Search Results (1,697)

Vision navigation systems provide significant advantages in agricultural scenarios such as pesticide spraying, weeding, and harvesting by interpreting crop row structures in real-time to establish guidance lines. However, the delay introduced by image processing causes the path and pose information relied upon by the controller to lag behind the actual vehicle state. In this study, a hierarchical delay-compensated cooperative control framework (HDC-CC) was designed to synergize Model Predictive Control (MPC) and Sliding Mode Control (SMC), combining predictive optimization with robust stability enforcement for agricultural navigation. An upper-layer MPC module incorporated a novel delay state observer that compensated for visual latency by forward-predicting vehicle states using a 3-DoF dynamics model, generating optimized front-wheel steering angles under actuator constraints. Concurrently, a lower-layer SMC module ensured dynamic stability by computing additional yaw moments via adaptive sliding surfaces, with torque distribution optimized through quadratic programming. Under varying adhesion conditions tests demonstrated error reductions of 74.72% on high-adhesion road and 56.19% on low-adhesion surfaces. In Gazebo simulations of unstructured farmland environments, the proposed framework achieved an average path tracking error of only 0.091 m. The approach effectively overcame vision-controller mismatches through predictive compensation and hierarchical coordination, providing a robust solution for vision autonomous agricultural machinery navigation in various row-crop operations. Full article

People with intellectual disability and visual impairment often have difficulties in accessing leisure events, engaging in cognitive activities, and performing physical exercise. The present study assessed a program aimed at helping six adults with moderate or moderate-to-mild intellectual disability and blindness in each of the aforementioned areas. The program relied on the use of a technology system involving a smartphone, which was supplied with Internet connection and fitted with the Live Transcribe and MacroDroid applications. These applications were set up to (a) enable the participants to use verbal utterances to successfully access preferred songs and comic sketches (leisure events) and answer series of verbal questions (cognitive activity) automatically presented to them, and (b) enable the smartphone to verbally guide the participants’ performance of series of body movements (physical exercise). The program was introduced according to a nonconcurrent multiple baseline design across participants. The intervention was divided into two phases, which included 17–33 and 39–48 sessions, respectively. The results showed that the participants’ baseline performance (without the support of the system) was generally poor. During the intervention with the system, all participants succeeded in accessing the music or comic events available, satisfactorily answering series of questions, and performing series of body movements. The Percentage of Nonoverlapping Data and the Tau (novlap) methods used to compare baseline and intervention performance produced indices of 1 for all participants (confirming the strong impact of the intervention). These results, which need replication to establish their generality, suggest that the technology system might represent a useful tool for helping people like the participants of this study. Full article

Modern crop breeding requires efficient tools for genetic identity and parentage verification to manage large-scale programs. To address this, we present GIPA (Genomic Identity and Parentage Analysis), a high-performance toolkit designed for these tasks. GIPA integrates key innovations: a sliding-window algorithm enhances accuracy by correcting genotyping errors, an intelligent system classifies samples by heterozygosity to streamline parentage analysis, and an integrated engine generates intuitive chromosome-level heatmaps. We demonstrate its utility in a soybean backcrossing scenario, where it identified a donor line with 98.02% genomic identity to the recipient, providing a strategy to significantly shorten the breeding program. In maize, its parentage module accurately identified the known parents of commercial hybrids with match scores exceeding 97%, validating its use for variety authentication and quality control. By transforming complex SNP data into clear, quantitative, and visual insights, GIPA provides a robust solution that accelerates data-driven decision-making in plant breeding. Full article

Electrochemical detection is widely used in environmental, health, and food analysis due to its portability, low cost, and high sensitivity. However, when analytes with similar redox potentials coexist, overlapping voltammetric signals often occur, which compromises detection accuracy and sensitivity. In this study, a simple second-derivative image sharpening (IS) algorithm is applied to the electrochemical detection of chlorophenol (CP) isomers with similar redox behaviors. Specifically, a graphene-modified electrode was employed for the electrochemical detection of two chlorophenol isomers: ortho-CP (o-CP) and meta-chlorophenol (m-CP) in the range from 1.0 to 10.0 μmol/L. After image-sharpening, the peak potential difference between o- and m-CP increased from 0.08 V to 0.12 V. The limits of detection (LOD) for o-CP and m-CP decreased from 0.6 to 0.9 μmol/L to 0.12 and 0.31 μmol/L, respectively. The corresponding sensitivities also improved from 0.92 to 1.35 A/(mol L⁻¹) to 4.11 and 3.71 A/(mol L⁻¹), respectively. Moreover, the sharpened voltammograms showed enhanced peak resolution, facilitating visual discrimination of the two isomers. These results demonstrate that image sharpening can significantly improve peak shape, peak separation, sensitivity, and detection limit in electrochemical analysis. The obtained algorithm is computationally efficient (<30 lines of C++ (Version 6.0)/OpenCV, executable in <1 ms on an ARM-M0 microcontroller) and easily adaptable to various programming environments, offering a promising approach for data processing in portable electrochemical sensing systems. Full article

