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Found 6374 publications
Structural Brain Abnormalities, Diagnostic Approaches, and Treatment Strategies in Vertigo: A Case-Control Study
Publication Name: Neurology International
Publication Date: 2025-09-01
Volume: 17
Issue: 9
Page Range: Unknown
Description:
Background/Objectives: Dizziness is a frequent medical complaint with neurological, otolaryngological, and psychological origins. Imaging studies such as CT (Computer Tomography), cervical X-rays, and ultrasound aid diagnosis, while MRI (Magnetic Resonance Imaging) is crucial for detecting brain abnormalities. Our purpose is to identify structural brain changes associated with vertigo, assess pre-MRI diagnostic approaches, and evaluate treatment strategies. Methods: A case-control study of 232 vertigo patients and 232 controls analyzed MRI findings, pre-MRI examinations, symptoms, and treatments. Statistical comparisons were performed using chi-square and t-tests (p < 0.05). Results: White matter lesions, lacunar infarcts, Circle of Willis variations, and sinusitis were significantly more frequent in vertigo patients (p < 0.05). Pre-MRI diagnostics frequently identified atherosclerosis (ultrasound) and spondylosis (X-ray). Common symptoms included headache, imbalance, and visual disturbances. The most frequent post-MRI diagnosis was Benign Paroxysmal Positional Vertigo (BPPV). Treatments included lifestyle modifications, physical therapy (e.g., Epley maneuver), and pharmacological therapies such as betahistine. Conclusions: MRI revealed structural brain changes linked to vertigo. Pre-MRI assessments are essential for ruling out vascular and musculoskeletal causes. A multidisciplinary treatment approach is recommended. Trial Registration: This study was registered in ClinicalTrials.gov with the trial registration number NCT06848712 on 22 February 2025.
Open Access: Yes
Developing a machine learning-based rapid visual screening method for seismic assessment of existing buildings on a case study data from the 2015 Gorkha, Nepal earthquake
Publication Name: Bulletin of Earthquake Engineering
Publication Date: 2025-09-01
Volume: 23
Issue: 12
Page Range: 4981-5019
Description:
Each existing building is required to be assessed before an impending severe earthquake utilizing Rapid Visual Screening (RVS) methods for its seismic safety since many buildings were constructed before seismic standards, without taking into account current regulations, and because they have a limited lifetime and safety based on how they were designed and maintained. Building damage brought on by earthquakes puts lives in danger and causes significant financial losses. Therefore, the fragility of each building needs to be determined and appropriate precautions need to be taken. RVS methods are used when assessing a large building stock since further in-depth vulnerability assessment methods are computationally expensive and costly to examine even one structure in a large building stock. RVS methods could be implemented in existing buildings in order to determine the damage potential that may occur during an impending earthquake and take necessary measures for decreasing the potential hazard. However, the reliability of conventional RVS methods is limited for accurately assessing large building stock. In this study, building inspection data acquired after the 2015 Gorkha, Nepal earthquake is used to train nine different machine learning algorithms (Decision Tree Classifier, Logistic Regression, Light Gradient Boosting Machine Classifier, eXtreme Gradient Boosting Classifier, Gradient Boosting Classifier, Random Forest Classifier, Support Vector Machines, K-Neighbors Classifier, and Cat Boost Classifier), which ultimately led to the development of a reliable RVS method. The post-earthquake building screening data was used to train, validate, and ultimately test the developed model. By incorporating advanced feature engineering techniques, highly sophisticated parameters were introduced into the developed RVS method. These parameters, including the distance to the earthquake source, fundamental structural period, and spectral acceleration, were integrated to enhance the assessment capabilities. This integration enabled the assessment of existing buildings in diverse seismically vulnerable areas. This study demonstrated a strong correlation between determining building damage states using the established RVS method and those observed after the earthquake. When comparing the developed method with the limited accuracy of conventional RVS methods reported in the literature, a test accuracy of 73% was achieved, surpassing conventional RVS methods by over 40% in accurately classifying building damage states. This emphasizes the importance of detailed data collection after an earthquake for the effective development of RVS methods.
Open Access: Yes
What makes CrossFit exercise unique? Addiction, passion, or motivation?
