Search Results (4,666)

Wide- and narrow-band composite-axis servo systems in inter-satellite laser communication face critical challenges in balancing high-precision dynamic tracking and strong robust anti-disturbance performance under the coupling effect of high-speed inter-satellite relative motion and multiple strong disturbances. To address this issue, this paper proposes a composite control method integrating adaptive non-singular terminal sliding-mode control and a nonlinear extended state observer. First, a full-link dynamic model covering electromechanical coupling and inter-axis disturbance transmission is constructed to accurately quantify the disturbance characteristics of coarse- and fine-tracking loops. Second, a third-order nonlinear extended state observer is designed to realize real-time high-precision estimation and feedforward compensation of lumped disturbances. On this basis, a self-consistent adaptive non-singular terminal sliding-mode control law is formulated. Under the explicitly stated observer-residual and reaching-phase assumptions, the ideal continuous model provides finite-time convergence of the sliding variable and tracking error. Finally, a wide- and narrow-band cooperative strategy based on error frequency division is introduced to achieve complementary performance between large-stroke coarse tracking and ultra-high-precision fine tracking. Numerical simulations yield a steady-state tracking-error point estimate of 0.30 μrad and a 20 dB disturbance-suppression bandwidth of 1200 Hz. In the semi-physical dynamic-tracking test, the proposed controller limits the peak error to 1.2 μrad; the instrument-only expanded uncertainty of the detector output is estimated as 0.12 μrad (coverage factor k = 2). At the reported evaluation points, the proposed method outperforms PID, conventional sliding-mode control, and linear active-disturbance-rejection control. Deterministic robustness simulations also show smaller tracking errors and shorter recovery times under parameter perturbation, actuator saturation, and temporary link occlusion. No Monte Carlo loss-of-lock probability is claimed. Full article

Trade-finance instruments may support export performance by alleviating financing constraints and reducing international payment risks. This study examines the short- and long-run relationships between Turkish Eximbank instruments and Turkey’s aggregate exports using annual data for 2001–2024. Three nested log-linear Autoregressive Distributed Lag (ARDL) models jointly incorporate short-term credits, medium- and long-term credits, insured shipment values and the real effective exchange rate. Intermediate-goods imports and external demand are added in the second model, while tariff and Russia–Ukraine war-period controls are introduced in the third. ADF, PP and KPSS tests examine the integration properties of the continuous variables and ARDL bounds tests evaluate the existence of long-run relationships. The bounds-test results support a relationship with levels in all three specifications, while the negative and significant error-correction coefficients indicate convergence toward equilibrium. Insured shipments have a positive and statistically significant short-run coefficient in every model and a positive long-run coefficient in the benchmark model. However, their long-run significance disappears after imported-input conditions and external demand are controlled for. Neither credit category exhibits a statistically significant relationship with exports. Intermediate-goods imports are positively associated with exports in both horizons, while external demand has a positive long-run relationship. The REER generally has the expected negative sign, but its significance is specification dependent. The findings identify insurance as the strongest short-run correlate of exports while showing that its long-run aggregate relationship is sensitive to macroeconomic conditions. Recipient-level data are required to establish causal program effects. Full article

Electrochemical parameter identification is crucial for evaluating the electrochemical processes in proton exchange membrane water electrolysis (PEMWE). Conventional characterization techniques-including polarization-curve fitting, electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and current interruption (CI)-face significant limitations for rapid diagnostics under high-current dynamic operation, arising from constraints in instrument current rating, measurement time, zero-current control, and noise amplification in numerical differentiation. In this study, we present a simple current step (CS) method to accurately identify key electrochemical parameters and perform overpotential breakdown by using a simplified equivalent circuit model with a current source. To address the numerical instability in derivative calculation caused by sampling noise during voltage transient analysis, a physics-informed neural network (PINN) is introduced to enhance signal smoothness while guaranteeing physical consist ency. Compared with standard characterization, the proposed CS-PINN method demonstrates high accuracy, with an error of less than 2% in overpotential breakdown, less than 5.3% in ohmic resistance, and 2.8% in the Tafel slope (at 5 A/cm²). These results confirm that the CS-PINN method provides a fast, accurate, and equipment-friendly route for rapid electrochemical parameter identification in PEMWE. Full article

