Availability Of Software Research Articles

Mixed reality simulation training in the assessment and management of acutely unwell patients in undergraduate medical education: a pilot study

Background: Development of the undergraduate simulation experience is needed to continue developing aspiring clinicians’ ability to assess and manage unwell patients. However, its heavy resource demand and ‘Generation Z’s’ desire for technologically enhanced learning means novel simulation modalities must now be considered. Mixed reality (MR) provides a platform to deliver such simulation; however, it is yet to be studied in this context. We conducted an observational cohort study with the aim to assess ift MR simulation improves students’ perceived ability to assess and manage unwell patients. Methods: We recruited 32 undergraduate medical students and asked them to rate their ability to assess and manage acutely unwell patients, out of 10. An MR simulation was then delivered using the Microsoft HoloLens and HoloScenario software produced by GigXR. Students then rated their assessment and management ability again, alongside their experience of the system and its usability. Data analysis used paired t-tests to assess for significant differences. Results: By attending the simulation, students showed a significant improvement in perceived ability to assess (p < 0.001) and manage (p < 0.001) acutely unwell patients. Mean assessment scores improved by 1.09/10 (95% confidence interval [CI 0.67, 1.52]) with 89% of students feeling more confident. Mean management scores improved by 1.63/10 (95% CI [1.15, 2.10]) with 84% of students reporting increased confidence levels. When considering usability, 69% of students did not find the MR system easy to use, with 75% of students having technical issues and 38% experiencing side effects. Overall, 88% of students believed the experience was beneficial to their learning. Conclusions: MR shows promise in its ability to deliver simulation training and improve students’ perceived ability to assess and manage unwell patients. Advances in software availability and content are required for integration into undergraduate medical curricula. Further research is required to assess if these results are replicated objectively.

A fast open data reduction workflow for the electron microprobe flank method to determine Fe3+/ΣFe contents in minerals

Abstract Knowing the Fe3+/ΣFe ratio in minerals is important to understand the formation and evolution of minerals and their host rocks. Variable Fe3+/ΣFe in, e.g., garnet is accompanied by a change of their characteristic FeLα and FeLβ X-ray emission lines, which can be quantified with electron microprobe measurements using the flank method. Previously, the required data reduction process to determine the Fe3+/ΣFe was complex. Here, we present a new data reduction tool taking garnet data as an example. This new Flank Reduction app is a freely available, graphical user interface (GUI)-driven, web-based application to reduce flank method data quickly and easily. The entire data reduction process is achieved in minutes compared to hours or days, as it was before. Flank Reduction provides comprehensive insights into, e.g., the flank method standards employed, data obtained, and errors through a wide array of controls and visualization tools. Documentation with comprehensive information on the flank method, data reduction, as well as training material such as video tutorials or sample data sets, are available on a dedicated webpage. Flank Reduction emphasizes the high value of Findable, Accessible, Interoperable, Reproducible (FAIR) and open research software and demonstrates how current developments in coding and app implementation can facilitate the development of powerful and expandable research software.

Optimising the Energy and Resources of Hotel Buildings in Cameroon from a Zero-Carbon Perspective

This article explores the potential for Cameroonian hotel buildings to achieve optimal energy and resource use, contributing to a zero-carbon future. It examines the opportunities that lie in high-performing hotels to achieve the country's ambitious environmental objectives such as reducing its greenhouse gas emissions by 32% by 2035 compared with the reference scenario under the Paris Agreement. Then, the article delves into the existing landscape of green building labels and certifications while focusing on those related on hotels specifically like the Green Key. It acknowledges the various hotels categories present in the country and how their specific characteristics influence resource demands. Additionally, it presents the regulations governing the construction and conversion of hotel establishments. Furthermore, the article discusses strategies for optimising the performance of building resources within the tropical context. These involve improving the insulation of the building envelope, the efficiency of systems and the use of renewable energy sources. The article highlights the importance of the prescriptive approach for assessing and the energy performance approach for optimising building performance, using the accessible EDGE energy simulation software. Those approaches are defined in the Ivorian Inter-ministerial Order No. 134/MPEER/MCLU of 18 November 2020, given that Cameroon and Côte d'Ivoire have some similar climate zones. To achieve the EDGE Zero Carbon level, it is essential to demonstrate minimum savings of 40% of energy, 20% of water and 20% of grey energy in materials, and 100% of energy- related emissions neutralised either by renewable energies or by carbon offsets. Finally, the concept of green financing is introduced, examining its potential to facilitate

