Web Portal Research Articles

Characteristics predisposing to the utilization of Internet websites offering e-prescriptions

Abstract Background The introduction of e-prescriptions in the Polish healthcare system was accompanied by the emergence of websites offering easy access to medication without adequate medical assessment. This study aimed to analyze the characteristics of Polish users of such services. Methods The analysis presented here is based on the online survey conducted in June 2023 among 1661 adult Internet users. The multivariable logistic regression model (MLRM) was developed for the variable reflecting the use of e-prescribing web services (EPWS). Sociodemographic variables, self-assessed health status, the presence of chronic disease (CHR) and disabilities (DIS), the frequency of Internet (IU) and social media use (SMU), and finally, digital health literacy (DHL) were included in MLRM as independent variables. Results The percentage of respondents who used EPWS was equal to 18.2% (n = 303). MLRM revealed that age, vocational and income status, CHR, SMU, and DHL were significant predictors of EPWS use. Older respondents were less likely than younger ones to use EPWS (odds ratio (OR), 95% confidentiality interval (95%CI): 0.97, 0.97-0.99. Persons suffering from the chronic disease, when compared to those without such disease, used EPWS less frequently (OR, 95CI: 0.59, 0.43-0.80) and unemployed when compared to employees (OR, 95%CI: 0.53, 0.32-0.88). A higher likelihood of using EPWS was observed among respondents with the highest income in comparison to those from the group with the lowest income (OR, 95%CI: 1.52, 1.02-2.52) and among more frequent social media users (OR, 95%CI: 3.88, 1.90-7.93). Finally, the increase of DHL score by 1 unit was associated with the increase of the likelihood of EPWS use by 9% (OR, 95%CI: 1.09, 1.05-1.12). Conclusions A significant number of adult Internet users utilize EPWS in Poland. Lower age, unemployment, and chronic diseases are negative predictors of EPWS use. More intense SMU and unexpectedly higher DHL predispose to the use of such services. Key messages • Even persons with high e health literacy are inclined to use web portals offering e-prescriptions. • The high prevalence of the utilization of e-prescribing websites requires awareness campaigns warning about related potential risks.

Building a community-driven bioinformatics platform to facilitate Cannabis sativa multi-omics research.

The web portal can be accessed at www.icgrc.info.

Insights into water insecurity in Indigenous communities in Canada: assessing microbial risks and innovative solutions, a multifaceted review.

Canada is considered a freshwater-rich country, despite this, several Indigenous reserves struggle with household water insecurity. In fact, some of these communities have lacked access to safe water for almost 30 years. Water quality in Canadian Indigenous reserves is influenced by several factors including source water quality, drinking water treatments applied, water distribution systems, and water storage tanks when piped water is unavailable. The objective of this multifaceted review is to spot the challenges and consequences of inadequate drinking water systems (DWS) and the available technical and microbiological alternatives to address water sanitation coverage in Indigenous reserves of Canada, North America (also known as Turtle Island). A comprehensive literature review was conducted using national web portals from both federal and provincial governments, as well as academic databases to identify the following topics: The status of water insecurity in Indigenous communities across Canada; Microbiological, chemical, and natural causes contributing to water insecurity; Limitations of applying urban-style drinking water systems in Indigenous reserves in Canada and the management of DWS for Indigenous communities in other high-income countries; and the importance of determining the microbiome inhabiting drinking water systems along with the cutting-edge technology available for its analysis. A total of 169 scientific articles matched the inclusion criteria. The major themes discussed include: The status of water insecurity and water advisories in Canada; the risks of pathogenic microorganisms (i.e., Escherichia coli and total coliforms) and other chemicals (i.e., disinfection by-products) found in water storage tanks; the most common technologies available for water treatment including coagulation, high- and low-pressure membrane filtration procedures, ozone, ion exchange, and biological ion exchange and their limitations when applying them in remote Indigenous communities. Furthermore, we reviewed the benefits and drawbacks that high throughput tools such as metagenomics (the study of genomes of microbial communities), culturomics (a high-efficiency culture approach), and microfluidics devices (microminiaturized instruments) and what they could represent for water monitoring in Indigenous reserves. This multifaceted review demonstrates that water insecurity in Canada is a reflection of the institutional structures of marginalization that persist in the country and other parts of Turtle Island. DWS on Indigenous reserves are in urgent need of upgrades. Source water protection, and drinking water monitoring plus a comprehensive design of culturally adapted, and sustainable water services are required. Collaborative efforts between First Nations authorities and federal, provincial, and territorial governments are imperative to ensure equitable access to safe drinking water in Indigenous reserves.

