Search Results (17,611)

Background/Objectives: Measures of excess body fat are often more informative for predicting health risk than body mass index (BMI) alone. With obesity prevalence increasing among young adults, this study evaluated whether adding dominant handgrip strength improves prediction of body fat percentage (BF%) and BF%-defined obesity in a university population. Methods: Cross-sectional data from 895 students (401 women, 494 men; mean age 19.9 years; fall 2015–spring 2016) in Kentucky, USA were analyzed. BMI was calculated from self-reported height and weight. BF% was estimated using bioelectrical impedance analysis (BIA), and dominant handgrip strength was measured with a hydraulic hand grip dynamometer. Sex-specific linear and logistic regression models assessed associations among BMI, grip strength, relative grip strength, and BF%. Results: BMI was a strong predictor of BF% in linear models (R² = 0.74 in women; 0.68 in men). Grip strength alone was not associated with BF% but showed an inverse association when combined with BMI. For BF%-defined obesity, BMI remained the most influential predictor, with grip strength contributing additional predictive value. Among men, age significantly modified these relationships, with marked differences between those aged 18–19 years versus older participants. Conclusions: BMI strongly predicted BF% and BF%-based obesity in this cross-sectional study of a predominantly white young adult population. Incorporating handgrip strength modestly improved classification, particularly among women, suggesting that a functional measure like hand grip strength may enhance obesity screening and health communication in young adults. Full article

Accurate and robust battery health prognostics are critical for reliable battery management in electronic devices and electric vehicles. Previous studies have demonstrated that combining electrochemical impedance spectroscopy (EIS) with machine learning enables accurate health-state forecasting in LiCoO₂ coin cells. However, the applicability of this EIS-AI paradigm across diverse chemistries and industrial-grade battery formats remains unvalidated, limiting its practical deployment in energy storage systems. Here, we develop an EIS–AI battery prognostic framework and validate its performance on LiNi_1/3Mn_1/3Co_1/3O₂ (NMC111) cylindrical cells and LiNi_0.8Mn_0.1Co_0.1O₂ (NMC811) pouch cells. A hybrid Convolutional Neural Network–Bidirectional Long Short-Term Memory (CNN–BiLSTM) architecture is developed to estimate state of health (SoH) and predict remaining useful life (RUL) from EIS spectra. Trained on an in-house dataset comprising over 13,000 impedance spectra from 22 cells (8 NMC111 and 14 NMC811), the model achieves robust performance, with average coefficients of determination (R²) exceeding 0.92 for SoH estimation and 0.90 for RUL prediction across various batteries and cycling protocols. Salient feature analysis further reveals chemistry- and protocol-dependent frequency regimes associated with degradation. These results demonstrate that impedance spectra constitute physically informative descriptors for data-driven battery prognostics and provide a scalable and interpretable pathway for deploying EIS-AI frameworks in real-world battery management systems (BMSs). Full article

This study systematically reviews the evolution of Qatar’s tourism sector to evaluate the historical barriers impeding its development and the strategic initiatives deployed to enhance destination competitiveness. The research’s primary aim is to provide a theory-driven longitudinal analysis of Qatar’s tourism evolution, identifying systemic barriers and adaptive responses required for long-term sustainability. Grounded in the theoretical synthesis of Butler’s Tourism Area Life Cycle (TALC) and Dynamic Capability Theory (DCT), the research employs a systematic literature review (SLR) guided by the PRISMA framework, screening 4846 records to analyze 24 final studies. The findings reveal five primary structural and perceptual barriers: a price–value mismatch (luxury perception), regional political instability, cultural and regulatory constraints, environmental vulnerabilities, and gaps in tourist infrastructure. Utilizing DCT, the results demonstrate how the destination exhibited adaptive governance by sensing these barriers and seizing strategic opportunities—such as mega-event hosting and visa reforms—to partially transform its tourism system. These insights highlight that while created resources drive initial visibility, sustaining long-term competitiveness and sustainable growth relies on continuous institutional reconfiguration and socio-cultural alignment. Full article