Small-scale and urban indoor farms typically rely on manual observation, which delays stress detection and yields inconsistent crop quality. While large language models (LLMs) and retrieval-augmented generation (RAG) have been explored for agricultural advisory systems, their integration into a single cloud-free indoor-farming platform that couples multimodal symptom interpretation with autonomous environmental control remains largely unexamined. This study presents an integrated platform built around an agentic AI advisory pipeline that runs entirely on-device on commodity hardware. The pipeline couples a RAG-grounded Mistral 7B language model with a LLaVA 7B vision-language model through condition-based routing, intent classification, multi-step reasoning, and an LLM validation gate, delivering context-aware text and image-based symptom-level guidance from a conversational interface. The advisory layer operates alongside vision-based plant monitoring and a deliberately isolated threshold-based control layer, in which an ESP32 microcontroller autonomously actuates irrigation and lighting against predefined thresholds while a Raspberry Pi 5 performs continuous plant detection and browning monitoring. On Cos lettuce, the advisory pipeline achieved 82.00% weighted accuracy across 50 queries spanning health, symptom, watering, pest, root-health, and growth-stage categories, scored against established plant pathology and postharvest references, with no incorrect responses recorded. The study contributes the design of an agentic advisory pipeline and its integration into a working, cloud-free indoor-farming platform, providing an on-device foundation for intelligent small-scale farming. Full article

Promoting morality among youth is an important educational priority in Thailand’s Southern Border Provinces. However, few culturally grounded learning interventions based on the Sufficiency Economy Philosophy have been systematically developed and evaluated. This study aimed to develop and preliminarily evaluate the Digital Learning Innovation for Strengthening Society (DLISS), a culturally grounded learning intervention designed to promote self-reported morality among youth. A four-phase research and development design was employed, including needs assessment, intervention and instrument development, preliminary field implementation, and post-implementation expert appraisal. Self-reported morality was assessed using the Sufficiency Economy Moral Scale (SEMS), which underwent psychometric evaluation with 1640 youth. Preliminary implementation involved 22 youth leaders assessed at pretest, immediate posttest, and post-reinforcement assessment. The SEMS demonstrated satisfactory psychometric properties. Participants showed statistically significant within-participant changes in the five measured dimensions of self-reported morality across the three assessment occasions. Experts rated the DLISS model favorably for its appropriateness, feasibility, utility, and contextual relevance. The DLISS model represents a promising culturally grounded learning intervention for promoting self-reported morality among youth. The findings provide preliminary evidence supporting further evaluation using larger samples and controlled research designs. Full article

This paper presents the metrological characterization of low-cost sensors integrated into a multi-sensor system for Indoor Environmental Quality monitoring, developed within the MIRABLE project. The analysis focuses on two domains: the thermal domain, using Sensirion SHT45 and SEN55 temperature sensors; and the Indoor Air Quality (IAQ) domain, using an Infineon photoacoustic spectroscopy (PAS)-based sensor for carbon dioxide (CO₂). All tests were conducted under controlled laboratory conditions using calibrated reference instruments. In the thermal domain, the influence of sensor integration within the device case was investigated at temperature (T) between 15 °C and 35 °C and relative humidities (RH) between 30 %rh and 60 %rh. The results revealed self-heating effects in the desk unit, causing temperature biases of up to 0.6 °C. In the IAQ domain, the repeatability and the impact of T and RH on CO₂ measurements were evaluated. T was identified as the main influencing factor; whereas, RH had a negligible effect. These results were supported by statistical analysis ANOVA. A correction strategy based on concentration intervals is proposed for operation between 15 °C and 25 °C, with an expanded uncertainty (k = 2) of (3.26–6.42) ppm for the with-case configuration. These results support the reliable use of the MIRABLE system. Full article

