To reveal the regional differentiation characteristics of carbon emissions during the construction phase of expressways and to improve prediction accuracy, six typical expressway projects located in the plain, hilly, and mountainous regions of Anhui Province were selected as case studies. A carbon emission accounting model for the construction phase was established based on the life cycle assessment method, and the effects of the bridge-tunnel ratio, subproject structure, and material and energy consumption on carbon emission intensity were systematically analyzed. On this basis, a regional carbon emission prediction model was developed and optimized using data from 21 completed expressways across the province. The results indicate that carbon emission intensity exhibits a significant topographic gradient, with mountainous regions showing higher values than hilly regions, and hilly regions higher than plain regions. The maximum carbon emission intensity in mountainous projects reaches 5.27 × 10⁷ kg CO₂/km, which is 2.86 times that of plain regions. As terrain complexity increases, the carbon emission structure shifts from being dominated by subgrade engineering and interchange engineering to being dominated by structural engineering, such as bridges and tunnels. In mountainous regions, emissions from structural engineering account for more than 50% of the total emissions. At the material level, cement and steel are identified as the primary emission sources, jointly accounting for 78% of total emissions in mountainous projects, and demonstrating the highest sensitivity to variations in total emissions. The prediction results show that the baseline model using the bridge-tunnel ratio as a single variable achieves a coefficient of determination (R²) of 0.69. After incorporating material and energy consumption variables, the optimized XGBoost model improves the coefficient of determination to 0.9517, achieving high-accuracy prediction using only eight categories of material and energy consumption indicators. Based on the analytical results, differentiated emission reduction pathways are proposed. In mountainous regions, priority should be given to optimizing the design of tunnels and interchange engineering and controlling the intensity of high-carbon structural materials. In plain and hilly regions, emphasis should be placed on low-carbon design and construction optimization of bridge and culvert engineering and subgrade engineering. This study provides a data-driven basis for regional carbon emission prediction and emission reduction decision-making during the construction phase of expressways.
Urban hydrology has evolved in response to the degradation of flow and water quality caused by urban expansion. To enhance urban hydrology and improve urban resilience, the 'Ramsar Wetland City' scheme accredits cities that successfully integrate wetland conservation with sustainable development. According to the Ramsar Convention's wetland city accreditation criteria (2023), Criterion A4 emphasises the wetland restoration and creation for flood regulation and water quality improvement, and Criterion A5 highlights spatial planning and integrated city management. However, current planning for constructed wetlands (CWs) at the catchment scale lacks a framework that coherently links performance goals, adjustable design factors, and the spatial allocation of interventions. This study introduces a problem-oriented approach for planning integrated constructed wetland systems (ICWS) at the catchment scale. This problem-oriented approach is defined as a planning framework in which management questions are organised along three dimensions: flow and water quality indicators, wetland design parameters, and spatial allocation. Our simulation is based on the Water Systems Integrated Modelling framework (WSIMOD). From the perspective of flow and water quality indicators, the strongest co-benefits were found between nitrate and phosphate, with phosphate reductions generally achieving twice the improvement as nitrate reductions. Moderate co-benefits were identified between high flow and pollutant load reduction, while minor co-benefits were observed between low flow and other indicators. In terms of wetland design parameters, surface area shows strong spatial variability, whereas the decay constants for nitrate and phosphate are consistent across the catchment. In terms of the spatial allocation of interventions, downstream CWs tended to enhance these cumulative effects rather than produce isolated improvements, reinforcing their role in system-wide optimisation. The novelty of this study lies in proposing a problem-oriented approach for the integrated planning of urban constructed wetlands across three dimensions, providing a reference for future efforts to develop and assess new wetland cities under the Ramsar Convention.
