Search Results (9,346)

Background: Abdominal aortic aneurysm (AAA) is a multifactorial vascular disease with limited therapeutic options, as no pharmacological treatments currently exist to mitigate the progression of small AAAs. Quality of life (QoL) has emerged as a valuable supplementary metric for assessing the efficacy of pharmacological interventions. This study evaluated QoL scores of MetAAA trial patients on metformin therapy compared to those with placebo intake. Methods: Overall, 54 patients with AAA were included in the MetAAA trial (ClinicalTrials.gov-Identifier:NCT03507413) and randomized to either metformin or placebo treatment. All participants were asked to complete three established and validated (in total 659 longitudinally collected) QoL questionnaires: (1) the 36-Item Short Form Health Survey (SF-36), (2) the Aneurysm Symptom Rating Questionnaire (ASRQ), and (3) the Aneurysm-Dependent Quality of Life questionnaire (ADQoL). Results: A superior health-related QoL was found in metformin-treated AAA patients compared to enrolled AAA patients receiving a placebo. In detail, AAA patients undergoing metformin treatment showed a superior overall current QoL score (p = 0.038), general health perception (p = 0.013), improved physical functioning (p = 0.004), and increased energy/lower fatigue scores (p = 0.008). Furthermore, fewer limitations due to cognitive distress (p = 0.001) and lower limb function (p = 0.021) were detected. Other QoL subscales did not show statistical significance. Inflammatory blood parameters suggest that while systemic inflammation may have some impact on perceived QoL, the relationship is largely limited. Conclusions: In patients with small AAA, metformin led to a limited improvement in health-related QoL compared to a placebo. Full article

Over 292 million tons of municipal solid waste (MSW) are generated annually in the United States, with more than half disposed of in landfills. Municipal solid waste landfills (MSWLFs) are stationary sources of air pollution and potential health risks for nearby communities. The Agency for Toxic Substances and Disease Registry (ATSDR) has completed over 300 public health assessments (PHAs) and related investigations at MSWLFs and open dumps since the 1980s. This paper reviews the ATSDR’s evaluations of air pathway concerns at 125 MSWLF sites assessed between 1988 and early 2025, with many being evaluated during the 1990s. Most sites were located in the Midwest and Northeast, and only 25% remained active. The ATSDR found no air-related public health hazard at 86% of sites. At sites where hazards were identified, common issues included elevated outdoor or indoor toxicants (e.g., hydrogen sulfide, benzene, trichloroethylene, and mercury) and unsafe methane accumulations. Contributing factors included older site designs, inadequate gas-collection, subsurface fires, and distance from nearby residences. Corrective actions effectively reduced exposures at the affected sites. Results suggest that well-located and maintained landfills minimize public health hazards, while aging or poorly managed sites pose risks. Continued monitoring and research are warranted as waste management shifts toward reducing, reusing, recycling, composting, and energy-recovery technologies to improve efficiency, advance technologies, and address systemic public health challenges. Full article

With the acceleration of urbanization and the continuous expansion of building stock, building maintenance plays a critical role in ensuring structural safety, extending service life, and promoting sustainable development. In recent years, the application of artificial intelligence (AI) in building maintenance has expanded significantly, markedly improving detection accuracy and decision-making efficiency through predictive maintenance, automated defect recognition, and multi-source data integration. Although existing studies have made progress in predictive maintenance, defect identification, and data fusion, systematic quantitative analyses of the overall knowledge structure, research hotspots, and technological evolution in this field remain limited. To address this gap, this study retrieved 423 relevant publications from the Web of Science Core Collection covering the period 2000–2025 and conducted a systematic bibliometric and scientometric analysis using tools such as bibliometrix and VOSviewer. The results indicate that the field has entered a phase of rapid growth since 2017, forming four major thematic clusters: (1) intelligent construction and digital twin integration; (2) predictive maintenance and health management; (3) algorithmic innovation and performance evaluation; and (4) deep learning-driven structural inspection and automated operation and maintenance. Research hotspots are evolving from passive monitoring to proactive prediction, and further toward system-level intelligent decision-making and multi-technology integration. Emerging directions include digital twins, energy efficiency management, green buildings, cultural heritage preservation, and climate-adaptive architecture. This study constructs, for the first time, a systematic knowledge framework for AI-enabled building maintenance, revealing the research frontiers and future trends, thereby providing both data-driven support and theoretical reference for interdisciplinary collaboration and the practical implementation of intelligent maintenance. Full article

