Search Results (2,827)

Leaks in pipe systems result in significant economic losses, environmental hazards, and public health risks. Transient-based leak detection methods, which exploit the dynamics of pressure waves in response to system anomalies, have emerged as efficient techniques for identifying and characterizing leaks in pressurized pipelines. These methods offer distinct advantages, including minimal data requirements, high sensitivity to low-pressure anomalies, and resilience to the ill-posed conditions often affecting steady-state models. This paper reviews transient-based leak detection, synthesizing findings from over 139 peer-reviewed publications spanning the past three decades. The review categorizes transient-based methods into transient damping, transient reflection, system response, and inverse transient methods, analyzing the prevalence, evolution, and research rate of each category over time. By structuring the review around key aspects such as simulation domain type, analysis approach, system response, solver strategies, adaptability to noise, viscoelasticity, and network complexity, this paper identifies significant trends and shifts in research focus. A comprehensive tabular dataset of 139 studies captures how research activity in various areas has accelerated, slowed, or reached stability, offering insights into the evolving priorities within the field. This review highlights areas for further development, particularly in addressing AI-enhanced applications, transient excitation and measurement sites design, noise resilience, comprehensive leak characterization, validation approaches, and scalability for complex network applications, providing a resource to guide future research in transient-based leak detection. Full article

Inductors are critical components in power electronic systems, yet their thermal behavior is often approximated using simplified lumped models that neglect internal gradients and transient spatial effects. This paper presents a benchmarking study of analytical thermal modeling approaches for cylindrical inductors, including 0D lumped, 1D radial, and 2D radial–axial transient formulations. Starting from the general heat conduction equation in cylindrical coordinates, closed-form or semi-analytical solutions are discussed under uniform internal heat generation and convective boundary conditions. The proposed framework provides a benchmark-oriented analytical reference for selecting the appropriate thermal model complexity in reliability-oriented design of inductive components in power electronic systems. The models are applied to a representative two-layer cylindrical inductor composed of a ferrite core and a copper winding, under identical loss and cooling assumptions, considering two axial lengths in order to assess geometric influence. Steady-state temperature levels, transient responses, modal time constants, and axial gradient indicators are extracted to quantify the differences among modeling levels. The results show that the dominant thermal behavior is governed by a single slow mode with a time constant on the order of one hour. The spatially averaged temperature predicted by the 0D model deviates by less than 2.5% from the 2D solution in steady-state conditions, with the 1D model providing accurate predictions when axial gradients remain weak. Full article

Bone tissue plays a vital role in the human body and possesses intrinsic self-repair mechanisms; however, large defects or pathological fractures may exceed its natural healing capacity. Bone tissue engineering provides promising strategies to restore bone integrity through the use of scaffolds, growth factors, and stem cells. While calcium phosphate (CaP)-based ceramics, such as hydroxyapatite (HAp) and tricalcium phosphate (TCP), represent the current benchmark, their limitations, including slow degradation (HAp) and limited osteoinductivity (TCP), have driven the development of alternative biomaterials. In this context, magnesium phosphate (MgP)-based materials have gained increasing attention due to their tunable resorption rate, improved biodegradability, and ability to stimulate osteogenesis and angiogenesis through the release of magnesium (Mg²⁺) ions. This study reports on composite scaffolds based on electrospun poly(ε-caprolactone) (PCL) fibres coated with MgP layers doped with lithium (Li) and zinc (Zn), designed to mimic the nanofibrous architecture of the extracellular matrix. Lithium and zinc were selected due to their known ability to modulate cellular response, with lithium promoting osteogenic activity and zinc contributing to improved cell proliferation and antibacterial potential. The phosphate phases obtained by coprecipitation were deposited onto the PCL fibres using Matrix-Assisted Pulsed Laser Evaporation (MAPLE), enabling controlled surface functionalization. Following thermal treatment, the formation of the crystalline magnesium pyrophosphate (Mg₂P₂O₇) phase was confirmed by chemical and structural characterization. The combination of a slowly degrading PCL matrix, providing sustained structural support, and a bioactive MgP coating, enabling rapid and controlled ion release, results in improved scaffold performance in terms of biocompatibility, biodegradability, and bioactivity. While the slow degradation rate of PCL ensures mechanical stability over an extended period, the surface-deposited MgP phase allows immediate interaction with the biological environment, facilitating faster ion release and enhancing cell–material interactions. These findings highlight the potential of the developed composites as promising candidates for trabecular bone regeneration and as viable alternatives to conventional CaP-based scaffolds in regenerative medicine. Full article