Several studies have examined the impact of exposure to war in early life on long-term health outcomes. However, few studies have examined differences in these effects by gender and type of war. This study examines the impact of exposure to multiple war events before the age of 10 on the long-term physical and mental health of adults aged 65 years and older in China, as well as differences these effects between wars of aggression and civil wars. This study employed an Ordinary Least Squares model with year and household fixed effects, using data from six waves (2002-2018) of the Chinese Longitudinal Healthy Longevity Survey. First, the study examined the impact of war shocks and war intensity on individual health. Second, we incorporated interaction terms between war shocks and gender and between war intensity and gender into the model to investigate gender differences in the health effects of war. Subsequently, this study tested the heterogeneity based on the nature of war and explored strategies to mitigate war-related trauma. The findings indicate that, compared with individuals not exposed to war, the physical and mental health of those exposed to war declined by 17.5% and 12.1%, respectively. Among those exposed to war, women had lower physical and mental health than men. Additionally, aggressive wars had a stronger negative impact on individual health than civil wars. They also worsened both physical and mental health among women to a greater extent than among men, whereas civil wars only caused greater harm to women's physical health. This result may be attributed to two interconnected factors. First, aggressive wars, characterized by plunder and widespread violence, are inherently destructive and cause severe trauma. Second, women's vulnerability in conflict amplifies their risk of experiencing such trauma. The study also explored whether active social participation and adequate health care in adulthood could alleviate war-related trauma. No evidence of such a compensatory effect was identified. The study concludes that war inflicts severe health damage, with aggressive wars causing greater trauma and women suffering disproportionately. These findings extend beyond existing medical frameworks, identifying women as a critical group requiring targeted, structural interventions. This study reveals new research directions for mitigating war-related health consequences and informs policies aimed at improving public well-being in post-conflict settings.
This study explores the possibility of producing sustainable structural lightweight concrete (LWC) based on limestone calcined clay cement (LC³) using waste from construction and demolition. The main innovation is the dual substitution of waste-derived materials for traditional LC³ constituents: crushed brick powder (CBP) was used in place of metakaolin (MK), and recycled concrete powder (RCP) was used in place of limestone powder (LSP). To achieve lower densities, nine concrete mixtures were created using crushed brick as both fine and coarse aggregates in addition to an air-entraining agent. Flowability, dry density, ultrasonic pulse velocity, compressive strength, resistance to magnesium sulfate attack and high temperatures (200 and 400 degrees Celsius), water absorption, and porosity were all assessed through an extensive experimental program. With only a small drop in 28-day compressive strength (5–8%) and a slight increase in water absorption (10–12%), the results showed that CBP is a very promising substitute for MK. All mixtures met the structural LWC requirements of DIN EN 1045-1 (dry density of 1650–1850 kg/m³ and strength > 24 MPa), but substituting RCP for LSP resulted in a more noticeable decrease in 28-day compressive strength (15–20%) and an increase in water absorption (13–18%). Additionally, after 180 days of sulfate exposure, all LC³ systems showed very little mass loss (< 0.7%) and maintained over 80% of their residual strength at 400 °C. According to the study, CBP and RCP can effectively and sustainably replace MK and LSP in LC³-based LWC, allowing for a 60% reduction in clinker while preserving structural integrity and promoting waste valorization.
Cognition is more engaged during early than later motor skill learning (MSkL), yet the impact of post-stroke cognitive impairment (PSCI) and brain connectivity on early MSkL remains unclear. We hypothesized that early MSkL would be impaired in people with chronic stroke compared to healthy individuals (HI), and that this impairment would be associated with PSCI, lesion burden, and structural and functional connectivity. Fifty-three people with chronic stroke and twenty-one mean age-matched HI completed a comprehensive neuropsychological assessment and trained with their contralesional/non-dominant upper limb on a speed/accuracy trade-off task across two sessions, one-week apart. Early and late MSkL were modelled and related to PSCI. To identify neural substrates and predictors of post-stroke early MSkL, multimodal brain imaging included voxel-based lesion symptom mapping, whole-brain microstructural integrity and structural-functional connectivity analyses. Both HI and people with stroke demonstrated typical MSkL patterns (retention and generalization), but HI showed steeper early MSkL. PSCI correlated with poorer early MSkL. Lesions overlapping the corticospinal tract, insula and frontal white matter tracts were associated with early MSkL deficits, while higher microstructural integrity in the posterior corpus callosum correlated with better early MSkL. Structural and functional connectome-based predictive modeling identified subcortical, temporal, visual-associative, and insular hubs with interhemispheric connections as key predictors of early MSkL after stroke. These findings indicate that early MSkL is selectively impaired in chronic stroke and related to PSCI and lesion burden. Multimodal neuroimaging highlighted the role of an interhemispheric network involving sensorimotor, salience, and associative regions in supporting early MSkL in chronic stroke.
