Search Results (15,559)

Lekethromycin (LKMS) is a novel macrolide veterinary antimicrobial. Its propensity for intracellular accumulation causes discrepancies between whole blood and plasma concentrations, complicating pharmacokinetic evaluations. This study compared the pharmacokinetic characteristics, dose proportionality, and bioavailability of LKMS in whole blood and plasma following intramuscular administration in pigs. Forty-two healthy pigs received LKMS via a single intravenous reference dose (5 mg/kg) for absolute bioavailability estimation or intramuscular (1, 2.5, 5, and 10 mg/kg) injection. Pharmacokinetic parameters were calculated using non-compartmental analysis, and dose proportionality was evaluated via a power model. LKMS exhibited rapid absorption and slow elimination, with a plasma half-life of 49.25 to 67.63 h. Whole blood exposure and peak concentrations were 1.5 to 3 times higher than in plasma, indicating extensive blood cell partitioning. As the intramuscular dose increased, the whole blood-to-plasma concentration ratio decreased from 2.83 to 1.15, suggesting a saturable cell uptake mechanism. Consequently, LKMS exhibited non-linear pharmacokinetics in whole blood but demonstrated linear, dose-proportional pharmacokinetics in plasma. Absolute bioavailability based on plasma ranged from 83.2% to 119.5%. Due to saturable blood cell binding, plasma is the optimal matrix for accurately evaluating LKMS systemic exposure and bioavailability in swine. Full article

Developing reliable Arabic question answering (QA) systems for Islamic fatwas requires datasets that capture the linguistic complexity and multi-step reasoning inherent in jurisprudential inquiries. However, the existing Arabic religious QA datasets primarily focus on direct retrieval or classification, often failing to address the multi-hop reasoning necessary for complex fatwa questions. To bridge this gap, we introduce MAFQA, a benchmark dataset specifically designed for multi-hop Arabic fatwa question answering. MAFQA was constructed from an extensive corpus of authentic fatwa records sourced from authoritative Islamic institutions. The dataset was developed via a semi-automated pipeline that integrates expert-guided identification of complex inquiries with a structured decomposition framework. This framework employs automated reasoning-pattern classification, semantic feature extraction, and template-guided annotation of subquestions and subanswers, followed by rigorous validation to ensure contextual grounding, logical coherence, and structural consistency. To evaluate the utility of the dataset, we conduct an extensive benchmarking study using Arabic-specialized, multilingual, and instruction-tuned language models across two primary tasks: question decomposition (QD) and generative question answering (QA). Performance is assessed using a comprehensive suite of lexical, semantic, relevance, and faithfulness metrics. Experimental results demonstrate that Arabic-specialized models consistently outperform their multilingual counterparts, with AraT5-base and AraBART achieving the highest performance in terms of lexical similarity, semantic alignment, and answer faithfulness. Full article

An electrical heating fluidized-bed thermal energy storage (EH-FB-TES) system is proposed for integration with a coal-fired power plant (CFPP) for deep peak shaving (DPS) due to its high energy storage density and extensive heat exchange performance. The primary objective of this study is to evaluate the thermodynamic performance and economic feasibility of the integrated EH-FB-TES system, specifically focusing on identifying the optimal coupling and heat recovery strategies for enhanced deep peak shaving performance. Since EH-FB-TES uses air flow for fluidization in the heating storage process, its coupling with the CFPP differs from other TES technologies, and the associated thermodynamic performance and cost are thereby analyzed. The results show that, in EH-FB-TES, the heat release efficiency is predominantly constrained by thermal losses. To increase the energy utilization efficiency, a two-stage heat recovery strategy is proposed to release the stored energy in the integration. The first stage is to heat up the feedwater extracted from the deaerator and the second one is to heat up the condensate water. The analyses also show that the selection of reinjection positions for the heated medium from EH-FB-TES greatly influences the system performance. Returning the stored thermal energy to heat up feedwater can effectively increase the output of the unit, while directly generating steam can be beneficial for coal saving. The integrated system achieves a maximum equivalent round-trip efficiency of 32.9% under 20 MW/800 °C conditions. An economic analysis reveals that, compared with other energy storage methods, EH-FB-TES can realize a relatively high energy storage density with a rather low cost. Under the present DPS compensation policy, for a 315 MW subcritical CFPP integrated with a 50 MW EH-FB-TES system, when heat storage is 8 h, heat release is 4 h per day, and the plant operates 100 days per year, the estimated static and dynamic payback periods are 3.06 years and 3.67 years, respectively. The integration of CFPP with EH-FB-TES could be promising for meeting DSP requirements. Full article