Urban residents require space-efficient interventions to mitigate chronic stress. While indoor digital nature shows promise, the precise impact of interactive design parameters remains unclear. This study investigated how interactive feedback intensity (none, slow, fast) and color hue (neutral, warm, cool) influence psychological and physiological restoration. Following negative emotion induction, healthy participants engaged in within-subject conditions evaluated via multimodal assessments, including EEG, HRV, and subjective scales (PANAS, PRS, SAM/PAD). Results identified interactive feedback intensity as the primary driver of restoration. Specifically, fast feedback improved positive affect by up to 20.4% and reduced negative affect by 20.8% compared to passive self-restoration. Neurologically, interactive engagement was associated with elevated EEG alpha-band activity by up to 97.8% relative to standing controls, a pattern consistent with cortical relaxation. Furthermore, while physical interaction was uniformly associated with physiological indices broadly consistent with recovery, color hue significantly moderated subjective outcomes. Neutral and warm hues generated significantly higher overall perceived restorativeness (M = 73.18 and M = 70.14, respectively) than the self-restoration control (M = 61.26). Notably, neutral tones were uniquely associated with modest changes in HRV time-domain indices suggestive of parasympathetic autonomic modulation. These findings provide actionable, empirically validated guidelines for deploying responsive digital interventions to support mental well-being in dense urban interiors. Full article

Environmental loading is a major driver of nonlinear GNSS vertical displacements, yet its spatiotemporal heterogeneity remains insufficiently understood in regions with complex topography. In this study, we investigate the environmental loading effects on GNSS vertical motions across Southwest China using observations from a network of 66 stations. Singular Spectrum Analysis (SSA) and Empirical Orthogonal Function (EOF) analysis were applied to extract annual signals, while component-wise RMS reduction quantified hydrological and atmospheric loading contributions. Spatial statistical analysis, cross-wavelet transform, and k-means clustering examined correlation patterns and phase hysteresis between GNSS observations and modeled loads. Results show that hydrological loading dominates seasonal vertical oscillations, but crustal responses exhibit pronounced spatial heterogeneity controlled by regional topography and hydro-climatic gradients. EOF analysis reveals a dipole pattern induced by the Hengduan Mountains’moisture-blocking effect. Atmospheric loading anomalously dominates the eastern Sichuan Basin, whereas Yunnan displays strong amplitudes with high heterogeneity due to karst hydrogeology. Phase analysis identifies three distinct regimes: a rapid elastic response on the Tibetan Plateau, (with the lag of ~20 ± 5 days, correlation coefficient R ≈ 0.65), intermediate delays in Yunnan (~60 ± 5 days, R ≈ 0.58), and pronounced hysteresis in the Sichuan Basin (~105 ± 5 days, R ≈ 0.38) linked to slow groundwater diffusion and poroelastic processes. These findings highlight the critical role of local hydrogeological dynamics in modulating GNSS vertical deformation and provide new insights for improving environmental loading corrections in complex mountainous regions. Full article

Biomass pyrolysis has emerged as a flexible platform for converting low-value residues into higher-value energy carriers (bio-oil, biochar and gas) and carbon-rich materials, with realistic potential for negative emissions when biochar is deployed in long-lived sinks. Over the last decade, three developments have driven the field forward: first, a finer mechanistic understanding of devolatilization and secondary reactions; second, major improvements in analytical techniques for characterising feedstocks and products; and third, more rigorous techno-economic and life-cycle assessments that place pyrolysis in a broader energy-system context. Recent experimental work on forestry and agro-industrial residues has clarified how biomass composition, ash chemistry and operating conditions jointly govern product yields, energy content and stability. Parallel advances in GC×GC–MS, high-resolution mass spectrometry, NMR and thermogravimetric methods have shifted the discussion from bulk “bio-oil” and “char” to families of molecules and well-defined structural domains, which can be deliberately targeted by reactor and catalyst design. Data-driven models, ranging from support vector machines applied to TGA curves to ANFIS and random forests for yield prediction, are now accurate enough to support process screening and multi-objective optimisation. At the system level, commercial fast pyrolysis biorefineries report overall useful energy efficiencies on the order of 80–86%, while slow pyrolysis configurations centred on biochar can be economically viable when carbon storage and co-products are appropriately valued. Thermodynamic analyses confirm that indirect gasification via fast-pyrolysis oil sacrifices some energy and exergy efficiency relative to direct solid-biomass gasification but may offer logistical and integration advantages. This review synthesises recent work on (i) feedstock and process characterisation; (ii) state-of-the-art analytical methods for bio-oil, biochar and gas; (iii) modelling and machine-learning tools; and (iv) energy-system deployment of pyrolysis products. Throughout, the emphasis is on how characterisation and modelling inform concrete design choices and on the trade-offs that arise when pyrolysis is considered as part of a wider decarbonisation portfolio. By integrating laboratory-scale characterisation with system-level modelling, this review aligns biomass pyrolysis with several United Nations Sustainable Development Goals (SDGs). The optimisation of thermochemical conversion pathways for forestry and agro-industrial residues directly supports SDG 7 (Affordable and Clean Energy) by enhancing the efficiency of bio-oil and syngas production. Furthermore, the deployment of biochar as a stable carbon sink for negative emissions and soil amendment addresses SDG 13 (Climate Action) and SDG 15 (Life on Land). By converting low-value waste streams into high-value energy carriers and chemicals within a circular bioeconomy framework, the research further contributes to SDG 12 (Responsible Consumption and Production) and SDG 9 (Industry, Innovation and Infrastructure). Full article

