Search Results (4,610)

Ultra-high-energy cosmic rays (UHECRs) are the most energetic particles known—and yet their origin is still an open question. However, with the precision and accumulated statistics of the Pierre Auger Observatory and the Telescope Array, in combination with advancements in theory and modeling—e.g., of the Galactic magnetic field—it is now possible to set solid constraints on the sources of UHECRs. The spectrum and composition measurements above the ankle can be well described by a population of extragalactic, homogeneously distributed sources emitting mostly intermediate-mass nuclei. Additionally, using the observed anisotropy in the arrival directions, namely the large-scale dipole >8 EeV, as well as smaller-scale warm spots at higher energies, even more powerful constraints on the density and distribution of sources can be placed. Yet, open questions remain—like the striking similarity of the sources that is necessary to describe the rather pure mass composition above the ankle, or the origin of the highest energy events whose tracked back directions point toward voids. The current findings and possible interpretation of UHECR data will be presented in this review. Full article

The article addresses the challenges of beam position tracking in Free-Space Optical Communication (FSOC) systems. A review of available photodetector technologies is presented, highlighting their operating principles and applications in optical links. The analysis indicates that most current monitoring devices function with the visible and near- or short-infrared ranges. However, due to the propagation characteristics of radiation in terrestrial environments, the mid-wave infrared (MWIR) region offers particularly promising opportunities. To the end, the work introduces a novel detector module based on an MWIR quadrant detector capable of simultaneously performing two essential tasks: monitoring beam position and receiving transmitted data. Such an integrated approach has the potential to significantly simplify the design of mobile FSOC systems, especially those requiring accurate transceivers’ tracking. The concept was validated through laboratory experiments on an MWIR link model, where both the signal bandwidth and position transfer function of the quadrant detector were examined. Full article

The global shift towards cleaner energy sources is driving the adoption of hydrogen as an environmentally friendly alternative to fossil fuels. Among the forms currently available, Liquid Hydrogen (LH₂) offers high energy density and efficient storage, making it suitable for large-scale transport by rail. However, the flammability of hydrogen poses serious safety concerns, especially when transported through confined spaces such as railway tunnels. In case of an accidental LH₂ release from a freight train, the rapid accumulation and potential ignition of hydrogen could cause catastrophic consequences, especially if freight and passenger trains are present simultaneously in the same tunnel tube. In this study, a three-dimensional computational fluid dynamics model was developed to simulate the dispersion and explosion of LH₂ following an accidental leak from a freight train’s cryo-container in a single-tube double-track railway tunnel, when a passenger train queues behind it on the same track. The overpressure results were analyzed using probit functions to estimate the fatality probabilities for the passenger train’s occupants. The analysis suggests that a significant number of fatalities could be expected among the passengers. However, shorter users’ evacuation times from the passenger train’s wagons and/or longer distances between the two types of trains might reduce the number of potential fatalities. The findings, by providing additional insight into the risks associated with LH₂ transport in railway tunnels, indicate the need for risk mitigation measures and/or traffic management strategies. Full article

Glottic insufficiency, often caused by laryngeal nerve injury, impairs voice quality and breathing. Current treatments, such as hyaluronic acid injection, require frequent reapplication every 3–6 months. This study aimed to investigate the therapeutic potential of small extracellular vesicles (sEVs) derived from Wharton’s Jelly mesenchymal stem cells (WJMSCs) incorporated into genipin-crosslinked gelatin hydrogels (GCGHs) for promoting vocal fold fibroblast (VFFs) regeneration in vitro. WJMSCs were isolated from umbilical cords, expanded to passage 4, and used for sEV isolation via tangential flow filtration (TFF). The sEVs (585.89 ± 298.93 µg/mL) were characterized using bicinchoninic acid assay (BCA), nanoparticle tracking analysis (NTA), transmission electron microscopy (TEM), and Western blot. Seven concentrations of sEVs were tested on VFFs to evaluate cytotoxicity and proliferation, identifying 75 µg/mL as the optimal dose. GCGHs were then combined with WJMSCs and sEVs and evaluated for physicochemical properties, degradation, biocompatibility, and immune response. The hydrogels were injectable within 20 min and degraded in approximately 42 ± 0.72 days. The optimal sEV concentration significantly enhanced VFFs proliferation (166.59% ± 28.11) and cell viability (86.16% ± 8.55, p < 0.05). GCGH-MSCs showed the highest VFFs viability (82.04% ± 10.51) and matrix contraction (85.98% ± 1.25) compared to other groups. All hydrogel variants demonstrated minimal immune response when co-cultured with peripheral blood mononuclear cells (PBMCs). GCGH is a promising scaffold for delivering WJMSCs and sEVs to support VFF regeneration, with demonstrated biocompatibility and regenerative potential. Further in vivo studies are warranted to validate these findings. Full article

