Search Results (30)

Air-pollution-related issues, including the rise in carbon dioxide emissions, require, among others, solutions that include using electric vehicles supplied by the energy obtained from renewable sources. These solutions also include the infrastructure for electric vehicle charging. However, the existing systems mostly employ independent subsystems (such as subsystems for the control of electric vehicle chargers, subsystems for the control of smart battery storage, etc.), leading to hardware redundancy, software complexity, increased hardware costs, and communication link complexity. An architecture of a system for remotely controlling a renewable-energy-source-powered sustainable electric vehicle charging station, which overcomes these deficiencies, is presented in this paper. Consideration is also given to the sizes and combinations of different parts (renewable sources, batteries, chargers, etc.) for various purposes (households, replacing current gas stations, big parking spaces in shopping centers, public garages, etc.). The ability to integrate a wide range of features into one system helps to optimize the use of several subsystems, including the ones that control electric vehicle chargers remotely, smart storage battery remote control, smart electricity meter remote control, and fiscal cash register remote control, creating a sustainable and economically efficient solution. In this manner, consumers of electric vehicles will have easier access to renewable-energy-powered sustainable charging stations. This helps to reduce the amount of air pollution and its harmful effects, including climate change, by promoting the use of electric vehicles that are powered by renewable energy sources. The energy independence and sustainability of the station were considered in such a way that the owner of the station achieves maximum economic benefits. Full article

Background/Objectives: In 2010, approximately 60.5 million people were affected by glaucoma, making it the leading cause of permanent vision impairment globally. With the rise of telehealth tools and technological advancements in glaucoma care, this review aims to provide an up-to-date analysis regarding remote monitoring systems in glaucoma management. Methods: A systematic literature search (in compliance with PRISMA guidelines) was conducted across six databases (CINAHL, MEDLINE, PsycINFO, Web of Science, Scopus, and Cochrane Library) and one grey literature source (Google Scholar), covering the period from 2000 to 2024. Relevant studies meeting predefined inclusion criteria were identified and analyzed. Results: The search identified 21 eligible studies focusing on various glaucoma telemonitoring tools. Several studies demonstrated the potential for continuous remote intraocular pressure (IOP) monitoring and highlighted the effectiveness of home-based visual field-testing technologies (e.g., Melbourne Rapid Fields, Eyecatcher, and VF-Home), which showed results closely matching in-clinic tests. All 21 studies underwent risk of bias assessment with appropriate tools based on study design, and none showed a high overall risk of bias, indicating robust methodology. Conclusions: Glaucoma telemonitoring tools are feasible and cost-effective, helping to reduce patient travel and waiting times and improving patient satisfaction. However, periodic in-person examinations remain necessary to optimally monitor disease progression and adjust treatments. Future directions should focus on interdisciplinary collaboration and the development of advanced algorithms (including artificial intelligence) to further enhance patient outcomes in teleglaucoma care. Full article

Faba bean (Vicia faba L.) is a globally significant legume valued for its applications in food, vegetables, and green manure, yet its high outcrossing rate (30–80%) poses challenges for production development. A rare short-winged trait identified in Yunnan, China, offers promise for developing low-outcrossing varieties, reducing outcrossing rates to below 5%. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) analyses revealed that the epidermal cells of normal wing petals are conical, while those of short-wing petals are tubular. This study examined 200 F₂ lines from crosses between ‘K0692’ (short-winged) and ‘Yundou 1183’, as well as ‘Yundoulvxin 1’ (short-winged) and ‘Yundou 1183’. The GWASs identified 10 SNP loci across chromosomes 2, 3, 4, and 5, with SNP_chr4::1013887633 explaining 22.20% of the wing trait variation. Key candidate genes were identified, such as VFH_III145120, which influences floral identity; and VFH_III149200, associated with epidermal differentiation. GO enrichment analysis demonstrated significant gene involvement in RNA localization, ribosome biogenesis, and preribosome metabolism, while KEGG analysis linked these genes to pathways in amino acid, nucleotide, and purine metabolism; ubiquitin-mediated proteolysis; and protein processing in the endoplasmic reticulum. These findings lay a foundation for breeding low-outcrossing faba bean varieties and enhancing sustainable faba bean cultivation. Full article

