Search Results (247)

Multi-UAV cooperative encirclement tasks have attracted considerable attention in areas such as military defense and target interception. Fixed-wing UAVs face substantial challenges due to intrinsic dynamic limits, including their minimum velocity and turning radius, particularly when engaging evasive target and navigating in obstacle environments. This paper presents a hybrid deep reinforcement learning approach, in which a cooperative task environment is developed for fixed-wing UAVs that jointly integrates encirclement and obstacle avoidance. A composite MADDPG framework enhanced with curriculum learning is designed, employing progressive task staging and reward optimization to accelerate convergence and improve policy stability. Simulation results demonstrate that the proposed method achieves single-step encirclement success rates exceeding 80% in complex environments, while maintaining 10-step success rates around 70%, thereby strengthening both encirclement capability and obstacle avoidance safety in fixed-wing UAV swarm. This study provides new insights into the intelligent cooperative control of fixed-wing UAVs in high-risk missions. Full article

Peer relationship difficulties during adolescence can significantly affect development. As classrooms become increasingly multiethnic, little is known about how native students navigate these contexts, while research on students with an immigrant background has mainly examined the onset of peer relationship difficulties. Moreover, the impact of the classroom ethnic composition—the proportion of students with an immigrant background relative to native students—remains unclear, with various theories offering conflicting perspectives. To address these gaps, this study examines the longitudinal development of peer relationship difficulties, considering students’ immigrant backgrounds and classroom ethnic composition. Two data collections were conducted (T1: December 2021/January 2022; T2: May/June 2022) in Italy. The sample included 604 first-year high school students (M_age = 15.16; SD_age = 0.56; 17.5% with an immigrant background; 52.9% males) nested within 30 classrooms across 8 schools. Results from the random intercept linear mixed model showed an increase in peer relationship difficulties for native students in medium and highly multiethnic classrooms, where the proportion of students with an immigrant background was above the sample mean, but not in low multiethnic classrooms (below the sample mean). Students with an immigrant background experienced an increase in peer relationship difficulties over time across all classroom conditions. Classroom ethnic composition plays a crucial role in shaping peer relationship difficulties, suggesting that the presence of multiple ethnic groups may present additional challenges. The study underscores the need for targeted, inclusive interventions and contributes to theoretical debates on the social dynamics of multiethnic classrooms. Full article

Spinal cord injury (SCI) often results in long-term locomotor impairments, and strategies to enhance functional recovery remain limited. While epidural electrical stimulation (EES) has shown clinical promise, our understanding of the mechanisms by which it improves function remains incomplete. Here, we use genetic tools in an animal model to perform neuromodulation and treadmill rehabilitation in a manner similar to EES, but with the benefit of the genetic tools and animal model allowing for targeted manipulation, precise quantification of the cells and circuits that were manipulated, and the gathering of extensive kinematic data. We used a viral construct that selectively transduces large diameter afferent fibers (LDAFs) with a designer receptor exclusively activated by a designer drug (hM3Dq DREADD; a chemogenetic construct) to increase the excitability of large fibers specifically, in the rat contusion SCI model. As changes in locomotion with afferent stimulation can be subtle, we carried out a detailed characterization of the kinematics of locomotor recovery over time. Adult Long-Evans rats received contusion injuries and direct intraganglionic injections containing AAV2-hSyn-hM3Dq-mCherry, a viral vector that has been shown to preferentially transduce LDAFs, or a control with tracer only (AAV2-hSyn-mCherry). These neurons then had their activity increased by application of the designer drug Clozapine-N-oxide (CNO), inducing tonic excitation during treadmill training in the recovery phase. Kinematic data were collected during treadmill locomotion across a range of speeds over nine weeks post-injury. Data were analyzed using a mixed effects model chosen from amongst several models using information criteria. That model included fixed effects for treatment (DREADDs vs. control injection), time (weeks post injury), and speed, with random intercepts for rat and time point nested within rat. Significant effects of treatment and treatment interactions were found in many parameters, with a sometimes complicated dependence on speed. Generally, DREADDs activation resulted in shorter stance duration, but less reduction in swing duration with speed, yielding lower duty factors. Interestingly, our finding of shorter stance durations with DREADDs activation mimics a past study in the hemi-section injury model, but other changes, including the variability of anterior superior iliac spine (ASIS) height, showed an opposite trend. These may reflect differences in injury severity and laterality (i.e., in the hemi-section injury the contralateral limb is expected to be largely functional). Furthermore, as with that study, withdrawal of DREADDs activation in week seven did not cause significant changes in kinematics, suggesting that activation may have dwindling effects at this later stage. This study highlights the utility of high-resolution kinematics for detecting subtle changes during recovery, and will enable the refinement of neuromechanical models that predict how locomotion changes with afferent neuromodulation, injury, and recovery, suggesting new directions for treatment of SCI. Full article

