Search Results (2,672)

Background: Body mass index (BMI) is commonly used to assess nutritional status; however, it cannot distinguish between fat and lean tissue. In young adults, this limitation may mask excess adiposity and distort diet–adiposity associations. Bioelectrical impedance analysis (BIA) provides more detailed measures, including percent of body fat (PBF), skeletal muscle mass (SMM), and the visceral fat level. Objectives: To examine how combining BMI with BIA-based classifications of adiposity influences the assessment of diet–body composition associations in young adults. Methods: This cross-sectional study of 285 young adults (median age 18 years, IQR: 18–20) used InBody BIA to classify participants by BMI and PBF. Dietary habits were assessed via food frequency questionnaire covering eight food groups. Group comparisons used Mann–Whitney U tests with Cohen’s d effect sizes; correlations used Spearman’s rank correlation. Results: Thirty-five participants (12.3%) were BMI-Normal but PBF-High (normal BMI with elevated body fat), a phenotype missed by BMI screening; overall BMI-PBF agreement was 75.4%. Physical activity (IPAQ) correlated significantly with body composition markers, PBF (rho = −0.177, p = 0.003) and SMM (rho = +0.186, p = 0.002), but not with BMI (rho = +0.060, p = 0.310). BMI showed an inverse association with self-reported sweets consumption (rho = −0.138, p = 0.020), likely reflecting a reporting bias rather than true intake, as this pattern disappeared when examining actual adiposity (PBF: rho = +0.032, p = 0.591). Conclusions: Combining BIA with BMI may improve the detection of elevated body fat (12.3% prevalence of normal BMI with elevated body fat); BMI-based screening may not identify all individuals with elevated body fat. Physical activity associations support the complementary value of BIA alongside BMI. Apparent diet–BMI associations may be confounded by adiposity misclassification and reporting bias. Full article

The characterization of supercapacitors (SCs), particularly electric double-layer capacitors (EDLCs), is useful for the design of energy management systems. This article presents a five-parameter dynamic model based on electrochemical impedance spectroscopy (EIS) data. Unlike conventional fixed-parameter models, this study explores an approach that accounts for voltage dependence. The model was evaluated using four commercial 58-farad SCs over a frequency range of 10 mHz to 300 kHz and at voltages ranging from 6.25% to 93.75% of the nominal value. The results show that the parameters vary with the state of charge; for example, the effective capacitance increased by up to 24% when moving from 6.25% to 50% of the nominal voltage. The model, fitted using nonlinear optimization algorithms, has a mean square percentage error (MSPE) of less than 3%. This approach estimates the dynamic behavior of the SCs, facilitating the simulation and tuning of management and protection strategies. Full article

Maintaining voltage stability and minimizing power losses for remote marine loads powered by long submarine cables is the challenging context of this paper. Flexible Alternating Current Transmission Systems (FACTS) are well-studied for terrestrial grids. However, their comparative performance and efficiency in the context of high-capacity submarine links remain a gap in the literature. This paper presents a rigorous analysis of the performance of a Unified Power Flow Controller (UPFC), Static Synchronous Series Compensator (SSSC), and Thyristor Controlled Series Capacitor (TCSC). A mathematical framework is developed to introduce the “solution circle” concept, which demonstrates that the series impedance values required to maintain a specific load voltage define a circle in the complex plane. A theoretical analysis is performed, revealing that the UPFC, with its two degrees of freedom, is significantly more efficient because it can select the minimum impedance magnitude on this circle. In contrast, SSSC and TCSC are limited to the reactive axis, which, under certain operating conditions, may not cross the solution circle; therefore, they may not meet the power quality objective. The results of a practical case study show that UPFC requires approximately half the rated power (22.4 MVA) compared to its counterparts (39.4 MVA) to achieve the same control objectives. Full article

Translating heterogeneous user requirements (URs) into robust engineering specifications for public-access products is a critical challenge, often impeded by information uncertainty and fragmented design processes. To address this, we propose an integrated decision-making framework underpinned by Rough Set Theory (RST) as a unified mathematical language for uncertainty management. The framework systematically guides customer-driven product development by integrating a series of RST-based methods: a Kano model analysis to screen URs, a novel rough-Shapley value model to determine their interdependent weights, a rough-QFD approach to translate them into weighted design requirements (DRs), and the rough-VIKOR method to select the optimal design alternative. A case study on public-access faucets validates the framework’s efficacy. The results demonstrate its capability to identify critical URs, derive robust DRs by systematically resolving technical attribute conflicts, and select a superior design solution that optimally balances hygiene, durability, and user experience. The application of the framework successfully identified Alternative ${\mathrm{A}}_1$ (Push-Activated Spout) as the optimal solution, demonstrating superior performance in proactive hygiene and core functionality. The results prove that maintaining data integrity through a unified RST pipeline effectively resolves early-stage design conflicts. This research contributes a rigorous, data-driven decision support system that enhances objectivity and information fidelity, providing a transparent and auditable methodology for designing human-centered public infrastructure. Full article

