Abstract: Objective: Web-based cognitive bias modification for interpretation (CBM-I) can improve interpretation biases and anxiety symptoms but faces high rates of dropout. This study tested the effectiveness of web-based CBM-I relative to an active psychoeducation condition and the addition of low-intensity telecoaching for a subset of CBM-I participants. Method: 1,234 anxious community adults (M_age = 35.09 years, 81.2% female, 72.1% white, 82.6% not Hispanic) were randomly assigned at Stage 1 of a sequential, multiple-assignment randomized trial to complete five weekly sessions of CBM-I or psychoeducation on our team’s public research website. After the first session, for Stage 2, an algorithm attempted to classify CBM-I participants as higher (vs. lower) risk for dropping out; those classified as higher risk were then randomly assigned to complete four brief weekly telecoaching check-ins (vs. no coaching). Results: As hypothesized (https://doi.org/j2xr; Daniel, Eberle, & Teachman, 2020), CBM-I significantly outperformed psychoeducation at improving positive and negative interpretation biases (Recognition Ratings, Brief Body Sensations Interpretation Questionnaire) and anxiety symptoms (Overall Anxiety Severity and Impairment Scale, Anxiety Scale from Depression Anxiety Stress Scales–Short Form), with smaller treatment gains remaining significant at 2-month follow-up. Unexpectedly, CBM-I had significantly worse treatment dropout outcomes than psychoeducation, and adding coaching (vs. no coaching) did not significantly improve efficacy or dropout outcomes (notably, many participants chose not to interact with their coach). Conclusions: Web-based CBM-I appears effective, but supplemental coaching may not mitigate the challenge of dropout.

Abstract: With the increased usage and diversity of methods and instruments being applied to analyze Data-Independent Acquisition (DIA) data, visualization is becoming increasingly important to validate automated software results. Here we present MassDash, a cross-platform DIA mass spectrometry visualization and validation software for comparing features and results across popular tools. MassDash provides a web-based interface and Python package for interactive feature visualizations and summary report plots across multiple automated DIA feature detection tools, including OpenSwath, DIA-NN, and dreamDIA. Furthermore, MassDash processes peptides on the fly, enabling interactive visualization of peptides across dozens of runs simultaneously on a personal computer. MassDash supports various multidimensional visualizations across retention time, ion mobility, m/z, and intensity, providing additional insights into the data. The modular framework is easily extendable, enabling rapid algorithm development of novel peak-picker techniques, such as deep-learning-based approaches and refinement of existing tools. MassDash is open-source under a BSD 3-Clause license and freely available at https://github.com/Roestlab/massdash, and a demo version can be accessed at https://massdash.streamlit.app.

Abstract: Abstract Summary Protein design requires information about how mutations affect protein stability. Many web-based predictors are available for this purpose, yet comparing them or using them en masse is difficult. Here, we present BenchStab, a console tool/Python package for easy and quick execution of 19 predictors and result collection on a list of mutants. Moreover, the tool is easily extensible with additional predictors. We created an independent dataset derived from the FireProtDB and evaluated 24 different prediction methods. Availability and implementation BenchStab is an open-source Python package and available at https://github.com/loschmidt/BenchStab with a detailed README and example usage at https://loschmidt.chemi.muni.cz/benchstab. The BenchStab dataset is available on Zenodo: Https://zenodo.org/records/10637728 Supplementary information The raw data collected in this study and their visualizations are available at Bioinformatics online.

Abstract: Abstract A recent trend in hydroinformatics has been the growing number of data, models, and cyber tools, which are web accessible, each aiming to improve common research tasks in hydrology through web technologies. Coupling web-based models and tools holds great promise for an integrated environment that can facilitate community participation, collaboration, and scientific replication. There are many examples of server-side, hydroinformatics resource coupling, where a common standard serves as an interface. Yet, there are few, if any, examples of client-side resource coupling, particularly cases where a common specification is employed. Toward this end, we implemented the basic model interface (BMI) specification in the JavaScript programing language, the most widely used programing language on the web. By using BMI, we coupled two client-side hydrological applications (HydroLang and HLM-Web) to perform rainfall–runoff simulations of historical events with rainfall data and a client-side hydrological model as a case study demonstration. Through this process, we present how a common and often tedious task – the coupling of two independent web resources – can be made easier through the adoption of a common standard. Furthermore, applying the standard has facilitated a step toward the possibility of client-side ‘Model as a Service’ for hydrological models.

