Search Results (28,398)

Cat welfare assessment in Animal-assisted aervices (AAS) is necessary to ensure engagement in AAS does not impair welfare. An initial systematic search conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines revealed a complete lack of studies specifically addressing this topic. Consequently, a second-step search was performed, widened to the existing tools for monitoring cat welfare in general. Three scoping reviews using PRISMA guidelines were performed, focusing on the three principal fields of welfare assessment: health, behaviour, and physiology/endocrinology. Studies published on Scopus in 2011–2026, written in English and assessing feline (Felis catus) welfare were selected. A total of 2728 records were identified, of which 43 met the inclusion criteria (including 7 reviews and 1 scientific report); the methods used to assess cat welfare were summarized and discussed for their potential application in AAS. Although multiple tools are available, most are context- or disease-specific and some are not validated. Approximately half of the studies employed more than one indicator or method, with behavioural parameters being the most frequently used through questionnaires or scores. This work provides a practical framework to support veterinarians, handlers, and researchers in the selection of appropriate tools for cat welfare monitoring in AAS. Full article

Excitation using nonlinear gradient magnetic fields is investigated as a means of sub-volume magnetic resonance imaging (MRI). Conventional gradient fields provide encoding along a single direction, whereas nonlinear gradient fields encode information simultaneously along at least two directions. This leads to excitation regions (FOX) that have curvilinear boundaries, which may be more tolerant to aliasing artifacts when the encoded field of view (FOV) is smaller than the FOX. This reduces the complexity of the required radiofrequency (RF) excitation pulses and enables accelerated reduced-FOV imaging with standard slice-selection RF-pulses. We demonstrate the approach using a Z2-harmonic field for cylindrical regions of interest (ROIs) with various radius/height ratios. The minimum-FOV that should be encoded is formulated in terms of ROI and RF pulse parameters to allow a theoretical evaluation of feasibility during study design. The investigated method is compared to one-dimensional and two-dimensional selective RF pulses in terms of echo time, scan time and specific absorption rate (SAR) using simulations and phantom experiments. The investigated method yields lower scan time while keeping the SAR unaltered compared to a conventional slice-selective RF pulse, and is more efficient in terms of SAR, echo time and scan time compared to two-dimensional selective excitation. Full article

Hydraulic fracturing is the core technology for stimulation and reform of low-permeability and unconventional oil and gas reservoirs. Reservoir fracability directly determines fracture morphology, complexity, and stimulated reservoir volume. To address the shortcomings of existing fracability evaluation models, such as poor applicability, subjective weighting and insufficient accuracy, five key indicators are selected, including brittleness index, brittle mineral index, stress difference coefficient, minimum horizontal principal stress and porosity. First, the three-dimensional discrete lattice method is used to clarify the influence of each parameter on fracture complexity. Then, the Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM) are combined to determine the indicator weights, a continuous fracability evaluation model is constructed, and a classification standard for fracturing applicability is established. The results show that the brittleness index has the greatest influence on fracture complexity with a weight of 0.3559, followed by brittle mineral index (0.2986), minimum principal stress (0.1994), stress difference coefficient (0.0993) and porosity (0.0467). The reservoir fracability indices of 0.37 and 0.59 are the mutation points of fracture complexity. Based on microseismic evaluation of stimulated reservoir volume (SRV) using an envelope surface method, it is found that reservoirs with low fracability are more suitable for fracturing designs characterized by large cluster spacing, fewer clusters, and smaller stage spacing. In contrast, reservoirs with medium and high fracability can develop more complex fracture networks by reducing cluster spacing, increasing the number of clusters, and adopting higher pumping rates. The research results can provide theoretical basis and technical support for hydraulic fracturing operation design. Full article