The present study aimed to determine the Genotype × Environment interaction (GEI), yield stability, and agronomic performance of 24 “Pinto” bean lines under semi-arid conditions in Central-West Mexico. All the lines possess a slow-darkening seed coat, a trait that prolongs visual quality and increases market value. The lines, which exhibit an indeterminate prostrate growth habit, were evaluated in three contrasting environments: irrigated, rainfed, and drought-stressed. A combined analysis of variance, Tukey’s test, and the additive main effects and multiplicative interaction (AMMI 2) model were applied to assess seed yield and agronomic traits. Average seed yield declined markedly across environments, from 2279 kg ha⁻¹ under irrigation to 593 kg ha⁻¹ under drought stress, with different lines performing best in each environment. AMMI 2 biplot analysis showed that the first two principal components explained 100% of GEI variability for seed yield, dry shoot biomass, total biomass, harvest index, pods per plant, and seeds per pod. Both genetic and environmental effects were significant, with notable GEI patterns. Despite pronounced environmental influence, several lines exhibited stable performance across environments. Line 11 consistently combined high yield and stability, positioning it as a strong candidate for cultivar registration and as a parent in breeding programs targeting semiarid regions. These results underscore the importance of multi-environment evaluation for identifying genotypes with broad or specific adaptation, contributing to genetic improvement and sustainable bean production under variable moisture regimes. Full article

Agriculture, food security, and economic stability are impacted by plant diseases, making their identification and diagnosis essential. This article illustrates the research trends in plant disease detection using transformers through a bibliometric analysis based on visualization. The publications used in this work were collected from Scopus and Web of Science databases. For visualization, programs such as Biblioshiny and VOSViewer 1.6.20 were used. The results demonstrate that China is the most productive country, accounting for 11 total publications and 126 citations. China Agricultural University was the most productive institute, with six publications, while the Frontiers in Plant Science journal was the most productive journal, with six publications and 102 citations. It also demonstrates that the most used research topics in this field are “deep learning”, “plant disease”, and “vision transformer”. This study provides insights into the application of transformers for plant disease detection, enabling researchers to better understand and explore this field. Full article

Background/Objectives: Sports-related concussions can result in prolonged symptoms and deficiencies in stability and balance. Effective and standardized rehabilitation protocols remain limited. This case report introduces a novel balance training program using virtual reality and force plate technology to address persistent post-concussion symptoms. Methods: A 20-year-old National Collegiate Athletic Association (NCAA) Division I football player with a history of multiple concussions and balance-related symptoms completed a 10-week intervention. The program utilized a multi-axis force platform and immersive visual tasks to train vestibular, oculomotor, and proprioceptive systems. Each weekly session consisted of seven tasks progressing in difficulty, which were completed three times per session. Performance was measured by the percentage of time a digital cursor remained within task boundaries using the distribution of their center of mass. Symptom self-reports were also recorded. Results: Cumulative mean performance improved from 75.87% in the first session to 91.67% in the final session. All individual template scores increased, including those on the most complex template, which rose from 55.76% to 80.20%. The patient also reported reduced dizziness, disorientation, and improved functional balance across the 10-week period. Conclusions: This virtual-reality-based balance training program shows promise in resolving persistent post-concussion symptoms. Its objective measurement, engaging format, and ease of use suggest potential for broader application in concussion rehabilitation. Full article

