Search Results (6,808)

Hyperloop ultra-high-speed transport presents a transformative opportunity for future mobility systems in smart cities. However, assessing its socio-economic impact remains challenging due to Hyperloop’s unique technological, modal, and operational characteristics. As a novel, fifth mode of transportation—distinct from both aviation and rail—Hyperloop requires tailored evaluation tools for policymakers. This study proposes a custom-designed framework to quantify its macroeconomic effects through changes in gross domestic product (GDP) at the city level. Unlike traditional economic models, the proposed approach is specifically adapted to Hyperloop’s multimodality, infrastructure, speed profile, and digital-green footprint. A Poisson pseudo-maximum likelihood (PPML) model is developed and applied at two technology readiness levels (TRL-6 and TRL-9). Case studies of Glasgow, Berlin, and Busan are used to simulate impacts based on geo-spatial features and city-specific trade and accessibility indicators. Results indicate substantial GDP increases driven by factors such as expanded 60 min commute catchment zones, improved trade flows, and connectivity node density. For instance, under TRL-9 conditions, GDP uplift reaches over 260% in certain scenarios. The framework offers a scalable, reproducible tool for policymakers and urban planners to evaluate the economic potential of Hyperloop within the context of sustainable smart city development. Full article

Background: RSV remains a leading cause of infant hospitalization worldwide, and the recently approved nirsevimab could represent an effective and safe prophylactic strategy to prevent severe infections in the general neonatal population. Objectives: We conducted a retrospective observational monocentric pilot study in a mixed preterm/term birth cohort to add real-world evidence of the efficacy and safety of nirsevimab in preventing severe RSV infection. Methods: We included a total of 2035 consecutive infants admitted to the Neonatal Unit, University Hospital “San Giovanni di Dio e Ruggi d’Aragona”, Salerno, Italy, from November 2024 to April 2025. We evaluated 30-day safety profiles and season-wide RSV infection rates, and the outcomes were also compared to newborns’ birth rate in the two previous seasons (2022–2023 and 2023–2024). Results: After the introduction of nirsevimab, a lower RSV infection rate was reported compared to previous seasons, and no adverse effects were observed. Compared to previous seasons, the clinical outcomes were more favorable, as only one unvaccinated neonate with RSV infection required invasive ventilation. Conclusions: In this real-world analysis, we demonstrated a good short-term safety profile of nirsevimab, as well as a potentially high efficacy in the general neonatal population with lower RSV infection incidence. However, future studies are needed to better assess its long-term safety and season-wide efficacy. Full article

Ashby’s law of requisite variety allows a comparison of systems with their environments, providing a necessary (but not sufficient) condition for system efficacy: A system must possess at least as much complexity as any set of environmental behaviors that require distinct responses from the system. However, to account for the dependence of a system’s complexity on the level of detail—or scale—of its description, a multi-scale generalization of Ashby’s law is needed. We define a class of complexity profiles (complexity as a function of scale) that is the first, to our knowledge, to exhibit a multi-scale law of requisite variety. This formalism provides a characterization of multi-scale complexity and generalizes the law of requisite variety’s single constraint on system behaviors to a class of multi-scale constraints. We show that these complexity profiles satisfy a sum rule, which reflects a tradeoff between smaller- and larger-scale degrees of freedom, and we extend our results to subdivided systems and systems with a continuum of components. Full article

This paper presents the design and implementation of a high-precision vehicle detection and classification system for toll stations on national highways in Colombia, leveraging LiDAR-based 3D point cloud processing and supervised machine learning. The system integrates a multi-sensor architecture, including a LiDAR scanner, high-resolution cameras, and Doppler radars, with an embedded computing platform for real-time processing and on-site inference. The methodology covers data preprocessing, feature extraction, descriptor encoding, and classification using Support Vector Machines. The system supports eight vehicular categories established by national regulations, which present significant challenges due to the need to differentiate categories by axle count, the presence of lifted axles, and vehicle usage. These distinctions affect toll fees and require a classification strategy beyond geometric profiling. The system achieves $89.9\%$ overall classification accuracy, including $96.2\%$ for light vehicles and $99.0\%$ for vehicles with three or more axles. It also incorporates license plate recognition for complete vehicle traceability. The system was deployed at an operational toll station and has run continuously under real traffic and environmental conditions for over eighteen months. This framework represents a robust, scalable, and strategic technological component within Intelligent Transportation Systems and contributes to data-driven decision-making for road management and toll operations. Full article

