Search Results (2,541)

This paper presents a symmetry-driven broadband circularly polarized magnetoelectric dipole antenna with bandpass filtering response, where the principle of symmetry is strategically employed to enhance both radiation and filtering performance. The antenna’s circular polarization is achieved through a symmetrical arrangement of two orthogonally placed metallic ME dipoles combined with a phase delay line, creating balanced current distributions for optimal CP characteristics. The design further incorporates symmetrical parasitic elements—a pair of identical inverted L-shaped metallic structures placed perpendicular to the ground plane at −45° relative to the ME dipoles—which introduce an additional CP resonance through their mirror-symmetric configuration, thereby significantly broadening the axial ratio bandwidth. The filtering functionality is realized through a combination of symmetrical modifications: grid slots etched in the metallic ground plane and an open-circuited stub loaded on the microstrip feed line work in tandem to create two radiation nulls in the upper stopband, while the inherent symmetrical properties of the ME dipoles naturally produce a radiation null in the lower stopband. This comprehensive symmetry-based approach results in a well-balanced bandpass filtering response across a wide operating bandwidth. Experimental validation through prototype measurement confirms the effectiveness of the symmetric design with compact dimensions of 0.96${\lambda }_0$ × 0.55${\lambda }_0$ × 0.17${\lambda }_0$ (${\lambda }_0$ is the wavelength at the lowest operating frequency), demonstrating an impedance bandwidth of 66.4% (2.87–5.05 GHz), an AR bandwidth of 31.9% (3.32–4.58 GHz), an average passband gain of 5.5 dBi, and out-of-band suppression levels of 11.5 dB and 26.8 dB at the lower and upper stopbands, respectively, along with good filtering performance characterized by a gain-suppression index (GSI) of 0.93 and radiation skirt index (RSI) of 0.58. The proposed antenna is suitable for satellite communication terminals requiring wide AR bandwidth and strong interference rejection in L/S-bands. Full article

Understanding how flowering phenology varies across spatial scales is essential for assessing plant responses to environmental heterogeneity under climate change. In this study, we investigated the flowering phenology of the plant species Taraxacum officinale across five sites in an agricultural region of Wanju, Republic of Korea. Each site contained five 1 m × 1 m quadrats, where the number of flowering heads was recorded at 1- to 2-day intervals during the spring flowering period (February to May). We applied the nlstimedist package in R to model flowering distributions and to estimate key phenological metrics including flowering onset (5%), peak (50%), and end (95%). The results revealed substantial variation in flowering timing and duration at both the intra-site (quadrat-level) and inter-site (site-level) scales. Across all sites, the mean onset, peak, end, and duration of flowering were day of year (DOY) 89.6, 101.5, 117.6, and 28.0, respectively. Although flowering onset showed relatively small variation across sites (DOY 88 to 92), flowering peak (DOY 97 to 108) and end dates (DOY 105 to 128) exhibited larger differences at the site level. Sites with dry soils and regularly mowed Zoysia japonica vegetation with minimal understory exhibited shorter flowering durations, while those with moist soils, complex microtopography, and diverse slope orientations showed delayed and prolonged flowering. These findings suggest that microhabitat variability—including landform type, slope direction, soil water content, and soil temperature—plays a key role in shaping local flowering dynamics. Recognizing this fine-scale heterogeneity is essential for improving phenological models and informing site-specific climate adaptation strategies. Full article

This study aims to explore the factors and mechanisms influencing the low-carbon development of Green Port Collection and Distribution Systems (GPCDSs) and to identify effective pathways and policy approaches to promote such development. Given the limited prior research integrating low-carbon policies, energy structure, and transportation systems, this study combines these three dimensions into a unified analytical framework. A scenario-based system dynamics model of GPCDS low-carbon development is established, incorporating factors such as low-carbon policies, energy structure, and transportation structure. The control variable method is employed to examine system behavior under 13 scenarios. The results indicate that freight subsidy policies and the internalization of carbon emission costs make the most substantial contributions to low-carbon development in GPCDS, yielding CO₂ emission reductions of 14.3% and 15.7%, respectively. Additionally, improvements in port railway infrastructure contribute to a 6.4% reduction in CO₂ emissions. In contrast, carbon taxes and energy structure adjustments have relatively limited effects, likely due to the delayed responsiveness of fossil fuel-dependent transportation sectors to pricing signals and the inherent inertia in transitioning energy systems. Full article

