Search Results (1,429)

This study assesses carbon footprint (CF) and explores mitigation potentials through improved resource efficiency for fire-resistant wood doors (WFDs) and fire-resistant bamboo doors (BFDs). Both WFDs and BFDs are certified to the Chinese national fire resistance standard GB 12955-2024, ensuring the same core fire resistance performance and functional equivalence. Results show that WFDs have a slightly lower CF (806.04 kg CO₂ e/m³) than BFDs (830.54 kg CO₂ e/m³), where the raw material phase acts as the main contributor (58.57–64.32%). Crucially, significant mitigation potentials are identified by enhancing resource efficiency across the product life cycle through reducing processing loss, and extending service lifespan, and sustainable recycling. Approximately 35.2 billion kg CO₂ will remain after reducing carbon loss by 5% in the Chinese wood/bamboo industrial sector. Recycling approaches (wood/bamboo panels, bio-based pellet fuel, and biochar) can be utilized with fewer emissions to economize bio-resources. The use of biochar provides greater carbon storage benefits and will help to limit the effects of climate change. Full article

Extreme hydrometeorological events are occurring more often under climate change, increasing the risk for cities in coastal zones and lower river reaches. Such areas are prone to compound flooding (CF), where flood duration and magnitude are amplified by the combined effects of storm surges, onshore winds, long-term sea-level rise, and increasingly frequent rainfall-driven floods. This study assesses the socio-economic risk of residential neighbourhoods (RNs) along the lower reach of the Danė River in the city of Klaipėda, Lithuania, using a composite socio-economic risk index (CSERI) developed in this study under an extreme flood scenario, if the sea level in the south-eastern Baltic Sea rises by 1 m by the end of the century. The results show a strong relationship between water levels in the Klaipėda Strait and the lower reach of the Danė River, confirming a CF regime, where flood magnitude is driven by the interaction between strait water level and river discharge. The CSERI is based on five risk sub-indices (SIs): the building risk SI, road infrastructure risk SI, population risk SI, economic entities risk SI, and cultural heritage risk SI. The assessment identifies RNs at greatest risk under climate change and anthropogenic pressure and indicates priority areas for adaptation measures to reduce potential socio-economic losses. The proposed CSERI provides a practical decision-support tool for sustainable and climate-resilient urban development in coastal cities. Full article

Objective: This study aimed to estimate the trends, projections, and determinants of standalone and coexisting forms of malnutrition (CFM) at the global, regional, national, and individual level among children under five in low- and middle-income countries (LMICs). It also assessed the projection trajectory towards the 2030 global nutrition targets (GNTs) for child growth including stunting, wasting, obesity, and CFM. Methods: Data from 48 LMICs were analyzed using the Multiple Indicator Cluster Surveys (MICS) and Demographic and Health Surveys (DHS). Children with complete anthropometry were included for national- and individual-level descriptive analyses. Projected prevalence of each form of malnutrition, including CFM, was calculated using the Annual Rate of Change. Inferential analyses employed generalized linear regression models with two-way interaction terms to identify determinants of each malnutrition type. Findings: By 2030, 22 of 48 LMICs are projected to achieve the GNT of stunting, wasting, and obesity, that is up from 10 countries currently, while Yemen and Zimbabwe are expected to remain off-track. Stunting is the most prevalent form, affecting 42 countries, with nine nations projected to have over 50% of children affected by a form of malnutrition. Wasting, obesity, and CFM are rising in several countries. Maternal education and household wealth were the strongest determinants, with children of uneducated mothers and from poorest households at the highest risk. Inequalities are narrowing slowly by 1–2% per year, and marked regional disparities persist. Conclusions: Many LMICs are off-track to meet child-growth targets when CFM is considered alongside standalone indicators. The government and global health partners must strengthen nutrition surveillance systems and equity-focused policies and programs to routinely capture CFM and prevent as well as manage all forms of malnutrition at the national and individual levels. Full article

