Web-based Repository Research Articles

Best practices for expansion of smoke-free and aerosol-free environments in Europe: Protocol for the consultation to experts.

Smoke-free legislation has been shown to positively impact reducing secondhand smoke (SHS) exposure, especially in countries that have implemented comprehensive legislation rather than partial bans. Also, secondhand aerosols (SHA) that come from the heating of tobacco or liquids, with or without nicotine, in electronic nicotine delivery systems (ENDS) have been proven to increase levels of harmful substances in the air. Therefore, protection against SHS and SHA exposure and expansion of smoke- and aerosol-free environments (SAFE) should be taken into account when creating or trying to expand or enforce clean air policies. This article aims to present the protocol for a consultation with experts on tobacco and nicotine control in order to identify best practices, barriers, and opportunities for the expansion of SAFE in Europe. We identified experts among policymakers, researchers, and tobacco regulators in European countries and invited them to participate in the consultation by completing an online survey designed, programmed, and pilot-tested using Survey Monkey. The responses to the questionnaire contained quantitative and qualitative information that was thematically analyzed. The experts' consultation allowed us to produce a report on barriers and opportunities for SAFE, a report and a position paper on SAFE best practices, a web-based repository of best practices, and a weight of evidence paper that assembles evidence supporting the expansion of SAFE on indoor and outdoor spaces.

Predictors of readmission and mortality in adults with diabetes or stress hyperglycemia after initial hospitalization for COVID-19

IntroductionWe previously reported predictors of mortality in 1786 adults with diabetes or stress hyperglycemia (glucose>180 mg/dL twice in 24 hours) admitted with COVID-19 from March 2020 to February 2021 to...

345 Fostering academic-community research teams to conduct community-engaged research in environmental justice communities: The RISE Communities R25 program

OBJECTIVES/GOALS: Residents of environmental justice (EJ) communities experience significantly higher rates of negative health outcomes associated with poor air quality. Low-cost air sensors may supplement regulatory monitoring to better measure air pollution at local scales, but widespread application of this technology remains limited due to many challenges. METHODS/STUDY POPULATION: To address these obstacles, we designed a training program to equip community and academic research partners with the skills and knowledge to successfully apply low-cost sensors in community-engaged environmental health research. The R esearch Innovations using Sensor Technology in Environmental Justice Communities (RISE Communities) program was established through an NIEHS R25 award in 2022 and has three specific aims: 1) Foster community-academic partnerships through research education, training, and team development activities, 2) Provide technical training in the application of low-cost sensors for indoor, outdoor, and personal air monitoring in EJ communities, and 3) Establish a community of practice to address air quality in communities nationwide. RESULTS/ANTICIPATED RESULTS: We hosted our first cohort in August 2023, training five community-academic research teams in team collaboration, community-engaged research, and technical skills for collecting and analyzing data from PurpleAir sensors. Each team received 12 sensors to take to their home EJ communities to begin their projects. Community of practice development continues through interactive webinars and development of a web-based repository of training videos and discussion board posts. Evaluation data show high participant learning and satisfaction, with mean confidence scores improving on 6/8 metrics. Evaluation data also suggest several areas for improvement such as more time spent in teams for planning and additional opportunities for interaction within the cohort and with program instructors for problem-solving. DISCUSSION/SIGNIFICANCE: Effective training for team-based community-engaged research requires careful planning for team development and study implementation. Longitudinal training and support for the technical aspects of utilizing air sensors is also critical to team success. The RISE Communities program is actively recruiting for future training cohorts.

