Search Results (1,936)

This research examines the risk factors that influence injury severity in individual motorcycle accidents, utilising a dataset of 5253 incidents. Five machine learning algorithms—multinomial logistic regression, classification trees, random forests, XGBoost, and neural networks—were used to classify the results into three groups: Death (13.48%), Injury (80.14%), and No injury (6.38%). In all models, passenger presence was the most important predictor of injury. Motorcycle accidents involving passengers do not always have more serious consequences for several overlapping reasons. On the one hand, a motorcycle with a passenger has a significantly higher mass, which increases the braking distance and kinetic energy at the moment of collision, hindering quick defensive manoeuvres, cornering, and reactions to sudden hazards. Often, the rider also refrains from sudden movements to prevent the passenger from losing their balance. In the case of single-rider motorcycle accidents on roadways, approximately 5% of those involved with a passenger were fatalities, while approximately 48% were uninjured; in the case of those without a passenger, no one was uninjured. It follows from the above that the presence of a passenger increases the rider’s sense of responsibility. Other factors that significantly increased risk were single-lane carriageways, vehicle overturning, contaminated road surfaces, and collisions with complex objects, e.g., like trees. The multinomial logistic regression model had an overall accuracy of 69.2% on the test set. The Recurrent Neural Network achieved the best overall accuracy of 79.56%. Balanced accuracy, as the average between sensitivity and specificity of the RNN model for the “death” class was 68.15%, for the “injury” class—72.6%, and for the “no injury” class—96.61%. The Area Under the ROC Curve of the Recurrent Neural Networks model for “no injury” was 0.97, indicating it was very good at distinguishing between this class and the other classes. Even though it was easy to tell which cases did not involve injuries, it was still hard to tell the difference between fatal and non-fatal injuries in all models. The results support interventions tailored to specific situations, such as improved road lighting and speed control in rural areas, as well as helmet enforcement and safety measures at intersections in cities. Full article

Pediatric obesity has shown a marked upward trend over the past decade, with a particularly significant impact in certain regions, to the extent that it is increasingly regarded as a global epidemic. The factors involved in its development and progression are highly diverse and complex. From genetic predisposition to the influence of epigenetic mechanisms, environmental exposures, nutritional patterns, psychosomatic factors, and endocrinological status, current evidence highlights multiple interacting pathways contributing to excessive weight gain in children. Although numerous studies have explored specific mechanisms and interventions, there remains a need for a comprehensive synthesis that integrates recent pathophysiological insights with practical clinical implications. This narrative review was undertaken to fill this gap by summarizing and analyzing the current literature on the mechanisms underlying pediatric obesity, emphasizing novel findings and evidence-based approaches. In light of recent advances in the field, this narrative review provides a comprehensive overview of the latest pathophysiological principles associated with childhood obesity, with particular emphasis on clinically relevant aspects. The review focuses on potential strategies to mitigate the impact of modifiable risk factors and highlights current trends in clinical research. The included studies were selected to cover the most relevant evidence on genetic, epigenetic, environmental, and psychosomatic determinants of pediatric obesity, providing a synthesis that informs both research and clinical practice. Its aim is to enhance the dissemination of knowledge regarding the underlying mechanisms involved in the development of pediatric obesity. In parallel, the review addresses evidence-based therapeutic approaches that may contribute to limiting the increasing incidence of the condition and its associated complications. Expanding the scope of scientifically grounded interventions may reduce obesity-related morbidity and substantially improve long-term outcomes in pediatric populations. Full article

