The main system controller is designed using ESP32 development module. The operation of the system can be monitored using an IoT dashboard and farmers can also control the system remotely. Alert will be given to the farmers if the condition of the system or plant does not meet the predefined settings. The values of EC together with temperature and humidity sensors are recorded for further analysis. A testbed is set up to provide fertigation to 120 polybags eggplants. Using the proposed fertigation system, the eggplants have been harvested earlier, therefore reducing the fertilizer usage. The cost of this IoT based fertigation system is lower compared to existing commercial products. [ABSTRACT FROM AUTHOR]

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Background: CARA set out to develop a data-visualisation platform to facilitate general practitioners to develop a deeper understanding of their patient population, disease management and prescribing through dashboards. To support the continued use and sustainability of the CARA dashboards, dashboard performance and user engagement have to be optimised. User research places people at the centre of the design process and aims to evaluate the needs, behaviours and attitudes of users to inform the design, development and impact of a product. Objective: To explore how different initial key messages impact the level of behavioural engagement with a CARA dashboard. Methods: Participating general practices can upload their practice data for analysis and visualisation in CARA dashboards. Practices will be randomised to one of three different initial landing pages: the full dashboard or one of two key messages: a between comparison (their practice prescribing with the average of all other practices) or within comparison (with practice data of the same month the previous year) with subsequent continuation to the full dashboard. Analysis will determine which of the three landing pages encourages user interaction, as measured by the number of 'clicks', 'viewings' and 'sessions'. Dashboard usage data will be collected through Google analytics. Discussion: This study will provide evidence of behavioural engagement and its metrics during the implementation of the CARA dashboards to optimise and sustain interaction. Trial registration: ISRCTN32783644 (Registration date: 02/01/2024). [ABSTRACT FROM AUTHOR]

In Germany, a comprehensive reimbursement policy for extracorporeal membrane oxygenation (ECMO) results in the highest per capita use worldwide, although benefits remain controversial. Public ECMO data is unstructured and poorly accessible to healthcare professionals, researchers, and policymakers. In addition, there are no uniform policies for ECMO allocation which confronts medical personnel with ethical considerations during health crises such as respiratory virus outbreaks.Retrospective information on adult and pediatric ECMO support performed in German hospitals was extracted from publicly available reimbursement data and hospital quality reports and processed to create the web-based ECMO Dashboard built on Open-Source software. Patient-level and hospital-level data were merged resulting in a solid base for ECMO use analysis and ECMO demand forecasting with high spatial granularity at the level of 413 county and city districts in Germany.The ECMO Dashboard (https://www.ecmo-dash.de/), an innovative visual platform, presents the retrospective utilization patterns of ECMO support in Germany. It features interactive maps, comprehensive charts, and tables, providing insights at the hospital, district, and national levels. This tool also highlights the high prevalence of ECMO support in Germany and emphasizes districts with ECMO surplus – where patients from other regions are treated, or deficit – origins from which ECMO patients are transferred to other regions. The dashboard will evolve iteratively to provide stakeholders with vital information for informed and transparent resource allocation and decision-making.Accessible public routine data could support evidence-informed, forward-looking resource management policies, which are urgently needed to increase the quality and prepare the critical care infrastructure for future pandemics. [ABSTRACT FROM AUTHOR]

Objective: This study's purpose was to explore universities' online dashboards that communicate information about COVID-19 cases to campus communities, and if dashboards adhere to American College Health Association (ACHA) recommendations. Methods: The websites of all four-year, public universities with an enrollment of at least 10,000 students were analyzed for the presence of COVID-19 dashboards, if dashboards contained recommended case features (eg, number of cases, tests, and people in quarantine/isolation), as well as other helpful features (eg, epidemiological curve, cluster information). Results: Of the 263 universities included in the study, 76% had a dashboard, but only 15% contained all recommended features. Most (62%) had an epidemiological curve, but few (3%) reported information related to clusters. Conclusion: Dashboards display case information and encourage behavior change; however, there is a need for improved adherence to the ACHA's recommendations for COVID-19 dashboards to maximize their potential impact on campus communities. [ABSTRACT FROM AUTHOR]

