Search Results (11,698)

Background: Evening meal-timing chronotypes often exhibit lower calcium intake; however, whether this relationship remains significant after accounting for overall diet quality remains unclear. This study examined the association between meal-timing chronotypes and calcium intake and evaluated whether this association is maintained after adjusting for overall diet quality. Methods: This cross-sectional study analyzed 3465 adults aged 30–49 years from the 2016–2018 Korea National Health and Nutrition Examination Survey. Meal-timing chronotypes were identified using dynamic time warping-based K-means clustering of 24-h energy intake distributions. Survey-weighted linear regression assessed the association between meal-timing chronotype and calcium intake and tested their interaction with the Korean Healthy Eating Index (KHEI; excluding dairy) to evaluate the moderating effect of diet quality. Multinomial logistic regression was conducted to estimate odds ratios (ORs) for low calcium intake according to meal-timing chronotypes. Models were adjusted for age, sex, education, occupation, household income, and physical activity. Results: After adjusting for sociodemographic and lifestyle factors, the evening meal-timing chronotype was significantly associated with higher odds of low calcium intake (OR = 2.2, p < 0.001). A significant interaction between chronotype and KHEI tertiles on calcium intake was observed (p < 0.001). Specifically, while calcium intake generally decreased as diet quality declined, individuals with an evening preference consistently showed significantly lower calcium intake across all KHEI tertiles compared to the morning preference group (β = −7.9, p < 0.001). Conclusions: The evening meal-timing chronotype showed a significant association with lower calcium intake, which remained significant even after accounting for overall diet quality. These findings suggest that circadian-related eating patterns, rather than just overall diet quality, play a structural role in determining calcium intake. Full article

Background/Objectives: Cervical cancer, primarily driven by persistent high-risk HPV infection, remains a major global health issue. Xiao-ai-fei honey ointment, a traditional Uyghur multi-ingredient preparation, has shown clinical promise in cancer treatment, but its mechanisms against cervical cancer are not fully understood. This study aimed to investigate the potential molecular mechanisms of ethanolic extract of Xiao-ai-fei honey ointment (XAFHO) in cervical cancer using network pharmacology, single-cell RNA sequencing, and experimental validation. Methods: Differentially expressed genes (DEGs) in cervical cancer were identified from TCGA database. Active components and corresponding targets of XAFHO were retrieved from the TCMSP database, and disease targets were obtained from GeneCard, OMIM, and the TTD. Intersection targets were subjected to multivariate Cox and LASSO regression to construct a prognostic model. Immune infiltration, TMB, and MSI were compared between risk groups. Single-cell RNA-seq data were analyzed to determine cellular origins and inter-cellular communication. In vitro assays were performed on HeLa and SiHa cells to assess the anti-cancer activity of XAFHO. Molecular docking evaluated binding affinities between active compounds and core targets. The expression and functional roles of FASN and SPP1 were further validated by RT-qPCR, Western blotting, and siRNA transfection. Results: Sixty-three potential XAFHO targets were identified, and an 11-gene prognostic model was established, effectively stratifying patients into high- and low-risk groups with significantly different overall survival (AUC > 0.7). The high-risk group exhibited an immunosuppressive microenvironment and higher TMB. Single-cell analysis revealed that FASN and ACACA were predominantly expressed in tumor cells, while SPP1 was enriched in macrophages/monocytes. Tumor cells communicated with immune cells via the TGFB1–TGFβR1/R2 axis, promoting immune evasion. In vitro, XAFHO significantly inhibited proliferation, colony formation, migration, and invasion of cervical cancer cells. Molecular docking confirmed the strong binding of quercetin, kaempferol, and isorhamnetin to FASN and SPP1 (binding energy < –6.0 kcal/mol). Functional validation indicated that upregulated FASN and SPP1 contribute to malignant behaviors in cervical cancer cells. Conclusions: This study integrates network pharmacology with single-cell and experimental approaches to demonstrate that XAFHO exerts multi-target and multi-cell anti-cervical cancer effects, potentially by modulating lipid metabolism and immune-related pathways via FASN and SPP1. These findings provide a scientific basis for the therapeutic application of XAFHO in cervical cancer. Full article