Botrytis cinerea is a major phytopathogenic fungus responsible for substantial economic losses in horticultural crops, underscoring the need for sustainable alternatives to synthetic fungicides. This study investigated the influence of physical, chemical and biological culture parameters on the antifungal activity of culture filtrates produced by Trichoderma harzianum BOL-12QD. Culture conditions were sequentially optimised by evaluating light-filter exposure, carbon and nitrogen source composition, potato ecotype selection, co-cultivation with Botrytis cinerea, and volatile-mediated interactions. Antifungal activity was assessed using mycelial growth inhibition assays against Botrytis cinerea. Among the individual factors, violet-filter illumination, a medium containing 5 g L⁻¹ glucose and 250 g L⁻¹ potato extract, the Leke Pek’e potato ecotype, ammonium nitrate as nitrogen source, and co-cultivation with Botrytis cinerea at 10⁴ conidia mL⁻¹ produced the highest inhibitory effects. Sequential integration of these optimised conditions resulted in enhanced antifungal activity, reaching up to 62% inhibition. Volatile organic compounds produced by Trichoderma harzianum BOL-12QD exhibited only minimal antifungal activity under the conditions tested, suggesting that volatile-mediated antagonism plays a limited role in this system. In contrast, culture-dependent modulation of extracellular metabolite profiles was evidenced by comparative ¹H NMR fingerprinting, which revealed condition-specific spectral differences, with the optimised treatment displaying a distinct metabolic signature relative to all other conditions. Cytotoxicity assays in murine peritoneal macrophages showed no significant reduction in cell viability at concentrations up to 200 μg mL⁻¹. In vivo exposure to the optimised culture filtrate (250 mg kg⁻¹ d⁻¹ for 10 days) induced transient treatment-related clinical observations without mortality, indicating a need for further detailed toxicological characterisation. Overall, these findings demonstrate that the antifungal activity of Trichoderma harzianum BOL-12QD is strongly modulated by interacting environmental, nutritional and biological culture parameters. The results support the potential of optimised culture filtrates as a source of bioactive metabolites for biocontrol applications, while highlighting the importance of integrated biochemical and toxicological evaluation. Full article

Background: This study aimed to compare the measurement agreement and intramethod reliability of four cephalometric analysis workflows: manual tracing, semi-automated digital analysis (Dolphin), fully automated AI-based analysis (WebCeph), and expert-adjusted AI analysis (WebCeph+). Methods: In this retrospective method-comparison study, 67 lateral cephalometric radiographs were initially included. After the exclusion of radiographs containing extreme values, 54 radiographs (35 females, 19 males; mean age: 15.0 ± 2.13 years) were analyzed. Twenty-one skeletal, dental, and soft-tissue parameters (13 angular, 8 linear) were evaluated across the four methods. Intramethod repeatability was assessed via the intraclass correlation coefficient (ICC). Intermethod comparisons were analyzed using ANOVA and post hoc pairwise tests. Pragmatic clinical relevance thresholds were predefined as ±2 degrees for angular measurements and ±2 mm for linear measurements. Results: All methods demonstrated high intramethod reliability, with ICC values exceeding 0.90 in 20 out of 21 parameters. Manual and Dolphin methods yielded statistically comparable results (p > 0.05). In contrast, WebCeph differed significantly from manual and/or Dolphin in seven parameters, including SNA, IMPA, Go-Gn length, Pog to N-perpendicular, Wits appraisal, nasolabial angle, and mentolabial angle (p < 0.05). Several discrepancies exceeded the predefined pragmatic thresholds (±2 degrees and ±2 mm), highlighting their potential clinical relevance. After expert adjustment (WebCeph+), statistically significant inter-workflow differences were no longer observed; however, residual individual-level variability remained for selected parameters. Conclusions: Fully automated WebCeph analysis showed limited agreement with manual and semi-automated methods for several clinically relevant measurements. Expert adjustment reduced systematic mean discrepancies and improved agreement with clinician-dependent workflows; however, residual individual-level variability remained for selected parameters. AI-driven cephalometric analysis should therefore be considered a supportive tool requiring specialist verification rather than an unsupervised replacement for conventional methods. Full article

