Search Results (1,474)

The increasing demand for low-alcohol wine products calls for effective vineyard strategies to reduce grape sugar concentration, while climate change is exacerbating sugar accumulation through warmer growing conditions. In this context, severe shoot trimming applied at specific phenological stages may represent a promising approach to induce sustained source limitation. A field experiment was conducted in 2025 on Vitis vinifera L. cv. Ortrugo to evaluate severe shoot trimming performed at the onset of berry softening. Vine growth, yield components, grape composition, and seasonal total soluble solids (TSSs) were monitored. Vine carbon reserves and shoot fruitfulness were assessed to evaluate carry-over effects. Experimental wines were produced to determine alcohol and fermentative aroma. Severe trimming markedly reduced leaf area and vine balance, leading to a sustained reduction in sugar accumulation. At harvest, grape TSSs decreased by 4.1 °Brix (17.6 vs. 21.7 °Brix) and the final wine alcohol concentration was lower by 3.4% (v/v). Yield was unaffected and no substantial negative effects on wine fermentative aroma were observed, while titratable acidity slightly increased. Even if trimming reduced winter starch concentration in roots, no reduction in shoot fruitfulness was observed in the subsequent spring. Severe trimming successfully reduced grape sugar and wine ethanol without compromising yield, aroma, or vine performance, supporting its potential for low-alcohol wine production and reduced-impact dealcoholization. Full article

Suspended ceiling systems are among the most seismically vulnerable non-structural components in buildings, posing significant life-safety risks and economic losses, yet understanding their full-field kinematic behavior under seismic loading remains a major experimental challenge. Conventional contact sensors offer limited spatial coverage and can alter the dynamic properties of lightweight panels due to mass loading. In contrast, non-contact optical alternatives are rarely feasible in shake-table environments due to restricted viewing angles, extensive areal coverage requirements, and the risk of equipment damage from falling panels. This study proposes an end-to-end three-dimensional displacement measurement framework for large-scale shake-table testing of suspended ceiling systems, employing consumer-grade cameras with purpose-built tools that cover the complete experimental workflow, including motion-based video trimming, semi-automated calibration, a robust multi-stage image-tracking pipeline that maintains trajectory continuity under extreme inter-frame displacements, and a ceiling system motion visualization and analysis tool. The framework was validated through a full-scale shake-table experiment continuously tracking 324 spatial nodes across 81 ceiling panels, achieving an RMSE below 3 mm in all spatial directions and exact peak-frequency agreement in 9 out of 10 test cases. A parallel processing architecture reduced total processing time from over 27 h to under 10 min without GPU acceleration, and six-degree-of-freedom rigid-body analysis resolved the complete panel failure sequence from constrained oscillation through multi-axis rotation to gravitational free fall, a level of kinematic detail unattainable with conventional instrumentation. This framework establishes a practical, scalable foundation for full-field seismic performance assessment of non-structural systems where conventional instrumentation is physically or logistically infeasible. Full article

Accurate transfer of implant position is essential for implant-supported prosthodontic workflows. This in vitro study compared the trueness and precision of five intraoral scanners in single crown, three-unit fixed partial denture, and full-arch implant-supported scanning scenarios using root mean square (RMS) deviation analysis. Two maxillary resin models, representing partially dentulous and fully edentulous conditions, were fabricated through a CAD/CAM and 3D-printing workflow with implant analogs and scan bodies. Reference datasets were obtained with an InEos X5 desktop scanner, and each intraoral scanner was used to perform 10 scans per scenario. After standardized scenario-specific trimming, datasets were analyzed in Geomagic Control X. Statistical analysis included two-way analysis of variance and follow-up one-way analysis of variance with Tukey post hoc comparisons using Bonferroni-adjusted thresholds. Trueness was affected by scanner type (p < 0.001) and scenario (p < 0.001), without interaction (p = 0.096). Precision was affected by scanner type (p = 0.012), scenario (p = 0.004), and their interaction (p < 0.001). iTero Lumina and Helios 600 showed lower trueness deviations, whereas Trios 5 showed greater deviations, especially in full-arch scans. Scanner selection and scan extent should therefore be considered when interpreting surface-based RMS accuracy in implant-supported digital scans. Full article

