Assessment Software Research Articles

AGMA-PESS: a deep learning-based infant pose estimator and sequence selector software for general movement assessment

The General Movement Assessment (GMA) is a validated evaluation of brain maturation essential to shaping early individual developmental trajectories of preterm infants. To ensure a reliable GMA, preterm infants should be recorded for 30 to 60 min before manually selecting at least three sequences with general movements. This time-consuming task of manually selecting short video sequences from lengthy recordings impedes its implementation within the Neonatal Unit. Moreover, an accurate pose estimation tool for preterm infants is paramount to developing the field of GMA automation. We introduce the AGMA Pose Estimator and Sequence Selector (AGMA-PESS) software, based on the state-of-the-art deep learning infant pose estimation network, to automatically select the video sequences for GMA at preterm and writhing ages and estimate the pose of infants in 2D. Its simplicity and efficiency make AGMA-PESS a valuable tool to promote GMA use within the Neonatal Unit, both for clinical practice and research purposes.

A study on digital tooth preparation assessment software in undergraduate pre-clinical skills teaching

IntroductionAims This research aims to evaluate the effectiveness and efficiency of the PrepCheck digital system as an additional feedback tool in enhancing undergraduate dental students’ tooth preparation skills and its potential to enhance students’ learning experience.Material and MethodsA total of 55 BDS3 students attending the “Crowns Course” and divided into three groups participated in the study. One group (n = 24) was randomly selected as the case group and received feedback using the digital tooth preparation analysis system, PrepCheck, alongside standard visual assessment. The other two groups (n = 31) served as controls and only received standard visual feedback. All students’ tooth preparations for the final test were digitally assessed using PrepCheck against a faculty-approved master preparation. The tooth preparation quality was compared between the case and control groups, employing two distinct grading methods. Additionally, a questionnaire was provided to students who used the digital system to gather their feedback.ResultsThe findings revealed a positive trend in performance among the case group when using the PrepCheck system. However, the analysis showed no statistically significant differences between the groups in both the tutor assessment only and tutor assessment in addition to using the PrepCheck report. Despite the absence of statistically significant differences, qualitative feedback from participants indicated a favourable reception of the digital system.ConclusionsWhile the PrepCheck digital system displayed potential in complementing traditional teaching methods and enhancing the learning experience, its integration posed challenges, particularly concerning time constraints. Further research is recommended to investigate further the potential longer-term effects and potential useful applications for integrating digital systems like PrepCheck into dental education.

Enhanced electrocatalytic performance and exceptional durability facilitate the effective degradation of m-dinitrobenzene wastewaters utilizing a novel SS/PbO2-Y2O3-SiC electrode

The intrinsic toxicity of m-dinitrobenzene (m-DNB) to human health and the environment has made dealing with m-DNB pollution a major concern. Herein, a novel hydrophobic anodic electrode SS/PbO2-Y2O3-SiC doped with Y and SiC was constructed via a simple electrodeposition strategy for efficient degradation of m-DNB. With a dense-uniform structure and hydrophobic surface, such SS/PbO2-Y2O3-SiC electrode exhibits obviously lower activation energy (8.17kJmol−1) and charge transfer resistance (1.15 Ω cm2), higher electrochemical active area (46.14 cm2) and stability (359 d), in comparison to SS/PbO2. The m-DNB removal efficiency of the as-prepared SS/PbO2-Y2O3-SiC anode was significantly increased to 96.4% in 180minutes, and the degradation reaction-order was determined to be 0.9559, which was in accordance with the quasi-first-order reaction kinetics. These are the possible degradation pathways of m-DNB under the action of both cathodic and anodic reactions, according to the GC-MS results. The -NO2 group of m-DNB was first reduced to the -NH2 group at the cathode surface, and then the m-phenylenediamine generated at the cathode was sequentially oxidised by the hydroxyl radicals generated from the anodic electrochemical process, resulting in the generation of H2O and CO2 at the anode surface. Additionally, the Assessment Software Tool (TEST) shows that the SS/PbO2-Y2O3-SiC anode can effectively reduce the risk and harm of m-DNB to the overall environment. This study offers novel perspectives on the development of a highly efficient PbO2 electrode for the degradation of m-DNB pollutants.

