Search Results (152)

To address the issue of poor film–soil separation in traditional subsoil residual film recovery machines, which leads to recovered film containing excessive soil, a film–soil conveying and separation device was designed. By establishing a mechanical model for the balanced conveyance of the film–soil composite, the range of conveyor chain inclination angles enabling stable transport was determined. Using RecurDyn 2023 simulation software, a sensitivity analysis was conducted on the effects of vibrating wheel speed, vibrating wheel mounting distance, and conveyor chain inclination angle on vibration characteristics. This analysis revealed that vibrating wheel speed and mounting distance have a significant impact on the vibrating mechanism. Based on the DEM–MBD (Discrete Element Method—Multi-Body Dynamics) coupling approach, a discrete element simulation model was built for the film–soil vibrating conveyor device, residual film, and soil. Using the primary conveyor chain speed, vibrating wheel speed, and mounting distance as experimental factors, and soil content rate and film leakage rate as experimental indicators, single-factor tests and a three-factor, five-level orthogonal rotational composite design test were performed. The results showed that, at a primary conveyor chain speed of 1.61 m/s, a vibrating wheel speed of 186.2 r/min, and a mounting distance of 688.2 mm, the soil content rate was 18.11% and the film leakage rate was 7.61%. The film–soil conveying and separation process was also analyzed via simulation. Field validation tests using the optimal parameter combination yielded relative errors of 3.43% and 5.51%, respectively, demonstrating effective film–soil separation. This research provides a theoretical foundation and equipment support for addressing residual film pollution in the cultivated layer of Xinjiang region. Full article

Grape marc spirits represent a significant category within the alcoholic beverage sector, particularly across Mediterranean Europe. This study aimed to construct a sensory flavor wheel—covering aroma, taste, and mouthfeel modalities—specifically for non-flavored and non-wood-aged grape marc distillates. To achieve this, we explored the feasibility of a novel methodological approach combining three rapid sensory techniques: Ultra Flash Profiling (UFP), Check-All-That-Apply (CATA), and Rate-All-That-Apply (RATA). Forty-five (45) samples from Greece, Cyprus, and Italy were evaluated by a trained panel of 12 assessors. UFP generated 205 initial descriptors, which were refined to 59 for CATA. Despite the long attribute list, CATA data helped identify the most relevant terms for the final RATA experiment. The sequential application of these methods, along with intermediate data filtering, led to the selection of 45 key descriptors with occurrence frequencies ranging from 33.3% to 97.7%. These were organized into a comprehensive flavor wheel grouped into 12 general categories. This approach offers a flexible framework for future flavor wheel construction in other under-characterized product categories. Full article

Accelerating the recovery of compacted soils caused by logging machinery using bioengineering techniques is a key goal of Sustainable Forest Management. This research was conducted on an abandoned skid trail with a uniform 15% slope and a history of heavy traffic, located in the Nav forest compartment of northern Iran. The main objectives were to assess (a) soil physical properties 35 years after skidding by a tracked bulldozer, (b) the impact of natural alder regeneration on soil recovery, and (c) the contribution of alder fine-root development to the restoration of compacted soils in beech stands. Soil physical properties and fine root biomass were analyzed across three depth classes (0–10 cm, 10–20 cm, 20–30 cm) and five locations (left wheel track (LT), between wheel tracks (BT), right wheel track (RT)) all with alder trees, and additionally control points inside the trail without alder trees (CPWA), as well as outside control points with alder trees (CPA). Sampling points near alder trees (RT, LT, BT) were compared to CPWA and CPA. CPA had the lowest soil bulk density, followed by LT, BT, RT, and CPWA. Bulk density was highest (1.35 ± 0.07 g cm⁻³) at the 0–10 cm depth and lowest (1.08 ± 0.4 g cm⁻³) at 20–30 cm. The fine root biomass at 0–10 cm depth (0.23 ± 0.21 g dm⁻³) was significantly higher than at deeper levels. Skid trail sampling points showed higher fine root biomass than CPWA but lower than CPA, by several orders of magnitude. Alder tree growth significantly reduced soil bulk density, aiding soil recovery in the study area. However, achieving optimal conditions will require additional time. Full article