Rainfall-induced landslide early warning systems require reliable estimation of soil moisture conditions. This study proposes a Soil Water Index (SWI) framework based on a three-stage TANK model. Through GLUE (Generalized Likelihood Uncertainty Estimation)-based behavioral parameter sampling and K-means clustering, SWI response characteristics were classified into two representative scenarios: slow drainage (Scenario 1) and fast drainage (Scenario 2). Two-stage thresholds—Watch (α = 0.40 × SWI_peak) and Warning (β = 0.70 × SWI_peak)—were established from SWI rise profile analysis at 500 m and 5 km resolutions, providing 20–27 and 4–5 h of lead time, respectively. Verification against the July 2025 heavy rainfall event across multiple resolutions and spatial extents yielded Hit Rates of 0.984–1.000, while FAR (False Alarm Ratio) remained structurally high (0.607–0.648 for grids sharing the rainfall field with occurrence sites). These findings confirm that SWI serves as an effective regional-scale necessary condition indicator for landslide-triggering moisture, but FAR reduction requires integration with slope susceptibility information. Full article

Efficient soil fertility monitoring is essential for sustainable agriculture, food security, and environmental management across Africa, yet conventional laboratory methods remain prohibitively costly and slow for continental-scale applications. Soil spectroscopy is considered as a rapid, non-destructive alternative with transformative potential. This review provides a systematic synthesis of spectroscopic applications across Africa, encompassing laboratory, field, airborne, and satellite-based platforms, while examining major data sources including the Africa Soil Information Service (AfSIS) and GEO-CRADLE spectral libraries. We critically evaluate the evolution of modeling approaches, revealing that Partial Least Squares Regression (PLSR) dominates, but a shift toward advanced frameworks like hybrid physically based models, ensemble learning and deep neural networks is essential. Critically, we identify a pronounced imbalance wherein laboratory spectroscopy prevails while imaging and satellite-based approaches remain comparatively underutilized, despite their unparalleled potential for scaling point measurements to continental extents. The review consolidates findings on key soil properties, demonstrating consistent successes for primary constituents with direct spectral responses (i.e., organic carbon), while revealing relative uncertainty for properties inferred indirectly via covariance (e.g., available phosphorus, potassium). Despite significant local and regional progress, the absence of a standardized pan-African spectral library and the intractable transferability problem remain formidable barriers. Future research must pivot decisively toward imaging spectroscopy and satellite platforms, mitigating PLSR dominance through systematic adoption of ensemble methods, transfer learning, and model harmonization frameworks to fully operationalize these technologies in support of Africa’s sustainable development goals. Full article

Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease in which B-cell dysregulation plays a central pathogenic role beyond autoantibody production. Advances in B-cell biology have led to the development of targeted therapies, including inhibition of the B-cell activating factor (BAFF) pathway. Belimumab, a monoclonal antibody that neutralizes soluble BAFF, modulates B-cell survival signals upstream, promoting progressive immunologic remodeling rather than rapid depletion. This review integrates current knowledge on BAFF-dependent B-cell biology with mechanistic, pharmacokinetic, and clinical data to provide a comprehensive framework for understanding belimumab’s effects in SLE and lupus nephritis (LN). Belimumab preferentially reduces transitional and naïve B cells, while memory B cells show a relative transient increase followed by a gradual return to baseline levels, reflecting redistribution rather than expansion, and long-lived plasma cells are largely unaffected. These effects result in progressive remodeling of B-cell compartment dynamics and contribute to broader modulation of adaptive immune amplification pathways. Pharmacokinetic data support a threshold-based model of BAFF neutralization, with exposure influenced by disease-related factors such as proteinuria in LN. Clinical response is primarily determined by baseline disease biology, with greater benefit observed in patients with serologically active disease and less established organ involvement. Across clinical trials and real-world studies, belimumab reduces disease activity and flares, enables glucocorticoid tapering, and slows organ damage accrual. In LN, it improves renal outcomes and reduces the risk of kidney-related events. Collectively, these findings support belimumab as a disease-modifying therapy in SLE. Further research is needed to refine patient selection and optimize treatment sequencing and combination strategies. Full article

Light-responsive hydrogel-based oscillators typically exhibit small oscillation amplitudes because solvent diffusion is intrinsically slow, and their dependence on external periodic light modulation further results in limited amplitude, poor stability, and insufficient autonomy. Inspired by the trigger and sliding mechanism of the ancient crossbow, this study introduces an innovative system that integrates a sliding-block mechanism with time-delay feedback, breaking from conventional approaches that rely on hydrogel inertia or external modulation, within a purely theoretical and simulation-based framework. By establishing a nonlinear dynamic model coupling solvent diffusion, photoisomerization, and optical attenuation, this research shows through numerical simulations that the system can exhibit two distinct modes under constant illumination: a stable state and a self-sustained oscillatory state. The model predicts that the oscillation frequency can be flexibly tuned by varying key parameters, including the crosslinking density, Flory–Huggins interaction parameters of the spiropyran and hydrophilic polymer, ring-opening reaction rate, light intensity, fraction of light-sensitive molecules, and sliding displacement, whereas the initial absorption coefficient has only a minor influence. The slider displacement is also identified as an effective means to regulate the oscillation amplitude. Furthermore, the expansion force at the container bottom is predicted to oscillate synchronously with the hydrogel’s volume change. This theoretical framework represents a paradigm shift from “static small deformation” to “dynamic large-amplitude oscillation”, significantly enhancing the mechanical responsiveness of the material. This work provides a novel and controllable strategy for the conceptual design of autonomous light-driven micromechanical systems. Full article

Optogenetic modulation employs light-sensitive proteins known as opsins to regulate cellular activity. A unique therapeutic application of this technique involves modulating pain perception by selectively targeting neural pathways within the spinal cord. Multi-Characteristic Opsin (MCO) represents an innovative optogenetic actuator capable of activation across a broad spectrum of light wavelengths, exhibiting a slow depolarizing phase that resembles natural photoreceptors. This study examines the current advancements in spinal optogenetic modulation utilizing MCO for pain management. Due to its high sensitivity, MCO facilitates minimally invasive, remotely controlled optogenetic modulation of spinal neurons. This approach enables the regulation of extensive spatial regions, provided the MCO channel receives sufficient light intensity to surpass the activation threshold. Nano-enhanced optical delivery (NOD) successfully transfected spinal neurons with the GAD67-MCO2-mCherry construct, as confirmed by membrane-localized mCherry fluorescence with DAPI-labeled nuclei. Using this platform, 5 Hz spinal optogenetic stimulation produced a significant reduction in formalin-evoked pain behaviors, demonstrating frequency-specific modulation of spinal pain circuits. Neither 2 Hz nor 10 Hz stimulation yielded comparable analgesic effects, underscoring the importance of precise stimulation parameters. The therapeutic impact also depended on transfection efficiency: reducing the fGNR–plasmid concentration diminished MCO expression and weakened the analgesic response. Together, these results show that effective spinal optogenetic pain modulation requires both optimal stimulation frequency and robust gene delivery. Full article