Semi-flexible pavement (SFP) combines the flexible properties of asphalt with the rigidity of a cementitious slurry, providing improved structural and durability performance. However, the reliance on ordinary Portland cement in SFP contributes notably to global CO₂ emissions. In particular, the sugarcane and ethanol industries generate substantial amounts of sugarcane bagasse ash (SBA), which is often disposed of despite its potential as a pozzolan. Therefore, this study explores the potential use of SBA, along with nano-silica (NS), as a partial cement replacement to develop a more sustainable and higher‑performing grout for SFP applications. Control grouts were formulated with water-to-cement (w/c) ratios ranging from 0.30 to 0.45 and superplasticizer (SP) dosages of 0% to 1.5%, while modified grouts incorporated 0-20% SBA (in 5% increments) and 1% NS. The optimal control grout was achieved at a w/c ratio of 0.35 and 1% SP, satisfying flow criteria and achieving a maximum 28‑day compressive strength of 48.50 MPa. The optimal sustainable grout contained 10% SBA and 1% NS, providing a 21.7% increase in compressive strength compared to the control grout. Microstructural observations confirmed a denser matrix with enhanced C-S-H formation and reduced voids, contributing to improved early strength and superior grout‑asphalt interaction. SFP specimens prepared with the optimized grout were evaluated for Marshall stability, resilient modulus (MR), indirect tensile strength (ITS), tensile strength ratio Hamburg wheel tracking, and fuel resistance. Compared to hot mix asphalt (HMA), SFP exhibited significantly enhanced performance, including approximately 88.5% higher Marshall stability, MR values exceeding 5000 MPa, 70% lower rut depth, 92% moisture‑induced strength retention, less than 5% mass loss, and approximately 93% retained strength under partial and full fuel immersion. These outcomes demonstrate the potential of SBA-NS-based SFP as a sustainable and durable pavement solution suitable for heavy‑duty and fuel‑exposed applications.
Nickel clusters have drawn considerable interest because of their distinctive structural and electronic characteristics, which differ significantly from those of their bulk-material counterparts. In this work, we investigate the structures of Ni metal atomic clusters (Ni n , n = 1-20) in neutral charge state. We also explore how these clusters interact with a range of gases such as CO, CO2, CH4, NO, NO2, NH3, H2, H2O, N2, O2, and SO2, and compute the adsorption energies, in an effort to assess their potential exploitation in sensing materials. The geometries of the clusters are optimized, and the adsorption energies are calculated using the Density Functional Theory (DFT) method at the B3LYP-GD3BJ/LANl2DZ level of theory. Indicators, including cohesive energy, HOMO-LUMO energy gap, dissociation energy, and conceptual DFT analysis descriptors, show that the stability of these clusters increases with increasing size. Ni19 was found to be the most stable cluster among those that we studied, having the highest binding energy and a compact icosahedral geometry. As the size of the clusters increased, the cohesive energy increased, while the HOMO-LUMO gap decreased, indicating a transition from molecular to metallic behavior. The calculated adsorption energies revealed weak physisorption (0 to -1 eV) for CH4, H2, H2O, and N2, and strong chemisorption (-4 to -20 eV) for O2, NO, NO2, and SO2, with NO and NO2 binding most strongly on Ni n , for n = 16-19. Charge analysis indicates greater electron transfer and partial covalent bonding for the strongly adsorbed gases.