CoFe₂O₄ nanoparticles were prepared using a hydrothermal method. All the studied samples were single-phase and were crystallized in a cubic Fd-3m structure. XRD and TEM analyses revealed that the particles had average sizes between 5 and 22 nm. It has been shown that, by using the PVP of different molecular masses, trends of growth and crystallization can be established, obtaining elongated 40 k, cubical 58 k, and rhomboidal 360 kg/mol nanoparticles. While using Ethylene glycol as solvent, the formation of separated “raspberry”-like nanostructures was revealed. The saturation magnetizations are somewhat smaller compared with crystalline CoFe₂O₄ saturation magnetization, but are high enough to have possible biomedical applications. FC and ZFC measurements show that the blocking temperature was around 100 K for the CF5 sample and around 20 K for the FC6 sample. The calculated anisotropy constants were between 7 and 10 kJ/m³, being close to previously reported values. The calculated blocking temperatures are in good agreement with experimental ones. The M_r/Ms ratio at room temperature was lower than 0.5, confirming the predominance of magnetostatic interactions. This paper serves as a good starting point for researchers seeking to synthesize a CoFe₂O₄ system with a desired size and growth tendency at the nanometer scale. Full article

Solvent-free, continuous manufacture of carbon-fiber/poly(ether ether ketone) (CF/PEEK) towpregs via fluidized-bed powder coating requires stable powder fluidization together with controllable coating residence time. A laboratory-scale continuous coating line comprising a creel, guiding/tension rollers, a vibrated fluidized-bed coater, as well as a take-up unit was designed and commissioned. Subsequently, a two-stage optimization and modeling framework was developed. First, PEEK powder fluidization was optimized using a Taguchi L9 design, varying air pressure ($P$), powder weight ($W$), and vibration frequency ($f$); bed expansion ratio ($\epsilon$) and average surface bubble diameter ${(D}_b)$ were measured and ANOVA identified air pressure as the primary contributor to $\epsilon$ (83.4%), establishing a stable operating window. Second, within this window, coating performance was assessed by varying line speed ($V_{line}$) and coating-roller position ($H_r$) in 12 runs and combining them into a geometry-based residence time ($R_t$) for simplified control. Coating quality was quantified based on fiber volume fraction ($Vf$) and composite tensile strength (${\mathsf{\sigma }}_c$) after consolidation. The best condition in the tested range was $Hr=0.5 \mathrm{c}\mathrm{m}$ and $V_{line}=1.5 \mathrm{m}/\mathrm{m}\mathrm{i}\mathrm{n}$ ($R_t=0.54 \mathrm{s}$), achieving 61.5% $Vf$ and 1800.5 MPa tensile strength. The resulting mathematical models predicted $Vf$ and ${\mathsf{\sigma }}_c$ with good accuracy ($R^2\ge 0.92$), supporting parameter selection and process optimization for continuous CF/PEEK towpreg production. Full article

Background: Blood-derived circulating cell-free microbial DNA (cfmDNA) has emerged as a potential non-invasive biomarker source for cancer detection. However, low biomass and high susceptibility to analytical variability raise concerns regarding the stability and interpretability of inferred microbial signatures. This study aimed to evaluate how different taxonomic profiling strategies influence downstream machine learning-based classification and feature interpretation in lung cancer. Methods: cfDNA sequencing data from 168 individuals (80 lung cancer patients and 88 non-cancer controls) were analyzed using two taxonomic profiling workflows: a Bracken-based abundance estimation approach and a BLAST-refined alignment-based strategy. Microbial profiles derived from each pipeline were evaluated using supervised machine learning models within a nested cross-validation framework. Feature stability and fold-change trends were compared across profiling strategies. Results: A Random Forest model achieved robust classification performance under both workflows (AUC 0.852 for Bracken-derived data and 0.906 for BLAST-derived data). However, substantial pipeline-dependent variation was observed in feature selection patterns and quantitative fold-change directionality. Although 13 genera were consistently selected across cross-validation folds in both workflows, the magnitude and direction of abundance differences were not uniformly concordant. Conclusions: Blood-derived microbial DNA profiles can support machine learning-based lung cancer classification; however, feature-level interpretation remains sensitive to taxonomic assignment strategy. These findings underscore the importance of pipeline-aware interpretation and methodological transparency in low-biomass blood microbiome research. Full article

