Search Results (10,149)

Background/Objectives: Adolescence is a critical period for the early detection of metabolic syndrome (MetS), a condition that increases the risk of cardiometabolic diseases in adulthood. Timely identification of at-risk adolescents enables targeted prevention strategies. This study aimed to analyze the discriminative capacity and accuracy of six biochemical and/or anthropometric indices related to lipid metabolism and adiposity for the early detection of MetS in a sample of Spanish adolescents. Methods: A cross-sectional study carried out according to the STROBE guidelines. A sample of 981 adolescents aged 11–16 years old were randomly recruited from schools in Southeastern Spain. The presence or absence of MetS was determined according to the International Diabetes Federation criteria. The following biochemical and/or anthropometric indices were evaluated: triglyceride glucose index, visceral adiposity index, logarithm children’s lipid accumulation product, triglyceride glucose-body mass index, triglyceride glucose-waist circumference, and triglyceride glucose-waist-to-hip ratio. Results: The triglyceride glucose-waist-to-hip ratio and triglyceride glucose-body mass index parameters were the strongest indicators associated with MetS in boys and girls, respectively, after adjusting for several factors. Moreover, all evaluated indices showed optimal AUC values, with the visceral adiposity index and triglyceride glucose-waist circumference index exhibiting the highest discriminative capacity in both genders. Conclusions: The evaluated biochemical and anthropometric indices—particularly visceral adiposity index and triglyceride-glucose-waist circumference—show promise as accessible biomarkers for identifying adolescents at metabolic risk. These indices may serve as practical tools in preventive health strategies aimed at improving metabolic health by screening adolescents at risk of MetS, thereby helping to reduce the future burden of non-communicable diseases. Full article

This study developed a new magnetic adsorbent from waste coconut shells using high-temperature carbonization, EDTA-2Na chelation, and Fe₃O₄ magnetic loading. Response surface methodology optimized the preparation conditions to a mass ratio of activated carbon: EDTA-2Na:Fe₃O₄ = 2:0.6:0.2. Characterization (SEM, XRD, FT-IR, and EDS) showed that EDTA-2Na increased the surface carboxyl and amino group density, while Fe₃O₄ loading (Fe concentration 6.83%) provided superior magnetic separation performance. The optimal adsorption conditions of Cu²⁺ by EDTA-2Na-Fe₃O₄-activated carbon composite material are as follows: when pH = 5.0 and the initial concentration is 180 mg/L, the equilibrium adsorption capacity reaches 174.96 mg/g, and the removal rate reaches 97.2%. The optimal adsorption conditions for Pb²⁺ are as follows: when pH = 6.0 and the initial concentration is 160 mg/L, the equilibrium adsorption capacity reaches 157.60 mg/g, and the removal rate reaches 98.5%. The optimal adsorption conditions for Cd²⁺ are pH = 8.0 and an initial concentration of 20 mg/L. The equilibrium adsorption capacity reaches 18.76 mg/g, and the removal rate reaches 93.8%. The adsorption followed the pseudo-second-order kinetics (R² > 0.95) and Langmuir/Freundlich isotherm models, indicating chemisorption dominance. Desorption experiments using 0.1 mol/L HCl and EDTA-2Na achieved efficient desorption (>85%), and the material retained over 80% of its adsorption capacity after five cycles. This cost-effective and sustainable adsorbent offers a promising solution for heavy metal wastewater treatment. Full article

Background/Objectives: We aimed to identify questionnaire items associated with an increased risk of developing hepatic steatosis in the general population. Methods: A total of 15,063 individuals aged ≥20 years who underwent general health checkups and had no hepatic steatosis at baseline were included. The relationship between questionnaire data at baseline and hepatic steatosis incidence over a median 4.2-year follow-up was investigated across body mass index (BMI) categories. Results: Among 15,063 individuals (mean [SD] age, 47.1 [10.2] years; 6769 [44.9%] male; mean [SD] BMI, 21.4 [2.6] kg/m²), 1889 individuals (12.5%) developed hepatic steatosis during follow-up. After adjusting for age, sex, and factors related to metabolic diseases and liver injury, the strongest questionnaire-based risk factor for hepatic steatosis was self-reported weight gain of 10 kg or more after the age of 20 across all BMI categories: total population (hazard ratio [HR], 2.11; 95% confidence interval [CI], 1.90–2.34; p < 0.001), Category 1 (BMI < 22) (HR, 2.33; 95% CI, 1.86–2.91; p < 0.001), Category 2 (BMI 22 to <25) (HR, 1.43; 95% CI, 1.25–1.63; p < 0.001), and Category 3 (BMI ≥ 25) (HR, 1.41; 95% CI, 1.12–1.77; p = 0.003). Conclusions: In this cohort study, self-reported weight gain of 10 kg or more after the age of 20 was associated with an increased risk of hepatic steatosis, independent of baseline BMI. Questionnaires capturing weight gain history may support universal screening efforts to identify individuals at elevated risk. Full article

