Assessment System Research Articles

Arthroscopic assisted versus open core decompression for osteonecrosis of the femoral head: A systematic review and meta-analysis.

Minimally invasive treatment options for osteonecrosis of the femoral head (ONFH) have been a prominent area of research in recent years. Arthroscopic-assisted treatments have been applied in the clinical management of ONFH; however, high-quality evidence verifying their effectiveness and safety is still lacking. To systematically assess the clinical efficacy and safety of arthroscopic-assisted core decompression (AACD) in treating ONFH. A comprehensive literature search was conducted in PubMed, Web of Science, EMBASE, Cochrane Library, Chinese National Knowledge Infrastructure, China Science and Technology Journal Database, WanFang, and the Chinese BioMedical Literature Database, from inception to June 25, 2024. We identified randomized controlled trials and non-randomized controlled studies on AACD for the treatment of ONFH based on predefined inclusion and exclusion criteria. A meta-analysis was performed using Review Manager 5.4.1 and Stata 17.0 software. The analyzed outcomes included operative time, intraoperative blood loss, length of hospital stay, postoperative femoral head collapse rate, Harris hip score, and postoperative complication rate. The Grades of Recommendations, Assessment, Development, and Evaluations (GRADE) system was used to assess the quality of evidence for the outcome indicators. A total of fourteen studies were included in this meta-analysis, comprising 1,063 patients-541 in the core decompression (CD) group and 522 in the AACD group. The meta-analysis revealed no significant differences between the two groups in terms of intraoperative blood loss, length of hospital stay, 12-month postoperative Harris hip score, or overall postoperative complication rate (P > 0.05). However, the AACD group had a longer operative time (MD = 31.19, 95% Cl: 5.32 to 57.07, P = 0.02) and a lower overall postoperative femoral head collapse rate (RR = 0.49, 95% Cl: 0.27 to 0.89, P = 0.02) compared with the CD group. Additionally, the AACD group showed significant improvements in Harris hip scores at 3 months (MD = 6.39, 95% Cl: 5.44 to 7.33, P < 0.00001), 6 months (MD = 7.56, 95% Cl: 6.63 to 8.49, P < 0.00001), ≥ 24 months (MD = 7.00, 95% Cl: 4.80 to 9.21, P < 0.00001), and at the last follow-up (MD = 6.89, 95% Cl: 5.30 to 8.48, P < 0.00001) compared to the CD group. The GRADE evidence assessment indicated that the overall postoperative complication rate was supported by moderate-quality evidence, while the evidence for operative time, intraoperative blood loss, postoperative femoral head collapse rate, and Harris hip score was of low quality. The evidence for length of hospital stay was deemed very low quality. This meta-analysis suggests that AACD is an effective and safe treatment for patients with ONFH. However, due to the limited quantity and quality of the included studies, these results should be interpreted with caution. Further high-quality studies are recommended to confirm these findings.

Comparison of Occupational Performance in Immersive Virtual and Real Environments Among Patients With Stroke: Observational Randomized Crossover Pilot Study.

