Search Results (8,202)

Nanomaterials (NMs) have shown broad application potential in wastewater deep treatment, but the actual application is constrained by some issues such as nanoparticle (NP) aggregation and poor recyclability. Different from previous comprehensive reviews, this article systematically synthesizes data from over 100 peer-reviewed studies (2012 to 2026) to review the preparation methods, purification mechanisms, and removal efficiencies for various pollutants, and the technical and economic feasibility of NMs, with an emphasis on carrier-assisted immobilization and NM–microbial aggregate interactions. To start with, the methods of preparation were roughly distinguished into two categories which were “top-down” and “bottom-up” methods. The advantages, disadvantages, and utilities of the physical, chemical, and eco-friendly methods of biosynthesis were investigated while paying particular attention to the function of the loading technique in preventing NP aggregation and improving recyclability. By using the technique of loading in the carrier, the growth of NPs could be restricted up to 2–50 nm. Secondly, seven basic mechanisms that underlie the process of removing pollutants by using NPs were explained: adsorption, catalytic degradation, ion exchange, surface complexation, antibacterial action, redox transformation, and waste recycling. Particular focus was placed on understanding the interactions between NMs, microbial aggregates, and extracellular polymeric substances in wastewater treatment systems. Extracellular polymeric substances (EPS) could capture >90% NMs and mitigate their toxicity. Once again, the removal efficiency and main influencing factors associated with different types of NMs, for the treatment of heavy metals, dyes, antibiotics, and pathogenic microorganisms were summarized. Removal efficiencies of the pollutants ranged from 70% to over 99%, but these values were strongly influenced by pH and matrix and often decreased substantially in real wastewater. The existing literature was used to classify the experimental substrates (single-solute systems, multi-solute synthetic systems, municipal wastewater, industrial wastewater, secondary effluent). The performance of NMs in different categories was compared, revealing the huge performance gap between ideal laboratory conditions and practical applications. Lastly, the economic viability of the methods based on the use of NMs for purifying water was assessed taking into consideration various factors such as raw materials’ prices, energy costs of the process of making materials, recyclability of the materials, and the possibility of introducing the use of NMs on a larger scale. Unlike existing reviews, this article aims to provide a quantitative mechanistic framework bridging the rational design, safe application, and engineering promotion of NMs in deep wastewater treatment. Full article

Collagen functional fragments retain selected activities of parent collagens while allowing greater flexibility in sequence design and precision fermentation. Although recent reviews have covered recombinant collagen production technologies, expression platforms, purification strategies, quality control, and biomedical applications, fragment selection, host–process matching, production, and characterization have received less integrated attention. This review focuses primarily on collagen-derived functional fragments, while collagen-mimetic peptides and collagen-like proteins are discussed as related design systems. The biological basis for fragmentation includes receptor-recognition motifs, matrikines and matricryptins, and basement membrane-derived fragments. The review further examines how motif context, Gly-X-Y organization, stabilizing sequence features, protease susceptibility, post-translational modification requirements, and host compatibility influence fragment stability, expression performance, production feasibility, and product integrity. Microbial production using Escherichia coli, Komagataella phaffii, and Saccharomyces cerevisiae is discussed from the perspectives of construct–host matching, secretory or intracellular production, prolyl 4-hydroxylase configuration, fermentation optimization and scale-up, and product characterization. Finally, we discuss AI-assisted, quality-guided design-build-test-learn workflows that integrate computational prediction, curated structural, extracellular-matrix, interaction, and protease resources, two-tier candidate evaluation, and format-appropriate experimental testing to support iterative sequence, host, and process optimization. The development of collagen functional fragments therefore depends on coordinated optimization of biological function, molecular design, microbial host performance, fermentation processes, and product characterization. Full article

