Availability Of Software Research Articles

COMPUTED TOMOGRAPHIC ANGIOGRAPHY DATA SET CONTAINING ABDOMINAL AORTIC SEGMENTATION

BACKGROUND: Artificial Intelligence (AI) is widely actively in radiology. The effectiveness of AI algorithms essentially depends on the availability of relevant and representative training and test datasets. Currently, such datasets are highly demanded in open access, particularly CT angiographic (CTA) studies of the abdominal aorta containing not only pathology classification but also vessel segmentation. The disadvantages of existing solutions include small sample volume, narrow specialization, and disparate data preparation methodology. AIM – Design of a CTA dataset containing abdominal aortic segmentation for cases of normal, dilatation, thrombosis, and calcinosis. METHODS: In accordance with the methodology of AI-algorithms testing, the terms of reference for datasets preparation were developed, the necessary sample volume was calculated and approval of the independent ethical committee was obtained. Previously designed original algorithm of semi-automatic segmentation of abdominal aorta on CTA-studies using open access software Slicer 3D was used. Inclusion criteria: CTA studies, or abdominal CT studies with contrast enhancement; presence of arterial phase of the scan; slice thickness not more than 3 mm. Exclusion criteria: presence of any foreign objects in the aortic lumen, aortic dissection. The algorithm was tested on patient data obtained from the Unified Radiologic Information System. Expert evaluation of the compliance of the obtained results with the formed requirements, as well as the assessment of time costs when using the developed segmentation algorithm was carried out. RESULTS: The calculated sample size was 100 CTA studies with a slice thickness ≤ 1.2 mm. Population data: the number of unique patients was 100, the proportion of female patients was 51%; the median age was 62 years ranged from 18 to 84 years. The proportion of pathologic studies was 61%, of which (including combined pathology): 60 cases contained calcification, both by 18 cases with aortic dilatation and thrombosed lumen. Different non-overlapping masks were used for each object. The dataset is presented in the public domain. The average processing time is 0.8 hours per 100 CT-images. CONCLUSION: The public dataset containing 100 CTA studies of segmented abdominal aorta for normal, dilated, thrombotic and calcified cases was created. Results are valuable for AI-algorithms design and anthropomorphic 3D-modeling.

An AI-Driven Approach to Automatic Code Analysis and Summarization for Enhanced Software Understanding

- The AI-Driven Code Analyzer is an innovative tool designed to address the challenges developers, students, and educators face in understanding complex code. With programming becoming an integral part of various industries, the need for accessible tools that simplify code comprehension has never been greater. This tool allows users to input code and receive detailed, step-by-step explanations of its functionality, helping to demystify programming logic and enhance understanding. Whether it’s a beginner struggling with foundational concepts or an experienced programmer dealing with an unfamiliar codebase, the AI-Driven Code Analyzer serves as a valuable resource for improving productivity and learning efficiency. At the heart of this tool lies its integration with the Gemini API, a sophisticated backend system that processes inputted code and generates human-readable explanations. This integration ensures a seamless and efficient user experience, providing accurate and insightful breakdowns of even the most complex algorithms. The modular design of the platform allows it to handle diverse programming languages and concepts, making it a versatile solution for various user needs. Complementing its technical prowess is a user-friendly interface that simplifies interaction, enabling users to focus solely on understanding the code rather than navigating the tool itself. The applications of the AI-Driven Code Analyzer extend far beyond individual use. In educational settings, it can be leveraged as a teaching aid, helping students grasp difficult programming concepts through real-world examples. In professional environments, it can assist developers in debugging, code reviews, and understanding legacy systems, significantly reducing time spent on manual analysis. By streamlining the process of code explanation, this tool not only fosters a deeper understanding of programming but also addresses the growing demand for accessible and intelligent software solutions in an increasingly tech-driven world. Key Words: Code Analysis, Code Summarization, Code Comprehension, Human-Readable Explanations, Natural Language Processing (NLP), Programming Logic, Collaborative Development, Productivity Enhancement, Educational Applications, System Architecture, Learning Efficiency

