Search Results (1,921)

Determining the transmission routes of pathogens in indoor environments is challenging, with most studies limited to specific case analyses and pilot experiments. When pathogens are instantaneously released by a patient in an indoor environment, the peak infection risk may not occur immediately but may instead appear at a specific moment during the pathogen’s spread. We developed a concise model to describe the temporal crest of infection risk. The model incorporates the transmission and degradation characteristics of aerosols and surface particles to predict infection risks via air and surface routes. Only four real-world outbreaks met the criteria for validating this phenomenon. Based on the available data, norovirus is likely to transmit primarily via surface touch (i.e., the fomite route). In contrast, crests of infection risk were not observed in outbreaks of respiratory diseases (e.g., SARS-CoV-2), suggesting a minimal probability of surface transmission in such cases. The new model can serve as a preliminary indicator for identifying different indoor pathogen transmission routes (e.g., food, air, or fomite). Further analyses of pathogens’ transmission routes require additional evidence. Full article

In this study, we investigate the return propagation mechanism, hedging effectiveness, and portfolio performance across several common agricultural commodities, crude oil, and S&P 500 index, ranging from July 2000 to June 2024 by using a time-varying parameter vector autoregression (TVP-VAR) connectedness approach and three common multiple assets portfolio optimization strategies. The empirical results show that, the total connectedness peaked during the 2008 global financial crisis, followed by the European debt crisis and the COVID-19 pandemic, while it remained relatively lower at the onset of the Russia-Ukraine conflict. In the transmission mechanism, commodities and S&P 500 index exhibit distinct and dynamic characteristics as transmitters or receivers. Portfolio analysis reveals that, with exception of the COVID-19 pandemic, all three dynamic portfolios outperform the S&P 500 benchmark across major global crises. Additionally, the minimum correlation and minimum connectedness strategies are superior than transitional minimum variance method in most scenarios. Our findings have implications for policymakers in preventing systemic risk, for investors in managing portfolio risk, and for farmers and agribusiness enterprises in enhancing economic benefits. Full article

This study investigates the seasonal dynamics of energy balance, evapotranspiration (ET), and Net Ecosystem Production (NEP) in the Dengkou desert ecosystem of Inner Mongolia, China. Using eddy covariance and meteorological data from 2019 to 2022, the research focuses on understanding how these processes interact in one of the world’s most water-limited environments. This arid research area received an average of 109.35 mm per annum precipitation over the studied period, classifying the region as a typical arid ecosystem. Seasonal patterns were observed in daily air temperature, with extremes ranging from −20.6 °C to 29.6 °C. Temporal variations in sensible heat flux (H), latent heat flux (LE), and net radiation (Rn) peaked during summer season. The average ground heat flux (G) was mostly positive throughout the observation period, indicating heat transmission from atmosphere to soil, but showed negative values during the winter season. The energy balance ratio for the studied period was in the range of 0.61 to 0.80, indicating challenges in achieving energy closure and ecological shifts. ET exhibited two annual peaks influenced by vegetation growth and climate change, with annual ET exceeding annual precipitation, except in 2021. Net ecosystem production (NEP) from 2019 to 2020 revealed that the Dengkou desert were a net source of carbon, indicating the carbon loss from the ecosystem. In 2021, the Dengkou ecosystem shifted to become a net carbon sink, effectively sequestrating carbon. However, this was sharply reversed in 2022, resulting in a significant net release of carbon. The study findings highlight the complex interactions between energy balance components, ET, and NEP in desert ecosystems, providing insights into sustainable water management and carbon neutrality strategies in arid regions under climate change effect. Full article