The Annual Delivery Program (ADP) for Liquefied Natural Gas (LNG) represents a complex maritime inventory-routing problem that requires the precise synchronization of production and distribution. This study introduces a novel Mixed Integer Linear Programming (MILP) model designed to optimize vessel routing and scheduling over a one-year horizon under a direct-shipment assumption. The model minimizes total logistics costs, encompassing both fixed annual fleet costs and daily operating costs. The novelty of the model can be summarized in two aspects. First, it simultaneously optimizes several decisions: the assignment of frequency of deliveries to customers, the assignment of vessels to customers, cargo load sizes, and vessel routing and scheduling. The key distinction is that, unlike existing formulations that take the frequency of deliveries to customers as a fixed parameter, this frequency is itself a decision variable selected from a customer-specific discrete set; the selected frequency partitions the planning horizon into uniform windows and sets each delivery’s cargo load size to the exact demand accumulated over its window from daily demand data. Second, it incorporates several relaxations of selected variables and valid inequalities that enable us to solve the complex model for moderate size problems within a reasonable computational time using the exact optimization approach. Using this novel model, we carried out extensive numerical analysis based on cost and operational parameter scenarios and developed important insights for the characteristics of a solution to the problem. Full article

High sound pressure level (SPL) acoustic sensing requires miniaturized microphones that can operate under large acoustic loading while maintaining mechanical linearity, sufficient sensing response, and broadband audio frequency behavior. This work targets high-SPL operation and numerically investigates a graphene piezoresistive MEMS microphone based on a membrane-supported beam–island diaphragm. The proposed structure retains a continuous membrane for acoustic load bearing, while the upper beam–island topology redirects deformation-induced strain toward beam root regions where graphene piezoresistors are placed. This design is intended to increase the local strain available for piezoresistive readout without simply relying on larger global diaphragm deflection. Finite-element analysis was used to optimize the diaphragm geometry and evaluate strain enhancement, pressure response linearity, modal behavior, and harmonic response. Under the 170 dB SPL reference condition, the optimized structure increases the peak structural strain from 47.83 με in a thickness-equivalent solid diaphragm to 562.53 με, achieving an approximately 11.8-fold enhancement in local sensing strain while maintaining a highly linear pressure response (R2 > 0.9999). Additionally, the results also show that the sensor exhibits a high first natural frequency of 64.07 kHz and a small response variation of approximately 0.94 dB within the 0–20 kHz target frequency range, indicating excellent dynamic stability and high-fidelity signal transduction characteristics. To connect the structural response with piezoresistive readout, first-order electromechanical output estimation was further performed using representative graphene gauge factors, quarter-bridge readout assumptions, contact resistance correction, and Johnson-noise-limited signal-to-noise ratio estimation. A ±5% geometric tolerance check further indicates that the membrane side length is the most fabrication-sensitive parameter, while the selected design remains generally robust except for reduced linearity margin under positive membrane side-length deviation. These results demonstrate the potential of the proposed graphene-based MEMS microphone for high-SPL broadband acoustic sensing applications in harsh and high-intensity acoustic environments. Full article

Background: Mechanical reliability and size-dependent strength behavior remain critical concerns for CAD/CAM restorative materials. This study evaluated resin-based CAD/CAM materials, including resin composite blocks (RCBs) and nanoceramics. The influence of specimen size on flexural strength and the applicability of Weibull-based strength predictions were assessed by comparing experimental and Weibull-predicted values. Methods: Twelve CAD/CAM materials were investigated, including ten resin-based materials and two controls (lithium disilicate ceramic and polymethyl methacrylate). Rectangular specimens (1 × 4 × 14 mm and 1 × 12 × 14 mm) were tested using a three-point bending test. Flexural strength, modulus, and resilience were calculated. Reliability and size dependence were assessed using two-parameter Weibull statistics and effective-volume-based predictions. Data were analyzed using statistical tests selected according to data distribution characteristics (α = 0.05). Results: RCBs exhibited higher flexural strength, modulus, and resilience than nanoceramics (p < 0.05). Weibull analysis indicated higher reliability and limited size dependence for RCBs, whereas nanoceramics showed greater variability. The ceramic control exhibited the expected reduction in strength with increasing specimen size. In contrast, resin-based materials showed inconsistent responses to changes in specimen size. Prediction error analysis revealed variable agreement between predicted and experimental values, indicating that agreement with classical Weibull assumptions was material-dependent. Conclusions: Resin-based CAD/CAM materials demonstrated limited size-dependent behavior compared with brittle ceramics. The reduced agreement between experimental and Weibull-predicted values suggests that effective-volume scaling may have limited applicability for these contemporary materials and should be interpreted cautiously on a material-specific basis. Full article