Publication Name: Sport Sciences for Health
Publication Date: 2025-09-01
Volume: 21
Issue: 3
Page Range: 2167-2183
Description:
Background: CrossFit is one of the fastest-growing exercise regimens worldwide. Around 4 million people practice CrossFit in over 100 countries. This high-intensity training is performed with passion, often involving pain for gain, which sets CrossFit apart from most traditional exercises. Aims: Based on this premise, we aimed to test the hypothesis that the risk of exercise addiction (REA), obsessive passion (OP), harmonious passion (HP), and internal motivational regulations are greater in CrossFit than in other exercises. Methods: This study employed a between-participants research design, adopting a survey-based, cross-sectional approach. The study involved 507 participants (62.7% male), comprising 238 practicing CrossFit enthusiasts and 269 mixed exercisers classified as controls. Results: CrossFit practitioners scored significantly higher than controls on REA (Cohen’s d = 0.18) and both OP (d = 0.30) and HP (d = 0.32), but not motivational regulations. The effect sizes were small. However, after controlling for OP and HP, the group differences in REA vanished. The prevalence of “high” REA was 25.2% in the CrossFit group compared to 13.4% in the controls (p < 0.001). However, after controlling for OP and HP in a binary logistic regression, the group differences disappeared again. At the same time, OP (odds ratio [OR] = 0.795) and HP (OR = 0.653) remained statistically significant predictors in the model. Two group-by-gender interactions suggested that women in CrossFit had greater intrinsic-effective regulation and introjected regulation than controls. In comparison, men in CrossFit exhibited lesser introjected regulation compared to controls. Conclusion: The findings suggest that passion is what distinguishes CrossFit from other exercises, but gender-related differences may also exist at motivational levels.
Open Access: Yes
Using Multivariate Statistical Analysis for Examining the Relationship between Food Waste Generation and Socio-economic Factors
Publication Name: Journal of Sustainable Development of Energy Water and Environment Systems
Publication Date: 2025-09-01
Volume: 13
Issue: 3
Page Range: 1-16
Description:
Food waste contributes to social inequalities and sustainability issues by worsening resource overuse and environmental harm. The United Nations Sustainable Development Goal 17 highlights the importance of reducing food waste to address hunger and promote a sustainable, economically viable global food system. This paper examines the geographic differences in food waste levels among European Union member nations and analyses the associations between food waste and diverse environmental, geographic, social and economic indicators, including Sustainable Development Goals and other sustainability metrics. Using dimensionality reduction methods, nontrivial multivariate connections between food waste and these parameters were identified, allowing for the characterisation of countries based on a few significant factors. Principal Component Analysis (PCA), applied to food waste data across European Union countries, uncovered three distinct groups: (1) those with elevated food waste in primary production, manufacturing and distribution stages; (2) those with lower waste in these domains yet elevated waste in restaurants and households; and (3) those with all of their food waste components smaller than or equal to the average. The multivariate linear correlation between the PCA factors and socio-economic parameters is nonsignificant, but a few (nonlinear) regularities could be identified: five of the six countries of the first group above are characterised by the population settled mainly on flatland and an above-average supply of meat or fish. Another pattern observed is that former Eastern Bloc countries belong to the third group. The research findings offer valuable insights that can inform the efforts of environmental experts, professionals and policymakers working in the circular economy and waste management domains. This knowledge can facilitate the development of more effective strategies aimed at mitigating food waste and promoting sustainability.
Open Access: Yes
Mind the Net: Parental Awareness and State Responsibilities in the Age of Grooming
Publication Name: Social Sciences
Publication Date: 2025-09-01
Volume: 14
Issue: 9
Page Range: Unknown
Description:
In the digital environment, grooming—classified as a communication-based risk—has shown a steadily increasing frequency in recent years. In Hungary, increasing attention has been directed to the protection of children’s rights in the digital space in alignment with ensuring their online safety, with both parents and the state playing crucial roles in ensuring a safe digital presence. Within this context, the state bears a particular responsibility to educate not only children but also parents. This study explores how public policies and institutional programs in Hungary address the prevention of grooming and the reactive management of this harm through parental awareness. It examines existing measures aimed at expanding knowledge related to prevention and response, based on a qualitative analysis of the normative foundations of the state’s educational obligations and the relevant academic literature. The study relies on questionnaire data collected from parents of children aged 7 to 18 to examine the effectiveness of state measures and parents’ perceptions of them. The findings of the empirical research may support the development of state-led parental education programs and identify current gaps. As such, it can play a guiding role in shaping the direction of a future, large-scale investigation.
Open Access: Yes
Achieving Sustainable Supply Chains: Applying Group Concept Mapping to Prioritize and Implement Sustainable Management Practices
Publication Name: Logistics
Publication Date: 2025-09-01
Volume: 9
Issue: 3
Page Range: Unknown
Description:
Background: Sustainability in supply chain management (SCM) practices is becoming increasingly important as environmental responsibility and social concerns, as well as enterprises’ competitiveness in terms of innovation, risk, and economic performance, become increasingly urgent. This paper aims to identify and prioritize concepts for implementing sustainable supply chains, drawing on sustainable supply chain management (SSCM) and green supply chain management (GSCM) techniques. Corporate supply chain managers across various industries, markets, and supply chain segments brainstormed management practices to enhance the sustainability of their supply chains. Four industry sectors were surveyed across five different value chain segments. Methods: A group concept mapping (GCM) approach incorporating multi-dimensional scaling (MDS) and hierarchical cluster analysis (HCA) was used. A hierarchy of practices is proposed, and hypotheses are developed about achievability and impact. Results: A decision-making matrix prioritizes eight solution concepts based on two axes: impact (I) and ease of implementation (EoI). Conclusions: Eight concepts are prioritized based on the optimal effectiveness of implementing the solutions. Pattern matching reveals differences between emerging and developed markets, as well as supply chain segments, that decision-makers should be aware of. By analyzing supply chains from a multi-part perspective, this research goes beyond empirical studies based on a single industry, geographic region, or example case.