Synergistic low-temperature plasma degradation of tetracycline with ferrocene

Low-temperature plasma technology has been successfully applied to the treatment of persistent organic pollutants in water. By combining catalysts with low-temperature plasma, the degradation efficiency and energy utilization efficiency of pollutants can be effectively improved. In this study, ferrocene (Fc) was added as a new catalyst to the low-temperature plasma system to treat tetracycline (TC) found in wastewater. The degradation efficiency of TC after 60 min of plasma treatment, Fc adsorption, and Fc/plasma treatment was compared, indicating that Fc/plasma improved the removal compared with using plasma alone. The effects of primary parameters such as Fc dosage, initial pH, discharge voltage, and anions in wastewater on TC removal efficiency were investigated. Under the conditions of Fc dosage of 400 mg/L, pH of 9, and discharge voltage of 20 kV, the degradation efficiency of TC was 76.59%. Results of free quenching experiments indicated that hydroxyl radicals played an important role in the treatment of TC. The characterizations of Fc showed that the structure of Fc before and after use in the plasma system changed little. In addition, toxicity testing using toxicity assessment software showed that only two to three degradation intermediate products had slightly higher toxicity than TC. The iron leaching concentration was 2.5 mg/L, and the Fc dissolution concentration was 1.72 mg/L after the reaction.

Efficient tetracycline hydrochloride degradation via peroxymonosulfate activation by N doped coagulated sludge based biochar: Insights on the nonradical pathway.

Coagulation could effectively remove microplastics (MPs). However, MPs coagulated sludge was still a hazardous waste that is difficult to degrade. Nitrogen-doped carbon composite (N-PSMPC) was prepared by carbonizing MPs coagulated aluminum sludge (MP-CA) doped with cheap urea in this study. Compared with the carbon material (PSMPC) produced by direct carbonization of MP-CA, N-PSMPC had a higher degree of defects, which could provide more active sites for peroxymonosulfate (PMS) activation. And then, the N-PSMPC was applied to the degradation of tetracycline hydrochloride (TC). The results showed that the N-PSMPC/PMS system exhibited excellent TC degradation performance at the pH range of 3-9, and the coexistence of CO32- and HCO3- inhibited the TC degradation. Moreover, the graphite N, pyridine N and carbonyl group were identified as the primary catalytic active sites. Three TC degradation pathways were speculated based on the intermediates detected by liquid chromatography-mass spectrometry, and the degradation mechanism was dominated by the nonradical pathway. In addition, the analysis of TC and intermediates by toxicity assessment software showed that N-PSMPC/PMS system could mitigate the TC toxicity. This study will provide a novel approach for the resourceful utilization of MP-CA and provide technical support for the removal of MPs and TC in water.

Association between post-stroke depression and post-stroke sleep disorders: a systematic review and meta-analysis.

Post-stroke depression (PSD) and post-stroke sleep disorders (PSSD) are common concurrent symptoms in post-stroke patients, and their early detection may have an impact on stroke recovery and prognosis. The purpose of this study is to determine the relationship between PSD and PSSD. We systematically searched PubMed, Embase, Web of Science, Cochrane Library, APA PsycInfo, Medline, Scopus, Technology Periodical Database (VIP), China Biology Medicine (CBM), China National Knowledge Infrastructure (CNKI), and WanFang Data databases for studies on the association between PSD and PSSD, with a search timeframe ranging from database construction to May 9, 2024, two researchers independently performed literature search, screening and quality assessment, and RevMan (version 5.4) and Stata (version 15.1) software were used for statistical analysis. We included 16 studies, nine in Chinese and seven in English, with 2,284 stroke patients. The results showed that the pooled Fisher's Z was 0.58 (95% CI = 0.52-0.65, P < 0.00001). After data transformation, the pooled r-value was 0.52, indicating a positive correlation between PSD and PSSD. The available evidence suggested that PSD was positively correlated with PSSD. Given the correlation between PSD and PSSD, alleviating PSSD may reduce the incidence of PSD, and improving PSD may also improve patients' sleep quality.