In order to reduce fungal contamination in grapes and increase the dehydration rate for producing raisins, the development of alternative technologies that do not compromise product safety and quality is required. This study examined the impact of innovative pre-drying methods using aqueous ozone (10 min-4.1 mg O₃ L⁻¹) and UV-C light (30.3 kJ m⁻² UV-C) on the incidence of Aspergillus carbonarius, as well as on air-drying kinetics and ultrastructure of epicuticular waxes in Sultanina grapes, when applied either individually or sequentially. The effect of the pre-treatments on the colour of the dehydrated grapes was also assessed. Grapes pre-treated with 30.3 kJ m⁻² UV-C and 10 min-4.1 mg O₃ L⁻¹ + 30.3 kJ m⁻² UV-C showed a lower incidence of A. carbonarius in storage at 20 ± 1 °C than those exposed to aqueous ozone (30 and 8% lower infection compared to the non-pretreated fruit at 15-day storage, respectively). Although the combined pre-treatment did not significantly improve the fungus inhibition with respect to the individual UV-C application, it allowed a higher dehydration rate during the drying process at 60 ± 1 °C. The drying time was reduced by ~31% compared to non-pretreated fruit, a result slightly lower than that achieved with the traditional chemical pre-treatment of ethyl oleate-K₂CO₃ (~39%). This enhancement in drying rate was partly attributed to marked alterations in the grape’s epicuticular wax layer. UV-C and the combined pre-treatment helped in reducing the browning of raisins. Therefore, the combined application of ozone and UV-C light could be an environmentally friendly alternative for both improving the microbiological quality of grapes and accelerating the drying process. Full article

The continuous emission of persistent and bioaccumulative pollutants into aquatic environments has become a critical global issue. Among these, per- and polyfluoroalkyl substances (PFASs) are of particular concern due to their exceptional stability, extensive industrial use, and adverse impacts on ecosystems and human health. Their resistance to conventional physical, chemical, and biological treatments stems from the strength of the carbon–fluorine bond, which prevents efficient degradation under standard conditions. This review provides a concise and updated assessment of emerging advanced oxidation processes (AOPs) for PFAS remediation, with emphasis on heterogeneous photocatalysis and electrochemical oxidation. Photocatalytic systems based on In₂O₃, Bi-based oxyhalides, and Ga₂O₃ exhibit high PFAS degradation under UV light, while heterojunctions and MOF-derived catalysts improve defluorination under solar irradiation. Electrochemical oxidation—particularly using Ti₄O₇ reactive electrochemical membranes and BDD anodes—achieves near-complete mineralization with comparatively low specific energy demand. Energy consumption (E_EO) was calculated from literature data for UV- and simulated-solar-driven photocatalytic systems, enabling a direct comparison of their energy performance. Although solar-driven processes offer clear environmental advantages, they generally exhibit higher E_EO values, mainly due to lower apparent quantum yields and less efficient utilization of the incident solar photons compared to UV-driven systems. Hybrid systems coupling photocatalysis and electro-oxidation emerge as promising strategies to enhance degradation efficiency and reduce energy requirements. Overall, the review highlights key advances and future research directions toward scalable, energy-efficient, and environmentally sustainable AOP-based technologies for PFAS removal. Full article

Neospora caninum, the causative agent of abortion in cattle, has a major economic impact worldwide. This review aims to provide an overview of key advances over the last 10 years in understanding host−pathogen interactions, molecular mechanisms, and emerging control strategies and puts them into a context with previously published important findings. More recently, novel diagnostic tools with improved sensitivity and specificity have been developed. These have supplemented the already existing methods to detect infection in clinical cases and are essential for investigations on parasite distribution, disease incidence and prevalence, and transmission of N. caninum. Epidemiological studies have revealed the influence of environmental, genetic, and ecological factors on parasite transmission dynamics, and emphasized the importance of integrated “One Health” strategies. Characteristics of different Neospora strains have been elucidated through animal models and molecular tools such as clustered regularly interspaced short palindromic repeats/CRISPR associated protein 9 (CRISPR/Cas9)-based gene editing, high-throughput sequencing, and advanced proteomics, aiming to shed light on stage-specific gene regulation and virulence factors, contributing to the development of interventions against neosporosis. Insights into immune modulation, immune evasion, and parasite persistence contributed to the efforts towards vaccine development. In terms of therapeutics, both repurposed drugs and more targeted inhibitors have shown promising efficacy in reducing parasite burden and mitigating vertical transmission in laboratory models. Here, more recent innovations in nanoparticle-based drug delivery systems and immunomodulatory strategies are prone to enhancing therapeutic outcomes. However, a significant challenge remains the integration of molecular and immunological insights into practical applications. Full article

