Search Results (17,253)

Fall detection systems are a critical application of human pose estimation, frequently struggle with achieving real-world robustness due to their reliance on domain-specific datasets and a limited capacity for generalization to novel conditions. Models trained on controlled, canonical camera views often fail when subjects are viewed from new perspectives or are partially occluded, resulting in missed detections or false positives. This study tackles these limitations by proposing the Viewpoint Invariant Robust Aggregation Graph Convolutional Network (VIRA-GCN), an adaptation of the Richly Activated GCN for fall detection. The VIRA-GCN introduces a novel dual-strategy solution: a synthetic viewpoint generation process to augment training data and an efficient inference-time aggregation method to form consensus-based predictions. We demonstrate that augmenting the Le2i dataset with simulated rotations and occlusions allows a standard pose estimation model to achieve a significant increase in its fall detection capabilities. The VIRA-GCN achieved 99.81% accuracy on the Le2i dataset, confirming its enhanced robustness. Furthermore, the model is suitable for low-resource deployment, utilizing only 4.06 M parameters and achieving a real-time inference latency of 7.50 ms. This work presents a practical and efficient solution for developing a single-camera fall detection system robust to viewpoint variations, and introduces a reusable mapping function to convert Kinect data to the MMPose format, ensuring consistent comparison with state-of-the-art models. Full article

Background: Parent education is a key component of family-centred care in neonatal intensive care units (NICUs). It supports positive parent-infant interactions, reduces parental stress and anxiety, and contributes to shorter hospital stays. Objectives: This paper reports on the adaptation of a South African parenting education intervention for parents of premature infants in the NICU: the NeuroSense PremmieEd programme. The study aimed to demonstrate the programme’s content validity, feasibility, and acceptability for preterm parent–infant dyads in public hospital NICUs, using a hybrid focus group discussion (FGD) method. The programme was based on an existing intervention and informed by literature on the components of parenting educational programmes and empirical data on parental expectations. Methods: A qualitative, iterative refinement process was undertaken using hybrid-format FGDs. A conceptual FGD was held during the design phase, followed by two consensus FGDs after pilot testing (reported separately). Stakeholders included end-users (mothers), clinicians, an instructional designer, a neurodevelopmental care expert, and programme facilitators. Results: The first FGD reviewed draft version 0.1 of the programme, confirming content relevance and clarity, while recommending adjustments, such as module integration, cultural and language alignment, and visual aids to support comprehension. Version 0.2 was then ready for pilot testing (reported elsewhere). The second and third FGDs led to refinements addressing emotional sensitivity in terminology, improved layout and readability, and the addition of home care guidance. Stakeholders highlighted the potential use of low-cost digital formats to enhance accessibility and standardisation. These revisions informed the final version 0.3. Conclusions: The hybrid FGD approach enabled input from diverse and geographically dispersed stakeholders. The NeuroSense PremmieEd programme was found to be feasible and acceptable by both mothers and healthcare professionals, supporting its suitability for broader implementation in resource-constrained settings. Full article

Tar-rich coal (with a tar yield ≥ 7%), as a special coal-based oil and gas resource, is of great significance for ensuring national energy security and promoting the clean conversion of coal. The selection of suitable geological sites represents a core challenge for the safe and efficient application of its in situ pyrolysis technology. Focusing on the tar-rich coal seams in the Santanghu Basin, this study constructed a comprehensive geological evaluation system for site selection by integrating numerical simulation, data mining, and laboratory experiments. The Analytic Hierarchy Process (AHP) and a fuzzy comprehensive evaluation method were employed to achieve a quantitative assessment and identify favorable areas within the study region. The results indicate that resource scale, coal seam conditions, and the properties of the roof and floor strata are the key controlling factors. One optimally comprehensive Class I favorable area (Tiao IV block) was successfully identified. This block exhibits a large resource scale, favorable coal seam conditions, a high tar yield, excellent geological sealing, and superior engineering compatibility, making it the recommended priority target for pilot testing. The evaluation system developed in this study can provide a theoretical basis and technical reference for the geological site selection of in situ pyrolysis of tar-rich coal in similar mining areas and advance its industrialization. Full article