We examined the relationships between self-directed learning skills, university belonging, and student engagement in open online and distance learning environments within the framework of Self-Determination Theory. The research was conducted using a correlational survey model. Data were collected from 696 university students enrolled at a large-scale open, online and distance learning institution in Türkiye. We used three instruments measuring self-directed learning skills, university belonging, and student engagement. The data were analyzed using partial least squares structural equation modeling. The findings indicate that university belonging significantly and positively predicts all dimensions of student engagement. While self-control skills, learning skills, and sustaining the desire to learn significantly explain university belonging, metacognitive awareness and ability to identify sources were found to have no significant effect. Furthermore, it was found that university belonging acts as a significant mechanism in the relationships between self-control skills, learning skills, and sustaining the desire to learn, and student engagement. In this open and distance learning context, student engagement was not explained by individual learning skills alone. University belonging may therefore be one mechanism that partly accounts for the association between self-directed learning and academic participation. The study contributes by testing self-directed learning at the level of its dimensions, by identifying university belonging as a mechanism that partly accounts for its association with engagement, and by situating this model in a large-scale open and distance learning setting. Full article

To address the limited cooling range of ventilation in deep, high-temperature development headings and the lack of coordinated design between coil-based cooling and the ventilation system, this study proposes a coupled “twin-forcing–coil” cooling scheme. Building on conventional overlap (forcing–exhausting) ventilation, a rear-mounted second forcing duct is added to the conventional overlap (force–exhaust combined) auxiliary ventilation system, forming a dual-duct forcing, single-exhausting configuration—hereafter termed the “twin-forcing–single-exhausting” (TFSE) system—that provides a booster (relay) air supply to mitigate the along-path attenuation of cooling capacity and the short-circuiting of cold air; an in situ heat-exchange coil wall further provides supplementary cooling where ventilation-based temperature control weakens. Using a development heading at the 790 m level of a metal mine in Yunnan as the engineering background, a three-dimensional numerical model coupling the roadway, ventilation system, and coil wall was established and validated against nine field monitoring points, showing average relative errors of approximately 1% for temperature and 2–3% for humidity, comparable to the measurement uncertainty of the field instrumentation. Because the numerical model does not account for evaporative and condensation phase-change processes, two supplementary development headings with standing water at the face were used for validation; results showed that model error increases with water accumulation and heading length, indicating the model’s applicability is limited to conditions with intact surrounding rock and minimal seepage. Six operating cases were designed with duct placement and coil spacing as variables. Results show that single-duct ventilation cooling decays markedly beyond 30 m from the face, whereas twin-forcing booster (relay) air supply effectively extends the cooling range, reducing the 30–70 m section temperature by 2.7–2.9 K; the second duct should be positioned where the first duct’s cooling capacity begins to attenuate but is not yet depleted. Based on only two spacing configurations tested (10 m and 15 m), coil-staggered spacing showed limited effect on cooling performance under the field conditions examined; this preliminary finding requires validation across a broader range of spacings. Among the chilled-water conditions tested, an inlet temperature of 280.65 K and a flow velocity of 0.5 m/s offered a reasonable trade-off between cooling uniformity and economic efficiency. Under the boundary conditions and equipment parameters of this case, energy consumption estimates further indicate that the cooling effect per unit electricity consumption of twin-forcing ventilation is roughly 6–8 times that of coil-based cooling, primarily due to pumping losses over the ~240 m chilled-water delivery distance. This energy penalty indicates that coil-based cooling is better suited as a localized, short-distance supplementary measure rather than as a means of extending the cooling range over long distances. Full article

This study presents an electrothermal coating approach for synthesizing cell-imprinted polymers (CIPs) on metallic microwires through localized resistive heating-induced polymerization. Imprinted polymers (IPs) are robust, cost-effective synthetic affinity materials widely used in sensing applications. However, conventional fabrication methods, including bulk and suspension polymerization, often lack spatial control, producing non-specific polymerization, heterogeneous coatings, and reduced sensor reproducibility. Electrochemical polymerization provides improved spatial control but requires specialized instrumentation and restricts monomer selection. Here, applying direct current (DC) to metallic microwires immersed in a prepolymer solution generated localized Joule heating, enabling controlled in situ polymerization and uniform coatings while minimizing undesired bulk polymerization. By optimizing the applied current and polymerization time, CIP coatings with tunable thicknesses were fabricated on gold-coated microwires. Under optimized conditions, ~6 µm thick coatings were imprinted using Salmonella templates. Scanning electron microscopy revealed bacteria-shaped cavities consistent with template removal and the formation of imprinted cavities. Rebinding experiments demonstrated enhanced bacterial capture, with CIP-coated microwires achieving ~70% capture efficiency, compared to 22% for bare microwires and 33% for non-imprinted polymer (NIP) controls. These results support the effectiveness of the proposed method for localized polymerization and demonstrate the enhanced capture of the template species by CIP-coated microwires relative to bare microwires and NIP-coated controls. Full article