Piezoelectric cantilever beam harvesters are widely considered for self-powered bridge monitoring, yet their performance is often constrained by resonance detuning under low-frequency ambient vibrations. This issue is particularly pronounced in bridge environments, where the dominant vibration frequencies are typically low and narrowly distributed. While several frequency tuning strategies have been proposed, their relative effectiveness under bridge-relevant conditions has not been systematically evaluated within a unified experimental framework. This study experimentally evaluated four tuning strategies for cantilever piezoelectric energy harvesters, i.e., spring tuning, magnetic tuning, tip mass adjustment, and beam length modification, to identify effective methods for matching the dominant frequency of bridge deck vibrations. A unified test platform using a common harvester configuration was established, and performance was quantified by resonant frequency alignment, maximum output voltage, and −3 dB bandwidth. Among the four methods, root-based spring tuning showed the best overall performance, achieving frequency matching while retaining strong electrical output, with a maximum voltage of 9.01 V and a bandwidth of approximately 1.5 Hz. Magnetic tuning also provided accurate frequency control, but reduced voltage by 15–25%. By contrast, tip mass and beam length tuning produced larger resonance shifts but caused voltage reductions of up to approximately 50%. Full article

Laser lift-off (LLO) is a critical process for separating ultra-thin polyimide (PI) films in flexible electronics manufacturing, yet traditional methods often induce thermal and mechanical damage due to high laser energy processing. To address this, we propose a low-threshold LLO method by integrating carbon nanotubes (CNTs) at the interface between a 500 nm PI film and a glass substrate. The interfacial thermal dynamics and separation quality were evaluated through finite element simulations and experimental validations using a 355 nm ultraviolet nanosecond laser. Results demonstrate that CNTs significantly enhance interfacial ultraviolet absorption and promote lateral heat diffusion due to their high axial thermal conductivity. This mechanism broadens the thermal decomposition zone and suppresses vertical heat transfer, thereby reducing the required LLO threshold from 180 mJ/cm² to 120 mJ/cm². Furthermore, the integration of CNTs reduces interfacial adhesion and alters the separation dynamics, resulting in the formation of smoother blisters with increased diameters and reduced heights compared to conventional LLO. These effects effectively minimize thermal and mechanical damage to the ultra-thin PI film and its integrated devices. This CNT-assisted LLO approach provides an efficient, low-damage solution for ultra-thin film separation, showing strong potential for advancing high-performance flexible electronics. Full article

Neighborhood-scale decarbonization is essential to achieving urban climate neutrality, yet existing methods often rely on complex, technology-intensive models that are difficult to implement in aging urban areas. This study introduces a simplified smart analysis method and decision-support framework to facilitate net-zero energy and emissions transitions at the neighborhood level through impactful, low-disruption interventions. Applied to a mixed-use neighborhood in Izmir, Türkiye, part of the European Union Mission for Climate-Neutral and Smart Cities, the methodology evaluates four intervention strategies: rooftop Photovoltaic systems, air-source heat pumps, solar-powered LED street lighting, and repurposing idle public spaces. The analysis quantifies energy demand, CO₂ emissions, and economic performance based on standardized data and incremental renovation scenarios. Results show that a gradual renovation approach, with a 10% annual replacement rate for heating systems, full rooftop Photovoltaic deployment, and street lighting retrofitting, can achieve a net-zero energy balance in 6–7 years. Redirecting fossil fuel and electricity subsidies to support renewable technologies makes these interventions economically viable within the same period. This framework demonstrates that neighborhood-scale climate neutrality can be attained without extensive structural changes, providing a replicable tool for cities with similar conditions aiming to meet European Union climate targets. Full article

The control code is an essential part of achieving energy-saving control in HVAC systems. Although there are existing methods for automatically generating control code, these methods still largely rely on expert knowledge for intervention. HVAC systems are highly personalized, with varying types of equipment, different quantities of equipment, and diverse data transmission protocols, all of which still require manual processing, resulting in low efficiency and a strong dependence on human input. To address this challenge, a method based on large language models is proposed. The basic idea is to leverage the understanding, reasoning, and coding capabilities of large language models, provide sufficient information to the model using the RAG (Retrieval-Augmented Generation) technique, and validate the accuracy of the code through a simulation model. By iterating repeatedly, the accuracy of the code is improved, ultimately enabling the automatic generation of control code. The evaluation used 173 laboratory rooms from an actual project to verify the efficiency and accuracy of this method. The results show that this method is highly efficient, processing a single room in just 5 min, and performs well under project-specific conditions, with a code generation accuracy of 97.1%. Full article