Resilience through urban planning has gained prominence since the adoption of the Sendai Framework for Disaster Risk Reduction (2015–2030), particularly in regions exposed to multiple natural hazards. This study examines how six Western Mediterranean countries—Spain, France, Italy, Tunisia, Algeria, and Morocco—address disaster risk prevention through urban and spatial planning. Although these countries share a similar geodynamic and climatic context, their approaches to integrating hazard prevention into planning frameworks vary significantly due to institutional, technical, and legal factors. Special attention is given to the case of Morocco, where delays in hazard integration are evident, particularly in the Maghreb region. Limited access to historical data, weak inter-agency coordination, and insufficient scientific capacity hinder effective planning. In response, Morocco has developed the Urbanization Suitability Map (USM) program, a non-binding planning tool inspired by the French Natural Risk Prevention Plan (PPRN). The USM tool overlays hazard information to guide land use decisions and mitigate risks such as floods, landslides, and seismic activity. Using a qualitative comparative analysis of regulatory texts, national planning strategies, and mapping instruments, this study identifies contrasting levels of disaster risk reduction integration across the six countries. The Moroccan USM initiative stands out as a pragmatic response to governance gaps and offers a transferable model for other countries with similar constraints. The findings underscore the need for clearer legislation, improved data systems, and multi-level coordination to enhance urban resilience. Recommendations are provided to strengthen hazard-informed planning practices and support more adaptive and sustainable land management in risk-prone areas. Full article

Gold (Au) and silver (Ag) nanoparticles (NPs) are used for drug transport and plant protection due to their insoluble nature and unique properties. To produce health-friendly NPs, toxic solvents should be replaced with plant-based synthesis. Plants, such as alfalfa (Medicago sativa L.), release biomolecules that reduce metal ions and form nanoclusters without free radicals, showing anti-inflammatory and antioxidant properties. In this study, callus cultures of two M. sativa genotypes, ‘Kometa’ and ‘La Bella Campagnola’, were exposed to two precursors (AgNO₃ and HAuCl₄) for 24 and 48 h to assess the feasibility of biological NP synthesis. Spectrophotometry showed significant (p ≤ 0.05) changes in light absorbance compared with the control. Dynamic light scattering and zeta potential measurements indicated a change in the composition of the liquid compared with the control. To improve image quality and obtain more accurate data, transmission electron microscopy (TEM) analysis was repeated, confirming the presence of quasi-spherical nanoparticles with diameters in the range of 5–25 nm for both AuNPs and AgNPs in the callus culture extracts of both genotypes. Nanoparticle Tracking Analysis demonstrated that the AgNPs and AuNPs from both genotypes displayed polydisperse size distributions, with a mean particle size ranging from 220 to 243 nm. Elemental analysis provided clear evidence that Ag and Au were present only in treated samples, confirming effective NP biosynthesis and excluding contamination. X-ray diffraction (XRD) analysis was performed to characterise the crystalline structure; however, due to the very small particle size (5–25 nm), no clear diffraction patterns could be obtained, as nanocrystals below ~20–30 nm typically produce signals below the detection limit of standard XRD instrumentation. The novelty of this research is the cost-effective, rapid biosynthesis of quasi-spherical AuNPs and AgNPs with diverse sizes and enhanced properties, making them more eco-friendly, less toxic, and suitable for antibacterial and anticancer studies. Full article

This study evaluated the decadal trends and spatial distribution of four irrigation suitability indices—Electrical Conductivity (EC), Sodium Adsorption Ratio (SAR), Magnesium Hazard (MH), and Kelley’s Ratio (KR)—using agricultural groundwater data collected from 157 monitoring sites across Korea between 2015 and 2024. Internationally recognized classification criteria were applied, long-term trends were analyzed using the Mann–Kendall test and Sen’s slope estimator, and spatial distributions for 2015, 2020, and 2024 were visualized using Inverse Distance Weighting (IDW). The results showed that EC and SAR remained at generally low absolute levels but exhibited statistically significant increasing trends with Sen’s slopes of +0.0038 and +0.0053/year, respectively, indicating the necessity of long-term salinization management. KR remained largely stable throughout the study period. In contrast, MH displayed a distinct pattern, with unsuitable levels concentrated in Jeju Island—approximately 15% of monitoring sites were classified as unsuitable for irrigation. This was interpreted as the combined effect of the basaltic aquifer’s geological and hydrological characteristics, seawater intrusion, and the relatively high mobility of Mg compared with Ca. This study uniquely integrates temporal trend tests with spatial mapping at a national scale and offers a mechanistic interpretation of MH vulnerability in Jeju’s volcanic aquifers. These findings emphasize the need for tailored regional management centered on groundwater abstraction control and continuous monitoring to ensure the sustainable use of agricultural groundwater. Full article