Objective: Our objective was to investigate the short-term effects of ambient ozone (O₃) meteorological factors and their interactions on hospitalizations for cerebral infarction in Zhengzhou, China. Methods: Daily data on air pollutants, meteorological factors, and hospitalization of cerebral infarction patients were collected from 1 January 2019 to 31 December 2023 in Zhengzhou, China. A generalized additive model was constructed to evaluate the association between ambient O₃ levels and hospitalization for cerebral infarction. A distributed lag non-linear model was applied to capture lagged and non-linear exposure effects. We further examined the modifying roles of temperature, humidity, wind speed, and atmospheric pressure, and conducted stratified analyses by sex, age, and season. Results: O₃ exposure was significantly associated with increased cerebral infarction risk, particularly during the warm season. A bimodal temperature-lag pattern was observed, as follows: moderate temperatures (10–20 °C) were associated with immediate effects, while cold (<10 °C) and hot (>30 °C) temperatures were linked to delayed risks. The association of O₃ and hospitalizations for cerebral infarction appeared stronger under high humidity, low wind speed, and low atmospheric pressure. Conclusions: Short-term O₃ exposure and adverse meteorological conditions are jointly associated with an elevated risk of cerebral infarction. Integrated air quality and weather-based warning systems are essential for targeted stroke prevention. Full article

Human Activity Recognition (HAR) using wearable sensor data is increasingly important in healthcare, rehabilitation, and smart monitoring. This study systematically compared three dynamic neural network architectures—Finite Impulse Response Neural Network (FIRNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU)—to examine their suitability and specificity for HAR tasks. A controlled experimental setup was applied, training 16,500 models across different delay lengths and hidden neuron counts. The investigation focused on classification accuracy, computational cost, and model interpretability. LSTM achieved the highest classification accuracy (98.76%), followed by GRU (97.33%) and FIRNN (95.74%), with FIRNN offering the lowest computational complexity. To improve model transparency, Layer-wise Relevance Propagation (LRP) was applied to both input and hidden layers. The results showed that gyroscope Y-axis data was consistently the most informative, while accelerometer Y-axis data was the least informative. LRP analysis also revealed that GRU distributed relevance more broadly across hidden units, while FIRNN relied more on a small subset. These findings highlight trade-offs between performance, complexity, and interpretability and provide practical guidance for applying explainable neural wearable sensor-based HAR. Full article

Loess Plateau is the region with the most concentrated loess distribution and the deepest loess soil layer in the world, and it is facing serious problems of soil erosion and ecological degradation. The nano carbon modification of soil surface properties is a novel strategy for soil improvement and enhancing the soil’s capacity to sequester carbon, which has been extensively researched. However, the mechanisms underlying the influence of carbon surface structure on the efficacy of loess soil remediation remain unclear. Herein, graphene oxide (GO) with a unique two-dimensional structure and adjustable surface properties was optimized as a model carbon filler to investigate the modification effect on loess. As a result, the addition amount of 0.03% GO significantly reduced the disintegration amount of loess, but, if inhibited for a long time, the disintegration effect would weaken. The highly reduced GO can delay the loess disintegration rate due to its enhanced hydrophobicity, but the inhibitory effect fails over a long period of time. After adjusting the reduce degree with a 50% SA (sodium ascorbate), the water-holding capacity of the modified soil in the high suction range is enhanced. This study reveals the synergistic mechanism of the sheet structure and surface properties of GO on the water stability of loess, providing a reference for the prevention and control of soil erosion and ecological restoration in the Loess Plateau. Full article