Geospatial Evaluation of Ambient Air Quality in Akure South Local Government Area, Ondo State, Nigeria

The study evaluates the ambient air quality in Akure South Local Government Area, Ondo State, Nigeria, focusing on particulate matter (PM2.5 and PM10) and its health implications on residents. Primary data were collected using Purple Air Monitor devices at 28 ground stations and structured questionnaires, base maps. The study utilized QGIS for mapping, SPSS for statistical analysis and WHO’s AirQ software for health risk assessment. Findings indicated exceedances of WHO and USEPA recommended limits for PM2.5 and PM10, with areas near major highways showing elevated PM levels. The health risk assessment revealed potential increases in hospitalizations and mortality due to air pollution. This research contributes uniquely by applying geospatial evaluation and health risk assessment tools for comprehensive air quality analysis. It highlights the urgent need for effective air quality management strategies, including the deployment of air quality monitoring stations and public education campaigns. The study provides crucial insights for policy makers, emphasizing the importance of mitigating air pollution’s adverse effects on urban settings. Received: 15 September 2024 / Accepted: 8 November 2024 / Published: 20 November 2024

Exploring bilateral breast size and density asymmetry: Insights from the saudi screening population

Background/objectivesThe swift appearance of asymmetry in breast size and density has been associated with an increased risk of breast cancer and other pathological changes. However, the occurrence of breast asymmetry and the factors influencing it have not been extensively studied among healthy, screened women in the Saudi population. Thus, this study aims to explore bilateral breast asymmetry in breast size and density among healthy, screened Saudi women and factors affecting the asymmetry. MethodsData of 1048 out of 1173 eligible women screened between 2012 and 2018 were extracted from Sheikh Mohammed Hussien AL-Amoudi Center of Excellence in Breast Cancer. The Laboratory for Individualized Radiodensity Assessment (LIBRA) software was used to measure percent density, dense area, and total area of breast from mammograms. Paired t-test was used to examine asymmetry between right and left breasts, and stratified analysis was performed to investigate the factors associated with breast asymmetry. ResultsNo significant differences were observed between the right and left breasts in percent density, dense area, and total breast area (p ≥ 0.2). However, for participants who never breastfed, the right breast area was slightly larger (average: 207.9 cm2) than the left breast (average: 202.8 cm2); p = 0.008. ConclusionThere were no significant differences found in the density, and size of the right and left breasts. However, women who breastfed tended to have slightly larger right breasts.

Incorporation of software in the life cycle assessment of an ICT service: A case study of an ICT service for energy efficiency in the transport sector

AbstractInformation communication and technology (ICT) services and solutions can improve resource efficiency in a variety of sector, but also result in direct environmental impacts. This study assesses the direct environmental impacts of an ICT service that improves vehicle fuel efficiency using a cradle‐to‐grave life cycle assessment (LCA). This is one of the first studies to examine the entire life cycle of an ICT service from development to use and maintenance, with a focus on software—an aspect that is typically neglected in previous studies. The results suggest that software development and maintenance and the use of in‐vehicle communicators for data transmission have the largest environmental impacts across multiple categories. Deployed across a fleet of 150,000 vehicles over 5 years, we estimate that the ICT service is responsible for 174 tCO2e. However, this is negligible compared with the total emissions of the fleet and the potential savings from the service, given a single diesel vehicle in this fleet emits around 130 tCO2e over the same period. We explore several scenarios to reduce the footprint of the ICT service. The largest potential reduction of around one‐third is achieved by replacing in‐house servers with cloud computing in a data center located in a region with low‐carbon electricity. The study demonstrates how LCA can be used to assess the environmental impacts of ICT services and the importance of considering software in these assessments.