The treatment landscape of metastatic hormone-sensitive prostate cancer (mHSPC) has transformed significantly with the advent of triplet therapy involving androgen deprivation therapy (ADT), docetaxel, and androgen receptor signalling inhibitors (ARSIs). While clinical guidelines increasingly support early intensification, real-world practice remains challenged by patient heterogeneity, evolving evidence, and limited consensus on treatment sequencing. This narrative review integrates evidence from landmark trials, clinical guidelines, and expert insights from oncologists managing mHSPC in India. Findings affirm that triplet therapy, particularly with darolutamide, improves survival in high-volume disease and underscores the need for personalized treatment based on disease burden, comorbidities, and genomic profiles. The review also highlights gaps in real-world data, sequencing strategies, and biomarker-driven therapy, reinforcing the need for precision medicine and locally relevant evidence to guide treatment. Ultimately, optimizing mHSPC management requires harmonizing guideline-based approaches with individualized, real-world decision making to improve patient outcomes. Full article

Background/Objectives: COVID-19 is a systemic viral infection that may lead to serious complications including acute kidney injury that requires kidney replacement therapy. The primary aim of this study was to evaluate urinary SerpinA3 (uSerpinA3) excretion as a biomarker of kidney recovery at 90 days, and the mortality in patients with critical COVID-19 and AKI requiring kidney replacement therapy (KRT). Methods: The study included patients with critical COVID-19 on invasive mechanical ventilation (IMV) requiring KRT. Blood and urine samples were obtained when KRT was initiated (day zero), and thereafter on days 1, 3, 7, and 14 post-replacement. uSerpinA3, kidney injury molecule-1 (uKIM-1), and neutrophil gelatinase-associated lipocalin (uNGAL) were measured in urine, and interleukin-6 (IL-6), interleukin-10 (IL-10), and tumor necrosis factor alpha (TNF-α) in peripheral blood. In addition, metabolomics in sample days zero and 3, and in the survivors on sample day 90 was performed by employing gas chromatography coupled with mass spectrometry. Results: A total of 60 patients were recruited, of whom 29 (48%) survived hospitalization and recovered kidney function by day 90. In the survivors, 79% presented complete recovery (CRR) and the remaining (21%) recovered partially (PRR). In terms of uSerpinA3, levels on days 7 and 14 predicted CRR, with AUC values of 0.68 (p = 0.041) and 0.71 (p = 0.030), respectively, as well as mortality, with AUC values of 0.75 (p = 0.007) and 0.76 (p = 0.015), respectively. Among the other biomarkers, the excretion of uKIM-1 on day zero of KRT had a superior performance as a CRR predictor [(AUC, 0.71 (p = 0.017)], and as a mortality predictor [AUC, 0.68 (p = 0.028)]. In the metabolomics analysis, we identified four distinct profiles; the metabolite that maintained statistical significance in predicting mortality was p-cresol glucuronide. Conclusions: This study strongly suggests that uSerpinA3 and uKIM-1 can predict CRR and mortality in patients with critical COVID-19 and AKI requiring KRT. Metabolic analysis appears promising for identifying affected pathways and their clinical impact in this population. Full article