Incomplete spinal cord injury (iSCI) results in impaired postural control and walking ability. Visual over-reliance may occur in iSCI individuals to maintain postural control. This can challenge their postural stability in various contexts of daily life activities. The present study assessed the feasibility, acceptability, and preliminary outcomes of balance training with intermittent visual deprivation using stroboscopic glasses on postural control and visual reliance during quiet standing in iSCI individuals. Training impact on walking performance was also evaluated. Seven chronic iSCI individuals participated in a 6-week home-based balance training program, three times weekly, using stroboscopic glasses. Postural and walking abilities were assessed pre- and post-training using a bipedal stance test (BST) and 10 m walking test (10 MWT). BST was performed, with open-eyes (OE) and closed-eyes (CE), on a force plate for three 30 s trials. The center of pressure (CoP) variables included were CoP area (A-CoP) and CoP mean velocity (MV-CoP). Romberg ratios (CE/OE) for two CoP variables were calculated. Duration and speed were measured in 10 MWT. Intervention feasibility was assessed using the feasibility and acceptability questionnaire. Data from able-bodied individuals were recorded and used as references of physiological performance. iSCI individuals were significantly less stable and showed visual over-reliance for postural steadiness compared to controls. Also, their walking ability was impaired. All iSCI individuals completed the training (adherence rate: 84%) and rated it highly feasible. A-CoP and MV-CoP significantly reduced after training in CE condition (p = 0.018, respectively) but not in OE condition (p > 0.05). The Romberg ratio of A-CoP was significantly lower (p = 0.018), but the Romberg ratio of MV-CoP was not (p > 0.05). A significant reduction in duration and increase in speed (p = 0.018, respectively) in performing the 10 MWT were observed. Preliminary findings from this explorative study indicated that 6-week home-based balance training with intermittent visual deprivation was feasible, acceptable, and had promising potential benefits in improving postural control with a reduction in visual over-reliance in iSCI individuals. The training enhanced also their walking performance. Full article

Background: This study compared the performance of a Head-mounted Virtual Reality Perimeter (HVRP) with the Humphrey Field Analyzer (HFA), the standard in automated perimetry. The HFA is the established standard for automated perimetry but is constrained by lengthy testing, bulky equipment, and limited patient comfort. Comparative data on newer head-mounted virtual reality perimeters are limited, leaving uncertainty about their clinical reliability and potential advantages. Aim: The aim was to evaluate parameters such as visual field outcomes, portability, patient comfort, eye tracking, and usability. Methods: Participants underwent testing with both devices, assessing metrics like mean deviation (MD), pattern standard deviation (PSD), and duration. Results: The HVRP demonstrated small but statistically significant differences in MD and PSD compared to the HFA, while maintaining a consistent trend across participants. MD values were slightly more negative for HFA than HVRP (average difference −0.60 dB, p = 0.0006), while pattern standard deviation was marginally higher with HFA (average difference 0.38 dB, p = 0.00018). Although statistically significant, these differences were small in magnitude and do not undermine the clinical utility or reproducibility of the device. Notably, HVRP showed markedly shorter testing times with HVRP (7.15 vs. 18.11 min, mean difference 10.96 min, p < 0.0001). Its lightweight, portable design allowed for bedside and home testing, enhancing accessibility for pediatric, geriatric, and mobility-impaired patients. Participants reported greater comfort due to the headset design, which eliminated the need for chin rests. The device also offers potential for AI integration and remote data analysis. Conclusions: The HVRP proved to be a reliable, user-friendly alternative to traditional perimetry. Its advantages in comfort, portability, and test efficiency support its use in both clinical settings and remote screening programs for visual field assessment. Its portability and user-friendly design support broader use in clinical practice and expand possibilities for bedside assessment, home monitoring, and remote screening, particularly in populations with limited access to conventional perimetry. Full article

Background/Objectives: Autism is characterized by atypical sensory processing, which affects spatial and temporal perception. Here, we explore sensory processing in children with autism, focusing on visuospatial and temporal tasks across visual and auditory modalities. Methods: Ninety-two children aged 4 to 6 participated, divided into three groups: autism (n = 32), neurotypical chronological age-matched controls (n = 28), and neurotypical developmental age-matched controls (n = 32). The autism group consisted of high-functioning children (26 boys). The participants completed computer-based tasks requiring spatial and temporal processing. Response accuracy and reaction times were recorded. Results: The autism group demonstrated higher accuracy in temporal tasks (visual and auditory modalities) and comparable accuracy in visuospatial modality, but slower response times in all tasks compared to both neurotypical controls. These results suggest a strategy that prioritizes accuracy over speed, while preserving spatial and temporal processing in autism. Conclusions: These findings suggest that temporal processing, rather than the sensory modality, drives decision-making strategies in children with autism. Our findings highlight the need for interventions aligned with autistic children’s slower but accurate processing style to support social interaction and reduce stress. In a fast-paced digitalized world, autistic children might benefit from slower, balanced, and inclusive, evidence-based approaches that align with their cognitive rhythm and reduce overstimulation. By incorporating these unique strategies, targeted programs can enhance the quality of life and adaptive skills of children with autism, thereby fostering better integration into social and sensory-rich environments. Full article

