Search Results (37,650)

Background: Javelin throw performance is strongly influenced by the coordination of the kinetic chain and by key biomechanical parameters related to technique execution. Understanding the functional biomechanical characteristics of javelin throw technique in junior athletes is essential for optimizing performance. Methods: This study investigated the biomechanical characteristics of javelin throw technique in junior athletes using an applied motion analysis approach. Kinematic, spatiotemporal, and performance-related variables were assessed during throwing trials at two evaluation time points, before and after a structured biomechanics-informed training period, using motion analysis tools and wearable measurement systems as instruments. Results: Significant pre–post changes were observed in technique-related variables (release angle and coordination indices) and in performance outcomes (throwing distance and ball throw speed). Conclusions: These findings highlight the functional relationships between biomechanical technique variables and javelin throw outcomes in junior athletes and suggest that field-based biomechanical monitoring can be useful for tracking technique-related changes during structured training in junior throwers. Full article

In this paper, the authors have analytically and experimentally investigated the friction torque in an angular contact ball bearing (ACBB) considering the following configurations: (i) a modified ball bearing with three equidistantly positioned balls without a cage and (ii) three modified ball bearings having four, six and eight balls with a phenolic cage. The experimental tests were realised at a low axial load and a rotational speed between 100 and 500 rpm under lubricated conditions. The test results for the ACBB with three balls without a cage showed that the friction torque is generated only by the rolling contacts between the balls and the two raceways in lubricated conditions. Considering the low axial load, the influence of the hydrodynamic rolling resistance was the dominant source of the frictional torque. The cage presence added supplementary friction, causing the friction torque to increase up to 60–65% compared to the cage-less configuration. Also, an additional increase in the frictional torque by 35–40% was observed for every two additional balls. The friction torque component that is generated by the cage presence does not depend on the number of balls added but rather on the rotational speed. All the tests were performed using the spin-down methodology, and the resulting friction torques (T_exp) were determined by integrating the dynamic equation during the deceleration process using Python-based software (Python version 3.10). The input and output parameters are presented for each test. Logarithmic diagrams revealing the dependence between the experimental friction torque and angular speed were obtained and fitted, and the relations have been determined for all tests. The analytical results of the friction torque were obtained based on Houpert’s model for all modified ball bearing configurations. Full article

Nanostructured calcium phosphate-based (CaP) biocomposites have proven to be ideal candidates for the creation of multifunctional systems with applications in biomedicine. This review presents a critical and integrative overview of recent advances in the synthesis of CaP nanocomposites with applications in bone tissue regeneration. An analysis of calcium phosphate-based nanocomposites is thus provided by correlating their composition, synthesis routes and biological properties, guiding the rational development of next-generation biomaterials for bone tissue engineering. The first section presents calcium phosphates, such as hydroxyapatite (HAp) or β-tricalcium phosphate (β-TCP), used in the preparation of nanocomposite materials. Next, the main biocomposite materials are analyzed as a result of the functionalization of calcium phosphates by metal ion substitutions or by the addition of polymers, bioglass or metal additives. Thus, biomaterials with excellent properties in applications such as tissue engineering have been obtained. The synergistic effect of materials in the composition of biocomposites favored the improvement of properties such as bioactivity, mechanical strength, antimicrobial activity, structure and porosity. Beyond classical osteoconductivity, CaP-based nanocomposites demonstrate a broad spectrum of biological activities like immunomodulatory effects, pro-healing signaling, anti-inflammatory pathways, antibacterial and antifungal mechanisms, and capabilities for precise drug delivery or theranostic applications. Full article

Soft-ground-story configurations in high-rise buildings present a critical vulnerability during seismic events, often leading to disproportionate structural damage and collapse. This study focuses on the systematic identification of soft-ground-story high-rise structures in Bucharest, a city located in a high seismic hazard zone influenced by Vrancea intermediate-depth earthquakes. The research employs a multi-step methodology combining field surveys, structural documentation, and analysis of architectural layouts from various sources to detect soft-ground-story irregularities across the urban building stock in Bucharest. The findings reveal that such configurations remain prevalent in mixed-use structures along major boulevards, where open ground floors were historically favoured for commercial purposes. The results provide a database of soft-ground-story high-rise buildings in Bucharest, highlighting their prevalence in distinct urban districts and their potential impact on seismic risk. Quantitative screening indicators, vertical element area ratio and mean axial stress in ground-story columns, are proposed for rapid vulnerability assessment. Dynamic measurements confirm a 33–38% increase in fundamental eigenperiods after the 1977 earthquake, indicating moderate-to-extensive damage states. These findings underscore the urgent need for targeted retrofitting strategies and inform seismic risk mitigation policies. The study provides a foundation for future integration of advanced diagnostic tools, such as image-based deep learning and vibration monitoring, into citywide seismic resilience planning. Full article