Vibrations occurring when playing a musical instrument can affect how the quality of the instrument is perceived by the player. Previous studies on violins have investigated how vibrotactile feedback influences certain perceptual attributes and the perceived quality or preference of the instruments. These studies have found that, in addition to auditory feedback, vibrotactile feedback had an important influence on the corresponding ratings. In these studies, however, to control the vibrotactile feedback independently from the auditory feedback was only possible to a limited extent, or not at all. To overcome this limitation, the present study introduces a concept for the creation of a violin-like instrument on which both vibrotactile and auditory feedback can be controlled individually. To apply this concept, the feedback that the instrument exposes by itself to the player is required to be as minimal as possible. This keeps interference with the intended feedback to a minimum. It was decided to use an electric violin as the basis, as the usual absence of a hollow body being the most important airborne excitation source meets this requirement in the auditory domain already quite well. In the vibrotactile domain, however, meeting this requirement is more challenging, as most of the structure-borne excitation sources persist. Therefore, the present study investigated the vibrotactile feedback of electric violins. Two setups for measuring the vibrotactile feedback exposed to the player at the neck of a violin are presented. One setup was intended to ensure high reproducibility while the other one was intended to resemble real playing scenarios more closely. Using these two setups, measurements were carried out for a set of six electric violins. The results were discussed regarding physical and perceptual aspects. Finally, one electric violin was selected for the creation of a violin-like instrument with independently controllable auditory and vibrotactile feedback. Full article

Szechuan pepper pungency is traditionally assessed by subjective sensory panels or laboratory instruments, hindering on-site detection. Perceived numbing sensation does not always correspond directly to alkylamide content because multiple electroactive constituents, including polyphenols and sanshools, may contribute to the overall sensory response. Chromatographic methods quantify individual compounds but may not fully reflect integrated human pungency perception. Electrochemical detection bypasses separation, as the voltammetric response integrates oxidative signals from multiple electroactive species. We developed a portable electrochemical system with a custom programmable-gain potentiostat, three-electrode detector, and STM32-controlled software for differential pulse voltammetry (DPV) measurement. Coupled with machine learning, it assessed Zanthoxylum bungeanum (red peppers) and Zanthoxylum schinifolium (green peppers). Fifteen replicate scans from each of 22 origins yielded 330 DPV curves calibrated against general Labeled Magnitude Scale (gLMS) scores from a trained panel. An artificial neural network (ANN) achieved R² = 0.937 for red peppers, while principal component analysis–support vector regression (PCA–SVR) achieved R² = 0.860 for green peppers. Competitive adaptive reweighted sampling (CARS) identified three characteristic potential intervals for each type: 0.17–0.21, 0.57–0.62, and 0.69–0.80 V for red peppers, and 0.24–0.27, 0.56–0.68, and 0.69–0.77 V for green peppers. These intervals indicate that pungency-related electrochemical information is distributed across multiple potential regions. The system shows potential for rapid and objective quality assessment of Szechuan pepper. Full article

Using 1135 customer–supplier–year observations involving Chinese A-share listed firms and their major suppliers from 2011 to 2023, together with prefecture-level government work reports and patent-assignment records, we examine whether environmental policy pressure faced by downstream customers shapes upstream suppliers’ external green technology acquisition. External green technology acquisition is measured as the log-transformed annual number of green patents assigned to each supplier. We find that suppliers acquire more external green patents when their customers face stronger local environmental policy pressure, with a one-standard-deviation increase in policy intensity associated with approximately 5.7% higher external green patent acquisition. The result is robust to placebo tests, alternative measures, and PPML estimation, while instrumental-variable estimates point in the same direction. Further analyses document stronger customer green-transition urgency and supplier-perceived supply-chain uncertainty under greater downstream policy intensity, and they show that the relationship is stronger among suppliers with weaker bargaining power or lower R&D intensity. Environment-related policy intensity is more strongly associated with end-of-pipe technology acquisition, whereas energy-transition and market-incentive policy intensity are more strongly associated with source-control technology acquisition. Overall, the findings indicate that environmental policy intensity in downstream customers’ cities is associated with upstream suppliers’ external green technology acquisition within observed customer–supplier relationships. Full article