This study explores the novel application of artificial neural networks to predict polycyclic aromatic hydrocarbons (PAHs) pollution in urban road dust by integrating magnetic properties, particle size distributions, and urban environmental features. A comprehensive dataset from 284 samples from Warsaw, Poland, included magnetic susceptibility (χ), saturation magnetization (Ms), remanent magnetization (Mrs), traffic intensity, granulometric fractions, and parameters such as building height, building layout, connection to the municipal central heating network, and geospatial coordinates. Principal component analysis (PCA) revealed that ∑PAH16 accumulation patterns are governed by the interplay between magnetic proxies (χ, Ms​, Mrs​), traffic intensity (T), and urban structural configurations, specifically heating grid status (C), building height (H), and building continuity (B; attached vs. detached structures), collectively accounting for 60.21% of the total variance. The predictive performance of the models was evaluated using 5-fold cross-validation. While the Linear Regression (LR) model showed low and unstable accuracy (R2 ranging from 0.05 to 0.32, mean 0.18), the Random Forest (RF) model provided a significantly more robust framework for capturing the nonlinear relationships between variables. SHAP (SHapley Additive exPlanations) analysis was employed to interpret the RF model, revealing that grain size fraction (F) and geospatial coordinates (LA, LO) were the primary drivers of PAH accumulation. In contrast, factors such as traffic intensity and building layout exhibited a marginal influence. The comparison of modeling approaches revealed a progressive increase in predictive performance as the ability to capture nonlinear and local relationships improved (R2 =≈0.18 for linear regression, ≈0.26 for ANN, and ≈0.40 for RF), indicating that PAH accumulation is governed by complex, context-dependent interactions rather than simple independent predictors. These findings demonstrate that integrating magnetic properties and urban features using machine learning provides a powerful tool for identifying pollution hotspots and understanding the complex mechanisms underlying the distribution of organic pollutants in urban environments.
The oxidative transformation of highly toxic Sb(III) to less toxic Sb(V) is a critical detoxification pathway. While engineered carboxymethyl cellulose-stabilized FeS nanoparticles (CMC-FeS) have been traditionally applied for in situ remediation of water and soil under anoxic environments, information on coupled transformation of CMC-FeS and Sb(III) under oxic conditions has been limited. This study explored the oxidation and immobilization process and dynamic quantitative mechanisms of Sb(III) by CMC-FeS under oxic conditions. Experimental evidence integrated with density functional theory calculations revealed that structural Fe(II) activated adsorbed O2 via single-electron transfer. Crucially, superoxide radicals (•O2-) were identified as the dominant oxidant, contributing 77.5% to Sb(III) oxidation, significantly outperforming hydroxyl radicals (•OH, 22.5%). Concurrently, CMC-FeS was transformed into lepidocrocite, effectively sequestering the generated Sb(V) predominantly through structural incorporation into the Fe (oxyhydr)oxide lattice. At equilibrium, 73.6% of Sb(III) was adsorbed, of which 98.0% was oxidized to Sb(V), with 52.8% of the generated Sb(V) retained in the solid phase. The Sb(III) oxidation increased with increasing CMC-FeS dosage, and the highest oxidation was observed at neutral pH. These findings elucidate the oxidative capacity of FeS in oxic environments and underscore the previously overlooked roles of •O2- and Fe (oxyhydr)oxides, suggesting that coupling CMC-FeS with oxygen offers a sustainable strategy for remediating redox-active contaminants.
Healthy aging involves complex neural reconfigurations across both structural and functional domains. While resting-state functional magnetic resonance imaging (rs-fMRI) has linked static functional connectivity alterations to aging, the whole-brain dynamics of functional activity and their covariance with structural changes remain poorly characterized. To address this gap, we integrated three data-driven approaches to profile functional dynamics in the aging brain and decode their association with structural atrophy. Using rs-fMRI data from 252 participants-145 young adults (22.7±3.4 years) and 107 older adults (68.7±6.5 years)-we made several key observations. First, normalized Shannon entropy revealed a significant reduction in spatiotemporal complexity among older individuals. Second, phase synchronization analysis of BOLD signals indicated enhanced global integration and metastability in older adults, particularly within the dorsal attention (DAN), ventral attention (VAN), and frontoparietal networks (FPN). Third, temporal asymmetry analysis demonstrated increased nonreversibility and a heightened functional hierarchy in the aging brain, again most evident in the FPN. Morphometric analyses confirmed widespread structural atrophy in older participants. Crucially, partial least squares (PLS) analysis uncovered significant covariance between morphometric patterns and dynamic functional metrics, underscoring a tight structure-dynamics coupling in aging. Furthermore, structural atrophy correlated significantly with variations in micro-architecture maps. Finally, we evaluated the behavioral relevance of these dynamics through correlations with cognitive performance. Our findings offer an integrative, multiscale perspective on neural decline in aging, emphasizing the interplay between dynamic functional reorganization and structural atrophy.