The rational design of supported Lewis acid catalysts is frequently impeded by an incomplete understanding of how the support’s synthetic history governs its intrinsic acidity and catalytic efficacy. Herein, we elucidate the structure–property–performance relationship linking the aging dynamics of a boehmite precursor to the activity of the resultant chlorinated alumina (Al₂O₃–Cl) catalyst in n-butane isomerization. Using n-butane as the probe feedstock, we investigated how alumina supports with distinct physicochemical properties regulate the performance of Al₂O₃–Cl catalysts for n-butane isomerization. By systematically adjusting the aging parameters (stirring rate, temperature, and time), we reveal that the structural evolution of the alumina support transitions from initial particle aggregation to Ostwald ripening and surface reconstruction. A decisive structure–performance correlation is identified: precursor synthesis conditions govern both the population and accessibility of specific surface hydroxyls (notably Type II terminal OH groups), which act as anchoring sites for the generation of active Lewis acid centers upon chlorination. Optimal aging parameters (300 rpm, 90 °C, 6 h) promote the formation of a hierarchical pore architecture with a maximized density of accessible hydroxyls, thereby affording enhanced Lewis acidity and superior isomerization activity. This work provides a fundamental framework for tailoring solid acid catalysts by precisely engineering the precursor architecture. Full article

The quality factor (Q) and its circumferential non-uniformity are essential for the resolution and long-term stability of Coriolis vibratory gyroscopes (CVGs). In practice, packaging and mounting anchors introduce torque-dependent and circumferentially non-uniform anchor dissipation, resulting in harmonic damping anisotropy. This paper presents an energy-consistent framework that quantitatively relates the tightening torque to both the mean damping factor $\eta =1/Q$ and its circumferential harmonic components. A hemispherical resonator gyroscope (HRG) is used for validation, where the dominant component is the fourth harmonic. By decomposing the energy dissipated per cycle, anchor loss is separated into friction loss and radiation loss. The friction channel is modeled using a partial-slip contact energy loss formulation combined with an equivalent tangential impedance coupling description, leading to a torque power-law scaling suitable for parameter identification. The radiation channel is described by an impedance coupling model that captures torque-enhanced anchor stiffness and potential saturation leakage under strong coupling. Controlled torque experiments show that $\eta \left(\vartheta \right)$ exhibits an almost pure fourth-harmonic dependence on the standing wave orientation for all tested torques. Within the accessible torque range, the mean damping decreases slightly with torque, while the harmonic amplitude increases and the phase progressively converges, supporting a friction-dominated interpretation. The phase convergence further suggests progressive stabilization of the contact state. The proposed approach provides quantitative guidance for torque selection and anchor structure design in resonant gyroscopes. Full article

Background/Objectives: Electroanatomic mapping (EAM) provides high-resolution spatial and electrogram information, but the prognostic utility of quantitative EAM features has not been systematically evaluated with contemporary artificial intelligence (AI) methods. We investigated whether an AI analysis of quantitative EAM exports from the CARTO system enhances the prediction of major arrhythmic events (MAEs). Methods: In this retrospective, multicenter cohort study, 248 consecutive patients undergoing left ventricular EAM at four tertiary electrophysiology centers were analyzed. Numerical EAM descriptors (spatial coordinates, unipolar/bipolar voltages, local activation time, impedance) were transformed into derived metrics, including local activation heterogeneity (GR), late-potential extent (LAT), bipolar–unipolar discrepancy (VLT), and low-amplitude scar extent (Scar Areas), and were spatially normalized via spherical projection. Clinical, anamnestic, and imaging variables were integrated. Machine learning and deep learning models were trained with an 80:20 train/test split and evaluated using three-fold cross-validation. Performance metrics included area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and precision. Results: Models incorporating both clinical and AI-processed EAM features achieved high discriminatory performance (test AUC up to 0.92; accuracy up to 0.896). Specificity was consistently high (≈0.97–0.998), whereas sensitivity remained modest (≈0.39–0.58). Among the EAM-derived features, GR was the most consistently informative predictor across algorithms and analyses; VLT, LAT, and Scar Areas also contributed substantially. Regionally, basal sub-mitral, subaortic, and posterolateral basal-to-mid zones exhibited the strongest associations with MAEs. Conclusions: AI-driven quantitative analysis of left ventricular EAM exports augments risk stratification for MAEs beyond conventional clinical and binary EAM descriptors. Reflecting local conduction heterogeneity, GR emerged as the dominant EAM predictor. Prospective validation in larger, disease-specific cohorts and real-time integration within EAM platforms are warranted. Full article