PROBLEMS OF CHOOSING A METHOD OF DENTAL TREATMENT OF TEETH AFTER ENDODONTIC INTERVENTION

The optimal way to restore the anatomical structure of teeth after endodontic intervention is a controversial topic. Teeth after endodontic intervention have different properties compared to intact living teeth. Changes in these properties are associated with volumetric loss of hard tissues, caries, final preparation of the cavity taking into account access to endodontic treatment. Choosing the optimal method of dental treatment of teeth requires compliance with many factors, such as: prevention of infection penetration into root canals, restoration of tooth contacts, restoration of chewing functions, protection against further carious and non-carious destruction, restoration of tooth aesthetics. Dentists are now more than ever aware of the interdependence of the endodontic and restorative aspects of dental treatment and how much this will affect achieving the best long-term outcome. Controversies of the clinical relevance of endodontic and restorative treatment choice issues are mostly unanswered based on clinical data and scientific evidence. The modern approach to tooth restoration after endodontic intervention is an important topic. To improve clinical outcomes, it is important to determine the effectiveness of treatment, the importance of preserving tooth structure, the choice of treatment method with restorative materials, and the integration of digital dentistry to improve diagnosis and treatment principles. Research rationale. The purpose of this study is to find and use literature data on the effectiveness of modern methods of dental treatment after endodontic intervention in Ukraine. Materials and methods. Scientific data from a review and systematic analysis of the literature were used. Materials were searched using the Google Scholar, PubMed, Google Scholar databases and open sources of the World Health Organization, the Ministry of Health of Ukraine and other government web portals of Ukraine. Results, Discussion. After conducting a literature analysis to compare the effectiveness of using cast metal inserts and fiberglass posts, we can come to the conclusions that retrospective studies on the relationship between successful restorations and such factors as the type of tooth, the volume of residual hard tissues, the number of occlusal contacts, the type of the final restoration and the position of the tooth in the dental arch are the main criteria for choosing a treatment method. A controversial choice is that metal abutments are associated with a higher risk of root fracture, their manufacture requires laboratory techniques, while the use of fiberglass posts is associated with a higher risk of decementation, and overloading of fiberglass posts leads to their fractures. Conclusions. Decision-making and the choice of methods of dental treatment after endodontic intervention remain difficult. However, the interdependence of endodontic treatment and restoration of the crown part of the tooth is clearly established. Physicians must consider both aspects of treatment equally to ensure the best possible outcomes for their patients. The use of digital scanning enables an accurate volumetric assessment of the residual hard tissues of the tooth, which can be used to provide tangible qualitative results of the analysis and decision-making with the choice of treatment method. The choice of treatment method is not defined in a single protocol and requires further careful study with new experimental developments, based on the latest technologies of world leaders in dentistry.

CannSeek? Yes we Can! Anopen-source single nucleotide polymorphism database and analysis portal for Cannabis sativa.

The CannSeek portal is available at https://icgrc.info/cannseek, https://icgrc.info/genotype_viewer.

9284 Leveraging Inter-Individual Transcriptional Correlation Structure To Infer Discrete Signaling Mechanisms Across Metabolic Tissues