Lead contamination remains a significant environmental and public health concern, creating a demand for analytical platforms that combine sensitivity, simplicity, and long-term stability. In this work, a graphene-containing molecular membrane matrix was developed for the fabrication of single-piece all-solid-state potentiometric sensors for Pb(II) detection. The sensing membrane consisted of poly(vinyl chloride), plasticizers, a Pb(II)-selective ionophore, lipophilic ionic sites, and dispersed graphene nanostructures, forming an integrated molecular sensing interface. Within the membrane phase, selective complexation of Pb(II) ions by the ionophore was coupled with graphene-assisted ion-to-electron transduction, enabling efficient signal generation without the need for a separate solid-contact layer. The influence of graphene incorporation and membrane thickness on sensor performance was systematically investigated. Among the tested configurations, a membrane prepared from 40 µL of sensing cocktail provided the best overall performance, combining high electrical capacitance, favorable surface properties, and superior potential stability. SEM imaging revealed a homogeneous membrane morphology without large graphene agglomerates, indicating effective dispersion of graphene within the polymer matrix. The optimized sensor exhibited a near-Nernstian slope of 30.3 mV dec⁻¹, a linear response range from 1.0 × 10⁻⁷ to 1.0 × 10⁻² M, a detection limit of 6.3 × 10⁻⁸ M, and a potential drift of only 0.35 mV h⁻¹. These results demonstrate that direct incorporation of graphene into an ion-selective membrane is an effective strategy for constructing robust and scalable single-piece potentiometric sensors for Pb(II) monitoring and highlight the potential of developed membrane materials for electrochemical sensing applications. Full article

In this work, a BiFeO₃/MoS₂ (BM) material was utilized to establish a piezophotocatalytic system under combined visible-light (Vis) illumination and mechanical stirring (MS), which synergistically activated peroxymonosulfate (PMS) toward the oxidation of 4-chlorophenol (4-CP), a representative refractory organic pollutant in water. Under mechanical stirring, the piezoelectric effect in BM generates a polarized electric field that promotes the separation of photogenerated electron–hole pairs, thereby providing more charge carriers for PMS activation and subsequent radical generation. The degradation performance, underlying mechanism, toxicity of degradation products, reusability, and applicability in different water matrices in the BM(1:3)/PMS process were comprehensively evaluated. The results indicated that BM(1:3) exhibited superior performance over other BM ratios (BM(2:1), BM(1:1), and BM(1:2)), achieving 91.6% removal of 4-CP within 30 min at a rotation speed = 1000 rpm, PMS = 2.0 mM, BM(1:3) = 0.5 mg/L, and initial 4-CP = 10 mg/L. Furthermore, water quality parameters exerted notable impacts on 4-CP decomposition. A pH of 4.7 was favorable, and the presence of Cl⁻ enhanced the 4-CP degradation, while HCO₃⁻ and H₂PO₄⁻ suppressed the removal efficiency; SO₄²⁻ and HA showed negligible influence. DFT calculations identified the reactive sites on 4-CP that are prone to attack by various reactive oxygen species (e.g., •O₂⁻, ¹O₂, •OH, and SO₄•⁻), resulting in the transformation of 4-CP through three degradation pathways into smaller organic intermediates, most of which were less toxic than 4-CP. The BM(1:3) catalyst exhibited satisfactory reusability; however, a significant decrease in 4-CP degradation efficiency was observed in the lake water matrix. Overall, the synergy between photocatalysis and the piezoelectric effect in the BM(1:3)/PMS system offers a useful research foundation for the piezophotocatalytic degradation of persistent organic pollutants such as 4-CP. Full article