In order to correctly measure the shock wave pressure generated by a near-field explosion, and while considering the limitations of the measurement and calibration method of the current bar pressure sensor, an improved shock wave pressure measurement method was designed based on a bar pressure sensor combined with photon Doppler velocimetry (PDV) and strain measurement. By measuring the strain on the pressure bar and the particle velocity on the rear-end face, the shock wave pressure applied on the front-end face of the pressure bar was calculated based on one-dimensional stress wave theory. On the other hand, a calibration method was designed to validate the reliability of the test system. Based on the split-Hopkinson pressure bar (SHPB) loading experiment, the transmission characteristics of stress wave in the bar and the accuracy of the system test results were verified. The results indicated that the stress wave measurement results were consistent with the one-dimensional elementary theoretical calculation results of stress wave propagation in different wave-impedance materials, and the peak deviation measured by PDV and strain measurement method was less than 1.5%, which proved the accuracy of the test method and the feasibility of the calibration method. Full article

Background: Faced with the profound impact of major infectious diseases on public life and economic development, humans have long sought to understand disease transmission and intervention strategies. To better explore the impact of individuals’ different coping behaviors—triggered by changes in their psychological security due to public information and external environmental changes—on the spread to infectious diseases, the model will place greater emphasis on quantifying psychological factors to make it more aligned with real-world situations. Methods: To better understand the interplay between information dissemination and disease transmission, we propose a two-layer network model that incorporates psychological safety factors. Results: Our model reveals key insights into disease transmission dynamics: (1) active defense behaviors help reduce both disease spread and information diffusion; (2) passive resistance behaviors expand disease transmission and may trigger recurrence but enhance information spread; (3) high-timeliness, low-fuzziness information reduces the peak of the initial infection but does not significantly curb overall disease spread, and the rapid dissemination of disease-related information is most effective in limiting the early stages of transmission; and (4) community structures in information networks can effectively curb the spread of infectious diseases. Conclusions: These findings offer valuable theoretical support for public health strategies and disease prevention after government information release. Full article

Addressing the challenges of bulky, low-efficiency sound-insulation materials at low frequencies, this work proposes an acoustic metamaterial based on curve fractal channels. Each unit cell comprises a concentric circular-ring channel recursively iterated: as the fractal order increases, the channel path length grows exponentially, enabling outstanding sound-insulation performance within a deep-subwavelength thickness. Finite-element and transfer-matrix analyses show that increasing the fractal order from one to three raises the number of bandgaps from three to five and expands total stop-band coverage from 17% to over 40% within a deep-subwavelength thickness. Four-microphone impedance-tube measurements on the third-order sample validate a peak transmission loss of 75 dB at 495 Hz, in excellent agreement with simulations. Compared to conventional zigzag and Hilbert-maze designs, this curve fractal architecture delivers enhanced low-frequency broadband insulation, structural lightweighting, and ease of fabrication, making it a promising solution for noise control in machine rooms, ducting systems, and traffic environments. The method proposed in this paper can be applied to noise reduction of transmission parts for ceramic automation production. Full article

Pain following orthodontic treatment is the chief complaint of patients undergoing this form of treatment. Although the use of diode lasers has been suggested for pain reduction, the mechanism of laser-induced analgesic effects remains unclear. Neuropeptides, such as substance P (SP) and calcitonin gene-related peptide (CGRP), contribute to the transmission and maintenance of inflammatory pain. Heat shock protein (HSP) 70 plays a protective role against various stresses, including orthodontic forces. This study aimed to examine the effects of diode laser irradiation on neuropeptides and HSP 70 expression in periodontal tissues induced by experimental tooth movement (ETM). For inducing ETM for 24 h, 50 g of orthodontic force was applied using a nickel–titanium closed-coil spring to the upper left first molar and the incisors of 20 male Sprague Dawley rats (7 weeks old). The right side without ETM treatment was considered the untreated control group. In 10 rats, diode laser irradiation was performed on the buccal and palatal sides of the first molar for 90 s with a total energy of 100.8 J/cm². A near-infrared (NIR) laser with a 808 nm wavelength, 7 W peak power, 560 W average power, and 20 ms pulse width was used for the experiment. We measured the number of facial groomings and vacuous chewing movements (VCMs) in the ETM and ETM + laser groups. Immunohistochemical staining of the periodontal tissue with SP, CGRP, and HSP 70 was performed. The number of facial grooming and VCM periods significantly decreased in the ETM + laser group compared to the ETM group. Moreover, the ETM + laser group demonstrated significant suppression of SP, CGRP, and HSP 70 expression. These results suggest that the diode laser demonstrated analgesic effects on ETM-induced pain by inhibiting SP and CGRP expression, and decreased HSP 70 expression shows alleviation of cell damage. Thus, although further validation is warranted for human applications, an NIR diode laser can be used for reducing pain and neuropeptide markers during orthodontic tooth movement. Full article