Integrating human–robot collaboration (HRC) into construction sites has significantly enhanced efficiency and quality. However, it also introduces new or intensifies existing risks as it brings in new entities, relationships, and construction activities. Safety remains the top priority and a persistent concern in HRC systems. However, the current literature on human–robot collaboration safety (HRCS) is vast yet fragmented, and a systematic exploration of its status and research trends in the construction context is still lacking. This paper explores advances in HRCS over the past two decades through a mixed quantitative and qualitative analysis method. Initially, 287 related articles were identified by keyword-searching in Scopus, followed by bibliometric analysis using CiteSpace to uncover the knowledge structure and track emerging research trends. Subsequently, a qualitative discussion highlights achievements in HRCS across five dimensions: (1) optimization of remote intelligent machinery; (2) hazard analysis and risk assessment in HRCS; (3) digital twin for safety monitoring; (4) cognitive and psychological impacts; (5) organizational management perspective. This study quantitatively maps the scientific landscape of HRCS at a macro level and qualitatively identifies key research areas. It provides a comprehensive foundation for understanding the evolution of HRCS and exploring future research directions and applications. Full article

Hypophosphatemia, defined as serum phosphate levels below 2.5 mg/dL, is a common yet underrecognized electrolyte disturbance in critically ill patients, with prevalence estimates reaching up to 80%. This review explores the intricate bidirectional relationship between hypophosphatemia and hyperventilation, emphasizing its profound implications for respiratory function and critical care management. Hypophosphatemia impairs oxygen delivery by depleting 2,3-diphosphoglycerate (2,3-DPG), disrupts central respiratory drive, and weakens respiratory muscles, leading to hyperventilation, ventilatory failure, and prolonged mechanical ventilation. Conversely, hyperventilation exacerbates hypophosphatemia through respiratory alkalosis, triggering intracellular phosphate shifts and metabolic cascades that rapidly deplete serum levels. This cycle creates significant challenges for ventilator weaning and increases morbidity and mortality. Underlying mechanisms include impaired ATP synthesis, altered chemoreceptor sensitivity, and systemic inflammatory responses. Hypophosphatemia-induced hyperventilation manifests as unexplained tachypnea and respiratory alkalosis, often misdiagnosed as anxiety or pain, while hyperventilation-induced hypophosphatemia contributes to diaphragmatic dysfunction and poor ventilatory performance. Common precipitating factors include refeeding syndrome, diabetic ketoacidosis, continuous renal replacement therapy, and malnutrition. Complications extend beyond respiratory dysfunction to include cardiac depression, immune dysfunction, prolonged ICU stays, and increased healthcare costs. Current diagnostic approaches rely on serum phosphate measurements, which poorly reflect total body stores due to significant intracellular shifts. Emerging biomarkers such as fibroblast growth factor 23 (FGF23) and advanced monitoring technologies, including continuous phosphate tracking, may enhance recognition. Treatment strategies emphasize targeted phosphate repletion based on severity, with intravenous supplementation and ventilatory support tailored to minimize complications. Preventive measures, including risk stratification, prophylactic supplementation, and ventilator management, are critical for high-risk populations. Despite advances, knowledge gaps persist in optimizing monitoring and repletion protocols, understanding genetic variations, and identifying ideal phosphate targets for improved respiratory outcomes. This review provides a comprehensive framework for recognizing and managing hypophosphatemia’s impact on respiratory dysfunction in critically ill patients. Adopting evidence-based interventions and leveraging emerging technologies can significantly improve clinical outcomes, reduce ICU complications, and enhance recovery in this vulnerable population. Full article

