Search Results (179,873)

With the advancement of remote sensing imagery and multimodal sensing technologies, monitoring plant trait dynamics has emerged as a critical area of research in modern agriculture. Traditional approaches, which rely on handcrafted features and shallow models, struggle to effectively address the complexity inherent in high-dimensional and multisource data. In contrast, deep learning, with its end-to-end feature extraction and nonlinear modeling capabilities, has substantially improved monitoring accuracy and automation. This review summarizes recent developments in the application of deep learning methods—including CNNs, RNNs, LSTMs, Transformers, GANs, and VAEs—to tasks such as growth monitoring, yield prediction, pest and disease identification, and phenotypic analysis. It further examines prominent research themes, including multimodal data fusion, transfer learning, and model interpretability. Additionally, it discusses key challenges related to data scarcity, model generalization, and real-world deployment. Finally, the review outlines prospective directions for future research, aiming to inform the integration of deep learning with phenomics and intelligent IoT systems and to advance plant monitoring toward greater intelligence and high-throughput capabilities. Full article

Background/Objectives: Hip-level amputees face ambulatory challenges due to the lack of a lower limb and prosthetic hip power. Some hip-level amputees restore mobility by using a prosthesis with hip, knee, and ankle joints. Powered prosthetic joints contain an actuator that provides external flexion-extension moments to assist with movement. Powered knee and powered ankle-foot units are on the market, but no viable powered hip unit is commercially available. This research details the development of a novel powered four-bar prosthetic hip joint that can be integrated into a full-leg prosthesis. Methods: The hip joint design consisted of a four-bar linkage with a harmonic drive DC motor placed in the inferior link and an additional linkage to transfer torque from the motor to the hip center of rotation. Link lengths were determined through engineering optimization. Device strength was demonstrated with force and finite element analysis and with ISO 15032:2000 A100 static compression tests. Walking tests with a wearable hip-knee-ankle-foot prosthesis simulator, containing the novel powered hip, were conducted with three able-bodied participants. Each participant walked back and forth on a level 10 m walkway. Custom hardware and software captured joint angles. Spatiotemporal parameters were determined from video clips processed in the Kinovea software (ver. 0.9.5). Results: The powered hip passed all force and finite element checks and ISO 15032:2000 A100 static compression tests. The participants, weighing 96 ± 2 kg, achieved steady gait at 0.45 ± 0.11 m/s with the powered hip. Participant kinematic gait profiles resembled those seen in transfemoral amputee gait. Some gait asymmetries occurred between the sound and prosthetic legs. No signs of mechanical failure were seen. Most design requirements were met. Areas for powered hip improvement include hip flexion range, mechanical advantage at high hip flexion, and device mass. Conclusions: The novel powered four-bar hip provides safe level-ground walking with a full-leg prosthesis simulator and is viable for future testing with hip-level amputees. Full article

Reservoir sedimentation, a global challenge causing an annual loss of 0.8–1% of reservoir storage capacity, disrupts fluvial sediment continuity and impacts ecology and societal needs. This study focuses on the Pulangi IV reservoir in the Philippines, a shallow and wide reservoir facing significant sedimentation issues. The research aims to investigate drawdown flushing and dredging of a flushing channel for future sustainable drawdown sluicing. A test flushing event was conducted and monitoring data, including discharge, suspended sediment concentration, bathymetry, and grain size distribution, were collected. Laboratory analyses, such as critical shear stress tests, were performed for model calibration. A 3D reservoir model and a 1D sediment transport model were applied incorporating cohesive sediment behavior. Scenarios were simulated to assess drawdown flushing, dredging and downstream impacts. Results highlight the importance of drawdown level, with cohesive sediment properties playing a critical role. Sedimentation downstream of the dam, resulting from dumped or flushed sediments, was low. However, downstream ecological and morphodynamic monitoring was found to be essential for all modeled strategies. This study demonstrates potential for establishing a flushing channel enabling future sustainable drawdown sluicing during floods by conducting repeated drawdown flushing in combination with dredging in the upper reservoir. Full article

