Search Results (5,304)

The sufficient capacity of railway lines is a key prerequisite for stable and sustainable transport, not only on main or high-speed lines, but also on lines of regional importance that complement the network. Their indispensable role is manifested not only daily, but especially in the event of incidents on the backbone network. One of the main characteristics of these support lines is that they are largely single-track. Another important characteristic is that they alternate between sections with different traffic loads, which significantly changes the capacity requirements along the whole line. Existing modernisation approaches are frequently implemented in a non-differentiated manner, thereby lacking segment-specific prioritisation. The present paper introduces a novel methodology for systematic identification and the ranking of line sections for capacity upgrades. The approach is comprised of three distinct steps: first, the line is segmented using traffic homogeneity criteria; second, limiting journey times are determined through analytical capacity calculations based on the ninth decile of train volumes; and third, infrastructure measures are identified when the actual journey times exceed these thresholds. Potential interventions encompass the introduction of additional block sections, the implementation of passing loops, or the introduction of double-tracking. The methodology was applied to the Havlíčkův Brod–Jihlava–Znojmo line, thereby demonstrating its ability to detect bottlenecks and propose targeted measures. The findings indicate that there is considerable potential for enhancing capacity while concomitantly improving operational safety and cost efficiency. Consequently, this will serve to reinforce the role of diversionary lines within the broader context of the rail network. The proposed framework provides infrastructure managers with a generalisable tool with which to prioritise investments and support the long-term development of resilient and sustainable railway systems. Full article

When excavating roadways in underground mines, stress redistribution within the surrounding rock mass leads to stress concentration and release. Should the concentrated stresses exceed the rock mass’s tensile or shear strength, rock deformation and failure occur. Thus, a knowledge of stress distribution around the roadway is of great significance for revealing the roadway instability mechanism and design support methods. In this work, the powerful complex variable function theory was used to solve the surrounding rock stress around the triple-arched roadway and the analytical results were verified with the on-site stress state. The results show that the tensile stress occurs on the roadway roof and floor under low lateral stress coefficients, while concentrated compressive stress emerges on the two sidewalls. However, the surrounding stress distribution exhibits an opposite characteristic under high stress levels. Beyond five times the roadway radius, the stress in the surrounding rock is unaffected by the roadway and approaches the in-situ stress. For the +1890 m level trackless transport roadway in Kunyang No. 2 phosphate mine, it is further calculated that the minimum stress concentration factor in the rib area of the roadway within the stress relief zone is 0.34, while the maximum stress concentration factor in the concentrated stress zone of the roof, floor, and sidewalls of the roadway is 5.87. The measured stress values of two monitoring points in the surrounding rock of this roadway are fairly consistent with the analytical values, suggesting the complex variable method for solving excavation-induced stresses are effective and reliable. Full article

In thermal engineering applications, finned surfaces are extensively employed to enlarge the effective heat transfer area and thereby enhance the efficiency of heat exchangers. The present study examines cylindrical tubes externally fitted with rectangular and triangular fins under the condition of a constant transverse cross-sectional area and total fin volume. For all five rectangular fin configurations analyzed, the cross-sectional area and total volume were kept constant, while for the five triangular fin configurations, these parameters were also maintained constant but were approximately half of those of the rectangular fins due to geometric characteristics. Both analytical calculations and numerical simulations using ANSYS Fluent were conducted to evaluate thermal performance across different fin thicknesses and heights. Results show that rectangular fins provide up to 9.75% higher heat flux than triangular fins at the optimal thickness; however, this improvement requires nearly a twofold increase in material consumption. The analysis further indicates that most heat transfer occurs near the fin base, where convective efficiency is highest, with effectiveness diminishing along the extended surface. These findings highlight the importance of selecting fin geometries that balance thermal performance with material economy. In conclusion, this study provides practical insights for designing more efficient and cost-effective heat exchangers. Full article

This study presents nanofractionation analytics coupled with in vivo profiling of zebrafish embryo paralysis and lethality in response to toxins in cone snail venoms. The focus of this study is on the development of this approach using venoms of Conus marmoreus, Conus ebraeus, and Conus bandanus. In brief, cone snail venoms were separated using reversed-phase chromatography following high-resolution nanofractionation on microplates with parallel mass spectrometry, enabled via a post-column flow split. All collected fractions were dried overnight, followed by assays on zebrafish embryos. For the paralysis assessment, we monitored swimming behavior and swimming distance and found that exposure to cone snail toxins led to paralysis and decreased movement and swim distance. To correlate the masses of eluted toxins with their paralyzing effects and potency, we compared the fractionation retention time versus normalized swimming distance. This allowed identification of the masses of toxins with paralyzing bioactivity, which were predominantly conopeptides. To assess lethality, zebrafish embryos were exposed to fractionated toxins for 24 h, after which they were inspected. The lethal doses and correlated toxins were identified by comparing retention times of fractionation versus the lethal dose values calculated for each fraction. We found that the most lethal venom was from C. bandanus, displaying the largest number of lethal peptides, followed by C. marmoreus and C. ebraeus. On the other hand, the most paralytic venom was from C. ebraeus, presenting a higher number of peptides with non-lethal paralytic effects, followed by C. bandanus and C. marmoreus. This study provides a pipeline to rapidly identify paralytic and lethal cone snail venom toxins using the zebrafish embryo model. Full article