In Mexico, syphilis and tuberculosis are infectious diseases subject to mandatory and immediate epidemiological surveillance, both with special systems that allow nominal follow-up for either variant. Surveillance uses the operational definitions of probable and confirmed cases established in the manual for epidemiological surveillance issued by the General Directorate of Epidemiology of the Ministry of Health. However, both diseases, mainly in the chronic state, present challenges because of their ability to mimic autoimmune disorders. This review explores the phenomenon of clinical and immunological mimicry in secondary and tertiary syphilis, as well as in extrapulmonary tuberculosis, and analyzes its implications for the accuracy of case reporting at the national level. Evidence shows that both infections can present systemic inflammatory features, such as elevated acute phase reactants, positive autoantibodies, and alterations in cerebrospinal fluid that resemble autoimmune profiles. These overlaps can lead to misdiagnosis, inappropriate immunosuppressive treatment and misclassification of confirmed cases within the Mexican surveillance system. Surveillance of these conditions is robust; however, current operational definitions have weaknesses, particularly when atypical or autoimmune conditions are present, as they only focus on cases with the highest prevalence or public health impact. This manuscript proposes the integration of differential diagnostic algorithms and expanded laboratory criteria, including autoimmune markers and molecular tests, into surveillance protocols. Although individual efforts exist in health institutions, in our country, the absence of autoimmune diseases in the national register of obligatory notification stands out, contrasting with surveillance models in other countries, where autoimmune diseases are tracked systematically. To improve diagnostic accuracy and reporting, surveillance systems should incorporate a syndromic and etiological approach, recognizing infectious autoimmune mimicry as a factor in the final recording of confirmed cases to avoid epidemiological silence. Full article

In this study, a numerical model consisting of high-resolution hydrodynamic and Lagrangian particle tracking modules based on the Finite-Volume Coastal Ocean Model framework was established to simulate the hydrodynamic conditions and characteristics of the sedimentation of aquaculture-derived organic matter (AOM) from cage aquaculture in Sansha Bay. The results showed that Sansha Bay was characterized by regular semidiurnal tides and large tidal ranges. Reciprocating currents with main currents directed northward and southward during the rising and falling tides, respectively, predominated the main channels of the bay. Residual feed had larger settling velocities than feces. The maximal dispersion distances of residual feed and feces during the spring tide were 217.1 and 1805.7 m, respectively, three times those during the neap tide (74.2 and 675.6 m, respectively). During the spring tide, the largest dispersion distance of AOM occurred at the rush moment. The AOM movement trajectories were mainly controlled by the main currents. Both the tidal structure and current characteristics affected the AOM sedimentation in Sansha Bay. The sedimentation characteristics of AOM were unrelated to feeding intensity. The results of simulations agreed with the field observations in this study, suggesting that the estimated model had a good accuracy and sensitivity. Full article

Background/Objectives: Sexuality is a frequently overlooked but clinically significant dimension in patients with obsessive–compulsive disorder (OCD). Beyond comorbid anxiety and depressive symptoms, OCD can substantially affect sexual functioning and include obsessions and compulsions relating to sexual content. This review aims to synthesize current evidence on sexual dysfunction in OCD and the role of sexuality in OCD symptom dimensions, as well as associated neurobiological, cognitive, and clinical outcomes. Methods: We conducted a review of the literature including studies published in the last 20 years using the PubMed and Cochrane databases. Our search strategy used the terms “sexual AND (Obsessive-compulsive disorder OR OCD)”, retrieving a total of 582 articles. After a screening and eligibility assessment based on predefined inclusion and exclusion criteria, 200 studies were included. Additional papers were retrieved through citation tracking. Results: Sexual dysfunction is highly prevalent in OCD patients, particularly among women, ranging from low desire and arousal to anorgasmia and pain during intercourse. Sexual obsessions affect a large proportion of OCD patients and are associated with an early onset, male sex, greater symptom severity, poorer insight, and suicidality. These obsessions often co-occur with aggressive or religious themes. Neuroimaging studies indicate distinct patterns of brain activation in patients with sexual obsessions. Treatment with SSRIs and CBT is often less effective in this subgroup, suggesting the need for targeted interventions. Conclusions: Sexuality-related symptoms in OCD patients constitute a distinct and clinically relevant domain that affects functioning, prognosis, and treatment response. Recognizing and addressing these symptoms is essential for the holistic and effective care of patients with OCD. Full article