Laboratory friction measurements are central to material screening for High-Friction Surface Treatments (HFST), yet metrological aspects including a proposed metrological traceability framework or uncertainty, and reproducibility are consistently underreported. This study applies a metrology-aligned framework to British Pendulum Tester (BPT) measurements performed in three states: dry, wet (water), and water–soap to assess operational adhesion and hysteresis components, document traceability to the International System of Units (SI), and report GUM-style uncertainty with covariance for the adhesion difference. Measurements were obtained for calcined bauxite (CB) and rhyolite (Rhy) in HFST and Coarse gradations across seven polishing protocols (baseline; LAA-1000/2000; MDA-105/180; PSV-10 h/20 h), using n = 3 replicates per Treatment × Material × State. Replicate-based Type A uncertainties were combined with instrument/system Type B components geometry, slider hardness, temperature, soap film consistency, and calibration to yield combined u_c and expanded uncertainty U_(k=2). The Wet–Soap cross treatment physical correlation ellipses demonstrate strong positive correlations (r ≈ 0.88–0.98; p < 0.001) between wet and soap states, supporting the interpretation that wet friction is governed primarily by hysteresis, with adhesion acting as a small offset under BPT kinematics. The slider hardness and temperature typically control the wet state uncertainty budget; including measured Wet–Soap covariance reduces adhesion U_(k=2) by up to ~6.5%, consistent with GUM’s law of uncertainty propagation. Together, these measurement science practices enhance road safety by making laboratory friction data traceable, comparable, and decision-ready. Full article

China’s transition toward a low-carbon and sustainable energy system requires renewable energy firms to align their technological decisions with environmental policy objectives. Drawing on the Porter hypothesis, this study examines how command-and-control, market-incentive, and voluntary environmental regulations influence firms’ utilization of three sustainable energy technologies (SETs): renewable electricity, energy-saving technologies, and waste management. It also assesses how these technological practices contribute to firm competitiveness. Survey data collected from 273 renewable energy firms in China’s hydropower, wind, and solar sectors were analyzed using partial least squares structural equation modelling. The results show that command-and-control and voluntary environmental regulations positively influence all three SET dimensions. Market-incentive environmental regulation positively affects energy-saving technologies and waste management but has no significant effect on renewable electricity utilization. Renewable electricity, energy-saving technologies, and waste management all positively contribute to firm competitiveness. These findings provide conditional support for the strong Porter hypothesis by demonstrating that technological responses that can improve firms’ competitiveness depend on the alignment between the regulatory instrument employed and the technology targeted. This study provides firm-level evidence for designing differentiated regulatory strategies that support both China’s decarbonization objectives and the competitiveness of renewable energy firms. Full article

Diabetes mellitus represents a growing global health challenge, establishing oral antidiabetic drugs as a therapeutic class of paramount importance. Consequently, to ensure drug safety, therapeutic efficacy, and accurate therapeutic drug monitoring, robust, selective and highly reproducible analytical methods are indispensable. This review provides a comprehensive overview of instrumental analytical techniques developed between 1985 and 2026 for quantifying oral antidiabetic agents. Based on a literature search across major databases—including PubMed, ScienceDirect and Springer—we systematically evaluated the application of UV-VIS spectrophotometry, liquid chromatography, and advanced electroanalytical methods. The reviewed literature encompasses methodologies ranging from routine quality control of bulk powders and pharmaceutical formulations to complex bioanalytical and pharmacokinetic applications. Liquid chromatography–tandem mass spectrometry (LC-MS/MS) emerged as the gold standard for precise bioanalysis due to its superior selectivity and sensitivity in complex biological matrices. Conversely, UV-VIS spectrophotometry and electrochemical methods remain highly relevant for cost-effective routine quality control in industrial manufacturing. Methodologies are categorized by drug therapeutic class, including biguanides, sulfonylureas, DPP-4 inhibitors, SGLT2 inhibitors, meglitinides, highlighting key validation parameters such as linearity, accuracy, and limits of detection. Finally, this review outlines future directions in the field of antidiabetic drug quantification. Full article