Conventional rehabilitation approaches involve therapists simulating various occupational tasks in health care settings or recreating real-life situations to assess and train patients in instrumental activities of daily living (IADLs). As an alternative, immersive virtual reality (IVR) has been widely used in stroke rehabilitation for years, but research comparing occupational performance between virtual and real environments is limited. This study aims to introduce a novel IVR shopping system designed for patients with stroke and to investigate the correlation of occupational performance in virtual and real environments among patients with stroke. Ten patients with stroke were recruited from the Department of Rehabilitation Medicine, Shenzhen Hospital, Southern Medical University, who met the inclusion and exclusion criteria for this observational, randomized crossover study; the patients were predominantly male (n=7), had experienced ischemic stroke (n=9), were aged 14 to 73 years, and had a time since stroke of 1 to 42 months. All patients attempted shopping tasks in virtual and real environments. The Mini-Mental State Examination (MMSE), Timed Up and Go Test (TUGT), modified Barthel index (MBI), and Lawton index (LI) were used to assess cognition, ambulation, and activities of daily living. Memory capacity and duration in the virtual and real environments were recorded as the primary parameters of occupational performance. The Wilcoxon test and Spearman correlation coefficients were used to analyze the differences and correlations between the 2 environments. The Wilcoxon test showed no significant differences between the virtual and real environments in memory capacity and duration of task completion (P>.99 and P=.99), and memory capacity in both environments correlated with the LI (ρ=0.81; P=.005). Memory duration had a relationship with the TUGT in the virtual environment (ρ=0.68; P=.03) and a borderline negative correlation with MMSE in the real environment (ρ=-0.58; P=.08). Considering the small sample size used in this study and the study's limitations, despite the significant correlation between shopping performance in IVR and the real world, it is still too early to conclude that IVR is a noninferior approach, but it presents the potential to be an alternative for assessment and training in IADLs when resources are limited. However, further research is needed to investigate the psychometric properties, clinical effects, and impact of virtual training on real-world performance. The implications for practice might include the following: (1) occupational performance in virtual shopping might be the same as real-world shopping, and more virtual IADLs could thus be developed; (2) virtual IADL assessment and training systems could be used in remote locations or locations with limited resources; and (3) more objective parameters of IADLs could be extracted from virtual environments.

Are local species prioritization lists sufficient for protecting endangered plants? Israeli red list as a test case

AbstractConserving species from extinction requires risk assessment and ranking for conservation priorities. The IUCN criteria of extinction risk are currently accepted globally, but only a small fraction of species were evaluated. When assessing species' extinction risk, sufficient information, in particular rate of population decline, is often partial or missing. Here we utilized the red list of Israeli endangered plant species, which prioritizes them for conservation, and evaluated their local extinction risk using IUCN criteria for local assessment. We found a relatively high similarity between the Israeli red number value and the IUCN assessments. Most pronouncedly, the habitat vulnerability index, used in the Israeli method, is correlated with the IUCN parameter of extinction rate in the last decade. We conclude that in the case of Israel, prioritization ranking of endangered species based on locally available information is a powerful tool for conservation even when some species information is lacking, facilitating local decision‐making. This finding may apply also to other countries using a local assessment system.

Personalized Real-Time Risk Assessment and Alert System to Mitigate Risks for Mothers with Deteriorating Health

A real-time alert system for pregnant women with worsening health is a digital solution that uses data and analytics to identify potential health risks and send alerts to healthcare providers, family members or the women themselves. This system that processes data and generates alters in real-time, enabling swift action to be taken in response to changing circumstances. The target for this system is to mitigate expectant mothers whose health is deteriorating or at risk of complications. Thus, the goal of this entitled article is to prevent complications and ensure timely medical interventions in worsening mother with deteriorating health condition.

Validation of computer vision-based ergonomic risk assessment tools for real manufacturing environments.

This study contributes to understanding semi-automated ergonomic risk assessments in industrial manufacturing environments, proposing a practical tool for enhancing worker safety and operational efficiency. In the Industry 5.0 era, the human-centric approach in manufacturing is crucial, especially considering the aging workforce and the dynamic nature of the entire modern industrial sector, today integrating digital technology, automation, and sustainable practices to enhance productivity and environmental responsibility. This approach aims to adapt work conditions to individual capabilities, addressing the high incidence of work-related musculoskeletal disorders (MSDs). The traditional, subjective methods of ergonomic assessment are inadequate for dynamic settings, highlighting the need for affordable, automatic tools for continuous monitoring of workers' postures to evaluate ergonomic risks effectively during tasks. To enable this perspective, 2D RGB Motion Capture (MoCap) systems based on computer vision currently seem the technologies of choice, given their low intrusiveness, cost, and implementation effort. However, the reliability and applicability of these systems in the dynamic and varied manufacturing environment remain uncertain. This research benchmarks various literature proposed MoCap tools and examines the viability of MoCap systems for ergonomic risk assessments in Industry 5.0 by exploiting one of the benchmarked semi-automated, low-cost and non-intrusive 2D RGB MoCap system, capable of continuously monitoring and analysing workers' postures. By conducting experiments across varied manufacturing environments, this research evaluates the system's effectiveness in assessing ergonomic risks and its adaptability to different production lines. Results reveal that the accuracy of risk assessments varies by specific environmental conditions and workstation setups. Although these systems are not yet optimized for expert-level risk certification, they offer significant potential for enhancing workplace safety and efficiency by providing continuous posture monitoring. Future improvements could explore advanced computational techniques like machine learning to refine ergonomic assessments further.