Calcium plus vitamin D supplementation during pregnancy has no impact on postpartum transient longitudinal changes in hip geometry in adolescent mothers: a secondary analysis of a randomised controlled trial.

We have previously demonstrated that calcium plus vitamin D supplementation during adolescent pregnancy reduces the magnitude of transient postpartum bone mass loss. In the present post hoc analysis, we further investigated the effect of calcium plus vitamin D supplementation during pregnancy in hip geometry throughout one year postpartum in Brazilian adolescents with low daily calcium intake (∼600 mg/d). Pregnant adolescents (14-19 years) were randomly assigned to receive calcium (600 mg/d) plus vitamin D3 (200 μg/d) or a placebo from 26 weeks of gestation until parturition. Dual-energy X-ray absorptiometry images were obtained at 5 (n 30 and 26 for calcium plus vitamin D and placebo, respectively), 20 (n 26 and 21) and 56 (n 18 and 12) weeks postpartum, and hip geometry parameters were analysed by Advanced Hip Assessment software. The effects of the intervention, time point and their interaction were assessed using repeated-measures mixed-effects models. No significant intervention effects or intervention × time interactions were observed on hip geometry parameters (P > 0·05). Time effects were observed in cross-sectional area, cross-sectional moment of inertia and section modulus parameters with decreases from the 5th to the 20th week postpartum followed by recovery from the 20th to the 56th week (P < 0·05). Our findings indicate that the postpartum period is associated with transient changes in the hip geometry of lactating adolescent mothers, regardless of the low calcium intake and the supplementation offered during pregnancy, suggesting that a physiological adaptation of these adolescents to low calcium intake is at play.

Diagnostic Accuracy of Automated Diabetic Retinopathy Image Assessment Software: IDx-DR and RetCAD.

Automated diabetic retinopathy (DR) screening using artificial intelligence has the potential to improve access to eye care by enabling large-scale screening. However, little is known about differences in real-world performance between available algorithms. This study compares the diagnostic accuracy of two AI screening platforms, IDx-DR and RetCAD, for detecting referable diabetic retinopathy (RDR). Retinal images from 758 patients with diabetes were collected during screening from various clinics in Poland. Each patient was graded by three graders with 320 patients graded by Polish and 438 patients graded by Indian graders, with the majority decision serving as the reference standard. The images were evaluated independently by the IDx-DR and RetCAD algorithms. Sensitivity, specificity, positive and negative predictive values, and agreement between algorithms and human graders were calculated and statistically compared. IDx-DR demonstrated higher sensitivity of 99.3% but lower specificity of 68.9% for RDR detection compared to RetCAD which had 89.4% sensitivity and 94.8% specificity. The positive predictive value was higher for RetCAD (96.4% vs 48.1% for IDx-DR) while the negative predictive value was higher for IDx-DR (99.5% vs 83.1% for RetCAD). Both algorithms achieved high sensitivity (> 95%) for sight-threatening diabetic retinopathy detection. In this direct comparison using the same patient cohort, the two algorithms showed differences in their operating parameters for RDR screening. IDx-DR prioritized avoiding false negatives over false positives while RetCAD maintained a more balanced trade-off. These results highlight the variable performance of current artificial intelligence screening solutions and suggest the importance of considering algorithm performance metrics when deploying automated diabetic retinopathy screening programs, based on available healthcare resources.

