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Found 6278 publications
Simulation of the Turning Assistant in Road Traffic Accident Reconstruction
Publication Name: Future Transportation
Publication Date: 2026-02-01
Volume: 6
Issue: 1
Page Range: Unknown
Description:
The accurate simulative reconstruction of blind spot accidents requires innovative simulation methods. The objective of this paper is to analyze the avoidability of a specific blind spot accident and assess the impact of various parameters as if an active turning assistant had been installed in the truck. Additionally, it proposes a novel adaptation of the turning assistant system, along with an adapted simulation model tailored for drawbar trailers. The analyses presented in this paper were performed using PC-Crash accident simulation software, applying the “Active Safety” module. After performing a simulation of an accident involving a right-turning truck with a center axle trailer and a pedestrian, the avoidability of the accident was examined by simulating the scenario as if the truck involved in the accident had been equipped with an active turning assistant system. Subsequently, a parameter analysis was conducted to analyze the effect of changes in the active turning assistant’s parameters and changes in the pedestrian’s direction of entry on the avoidability of the accident. In doing so, we determined the parameters for the worst-case (collision) and the best-case (no collision) scenarios. Finally, an adaptation and further development of the active turning assistant, along with a corresponding simulation method for drawbar trailers, are proposed.
Open Access: Yes
Noise, Vibration, and Harshness (NVH) Challenges in Hydrogen Internal Combustion Engine Vehicles
Publication Name: Energy Science and Engineering
Publication Date: 2026-02-01
Volume: 14
Issue: 2
Page Range: 1067-1080
Description:
This paper presents a state-of-the-art literature review on noise, vibration, and harshness (NVH) in hydrogen-fuelled internal combustion engines. Studies published between 2011 and 2025 were screened, covering fundamental flame physics, test-bench work, and recent prototype vehicles. The review links hydrogen's core properties—high flame speed, wide flammability, low ignition energy, strong diffusivity—to specific NVH outcomes such as rapid pressure rise, knock, back-fire, and block resonance. For each pathway we summarise measured noise levels, vibration signatures, and psycho-acoustic findings. Mitigation methods are then grouped: lean premixing, direct injection, adaptive ignition timing, exhaust tuning, and structural damping. Results show that, with these measures, hydrogen engines can approach the NVH envelope of modern gasoline units. Remaining gaps lie in long-term durability under high-frequency loading and in full-vehicle sound quality. Overall, the review clarifies current knowledge, highlights consistent trends, and points to research still needed for quiet, smooth hydrogen mobility.
Open Access: Yes
DOI: 10.1002/ese3.70400
Exercise addiction revisited: From symptoms to treatment
Publication Name: Theory and Psychology
Publication Date: 2026-02-01
Volume: 36
Issue: 1
Page Range: 68-89
Description:
This paper critically examines “exercise addiction,” a form of dysfunctional exercise behavior often mischaracterized as “exercise dependence.” While dependence is part of addiction, compulsion plays an equally significant role. Unlike substance-based addictions, exercise addiction involves delayed gratification achieved through intense physical effort. It often includes a masochistic drive to uphold self-imposed personal standards or maintain a positive social image. This addiction presents unique symptoms and significant challenges in assessment, as evaluations among healthy exercisers only yield questionnaire-based “risk” scores. The rate at which such high-risk scores turn into morbidity is unknown. Thus, the literature can be misleading via an artificial connection between research-based risk scores and clinically problematic cases. Indeed, such cases typically surface in clinics, not research settings. This complex and diverging path between research endeavors and applied medicine hinders the gathering of robust evidence for exercise addiction being a mental dysfunction, which is the reason why it is currently not classified as a dysfunction in the DSM-5. This paper clarifies exercise addiction and presents evidence for problematic cases based on symptoms and areas of self-harm. Furthermore, the paper distinguishes between commitment and addiction to exercise, presenting the most common theoretical models for exercise addiction. Finally, the work forwards a hierarchical 10-stage treatment framework. Overall, the paper emphasizes the urgent need for close collaboration between researchers and clinicians to accurately classify and address this complex behavioral disorder.
