Search Results (43,131)

Developing a Pueraria lobata compound beverage is of great significance for enhancing the utilization value of Pueraria lobata resources. However, its flavor balance, physical stability, and quality changes during storage require further investigation. This study aimed to develop a high-quality Pueraria lobata compound beverage and establish a reliable shelf-life prediction model. The optimal formulation was determined using orthogonal design and multi-index evaluation, including extract stock solution, mogroside, citric acid, and a composite stabilizer consisting of xanthan gum (XG) and sodium carboxymethyl cellulose (CMC-Na). GC-MS analysis identified multiple volatile compounds collectively forming the characteristic flavor profile. During storage, physicochemical properties, sensory quality, and active component contents changed to varying extents, with deterioration significantly accelerated at higher temperatures. Among the quality indicators, Zeta potential was selected as the most suitable predictor because it showed a strong correlation with sensory scores and fitted the first-order kinetic model well. Based on the established Arrhenius-based prediction model, the predicted shelf-lives of the Pueraria lobata compound beverage at 4 °C, 27 °C, and 37 °C were 193, 104, and 82 days, respectively. These findings provide a solid theoretical basis for formulation design, stability improvement, and shelf-life evaluation of functional Pueraria lobata beverages. Full article

To improve the accuracy and stability of X-ray pulsar time-delay estimation for multi-scenario celestial remote sensing and navigation, this paper proposes a time-delay estimation method based on a waterfall-plot multi-criteria framework and develops an end-to-end simulation framework for multi-scenario applications. First, a pulsar profile waterfall-plot model is built, and principal component analysis is performed to characterize candidate periodic structures. The contribution rate of the principal eigenvalue is used to describe the overall significance of the candidate period, and the projection variance of the first principal component is used to measure the prominence of the candidate pattern in the principal subspace. Second, support vector regression is used to fit the peak track of the waterfall plot, and a regression slope is used to describe the geometric stability of the candidate period. These three indicators are fused for pulsar period and time-delay estimation. Tests based on Insight-HXMT satellite observation data show that, compared with the ${\chi }^2$ and $Z^2$ test methods, our method improves time-delay estimation accuracy by 68.68% and 50.43%, respectively. Multi-scenario navigation simulations indicate positioning improvements of approximately 0.83 km, 3.04 km, and 1.05 km in the Earth-orbiting, Earth–Moon transfer, and Mars approach scenarios, respectively. These results suggest that the proposed framework can improve pulsar time-delay estimation and may provide useful measurement support for celestial remote sensing and navigation. Full article

A significant wave height (SWH) estimation method for X-band ocean radar images based on the shadow modulation principle is studied. The conventional shadow method obtains the wave steepness by analyzing the bright and dark patterns in the radar image and then calculates the SWH. The shadow method relies on accurate estimation of wave steepness, which is the most reliable in the upwave area, so it shows a strong azimuth dependence. Under the actual observation conditions, it is usually difficult to obtain an ideal analysis region to effectively mitigate the direction dependence due to the limitations of physical obstacles and platform attitude changes, which affects the inversion accuracy. To solve the problem, this paper proposes a wave steepness correction method based on harmonic fitting. By establishing a harmonic fitting model between wave steepness and wave angle, the method reconstructs the continuous and stable wave steepness distribution with wave angle from $0°$ to $360°$ according to limited data points. Then, the wave steepness independent of azimuth is obtained when the wave angle is $0°$. The effectiveness of the proposed wave steepness correction method is validated using a total of 466 sets of radar data collected from 8 November to 18 November 2014 and 10 January to 20 January 2015. After applying the wave steepness correction method, compared to the conventional shadow method without correction, although the correlation coefficient (CC) increased by only 0.07, the bias (BIAS) decreased by 0.12 m, and the average root mean square error (RMSE) decreased by 0.12 m. Full article