A Comparative Analysis of the Environmental Impacts of Wood–Aluminum Window Production in Two Life Cycle Assessment Software

In the construction sector, there is a shift towards environmentally conscious practices that prioritize the minimization of environmental burdens. In this study, we dealt with a cradle-to-gate life cycle assessment (LCA) of a wood–aluminum window in two software tools. SimaPro (PRé Sustainability) and Sphera LCA for Experts (formerly known as GaBi) were selected. The results from both software tools were compared to assess the output uniformity of the two selected tools. The results indicate the similarities and differences in the software tools. The most similar results were achieved for impact categories Photochemical Ozone Formation (1.1% difference), Human Toxicity, cancer (total) (3.6% difference), Climate Change (3.7% difference) and for Resource Use, fossils (4.5% difference), respectively. On the other hand, the results were most different in the impact categories Ozone Depletion (84.7% difference), Resource Use, minerals and metals (75% difference), Ecotoxicity, freshwater—inorganics (35.6%) and Ecotoxicity, freshwater (total) (31.2%), respectively. The differences in the LCA results between SimaPro and GaBi were analyzed in-depth and were mainly attributable to using different databases in the transportation process and due to different system boundaries in some processes, with the Ecoinvent data containing significantly more background processes and inconsistencies in the implemented characterization factors.

WACARDIA: Graphical MATLAB software for Wireless Assessment of CARDiac Interoceptive Accuracy

Many theories of psychological function emphasize the importance of bodily sensations and the ability to accurately detect them, known as interoceptive accuracy. The most common measure of interoceptive accuracy uses heartbeat detection tasks such as the Whitehead Task, yet to our knowledge there are no freely accessible programs to conduct this task. In this paper, we present novel software called WACARDIA (Wireless Assessment of CARDiac Interoceptive Accuracy), which is free, open-source software that conducts the heartbeat detection task using Matlab and Psychtoolbox. WACARDIA contains several key features supporting participant engagement, operator convenience, and measurement accuracy. First, the program includes an optional practice trial of unlimited duration, a participant-facing graphical interface, and the ability to perform heartbeat detection training. Second, the operator is provided with a graphical user interface, live trial feedback, an accurate wireless electrocardiogram device, and a separate program to conduct the related Heartbeat Tracking task. Finally, the program ensures the accuracy of collected data by scheduling the delivery of tones with high precision and implementing fail-safes to automatically reset erroneous measurements. This paper includes flowcharts that help create transparency by describing our algorithm. We also outline customizable aspects of the program with the intent to have WACARDIA’s algorithm expanded to accommodate more situations and applications. With this paper, we hope to encourage the practice of publicizing research software to contribute to the transparency, rigor, and reproducibility of scientific studies. WACARDIA and video tutorials are available at www.github.com/iankleckner/wacardia and http://wacardia.iankleckner.com.

ANALYSIS OF THE RE–ENTRY PHASE OF STARLINK–1353 SATELLITE

Eighty-three percent of all operational satellites are deployed in LEO, where Starlink is the largest mega-constellation with 5,233 satellites in working phase (data available for June 2024) (Planet4589, 2023). To date, SpaceX has launched the first 6,505 Starlink satellites out of 11,908 units planned (with a possible supplement of 22,488 units). One of the failed satellites was the Starlink–1353 (2020–025G) unit, for which the controlled decay above Hokkaido Island, on February 21, 2023, was in the field-of-view of one telescope from Kitasubaru Astronomical Observatory. Luckily, in that moment the telescope was performing observations on the Orion Nebula region, in a live streaming session (Kitasubaru, 2024). The major break-up was captured by the video camera of the telescope and based on the frame–by–frame image analysis, W identified 15 fragments after the atmospheric re–entry. According to our analysis based on Debris Assessment Software (DAS) (NASA), the major breakup occurred at 64.4 km above the sea level and some fragments were spread over an area of 15.13 m2. The paper presents hypothesis about the composition of the fragments that crossed the sky above Japan and if these can reach the sea level. In order to study the dynamical behaviour of Starlink–1353, before the moment of planned re–entry maneuvers, the observation recorded by Berthelot Observatory (IAU Code L54) were used. Orbital evolution of the satellite is presented using numerical integration for the available Two Line Elements (TLE) values. Using the last TLE, published five hours before re–entry, an estimated time 10:46 UTC, February 21, 2023 was computed.