In high-dynamic bipedal locomotion control, robotic systems are often constrained by motor torque limitations, particularly during explosive tasks such as jumping. One of the key challenges in reinforcement learning lies in bridging the sim-to-real gap, which mainly stems from both inaccuracies in simulation models and the limitations of motor torque output, ultimately leading to the failure of deploying learned policies in real-world systems. Traditional RL methods usually focus on peak torque limits but ignore that motor torque changes with speed. By only limiting peak torque, they prevent the torque from adjusting dynamically based on velocity, which can reduce the system’s efficiency and performance in high-speed tasks. To address these issues, this paper proposes a reinforcement learning jump-control framework tailored for tendon-driven bipedal robots, which integrates dynamic torque boundary constraints and torque error-compensation modeling. First, we developed a torque transmission coefficient model based on the tendon-driven mechanism, taking into account tendon elasticity and motor-control errors, which significantly improves the modeling accuracy. Building on this, we derived a dynamic joint torque limit that adapts to joint velocity, and designed a torque-aware reward function within the reinforcement learning environment, aimed at encouraging the policy to implicitly learn and comply with physical constraints during training, effectively bridging the gap between simulation and real-world performance. Hardware experimental results demonstrate that the proposed method effectively satisfies actuator safety limits while achieving more efficient and stable jumping behavior. This work provides a general and scalable modeling and control framework for learning high-dynamic bipedal motion under complex physical constraints. Full article

Background: Despite decades of high childhood vaccination coverage, pertussis has re-emerged in the Autonomous Province of Vojvodina (AP Vojvodina), Serbia. We aimed to describe the temporal, seasonal, and age-specific patterns of pertussis in AP Vojvodina and to analyze trends by vaccination status in order to highlight changes in epidemiology and potential gaps in vaccine-induced protection. Methods: We retrospectively analyzed 2796 pertussis cases reported between January 1997 and December 2024, examining temporal, seasonal, and age-specific trends, stratifying by vaccination status across four consecutive periods (1997–2003, 2004–2010, 2011–2017, and 2018–2024). Results: Throughout the 28-year period, after low and sporadic cases in the pre-2012 period, a dramatic rise was observed in 2014, 2017, and 2018, culminating in the highest annual number of reported cases in 2024 (1011 cases). Throughout this period, primary vaccination coverage with the DTwP/DTaP three-dose series ranged between 91% and 98%, while first booster coverage gradually declined from 98% in the early 2000s to 83% in 2024. Regarding seasonality, a sharp increase in cases began in 2012, peaking in November 2023 (>350 cases) and early 2024 (312 in January, 268 in February), with a seasonal shift from summer peaks in the 2011–2017 period to higher incidence rates during colder months more recently. Adolescents aged 10–14 years had the highest cumulative incidence (1149.4/100,000), followed by infants under 12 months (978.5/100,000), despite the latter representing fewer absolute cases. The proportion of pertussis in fully vaccinated individuals rose from 6.3% (1997–2003) to 49.7% (2018–2024). Conclusions: These findings suggest that booster immunization in adolescence and routine maternal vaccination during pregnancy could reduce transmission, particularly to infants. Enhanced surveillance and updated immunization policies are critical to mitigating future pertussis outbreaks. Full article