Impact of Nutritional Minerals Biomarkers on Cognitive Performance Among Bangladeshi Rural Adolescents—A Pilot Study

Background: Nutritional metals (NM) are essential for neurodevelopment and cognitive performance during growth. Nevertheless, epidemiological evidence regarding the associations between NM and brain function remains understudied, particularly among adolescents. Therefore, the objective of this pilot study was to examine the effects of NM biomarkers such as iron (Fe), selenium (Se), zinc (Zn), magnesium (Mg), and copper (Cu) on neurobehavioral functions among a group of rural Bangladeshi adolescents. Methodology: We conducted a cross-sectional study involving 105 adolescents aged 13–17 from Araihazar, Bangladesh. Cognitive function was assessed using the computer-based Behavioral Assessment and Research System (BARS), focusing attention, memory, and executive function, and blood NM levels (Fe, Se, Zn, Mg, and Cu) were measured. Associations between individual minerals, NM composite scores, and cognition were analyzed using multiple linear regressions. Results: This study included 47 boys and 58 girls with an average age of 15 years. Fe levels were correlated with Continuous Performance Test (CPT) latency (r = −0.42, p &lt; 0.05) and Se levels correlated with Match-to-Sample (MTS) correct count (r = 0.32, p &lt; 0.01). Linear regressions showed that Se was associated with MTS correct count (b = 0.02, 95%CI: 0.01, −0.04), reflecting visual memory, and Fe was associated with CPT latency (b = −0.68, 95%CI: −1.11, −0.26), reflecting improved attention. The same BARS measures were also significantly associated with the 3-NM composite score. Conclusions: Our findings suggest that NM, particularly Fe, Se, and NM mixtures, could play a crucial role in brain development and neurocognitive function during adolescence. Further studies will help design national public health policies and strategies to address and mitigate brain health deficiencies among adolescents.

A subjective and objective fusion visual fatigue assessment system for different hardware and software parameters in SSVEP-based BCI applications.

With the development of brain-computer interface industry, large amounts of related applications have entered people's vision. BCI applications based on steady-state visual evoked potentials (SSVEP) are widely used because they do not require pre-training and have high information transmission rates. However, in the actual use of SSVEP stimulus paradigm, the subjects will produce visual fatigue with the use, and fatigue will affect the transmission efficiency. In this experiment, an experimental environment consisting of two paradigm stimulus frequencies (7.5Hz, 15Hz), three resolutions (800 × 600, 1280 × 720, 1920 × 1080) and three refresh rates (120Hz, 240Hz, 360Hz) is set up. The Likert scale is used to collect subjective fatigue and preference scores, and the EEG acquisition system and eye tracker are used to collect objective data. Using the proposed information entropy-CRITIC algorithm to combine subjective and objective indicators, a fatigue assessment system (display screen fitness-DSF) is innovated to score different experimental environments. The higher the DSF score, the better the visual experience. The results show that when using the 7.5Hz SSVEP paradigm, the combination of 360Hz and 1920 × 1080 can bring the best visual experience. When using the 15Hz SSVEP paradigm, the combination of 240Hz and 1280 × 720 is the best. DSF provides powerful help for hardware and software selection guidance and vision protection when using SSVEP-based BCI applications.