Objectives: Paratubal cysts (PTCs) are embryological remnants and are potentially hormonally responsive. Since hyperandrogenism (HA) is representative of polycystic ovary syndrome (PCOS), we examined whether biochemical hyperandrogenism is associated with PTCs in women with PCOS and if body mass index (BMI) and insulin resistance (IR) mediate this association. Methods: This retrospective study included 577 women diagnosed with PCOS at a tertiary academic center from 2010 to 2018. Clinical data included age at diagnosis, BMI, and diagnoses of hypertension, non-alcoholic fatty liver disease, and metabolic syndrome. Laboratory measures included total testosterone, sex hormone-binding globulin, anti-Müllerian hormone, luteinizing hormone, fasting glucose, insulin, and triglycerides (TG). Derived indices included a free androgen index (FAI), homeostasis model assessment of insulin resistance (HOMA-IR), and fasting glucose-to-insulin ratio. PTCs were identified through imaging or surgical findings. Structural equation modeling (SEM) assessed direct and indirect relationships between FAI, BMI, HOMA-IR, and PTCs, while adjusting for diagnostic age. Results: PTCs were identified in 2.77% of participants. BMI, FAI, TG, and IR indices were significantly higher for women with PTCs than those without PTCs. SEM revealed significant indirect effects of FAI on PTCs via BMI and HOMA-IR. The direct effect was negative, resulting in a non-significant total effect. A sensitivity model using HOMA-IR as the predictor showed a significant direct effect on PTCs without mediation via FAI. Conclusions: Biochemical HA may influence PTC development in PCOS through metabolic pathways, establishing the need to consider metabolic context when evaluating adnexal cysts in hyperandrogenic women. Full article

Chromium–aluminum nitride (CrAlN) coatings were deposited on polished H13 tool steel substrates using direct current (DC) magnetron sputtering. The Cr/Al composition in the target was varied by inserting either four or eight chromium (Cr) plugs into cavities machined into an aluminum (Al) plate target. Nitrogen was introduced as a reactive gas to facilitate the formation of the nitride phase. Coatings were deposited at substrate bias voltages of −30 V, −50 V, and −60 V to study the combined effects of composition and ion energy on coating properties. Compositional analysis of coatings deposited at a −50 V bias revealed Cr/Al ratios of approximately 0.8 and 1.7 for the 4- and 8-plug configurations, respectively. This increase in the Cr/Al ratio led to a 2.6-fold improvement in coating hardness. Coatings produced using the eight-Cr-plug target exhibited a nearly linear increase in hardness with increasing substrate bias voltage. Cross-sectional scanning electron microscopy revealed a uniform bilayer structure consisting of an approximately 0.5 µm metal interlayer beneath a 2–3 µm CrAlN coating. Surface morphology analysis indicated the presence of coarse microdroplets in coatings with the lower Cr/Al ratio. These microdroplets were significantly suppressed in coatings with higher Cr/Al content, especially at increased bias voltages. This suppression is likely due to enhanced ion bombardment associated with the increased Cr content, attributed to Cr’s relatively higher atomic mass compared to Al. Coatings with lower hardness exhibited greater scratch resistance, likely due to the influence of residual compressive stresses. The findings highlight the critical role of both Cr/Al content and substrate bias in tailoring the tribo-mechanical performance of PVD CrAlN coatings for wear-resistant applications. Full article