The purpose of this paper is to investigate the seismic damage performance levels of reinforced concrete (RC) external beam–column joints exhibiting beam flexural failure mode based on acoustic emission (AE) characteristics. To achieve this purpose, two specimens of RC external beam–column joints with beam flexural failure mode were tested under constant axial compression at the column and low-cyclic lateral loading at the end of the beam. During the tests, six AE-based indicators—namely AE hit ($H_{\mathrm{AE}}$), AE energy ($E_{\mathrm{AE}}$), AE count ($C_{\mathrm{AE}}$), amplitude ($A_{\mathrm{AE}}$), rise time (RT), and peak frequency ($f_{\mathrm{p}}$)—were measured using the PCI-2 Acoustic Emission System equipped with R6$\alpha$ piezoelectric sensors. In addition, five damage performance levels, i.e., no damage, minor damage, medium damage, serious damage, and collapse, were proposed based on the analysis of AE monitoring results. After calibration, the fiber finite element method was used to conduct a numerical simulation of 432 joints subjected to lateral loading. An empirical expression for the material parameter of the Park–Ang damage model was presented based on simulated results. Suggested five damage performance levels were used together with a response databank from the numerical analysis to obtain the limit damage values. This work provides a quantitative AE-based framework for seismic damage assessment of RC external beam–column joints with beam flexural failure mode, which can inform performance-based seismic design and post-earthquake safety evaluation. Full article

Edge computing has emerged as a promising paradigm to minimize latency and energy consumption while improving computational efficiency for mobile devices. Latency-sensitive applications such as autonomous driving, augmented reality, and industrial automation require ultra-low response times, making efficient task offloading a necessity in edge computing. However, distributing optimally computational tasks among edge servers remains a challenge, especially when considering latency, energy consumption, and workload balancing simultaneously. Although existing approaches have focused on one or two of these objectives, they do not provide a holistic solution that incorporates all three factors. In addition, some existing solutions do not take advantage of parallelism at the edge layer, resulting in bottlenecks and inefficient resource usage. In this paper, we propose a novel learning-based task offloading model that integrates parallel processing at the edge layer, adaptive workload balancing, and joint latency–energy optimization. Moreover, by dynamically adjusting the number of selected edge servers for parallel execution, our approach achieves optimal trade-offs between performance and resource efficiency. Our experimental setup includes several edge servers and several randomly deployed devices. It employs Apache HTTP Benchmark (AB) to generate realistic Mobile Edge Computing workloads. The obtained results show that our method outperforms existing approaches by reducing latency, lowering energy consumption, and maintaining a balanced workload across edge nodes. Full article

Background. Nanoparticle-mediated radiotherapy is a promising approach to enhance tumor radiosensitivity while reducing damage to healthy tissues. Particularly, melanoma is a highly aggressive malignancy with an increasing global incidence and limited therapeutic options in advanced stages, due to its intrinsic radioresistance and narrow therapeutic window in metastatic settings. In this study, we developed a systematic library of gadolinium-doped iron oxide nanoparticles (Fe-Gd NPs) with controlled compositions (0–75% Gd) to investigate the functional and compositional determinants of radiosensitization in melanoma. Methods. The physicochemical properties of the Fe-Gd NPs, including the morphology, crystallinity, and composition, were thoroughly characterized and correlated with biological responses. The biological evaluation was performed using both 2D and tissue-relevant 3D melanoma models, integrating metabolic viability assays (MTT/MTS), mitochondrial function (ATP quantification, MitoTracker analysis), and clonogenic survival following low-energy X-Ray irradiation (150 kV, 4 Gy). In vivo systemic tolerance and response in non-tumor tissues were investigated in BALB/C mice. Results. Our results showed that radiosensitization did not increase linearly with the Gd content, with the 25% Fe-Gd NPs being identified as a therapeutic window and having the most pronounced effect in melanoma cell models, while maintaining good systemic safety in vivo. This study provides functional evidence that nanoparticle-mediated radiosensitization is not only determined by a high Z content, but also by tumor-specific metabolic adaptability and the nanoparticle composition. Conclusions. These findings support the rational design of Fe-Gd nanoparticles with optimized therapeutic windows and highlight the importance of metabolic and 3D tissue-relevant models in preclinical evaluation of nanoparticle-mediated radiotherapy. Full article