Background/Objectives: Cognitive impairment is one of the most common and debilitating clinical features of Multiple Sclerosis (MS). Neuropsychological assessment, however, is time-consuming and requires personal resources, so, due to limited resources in daily clinical practice, information on cognitive profiles is often lacking, despite its high prognostic relevance. Time-saving and effective tools are required to bridge this gap. This study evaluates the sensitivity and specificity of a revised version of TRACK-MS (TRACK-MS-R), a recently published screening tool to identify cognitive impairment in MS in a fast and reliable way, offering a balance between efficiency and diagnostic yield for the individual patient. Methods: In this prospective cross-sectional study, 102 MS patients and 94 age-, sex-, and education-matched healthy controls (HC) completed an extensive neuropsychological assessment, including TRACK-MS-R, to test for cognitive processing speed (Symbol Digit Modalities Test, SDMT) and verbal fluency (Regensburger Word Fluency Test, RWT). Sensitivity of TRACK-MS-R was assessed by using the BICAMS-M battery as a reference, and specificity was determined by comparing MS patients to HC. Results: TRACK-MS-R demonstrated high sensitivity (97.44%) when compared to the gold standard as represented by BICAMS-M for early and accurately detecting cognitive impairment in MS patients. Additionally, as a potential cognitive marker, TRACK-MS-R showed a specificity of 82.98% in distinguishing MS patients from healthy controls. Conclusions: TRACK-MS-R proves to be a highly sensitive and time-efficient screening tool for detecting cognitive impairment in patients with MS, while demonstrating good specificity compared to HC. Whereas high sensitivity is a prerequisite for a valid screening tool, its relatively modest specificity compared to BICAMS-M (62.9%) calls for caution in interpreting standalone results but instead indicates more extensive neuropsychological testing. Its briefness and diagnostic accuracy support its implementation in routine clinical practice, particularly in time-constrained settings. Full article

Accurately simulating the asymmetric spectral profiles of blue LEDs is crucial for photobiological research, yet it remains a challenge for traditional symmetric models. This study proposes a novel spectral simulation model that effectively captures these asymmetries. The proposed model structure is partly motivated by known broadening and dispersion mechanisms observed in real LED spectra; it employs a ‘base model + correction’ framework, where an Exponentially Modified Gaussian (EMG) function captures the primary spectral shape and falling edge and an Asymmetric Pseudo-Voigt (APV) function corrects the deviations on the rising edge. Requiring only the central wavelength and bandwidth as user inputs, the simulation results exhibit a high degree of agreement with the experimental data spectra. The model provides a rapid and robust tool for pre-evaluating light sources against regulatory criteria (e.g., >99% of the spectral intensity is in the 400–500 nm band), thereby enhancing the efficiency of experimental design in blue light protection studies. Full article

Cardiovascular disease (CVD) remains Europe’s leading cause of mortality, responsible for >45% of deaths. Beyond established risk factors (hypertension, diabetes, dyslipidaemia, smoking, obesity), psychosocial elements—depression, anxiety, financial stress, personality traits, and trauma—significantly influence CVD development and progression. Behavioural Cardiology addresses this connection by systematically incorporating psychosocial factors into prevention and rehabilitation protocols. This review examines the HEARTBEAT model, developed by Greece’s first Behavioural Cardiology Unit, which aligns with current European guidelines. The model serves dual purposes: primary prevention (targeting at-risk individuals) and secondary prevention (treating established CVD patients). It is a personalised medicine approach that integrates psychosocial profiling with traditional risk assessment, utilising tailored evaluation tools, caregiver input, and multidisciplinary collaboration to address personality traits, emotional states, socioeconomic circumstances, and cultural contexts. The model emphasises three critical implementation aspects: (1) digital health integration, (2) cost-effectiveness analysis, and (3) healthcare system adaptability. Compared to international approaches, it highlights research gaps in psychosocial interventions and advocates for culturally sensitive adaptations, particularly in resource-limited settings. Special consideration is given to older populations requiring tailored care strategies. Ultimately, Behavioural Cardiology represents a transformative systems-based approach bridging psychology, lifestyle medicine, and cardiovascular treatment. This integration may prove pivotal for optimising chronic disease management through personalised interventions that address both biological and psychosocial determinants of cardiovascular health. Full article

Diabetic retinopathy (DR) is a progressive, multifactorial complication of diabetes and one of the major global causes of visual impairment. Its pathogenesis involves chronic hyperglycaemia-induced oxidative stress, inflammation, mitochondrial dysfunction, neurodegeneration, and pathological angiogenesis, as well as emerging systemic contributors such as gut microbiota dysregulation. While current treatments, including anti-vascular endothelial growth factor (anti-VEGF) agents, corticosteroids, and laser photocoagulation, have shown clinical efficacy, they are largely limited to advanced stages of DR, require repeated invasive procedures, and do not adequately address early neurovascular and metabolic abnormalities. Resveratrol (RSV), a naturally occurring polyphenol, has emerged as a promising candidate due to its potent antioxidant, anti-inflammatory, neuroprotective, and anti-angiogenic properties. This review provides a comprehensive analysis of the molecular mechanisms by which RSV exerts protective effects in DR, including modulation of oxidative stress pathways, suppression of inflammatory cytokines, enhancement of mitochondrial function, promotion of autophagy, and inhibition of pathological neovascularisation. Despite its promising pharmacological profile, the clinical application of RSV is limited by poor aqueous solubility, rapid systemic metabolism, and low ocular bioavailability. Various routes of administration, including intravitreal injection, topical instillation, and oral and sublingual delivery, have been investigated to enhance its therapeutic potential. Recent advances in drug delivery systems, including nanoformulations, liposomal carriers, and sustained-release intravitreal implants, offer potential strategies to address these challenges. This review also explores RSV’s role in combination therapies, its potential as a disease-modifying agent in early-stage DR, and the relevance of personalised medicine approaches guided by metabolic and genetic factors. Overall, the review highlights the therapeutic potential and the key translational challenges in positioning RSV as a multi-targeted treatment strategy for DR. Full article