Real-time quaking-induced conversion (RT-QuIC) is highly sensitive for prion detection; however, inhibitory factors present in tissue homogenates readily interfere with the assay. We previously reported that recombinant cervid prion protein (rCerPrP) enabled the establishment of practical RT-QuIC for detecting chronic wasting disease and atypical bovine spongiform encephalopathy (BSE) prions, i.e., detecting low levels of prions in high concentration of brain tissue homogenates. Accordingly, the present study aimed to establish RT-QuIC for detecting classical BSE (C-BSE) and classical and atypical scrapie (C- and A-scrapie, respectively). A single-step lipid extraction using a 3:1 mixture of 2-butanol and methanol was effective as a pretreatment to remove inhibitors from brain homogenates. Among three rPrPs extensively evaluated, recombinant sheep PrP (rShPrP) was the most suitable substrate for practical detection of C-BSE prions. rCerPrP-173S/177N and rCerPrP-98S/173S/177N, which carry sheep-type amino acid substations at codons 173 and 177 and at codons 98, 173, and 177, showed excellent performance for detecting C-scrapie prions. Moreover, rCerPrP-98S/173S/177N, but not rCerPrP-173S/177N, was identified as an optimal substrate for detecting A-scrapie prions. These results suggested that combining inhibitor-removal pretreatment with the optimization of rPrP substrate for each animal prions further enhanced of RT-QuIC performance. Full article

Background/Objectives: Multidrug-resistant (MDR) Acinetobacter baumannii (Ab) has emerged as a significant bacterial pathogen responsible for nosocomial infections. The most common clinical manifestations of Ab infection include ventilator-associated pneumonia and catheter-related bloodstream/urinary infections. Given the extensive MDR phenotype of Ab, preventive vaccination strategies are crucial for protecting susceptible populations. Methods: We utilized immunoinformatics to identify candidate peptides containing both putative B- and T-cell epitopes from proteins associated with Ab pathogenesis. Subsequently, we designed novel Acinetobacter Multi-Epitope Vaccines (AMEVs), each comprising an Ab thioredoxin A (TrxA) leader protein, five to seven of the identified peptide antigens, and a C-terminal His(6x)-tag to facilitate protein purification. Results: Subcutaneous vaccination of C57BL/6 mice with AMEV1 or AMEV2, formulated with TiterMax adjuvant, conferred 60% and 80% protection, respectively, against intraperitoneal Ab challenge. AMEV vaccination induced a robust antibody response to each corresponding whole protein and most of its component peptides. We then constructed an improved vaccine, AMEV5, which included the Ab TrxA protein and seven confirmed B-cell epitope peptides. Subcutaneous immunization of BALB/c mice (n = 10 per group) with rAMEV5 emulsified in Adda03 adjuvant activated antigen-specific IL-5-secreting T cells and antibody-producing B cells. Evaluation of vaccine efficacy demonstrated that AMEV2- and AMEV5-immunized mice were protected from a lethal intraperitoneal Ab challenge, with survival rates of 70% and 90%, respectively. Conclusions: These study results provide insights into the application of reverse vaccinology to combat the rise of MDR Acinetobacter infection. Full article

Public bus systems are vital to achieving sustainable urban mobility in developing countries; yet, the quality of bus stops, a critical interface between users and transit services, remains widely overlooked. This study evaluates bus stop quality in Sulaymaniyah, Iraq, from bus users’ perspectives by integrating importance–performance analysis (IPA) and the customer satisfaction index (CSI) with level of conformity analysis (CR) using extensive, real-world survey data. The objective was to identify priority areas to help improve the quality of public bus stop provision in the city and ensure the most efficient allocation of resources by focusing on the quality attributes that matter most to bus users. The results highlight six critical service quality attributes that require immediate improvement due to their high importance to users and low service quality performance: (i) safety barriers to prevent traffic accidents while waiting at bus stops; (ii) accessibility of bus stops for elderly and disabled users; (iii) availability of signage and timetables/maps; (iv) overall bus stop quality; (v) narrow bus stop platforms; and (vi) waiting time at bus stops. Addressing these gaps is essential to enhance user satisfaction and ensure that users have a safer, more inclusive, and reliable PT experience. This study offers evidence-based recommendations to enhance bus stop design and service quality, thus contributing to improved user satisfaction and increased ridership. More broadly, the results can be applied to other rapidly urbanizing developing cities seeking to provide equitable, safe, and user-centered bus transit systems. Full article