Open Access: Yes
Developing a Consistent and Transparent Corporate Sustainability Rating System with a Sector-Agnostic Approach
Publication Name: Journal of Sustainability Research
Publication Date: 2025-09-01
Volume: 7
Issue: 3
Page Range: Unknown
Description:
Background: Development of objective, quantitative sustainability reporting scores for international companies has to be based on legal, regulatory, and public policy standards as well as focused exclusively on environmental, social, and governance (ESG) issues. The key performance indicators (KPIs) developed here differ from traditional agencies’ rating schemes in that they are equally applicable across industrial sectors. They measure performance in terms of several environmental Global Reporting Initiative (GRI) indicators. The KPIs quantify performance by systematically linking corporate revenues with sustainability metrics, thereby yielding readily comparable, numerical scores. Methods: This report illustrates their utility with data on carbon dioxide (CO2 ) emissions from leading companies within the S&P Global ESG ranking for 2023. Results: The findings reveal significant gaps in managing Scope 3 emissions, which dominate the value chain and present the greatest challenge for corporate sustainability. These disparities highlight the need for improved data transparency and harmonized reporting standards to ensure consistent and actionable sustainability assessments. Conclusions: By bridging these gaps, the KPIs enable more equitable comparisons across industries and encourage better alignment of corporate strategies with global climate objectives. The additional transparency and insights in turn afford investors, managers, policy makers, and other stakeholders’ better information for their decision making.
Open Access: Yes
DOI: 10.20900/jsr20250054
Full-surface geometric analysis of DMLS-manufactured stainless steel parts after post-processing treatments
Publication Name: Results in Engineering
Publication Date: 2025-09-01
Volume: 27
Issue: Unknown
Page Range: Unknown
Description:
The study examines the geometric behavior of corrosion-resistant steel components manufactured using the DMLS (Direct Metal Laser Sintering) process after various post-treatment methods. Full-surface 3D optical scanning was used to evaluate geometric deviations before and after three different treatments: stress relief heat treatment, immediate base plate removal, and natural aging. The results showed that heat treatment amplified the distortions caused by existing residual stresses, with elliptical deformation nearly doubling (i.e., deteriorating by approximately 200 %). Immediate removal resulted in asymmetrical, teardrop-shaped distortion that exceeded the ±0.1 mm tolerance limit. Natural aging effectively stabilized the geometry, with circularity deviation remaining within the ±0.1 mm limit. The results highlight the critical role of thermal management and post-processing in ensuring the dimensional accuracy of DMLS parts. The research demonstrates the advantages of full-surface, high-precision optical metrology in the detailed analysis of shape changes occurring during additive manufacturing, with the maximum permissible error of the measuring system limited to 0.01 mm in our measurements.
Open Access: Yes
A proposed wavelet analysis based fault diagnosis scheme of power transformers using fault signatures and CT saturation
Publication Name: Results in Engineering
Publication Date: 2025-09-01
Volume: 27
Issue: Unknown
Page Range: Unknown
Description:
Diagnosis of concealed internal faults within power transformer is a key for high grid reliability to ensure continuity of power supply to customers. One of the urgent situations of power transformer is the faults under CT saturation and the operation under inrush currents that lead to huge failure of fault identification of the power transformer. In this paper, a fault identification scheme is designed using details and approximate coefficients obtained by discreet wavelet transform applied to a differential current signal under different situations. Also, this paper considers the impact of transformer internal faults such as turn to earth and turn to turn faults, external faults, and inrush currents. The signature of processing differential current is employed for identifying these fault conditions since such fault has a distinct differential current signature. The simulation tests are performed on a 115/22 kV power transformer using ATP-EMTP real-time simulator. Different wavelet families are assessed to show that the optimum mother wavelet, db1, has high fault detection and classification performance. The proposed scheme is verified for transformer energization conditions, and the influence of CT saturation is also considered in this study. Moreover, one of the most important proposed scheme features is simplicity with high lights aspects toward all fault conditions and fault types at different fault location and different fault resistances. Intensive simulation results are obtained to prove the improved selectivity and sensitivity of the proposed scheme for identifying internal transformer faults. Furthermore, sensitivity analysis is not only conducted in terms of transformer loading and fault resistance variation, but transformer scalability study is also verified. Finally, to evaluate the performance of the proposed scheme, an assessment study is adopted to show the accuracy and reliability of differential protection scheme.
Open Access: Yes