Background: The CFTR modulator elexacaftor/tezacaftor/ivacaftor (ETI) has transformed cystic fibrosis (CF) care, but national-level real-world data on long-term effectiveness, durability of response, and treatment de-escalation remain limited. Methods: We conducted a nationwide longitudinal study using the Italian Cystic Fibrosis Registry. People with CF aged ≥6 years who initiated ETI between October 2019 and December 2022 and received ≥3 months of continuous therapy were included. Lung function (percent predicted FEV₁, ppFEV₁), nutritional status (BMI or BMI z-score), hospital days, complications, microbiology, and chronic treatments were assessed during the two years before and up to two years after ETI initiation. Longitudinal changes were analyzed using generalized estimating equations with multiple imputation for missing data. Results: The cohort included 2276 individuals (mean age 27.9 ± 13.3 years; 49% female). Mean ppFEV₁ declined during the pre-ETI period but increased by 9.9 percentage points at 12 months after ETI initiation (p < 0.001) and remained 6.8 percentage points above baseline at 24 months. A decline between 12 and 24 months was observed overall, except in individuals with severe baseline lung disease (ppFEV₁ < 40%), who maintained stable improvements. Mean annual hospital days decreased by approximately 65% and remained low throughout follow-up. Nutritional status improved, with a mean BMI increase of approximately 1.05 kg/m² compared with immediate pre-treatment in adults and a BMI z-score increase of 0.2 SD compared with pre-treatment timepoints in children. Use of most standard CF therapies declined substantially, particularly among individuals with ppFEV₁ ≥ 40%. The prevalence of allergic bronchopulmonary aspergillosis decreased, while liver disease prevalence increased modestly, largely reflecting transient elevations in liver enzymes. Conclusions: In this nationwide real-world cohort, ETI was associated with sustained improvements in lung function, nutritional status, and hospitalization burden. The attenuation of lung function gains after the first year, particularly in less severe disease, supports the need for individualized monitoring and cautious treatment de-escalation in the ETI era. Full article

Microbial fuel cell (MFC) technology is emerging as an effective tool for bioelectricity generation and wastewater treatment. This work is aimed at investigating the impact of an Fe₂O₃-modified carbon felt (CF) anode in a dual-chamber MFC for the treatment of synthetic wastewater containing sunset yellow FCF dye (at different concentrations). The Fe₂O₃ nanoparticles were synthesized using a hydrothermal approach, characterized, and then used to modify CF as an MFC anode. The MFC experiments were performed using bare and Fe₂O₃-modified CF anodes to investigate their efficiency in decolorizing sunset yellow FCF dye while simultaneously generating bioelectricity. Furthermore, the phytotoxicity of synthetic wastewater containing the sunset yellow FCF dye on wheat plants (Triticum aestivum) was investigated before and after treatment in MFCs. MFCs 1, 3, and 5 were equipped with bare CF anodes and fed with synthetic wastewater containing sunset yellow FCF dye at 250 mg/L, 200 mg/L, and 150 mg/L, respectively. Whereas MFC-2, -4 and -6 were equipped with Fe₂O₃-modified CF anodes and fed with sunset yellow FCF dye at concentrations of 250 mg/L, 200 mg/L, and 150 mg/L, respectively. MFC-2, -4 and -6 demonstrated superior MFC operational characteristics regarding dye decolorization with simultaneous power generation. The power densities for MFC-2, -4 and -6 were calculated to be 303.03 mW/m², 353.45 mW/m², and 402.15 mW/m², with dye decolorization efficiencies of 76 ± 3.0%, 80 ± 4.2%, and 93.3 ± 3.0%, respectively. Moreover, phytotoxicity studies revealed that the treated wastewater samples exhibited lower phytotoxicity than the untreated samples. Conclusively, MFCs fabricated with Fe₂O₃-modified CF displayed better operational performance characteristics compared to those equipped with an unmodified CF anode. Full article