Petrological knowledge on weathering processes controlling the mobility of chemical elements is still limited in the dry tropical zone of Cameroon. This study aims to investigate the mobility of major and trace elements during rhyolite weathering and soil formation in Mobono by understanding the mineralogical and elemental vertical variation. The studied soil was classified as Cambisols containing mainly quartz, K-feldspar, plagioclase, smectite, kaolinite, illite, calcite, lepidocrocite, goethite, sepiolite, and interstratified clay minerals. pH values ranging between 6.11 and 8.77 indicated that hydrolysis, superimposed on oxidation and carbonation, is the main process responsible for the formation of secondary minerals, leading to the formation of iron oxides and calcite. The bedrock was mainly constituted of SiO₂, Al₂O₃, Na₂O, Fe₂O₃, Ba, Zr, Sr, Y, Ga, and Rb. Ce and Eu anomalies, and chondrite-normalized La/Yb ratios were 0.98, 0.67, and 2.86, respectively. SiO₂, Al₂O₃, Fe₂O₃, Na₂O, and K₂O were major elements in soil horizons. Trace elements revealed high levels of Ba (385 to 1320 mg kg⁻¹), Zr (158 to 429 mg kg⁻¹), Zn (61 to 151 mg kg⁻¹), Sr (62 to 243 mg kg⁻¹), Y (55 to 81 mg kg⁻¹), Rb (1102 to 58 mg kg⁻¹), and Ga (17.70 to 35 mg kg⁻¹). LREEs were more abundant than HREEs, with LREE/HREE ratio ranging between 2.60 and 6.24. Ce and Eu anomalies ranged from 1.08 to 1.21 and 0.58 to 1.24 respectively. The rhyolite-normalized La/Yb ratios varied between 0.56 and 0.96. Mass balance revealed the depletion of Si, Ca, Na, Mn, Sr, Ta, W, U, La, Ce, Pr, Nd, Sm, Gd and Lu, and the accumulation of Al, Fe, K, Mg, P, Sc, V, Co, Ni, Cu, Zn, Ga, Ge, Rb, Y, Zr, Nb, Cs, Ba, Hf, Pb, Th, Eu, Tb, Dy, Ho, Er, Tm and Yb during weathering along the soil profile. Full article

Colorectal cancer (CRC) constitutes a major global health concern, ranking as the third most common cancer and the second leading cause of cancer-related mortality. The current review explores sex-based differences in CRC epidemiology, risk factors, tumor biology, and clinical outcomes. Males exhibit a higher incidence and mortality rate, with left-sided (distal) CRC predominating, while females are more frequently diagnosed with right-sided (proximal) tumors, which tend to be more aggressive and less responsive to conventional chemotherapy. Genetic disparities, including microsatellite instability and X-chromosome tumor suppressor genes, contribute to sex-specific differences in tumor progression and treatment response. Immune variations also influence disease outcomes, with females exhibiting stronger immune surveillance but higher exhaustion markers. Lifestyle factors such as body mass index (BMI), smoking, and hormonal influences further modulate CRC risk. While males are more vulnerable to obesity-related CRC, central obesity (waist-to-hip ratio) emerges as a stronger predictor in females. Additionally, smoking increases CRC risk differentially by tumor location. These findings underscore the importance of sex-specific approaches in CRC prevention, screening, and treatment, advocating for personalized medicine strategies tailored to gender-based biological and clinical distinctions. Full article

Aiming at the lightweight design of a bridge-shed integration structure, this paper presents a three-layered absorbing system in which a part of the sand cushion is replaced by expanded polystyrene (EPS) geofoam and the reinforced concrete (RC) protective slab is arranged above the sand cushion to enhance the composite system’s safety. A three-dimensional Smoothed Particle Hydrodynamics–Finite Element Method (SPH-FEM) coupled numerical model is developed in LS-DYNA (Livermore Software Technology Corporation, Livermore, CA, USA, version R13.1.1), with its validity rigorously verified. The dynamic response of rockfall impacts on the shed slab with composite cushions of various thicknesses is analyzed by varying the thickness of sand and EPS materials. To optimize the cushion design, a specific energy dissipation ratio (SEDR), defined as the energy dissipation rate per unit mass (η/M), is introduced as a key performance metric. Furthermore, the complicated interactional mechanism between the rockfall and the optimum-thickness composite system is rationally interpreted, and the energy dissipation mechanism of the composite cushion is revealed. Using logistic regression, the ultimate stress state of the reactive powder concrete (RPC) slab is methodically analyzed, accounting for the speed and mass of the rockfall. The results are indicative of the fact that the composite cushion not only has less dead weight but also exhibits superior impact resistance compared to the 90 cm sand cushions; the impact resistance performance index SEDR of the three-layered absorbing system reaches 2.5, showing a remarkable 55% enhancement compared to the sand cushion (SEDR = 1.61). Additionally, both the sand cushion and the RC protective slab effectively dissipate most of the impact energy, while the EPS material experiences relatively little internal energy build-up in comparison. This feature overcomes the traditional vulnerability of EPS subjected to impact loads. One of the highlights of the present investigation is the development of an identification model specifically designed to accurately assess the stress state of RPC slabs under various rockfall impact conditions. Full article