This work presents the experimental evaluation of a robotic walker following the full implementation of its sensor and motorization system. The aging population and increasing mobility impairments drive the need for assistive robotic technologies that enhance safe and independent movement. The main objective was to validate the device’s behavior in real-use scenarios by assessing its stability, responsiveness, and accuracy in detecting user movement. Tests were carried out in straight-line walking and on paths involving directional changes, both with and without motor assistance, using a cohort of five test users. Principal Component Analysis (PCA) and t-SNE dimensionality reduction techniques were applied to analyze the inertial (IMU) and proximity (TOF) sensor data, complemented by motor control monitoring through wheel Hall sensors, to explore gait patterns and system performance. Additionally, synchronized measurements between the user’s and walker’s inertial units and Time-of-Flight sensors allowed the evaluation of spatial alignment and motion correlation. The results provide a foundation for future system adjustment and optimization, ensuring the walker offers effective, safe, and adaptive assistance tailored to the user’s needs. Findings reveal that the walker successfully distinguishes individual gait patterns and adapts its behavior accordingly, demonstrating its potential for personalized mobility support. Full article

The terrain in hilly and mountainous areas is complex, and the level of agricultural mechanization is low. This article systematically reviews the research progress of key technologies for agricultural machinery power chassis in hilly and mountainous areas, and conducts an analysis of five aspects: the power system, walking system, steering system, leveling system, and automatic navigation and path tracking control system. In this manuscript, (1) in terms of the power system, the technical characteristics and application scenarios of mechanical, hydraulic, and electric drive systems were compared. (2) In terms of the walking system, the performance differences between wheeled, crawler, legged, and composite walking devices and the application of suspension systems in agricultural machinery chassis were discussed. (3) In terms of the steering system, the steering characteristics of wheeled chassis and crawler chassis were analyzed, respectively. (4) In terms of the leveling system, the research progress on hydraulic and electric leveling mechanisms, as well as intelligent leveling control algorithms, was summarized. (5) The technology of automatic navigation and path tracking for agricultural machinery chassis was discussed, focusing on multi-sensor fusion and advanced control algorithms. In the future, agricultural machinery chassis will develop towards the directions of intelligence, automation, greening, being lightweight, and being multi-functionality. Full article

Single sapphire crystals has been widely used in technology such as light emitting diodes, lasers, high-temperature and high-voltage devices, special windows, and optical systems, and grinding is an important process of their machining. In order to reveal the influence of the grinding wheel speed, grinding depth, and feed rate on the ground surface quality of sapphire crystals, a three-factor and five-level orthogonal experiment was designed and completed. Variance and range analysis was conducted on the experimental results using the surface roughness Ra and subsurface crack damage depth (SSD) as evaluation indicators, and optimized parameter combinations were explored. Furthermore, mathematical prediction models for the power regression of the Ra and SSD were established based on the experimental data. The research results indicate that within the range of the process parameters used in this experiment, the grinding process did not achieve the full ductile removal of the material. Some of the material was removed in a brittle mode, forming fractured pits on the ground surface, and median crack propagation occurred in the subsurface, forming a subsurface microcrack damage layer. The influence of the grinding parameters on the Ra and SSD showed a consistent trend, which was that the parameter with the greatest impact was the grinding wheel speed, followed by the feed rate and grinding depth. The Ra and SSD obtained under the optimized grinding parameter combination were 0.326 μm and 2.86 μm, respectively. The research results provide an experimental basis and guidance for improving the surface quality of sapphire crystals during grinding. Full article

With the vigorous development of speedy railway technology, steel rails, as an important structural infrastructure in speedy railways, play a crucial role in ensuring the safety of the entire speedy railway operation. A brand-new type of speedy rail inspection robot and its fault detection method are proposed to solve a number of problems, such as the difficulty and low accuracy of real-time online detection of rail defects and damage in speedy railways. The brand-new rail inspection robot is driven by two drive wheels and adopts a standard rail gauge of 1435 mm, which ensures its speedy and smooth operation on the track as well as accurate motion posture information. Firstly, 12 common types of surface damage of the rail head were analyzed and classified into five categories based on their damage characteristics. The motion state of the rail inspection robot under the five types of surface damage of the rail head was analyzed and subjected to kinematic analysis. This study analyzed the relationship between the distinctive types of damage and the motion posture of the robot during the inspection of the five types of damage. Finally, experimental tests were conducted, and it was found that the robot’s motion posture would undergo sudden changes when inspecting distinctive types of injuries; the highest error rate was 3%. The effectiveness of this method was verified through experiments, and the proposed new track detection robot can greatly improve the track detection efficiency of high-speed railways and has specific academic research value and practical application value. Full article