Abstract Disclosure: M. Zhou: None. I. Tamburini: None. C. Van: None. J. Molendijk: None. L.M. Velez: None. C. Nguyen: None. R. Yeo: None. C. Filho: None. A.L. Hevener: None. J. Justice: None. L.M. Sparks: None. E.E. Kershaw: None. D. Nicholas: None. M. Seldin: None. Inter-organ communication is a vital process to maintain physiologic homeostasis, and its dysregulation contributes to many human diseases. Given that circulating bioactive factors are stable in serum, occur naturally, and are easily assayed from blood, they present obvious focal molecules for therapeutic intervention and biomarker development. A major obstacle in the characterization of such soluble factors is that defining their tissues and pathways of action requires extensive experimental testing in cells and animal models. Recently, studies have shown that secreted proteins mediating inter-tissue signaling could be identified by “brute-force” surveys of all genes within RNA-sequencing measures across tissues within a population. Expanding on this intuition, we reasoned those parallel strategies could be leveraged to understand how individual genes mediate signaling across metabolic tissues through correlative analyses of genetic gene variation between individuals. Thus, genetics comparison of quantitative levels of gene expression relationships between organs in a population could aid in understanding cross-organ signaling by adopting a gene-centric approach. Here, we surveyed gene-gene genetic correlation structure for ∼6.1x10^12 gene pairs across 18 metabolic tissues in 310 human individuals and 7 tissues in 103 diverse strains of mice fed a normal chow or HFHS diet. where the variation of genes such as FGF21, ADIPOQ, GCG, and IL6 showed enrichments that recapitulate experimental observations. Further, similar analyses were applied to explore both local within-tissue signaling mechanisms (liver PCSK9) as well as genes encoding enzymes producing metabolites (adipose PNPLA2), where genetic inter-individual correlation structure aligned with known roles for these critical metabolic pathways. Examination of sex hormone receptor correlations in mice highlighted the difference in tissue-specific variation in relationships with metabolic traits. Finally, we utilized this resource to suggest new functions for metabolic coordination between organs. For example, we prioritized key proteins for putative signaling between skeletal muscle and hippocampus, and further suggest colon as a central coordinator for systemic circadian clocks. We refer to this resource as Genetically-Derived Correlations Across Tissues (GD-CAT) where all tools and data are built into a web portal enabling users to perform these analyses without a single line of code (gdcat.org). This resource enables the querying of any gene in any tissue to find genetic coregulation correlated patterns of genes, cell types, pathways, and network architectures across metabolic organs. Presentation: 6/1/2024

7226 Leveraging Inter-Individual Transcriptional Correlation Structure To Infer Discrete Signaling Mechanisms Across Metabolic Tissues

Abstract Disclosure: M. Zhou: None. I. Tamburini: None. C. Van: None. J. Molendijk: None. L.M. Velez: None. C. Nguyen: None. R. Yeo: None. C. Filho: None. A.L. Hevener: None. J. Justice: None. L.M. Sparks: None. E.E. Kershaw: None. D. Nicholas: None. M. Seldin: None. Inter-organ communication is a vital process to maintain physiologic homeostasis, and its dysregulation contributes to many human diseases. Given that circulating bioactive factors are stable in serum, occur naturally, and are easily assayed from blood, they present obvious focal molecules for therapeutic intervention and biomarker development. A major obstacle in the characterization of such soluble factors is that defining their tissues and pathways of action requires extensive experimental testing in cells and animal models. Recently, studies have shown that secreted proteins mediating inter-tissue signaling could be identified by “brute-force” surveys of all genes within RNA-sequencing measures across tissues within a population. Expanding on this intuition, we reasoned those parallel strategies could be leveraged to understand how individual genes mediate signaling across metabolic tissues through correlative analyses of genetic gene variation between individuals. Thus, genetics comparison of quantitative levels of gene expression relationships between organs in a population could aid in understanding cross-organ signaling by adopting a gene-centric approach. Here, we surveyed gene-gene genetic correlation structure for ∼6.1x10^12 gene pairs across 18 metabolic tissues in 310 human individuals and 7 tissues in 103 diverse strains of mice fed a normal chow or HFHS diet. where the variation of genes such as FGF21, ADIPOQ, GCG, and IL6 showed enrichments that recapitulate experimental observations. Further, similar analyses were applied to explore both local within-tissue signaling mechanisms (liver PCSK9) as well as genes encoding enzymes producing metabolites (adipose PNPLA2), where genetic inter-individual correlation structure aligned with known roles for these critical metabolic pathways. Examination of sex hormone receptor correlations in mice highlighted the difference in tissue-specific variation in relationships with metabolic traits. Finally, we utilized this resource to suggest new functions for metabolic coordination between organs. For example, we prioritized key proteins for putative signaling between skeletal muscle and hippocampus, and further suggest colon as a central coordinator for systemic circadian clocks. We refer to this resource as Genetically-Derived Correlations Across Tissues (GD-CAT) where all tools and data are built into a web portal enabling users to perform these analyses without a single line of code (gdcat.org). This resource enables the querying of any gene in any tissue to find genetic coregulation correlated patterns of genes, cell types, pathways, and network architectures across metabolic organs. Presentation: 6/1/2024