The optical properties of greenhouse cover materials play a critical role in controlling the internal light environment, directly affecting photosynthetic performance and crop productivity. This study evaluates the impact of a high photosynthetically active radiation (PAR) transmittance and high-light-diffusivity polyethylene film on the microclimate, photosynthetic activity, yield, and disease incidence of cucumber (Cucumis sativus L.) crops grown in a Mediterranean passive solar greenhouse. Trials were conducted over two consecutive autumn–winter seasons using a multi-span greenhouse divided into two sectors: one covered with an experimental high-transmittance film and the other with a standard commercial plastic. The experimental cover increased PAR transmission by 8.7% and 11.6% at canopy level in the first and second seasons, respectively, leading to improvements in leaf-level net photosynthesis of 9.3% and 17.9%. These effects contributed to yield increases of 5.0% and 17.3% in the respective seasons. The internal air temperature rose by up to 1.3 °C without exceeding critical thresholds, and no significant differences were observed in plant morphology or fruit quality between treatments. Additionally, the experimental film reduced the incidence of major fungal diseases, particularly under higher disease pressure conditions. The use of high-PAR-transmittance films enhances radiation use efficiency and crop performance in resource-limited environments without increasing energy inputs. This approach offers a sustainable, low-cost strategy to improve yield and disease resilience in protected cropping systems under passive climate control. Full article

Urban intersections are critical nodes for roadway safety, congestion management, and autonomous vehicle coordination. Traditional traffic control systems based on fixed-time signals and static sensors lack adaptability to real-time risks such as red-light violations, near-miss incidents, and multimodal conflicts. This study presents a grid-enabled framework integrating computer vision and machine learning to enhance real-time intersection intelligence and road safety. The system overlays a computational grid on the roadway, processes live video feeds, and extracts dynamic parameters including vehicle trajectories, deceleration patterns, and queue evolution. A novel active learning module improves detection accuracy under low visibility and occlusion, reducing false alarms in collision and violation detection. Designed for edge-computing environments, the framework interfaces with signal controllers to enable adaptive signal timing, proactive collision avoidance, and emergency vehicle prioritization. Case studies from multiple intersections typical of US cities show improved phase utilization, reduced intersection conflicts, and enhanced throughput. A grid-based heatmap visualization highlights spatial risk zones, supporting data-driven decision-making. The proposed framework bridges static infrastructure and intelligent mobility systems, advancing safer, smarter, and more connected roadway operations. Full article

The problem was recently reported that the far-zone electromagnetic momentum of light produced by scattering on a spatially anisotropic random medium can be the same at every azimuthal angle of scattering. Here, we extend the analysis to focus on the possibility of producing a rotationally symmetric spectral degree of coherence (SDOC) generated by scattering by an anisotropic process. The necessary and sufficient conditions for producing such a SDOC in the far zone are derived when a polychromatic electromagnetic plane wave is scattered by an anisotropic Gaussian Schell-model medium. We find that, unlike the generation of a rotationally symmetric momentum flow, it is not enough to simply restrict the structural characteristics of the medium and the incident light source to achieve a SDOC with rotational symmetry. An additional and essential requirement is that the azimuthal angles of scattering corresponding to the two observation points of the SDOC must be constrained to be equal. Only when all these constraints are satisfied simultaneously can a rotationally symmetric electromagnetic SDOC generated by scattering by an anisotropic process be realized. In addition, we find that although the medium parameter conditions for generating a rotationally symmetric SDOC and a rotationally symmetric momentum flow are completely different, it remains possible that the SDOC and the momentum flow produced by a spatially anisotropic medium can still simultaneously exhibit rotational symmetry, provided that the distribution of the correlation function of the scattering potential of the medium is isotropic in the plane perpendicular to the incident direction. Our results not only contribute to a deeper understanding of the far-field distribution of light scattering on an anisotropic scatterer, but also have potential applications in light-field manipulation and in the inverse scattering problem. Full article