Objectives: Chronic pain corresponds to hypersensitivity to painful stimuli; however, its relation to acute pain sensitivity in children is poorly understood. We explored this relationship by comparing acute and chronic pain measures, along with related factors, in children with chronic pain syndromes versus controls, before and after therapeutic intervention. Methods: This prospective controlled cohort study involved 57 children with chronic pain undergoing intensive interdisciplinary pain treatment in a hospital-based pain rehabilitation program and 50 controls. Participants, aged 7–18, were tested using a cold pressor task (CPT) at admission, discharge, and first follow-up visit. Data on sleep, anxiety, psychological distress, functional impairment, and pain were collected. Results: Significant differences were found between control and treatment groups in average pain threshold (p < 0.001), pain tolerance (p = 0.035), sleep visual analog scale (VAS) (p < 0.001), functional disability inventory (p < 0.001), patient reported outcomes information system anxiety assessment tool (p < 0.001), general anxiety disorder 7-item scale (p < 0.001), pain VAS (p < 0.001) and total brief symptom inventory (BSI) (p < 0.001) scores at admission with children with chronic pain scoring worse on all measures save the pain VAS during the CPT. After treatment and at follow-up, function and mental health measures improved but not acute pain threshold. Conclusions: At treatment completion, function and mental health significantly improved but acute pain threshold and sleep quality were unchanged. These findings suggest that while chronic pain treatment improves overall function and mental health, acute pain thresholds may not be a suitable indicator for evaluating the efficacy of interventions. Full article

Steel reinforcement is one of the most important materials used in the construction industry. This research optimizes reinforcement bar fabrication by integrating Building Information Modeling (BIM) with visual programming in Dynamo. On-site rebar cutting and bending generate significant material waste, increasing costs and environmental impact. To address this, an intelligent Dynamo script was developed to extract detailed 3D rebar and 4D scheduling data from BIM models. The script optimizes material usage by specifying cut-off lengths to improve reuse and minimize waste. Validation through two real-world case studies demonstrated the method’s significant potential. Effectiveness was assessed using benchmarks comparing the number of bars saved, waste reduced, and overall cost savings. The study confirms that optimized fabrication significantly cuts waste and cost. Its effectiveness, however, varies with rebar type and structural component, with the most significant gains observed in medium-length bars and pile caps. By offering a novel tool for sustainable construction, this research advances BIM-enabled reinforcement design and material optimization. Full article

Smart contracts are central to blockchain ecosystems, yet their development remains technically demanding, error-prone, and tied to platform-specific programming languages. This paper introduces SCEditor-Web, a web-based modeling environment that combines model-driven engineering (MDE) with generative artificial intelligence (Gen-AI) to simplify contract design and code generation. Developers specify the structural and behavioral aspects of smart contracts through a domain-specific visual language grounded in a formal metamodel. The resulting contract model is exported as structured JSON and transformed into executable, platform-specific code using large language models (LLMs) guided by a tailored prompt engineering process. A prototype implementation was evaluated on Solidity contracts as a proof of concept, using representative use cases. Experiments with state-of-the-art LLMs assessed the generated contracts for compilability, semantic alignment with the contract model, and overall code quality. Results indicate that the visual-to-code workflow reduces manual effort, mitigates common programming errors, and supports developers with varying levels of expertise. The contributions include an abstract smart contract metamodel, a structured prompt generation pipeline, and a web-based platform that bridges high-level modeling with practical multi-language code synthesis. Together, these elements advance the integration of MDE and LLMs, demonstrating a step toward more accessible and reliable smart contract engineering. Full article