Objective: New York City's automated mortality syndromic surveillance system monitors temporal and spatial patterns in mortality. To describe the use of the syndromic surveillance system, we used the system to find mortality patterns for the 15 leading causes of death and for deaths from rare and reportable diseases in New York City from February 2015 through June 2020. We used results to find aberrations that indicate threats to public health. Methods: We used unobserved components models to analyze time series of mortality counts for leading causes of death, historical limits methods for rare and reportable diseases, and SaTScan for temporal–spatial cluster analysis. We obtained data on the number of deaths from the electronic death registry system maintained by the city's Bureau of Vital Statistics. Results: The mortality syndromic surveillance system detected an increase in the number of deaths from heart disease by April 1, 2020, when 75.0 deaths occurred on March 24, 2020, instead of an expected 45.8 deaths (95% upper prediction limit of 61.0) and an increase in the number of deaths from all causes on March 20, 2020, when 194.0 deaths were observed while 150.1 deaths were expected (95% upper prediction limit of 178.0). The number of deaths from all causes returned to normal the week beginning June 14, 2020, when 990.0 deaths were observed and 998.8 deaths were expected. Practice Implications: When compared with efforts from New York City to provide yearly vital statistics, the automated mortality syndromic surveillance system can provide timely mortality data with fewer resources and raise the capacity to detect anomalous increases in mortality. [ABSTRACT FROM AUTHOR]

In this paper we propose a dashboard of indicators of territorial attractiveness at NUTS3 level in the framework of the EU Regional Competitiveness Index (RCI). Then, the Fuzzy C-Medoids Clustering model with multivariate data and contiguity constraints is applied for partitioning the Italian provinces (NUTS3). The novelty is the territorial level analized, and the identification of the elementary indicators at the basis of the construction of the eleven composite competitiveness pillars. The positioning of the Italian provinces is deeply analyzed. The clusters obtained with and without contraints are compared. The obtained partition may play an important role in the design of policies at the NUTS3 level, a route already considered by the Italian government. The analysis developed and the related set of indicators at NUTS3 level constitute an information base that could be effectively used for the implementation of the National Recovery and Resilience Plan (NRRP). [ABSTRACT FROM AUTHOR]

For guaranteeing the safe and effective functioning of aircraft, image processing techniques can be a valuable tool to detect and evaluate aircraft panel values. In the pursuit of this objective, a dataset covering multiple aircraft models, various sessions, and different lighting conditions was compiled. Four tasks were examined through comparative analysis: object detection, display classification, needle masking, and needle angle detection. YOLOv8 demonstrated high performance in object detection and classification. In the classification task, the adaptability of needle-type device reading was examined by using the well-established models VGG16, Mobilenet V2, and Xception. Denoising autoencoder, U-net, and GrabCut methods were examined for needle masking, and the least squares method was applied to detect needle angle. As we move from the proof-of-concept phase to envisioning the development of an end-to-end system, this work provides significant analysis of image processing methodologies for reading aircraft dashboards. [ABSTRACT FROM AUTHOR]

Background This study was conducted as an effort to develop a Korean construction job exposure matrix (KoConJEM) based on 60 occupations recently consolidated by the construction workers mutual aid association for use by the construction industry. Methods The probability, intensity, and prevalence of exposure to 26 hazardous agents for 60 consolidated occupations were evaluated as binary (Yes/No) or four categories (1 to 4) by 30 industrial hygiene experts. The score for risk was calculated by multiplying the exposure intensity by the prevalence of exposure. Fleiss' kappa for each hazardous agent and occupation was used to determine agreement among the 30 experts. The JEM was expressed on a heatmap and a web-based dashboard to facilitate comparison of factors affecting exposure according to each occupation and hazardous agent. Results Awkward posture, heat/cold, heavy lifting, and noise were hazardous agents regarded as exposure is probable by at least one or more experts in all occupations, while exposure to asphalt fumes was considered hazardous in the smallest number of occupations (n = 5). Based on the degree of agreement among experts, more than half of the harmful factors and most occupations showed fair to good results. The highest risk value was 16 for awkward posture for most occupations other than safety officer. Conclusions The KoConJEM provides information on the probability, intensity, and prevalence of exposure to harmful factors, including most occupations employing construction workers; therefore, it may be useful in the conduct of epidemiological studies on assessment of health risk for construction workers. [ABSTRACT FROM AUTHOR]