Search Results (11,821)

Background: Adaptive deep brain stimulation (aDBS) for Parkinson’s disease (PD) relies on accurate detection of beta oscillatory activity. However, electrocardiographic (ECG) artifacts frequently contaminate local field potentials (LFPs), compromising control algorithms. While offline cleaning methods exist, their feasibility for real-time operation within the strict timing constraints of current sensing-enabled devices remains unknown. Methods: We evaluated four ECG removal algorithms, template subtraction (TS), singular value decomposition (SVD), extended SVD (eSVD), and the Perceive toolbox (PR), on simulated datasets (contaminated at −30 to +20 dB) and clinical recordings from 20 PD patients. Algorithms were assessed for artifact removal quality (beta power preservation, signal-to-noise ratio) and real-time feasibility (99th percentile processing latency—P₉₉ < 50 ms). Results: Only TS and standard SVD met the real-time feasibility threshold, with TS achieving superior timing consistency (P₉₉ ≈ 10 ms). eSVD and PR proved incompatible with closed-loop requirements (P₉₉ > 90 ms). While eSVD yielded the highest artifact suppression at extreme contamination, it suffered from poor signal preservation at moderate levels. TS demonstrated the best balance, maintaining beta power accuracy within ±12% across clinically relevant contamination levels. Conclusions: TS is the recommended method for real-time aDBS applications, offering a safety-critical balance of computational efficiency and biomarker fidelity. Full article

Quadrotor motion planning in cluttered environments presents significant challenges in achieving both computational efficiency and trajectory smoothness, particularly in low-altitude economy and intelligent energy system applications where autonomous aerial vehicles perform infrastructure inspection and power line monitoring. Many existing methods either rely on sampling-based algorithms that suffer from long computation times and suboptimal paths, or employ trajectory representations that produce high-order derivative discontinuities unsuitable for agile flight. In this work, we propose an efficient hierarchical motion planning framework that integrates a JPS–Bresenham-based path search with safe flight corridor construction and Bézier curve optimization. Our approach addresses trajectory generation through a two-stage process: a front-end path search that efficiently identifies collision-free paths with reduced waypoints, followed by a back-end optimization that leverages convex safe corridors with overlapping regions to expand the solution space. Through comprehensive benchmark experiments across six different map scenarios, we demonstrate that our method outperforms RRT* and PRM in both path quality and computational efficiency. Monte Carlo experiments across varying map sizes and obstacle densities confirm robustness and scalability advantages. Comparative studies with state-of-the-art planners demonstrate superior success rates and cost efficiency while maintaining strict kinodynamic feasibility. The Bézier-based optimization reduces snap integral by up to 55% compared to ordinary polynomial approaches, demonstrating its superiority for fast quadrotor trajectory planning in complex environments. Full article

Asymmetric Cascaded Multilevel Inverters (ACMLIs) have emerged as a prominent solution for medium- and high-power applications due to their ability to provide an increased number of output voltage levels with fewer power switches. However, maintaining low total harmonic distortion (THD) and ensuring robust stability under varying operating conditions remain significant challenges. This study experimentally validates a voltage-feedback Proportional-Resonant (PR) control strategy for a seven-level ACMLI. Unlike conventional current-feedback methods, the proposed approach directly regulates the output voltage, providing superior harmonic suppression and enhanced steady-state accuracy. The stability and dynamic performance of the controller were theoretically analyzed using Bode diagrams and root locus methods, and further verified through the MATLAB Curve Fitting Tool (CFT) with a high correlation (R² = 0.9989). Experimental results demonstrate that the integration of the PR controller significantly improves power quality, reducing the current THD from 6.55% to 3.68% and the voltage THD to 2.94%. These findings confirm that the system fully complies with IEEE 519 standards and outperforms several existing strategies in the literature. The results establish the voltage-feedback PR control as a robust, high-precision, and practical alternative for power quality-oriented multilevel inverter applications in modern energy systems. Full article