Industrial robots play a crucial role in modern manufacturing, but ensuring safe human–robot collaboration remains a challenge. Traditional collision avoidance methods, such as physical barriers and emergency stops, are limited in efficiency and flexibility. This study proposes the Asymmetry Elliptical Likelihood Potential Field (AELPF) algorithm, a novel real-time collision avoidance system inspired by autonomous driving technologies. The AELPF method leverages LiDAR sensors to dynamically compute an asymmetric elliptical repulsive field, enabling precise obstacle detection and avoidance in 3D environments. Unlike conventional potential field approaches, the AELPF accounts for both vertical and horizontal deviations, allowing it to adapt to complex industrial settings. To quantify the performance of AELPF, we compare it to two commonly used algorithms: the Vector Field Histogram (VFH) and the Follow the Gap Method (FGM). In terms of processing time, the VFH algorithm requires 50 ms per cycle, while the FGM algorithm operates at 22 ms. In contrast, the the AELPF, when using only a single channel, processes at 12 ms, which is significantly faster than both the VFH and FGM. These results indicate that the AELPF not only provides faster decision-making but also ensures smoother, more responsive navigation in dynamic environments. Both simulation and physical experiments confirm that the AELPF significantly improves obstacle avoidance, particularly in the z-axis direction, reducing the risk of collisions while maintaining operational efficiency. Full article

A variable frequency hopping (VFH) signal is a kind of frequency hopping (FH) signal that varies both in frequency and dwell time. However, in radio surveillance, the existing methods for unidentified signals using VFH cannot be effectively handled. In this paper, we proposed an improved joint analysis method based on time–frequency domain features, which adopts multi-level processing to solve the time–frequency domain feature analysis problem of the VFH signal. First, the received signal is pre-processed by Short-Time Fourier Transform (STFT) and binarization, and a highly discriminative time–frequency image is obtained; then, the fixed frequency signal is removed based on the feature of connected domains, and the conventional frequency hopping (CFH) signal is removed by density-based spatial clustering of applications with noise (DBSCAN); finally, the overlapping region is cropped by the joint energy peak time–domain continuity properties. After the above multi-level joint processing method, the problem of VFH signal processing is effectively solved. The simulation result shows that the Mean Square Error (MSE) between the output results and the time–frequency image of the original VFH signal tends to be close to 0 when the Signal-to-Noise ratio (SNR) is 5 dB. Full article

This paper presents a comprehensive evaluation of the previously introduced multidisciplinary model to quantify human uncertainty (MMtQHU) within a realistic 5G-enabled cyber–physical–social systems (CPSS) environment. The MMtQHU, which integrates human, social, and environmental factors into CPSS modeling, is applied to the Ingolstadt traffic scenario (InTAS), a detailed urban simulation reflecting high-traffic conditions. By modeling unpredictable driver behaviors, such as deviations from optimal routes, the study assesses the model’s effectiveness in managing human-induced uncertainties in vehicle-for-hire (VFH) applications. The evaluation shows that human uncertainty significantly impacts 5G network resource allocation and traffic dynamics. A comparative analysis of traditional resource allocation methods reveals their limitations in handling the dynamic nature of human behavior. These findings underscore the necessity for advanced, adaptive strategies, potentially leveraging artificial intelligence and machine learning to enhance the resilience and efficiency of 5G networks in CPSS environments. The study offers valuable insights for future advancements in robust and adaptive 5G infrastructure by highlighting the critical role of integrating human behavior into CPSS models. Full article

In this paper, we present a novel three-dimensional spatial path planning algorithm based on the Vector Field Histogram* (VFH*) approach, specifically tailored for underwater robotics applications. Our method leverages the strengths of VFH* in obstacle avoidance while enhancing its capability to handle complex three-dimensional environments. Through extensive simulations, we demonstrate the superior performance of our algorithm compared to traditional methods, such as RS-RRT algorithm. Our results show significant improvements in terms of computational efficiency and path optimality, making it a viable solution for real-time path planning in dynamic underwater environments. Full article

Driving a motorized wheelchair is not without risk and requires high cognitive effort to obtain good environmental perception. Therefore, people with severe disabilities are at risk, potentially lowering their social engagement, and thus, affecting their overall well-being. Therefore, we designed a cooperative driving system for obstacle avoidance based on a trained reinforcement learning (RL) algorithm. The system takes the desired direction and speed from the user via a joystick and the obstacle distribution from a LiDAR placed in front of the wheelchair. Considering both inputs, the system outputs a pair of forward and rotational speeds that ensure obstacle avoidance while being as close as possible to the user commands. We validated it through simulations and compared it with a vector field histogram (VFH). The preliminary results show that the RL algorithm does not disruptively alter the user intention, reduces the number of collisions, and provides better door passages than a VFH; furthermore, it can be integrated on an embedded device. However, it still suffers from higher jerkiness. Full article