Current security solutions predominantly rely on cloud-based implementations, often neglecting computational resource constraints and operational efficiency. While contemporary methodologies typically require additional training, the few that operate without retraining frequently yield suboptimal performance. To address these limitations, this work leverages a pre-trained MTCNN architecture to detect faces of copyright-protected individuals. We construct a facial landmark database comprising five critical fiducial points, which serves as a supplementary module integrated into the stable diffusion framework, enabling real-time security filtering for synthesized video content. The proposed system utilizes MTCNN models pre-trained in the cloud to build a repository of copyrighted facial signatures, generating a geometric parameter database of facial landmarks. This database, coupled with a parallel verification unit, functions as a plugin within the standard Stable Diffusion pipeline. By leveraging Stable Diffusion’s native decoder, we decode stochastic frames from the U-Net latent representations and perform real-time comparative analysis to identify potential copyright violations in generated video sequences. Upon detecting an infringement, an on-screen display (OSD) alert notifies the user and immediately halts the text-to-video (T2V) generation process. Experimental evaluations demonstrate that our framework effectively mitigates the resource constraints and latency issues inherent in edge deployment scenarios of prior security implementations. Leveraging MTCNN’s proven robustness and extensive edge compatibility for facial recognition, the proposed detection and obfuscation plugin integrates seamlessly with Stable Diffusion while preserving generation quality. Full article

Wireless sensor networks (WSNs) are highly susceptible to Denial-of-Service (DoS) attacks due to their resource-constrained and distributed nature. In this study, we propose a novel trust-based malicious node detection mechanism that leverages a Depth-First Search (DFS) strategy to trace and identify attack sources within clustered WSN architectures efficiently. The proposed approach dynamically evaluates trust scores between nodes to detect anomalous behaviors and employs a honeypot-based redirection system to isolate compromised nodes from the main communication flow. This combination enhances detection accuracy while minimizing false positives and energy overhead. The method is implemented and evaluated using a custom simulation environment. Comparative experimental results against state-of-the-art techniques such as the Evolved Trust Updating Mechanism (EVO) and Multi-agent Trust-based Intrusion Detection System (MULTI) demonstrate that our Trust-Based Honeypot (TBHP) achieves superior performance in terms of detection rate, false-alarm rate, and network lifetime extension. Full article

Capturing kinematic data in outdoor sports is challenging, as motions span large capture volumes and occur under difficult environmental conditions. Video-based approaches, particularly with pan–tilt–zoom cameras, offer a practical solution, but the extensive manual post-processing required limits their use to short sequences and few athletes. This study presents a motion capture pipeline that automates the detection of both reference points and sport-specific keypoints to overcome this limitation. The field test employed eight cameras covering a $250\times 80\times 30 \mathrm{m}$ capture volume with nearly 300 reference points. Ten state-certified ski instructors performed eight standardized maneuvers. Reference points were localized through a hybrid approach combining YOLO object detection and ArUco marker identification. AlphaPose was fine-tuned on a new manually annotated dataset to detect skier-specific keypoints (e.g., skis, poles) alongside anatomical landmarks. Continuous frame-wise calibration and 3D reconstruction were performed using Direct Linear Transformation. Evaluation compared automated detections with manual annotations. Automated reference point detection achieved a mean localization error of $4.1$ pixels ($0.1\%$ of 4K width) and reduced 3D segment-length variation by $23\%$. The skier-specific keypoint model reached $98\%$ PCK, mAP of $0.97$, and an MPJPE of $10.3$ pixels while lowering 3D segment-length variation by $0.5 \mathrm{cm}$ compared to manual digitization and $0.6 \mathrm{cm}$ relative to a pretrained model. Replacing manual digitization with automated detection improves accuracy and facilitates kinematic data collection in large outdoor fields with many athletes and trials. The approach also enables the creation of sport-specific datasets valuable for biomechanical research and training next-generation 3D pose estimation models. Full article