Background: The glucocorticoid receptor NR3C1 exhibits antiepileptic properties, but the mechanisms governing its stability during epileptogenesis remain elusive. This study investigated whether the E3 ubiquitin ligase TRIM8 regulates neuronal hyperexcitability and epileptic activity by modulating NR3C1. Methods: We established an in vivo epilepsy model via intrahippocampal kainic acid (KA) injection and an in vitro epileptiform model using Mg²⁺-free artificial cerebrospinal fluid in primary hippocampal neurons. The roles of TRIM8 and NR3C1 were assessed using in vivo and in vitro gain- and loss-of-function approaches, alongside co-immunoprecipitation, Western blotting, immunofluorescence and whole-cell patch-clamp recording. Results: TRIM8 is significantly upregulated in hippocampal and temporal lobe neurons in epileptic mice. TRIM8 was markedly upregulated in the hippocampal neurons of epileptic mice, inversely correlating with NR3C1 levels. Mechanistically, TRIM8 interacted with NR3C1, promoting its polyubiquitination and proteasomal degradation. This TRIM8-mediated NR3C1 reduction enhanced the phosphorylation of AMPA receptor (AMPAR) subunits GluR1 (Ser831) and GluR2 (Ser880) without affecting total receptor expression. In vitro, TRIM8 overexpression exacerbated calcium dysregulation, neuronal injury, and AMPAR phosphorylation; crucially, concurrent NR3C1 overexpression rescued these effects. In vivo, knockdown of TRIM8 significantly reduced seizure frequency, prolonged the latency to the first Stage III seizure, shortened average seizure duration, and decreased total seizure burden in KA-induced epileptic mice. Electrophysiologically, TRIM8 overexpression significantly increased the frequency of spontaneous action potentials and amplitudes of spontaneous excitatory postsynaptic currents under Mg²⁺-free conditions. Furthermore, in vivo knockdown of TRIM8 attenuated KA-induced seizure severity, restored NR3C1 protein stability, and suppressed aberrant AMPAR phosphorylation in the hippocampus. Triple immunofluorescence staining showed that KA-induced epilepsy increased TRIM8 but decreased NR3C1 immunoreactivity in NeuN⁺ hippocampal neurons, and TRIM8 knockdown reversed these changes. Conclusions: TRIM8 acts as a critical driver of epileptiform activity by targeting NR3C1 for degradation, thereby disinhibiting AMPAR phosphorylation and enhancing network hyperexcitability. The TRIM8-NR3C1-AMPAR axis emerges as a previously unrecognized molecular pathway in epileptogenesis, highlighting its potential as a promising therapeutic target for epilepsy. Full article

Aquaponic systems show complex multivariate dynamics in water quality parameters, with dissolved oxygen (DO) being a key indicator of biological stability. This study presents a dynamic multivariate predictive framework for short-term dissolved oxygen forecasting utilizing IoT data gathered from various heterogeneous aquaponic ponds. The issue is redefined as a regression task to forecast future DO values within a brief time-frame (~5 min), enabling early warning functionalities instead of utilizing a rule-based classification method. To ensure structural robustness across systems, we applied intra-pond percentile trimming and normalization procedures to mitigate the differences in scale between ponds. Using a Leave-One-Pond-Out (LOPO) validation scheme, we tested model performance and cross-system generalization. An MLP feedforward neural network with lagged temporal variables had an average RMSE of 0.83 on a normalized scale. Regime-based error analysis showed that the RMSE increased from 0.80 on stable conditions to 1.43 under high-volatile regimes. A comparative LSTM model did not produce substantial performance enhancements. Sensitivity analysis revealed lagged impacts of pH and turbidity on subsequent DO dynamics, indicating the need for operational measures such as aeration modification and suspended solids management. Full article

The growing demand for high-speed marine transportation requires continuous improvement in ship design to achieve higher hydrodynamic efficiency. From an engineering design perspective, hull form modification is a key approach to optimizing the performance of planing vessels, particularly through the implementation of stepped hull configurations. This study aims to investigate the effects of step geometry and step position on the resistance and trim characteristics of a planing hull based on Taunton et al.’s Model C, with the objective of improving vessel efficiency. The design methodology integrates hull geometry modification, parametric variation in step position and step height, and numerical performance assessment. In this research, the governing equations are solved using the Reynolds-Averaged Navier–Stokes (RANS) framework with the Finite Volume Method (FVM) as the discretization technique. The turbulence model used is k-ω SST, while the interaction between water and air phases is represented using the Volume of Fluid (VOF) method. From a design performance perspective, the results demonstrate that stepped hull geometry significantly influences resistance and trim characteristics. The optimal design configurations achieved a resistance reduction of up to 17.93% and a trim of 1.53° was achieved with a stepped position of 430 mm from the transom and a stepped height of 25 mm (Model A3) at Fr 2.28. Meanwhile, a resistance reduction of 15.49% and a trim of 1.46° were observed for a stepped position of 860 mm from the transom and a stepped height of 25 mm (Model B3) at Fr 2.72. These findings highlight the importance of step geometry and placement as key design variables in improving planing hull performance. This study demonstrates that CFD-based evaluation can effectively support engineering design decisions for stepped hull optimization, providing a systematic approach for improving hydrodynamic efficiency in high-speed vessel design. Full article