A web portal for exploring kinase-substrate interactions

Interactions between protein kinases and their substrates are critical for the modulation of complex signaling pathways. Currently, there is a large amount of information available about kinases and their substrates in disparate public databases. However, these data are difficult to interpret in the context of cellular systems, which can be facilitated by examining interactions among multiple proteins at once, such as the network of interactions that constitute a signaling pathway. We present KiNet, a user-friendly web portal that integrates and shares information about kinase-substrate interactions from multiple databases of post-translational modifications. KiNet enables the visual exploration of these interactions in systems contexts, such as pathways, domain families, and custom protein set inputs, in an interactive fashion. We expect KiNet to be useful as a knowledge discovery tool for kinase-substrate interactions, and the aggregated KiNet dataset to be useful for protein kinase studies and systems-level analyses. The portal is available at https://kinet.kinametrix.com/.

Progress made in digitalizing antimicrobial resistance surveillance in a One Health approach in Kenya.

Antimicrobial resistance (AMR) is a major threat to global public health, affecting human and animal health, agriculture, food safety, and the environment. The control of AMR is often challenging, particularly when data are scanty or siloed in individual sectors. To develop evidence-based control policies for AMR, an electronic information system that integrates AMR data from various sectors, in a One Health approach, is critical. Acknowledging the interconnectedness of AMR in humans, animals, and the environment and the need to assess the AMR burden using a One Health approach, Kenya's National Antimicrobial Stewardship Interagency Committee (NASIC), with support from FIND, integrated human and animal health AMR data at the national AMR data repository and developed the One Health AMR Surveillance System (OHAMRS). The OHAMRS comprises two core digital components: interoperability middleware for integrating data from various sources and a DHIS2 web portal for the analysis and visualization of AMR surveillance data from the human and animal health sectors. These components are scalable for future inclusion of data from other One Health sectors, e.g., the environment, food/feed, and aquaculture sectors. The OHAMRS has 42 dashboards that facilitate the presentation, interpretation, and dissemination of actionable information relating to AMR, including 17 dashboards for human and animal health priority pathogens and 8 for drug-resistance indicators. The priority pathogen dashboards provide visualization of antimicrobial susceptibility patterns, resistance and susceptibility trends, resistance tables, and geospatial susceptibility maps. Other dashboards include surveillance sites and specimen reports, data completeness, data reconciliation, sample testing workload, a One Health intersectoral dashboard, and other reporting tools for diverse stakeholders. Digitalizing AMR surveillance through a One Health lens is pivotal to understand AMR prevalence and patterns across various sectors. The OHAMRS provides comprehensive data analysis and presentation, informing policymaking on AMR control. Digital tools such as the OHAMRS are vital in facilitating the availability of data and actionable information on AMR required to address the AMR crisis in Kenya.

Artificial Intelligence-Powered Technologies For Independent Living Among Older Adults: A Review

Abstract Background The ageing populations in Ireland and around the world has led to an increased focus on technologies that support independent living for older adults. Artificial intelligence (AI) has emerged as a promising solution, with various AI-powered technologies being proposed to assist their daily lives. This review aims to synthesize the findings of studies exploring AI-powered technologies for independent living among older adults. Methods A systematic literature search was conducted using relevant databases, including PubMed, IEEE Xplore, and Google Scholar. The search terms included “artificial intelligence” and “independent living”. Studies published between 2009 and 2023 that investigated AI-powered technologies for independent living among older adults were included in the analysis. Results The included studies investigated various AI-powered technologies including tablets, wearable devices like smartwatches, web portals for carers, Internet of Things (IoT) solutions, user-centered design considerations, the integration of AI with sociology and healthcare, smart home technology, and ambient information systems. The pooled results indicated that AI-powered technologies can improve independent living outcomes for older adults. Benefits included real-time monitoring and health deterioration recognition, fall detection, personalised care, cognitive assistance and reduced isolation. User-centered design approaches and the integration of AI with sociology and healthcare were also found to be essential factors in the successful implementation of these technologies. Conclusion This analysis provides evidence supporting the effectiveness of AI-powered technologies in promoting independent living among older adults. IoT solutions and smart home technology appear to be particularly promising. However, the successful implementation of these technologies requires a multidisciplinary approach, incorporating user-centered design and the integration of AI with sociology and healthcare. Further research is needed to explore the long-term impact of AI-powered technologies on the well-being and autonomy of older adults.