Large-diameter axial ventilation fans are widely used in poultry houses to regulate ai flow, temperature, and air quality. However, conventional induction motors driving these fans typically operate at fixed speed and suffer efficiency degradation under low-speed, high-torque conditions due to slip-induced rotor copper losses. This study presents an experimental investigation of a manufacturing constrained conversion of a commercial induction motor platform into a direct-drive surface permanent magnet synchronous motor (PMSM). Instead of developing a completely new motor design, the proposed approach reuses the existing stator lamination, housing structure, and winding production process while redesigning the rotor electromagnetic structure to incorporate surface-mounted permanent magnets. Experimental testing was conducted using a dynamo meter-based measurement system to evaluate the performance of both the commercial induction motor and the converted PMSM prototype. The results show that the commercial induction motor exhibits significant efficiency degradation at high torque due to increased slip, whereas the PMSM eliminates slip-dependent rotor copper losses and maintains efficiencies above 88% within the typical ventilation operating range of 650–750 rpm. This study further relates airflow demand to rotational speed using fan affinity laws, highlighting the cubic relationship between speed and input power and demonstrating the energy-saving potential of variable-speed PMSM drives. The proposed conversion framework therefore provides a practical pathway for improving the energy efficiency of agricultural ventilation systems while maintaining compatibility with existing motor manufacturing infrastructure. Full article

Estimating ground motion parameters at an unsampled site is challenging for seismologists and engineers alike. An attempt is made to apply Kriging interpolation to estimate peak ground accelerations at specific nuclear power plant sites. However, issues such as data quality and Kriging assumptions pose challenges to how practical and reasonable Kriging interpolation results may be in terms of estimating ground motion parameters. Peak ground acceleration data from the 2016 Gyeongju and 2017 Pohang earthquakes were taken from a local seismological agency. Peak ground acceleration, logarithms of the peak ground acceleration, and residuals between the recorded data and global and local ground motion models were used to select and derive empirical variogram models. The leave-one-out cross-validation process suggested estimating peak ground acceleration residuals from a locally developed ground motion model using an Exponential variogram model. Kriging estimates were compared to a site-specific ground motion model. These estimates appeared reasonable at one site but were significantly off at the other site. On the whole, Kriging estimates were lower than ground motion model predictions. When viewed relative to the nearest recordings, Kriging estimates appeared inconsistent across the two earthquake events. A nearest neighbor approach to computing Kriging estimates suggested a minimum of five data points but much more for modeling an empirical variogram. Results also suggest focusing on validation processes more than variogram selection. This suggests caution when applying Kriging for ground motion-related assessments in South Korea. Full article

The rapid integration of distributed solar photovoltaic (PV) generation is reshaping low-voltage distribution grids (LVDGs), creating voltage rise, reverse power flow, and congestion challenges for distribution system operators (DSOs). Flexibility in generation and demand, broadly understood as the capability to adjust generation or consumption in response to variability and uncertainty in net load, is increasingly central to cost-effective grid operation under high PV penetration. This review examines flexibility and controllability options in LVDGs, focusing on voltage regulation methods, supply- and demand-side flexibility resources, and market-based coordination mechanisms. The Norwegian Regulation on Quality of Supply (FoL) provides the regulatory context: it enforces 1 min average voltage compliance, stricter than the 10 min averaging window of EN 50160, making short-duration voltage excursions operationally significant and directly influencing the trade-off between curtailment, grid reinforcement, and local flexibility measures. Inverter-based active–reactive power control emerges as the most cost-effective overvoltage mitigation option, complemented by local battery energy storage systems (BESS) and demand response for congestion relief and energy shifting. Key gaps include limited LV observability, insufficient application of quasi-static time series (QSTS) assessment in planning, and underdeveloped DSO-aggregator coordination frameworks. Combined inverter control, feeder-end storage, and demand-side flexibility can defer costly reinforcements, particularly in rural 230 V IT feeders where voltage constraints dominate. Full article

Monitoring air quality is crucial for understanding and improving public health. There is interest in developing ultra-sensitive, low-power, cost-effective sensors. This work demonstrates that structural modulation of Sn nanoparticles through controlled deposition and oxidation enables a transition from metallic to semiconducting percolative networks, significantly enhancing NO₂ sensing performance at room temperature. The proposed percolation-driven sensing mechanism provides a new framework for understanding charge transport and gas interaction in nanostructured metal oxide systems. The nanoparticles are deposited near the percolation threshold for electrical conduction and, upon exposure to air, consist of a tin core and an amorphous Sn₃O₄ surface. Post-deposition heating in air at 320 °C for two hours forms SnO and Sn₃O₄ on top of the gold electrodes and polycrystalline SnO in the tetragonal litharge phase, known as Romarchite, on the glass between the electrodes. Both as-deposited and heat-treated sensors were capable of detecting NO₂ at room temperature, with a limit of detection in the parts-per-billion range. A percolation model is used to explain their operating currents, in which NO₂ reacts at nanoparticle gaps and intra-grain boundaries to form charge-depletion regions that primarily determine their resistance. Heat treatment has also been found to cause disproportionation of SnO, resulting in tin-rich precipitates and increasing the operating current to the milliampere range. These precipitates, although oxidized on their surfaces when exposed to air, may serve as bridges that reduce the total resistance of the percolating paths. Full article