Degenerative mitral stenosis (MS) secondary to extensive mitral annular calcification (MAC) represents a growing clinical challenge in an aging population. These patients are often elderly, frail, and harbor a significant burden of comorbidities, rendering conventional mitral valve surgery prohibitively high-risk. While transcatheter mitral valve replacement (TMVR) has emerged as a potential alternative, the current evidence is only derived from single-arm observational registries. Therefore, the transition toward randomized controlled trials to define optimal patient selection and long-term prosthetic durability is necessary. This review examines the current landscape of TMVR for degenerative MS, focusing on the role of multimodal pre-procedural planning, procedural technique, and prevention of the principal complications. The integration of echocardiography and multi-slice computed tomography (MSCT) is essential for evaluating anatomical feasibility, particularly in predicting neo left ventricle outflow tract (neo-LVOT) obstruction, the primary determinant of procedural mortality. However, it is limited due to the absence of standardized protocol. We are showing the outcomes of off-label balloon-expandable aortic prostheses and dedicated TMVR system, which are the only two devices which data in patients with MS are available. Despite high technical success rates in specialized centers, complications, including paravalvular leak, valve thrombosis, and device migration, remain more prevalent than in aortic interventions. We present some tips and tricks to prevent and manage adverse events. TMVR represents a transformative frontier for inoperable patients with severe MAC. However, its routine clinical adoption requires further refinement of dedicated technologies and standardized imaging protocols to improve safety and bridge the gap between palliative medical therapy and definitive intervention. Full article

Combined central and peripheral demyelination (CCPD) is a rare neuroimmunological condition involving inflammatory demyelination of both the central nervous system (CNS) and peripheral nervous system (PNS). We report a chronic progressive CCPD case initially diagnosed as chronic inflammatory demyelinating polyneuropathy (CIDP) and treated with conventional CIDP-directed immunotherapies, with subsequent development of multiple sclerosis (MS)-like CNS demyelination. An extensive diagnostic evaluation excluded alternative infectious, metabolic, paraneoplastic, and antibody-mediated etiologies affecting either compartment. In the absence of a unifying pathogenic autoantibody, the combined clinical, radiological, cerebrospinal fluid, and electrophysiological findings support a shared immune-mediated process. Within this framework, B cells are implicated through antibody-independent mechanisms, including antigen presentation, pro-inflammatory cytokine production (e.g., IL-6), and amplification of Th1/Th17-driven inflammation. Interactions between B cells and the complement system via CR1 (CD35) and CR2 (CD21), together with dysfunction of the blood–brain barrier (BBB) and blood–nerve barrier (BNB), may facilitate parallel immune activation across both compartments. In this case, the observed radiological and electrophysiological stabilization under anti-CD20 therapy is consistent with a B-cell-driven pathogenic model in CCPD. Full article

Silicone rubber is extensively used in engineering applications due to its toughness and impact resistance; however, traditional characterisation methods fail to capture its nonlinear deformation characterisation and triaxial mechanical behaviour. To address this, we derived a constitutive model within the framework of continuum mechanics that assumes a condition of near incompressibility and conducted uniaxial, planar, and equibiaxial tension tests to fit the model parameters. Through systematic analysis of triaxial mechanical responses under these three loading modes, we determined the material’s nonlinear large-deformation behaviour and sensitivity to the biaxiality ratio. Comparative analyses with classical hyperelastic models show that the proposed model achieves a good balance between the number of parameters and fitting accuracy. After the parameter-fitting process, we performed finite element simulations of the three loading modes. The simulation results show good agreement with experimental data in terms of deformation patterns and stress–strain curves. This study provides a novel theoretical tool for evaluating the mechanical properties and structural designs of soft materials. Full article

