Search Results (2,876)

The increasing interest in sustainable materials has led to the development of bio-based composites for additive manufacturing applications. This study aimed to investigate the influence of key printing parameters and new-generation infill patterns together on the maximum compressive force of PLA–wood bio-composites produced by Material Extrusion. By optimizing this material, low-cost wood-like products can be produced. New-generation 3D infill patterns (octet, cubic-subdivision, and lightning which is a biomimetic infill pattern) infill densities, printing temperatures, and layer heights were selected as variables/factors, and the Taguchi method was applied for design of the experiment. The signal-to-noise ratio and Analysis of Variance were used to evaluate the statistical significance and contribution of each parameter to the mechanical response. The signal-to-noise ratio indicated that the optimal printing settings were as follows: printing temperature, 205 °C; infill density, 80%; infill pattern, octet; and layer height, 0.2 mm (7123.4 N). ANOVA results showed that infill density was the most significant factor affecting maximum compressive force at 60%, while infill pattern also exhibited a notable effect. According to these results, infill density and infill pattern are the most important factors for achieving high compressive strength. These findings suggest that optimizing infill architecture and density can improve the mechanical performance of PLA–wood composites, also they can offer assistive design guidelines for lightweight and eco-friendly components. Full article

The escalating global demand for large-scale, cost-effective, and sustainable high-quality protein has positioned single-cell protein (SCP) production from one-carbon (C1) gases as a highly promising solution. In this study, eight chemolithoautotrophic hydrogen-oxidizing bacteria (HOB) were isolated from mangrove sediments. Based on the 16S rRNA gene sequence analysis, they belonged to genera Sulfurimonas, Sulfurovum, Thiomicrolovo, and Marinobacterium. Among these, Thiomicrolovo sp. ZZH C-3 was identified as the most promising candidate for SCP production based on the highest biomass and protein content, and was selected for further characterization. Strain ZZH C-3 is a Gram-negative, short rod-shaped bacterium with multiple flagella. It can grow chemolithoautotrophically by using molecular hydrogen as an energy source and molecular oxygen as an electron acceptor. Genomic analysis further confirmed that ZZH C-3 harbors a complete reverse tricarboxylic acid (rTCA) cycle gene set for carbon fixation, and diverse hydrogenases (Group I, II, IV) for hydrogen oxidation. Subsequently, its cultivation conditions and medium composition for SCP production were systematically optimized using single-factor experiments and response surface methodology (RSM). Results showed that the optimal growth conditions were 28 °C, pH 7.0, and with 1 g/L (NH₄)₂SO₄ as the nitrogen source, 5–10% oxygen concentration, 9.70 mg/L FeSO₄·7H₂O, 0.17 g/L CaCl₂·2H₂O, and 1.90 mg/L MnSO₄·H₂O. Under the optimized conditions, strain ZZH C-3 achieved a maximum specific growth rate of 0.46 h⁻¹. After 28 h of cultivation, the optical density at 600 nm (OD₆₀₀) reached 0.94, corresponding to a biomass concentration of 0.60 g/L, and the protein content ranked at 73.56%. The biomass yield on hydrogen (Y_H2) was approximately 3.01 g/g H₂, with an average H₂-to-CO₂ consumption molar ratio of about 3.78. Compared to the model HOB Cupriavidus necator, strain ZZH C-3 exhibited a lower H₂/CO₂ consumption ratio, superior substrate conversion efficiency, and high protein content. Overall, this study not only validated the potential of mangrove HOB for SCP production but also offers new insights for future metabolic engineering strategies designed to enhance CO₂-to-biomass conversion efficiency. Full article