In this study, phenol adsorption from aqueous solutions was investigated using a carbonized adsorbent derived from a 1:1:1 mixture of banana, carrot, and potato peels, representing a major fraction of municipal bio-waste in Serbia. The material (CARB_BCP) was characterized by pH_pzc, SEM, FTIR, and BET analyses. The results indicated a highly porous structure with developed micro- and mesoporosity and a high specific surface area (S_BET = 483 m²/g). FTIR confirmed the formation of a stable aromatic carbon structure, while the high pH_pzc value (10.55) suggested a limited role of electrostatic interactions. Adsorption experiments performed at an initial phenol concentration of 1858 mg/L, room temperature, and an adsorbent dose of 0.1 g achieved a removal efficiency of 20.5%. The Langmuir model provided the best fit, indicating monolayer adsorption, with good agreement between theoretical (≈187 mg/g) and experimental (≈190 mg/g) capacities. Kinetic analysis followed the pseudo-second-order model, suggesting chemisorption as the rate-controlling step. The adsorption mechanism was mainly governed by π–π interactions, hydrophobic effects, and hydrogen bonding. These results demonstrate that CARB_BCP, derived from biodegradable waste, is a promising low-cost adsorbent for wastewater treatment. Full article

We evaluated the effects of a 12-week multidisciplinary program on health-related physical fitness and depressive symptoms in overweight and obese women (aged 45–64 years) diagnosed with noncommunicable diseases (NCDs). Methods: A longitudinal, pre-experimental, proof-of-concept study was conducted. Thirty-one women completed multidisciplinary interventions [nutritional education or psychoeducation (each once a week), and resistance training (twice a week)]. Body composition (bioelectrical impedance), physical fitness (maximal isometric strength, lower limb strength–endurance, flexibility, and aerobic fitness), and depressive symptoms (PHQ-9) were measured at baseline and post-intervention. Results: Significant improvements in body composition were observed in terms of lean mass (Δ% = 3.7; p < 0.001), fat-free mass (Δ% = 3.6; p < 0.001), skeletal muscle mass (Δ% = 5.2; p < 0.001), fat mass (Δ% = −3.5; p < 0.001), body fat percentage (Δ% = −4.7; p < 0.001), and visceral fat level (Δ% = −2.9; p = 0.012). Physical fitness exhibited a large effect size in the chair stand test (d = 0.91) and the 6 min walk test (d = 1.22). Depressive symptom scores substantially decreased (p < 0.001). Conclusion: The program demonstrated potential efficacy in mitigating sarcopenic obesity, enhancing functional capacity, and reducing depressive symptoms, indicating potential clinical viability for the integrated management of multimorbidity. Full article

Continuous streamflow monitoring is fundamental for water management in high-mountain Andean basins. Traditionally, this process relies on empirical regressions, although artificial intelligence (AI) has recently emerged as a robust alternative. However, extreme geomorphological dynamics compromise classical hydraulic methods, while AI models frequently lack physical validation. In this context, this study compares the performance of Artificial Neural Networks against traditional methods to reduce uncertainty in stage–discharge rating curves. The methodology, applied to a nested basin scheme in Loja, Ecuador, contrasted traditional exponential fits with a Multilayer Perceptron optimized using the Levenberg–Marquardt algorithm. The analysis included the evaluation of uncertainty bands and a sub-hourly spatial validation based on the principle of mass conservation. Results evidence that AI refines statistical accuracy (NSE > 0.95) and effectively adapts to bed non-linearity; nevertheless, cross-validation revealed a high susceptibility to algorithmic overfitting. It is concluded that while AI offers superior analytical flexibility for interpolating non-linear dynamics, traditional methods remain more robust for extreme flood extrapolation. Furthermore, while AI reduces computational complexity, it entails a higher “data cost” requiring denser field gauging campaigns. Operational viability requires rigorous dynamic uncertainty controls and spatial water balance validation. Full article

Enterprise systems are widely adopted in organizations, yet user acceptance remains a major challenge due to the complex interplay of cognitive, social, motivational, and innovation-related factors. Existing technology acceptance models often provide fragmented explanations by focusing on limited determinants. This study proposes TAM 4, an exploratory framework integrating constructs from the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), Hedonic-Motivation System Adoption Model (HMSAM), and Diffusion of Innovation (DOI). The study was conducted in the context of enterprise application usage and professional enterprise system training environments involving organizational users, trainees, and practitioners. Data were collected from 115 enterprise system users (trainees and practitioners). To consolidate overlapping indicators and strengthen construct definition, principal component analysis (PCA) was applied, yielding seven higher-order constructs that explain 81.642% of cumulative variance. The framework was validated using PLS-SEM with three scenario-based structural models (full mediation, partial mediation, and direct effects). The results show that Model 3 provides the best fit and predictive performance (SRMR = 0.048; NFI = 0.786), indicating that enterprise system adoption is better explained through a direct effect structure rather than a purely mediated TAM pathway. The novelty of this study lies in introducing TAM 4 as a PCA-driven multi-theory acceptance model and evaluating its explanatory robustness through multi-scenario model comparison, offering practical insights for improving enterprise system implementation strategies. Full article