Abstract: This paper presents the development of a web-based course timetabling system based on an enhanced genetic algorithm. The enhanced method utilizes a heuristic mutation which concentrates on mutating the infeasible genes to improve the algorithms' exploration and exploitation capability. The method was implemented using a free and open-source application and can be accessed online. Based on the actual datasets from Caraga State University, the enhanced method optimized the use of classroom resources by using a smaller number of rooms. The generated timetable is more efficient as it satisfies not just hard constraints, which are conflicting schedules, but also soft constraints.

Abstract: With the current development of Information Technology, of course, it has a big impact on very significant changes in various fields. Sinar Baru Property is a property development company. Until now the system for sending and receiving goods at Sinar Baru Property is still conventional and not yet web-based and has not been planned, organized, actuated, controlled, so that it is constrained in needing materials for construction. The purpose of this research is to find out the system that is currently running, as well as to design a web-based system for sending and receiving goods using planning, organizing, actuating, controlling analysis at Sinar Baru Property. The research method used is descriptive method and in analyzing and designing the system is the method of analysis and object-oriented design using the Unified Modeling Language. The results of this study are in the form of an application, namely a web-based information system for sending and receiving goods that has a good level of quality and can function to provide information about shipping and receiving data quickly, precisely and accurately and supports digital concepts.

Abstract: Web applications are often built as Single Page Applications (SPA), for example applications offered by Google, Facebook, Twitter or Netflix. Users interact with SPAs through a single HTML page that is dynamically rewritten with new data from the web server (instead of a web browser that loads entire new HTML pages). Just like with any type of software system, debugging is a common activity during the development and maintenance of SPAs. In order to fix bugs observed during runtime, developers often try to reproduce the bug first to better understand it. However, research has shown that reproducing bugs is not always possible. In this paper we (i) develop a technique for Application Monitoring (AM) to collect data to support bug reproduction; and (ii) apply the monitoring technique in a SPA test bed as well as a real-world SPA application to show its feasibility. As part of our research we developed an initial version of the AM technique and implemented it in a prototype. Our evaluation using this prototype showed that it not only improves the efficiency of the bug reproduction process but also reduces information gaps caused by incomplete bug reports submitted by users. Additionally, compared to the information provided by users, data provided by AM is more accurate and detailed and covers a wider range of data. Future work includes deploying the AM framework in more SPAs and investigating how AM can be integrated into software developer workflows.

Abstract: This study aimed to investigate the use of and willingness to adopt web-based technology for self-management of type 2 diabetes among Arabic-speaking immigrants in Saudi Arabia. Conducted in Taif in 2022, it involved participants with type 2 diabetes mellitus, utilizing a study-specific questionnaire to gather data on demographics, disease specifics, and attitudes towards using this technology for diabetes management. Out of the 109 individuals who responded, 91 completed the survey and reported accessing web-based technology and an average usage of two hours per day. The primary use was for social media (90.1%) and information searching (73.6%). The study found a high willingness to use web-based technology for dietary planning (85.7%), physical activity monitoring (94.5%), and communication with healthcare providers (93.41%). Notably, younger participants, those with higher education, and married individuals showed more inclination towards using such technology, as indicated by significant correlations (p < 0.001, CI = 0.03–0.38; p < 0.039, CI = 1.06–10.26; p = 0.024, CI = 1.23–19.74). Over half of the participants (56%) considered web-based technology beneficial for diabetes management, with many finding it time-saving (61.5%). In conclusion, a significant proportion of participants demonstrated a strong preference for integrating web-based technology into their diabetes self-management routines. This preference was particularly evident in key areas such as diet, physical activity, and glucose monitoring. These findings underscore the potential of web-based technologies in supporting effective diabetes management among Arabic-speaking immigrants, highlighting the need for targeted interventions that leverage these digital tools.