Seismic risk assessment is a probabilistic approach that evaluates the likelihood of earthquake occurrence, structural response, expected damage levels, economic losses, and potential casualties by incorporating the inherent uncertainties associated with seismic hazards and urban building characteristics. The primary objective of this study is to quantify and spatially characterize the distribution of damage states at the urban scale. Buildings were classified according to their structural system, age, and number of stories. The structures were initially modeled, analyzed, and designed in ETABS, and the beam and column section properties were extracted for each structural type. Finite element models were subsequently developed in OpenSees, and Incremental Dynamic Analysis, IDA, was performed to evaluate the seismic performance of building groups and large-scale seismic risk. The application of this approach to urban-scale seismic risk evaluation distinguishes this research from similar previous investigations. Given the considerable number of models, the extensive dataset, and the necessity for updating results under varying input conditions, a Bayesian Probabilistic Network was employed. In addition, GIS-based mapping was used to present the findings, including the exceedance probabilities of different damage states and the spatial distribution of collapse probability. The outcomes of this study identify areas that may exhibit relatively higher seismic vulnerability, emphasizing the potential need for targeted retrofitting strategies or, enhanced preparedness for post-earthquake emergency response and rescue operations.
Research-based learning (RBL) is widely considered important for fostering higher-order learning and innovation in higher education, yet the mechanisms linking students' participation in RBL to innovative capability remain insufficiently understood. Drawing on Social Cognitive Theory and Self-Determination Theory, this study examined whether self-efficacy (SE) mediates the associations of participation quality (PQ) and intrinsic learning motivation (ILM) with perceived innovative capability (INCA). Data were collected through an online survey conducted from March to April 2025 at a comprehensive science-and-engineering university in central China. Although 843 valid questionnaires were obtained, structural analyses were limited to the 340 undergraduates who reported prior participation in RBL, because PQ was measured only in this subgroup. Confirmatory factor analysis and covariance-based structural equation modeling were performed. Indirect effects were tested using bias-corrected bootstrap resampling (5000 draws), and alternative structural specifications were compared using Wald tests. The results showed that both PQ and ILM significantly predicted SE, and SE was positively associated with INCA. PQ had both a direct effect on INCA and an indirect effect through SE, whereas the effect of ILM on INCA was transmitted primarily through SE. Competing-model comparisons supported a more parsimonious specification in which the direct path from ILM to INCA was removed, while the paths from PQ to INCA and from SE to INCA were retained. These findings highlight the central role of self-efficacy in translating high-quality participation and motivational resources in RBL into innovation-related development.
Global flood risk has intensified dramatically since 2000, yet its alignment with disaster-related SDGs remains unclear, limiting our understanding of how to effectively reduce it. This study develops a composite Flood Risk Index (FRI) based on the hazard - exposure - vulnerability framework and constructs comparable SDG sub-indicator scores for six disaster-related metrics. Using data for 111 countries from 2000 to 2024, long-term trajectories were evaluated via OLS regression slopes, and structural turning points were detected through a Pruned Exact Linear Time (PELT) algorithm for both FRIs and SDGs. Results show a persistent global rise in flood risk, predominantly driven by hazard intensification throughout the study period (R2 = 0.64-0.93), while exposure and adjusted vulnerability exhibited weaker, phase-dependent associations, becoming more prominent in the mid-2000s and after 2019. Four phases of FRI evolution of an initial surge (2000-2005) (0.000177), global escalation (2006-2010) (0.000614), transitional stabilisation (2011-2018) (-0.000156), and mild post-stabilisation decline (2019-2024) (-0.000064) reflect shifts in the underlying risk structure. Coupling results reveal that only SDG 1.5.2 (economic loss) and SDG 11.5.3 (infrastructure disruption) show significant negative associations with long-term FRI trends, while most SDGs display no significant relationship with flood risk at the global level. A similar pattern is observed in within-country analyses, where only a few nations show (positive or negative) significant SDG-FRI relationships, mainly under the former two and SDG 1.5.1, like Namibia, Indonesia, and Algeria, implying a structural misalignment between global SDG progress and actual flood-risk reduction. This finding highlights the need to recalibrate disaster-related SDG indicators to better reflect hazard intensification, exposure dynamics, and the evolving socio-institutional determinants of flood vulnerability.