An Innovative Framework for Automated Software Testing and Validation

The rising scale and the intricate nature of these systems make the verification & validation (V&V) of classifications that are automated more costly and to much time-taking. Furthermore, the V and V of the following systems might be hampered if the techniques and procedures are not effectively documented, assessed, and selected. Practitioners must employ appropriate V and V methodologies and conduct acceptable V and V procedures to ensure the following systems perform as proposed and in cost-effective way. Earlier efforts have produced several categorizations and models that may be used to categorize V and V approaches and technologies. The goal of this study is to give a wide, comprehensive, and simple framework for characterization needs, rather than focusing on particular parts of V and V methodologies and procedures. To that purpose, in this study, we provide a multi-domained and multi-dimensioned framework for characterizing and classifying V and V approaches and tools in an organized manner. The framework reflects a complete description of several key features of V&V. As an example of usage, a web-based repository has been created based upon the framework to gather information regarding the use of V and V approaches and tackles. Experts and scholars may readily learn about and select acceptable V and V procedures this way.

Abstract 943: Identification and validation of unusual drug combinations identified from combination databases

Abstract There is a noted trend in the identification and subsequent approval of rational drug combinations to treat various diseases, particularly cancer. When applied in a clinical setting, synergistic combinations can have significant benefits including improved patient response and avoiding or overcoming drug resistance. Although multiple strategies have been successfully implemented to identify rational drug combinations, extensive validation is initially required to confirm a combination as synergistic. The existence and growing use of web-based repositories containing comprehensive drug combination data is a key resource and can be a valuable starting point for identifying synergistic combinations. However, are synergistic combinations from these datasets expected or rational and can they be validated experimentally? By mining available drug combinations from the DrugCombo database, we wanted to identify unusual drug combinations reported as synergistic and experimentally validate these with dose-response assays. In addition, we set out to establish if cytokines could be used as an inhibition biomarker to easily assess synergy. We found multiple unexpected synergies including a predicted synergy between the JAK1/2 inhibitor Ruxolitinib with Maraviroc, a CCR5 antagonist, or Levetiracetam, an SV2A binding anti-epileptic reported in the lymphoma cell line, L-1236. Experimentally, these predicted synergies could not be validated. In the context of synergistic drug combinations, this work shows that experimental validation is crucial, particularly for combinations with uncertain biological mechanisms. Citation Format: Rainer Grant, Marco Pinheiro, Rachel Weller Roska, Robert Felix. Identification and validation of unusual drug combinations identified from combination databases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 943.

Allele Frequency Net Database.

The allele frequency net database (AFND, http://www.allelefrequencies.net ) is an online web-based repository that contains information on the frequencies of immune-related genes and their corresponding alleles in worldwide human populations. At present, the website contains data from 1784 population samples in more than 14 million individuals from 129 countries on the frequency of genes from different polymorphic regions including data for the human leukocyte antigen (HLA) system. In addition, over the last four years, AFND has also incorporated genotype raw data from 85,000 individuals comprising 215 population samples from 39 countries. Moreover, more population data sets containing next generation sequencing data spanning >3 million individuals have been added. This resource has been widely used in a variety of contexts such as histocompatibility, immunology, epidemiology, pharmacogenetics, epitope prediction algorithms for population coverage in vaccine development, population genetics, among many others. In this chapter, we present an update of the most used searching mechanisms as described in a previous volume and some of the latest developments included in AFND.

Academic Dishonesty in Online Accounting Assessments—Evidence on the Use of Academic Resource Sites

ABSTRACT As accounting programs increase their online offerings, understanding the challenges of maintaining academic integrity online is crucial. This study documents an emerging method of online academic dishonesty—on-demand services from academic resource sites (ARS) such as Chegg.com. ARS are web-based repositories of textbook problems, homework solutions, etc., and many of them employ subject-matter experts to answer questions in real time, potentially during active exams. In periods of fewer online exam safeguards, 13–25 percent of intermediate accounting students are identified as using Chegg during exams. Corroborating evidence shows an anomalous improvement in student performance in online exams with minimal safeguards, which is attenuated by an increase in mitigation policies. Survey responses confirm that students are familiar with and use ARS, including 10 percent who acknowledge use during quizzes or exams. These findings help formulate suggestions about practices educators can employ to decrease pervasive use of ARS in online learning. JEL Classifications: M49.