Cancer is a systemic disease rather than a localized pathology and is characterized by widespread effects, including whole-body exhaustion and chronic inflammation. A thorough understanding of cancer pathophysiology requires a systemic approach that accounts for the complex interactions between cancer cells and host tissues. To explore these dynamics, we employed a comprehensive metabolomic analysis of plasma samples from patients with either esophageal or head and neck squamous cell carcinoma (SCC). Plasma samples from 149 patients were metabolically profiled and correlated with clinical data. Among the metabolites identified, lysophosphatidylcholine (LPC) emerged as the sole biomarker strongly correlated with prognosis. A significant reduction in plasma LPC levels was linked to poorer overall survival. Plasma LPC levels demonstrated minimal correlation with patient-specific factors, such as tumor size and general condition, but showed significant association with the response to immune checkpoint inhibitor therapy. Proteomic and cytokine analyses revealed that low plasma LPC levels reflected systemic chronic inflammation, characterized by high levels of inflammatory proteins, the cytokines interleukin-6 and tumor necrosis factor-α, and coagulation-related proteins. These findings indicate that plasma LPC levels may be used as reliable biomarkers for predicting prognosis and evaluating the efficacy of immunotherapy in patients with SCC. Full article

Objective: This retrospective observational study evaluated the efficacy and safety of an ovarian stimulation protocol for embryo banking that involves continuous administration of clomiphene citrate (CC) in combination with gonadotropins, without the use of GnRH antagonists. Methods: Conducted at the Serum IVF Clinic in Athens, Greece, the study included 250 women aged 25–45 who underwent IVF for embryo banking. The protocol involved administering 150 mg of CC daily from day 2 of the menstrual cycle until the day before hCG trigger, alongside 150 IU/day of Meriofert. Outcomes assessed included oocyte yield, fertilization rates, incidence of ovarian hyperstimulation syndrome (OHSS), and hormonal correlations. Comparative and regression analyses explored differences between age groups and predictors of success. Results: The protocol demonstrated a favorable safety profile with no cases of OHSS and yielded a mean of 10.25 oocytes per patient. Group analysis showed significantly more oocytes retrieved in women under 40 (mean: 12.5) versus those over 40 (mean: 8.43), while fertilization rates were paradoxically higher in the older cohort (59.16% vs. 30.68%, p < 0.0001). Regression models revealed basal FSH to be a significant inverse predictor of oocyte yield, but it was positively associated with fertilization rate. Continuous CC use effectively suppressed premature LH surges without compromising oocyte or embryo quality, allowing flexible and cost-effective stimulation with minimal monitoring. Conclusions: Continuous administration of clomiphene citrate in combination with gonadotropins presents a promising, antagonist-free ovarian stimulation protocol for embryo banking. The approach is economically efficient, reduces monitoring requirements, and maintains safety and effectiveness and is particularly notable in women over 40. Further studies are warranted to validate these findings and refine protocol mechanisms. Full article