This work presents the design of a compact, wideband circular microstrip patch antenna for microwave imaging-based brain tumor detection. The main contribution is the development of a compact antenna structure incorporating enhanced ground-plane slot modifications, which significantly improves impedance bandwidth while maintaining a small electrical size, making it highly suitable for medical imaging systems. In addition, the study integrates antenna design, safety evaluation, and microwave imaging analysis within a unified framework to assess tumor localization feasibility using a realistic head model in CST Microwave Studio. The proposed antenna is fabricated on an FR-4 substrate with dimensions of 37 × 54.5 × 1.6 mm³, corresponding to an electrical size of 0.176λ × 0.260λ × 0.0076λ at the lowest operating frequency of 1.43 GHz. Ground-plane slot enhancements are introduced to achieve wideband performance, resulting in an impedance bandwidth from 1.43 to 4 GHz and a fractional bandwidth of 94.7%. The antenna exhibits a maximum realized gain of 3.7 dB. To evaluate its suitability for medical applications, specific absorption rate (SAR) analysis is performed using a realistic human head model at multiple antenna positions and at 1.5, 2.1, 2.5, 3.3, and 3.9 GHz frequencies. The computed SAR values range from 0.109 to 1.56 W/kg averaged over 10 g of tissue, satisfying the IEEE C95.1 safety guideline limit of 2 W/kg. For tumor detection assessment, time-domain simulations are conducted in CST Microwave Studio using a monostatic radar configuration, where the antenna operates as both transmitter and receiver at twelve angular positions around the head with 30° increments. The collected scattered signals are processed using the Delay-and-Sum (DAS) beamforming algorithm to reconstruct dielectric contrast maps and localize the tumor. It should be noted that the tumor-imaging demonstrations presented in this work are based on numerical simulations, while experimental validation is limited to the characterization of the fabricated antenna. Nevertheless, the findings indicate that the proposed antenna is a promising candidate for noninvasive, low-cost microwave brain tumor imaging applications. Full article

Despite substantial research conducted over the past decades, the transition to a circular construction industry remains in its infancy. The deconstruction of buildings to recover materials for reuse is recognized as a promising strategy for advancing circularity. However, terminological ambiguity and a lack of conceptual consensus continue to lead to misinterpretation and may impede theoretical and practical progress. Based on a systematic literature review of 51 academic and non-academic sources, this paper analyzes the use of core terminology related to deconstruction processes. Ten central terms and expressions are identified, among which ‘demolition’ and ‘deconstruction’ are the most consistently applied, whereas ‘selective demolition’ is used with varying interpretations. To further document the current state of terminology in the field, a glossary of general terms commonly employed is also presented. Clear communication and the explicit definition of applied terms are essential to ensure efficient on-site construction processes and the relevance and value of future studies in this field. To this end, this study aims to enhance transparency and contribute to coherence within the terminological landscape of deconstruction research. Full article

This paper introduces a compact sub-6 GHz multiple-input multiple-output (MIMO) antenna array developed for 5G smartphone applications. The design employs eight planar inverted-F antenna (PIFA) elements arranged to realize dual-band and dual-polarized operation. The antenna achieves impedance bandwidths of 3.3–3.7 GHz (11.4%) and 5.3–5.8 GHz (10%), covering key sub-6 GHz fifth-generation (5G) bands. To enhance diversity performance, the elements are distributed along the edges of the smartphone mainboard, enabling excitation of orthogonal polarization modes while maintaining an overall board size of 75 mm × 150 mm on an FR4 substrate. Even without the use of dedicated decoupling structures, the closely spaced antenna elements exhibit satisfactory isolation levels, varying between −12 dB and −22 dB across the operating bands. The antenna array achieves wide impedance bandwidths of approximately 400 MHz at 3.5 GHz and more than 500 MHz at 5.5 GHz, supporting high data-rate communication. In addition, the proposed system demonstrates very low correlation and active reflection, with envelope correlation coefficient (ECC) values below 0.002 and total active reflection coefficient (TARC) levels better than −20 dB. User interaction effects are also investigated, and the results confirm acceptable SAR levels and stable radiation behavior in the presence of the human body. Owing to its planar, dual-band/dual-polarization capability and compliance with safety requirements, the proposed antenna represents a promising practical solution for contemporary 5G handheld devices and future multi-band mobile platforms. Full article