Bipolar junction transistor (BJT)-based 2D temperature-sensor arrays are factory-calibrated to ±0.1 °C, but post-deployment thermal and mechanical stresses drift their per-sensor gain–offset parameters by an order of magnitude, and in-lab recalibration is impractical. We present RASC (Region-Aware Self-Calibration), a five-stage algorithm that decomposes the global ill-posed problem into local cluster-level problems, runs robust alternating estimation (trimmed-mean field reconstruction + Huber iteratively reweighted least squares (IRLS)) inside each cluster, and reconciles overlapping estimates by linear consensus on the cluster-overlap graph with provable exponential convergence. On 7632 frames from a deployed 16 × 16 array exhibiting ≈5× factory-spec non-uniformity, RASC cuts the locally non-smooth fixed-pattern residual by 71 ± 5% (10-fold cross-validation (CV)), reducing this residual to a level comparable to the ±0.1 °C factory specification (as assessed by local-smoothness residual metrics, not independent absolute-temperature validation) while perturbing the calibrated field by only 0.041 °C RMSE; reduction concentrates at the edges (78% vs. 55% interior). In simulations on 8 × 8 to 32 × 32 arrays, RASC matches an oracle centralised extended Kalman filter (EKF) within 0.10 °C with ≈4× lower bandwidth. The real-data evaluation is a single-deployment proof of concept on one array and one host PCB; broader, longitudinal validation remains future work. Full article

The valorization of culinary by-products into functional bioactive resources represents a significant advancement in sustainable biotechnology. This study characterizes an extract derived from “battuto toscano” by-products, a traditional blend of garlic, onion, carrot, and celery trimmings, recovered through circular economy principles. Comprehensive antioxidant profiling was performed alongside biological evaluations on human cell lines and anti-glycation assays. Results from Folin–Ciocalteu, FRAP, and TEAC assays confirmed a high concentration of secondary metabolites with significant scavenging capacity. In vitro testing on primary human fibroblasts and HaCaT keratinocytes revealed a concentration- and time-dependent biological response, with lower concentrations showing better compatibility and transiently enhancing HaCaT metabolic activity. Furthermore, BTE reduced AGE-associated fluorescence in the BSA–glucose model, particularly at 5 mg/mL, supporting its potential anti-glycation activity. These findings establish “battuto toscano” by-products as a reservoir of sustainable biomolecules. This study offers a transformative resource for the pharma/nutraceutical sectors by bridging culinary tradition with biomedical innovation. Full article

Background and Objectives: Recent studies suggest that remimazolam, a novel ultra-short-acting benzodiazepine, has an excellent pharmacokinetic and safety profile, favourable for ambulatory procedures. Although remimazolam has been studied as a sole agent for anaesthesia in day case gynaecological surgery, studies assessing its use in combination with other anaesthetics remain scarce. The aim of this study was to investigate the effects of a low-dose remimazolam adjunct on the characteristics of an intravenous propofol–remifentanil anaesthesia regimen. Materials and Methods: A single-centre retrospective observational cohort study was conducted on patients who underwent brief day case gynaecological surgery under general intravenous anaesthesia using remifentanil and propofol from November 2024 to January 2025. The patients were divided into two groups depending on whether they received remimazolam as an adjunct. To account for confounding, propensity scores (PSs) were estimated from baseline characteristics and used to derive stabilised inverse probability of treatment weights (IPTWs). Weighted regression models were then applied to estimate treatment effects on postoperative recovery time measures, consumption of anaesthetics, and incidence of any adverse effects intraoperatively and postoperatively. Cost effectiveness was evaluated using the incremental cost-effectiveness ratio (ICER). Results: The clinical data of 51 patients were retrospectively examined: 32 patients were assigned to the intervention group, and 19 patients were assigned to the reference group; after IPTW and PS trimming, the sum of weights was 22 in the intervention group and 58.8 in the reference group. The use of remimazolam as an adjunct was associated with 3.5 min shorter time to eye opening (p < 0.001) and 3.6 min shorter time to full consciousness (p = 0.002); the total consumption of propofol was decreased by 3 mg/kg (p < 0.001); the median dose of remimazolam adjunct was 0.12 mg/kg, or 10 mg per case. There were no statistically significant adverse effects. ICER was 2.35 € per minute of operating room (OR) time saved. Conclusions: In the setting of day case gynaecological surgery, the addition of remimazolam to a propofol–remifentanil regimen reduced propofol requirements and shortened recovery time without an increase in adverse effects. This may represent a more efficient anaesthetic approach for ambulatory procedures with a comparable safety profile. Full article