Inflammatory muscle loss results from excessive inflammatory responses, causing muscle damage and weakness. In the current investigation, we evaluated the protective effects of diphlorethohydroxycarmalol (DPHC) against tumor necrosis factor-alpha (TNF-α)-induced skeletal muscle inflammation and muscle loss and elucidated the underlying mechanisms. Furthermore, the effect of DPHC on swimming performance was confirmed under TNF-α-induced inflammatory muscle loss-conditioned zebrafish by assessing the swimming number, distance moved, time spent swimming, frequency of swimming zebrafishes in an upstream swim track (Zone A). In vivo behavioral endurance test results indicated that TNF-α treatment significantly decreased the number of swimming zebrafish and swimming distance in Zone A compared with the Control. Meanwhile, the DPHC treatment significantly increased the number of swimming zebrafish and swimming distance in Zone A compared to TNF-α-induced zebrafish. These findings indicate that DPHC treatment effectively improved the swimming performance of TNF-α-induced zebrafish. In an additional study, TNF-α significantly induced inflammatory muscle loss by upregulating nuclear factor kappa light chain enhancer of activated B cells (NF-κB) mitogen activated protein kinase (MAPK) associated proteins and MuRF-1 in the skeletal muscle tissues of TNF-α-induced zebrafish. However, DPHC administration significantly counteracted TNF-α-induced inflammation and muscle loss by downregulating NF-Κb and MAPK-associated proteins, as well as the muscle degradation-related proteins MuRF-1 and MAFbx, in the skeletal muscle tissues of TNF-α-induced zebrafish. In summary, our research findings demonstrated that DPHC from Ishige okamurae could be used for the development of nutraceuticals or functional foods targeting inflammatory muscle loss. Full article

In this study, a novel comparison between single phase 7-Level Packed U—Cell (PUC) inverter and single phase 9-Level Cross Switches Cell (CSC) inverter with Model Predictive Controller (MPC) for solar grid-tied applications is presented. Our innovation introduces a unique approach by integrating PV solar panels in PUC and CSC inverters in their two DC links rather than just one which increases power density of the system. Another key benefit for the proposed models lies in their simplified design, offering improved power quality and reduced complexity relative to traditional configurations. Moreover, both models feature streamlined control architectures that eliminate the need for additional controllers such as PI controllers for grid reference current extraction. Furthermore, the implementation of Maximum Power Point Tracking (MPPT) technology directly optimizes power output from the PV panels, negating the necessity for a DC-DC booster converter during integration. To validate the proposed concept’s performance for both inverters, extensive simulations were conducted using MATLAB/Simulink, assessing both inverters under steady-state conditions as well as various disturbances to evaluate its robustness and dynamic response. Both inverters exhibit robustness against variations in grid voltage, phase shift, and irradiation. By comparing both inverters, results demonstrate that the CSC inverter exhibits superior performance due to its booster feature which relies on generating voltage level greater than the DC input source. This primary advantage makes CSC a booster inverter. Full article

The evolution of the winemaking industry towards intelligent and digitalized systems is crucial for precision winemaking and ensuring product safety. In this context, the Internet of Things (IoT) provides a key strategy for real-time monitoring and data management throughout the winemaking process. However, comprehensive multi-parameter IoT-based monitoring and time-series prediction of physicochemical parameters during storage are currently lacking, limiting the ability to assess storage conditions and provide early warning of quality deterioration. To address these gaps, a multi-parameter IoT monitoring system was designed and developed to track conductivity, dissolved oxygen, and temperature in real time. Data were transmitted via a 4th-generation (4G) mobile communication module to the TLINK cloud platform for storage and visualization. An 80-day storage experiment confirmed the system’s reliability for long-term monitoring, and analysis of parameter trends demonstrated its effectiveness in assessing storage conditions and wine quality evolution. Furthermore, Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Temporal Convolutional Network (TCN) models, and Autoregressive Integrated Moving Average (ARIMA) were implemented to predict physicochemical parameter trends. The TCN model achieved the highest predictive performance, with coefficients of determination (R²) of 0.955, 0.968, and 0.971 for conductivity, dissolved oxygen, and temperature, respectively, while LSTM and GRU showed comparable results. These results demonstrate that integrating IoT-based multi-parameter monitoring with deep learning time-series prediction enables real-time detection of abnormal storage and quality deterioration, providing a novel and practical framework for early warning throughout the wine storage process. Full article