Background: Acute cholecystitis, a leading cause of urgent surgical intervention, poses challenges in predicting severity and operative complexity. This study characterized the immuno-inflammatory profile distinguishing acute from chronic cholecystitis and assessed whether blood-derived ratios—neutrophil-to-lymphocyte (NLR), monocyte-to-lymphocyte (MLR), and platelet-to-lymphocyte (PLR)—correlate with histologic severity and surgical difficulty. Methods: The study retrospectively analyzed 759 patients undergoing cholecystectomy from 2016 to 2024. Inflammatory indices from preoperative bloodwork were compared across histopathologic subtypes (catarrhal, phlegmonous, gangrenous), clinical features, and surgical outcomes, including conversion to open procedure. Logistic regression and ROC analyses identified predictors of acute inflammation and conversion. Results: Acute cholecystitis patients showed elevated NLR (7.0 vs. 3.1), MLR (0.44 vs. 0.26), and PLR (194 vs. 142; all p < 0.001). NLR was the only independent predictor of acute disease (OR = 1.29, 95% CI 1.203–1.390, p < 0.001), with superior discrimination (AUC = 0.806, cut-off = 3.56; sensitivity 73.1%, specificity 80.4%). NLR and PLR rose progressively from catarrhal to phlegmonous and gangrenous subtypes (p < 0.05), mirroring conversion rates (0% catarrhal, 3.2% phlegmonous, 10.5% gangrenous; p = 0.001). Conclusions: Routine hematologic ratios capture systemic immune activation in acute cholecystitis, reflecting histologic severity and operative risk. NLR, integrating innate and adaptive immune dynamics, offers a practical biomarker for preoperative risk stratification in acute care surgery. Full article

As the world progresses towards more sustainable food systems, an increasing number of individuals are inclined to reduce meat consumption and transition to plant-based protein sources. Given the implications of climate change and escalating public health issues, plant-based protein sources appear to be a viable alternative; yet, this transition will be challenging to implement. Legumes, cereals, oilseeds, microalgae, and mycoprotein constitute the primary sources of plant-derived protein. Each possesses distinct functional attributes; yet, they also exhibit certain nutritional constraints. The restrictions mostly pertain to the composition of essential amino acids and the body’s efficacy in utilizing micronutrients such as iron, zinc, and vitamin B₁₂. From an ecological perspective, plant-based proteins often exert a significantly lesser impact on the environment compared to conventional meat. This reduces greenhouse gas emissions and optimizes resource utilization. Recent technological advancements, including fermentation methods, shear cell structuring, and high-moisture extrusion, have significantly improved the texture and flavor of plant-based products. However, consumer perceptions of the sensory attributes of these products significantly influence their acceptance. Current research priorities include improving protein digestibility, mitigating antinutritional factors, reducing salt content, and generating robust long-term data on health effects/health benefits. Ultimately, replacing meat with plant-based proteins involves not only scientific and nutritional considerations but also requires significant cultural and societal transformations to establish a more balanced and sustainable food system. Full article

Artificial levees along major rivers are critical for flood-risk mitigation, yet many aging structures have poorly constrained internal composition and material heterogeneity, limiting the reliability of conventional safety assessments. This study develops a quantitative, non-destructive framework for characterizing levee internal structure by integrating electrical resistivity tomography (ERT) with borehole (BH) observations. ERT profiles were combined with borehole measurements of grain size (D50) and water content to investigate subsurface compositional variability and to evaluate relationships between sedimentological and geophysical parameters. Grain-size data from borehole samples were modeled using four predictive approaches—random forest regression (RFR), artificial neural networks (ANN), linear regression (LR), and support vector regression (SVR)—based on ERT-derived resistivity and moisture information. The results reveal pronounced internal heterogeneity within the investigated levees and demonstrate consistent relationships between sediment composition, water content, and electrical resistivity. Among the tested models, the ensemble-based RFR provided the highest predictive performance (R² = 0.81). These findings indicate that D50 characteristics of levee materials can be reliably inferred from ERT data using machine learning, reducing the need for destructive sampling. The proposed approach offers a transferable methodology for levee assessment and supports future applications in non-destructive monitoring, spatially explicit flood-risk analysis, and climate-resilient flood-protection management. Full article