We present a material distribution topology optimization (TO) framework that directly generates capacity-specific radial trims for severe-service control valves. The method uses an out-of-plane resistance modified two-dimensional turbulence model and objective functions that maximize directional change to create tortuous pressure-staging geometries at predefined channel depths. Four trims targeting non-dimensional capacities ($C_V$) of 0.672, 0.96 (two objectives), and 1.248 were optimized, MSLA-printed, and tested in a globe valve using IEC 60534 procedures. The measured capacities ranged from −13.7% to +4.8% of the targets for a fully 2D optimization process, dropping to a maximum of 7.8% when coupled with a hybrid 3D tuning step. Acoustic detection indicated incipient cavitation at a pressure drop ratios greater than $0.87$ for the most highly staged design and $0.73$ for the highest capacity design, which is consistent with our simulations of the flow field before fabrication. These results demonstrate that TO can deliver fit-to-service, capacity-tuned trims with excellent cavitation suppression, reducing reliance on large parametric design libraries. Full article

Observation of welding features is important for GMAW training and instruction because the welding arc, molten pool, filler wire, and groove can be difficult to distinguish during welding. In this study, a compact, low-cost, and practical visualization system was developed to support gas metal arc welding (GMAW) skill training from both the welder’s and instructor’s perspectives. The system consists of a welder-side unit and an instructor-side unit and uses a commercial camera, optical filters, a wide-angle lens, and a compact computer. Welding images were acquired under actual GMAW conditions, and the effects of optical filter selection, exposure time, tone mapping, and trimming methods were investigated. A 600 nm long-pass filter and an exposure time of 20,000 μs provided a suitable balance between arc-light suppression, brightness stability, and image clarity. Gamma correction improved the visibility of key regions, including the molten pool, arc, torch, groove, and wire. In addition, low-pass-filtered centroid tracking enabled stable trimming of the weld region from wide-angle images. The developed system achieved real-time display and recording of standardized welding images, demonstrating its potential to support GMAW training through improved image visibility, real-time monitoring, and standardized image recording, while also providing visual data for post-weld review and future skill-assessment applications. Full article

The digital preservation of built cultural heritage requires precise documentation techniques capable of capturing complex architectural geometries often affected by occlusions and data voids. This study presents a robust multi-sensor fusion workflow integrating Terrestrial Laser Scanning (TLS) and Unmanned Aerial Vehicle (UAV) photogrammetry for the 3D reconstruction of the Hasaköy (Sasima) Church in Niğde, Türkiye. To address the limitations of traditional registration methods, specifically the susceptibility of the Iterative Closest Point (ICP) algorithm to local minima in datasets with partial overlaps, this study proposes a fine-tuning approach based on the Multi-population Based Differential Evolution (MDE) algorithm. The methodology employs a coarse-to-fine strategy, initiating with Fast Point Feature Histogram (FPFH) extraction and RANSAC (Random Sample Consensus) for global alignment, followed by TR-ICP, MDE, PSO, and Aquila Optimizer (AO) evaluation, computational-time analysis, FPFH-radius sensitivity testing, and 6-DoF transformation decomposition to characterize both accuracy and operational cost. In the 30-run fine-tuning evaluation, MDE reduced the mean bidirectional trimmed RMSE from 0.4152 m for TR-ICP to 0.3726 m. With a population parameter of 10, MDE retained a low median RMSE of 0.3718 m, while PSO exhibited a wider stochastic tail under the same bounded 6-DoF search budget. AO produced a higher mean bidirectional trimmed RMSE of 0.5233 m. The decimeter-scale bidirectional RMSE should be interpreted as a cross-source, partial-overlap distance metric rather than sensor precision; the overlapping facade objective was approximately 2.4–2.8 cm, and the UAV block was independently controlled with a 1.34 cm GCP RMSE. This study establishes a transparent and reproducible framework for heritage documentation, supporting the faithful digital preservation of endangered monuments with complex typologies. Full article