Open Access: Yes
Assessment of soil erosion patterns in Maharloo watershed using remote sensing techniques and early warning signals
Publication Name: Journal of Arid Environments
Publication Date: 2026-02-01
Volume: 232
Issue: Unknown
Page Range: Unknown
Description:
This study assessed the soil erosion dynamics in Iran's Maharloo watershed using remote sensing indices (Normalized Difference Vegetation Index (NDVI), Normalized Difference Salinity Index (NDSI), and Topsoil Grain Size Index (TGSI)) and machine learning models (RF, SVM, and BRT). Landsat 8 satellite images (2005–2024) were processed via the Google Earth Engine, with field validation ensuring accuracy. Among the indices, TGSI (R2 = 0.86), NDSI (R2 = 0.89), and NDVI (R2 = 0.87) showed the strongest correlations with ground data (Rain, Soil and Vegetation). The RF outperformed the other models (AUC = 0.89), identifying the central and western regions as warning erosion zones. Breakpoint analysis revealed abrupt changes in NDVI and NDSI (2013), while early warning signals (autocorrelation, variance, and skewness) indicated an escalating erosion warning, particularly near wetlands and rainfed fields. Spatial trends highlighted significant NDVI declines (Kendall's τ = 0.69) in wetland peripheries and NDSI increased (τ = 0.52) in northern farmlands. These findings underscore the efficacy of integrating machine learning and remote sensing for erosion monitoring, providing actionable insights for land management and conservation strategies.
Open Access: Yes
US financial stress, regional spillovers, and global economic policy uncertainty
Publication Name: Finance Research Letters
Publication Date: 2026-02-01
Volume: 89
Issue: Unknown
Page Range: Unknown
Description:
We study how financial stress originating in the United States (US), Advanced Economies (ADV), and Emerging Markets (EM) relates to movements in Economic Policy Uncertainty (EPU). Using monthly data for 2000-2024, we estimate horizon-specific responses to ΔEPU to one-standard-deviation innovations in ΔFinancial Stress Index (FSI) via Jordà (2005) local projections with four lags and standard controls ΔBloomberg Commodity Index (BCOM), ΔFederal Funds Rate (FEDFUNDS), ΔU.S. Dollar Index (DollarIdx), ΔCBOE Volatility Index (VIX). Across regions, the impact coefficient is negative,indicating that stress shocks are associated with an immediate reduction in the month-over-month change of EPU. Beyond impact, responses are small in magnitude, yielding limited persistence; cumulative effects over six months are modest and typically encompassed by wide confidence bands. Taken together, the evidence suggests that policy-uncertainty index adjusts quickly to stress realizations, with little systematic propagation at monthly horizons. This transience is most consistent with information/communication channels whereby policy guidance and rapid market repricing compress subsequent uncertainty innovations, while allowing for regional heterogeneity.
Open Access: Yes
Data-Driven Planning for Casualty Evacuation and Treatment in Sustainable Humanitarian Logistics
Publication Name: Algorithms
Publication Date: 2026-02-01
Volume: 19
Issue: 2
Page Range: Unknown
Description:
After large-scale disasters, swift and robust humanitarian logistics are crucial to provide timely assistance to injured people and displaced individuals. This study proposes a bi-objective optimization model for humanitarian logistics network design to simultaneously consider the facility location-allocation decisions, along with the transportation operation issues under uncertainty. The framework addresses the needs of both severely and mildly injured casualties and homeless populations. A hybrid robust optimization approach is accordingly developed that incorporates scenario-based, box-type, and polyhedral uncertainty representations to handle the uncertainty of factors such as casualty volume, travel times, facility failures, and demands for resources. More recently, machine learning methods have been applied to classify casualties and displaced individuals with respect to their geographic distribution and severity, further improving demand estimates and operational efficacy. This study seeks to develop a data-driven and robust optimization framework for designing humanitarian logistics networks under uncertainty, enabling decision-makers and emergency planners to gain insights into enhancing casualty evacuation, medical treatment, and shelter allocation in disaster response operations. The case of the Kermanshah earthquake in Iran is used for assessing the applicability of the model. The computational experiments and comparative analyses conducted show that the developed model exhibits high efficiency and robustness. The results are useful for guiding disaster preparedness and strategic decisions in humanitarian logistics. Besides operational performance, the model optimizes sustainability in the area of emergency response based on cost efficiency and social fairness, as underlined by SDGs 3 and 11.