Adverse climate events have recently highlighted an increasing need to deploy sustainable energetic infrastructures. The existing electric conversion circuits for solar energy provide high efficiency; however, gaps in sustainability and robustness can be identified by considering their operation during intense perturbations, potentially occurring for interplanetary energy transfer. Additionally, charging characteristics for energy storage units influence differently the operation life of battery arrays, with increased stability providing favorable operating conditions. Therefore, the present study develops an alternative controller for managing solar energy as well as a prototype for tracking the maximum power point, both constrained by robustness and renewability studies. For the presented design, stability analyses and simulations validated the management of electric energy from solar panels and the developed configuration resulted in improving current peak integral transient characteristics by using an alternative control method, demonstrating stability for an indefinite number of energy storage units. Furthermore, the estimation for VLSI (Very-Large-Scale Integration) of this constrained design has been concluded to potentially provide a solution with adequate performance, comparable to state-of-the-art computational circuits. However, certain limitations could arise when substituting the main computation parts with analyzed solutions and proceeding with integration-based manufacturing. Full article

This paper addresses the path tracking problem of underactuated unmanned surface vessels (USVs) in the presence of unknown external disturbances. A fixed-time adaptive integral sliding mode control (AISMC) method, incorporating a nonlinear disturbance observer (NDO), is proposed. Initially, a three-degree-of-freedom dynamic model of the USV is developed, accounting for external disturbances and model uncertainties. Based on the vessel’s longitudinal and transverse dynamic position errors, a virtual control law is designed to ensure fixed-time convergence, thereby enhancing the position error convergence speed. Next, a fixed-time NDO is introduced to estimate real-time external perturbations, such as wind, waves, and currents. The observed disturbances are fed back into the control system for compensation, thereby improving the system’s disturbance rejection capability. Furthermore, a sliding mode surface is designed using a symbolic function to address the issue of sliding mode surface parameter selection, leading to the development of the adaptive integral sliding mode control strategy. Finally, compared with traditional SMC and PID, the proposed AISMC-NDO offers higher accuracy, faster convergence, and improved robustness in complex marine environments. Full article

Target tracking in typical radar applications faces critical challenges in complex environments, including nonlinear dynamics, non-Gaussian noise, and sensor outliers. Current robustness-enhanced approaches remain constrained by empirical kernel tuning and computational trade-offs, failing to achieve balanced noise suppression and real-time efficiency. To address these limitations, this paper proposes the variational Bayesian-based maximum correntropy criterion cubature Kalman filter (VBMCC-CKF), which integrates variational Bayesian inference with CKF to establish a fully adaptive robust filtering framework for nonlinear systems. The core innovation lies in constructing a joint estimation framework of state and kernel size, where the kernel size is modeled as an inverse-gamma distributed random variable. Leveraging the conjugate properties of Gaussian-inverse gamma distributions, the method synchronously optimizes the state posterior distribution and kernel size parameters via variational Bayesian inference, eliminating reliance on manual empirical adjustments inherent to conventional correntropy-based filters. Simulation confirms the robust performance of the VBMCC-CKF framework in both single and multi-target tracking under non-Gaussian noise conditions. For the single-target case, it achieves a reduction in trajectory average root mean square error (Avg-RMSE) by at least 14.33% compared to benchmark methods while maintaining real-time computational efficiency. Integrated with multi-Bernoulli filtering, the method achieves a 40% lower optimal subpattern assignment (OSPA) distance even under 10-fold covariance mutations, accompanied by superior hit rates (HRs) and minimal trajectory position RMSEs in cluttered environments. These results substantiate its precision and adaptability for dynamic tracking scenarios. Full article