Monitoring surface deformation at reclaimed airports under construction is crucial for ensuring construction safety. However, significant variations in surface scattering characteristics cause severe decorrelation, limiting the effectiveness of conventional single-polarization Interferometric Synthetic Aperture Radar (InSAR). To address the issue of insufficient coherent pixels, we propose a dual-polarization sequential InSAR technique and compare its performance with traditional Persistent Scatterer Interferometry (PSI) and Distributed Scatterer Interferometry (DSI) at the Dalian Jinzhou Bay International Airport (DJBIA). Using 89 Sentinel-1A dual-polarization (VV-VH) images (August 2022 to October 2025), the results demonstrate that VV and VH polarizations exhibit significant spatial complementarity, highlighting the necessity of multi-polarization data. Further, to address the issue of long-term changes in scattering characteristics, we applied the Sequential Estimation and Total Power-Enhanced Expectation Maximization Inversion (SETP-EMI) method, which dynamically integrates dual-polarization information and performs adaptive phase optimization. This approach significantly enhances monitoring capability in low-coherence areas of the airport under construction, effectively suppressing phase noise, improving interferogram quality, and yielding a more complete and reliable deformation field. Overall, this study systematically validates the SETP-EMI method with dual-polarization information for deformation monitoring at reclaimed airports under construction, providing technical support for engineering safety control and research on reclamation subsidence mechanisms. Full article

The limited availability of high-quality timber and the increasing demand for wood-based panels have encouraged the exploration of alternative and sustainable lignocellulosic resources. Rattan waste is abundant in Indonesia; however, its low mechanical strength and limited durability restrict its direct application in composite materials. This study investigated the effect of furfuryl alcohol (FA) modification and different adhesive systems on the performance of rattan-based particleboard. Rattan particles were immersed in FA for 24 h and used to produce particleboards (300 × 300 × 10 mm) bonded with phenol formaldehyde (PF), melamine formaldehyde (MF), and urea formaldehyde (UF) adhesives at a resin content of 12%. The boards were manufactured under controlled hot pressing conditions and conditioned for 14 days prior to testing. Furfurylation significantly improved dimensional stability by reducing moisture content, water absorption, thickness swelling, and leaching, with anti-swelling efficiency values ranging from 43.25% to 71.06%. Some selected mechanical properties, including internal bonding strength, hardness, and screw holding power, were also enhanced. However, the modification showed limited influence on the modulus of elasticity and, in some cases, reduced the modulus of rupture. Among the adhesive systems, MF-bonded boards exhibited the most balanced mechanical performance. Furfurylation also produced darker and more uniform board surfaces. These findings indicate that furfurylated rattan particleboards are suitable for non-structural and decorative applications. Full article

With the rapid advancement of digital integrated circuits, transistor sizes and integration levels have grown at an unprecedented rate, leading to increasingly complex design processes. A key challenge in digital layout design is the placement and routing of standard cell circuit layouts, which directly impact chip quality and performance. Power is a critical factor in evaluating standard cells. To enable low-power standard cell layouts, the depth-first search (DFS) algorithm is proposed to model and place the standard cell. Additionally, the study aims to satisfy Design Rule Checking (DRC), a grid routing strategy based on the deep reinforcement learning (DRL) algorithm, which quickly identifies cell boundaries and barriers such as existing nets as well as contacts, while optimizing metal routing to achieve minimal power. Results show that the standard cell layouts generated by the DRL-based model achieve over a 90% reduction in design time and approximately 5% improvements in power compared with manual layouts. The proposed method facilitates the rapid development of standard cell library and has important engineering value. Full article