Analisis Sistem Informasi Manajemen Berbasis Teknologi di MTS YPAK Cigugur

The purpose of this study was to analyze the management information system used in MTS YPAK Cigugur. The method applied in this study is qualitative descriptive analysis. Data collection techniques were carried out by interviewing the operator staff of MTS YPAK Cigugur. In addition, the researcher also conducted a literature study on a number of scientific journals related to the topic to be analyzed. The results of the study indicate that the management information system has been implemented well in MTS YPAK Cigugur. The management information system model used in MTS YPAK Cigugur is the education management information system or EMIS developed by the Ministry of Religion to assist Islamic educational institutions in managing data related to student data, educator and education data, facilities and infrastructure, and other institutional interest data. In its implementation, there are various aspects that influence it, including the procurement of adequate software such as computers and laptops, the availability of software for data processing and adequate networks to support the smooth running of the data processing process, and human resources as users who are capable and understand technology-based management information systems.

Unlocking inclusive education: A quality assessment of software design in applications for children with autism

Digital technologies are an essential resource for maximizing education opportunities, yet the COVID-19 pandemic has exposed learning inequities, particularly among underrepresented groups such as children with autism. In this study, we have evaluated the quality of a distinctive dataset of multiplatform software applications, encompassing both assistive and mainstream software, first-hand acquired from special education professionals and families of children with autism. Through a heuristic evaluation based on a system indicators, and an in-depth analysis, we aimed to (1) assess the quality and effectiveness of assistive technologies in supporting the education of children with autism; (2) determine the adaptability of mainstream applications to the unique educational needs of children with autism; and (3) explore the features and constraints of applications targeting children with ASD, categorized according to the needs they cover. The resulting quality ranking, organized by cognitive domains, provides insights into the engagement and effectiveness of applications supporting the learning of children with autism. Furthermore, the findings delineating the functionalities and limitations of these applications contribute to the identification of necessary software engineering best practices. These practices align with user-centered design principles and drive the development of accessible software, thereby fostering high-quality inclusive education for children with autism.

An Update on the iglu Software Package for Interpreting Continuous Glucose Monitoring Data.

Background: Continuous glucose monitors (CGMs) are increasingly used to provide detailed quantification of glycemic control and glucose variability. An open-source R package iglu has been developed to assist with automatic CGM metrics computation and data visualization, providing a comprehensive list of implemented CGM metrics. Motivated by the recent international consensus statement on CGM metrics and recommendations from recent reviews of available CGM software, we present an updated version of iglu with improved accessibility and expanded functionality. Methods: The functionality was expanded to include automated computation of hypo- and hyperglycemia episodes with corresponding visualizations, composite metrics of glycemic control (glycemia risk index and personal glycemic state), and glycemic metrics associated with postprandial excursions. The algorithm for mean amplitude of glycemic excursions has been updated for improved accuracy, and the corresponding visualization has been added. Automated hierarchical clustering capabilities have been added to facilitate statistical analysis. Accessibility was improved by providing support for the automatic processing of common data formats, expanding the graphical user interface, and providing mirrored functionality in Python. Results: The updated version of iglu has been released to the Comprehensive R Archive Network (CRAN) as version 4. The corresponding Python wrapper has been released to the Python Package Index (PyPI) as version 1. The new functionality has been demonstrated using CGM data from 19 subjects with prediabetes and type 2 diabetes. Conclusions: An updated version of iglu provides comprehensive and accessible software for analyses of CGM data that meets the needs of researchers with varying levels of programming experience. It is freely available on CRAN and on GitHub at https://github.com/irinagain/iglu.