NPreciSe - An Automated Satellite Precipitation Product Assessment Tool.

Satellite-based Quantitative Precipitation Estimates (QPE) are indirect estimates of precipitation rates and as such are often prone to errors, warranting a need for characterizing the associated uncertainties before being used in application-specific studies. Moreover, multiple satellite-based QPE products are offered through different agencies, each with their own specifications, formats and requirements, posing a challenge to understanding the products uncertainties. This manuscript presents a standardized validation system named NPreciSe - NOAA Satellite-based Precipitation Validation System, which assesses the performance of satellite-based precipitation products in near real-time over the continental United States. NPreciSe is coupled with a user-interactive web platform and built using an open-source software, Python. It is structured to help (1) the end-users determine the best satellite QPE for their specific application, and (2) the algorithm developers identify systematic biases in QPE retrievals. This manuscript presents the capabilities of the NPreciSe, discusses the methodology adopted in developing the standardized validation system, and introduces the web portal.

Community-Supported Shared Infrastructure in Support of Speech Accessibility.

The Speech Accessibility Project (SAP) intends to facilitate research and development in automatic speech recognition (ASR) and other machine learning tasks for people with speech disabilities. The purpose of this article is to introduce this project as a resource for researchers, including baseline analysis of the first released data package. The project aims to facilitate ASR research by collecting, curating, and distributing transcribed U.S. English speech from people with speech and/or language disabilities. Participants record speech from their place of residence by connecting their personal computer, cell phone, and assistive devices, if needed, to the SAP web portal. All samples are manually transcribed, and 30 per participant are annotated using differential diagnostic pattern dimensions. For purposes of ASR experiments, the participants have been randomly assigned to a training set, a development set for controlled testing of a trained ASR, and a test set to evaluate ASR error rate. The SAP 2023-10-05 Data Package contains the speech of 211 people with dysarthria as a correlate of Parkinson's disease, and the associated test set contains 42 additional speakers. A baseline ASR, with a word error rate of 3.4% for typical speakers, transcribes test speech with a word error rate of 36.3%. Fine-tuning reduces the word error rate to 23.7%. Preliminary findings suggest that a large corpus of dysarthric and dysphonic speech has the potential to significantly improve speech technology for people with disabilities. By providing these data to researchers, the SAP intends to significantly accelerate research into accessible speech technology. https://doi.org/10.23641/asha.27078079.

Proteogenomic analysis integrated with electronic health records data reveals disease-associated variants in Black Americans.

Most genome wide association studies (GWAS) of plasma proteomics have focused on White individuals of European ancestry, limiting biological insight from other ancestry enriched protein quantitative loci (pQTL). We conducted a discovery GWAS of ~3,000 plasma proteins measured by the antibody based Olink platform in 1,054 Black adults from the Jackson Heart Study (JHS), and validated our findings in the Multi-Ethnic Study of Atherosclerosis (MESA). The genetic architecture of identified pQTLs were further explored through fine mapping and admixture association analysis. Finally, using our pQTL findings, we performed a phenome wide association study (PheWAS) across two large multi-ethnic electronic health record (EHR) systems in All of Us and BioMe. We identified 1002 pQTLs for 925 proteins. Fine mapping and admixture analyses suggested allelic heterogeneity of the plasma proteome across diverse populations. We identified associations for variants enriched in African ancestry, many in diseases that lack precise biomarkers, including cis-pQTLs for Cathepsin L (CTSL) and Siglec-9 that were linked with sarcoidosis and non-Hodgkin's lymphoma, respectively. We found concordant associations across clinical diagnoses and laboratory measurements, elucidating disease pathways, including a cis-pQTL associated with circulating CD58, white blood cell count, and multiple sclerosis. Our findings emphasize the value of leveraging diverse populations to enhance biological insights from proteomics GWAS, and we have made this resource readily available as an interactive web portal.