Climate change is expected to reduce water availability during cropping season, while growing populations and rising living standards will increase the global water demand. This creates an urgent need for national water management tools to optimize water allocation. In particular, agriculture requires targeted approaches to improve efficiency. Alongside field measurements and remote sensing, agro-hydrological models have emerged as a particularly valuable resource for assessing and managing agricultural water demand. This study introduces WaterCROPv2, a state-of-the-art agro-hydrological model designed to estimate national-scale irrigation water demand while effectively balancing accuracy with practical data requirements. WaterCROPv2 incorporates innovative features such as hourly time-step computations, advanced rainwater canopy interception modeling, detailed soil-dependent leakage dynamics, and localized daily evapotranspiration patterns based on meteorological data. Through comprehensive analyses, WaterCROPv2 demonstrates significantly enhanced reliability in estimating irrigation water needs across various climatic regions, particularly under contrasting dry and wet conditions. Validation against independent data from the Italian National Institute of Statistics (ISTAT) for maize cultivation in Italy in 2010 confirms the model’s accuracy and underscores its potential for broader international applications. A spatial analysis further reveals that the estimation errors align closely with regional precipitation patterns: the model tends to slightly underestimate irrigation needs in the wetter northern regions, whereas it somewhat overestimates demand in the drier southern areas. WaterCROPv2 has also been used to analyze irrigation water requirements for maize cultivation in Italy from 2005 to 2015, highlighting its significant potential as a strategic decision-support tool. The model identifies optimal cultivation areas, such as the Pianura Padana, where the irrigation requirements do not exceed 200 mm for the entire maize growing period, and unsuitable regions, such as Salentino, where over 500 mm per season are required due to the local climatic conditions. In addition, estimates of the water volumes required for the current extent of maize cultivation show that the Pianura Padana region demands nearly three times the amount of water used in the Salentino area. The model has also been used to identify regions where adopting efficient irrigation technologies could lead to substantial water savings. With micro-irrigation currently covering less than 18% of irrigated land, simulations suggest that a complete transition to this system could reduce the national water demand by 21%. Savings could reach 30–40% in traditionally water-rich regions that rely on inefficient irrigation practices but are expected to be increasingly exposed to temperature increases and precipitation shifts. The analysis shows that those regions currently lacking adequate irrigation infrastructure stand to gain the most from targeted irrigation system investments but also highlights how incentives where micro-irrigation is already widespread can provide further 5–10% savings. Full article

Background: Alzheimer’s disease (AD) involves ongoing neurodegeneration, with phosphorylated tau (PTAU) intracellular accumulation closely associated with cortical shrinking. However, not everyone with high PTAU levels shows the same degree of neurodegeneration, implying that other biological stress factors might influence tau’s harmful effects. This research explores whether cerebrospinal fluid erythrocyte burden (CTRED), a marker indicating vascular–CSF barrier disruption and heme toxicity, affects the link between PTAU181 levels and entorhinal cortex atrophy in AD. Methods: We examined 25 observations from 18 patients with AD using a linear mixed effects model. The dependent variable was entorhinal cortex volume, with fixed effects for PTAU, CTRED, and their interaction. Random intercepts accounted for variability within subjects. A cognitively normal (CN) control group was included for comparison. Results: CTRED is significantly associated with reduced entorhinal volume (p = 0.005). A notable interaction between CTRED and PTAU was also found (p = 0.004), suggesting that higher CTRED enhances PTAU’s atrophic effects. PTAU alone was not a significant predictor. No significant effects were observed in the CN group, which supports the specificity of the disease. Conclusions: CTRED alters the neurotoxic impact of PTAU on the entorhinal cortex in AD, supporting a multi-hit model of degeneration that involves tau pathology and erythrocyte-derived stress. These findings emphasize the clinical importance of vascular–CSF biomarkers in predicting neurodegeneration and guiding targeted treatments. Full article