A new data-driven Life Cycle Assessment tool at the urban scale: the case of the Milan building stock analysis to reduce the related environmental potential impacts

Abstract Given the ambitious targets for greenhouse gas emissions reduction set by the European Union and the importance of cities in achieving these goals, there is an increasing need to analyze a city’s environmental footprint with a life cycle approach. The life cycle assessment is considered the leading methodology for environmental metrics, permitting a holistic environmental perspective on cities. Life Cycle Assessment software applications are aimed at single product evaluation, making urban scale, data management, and environmental assessment complicated or impractical, mainly due to the massive data processing required. The novelty of this work is a new tool, utilizing a data-driven approach, that allows an extensive environmental evaluation of buildings (following the EN 15978 standard, considering 20 impact categories). The tool was applied to analyze the city of Milan. Approximately 240 000 building units were investigated and compared using as activity data the information described in the energy performance certificates of building units. The results for Residential, Commercial, and Retail building units (old and new) are 58, 65, and 84 kg CO2eq / (m2 of useful floor area * year), respectively, considering space heating, domestic hot water, and controlled mechanical ventilation. Actions linked with: (i) improving energy systems, (ii) the decarbonization of energy carriers (i.e., electricity and natural gas), and (iii) the retrofitting of envelopes by running the tool developed. The outcomes obtained were used to verify pieces of legislation listed in the “Fit for 55” and “REPowerEU.” The scenarios lead to the conclusion (for Milan) that the reduction of greenhouse gas emissions by at least 55% (by 2030) is achievable only by retrofitting at a rate of 1.6% per year both energy systems and envelopes, plus also acting on the decarbonization of energy carriers.

The Role of Artificial Intelligence (AI) and machine learning in social work practice

The integration of Artificial Intelligence (AI) and Machine Learning (ML) into social work practice is transforming the landscape of service delivery and decision-making. This paper explores how these technologies enhance case management, predictive analytics, and resource allocation in critical areas such as child welfare, mental health, and substance abuse treatment. Key trends highlighted include the use of AI-based predictive analytics to identify at-risk populations and facilitate early interventions, as well as the deployment of chatbots and virtual assistants for providing accessible mental health counselling and social support. Furthermore, the paper addresses ethical considerations and challenges associated with AI implementation, particularly the potential biases in algorithms that may affect the assessment of social needs. Additionally, the integration of AI tools into social work education and training is examined to prepare future professionals for a technology-driven environment. By analysing the current applications of Natural Language Processing (NLP) for client data analysis, AI-powered software for predictive risk assessments, and automated case management systems, this paper advocates for a balanced approach to AI adoption, ensuring that the core values of social work, such as equity and social justice, remain central to practice. Ultimately, this exploration underscores the potential of AI and ML to enhance social work outcomes while also emphasizing the necessity of ethical frameworks and ongoing training for practitioners.

Strengthening Rasch Modeling for Objective and Fair Assessment for Chemistry Teachers

The competence of a good chemistry teacher will contribute to a fair assessment ability. This service aims to improve the professional competence of the sub-field of assessment for chemistry teachers at madrasahs in the Mranggen sub-district. This service is participatory by processing the results in a quantitative descriptive manner with one variable, namely the professional competence of the teacher's assessment. Service Locations in Madrasahs, Mranggen District. The number of participants in this service is 20 active chemistry teachers. Data collection techniques using closed and open questionnaires. Data validity uses content validity. Data reliability using Croncbach's Alpha technique. Data analysis techniques use the percentage formula to determine the achievement of each component through statistical data. The results of Community Service found that the professional competence of chemistry teachers at madrasas in the Mranggen sub-district was on average in the very good category, but variations in the use of assessment software were very lacking and had never been carried out. The service contribution gives a good value for changes in the ability to use the Rasch model assessment software after the service is over, but this depends on the amount of motivation the participants have.