In the operation process of modern industrial equipment, as the core transmission component, the operation state of the gearbox directly affects the overall performance and service life of the equipment. However, the current gear operation is still faced with problems such as poor monitoring, a single detection index, and low data utilization, which lead to incomplete evaluation results. In view of these challenges, this paper proposes a shape and property integrated gearbox monitoring system based on digital twin technology and artificial intelligence, which aims to realize real-time fault diagnosis, performance prediction, and the dynamic visualization of gear through virtual real mapping and data interaction, and lays the foundation for the follow-up predictive maintenance application. Taking the QPZZ-ii gearbox test bed as the physical entity, the research establishes a five-layer architecture: functional service layer, software support layer, model integration layer, data-driven layer, and digital twin layer, forming a closed-loop feedback mechanism. In terms of technical implementation, combined with HyperMesh 2023 refinement mesh generation, ABAQUS 2023 simulates the stress distribution of gear under thermal fluid solid coupling conditions, the Gaussian process regression (GPR) stress prediction model, and a fault diagnosis algorithm based on wavelet transform and the depth residual shrinkage network (DRSN), and analyzes the vibration signal and stress distribution of gear under normal, broken tooth, wear and pitting fault types. The experimental verification shows that the fault diagnosis accuracy of the system is more than 99%, the average value of the determination coefficient (R²) of the stress prediction model is 0.9339 (driving wheel) and 0.9497 (driven wheel), and supports the real-time display of three-dimensional cloud images. The advantage of the research lies in the interaction and visualization of fusion of multi-source data, but it is limited to the accuracy of finite element simulation and the difficulty of obtaining actual stress data. This achievement provides a new method for intelligent monitoring of industrial equipment and effectively promotes the application of digital twin technology in the field of predictive maintenance. Full article

Recommendation systems (RSs) play a vital role in e-commerce and content platforms, yet balancing efficiency and recommendation quality remains challenging. Traditional deep models are computationally expensive, while heuristic methods like particle swarm optimization struggle with discrete optimization. To address these limitations, this paper proposes elite-evolution-based discrete particle swarm optimization (EEDPSO), a novel framework specifically designed to optimize high-dimensional combinatorial recommendation tasks. EEDPSO restructures the velocity and position update mechanisms to operate effectively in discrete spaces, integrating neighborhood search, elite evolution strategies, and roulette-wheel selection to balance exploration and exploitation. Experiments on the MovieLens and Amazon datasets show that EEDPSO outperforms five metaheuristic algorithms (GA, DE, SA, SCA, and PSO) in both recommendation quality and computational efficiency. For datasets below the million-level scale, EEDPSO also demonstrates superior performance compared to deep learning models like FairGo. The results establish EEDPSO as a robust optimization strategy for recommendation systems that effectively handles the cold-start problem. Full article

Consumer attitude shift and green transport advocacy in the sharing economy highlight shared two-wheeled electric scooters (STWESs) for short-distance commuting. Current designs often overlook user emotions and aesthetic alignment with product characteristics. A product design methodology is proposed in this study, constructing optimization models from both the functional experiential and perceptual visual layers. Utilizing context analysis theory (CAT) and the KANO model, an STWES contextual requirements optimization model is formulated. The expert method is then applied to identify five key design elements, generating a category diagram based on typical samples, followed by Kansei evaluation. Using quantitation theory type I (QT-1), regression equations are fitted to determine the impact of different design categories on Kansei evaluation. Illustrated in a campus setting, this approach optimizes the shared mobility experience, meeting college students’ aesthetic preferences. This method serves as a valuable reference for product design in diverse contexts. Full article

Greenhouse cultivation in Almería, Spain, has experienced continuous growth over the last five decades, and this area has established itself as one of Europe’s leading vegetable-producing regions. With 8201 hectares under cultivation, tomatoes are the most important crop, accounting for 63% of the total value of greenhouse tomato production in Spain. The aim of this study is to design and develop a tool that facilitates tomato trellising under greenhouse conditions and allows it to be carried out at the ground level. An operating principle is developed, and a static analysis of the tool is carried out. Time, costs, and risk of falling from height are compared with traditional methods (ladders, stilts, manual wheeled scaffolding, and motorized scaffolding). The tool incorporates a telescopic carbon fiber mast, a direct-current motor, and electromagnets. The results indicate that the tool is the second fastest method (4′38″) and has the second lowest cost (EUR 8026.93). It is concluded that it is a viable option for trellising, since it eliminates the risk of falling from height while maintaining competitive times and reasonable costs. Full article