This study investigates the thermal dynamics and material behavior involved in the baking process for Lebanese flatbread, focusing on the heat transfer mechanisms, water loss, and dough expansion under high-temperature conditions. Despite previous studies on flatbread baking using impingement or conventional ovens, this work presents the first experimental investigation of the traditional Lebanese flatbread baking process under realistic industrial conditions, specifically using a high-temperature tunnel oven with direct flame heating, extremely short baking times (~10–12 s), and peak temperatures reaching ~650 °C, which are essential to achieving the characteristic pocket formation and texture of Lebanese bread. This experimental study characterizes the baking kinetics of traditional Lebanese flatbread, recording mass loss pre- and post-baking, thermal profiles, and dough expansion through real-time temperature measurements and video recordings, providing insights into the dough’s thermal response and expansion behavior under high-temperature conditions. A custom-designed instrumented oven with a steel conveyor and a direct flame burner was employed. The dough, prepared following a traditional recipe, was analyzed during the baking process using K-type thermocouples and visual monitoring. Results revealed that Lebanese bread undergoes significant water loss due to high baking temperatures (~650 °C), leading to rapid crust formation and pocket development. Empirical equations modeling the relationship between baking time, temperature, and expansion were developed with high predictive accuracy. Additionally, an energy analysis revealed that the total energy required to bake Lebanese bread is approximately 667 kJ/kg, with an overall thermal efficiency of only 21%, dropping to 16% when preheating is included. According to previous CFD (Computational Fluid Dynamics) simulations, most heat loss in similar tunnel ovens occurs via the chimney (50%) and oven walls (29%). These findings contribute to understanding the broader thermophysical principles that can be applied to the development of more efficient baking processes for various types of bread. The empirical models developed in this study can be applied to automating and refining the industrial production of Lebanese flatbread, ensuring consistent product quality across different baking environments. Future studies will extend this work to alternative oven designs and dough formulations. Full article

Post-traumatic stress disorder (PTSD) is a chronic mental health condition resulting from exposure to traumatic events. It is associated with long-term neurobiological changes and disturbances in emotional regulation. Understanding the sociodemographic profiles, biomarkers, and emotional control in patients with PTSD helps to better comprehend the impact of the disorder on the body and its clinical course. An analysis of biomarkers such as Interleukin-18 (IL-18), Inositol-Requiring Enzyme 1 (IRE1), Phosphorylated Extracellular Signal-Regulated Kinase (pERK), and Activating Transcription Factor–6 (ATF-6) in PTSD patients with varying durations of illness (≤5 years and >5 years) and a control group without PTSD revealed significant differences. Patients with recently diagnosed PTSD (≤5 years) showed markedly elevated levels of inflammatory and cellular stress markers, indicating an intense neuroinflammatory response during the acute phase of the disorder. In the chronic PTSD group (>5 years), the levels of these biomarkers were lower than in the recently diagnosed group, but still significantly higher than in the control group. An opposite trend was observed regarding the suppression of negative emotions, as measured by the Courtauld Emotional Control Scale (CECS): individuals with chronic PTSD exhibited a significantly greater suppression of anger, depression, and anxiety than those with recent PTSD or healthy controls. Correlations between biomarkers were strongest in individuals with chronic PTSD, suggesting a persistent neuroinflammatory dysfunction. However, the relationships between biomarkers and emotional suppression varied depending on the stage of PTSD. These findings highlight the critical role of PTSD duration in shaping the neurobiological and emotional mechanisms of the disorder, which may have important implications for therapeutic strategies and patient monitoring. Full article

Tennis is a demanding sport that requires physical abilities and optimal body composition. The aim of this study was to investigate the anthropometric characteristics, body composition, and somatotype development of young Slovenian tennis players (754 boys and 514 girls aged 12 to 18 years) over the last two decades. Using standardised anthropometric measurements and the Heath-Carter method, somatotypes were calculated and analysed by age and gender. The results showed clear age- and gender-specific trends and differences in both somatotype profiles and detailed anthropometric characteristics. Significant differences were found in height, body mass, BMI, skinfolds, girths, and limb lengths, with gender differences becoming more pronounced in the older age groups. In boys, mesomorphy increased with age, reflecting an increase in musculature, while in girls, a shift from ectomorphic to endomorphic profiles was observed during adolescence, probably influenced by pubertal and hormonal changes. Significant sex-specific differences were observed in all three somatotype components in most age groups, especially in fat mass and muscle. The longitudinal design provides valuable data and insights into the evolving physical profiles of adolescent tennis players that support more effective talent identification and training. Despite the changes that have taken place in tennis over time, standardised measurement protocols ensured comparability, making the results relevant for practitioners working with adolescents in tennis development. Full article