Guidelines and Standard Frameworks for AI in Medicine: Protocol for a Systematic Literature Review.

Applications of artificial intelligence (AI) are pervasive in modern biomedical science. In fact, research results suggesting algorithms and AI models for different target diseases and conditions are continuously increasing. While this situation undoubtedly improves the outcome of AI models, health care providers are increasingly unsure which AI model to use due to multiple alternatives for a specific target and the "black box" nature of AI. Moreover, the fact that studies rarely use guidelines in developing and reporting AI models poses additional challenges in trusting and adapting models for practical implementation. This review protocol describes the planned steps and methods for a review of the synthesized evidence regarding the quality of available guidelines and frameworks to facilitate AI applications in medicine. We will commence a systematic literature search using medical subject headings terms for medicine, guidelines, and machine learning (ML). All available guidelines, standard frameworks, best practices, checklists, and recommendations will be included, irrespective of the study design. The search will be conducted on web-based repositories such as PubMed, Web of Science, and the EQUATOR (Enhancing the Quality and Transparency of Health Research) network. After removing duplicate results, a preliminary scan for titles will be done by 2 reviewers. After the first scan, the reviewers will rescan the selected literature for abstract review, and any incongruities about whether to include the article for full-text review or not will be resolved by the third and fourth reviewer based on the predefined criteria. A Google Scholar (Google LLC) search will also be performed to identify gray literature. The quality of identified guidelines will be evaluated using the Appraisal of Guidelines, Research, and Evaluation (AGREE II) tool. A descriptive summary and narrative synthesis will be carried out, and the details of critical appraisal and subgroup synthesis findings will be presented. The results will be reported using the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analyses) reporting guidelines. Data analysis is currently underway, and we anticipate finalizing the review by November 2023. Guidelines and recommended frameworks for developing, reporting, and implementing AI studies have been developed by different experts to facilitate the reliable assessment of validity and consistent interpretation of ML models for medical applications. We postulate that a guideline supports the assessment of an ML model only if the quality and reliability of the guideline are high. Assessing the quality and aspects of available guidelines, recommendations, checklists, and frameworks-as will be done in the proposed review-will provide comprehensive insights into current gaps and help to formulate future research directions. DERR1-10.2196/47105.

Digital Health: A Web-based Repository with Back School Recommendations and Exercises against Paravertebral Pain (with a Comparative Study of the Opinions of Responders of Different Generations)

Digital Health (DH) is a relatively new concept for our country. The current article is oriented to the application of DH technologies for the prevention of paravertebral pain, by a web-based repository. In the repository, we included Back school recommendations, position techniques, exercises, activities, sports, and clinical cases of our own rehabilitation practice.

The Case Study of the Serbian Copyist Ioan. On the Development of a Scientific Method for South Slavonic Palaeography

The present research aims to address the case study about the Serbian copyist anagnost Ioan through the use of the web-based repository. The same scribe's signature is observed in the manuscripts Dečani No 127 and No 119, which are also connected by the typology and a similar dating. The goal is to compare the distinctive features of both manuscripts and the handwriting of the 14th century scribes who contributed to the copying. In conducting this research, we will use a new descriptive scientific model, created and tested by the research project team.

A hybrid convolutional neural network with long short-term memory (HCNN-LSTM) model based Edge System Recommendation(ESR) for cloud service providers

Massive entities with significant state denaturation exist in the physical world, and users urgently want real-time and intelligent entity information acquisition. Now a days hand held devices and Electronic Device usage are increased rapidly. For effective cloud service edge systems are used. As rapid growth of internet and hardware technologies many edge providers are in the market. For Cloud Service Providers (CSP) it will be a chaos to choose optimised and reliable edge system for their usage. A hybrid convolutional neural network with Long Short-Term Memory (HCNN-LSTM) based Edge System Recommendation (ESR) Algorithm for Cloud Service Providers. An entity identification technique suitable for the edge is suggested to enhance the precision and responsiveness of entity state data search. It conducts accurate entity identification using the HCNN-LSTM while considering entity feature information. Even for new CSP optimised Edge System will be easily allocated. For this Recommendation Algorithm a total of 3 Servers and 25 Edge Systems with varied configuration are tested. 1000 GB hybrid data is used for transaction. The dataset collected from Kaggle online web-based repository. This proposed algorithm proves 95% more effective than existing techniques.