Abstract: One year ago we was reading an article about Teleconferencing / chatting, which as we said it is a method of using technology to bring people and ideas "together" despite of the geographic barriers. From that time and on we started wondering if we can participate in that technology and how? The idea of creating a chat server was initiated and it has two dimensions, one to have an experience in network programming and the other is to let people conduct meetings with others in different locations. Such that it crosses time zones, can reach many people, and reduce the paper flood.

Abstract: ABSTRACT The advent of advanced sequencing technologies has significantly reduced the cost and increased the feasibility of assembling high-quality genomes. Yet, the annotation of genomic elements remains a complex challenge. Even for species with comprehensively annotated reference genomes, the functional assessment of individual genetic variants is not straightforward. In response to these challenges, recent breakthroughs in machine learning have led to the development of DNA language models. These transformer-based architectures are designed to tackle a wide array of genomic tasks with enhanced efficiency and accuracy. In this context, we introduce GENA-Web, a web-based platform that consolidates a suite of genome annotation tools powered by DNA language models. The version of GENA-Web presented here encompasses a diverse set of models trained on human data, including the prediction of promoter activity, annotation of splice sites, determination of various chromatin features, and a model for scoring of enhancer activity in Drosophila. GENA-Web is accessible online at https://dnalm.airi.net/

Abstract: Abstract Background Web-based self-help interventions for parents of children with ADHD and other externalizing disorders have been proven to be effective. In order to recommend individualized and optimized interventions, a better understanding of the acceptance and utilization of this innovative treatment approach is needed. Previous research has frequently employed subjective reports of utilization, but the validity of these studies may be limited. Methods Data from the German WASH study were used. Participants ( n = 276) were randomly assigned to the intervention condition (a) web-based self-help or (b) web-based self-help with optional telephone-based support calls. Data collection took place at baseline (T1) and 12 weeks later (T2). Utilization data were tracked using a log file generated for each participant at T2. Prediction models were calculated using CART (Classification and Regression Trees), a method known mostly from the field of machine learning. Results Acceptance, of the intervention as defined in this paper was very high on objective (89.4% have taken up the intervention) and subjective measures (91.4% reported having used the intervention and 95.3% reported they would recommend the intervention to a friend). The average number of logins corresponded to recommendations. Predictors of acceptance and predictors of utilization were similar and included, e.g., child’s externalizing symptoms, parental psychopathology, and above all additional telephone-based support by counselors. Conclusions Through a detailed identification of acceptance and utilization, and the predictors thereof, we were able to gain a better understanding of the acceptance and utilization of web-assisted self-help for a parent management intervention in the treatment of children with ADHD and ODD. These findings can be used to recommend web-based interventions to particularly suitable families. It should be noted that some form of support is required for an intensive engagement with the content of the program. Trial Registration The protocol of the study (German Clinical Trials Register DRKS00013456 conducted on January 3rd, 2018) was approved by the Ethics Committee of the University Hospital, Cologne.

Abstract: Crowdsourcing plays an important role in Web and social media research, from data annotation, to online experiments and user surveys. With the emergence of Generative AI (GenAI), researchers are considering how models and tools such as GPT might replace crowdwork. Many have already evaluated GPT on annotation tasks. However, it is less clear how GenAI might impact other types of tasks, or to what extent crowdworkers have already incorporated it into their work processes. Thus, we asked crowdworkers directly regarding their use of GenAI, via a survey at two points in time, across three commercial platforms. We found evidence that workers' self-reported use of GenAI did not change over time, but rather, was strongly correlated to the platform in which they operate, with MTurk workers using GenAI much more often than those operating at Clickworker and Prolific. As most respondents reported that survey completion is their "usual type of task", we discuss the implication of the use of GenAI in user surveys, via specific examples of ICWSM research.