Change-oriented Leadership in the Context of Transitioning to Strategic Autonomy

Growing geopolitical tensions have transformed the business landscape , driving domestic firms toward an era of strategic independence (Yale School of Management, 2024). This research examines a well-known Eastern European consulting firm that, after transitioning to an independent entity, was confronted with a new personnel assessment system. This shift necessitates a comprehensive understanding of employee readiness and resistance — fundamental concepts in change management literature (Armenakis et al., 1993). Our study incorporated quantitative methods to divide employees according to their readiness for the new system (k-means clustering, factor analysis, and discriminant analysis). At the same time, it employed qualitative research methods to explore motives and attitudes behind employee resistance or readiness (Choi &amp; Ruona, 2011). Based on their adaptability to the new system, we identified three distinct clusters of employees: “Active Supporters,” “Cautious Appraisers,” and “Conservative Skeptics,” allowing us to pinpoint specific non-readiness factors and formulate tailored strategies to address them. The findings suggest that emotional involvement, openness to change, and previous experiences with similar practices significantly influence employee readiness. To mitigate these issues, the paper proposes a strategy rooted in psychological safety and differentiated error management, as advocated by Edmondson (2023), to enhance the organization's learning capability and adaptability. Our results align with previous research indicating that stronger attitudes, often based on personal experience, significantly predict behavior (Eagly &amp; Chaiken, 1993). We found that the initial uncertainty of organizational changes served as a major stressor, underscoring the importance of understanding and conceptualizing changes (Kramer, 2015). Unlike Schwartz (1994), the value orientation of “Tradition” did not exert significant influence, but values of “Autonomy,” “Stimulation,” “Achievement” (consistent with Sortheix &amp; Lönnqvist, 2014), “Hedonism,” and “Power” positively impacted employee openness to changes. The implications of this study extend to other Eastern European companies undergoing similar transitions, providing guidance on how change can be managed effectively in the context of transitioning to strategic autonomy.

Psychological assessment and the role of the psychologist in early palliative care

BackgroundEarly palliative care (EPC) is a recommended model for improving the quality of life for patients with advanced cancer and their caregivers. However, limited research has focused on the role of psychological evaluation within EPC. The Veneto Institute of Oncology (IOV), a Comprehensive Cancer Centre, employs an interdisciplinary team to assess patients with advanced-stage disease. This study aims to assess the psychological needs of these patients, investigate any correlations between psychological symptoms (PSs) and factors such as awareness of diagnosis and prognosis, symptoms detected using the Edmonton Symptom Assessment System (ESAS), as well as the patient’s gender, age, social issues, and survival and to clarify the psychologist’s role within the interdisciplinary team.MethodsData were retrieved from a prospectively maintained database. From 1st January 2018 to 31st December 2021, 819 consecutive patients were evaluated during EPC consultations, with 753 participants enrolled in the study. The ESAS was administered to each patient before the consultation.ResultsMore than half of the patients (385, 57.1%) reported at least one PS, with an ESAS score of ≥4. Specifically, 34.9% reported depression, 28.7% reported anxiety, and 43.2% indicated feeling “not well.” Referring oncologists tended to overestimate the presence of PSs compared to patient self-reports (51.8% versus 41.3%). According to the psychologists’ assessment, 29.2% of participants were found to have depression, and 10.8% of participants had anxiety. Additionally, 31 patients (10.8%) with psychological disorders were diagnosed with an adaptation disorder related to a physical condition. The psychology service engaged 47% of patients, while 18.5% declined psychological support. Patients exhibiting other ESAS symptoms with scores of ≥4 had an increased odds ratio for reporting PSs of ≥4. However, multivariable analysis revealed no significant relationship between PSs and awareness of diagnosis and prognosis.ConclusionThe systematic use of self-assessment in EPC is essential for understanding patient’s experience, determining whether PSs stem from physical disorders, and prioritizing interventions. Awareness of prognosis does not correlate with increased anxiety and depression in patients. Therefore, EPC is an ideal opportunity to discuss prognosis and facilitate patients’ end-of-life choices early in their care journey.