Robust autonomous-driving detection requires using RGB texture and infrared thermal cues without sacrificing real-time inference. Existing RGB-IR detectors often rely on static feature concatenation or quadratic attention, which makes them sensitive to modality imbalance, small spatial offsets, and deployment cost. We propose MobileMamba-DETR, a lightweight DETR-style detector that treats dual-modal fusion as a selective state-space process. Its principal design is an SS2D-based cross-modal interaction module that uses normalized RGB-IR contrast as a guide, while a MobileMamba backbone, spectral–spatial encoder, and dynamic convolutional decoder provide efficient multi-scale representation and query localization. On M3FD and FLIR-ADAS, MobileMamba-DETR achieves mAP${}_{50}$ of 83.6% and 78.3%, respectively, with 38.7M parameters and 42 FPS inference at $640\times 640$ on an RTX 3090. The results, ablations, and seed-based validation show that selective state-space fusion improves accuracy while retaining real-time throughput. Full article

Roof stability plays a crucial role in maintaining the overall stability of surrounding rocks to ensure safety of tunnel construction and operation. In this work, tension cut-off (TC) technique is introduced to modify the Hoek–Brown (HB) criterion to describe the tensile failure of rock strata. Thereafter, stability analysis of anchor bolt-reinforced tunnel roofs in rock strata subjected to a hybrid tensile-shear fracture is performed. The work balance equation is established by equating the external work rates of the falling block and the anchor bolts to the internal energy dissipation rate. Two stability indicators, that is the stability number (N) and the factor of safety (FoS) are proposed to quantitatively analyze the stability of tunnel roofs. Optimization algorithms combining genetic algorithm and particle swarm optimization are programmed to capture the optimal upper bound solutions. The influences of TC, strength criterion parameters, and anchor bolt-reinforcement strength on roof stability are explored in this work. It was found that increasing the anchor tension T improves the FoS of reinforced tunnel roofs, with an increase of up to 68% observed for rectangular tunnel roofs under the selected representative case, while the improvement is relatively less pronounced for circular tunnel roofs. Regarding anchor support, as ξ increases, the N for rectangular tunnels nearly doubles. This work provides a theoretical basis for preliminary designing of tunnels in reinforced rock strata. Full article

Direction-of-arrival (DOA) estimation of cyclostationary signals is an important problem in array signal processing, especially in sensor-limited and underdetermined scenarios. Sparse arrays and cyclostationary statistics can improve virtual degrees of freedom and target selectivity, but incomplete difference coarray information caused by missing lags may degrade virtual covariance reconstruction and reduce the reliability of DOA estimation in closely spaced, coherent, and interference-contaminated environments. To address this issue, this paper proposes a cyclostationary DOA estimation method based on an augmented extended coprime array (AECA), SVT-based hole recovery, and weighted atomic norm minimization (ANM). The proposed method first constructs the cyclic correlation matrix at the target cyclic frequency and maps it into the AECA-based virtual coarray domain. Redundant lag observations are then aggregated, and an iterative hole recovery procedure is applied to obtain an initial structured virtual covariance matrix. On this basis, a weighted ANM-based covariance refinement model is introduced, where directly observed lags and SVT-recovered hole entries are assigned different confidence levels. The final DOA estimates are obtained using MUSIC on the refined virtual covariance matrix. Simulation results under the considered underdetermined, closely spaced, coherent-source, and interference-contaminated scenarios show that the proposed method achieves lower RMSE and clearer spectral responses than the selected baseline methods. Additional ablation, parameter sensitivity, cyclic frequency mismatch, non-Gaussian noise, and runtime analyses further clarify the contribution, robustness range, and computational cost of the proposed framework. Full article