In most metaheuristic approaches, particles are handled based on their fitness values without considering the distribution of solutions within the search space. Although this approach is simple, it causes particles to prematurely converge into a limited region of the search space due to the loss of diversity within the population. To address this limitation, this study proposes a metaheuristic approach in which particles are assigned to different search behaviors based on their Euclidean distance to the best solution. At each iteration, the population is divided into three groups: an exploitation set composed of the closest particles, an exploration set composed of the farthest particles, and a reference set composed of intermediate-distance particles. Two dedicated operators manage these groups: exploitation particles perform fine-grained refinement around the current best, whereas exploration particles search for new regions guided by randomly selected reference particles. In addition, an elitist acceptance mechanism ensures that only improved positions are retained, thereby promoting monotonic progress. This distance-based framework provides a distributed population of particles, where each particle is driven by its relevance to the optimal solution in the search space. This ensures a good diversity of solutions and prevents premature convergence and redundant search efforts. Experimental results on benchmark functions show that the method outperforms several State-of-the-Art metaheuristic algorithms in both solution quality and convergence behavior. Full article

Real-world information diffusion frequently spans multiple heterogeneous platforms and relational layers, making multilayer influence maximization (MLIM) a critical and challenging problem. Existing methods for multilayer networks often rely on local structural signals for surrogate evaluation, failing to accurately characterize multi-hop diffusion and inter-layer coupling effects. In discrete combinatorial search, meta-heuristic random exploration often disrupts the structural inheritance and reuse of effective node configurations, compromising search stability and quality. To address these challenges, this paper proposes a Probabilistic-Based Multilayer Slime Mold Algorithm (PB-MSMA). It employs the slime mold algorithm as its search framework to perform discrete combinatorial optimization within a controlled candidate space. It utilizes the Preference-based Expected Diffusion Value (P-EDV) as a surrogate fitness metric during the search phase. This design reduces the need for repeated Monte Carlo simulations for iterative candidate evaluation while improving the characterization of inter-layer and higher-order diffusion effects. Furthermore, a probabilistic pipeline mechanism is introduced to encode recurring effective node configurations from historical searches as statistical priors, guiding the search process to enhance structural inheritance and stability. After the seed sets are obtained, the final influence spread of all compared methods is evaluated using 10,000 Monte Carlo simulations under the MLIC model. Experiments on six real-world multilayer network datasets and nine seed budgets show that PB-MSMA achieves a dataset-level improvement range of 3.68–14.50% over representative baselines, including CELF, DPSOMIM, Degree, DIRCI, and PRGC, with an average improvement of 10.32%. These results indicate that PB-MSMA provides an efficient seed-selection strategy for multilayer diffusion scenarios where repeated simulation-based evaluation is costly. Full article

To overcome the limited high-temperature capability of silica-based fiber Bragg gratings (FBGs) and the accuracy degradation of gold-coated FBGs induced by residual stress, a temperature sensor based on a gold-coated FBG with high-temperature alloy packaging is proposed and fabricated. By introducing a high-temperature annealing pretreatment to the gold-coated fiber, residual stress is effectively relieved, enabling high-precision temperature measurement in high-temperature environments. Within the range of 20–800 °C, the annealed sensor achieves an accuracy of 0.72% F.S., a sensitivity of 9.65 pm/°C, and a linearity of 0.9997, in close agreement with theoretical predictions. After ambient vibration and high-temperature thermo-vibration tests, the maximum center wavelength shifts are 13 pm and 46 pm, corresponding to temperature variations of approximately 1.35 °C@24 °C and 4.77 °C@800 °C. These results demonstrate stable sensor performance under high-temperature testing conditions. In addition, a fitting formula applicable to different center wavelengths is proposed, significantly reducing calibration effort. The sensor features a simple structure, easy installation, and reliable performance, providing an effective solution for temperature sensing in extreme environments. Full article