Alkali-activated binders (AABs) represent eco-friendly alternatives to ordinary Portland cement. Nevertheless, the synergistic influences of calcium dosage and aluminosilicate stoichiometry on phase assemblage, gel nanostructure, and mechanical properties have not been fully elucidated. Herein, AAB samples with graded CaO contents were fabricated, and the co-regulatory mechanisms of CaO dosage and Si/Al molar ratio on compressive strength and microstructural evolution were systematically explored through compressive strength tests, XRD, TG-DTG, FTIR, and SEM-EDS. In addition, pure reference C-S-H and N-A-S-H gels were synthesized by using the sol–gel method for comparison with AAB pastes. The results reveal that CaO dosage acts as the primary parameter dictating gel phase transition and strength level, categorizing the prepared AABs into three distinct zones: low-calcium region (CaO < 10 wt.%), medium-calcium region (10–20 wt.%), and high-calcium region (CaO > 20 wt.%). Combined grey relational and partial correlation analyses clarify the collinearity-induced false correlations and reveal the stage-dependent independent effects of oxide molar ratios on AABs’ compressive strength. Low-calcium AAB matrices are dominated by N-A-S-H gel networks coexisting with abundant low-strength zeolite crystals, which deteriorate thermal stability and retard strength gain. Increasing CaO content triggers a progressive phase transformation from N-A-S-H gel to high-strength C-(A)-S-H gel. Abundant Ca-rich chabazite and C-S-H gel form in high-calcium systems, which fill internal pores and microcracks and greatly enhance matrix densification and thermal resistance. This work clarifies the multiscale regulatory mechanism of calcium species over gel polycondensation, crystalline phase development, and mechanical performance of AABs, offering fundamental theoretical guidance for the customized design and property optimization of high-strength alkali-activated binders. Full article

Cost control in engineering, procurement, and construction (EPC) public works is shaped by interacting drivers, nonlinear feedback, and qualitative judgments. Existing studies usually apply the three relevant method families separately: DEMATEL-ISM maps causal structure but does not propagate hesitation-aware expert judgments into cost trajectories; fuzzy systems represent uncertainty but commonly lack a verified causal hierarchy; and system dynamics (SDs) capture dynamic accumulation but often rely on crisp inputs. The resulting absence of a traceable causal screening to uncertainty to dynamic cost link is the specific gap addressed in this study. We therefore develop a transparent three-stage pipeline combining the Decision-Making Trial and Evaluation Laboratory–Interpretive Structural Modeling (DEMATEL-ISM) method, triangular intuitionistic fuzzy reasoning (TIFR), and SDs. DEMATEL-ISM identifies the causal hierarchy; TIFR represents membership, non-membership, and hesitation in design complexity and human–technology synergy judgments; and SDs evaluate stage-specific cost trajectories. Recalculation from the supplied 17 × 17 direct influence matrix produced a six-level hierarchy in which senior management decision-making capability and the level of integration occupy the two deepest driving levels. For the Urumqi Civic Center case, the baseline terminal cost absolute percentage error was 0.492%. A coordinated intervention scenario shifted the simulated terminal cost by CNY 12.1243 million (6.1%) relative to the baseline; this is a model-based scenario difference, not an observed project saving. Integration had the largest simulated effects on design and transportation costs, whereas senior management decision-making capability had the largest effects on procurement and construction costs. Security cost curves showed a complementary pattern between managerial capability and workers’ professional competence, but no statistical interaction effect is claimed. The framework is intended for within-case scenario comparison and intervention prioritization; multi-project and time-series validation remains necessary. Full article

The interface failure modes between fibers and asphalt mastic exhibit complex and diverse morphologies under the influence of multiple factors, making cluster analysis difficult. To address this issue, this study proposes an improved growth curve mixture model (IGCMM) for the unsupervised clustering of interface failure modes. Through single-fiber pull-out tests on 90 specimens under three temperatures (−10 °C, 25 °C, and 60 °C) and three fiber types (basalt, glass, and polyester), load–displacement curves were obtained. The multivariate power exponential (MPE) distribution was used to characterize the peak and heavy-tailed features of residuals. Due to the high dimensionality caused by the joint analysis of multiple datasets, principal component analysis (PCA) was employed to compress the 200-dimensional curve data into three principal components, with all model parameters estimated in the low-dimensional space. The Expectation–Maximization (EM) algorithm combined with the extended Bayesian Information Criterion (eBIC) determined the optimal eight failure mode clusters. The results exhibit a high posterior assignment confidence: 96.7% of samples had posterior probabilities exceeding 0.999. The eight statistical patterns were successfully mapped to four theoretical failure modes—fiber pull-out, medium-temperature matrix failure, high-temperature matrix failure, and mixed failure—revealing the coupled regulatory mechanism of temperature and fiber type on interface failure. The framework established in this study—“data-driven clustering–physical parameter anchoring–failure mechanism interpretation”—provides new theoretical tools and methodological support for the mesoscale interface failure diagnosis and crack resistance optimization design of fiber-reinforced asphalt pavement materials. Full article