Denoising low-field MR images with a deep learning algorithm based on simulated data from easily accessible open-source software

In this study, we introduce a denoising method aimed at improving the contrast ratio in low-field MRI (LFMRI) using an advanced 3D deep convolutional residual network model. Our approach employs synthetic brain imaging datasets that closely mimic the contrast and noise characteristics of LFMRI scans, addressing the limitation of available in-vivo LFMRI datasets for training deep learning models. In the simulation data, the Relative Contrast Ratio (RCR) increased, and similar improvements were observed in the in-vivo data across different imaging conditions. Comparative evaluations demonstrate that our model performs better than the widely used non-deep learning method, BM4D, in enhancing RCR and maintaining high spatial frequency components in in-vivo data.

Genomic analysis made easy (Game V1): An automated software for plant genome assembly and annotation from illumina sequencing

The recent development and affordable accessibility of the next-generation high-throughput sequencing technology and artificial intelligence have propelled more researchers to get involved in genomics and to the threshold of a new beginning in understanding, utilizing, and conserving the biodiversity. However, one of the biggest challenges for the analysis of high-throughput sequencing reads is the whole genome assembly and annotation. Availability of user-friendly free software that manages all types of sequenced DNA to be used in a local environment is lacking. Hence, the Genomic Analysis Made Easy (GAME v1) software has been developed using Python to provide a user-friendly, fast, free, and automated GUI-based solution for plant genome assembly and annotation. The software performs on a Linux-based operating environment with a minimum of 16 GB RAM and 100 GB disc space, fully automated from the installation to execution, thus requiring minimal bioinformatics expertise for the execution. The GAME v1 generates detailed quality reports of the raw reads, GenomeScope heterozygosity report, QUAST contigs and scaffolds results, BUSCO summary plot, COG functional annotation chart, GO chart, NCBI and UniProt annotations, KEGG pathway distribution graph, and RepeatMasker plots. The nuclear genome of Chenopodium pallidicaule retrieved from NCBI was assembled and annotated successfully using GAME v1, revealing preliminary genome size estimate of around 419.54 Mb based on GenomeScope analysis prior to assembly. The final assembly, as assessed by QUAST, unveiled a total length of 285.85 Mb (0.29 Gb) containing 23,806 genes. This automated solution will facilitate plant genomics research by revealing the underlying insights of draft nuclear genomes. The software is available at https://arraygen.com/game Bangladesh J. Plant Taxon. 31(2): 225-238, 2024 (December)

A Virtual Laboratory on Recursive Least-Squares Estimation for Undergraduate Courses

This paper describes the creation of an educational resource focused on identifying dynamic systems, with a particular emphasis on parametric estimation, for undergraduate courses. This virtual laboratory is easily reproducible with accessible materials and software, allowing easy system modification. The Recursive Least-Squares (RLS) with a forgetting factoris a solid and efficient method that enables students to experiment with parameters and better understand the subject matter. We show three experiments to provide an exhaustive RLScomprehension. Finally, we envision the virtual laboratory as useful for educational purposes and other applications in automatic control.

Streamlining segmentation of cryo-electron tomography datasets with Ais.

Segmentation is a critical data processing step in many applications of cryo-electron tomography. Downstream analyses, such as subtomogram averaging, are often based on segmentation results, and are thus critically dependent on the availability of open-source software for accurate as well as high-throughput tomogram segmentation. There is a need for more user-friendly, flexible, and comprehensive segmentation software that offers an insightful overview of all steps involved in preparing automated segmentations. Here, we present Ais: a dedicated tomogram segmentation package that is geared towards both high performance and accessibility, available on GitHub. In this report, we demonstrate two common processing steps that can be greatly accelerated with Ais: particle picking for subtomogram averaging, and generating many-feature segmentations of cellular architecture based on in situ tomography data. Featuring comprehensive annotation, segmentation, and rendering functionality, as well as an open repository for trained models at aiscryoet.org, we hope that Ais will help accelerate research and dissemination of data involving cryoET.