The challenge for healthcare policy makers, managers and practitioners is finding ways to effectively collaborate with patients and community to plan, deliver and evaluate services. The study examined how managers engage the community with the strategic redesign of health services. The study focused on four large scale redevelopment projects, valued at A$2.8B, occurring within a health district in New South Wales, Australia. The study employed a multiple qualitative methods design comprising semi-structured interviews and focus groups. Participants were professionals (n = 24) involved in the strategic planning of health facility redevelopment. Thematic analysis was used to identify, analyse and report findings. Three issues emerged as significant factors influencing engagement, including the following: establishing a new mindset to service planning and delivery; future proofing service delivery; and management of stakeholder expectations. The unique contribution of the research is the identification of three interwoven strategies with 30 actions proposed to assess, understand and respond to external factors: 1. Foster an environment that allows for flexible and adaptable thinking and discussion; 2. Develop systems, structures and processes that facilitate engagement; 3. Encourage systems thinking for effective continuous service provision and redevelopment. Large scale redevelopment projects provide a platform for the strategic redesign of health services. When doing so, engaging the community with strategic planning, implementation and evaluation of healthcare services can lead to improved care outcomes. Full article

Ultra-short-term wind power forecasting is challenged by high volatility and complex temporal patterns, with traditional single-model approaches often failing to provide stable and accurate predictions under diverse operational scenarios. To address this issue, a framework based on the TCN-ELM hybrid model with temporal alignment clustering and feature refinement is proposed for ultra-short-term wind power forecasting. First, dynamic time warping (DTW)–K-means is applied to cluster historical power curves in the temporal alignment space, identifying consistent operational patterns and providing prior information for subsequent predictions. Then, a correlation-driven feature refinement method is introduced to weight and select the most representative meteorological and power sequence features within each cluster, optimizing the feature set for improved prediction accuracy. Next, a TCN-ELM hybrid model is constructed, combining the advantages of temporal convolutional networks (TCNs) in capturing sequential features and an extreme learning machine (ELM) in efficient nonlinear modelling. This hybrid approach enhances forecasting performance through their synergistic capabilities. Traditional ultra-short-term forecasting often focuses solely on historical power as input, especially with a 15 min resolution, but this study emphasizes reducing the time scale of meteorological forecasts and power samples to within one hour, aiming to improve the reliability of the forecasting model in handling sudden meteorological changes within the ultra-short-term time horizon. To validate the proposed framework, comparisons are made with several benchmark models, including traditional TCN, ELM, and long short-term memory (LSTM) networks. Experimental results demonstrate that the proposed framework achieves higher prediction accuracy and better robustness across various operational modes, particularly under high-variability scenarios, out-performing conventional models like TCN and ELM. The method provides a reliable technical solution for ultra-short-term wind power forecasting, grid scheduling, and power system stability. Full article

This study explores the issue of fixed-time dynamic event-triggered consensus control for uncertain nonlinear multi-agent systems (MASs) within directed graph frameworks. In practical applications, the system encounters multiple constraints such as unknown time-varying parameters, unknown external disturbances, and input dead zones, which may increase the communication burden of the system. Therefore, achieving fixed-time consensus tracking control under the aforementioned conditions is challenging. To address these issues, an adaptive fixed-time consensus tracking control method based on boundary estimation and fuzzy logic systems (FLSs) is proposed to achieve online compensation for the input dead zone. Additionally, to optimize the utilization of communication resources, a periodic adaptive event-triggered control (PAETC) is designed. The mechanism dynamically adjusts the frequency at which the trigger is updated in real time, reducing communication resource usage by responding to changes in the control signal. Finally, the efficacy of the proposed approach is confirmed via theoretical evaluation and simulation. Full article