This paper investigates a swarming strength allocation Bayesian game approach under incomplete information to address the high-value targets protection problem of swarming unmanned systems. The swarming strength allocation Bayesian game model is established by analyzing the non-zero sum incomplete information game mechanism during the protection process, considering high-tech and low-tech interception players. The model incorporates a game benefit quantification method based on an improved Lanchester equation. The method regards massive swarm individuals as a collective unit for overall cost calculation, thus avoiding the curse of dimensionality from increasing numbers of individuals. Based on it, a Bayesian Nash equilibrium solving approach is presented to determine the optimal swarming strength allocation for the protection player. Finally, compared with random allocation, greedy heuristic, rule-based assignment, and Colonel Blotto game, the simulations demonstrate the proposed method’s robustness in large-scale strength allocation. Full article

Low-Altitude and Slow-Speed Small (LSS) targets pose significant challenges to air defense systems due to their low detectability and complex maneuverability. To enhance defense capabilities against low-altitude targets and assist in formulating interception decisions, this study proposes a new threat assessment algorithm based on multisource data fusion under visible-light detection conditions. Firstly, threat assessment indicators and their membership functions are defined to characterize LSS targets, and a comprehensive evaluation system is established. To reduce the impact of uncertainties in weight allocation on the threat assessment results, a combined weighting method based on bias coefficients is proposed. The proposed weighting method integrates the analytic hierarchy process (AHP), entropy weighting, and CRITIC methods to optimize the fusion of subjective and objective weights. Subsequently, Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Dempster–Shafer (D-S) evidence theory are used to calculate and rank the target threat levels so as to reduce conflicts and uncertainties from heterogeneous data sources. Finally, the effectiveness and reliability of the two methods are verified through simulation experiments and measured data. The experimental results show that the TOPSIS method can significantly discriminate threat values, making it suitable for environments requiring rapid distinction between high- and low-threat targets. The D-S evidence theory, on the other hand, has strong anti-interference capability, making it suitable for environments requiring a balance between subjective and objective uncertainties. Both methods can improve the reliability of threat assessment in complex environments, providing valuable support for air defense command and control systems. Full article

Diaporthe eres is a harmful pathogen affecting Hongyang kiwifruit (Actinidia chinensis) after harvest, yet the antioxidant defense strategies are not well understood. This research thoroughly examines the dynamics of the antioxidant response during the infection process. Significant findings indicate an initial 3-day latent period (0–3 dpi) that allowed for pathogen establishment, followed by irreversible tissue breakdown characterized by water-soaked lesions at 4 dpi. The study identified a biphasic activation pattern of superoxide dismutase (SOD) with dual activity peaks (1 dpi and 4 dpi), orchestrated by mitochondrial hub gene CEY00_Acc02790 that coordinates peroxidase (POD) networks, while peroxidase (POD) activity exhibited a synchronized but temporary increase, peaking at 4 dpi. Further bioinformatic analysis revealed the possible functional specialization of POD isoforms: α-helix-rich extracellular variants drove cell wall reinforcement through lignification, while random coil-dominant intracellular variants formed to mitigate cytoplasmic reactive oxygen species (ROS) damage, establishing dual physicochemical barriers. Malondialdehyde (MDA) levels rose significantly by 3 dpi, indicating permanent membrane damage. Collectively, these findings elucidate the mechanistic foundation of the Actinidia–Diaporthe pathosystem, identifying the bimodal SOD response and POD specialization as prime targets for developing resistant cultivars and precision postharvest interventions, ultimately reducing losses through biochemical interception of pathogenesis. Full article

This work introduces a comprehensive vision-based framework for autonomous space debris removal using robotic manipulators. A real-time debris detection module is built upon the YOLOv8 architecture, ensuring reliable target localization under varying illumination and occlusion conditions. Following detection, object motion states are estimated through a calibrated binocular vision system coupled with a physics-based collision model. Smooth interception trajectories are generated via a particle swarm optimization strategy integrated with a 5–5–5 polynomial interpolation scheme, enabling continuous and time-optimal end-effector motions. To anticipate future arm movements, a Transformer-based sequence predictor is enhanced by replacing conventional multilayer perceptrons with Kolmogorov–Arnold networks (KANs), improving both parameter efficiency and interpretability. In practice, the Transformer+KAN model compensates the manipulator’s trajectory planner to adapt to more complex scenarios. Each component is then evaluated separately in simulation, demonstrating stable tracking performance, precise trajectory execution, and robust motion prediction for intelligent on-orbit servicing. Full article