In order to further enhance the extraction yield of total flavonoids from Scutellaria baicalensis Georgi, the extraction process was optimized, and its composition and antioxidant activity were also analyzed. Through single-factor and response surface methodology optimization, the optimal extraction process of total flavonoids from S. baicalensis was obtained as follows: 56% ethanol concentration, 40:1 (mL/g) ratio of liquid to solid, 50 °C extraction temperature, and 1 h of extraction time. Under the optimal extraction conditions, the total flavonoid yield reached was 165.40 mg/g, which was 70.16% higher than the blank group and 89.68% higher than previously reported results. The major composition of total flavonoids was analyzed using UHPLC-MS/MS. A total of 60 flavonoid compounds were identified, of which 20 flavonoids had not been reported previously. The in vitro antioxidant activity of the total flavonoids was analyzed by DPPH and ABTs assays. IC₅₀ of the total flavonoids on DPPH and ABTs free radicals were 0.52 μg/mL and 0.66 μg/mL, respectively, which indicated that the total flavonoids of S. baicalensis had a remarkable free radical scavenging ability. This study should provide theoretical and technical support for the industrial production and bioactivity-oriented utilization of flavonoids from S. baicalensis. Full article

Background/Objectives: The widespread development of anthelmintic resistance in gastrointestinal nematodes constitutes a major production-limiting factor in grazing ruminants. Resistance mechanisms often involve drug efflux transporters like P-glycoprotein (P-gp). This study aimed to evaluate the potential of the phytochemicals cinnamaldehyde (CNM) and thymol (TML) to modulate P-gp activity and enhance the pharmacokinetic profile and efficacy of levamisole (LVM) in lambs. Methods: An ex vivo diffusion assay using sheep ileum was conducted to assess the influence of CNM, TML, and LVM on the transport of the P-gp substrate Rhodamine 123 (Rho123). Subsequently, a clinical trial was performed in lambs naturally infected with resistant nematodes. Animals received LVM (3.75 mg/kg) subcutaneously, either alone or co-administered with CNM or TML (80 mg/kg). Plasma LVM concentrations were analyzed by HPLC, and anthelmintic efficacy was determined via the Fecal Egg Count Reduction (FECR) test. Results: Ex vivo assays demonstrated that CNM, TML and LVM significantly reduced the efflux ratio of Rho123, confirming P-gp inhibition. The pharmacokinetic parameters of LVM did not differ significantly in the co-administered groups. However, the combination of LVM + TML tended to increase the total systemic exposure of LVM. Although all experimental groups showed a significant reduction in EPG between day 0 and day 7 (FECR 50–58%), the magnitude of this reduction did not differ significantly among treatments. Conclusions: While CNM and TML effectively inhibited P-gp activity ex vivo and slightly modified LVM pharmacokinetics, these effects were insufficient to yield clinically meaningful improvements in its efficacy against nematodes under the tested conditions. Future strategies should focus on optimizing delivery systems to maximize phytochemical–drug interactions. Full article

Aeolian sand is abundant in arid deserts, but its high replacement in cement-stabilized bases can reduce strength and raise cracking risk. Strain localization and crack evolution are also poorly quantified. This study aimed to optimize the early age performance of cement-fly ash stabilized aeolian sand gravel (CFSAG) and clarify its failure mechanism. A Box–Behnken response surface methodology varied the cement content, cement-to-fly ash ratio, coarse aggregate gradation, and aeolian sand content. The 7-d unconfined compressive strength (UCS) and splitting tensile strength (STS) were tested. Digital image correlation (DIC) recorded full-field strains and crack metrics in compression and splitting. SEM–EDS was used to interpret microstructural changes. The aeolian sand content dominated UCS, whereas the cement content and cement-to-fly ash ratio mainly controlled STS. Factor interactions were non-negligible and supported the joint optimization of the two strength indices. DIC identified a crack propagation threshold near 0.9 P_max in splitting. Excess aeolian sand (>50%) caused earlier localization, more cracks, and wider openings. In the appropriate amount of aeolian sand mixtures, hydration products filled voids and improved paste continuity. SEM–EDS indicated that excessive fines increased porosity and weakened the interfacial transition zone. Overall, the combined RSM–DIC–SEM approach links mix design with deformation and microstructure evidence. It provides practical guidance to balance strength and cracking resistance at early ages for cement-stabilized bases in desert highway engineering. Full article