Energy consumption accounts for a significant proportion of China’s building operations, exhibiting notable regional variations influenced by geographic characteristics. Factors affecting building energy consumption during transitional seasons are particularly complex in severely cold regions. This study selected a university library in Hohhot, Inner Mongolia Autonomous Region, as its research subject, employing a hybrid TCN–transformer model to conduct predictive experiments on short-term building energy consumption. We first collected environmental data from Hohhot’s spring–summer transitional period. Following parameter screening and preprocessing, this dataset was input into the TCN–transformer model. By integrating TCN with transformer’s self-attention mechanism, the model addresses the region’s high noise levels and non-stationarity, enabling precise forecasting. To validate the effectiveness of the proposed model, a comparative analysis was conducted against traditional models, namely SVR and LSTM, on the same dataset. The results demonstrated that TCN–transformer achieves superior comprehensive performance, evidenced by a higher prediction accuracy (R² = 0.8765) and lower error (MAE = 0.24603, RMSE = 0.32829), outperforming the baseline models. This research provides an innovative and efficient hybrid modelling approach and technical methodology for predicting building energy consumption during transitional seasons in severely cold regions, holding positive implications for enhancing building energy efficiency and promoting sustainable development. Full article

Background: Nutrition problems among primary school children increase the risk of illness, reduce school attendance, and impair academic performance. The Indonesian national school feeding program (ProGAS—Program Gizi Anak Sekolah) was developed to address these issues through the provision of healthy breakfast, nutrition education, and character building. Methods: This study employed a mixed-methods design involving 454 primary school students aged 8–14 years from 24 schools across four provinces. Data collection included structured questionnaires, 24 h dietary recalls, and anthropometric measurements. In-depth interviews with school principals, teachers, cooking teams, parents, students, nutritionists, and district education office staff were conducted to capture experiences and opinions on the ProGAS implementation. Results: ProGAS significantly improved students’ dietary diversity, meal frequency, handwashing with soap, and nutrition knowledge, alongside a positive trend in school attendance. Improvements included higher mean dietary diversity, increased proportion of students eating ≥3 meals/day, greater correct responses on balanced nutrition, and higher rates of handwashing before meals (all p < 0.01). Children also developed positive behaviors such as praying before meals, queuing, and taking responsibility for cleaning dishes. However, students’ breakfast habits did not significantly improve, the delivery of nutrition education was suboptimal, and no significant changes were observed in nutrient intakes or nutritional status based on BMI-for-age. While the energy and protein contributions of the ProGAS menu met the recommended 25–30% of daily requirements for breakfast, its micronutrient contributions remained below the recommended levels. Key management gaps include the delivery of nutrition education to students and the monitoring of implementation by local and national authorities. Conclusions: ProGAS demonstrated positive impacts on some dietary and hygiene practices as well as learning environment. To achieve greater improvements in breakfast habits, nutrient intake and nutritional status, it is recommended to strengthen the school feeding menus not only for dietary diversity but also for nutrient density, enhance capacity building for teachers, deliver regular and engaging nutrition education, and reinforce program monitoring. Full article

The investigation of environmentally friendly, Pb-free ceramic dielectric materials with excellent energy storage capability represents a fundamental yet challenging research direction for the development of next-generation high-power capacitors. In this study, linear dielectric Ca_0.7La_0.2(Mg_1/3Nb_2/3)O₃ was added into [0.65BaTiO₃–0.35(Na_0.5Bi_0.5)TiO₃] to form a solid solution. The introduction of Ca_0.7La_0.2(Mg_1/3Nb_2/3)O₃ modified the crystal structure, enhanced insulation performance and breakdown strength, and reduced hysteresis loss. These improvements collectively contributed to higher energy storage density and efficiency (η). The ceramic pellet with the optimal 10 mol% Ca_0.7La_0.2(Mg_1/3Nb_2/3)O₃ demonstrated a higher retrievable energy density (~3.40 J cm⁻³) and efficiency (~81%) at a breakdown strength of 340 kV cm⁻¹ compared to BaTiO₃-based ferroelectric ceramics. The sample also exhibited good stability across a temperature range of 30–90 °C and a frequency range of 0.5–300 Hz. Thus, the as-prepared ceramics sample exhibited significant potential for pulsed power device applications. Full article