Abstract: Smart Village is a flagship program of the Sinjai Regency Government which aims to facilitate website-based government services to the community. As time goes by and the serious commitment of the Sinjai Regency Government to accelerate development in the area until 2023, 67 villages and 13 sub-districts are now integrated with Smart Village or already have a website. This research aims to describe how the smart village program is implemented in Sinjai Regency and what factors support the implementation of the web-based smart village policy. This research method uses a qualitative method with a case study approach with collection techniques using studies based on interview results. The results of this research show that the implementation of a web-based Smart Village in Sinjai Regency has gone well. Policy implementation is not only influenced by internal factors but also by external factors. Internal Factors are four important conditions in achieving successful policy implementation according to George C.E. III, namely: Communication, Resources, Dispositions (disposition/behavior), and Bureaucratic Structure (bureaucratic structure). Meanwhile, the external factors are village community participation, support from community leaders, and support from stakeholders.

Abstract: This work shows the original projection of a 1:57,600 scale map of southern Germany at the end of the 18th century, produced under the direction of Karl-Heinrich von Schmitt (1743–1805). The sections of the map were scanned and georeferenced as part of the MAPIRE project, and the results are publicly available. In the present work, we use contemporary documents, in particular the books of César-Francois Cassini de Thury and manuscript sketches of the map found in the Military Archive of Vienna, to show that the overall projection of the map is identical to that used in Cassini’s survey of France (first half of the 18th century). In the archive, we managed to find the overview sheet on which—in addition to the Paris Cassini coordinate system—the section grid of the Schmitt map was also constructed. This sketch served as the basis for the compilation and copying work, wherein the existing map works and survey sketches were inserted into 197 sections of the Schmitt map. Thus, the map coordinate system can be modeled in GIS systems using the Cassini (or Cassini-Soldner) projection, with the Paris Observatory as the projection origin. The georeferencing accuracy of using the pure Cassini projection is around 1–1.3 km (at the extremes, around 5 km), which is much more inaccurate than the one used in later topographic surveys. It is considered a combined result of the compilation of the different maps, presumably surveyed by graphic triangulation with measuring tables.

Abstract: Abstract: Malaria is a serious health concern for modern humans, affecting people of all ages. Infected mosquitoes carry the fatal parasites responsible for malaria. Malaria can be diagnosed by examining a sample of the patient's blood under a microscope for parasites. The project comprises creating a web tool that employs deep learning to detect malaria parasites in blood smear photos. Convolutional neural network (CNN) models such as ResNet50, VGG19, and Customized CNN can be used to collect and categorize a set of blood smear images in order to identify patterns and characteristics. Convolutional layers, maxpooling layers, entirely linked layers, and a SoftMax layer are all utilized to create a Convolutional Neural Network (CNN) model. This technique can improve the accuracy of parasite diagnosis, increase detection rates, and reduce the disease's impact on global health.

Abstract: We are now in an era of new technologies, with immersive technologies being one of the most intriguing. Architects, scientists, engineers, arts, entertainment, video game industries, and education utilize these interactive technologies. Immersive technologies include numerous technologies for managing Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR). With these technologies, we can now carry out practical activities in the field of education in the form of simulations in VR, AR, and MR. Although AR, VR, and MR can be used to give more experiences for practical activities, it is still challenging for medical schools to use them in practical lessons. Innovation is needed to overcome the challenge. This paper presents our work in developing WebXR, which combines VR, AR, and MR in the same environment in real time. We aim to make VR, AR, and MR applications more flexible for medical schools. The developed WebXR provides standard operating procedures for intramuscular injections, infusion installation, and feeding the elderly. We conducted software testing, user testing, pre- and post-test testing. The test results showed the flexibility of WebXR that leads to significant advantages for medical school lessons.