Growing environmental concern over plastic pollution has increased the need to address the persistence of PET-derived monomers, such as bis(2-hydroxyethyl) terephthalate (BHET) and terephthalic acid (TPA). This work examines the use of excimer radiation lamps combined with hydrogen peroxide (H₂O₂) to enhance advanced oxidation processes (AOPs) for their degradation. This approach stands out for its high selectivity, absence of mercury, and lower production of toxic byproducts. Experimental tests assessed how different operational factors affect pollutant degradation, such as the initial pollutant concentration (50–200 mg/L), the reaction volume (125–500 mL), and the H₂O₂:monomer mass ratio (0:1–6:1 for BHET and 0:1–4:1 for TPA). For BHET, the best results occurred with a 5:1 mass ratio, while TPA degraded optimally with a 3:1 ratio, with a 250 mL reaction volume and a 100 mg/L initial concentration for both compounds. Under these conditions, total degradation of the initial monomers was achieved in around 30 and 80 min for BHET and TPA, respectively, and at the end of the reaction, COD decreased by 46% and 32% relative to their initial values. In both cases, hydrogen peroxide was crucial since UV radiation alone led to much lower degradation efficiency. These results emphasize the need to optimize operational conditions for greater efficiency and establish a starting point for future use of excimer technology in the treatment of wastewater contaminated with PET and its derivatives. Additionally, the degradation data closely matched a pseudo-first-order kinetic model (R² ≈ 1), confirming its reliability for predictive analysis, which is of high importance for the simulation and optimization of the process. Full article

The Zhundong coalfield in Xinjiang contains vast reserves and is a crucial source of thermal coal. However, the Zhundong coal has a high content of alkali and alkaline earth metals, which makes it prone to ash deposition and slagging in boilers, thereby limiting its large-scale utilization. Fluidized-bed preheating is an emerging clean combustion technology that can reduce the slagging and fouling risks associated with high-alkali coal by modifying its fuel properties. This study employs circulating fluidized-bed preheating technology to treat high-alkali coal, with a focus on investigating the effect of the preheated air equivalence ratio on fuel preheating modification. Through microscopic characterization of both the raw coal and preheated char, the release and transformation behaviors of elements and substances during the preheating process are revealed. The results demonstrate that fluidized preheating promotes alkali metal precipitation, and increasing the preheated air equivalence ratio (λ_Pr) enhances gas production and elemental release, with a volatile fraction mass conversion of up to 84.57%. As the λ_Pr value increased from 0.28 to 0.40, the average temperature in the preheater riser increased from 904 °C to 968 °C. Compared to the raw coal, the specific surface area of the preheated char was enhanced by a factor of 3.6 to 9.1 times, with a more developed pore structure and less graphitization, thus enhancing the surface reactivity of the preheated char. The increase in λ_Pr also facilitated the conversion from pyrrolic nitrogen to pyridinic nitrogen, thus improving combustion performance and facilitating subsequent nitrogen removal. These findings provide essential data support for advancing the understanding of preheating characteristics in high-alkali coal and for promoting the development of efficient and clean combustion technologies tailored for high-alkali coal. Full article