Backscatter communication (BackCom) has emerged as an energy-efficient and low-cost communication paradigm, in which wireless devices transmit information by reflecting incident signals rather than actively generating radio frequency signals. Owing to the extremely low power consumption and hardware cost, BackCom is particularly suitable for Internet of Things (IoT) devices with stringent low energy and cost constraints. However, due to the severe double channel attenuation inherent in backscatter links, conventional ground-based deployment of transmitters and receivers often suffers from poor communication quality and low energy efficiency. Unmanned aerial vehicles (UAVs), with their high mobility and favorable line-of-sight (LoS) links, can act as dynamic aerial transmitters and receivers in BackCom, thereby mitigating channel attenuation and improving both communication reliability and energy efficiency. To enhance the data collection efficiency of UAV-assisted BackCom systems under a limited mission duration, this paper proposes a joint optimization method for communication resource allocation and UAV trajectory design under task time constraints. Specifically, a mixed-integer non-convex optimization problem is formulated to maximize the number of devices served by the UAV within a given task duration. The original problem is then decomposed into two subproblems, namely communication resource allocation optimization and UAV trajectory optimization. An iterative algorithm based on Block Coordinate Descent (BCD) and Successive convex approximation (SCA) is developed to obtain an efficient solution. Simulation results demonstrate that the proposed method can effectively increase the number of served devices within the specified mission time limit. Full article

Background: Neoadjuvant therapy (NAT) is increasingly investigated in operable pancreatic ductal adenocarcinoma (PDAC), yet its role in strictly resectable disease remains controversial. Randomized trials have been conducted both in borderline resectable and resectable PDAC and have demonstrated survival advantages, while evidence in strictly resectable tumors remains poor. We conducted an umbrella review of systematic reviews and meta-analyses (SRMAs) to comprehensively evaluate the highest level of available evidence on NAT versus upfront surgery in operable PDAC. Methods: We performed an umbrella review of completed SRMAs assessing neoadjuvant chemotherapy (NAC) and/or chemoradiotherapy (NACRT) in resectable and borderline resectable PDAC. MEDLINE/PubMed, Embase, and Cochrane Library were searched from inception through November 2025. Eligible SRMAs reported at least one clinical outcome, including overall survival (OS), disease-free/event-free survival (DFS/EFS), resection rate, R0 resection, nodal status, or perioperative outcomes. Methodological quality was appraised using AMSTAR-2 and ROBIS tools. Overlap among SRMAs was quantified using the Corrected Covered Area (CCA), and RCT-only evidence was prioritized for causal inference. Evidence credibility was graded using an Ioannidis-style classification framework. Results: Thirty-four SRMAs published between 2010 and 2025 were included. In strictly resectable PDAC, RCT-only meta-analyses showed no definitive OS benefit for NAT compared with upfront surgery (pooled HR approximately 0.85, 95% CI 0.68–1.05), although a significant improvement in EFS was observed (HR approximately 0.77, 95% CI 0.65–0.90). Trial sequential analyses suggested insufficient information size for conclusive OS benefit in resectable disease. Conversely, in pooled resectable and borderline resectable populations, NAT significantly improved OS (HR approximately 0.66, 95% CI 0.52–0.85), with subgroup analyses indicating that the survival advantage was primarily driven by borderline resectable tumors. NAT consistently increased R0 resection and node-negative (pN0) rates and reduced non-curative explorations. However, neoadjuvant strategies were associated with treatment-related attrition and, in some analyses, lower overall resection rates. Comparative evidence suggested improved pathological outcomes with chemoradiotherapy versus chemotherapy alone, without a consistent survival advantage. Conclusions: Current high-level evidence supports NAT as the preferred strategy for borderline resectable PDAC, demonstrating consistent survival and pathological benefits. In strictly resectable disease, NAT improves disease-control endpoints and pathological surrogates, but a definitive OS advantage has not been consistently demonstrated in RCT-only syntheses. This should not be interpreted as evidence of equivalence between NAT and a surgery-first strategy, given the heterogeneity, limited power, and therapeutic-era effects of the available literature. Treatment decisions in resectable PDAC should therefore be individualized, balancing potential oncologic benefits against attrition risk. Future adequately powered randomized trials employing contemporary multi-agent regimens are needed to clarify the survival impact of NAT in strictly resectable disease. Full article