Windborne debris generated during tornadoes and hurricanes plays a critical role in building damage. This damage occurs either through direct impact on structural and nonstructural components or indirectly by increasing internal pressure when debris penetrates openings (e.g., windows and doors) or creates new ones. These breaches can significantly raise internal pressure, even at lower wind speeds compared to debris-free conditions. Current provisions in ASCE 7, the nationally adopted standard for wind load calculations in the United States, account for factors such as building geometry, location, and exposure category. However, they do not consider the effects of windborne debris on internal pressure coefficients. This study proposes an enhancement to ASCE 7 by incorporating debris effects through the use of a more conservative enclosure classification. Real-world damage observations from three tornado-impacted residential buildings are presented, followed by a failure mechanism analysis, supporting analytical fragility data, and numerical simulations of debris effects on building damage. The findings suggest that treating buildings as Partially Enclosed under ASCE 7 can more accurately reflect debris-induced internal pressures and improve building resilience under extreme wind events. Full article

Background/Objectives: Screening for late-onset and term preeclampsia (PE) is essential, as the early identification of women at high risk enables closer monitoring and reduces adverse outcomes. The existing algorithms combining maternal factors, biophysical and biochemical markers have not been validated outside the populations in which they were originally developed. This study aimed to evaluate the predictive performance of the Fetal Medicine Foundation (FMF) third-trimester algorithm in our population and develop a novel model to improve the predictions. Methods: An observational, analytical, prospective cohort follow-up study was conducted at the Health Department of Alicante, Dr. Balmis General University Hospital, including 1580 singleton pregnancies recruited between February 2022 and November 2023 during routine third-trimester ultrasounds. Maternal clinical characteristics, blood pressure, the uterine artery pulsatility index (UtA-PI), and the sFlt-1/PlGF ratio were recorded. The FMF third-trimester algorithm was retrospectively applied at the end of pregnancy using clinical, biophysical, and biochemical data from 30 + 0 to 37 + 6 weeks via the freely accessible online calculator. The data analysis was performed using SPSS v.28 and R v.4.3.1. Results: A total of 1580 women were included, with a prevalence of late-onset PE of 2.9%. The FMF model achieved an area under the curve (AUC) of 0.87 (95% CI: 0.81–0.92), while our own model showed a superior performance, with an AUC of 0.94 (95% CI: 0.92–0.97). Conclusions: The FMF third-trimester algorithm demonstrated a good predictive performance for late-onset PE. Our newly developed model achieves an even higher predictive accuracy and offers a simplified approach to excluding the UtA-PI, which facilitates its use in routine clinical practice. Full article

The exponential growth of space objects in near-Earth and geostationary orbits has posed severe threats to space environment safety, with debris clouds from spacecraft breakup events being a critical concern. Debris cloud tracing, as a key technology for locating breakup points, faces dual challenges of insufficient precision in analytical methods and excessive computational load in numerical methods. To balance traceability accuracy with computational efficiency, this paper proposes a breakup time determination method integrating a clustering algorithm and the minimization of average relative distance. The method first calculates the average relative distance between fragment pairs and preliminarily estimates the breakup epoch using a golden section step-size optimization strategy. Subsequently, the density peak clustering (DPC) algorithm is introduced to eliminate abnormal fragments. The breakup epoch is then refined based on the cleansed fragment dataset, achieving high-precision localization. Validation through simulations of real breakup events demonstrates that this method significantly improves localization accuracy. It establishes a highly reliable temporal benchmark for space collision tracing, debris diffusion prediction, and orbital safety management. Full article