Background/Objectives: Stunting and weight faltering (WF) remain pressing public health challenges in low- and middle-income countries, with long-term consequences for child growth, development, and survival. While the role of gut health in early growth is increasingly recognized, evidence on how the gut microbiome and metabolome respond to nutritional interventions in WF infants is scarce. This study explored gut microbiome and metabolome changes in Indonesian infants aged 6–12 months who overcame WF following a one-month intervention. Methods: Infants were assigned to either a Nutritional Advice (NA) group or a Nutritional Advice plus Oral Nutritional Supplements (NAONS) group. Stool samples were collected before and after the intervention for microbiome (16S rRNA sequencing) and metabolome (LC-MS) analysis. Results: Significant shifts in gut microbial composition (beta diversity) and species richness (Chao1 index) were observed in both groups, suggesting enhanced microbial diversity and gut resilience. Within-group analysis revealed increases in beneficial genera such as Faecalibacterium and Peptostreptococcus, and a reduction in pro-inflammatory Fusobacterium in the NA group. The NAONS group showed a notable decrease in Proteus, a potentially pathogenic genus. Between-group comparisons indicated higher abundances of Lactococcus and Leuconostoc in the NAONS group, likely reflecting the influence of milk protein-rich supplements on microbial colonization, favoring lactic acid bacteria over SCFA-producing taxa, leading to better gut health. Metabolome analysis revealed significant changes in the NA group, increases in metabolites like Threonine, Tryptophan, and Xylose pointed to improved energy metabolism and gut health, while a decrease in Oxalic Acid suggested better metabolic efficiency. In contrast, the NAONS group, while benefiting from rapid weight gain, displayed a distinct metabolic profile influenced by high milk protein intake. No significant correlations were found between microbiome and metabolome changes, highlighting the complexity of gut-host interactions, suggesting that the interventions led to independent shifts in the aforementioned profiles. Conclusions: Overall, the findings suggest that nutritional interventions may enhance gut health and support recovery from weight faltering, providing insights into strategies that may contribute to restoring healthy growth trajectories and preventing stunting by modulating gut health. Full article

This paper presents the design, implementation and experimental validation of a modular battery management system (BMS) featuring active cell balancing. The proposed BMS consists of a master module and multiple slave submodules responsible for monitoring and balancing 22 cells connected in series. The master module collects voltage and temperature data from the slave submodules and measures the battery current to estimate the cells’ state of charge (SoC). Each slave module performs cell voltage and temperature measurements and controls a balancing circuit based on dc-dc converters. This work describes in detail the development and validation of the dc-dc converter based in the switched inductor topology, presenting the converter’s operational principles, a theoretical and simulation-based analysis of its performance, the implementation of the MOSFETs driver circuits based on PNP transistors and experimental results obtained from a submodule prototype. The results demonstrate the capability of the switched inductor converter to achieve effective voltage equalization by transferring energy from the cells with higher voltages to cells with lower voltages. Full article

The Internet of Things (IoT) has become deeply embedded in modern society, enabling applications across smart homes, healthcare, industrial automation, and environmental monitoring. However, as billions of interconnected devices continuously collect and exchange sensitive data, privacy and security concerns have escalated. This survey systematically reviews the state-of-the-art privacy-preserving techniques in IoT systems, emphasizing approaches that protect user data during collection, transmission, and storage. Peer-reviewed studies from 2016 to 2025 and technical reports were analyzed to examine applied mechanisms, datasets, and analytical models. Our analysis shows that blockchain and federated learning are the most prevalent decentralized privacy-preserving methods, while homomorphic encryption and differential privacy have recently gained traction for lightweight and edge-based IoT implementations. Despite these advancements, challenges persist, including computational overhead, limited scalability, and real-time performance constraints in resource-constrained devices. Furthermore, gaps remain in cross-domain interoperability, energy-efficient cryptographic designs, and privacy solutions for Unmanned Aerial Vehicle (UAV) and vehicular IoT systems. This survey offers a comprehensive overview of current research trends, identifies critical limitations, and outlines promising future directions to guide the design of secure and privacy-aware IoT architectures. Full article