In this article, we consider a class of nonhomogeneous neutral linear systems with Caputo-type fractional derivatives, having incommensurate orders of differentiation and distributed delays. The main goal is to investigate the influence of the Perron condition on the stability properties of the corresponding homogeneous neutral linear system, when the nonhomogeneous system satisfies this condition. We first prove that, for any partially absolutely continuous initial functions, the investigated nonhomogeneous system has a unique global absolutely continuous solution. Furthermore, if the nonhomogeneous system satisfies the Perron condition, we establish that the fundamental and the extended fundamental matrices of the corresponding homogeneous system are uniformly bounded under certain boundedness conditions, which are also used in the classical case for systems with first-order derivatives. This uniform boundedness implies that the zero solution of the homogeneous system is uniformly stable. Finally, it is proved that the extended fundamental matrix Q(t,s) tends to zero as t → ∞, thereby demonstrating that the zero solution of the investigated homogeneous system is uniformly asymptotically stable. Full article

Wound healing is a dynamic and highly coordinated process that involves inflammation, cell proliferation, angiogenesis, re-epithelialization, extracellular matrix remodeling, and tissue maturation. The altered expression of important signaling pathways, such as transforming growth factor-β (TGF-β)/Smad, nuclear factor-κB (NF-κB), phosphoinositide 3-kinase/protein kinase B (PI3K/Akt), mitogen-activated protein kinase (MAPK), and Wnt/β-catenin, may be responsible for slower wound healing, chronic inflammation, excessive fibrosis, and impaired tissue regeneration. Multifunctional nanomaterials are a promising strategy for tuning these highly coordinated processes due to their tunable physicochemical properties, high surface area, and the ability to deliver cargo, as well as the integration of antimicrobial, antioxidant, anti-inflammatory, and pro-angiogenic properties. The aim of current review is to summarize the potential of multifunctional nanomaterials to promote wound healing, with a focus on mechanisms of action and modulation of key cellular signaling pathways. A systematic review of the literature was conducted using PubMed, Scopus, Web of Science, and Google Scholar, searching for publications from 1996 to June 2026, and representative experimental, mechanistic, preclinical, and translational studies were critically evaluated. In this review, the authors discuss the role of nanomaterial properties, therapeutic payload, molecular targets, modulation of cellular signaling pathways, and regenerative effects. These platforms have been shown in in vitro and animal studies to influence inflammatory signaling, oxidative stress, angiogenesis, collagen remodeling, re-epithelialization, cellular proliferation, and migration. However, the modulation of these pathways are dose-responsive, time-dependent, and cell- and wound-stage-specific. Despite the promising therapeutic potential of nanomaterial-based wound care strategies, the available evidence remains predominantly preclinical, with relatively limited clinical data supporting their use in humans. Concerns regarding long-term toxicity, biodistribution, batch-to-batch reproducibility, sterilization, scalable manufacturing, regulatory approval, and commercial feasibility further challenge translation into clinical practice. Multifunctional nanomaterials may offer a promising approach for pathway-specific and multimodal wound management; however, comprehensive mechanistic studies, long-term safety and biodistribution assessments, and well-designed clinically relevant investigations are required to establish their efficacy, safety, and true translational potential. Full article