Background: Changes in body composition, such as decreased muscle mass and increased adipose tissue, are significant in older adults, impacting health, functional capacity, and increasing the risk of metabolic diseases, functional decline, and frailty. Bioelectrical Impedance Analysis (BIA) is a non-invasive tool for assessing body composition, including fat-free mass (FFM), skeletal muscle mass (SMM), and fluid distribution (e.g., ECW/TBW ratio). Complementing BIA, the Mini Nutritional Assessment (MNA) serves as a validated tool for identifying malnutrition risk in the elderly. This study aimed to understand the correlation between BIA-derived parameters, MNA scores and clinical outcomes. Methods: This cross-sectional study involved 195 older adults (mean age 72.8 ± 5.4 years), divided into two groups based on body composition profiles determined by cluster analysis. Data collected included demographics, comprehensive BIA parameters (BMI, fat mass, FFM, SMM, ECW/TBW, phase angle), MNA scores, self-assessed health, chronic disease prevalence, frailty index (TFI), and functional limitations (EQ-5D). Statistical analyses included descriptive statistics, t-tests/ANOVA, chi-square tests, Pearson’s/Spearman’s correlations, point-biserial correlations, regression analyses, and ROC curve analysis to compare groups, explore variable relationships, and assess predictive abilities for malnutrition risk. Results: The first group had significantly higher BMI, AFM (AFM), FFM, and SMM, but a lower ECW/TBW ratio compared to Group 2 (N = 115), which was predominantly female and had higher frailty scores. MNA scores showed significant positive correlations with FFM (rho = 0.165, p = 0.021) and SMM (rho = 0.182, p = 0.011), and a negative correlation with ECW/TBW (rho = −0.188, p = 0.008). Higher adiposity (BMI, fat mass) correlated positively with arterial hypertension and obesity. Lower FFM and SMM were negatively correlated with gastroesophageal reflux disease. Skeletal muscle mass (AUC = 0.634, cut-off ≤ 17.3 kg) and ECW/TBW ratio (AUC = 0.626, cut-off ≥ 49.7%) showed modest discriminatory capacity to identify malnutrition risk. Individuals at risk of malnutrition reported greater functional limitations and lower self-assessed health. Numerous BIA parameters, including segmental muscle mass, total body water, phase angle, and impedance values, significantly correlated with MNA scores. Conclusions: The study highlights the importance of body composition analysis, particularly BIA, in correlation with MNA, for assessing nutritional status, functional limitations, and chronic disease associations in older adults. Integrating BIA and MNA into geriatric assessments provides a complementary profile of nutritional and functional vulnerability. Full article

Aiming at the problem that insulation fault location in multi-branch cable networks of train DC medium-voltage power supply systems is disturbed by impedance mismatch at the injection end, this paper proposes an impedance matching method based on a resistance–capacitance composite coupling network to suppress false reflections and improve location accuracy. Firstly, the mechanism of multiple false reflections caused by injection-end mismatch is theoretically analyzed, and the expression of reflected waves and their influence on waveform superposition are derived. On this basis, an RC coupling network is designed to achieve effective matching between the measurement end and the cable characteristic impedance (about 97 Ω) within the 8–12 MHz frequency band, suppressing the amplitude of false reflections to less than 2% of the incident wave. Verification through MATLAB R2022b/ANSYS Q3D 2024R2 co-simulation and a 1:8 scaled experimental platform shows that the proposed coupling network reduces the absolute fault location error in a multi-branch network from 6.936 m to 0.188 m, decreases waveform distortion by about 40.8% and lowers the equivalent noise enhancement factor by about 55.2%. This study provides a reliable front-end matching solution for accurate fault location in complex cable networks, with clear value for engineering applications. Full article

Today’s distribution networks are becoming increasingly complex, necessitating highly accurate and robust fault diagnosis methods. Traditional methods based on impedance or traveling waves often lack flexibility and precision in these dynamic environments. This study proposes a hybrid approach based on the synergy between machine learning (ML) techniques and a recent metaheuristic, the Northern Goshawk Optimizer (NGO). Fault location is performed using a cubic spline interpolation model. Classification is handled by a decision tree, while fault resistance—a key parameter that significantly influences diagnostic performance—is optimized using the NGO algorithm. The effectiveness of the proposed method is evaluated through a series of experiments conducted on the IEEE 34-bus test network. These experiments encompass various fault scenarios (single line-to-ground, line-to-line, double line-to-ground, and three-phase faults) as well as voltage and load variation conditions. Fault resistance values considered in the study are 0, 10, 50 and 100 ohms. The results highlight the robustness and efficiency of the hybrid approach, achieving an accuracy rate of up to 99.999% in fault location. This level of performance enables reliable identification of both the fault location and the affected line. Full article