Artificial intelligence is rapidly reshaping skill expectations across media, marketing, and journalism, however, university curricula are not evolving at a comparable speed. To quantify the resulting curriculum–skill gap in communication-related programs, two synchronous corpora were assembled for the period July 2024–June 2025: 66 course descriptions from six leading UK universities and 107 graduate-to-mid-level job advertisements in communications, digital media, advertising, and public relations. Alignment around AI, datafication, and platform governance was assessed through a three-stage natural-language-processing workflow: a dual-tier AI-keyword index, comparative TF–IDF salience, and latent Dirichlet allocation topic modeling with bootstrap uncertainty. Curricula devoted 6.0% of their vocabulary to AI plus data/platform terms, whereas job ads allocated only 2.3% (χ² = 314.4, p < 0.001), indicating a conceptual-critical emphasis on ethics, power, and societal impact in the academy versus an operational focus on SEO, multichannel analytics, and campaign performance in recruitment discourse. Topic modeling corroborated this divergence: universities foregrounded themes labelled “Politics, Power & Governance”, while advertisers concentrated on “Campaign Execution & Performance”. Environmental and social externalities of AI—central to the Special Issue theme—were foregrounded in curricula but remained virtually absent from job advertisements. The findings are interpreted as an extension of technology-biased-skill-change theory to communication disciplines, and it is suggested that studio-based micro-credentials in automation workflows, dashboard visualization, and sustainable AI practice be embedded without relinquishing critical reflexivity, thereby narrowing the curriculum–skill gap and fostering environmentally, socially, and economically responsible media innovation. With respect to the novelty of this research, it constitutes the first large-scale, data-driven corpus analysis that empirically assessed the AI-related curriculum–skill gap in communication disciplines, thereby extending technology-biased-skill-change theory into this field. Full article

Background: Globally, uncorrected refractive errors are recognized as the primary cause of visual impairment and blindness. According to a report by the World Health Organization (WHO), providing spectacle lenses at an affordable cost remains a significant challenge, particularly for underprivileged populations in developing countries. This challenge contributes to the low compliance with spectacle wear worldwide. However, the benefits of wearing spectacles are influenced by the perceptions of the population regarding spectacle use. Methods: A quantitative, cross-sectional survey-based study was conducted at a superior educative center in Oman, the University of Buraimi. Participants were recruited from the four major colleges, namely, the College of Health Sciences (COHS), College of Business (COB), College of Engineering (COE), and College of Law (COL), and the Center for Foundation Studies (CFS). This study was conducted over the period from 18 December 2022 to 18 December 2023. Essential data were collected using an electronic questionnaire facilitated by the Google platform. The initial section of the questionnaire outlines this study’s objectives and its benefits to the community. The digital survey comprises three sections: the first section addresses the sociodemographic profile of the participants; the second section explores perceptions related to spectacles; and the third section examines visual symptoms associated with spectacle wear. In this study, a pre-tested survey was administered following consultation with a panel of three subject matter experts who reviewed the clarity and content validity of the test items. Data analyses were performed using descriptive statistics, and linear regression was applied to assess the effect of socioeconomic profile on perceptions of spectacles. Additionally, data entry, processing, and analysis were conducted using SPSS 25 software. The overall mean score for spectacle-related visual symptoms was 2.51 ± 0.75, indicating a moderate level of symptom occurrence. Results: A total of 415 participants (N = 415) were included in this study, comprising 133 males (32.0%) and 282 females (68.0%). The most prominent symptoms related to spectacle perception were “light sensitivity” and “eye pain”, with mean values of 3.03 ± 1.30 and 3.04 ± 1.25, respectively. Additionally, 249 participants (60%) reported moderate concern regarding spectacle-related visual symptoms. Among female participants, 118 (41.8%) exhibited little concern about visual symptoms associated with spectacle wear, whereas this was observed in 25.6% of male participants. Descriptive statistics indicated the mean perceived spectacle-related disadvantages score measured on a scale of 0 to 4 was 2.88 ± 1.16 (57.69% ± 23.15% in percentages), reflecting a moderate perception of such disadvantages. The linear regression model demonstrated statistical significance, as indicated by the likelihood ratio chi-square = 199.194 (df = 15, p < 0.001). The most significant predictor was study major (χ² = 72.922, p < 0.001). Conclusions: The present study indicates that undergraduate students generally exhibit a low perception of the disadvantages associated with wearing spectacles. Randomized sampling should be preferred in future studies to the convenience sampling technique. The most frequently reported visual symptoms include “light sensitivity and eye pain” among spectacle wearers. Therefore, it is imperative to implement health education programs and foundational studies across colleges to address these issues among undergraduate university students. Full article