Introducing DigiCAT: A digital tool to promote the principled use of counterfactual analysis for identifying potential active ingredients in mental health

Background Given the challenges and resources involved in mental health intervention development and evaluation, it is valuable to obtain early evidence on which intervention targets represent the most promising investments. Observational datasets provide a rich resource for exploring these types of questions; however, the lack of randomisation to treatments in these data means they are vulnerable to confounding issues. Counterfactual analysis refers to a family of techniques within the potential outcomes framework that can help address confounding. In doing so, they can help differentiate potential intervention targets that may reflect genuine active ingredients in mental health from those that are only associated with mental health outcomes due to their common dependence on ‘third variables’. However, counterfactual analysis is rarely used for this purpose and where it is used in health research it is often implemented in a suboptimal fashion. One key reason may be a lack of accessible tutorials and software that embeds best practices. Methods To help promote the principled use of counterfactual analysis we developed DigiCAT. DigiCAT is an open digital tool built in R and Shiny that implements a range of counterfactual analysis methods. It is accompanied by accessible tutorials. The tool has been designed to handle real data, with capabilities for missing data, non-binary treatment effects, and complex survey designs. Results The current article describes the development of DigiCAT, drawing on user and lived experience expert input and provides an overview of its features and examples of its uses. Conclusions Counterfactual analysis could help prioritise intervention targets by establishing which ones remain associated with mental health outcomes after accounting for potential confounding. Accessible digital tools supported by clear guidance may help promote the uptake and principled use of these techniques.

تأثير مولدات التوزيع (DG) على شبكة التوزيع الكهربائية الزهراء-ليبيا 30 كيلو فولت

Libyan electric distribution networks are suffering many problems of voltage limits violation, high system losses and low system performance. In this paper, a load flow study will be performed for a large power distribution of Alzahra area in Libya that include Alzahra power station. Considering distribution generation (DG) penetration method instead of conventional replanning methods, such as the expanding and adding methods that needs efforts and time. Alzahra 30KV electric system is taken as the case study including Alzahra power plant, different operation cases are considered includes the operation of the considering DG penetration during peak loads. The availability of high-performance software's such as NIPLAN helps in redesigning and replanning of electric power system for enhancing performance and solving system problems. The loss in the general phase was 8MW, and after increasing the loads by 8%, the loss ratio increased to 10MW. When adding the distribution generation in the right place, we note that the loss has been saved to approximately 4.5MW. KEYWORDS: DG, Penetration, Load flow, NIPLAN software, Voltage drop, Power system planning.

Unveiling the microbial realm with VEBA 2.0: a modular bioinformatics suite for end-to-end genome-resolved prokaryotic, (micro)eukaryoticand viral multi-omics from either short- or long-read sequencing.

The microbiome is a complex community of microorganisms, encompassing prokaryotic (bacterial and archaeal), eukaryotic, and viral entities. This microbial ensemble plays a pivotal role in influencing the health and productivity of diverse ecosystems while shaping the web of life. However, many software suites developed to study microbiomes analyze only the prokaryotic community and provide limited to no support for viruses and microeukaryotes. Previously, we introduced the Viral Eukaryotic Bacterial Archaeal (VEBA) open-source software suite to address this critical gap in microbiome research by extending genome-resolved analysis beyond prokaryotes to encompass the understudied realms of eukaryotes and viruses. Here we present VEBA 2.0 with key updates including a comprehensive clustered microeukaryotic protein database, rapid genome/protein-level clustering, bioprospecting, non-coding/organelle gene modeling, genome-resolved taxonomic/pathway profiling, long-read support, and containerization. We demonstrate VEBA's versatile application through the analysis of diverse case studies including marine water, Siberian permafrost, and white-tailed deer lung tissues with the latter showcasing how to identify integrated viruses. VEBA represents a crucial advancement in microbiome research, offering a powerful and accessible software suite that bridges the gap between genomics and biotechnological solutions.

The feasibility of CT simulation-free adaptive radiation therapy.