Accurate peak detection in the frequency domain is fundamental to reliable range estimation in Frequency-Modulated Continuous-Wave (FMCW) radar systems, particularly in challenging conditions characterized by a low signal-to-noise ratio (SNR) and phase noise impairments. This paper presents a comprehensive comparative analysis of five peak detection algorithms: FFT thresholding, Cell-Averaging Constant False Alarm Rate (CA-CFAR), a simplified Matrix Pencil Method (MPM), SVD-based detection, and a novel Learned Thresholded Subspace Projection (LTSP) approach. The proposed LTSP method leverages singular value decomposition (SVD) to extract the dominant signal subspace, followed by signal reconstruction and spectral peak analysis, enabling robust detection in noisy and spectrally distorted environments. Each technique was analytically modeled and extensively evaluated through Monte Carlo simulations across a wide range of SNRs and oscillator phase noise levels, from $-100$ dBc/Hz to $-70$ dBc/Hz. Additionally, real-world validation was performed using a custom-built harmonic FMCW radar prototype operating in the 2.4–2.5 GHz transmission band and 4.8–5.0 GHz harmonic reception band. Results show that CA-CFAR offers the highest resilience to phase noise, while the proposed LTSP method delivers competitive detection performance with improved robustness over conventional FFT and MPM techniques. Furthermore, the hardware feasibility of each algorithm is assessed for implementation on a Xilinx FPGA platform, highlighting practical trade-offs between detection performance, computational complexity, and resource utilization. These findings provide valuable guidance for the design of real-time, embedded FMCW radar systems operating under adverse conditions. Full article

During the COVID-19 pandemic, some studies suggested that transmission events could originate from schools. This study aimed to evaluate early-warning methods for identifying asymptomatic COVID-19 cases by implementing screening programs in schools. This study was conducted between September 2021 and May 2023, employing a rotation-screening plan for COVID-19 detection on a sample of students aged 14 to 19 years attending secondary schools in the regions of Tuscany, Veneto, Apulia and Friuli-Venezia Giulia. The schools were divided into two groups: experimental and control, with a ratio of 1:2. Two types of molecular salivary tests for SARS-CoV-2 were used to conduct the screening. This study included 16 experimental schools and 32 control schools. Out of 2527 subjects, 11,475 swabs were administrated, with 9177 tests deemed valid for analysis (a 20% loss of tests). Among these, 89 subjects (3.5%) tested positive. In control schools, 1895 subjects (6.5%) tested positive for SARS-CoV-2. This study recorded peaks in infections during the winter and autumn months, consistent with patterns observed in the general population. Beginning in September 2022, a shift occurred, with 2.6% of positive cases reported in the case schools compared to 0.3% in the control schools. Initially, most cases of COVID-19 were detected in the control schools; however, as the pandemic emergency phase concluded, cases were primarily identified through active screening in experimental schools. Although student participation in the active screening campaign was low during the project’s extension phase, this approach was efficacious in the early identification of positive cases. Full article

In order to obtain the optimal heat treatment process of Er-containing 7075 aluminum alloy, the effects of pre-stretching and the interval time between pre-stretching and aging on the microstructure and mechanical properties of Er-containing 7075 aluminum alloy during solution treatment followed by pre-stretching and two-stage aging processes were investigated by mechanical property tests, metallographic tests, scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The results show that the mechanical properties of Er-containing 7075 aluminum alloy can be significantly improved by increasing the extrusion ratio. Pre-stretching provides nucleation sites for the precipitation of reinforcing phases, accelerates the aging strengthening process, and shortens the peak aging time. The crack source of fracture in Er-containing 7075 aluminum alloy is attributed to the segregated second phases containing Cu and Er in the alloy. The research results have significant engineering significance for the optimization of the heat treatment process of Er-containing 7075 aluminum alloy. Full article