Grades and Learning Styles: New Software for Analyzing Correlations in a Longitudinal Study Across Different Branches of Knowledge and Years

Knowing how students engage with their materials helps educators design methodologies to enhance the learning process. To help teachers in determining students’ average learning style profiles and analyzing potential connections between learning styles and academic performance, new freely accessible software, integrated with Moodle, has been developed in this work. A comprehensive case study involving one thousand students across various subjects and degrees from several branches of knowledge in different years has been conducted using this tool. The analysis reveals low participation in the survey, with only 6 out of 19 courses having a participation rate that surpasses 50%), where respondents generally achieved higher grades compared to non-participants (on a grade scale from 0 to 10, participants scored on average one point higher than those who did not complete the questionnaire), suggesting that they were more motivated. Higher-level courses have higher participation rates, but overall participation has declined over the years. Despite slight differences in learning styles between courses, the general pattern remains similar. The correlation between learning styles and grades, analyzed through linear regression, shows that this model performs better when both learning styles and grade marks are distributed by score rather than by level.

Assessing Geometric and Radiometric Accuracy of DJI P4 MS Imagery Processed with Agisoft Metashape for Shrubland Mapping

The rise in inexpensive Unmanned Aerial Systems (UAS) and accessible processing software offers several advantages in forest ecosystem monitoring and management. The increase in usability of such tools can result in the simplification of workflows, potentially impacting the quality of the generated data. This study offers insights into the precision and reliability of the DJI Phantom 4 Multispectral (P4MS) UAS for mapping shrublands using the Agisoft Metashape (AM) for image processing. Geometric accuracy was evaluated using ground control points (GCPs) and different configurations. The best configuration was then used to produce orthomosaics. Subsequently, the orthomosaics were transformed into reflectance orthomosaics using various radiometric correction methods. These methods were further assessed using reference panels. The method producing the most accurate reflectance values was then chosen to create the final reflectance and Normalised Difference Vegetation Index (NDVI) maps. Radiometric accuracy was assessed through a multi-step process. Initially, precision was measured by comparing reflectance orthomosaics and NDVI derived from images taken on consecutive days. Finally, reliability was evaluated by comparing the NDVI with NDVI from a reference camera, the MicaSense Altum AL0, produced with images acquired on the same days. The results demonstrate that the P4MS is both precise and reliable for shrubland mapping. Reflectance maps and NDVI generated in AM exhibit acceptable geometric and radiometric accuracy when geometric calibration is performed with at least one GCP and radiometric calibration utilises images of reflectance panels captured at flight height, without relying on incident light sensor (ILS) data.

Testing the web accessibility of hotel and restaurant complexes

Web accessibility is a necessity enabling people with disabilities to engage in a digital realm regardless of their physical, cognitive, or sensory capabilities. Nowadays, web accessibility assumes significant importance across various domains, including governmental aid, healthcare services, education, cultural activities, sports, and the service sector. Nevertheless, developers and testers often face uncertainty about actions to be taken when addressing accessibility concerns. This article delves into website accessibility matters, outlines key principles for developing accessible web-oriented software, introduces an accessibility testing checklist for web content, conducts both manual and automated testing of the websites of hotel and restaurant complexes, and offers recommendations for enhancing web accessibility levels.

Electromagnetic Simulation of a Negative Refractive Index Lens Antenna

Abstract Lens antennas are well known to achieve good multi-beam radiation patterns. When lens material is formed by a negative refractive index material, multi-beam radiation patterns are improved because the lens thickness is reduced. An electromagnetic simulator is convenient for obtaining radiation characteristics. However, the suitable electromagnetic simulator for a negative refractive index lens simulation is limited. Only a few electronic simulators can simulate a negative refractive index value. In this paper, the availability of HFSS software is examined. Calculation methods such as structure forming and calculation parameter setting are explained. Calculated results of electrical near field distribution, aperture distribution of amplitude and phase and radiation pattern are shown. By comparing calculated results with theoretical values, accuracies of calculated results are ensured.