Novel on-board CBCT allows for improved image quality and Hounsfield unit accuracy. When coupled with online adaptive tools, this may have potential to allow for simulation and treatment to be completed in a single on-table session. To study the feasibility of a high-efficiency radiotherapy treatment workflow without the use of a separate session for simulation imaging. The dosimetric accuracy, overall efficiency, and technical feasibility were used to evaluate the clinical potential of CT simulation-free adaptive radiotherapy. Varian's Ethos adaptive radiotherapy treatment platform was upgraded with a novel CBCT system, HyperSight which reports image quality and Hounsfield unit accuracy specifications comparable to standard fan-beam CT. Using in-house developed MATLAB software, CBCT images were imported into the system and used for planning. Two test cases were completed on anthropomorphic phantoms equipped with small volume ion chambers (cross-calibrated to an ADCL traceable dose standard) to evaluate the feasibility and accuracy of the workflows. A simulated palliative spine treatment was planned with 8Gy in one fraction, and an intact prostate treatment was planned with 60Gy in 20 fractions. The CBCTs were acquired using HyperSight with default thorax and pelvis imaging protocols and reconstructed using an iterative algorithm with scatter removal, iCBCT Acuros. CBCTs were used for contouring and planning, and treatment was delivered via an online adaptive workflow. In addition, an external dosimetry audit was completed using only on-board CBCT imaging in an end-to-end head and neck phantom irradiation. An extended-field CBCT acquisition can be acquired in 12s, in addition to the time for longitudinal table shifts, and reconstructed in approximately 1min. The superior-inferior extent for the CBCT planning images was 38.2cm, which captured the full extent of relevant anatomy. The contouring and treatment planning for the spine and prostate were completed in 30 and 18min, respectively. The dosimetric agreement between ion chamber measurements and the treatment plan was within a range of -1.4 to 1.6%, and a mean and standard deviation of 0.41±1.16%. All metrics used in the external audit met the passing criteria, and the dosimetric comparison between fan-beam and CBCT techniques had a gamma passing rate of 99.0% with a criteria of 2%/2mm. Using an in-house workflow, CT simulation-free radiation therapy was shown to be feasible with acceptable workflow efficiency and dosimetric accuracy. This approach may be particularly applicable for urgent palliative treatments. With the availability of software to enable this workflow, and the continued advancement of on-treatment adaptation, single-visit radiation therapy may replace current practice for some clinical indications.

Research trends in international public sector accounting standards (IPSAS): a bibliometric analysis

Purpose This study aims to provide quantitative information on the research trends of international public sector accounting standards (IPSAS). Design/methodology/approach The study used bibliometric analysis to determine the research trends in IPSAS literature. The method was applied to papers indexed in the Scopus database to analyze the growth and publication trends of the selected papers. The research team rigorously compiled a list of keywords relevant to IPSAS after consultation with the principal researcher. The study did not apply document type, year or language filter. The search query resulted in 475 documents. The study used MS Access, Excel and Biblioshiny software for the data analysis and visualization. Findings The acceptance and application of IPSAS by many countries and UN system organizations have led to the rise in IPSAS literature globally. The study finds the USA to be the most productive country, with Italy, Spain and the UK as second, third and fourth, respectively. Similarly, the University of Zaragoza has produced the most publications in the field, followed by the University of Salerno and Ghent University. Practical implications This study provides the current state of IPSAS research globally; as a result, it supports the development of policies by the users of this standards. This information can inform the development or revision of public sector accounting policies and standards. Originality/value To the best of the authors’ knowledge, this is the first study that provides a bibliometric analysis of the growth and publication trends of IPSAS literature. The findings in this study uncover different areas of IPSAS research productivity globally.