Direct ocean carbon capture (DOC) has emerged as a promising strategy for mitigating atmospheric CO₂ levels and addressing ocean acidification. Unlike direct air carbon capture methods, DOC leverages the ocean’s vast carbon storage capacity, offering a scalable and efficient route for carbon dioxide removal. This systematic comparative review categorizes existing DOC methods into three types: (1) biological carbon capture, which relies on photosynthesis by microalgae and marine microorganisms; (2) electrochemical carbon capture, which utilizes water electrolysis to generate H⁺ and OH⁻ ions for pH-driven CO₂ removal; and (3) physical carbon capture, which employs hollow fiber membranes to directly separate CO₂ from seawater. For each technology, we evaluate efficiency, energy consumption, cost, technology readiness level (TRL), scalability, and major challenges. By integrating recent pilot data and providing a critical assessment, this review offers a roadmap for future research in direct seawater CO₂ capture. The comparative analysis reveals that electrochemical methods achieve the highest efficiency (60–85%) but face membrane fouling and electrode degradation challenges, while biological methods offer low-energy operation but suffer from slow kinetics and high harvesting costs, and membrane-based methods provide high removal rates (up to 94%) but require improved fouling resistance. Full article

High-value metabolites, such as antibiotics and enzymes, are primarily produced using filamentous fungi. However, their morphological complexity increases broth viscosity during biomass growth, hindering industrial scale-up by impairing both power input and mass transfer. The interaction between biomass growth, rheology, power input, and oxygen transfer is first addressed here by evaluating mycelial rheology and determining the volumetric mass transfer coefficient (k_La) (dynamic method) and oxygen uptake rate (respirometry) across different operating conditions. These confirmed that the mycelial broth’s pseudoplastic behavior significantly influences volumetric power input and k_La correlations. However, specific power input analysis revealed that operating at higher stirring rates (800 rpm) at higher cell-density cultures is 28.17% more energetically efficient than at low speeds (500 rpm). Furthermore, the oxygen supply-to-demand ratio, calculated via Excel model-fitting, allowed for the estimation of “metabolic power input” which represents the required energy to fit oxygen demand. Results also reveal that at 3.67 ± 0.34 g L⁻¹ of biomass effectively channel up to 51% of total energy toward aerobic metabolism, compared to only 17–30% for 0.73 ± 0.01 g L⁻¹ of biomass. These findings show that volumetric power inputs around 4 kW m⁻³ improve oxygen transfer efficiency, even at relatively high biomass concentrations. Full article

Direct methanol fuel cells (DMFCs) offer significant advantages including high energy density and rapid refueling, making them promising power sources for portable electronic products. However, their practical application, particularly in passive systems, is hindered by critical mass transport limitations: water flooding in the cathode and CO₂ bubble blockage in the anode. Herein, a novel dual-gradient patterned wettability current collector (CC) was designed to alleviate this mass transport impedance. The design uniquely integrates wedge-shaped gradients with surface energy gradients to create a unified, self-driven mechanism for efficient water and CO₂ bubble transport at both electrodes. A mathematical model was developed to quantitatively evaluate the effects of the dual-gradient structure. The results confirm that water removal is enhanced when the cathode current collector features a hydrophobic periphery with a dual-gradient patterned wettability interior on the gas-diffusion-layer side and a fully hydrophilic air-side surface, whereas an inverted pattern facilitates anode CO₂ removal. Optimal fabrication parameters on 316 L stainless steel were established by investigating laser scanning conditions and low-surface-energy agent concentrations. The experimental results show that the passive DMFCs incorporating the optimized current collectors delivered marked performance improvements. At 1 mol·L⁻¹ methanol, the novel anode and cathode current collectors increased peak power density by 15.6% and 14.5%, respectively. Electrochemical impedance spectroscopy revealed a 31.4% and 31.9% reduction in mass transfer resistance of the cell with novel anode and cathode current collectors, respectively, confirming improved gas–liquid self-driven efficiency. Furthermore, the new cells exhibited substantially enhanced long-term stability over 18 h of continuous discharge, attributed to the robust wettability achieved via laser–silane modification. Overall, these findings suggest that the proposed dual-gradient wettability design is a promising method for improving internal mass transport, potentially supporting the development of more robust passive DMFCs. Full article