Diode-pumped alkali vapor lasers (DPALs) offer high quantum efficiency, low thermal loading, excellent beam quality, and emission wavelengths matched to important application scenarios. Extending DPALs toward pulsed regimes is of particular interest for applications such as lidar, free-space optical communication, and precision material processing, where high peak power and flexible temporal control are required. This review surveys the key technologies underlying DPAL systems and summarizes the progress in pulsed-generation approaches. The pulsed techniques reported to date are systematically reviewed, including pump modulation, intracavity modulation, cavity dumping, and mode-locking, together with a comparison of their performance. The current status indicates that pulsed DPALs remain at an early stage, with limitations in parameter space exploration and performance scaling. Future developments are expected along several directions, including further exploration of mode-locked DPALs, burst-mode pulse generation for structured temporal output, power scaling through MOPA architectures, and spectral extension via nonlinear frequency conversion. These directions collectively define the pathway toward high-performance pulsed DPAL systems. Full article

Background/Objectives: Efficient management of intensive care unit (ICU) resources is a critical challenge for modern healthcare systems, which must balance high-quality patient care with operational and financial performance. ICU length of stay (LOS) is a key metric of clinical complexity and hospital efficiency. However, traditional methods for predicting LOS often fail to capture the complex, nonlinear interactions among physiological, demographic, and treatment-related variables. Machine learning (ML) and deep learning (DL) models have emerged as promising tools for enhancing predictive accuracy and supporting data-driven decision-making. Methods: This study presents a systematic review and meta-analysis of ML and DL approaches for predicting ICU LOS in adult patients. Following PRISMA guidelines, eight scientific databases were searched, yielding 33 eligible studies published between 2015 and 2025. Results: Mixed medical–surgical ICUs were the most common setting (51.5%), and 45.5% of datasets were sourced from public repositories. Most studies (19/33) focused on binary classification of prolonged stays, although thresholds ranged from >48 h to ≥14 days. The pooled results from ten studies yielded an AUROC of 0.9005 (95% CI: 0.8890–0.9121), indicating strong predictive capability across diverse clinical contexts. Subgroup analyses showed comparable performance between specialized surgical and general ICUs. Conclusions: These findings suggest that AI-driven LOS prediction models exhibit strong discriminatory power for ICU LOS prediction, supporting hospital capacity planning. However, to translate this into reliable clinical support, the methodological heterogeneity, scarcity of external validation, and near absence of calibration reporting identified in this review need to be addressed. Full article

The field production of tomato faces challenges regarding abiotic stress factors, which unfavorably impact fruit quality traits. Hedgerows, a form of agroforestry, offer a climate-resilient strategy to buffer temperatures and reduce the impact of direct wind stress on crop production. This study assessed the impact of hedgerow microclimate modulation effects on open-field tomato fruit quality, employing three genotypes (Roma, Ace55, and Szentlőrinckáta). Key quality traits (Total Soluble Solids (TSS), Titratable Acidity (TA), Sugar–Acid Ratio (SAR), Ferric-Reducing Antioxidant Power (FRAP), Total Phenolic Content (TPC), Chroma (C*), and Hue (h^o)) were measured over two harvests per season, in two consecutive years (2023–2024). Plots were positioned at five distances (3, 6, 9, 12, and 15 m from the hedge) on both windy and protected sides (W1–W5 and P1–P5, respectively, with 1 showing the closest position). We observed that the microclimate of the protected side was consistently warmer, with an average deviation from the reference temperature of +3.54 °C at mid-distances and +0.38 °C higher overall across both growing seasons. Results show that mid-distance zones (P3–P4, W3–W4) consistently exhibited the highest C* (up to 39.44) at W4 and TSS values at W1 (7.00 °Bx). Protected sides favored higher TA at P3 (0.70%) and Hue (h^o) values at P3 with (53.06 ± 0.30) with Ace55 and SAR at P3 (16.35) with Szentlőrinckáta. Windy sides significantly enhanced FRAP and TPC, with the Szentlőrinckáta genotype exhibiting the highest antioxidant capacity at W1 (23.67 mg AAE 100 g⁻¹, FRAP) and TPC (244.17 mg GAE 100 g⁻¹). At W4, Roma showed a 9.4% increase in TPC in the second harvest, while Ace55 showed the highest FRAP values during late-season sampling, highlighting genotype-specific antioxidant resilience under contrasting microclimates. These findings suggest that mid-distance zones and microclimatic variation between windy and protected sides remarkably influence fruit quality traits and antioxidant profiles. Full article