Inter-software reliability and agreement for follicular and luteal morphometric and echotextural ultrasonographic parameters in beef cattle

This study aimed to compare the inter-software and inter-observer reliability and agreement for the assessment of follicular and luteal morphometry and echotexture parameters in beef crossbreed females (3/8 Bos taurus indicus and 5/8 Bos taurus taurus). B-mode and color Doppler ultrasonographic ovarian images were obtained at specific time points of estradiol-progesterone-based protocols for timed artificial insemination (TAI). Sonograms were analyzed by two observers using a licensed (IASP1) and an open access (IASP2) software package. A total of 292 snap-shot sonograms were analyzed for morphometric parameters and 504 for echotexture parameters. inter-software reliability was judged moderate to excellent (ICC or CCC=0.73–0.98), whereas inter-observer reliability for morphometric parameters was deemed good to excellent (ICC or CCC=0.82–0.98). A small percentage (up to 10.95 %) of measured parameters fell outside the limits of inter-software and inter-observer agreement. For echotexture parameters, inter-software reliability varied widely (ICC or CCC=0.16–0.95) based on the size of regions of interest (ROI), while inter-observer reliability ranged from moderate to excellent (ICC or CCC= 0.71–0.97). The highest inter-software reliability for pixel value and heterogeneity value was observed for the corpus luteum (ICCs=0.81–0.95; P>0.05), followed by the peripheral follicular antrum (ICCs=0.75–0.78; P<0.05). However, lower reliability was determined for the follicular wall (ICCs=0.08–0.33; P<0.0001) and perifollicular stroma (ICCs=0.16–0.46; P<0.05). In conclusion, both software packages showed high reproducibility for morphometric measurements, while echotexture measurements were more challenging to replicate based on ROI sizes. Caution is advised when selecting ROI sizes for echotexture measurements in bovine ovaries.

Deep learning framework for peak detection at the intact level of therapeutic proteins.

While automated peak detection functionalities are available in commercially accessible software, achieving optimal true positive rates frequently necessitates visual inspection and manual adjustments. In the initial phase of this study, hetero-variants (glycoforms) of a monoclonal antibody were distinguished using liquid chromatography-mass spectrometry, revealing discernible peaks at the intact level. To comprehensively identify each peak (hetero-variant) in the intact-level analysis, a deep learning approach utilizing convolutional neural networks (CNNs) was employed in the subsequent phase of the study. In the current case study, utilizing conventional software for peak identification, five peaks were detected using a 0.5 threshold, whereas seven peaks were identified using the CNN model. The model exhibited strong performance with a probability area under the curve (AUC) of 0.9949, surpassing that of partial least squares discriminant analysis (PLS-DA) (probability AUC of 0.8041), and locally weighted regression (LWR) (probability AUC of 0.6885) on the data acquired during experimentation in real-time. The AUC of the receiver operating characteristic curve also illustrated the superior performance of the CNN over PLS-DA and LWR.

IMAGE: An Open-Source, Extensible Framework for Deploying Accessible Audio and Haptic Renderings of Web Graphics

For accessibility practitioners, creating and deploying novel multimedia interactions for people with disabilities is a nontrivial task. As a result, many projects aiming to support such accessibility needs come and go, or never make it to a public release. To reduce the overhead involved in deploying and maintaining a system that transforms web content into multimodal renderings, we created an open-source, modular microservices architecture as part of the IMAGE project. This project aims to design richer means of interacting with web graphics than is afforded by a screen reader and text descriptions alone. To benefit the community of accessibility software developers, we discuss this architecture and explain how it provides support for several multimodal processing pipelines. Beyond illustrating the initial use case that motivated this effort, we further describe two use cases outside the scope of our project in order to explain how a team could use the architecture to develop and deploy accessible solutions for their own work. We then discuss our team’s experience working with the IMAGE architecture, informed by discussions with six project members, and provide recommendations to other practitioners considering applying the framework to their own accessibility projects.