Background: Spondyloarthritis (SpA) typically develops before 40 years of age, but increasing life expectancy has led to a growing number of cases in older adults. It is well known that age at onset may influence disease presentation, comorbidities, and patient outcomes. Objectives: To assess whether age at onset influences SpA clinical presentation. Methods: We analyzed clinical, demographic, clinimetric, and imaging data in 272 SpA patients, grouped by onset age: early (≤40, n = 119), intermediate (41–59, n = 127), and late (≥60, n = 26). All patients had a minimum follow-up duration of 12 months. Their epidemiologic, clinic, and clinimetric data were collected, as well as patient-reported outcome measures (PROs) [Patient Global Assessment (PGA), Health Assessment Questionnaire (HAQ), FACIT-Fatigue (FACIT-F), SHORT-FORM 36 (SF-36), Hospital Anxiety and Depression Scale (HADS), Work Productivity and Activity Impairment Questionnaire (WPAI), CSI (Central Sensitization Inventory), and Psoriatic Arthritis Impact of Disease (PsAID) questionnaire]. In univariate analyses, differences in categorical variables across onset groups were assessed using Fisher’s exact test; for continuous variables, between-group comparisons were performed using the Mann–Whitney U test (two-tailed) or the Kruskal–Wallis test, as appropriate, with Bonferroni correction for post hoc analyses. Multivariable regression models were subsequently fitted, adjusting for sex, diagnosis, and disease duration. For binary outcomes, multivariable logistic regression models were used, while multivariable linear regression models (ANCOVA) were applied for continuous outcomes. The overall association between onset group and each outcome was formally tested using likelihood ratio tests, comparing models including the onset variable with nested models excluding it. A p-value < 0.05 was considered statistically significant. Results: Patients’ mean age was 60.0 ± 13.7 years; 55.9% of them were males; and there were 188 cases (69.1%) of psoriatic arthritis (PsA) and 84 cases (30.9%) of ankylosing spondylitis (AS). In early-onset patients, inflammatory back pain (IBP) was more frequent, whereas late-onset patients more often presented with joint swelling. A family history of SpA and psoriasis was less common in late-onset forms. Comorbidities, including osteoporosis, osteoarthritis, hypertension, hyperuricemia, and diabetes, were more prevalent in older-onset patients, resulting in a higher overall comorbidity burden in Groups 2 and 3. Patient-reported outcomes were largely similar across age groups, although work activity limitation was more pronounced in younger patients. Conclusions: Age at onset seems to influence SpA phenotypes: early-onset could favor axial involvement, while late-onset may associate with peripheral arthritis. Late-onset forms are associated with a more severe comorbidity burden, in particular for cardiovascular risk factors. Lung involvement proved to be more prevalent with respect to the general population, so it should be checked in the routinary assessment of SpA patients. These findings suggest that rheumatologists could tailor their routine assessments based on patients’ age at disease onset. Interestingly, work productivity seems more impacted in early-onset patients. All these points highlight the importance of age at disease onset in SpA, guiding toward personalized medicine in terms of follow-up, therapy, and more holistic patient management. Full article

Underground hydrogen storage (UHS) in depleted oil and gas reservoirs is regarded as a highly promising subsurface option due to its large storage capacity. In such reservoirs, the pore structure provides the primary space for hydrogen storage and governs matrix flow and diffusion. Tree-shaped fracture networks generated by hydraulic fracturing or cycling injection–production typically exhibit much higher transmissivity and serve as the dominant pathways. In this study, the geometry of multilevel branching fractures was parameterized, and two classes of tree-shaped fracture configurations were constructed, including point–line-type (PLTSF) and disc-shaped (DSTSF) networks. Analytical models were developed to evaluate the equivalent permeability of tree-shaped fracture networks with either elliptical or rectangular cross-sections. The Klinkenberg slip correction and a gas-type factor associated with molecular kinetic diameter were incorporated. The apparent equivalent permeability of hydrogen (k_app,H2) was quantified and compared with those of nitrogen and methane under identical conditions. The main findings were as follows: (1) the fracture width ratio (β) was identified as the primary factor controlling network conductivity, while the height ratio (α) amplified or attenuated this effect at a given β; (2) as the main-fracture aspect ratio, the branching order (n) or branching angle (θ) increased, the rectangular cross-sections were more favorable for maintaining higher permeability compared to the elliptical cross-section; (3) under typical operating pressures of 5–30 MPa, the apparent permeability of hydrogen was approximately 2–9% higher than that of methane and nitrogen; and (4) by introducing the fracture volume fraction, the REV-scale equivalent-permeability expression was derived for fractured rock masses containing tree-shaped fracture networks. The proposed framework provides a theoretical basis and parametric support for quantifying fracture flow capacity for UHS in depleted reservoirs. Full article

To investigate the mechanism by which ground granulated blast-furnace slag (GBFS) affects the performance of steam-cured cementitious materials, this study systematically analyzes the effect of GBFS on the mechanical strength and hydration products of mortar by adjusting the GBFS content (0%, 20%, 30%, 50%), curing temperature (50 °C for 7 h, 80 °C for 7 h), and curing time (3 d, 28 d). The results show that although increasing the steam-curing temperature can improve the strength activity index of GBFS-containing mortar, higher temperatures tend to induce later-age strength retrogression in such mixtures. Steam-curing not only promotes the massive formation of calcium hydroxide with coarse crystals but also increases the initial Ca/Si ratio of calcium silicate hydrate (C–S–H) gels, which is a crucial factor contributing to the high susceptibility of steam-cured concrete to brittle fracture; however, the incorporation of GBFS can effectively mitigate this issue. Furthermore, under the steam-curing condition of 80 °C, the addition of GBFS facilitates the formation of hydrogarnet and delayed ettringite, which is unfavorable for the long-term strength development and durability improvement in concrete. Full article