ANSYS Modelling of Piezoelectric Smart Beam using Ritz Vector Method and Sub-structuring Analysis

Abstract Finite element analysis (FEA) is an important tool for smart structure modelling, particularly in the context of piezoelectric beams. A key challenge in such modelling is the derivation of electro-elastic coupling, which explains how these structures respond mechanically to electrical loading. Traditional methods rely on intricate shape functions that encompass both electrical and mechanical degrees of freedom, rendering the process complex. In this study, an innovative approach—the so-called Ritz vector method— which facilitates modelling of the system based on loading effect is implemented to simplify electro-elastic coupling calculations. The method previously applied in MSC Nastran with a thermal analogy system and validated experimentally is now implemented in the widely accessible ANSYS software. By harnessing ANSYS’ robust piezoelectric capabilities and sub-structuring analysis for matrix extraction, the essential piezoelectric coupling and dielectric matrices are derived for piezoelectric stack and patch actuator driven cantilevered beams. Subsequently, state space models of these smart structures are constructed using MATLAB and results are compared with ANSYS FEA static and dynamic response. Active Disturbance Rejection Control (ADRC) was implemented on the modelled beams and results show significant suppression of free vibration due to impulse excitation of the tip. This work portrays the potential of the Ritz vector method, a powerful yet underexplored tool that simplifies electro-elastic coupling calculations for piezoelectric smart structures.

Development and evaluation of a low-cost database solution for the Community Paramedicine at Clinic (CP@clinic) database.

The Community Paramedicine at Clinic (CP@clinic) program is a community program that utilizes community paramedics to support older adults in assessing their risk factors, managing their chronic conditions, and linking them to community resources. The aim of this project is to design a low-cost, portable, secure, user-friendly database for CP@clinic sessions and pilot test the database with paramedics and older adult volunteers. The CP@clinic program database using the Microsoft Access software was first developed through consultation with the CP@clinic research team. Next, the database was pilot tested with two sets of older adults and one set of paramedics to assess user experience. Volunteers completed a survey regarding their perceptions of the level of difficulty when using the database. A computer-based database was the best option as it provided flexibility while reducing costs. The final database should perform calculations and summarize risk assessment data, provide recommended resources, generate automated reports, capture changes in medical and medication history, and ensure that the sensitive information is secure. During pilot testing, the older adult participants and the paramedics indicated that the database was easy to use. This low-cost, user-friendly and secure database captures initial and follow-up data, incorporates algorithms that guide the paramedics, and calculates risk factor scores for the participants. This solution to a healthcare database is translatable to other health research studies in which ongoing patient data is collected electronically and longitudinally.

Vulnerability of Wi-Fi wireless network to signal interference

Wi-Fi networks are often susceptible to signal interference that can disrupt services, intercept sensitive data, and allow unauthorized access. Exploiting this vulnerability, attackers can launch Intentional Electromagnetic Interference (IEMI) attacks or protocol-based attacks. IEMI attacks include, but are not limited to, jamming, which involves the introduction of interference signals in the frequency band used by a given Wi-Fi network, thus disrupting its proper operation. The article presents research on different types of IEMI attacks, aimed at illustrating this type of threat to video transmission from Wi-Fi cameras and discusses methods of protection against this type of attack. The paper examines the methods of jamming the wireless network band, which are used on the distribution methods and the Sweeping Jammer methods that cyclically disrupt all available devices. Based on experiments, it has been confirmed that SOHO devices are highly susceptible to this type of simple attacks and implementing a method to minimize the effects of jamming yields poor results. The simplicity of this type of attack and the high availability of software and hardware tools on the market make the threat highly popular and still dangerous.

An Easily Accessible, Semi-Automated Approach to Creating Personalized Normative Feedback and Risk Feedback Graphics.