The detection of chiral properties is crucial for pharmacology and biochemistry, yet standard circular dichroism spectroscopy suffers from low sensitivity when probing minute sample volumes. While complex asymmetric chiral nanostructures can enhance these Circular Dichroic (CD) signals, their fabrication is intricate and costly. In this work, we analyzed an alternative based on extrinsic chirality in achiral square arrays of plasmonic circular NHAs realized via Displacement Talbot Lithography (DTL), thus exploring the chiroptical response arising from symmetry breaking induced by oblique illumination. Unlike isolated nanoparticles, nanohole arrays (NHAs) support propagating Surface Plasmon Polaritons (SPPs), allowing for unique light confinement capabilities essential for high-throughput sensing. A careful characterization in terms of Stokes parameters has been performed over a selected range of different optical angles of incidence and sample orientation to disentangle extrinsic chiral contribution from spurious effects related to sample imperfections. By optimizing such extrinsic chiral contributions, enhanced chiroptical response could be engineered by significantly amplifying the interaction between light and chiral biomolecules trapped within the holes. This methodology establishes DTL-fabricated achiral NHAs as an ultrasensitive, cost-effective platform for the detection and discrimination of enantiomers in biosensing applications. Full article

The rapid advancement of autonomous vehicle systems (AVS) has introduced complex challenges to road safety. While some studies have investigated the contribution of factors influencing AV-involved crashes, few have focused on the impact of vehicle-specific factors within AVS on crash outcomes, a focus that gains importance due to the absence of a human driver. To address this gap, the advanced machine learning algorithm, LightGBM (v4.4.0), is employed to quantify the potential effects of vehicle factors on crash severity and collision types based on the Autonomous Vehicle Operation Incident Dataset (AVOID). The joint effects of different vehicle factors and the interactive effects of vehicle factors and environmental factors are studied. Compared with other frequently utilized machine learning techniques, LightGBM demonstrates superior performance. Furthermore, the SHapley Additive exPlanation (SHAP) approach is employed to interpret the results of LightGBM. The analysis of crash severity revealed the importance of investigating the vehicle characteristics of AVs. Operator type is the most predictive factor. For road types, highways and streets show a positive association with the model’s prediction of serious crashes. Crashes involving vulnerable road users can be attributed to different factors. The road type is the most significant factor, followed by precrash speed and mileage. This study identifies key predictive associations for the development of safer AV systems and provides data-driven insights to support regulatory strategies for autonomous driving technologies. Full article

Multilayer liquid crystal devices can offer enhanced optical functionalities for augmented reality and photonic applications, but fabrication remains severely limited by solvent incompatibility between photoalignment materials and underlying polymerized layers. Conventional photoalignment agents use aggressive solvents like N,N-dimethylformamide that damage polymerized substrates, necessitating protective interlayers. This study demonstrates a water-soluble photoalignment approach using AbA-2522 that eliminates these fabrication barriers. The water-soluble alignment material enables direct multilayer processing without layer damage while maintaining alignment quality equivalent to conventional materials. We successfully fabricate compact transmissive devices integrating liquid crystal polarization gratings with quarter-wave plates, achieving a first-order diffraction efficiency of 65.4% for 9 μm period gratings for linearly polarized incident light (λ = 457 nm). The multilayer structure exhibits highly selective polarization-dependent diffraction with efficiency ratios exceeding 10:1 between preferred and suppressed orders, eliminating external polarization control elements. Polarized optical microscopy confirms excellent alignment uniformity, while the fabrication process offers environmental benefits and reduced complexity. This approach establishes a practical pathway for advanced multilayer photonic devices critical for next-generation augmented reality systems and photonic integration, addressing fundamental challenges that have limited multilayer liquid crystal device development. Full article

This study theoretically investigates the nonlinear optical response of asymmetric dielectric structures embedded with graphene and demonstrates tunable optical bistability in the terahertz frequency range. Our findings reveal that the bistable behavior can be effectively modulated by varying the incident angle, the working wavelength, and the thickness and permittivity of the dielectric layers. In symmetric dielectric configurations, transmittance is enhanced, whereas in asymmetric structures, it is reduced. The thresholds of optical bistability decrease with increasing wavelength of the incident light, while they increase with thicker dielectric layers or higher permittivity of the dielectric medium. Furthermore, widening the bistability range can be achieved by increasing the incident angle. The proposed asymmetric graphene–dielectric layered structure offers a promising platform for the development of advanced terahertz active photonic devices, including optical modulators, optical switches, and mid-infrared functional components. Full article