Course Bit E-Learning Platform

E-learning: An Essential Component of Modern Education E-learning, or electronic learning, is a crucial aspect of contemporary education, encompassing any learning or teaching method facilitated by technology. It involves the use of specialized media and communication systems to conduct academic activities, whether through networked learning or other technological means. E-learning can occur both inside and outside the classroom, adapting to advancements in curriculum and devices. Key Features and Benefits of E-learning: - Computer-based learning - Growing Demand - Internet-based Implementation - Standardization Need - Accessible Software - Course Availability - Resource Utilization

Cybersecurity Measures Safeguarding Digital Assets and Mitigating Risks in an Increasingly Interconnected World

As interconnectivity and reliance on digital technologies continue to rise exponentially, so too do cybersecurity threats and risks. Malicious cyber actors are employing increasingly sophisticated techniques to target valuable data and disrupt critical systems and infrastructure. The impacts of successful cyber-attacks can be financially devastating and undermine an organization's reputation and customer trust. This paper examines how firms may utilize strong cybersecurity to protect digital assets and reduce risks in a connected society. As technology and communications improve, cyber threats do too. Problems keep popping up. Malware, phishing scams, and data breaches still harm businesses. Hackers can also get in simpler with more linked devices and the Internet of Things. This makes protecting digital assets and systems, networks, and critical infrastructure from sophisticated cyberattacks even more crucial. Cybercriminals can steal data, intellectual property, money, and customer information in many ways. Advanced persistent threats are used by state-backed parties for eavesdropping and geopolitics. Therefore, organizations in all professions and industries must prioritize safety and risk reduction. Businesses may increase their safety with technical, process-based, and strategic cybersecurity solutions, according to the report. This requires strong access restrictions, networks, encryption, software security, and audits. Human aspects like cyber awareness training and a comprehensive plan that matches an organization's risks and resources are considered. A thorough security plan discusses international conventions, following the rules, and using modern technologies. Two case studies demonstrate real-world operations. The first describes how a large retailer stopped a complex APT with numerous defenses. Learn how crucial segmentation, detection tools, incident reaction, and public-private partnerships are. The second one examines a major hotel chain data breach and offers simple measures like strong passwords and vendor tracking to reduce similar dangers. Even if digital adversaries are getting smarter, basic cybersecurity "hygiene." can block many attempts, the report concludes. No organization is totally safe, but following basic rules, laws, and best practices can help protect people, organizations, and governments' assets in today's linked globe. Researchers may investigate how blockchain and AI might lessen hacking risks.

Проблемы производства компьютерно-технической экспертизы мобильных телефонов при расследовании хищения денежных средств бесконтактным способом

The article reviews special aspects of the contactless method of embezzlement of electronic money from private bank accounts by using software for remote access to a mobile phone. The paper off ers a specifi c example to show the algorithm of an expert study aimed at obtaining important information from the criminalistic point of view. The author reviews the main reasons for lowering quality of expert studies and suggests measures aimed at raising the effi ciency of solution and timeliness of investigation of crimes falling within the category under consideration.

Exploring the possibility of adding DGGS support to the S-100 Universal Hydrographic Data Model

reference systems. A DGGS is a spatial reference system consisting of multiple layers of grids with increasing resolution which partition the globe into polygon shaped cells of equal area. Individual cells can be easily identified and basic Geographic Information System (GIS) operations can be performed on data stored within the cells. Advantages of using DGGS for spatial data include the ability to integrate data layers of different data types in a statistically uniform way, the possibility to avoid distortions caused from projection, and the capability to scale analysis across multiple resolution levels. The benefits of using DGGS for hydrographic data, specifically Electronic Navigational Charts (ENC) are examined. The addition of DGGS to S-100 would provide a uniform gridding system for ENC cells, and would eliminate distortions in the Polar Regions caused when projecting rectangular cells based on latitude and longitude. The Open Geospatial Consortium (OGC) led a pilot project for which one of the participants developed a server that offers S-100 marine protected area data organized according to DGGS. Because of this success and the availability of open-source software for the implementation of DGGS, the BSH (German Federal Maritime and Hydrographic Agency) investigated the feasibility and possible benefits of using Discrete Global Grid Systems for S-100 data. The outcome was successful. However, it is recognized that DGGS as a standard is not yet advanced enough and the available software tools are inadequate for wide implementation. More investigation needs to be done, and additionally the best grid shape, orientation and aperture for a uniform grid for hydrographic data need to be determined. Overall, DGGS should be considered for future versions of S-100, the new universal hydrographic data model, because the benefits for ENCs and hydrographic data are clear and in the future, it is expected that DGGS will revolutionize GIS.