This study presents a computational, simulation-based investigation of the dielectric response of human hand tissues, skin, fat, muscle, and bone to radiofrequency (RF) electromagnetic fields emitted by mobile devices. The widespread adoption of handheld devices and the deployment of fifth-generation (5G) networks, including millimetre-wave (mmWave) bands, have intensified concerns regarding localized human exposure to RF radiation, particularly in the hand, which serves as the primary interface during device operation. Using validated dielectric property datasets, numerical simulations were performed across the frequency range of 0.5–40 GHz, employing the Finite-Difference Time-Domain (FDTD) method to solve Maxwell’s equations, with analytical evaluations conducted in Maple-18. A heterogeneous multilayer hand phantom was developed, and simulations were conducted under controlled exposure conditions, including a transmitted power of 1 W, antenna gain of 2 dBi, and incident power density of 5 W/m², consistent with ICNIRP and NCC safety guidelines. Tissue responses were assessed over a temperature range of 10–40 °C to account for thermal variability. The results demonstrate strong frequency- and temperature-dependent behaviour of dielectric properties, intrinsic impedance, reflection coefficient, attenuation, and specific absorption rate (SAR). At lower frequencies (<1 GHz), RF energy penetrated more deeply with distributed absorption and relatively low SAR values, whereas higher frequencies (3–40 GHz) produced highly localized absorption in superficial tissues, particularly skin and muscle. Increasing temperature led to significant increases in permittivity, conductivity, and SAR, with up to a twofold enhancement observed between 10 °C and 40 °C. These findings confirm that 5G and mmWave exposures result in predominantly surface-confined energy deposition in hand tissues. The study provides a robust computational framework for evaluating hand device electromagnetic interactions and offers quantitative insights relevant to antenna design, exposure compliance assessment, and the development of evidence-based safety guidelines. Full article

The travertine formed through the precipitation of supersaturated calcium carbonate from geothermal or surface waters due to CO₂ degassing, evaporation, and biological activities not only exhibits remarkable landscape value but also holds significant scientific importance in geological research. Current conservation efforts face critical challenges including travertine degradation, increased algal biomass accumulation, and progressive marshification processes. The study focused on how Vallisneria natans (V. natans) and Ceratophyllum demersum (C. demersum) affected travertine deposition. Analyzing the physical and chemical parameters, phase structure, crystal morphology, and microbial community in the aquatic environment, it was observed that under conditions of low c (Ca²⁺) concentration in solution (≤100 mg L⁻¹), both species significantly increased the rate of travertine deposition. The effect of plant biomass was species-specific: V. natans showed the highest promotion at 70 g L⁻¹, while C. demersum performed effectively at moderate biomass levels (140 and 280 g L⁻¹). Specifically, C. demersum exhibited enhanced photosynthetic activity, elevated pH, increased dissolved oxygen (DO) content and more epibiotic microorganisms, with higher levels of Aeromonas compared to V. natans. Therefore, C. demersum demonstrated a greater capacity for travertine deposition. However, the culture environment with elevated c (Ca²⁺) ≥ 500 mg L⁻¹ or higher biomass levels (420 g L⁻¹) impeded the stable growth of submerged plants and exerted a stress effect on them, hindering travertine deposition. The morphology of travertine crystals promoted by the two submerged macrophytes was distinct. In the V. natans treatment, the crystals were square and elongated, whereas in the C. demersum treatment, they were spheraragonite, droplet-like, and petal-shaped. This study reveals the mechanisms by which submerged macrophytes promote travertine deposition and provides new insights for adopting nature-based ecological restoration strategies to sustainably maintain travertine landscapes. By leveraging the promoting effects of submerged macrophytes, travertine deposition and the aquatic environment were improved while reducing energy and chemical inputs. Such biological regulation approaches help synergistically achieve the dual objectives of geological heritage conservation and ecosystem health restoration. Full article