Background: Myocardial fibrosis (MF) results from excessive collagen deposition in the cardiac interstitium, causing structural and functional cardiac impairments that underlie multiple cardiovascular diseases. Grape seed oil (GSO), rich in various bioactive fatty acids, demonstrates established cardiovascular benefits, yet its potential mechanisms against MF remain incompletely elucidated. This study was designed to investigate the inhibitory effects of bioactive components from GSO on TGF-β1-induced fibrosis in cardiac fibroblasts (CFs) and to elucidate the underlying molecular mechanisms. Methods: GSO was obtained using supercritical CO₂ extraction technology. Initially, the anti-fibrotic activity of GSO was evaluated in vitro: a fibrosis model was established by inducing cardiac fibroblasts with TGF-β1 (10 ng/mL for 48 h), followed by treatment with 20% (v/v) GSO. Subsequently, the bioactive constituents of GSO were identified by Gas Chromatography-Mass Spectrometry (GC-MS). Network pharmacology approaches were employed to predict its potential therapeutic targets and associated signaling pathways. Molecular docking simulations were then performed to validate the binding interactions between the key bioactive components and the core targets obtained from enrichment analysis. Finally, the predicted core pathway was experimentally verified by Western blot analysis. Results: In vitro experiments demonstrated that 20% GSO treatment significantly downregulated TGF-β1-induced fibrotic markers at both transcriptional (MMP9, MMP2, Col1a1) and protein (TGF, Col I/III, α-SMA) levels (p < 0.01). GC-MS analysis identified nine fatty acids in GSO, including palmitic acid and linolenic acid. Network pharmacology revealed interactions between these compounds and 357 myocardial fibrosis-related targets. Molecular docking confirmed strong binding affinities (below −5.0 kcal/mol) of key components (heptadecanoic acid, palmitic acid) to core targets (MMP-9, PTGS2, MAPK3). Western blot analysis further verified that GSO significantly inhibited the expression of PI3K-AKT pathway-related proteins (p < 0.01). Conclusions: The fatty acids in GSO (linolenic acid, palmitic acid) attenuate myocardial fibrosis by inhibiting the PI3K/AKT signaling pathway and downregulating key fibrotic markers. These findings establish a novel theoretical foundation for the treatment of myocardial fibrosis and highlight the potential value of grape industry byproducts in cardiovascular therapeutics. Full article

This study presents a comprehensive numerical investigation into the combined bending–shear behaviour of hollow-flanged cold-formed steel (HFCFS) beams filled with lightweight concrete (LWC). Although previous research has independently examined the pure bending and pure shear responses of these composite members, their structural performance under simultaneous bending and shear remains unexplored. In this work, advanced three-dimensional finite element (FE) models were developed in ABAQUS to simulate the nonlinear behaviour of LWC-filled HFCFS beams subjected to various shear-span ratios. The modelling approach was validated using published experimental data and extended through a systematic parametric study that considered three beam geometries, two steel yield strengths (350 MPa and 450 MPa), two lightweight-concrete strengths (30 MPa and 50 MPa), and aspect ratios ranging from 1.5 to 3.5. The results demonstrated a clear progression of governing failure modes, from web shear buckling at low aspect ratios to combined shear–flexure interaction at intermediate spans and flexural-dominated failure at larger spans. Normalised shear and bending demand–capacity ratios (V/Vu and M/Mu) were used to identify the dominant limit state, revealing a predictable transition from shear-controlled to flexure-controlled behaviour. The findings enhance the understanding of composite thin-walled steel–concrete systems under combined actions and highlight the need for dedicated design rules for CF-HFCFS beams operating within the bending–shear interaction domain. Full article

