Search Results (6,348)

Artificial intelligence (AI) is used in tasks that usually require human intelligence. The motivation behind this study is the growing interest in deploying AI in public spaces, particularly in autonomous vehicles such as flying drones, to address challenges in navigation and control. The primary challenge lies in developing a robust, cost-effective system capable of autonomous navigation in real-world environments, handling obstacles, and adapting to dynamic conditions. To tackle this, we propose a novel approach integrating machine learning (ML) algorithms, specifically, reinforcement learning (RL), with a comprehensive simulation and testing framework. Reinforcement learning machine algorithms designed to solve problems requiring optimization of the solution for the highest possible reward were used. It was assumed that the algorithms do not have to be created from scratch, but they need a well-defined training environment that will appropriately reward or punish the actions taken. This study aims to develop and implement a novel approach to autonomous drone navigation using machine learning (ML) algorithms. The primary innovation lies in the comprehensive integration of ML algorithms with a real-world drone control system, encompassing both simulations and real-world testing. A vital component of this approach is creating a multi-stage training environment that accurately replicates actual flight conditions and progressively increases the complexity of scenarios, ensuring a robust evaluation of algorithm performance. This research also introduces a new approach to optimizing system cost and accessibility. It involves using commercially available, cost-effective drones and open-source or free simulation tools, significantly reducing entry barriers for potential users. A critical aspect of this study is to assess whether affordable components can provide sufficient accuracy and stability without compromising system quality. The authors developed a system capable of autonomously determining optimal flight paths and controlling the drone, allowing it to avoid obstacles and respond to dynamic conditions in real time. The performance of the trained algorithms was confirmed through simulations and real-world flights, which allowed for assessing their usefulness in practical drone navigation scenarios. Full article

Silicon–glass anode bonding is the key technology in the process of wafer-level packaging for MEMS sensors. During the anodic bonding process, the device may experience adhesion failure due to the influence of electric field forces. A common solution is to add a metal shielding layer between the glass substrate and the device. In order to solve the problem of device failure caused by the electrostatic attraction phenomenon, this paper designed a double-ended solidly supported cantilever beam parallel plate capacitor structure, focusing on the study of the critical size of the window opening in the metal layer for the electric field shielding effect. The metal shield consists of 400 Å of Cr and 3400 Å of Au. Based on theoretical calculations, simulation analysis, and experimental testing, it was determined that the critical size for an individual opening in the metal layer is 180 μm × 180 μm, with the movable part positioned 5 μm from the bottom, which does not lead to failure caused by stiction due to electrostatic pull-in of the detection structure. It was proven that the metal shielding layer is effective in avoiding suction problems in secondary anode bonding. Full article

(1) Background: A parsimonious test battery is deemed necessary to efficiently assess the functional performance of athletes avoiding redundant measurements. This study investigates the interrelationships between elements of an experimental field-based test battery during pre-season assessment (PA), with the purpose of enhancing comprehension of the underlying structure of the assessed variables and suggesting guidelines for the tests incorporated in a PA. (2) Methods: Sixty-two professional football athletes performed a PA, including isometric muscle strength, triple hop and core stability tests, the LESS, and evaluation of landing performance through kinetic and electromyographic data. (3) Results: For the dominant lower limb, the factor analysis resulted in six factors, explaining 79.04% of the variance including core stability, ground reaction forces, dynamic balance, hamstrings strength, quadriceps–hamstring EMG ratio, and quadriceps performance. For the non-dominant lower limb, factor analysis resulted in five factors, explaining 76.60% of the variance including core stability, dynamic balance, ground reaction force, quadriceps–hamstring EMG ratio, and quadriceps–abductors strength. The LESS was loaded with various factors. (4) Conclusions: Given the need for efficient field-based assessments that can be repeated throughout the season without sacrificing data quality, we suggest incorporating the LESS, the prone bridge test, and force-plate-based landing performance evaluation as key elements of the PA. Full article

In this paper, we propose an optimal parking path planning method based on numerical solving, which leverages the concept of the distance between convex sets. The obstacle avoidance constraints were transformed into continuous, smooth nonlinear constraints using the Lagrange dual function. This approach enables the determination of a globally optimal parking path while satisfying vehicular kinematic constraints. To address the inefficiency typically associated with numerical solving, a warm start strategy was employed for the optimization variables: first, the Hybrid A* algorithm was utilized to generate the initial path values; next, a velocity planning problem was formulated to obtain initial velocity values; and finally, converted convex optimization problems were used to compute the initial dual variables. The optimality of the proposed method was validated through a real car test with ACADO as a solver in three typical parking scenarios. The results demonstrate that the proposed method achieved smoother parking paths in real time. Full article