Personalized normative feedback interventions show efficacy in reducing health risk behaviors (e.g., alcohol use, sexual aggression). However, complex personalized normative feedback interventions may require manual methods of inputting participant data into graphics, which introduces error, and automated approaches require substantial technical costs and funding and may limit the types of feedback that can be provided. To make personalized normative feedback more accessible, we outline a method of using easily accessible software programs including IBM Statistical Package for the Social Sciences (SPSS), Microsoft Excel, and Microsoft PowerPoint, to create and display complex personalized normative feedback graphics. We also describe methods through which personalized normative feedback graphics can be created within a larger preventive intervention for alcohol and sexual assault in college men. We first provide step-by-step instructions for collecting data and then creating semi-automated syntax files within SPSS and Excel to merge participant data into complex personalized normative feedback graphics in Excel. To do so, we append annotated syntax in text and in supplemental material. Next, we outline the process of creating risk feedback graphics, whereby individual items or exact wording of items are displayed back to the participant. Finally, we provide guidance regarding the process of translating graphics from Excel for viewing via PowerPoint without having to manually update PowerPoint slides for each presentation. Via the described syntax and graphic generation, researchers are then able to create semi-automated personalized normative feedback and risk feedback graphics. This tutorial may help in increasing the dissemination of complex personalized normative feedback interventions.

The Role of ICT Resources Available to Students Influencing their Academic Performance: A Comparative Study between Private and Public Schools in Sindh-Pakistan

In today's digital age, Information and Communication Technology (ICT) resources play a crucial role in shaping students' academic performance. This comparative study aims to analyze the impact of ICT resources on students' academic performance in both private and public schools in Larkana Sindh, Pakistan. The study utilizes a quantitative methodology, collecting data through questionnaires administered to 100 students using stratified random sampling. This study used Smart PLS 4.0 for Data Analysis. The questionnaires assess the availability and utilization of ICT resources, including computers, internet connectivity, and educational software. Additionally, student records provide insight into academic achievements. The research sheds light on disparities in access to and utilization of ICT resources between private and public institutions. It underscores how resources in private schools contribute to an enriched learning experience and improved academic performance. Conversely, public educational institutions in Sindh often encounter challenges in providing adequate ICT resources, which can negatively impact academic achievement. By highlighting these discrepancies, the study emphasizes the importance of addressing inequities in ICT resource allocation. Policymakers and educators must work to ensure that all students, regardless of school type, have equal access to ICT resources. Bridging this gap is crucial for enhancing students' academic success and preparing them for the demands of the digital era.

Barriers to Colonoscopy Quality Measurement in Rural Wisconsin.

Patients in rural areas have reduced colonoscopy access, which is critical for colorectal cancer prevention. General surgeons perform most colonoscopies in rural areas. The Surgical Collaborative of Wisconsin's Rural Task Force identified colonoscopy as a high priority initiative due to high volume and lack of quality measure access, both necessary for assessing and improving performance. Assess the capacity for colonoscopy quality measurement and improvement in rural Wisconsin hospitals. In October 2019-January 2020, the Surgical Collaborative of Wisconsin, Rural Wisconsin Health Cooperative, and Wisconsin Collaborative for Healthcare Quality collaborated to design/distribute a survey to 44 Rural Wisconsin Health Cooperative hospitals (n = 25 completed, response rate 57%). Descriptive statistics summarized survey items. Surgeons in each of six rural hospitals participated in stakeholder interviews. Rural Wisconsin Health Cooperative hospitals. Colonoscopy providers, procedure volume/capacity, informatics and quality measurement infrastructure, barriers to quality measurement and improvement. Most colonoscopy providers in rural hospitals were surgeons (66.3%) followed by family/internal medicine (20.0%) and gastroenterologists (13.8%). Average hospital volume/week was 19.9 colonoscopies (SD = 13.4). Hospitals reported operating at ~75% capacity. Withdrawal time was the most tracked measure (44.0%), followed by adenoma detection (36.0%), and cecal intubation (28.0%) rates. Approximately one-third of hospitals (36.0%) utilized procedure reporting software. Most hospitals (80.0%) did not have access to onsite pathology. Surgeons reported barriers to quality measurement/improvement, including insufficient resources for electronic medical record-based reporting and the need for targeted educational opportunities that do not require travel. Single state; may not represent experience of all rural hospitals. The lack of access to colonoscopy quality measures suggests the opportunity to develop a flexible approach that considers reporting software availability and electronic medical record differences. Improving access to measures and education/training opportunities may improve availability of high-quality colonoscopy for patients in rural Wisconsin. See Video Abstract.