To Study the Use of Entropy and the Preprocessing Step in Analyzing Web Users' Behavior and Improving Web Mining

The study of entropy's application to online use mining is the main goal of the work. By using the Reference Length approach, entropy provides an additional option for figuring out the ratio of auxiliary pages in the session identification. Two distinct online portals were used for the experiment. The first log file was downloaded via the web portal of a virtual learning environment course. The online gateway with anonymous access provided the second log file. When entropy and sitemap estimations of the ratio of auxiliary pages were compared, it was discovered that entropy could replace the sitemap estimate of the ratio of auxiliary pages with a full-valued substitute in the situation of sitemap abundance.

Patients’ and stakeholders’ experiences of a personalized self-management SUPport program (P-SUP) for patients with type 2 diabetes mellitus and/or coronary heart disease: a qualitative process evaluation

BackgroundChronic diseases such as type 2 diabetes mellitus and coronary heart disease cause medical, social, and economic burdens worldwide. Disease management programs in Germany mostly lack components to improve patients’ self-management and health-promoting lifestyles despite clear guideline recommendations. Therefore, a Personalized Self-Management Support Program (P-SUP) was developed, which includes: (1) peer support groups; (2) telephone coaching; (3) feedback reports and, (4) a web portal. This study aims to explore patients’ and implementing stakeholders’ experiences in the implementation of P-SUP to identify barriers and facilitators to the implementation of the intervention.MethodsA qualitative study was conducted using face-to-face focus group interviews with participating patients and telephone-based one-to-one expert interviews with implementing stakeholders, involved in the delivery of the intervention. The transcribed interview reports were analyzed using qualitative content analysis, and the contents were categorized according to Donabedian’s Structure-Process-Outcome framework.ResultsA total of six themes among patients (N = 35) and five themes among implementing stakeholders (N = 32) represent the experiences. The patient themes were: (1) technical conditions, (2) indoor facilities, (3) group composition, (4) acceptance of digital components, (5) supervision and feedback and (6) impact on lifestyle behavior. The themes among the implementing stakeholders were: (1) multiprofessional approach, (2) human resources, (3) patient acceptance, (4) supervision and feedback and (5) impact on lifestyle behavior.ConclusionsMultiprofessional interventions such as P-SUP appear to be valuable for patients and implementing stakeholders. Although infrastructural barriers made the implementation of peer support and digital patient education difficult, patients rated the exchange with peers and experts on health-related topics positively. The lack of supervision and feedback during the course of the intervention might be compensated by regular telephone coaching. The findings from this study can be used in future studies to guide researchers and implementing stakeholders and to improve the feasibility and effectiveness of complex interventions in different contexts.Trial registrationThe P-SUP study was registered in the German Clinical Trials Register (DRKS) on 16/07/2020 under the registration number DRKS00020592.

Integrating deep learning techniques for effective river water quality monitoring and management

Effective river water quality monitoring is essential for sustainable water resource management. In this study, we established a comprehensive monitoring system along the Kaveri River, capturing real-time data on multiple critical water quality parameters. The parameters collected encompassed water contamination levels, turbidity, pH measurements, temperature, and total dissolved solids (TDS), providing a holistic view of river water quality. The monitoring system was meticulously set up with strategically positioned sensors at various river locations, ensuring data collection at regular 5-min intervals. This data was then transmitted to a cloud-based web portal, facilitating storage and analysis. To assess water quality, we introduced a novel hybrid approach, combining Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks. The proposed CNN-LSTM model achieved a validation accuracy of 98.40%, surpassing the performance of other state-of-the-art methods. Notably, the practical application of this system includes real-time alerts, promptly notifying stakeholders when water quality parameters exceed predefined thresholds. This feature aids in making informed decisions in water resource management. The study's contributions lie in its effective river water quality monitoring system, which encompassing various parameters, and its potential to positively impact environmental conservation efforts by providing a valuable tool for informed decision-making and timely interventions.