The navigation obstacle avoidance method based on deep reinforcement learning has stronger adaptability and better performance compared to traditional algorithms in complex unknown dynamic environments, and has been widely developed and applied. However, when using multimodal information input, deep reinforcement learning strategy networks extract features that differ significantly between simulated and real world environments, resulting in poor algorithm output strategies and difficulty in transferring models obtained from simulation training to actual environments. To address the aforementioned issues, this article utilizes image segmentation to narrow the gap in environmental features, integrates multimodal information, and designs a deep reinforcement learning multimodal local obstacle avoidance algorithm, MMSEG-PPO, based on proximal strategy optimization algorithms. The algorithm is then ported to practical environments for deployment and testing. The experiment shows that the algorithm proposed in this article reduces the gap between the simulation environment and the actual environment, and has better performance and generalization when transplanted to the real world environment. Full article

Existing support systems for thermal pipeline trenches often fail to meet the specific needs of narrow strips, tight timelines, and short construction periods in urban environments. This study introduces a novel recyclable, non-embedded support system composed of corrugated steel plates, retractable horizontal braces, angle steel, and high-strength bolts designed to address these challenges. The system’s effectiveness was validated through prototype testing and optimized using Abaqus finite element simulations. The research hypothesizes that this new support structure will enhance construction efficiency, reduce installation costs, and provide adaptable and sustainable solutions in urban trench applications. Prototype tests demonstrated that the proposed support had maintained safety and stability in trenches of 2 m and 3 m depth under a 58 kPa load and rainfall, as well as the 4 m deep trenches under asymmetric loading of 80 kPa. Optimization of the proposed system included installing two screw jacks on each horizontal brace and adjusting the corrugated plates, resulting in reduced weight, improved node strength, and enhanced screw jack adjustability. Numerical simulations confirmed the optimized system’s reliability in trenches up to 3 m deep, with caution required for deeper applications to avoid structural failure. The proposed support system offers notable advantages over traditional methods by improving construction efficiency, flexibility, and adaptability while also reducing costs, ensuring safety, and promoting environmental sustainability. Its modular design allows for rapid installation and disassembly, making it suitable for projects with strict deadlines and diverse construction conditions. The findings uphold the initial hypotheses and demonstrate the system’s practicality in urban trench projects. Full article

The deployment of Advanced Air Mobility requires the continued development of technologies to ensure operational safety. One of the key aspects to consider here is the availability of robust solutions to avoid tactical conflicts between drones and other flying elements, such as other drones or birds. Bird detection is a relatively underexplored area, but due to the large number of birds, their shared airspace with drones, and the fact that they are non-cooperative elements within an air traffic management system, it is of interest to study how their detection can be improved and how collisions with them can be avoided. This work demonstrates how a LiDAR sensor mounted on a drone can detect birds of various sizes. A LiDAR simulator, previously developed by the Aerolab research group, is employed in this study. Six different collision trajectories and three different bird sizes (pigeon, falcon, and seagull) are tested. The results show that the LiDAR can detect any of these birds at about 30 m; bird detection improves when the bird gets closer and has a larger size. The detection accuracy is higher than 1 m in most of the cases under study. The errors grow with increasing drone-bird relative speed. Full article

Flexible resources (FRs) have significant potential in ensuring the dynamic balance between supply and demand as well as enhancing the security of active distribution networks (ADNs). However, determining the optimal FR capacity in an economically reasonable manner remains a challenging task. This paper addresses the lack of representativeness of wind turbine (WT) and photovoltaic (PV) power output scenarios in the planning stage by generating a basic set of joint WT-PV output scenarios using random sampling. Subsequently, a Wasserstein confidence set (WCS) is established based on data-driven technology to better represent the unknown distribution of the actual WT-PV joint fluctuations. This provides a more detailed description of the scenario set, enabling the precise quantification of the risk of resource allocation scenarios and enhancing the flexibility and rigor of the subsequent optimal configuration model (OCM). To improve the coordination of active–reactive FRs, a bi-level OCM with multi-timescale considerations is developed. Compared to traditional configuration methods, the proposed model not only improves economic efficiency but also ensures that system voltage remains within safe limits after configuration. The effectiveness and superiority of the proposed optimal configuration method are demonstrated through simulations on an improved 33-bus test system, where the model achieved a 9.208% reduction in annual cost compared to robust methods while maintaining voltage quality and avoiding overvoltage or equipment overloads. Full article