To explore the application of precast concrete construction methods in underground stations, a combined precast and cast in situ construction method was adopted for a long-span column-free underground subway station. To study the stability of large-span underground arch structures under asymmetric loading, a full-scale test was conducted using the displacement-force control method. Steel blocks were used to simulate the overlying soil and additional loads on the upper surface of the arch, while the displacement of the arch foot was applied by adjusting the tension of the cables. The maximum tensile stress and maximum compressive stress of the steel bars appeared at the midpoints of the left and right arches, which were less than the yield stress of the steel bars. The results show that the structural stability meets the design requirements and provides a considerable safety margin. A comprehensive analysis of the arch structure under asymmetric loading was carried out through on-site monitoring, numerical simulation, and analytical solutions. The results are in good agreement: compared with the experimental results, the calculated values increase the maximum deflection of the arch by 13.67%, which verifies the reliability of the numerical simulation and analytical solution methods under the same boundary conditions. However, restricted by test conditions, the loading in this study was only applied on one side of the arch crown, which differs from the actual working condition involving full loading first followed by unloading on one side. Full article

The paper presents a hybrid intelligent expert diagnostic system (HIESD) of power transformer (PT) subsystems realized on the basis of integration of measuring and computing hardware and software complexes into a single functional architecture. HIESD performs online diagnostics of four main subsystems of PT: 1—insulating (liquid and solid insulation); 2—electromagnetic (windings, magnetic conductor); 3—voltage regulation; and 4—high-voltage inputs. Computational complexes and modules of the system are connected with the real object of power grids, 110/10 kV substation, which interact with each other and contain a relational database of retrospective offline data of the PT “life cycle” (including test and measurement results), supplemented by online monitoring data of the main subsystems, corrected by high-precision test measurements; analytical complex, in which the work of calculation modules of the operational state of PT subsystems is supplemented by predictive analytics and machine learning modules; and a knowledge base, sections of which are regularly updated and supplemented. The system architecture is tested at industrial facilities in terms of online transformer diagnostics based on dissolved gas analysis (DGA) data. Additionally, a theoretical model of diagnostics based on the electromagnetic characteristics of the transformer, which takes into account distorted and nonlinear modes of its operation, is presented. The scientific significance of the work consists of the presentation of the following new provisions: Methodology and algorithm for diagnostics of electromagnetic parameters of ST, taking into account nonlinearity and non-sinusoidality of winding currents and voltages; formation of optimal client–service architecture of training models of hybrid system based on the processes of data storage and management; and modification of the moth–flame algorithm to optimize the smoothing coefficient in the process of training a probabilistic neural network Full article

The integration of solar generation into national energy balances is associated with a wide range of technical, economic, and organizational challenges, the solution of which requires the adoption of innovative strategies for energy system management. The inherent variability of electricity production, driven by fluctuating climatic conditions, complicates system balancing processes and necessitates the reservation of capacities from conventional energy sources to ensure reliability. Under modern market conditions, the pricing of generated electricity is commonly based on day-ahead forecasts of day energy yield, which significantly affects the economic performance of solar power plants. Consequently, achieving high accuracy in day-ahead electricity production forecasting is a critical and highly relevant task. To address this challenge, a physico-statistical model has been developed, in which the analytical approximation of daily electricity generation is represented as a function of a random variable—cloud cover—modeled by a β-distribution. Analytical expressions were derived for calculating the mathematical expectation and variance of daily electricity generation as functions of the β-distribution parameters of cloudiness. The analytical approximation of daily generation deviates from the exact value, obtained through hourly integration, by an average of 3.9%. The relative forecasting error of electricity production, when using the mathematical expectation of cloudiness compared to the analytical approximation of daily generation, reaches 15.2%. The proposed forecasting method, based on a β-parametric cloudiness model, enhances the accuracy of day-ahead production forecasts, improves the economic efficiency of solar power plants, and contributes to strengthening the stability and reliability of power systems with a substantial share of solar generation. Full article

The second virial coefficient (SVC) of the Lennard-Jones fluid is a cornerstone of molecular theory, yet its calculation has traditionally relied on the complex integration of the pair potential. This work introduces a fundamentally different approach by reformulating the problem in terms of ordinary differential equations (ODEs). For the classical component of the SVC, we generalize the confluent hypergeometric and Weber–Hermite equations. For the first quantum correction, we present entirely new ODEs and their corresponding exact-analytical solutions. The most striking result of this framework is the discovery that these ODEs can be transformed into Schrödinger-like equations. The classical term corresponds to a harmonic oscillator, while the quantum correction includes additional inverse-power potential terms. This formulation not only provides a versatile method for expressing the virial coefficient through a linear combination of functions (including Kummer, Weber, and Whittaker functions) but also reveals a profound and previously unknown mathematical structure underlying a classical thermodynamic property. Full article