Most public seismic recordings, sampled at hundreds of Hz, tend to be unlabelled, i.e., not catalogued, mainly because of the sheer volume of samples and the amount of time needed by experts to confidently label detected events. This is especially challenging for very low signal-to-noise ratio microseismic events that characterise landslides during rock and soil mass displacement. Whilst numerous supervised machine learning models have been proposed to classify landslide events, they rely on a large amount of labelled datasets. Therefore, there is an urgent need to develop tools to effectively automate the data-labelling process from a small set of labelled samples. In this paper, we propose a semi-supervised method for labelling of signals recorded by seismometers that can reduce the time and expertise needed to create fully annotated datasets. The proposed Siamese network approach learns best class-exemplar anchors, leveraging learned similarity between these anchor embeddings and unlabelled signals. Classification is performed via soft-labelling and thresholding instead of hard class boundaries. Furthermore, network output explainability is used to explain misclassifications and we demonstrate the effect of anchors on performance, via ablation studies. The proposed approach classifies four landslide classes, namely earthquakes, micro-quakes, rockfall and anthropogenic noise, demonstrating good agreement with manually detected events while requiring few training data to be effective, hence reducing the time needed for labelling and updating models. Full article

Accurate parameter estimation is essential for gravitational wave data analysis. In extreme mass-ratio inspiral binary systems, orbital eccentricity is a critical parameter for parameter estimation. However, the current software for the parameter estimation of the gravitational wave often neglects the direct estimation of orbital eccentricity. To fill this gap, we have developed the MatBYIB, a MATLAB-based software (Version 1.0) package for the parameter estimation of the gravitational wave with arbitrary eccentricity. The MatBYIB employs the Analytical Kludge waveform as a computationally efficient signal generator and computes parameter uncertainties via the Fisher Information Matrix and the Markov Chain Monte Carlo. For Bayesian inference, we implement the Metropolis–Hastings algorithm to derive posterior distributions. To guarantee convergence, the Gelman–Rubin convergence criterion (the Potential Scale Reduction Factor $\widehat{R}$) is used to determine sampling adequacy, with MatBYIB dynamically increasing the sample size until $\widehat{R}<1.05$ for all parameters. Our results demonstrate strong agreement between predictions based on the Fisher Information Matrix and full MCMC sampling. This program is user-friendly and allows for the estimation of the gravitational wave parameters with arbitrary eccentricity on standard personal computers. Full article

Background: Plantar fasciitis (PF) is a common enthesopathy in patients with ankylosing spondylitis (AS). Shear wave elastography (SWE) and the Belgrade ultrasound enthesitis score (BUSES) may detect PF, but their comparative diagnostic performance is unclear. Objective: To compare SWE with the BUSES for identifying PF in individuals with and without AS. Methods: In this cross-sectional study, 96 participants were stratified into AS and non-AS populations, each further divided based on the presence or absence of clinical PF. Demographic data, the American Orthopedic Foot and Ankle Society Score (AOFAS), and the BASDAI score were recorded. All subjects underwent grayscale ultrasonography, the BUSES scoring, and SWE assessment of the plantar fascia. Logistic regression models were constructed for each population, controlling for age, body mass index (BMI), and fascia–skin distance. ROC curve analyses were performed to evaluate diagnostic accuracy. Results: In both AS and non-AS groups, SWE and the BUSES were significant predictors of PF (p < 0.05). SWE demonstrated slightly higher diagnostic accuracy, with area under the curve (AUC) values of 0.845 (AS) and 0.837 (non-AS), compared to the BUSES with AUCs of 0.785 and 0.831, respectively. SWE also showed stronger adjusted odds ratios in regression models. The interobserver agreement was good to excellent for both modalities. Conclusions: Both SWE and the BUSES are effective for PF detection, with SWE offering marginally superior diagnostic performance, particularly in AS patients. SWE may enhance the early identification of biomechanical changes in the plantar fascia. Full article