Quadrotor motion planning in cluttered environments presents significant challenges in achieving both computational efficiency and trajectory smoothness, particularly in low-altitude economy and intelligent energy system applications where autonomous aerial vehicles perform infrastructure inspection and power line monitoring. Many existing methods either rely on sampling-based algorithms that suffer from long computation times and suboptimal paths, or employ trajectory representations that produce high-order derivative discontinuities unsuitable for agile flight. In this work, we propose an efficient hierarchical motion planning framework that integrates a JPS–Bresenham-based path search with safe flight corridor construction and Bézier curve optimization. Our approach addresses trajectory generation through a two-stage process: a front-end path search that efficiently identifies collision-free paths with reduced waypoints, followed by a back-end optimization that leverages convex safe corridors with overlapping regions to expand the solution space. Through comprehensive benchmark experiments across six different map scenarios, we demonstrate that our method outperforms RRT* and PRM in both path quality and computational efficiency. Monte Carlo experiments across varying map sizes and obstacle densities confirm robustness and scalability advantages. Comparative studies with state-of-the-art planners demonstrate superior success rates and cost efficiency while maintaining strict kinodynamic feasibility. The Bézier-based optimization reduces snap integral by up to 55% compared to ordinary polynomial approaches, demonstrating its superiority for fast quadrotor trajectory planning in complex environments. Full article

Asymmetric Cascaded Multilevel Inverters (ACMLIs) have emerged as a prominent solution for medium- and high-power applications due to their ability to provide an increased number of output voltage levels with fewer power switches. However, maintaining low total harmonic distortion (THD) and ensuring robust stability under varying operating conditions remain significant challenges. This study experimentally validates a voltage-feedback Proportional-Resonant (PR) control strategy for a seven-level ACMLI. Unlike conventional current-feedback methods, the proposed approach directly regulates the output voltage, providing superior harmonic suppression and enhanced steady-state accuracy. The stability and dynamic performance of the controller were theoretically analyzed using Bode diagrams and root locus methods, and further verified through the MATLAB Curve Fitting Tool (CFT) with a high correlation (R² = 0.9989). Experimental results demonstrate that the integration of the PR controller significantly improves power quality, reducing the current THD from 6.55% to 3.68% and the voltage THD to 2.94%. These findings confirm that the system fully complies with IEEE 519 standards and outperforms several existing strategies in the literature. The results establish the voltage-feedback PR control as a robust, high-precision, and practical alternative for power quality-oriented multilevel inverter applications in modern energy systems. Full article

Background/Objectives: KRAS G12C mutations define a clinically actionable subset of solid tumors, particularly non–small cell lung cancer. Clinical responses to approved covalent inhibitors remain limited by intrinsic and acquired resistance, highlighting the need for structurally distinct inhibitor scaffolds to expand therapeutic options. The objective of this study was to identify novel covalent binders targeting the KRAS G12C switch-II pocket through large-scale in silico screening and experimental validation. Methods: More than 1.9 million small molecules from diverse commercial libraries were screened using covalent docking, followed by multi-stage refinement incorporating molecular dynamics simulations, MM/GBSA free-energy estimation, and cancer-focused QSAR modeling. Results: This integrated workflow yielded 50 prioritized compounds spanning several chemically distinct scaffold classes. These candidates displayed favorable predicted binding energetics, stable ligand-protein interactions over extended simulation timescales, and low structural similarity to clinically approved KRAS G12C inhibitors sotorasib and adagrasib. Benchmarking against these clinical agents, using identical computational parameters, yielded comparable predicted binding energies for several candidate molecules. In cellular NanoBRET target-engagement assays, selected scaffolds, including K788-7251 and AN-989/14669131, exhibited sub-micromolar engagement of KRAS G12C with minimal endothelial cytotoxicity. Conclusions: Collectively, these findings identify structurally distinct, KRAS G12C inhibitor chemotypes and provide tractable starting points for the development of next-generation targeted therapies. Full article