Artificial intelligence for assessing the planets' positions as a precursor to earthquake events

Questions about interconnection possibilities between planets’ positions and seismic events on the earth have emerged recently in TV channels, social media, etc. In this study, an Artificial Neural Network (ANN) and Random Forest Regression (RFR) are used to predict the number of earthquakes that can occur on Earth, depending on the Earth’s position relative to other planets and solar positions. Our new integration dataset contains 9809 observations and nine features firstly from the global earthquake archive, which is an authoritative layer by Esri, and secondly from the accurate data web portal “theskylive.com.”.The results obtained from RFR and ANN prove the partial influence of planets positions on sesimic activity on the earth. In other words, quantitatively through the ANN that gets an accuracy of 68.27 %, MAE of 5.36, MSE of 52.78, RMSE of 7.26, R-Squared of 0.65, and also through the RFR that gets an accuracy of 65.06 %, MAE of 5.60, MSE of 58.21, RMSE of 7.63, R-Squared of 0.67, prove the partial influence on one hand. Qualitatively through the curve of the training phase of the ANN, which is a decreasing and convex function, reinforces the aforementioned proof on the other hand. For these reasons, it can be deduced that there is a possible connection between tectonic stress triggers and the positions of the planets in the solar system. Our dataset was uploaded to the github(https://github.com/mouddentarik/Earthquake01.) as well as the code will be publicly available at the github(https://github.com/mouddentarik/PythonCode_Earthquakes-.) to share our results.

Assessing the capabilities of the "Jobs Russia" web portal in solving the problems of analyzing green employment in the labor market

Subject. This article examines the demand for professions related to the green economy. Objectives. The article aims to assess the various tools offered for searching in electronic systems for information about job vacancies involving participation in solving environmental problems. Methods. For the study, I used a comparative analysis. Results. The article finds that the electronic portal Jobs Russia is ahead of competitors in terms of the number and variety of additional services for finding environmentally oriented companies. Conclusions. An important advantage of the Jobs Russia portal is the reliability of the information posted, confirmed by the competent authorities.

Representation in the UK MS Register: A Comparison of Nationwide Ethnicity and Register Data

BackgroundThe United Kingdom MS Register (UKMSR) collects longitudinal data on people with Multiple Sclerosis (pwMS) from clinical sources and as Patient Reported Outcomes (PROs) via a web portal. People from non-white ethnicities are often poorly represented in research and clinical trials; the UKMSR aims to be representative of people with MS (pwMS) across the UK. AimTo compare ethnic representation in the UKMSR to data from the Office for National Statistics (ONS). MethodEthnicity data was taken from the UKMSR as a ‘snapshot’ in 2024. Comparative data from ONS in England and Wales was gathered. Due to low numbers in the UKMSR of some ethnicities and areas, participants were grouped into ‘White’ and ‘All Other Ethnicities’. Using Chi-Sq tests, we compared ethnicities across ten regions of ONS 2021 Census data. ResultsTen regions were compared (nine in England, Wales as one). Analysis of both web-reported (n = 18648) and clinical (n = 5456) ethnicity found UKMSR diversity to be significantly lower than national statistics (p < .05), with the exception of the clinical Register in Wales (numbers were insufficient to test) and clinical Register in the English West Midlands. The clinical Register was more representative in 7/10 regions than the web Register. DiscussionThe clinical Register, via NHS hospital sites reaches a more diverse audience than the patient-reported web Register; further work is needed in reaching a broader audience of pwMS, as well as harmonising discrepancies between the clinical and web Register populations.

Pillar 3: The impact of language complexity on the preferences of commercial bank website users

This research explores the impact of document complexity and readability on user preferences for disclosure information on commercial bank web portals, with a focus on Pillar 3 disclosures. The study investigates the usage patterns of disclosed information by stakeholders. Through an analysis of web portal access variables and document complexity and readability measures, the study identifies correlations between text complexity/readability and user preferences. The experiment used traditional readability measures like the Gunning Fog Index and Flesch Reading Ease but also focused on less-used metrics such as LIX, various text characteristics, and part-of-speech metrics. The findings reveal that while stakeholders show interest in financial documents despite their complexity, preferences in using these documents vary based on document type and readability. Notably, documents with higher complexity tend to attract more attention, suggesting potential challenges in accessibility and comprehension. The paper highlights the importance of presenting disclosure information in a manner that enhances readability and accessibility to better engage stakeholders. Additionally, the research introduces user preference indicators aligned with web portal access metrics, providing insights into stakeholders’ behavior. The research followed up on previous findings of extremely low interest in Pillar 3 information from commercial bank stakeholders. The results showed that stakeholders are more interested in less demanding and more readable texts such as annual reports, and as Pillar 3 documents are more complex and harder to read, they are less interested in them. The research concludes that stakeholders’ increasing interest in this information requires finding approaches to presenting it in less complicated and more readable ways.