This study compared the effectiveness of the Sequencing Batch Biofilter Granular Reactor (SBBGR) plant with and without the integration of ozone (BIO-CHEM process) in the remediation of medium-aged landfill leachate. Special attention is given to the removal of per- and polyfluoroalkyl substances (PFAS) as a group of bioaccumulative and persistent pollutants. The findings highlight the high SBBGR performance under biological process only for key wastewater contaminants, with 82% for chemical oxygen demand (COD), 86% for total nitrogen, and 98% for ammonia. Moderate removal was observed for total (TSS) and volatile (VSS) suspended solids (41% and 44%, respectively), while phosphorus and colour removal remained limited. Remarkably, the SBBGR process achieved complete removal of long-chain PFAS, while its performance declined for shorter-chain PFAS. BIO-CHEM process significantly improved COD (87.7%), TSS (84.6%), VSS (86.7%), and colour (92–96%) removal. Conversely, ozonation led to an unexpected increase in the concentrations of several PFAS in the effluent, suggesting ozone-induced desorption from the biomass. SBBGR treatment was characterised by a low specific sludge production (SSP) value, i.e., 5–6 times less than that of conventional biological processes. SSP was further reduced during the application of the BIO-CHEM process. A key finding of this study is a critical challenge for PFAS removal in this combined treatment approach, different from other ozone-based methods. Full article

Conducting scientific research in craniomaxillofacial surgery presents distinct challenges, particularly in the Asia Pacific region. This study aimed to assess research interests, barriers, and support needs among surgeons in the region through an anonymous online survey conducted via Google Forms from 12 to 31 May 2025, with 169 responses collected. The survey included 13 structured questions and an open-ended comment section. Findings were compared with a similar survey done in Latin America in 2024, to identify regional differences. The results revealed a significant gap in research participation, with 18.3% of Asia Pacific respondents having no publications, unlike Latin America, where all had at least one. Familiarity and participation in the Arbeitsgemeinschaft für Osteosynthesefragen Program for Education and Excellence in Research (AO PEER) were lower in Asia Pacific (29% and 6.5%), and greater challenges were reported in establishing topics, research methodology, and data collection. Although interest was high, only 42% conducted research frequently, and 90.5% indicated a need for mentorship. Despite higher awareness of AO grant opportunities (58%), barriers, like inadequate support for scientific research, lack of training, and limited time, persist. These findings highlight the need for AO Craniomaxillofacial surgery (AOCMF) to implement targeted strategies, such as research training, mentorship, promotion of funding opportunities, and support for multi-center collaborations, to enhance research participation across the region. Full article

With the rapid development of artificial intelligence, multi-party collaboration based on data sharing has become an inevitable trend. However, in practical applications, shared data often originate from multiple providers. Therefore, achieving secure and efficient data sharing while protecting the rights and interests of each data provider is a key challenge currently faced. Existing access control methods have the following shortcomings in multi-owner data scenarios. Most methods rely on centralized management, which makes it difficult to solve conflicts caused by inconsistent permission policies among multiple owners. There are problems such as poor consistency of permission management, low security, and lack of protection for the autonomous will of each owner. To this end, our paper proposes a fine-grained decentralized autonomous access control scheme based on blockchain, which includes three core stages: formulation, deployment, and execution of access control policies. In the access control policy formulation stage, the scheme constructs a multi-owner data policy matrix and introduces a benefit function based on a Stackelberg game to balance conflicting attributes to form a unified access policy. Secondly, in the access control policy deployment stage based on smart contracts, all data owners vote on the access control policy by calculating their own benefits to achieve a consensus on joint decision-making on the policy. Finally, in the policy execution and joint authorization phase, a decentralized authorization method based on threshold passwords is used to distribute access keys to each owner, ensuring that data is only granted after receiving authorization from a sufficient number of owners, thereby ensuring the ultimate control of each owner and the fine-grained access control. Finally, we verified the feasibility of the solution through case analysis and experiments. Full article

Pulmonary coinfection involving both viral and opportunistic pathogens is an emerging challenge in immunosuppressed patients. We report the case of a 59-year-old man with rheumatoid arthritis on long-term immunosuppressive therapy who developed necrotizing pneumonia and acute respiratory failure and was ultimately diagnosed with triple pulmonary coinfection by SARS-CoV-2, Nocardia cyriacigeorgica, and Aspergillus fumigatus. Diagnosis required comprehensive imaging, bronchoscopy with BAL, and microbiological work-up. The case was complicated by septic shock, multiple organ failure, and family-driven end-of-life decisions. This report highlights the diagnostic and therapeutic complexity of triple coinfection in the ICU, emphasizing the importance of systematic microbiology, imaging, and interdisciplinary care in critically ill immunocompromised hosts. Full article