Abstract: Background: Continuous Glucose Monitoring (CGM) systems have revolutionized diabetes management by providing real-time blood glucose tracking. However, there is a need for openly accessible tools that can analyze CGM data in relation to specific events like meals or exercise, which often require extensive technical skills to interpret, thus restricting its broader use among researchers and clinicians. Developing user-friendly web applications to facilitate this analysis could significantly broaden accessibility and utility. Method: Diametrics was built with a focus on ease-of-use and versatility. The application's efficacy was validated against iglu, an established R tool with a no-code web app for CGM analysis, using data from 418 participants from three studies. The unique period-specific analysis feature was demonstrated through an illustrative case study. Results: Diametrics proved effective at replicated established CGM metrics, demonstrating high concordance with iglu. The platform supports a wide range of CGM devices, accommodates data in various formats, and offers extensive customization in the analysis settings. The case study highlighted Diametrics' ability to integrate exercise-related data with CGM readings, enabling detailed analyses of how different exercise types, intensities, and times of day impact glucose levels. Conclusions: Diametrics is a freely available, reproducible, user-friendly, and accurate web-based tool for CGM data analysis with a unique capability to analyze data over specific time periods. With its intuitive design and open-source accessibility, Diametrics provides a valuable resource in diabetes research and management, empowering users of various technical levels to perform complex analyses with ease.

Abstract: In the rapidly expanding information era, the Internet has become an indispensable part of peoples' lives, and in this rapidly globalizing world, communication amongst people is paramount. Users can now access websites and other online resources because of the HTTP (Hypertext Transfer Protocol) request-response protocol, which is used to transfer data over the internet. However, one of its disadvantages is that clients cannot access servers' real-time data. Therefore, real-time communication is not possible with technologies like HTTP streaming, long polling, and polling. As a result, WebRTC, or Web Real-Time Communication, and the Web Socket Protocol were used. The latter enables browser-to-browser sharing of media and data in real time. With the help of this peer-to-peer technology, web browsers can now communicate in real time. Almost all contemporary browsers have this technology, which allows them to talk to each other rather than just web servers. Thus, this paper covers the importance of communicating in real-time, the limitations of traditional web real-time communication, an overview of web sockets, and the differences between HTTP and Web Socket Protocol. The paper then explains the significance of audio and video conferencing in the modern world and provides an overview of Web Real-Time Communication (WebRTC), including its architecture and the use of a web-RTC-based system.

Abstract: Abstract Background The detection of uniparental disomies (the inheritance of both chromosome homologues from a single parent, UPDs) is not part of most standard or commercial NGS-pipelines in human genetics and thus a common gap in NGS diagnostics. To address this we developed a tool for UPD-detection based on panel or exome data which is easy to use and publicly available. Results The app is freely available at https://altafplotter.uni-leipzig.de/ and implemented in Python, using the Streamlit framework for data science web apps. It utilizes bcftools and tabix for processing vcf files. The source code is available at https://github.com/HUGLeipzig/altafplotter and can be used to host your own instance of the tool. Conclusion We believe the app to be a great benefit for research and diagnostic labs, which struggle identifying and interpreting UPDs in their NGS diagnostic setup. The information provided allows a quick interpretation of the results and thus is suitable for usage in a high throughput manner by clinicians and biologists.

Abstract: The children with ASD have difficulty in showing empathy and also in recognizing and identifying emotions. This research introduces a web-based facial emotion recognition system designed to assist ASD children in recognizing and understanding emotions in others, ultimately enhancing their social skills. The system is implemented using the Flask web framework & CNN, providing a user-friendly interface for both children and caregivers or therapists. This study employs deep learning to detect face and analyze facial expressions and accurately classify emotion out of 6 emotions i.e., fear, angry, joy, natural, sadness, surprise displayed by individuals with ASD A CNN-based FER model trained on an autistic children dataset helps children with ASD recognize and understand facial emotions, a skill crucial for successful social interactions, targeting 6-12 year old. The CNN model has potential applications of FER in real-time social scenarios comparing with the existing methods like facial coding system, local binary pattern etc. our model aims to provide personalized and interactive learning environment where the facial emotions of children with ASD are detected through web cam during a learning session and unique emotion is detected which is graphically represented at the end of the session with the benefit of web based flask framework to assist educators, therapists to improve learning techniques, social skills among ASD children. Ultimately promoting a better quality of life for people who belong in the autistic spectrum.