Juridical Review of The Amount of Administrative Sanctions in the Form of Interest and Interest Rewards PP No 35 of 2023

This research is motivated by the tax collection system in Indonesia using the Self Assessment System. The Self Assessment System is a tax collection system in which the government gives full trust to taxpayers to calculate, deposit and report their own tax obligations. Taxpayers are considered capable of calculating taxes, able to understand the current tax regulations, and have high levels of honesty, and are aware of the importance of paying taxes. Thus, the success of tax collection depends a lot on the taxpayers themselves. The legal research method used in this research is normative juridical research which is research carried out or aimed only at written regulations with the nature of descriptive analysis research which is a method that functions to describe or provide an overview of the object being studied. The data source used is secondary data with quantitative data analysis. The results of this research are Article 113 of the Job Creation Law, taxpayers submit requests for interest compensation to the Head of the KPP where the Taxpayer is registered or where the PKP is confirmed. Submission of applications can be done electronically or in writing by including the Taxpayer's domestic account number. After the taxpayer submits a request for interest compensation to the KPP, no later than one month after the application for interest compensation is received in full, the KPP will process the Taxpayer's application. Interest compensation is paid by the Directorate General of Taxes by transferring it to the account of the Taxpayer who is entitled to receive the interest compensation, then the reporting of the receipt of the interest compensation is reported in the Annual SPT in the following tax yea

Predictive Analysis System for National Ranking and Accreditation of HEIs

Predictive analytical models have been applied in context of the Indian higher educational institutions dataset. This study is aimed to compare the predictive accuracy level of various machine learning algorithms (multi-class classification prediction algorithms) to assess the grading system applicable to a college based on various parameters outlined by NAAC (National Assessment and Accreditation Council). NAAC is an apex body to assess and accredit HEIs of India. An ensemble classification method is proposed to best predict the academic grading of university-affiliated colleges of India for the NAAC accreditation system. This maiden attempt for using PA (Predictive Analysis) on such institutional credential data would be beneficial to colleges applying for NAAC accreditation to judge their grade prior to final assessment. Thus they would be able to identify their strengths and weaknesses and eventually work towards further improving upon their grade. Such a system would pave the way for designing such predictive systems to assess the institutional rankings for several other assessment systems.

Novel nerve regeneration assessment method using adult zebrafish with crush spinal cord injury.

Zebrafish (Danio rerio), an alternative to rodents, are widely used in neurological, genetic, and toxicology research. The zebrafish larval spinal cord injury model has been used in neural mechanistic analyses owing to its high regenerative capacity and throughput; however, it also had several limitations in imitating rodents. Therefore, we investigated the use of adult zebrafish as an alternative model to rodents for evaluating nerve regeneration. Here, we established a novel spinal cord regeneration evaluation method, which was based on the maximum swimming speed of adult zebrafish in a custom-built hydrodynamic-based aquarium. The spinal cords of adult male zebrafish were crushed using forceps, and maximum swimming speed and histological spinal cord regeneration were evaluated. Spinal cord-injured zebrafish showed a significant decline in motor function, followed by recovery at 3weeks postoperatively, accompanied by histological regeneration. Spinal cord regeneration can be indirectly assessed by monitoring maximum swimming speed. They were also fed a diet containing fig extract, which can promote peripheral nerve regeneration; they were fed daily starting 1week before the operation. Maximum swimming speed was measured time-dependently until 3weeks postoperatively. Fig-consuming fish showed improved recovery of maximum swimming speed compared to the controls, which was consistent with the histological analysis. In summary, we established a spinal cord regeneration assessment system using adult zebrafish in a customized aquarium, which enables researchers to evaluate spinal cord regeneration in adult zebrafish similar to that of rodent experiments, contributing to faster and easier screening of neuroregenerative technology.