Durian is a major tropical crop in Southeast Asia, but its yield and quality are severely impacted by a range of pests and diseases. Manual inspection remains the dominant detection method but suffers from high labor intensity, low accuracy, and difficulty in scaling. To address these challenges, this paper proposes EN-YOLO, a novel enhanced YOLO-based deep learning model that integrates the EfficientNet backbone and multimodal attention mechanisms for precise detection of durian pests and diseases. The model removes redundant feature layers and introduces a large-span residual edge to preserve key spatial information. Furthermore, a multimodal input strategy—incorporating RGB, near-infrared and thermal imaging—is used to enhance robustness under variable lighting and occlusion. Experimental results on real orchard datasets demonstrate that EN-YOLO outperforms YOLOv8 (You Only Look Once version 8), YOLOv5-EB (You Only Look Once version 5—Efficient Backbone), and Fieldsentinel-YOLO in detection accuracy, generalization, and small-object recognition. It achieves a 95.3% counting accuracy and shows superior performance in ablation and cross-scene tests. The proposed system also supports real-time drone deployment and integrates an expert knowledge base for intelligent decision support. This work provides an efficient, interpretable, and scalable solution for automated pest and disease management in smart agriculture. Full article

Background: The emergence and spread of the tigecycline resistance gene tet(A)-v1 in carbapenem-resistant Klebsiella pneumoniae (CRKP) poses significant public health challenges. However, the prevalence of tet(A)-v1-positive CRKP, especially in pediatric patients, remains poorly understood. This study aims to address the gap by performing an in-depth analysis of isolates collected from a children’s hospital in China. Methods: A 4-year retrospective study was conducted in the children’s hospital in Suzhou, China. Non-duplicated specimens were obtained from pediatric patients, and antimicrobial susceptibility profiles were assessed. Whole-genome sequencing and bioinformatics analyses were conducted to characterize the genetic background, antimicrobial resistance determinants, hypervirulence-associated genes, diversity of tet(A)-v1-carrying plasmids, the genetic environment of tet(A)-v1, and the potential for clonal transmission. Conjugative transferability of tet(A)-v1-carrying plasmids was also evaluated via conjugation assays. Results: Of the 73 tet(A)-v1-positive CRKP isolates from pediatric patients, 10.96% were non-susceptible to tigecycline. These isolates exhibited high genetic diversity, spanning across 13 STs (sequence types), with ST17 being predominant. Three carbapenemases were identified, with IMP being the most common. Isolates from diverse backgrounds, such as ST17, ST20, ST323, ST792, and ST3157, demonstrated evidence of clonal transmission. The tet(A)-v1 gene was located on 14 distinct plasmids across seven replicon types, with IncFIA/IncHI1 and IncFII being most commonly detected. All tet(A)-v1-carrying plasmids were multidrug-resistant, and 68.49% were conjugatively transferable, indicating a high potential for horizontal transfer. Four genetic contexts bordering tet(A)-v1 were identified, which points to active clonal dissemination. Conclusions: Although limited to a single hospital, this study represents one of the first in-depth investigations of tet(A)-v1-positive CRKP in pediatric patients, providing valuable insights into the prevalence and spread of tet(A)-v1 in this vulnerable group. These findings emphasize the urgent need for enhanced surveillance and infection control measures to curb the spread of tet(A)-v1-positive CRKP in pediatric healthcare environments, offering critical insights to mitigate its public health impact. Full article