In the semi-desert aeolian sand areas of Northern China, surface deformation monitoring with SAR is challenged by loss of coherence due to mobile dunes, seasonal vegetation changes, and large-gradient, nonlinear subsidence from underground mining. This study utilizes PALSAR-2 (L-band, 3 m resolution) and Sentinel-1 (C-band, 30 m resolution) data, applying InSAR and Offset tracking methods combined with differential, Stacking, and SBAS techniques to analyze deformation monitoring effectiveness and propose an efficient dynamic monitoring strategy for the Shendong Coalfield. The main conclusions can be summarized as follows: (1) PALSAR-2 data, which has advantages in wavelength and resolution (L-band, multi-look spatial resolution of 3 m), exhibits better interference effects and deformation details compared to Sentinel-1 data (C-band, multi-look spatial resolution of 30 m). The highly sensitive differential-InSAR (D-InSAR) can promptly detect new deformations, while Stacking-InSAR can accurately delineate the range of rock strata movement. SBAS-InSAR can reflect the dynamic growth process of the deformation range as a whole, and SBAS-Offset is suitable for observing the absolute values and morphology of the surface moving basin. The combined application of Stacking-InSAR and Stacking-Offset methods can accurately acquire the three-dimensional deformation field of mining-induced strata movement. (2) The spatiotemporal process of surface deformation caused by coal mining-induced strata movement revealed by InSAR exhibits good correspondence with both the underground mining progress and the development of ground fissures identified in UAV images. (3) The maximum displacement along the line of sight (LOS) measured in the mining area is approximately 2 to 3 m, which is close to the 2.14 m observed on site and aligns with previous studies. The calculated advance influence angle of the No. 22308 working face in the study area is about 38.3°. The influence angle on the solid coal side is 49°, while that on the goaf side approaches 90°. These findings further deepen the understanding of rock movement and surface displacement parameters in this region. The dynamic monitoring strategy proposed in this study is cost-effective and operational, enhancing the observational effectiveness of InSAR technology for surface deformation due to coal mining in this area, and it enriches the understanding of surface strata movement patterns and parameters in this region. Full article

Background: Limosilactobacillus reuteri (L. reuteri), present in the oral and intestinal microbiota, can colonize the oral cavity through breastfeeding and dairy intake, promoting oral health by balancing the microbiota, inhibiting pathogens, and modulating immune responses. This study aimed to evaluate the preventive role and therapeutic potential of L. reuteri in pediatric oral health. Methods: A literature review was conducted using PubMed, Wiley Library, and the Cochrane Library, supplemented by manual screening, according to PRISMA guidelines and covering the period from January 2011 to 31 December 2024. Results: From 835 records identified, 12 studies met the inclusion criteria. Data shows that L. reuteri strains produce antimicrobial substances that disrupt biofilms and inhibit Streptococcus mutans and other lactobacilli, leading to increased oral pH and improved periodontal indices. The effectiveness of probiotics was found to be strain-specific and transient, with continuous intake and adequate oral hygiene enhancing their ability to colonize the oral cavity. Conclusions: Probiotics show significant potential as therapeutic interventions for controlling cariogenic bacteria and supporting gum health in children. Through mechanisms including bacterial co-aggregation, competitive exclusion, antimicrobial compound synthesis, and immune modulation, probiotics may effectively reduce the risk of tooth decay and gum disease. Their effectiveness depends on the strain, regular intake, proper dosing, good oral hygiene, and suitable delivery, which enhance oral colonization and clinical benefits. Full article

To address the utilization challenges of rural settlements in metropolitan suburbs, this study takes the suburban areas of Wuhan as its research object. Based on mobile signaling data and multi-source geographic data, it evaluates their utilization efficiency and construction suitability from both dynamic and static dimensions, and proposes zoning optimization strategies. The study constructed a population mobility network, revealing that rural population flow in Wuhan radiates primarily from the main urban core, with net inflow or balance prevalent in near-suburban areas and net outflow dominant in distant suburbs. The results indicate that only 11.45% of villages achieve medium-to-high utilization efficiency, while 94.50% of the area is classified as highly suitable for development. Based on the “Efficiency-Potential” matrix, villages are categorized into five types, including key development type, gradual optimization type, potential activation type, steady-state improvement type and priority exit type. This study contributes to our understanding of the relationship between rural population and land, and provides support for the optimization of suburban settlements and rural revitalization. Full article