YKL-40 is a glycoprotein that may be present at elevated levels in many cancers and neurodegenerative diseases. It has been investigated in numerous studies as a potential biomarker for several conditions, including Alzheimer’s Disease (AD). In this study, a biosensor with Surface Plasmon Resonance imaging (SPRi) detection, sensitive to YKL-40, was constructed for the detection of this analyte in the blood plasma of AD patients. Extensive validation of the biosensor was performed. This included the determination of analytical parameters such as the biosensor’s response characteristics, detection and quantification limits, precision, accuracy, repeatability, selectivity, stability, and performance in natural samples. Validation parameters were primarily tested using standard solutions, while natural samples were employed to evaluate repeatability, stability, and assay accuracy in three groups of samples from different patients. A YKL-40-specific antibody was used as the receptor layer, immobilized on a gold plate using the EDC/NHS protocol on thiol 11-MUA. The biosensor exhibited a wide operating range (1–200 ng/mL), a low detection limit (LOD) of 2 pg/mL, and a quantification limit (LOQ) of 7 pg/mL. High precision and accuracy were confirmed by the calculated standard deviations (SD) and coefficients of variation (CV), which ranged from 0.0009 to 7.02 ng/mL and from 0.12% to 9.24%, respectively. The sensor also demonstrated good repeatability (CV = 4.995%) and was capable of detecting the analyte of interest in complex biological matrices. Its applicability was confirmed in a study using plasma from AD patients and two selected control groups: plasma from smokers and patients with prostatitis. This allowed the assessment of YKL-40 levels across different groups. The results were consistent with literature values, and statistical analysis confirmed the significance of concentration differences between groups. Furthermore, ROC curve analysis confirmed the diagnostic usefulness of the constructed YKL-40 test in the context of Alzheimer’s disease. Full article

Background: Orthopedic scientific publications play an important role worldwide. Because of the limited evidence in the Latin American literature, we aimed to evaluate the determinants of scientific publication among Peruvian orthopedics as an approach to the Latin American context. Methods: Analytical cross-sectional study. Orthopedic specialists and residents were enrolled during the 52nd Peruvian National Congress of Orthopedics and Traumatology. A form validated by experts was applied to collect variables. The crude and adjusted coefficients were calculated using bivariate and multivariate regression with 95% confidence intervals. Results: A total of 310 participants were included in our study. The prevalence of the scientific orthopedic publication was 34.84%. Multivariate regression showed that, working in a private hospitals, having an interest in tumors and pediatric orthopedics, being involved in teaching activity, belonging to a scientific society other than the Peruvian Society of Orthopedics and Traumatology, having more than one research project, having an international rotation, and active participation in meetings were factors associated with publishing orthopedic scientific articles, while coming from a university in the highlands as an undergraduate and having more than ten shifts per month was associated with publishing fewer scientific articles. Among residents, having had an international rotation was associated with publishing scientific articles. Conclusions: The determinants of scientific production described will serve to increase scientific production in different contexts considering the orthopedist’s training stage. Full article

The electromagnetic density of states (EM-DOS) plays a crucial role in understanding light–matter interactions, especially at metal–dielectric interfaces. This study explores the impact of interface geometry, material properties, and nanostructures on EM-DOS, with a focus on surface plasmon polaritons (SPPs) and evanescent waves. Using a combination of analytical and numerical methods, the behavior of EM-DOS is analyzed as a function of distance from metal–dielectric interfaces, showing exponential decay with penetration depth. The influence of different metals, including copper, gold, and silver, on EM-DOS is examined. Additionally, the effects of dielectric materials, such as Ti${\mathrm{O}}_2$, PMMA, and ${\mathrm{Al}}_2$${\mathrm{O}}_3$, on the enhancement of electromagnetic field confinement are discussed. The study also investigates the effect of nanostructures, like nanohole and nanopillar arrays, on EM-DOS by calculating effective permittivity and analyzing the interaction of quantum emitters with these structures. Results show that nanopillar arrays enhance EM-DOS more effectively than nanohole arrays, especially in the visible spectrum. The findings provide insights into optimizing plasmonic devices for applications in sensing, quantum technologies, and energy conversion. Full article

Food industry generates substantial waste, raising economic and environmental concerns. Green Chemistry (GC) highlights the extraction of nutritional and bioactive compounds as a key strategy for waste valorization, driving interest in sustainable methods to recover valuable compounds efficiently. This review evaluates the sustainability of widely used emerging extraction technologies—Microwave-, Ultrasound- and Enzyme-Assisted, as well as Supercritical Fluid Extraction—and their alignment with GC principles for agri-food waste valorization. It first outlines the principles, key parameters, and main advantages and limitations of each technique. Subsequently, sustainability is then assessed in selected studies using the Analytical GREEnness Metric Approach (AGREEprep). By calculating the greenness score (GS), this metric quantifies the adherence of extraction processes to sustainability standards. The analysis reveals variations within the same extraction method, influenced by solvent choice and operating conditions, as well as differences across the techniques, highlighting the importance of process design in achieving green and efficient valorization. Full article