Corporate governance is increasingly recognised as a key mechanism supporting sustainability transparency, accountability, and long-term value creation. While prior research has examined governance–performance relationships and sustainability outcomes using proprietary ESG ratings, evidence on how governance structures enable sustainability disclosure remains limited, particularly in Central and Eastern Europe (CEE). This gap reflects heterogeneous institutional environments and uneven ESG data availability in emerging European markets. To address this limitation, this study develops and applies a Corporate Governance–Sustainability Index for Central and Eastern Europe (CGSI–CEE). The index integrates core governance mechanisms (such as board effectiveness, leadership structure and ownership discipline) with sustainability transparency indicators, namely ESG report publication and CO₂ emissions disclosure. The CGSI–CEE is constructed using publicly available firm-level data from CEE blue-chip companies over the 2018–2024 period and follows a transparent, theory-driven weighting scheme. The results reveal substantial heterogeneity in governance-enabled sustainability capacity across firms, sectors, and countries. Bivariate results indicate a negative association with short-term accounting profitability and a positive association with market valuation; however, these relationships weaken once firm-level characteristics are controlled for, reinforcing the interpretation of CGSI–CEE as a structural governance-capacity measure rather than a direct performance determinant. Full article

Viral hemorrhagic fevers (VHFs) comprise a heterogeneous group of severe infectious diseases that continue to represent a major global health concern. Although many VHFs remain endemic to regions of Africa, Asia, and the Americas, their wide geographic distribution, together with increasing international travel and global trade, facilitates the importation of cases into non-endemic areas and raises the risk of secondary transmission under favorable ecological and epidemiological conditions. These infections are frequently associated with high case-fatality rates and impose a substantial social and economic burden, including pressure on healthcare systems, disruption of essential services, and long-term physical and psychological sequelae among survivors. Despite notable advances in recent years, therapeutic options for VHFs remain limited. Supportive care continues to represent the cornerstone of clinical management for most infections, while pathogen-targeted therapies are available only for a restricted number of diseases. Monoclonal antibody-based therapies have achieved the most significant regulatory success to date, particularly for Ebola virus disease. In parallel, several small-molecule antivirals have been investigated in preclinical and clinical settings, including during outbreak responses, although inconsistent efficacy and safety concerns have limited widespread approval. Vaccine development has progressed further, with licensed vaccines available for selected VHFs, including Ebola, yellow fever, and dengue, and multiple candidates based on diverse technological platforms advancing through clinical evaluation. In addition to summarizing current therapeutic and vaccine strategies, this review highlights pharmaceutical development considerations relevant to biologic therapeutics and selected vaccine platforms, including formulation stability, pharmacokinetic behavior, delivery routes, storage requirements, and logistical constraints affecting deployment during outbreak responses. Using a comparative cross-pathogen framework, the review synthesizes recent literature to identify translational gaps, regulatory challenges, and future priorities for the development of safer and more effective medical countermeasures against VHFs. Full article

Acute coronary syndromes (ACS) are a major cause of mortality worldwide, and although interventional treatment has significantly improved mortality and morbidity related to ischemic heart disease, there is constant concern about optimizing drug treatment. In this regard, multiple studies have been conducted on inflammation in myocardial infarction (MI), starting from its implications in the atherosclerosis process. The aim of this review is to analyse the current evidence related to the subject and the correlation between the inflammatory state at presentation and the prognosis of patients with MI, identifying key points, possible therapeutic limitations, and future research directions. Both innate and acquired immune components are involved in the inflammatory cascade, with an increase in inflammatory cell and cytokine levels. To analyse the degree of inflammation and determine when it is excessive, numerous inflammatory markers have been studied, from acute phase proteins such as high-sensitivity C-reactive protein (hsCRP) and fibrinogen, to the ratios between inflammatory cells and interleukins involved in the main inflammatory pathways. Their association with post-infarction mortality and morbidity has been observed, but they must be integrated into the clinical context for the selection of patients who would benefit most from their reduction. New anti-inflammatory therapies are being studied in light of these findings, and progress is expected. Early trials with non-selective anti-inflammatory drugs have highlighted the importance of selective inhibition so as not to disrupt healing, and drugs are now being studied that target specific pathways that are exacerbated in infarction and lead to excessive remodelling. Several inflammatory pathways have been investigated but the results are inconclusive in terms of improving prognosis, requiring further studies to formulate future therapeutic indications. Full article

Inflammasomes are cytosolic multiprotein complexes that detect pathogens, cellular stress, and damage-associated molecular signals, thereby orchestrating innate immune responses. Increasing evidence suggests that dysregulated inflammasome activation contributes to persistent neuroinflammation and to a wide range of neuropsychiatric disorders, including mood disorders, schizophrenia, Alzheimer’s disease, and autism spectrum disorders. Together, these findings emphasize the critical role of neuroimmune interactions in the pathophysiology of mental disorders. Recent molecular studies have substantially advanced our understanding of the crosstalk among neurons, microglia, astrocytes, and peripheral immune cells, uncovering complex regulatory networks mediated by cytokines, neurotrophins, and neurotransmitters. By examining key inflammatory mediators and cell type-specific mechanisms, this review consolidates current knowledge and proposes conceptual frameworks to guide future investigations and facilitate the development of targeted therapeutic strategies for neuropsychiatric disorders. Full article