Conductive hydrogels frequently struggle to balance high conductivity, robust mechanical strength, excellent UV resistance, and antibacterial properties, a limitation that restricts their applications in intelligent wearable sensors. In this work, a comprehensive strategy was developed to fabricate a semi-interpenetrating polymer network (semi-IPN) composite hydrogel. This hydrogel consists of a polyacrylic acid (PAA) network interpenetrated by linear glucurono-dialdehyde xylan (GlcU-DAX) via hydrogen-bonding, reinforced by the synergistic multifunctional effects of GlcU-DAX and silver nanoparticles (AgNPs). Mechanistic investigations demonstrate that GlcU-DAX, which is rich in hydroxyl, carboxyl, and aldehyde groups, plays multiple critical roles in the hydrogel matrix. It not only serves as one of the two main components of the semi-IPN structure, but also acts as a reducing agent for the formation of AgNPs from silver salts. Meanwhile, GlcU-DAX functions as a dispersing stabilizer via electrostatic repulsion originating from its carboxyl groups. This effect helps homogenize acrylic acid (AA) and GlcU-DAX in the precursor solution to form uniform semi-IPNs, while also inhibiting the aggregation of the as-reduced AgNPs and maintaining their small, well-dispersed size within the hydrogel. In addition, GlcU-DAX also acts as a promoter for the polymerization of AA. This innovative application mode fully leverages the structural advantages of xylan. Meanwhile, the reduced AgNPs with small size endow the hydrogel with inherent mechanical reinforcement, UV-blocking capability, and antibacterial activity via Ag+ active species. AgNPs also enhance the coordination interactions between GlcU-DAX and PAA, thereby further improving the hydrogel's mechanical and conductive properties. Under optimized conditions, the as-prepared hydrogel exhibits outstanding comprehensive performance, including superior mechanical properties (1235.66% elongation at break, 51.72 kPa tensile stress, 218.07 kPa compressive stress), excellent compression fatigue resistance (95.1% stress retention after 200 cycles at 50% strain), nearly complete UV shielding (transmittance close to zero in both UVA and UVB regions), strong substrate adhesion (up to 36.64 kPa on wood), and high conductivity (0.59 S m-1). This work not only expands the high-value utilization of xylan and provides a sustainable route for nanomaterial synthesis, but also offers important insights into the design of multifunctional biomass-based materials for advanced flexible wearable electronics.
To ensure the prefabrication quality of concrete segmental beams for assembled railway bridges, this study investigates the main factors affecting the casting and curing of such beams. Using the Zheng-Xu regional railway bridge as a case study, this study analyzes the impact of environmental temperature, formwork materials, formwork thickness, pouring temperature, wind speed, and prestressed ducts on the thermal-structural coupled stresses in the beams, based on meteorological conditions at the prefabrication yard. A detailed concrete curing control plan is proposed. The research results show that formwork materials and pouring temperature have a significantly greater influence on the early thermal effects of prefabricated concrete segmental beams than other factors. Formwork materials exhibit the highest sensitivity to temperature and temperature stress, with sensitivities of 17.8% and 36.1%, respectively, followed by pouring temperature, which has sensitivities of 12.7% and 21.7% to temperature and temperature stress, respectively, and is positively correlated with peak temperature and peak stress. Wind speed and prestressed ducts are sensitive to temperature stress, with their sensitivities being less than 5%. Prestressed ducts promote internal heat dissipation in concrete segmental beams, reducing the internal peak temperature and the temperature difference between the interior and exterior, thereby lowering the risk of cracking. The better the thermal insulation performance of the formwork materials, the later and higher the temperature peak. Additionally, the thickness of the formwork materials has a greater impact on the temperature and stress of the segmental beam concrete. Based on the identified temperature field and thermal stress patterns for each significant factor, this study proposes detailed curing plans, including winter steam curing and summer spray curing. These strategies effectively reduce the internal-external temperature difference, minimize surface stresses, and mitigate the risk of cracking. The quality of prefabricated concrete segmental beams confirms the scientificity and rationality of the fine-curing control plan, which can serve as a reference for the detailed control of prefabrication and curing.