In vitro cell barrier models have been increasingly integrated into pharmaceutical and academic research pipelines to evaluate drug safety and drug delivery due to a shift towards New Approach Methodologies (NAMs) in research and regulatory safety assessment. Such models require reliable and interpretable functional readouts. Bioimpedance-based monitoring, particularly transepithelial/endothelial electrical resistance (TEER), is a widely adopted readout due to its non-invasive and real-time capabilities. However, substantial variability arises from differences in measurement settings, frequency selection, electrode configuration, impedance measuring techniques, and data analysis strategies. In numerous studies, TEER is approximated from single-frequency impedance magnitude measurements, which do not isolate the resistive component associated with tight junction-mediated paracellular transport but instead reflect the combined response of a coupled electrochemical system. This review clarifies impedance measuring techniques and systematically analyzes impedance-based measurement and analysis strategies for in vitro biological cell barrier integrity. We compare mono-frequency and broadband acquisition approaches, examine the influence of electrode–electrolyte interfaces, electrode geometry, and culture configuration, and evaluate equivalent circuit modeling and phase-resolved electrical impedance spectroscopy (EIS). Based on this comparison, we propose a three-level analytical hierarchy adapted to experimental objectives and instrumentation constraints. We conclude that phase-informed impedance analysis and harmonized reporting are essential to improve measurement reproducibility, inter-platform comparability, and integration of impedance-derived cell barrier assessment within NAMs-oriented research workflows. Full article

To optimize the stiffness matrix structure for frequency-domain elastic wave forward modeling in 2D VTI (transversely isotropic with a vertical symmetry axis) media—thereby reducing memory consumption and improving computational efficiency—we simplify the conventional 25-point finite-difference scheme to derive a 17-point frequency-domain finite-difference scheme. This approach reformulates the finite-difference operators for the partial derivatives and acceleration terms in the elastic wave equations, reducing the number of grid points involved in the computation by $30\%$ compared to the 25-point scheme. The optimized matrix construction leverages sparse matrix storage techniques, decreasing memory usage by approximately $27\%$. Numerical validation, conducted using a double-layer VTI medium model and the Marmousi model with three major faults and an anticline containing limestone layers at the base of the faults, demonstrates that the 17-point finite-difference scheme maintains comparable accuracy while requiring $14\%$ less computation time and featuring a $25\%$ reduction in nonzero elements within the impedance matrix. Comparisons of wavefield snapshots and receiver components (horizontal component U and vertical component V) support this conclusion. These improvements enable the use of more efficient iterative solvers. Full article

To address the shortage of natural aggregates and freshwater, and promote the recycling of construction and demolition waste and localized construction materials for marine engineering, this study explores the electrochemical corrosion characteristics and deterioration mechanism of steel bars in recycled concrete aggregate (RCA)–seawater sea-sand concrete (SSC) concrete. Using RCA replacement rates (0%, 50%, 100%) as the core variable, specimens were prepared. Vacuum water saturation, open-circuit potential (OCP) monitoring, Tafel polarization scanning and electrochemical impedance spectroscopy (EIS) were adopted to study steel corrosion evolution within 180 days. The results show that RCA incorporation accelerates OCP negative drift and reduces passivation film stability, with more severe corrosion at higher replacement rates: the RCA100 group showed obvious corrosion after 60 days, while the RCA50 and RCA0 groups initiated corrosion at 90 days (RCA50 corroded faster). The surface mortar and internal microcracks of RCA enhance the water absorption and ion permeability of concrete, which, coupled with chloride ions, accelerates steel corrosion. This study clarifies the correlation between RCA replacement rate and corrosion parameters, providing data support for mix ratio optimization and marine engineering applications. Full article