Open science and data sharing in cognitive neuroscience with MouseBytes and MouseBytes+

Open access to rodent cognitive data has lagged behind the rapid generation of large open-access datasets in other areas of neuroscience, such as neuroimaging and genomics. One contributing factor has been the absence of uniform standardization in experiments and data output, an issue that has particularly plagued studies in animal models. Touchscreen-automated cognitive testing of animal models allows standardized outputs that are compatible with open-access sharing. Touchscreen datasets can be combined with different neuro-technologies such as fiber photometry, miniscopes, optogenetics, and MRI to evaluate the relationship between neural activity and behavior. Here we describe a platform that allows deposition of these data into an open-access repository. This platform, called MouseBytes, is a web-based repository that enables researchers to store, share, visualize, and analyze cognitive data. Here we present the architecture, structure, and the essential infrastructure behind MouseBytes. In addition, we describe MouseBytes+, a database that allows data from complementary neuro-technologies such as imaging and photometry to be easily integrated with behavioral data in MouseBytes to support multi-modal behavioral analysis.

Quality improvement dissemination in pediatric surgery: The APSA quality and safety toolkit

Shared experiential learning is critical in the field of pediatric surgery to support the translation of evidence into practice. Surgeons who develop QI interventions in their own institutions based on the best available evidence create work products that can accelerate similar projects in other institutions, rather than continuously reinventing the wheel. The American Pediatric Surgical Association (APSA) Quality and Safety Committee (QSC) toolkit was created to facilitate knowledge-sharing and thereby hasten the development and implementation of QI. The toolkit is an expanding open-access web-based repository of curated QI projects that includes evidence-based pathways and protocols, stakeholder presentations, parent/patient educational materials, clinical decision support (CDS) tools, and other components of successful QI interventions in addition to contact information for the surgeons who developed and implemented them. This resource catalyzes local QI endeavors by showcasing a range of projects that can be adapted to fit the needs of a given institution, and it also serves as a network to connect interested surgeons with successful implementers. As healthcare shifts towards value-based care models, quality improvement becomes increasingly important, and the APSA QSC toolkit will continue to adapt to the evolving needs of the pediatric surgery community.

Assistive technology, information asymmetry and the role of brokerage services: a scoping review

ObjectivesAccess to assistive technologies (ATs) is a human right for people with disabilities, but there are a range of barriers, including lack of adequate information. This review aimed to explore...

Building a ‘Virtual Library’: continuing a global collaboration to strengthen research capacity within Nepal and other low- and middle-income countries

ABSTRACT To fill the gap in health research capacity-building efforts, we created the ‘Virtual Library’ (VL) – a web-based repository of context-relevant resources for health researchers in low- and middle-income countries (LMICs). This paper describes the participatory process used to systematically develop the VL, and describes how our interprofessional team – representing both an LMIC (Nepal) and a high-income country (HIC) (USA, US) – engaged in shared meaning-making. A team of researchers and clinicians representing a range of subdisciplines from Nepal and the US created a replicable search strategy and standardized Resource Screening Guide (RSG) to systematically assess resources to be included within the VL. Descriptive methods were used to summarize findings from the RSG and lessons learned from the collaborative process. Collectively, 14 team members reviewed 564 potential resources (mean = 40, SD = 22.7). Mean RSG score was 7.02/10 (SD = 2). More than 76% of resources met each of the four quality criteria (relevant; reputable, accessible; understandable). Within the published VL, 298 resources were included, organized by 15 topics and 45 sub-topics. Of these, 223 resources were evaluated by the RSG; 75 were identified by team member expertise. The collaborative process involved regular meetings, iterative document revisions, and peer review. Resource quality was better than expected, perhaps because best practices/principles related to health research are universally relevant, regardless of context. While the RSG was essential to systematize our search and ensure reproducibility, team member expertise was valuable. Pairing team members during peer-review led to bi-directional knowledge sharing and was particularly successful. This work reflects a highly collaborative global partnership and offers a model for future health research capacity-building efforts. We invite engagement with the Virtual Library <https://lmicresearch.org> as one supportive pillar of infrastructure to develop individual and institutional research capacity.