Design standards for manual handling equipment tend to measure maximal loads and moving forces using a smooth, flat, horizontal steel plate; yet, in everyday use, such equipment is used on floor coverings. Such test methods therefore overestimate the maximal loads acceptable for operators, which increases the risk of injury including the development of musculoskeletal disorders. This study presents a new approach for calculating the pushing force for manually handled equipment moving longitudinally on resilient floor coverings from the pushing force measured on a steel plate. This method combines corrective forces with the pushing force model presented in this study. Corrective force abaci, which describe corrective forces as functions of the hardness of the floor covering’s base foam, are provided for each type of tread and bearing in the cart’s wheels. These abaci have been elaborated from pushing force measurements obtained with 44 wheel designs (of varying diameters, treads and bearings) tested on five different floors on a custom-built test bench. A mean deviation between experimental results and model predictions of 5.1% is obtained for pushing forces. These results permit us to account for the real conditions in which manual handling equipment is used and help in reducing the incidence of musculoskeletal disorders. Full article

Background/Objectives: Very few studies describe the various feelings experienced in the emergency department (ED). Our study describes the pain, stress, and negative and positive emotions experienced by patients admitted to the ED in relation to age, gender, and reason for ED admission. Methods: Patients admitted to the ED of seven French hospitals were surveyed as part of the randomised multicentre study SOFTER IV (n = 2846). They reported the intensity of their pain on a numerical rating scale of 0 to 10, the intensity of their stress on an equivalent scale, and their emotions on a five-point rating scale using an adapted version of the Geneva Emotion Wheel proposed by Scherer, based on eight core emotions: fear, anger, regret, sadness, relief, interest, joy, and satisfaction. Results: Patients reported an average pain rating of 4.5 (SD = 3.0) and an average stress rating of 3.4 (SD = 3.1). Forty-six percent reported at least one strong negative emotion, and the two most frequently reported were fear and sadness. Forty-seven percent of patients described feeling at least one strong positive emotion, and the two most frequently reported were interest and relief. Pain was significantly higher among female patients under 60 admitted for injury. Stress was significantly higher among female patients under 60 admitted for illness. Emotions of negative valency were significantly higher among women admitted for injury. Emotions of positive valency were significantly higher among men over 60 admitted for illness. Conclusions: Experiences of pain, stress, and emotions have a strong presence in the ED. The reporting of these feelings varies depending on age, gender, and reason for ED admission. Full article

In recent years, LiDAR Odometry (LO) and LiDAR Inertial Odometry (LIO) algorithms for robot localization have considerably improved, with significant advancements demonstrated in various benchmarks. However, their performance in agricultural environments remains underexplored. This study addresses this gap by evaluating five state-of-the-art LO and LIO algorithms—LeGO-LOAM, DLO, DLIO, FAST-LIO2, and Point-LIO—in a blueberry farm setting. Using an Ouster OS1-32 LiDAR mounted on a four-wheeled mobile robot, the algorithms were evaluated using the translational error metric across four distinct sequences. DLIO showed the highest accuracy across all sequences, with a minimal error of 0.126 m over a 230 m path, while FAST-LIO2 achieved its lowest translational error of 0.606 m on a U-shaped path. LeGO-LOAM, however, struggled due to the environment’s lack of linear and planar features. The results underscore the effectiveness and potential limitations of these algorithms in agricultural environments, offering insights into future improvements and adaptations. Full article

Roadway mortality increased during COVID-19, reversing a multi-decade downward trend. The Fatality Analysis Reporting System (FARS) was used to examine contributing factors pre-COVID-19 and in the COVID-19 era using the five pillars of the Safe System framework: (1) road users; (2) vehicles; (3) roadways; (4) speed; and (5) post-crash care. Two study time periods were matched to control for seasonality differences pre-COVID-19 (n = 1725, 1 April 2018–31 December 2019) and in the COVID-19 era (n = 2010, 1 April 2020–31 December 2021) with a three-month buffer period between the two time frames excluded. Four of the five pillars of the safe system had road safety indicators that worsened during the pandemic. Mortality was 19.7% higher for motor vehicle occupants and 45.1% higher for riders of motorized two-wheeled vehicles. In adjusted analyses, failure to use safety equipment (safety belts/helmets) was associated with 44% higher mortality. Two road user groups, non-motorized bicyclists and pedestrians, did not contribute significantly to higher mortality. Urban roadway crashes were higher compared to rural crashes. Additional scientific inquiry into factors associated with COVID-19-era mortality using the Safe System framework yielded important scientific insights to inform prevention efforts. Motorized two-wheeled vehicles contribute disproportionately to pandemic-era higher mortality and constitute an emerging road safety issue that deserves further attention. Full article