China has rich bamboo resources, with Moso bamboo (Phyllostachys edulis) being the most economically important species. Bamboo shoot bud development directly determines the eating quality of the shoots and the properties of bamboo materials; however, the intrinsic biological characteristics of this process have hindered foundational research. Traditional methods using whole shoot buds or mixed tissues obscure cellular and tissue heterogeneity, limiting our mechanistic understanding. This review synthesizes cytological features, molecular networks, and technical limitations pertaining to Moso bamboo shoot bud development, identifying four key bottlenecks: tissue homogenization masking cellular heterogeneity, loss of spatial positional information impeding analysis of position effects, challenges in single-cell technology application due to sample preparation and data interpretation issues, and unresolved coupling between chromatin accessibility and transcriptional regulation. To address these, we propose a core strategy centered on constructing a single-cell resolution, spatially resolved, multi-omics integrated, and functionally validated framework. Key approaches include developing bamboo-specific single-cell sequencing and spatial transcriptomics, integrating positional information with multi-omics data to identify spatially distinct regulatory targets, standardizing technical pipelines and functional validation platforms, and elucidating epigenetic–transcriptional coupling. Overcoming these bottlenecks will reveal the molecular basis of bamboo’s unique developmental patterns and provide key targets for the genetic improvement of the shoot quality and mechanical properties of bamboo. Full article

Metal mesh reflective surfaces are widely used in deployable antennas mounted on satellites where lightweight and stowability are required; however, quantitative characterization of reflective performance is difficult due to complex woven/knitted structures. This paper presents a modeling method that characterizes the reflection coefficient of complex mesh fabrics by combining a per-band effective wire radius r_eff estimation procedure with the Casey surface impedance model. The lattice spacing is fixed from the specimen geometry, the electrical conductivity is set to the material property of gold ($\sigma$ = 45.2 MS/m), and r_eff is determined as a single parameter that minimizes the error against the measured reflection coefficient in each frequency band. For validation, waveguide-contact measurements were performed on three Atlas-series mesh specimens fabricated with gold-coated molybdenum wire (diameter: 30 μm), measuring each specimen across all three waveguide standards (WR-340, WR-90, WR-28) with nine repeated trials per configuration, totaling 162 measurement runs. The estimated r_eff ranged from 10.1 to 44.5 μm depending on band and polarization, with RMSE below 0.021 dB in all native-band fits. Even for the same specimen, directional r_eff values differed by up to 1.78× due to the anisotropy of the weave structure, confirming that polarization dependence must be considered in mesh reflector antenna design. Full article

This study reported highly dispersible mesoporous silica (MSP) with a uniform particle size, which was used as host to load 1,10-Phenanthroline (Phen) to prepare Phen@MSP microcontainer. Improving the dispersion of microcontainers prevents performance degradation caused by their agglomeration. Phen can form a red-colored complex with Fe²⁺ ions generated during corrosion of steel substrate, enabling early corrosion warning while also acting as a corrosion inhibitor to suppress further corrosion of the substrate. Phen@MSP microcontainers were incorporated into a waterborne epoxy (EP) resin to construct a coating with dual functionality of corrosion self-diagnosing and self-healing. As a key component, the average diameter of Phen@MSP microcontainers is approximately 1 μm, with a Phen loading rate of 18.45 wt.% in the microcontainers. Surface observation shows that substrate corrosion can be detected within 10 min by the appearance of red color. After 30 d of immersion in 3.5 wt.% NaCl solution, the impedance modulus value (|Z|_0.01Hz) of the 5 wt.% Phen@MSP coating (2.27 × 10⁹ Ω·cm²) on Q235 carbon steel substrate is five orders of magnitude higher than that of the blank coating (8.79 × 10³ Ω·cm²). Salt spray tests demonstrate that the 5 wt.% Phen@MSP coating effectively suppressed corrosion propagation on the substrate. Full article