Utilizing 3D Model and Comparison Software Tools in Improving Assessment Methods: A Pilot Study

Purpose/Objectives: This manuscript investigates the effectiveness of computer-assisted design and manufacturing (CAD/CAM) technology in preclinical dental education. The COVID-19 pandemic created a need for remote teaching approaches. In preclinical fixed prosthodontics courses, traditional evaluation methods rely on faculty to visually grade laboratory projects utilizing rubrics and 2D images. Assessment and feedback vary amongst faculty, and faculty calibration has been inconsistent in reducing intra-and inter-rater variability. This study aimed to compare faculty assessment of student full coverage crown (FCC) preparations traditionally versus digitally through 3D model visual assessment and/or comparative analysis software reports. Methods: Eighteen UTHealth Houston School of Dentistry faculty participated, each randomly assigned into one of three assessment groups: traditional visual Group (TV), 3D Group (3D), and 3D visual assessment supplemented with comparative analysis software report (3D+) Group. Faculty graded the same eight lithium disilicate typodont preparations for all three assessment groups. Results: Survey results showed the ease of use and efficiency among the three assessment methods varied significantly. Grading scores revealed that axial wall reduction significantly differed among the three assessment methods. Conclusion: This study concludes that the combination of the two digital assessment methods can overcome the limitations of traditional evaluation methods and digital methods alone by providing objective feedback to students and enhancing their learning experience.

Prevalence and associated factors of ECG abnormality patterns indicative of cardiac channelopathies among adult general population of Tehran, Iran: a report from the Tehran Cohort Study (TeCS)

BackgroundThe characteristics of electrocardiogram (ECG) abnormalities related to cardiac channelopathies potentially linked to sudden cardiac death (SCD) are not widely recognized in Iran. We examined the prevalence of such ECG patterns and their related factors among adult residents of Tehran, Iran.MethodsThe clinical characteristics and 12-lead ECGs of Tehran Cohort Study participants were examined. Long QT intervals, short QT intervals, Brugada syndrome (BrS) patterns, and early repolarization (ER) were evaluated using computer-based assessment software validated by cardiologists. Logistic regression models were employed to identify the factors associated with the prevalence of different ECG patterns.ResultsOut of 7678 available ECGs, 7350 were included in this analysis. Long QT interval, ER pattern, BrS patterns, and short QT interval were found in 3.08%, 1.43%, 0.31%, and 0.03% of participants, respectively. The prevalence of long QT interval increased with age, opium consumption, and presence of hypertension. Younger age, lower body mass index (BMI), alcohol use and male sex were independently linked to an elevated prevalence of ER pattern. Most individuals with BrS patterns were men (95%) and had lower BMI, high- and low-density lipoprotein, and total cholesterol compared to those without the BrS pattern. At a mean follow-up of 30.2 ± 5.5 months, all-cause mortality in the group exhibiting abnormal ECG patterns (6.3%) was approximately twice as high as that in the group without such patterns (2.96%).ConclusionAbnormal ECG patterns corresponding to channelopathies were relatively rare among adult residents of the Tehran population, and their prevalence was influenced by various factors.Clinical trial numberNot applicable.

Natural Language Processing Risk Assessment Application Developed for Marble Quarries

In this study, by using the texts describing the hazards and precautions taken during text mining, the necessary processes were carried out to first estimate the probability value and severity value of the risk and then calculate the risk values by Natural Language Processing analysis. In order to be used within the scope of the study, two data sets were generated from the data in the risk assessment report prepared by applying the L-type matrix risk assessment in marble quarries between 2015 and 2021. Stochastic Gradient Descent (SGD) was used for classification and prediction by analyzing text data. One data set was used to analyze the probability value of the risk and the other was used to analyze the severity value of the risk. In light of the results, when a text containing hazard and precaution information was entered, a system was developed that analyzed this text, estimated the probability and severity values, and calculated the risk assessment score. The application of the SGD algorithm to learning models developed on text data yielded an accuracy rate of 91.2% in the risk probability data set and 97.5% in the risk severity data set. The results indicated that the models were capable of conducting automatic risk assessment on text data and of effectively predicting the requisite probability and severity values. Due to the high accuracy rates obtained during the study, this risk assessment software was recommended for use in marble quarries.