Vortex-induced vibrations (VIVs) pose significant risks to the structural integrity of subsea cables and pipelines under free-span conditions. It is extremely helpful to be able to screen for VIV and understand for a particular cable or pipeline what the minimum free-span threshold lengths are beyond which in-line and/or cross-flow VIV can be excited, causing fatigue problems. To date screening is a more complex and detailed task. This paper introduces a universal dimensionless velocity, V*, and one graph that can be used across all types of VIV free spans to quickly assess minimum free-span threshold lengths. Natural frequencies are not required to be calculated for screening each time, as they are implicit in the curve. The universal criteria are developed via non-dimensional analysis to establish the significant physical mechanisms, after which the relationships are populated, forming a single curve for in-line and for cross-flow VIV with a typical mass ratio and a conservative zero as-laid tension case. Full article

This study optimizes the production of activated carbons from hydrothermally carbonized (HTC) biomass using potassium hydroxide (KOH) and phosphoric acid (H₃PO₄) as activating agents. A 2³ factorial experimental design evaluated the effects of agent-to-precursor ratio, dry impregnation time, and activation duration on mass yield and iodine adsorption capacity. KOH-activated carbons achieved superior iodine numbers (up to 1289 mg/g) but lower mass yields (18–35%), reflecting enhanced porosity at the cost of material loss. Conversely, H₃PO₄ activation yielded higher mass retention (up to 54.86%) with moderate iodine numbers (up to 1117.3 mg/g), balancing porosity and yield. HTC pretreatment at 190 °C reduced the ash content, thereby enhancing the stability of hydrochar. These findings highlight the trade-offs between adsorption performance and process efficiency, with KOH suited for high-porosity applications (e.g., water purification) and H₃PO₄ for industrial scalability. The study advances biomass waste valorization, aligning with circular economy principles and offering sustainable solutions for environmental and industrial applications, such as water purification and energy storage. Full article

This study presents the synthesis and physicochemical characterization of coordination compounds formed between chrysin, a natural flavonoid, and transition metal ions: Mn(II), Co(II), and Zn(II). The complexes were obtained under mildly basic conditions and analyzed using elemental analysis, thermogravimetric analysis (TGA), silver-assisted laser desorption/ionization mass spectrometry (SALDI-MS), FT-IR spectroscopy, and ¹H NMR. The spectroscopic data confirm that chrysin coordinates as a bidentate ligand through the 5-hydroxyl and 4-carbonyl groups, with structural differences depending on the metal ion involved. The mass spectrometry results revealed distinct stoichiometries: 1:2 metal-to-ligand ratios for Mn(II) and Co(II), and 1:1 for Zn(II), with additional hydroxide coordination. Biological assays demonstrated that Co(II) and Mn(II) complexes exhibit enhanced antibacterial and anti-biofilm activity compared to free chrysin, particularly against drug-resistant Staphylococcus epidermidis, whereas the Zn(II) complex showed negligible biological activity. Full article

Simulated data created in silico using a previously reported method were sampled by bootstrapping to generate data sets for training multiple copies of an ensemble learner (i.e., a machine learning (ML) method). The posterior probabilities of class membership obtained by applying the ensemble of ML models to previously unseen validation data were fitted to a beta distribution. The shape parameters for the fitted distribution were used to calculate the subjective opinion of sample membership into one of two mutually exclusive classes. The subjective opinion consists of belief, disbelief and uncertainty masses. A subjective opinion for each validation sample allows identification of high-uncertainty predictions. The projected probabilities of the validation opinions were used to calculate log-likelihood ratio scores and generate receiver operating characteristic (ROC) curves from which an opinion-supported decision can be made. Three very different ML models, linear discriminant analysis (LDA), random forest (RF), and support vector machines (SVM) were applied to the two-state classification problem in the analysis of forensic fire debris samples. For each ML method, a set of 100 ML models was trained on data sets bootstrapped from 60,000 in silico samples. The impact of training data set size on opinion uncertainty and ROC area under the curve (AUC) were studied. The median uncertainty for the validation data was smallest for LDA ML and largest for the SVM ML. The median uncertainty continually decreased as the size of the training data set increased for all ML.The AUC for ROC curves based on projected probabilities was largest for the RF model and smallest for the LDA method. The ROC AUC was statistically unchanged for LDA at training data sets exceeding 200 samples; however, the AUC increased with increasing sample size for the RF and SVM methods. The SVM method, the slowest to train, was limited to a maximum of 20,000 training samples. All three ML methods showed increasing performance when the validation data was limited to higher ignitable liquid contributions. An ensemble of 100 RF ML models, each trained on 60,000 in silico samples, performed the best with a median uncertainty of 1.39x${10}^{-2}$ and ROC AUC of 0.849 for all validation samples. Full article