Geographic Information System and Contamination Indices for Environmental Risk Assessment of Landfill Disposal Sites in Central Saudi Arabia

Landfills pollute air, soil, and surface and groundwater worldwide. The present work aims to assess the environmental risks of three landfills in southern Riyadh using GIS, soil quality guidelines, and contamination indices. GIS tools indicated an increase in the area of the landfill sites with time. The concentration of heavy metals (HMs) in the investigated landfills had the following descending order: Fe (11,532 mg/kg) ˃ Al (5405 mg/kg) ˃ Pb (561.7 mg/kg) ˃ Zn (356.8 mg/kg) ˃ Mn (165 mg/kg) ˃ Cr (74.8 mg/kg) ˃ Cu (42.7 mg/kg) ˃ Ni (22.4 mg/kg) ˃ V (21.8 mg/kg) ˃ As (5.16 mg/kg) ˃ Co (4.08 mg/kg). The highest values of Al, As, Co, Ni, Pb, V, and Zn were recorded from Al Kharj road landfill (RL3). However, the average values of all HMs were lower than those from most worldwide soils and backgrounds, except for Zn, Cu, Cr, and Pb. Results of enrichment factor and statistical analysis indicated deficiency to minimal enrichment and geogenic sources for Al, Co, Mn, and V, while those of As, Cr, Pb, Zn, and Cu showed EF ˃ 2, which might be indicative of anthropogenic activities, especially in RL3. Additionally, very high contamination and a high effects range—median were reported in individual samples, especially for Pb, As, and Zn, indicating frequent adverse effects for these HMs. The difference in contamination for the HMs in the studied landfill sites might be attributed to the difference in the magnitude of input for each metal into the landfill site and/or the difference in the removal rate of each metal from it.

Development of Database System Principles and Applications Course based on Task-based Learning and Team-based Learning to Enhance Database Design Abilities of Second Year Students in Fujian University of Technology

Background and Aim: The undergraduate database system principles and applications course grapples with issues such as the gap between theory and practice, outdated content, and limited teaching methods. Addressing these challenges necessitates a comprehensive reform to enhance students' practical skills and adaptability to technological advancements. This study aimed to：1) study the background information focusing on course components of Database system principle and application course to enhance students’ database design ability, 2) develop a Database system principle and application course based on Task-based learning and Team-based learning to enhance students’ database design ability, and 3) determine the effectiveness of implementing the database system principle and application course based on Task-based learning and Team-based learning. Materials and Methods: The sample was second-year students majoring in Internet of Things engineering in the academic year 2023-2024 of Fujian University of Technology, the People’s Republic of China was 30 students from 1 classroom derived by cluster random sampling. The experimental design adopted in this study is a group Post-test-only design. The research instruments from each Phase of the study were as follows: Phase I: Interview forms for teachers and students on course-related questions. Phase II: 1) Database system principles and applications course based on Task-based learning and Team-based learning with a very high level of appropriateness. 2) Eight lesson plans based on Task-based learning and Team-based learning with a very high level of appropriateness. 3) An evaluation form of database design ability includes knowledge and skills. 4) a learning achievement test and 5) a student satisfaction questionnaire with a reliability of 0.897. The data were analyzed by using mean, standard deviation, and the one-sample t-test. Results: The results of the study were as follows: 1) The researchers reviewed the literature about the Database System Principles and Applications course and interviewed four teachers and 20 students for problems of the Database System Principles and Applications course, and the information gathered was used to develop the course. The database system principles and applications course in undergraduate education faces problems such as the disconnection between theory and practice, the lag in updating course content, and the single teaching method. These challenges emphasize the urgent need for comprehensive reform of the course content, teaching methods, and assessment system to enhance students' practical skills and their ability to adapt to the rapidly changing technological environment. 2) The Database System Principles and Applications Course based on Task-based Learning and Team-based Learning consisted of the principle, objective, content, instructional strategy, materials, and evaluation. 3) After implementing through Database system principles and applications course based on Task-based learning and Team-based learning, the students’ database design ability (Knowledge) was higher than the determined criterion of 70% at a significance level of .05 (M = 31.33, SD = 3.76, t = 4.825, p = .000) and the students’ database design ability (Skills) was higher than the determined criterion of 70% at a significance level of .05 (M = 45.12, SD = 2.89, t = 5.913, p = .000). 4) The students’ satisfaction was statistically higher than the determined criterion of 70% at a .05 level of statistical significance. Conclusion: To development of a task-based learning and team-based learning database system principles and applications course is significantly effective in enhancing students' database design ability.