The Roma population is one of the most discriminated social groups. Ignorance of their culture, traditions, etc. generates prejudices and stereotypes that hinder the processes of intercultural coexistence. The aim is to make the Roma people visible and to intervene in the university population, promoting intercultural and inclusive learning spaces to reduce behaviors that generate inequalities. Students from the University of Valladolid were involved, 1255 students in particular, distributed in control and experimental groups. The instrument consists of 40 closed questions and one open-ended. A quantitative analysis was carried out in the anti-Gypsy attitudes categories with t-tests. Item to item differences were not significant in categories A, B and C, but there were differences in D between the experimental and the control groups, which confirms important trends in the target population. Prejudices towards the Roma population continue to exist. University students who receive training have fewer prejudices than students who do not, although other variables can influence the process. Of the students, 72.2% are disturbed by the same negative behaviors, regardless of the ethnic group, and half of them are disturbed by behaviors based on prejudices. It is confirmed the need for preventive interventions to avoid the establishment of erroneous beliefs about the Roma community. Full article

The full potential of glauconite-based nanocomposites as micronutrient fertilizers remains underexplored, particularly their interaction with Zn, Cu, and B. Despite the promising applications, the mechanisms of nutrient sorption and their effects on plant growth require further investigation, especially concerning structural changes and nutrient delivery efficiency. This study investigates the modification of glauconite with Zn, Cu, and B solutions to create multifunctional nanocomposites with enhanced properties. It was established that the activation process preserves the primary globular–lamellar morphology of glauconite while introducing structural changes. Nanocomposites were synthesized using chemical activation and characterized using XRD, SEM-EDS, TEM, FTIR, and BET analyses. Agrochemical tests evaluated their effects on oat growth under controlled conditions. Nanocomposites with zinc sulfate exhibited an increase in specific surface area and mesoporosity, enhancing sorption capacity and facilitating the formation of inner-sphere complexes on the mineral’s basal surface. Modification with copper led to the formation of secondary phases, such as sulfates, on the surfaces of microflakes and globules while preserving the crystalline structure with inner-sphere coordination of Cu²⁺. Boron-modified nanocomposites were characterized by localized restructuring, pore channeling, and an increase in mesopore diameter, along with the formation of outer-sphere complexes relative to the basal surface of glauconite. Thermogravimetric and calorimetric analyses with mass spectrometry revealed specific endothermic and exothermic effects, particularly in Zn-modified samples, confirming changes in dehydration energetics. Agricultural tests on oats (Avena sativa) demonstrated the effectiveness of Cu- and B-modified nanocomposites in improving plant growth parameters, including a 7% increase in plant height and a 6.4% increase in dry weight. Zn-modified nanocomposites showed high germination rates (up to 100%) at low dosages but require optimization to avoid phytotoxicity at higher concentrations. The findings highlight the potential of adapting nanocomposites for targeted nutrient release. Additionally, glauconite nanocomposites have potential applications in restoring degraded soils, treating polluted runoff, and developing slow-release agrochemical systems. Full article

River ecosystems are integral to sustainable environmental development, playing a crucial role in understanding suspended solid matter (SSM) transport dynamics and soil conservation. Accurate monitoring of SSM concentrations in watersheds is foundational for these studies. This research introduces and evaluates a novel HHSW·NUG-1 photoelectric sand meter, specifically designed for SSM measurement. Its reliability was validated at three hydrological stations, including Xiaolangdi. The instrument, based on light scattering principles, is optimized for environments with high SSM loads and rapid flow rates. Laboratory tests indicate a measuring range of 0 to 730 kg/m³, and field trials show effective operation within 0 to 375 kg/m³, meeting the monitoring needs of hydrological stations. Through comparative analysis of measurement data, we established conversion relationships for various SSM concentration ranges, confirming that the instrument’s system error is less than 1%. The photoelectric sand meter adheres to standards outlined in the “Guidelines for SSM Test in Rivers”, demonstrating stability in reliability, calibration methods, observation accuracy, real-time monitoring, data storage, and continuous operation. For optimal use, adherence to relevant hydrological instrument standards is recommended, particularly in stations requiring SSM analysis. Standard sampling and calibration of conversion coefficients should be conducted, and proper sensor installation is crucial to avoid interference from flow conditions. In conclusion, the HHSW·NUG-1 optoelectronic sand meter exhibits stable and reliable performance in practical applications, with broad potential for rapid deployment in other river hydrological stations. Full article

Pollen–food allergy syndrome (PFAS), also known as oral allergy syndrome, is a common condition affecting individuals sensitized to pollens such as birch, ragweed, and grass. This syndrome arises from immunological cross-reactivity between pollen allergens and structurally similar proteins found in various fruits, vegetables, and nuts. Although typically presenting with mild oral and pharyngeal symptoms, PFAS can occasionally result in severe allergic reactions, underscoring its clinical significance. This review explores the pathophysiology of PFAS, highlighting the molecular mechanisms underlying cross-reactivity and examining the main protein families involved, including those contributing to variations in symptom severity. Current diagnostic approaches, including skin prick testing, specific immunoglobulin E measurements, and component-resolved diagnostics, are discussed. Emerging diagnostic tools and biomarkers with potential to enhance accuracy are also examined. Therapeutic strategies for PFAS primarily focus on symptom management and avoidance of trigger foods. However, novel approaches such as allergen immunotherapy and biologics targeting key immune pathways are gaining traction as potential interventions for more severe or refractory cases. By addressing the diagnostic and therapeutic challenges of PFAS, this paper aims to provide clinicians and researchers with a comprehensive understanding of this condition, fostering improved patient care and the development of innovative treatment strategies. Full article