Urban infrastructure works conducted under live traffic conditions often face a persistent gap between approved traffic management plans and their actual field implementation. This gap remains underexplored in longitudinal studies, particularly in utility projects from low- and middle-income urban contexts. This study evaluates a risk-based supervisory approach that integrates daily monitoring of the Traffic Management Plan (TMP) with a corporate risk management framework aligned with ISO 31000. The dataset includes 288 supervised workdays over 16 months (November 2023–February 2025), 99 non-conformity tickets, 96 signal-theft events (137 units), and seven traffic incidents. The analysis combines descriptive statistics, hypothesis testing, logistic regression, segmented longitudinal analysis, count models, response-time evaluation, and a composite risk index. TMP non-compliance decreased from 18.8% to 6.9% between the first and second halves of the study period ($p=0.0028$). The odds of non-compliance were significantly higher during the staff transition period in April–May 2024 (OR = 3.50; 95% CI: 1.24–9.82), while day and night shifts showed comparable rates. Monthly patterns indicate that staff instability and signal theft contributed to non-compliance levels, and ticket resolution remained slow (mean response time: 69.9 days). These findings highlight the importance of supervisory continuity, contractor stability, and timely corrective actions in improving work zone safety. Full article

The geological environment of southeastern Tibet is characterized by complex tectonics and high climatic sensitivity, and giant accumulation landslides pose significant threats to infrastructure and human safety. This study investigates the Pangcun giant accumulation landslide using SBAS-InSAR (2017–2024), UAV photogrammetry, field investigations, and wavelet coherence analysis to examine its deformation and driving mechanisms. The landslide exhibits continuous, slow deformation with clear spatial heterogeneity, divided into two zones, with the largest displacement occurring in the middle of Zone B. Field evidence is consistent with the InSAR results. Wavelet coherence analysis reveals a lagged response of displacement to precipitation at a timescale of about three months. The landslide’s evolution is controlled by unfavorable topography and fragmented materials, with precipitation as the primary trigger. Human activities (agricultural irrigation and slope-toe road excavation) and seismic disturbances also contribute to its progressive development. Full article

Background/Objectives: Elevated central adiposity (ECA) in childhood is associated with early cardiometabolic risk and hemodynamic alterations. However, evidence in Spanish schoolchildren regarding the relationship between eating behavior traits and central adiposity is limited, particularly across developmental stages. This study aimed to examine the association between Children’s Eating Behaviour Questionnaire (CEBQ) subscales and ECA, and to explore potential differences by age group. Methods: A cross-sectional study was conducted in 496 rural schoolchildren aged 6–15 years. ECA was defined using the waist-to-height ratio (WHtR) and sex-specific cut-offs validated for the Spanish pediatric population. Eating behavior was assessed with the CEBQ (Z-scores), and diet quality was measured using the KIDMED index. Multivariable logistic regression models were adjusted for sex, KIDMED score, and maternal education. Analyses were subsequently stratified by age (6–9 and 10–15 years). Results: The prevalence of ECA was 45.90%. In fully adjusted models, higher Food Responsiveness (FR) was associated with increased odds of ECA, while Satiety Responsiveness (SR) acted as a protective factor; sex also showed an independent association. After stratification, sex remained the only significant predictor in children aged 6–9 years. Among those aged 10–15 years, FR was significantly associated with ECA (p = 0.008), while Slowness in Eating (SE) showed a borderline positive association in the adjusted model (p = 0.049) and was therefore interpreted cautiously. SR and Emotional Undereating (EU) showed protective trends near significance (p = 0.081 and p = 0.082, respectively). Conclusions: The association between eating behavior traits and ECA varies by age. In older children, FR showed a robust association with ECA, whereas no behavioral predictors were observed in younger children. The protective role of SR in the global model and the emergence of behavioral predictors in older participants highlight the importance of targeted interventions during late childhood. Full article

Permanent magnet synchronous motors (PMSMs) are widely used in agricultural unmanned aerial vehicle (UAV) electromechanical systems for their high efficiency and power density. While sliding mode control (SMC) offers robustness for PMSM drives, conventional designs face challenges like slow convergence, singularity, and chattering. This paper proposes a model-free improved non-singular fast terminal SMC scheme with an improved adaptive super-twisting algorithm and a disturbance observer (MFINFTSMC-IADSTA-IFTSMO) for agricultural UAV applications. The designed sliding surface ensures fixed-time convergence without singularity, the adaptive reaching law reduces chattering, and the observer enables feedforward compensation of disturbances. Closed-loop stability is proven via Lyapunov theory. DSP-based experiments demonstrate that the proposed method outperforms existing SMC variants in dynamic response, steady-state accuracy, chattering suppression, and disturbance rejection. Specifically, the proposed method achieves a start-up convergence time of only 0.35 s, which is 56.25% shorter than that of the classic SMC-STA method, fully verifying its superior fast convergence performance. Full article