This article argues that science literacy should explicitly include a history of science literacy component. Drawing on recent work in History and Philosophy of Science (HPS), the claim is that understanding current science requires the ability to assess the epistemic standing of scientific claims by considering historical patterns of theory change, stabilization, failure, and continuity. This proposal fits well with contemporary conceptions of science literacy and Nature of Science education, both of which increasingly emphasize evaluation, orientation, and evidence-based judgment. Starting from broad HPS consensus claims, the focus is on one particularly prominent HPS lesson: the relationship between scientific success and truth. On this basis, the article develops a simple classroom tool and illustrates it with a case study on the transition from the Old Quantum Theory to modern Quantum Mechanics. The proposal aims to help students avoid both uncritical endorsement of scientific claims and unwarranted skepticism in scientific reliability, and may thus contribute to a form of science literacy that is philosophically and historically informed. Full article

In modern reliability engineering, modeling bounded lifetime data under realistic experimental conditions is still challenging, especially when censoring schemes and unit removals are random. This study proposes a new and unified reliability framework by combining the flexible powering new power (PNP) distribution with a grouping-based progressive first-failure mechanism using a beta-binomial random design. The proposed approach explicitly accounts for the randomness in group removals, providing a more realistic description of practical life-testing experiments. Classical estimation is carried out using maximum likelihood methods with the Newton-Raphson algorithm, along with confidence intervals constructed under both standard and log-transformed parameterizations. To increase flexibility in inference, a Bayesian approach is developed based on a joint gamma and shifted log-normal prior, which respects parameter constraints and incorporates prior uncertainty. Since the posterior distributions cannot be obtained in closed form, a Metropolis-Hastings Markov chain Monte Carlo algorithm is used to generate reliable posterior estimates and credible intervals. Additionally, beyond sensitivity analysis, multiple prior robustness diagnostics are incorporated to ensure reliable hyperparameter calibration and to safeguard against prior misspecification. The performance of the proposed estimators is carefully examined through extensive Monte Carlo simulations under different censoring schemes and parameter settings. The simulation results indicate that the proposed Bayesian procedures often provide more stable estimation and shorter interval estimates with competitive coverage probabilities compared with the corresponding classical methods, particularly under moderate-to-heavy censoring settings. To demonstrate its practical usefulness, the proposed model is applied to two real datasets on tensile strength of carbon and polyester fibers, where it provides a good fit and useful insights into material reliability and failure behavior. In the same applications, the practical relevance and superior performance of the proposed distribution are demonstrated, where it outperforms existing bounded versions of several well-known models, including the gamma, Weibull, and Birnbaum-Saunders distributions. Overall, this work contributes to reliability analysis by offering a flexible and computationally efficient framework that accounts for both random censoring and complex lifetime patterns, with potential applications in engineering, materials science, and applied reliability studies. Full article

Physical inactivity and declining health-related physical fitness among college students are growing global public health concerns. High-intensity interval training (HIIT) is a time-efficient strategy to improve multiple components of health-related physical fitness. Emerging evidence suggests that exercise timing may influence physiological responses and adherence through circadian rhythm regulation; however, its feasibility in college settings, particularly in China, remains unclear. This study aims to evaluate the feasibility and preliminary effectiveness of an eight-week time-specific HIIT programme among Chinese college students, and to compare outcomes between morning and evening training. In this mixed-methods feasibility randomized controlled trial, approximately 72 students with low physical activity levels and intermediate chronotype will be randomly assigned to a morning HIIT group, evening HIIT group, or control group. Intervention groups will complete three HIIT sessions per week for eight weeks. Primary outcomes include feasibility indicators (recruitment, retention, adherence, and data completeness). Secondary outcomes assess changes in body composition, cardiorespiratory fitness, muscular strength, endurance, and flexibility. Quantitative data will be analysed using descriptive and repeated-measures methods, while qualitative interviews will be thematically analysed. Findings will inform the feasibility and design of future large-scale trials and contribute to chrono-exercise research in college populations. Full article