Against the backdrop of ongoing climate change, the Qinghai–Tibet Plateau, a region highly sensitive to climatic variation, exhibits intricate spatiotemporal patterns in reference crop evapotranspiration (ET_O), with significant implications for regional water-resource planning. This study selected four agro-climatic zones across the plateau region (TSA, TSH, TAZ, and WCH). Long-term daily observations from 28 meteorological stations were used to estimate ET_O via the FAO 56 Penman–Monteith equation. This extensive dataset enabled robust trend analysis using the Mann–Kendall test, alongside a cloud-model framework, and analyses of sensitivity and contributions to evaluate ET_O’s spatiotemporal evolution, its distributional uncertainty, and the underlying drivers. Results reveal pronounced regional heterogeneity in the interannual variability of ET_O. Annual ET_O declined in TSH and TSA (trend rates of −1.12 and −6.58 mm·10a⁻¹, respectively) and increased in TAZ and WCH (15.76 and 10.74 mm·10a⁻¹, respectively). At monthly and seasonal timescales, ET_O exhibited an unimodal pattern, with the greatest stability in winter and spring and lower stability in summer and autumn. The cloud-model parameter He indicates that ET_O stability is greatest in TSH and weakest in WCH, with He values of 7.15 and 12.29 mm, respectively. Contribution-rate analyses identify T_max and T_mean as the principal determinants of rising ET_O across all study zones, reflecting the largest individual contributions. Temperature-related factors together account for the majority of ET_O variability across the regions, with their absolute contributions ranging from 5.61% to 8.63%, well above those of aerodynamic factors (0.62–1.78%). Stability assessments indicate that ET_O is generally more unstable than its meteorological drivers, with substantial regional disparities, implying that ET_O evolution cannot be explained by a single controlling factor. Overall, the study characterizes the uncertainty in ET_O variations under complex terrain, highlights the value of the cloud model for refined hydrological assessments, and provides a scientific basis for adaptive agricultural water-resource management in the region. Full article

The characterization of ductile fracture in thin metallic sheets is challenging due to extensive plastic deformation and stable crack growth under plane-stress conditions. This study investigates the applicability of the load separation criterion as a single-specimen method for evaluating fracture behavior in thin aluminum sheets. Experimental tests were performed on double-edge-notched tension (DENT) specimens manufactured from a 1.2 mm thick commercial aluminum sheet with ligament lengths ranging from 4 to 20 mm. Load–displacement responses were analyzed using curve-fitting techniques to determine the separation parameter, geometry function, plastic η-factor, and the plastic component of the J-integral. The separation parameter stabilized in the plastic regime, and the geometry function followed a power-law relationship with the normalized ligament ratio, confirming the validity of the load separation assumption. The calculated fracture toughness values showed consistent averages of approximately 58–60 kJ/m² across different fitting approaches, which are in good agreement with the essential work of fracture (EWF) value of about 51.5 kJ/m² reported for the same material. These results demonstrate that the load separation approach provides a reliable and efficient framework for determining fracture parameters in thin ductile aluminum sheets using a single specimen. The methodology offers practical advantages for fracture assessment and structural integrity analysis of lightweight sheet structures in aerospace, automotive, and marine applications. Full article

With the rapid advancement of autonomous driving technology and the commercialization of Human–Machine Interface (HMI) services, camera-based systems for external environment perception are being extensively deployed. While comprehensive camera systems enhance safety and convenience, they simultaneously raise serious privacy concerns by collecting facial and biometric information of Vulnerable Road Users (VRUs) and passengers. Although facial anonymization technology has emerged as a key solution, the field currently faces a fundamental challenge: the absence of unified performance evaluation criteria. Existing studies employ disparate evaluation metrics, making objective inter-model comparison and performance verification difficult. This study proposes quantitative evaluation metrics and corresponding evaluation criteria that enable systematic and objective assessment of facial anonymization model performance. Through large-scale experiments, we developed quantitative evaluation metrics encompassing facial landmark variations, visual similarity, and re-identification prevention capability, and derived specific threshold values based on statistical methodologies. Furthermore, to validate the proposed evaluation criteria, we conducted systematic empirical assessments using models that adopt different technical approaches. The validation experiments showed that the evaluation criteria proposed in this study can be applied across models with distinct technical characteristics. This research is expected to contribute to resolving the heterogeneous evaluation criteria issues in existing studies by providing unified evaluation criteria. It may also support the development of privacy protection technologies in autonomous driving environments. Full article