Evolving Educational Testing to Meet Students’ Needs: Design‐in‐Real‐Time Assessment

AbstractThe goal in personalized assessment is to best fit the needs of each individual test taker, given the assessment purposes. Design‐In‐Real‐Time (DIRTy) assessment reflects the progressive evolution in testing from a single test, to an adaptive test, to an adaptive assessment system. In this article, we lay the foundation for DIRTy assessment and illustrate how it meets the complex needs of each individual learner. The assessment framework incorporates culturally responsive assessment principles, thus making it innovative with respect to both technology and equity. Key aspects are (a) assessment building blocks called “assessment task modules” (ATMs) linked to multiple content standards and skill domains, (b) gathering information on test takers’ characteristics and preferences and using this information to improve their testing experience, and (c) selecting, modifying, and compiling ATMs to create a personalized test that best meets the needs of the testing purpose and individual test taker.

Trajectories of attention problems in preschoolers born very preterm.

Children born preterm are at heightened risk for neurodevelopmental impairment, including specific deficits in attention. Few studies have investigated change over time in attention problems prior to school entry. The current study aims to describe trajectories of attention problems from age 2 through 5 years in a cohort of children born <30 weeks of gestational age (GA), identify sociodemographic, medical, and neurobehavioral characteristics associated with attention trajectories, and test whether attention problem trajectories predict the risk of a reported attention-deficit/hyperactivity disorder (ADHD) diagnosis. We studied 608 infants from the Neonatal Neurobehavior and Outcomes in Very Preterm Infants (NOVI) Study, a prospective, multisite study of infants born <30 weeks of GA. Parents reported on child attention problems at ages 2, 3, 4, and 5 years using the Child Behavior Checklist and the Behavior Assessment System for Children. Sociodemographic and medical characteristics were assessed via maternal interview and medical record review. Neurobehavioral characteristics were determined using neonatal and 2-year assessments. Parent report of child ADHD diagnosis was obtained. We used latent growth curve (LGC) modeling to test our study aims. A linear LGC model provided the best fit to the data. The average trajectory of attention problems evidenced low initial levels of symptoms and little change over time, yet there was significant heterogeneity in both initial levels and change over time. Individual differences in trajectory parameters were associated with sociodemographic, medical, environmental, and neurobehavioral characteristics. Children with higher initial levels of attention problems as well as steeper increases in attention problems over time were more likely to have a reported ADHD diagnosis. There is significant heterogeneity in trajectories of attention problems from age 2 to 5 in children born <30 weeks of GA and these differences have clinical relevance. These data could inform follow-up guidelines for preterm infants.

Turbulence correlation between moving trains and anemometer towers: Theoretical analysis, field measurements and simulation

A precise command of railway operations according to the measured instantaneous wind speed on an anemometer tower along a railway line is the development trend, whose challenges lie in the unknown transfer relation(s) between wind speed fluctuations on a moving train and an anemometer tower, i.e. the turbulence correlation between them. To address this issue, in the current work, the cross-correlation functions of wind speed fluctuations at the moving train and anemometer tower are derived, and an empirical formula of the coherence functions is obtained. The turbulence correlation is inversely related to the separation distance from the anemometer tower to the line, and there is little correlation when this distance is longer than double the longitudinal turbulence length scale. Field measurements of wind characteristics were carried out on an anemometer tower and a moving vehicle, and the turbulence correlation and its expression were validated. Three methods are proposed and compared to evaluate the instantaneous wind speed at the anemometer tower and moving train with this correlation. The methods based on the cross-spectral density and coherence function can accurately simulate the correlation, and the latter performance is slightly better (its simulation of the frequency domain correlation is 52.9% better than the former); the method based on solely independent and identically distributed random phases cannot fully simulate the correlation. From this, the effects of the correlation on train operations are studied and analysed in detail. Our analysis shows that neglecting this correlation leads to conservative estimates: wind speed differences between the anemometer tower and the moving train are at least 18.1% greater, and the safety and economic assessments of train operations in crosswinds are underestimated by at least 32.0%. Considering the correlation can reduce the (excess) safety risk/margin and is an inevitable development of adapting to the detailed assessment of the crosswind stability of vehicles. The quantitative description and simulation of the correlation presented in this work point to the critical importance of wind speed monitoring systems for the detailed crosswind assessment, and provide a theoretical basis for further research work on the crosswind stability of vehicles under true/realistic turbulent flow wind.