How older adults psychologically appraise their health while managing multiple chronic conditions is a behavioral-science question as much as a clinical one. This study estimated the weighted prevalence of favorable mental-health self-appraisal, identified its behavioral, social, and functional correlates, and compared the relative salience of diagnosed-condition burden and functional limitation among U.S. adults aged ≥ 50 years with multimorbidity. This retrospective cross-sectional secondary analysis used the 2023 Medical Expenditure Panel Survey (MEPS) Full Year Consolidated Data File (HC-251). Multimorbidity was defined as at least two diagnosed chronic priority conditions. The primary outcome represents favorable mental-health self-appraisal, derived from MNHLTH53 (excellent/very good/good vs. fair/poor). Covariates were organized using Andersen’s Behavioral Model and health-psychology concepts of adaptation, resources, and lived functional burden. Weighted prevalence estimates and survey-weighted logistic regression models were fitted using PERWT23F, VARSTR, and VARPSU. Robustness checks examined a stricter outcome threshold, proxy adjustment/non-proxy restriction, and a physical-health extension model. The analytic sample included 5523 respondents, representing approximately 77.9 million U.S. adults aged ≥ 50 years with multimorbidity. The weighted prevalence of favorable perceived mental-health self-appraisal was 86.6% (95% CI 85.4–87.7). In the fully adjusted core model (complete-case n = 5330), age 65–74 years (aOR 1.52, 95% CI 1.17–1.98) and age ≥ 75 years (aOR 1.79, 95% CI 1.36–2.36) were associated with higher odds of favorable appraisal. Lower odds were observed for Hispanic respondents, non-Hispanic Asian respondents, lower educational attainment, lower income, non-employment, ≥4 diagnosed conditions, and any functional limitation. The strongest inverse association was limitation status (aOR 0.32, 95% CI 0.27–0.39). Sensitivity analyses were directionally consistent. Favorable mental-health self-appraisal remained common in this medically complex older population, but it was socially and functionally patterned. Functional limitation appeared more behaviorally salient than diagnosis count alone. Because the analysis was cross-sectional and based on household-interview reported measures, these results should be interpreted as associations rather than causal effects. Full article

Background and Clinical Significance: Cutaneous paraneoplastic phenomena are infrequently characterised in colorectal cancer (CRC), and chronic pruriginous inflammatory eruptions in particular have received limited attention. In older adults, persistent treatment-resistant dermatoses of unclear aetiology may represent overlooked extraintestinal diagnostic clues to occult malignancy, including potentially curable CRC. Faecal immunochemical testing (FIT) for occult bleeding is a low-cost, non-invasive tool whose role outside conventional alarm-symptom triage remains underexplored. Case presentation: A 72-year-old woman presented for outpatient evaluation with several months of pruriginous, pustular, and crusted symmetric eruption involving the dorsal aspects of the limbs, refractory to standard dermatologic treatment, and without gastrointestinal symptoms. A non-invasive systemic stool-based work-up demonstrated detectable faecal haemoglobin (iFOBT), mildly elevated faecal calprotectin (51.6 mg/kg, ULN 50 mg/kg), markedly elevated faecal alpha-1-antitrypsin (631 µg/mL; 2.3× ULN), and predominance of Escherichia coli on stool culture. Colonoscopy revealed a locally advanced rectal adenocarcinoma; staging classified the lesion as cT3N1M0. The patient received long-course neoadjuvant chemoradiotherapy (50 Gy, concurrent capecitabine) followed by low anterior resection with total mesorectal excision and pathological complete response (ypT0N0, R0), and adjuvant capecitabine. The cutaneous eruption resolved progressively in parallel with antineoplastic therapy without specific dermatologic intervention. The patient remains in remission at over 36 months. Conclusions: Persistent, unexplained, treatment-resistant pruriginous/pustular cutaneous eruptions may, in selected patients, coincide with an underlying malignancy, including colorectal cancer, and should prompt careful individualised clinical assessment, including review of age-appropriate colorectal cancer screening status. This single case raises the hypothesis that quantitative faecal immunochemical testing (FIT) may be prospectively evaluated as a low-cost, non-invasive triage tool in carefully selected patients aged ≥50 years with persistent dermatoses of unclear aetiology, even in the absence of gastrointestinal symptoms. Positive FIT results should be managed according to established local colorectal referral pathways. NICE diagnostics guidance DG56 supports FIT use in symptomatic adults with suspected lower gastrointestinal pathology; however, any extension of FIT to extraintestinal presentations remains investigational and requires formal validation through prospective studies assessing diagnostic yield, cost-effectiveness, and stage distribution. Full article