Modeling loss data is a crucial aspect of actuarial science. In the insurance industry, small claims occur frequently, while large claims are rare. Traditional heavy-tail distributions, such as Weibull, Log-Normal, and Inverse Gaussian distributions, are not suitable for describing insurance data, which often exhibit skewness and fat tails. The literature has explored classical and Bayesian inference methods for the parameters of composite distributions, such as the Exponential–Pareto, Weibull–Pareto, and Inverse Gamma–Pareto distributions. These models effectively separate small to moderate losses from significant losses using a threshold parameter. This research aims to introduce a new composite distribution, the Gamma–Pareto distribution with two parameters, and employ a numerical computational approach to find the maximum likelihood estimates (MLEs) of its parameters. A novel computational approach for a nonlinear regression model where the loss variable is distributed as the Gamma–Pareto and depends on multiple covariates is proposed. The maximum likelihood (ML) and Approximate Bayesian Computation (ABC) methods are used to estimate the regression parameters. The Fisher information matrix, along with a multivariate normal distribution as the prior distribution, is utilized through the ABC method. Simulation studies indicate that the ABC method outperforms the ML method in terms of accuracy. Full article

The fast-increasing penetration of photovoltaic (PV) power raises the issue of grid stability due to its intermittency and lack of inertia in power systems. Solar irradiance forecasting effectively supports advanced control, mitigates power intermittency, and improves grid resilience. Irradiance forecasting based on data-driven methods aims to predict the direction and level of power variation and indicate quick action. This article presents a comprehensive review and comparative analysis of data-driven approaches for time-series solar irradiance forecasting. It systematically evaluates nineteen representative models spanning from traditional statistical methods to state-of-the-art deep learning architectures across multiple performance dimensions that are critical for practical deployment. The analysis aims to provide actionable insights for researchers and practitioners when selecting and implementing suitable forecasting solutions for diverse solar energy applications. Full article

The numerical analysis technique is one of the primary methods for the design and development of floating offshore wind turbines (FOWTs). This study presents a detailed investigation into the influences of fully coupled and decoupled numerical analysis methods on the dynamic responses of a floating offshore wind turbine. The fully coupled analysis is implemented via bidirectional FAST-OrcaFlex co-simulation, considering the dynamic interaction between rotor operation and platform motions. The decoupled analysis is conducted using OrcaFlex for wave-induced response analysis, incorporating unidirectional imported FAST-based thrust time series. First, the numerical tools used for simulating fully coupled numerical model of OC5 DeepCwind are verified against published model test data, including free-decay test, white noise wave test and working condition test. Then, the fully coupled and decoupled numerical models are compared under wind fields of different turbulence intensities and wind speeds to reveal the dynamic coupling effects. The results indicate that the predictions of the decoupled model are more aligned with the experimental data compared to those of the fully coupled model under conditions of combined wave and steady winds. The differences between the fully coupled and decoupled models are minor under wave-only condition. However, under turbulent condition, the decoupled model overestimates surge by up to 10% and mooring tension by less than 5%, while pitch deviations can reach 17%. These findings support the use of the decoupled method in preliminary design stages—especially for mooring system optimal design—to save computational cost and time. For detailed designs involving turbulent winds, low-frequency structure response analysis or pitch-sensitive performance, the fully coupled approach is recommended to ensure accuracy. This study could offer practical guidance for selecting suitable numerical methods in FOWT design and analysis. Full article