In an unmanned orchard, various tasks such as seeding, irrigation, health monitoring, and harvesting of crops are carried out by unmanned vehicles. These vehicles need to be able to distinguish which objects are fruit trees and which are not, rather than relying on human guidance. To address this need, this study proposes an efficient and robust method for fruit tree detection in orchard point cloud maps. Feature extraction is performed on the 3D point cloud to form a two-dimensional feature vector containing three-dimensional information of the point cloud and the tree target is detected through the customized deep learning network. The impact of various feature extraction methods such as average height, density, PCA, VFH, and CVFH on the detection accuracy of the network is compared in this study. The most effective feature extraction method for the detection of tree point cloud objects is determined. The ECA attention module and the EVC feature pyramid structure are introduced into the YOLOv8 network. The experimental results show that the deep learning network improves the precision, recall, and mean average precision by 1.5%, 0.9%, and 1.2%, respectively. The proposed framework is deployed in unmanned orchards for field testing. The experimental results demonstrate that the framework can accurately identify tree targets in orchard point cloud maps, meeting the requirements for constructing semantic orchard maps. Full article

This study presents the efficiency of TSS and organic pollutants (BOD₅ and COD) removal in a hybrid constructed wetland wastewater treatment plant (VF-HF type) with an aeration system. This study was conducted over 6 years (2017–2022) in a facility with a capacity of 4.5 m³/day located in southeastern Poland and designed to treat real domestic wastewater from a school building. The studied facility consists of a three-chambered septic tank, a pumping station with an aeration system, and two beds with vertical and horizontal flow planted with giant miscanthus and willow. As a result of artificial aeration, the dissolved oxygen concentration in wastewater after mechanical treatment increased significantly, by an average of 1.18 mg O₂/L, and was negatively correlated with wastewater temperature. The cumulative pollutant removal effects of the treatment plant (primary settling tank + VFCW + HFCW) were 81% for TSS, 98% for BOD₅, and 89% for COD. There was no statistically significant effect of aeration on the organic pollutant removal effects in the VF bed, and such an effect was found for the temperature of wastewater entering the VF bed. The TSS, BOD₅, and COD removal effects in the VF bed and BOD₅ in the VF-HF system were positively correlated with air temperature. The technological reliability of the treatment plant was 98% for TSS and 100% for BOD₅ and COD. The use of artificial aeration of wastewater makes it possible to achieve high organic pollutant removal efficiency in SSF CWs and to compensate for limitations due to the reduction in the area of constructed wetland beds. Full article

The shoot apical meristem culture has been used widely to produce virus-free plantlets which have the advantages of strong disease resistance, high yield, and prosperous growth potential. However, this virus-free plant will be naturally reinfected in the field. The physiological and metabolic responses in the reinfected plant are still unknown. The flower of chrysanthemum ‘Hangju’ is a traditional medicine which is unique to China. In this study, we found that the virus-free ‘Hangju’ (VFH) was reinfected with chrysanthemum virus B/R in the field. However, the reinfected VFH (RVFH) exhibited an increased yield and medicinal components compared with virus-infected ‘Hangju’ (VIH). Comparative analysis of transcriptomes was performed to explore the molecular response mechanisms of the RVFH to CVB infection. A total of 6223 differentially expressed genes (DEGs) were identified in the RVFH vs. the VIH. KEGG enrichment and physiological analyses indicated that treatment with the virus-free technology significantly mitigated the plants’ lipid and galactose metabolic stress responses in the RVFH. Furthermore, GO enrichment showed that plant viral diseases affected salicylic acid (SA)-related processes in the RVFH. Specifically, we found that phenylalanine ammonia-lyase (PAL) genes played a major role in defense-related SA biosynthesis in ‘Hangju’. These findings provided new insights into the molecular mechanisms underlying plant virus–host interactions and have implications for developing strategies to improve plant resistance against viruses. Full article

An Autonomous Underwater Helicopter (AUH) is a disk-shaped, multi-propelled Autonomous Underwater Vehicle (AUV), which is intended to work autonomously in underwater environments. The near-bottom area sweep in unknown environments is a typical application scenario, in which the complete coverage path planning (CCPP) is essential for AUH. A complete coverage path planning approach for AUH with a single beam echo sounder, including the initial path planning and online local collision avoidance strategy, is proposed. First, the initial path is planned using boustrophedon motion. Based on its mobility, a multi-dimensional obstacle sensing method is designed with a single beam range sonar mounted on the AUH. The VFH+ algorithm is configured for the heading decision-making procedure before encountering obstacles, based on their range information at a fixed position. The online local obstacle avoidance procedure is simulated and analyzed with variations of the desired heading direction and corresponding polar histograms. Finally, several simulation cases are set up, simulated and compared by analyzing the heading decision in front of different obstacle situations. The simulation results demonstrate the feasibility of the complete coverage path planning approach proposed, which proves that AUH completing a full coverage area sweep in unknown environments with a single beam sonar is viable. Full article