The waveform stacking location method achieves microseismic source localization by computing characteristic functions (CFs) and stacking multi-channel data, without phase picking. It has been widely applied in geotechnical engineering. However, the low signal-to-noise ratio (SNR) caused by weak event energy and ambient noise often degrades localization accuracy. To enhance the localization precision and stability under low SNR conditions, this study employs the Stockwell transform (S-transform) to convert noisy time-domain data into the time–frequency domain. By analyzing the energy distribution of microseismic signal and noise in the time–frequency domain, frequency and time coefficients are introduced to enhance the energy of microseismic signal. Event location is achieved through the computation of CFs and multiple-cross-correlation stacking. Comparison of the location results when computing the CFs by the new method, the short-term average to long-term average ratio (STA/LTA) method, and the envelope (Env) method under varying noise levels demonstrates the superior noise resistance and improved localization accuracy of the new method. Finally, the effectiveness of the new method is validated using real seismic data collected from a coal mine. Full article

Background: Human milk hyaluronan (HA), a glycosaminoglycan with barrier-protective and immunomodulatory functions, may be influenced by maternal characteristics. The effects of maternal obesity and acute dietary intake on milk HA concentrations remain unclear. Methods: This secondary analysis included 35 lactating mothers (n = 19 normal weight [NW], n = 16 obese [OB]) at 6 weeks postpartum who participated in two separate, but standardized, protocols: (1) Study One, which consisted of hourly milk collections for six hours following a standardized high-fat meal with a sugar-sweetened beverage beginning at 6:00 am, and (2) Study Two, which consisted of daily morning milk collections for seven consecutive days to assess temporal stability (Monday-Sunday). HA concentrations were quantified by an ELISA and analyzed using a mixed-effects and repeated-measures ANOVA. Results: In Study One, postprandial HA concentrations remained stable with no effect of time, BMI, or time × BMI interaction (p > 0.05). In Study Two, HA did not vary significantly by day (p = 0.082) but was higher in OB versus NW mothers (151.9 ± 18.7 vs. 96.5 ± 12.4 ng/mL; p = 0.0396), with the largest difference observed on Day 1 (p = 0.0117). Mean HA values trended upward later in the week (Day 6 and 7), suggesting potential influences of habitual dietary intake or weekend energy patterns. Conclusions: Milk HA concentrations were not altered by acute dietary intake but were consistently higher across multiple days in mothers with obesity. These results indicate that milk HA varies with maternal metabolic status and may also be influenced by habitual dietary patterns, including fluctuations between weekday and weekend intake. Full article

Reliable water vapor permeability (WVP) testing is crucial for sustainable construction, enabling accurate assessment of bio-mineral materials like hemp concrete, which reduce the environmental impact through renewable sourcing and improved energy efficiency. However, most studies testing or conditioning porous building materials in environmental chambers overlook the influence of chamber occupancy on airflow and humidity evacuation. While the usual practice is to collect anemometric velocity results in selected locations, few investigations apply computational fluid dynamics (CFD) to analyze the entire flow field, and humidity-field assessment is practically absent. This study addresses this gap by using CFD to examine how sample arrangement affects airflow and relative humidity (RH) in a climatic chamber containing sixteen hemp concrete specimens in dry- and wet-cup setups, aiding the reliable characterization of hygroscopic eco-composites. Three arrangements were modeled in ANSYS Fluent (2024 R1) using turbulence and species transport. Results show that unoptimized wet-cup placements cause RH deviations exceeding ISO’s ±5% tolerance, potentially biasing permeability data and undermining comparability across laboratories. A balanced wet–dry layout maintained RH within limits, improving testing reproducibility. Velocity maps reveal strong gradients above exposed sample surfaces, suggesting that standard anemometric protocols may require refinement. The presented approach highlights chamber loading as a hidden factor influencing WVP results and provides a transferable CFD-based framework to enhance testing accuracy, support sustainable material qualification, and accelerate the standardization of green-building methodologies. Full article