The advancements made in the mass spectrometry imaging (MSI) field have allowed for the generation of very large-scale data sets. These data are often interrogated by machine learning (ML), although storing and handling data sets of this size can be difficult. To aid impacted researchers, we seek to evaluate feature reduction strategies that will minimize the amount of data stored while still maintaining the ability to correctly classify the data. Two different feature selection strategies are tested on six different data sets, leveraging XGBoost as the machine learning algorithm. The study provides evidence that selecting features based on the greatest average abundance across all samples is best suited to scale down the feature set at a more modest trimming level, while selecting features based on statistical analysis via a Student’s t-test is better suited for a more aggressive trimming level. These trends were present regardless of training set size or cross-validation strategy. The results from this work provide insight into when these feature filtering steps can be used effectively and when another data reduction strategy, including not restricting the data set, should be considered. Full article

Garlic, a significant global specialty economic crop, is currently facing severe challenges from labor shortages and escalating production costs. Achieving full-process mechanized production is the core approach to ensuring sustainable industrial development and enhancing international competitiveness. This paper systematically reviews the research progress and application status of mechanized equipment throughout the entire crop cycle of garlic production, including seeding, field management, harvesting, and post-harvest processing and sorting. The study reveals that garlic equipment is undergoing a profound transformation from traditional mechanization to “opto-electro-mechanical integration” and intelligence. In the seeding phase, breakthroughs have been made in pneumatic precision seed-metering and machine vision-based clove bud orientation technologies, significantly improving the quality of upright planting. In field management, precise variable-rate application and targeted weeding have been preliminary realized through plant protection Unmanned Aerial Vehicle (UAV) downwash airflow field simulation (CFD) and deep learning-based image segmentation. In the harvesting phase, relying on 3D Discrete Element Method (3D-DEM) soil-cutting simulation and adaptive profile root-trimming technology, the industry is accelerating the transition from inefficient segmented harvesting to low-damage combined harvesting. In the post-harvest phase, hyperspectral imaging (HSI) and multi-label convolutional neural networks (CNNs) have been utilized to achieve high-speed non-destructive detection of internal and external quality. However, industry still faces critical bottlenecks such as the insufficient integration of machinery and agronomy, poor robustness of intelligent perception algorithms in complex environments, and high damage rates of core soil-engaging components. Future research should focus on lightweight algorithm deployment, digital twin-driven virtual prototyping, and the construction of regional standardized machinery–agronomy systems, aiming to build an efficient and universal intelligent production closed-loop for garlic. Full article

This paper investigates altitude control of the Unmanned Aerial Vehicle (UAV) through the elevator. Elevators are flight control surfaces, which control lateral altitude by changing the pitch balance. The angle deflection along with the thrust from propulsion system is matched and guided by the system for the gain or loss of altitude over desired range of distance. A linear time-invariant elevator–altitude channel model is obtained by linearizing the six-degree-of-freedom equations of motion about a steady, level-flight trim condition. The resulting transfer function is analyzed using state-space representation and root-locus techniques, revealing that the uncompensated unity-feedback system is unstable. A proportional-integral (PI) controller is then designed and implemented in a unity-feedback configuration. The closed-loop dynamics are evaluated through time-domain simulations under step, ramp, and parabolic altitude commands, and key performance indices such as rise time, settling time, overshoot, and steady-state error are extracted. The Routh–Hurwitz criterion is used to derive an admissible gain range and to select a gain that balances response speed and robustness. The steady-state error is quantified analytically for step, ramp, and parabolic inputs, confirming a finite error for step inputs and infinite error for ramp and parabolic inputs, consistent with a type-0 system. The results demonstrate that a simple PI-based elevator controller can stabilize the linearized altitude channel and significantly improve transient performance, providing a useful baseline for more advanced nonlinear or adaptive designs in UAV flight-control applications. Full article