Paraneoplastic neurological syndromes (PNSs) are immune-mediated disorders caused by an antitumor response that cross-reacts with the nervous system, leading to severe and often irreversible neurological disability. Once considered exceedingly rare, PNSs are now increasingly recognized owing to the identification of novel neural autoantibodies, wider use of commercial testing, and the emergence of immune checkpoint inhibitor (ICI)-related neurotoxicity that phenotypically overlaps with classic PNS. In this narrative review, we performed a structured search of PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar, without date restrictions, to summarize contemporary advances in the epidemiology, pathogenesis, diagnosis, and management of PNS. Population-based data show rising incidence, largely reflecting improved ascertainment and expanding indications for ICIs. Pathogenetically, we distinguish T-cell-mediated syndromes associated with intracellular antigens from antibody-mediated disorders targeting neuronal surface proteins, integrating emerging concepts of molecular mimicry, tumor genetics, and HLA-linked susceptibility. The 2021 PNS-Care criteria are also reviewed, which replace earlier “classical/non-classical” definitions with risk-stratified phenotypes and antibodies, and demonstrate superior diagnostic performance while underscoring that “probable” and “definite” PNS should be managed with equal urgency. Newly described antibodies and methodological innovations such as PhIP-Seq, neurofilament light chain, and liquid biopsy are highlighted, which refine tumor search strategies and longitudinal monitoring. Management principles emphasize early tumor control, prompt immunotherapy, and a growing repertoire of targeted agents, alongside specific considerations for ICI-associated neurological syndromes. Remaining challenges include diagnostic delays, limited high-level evidence, and the paucity of validated biomarkers of disease activity. Future work should prioritize prospective, biomarker-driven trials and multidisciplinary pathways to shorten time to diagnosis and improve long-term outcomes in patients with PNS. Full article

Ellipsometric mapping measurements and Bayesian evaluation were performed with a non-collimated, imaging ellipsometer using an LCD monitor as a light source. In such a configuration, the polarization state of the illumination and the local angle of incidence vary spatially and spectrally, rendering conventional spectroscopic ellipsometry inversion methods hardly applicable. To address these limitations, a multilayer optical forward model is augmented with instrument-specific correction parameters describing the polarization state of the monitor and the angle-of-incidence map. These parameters are determined through a Bayesian calibration procedure using well-characterized Si-SiO₂ reference wafers. The resulting posterior distribution is explored by global optimization based on simulated annealing, yielding a maximum a posteriori estimate, followed by marginalization to quantify uncertainties and parameter correlations. The calibrated correction parameters are subsequently incorporated as informative priors in the Bayesian analysis of unknown samples, including polycrystalline–silicon layers deposited on Si-SiO₂ substrates and additional Si-SiO₂ wafers outside the calibration set. The approach allows consistent propagation of calibration uncertainties into the inferred layer parameters and provides credible intervals and correlation information that cannot be obtained from conventional least-squares methods. The results demonstrate that, despite the broadband nature of the RGB measurement and the limited number of analyzer orientations, reliable layer thicknesses can be obtained with quantified uncertainties for a wide range of technologically relevant samples. The proposed Bayesian framework enables a transparent interpretation of the measurement accuracy and limitations, providing a robust basis for large-area ellipsometric mapping of multilayer structures. Full article

This study aimed to assess the impact of gradual versus abrupt light–dark transitions on the pectoral muscle, heart, tibia, and eye tissues of broilers, focusing on rearing disorders. A total of 270 male broiler chicks (ROSS-308) were divided into three groups according to the type of light transition: abrupt, 30-min gradual, and 1-h gradual changes in light intensity. The broilers were reared for six weeks, after which samples were collected for gross examination, morphometric and histomorphometric measurements, and histopathological analysis of the pectoral muscle, heart, tibia, and eye. White striping incidence in the pectoral muscle was not significantly affected by light–dark transition type. Results indicated that broilers in the 30-min gradual transition group had a higher relative heart weight than those in the abrupt-transition group (p < 0.05), although the RV/TV ratio did not differ. Tibial measurements, including weight, length, and cortical index, showed no differences across groups. Broilers exposed to a 1-h gradual transition between light and dark periods showed significantly greater eye weights compared to both the birds in the abrupt transition group and the birds in the 30-min transition group (p < 0.01). Overall, gradual light transitions did not substantially affect pectoral muscle or bone health but had minor effects on heart and eye weights in broilers reared under intensive production systems. Full article