Downhole kick is one of the most severe safety hazards in deep and ultra-deep well drilling operations. Traditional monitoring methods, which rely on surface flow rate and fluid level changes, are limited by their delayed response and insufficient sensitivity, making them inadequate for early warning. This study proposes a real-time monitoring technique for gas content in drilling fluid based on the attenuation principle of Ba-133 γ-rays. By integrating laboratory static/dynamic experiments and Geant4-11.2 Monte Carlo simulations, the influence mechanism of gas–liquid two-phase media on γ-ray transmission characteristics is systematically elucidated. Firstly, through a comparative analysis of radioactive source parameters such as Am-241 and Cs-137, Ba-133 (main peak at 356 keV, half-life of 10.6 years) is identified as the optimal downhole nuclear measurement source based on a comparative analysis of penetration capability, detection efficiency, and regulatory compliance. Compared to alternative sources, Ba-133 provides an optimal energy range for detecting drilling fluid density variations, while also meeting exemption activity limits (1 × 10⁶ Bq) for field deployment. Subsequently, an experimental setup with drilling fluids of varying densities (1.2–1.8 g/cm³) is constructed to quantify the inverse square attenuation relationship between source-to-detector distance and counting rate, and to acquire counting data over the full gas content range (0–100%). The Monte Carlo simulation results exhibit a mean relative error of 5.01% compared to the experimental data, validating the physical correctness of the model. On this basis, a nonlinear inversion model coupling a first-order density term with a cubic gas content term is proposed, achieving a mean absolute percentage error of 2.3% across the full range and R² = 0.999. Geant4-based simulation validation demonstrates that this technique can achieve a measurement accuracy of ±2.5% for gas content within the range of 0–100% (at a 95% confidence interval). The anticipated field accuracy of ±5% is estimated by accounting for additional uncertainties due to temperature effects, vibration, and mud composition variations under downhole conditions, significantly outperforming current surface monitoring methods. This enables the high-frequency, high-precision early detection of kick events during the shut-in period. The present study provides both theoretical and technical support for the engineering application of nuclear measurement techniques in well control safety. Full article

Island electrical networks often face stability and resilience issues due to their weakly meshed structure, which lowers system inertia and compromises supply continuity. This challenge is further intensified by the increasing integration of renewable energy sources, promoted by decarbonization goals, whose intermittent and variable nature complicates grid stability management. To address this, Red Eléctrica de España—the transmission system operator of Spain—has planned several improvements in the Canary Islands, including the installation of new wind farms and a second transmission circuit on the island of La Palma. This new infrastructure will complement the existing one and ensure system stability in the event of N-1 contingencies. This article evaluates the stability of the island’s electrical network through dynamic simulations conducted in PSS^®E, analyzing four distinct fault scenarios across three different grid configurations (current, short-term upgrade and long-term upgrade with wind integration). Generator models are based on standard dynamic parameters (WECC) and calibrated load factors using real data from the day of peak demand in 2021. Results confirm that the planned developments ensure stable system operation under severe contingencies, while the integration of wind power leads to a 33% reduction in diesel generation, contributing to improved environmental and operational performance. Full article

The icebreaking process of water-exiting vehicles involves complex nonlinear interactions as well as multi-physical field coupling effects among ice, solids, and fluids, which poses enormous challenges for numerical calculations. Addressing the low solution accuracy of traditional grid methods in simulating large deformation and destruction of ice layers, a numerical model was established based on the FEM-SPH-SALE coupling algorithm to study the dynamic characteristics of the water-exiting vehicle on the icebreaking process. The FEM-SPH adaptive algorithm was used to simulate the damage performance of ice, and its feasibility was verified through the four-point bending test and vehicle breaking ice experiment. The S-ALE algorithm was used to simulate the process of fluid/structure interaction, and its accuracy was verified through the wedge-body water-entry test and simulation. On this basis, numerical simulations were performed for different ice thicknesses and initial velocities of vehicles. The results show that the motion characteristics of the vehicle undergoes a sudden change during the ice-breaking. The head and middle section of the vehicle are subject to greater stress, which is related to the transmission of stress waves and inertial effect. The velocity loss rate of the vehicle and the maximum stress increase with the thickness of ice. The higher the initial velocity of the vehicle, the larger the acceleration and maximum stress in the process of the vehicle breaking ice. The acceleration peak is sensitive to the variation in the vehicle’s initial velocity but insensitive to the thickness of the ice. Full article