In recent years, the traditional orchard sprayer has had problems, such as waste of liquid agrochemicals, low target coverage, high manual dependence, and environmental pollution. In this study, an automatic swing-arm sprayer for orchards was developed based on the standardized pear orchard in Pinggu, Beijing. Firstly, the structural principles of a crawler-type traveling system and swing-arm sprayer were simulated using finite element software design. The combination of a diffuse reflection photoelectric sensor and Arduino single-chip microcomputer was used to realize real-time detection and dynamic spray control in the pear canopy, and the sensor delay compensation algorithm was used to optimize target recognition accuracy and improve the utilization rate of liquid agrochemicals. Through the integration of innovative structural design and intelligent control technology, a vertical droplet distribution test was carried out, and the optimal working distance of the spray was determined to be 1 m; the nozzle angle for the upper layer was 45°, that for the lower layer was 15°, and the optimal speed of the swing-arm motor was 75 r/min. Finally, a particle size test and field test of the orchard sprayer were completed, and it was concluded that the swing-arm mode increased the pear tree canopy droplet coverage by 74%, the overall droplet density by 21.4%, and the deposition amount by 23% compared with the non-swing-arm mode, which verified the practicability and reliability of the swing-arm spray and achieved the goal of on-demand pesticide application in pear orchards. Full article

Botulism is a severe muscle paralysis disease mediated by the botulinum toxin. Here, we reported a foodborne botulism case caused by Clostridium botulinum subtype A5(b3) from self-packaged vacuum spicy rabbit heads. Treatment for this case was delayed due to misdiagnosis and insufficient diagnostic capacity in three hospitals, which resulted in progressive clinical deterioration, and eventually, the patient was transferred to Shandong Public Health Clinical Center for specialized therapy. The case was suspected as foodborne botulism by the Qilu Medical-Prevention Innovation Integration pathway and multi-disciplinary consultation. An epidemiological investigation and laboratory confirmation revealed that the botulinum neurotoxin originated from vacuum-packaged spicy rabbit heads distributed via interprovincial cold chain logistics. After treatment with botulism antiserum, the patient’s condition significantly improved, and they were discharged after recovery. We revealed that this foodborne botulism outbreak was caused by the Clostridium botulinum A5(b3) subtype from food by whole-genome sequencing and SNP typing. All the strains belonged to Group I carrying the botulinum neurotoxin gene classified as the ha cluster. Toxin A was confirmed by MBA and other methods, while toxin B was non-functional due to the truncated bont/B gene. Other virulence genes and antibiotic resistance genes were also detected. Our findings indicate that self-packaged vacuum meat products represent an emerging risk factor for botulism transmission when stored improperly. Importantly, the recurrent misdiagnosis in this case underscored the urgent need to enhance the training of healthcare professionals in medical institutions to improve the diagnostic accuracy and clinical management of botulism. Full article

As many renewable energy sources have been waiting to be interconnected with distribution systems due to the lack of power system infrastructure in Korea, studies to solve the delayed problem for renewable energy sources required. In order to overcome these problems, this paper presents an introduction model and optimal capacity algorithm of a VPL (virtual power line) device, which is a virtual power line operation technology to manage the power system by operating an ESS installed at the coupling point of renewable energy source without additionally expanding the power system infrastructure in a conventional way; this paper also proposes an economic evaluation method to assess the feasibility of the VPL device. The optimal capacity of the VPL device is determined by solving the over-voltage problem for the customer, and the economic evaluation method for the VPL device is considered by cost and benefit elements to evaluate the feasibility of introduction model for VPL device. From the simulation result of the proposed optimal capacity algorithm and economic evaluation method based on the introduction model in the VPL device, and it was confirmed that the optimal kW capacity of VPL device was selected as the maximum value in power control values, and the optimal kWh capacity was also determined by accumulating the power control values over the time intervals; also, the proper capacity of the VPL can be more economical than the investment cost of power system infrastructure expansion in the conventional method. Full article