Identifying knowledge gaps and predictors of performance are proven ways to implement changes to a curriculum. This cross-sectional study investigates the subjective and objective competency of 52 medical students at McGill University in musculoskeletal (MSK) medicine, with a focus on orthopaedic surgery. We surveyed medical students to assess their confidence levels in orthopaedic surgery and their perceptions of its teaching. The students then completed a 25-question orthopaedics-focused exam as an objective assessment of their knowledge. Descriptive statistics were calculated, exam performance was compared across academic years, predictors of exam scores were analyzed, and student self-assessment accuracy was evaluated. Students reported lower confidence in orthopaedic surgery than in many other specialties, exam scores varied significantly across academic years (p = 0.007), and predicted exam performance was the only significant predictor of test score in multiple linear regression (R² = 0.313, p = 0.025). Calibration analysis revealed a substantial miscalibration, where students with higher predicted scores tended to overestimate their performance, while those with lower predictions tended to underestimate themselves (intercept = 27.2, slope = 0.54). A Bland–Altman plot demonstrated wide limits of agreement between predicted and actual scores (mean bias −1.2%, 95% LoA −35.0% to +32.6%). These findings highlight meaningful orthopaedic knowledge gaps and miscalibrated self-assessment, emphasizing the need for targeted, structured educational interventions in the MSK curriculum. Full article

Cryptosporidium is a major waterborne parasite that causes gastrointestinal illness. Conventional assays, including microscopy and immunological identification, often suffer from false positives or negatives due to non-specific binding or morphological differences between Cryptosporidium species. We developed a novel qPCR assay based on a Cryptosporidium-specific Conserved Signature Protein (CSP) to address the limitations of testing complex samples, including those from recreational waters. The CSP (hypothetical protein (cgd2_3830)) was identified as taxonomically unique to Cryptosporidium species. The CSP sequence and designed qPCR assay primers/probe demonstrated high specificity for the targeted Cryptosporidium species when tested against NCBI RefSeq databases. qPCR assay efficiency was determined as 95% and an R² value of 0.99, with a slope and intercept of −3.4 and 40.1, respectively. Additionally, the Lower Limit of Detection (ALLOD) was determined as three gene copies, suggesting the potential to detect even a single oocyst. No non-specific amplification products or primer dimers were observed when the qPCR assay was evaluated using recreational water, fecal solution, and wastewater, while spike-in-control tests indicated minimal interference with the sensitivity of the assay, highlighting application for testing complex environmental DNA extracts. These findings highlight the application of the novel CSP-based qPCR assay for the rapid and sensitive detection of Cryptosporidium sp., thereby circumventing the sequence variability and multi-copy limitations associated with existing molecular markers. This proof-of-concept study presents a diagnostic framework utilizing CSP-based markers for developing water quality monitoring strategies, with scope for expansion to other microbial pathogens and potential applications in clinical and food safety settings. Full article

Vertical containment barriers—critical for intercepting contaminant transport in subsurface environments—demand materials that balance low permeability with adequate strength, particularly in stress-sensitive mountainous terrain. Plastic concrete, as a key barrier material, provides essential properties, including exceptional stress relaxation, to suppress fracture development under compressive loads, coupled with effective seepage control. This study examines its strength performance through experiments on varied mixing techniques (dry, wet, and 24 h hydration), unconfined compression under uncontaminated conditions (water–binder ratios: 1.3–2.1, bentonite content: 20–30%, ages: 14–90 days), barium ion immersion (1–5 g/L, pH 7–11), and dry–wet cycling (10 cycles). Key findings demonstrate that (1) the strength of samples prepared by dry mixing and wet mixing is lower than that of samples mixed for 24 h, and all specimens met the target design strength following 28 days of curing; (2) under pollution-free conditions, strength decreases with higher water–binder ratios and bentonite content, showing a linear relationship. Strength increases exponentially with age; (3) in the presence of Ba²⁺, strength gradually decreases as Ba²⁺ concentration and pH increase, particularly notably at 3 g/L Ba²⁺ and pH 11. Strength increases with age, following a power relationship; (4) under dry–wet cycles, ion concentration has minimal impact on sample quality and surface state but significantly affects strength, with higher ion concentrations leading to greater strength loss and susceptibility to cycles; (5) during solution immersion, higher ion concentrations and pHs result in greater strength loss and worse erosion resistance. Full article