Low back pain is common and negatively impacts quality of life and workplace productivity. However, few studies have focused on small- and medium-sized enterprises (SMEs) where risk factors are prevalent. This cross-sectional study examined the association and structural relationships between physical and social factors in low back pain among Japanese SME workers. We analyzed survey data collected between April 2021 and August 2022 from 762 SME workers aged 18–65 years in Shimane, Japan, to assess acute (less than 3 months) and chronic low back pain using a self-reported questionnaire. Workplace physical (physical load) and social (stress of interpersonal relations) factors were measured using a brief job stress-related questionnaire. Associations between workplace factors and acute and chronic low back pain were evaluated using multivariable, multinomial logistic regression. Among the 762 workers, 50.9% and 7.3% reported acute and chronic low back pain, respectively. The odds ratio (OR) for acute pain was 2.08 for ‘Very much so’ in those with a high physical load. Compared with those with low interpersonal stress, the OR for chronic pain was 2.20 for medium stress and 2.82 for high stress. Reducing physical workloads may mitigate acute low back pain, while lowering interpersonal stress at work may reduce chronic low back pain. Future studies should investigate whether improving workplace physical and social factors is longitudinally effective. Full article

Soil erosion is a major threat to the sustainable productivity of arable lands, making the accurate prediction of soil erodibility essential for effective soil conservation planning. Soil erodibility is strongly controlled by intrinsic soil properties that regulate aggregate resistance and detachment processes under erosive forces. In this study, machine learning (ML) models, including the Multi-layer Perceptron Regressor (MLP), Random Forest (RF), Decision Tree (DT), and Extreme Gradient Boosting (XGBoost), were applied to predict the soil erodibility factor (K-factor). A comprehensive set of soil properties, including soil texture, clay ratio (CR), organic matter (OM), aggregate stability (AS), mean weight diameter (MWD), dispersion ratio (DR), modified clay ratio (MCR), and critical level of organic matter (CLOM), was analyzed using 110 soil samples collected from the northern part of Adana Province, Türkiye. The observed K-factor was calculated using the RUSLE equation, and ML-based predictions were spatially mapped using Geographic Information Systems (GISs). The mean K-factor values for arable, forest, and horticultural land uses were 0.065, 0.071, and 0.109 t h MJ⁻¹ mm⁻¹, respectively. Among the tested models, XGBoost showed the best predictive performance, with the lowest MAE (0.0051) and RMSE (0.0110) and the highest R² (0.9458). Furthermore, the XGBoost algorithm identified the CR as the most influential variable, closely followed by clay and MCR content. These results highlight the potential of ML-based approaches to support erosion risk assessment and soil management strategies at the regional scale. Full article

Background: Caffeine, dairy products and other food items may influence retinal microcirculation. Retinal microvascular indices provide quantitative biomarkers of systemic microvascular health and are increasingly used in clinical and research settings. The aim of this study was to elucidate the possible effects of these food products on structural and functional indices of the retinal microcirculation. Methods: Based on a registered protocol, we identified eligible interventional/observational studies examining the association of these factors with retinal biomarkers, including central retinal artery equivalent (CRAE), central retinal vein equivalent (CRVE), arteriolar-to-venular diameter ratio (AVR), retinal vascular tortuosity, vessel diameter index (VDI) and retinal vessel flicker light-induced dilation (FID). Results: Fourteen studies were included addressing caffeine (4), dairy products (2) and other food (9) consumption. Acutely, caffeine intake was dose-dependently associated with narrowed CRAE, CRVE, decreased VDI and increased AVR and FID. Long-term, caffeine consumption was associated with larger CRVE and lower AVR, while decaffeinated coffee with larger CRAE and AVR and narrower CRVE. Low-fat dairy products, fish and fiber were associated with larger CRAE, smaller CRVE, and increased AVR, while red meat consumption was associated with narrower CRAE and lower AVR. Increased salt intake was associated with increased venular tortuosity, while almond consumption was associated with larger CRVE. Owing to substantial study heterogeneity, a meta-analysis was not feasible. Conclusions: Potentially clinically meaningful associations between food groups and retinal indices were identified. These associations should be considered when evaluating retinal microcirculation and assessing CVD risk since modification of these factors may be beneficial for the cardiovascular system. Full article