Environmental transparency in food manufacturing requires efficient carbon footprint data collection, yet multi-departmental coordination often creates time-consuming, fragmented processes that impede adoption. This study applies lean office methodologies to optimize carbon footprint assessment processes in food manufacturing. Using a case study approach at a Thai food processing facility, we implemented flow process charts, value stream mapping, eight waste analysis, and ECRS methodology to evaluate the data collection process for strawberry jam production. The baseline assessment documented 142 activities across 12 departments, requiring 17,540 min. The lean interventions included establishing a centralized cross-functional team, developing standardized data collection templates, implementing a unified digital repository system, and consolidating redundant verification procedures. The improved process reduced activities from 142 to 63, decreased the required time from 17,540 to 11,190 min (36.2% reduction), and eliminated 95.8% of non-value-added activities while maintaining regulatory compliance. These efficiency gains enable more frequent environmental assessments and facilitate the broader adoption of carbon footprint measurement within resource-constrained manufacturing contexts. The study demonstrates that lean principles effectively optimize environmental assessment processes themselves, providing a replicable framework adaptable across diverse food manufacturing facilities and product lines while addressing critical adoption barriers including resource constraints and administrative complexity. Full article

Urban business-to-business distribution in Casablanca relies heavily on light commercial vehicles (LCVs) operating in a constrained street environment where loading/unloading access, intersection capacity, and recurring bottlenecks jointly shape performance and environmental impacts. However, high-resolution freight origin–destination (OD) observations and junction calibration data are limited, which complicates direct estimations of congestion and externalities attributable to commercial activity. This study develops a reproducible, large-scale modeling workflow that couples tour-based freight demand generation in order units with simulation-based traffic assignment (SBA) on a metropolitan network and translates network performance into emissions and monetary losses. Warehouses are modeled as primary producers and commercial activity zones as attractors via sector-tagged production and attraction functions; the resulting order distribution is converted to OD vehicle trips using the tour-based trip generation procedure with the mean targets-per-tour fixed to one to ensure numerical stability, yielding a direct-shipment approximation appropriate for stress–response analysis. Junction impedance is represented through turn-type volume–delay relationships and node-level impedance procedures, and congestion is evaluated using vehicle kilometers traveled/vehicle hours traveled (VKT/VHT)-based indicators, delay-intensity measures, and link/node bottleneck rankings. Across demand-scaling scenarios, VKT increases from 302,159 to 1,017,686 veh·km/day, while network delay rises nonlinearly from 392.5 to 2738.4 veh·h/day, indicating saturation-driven amplification of time losses. The Handbook of Emission Factors for Road Transport (HBEFA)-compatible emission estimates scale with activity: total carbon dioxide (CO₂) increases from 154.1 to 519.5 t/day, and nitrogen oxides (NOx) and particulate matter (PM_2.5) totals rise proportionally under fixed fleet assumptions. Monetizing delay with a purchasing-power-adjusted value-of-time range yields a congestion cost per trip that increases from approximately 0.20 to 0.41 Moroccan dirham, MAD/trip (at 60 MAD/veh·h), consistent with rising delay intensity. Bottleneck extraction shows welfare losses to be structurally concentrated on a small persistent corridor set, led by ‘Boulevard de la Résistance’, with recurrent hotspots including ‘Rue d’Arcachon’ and ‘Rue d’Ifni’. The framework supports policy-relevant reporting of congestion, emissions, and welfare impacts under data scarcity, with explicit sensitivity bounds. Full article

Background and Objectives: Weight gain during winter holidays has been reported in several studies, but most of them focus on short-term changes and rely primarily on body weight or BMI. This study investigates if body composition alterations associated with winter holiday period persist over a one-year follow-up in a Romanian adult population. Materials and Methods: This prospective longitudinal observational study included three assessment points: before the winter holidays (T1), immediately after the holidays (T2), and one year later (T3). Bioelectrical impedance analysis was used to obtain body composition parameters. A total of 120 participants completed all three assessments and were included in the longitudinal analysis. Results: Body weight and visceral fat area increased modestly yet significantly between T1 and T2. At the one-year follow-up, values remained similar to those observed immediately after the holiday period, suggesting persistence at group level (body weight: 68.25 → 69.40 → 69.45 kg and visceral fat area: 98.49 → 100.54 → 101.42 cm²). The net change observed during the holiday period was similar in magnitude to the overall annual difference. Changes in body weight were significantly associated with changes in visceral fat both during the holiday period and across the entire follow-up. Conclusions: Modest increases in body weight and visceral fat observed during the winter holidays were still present at one year. These findings suggest that short seasonal periods may contribute to overall annual changes in body weight and fat distribution. Full article