This study investigates the synergistic mechanical and durability performance of slag-based geopolymer composites reinforced with alkali-treated date palm fibers (TDPF) and polypropylene fibers (PPF), with particular emphasis on interfacial behavior, pore structure evolution, and acid resistance. The novelty of this research lies in the combined microstructural-mechanical-durability assessment of treated agro-waste fibers directly compared with synthetic fibers under identical geopolymer conditions, including exposure to sulfuric acid. Fibers were incorporated at volume fractions of 0.15%, 0.30%, and 0.50%, with lengths of 6 mm and 12 mm. The optimal composition (0.50% TDPF, 12 mm) achieved a 22.8% increase in compressive strength at 28 days and a 19.1% increase at 90 days. Flexural strength improved by up to 29.9% at early age and remained enhanced (approximately 18-19%) at later ages. SEM-EDS and FTIR analyses confirmed improved fiber-matrix interaction and enhanced integration within the aluminosilicate network in TDPF composites. Water absorption and open porosity were influenced by fiber type and dosage; however, optimized long-fiber mixtures reduced pore connectivity despite the hydrophilic nature of natural fibers. After 15 days of exposure to 3.5% H₂SO₄ solution, fiber-reinforced composites maintained structural integrity, with strength degradation limited to approximately 9-10%, demonstrating stable chemical resistance. Overall, the results indicate that alkali-treated date palm fibers provide competitive mechanical performance while offering a sustainable alternative to synthetic reinforcement in geopolymer composites, thereby supporting low-carbon and circular construction strategies.
Antibiotic contamination in environmental waters poses both ecological and health hazards. However, detecting antibiotics using fluorescence techniques is challenging due to pH-dependent spectral variability and interference from dissolved organic matter (DOM). In this study, the excitation-emission matrix (EEM) fluorescence spectroscopy combined with parallel factor analysis (PARAFAC) was used to characterize the intrinsic fluorescence properties of 27 antibiotics. Based on environmental prevalence and structural class, antibiotics were systematically selected at three environmentally relevant pH values (5, 7, and 9) that reflect the typical pH range found in natural and wastewater systems. Results revealed strong stability in fluoroquinolones, pH-dependent enhancement in tetracyclines, and negligible emission in several other classes. Based on these results, Random Forest classifiers trained on 19 spectral features achieved 85.2% accuracy for pH response prediction and 92.6% for detection feasibility. Based on these findings, we developed a Detection Risk Index (DRI) that categorizes 44% of antibiotics as low risk, 33% as medium risk, and 22% as high risk for EEM-based detection. Five antibiotics were selected for DOM interaction and wastewater validation studies based on their DRI and environmental relevance. Experimentation with DOM interaction patterns showed that there is a wide range of quenching behavior among antibiotics, ranging from dynamic quenching to fluorescence enhancement. Notably, the directional consistency between laboratory DOM quenching at neutral pH and fluorescence matrix effects in wastewater indicates that controlled experiments can predict environmental interference. The results provide valuable information for monitoring antibiotics using fluorescence techniques in environmental waters.