Abstract: Electrocardiogram (ECG) acts as a symptomatic tool that routinely analyzes the functions of the heart. Till recently, most ECG records were kept on thermal paper. The evaluation of ECG charts needs considerable training and can be time-consuming and daunting process. The evaluation of ECG charts needs considerable training and can be time-consuming and daunting process. We can perform diagnosis and analysis with automation by digitizing the paper ECG. We can perform diagnosis and analysis with automation by digitizing the paper ECG. The main goal of this chapter is physical to-digital fusion of ECG signal and implement machine learning algorithm. This can be achieved by extracting the P, QRS, and T waves in ECG signals to demonstrate the heart's electrical activity using various techniques. The web-based application can make use of a machine-learning algorithm that analyzes and diagnoses cardiac disorders and normal conditions by uploading the ECG image. Thereby it reduces the time-consuming and daunting process for the analysis of ECG reports.

Abstract: This narrative review explores the impact of checklists and error reporting systems on hospital patient safety and medical errors. A systematic search of academic databases from 2013 to 2023 was conducted, and peer-reviewed studies meeting inclusion criteria were assessed for methodological rigor. The review highlights evidence supporting the efficacy of checklists in reducing medication errors, surgical complications, and other adverse events. Error reporting systems foster transparency, encouraging professionals to report incidents and identify systemic vulnerabilities. Checklists and error reporting systems are interconnected. Interprofessional collaboration is emphasized in checklist implementation. In this review, limitations arise due to the different methodologies used in the articles and potential publication bias. In addition, language restrictions may exclude valuable non-English research. While positive impacts are evident, success depends on organizational culture and resources. This review contributes to patient safety knowledge by examining the relevant literature, emphasizing the importance of interventions, and calling for further research into their effectiveness across diverse healthcare and cultural settings. Understanding these dynamics is crucial for healthcare providers to optimize patient safety outcomes.

Abstract: In Indonesia, the rental business of temporary accommodations or boarding houses ('kost') has significantly grown due to the influx of individuals from various cities or regions seeking temporary residence for educational pursuits, work, entrepreneurship, or marriage. Boarding house owners often manage not just one or two rooms but can have dozens or even hundreds of rooms. This extensive scale makes it challenging for boarding house owners to efficiently handle payment data, accurately record information, and report room damages using conventional methods. To address these challenges, an application was developed to streamline data management for boarding house owners, enabling them to efficiently manage their businesses. The data collection methods employed for developing this application included observation, interviews, and literature review, following the waterfall model for software development. The obtained results from this application development facilitate better service management for boarding house owners, enhancing cost and time efficiency while improving the quantity and quality of managed information.

Abstract: Dalam penulisan penelitian ini, penulis melakukan peneltian bagaimana proses pelanggaran dan poin yang diberikan kepada siswa siswinya karena SMK Swasta Satria Bingai merupakan sekolah ternama. Sekolah tersebut memiliki peraturan dan tingkat kedisiplinan yang kuat terhadap siswa siswinya, barang siapa yang terlambat atau melakukan pelanggaran maka pihak sekolah akan melakukan tindakan sanksi tegas agar siswa siswinya tidak akan mengulangi perbuatannya itu. Untuk meningkatkan kualitas siswa siswinya diperlukan informasi dan data yang akurat secara terkomputerisasi. Permasalahan yang ada yaitu kesuliatan dalam menentukan besarnya poin siswa dalam setiap melakukan pelanggaran, terjadinya kesalahan dalam pencatatan poin siswa yang melanggar, salah dalam perhitungan poin siswa dan tidak tersedianya database untuk menyimpannya. Pada penelitian ini, penulis menggunakan metode wawancara, kepustakaan, observasi dan membangun sistem menggunakan metode waterfall. Penulis juga menggunakan metode perancangan berbasis object oriented seperti UML (Unified Modeling Language). Untuk perancangan sistem yang akan di buat digunakan relasi table dan ERD (Entity Relationship Diagram). Hasil penelitian yang di lakukan oleh penulis di harapkan dapat membantu sekolah SMK Swasta Satria Bingai dapat mendidik siswa siswinya lebih baik lagi.