This paper addresses the long-standing question of understanding the origin and evolution of low-frequency unsteadiness interactions associated with shock waves impinging on a turbulent boundary layer in transonic flow (Mach: $1.1$ to $1.3$). To that end, high-speed experiments in a blowdown open-channel wind tunnel have been performed across a convergent–divergent nozzle for different expansion ratios (PR = 1.44, 1.6, and 1.81). Quantitative evaluation of the underlying spectral energy content has been obtained by processing time-resolved pressure transducer data and Schlieren images using the following spectral analysis methods: Fast Fourier Transform (FFT), Continuous Wavelet Transform (CWT), as well as coherence and time-lag evaluations. The images demonstrated the presence of increased normal shock-wave impact for PR = 1.44, whereas the latter were linked with increased oblique $\lambda$-foot impact. Hence, significant disparities associated with the overall stability, location, and amplitude of the shock waves, as well as quantitative assertions related to spectral energy segregation, have been inferred. A subsequent detailed spectral analysis revealed the presence of multiple discrete frequency peaks (magnitude and frequency of the peaks increasing with PR), with the lower peaks linked with large-scale shock-wave interactions and higher peaks associated with shear-layer instabilities and turbulence. Wavelet transform using the Morlet function illustrates the presence of varying intermittency, modulation in the temporal and frequency scales for different spectral events, and a pseudo-periodic spectral energy pulsation alternating between two frequency-specific events. Spectral analysis of the pixel densities related to different regions, called spatial FFT, highlights the increased influence of the feedback mechanism and coupled turbulence interactions for higher PR. Collation of the subsequent coherence analysis with the previous results underscores that lower PR is linked with shock-separation dynamics being tightly coupled, whereas at higher PR values, global instabilities, vortex shedding, and high-frequency shear-layer effects govern the overall interactions, redistributing the spectral energy across a wider spectral range. Complementing these experiments, time-resolved numerical simulations based on a transient 3D RANS framework were performed. The simulations successfully reproduced the main features of the shock motion, including the downstream migration of the mean position, the reduction in oscillation amplitude with increasing PR, and the division of the spectra into distinct frequency regions. This confirms that the adopted 3D RANS approach provides a suitable predictive framework for capturing the essential unsteady dynamics of shock–boundary layer interactions across both temporal and spatial scales. This novel combination of synchronized Schlieren imaging with pressure transducer data, followed by application of advanced spectral analysis techniques, FFT, CWT, spatial FFT, coherence analysis, and numerical evaluations, linked image-derived propagation and coherence results directly to wall pressure dynamics, providing critical insights into how PR variation governs the spectral energy content and shock-wave oscillation behavior for nozzles. Thus, for low PR flows dominated by normal shock structure, global instability of the separation zone governs the overall oscillations, whereas higher PR, linked with dominant $\lambda$-foot structure, demonstrates increased feedback from the shear-layer oscillations, separation region breathing, as well as global instabilities. It is envisaged that epistemic understanding related to the spectral dynamics of low-frequency oscillations at different PR values derived from this study could be useful for future nozzle design modifications aimed at achieving optimal nozzle performance. The study could further assist the implementation of appropriate flow control strategies to alleviate these instabilities and improve thrust performance. Full article

EMFIT, also referred to as EMFi, is a ferroelectret film related to polyvinylidene fluoride (PVDF) sensors. It is an electroactive polymer (EAP) based on a polyolefin structure and consists of three layers of polyester film. Its application in geophysical monitoring has not been reported in the literature. At present, EMFIT is mainly employed in ballistocardiography and medical sleep monitoring, as developed by the manufacturer Emfit Ltd. (Vaajakoski, Finland). Within the multidisciplinary monitoring network of the National Institute for Earth Physics (NIEP), EMFIT is used as a pressure sensor in combination with infrasound transducers and microphones deployed in seismic areas. The primary aim of this study is to evaluate its suitability for detecting seismic noise that precedes earthquakes, generated by rock fracturing associated with crustal deformation. Although similar studies have been reported, they have not involved the use of EMFIT sensors. The novelty of this approach lies in the large surface area and mechanical flexibility of the material. Beyond seismic forecasting, the research also examines whether this type of sensor can contribute to seismic monitoring as a complement to conventional instruments such as accelerometers, seismometers, and microbarometers. Data analysis relies primarily on spectral time-series methods and incorporates measurements from other acoustic sensors (microphones and microbarometers) as well as a weather station. The working hypothesis is the potential correlation between the recorded data and the presence of enhanced noise prior to the detection of seismic waves by standard seismic sensors. The target area for this investigation is Vrancea, specifically the Vrâncioaia seismic station, where multidisciplinary monitoring includes infrasound, radon, thoron, soil temperature, and atmospheric electrical discharges. Preliminary tests suggest that the EMFIT sensor may function as a highly sensitive device, effectively serving as an “ear” for detecting ground noise. Full article

This study presents an innovative approach to the production of hydrogen from liquids following hydrothermal treatment of biowaste, offering a potential solution for renewable energy generation and waste management. By combining biological and hydrothermal processes, the efficiency of H₂ production can be significantly improved, contributing to a reduced carbon footprint and lower reliance on fossil fuels. The inoculum used was fermented sludge from a wastewater treatment plant, which had been thermally pretreated to enhance microbial activity towards hydrogen production. Kitchen waste, consisting mainly of plant-derived materials (vegetable matter), was used as a substrate. The process was conducted in batch 1-L bioreactors. The results showed that higher pretreatment temperatures (up to 180 °C) increased the hydrolysis of compounds and enhanced H₂ production. However, temperatures above 180 °C resulted in the formation of toxic compounds, such as catechol and hydroquinone, which inhibited H₂ production. The highest hydrogen production was achieved at 180 °C (approximately 66 mL H₂/g_TVSKW). The standard Gompertz model was applied to describe the process kinetics and demonstrated an excellent fit with the experimental data (R² = 0.99), confirming the model’s suitability for optimizing H₂ production. This work highlights the potential of combining hydrothermal and biological processes to contribute to the development of sustainable energy systems within the circular economy. Full article