As carbon dioxide (CO2) injection plays an increasingly important role in greenhouse gas mitigation and enhanced oil recovery (EOR), a fundamental understanding of CO2-oil interfacial dynamics is essential for optimizing miscibility and displacement efficiency. In this study, molecular dynamics simulations (MD) are employed to systematically investigate interfacial evolution in CO2-alkane systems, with particular emphasis on the effects of pressure, temperature, and alkane chain length, among which chain length exerts the most pronounced influence on interfacial behavior. Results show that increasing pressure significantly enhances interfacial mass transfer and reduces the density of the alkane bulk phase, whereas increasing temperature promotes CO2 escape from the oil phase, leading to a corresponding density increase under constant-pressure conditions. Compared with short-chain alkanes, long-chain alkanes exhibit weaker pressure sensitivity and narrower interfacial characteristic lengths, which are primarily attributed to their more ordered molecular structures and tighter packing. These structural features effectively suppress CO2 dissolution, resulting in lower solubility and reduced oil swelling capacity. The minimum miscibility pressure (MMP) is determined using the vanishing interfacial tension (VIT) method. The results reveal that long-chain alkanes possess lower configurational entropy and higher interfacial stability, which increases resistance to CO2-oil miscibility and fundamentally accounts for the observed increase in MMP with alkane chain length. Overall, this work provides molecular-level insights into the interfacial evolution and miscibility mechanisms of CO2-oil systems, offering valuable theoretical guidance for optimizing CO2 injection pressure and composition-dependent strategies in EOR applications.
The structural diversity and complex transport behavior of per- and polyfluoroalkyl substances (PFAS) complicate a universal characterization of their removal in membrane systems. This study compiles 2353 data points from the literature on PFAS rejection by nanofiltration and reverse osmosis membranes, spanning a broad range of PFAS, membranes, feedwater compositions, and operating conditions. Using machine learning, this data set is modeled to evaluate how solute, membrane, and solution properties jointly influence PFAS removal. Of the 13 experimental system descriptors analyzed, membrane water permeance and PFAS molecular volume demonstrated the strongest main effect on rejection, emphasizing the significance of steric exclusion. The effects of background ions and dissolved organic matter were highly condition-dependent, exhibiting nonmonotonic behavior governed by competing mechanisms. Low concentrations of organic matter and ions enhanced PFAS rejection, consistent with complexation that increases apparent solute size, while higher concentrations reduced PFAS rejection, indicating that charge shielding and concentration polarization increasingly drive transport behavior. Overall, this analysis provides a unified, data-driven framework for interpreting previously inconsistent findings across studies, identifies critical gaps in existing experimental data, and highlights opportunities to guide targeted membrane design and treatment strategies.
Nitrate accumulation remains a major constraint for nitrogen removal in microalgal-bacterial granular sludge (MBGS) systems, primarily due to insufficient denitrification within oxygen-rich microenvironments. This study investigated the effects of bioaugmenting MBGS with two direct ammonia-oxidizing (Dirammox) bacteria, Acinetobacter sp. ACI-9 and Alcaligenes ammonioxydans sp. HO-1, with particular emphasis on extracellular polymeric substances (EPS) characteristics, microbial community structure, and nitrogen transformation pathways. Three parallel sequencing batch reactors (SBRs) were operated for 70 days: a control reactor (RN), and two bioaugmented reactors inoculated with ACI-9 (RA) and HO-1 (RH), respectively. Bioaugmentation preserved granule structural stability and enhanced overall nitrogen removal performance. Relative to the control, ACI-9 bioaugmentation reduced nitrate accumulation by 19.26%, whereas HO-1 exerted a comparatively weaker effect. Microbial community analyses revealed increased community diversity and the selective enrichment of taxa associated with floc formation, endogenous carbon turnover, and nitrogen reduction processes. Functional gene profiling suggested coordinated shifts in genes involved in nitrate processing and downstream denitrification following bioaugmentation. In particular, ACI-9 showed a stronger late-stage nosZ-associated signal than HO-1, while the Dirammox-related gene dnfABC remained detectable in all reactors, suggesting persistent Dirammox-related genetic potential in the MBGS system. Overall, ACI-9 induced more pronounced structural and functional responses than HO-1, underscoring the critical role of strain-specific pathway integration in mitigating nitrate accumulation and improving nitrogen removal efficiency in MBGS systems.