Background/Objectives. Multi-drug-resistant (MDR) microorganisms pose a significant challenge in healthcare settings, particularly with beta-lactam-resistant Gram-negative bacteria and glycopeptide-resistant enterococci. Culture represents the most reliable technique in determining their presence within surveillance swabs. However, it requires a long time-to-result (TTR) and shows low sensitivity. Molecular techniques integrate diagnostic procedures, allowing TTR reduction and precise identification of genes. Methods. During our usual surveillance campaign, we had the opportunity to evaluate the Allplex Entero-DR assay (Seegene Inc., Seoul, Republic of Korea) and the Entero-DR Plus assay (Arrow Diagnostics srl, Genova, Italy) molecular kits for the detection of extended-β-lactamases (ESBL), carbapenem- and vancomycin-resistant genes, as well as Acinetobacter spp. and Pseudomonas aeruginosa spp. identification directly from rectal swabs. A comparison between these tests and the culture-based routine completed the study. Results. The analysis included 300 rectal swabs from the University Hospital Policlinico (Catania, Italy). One hundred and eighty-eight samples (62.6%) resulted as positive for at least one Allplex™ target, reaching optimal sensitivity and negative predictive value (100%). Our results underlined the ubiquitous blaCTX-M and van genes presence and demonstrated the diffusion of double-carbapenemases genes and metallo-β-lactamases-producing strains. In our epidemiological setting, few data were collected about carbapenem-resistant P. aeruginosa and Acinetobacter spp., which require further evaluations on simultaneous respiratory colonization and higher sample numbers. Conclusions. Our analysis highlighted the importance of combining conventional and advanced diagnostic methods in investigating MDR pathogens. The right approach should be based on the prevalence and variability of resistance mechanisms within a specific epidemiological area. Remarkably, molecular screenings may exclude negative samples within high-risk areas due to a significant negative predictive value. Full article

The advancement of laser-induced graphene (LIG) has significantly enhanced the development of wearable and flexible electronic devices. Due to its exceptional physical, chemical, and electronic properties, LIG has emerged as a highly effective active material for wearable sensors. However, despite the wide range of materials suitable as precursors for LIG, the scarcity of stretchable and biocompatible polymers amenable to laser graphenization has remained a persistent challenge. In this study, laser-induced graphene (LIG) was fabricated directly on biocompatible and flexible cross-linked PDMS/PEG (with M_n (PEG) = 400 g/mol) composites for the first time, enabling their application in wearable sensors. The addition of PEG compensates for the low carbon content in PDMS, enabling efficient laser graphenization. Laser parameters were systematically optimized to achieve high-quality graphene, and a comprehensive characterization with varying PEG content (10–40 wt.%) was conducted using multiple analytical techniques. Tensile tests revealed that incorporating PEG significantly enhanced elongation at break, reaching 237% for PDMS/40 wt.% PEG while reducing Young’s modulus to 0.25 MPa, highlighting the excellent flexibility of the substrate material. Surface analysis using X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), and Raman spectroscopy demonstrated the formation of high-quality few-layer graphene with the fewest defects in PDMS/40 wt.% PEG composites. Nevertheless, the adhesion of electrical contacts to LIG that was directly induced on PDMS/PEG proved to be challenging. To overcome this challenge, we produced devices by means of laser induction on polyimide and transfer to PDMS/PEG. We demonstrate the practical utility of such devices by applying them to monitor limb motion in real time. The sensor showed a stable and repeatable piezoresistive response under multiple bending cycles. These results provide valuable insights into the fabrication of biocompatible LIG-based flexible sensors, paving the way for their broader implementation in medical and sports technologies. Full article

Introduction: Tuberculosis (TB) predominantly affects older adults in Japan, and prolonged hospitalization remains a challenge. This study evaluated both clinical and social factors influencing hospitalization duration. Methods: We retrospectively analyzed 203 patients with smear-positive pulmonary TB admitted to NHO Wakayama Hospital (2017–2022). Stepwise multiple regression was used to identify factors associated with hospitalization duration. Results: Key factors included time to smear negativity, duration from isolation release to discharge, independence in daily life, and discharge destination. Prolonged stays were often due to social issues, such as difficulties in arranging transfers to long-term care homes or family acceptance. Conclusions: While Japan is developing new discharge criteria based on clinical indicators, our findings highlight the significant impact of non-clinical, social factors on hospitalization duration. Addressing these factors is essential for effective discharge planning. Full article