By assuming that both travel and departure time are normally distributed variables, a multi-objective stochastic optimization model for the multi-airport flight cooperative scheduling problem (MAFCSP) with CvaR of travel and departure time is firstly proposed. Herein, conflicts of flights from different airports at the same waypoint can be avoided by simultaneously assigning an optimal route to each flight between the airport and waypoint and determining its practical departure time. Furthermore, several real-world constraints, including the safe interval between any two aircraft at the same waypoint and the maximum allowable delay for each flight, have been incorporated into the proposed model. The primary objective is minimization of both total carbon emissions and delay times for all flights across all airports. A feasible set of non-dominated solutions were obtained using a two-stage heuristic approach-based NSGA-II. Finally, we present a case study of four airports and three waypoints in the Beijing–Tianjin–Hebei region of China to test our study. Full article

Antivirus (patch) is one of the most powerful tools for defending against malware spread. Distributed patching is superior to its centralized counterpart in terms of significantly lower bandwidth requirement. Under the distributed patching mechanism, a novel malware propagation model with double delays and double saturation effects is proposed. The basic properties of the model are discussed. A pair of thresholds, i.e., the first threshold $R_0$ and the second threshold $R_1$, are determined. It is shown that (a) the model admits no malware-endemic equilibrium if $R_0\le 1$, (b) the model admits a unique patch-free malware-endemic equilibrium and admits no patch-endemic malware-endemic equilibrium if $1<R_0\le R_1$, and (c) the model admits a unique patch-free malware-endemic equilibrium and a unique patch-endemic malware-endemic equilibrium if $R_0>R_1$. A criterion for the global asymptotic stability of the malware-free equilibrium is given. A pair of criteria for the local asymptotic stability of the patch-free malware-endemic equilibrium are presented. A pair of criteria for the local asymptotic stability of the patch-endemic malware-endemic equilibrium are derived. Using cybersecurity terms, these theoretical outcomes have the following explanations: (a) In the case where the first threshold can be kept below unity, the malware can be eradicated through distributed patching. (b) In the case where the first threshold can only be kept between unity and the second threshold, the patches may fail completely, and the malware cannot be eradicated through distributed patching. (c) In the case where the first threshold cannot be kept below the second threshold, the patches may work permanently, but the malware cannot be eradicated through distributed patching. The influence of the delays and the saturation effects on malware propagation is examined experimentally. The relevant conclusions reveal the way the delays and saturation effects modulate these outcomes. Full article

Background/Objectives: Supernumerary teeth, or hyperdontia, refer to a developmental anomaly defined by the presence of additional teeth beyond the normal dentition. Hyperdontia may result in clinical complications including delayed eruption, crowding, and malocclusion. Despite its prevalence having been studied in various populations, data from geographically isolated or peripheral groups remain limited. This study aimed to investigate the prevalence and distribution of supernumerary teeth in a sample of children and adolescents from the island of Lesvos, Greece. Methods: A retrospective cross-sectional study was conducted using panoramic radiographs from 621 Caucasian children aged 9–16 years who attended orthodontic or general/pediatric dental clinics in Mytilini, Lesvos island, Greece. Radiographs were examined for the presence, number, type, and location of supernumerary teeth. The analysis included data to explore gender and arch distribution. Results: Supernumerary teeth were identified in 15 individuals, corresponding to a prevalence of 2.4%. A slightly higher occurrence was observed in males (1.4%) than in females (1%). The majority of supernumerary teeth were situated in the maxillary arch (1.9%). Mesiodens represented the most frequently observed type, followed by supernumerary lateral incisors, paramolars, and a single supernumerary central incisor. Conclusions: The prevalence of supernumerary teeth in this population is consistent with reported findings. Mesiodens was the most frequently observed type, with a predominance in the maxillary arch. Early detection of supernumerary teeth is crucial for accurate diagnosis and effective management. Full article