The aim of this paper is to test and compare different neuro-evolution methods to train a simulated biped walker to learn to walk. After this step, the best neuro-evolution technique is ported to a real biped, which would train itself to walk. The goal is to reduce the number of falls for the real biped in order to avoid destroying the physical unit. The following four neuro-evolution methods were tested: Deep Q-Learning (DQN), NeuroEvolution of Augmenting Topologies (NEAT), Deep Deterministic Policy Gradients (DDPG), and Augmented Random Search (ARS). The best results from simulations were obtained with the ARS method, but the fastest and easiest to implement on the real biped was the NEAT algorithm. Full article

Nitridation of different materials using ion implantation is of considerable interest for many applications. As electronic components, oxynitride (SiO_xN_y) layers exhibit beneficial properties such as precise compositional variability, refractive index tunability, oxidation resistance, and low mechanical stress. In the present study we investigate nanoscale SiO_xN_y synthesized using ion implantation methods. To introduce N⁺ ions into a shallow Si subsurface region, both conventional ion beam implantation and plasma immersion ion implantation with subsequent high-temperature treatment in dry O₂ are used. The optical and morphological properties and chemical bonding of formed SiO_xN_y layers were studied by applying spectroscopic ellipsometry in the range of VIS-Near IR (SE) and IR (IR-SE), Raman spectroscopy and Atomic Force Microscopy (AFM). Monte Carlo modeling of implant profiles contributed to understanding physical and chemical processes and predicted different influences of the incorporated N⁺ ions on the oxidation mechanism, confirmed by the thickness dependence of SiO_xN_y/Si layers obtained from the SE data analysis. IR-SE spectral analysis established the formation of Si-O, Si-N, Si-N-O and Si-Si chemical bonds in the grown layers. The occurrence of amorphization of the Si crystal lattice due to incorporation of high-energy N⁺ ions into the Si lattice is confirmed by the Raman and ellipsometry results. The free Si atoms can congregate, forming nanocrystalline clusters. AFM imaging revealed that both implantation methods left the surface of the resulting SiO_xN_y layers considerably smooth with similar roughness parameter values. The results of the studies imply that the technological approaches used allow the production of high-quality nanoscale silicon oxynitride films with appropriate tunable composition and properties for possible application in advanced electronic devices for nanoelectronics, optoelectronics and sensor applications. Full article

The Johnson–Mehl–Avrami–Kolmogorov (JMAK) formalism provides a classical framework for describing polymer crystallization kinetics; its applicability under finite-domain confinement requires quantitative assessment. In this work, the influence of one-dimensional geometric restriction on cylindrical growth in polymer thin films is investigated using a stochastic Monte Carlo approach. The model considers site-saturated nucleation on randomly distributed cylindrical nanofibers with constant radial growth velocity under hard-wall boundary conditions. Crystallization kinetics were evaluated through automated segmented regression of the double-logarithmic JMAK representation. Under confinement, the Avrami plot departs from single-slope linearity and exhibits two successive quasi-linear regimes characterized by effective parameter pairs $\left(n_1,\ln k_1\right)$ and $\left(n_2,\ln k_2\right)$. The primary exponent $n_1$ remains thickness-independent, consistent with early-stage radial expansion prior to boundary interaction. The secondary exponent $n_2$ displays a non-monotonic dependence on reduced film thickness, reflecting the competing influence of wall-induced truncation and inter-domain impingement on late-stage transformation. These results support a geometric interpretation in which finite-domain constraints modify the apparent Avrami response through the competing effects of wall-induced truncation and inter-domain impingement and provide a reproducible framework for analyzing dual-regime Avrami behavior in confined crystallization systems. Full article

Magnetic superconductor EuRbFe₄As₄ is a quite unique system in which macroscopic superconductivity and magnetic ordering coexist, with interesting interactions between Abrikosov vortices and Eu²⁺ spins that were investigated mostly by static (DC) magnetization measurements. Our aim is to study the dynamic interactions between the two sub-systems using AC susceptibility measurements in a wide range of temperatures and superimposed DC fields. In low DC fields, the magnetic transition at 15 K is clearly visible. We have observed very little difference between the AC susceptibility in different cooling regimes, but large difference for different field orientation. For field perpendicular to the superconducting planes, we have observed an anomalous dependence just below the critical temperature, which is absent in the parallel field orientation. We explained the anomaly by the interplay between the sample dimensions and the temperature dependence of the London penetration depth which may allow the paramagnetic Meissner-like response to be detected in the temperature dependence of the AC susceptibility. We stress that the newly reported phenomenon reflects an AC-susceptibility manifestation of a field-stabilized critical state rather than a thermodynamic phase. In addition, we have observed a paramagnetic AC response in the normal phase, in both field orientations, indicative of interactions between Eu²⁺ spins and flux lines. Full article