Reviewability and supportability: New complementary principles to empower research software practices

In today's scientific landscape, research software has evolved from being a supportive tool to becoming a fundamental driver of discovery, particularly in life sciences. Beyond its roots in software engineering, research software now plays a crucial role in facilitating efficient data analysis and enabling the exploration of complex natural phenomena. The advancements in simulations and modeling through research software have significantly accelerated the pace of scientific research while reducing associated costs. This growing reliance underscores the importance of software in ensuring reproducibility – a cornerstone of scientific rigor and trustworthiness. Although verifying reproducibility presents challenges, well-developed and openly accessible research software enhances transparency and aids in the early detection of errors. Although verifying reproducibility can be challenging, well-developed and accessible research software improves transparency and facilitates error detection. This mini-review examines the characteristics of research software and summarizes the key events that have shaped its development, alongside changes in requirements and guidelines. Moreover, we propose two additional principles – reviewability and supportability – complementing the widely accepted FAIR principles (Findability, Accessibility, Interoperability, and Reusability). These new principles aim to improve the efficiency and effectiveness of software evaluation during the peer review process. Through this review, we aim to assist scientists, especially those without extensive software development expertise, in understanding best practices for developing research software and the underlying motivations driving these practices.

Deepfakes and Higher Education: A Research Agenda and Scoping Review of Synthetic Media

The availability of software which can produce convincing, yet synthetic media poses both threats and benefits to tertiary education globally. While other forms of synthetic media exist, this study focuses on deepfakes: advanced Generative AI (GenAI) imitations of real people’s likeness or voice. This conceptual paper assesses the current literature on deepfakes across multiple disciplines by conducting an initial scoping review of 182 peer-reviewed publications. The review reveals three major trends: detection methods, malicious applications, and potential benefits, although no specific studies on deepfakes in the tertiary educational context were found. Following a discussion of these trends, we apply the findings to postulate the major risks and potential mitigation strategies of deepfake technologies in higher education, as well as potential beneficial uses to aid the teaching and learning of both deepfakes and synthetic media. This culminates in the proposal of a research agenda to build a comprehensive, cross-cultural approach to investigate deepfakes in higher education.

Creation of Stem-Centers Within Experimental Activities (Best Practices)

The article is devoted to the analysis of the organization of the creation of STEM centers as innovative educational environments aimed at the formation and development of STEM competencies and creative activity of education seekers, the development of innovative models of education and the professional improvement of pedagogical workers in the STEM direction. It was found that the organization of the creation of STEM centers requires the provision of organizational, scientific-methodical, material and technical conditions and personnel support. It was determined that the organizational conditions include the development and adoption of the necessary regulatory documents that determine the principles of STEM-centers' activities. The scientific and methodological conditions provide for the development and adaptation of educational programs and educational and methodological materials, lesson plans and manuals focused on the integration of STEM disciplines. Material and technical conditions provide for the availability of modern equipment, computer classes, laboratories, workshops, software and other technical means and resources. Staffing requires the involvement of qualified teachers, trainers, instructors, methodologists, specialists in STEM disciplines. The study is aimed at studying the best practices of creating STEM centers within the framework of the implementation of an innovative educational project at the all-Ukrainian level on the topic "Organizational and scientific-methodical conditions for the creation of STEM centers" in 2022-2027. The author of the article provided practical recommendations for organizing the creation of STEM centers, taking into account the results of the survey of basic educational institutions of the innovative educational project and the needs of modern education.

The State of Digital Accessibility

If you are new to digital accessibility, and even if you are not, it can be difficult to stay abreast of the big picture, and the tech industry moves fast. So, we asked a team of experts to bring us up to speed. Not only do they have day jobs that involve digital accessibility, but they also have lived experience of disability. We posed the following questions to them: What's the state of accessibility? Key challenges? Why do we need accessible software? How can we make the case for accessibility? Who's leading the way? Where do we go from here?