Open Access: Yes
DOI: 10.3390/a19020104
Parents’ first aid knowledge and educational expectations based on a study conducted in Győr-Moson-Sopron county
Publication Name: Orvosi Hetilap
Publication Date: 2026-02-01
Volume: 167
Issue: 7
Page Range: 265-273
Description:
Introduction: Childhood injuries are among the leading causes of mortality worldwide and in Hungary. The quality of first aid provided by laypeople has a fundamental impact on survival rates. Objective: To assess parents’ knowledge of first aid, to explore their need for further practical training, and to determine whom they consider the most reliable source of such knowledge. Method: During our quantitative research conducted in Győr-Moson-Sopron county, we used a self-designed, online, anonymous questionnaire (n = 545) and performed descriptive statistical analyses. Associations were examined using the chi-square test and binary logistic regression (p<0.05). Results: The majority of parents (94.3%) possess basic, primarily theoretical first aid knowledge; however, this knowledge is often incomplete or outdated. The greatest deficiencies were in the practical application of cardiopulmonary resuscitation and in the airway obstruction caused by foreign bodies. The majority of respondents (93.4%) would be willing to learn from paramedics (84.9%), health visitor (60%), registered nurses (57.6%), physicians (56.4%). Based on the association analyses, first aid experience gained in real-life emergency situations was significantly associated with self-reported willingness to intervene (p = 0.012) as well as with a more favorable self-assessment of first aid competence (p<0.001). According to the results of the binary logistic regression, having an official, examination-based first aid qualification was an independent predictor of having provided first aid in a real-life emergency situation; among respondents without such qualification, the odds of providing first aid were reduced by approximately half (OR = 0.516; p = 0.001; 95% CI: 0.345–0.774). Conclusion: The goal is to clarify the knowledge of parents and provide training in practical skills from professionals. Both formal first aid training and practical experience play a decisive role in shaping the willingness to intervene in real-life emergency situations as well as self-confidence. These findings support the need for structured, practice-oriented first aid education among parents. Orv Hetil. 2026; 167(7): 265–273.
Open Access: Yes
Experimental investigation and finite element analysis of varying bitumen content in asphalt mixtures
Publication Name: Discover Applied Sciences
Publication Date: 2026-02-01
Volume: 8
Issue: 2
Page Range: Unknown
Description:
The percentage of bitumen in asphalt mixtures plays a crucial role in determining pavement performance throughout its service life. This study investigates the effect of varying bitumen contents on the mechanical behaviour and durability of asphalt mixtures. Three mixtures containing 4.7%, 5.1%, and 5.5% bitumen binder were evaluated through a comprehensive set of laboratory tests, including Marshall stability and flow, semi-circular bending, pressure aging vessel, wheel rutting, dynamic modulus, creep compliance, and fatigue performance tests, supported by finite element modeling. The nonlinear plastic behaviour and damage evolution were analyzed using the Perzyna-type viscoplastic model and Lemaitre’s isotropic damage model. Results indicate that mixtures with lower bitumen content (4.7%) exhibit earlier fatigue damage, while higher bitumen content (5.5%) leads to increased rutting and creep compliance. The 5.1% bitumen mixture demonstrated the most balanced performance, showing 40% less induced plastic strain damage than the 4.7% mixture and 27% less than the 5.5% mixture.
Open Access: Yes
Preference using Root Value based on Aggregated Normalizations (PROVAN): A data-driven method for socio-economic and innovation assessment
Publication Name: Socio Economic Planning Sciences
Publication Date: 2026-02-01
Volume: 103
Issue: Unknown
Page Range: Unknown
Description:
Socio-economic development (SED) remains a critical priority for policymakers aiming to foster inclusive growth and drive national progress. This study presents a comprehensive multi-criteria assessment of regional SED across 16 Indian states, focusing on the influence of innovation (INV) performance and foreign direct investment (FDI) on achieving sustainable development goals (SDGs). A new multi-criteria decision-making (MCDM) method, called Preference using Root Value based on Aggregated Normalisations (PROVAN), is introduced in this paper to enhance decision accuracy by integrating five different normalization techniques. Criteria weights are determined using an extended version of Weights by ENvelope and SLOpe (WENSLO) method, which incorporates multiple normalization strategies to improve robustness. The evaluation considers nine SED and seven INV criteria derived from secondary data sources. The causal relationships are statistically analyzed using Somer's δ test, and the model's reliability is confirmed through comparative and sensitivity analyses. Results reveal that Maharashtra emerges as the top-performing state in both SED (1.5572) and INV (1.5473), followed by Tamil Nadu and Karnataka, indicating strong performance across socio-economic and innovation indicators. The findings highlight significant inter-state disparities and confirm that states with stronger innovation capabilities tend to achieve better socio-economic outcomes. FDI is shown to positively influence sustainable economic development, reinforcing the strategic importance of attracting capital to advance SDGs. The proposed PROVAN-WENSLO framework offers a robust and adaptable tool for regional development planning and policy formulation.
Open Access: Yes