Acceptance and adoption of tele-rehabilitation by physiotherapists from Nigeria, a low resource setting: a mixed-method study

BackgroundAdoption of tele-rehabilitation among physiotherapists in developed countries has risen exponentially to complement conventional physical contact physiotherapy. However, many low- and middle-income countries like Nigeria where barriers to utilization of tele-physiotherapy were earlier identified still demonstrates limited evidence on its acceptance and adoption till date.MethodThis was a mixed-method design of quantitative and qualitative study, aimed at investigating acceptance and adoption of tele-rehabilitation among physiotherapists in Nigeria. Respondents comprised 331 physiotherapists practising in Nigeria and registered with the Medical Rehabilitation Therapists (Registration) Board of Nigeria (MRTB). Quantitative approach involved completion of a 33-item structured questionnaire shared as Google Forms to respondents’ WhatsApp and emails. Qualitative aspect involved in-depth interview with 12 physiotherapists at the clinics, using a 10-item semi-structured interview guide, and recorded with a voice recorder. Quantitative data was analysed using descriptive and inferential statistics at p < 0.05 alpha level. Qualitative data was analysed using thematic content analysis.ResultsRespondents comprised 172 males and 159 females. Their mean age and years of experience were 33.42 ± 8.95 and 8.86 ± 8.037 years, respectively. Pre-lockdown, only 62 (18.7%) respondents offered tele-physiotherapy. During the 35-day total lockdown, 114 (34.4%) offered tele-physiotherapy. Majority (155 (46.8%)) used smartphone apps. Fifty-seven (17.2%) respondents were confident that tele-rehabilitation can complement conventional physiotherapy, while 72 (21.8%) kept offering post-lockdown. Use of digital technology was highest for patient education (97 (29.3%)), especially for musculoskeletal conditions (85 (25.7%)). There were significant associations between pre-lockdown duties (p = 0.036), post-lockdown duties (p = 0.005) and use of digital health technology (p = 0.001) with respondents’ age. Significant associations also existed between respondents’ years of practice and each of post-lockdown duties (p = 0.017) and use of digital health technology (p = 0.001). Qualitative approach revealed that facilitators to adoption and acceptance of tele-rehabilitation included patient education, training of physiotherapists, availability of evidence-based guidelines and tele-health software and hardware systems. Barriers were lack of or limited technological infrastructures, finances, hospital management support, and knowledge of information and communication technology.ConclusionsPhysiotherapists in Nigeria demonstrated moderate acceptance but low adoption of tele-rehabilitation, in varied comparison with clinicians and physiotherapists in other climes. Training of physiotherapists in tele-rehabilitation and provision of enabling technological environment by regulatory bodies and policy makers are recommended.

Increasing the reliability of diagnosis of diabetic retinopathy based on machine learning

This paper discusses the method of measuring and analyzing the parameters of the retina with subsequent diagnosis based on them of pathological changes due to diabetic retinopathy, which is crucial in the field of medicine to help doctors in timely detection and treatment of the disease. The main problem of biomedical image data analysis is insufficient pre-processing of images for further clear determination of informative indicators. This paper explores the application of machine learning and image processing techniques to develop an effective method for the diagnosis of diabetic retinopathy. The main focus is on obtaining the optimal model using machine learning and different types of neural networks. This paper considered and analyzed such methods of image preprocessing as: median filtering, grayscale conversion, cropping of non-informative areas of the image, selection of contours. The classification results of three rules (Classical Neural Networks (CNNs), Deep Neural Networks (DNNs) and Convolutional Neural Networks (CNNs) were analyzed, and through experimental studies it was determined that the ANN performed the task best (accuracy=87.1 %, reliability=84.6 %, sensitivity=91.6 %, specificity=84 %). An information model was obtained to support decision-making in assessing the condition of the retina using the processing of the obtained microscopic images and further analysis of informative parameters, and a database of more than 35,000 samples and informative features of the retina was formed. Given the sufficient quality of classification and the availability of software and hardware, this method can be developed and applied in practice in medical institutions after conducting all the necessary clinical studies