The Effect of Using Data Pre-Processing by Imputations in Handling Missing Values

The evolution of big data analytics through machine learning and artificial intelligence techniques has caused organizations in a wide range of sectors including health, manufacturing, e-commerce, governance, and social welfare to realize the value of massive volumes of data accumulating on web-based repositories daily. This has led to the adoption of data-driven decision models; for example, through sentiment analysis in marketing where produces leverage customer feedback and reviews to develop customer-oriented products. However, the data generated in real-world activities is subject to errors resulting from inaccurate measurements or fault input devices, which may result in the loss of some values. Missing attribute/variable values make data unsuitable for decision analytics due to noises and inconsistencies that create bias. The objective of this paper was to explore the problem of missing data and develop an advanced imputation model based on Machine Learning and implemented on K-Nearest Neighbor (KNN) algorithm in R programming language as an approach to handle missing values. The methodology used in this paper relied on the applying advanced machine learning algorithms with high-level accuracy in pattern detection and predictive analytics on the existing imputation techniques, which handle missing values by random replacement or deletion.. According to the results, advanced imputation technique based on machine learning models replaced missing values from a dataset with 89.5% accuracy. The experimental results showed that pre-processing by imputation delivers high-level performance efficiency in handling missing data values. These findings are consistent with the key idea of paper, which is to explore alternative imputation techniques for handling missing values to improve the accuracy and reliability of decision insights extracted from datasets.

HIET Web-based digital repository for health informatics evaluation tools

PurposeEvaluating health information systems is an integral part of the life cycle and development of information systems as it can improve the quality of health care. The purpose of this paper is to introduce a bilingual Web-based repository of health-related software products evaluation tools.Design/methodology/approachThe present paper is an applied-developmental study that includes the stages of analysis, design, implementation and evaluation procedures. By searching valid databases as well as holding focus group meetings with a group of experts, the necessary elements for designing a Web-based repository were identified, and also unified modelling language diagrams were designed by using a visual paradigm. The coding(programming) was conducted based on the Gantlet Web Systems Development Framework at the next stage. Finally, after implementing and testing the system, the content was added to the repository, and then the repository was evaluated in terms of usability testing.FindingsThe health informatics evaluation tools (HIET) repository provides a functional and selective environment that facilitates the sharing, online storage and retrieval of assessment tools by the scientific community. The HIET repository is easily accessible at www.hiet.ir/ The website is implemented in structured query language (MySQL), personal homepage. Hypertext Preprocessor (PHP) and Linux, Apache, MySQL, and PHP (LEMP) and supports all major browsers.Originality/valueThe HIET repository, as mentioned earlier, serves as an application environment for sharing, storing and online retrieving the assessment tools of health information systems. Therefore, this tool not only facilitates the search, retrieving and study of many evaluation-related papers, which are time-consuming and stressful for researchers and students but can lead to a faster and more scientific evaluation of information systems.