Background: Unplanned pregnancy is a public health issue and understanding women’s decision making aids practitioners in assessing fertility trends, contraception use, and family planning counselling. In Italy, Catholicism reinforces ‘natural reproduction’ and ‘traditional’ contraception, making it an ‘Imperfect Contraceptive Society.’ A valid and reliable measure of pregnancy intentionality is increasingly important, and the London Measure of Unplanned Pregnancy (LMUP) has proved effective. Objectives and Methods: This study comprised four stages: (1) English–Italian translation and back-translation to create the Italian version [LMUP-IT]; (2) online data collection from postnatal women; (3) evaluation of its psychometric properties (targeting, reliability, construct validity via CFA and measurement invariance with a UK sample, ‘known groups’ hypothesis testing); and (4) exploratory analysis of its associations with perinatal mental health. The sample comprised 450 postnatal women (M_age = 33.6 ± 4.5). Results: The LMUP-IT was shown to be reliable (ωT = 0.81, α = 0.76), with acceptable targeting. Measurement invariance testing confirmed consistency with the UK sample in factor structure, loadings, intercepts, and errors. LMUP-IT scores significantly correlated with well-known indicators of perinatal mental health. Conclusions: Overall, the LMUP-IT is a reliable measure of pregnancy intention in Italian for postpartum women. Understanding pregnancy intention will help healthcare professionals tailor interventions to better support women’s mental health during the transition to motherhood. Full article

Polyphagous fruit fly (Diptera: Tephritidae) pests from the Pacific Islands pose a biosecurity risk to New Zealand, a country free from pest fruit flies. Among them, Bactrocera facialis, B. passiflorae, B. kirki, and B. distincta are sympatric species commonly intercepted at immature stages at the border. However, current mitochondrial cytochrome oxidase I (COI) barcode data lack sufficient variation for a confident identification of the above four species. To address this, we generated COI barcode data for 403 fruit fly individuals including these four species and an additional 17 related fruit fly species. A phylogenetic analysis of the COI sequences of B. facialis revealed two genetically distinct populations, one closely related to B. passiflorae. Complete mitochondrial genomes were explored, identifying minor fixed differences in Cytochrome b (CYTB), NADH dehydrogenase 2 (ND2), and ATP synthase membrane subunit 6 (ATP6) genes. Based on sequence data for COI, ND2, and ATP6 genes, a multiplex real-time PCR assay has been developed and validated for the four target species. Each assay demonstrated high specificity, with no cross-reactions, and sensitivity as low as 10 copies/μL of the target DNA. This study shows that the developed assays enable the rapid and reliable identification of the target fruit fly species, supporting global biosecurity efforts. Full article

Fruit flies that belong to the genus Zeugodacus (Diptera: Tephritidae) pose significant threats as invasive pests of agricultural crops in Asia and sub-Saharan Africa. The intensification of transboundary trade in fresh horticultural produce has increased the risk of introducing invasive species such as fruit flies, more so through the inadvertent transport of their immature developmental stages. Such immature stages of fruit flies belonging to the Tephritidae family are frequently intercepted at the international borders worldwide and are unable to be identified to the species level using morphological characteristics. Molecular identification using mitochondrial Cytochrome Oxidase I (COI) gene has proven to be quite useful, as they are not constrained by developmental stages, sex, or colour morphs of the pest species in question. Also, real-time PCR-based species-specific assays offer quicker turnaround time since they do not require any post-PCR procedures. This study evaluated the utility of a real-time PCR assay based on the COI gene region to identify Zeugodacus cucurbitae from other Tephritid species. The developed real-time PCR assay provides a swift and precise way of discriminating between these highly invasive pest species during an interception event for rapid decision making. High specificity, having no cross-reactions with closely related Tephritids, and sensitivity of the developed assay will be extremely useful in discriminating Z. cucurbitae from other closely related fruit fly species. Z. cucurbitae-specific real-time PCR developed in this study is appropriate for organizations that carry out routine diagnostics to facilitate fresh produce imports and exports. Our assay is fully optimized for rapid deployment at international borders, offering reliable detection of the target species regardless of developmental stage, sex, or geographic origins. Full article