The rapid development of the Internet of Things (IoT) has imposed increasingly stringent power consumption requirements on receiver design. Unlike phase-locked loops (PLLs), free-running oscillators eliminate power-hungry loop circuitry. However, the inherent frequency offset of free-running oscillators introduces uncertainty in the intermediate frequency (IF), preventing the receiver from aligning with the desired channel. To address this, we present a reconfigurable channel receiver employing a free-running oscillator and frequency estimation for low-power IoT applications. The proposed receiver first captures a specific preamble sequence corresponding to the desired channel through multiple parallel sub-channels implemented in the digital baseband (DBB), which collectively cover the expected IF frequency range. The desired IF frequency is estimated using the proposed preamble-based frequency estimation (PBFE) algorithm. After frequency estimation, the receiver switches to a single-channel mode and tunes its passband center frequency to the estimated IF frequency, enabling high-sensitivity data reception. Measurement results demonstrate that the PBFE algorithm achieves reliable frequency estimation with a minimum IF signal-to-noise ratio (SNR) of 2 dB and an estimation error below 22 kHz. In single-channel mode, with a residual frequency offset of 30 kHz, an 8-point energy accumulation decoding scheme achieves a bit error rate (BER) of 10⁻³ at an IF SNR of 5.2 dB. Compared with the case of the original 50 kHz IF frequency offset, the required SNR is improved by 4.1 dB. Full article

Household waste systems are a frontline test of Australia’s circular economy transition, yet progress remains highly uneven and structurally constrained. Despite strong national targets for resource recovery and emissions reduction, local governments are expected to deliver circular outcomes without uniform access to infrastructure, funding, or technical capability. This study assesses the status, implementation, and progress of household waste management, energy recovery, and circular economy initiatives at the local government level in Australia. Using content analysis of data from 520 local government areas across six states, the study maps differences in service provision (e.g., general waste, mixed recycling, and food organics and garden organics [FOGO] collection), policy instruments, public-facing education, and participation in circular economy programs. The findings reveal that while a majority (92.5%) of councils provide general waste bins, 47% offer FOGO bins, and 78% supply mixed recyclable bins, only a small fraction (2.6%) offers a separate glass bin stream. Fewer than one in ten councils reference any form of energy recovery or waste-to-energy initiative, indicating that resource–energy integration remains emergent and geographically concentrated. Despite national policies such as the National Waste Policy Action Plan, significant regional disparities persist, particularly between metropolitan and rural councils. Guided by environmental governance theory and systems thinking, the study shows how policy fragmentation, funding limitations, and infrastructure inequities create systemic barriers to circularity. The study concludes by recommending targeted co-funding for rural councils, stronger policy support for organics and energy recovery infrastructure, and more coherent multi-level governance to achieve Australia’s 2030 waste and circular economy targets. This research contributes an evidence-based framework for understanding how governance structures and resource asymmetries shape local progress toward a circular economy. Full article

Mesozooplankton are pivotal for Black Sea food webs, yet they are highly vulnerable to hydrographic variability, eutrophication, and human pressures. This study analysed mesozooplankton dynamics along the Romanian coast (2013–2020) across three sectors (north, central, and south) and two distinct periods (cold and warm seasons), integrating Abundance–Biomass Comparison (ABC) curves with Fuzzy Cognitive Mapping (FCM). Results revealed a clear disturbance gradient: the Danube-influenced north supported high abundances of small-bodied taxa; the central sector maintained the most resilient and functionally diverse assemblages; and the southern sector showed chronic degradation with Noctiluca scintillans dominance. ABC curves quantified disturbance, with curve convergence in the north and near overlap in the south during summer, while FCM highlighted network simplification and reduced functional redundancy. Climate scenario simulations projected further declines in cladocerans and meroplankton under warming and freshening, whereas copepods showed relative resilience. Collectively, the findings demonstrate progressive simplification of mesozooplankton and declining energy transfer efficiency, underscoring the need to integrate zooplankton-based indicators into Black Sea monitoring and management frameworks. Full article