Investigating the spatio-temporal differentiation patterns and driving factors of ecosystem services (ESs) supply and demand is of great significance for early warning of ecosystem imbalance risks and identifying regional natural resource supply–demand conflicts. This study takes the typical coal-grain overlapping area (CGOA) in Eastern China as the research object, dividing it into mining townships (MT) and non-mining townships (NMT) for comparative analysis. By integrating the InVEST model, ESs supply–demand ratio (ESDR) index, four-quadrant model, and the XGBoost-SHAP algorithm, the study systematically reveals the spatiotemporal differentiation characteristics and driving mechanisms of ESs supply and demand from 2000 to 2020. The results indicated that: (1) grain production (GP) service maintained a continuous supply–demand surplus, with the ESDR of NMT areas surpassing that of MT areas in 2020. The ESDR of water yield (WY) service was significantly influenced by interannual fluctuations in supply, showing deficits in multiple years. The decline in carbon sequestration (CS) service and sharp increase in carbon emissions led to a continuous decrease in the ESDR of CS service, with MT areas facing a higher risk of carbon deficit. (2) The spatial heterogeneity of ESs supply and demand was significant, with GP and CS services exhibiting a typical urban-rural dual spatial structure, and the overall region was dominated by the Type II ESs supply–demand matching (ESDM) pattern. The ESDR of WY service generally decreases from Southeast to Northwest across the region. with the Type IV ESDM pattern dominating in most years. (3) Human activities are the core driving force shaping the supply–demand patterns of ESs. Among these, land use intensity exhibits a nonlinear effect, high population density demonstrates an inhibitory effect, and MT areas are more significantly affected by coal mining subsidence. Natural environmental factors primarily drive WY service. The research findings can provide a scientific reference for the coordinated allocation of regional natural resources and the sustainable development of the human–land system. Full article

Low-permeability waterflooding reservoirs face numerous challenges, including low productivity per well, inadequate formation pressure maintenance, poor waterflood response, and low water injection utilization efficiency. Illustrated by Bai 153 Block in the Changqing Oilfield, the primary concern has shifted in recent years from fracture water breakthrough to formation blockages. Currently, low-yield wells (≤0.5 t) constitute a significant proportion (27.5%), with a recovery factor of only 0.41%. The effectiveness of stimulation treatments is influenced by reservoir properties, treatment types, process parameters, and production performance. Selecting candidate wells requires collecting and analyzing data such as individual well block characteristics. Evaluating treatment effectiveness involves substantial effort and complexity. Early fracturing treatments exhibited significant variations in effectiveness, and the primary controlling factors influencing fracturing success remained unclear. This paper proposes a big data analysis-based method for evaluating stimulation effectiveness in low-permeability waterflooding reservoirs. Utilizing preprocessed geological, construction, and production data from the target block, an integrated application of the Random Forest algorithm and Recursive Feature Elimination ranks the importance of factors affecting treatments and identifies the block’s main controlling factors. Using these factors as target parameters, a multivariate quantitative evaluation model for fracturing effectiveness is established. This model employs the Pearson correlation coefficient method, Recursive Feature Elimination, and the Random Forest algorithm. Results from the quantitative model indicate that the primary main controlling factors that significantly affect post-fracturing oil increment are production parameters, geological parameters such as vertical thickness, fracture pressure, and oil saturation; engineering parameters such as sand ratio, blowout volume, and fracturing method; and production parameters such as pre-measure cumulative fluid production, production months, and pre-measure cumulative oil production, which are most closely related to post-fracturing oil increment. These parameters show the strongest correlation with incremental oil production. The constructed quantitative model demonstrates a linear correlation rate exceeding 85% between predicted fracturing stimulation and actual well test production, verifying its validity. This approach provides a novel method and theoretical foundation for the post-evaluation of oil increment effectiveness from stimulation treatments in low-permeability waterflooding reservoirs. Full article