AgYields - a national database for collation of past, present and future pasture and crop yield data

The New Zealand agricultural sector has a rich heritage of measuring yield and growth rates for pastures and crops. Historically these datasets were collected by Government departments, Crown research institutes, Universities and more latterly seed companies and private research providers as well as on-farm. These data are expensive to collect, spatially and temporally patchy, and stored in a range of electronic and physical platforms. Meanwhile the potential value of such data is increasing with the ability to create meta-analyses and simulation modelling to create resilience in crop and pasture systems to meet the needs of the changing regulatory and climate environment. A challenge of data collection is the different priorities and skill sets of those undertaking the task. Thus, there is a need to provide guidelines for the collection, collation and publication of such data to standardize best practice and maximize the value gained from increasingly scarce resources available for pasture and crop research to support the primary industries. In addition, declining funding for field research, means there is an urgent need to draw together existing and future data into a publicly accessible industry good resource. This paper outlines the development of the AgYields web-based repository for pasture and crop growth rate and yield data. It describes the rationale for the database and the need for standardization of data collection to maximize the value of stored data in common formats. The intent is to provide a resource to enhance livestock and crop production systems throughout New Zealand and provide guidelines for future data collection.

Crania Canaria 2.0: construyendo una colección virtual de cráneos

El Museo Canario stores a large collection of aboriginal skulls that have been essential to the study of the origin and chronology of the population of the Canary archipelago since the 19th century. Regrettably, research has been dominated by biased and racial interpretations of both bioarchaeological and cultural evidence. When scientific racism and craniometric studies were rejected, studies of the Canarian indigenous skulls variability was also abandoned without replies. However, digital technologies and virtual sciences allow us to improve research and re-evaluate old paradigms. In this work, we present a digitalisation project aiming to construct a virtual database of the indigenous Canarian skulls, using a simple method of digitalisation that is very suitable to deal with large collections- The procedure, involving a portable 3D structured light scanner has allowed us to digitally reproduce more than 400 skulls stored at Museo Canario. This work offers a wide variety of possibilities for archaeology and anthropology. The versatility of 3D digital models enables the generation of interactive documentation, educational material for digital conservation and dissemination purposes. Indeed, 3D models are easily shared and can be displayed over diverse web-based repositories and online platforms and so, creating virtual online museums. We have created a profile in Sketchfab (https://sketchfab.com/craniacanaria2.0) where we intend to upload gradually the complete virtual collection of skulls we have realised. Moreover, digital skulls can serve as research objects. We discuss the advantages of studying 3D objects in a computerised environment, which includes traditional anthropometric studies (linear measurements and angles) but also 3D geometric morphometric approaches. In fact, in future studies, we will apply 3D geometric morphometrics for reassessing skull variation of ancient Canarians going beyond old paradigms and taking into account the latest advances in archaeology, anthropology and genetics in Canarian research. Highlights:- El Museo Canario stores an exceptional human skull collection that has served as the basis for numerous studies seeking to reveal the origin and chronology of the indigenous population.- This study presents an easy methodology for obtaining digital imagery using a 3D surface scanner, which allows constructing a virtual skull collection comprising more than 400 individuals.- Virtual 3D models have numerous advantages and applications in anthropology and archaeology, not only improving research but also permitting the re-evaluation of old paradigms.

3D GIS Interactive Visualization of the Archaeological Sites in Qatar for Research and Learning

This project provides a proficient approach to coordinate archeological ex-ercises, information administration, digital object representation, and spa-tial investigation. The proposed framework furnishes the client with the in-tuitive investigation of the 3D model artifacts along with detailed infor-mation on specific points of interest alongside their 3D geographic infor-mation system (3D GIS). A parallel result is the utilization of fully trans-parent and cost-effective open source tools and free software. The work ad-dressed the creation of a computerized system that aids classification, ad-ministration, and representation of archeological discoveries inside a 3D web-based repository; and the utilization of 3D digital models as a restora-tion of the artifacts to allow navigation through the data; besides enabling 3D GIS to spatially store, share, envision and examine complex archeologi-cal components; This work is one of the first of its type in Qatar to archive and record all of the archeological data from the Murwab site in Qatar.