Remote Sensing Techniques for Assessing Snow Avalanche Formation Factors and Building Hazard Monitoring Systems

Snow avalanches, one of the most severe natural hazards in mountainous regions, pose significant risks to human lives, infrastructure, and ecosystems. As climate change accelerates shifts in snowfall and temperature patterns, it is increasingly important to improve our ability to monitor and predict avalanches. This review explores the use of remote sensing technologies in understanding key geomorphological, geobotanical, and meteorological factors that contribute to avalanche formation. The primary objective is to assess how remote sensing can enhance avalanche risk assessment and monitoring systems. A systematic literature review was conducted, focusing on studies published between 2010 and 2025. The analysis involved screening relevant studies on remote sensing, avalanche dynamics, and data processing techniques. Key data sources included satellite platforms such as Sentinel-1, Sentinel-2, TerraSAR-X, and Landsat-8, combined with machine learning, data fusion, and change detection algorithms to process and interpret the data. The review found that remote sensing significantly improves avalanche monitoring by providing continuous, large-scale coverage of snowpack stability and terrain features. Optical and radar imagery enable the detection of crucial parameters like snow cover, slope, and vegetation that influence avalanche risks. However, challenges such as limitations in spatial and temporal resolution and real-time monitoring were identified. Emerging technologies, including microsatellites and hyperspectral imaging, offer potential solutions to these issues. The practical implications of these findings underscore the importance of integrating remote sensing data with ground-based observations for more robust avalanche forecasting. Enhanced real-time monitoring and data fusion techniques will improve disaster management, allowing for quicker response times and more effective policymaking to mitigate risks in avalanche-prone regions.

An Investigation Into To The Use Of Artificial Intelligence In The Indian Tax System

Indian taxation is main source of public finance in developing economy. The Indian tax system has long been plagued by issues including tax evasion and ineffective administration. Tax administration systems must constantly be designed to reduce errors and speed up decision-making. The Indian tax system is beset by a shortage of workers to do labor-intensive duties including data input, return inspection, tax audits, etc. The Indian government recently announced the use of artificial intelligence and machine learning in the tax assessment system in order to handle the evolving tax landscape in conjunction with the use of analytics. In the field of taxes, artificial intelligence, or AI, is a relatively recent development.

Teacher support in AI-assisted exams: an experimental study to inspect the effects on demotivation, anxiety management in exams, L2 learning experience, and academic success

Although AI technologies show great promise for education, their inclusion into assessment systems has generated debates regarding student motivation, anxiety, learning opportunities, and academic results. This study explored the influence of teacher support in AI-assisted exams on L2 learners’ demotivation, anxiety, L2 learning experience, and academic success. Conducted at a large university in Ethiopia, participants included 92 BA Management students from two intact classes, equally distributed by gender and ranging in age from 18 to 23. The two intact classes were randomly divided into an experimental and a control group. Using a quantitative quasi-experimental pretest–posttest control group design, the study administered an Oxford Quick Placement Test, the Academic Motivation Scale, the Foreign Language Classroom Anxiety Scale, the L2 Learning Experience Scale, and a researcher-made test to assess academic success. The AI tools integrated into the exams included automated assessment and feedback systems to enhance learner engagement. Chi-square analyses and independent samples t-tests revealed significant positive effects of teacher support on reducing demotivation and anxiety, enhancing L2 learning experiences, and improving academic success in the experimental group compared to the control group, highlighting the benefits of combining AI tools with teacher support. These findings suggest that teacher support in AI-assisted exams can substantially benefit L2 learners. Additionally, the findings indicate that AI-assisted exams can considerably improve learning outcomes when paired with effective teacher involvement, highlighting implications for various stakeholders in L2 instruction. Implications of the study, limitations, and suggestions for future research are discussed.