Heterogeneous multi-core systems (HMCSs) typically face a dilemma: heuristics (e.g., Linux CFS) are fast but blind to global constraints, while meta-heuristics (e.g., GAs) are globally optimal but too slow for real-time OS interaction. To bridge this gap without relying on “black-box” neural networks, we introduce the Tissue P System-Inspired Task Allocator (TPSTA). By mapping HMCS and parallel task scheduling to Tissue P System models and vectorized linear algebra problems, TPSTA achieves a computational complexity of $\mathrm{O}\left(\mathrm{M}/\mathrm{W}\right)$, effectively compressing the decision space. Our rigorous evaluation across four dimensions reveals a system strictly bound by physical constraints rather than algorithmic heuristics. (1) Under sufficient resource provisioning (four chips), TPSTA achieves a 0.00% Deadline Miss Ratio (DMR). Crucially, stress tests on constrained hardware (two chips) show graceful degradation to a 12.88% DMR, matching the optimal theoretical bound of EDF, whereas standard heuristics collapse to failure rates > 68%. On a massive 4096-core cluster, TPSTA outperforms the Linux GTS scalar baseline by 14.4×, maintaining low latency where traditional algorithms fail (>8 s). (3) Adaptability: The system demonstrates adaptive routing in handling hardware heterogeneity; without explicit rule-coding, it autonomously prioritizes data locality during NUMA transfers and migrates compute-bound tasks during thermal throttling events. (4) Physical Limits: Finally, our roofline analysis confirms that while the algorithmic speedup is theoretically linear, practical performance saturates at ~375× due to the Memory Wall, validating the isomorphism between synaptic bandwidth and hardware memory channels. Full article

To address the engineering problems of high cement content, high brittleness, and weak frost resistance of cement-improved loess in the seasonal frozen soil area of Northwest China, F1 ion curing agent (F1) and cement composite improved loess (FCIL) were used in this paper. Through unconfined compressive (UC) strength tests, consolidated undrained (CU) triaxial shear tests, and microscopic pore characteristics analysis, the mechanical properties, freeze–thaw cycle deterioration law, and microscopic pore structure of FCIL were studied. The effects of cement content (C_c), F1 dosage (C_F), number of freeze–thaw cycles (N_F-T), and confining pressure (σ₃) on the strength, deformation behavior, and pore characteristics of FCIL were analyzed. The synergistic improvement mechanism of FCIL, as well as the freeze–thaw damage mechanism, was elucidated. The results show that C_c is the primary factor controlling the strength of improved loess. The incorporation of F1 can further increase UCS and markedly enhance the failure strain (ε_f), thereby achieving simultaneous improvements in strength and ductility. An appropriate mix proportion was identified as C_F = 0.2 L/m³ and C_c = 6%. After 7 d curing, FCIL exhibited a UCS of 1.35 MPa, a cohesion (c) of 205 kPa, an internal friction angle (φ) of 36.2°, and ε_f 1.8 times that of loess improved with C_c = 6% cement alone. CU triaxial shear tests indicate that, under all tested conditions, the stress–strain responses of FCIL exhibit σ3-sensitive strain-softening behavior. As C_c and σ₃ increase, triaxial peak strength (q_max) and secant modulus (E₅₀) increase significantly. Compared with natural loess (NL), FCIL shows a markedly lower porosity (n), a substantial increase in the proportion of micropores, and reductions in medium and small pores. After multiple freeze–thaw cycles, the evolution of the pore structure is effectively restrained. This indicates that the combined use of F1 and cement promotes the formation of a dense layered stacking structure, significantly improves the microscopic pore-size distribution, and enhances the mechanical performance of loess under freeze–thaw environments. Full article