The Luhua chicken is an outstanding local breed in China that has been placed under conservation due to the impact of specialized breeding and the widespread adoption of commercial varieties. As such, this study analyzed reproductive traits across three consecutive generations and utilized whole-genome resequencing data from 60 Luhua chickens to assess conservation efficacy through genetic diversity, run of homozygosity (ROH) distribution, kinship, and population structure so as to better conserve the breed. The results show that, across generations, the body weight at first egg increased, the age at first egg was delayed, and the egg weight at first laying increased. No significant variations were found in the body weight at 300 d or the total egg number. The key genetic parameters of the polymorphism information content (PIC), expected heterozygosity (HE), observed heterozygosity (HO), and mean identical-by-state (IBS) distance were 0.234, 0.351, 0.277, and 0.782, respectively. The majority of ROHs ranged from 0.5 to 1 Mb, and the inbreeding coefficient based on ROHs was calculated at 0.021. The findings reveal that these traits remained unchanged across the three generations. Our research suggests that optimizing the mating plan of Luhua chickens is essential to minimize inbreeding risk. Furthermore, the methodology applied in this study provides a valuable reference for the conservation monitoring of other indigenous chicken breeds. Full article

In Next-Generation Low-Earth-Orbit (LEO) satellite networks, securing inter-satellite communication links (ISLs) through robust authentication is critical due to the dynamic and distributed nature of non-terrestrial environments. Traditional authentication frameworks often fall short under these conditions, prompting the adoption of Zero-Trust Security (ZTS) models. However, existing ZTS protocols incur significant computational overhead, especially as the number of satellite nodes increases, thereby affecting both communication network efficiency and security. To address this, a novel bio-inspired intelligent ZTS approach, i.e., Manta Ray Foraging Cost-Optimized Zero-Trust Security (MRFCO-ZTS), has been developed to leverage bio-inspired data-enabled learning principles to enhance secure satellite communication. The model ingests high-density satellite network data and continuously verifies access requests by formulating a cost function that balances the risk level, attack likelihood, and computational delay in an effective manner. The Manta Ray Foraging Optimization (MRFO) algorithm is applied to minimize this cost function and to enable efficient classification of nodes as detector or attacker based on historical authentication as well as nodes dynamic behaviors. MRFCO-ZTS enables precise identification of attacker behavior while ensuring secure data transmission among verified satellites. The developed MRFCO-ZTS framework is evaluated using a series of numerical simulations under varying satellite user loads, with performance assessed in terms of security accuracy, latency, and operational efficiency. Full article

Driven by the rapid expansion of e-commerce in China, there is a growing demand for high-efficiency, sustainability-oriented logistics solutions in rural regions, particularly for the time-sensitive distribution of perishable agricultural commodities. Traditional logistics systems face considerable challenges in these geographically complex regions due to limited infrastructure and extended travel distances. To address these issues, this study proposes an intelligent cooperative delivery system that integrates automated drones with conventional trucks, aiming to enhance both operational efficiency and environmental sustainability. A mixed-integer linear programming (MILP) model is developed to account for the diverse terrain characteristics of rural China, including forest, lake, and mountain regions. To optimize distribution strategies, the model incorporates an improved Fuzzy C-Means (FCM) algorithm combined with a hybrid genetic simulated annealing algorithm. The performance of three transportation modes, namely truck-only, drone-only, and truck–drone integrated delivery, was evaluated and compared. Sustainability-related externalities, such as carbon emission costs and delivery delay penalties, are quantitatively integrated into the total transportation cost objective function. Simulation results indicate that the cooperative delivery model is especially effective in lake regions, significantly reducing overall costs while improving environmental performance and service quality. This research offers practical insights into the development of sustainable intelligent transportation systems tailored to the unique challenges of rural logistics. Full article