Background: Hepatitis B virus (HBV) infection continues to be a major public health concern, especially in sub-Saharan Africa, where widespread epidemics and restricted availability of long-term antiviral therapies result in higher mortality and morbidity rates. Drug repurposing represents a strategic approach to accelerate the discovery of effective therapies by leveraging agents with demonstrated antiviral and immunomodulatory activity. Product Nkabinde (PN) is a patented African polyherbal formulation initially developed for the treatment of HIV. Recent experimental studies demonstrate PN’s potent anti-HIV activity and significant immunomodulatory effects in human immune cells, implicating host-directed mechanisms relevant to chronic viral infections. This study combines an integrative application of network pharmacology and molecular docking to evaluate the repurposing potential of PN as a multi-target agent in HBV. Method: Bioactive components of PN were screened, and compound-associated targets were intersected with HBV-associated genes (proteins) to construct a protein–protein interaction (PPI) network. Topological analysis identified 10 hub targets (STAT1, STAT3, SRC, HCK, EGFR, SYK, PIK3CA, PIK3CB, PIK3R1, and PTPN11). Gene Ontology and KEGG pathway enrichment were performed with an FDR cut-off < 0.05. Significantly enriched pathways included JAK–STAT signaling, chemokine signaling, EGFR-TKI resistance, PI3K complex signaling, and viral infection pathways, particularly those related to Kaposi sarcoma virus and HSV-1, indicating immunoregulatory and antiviral roles. Molecular docking was performed using AutoDock Vina 1.1.2 to evaluate binding affinity and interaction mode of key PN phytochemicals against the hub proteins, and results were compared to their respective co-crystallized ligands. Results: Molecular docking indicated that major phytochemicals from PN exhibited significant binding affinities across all 10 hub host targets, typically outperforming or closely matching their respective co-crystallized ligands. The strongest contacts were observed for β-sitosterol–PIK3CB (−14.2 kcal/mol) and oleanolic acid–SYK (−14.0 kcal/mol), which were significantly stronger than the co-crystallized ligands (−7.9 and −8.3 kcal/mol, respectively), indicating robust stabilization within catalytic and regulatory pockets. Procyanidin B2 toward HCK (−10.5 vs. −7.9 kcal/mol) and PIK3CA (−9.5 vs. −7.3 kcal/mol), quercetin toward PIK3R1 (−10.6 vs. −8.2 kcal/mol) and PTPN11 (−9.2 vs. −7.5 kcal/mol), rutin toward SRC (−10.5 vs. 7.8 kcal/mol), and diosgenin toward EGFR (−9.4 vs. 8.4 kcal/mol). Procyanidin B2 maintained robust multi-hydrogen bonding networks, demonstrating significant binding, despite STAT1 and STAT3 docking showing identical affinities to co-crystals. Conserved hydrogen bonds, π–cation interactions, and significant hydrophobic packing at ATP-binding clefts and regulatory domains supported these interaction patterns, indicating competitive suppression of host signaling nodes taken over by HBV. Conclusions: Together, these results demonstrate that the components of PN possess strong multitarget binding capabilities across the PI3K/AKT, JAK–STAT, SRC-family kinase, EGFR, and SYK pathways, supporting their potential repurposing as host-directed HBV therapeutics with the ability to impede immune evasion, viral persistence, and HBV-associated oncogenic progression. Full article

This paper presents a novel voltage differencing transconductance amplifier (VDTA)-based mixed-mode inverse filter capable of operating in voltage mode, transadmittance mode, transimpedance mode, and current mode using a single topology. The proposed configuration employs only three VDTAs with two resistors and three capacitors, offering low component count, high input/output impedance flexibility, and no requirement for component matching. It simultaneously realizes first-order inverse lowpass and highpass, as well as second-order inverse bandpass responses. A comprehensive non-ideal analysis, which includes the effects of VDTA parasitic impedances, determines the practical operating frequency range. The design is validated through PSPICE simulations using 0.18 μm CMOS technology, showing close alignment between theoretical predictions and simulation results, with cutoff frequencies of approximately 1.60 MHz and low power consumption of 0.972 mW. Further analyses confirm orthogonal tuning capability, acceptable temperature stability, and robustness against component tolerances. In a practical application, the proposed inverse filter is employed to implement a mixed-mode PID controller, which significantly improves transient response characteristics by reducing rise time, settling time, and steady-state error. These findings highlight the effectiveness and versatility of the proposed design for analog signal processing and control system applications. Full article

This letter presents a Ku-band 2 × 2 patch array antenna that supports dual-polarization operation using a simple cooperative feed network. Depending on the selected input port of the proposed simple feed network, the 2 × 2 array antenna radiates either vertically or horizontally polarized waves. The proposed feed structure consists of two serially connected power dividers placed on the same geometrical plane, enabling dual-polarization without additional multilayer routing. The microstrip line-based feed network also enables a 180${}^{\circ }$ reversed placement of the radiating elements thereby improving the cross-polarization ratio of the proposed array antenna, achieving better than 30 dB across the operating band. The fabricated antenna, designed for a center frequency of 14.9 GHz with a 6.8% fractional bandwidth, demonstrates a realized gain higher than 10 dB for both polarization modes. Measurement results in terms of the input impedance bandwidth, isolation, gain, and cross-polarization ratio are in good agreement with simulation results. Full article