The accurate calibration of snow parameters is necessary to establish an accurate simulation model of snow, which is generally used to study tire–snow interaction. In this paper, an innovative parameter inversion method based on in situ test results is proposed to calibrate the snow parameters, which avoids the damage to the mechanical properties of snow when making test samples using traditional test methods. A coupled Eulerian–Lagrangian (CEL) model of plate loading in snow was established; the sensitivity of snow parameters to the macroscopic load–sinkage relationship was studied; a plate-loading experiment was carried out; and the parameters of snow at the experimental site were inverted. The parameter inversion results from the snow model were verified by the experimental test results of different snow depths and different plate sizes. The results show the following: (1) The material cohesive, angle of friction, and hardening law of snow have great influence on the load–sinkage relationship of snow, the elastic modulus has a great influence on the unloading/reloading stiffness of snow, and the influence of density and Poisson’s ratio on the load–sinkage relationship can be ignored. (2) The correlation coefficient between the inversion result and the matching test data is 0.979, which is 0.304 higher than that of the initial inversion curve. (3) The load–sinkage relationship of snow with different snow depths and plate diameters was simulated by using the model parameter of inversion, and the results were compared with the experimental results. The minimum correlation coefficient was 0.87, indicating that the snow parameter inversion method in this paper can calibrate the snow parameters of the test site accurately. Full article

High-risk Human Papillomavirus (HPV) is a sexually transmissible virus that causes cancer. Vaccination against HPV is available up to age 45. Gay and bisexual men (GBM) are at high risk for oropharyngeal and anal cancers caused by HPV. As part of a larger study of HPV prevention in GBM, we obtained anal swabs for HPV and offered HPV vaccination to GBM in Dar es Salaam, Tanzania. Participants were recruited by an outreach worker experienced with the GBM subculture using Respondent-Driven Sampling (RDS) from seeds. Eighty-three of a possible one hundred participants (mean age 26) were enrolled, tested, and given a first vaccination dose. Anal swabs were tested for twenty-eight HPV genotypes, both high and low risk for carcinogenicity, and a median of seven different HPV genotypes was found in participants. A total of 87% of participants carried at least one HPV genotype, and 76% carried at least one high-risk genotype. As a result of harassment and unanticipated risk to participants and staff at the unmarked community-based site, this study was terminated before the sample size was reached. Since a full course of vaccine was the standard of care, participants were contacted using the contact method they had provided to arrange follow-up vaccination doses at an alternative clinical site. Twenty-nine percent received the additional vaccination. A further 6% made appointments but did not attend, and another 10% would have received the second vaccination if they were incentivized to attend. The rate of HPV in anal samples was significantly higher than in our study using the same recruitment method in the same city in 2011–2012. The HIV rate was 45%. Anal HPV rates, including high-risk HPV rates, were significantly higher than in a similar population of gay and bisexual men 12 years ago. It is possible to provide HPV vaccination to gay and bisexual men in Tanzania and have approximately 45% potentially re-attend for a second dose if they are incentivized. Great care must be used to situate vaccination to avoid stigma leading to harassment, especially where homosexuality is criminalized. We infer that the high-risk harassment faced by participants and lack of incentive for the second visit depressed the return rate for revaccination. Full article

Improving parental self-efficacy has been linked with reductions in child mental health difficulties; however, underlying mechanisms remain unclear, especially for fathers. This study investigated whether father self-efficacy influences child mental health difficulties indirectly through parenting style and parent-facilitated regulation of children’s negative emotions. A community sample of American fathers (N = 350, M = 39.45 years old) completed self-reports on father self-efficacy, parenting styles, parent-facilitated emotion regulation, and their children’s mental health difficulties (aged 4–12). Path analysis was used to test a cross-sectional, parallel–sequential indirect effect model. Father self-efficacy had a significant indirect effect on child mental health difficulties via three significant pathways of permissive parenting, authoritative parenting–acceptance of child’s negative emotions, and authoritarian parenting–avoidance of child’s negative emotions. Our model explained a moderate amount of variance in child mental health difficulties. The findings support promoting father self-efficacy through parenting interventions and highlight parenting beliefs as important for clinicians providing child mental health care. Full article