Background: Liquid biopsy using circulating tumor DNA (ctDNA) is rapidly reshaping gastrointestinal (GI) oncology. The highest-impact applications are molecular residual disease (mRD) detection after curative-intent therapy and early recognition of progression or resistance during systemic treatment. Methods: We performed a structured, clinically oriented narrative synthesis by using explicit search, eligibility, evidence prioritization, and clinical interpretation rules, integrating landmark prospective cohorts, randomized ctDNA-guided strategy trials where available, meta-analyses, key methodological research (e.g., pre-analytics, assay design, and clonal hematopoiesis (CH)/clonal hematopoiesis of indeterminate potential (CHIP)), and selected trial registries. Results: In resected colorectal cancer (CRC), postoperative ctDNA positivity is among the strongest known biomarkers of recurrence risk; large prospective studies demonstrate clear separation of disease-free survival (DFS)/overall survival (OS) between mRD+ and mRD− patients. In stage II colon cancer, randomized data (DYNAMIC) show that a ctDNA-guided strategy reduces adjuvant chemotherapy exposure without compromising long-term outcomes. In metastatic CRC, ctDNA supports early response monitoring and resistance tracking; ctDNA-selected anti-EGFR rechallenge provides a model of biomarker-driven actionability (CHRONOS). In gastroesophageal cancers, longitudinal ctDNA dynamics correlate with relapse risk and treatment efficacy, and in esophageal squamous cell carcinoma, ctDNA after neoadjuvant chemoradiotherapy informs residual disease risk and adjuvant stratification. In pancreatic ductal adenocarcinoma and hepatobiliary malignancies, sensitivity is constrained by low shedding and background cell-free DNA (cfDNA), yet ctDNA positivity remains clinically meaningful, and emerging data in resected extrahepatic cholangiocarcinoma (STAMP-linked analyses) show that ctDNA dynamics during adjuvant therapy predict recurrence. Conclusions: ctDNA is a clinically validated biomarker for mRD in CRC, whereas in other GI cancers, it remains a promising but methodologically heterogeneous tool whose clinical utility is tumor- and context-dependent. The next phase requires interventional trials demonstrating outcome improvement, harmonized sampling and reporting standards, and rigorous control of confounders (notably CH/CHIP). Full article

The primary objective of this study is to develop a specialized deep learning framework specifically adapted for the unique physical characteristics of neurovascular Optical Coherence Tomography (OCT) imaging. Although Polyp-PVT, originally designed for polyp segmentation, shows promise for OCT analysis, it faces limitations in neurovascular applications. The default RGB input wastes resources on duplicated grayscale data, while its fixed-scale fusion struggles with vascular curvature variations. Furthermore, the attention mechanism fails to capture radial vessel patterns, and geometric constraints limit thin boundary detection. To address these challenges, we propose Brain-OCT-PVT with key innovations: a single-channel input stem reducing parameters by two-thirds; a Radial Intensity Module (RIM) using polar transforms and angular convolution to model annular structures; and a Deformable Cross-scale Fusion Module (D-CFM) with learnable offsets. The Boundary-aware Attention Module (BAM) combines Laplace edge detection with Swin-Transformer for sub-pixel consistency. A specialized loss function combines Dice Similarity Coefficient (Dice), BoundaryIoU on 2-pixel dilated edges, and Focal Tversky to handle extreme class imbalance. Evaluation on 13 clinical cases achieves a Dice score of 95.06% and an 95% Hausdorff Distance (HD95) of 0.269 mm, demonstrating superior performance compared to existing approaches. Full article

With hydropower supplying nearly 94% of Ethiopia’s electricity, the national power grid is extremely vulnerable to recurrent droughts and erratic rainfall. To mitigate this risk, this study examines the wind power potential across five specific locations: Arerti, Sela Dingay, Debre Berhan, Mega, and Gode. By combining on-site mast measurements with datasets from NASA and the Global Wind Atlas, we evaluated wind characteristics at industry-standard hub heights of 80 m and 100 m. The analysis focused on wind power density (WPD), Weibull stability parameters (k and c), and directional consistency. The results indicate that Gode and Mega are the premier choices for commercial development, showing average speeds above 8.5 m/s and power densities exceeding 500 W/m2 at the 100 m level. Gode stands out as the most reliable site, with a Weibull shape factor (k) of 2.8 and a scale factor (c) of 9.1 m/s. We modeled a standard 3 MW turbine while factoring in a 20% loss for real-world conditions; this yielded net annual energy productions of 9461 MWh (36% CF) for Gode, 9040 MWh (34.4% CF) for Mega, and 8619 MWh (32.8% CF) for Arerti. While Sela Dingay and Debre Berhan have lower initial yields, their feasibility improves significantly when using towers taller than 80 m. Wind rose data reveals that Gode and Arerti have highly unidirectional flows, which simplifies turbine micro-siting. Notably, Arerti provides a unique economic advantage due to its location right next to existing 132/230 kV transmission infrastructure and industrial load centers. Overall, these findings provide a definitive technical roadmap for Ethiopia to diversify its energy portfolio and meet its Climate-Resilient Green Economy (CRGE) objectives. Full article