This study aimed to determine the incidence and virulence factor profiling of Vibrio species from hospital wastewater (HWW) and community wastewater effluents. Wastewater samples from selected sites were collected, processed, and analysed presumptively by the culture dependent methods and molecular techniques. A total of 270 isolates were confirmed as Vibrio genus delineating into V. cholerae (27%), V. parahaemolyticus (9.1%), V. vulnificus (4.1%), and V. fluvialis (3%). The remainder (>50%) may account for other Vibrio species not identified in the study. The four Vibrio species were isolated from secondary hospital wastewater effluent (SHWE), while V. cholerae was the sole specie isolated from Limbede community wastewater effluent (LCWE) and none of the four Vibrio species was recovered from tertiary hospital wastewater effluent (THWE). However, several virulence genes were identified among V. cholerae isolates from SHWE: ToxR (88%), hylA (81%), tcpA (64%), VPI (58%), ctx (44%), and ompU (34%). Virulence genes factors among V. cholerae isolates from LCWE were: ToxR (78%), ctx (67%), tcpA (44%), and hylA (44%). Two different genes (vfh and hupO) were identified in all confirmed V. fluvialis isolates. Among V. vulnificus, vcgA (50%) and vcgB (67%) were detected. In V. parahaemolyticus, tdh (56%) and tlh (100%) were also identified. This finding reveals that the studied aquatic niches pose serious potential health risk with Vibrio species harbouring virulence signatures. The distribution of virulence genes is valuable for ecological site quality, as well as epidemiological marker in the control and management of diseases caused by Vibrio species. Regular monitoring of HWW and communal wastewater effluent would allow relevant establishments to forecast, detect, and mitigate any public health threats in advance. Full article

NDBs were fabricated from gum Arabic (GA) and polyvinyl alcohol (PVA) in different ratios using novel techniques (casting, dehydration, and peeling). The GA/PVA blends were cast with a novel vibration-free horizontal flow (VFHF) technique, producing membranes free of air bubble defects with a homogenous texture, smooth surface, and constant thickness. The casting process was achieved on a self-electrostatic template (SET) made of poly-(methyl methacrylate), which made peeling the final product membranes easy due to its non-stick behavior. After settling the casting of the membranous, while blind, the sheets were dried using nanometric dehydration under a mild vacuum stream using a novel stratified nano-dehydrator (SND) loaded with P₂O₅. After drying the NDB, the dry, smooth membranes were peeled easily without scratching defects. The physicochemical properties of the NDBs were investigated using FTIR, XRD, TGA, DTA, and AFM to ensure that the novel techniques did not distort the product quality. The NDBs retained their virgin characteristics, namely, their chemical functional groups (FTIR results), crystallinity index (XRD data), thermal stability (TGA and DTA), and ultrastructural features (surface roughness and permeability), as well as their microbial biodegradation ability. Adding PVA enhanced the membrane’s properties except for mass loss, whereby increasing the GA allocation in the NDB blend reduces its mass loss at elevated temperatures. The produced bioplastic membranes showed suitable mechanical properties for food packaging applications and in the pharmaceutical industry for the controlled release of drugs. In comparison to control samples, the separated bacteria and fungi destroyed the bioplastic membranes. Pseudomonas spp. and Bacillus spp. were the two main strains of isolated bacteria, and Rhizobus spp. was the main fungus. The nano-dehydration method gave the best solution for the prompt drying of water-based biopolymers free of manufacturing defects, with simple and easily acquired machinery required for the casting and peeling tasks, in addition to its wonderful biodegradation behavior when buried in wet soil. Full article

In this paper, we propose a fusion algorithm that integrates the 3D vector field histogram plus (VFH+) algorithm and the improved dynamic window approach (DWA) algorithm. The aim is to address the challenge of cooperative obstacle avoidance faced by multi-UAV formation flying in unknown environments. First, according to the navigation evaluation function of the standard DWA algorithm, the target distance is introduced to correct the azimuth. Then, aiming at the problem that the fixed weight mechanism in standard DWA algorithm is unreasonable, we combine the A* algorithm and introduce variable weight factors related to azimuth to improve the target orientation ability in local path planning. A new rotation cost evaluation function is added to improve the obstacle avoidance ability of two-dimensional UAV. Then, 3D VFH+ algorithm is introduced and integrated with improved DWA algorithm to design a distributed cooperative formation obstacle avoidance control algorithm. Simulation validation suggests that compared with the traditional DWA algorithm, the improved collaborative obstacle avoidance control algorithm can greatly optimize the obstacle avoidance effect of UAVs’ formation flight. Full article