This paper presents an open-source, fully parametric three-component total knee arthroplasty (TKA) implant system and an automated surgical planning pipeline, addressing the absence of publicly available, modifiable TKA design frameworks in the literature. A cruciate-retaining femoral component, tibial baseplate, and polyethylene insert were designed in Autodesk Fusion with 160 parameters governing all anatomically significant geometry. The femoral articulation surface uses a tangency-constrained triple-radius J-curve. An automated Blender (v. 5.1) Python pipeline performs bone model alignment, size selection from a twelve-size chart, Boolean resection via parametric cutting blocks, and final component placement. Prototypes were 3D printed and validated on 1:1 anatomical bone models. The implant system achieved flush seating on all resection surfaces and impingement-free articulation through the full range of motion on all bone sets. The pipeline correctly aligned bone models, performed resections, and selected appropriately sized implants in all 11 cases, processing each in 1–1.5 min. The system is the first open-source TKA framework to simultaneously provide full parametric definition, documented design rationale, three-component coverage, an automated planning pipeline, and an additive manufacturing fabrication path. By releasing the complete parametric model and pipeline as open source, this work enables independent validation, population-specific adaptation, and iterative improvement by the global research community. Full article

Platinum ditelluride (PtTe₂) is an emerging topological semimetal with intriguing optoelectronic properties. Scalable and controllable growth techniques are fundamental for its technological exploitation. Here, we synthesize large-area PtTe₂ films by tellurization of pre-deposited platinum layers. By selectively modifying the tellurization parameters, we demonstrate the possibility of controlling the layer orientation of tellurized films and of introducing microscopic corrugation in the PtTe₂ film. The first result is obtained by increasing the thermal budget of the process, which changes PtTe₂ preferential crystalline orientation from (001) to (1−13)/(103) growth directions. The latter result is achieved by modifying the heating rate of the process at a fixed growth temperature equal to 550 °C. From the Raman analysis of a wrinkled sample, we find the coexistence of tensile and compressive strains depending on the corrugation site. The demonstrated control over grain orientation and microscopic corrugation provides a powerful strategy to tailor the structural and strain landscape of topological semimetals, providing a robust platform for strain engineering. Full article

CT perfusion (CTP) is widely used in acute ischemic stroke imaging, particularly for treatment selection beyond conventional time windows. However, automated perfusion maps are not direct measurements of irreversible tissue injury, but estimates shaped by deconvolution strategy, temporal correction, dispersion handling, and software-specific thresholds. This review provides a clinically oriented explanation of how CTP algorithms influence the estimation of ischemic core and hypoperfused tissue. Particular attention is given to singular value decomposition (SVD) methods, Bayesian approaches, and timing parameters, including time to maximum (Tmax), Delay, time to peak (TTP), and mean transit time (MTT). Differences in residue function estimation and threshold definition may generate variable outputs across software platforms, even from the same source dataset. Perfusion thresholds should therefore not be treated as universally interchangeable. CTP findings should be integrated with clinical status, non-contrast CT, CT angiography (CTA), collateral status, occlusion site, and imaging-to-treatment context, serving as decision-support tools rather than isolated measures of tissue viability. Full article

This paper presents Resilient Edge-IVA (Intelligent Video Analytics), an integrated framework designed to ensure real-time inference stability and high-speed embedding-based similarity search in resource-constrained edge computing environments. Conventional systems often face Quality of Experience (QoE) degradation caused by computational overhead and hardware-level bottlenecks. To address these challenges, this study proposes a “Whole-cycle” methodology employing a perception-driven, three-tier adaptive control algorithm. This algorithm dynamically modulates encoding parameters, such as resolution and bitrate, by utilizing real-time inference latency and CPU utilization as feedback signals. Furthermore, the framework incorporates an event-density-based Data Diet mechanism. This mechanism selectively adjusts video quality based on object detection results, preserving high-fidelity imagery for critical events while significantly reducing data volume during static intervals. The backend implements a hybrid storage architecture combining the Milvus vector database for CLIP-based high-dimensional visual embeddings with a PostgreSQL relational database for structured metadata. These systems are linked via a deterministic hash key to ensure data atomicity and facilitate high-speed, multi-dimensional embedding-based retrieval. Experimental evaluations conducted on a Raspberry Pi 5 and Hailo-8 NPU demonstrate that the proposed framework maintains a frame drop rate below 0.3% even under extreme workloads, providing a 13-fold improvement in operational stability over static configurations. The results also confirm a 54.2% reduction in total storage occupancy and a Hash Mapping Consistency (HMC) score of 0.89. These findings validate the framework’s effectiveness in reconciling real-time processing stability with storage efficiency. Building upon this baseline, future research will extend the framework to multi-class environments, targeting applications such as Intelligent Transport Systems (ITS). Full article