The Andes serve as natural laboratories where biomes shape faunal communities into mosaics of habitats prone to fragmentation, making protected areas such as the Chimborazo Reserve (RC) critical refuges in the face of climate change. Based on this premise, patterns of biotic specialization and inter-biome faunal connectivity were evaluated through the ordering and co-scaling of family-level taxa in factorial space. A geospatial design was employed, stratifying the area into 400 ha cells, which were distributed across the high-Andean tundra (T), paramo grassland (G), and Andean forest (F) biomes and selected via simple proportional random sampling. A validated database of 2511 occurrences was compiled for the classes reptilia, aves, mammalia, amphibia, and insecta, comprising a total of 48 families, integrating records from global platforms and field surveys. The resulting matrix of 102 sampling cells (across three biomes) with 48 taxonomic families was analyzed using principal component analysis (HJ-biplot), k-means clustering, and bidirectional biclustering. It was found that Cluster 3 reflected a marked ecotone effect and faunal connectivity between F and G, dominated by generalist families with high evolutionary success such as Thraupidae, Tyrannidae, and waterbirds. In contrast, Clusters 1 and 2 revealed structural discontinuities and high biogeographic specialization in response to abiotic stress in the tundra, isolating taxa adapted to extreme conditions (Tropiduridae, Cricetidae, and Thinocoridae). Biclustering confirmed that the heterogeneity of the terrain mitigates climatic severity at the forest edge, acting as a microclimatic refuge for specialized nectar-eaters (Trochilidae) associated with Chuquiraga jussieui. The zoological structure of the RC reflects a distinct and predictable faunal partition that is strongly influenced by the interaction between the altitudinal gradient and microtopography. The coexistence of zones of diffuse transitions that promote biotic connectivity alongside nuclei of maximum specialization and ecological isolation was confirmed, which is essential for planning conservation measures. Full article

Surface-figure stability is essential to high-resolution optical remote-sensing systems that employ lightweight annular primary mirrors. This study proposes a variable triangular active support layout for a 660 mm annular thin mirror with a 100 mm central aperture. The layout is parameterized within a one-sixth annular sector and constructed over the full aperture by six-fold rotational replication. Finite-element influence functions, Annular Zernike modal fitting, and Kriging surrogate modeling are integrated to assess modal controllability while reducing the cost of repeated finite-element analyses. The objective function accounts for surface-figure maintenance under gravity, correction residuals for representative low-order Annular Zernike modes, geometric constraints, and the actuator-force limit. Optimization is performed using the covariance matrix adaptation evolution strategy (CMA-ES), followed by local refinement. For a 36-point support configuration, the optimized variable triangular layout satisfies the 12.66 nm RMS residual requirement under axial and radial gravity and for all representative Z₄–Z₁₁ target surfaces. Among the annular, triangular, square, hexagonal, Fibonacci, and proposed layouts, the proposed layout yields the lowest composite objective-function value, a mean corrected RMS residual of 2.15 nm, and an effective response-matrix rank of 35. Monte Carlo simulations with independent ±1 mm support-position perturbations further demonstrate its robustness to installation errors. Full article

Recent studies have witnessed significant advances in unified multi-weather image restoration, which aims to handle diverse weather degradations within a single model. In this work, we observe that rain, haze, and snow restoration exhibit substantial differences in both degradation characteristics and learning dynamics, making straightforward joint optimization prone to performance imbalance and ineffective knowledge transfer. To this end, we propose UMWIR-Net, a unified multi-weather image restoration network equipped with an Asymmetric Task Collaborative Learning strategy. ATCL consists of Intra-Task Difficulty Optimization and Inter-Task Contribution Scheduling. Specifically, Intra-Task Difficulty Optimization jointly models the remaining restoration error and recent learning progress to dynamically estimate the optimization difficulty of each weather task, thereby assigning larger weights to slowly converging and under-optimized tasks. Inter-Task Contribution Scheduling measures the directional influence of a source-task update on the validation objective of a target task, constructs an asymmetric task-contribution matrix, and accordingly promotes tasks that provide stronger transferable knowledge while compensating those that benefit less from collaborative learning. In this manner, different weather restoration tasks collaborate selectively and asymmetrically, allowing the model to exploit complementary knowledge across tasks and improve overall restoration performance. Furthermore, UMWIR-Net adopts a wavelet-based Transformer backbone to capture low- and high-frequency information, enabling effective modeling of both global structures and local details for diverse weather restoration. Extensive experiments on multi-weather image restoration datasets show that UMWIR-Net achieves state-of-the-art performance and delivers more balanced restoration quality across rain, haze, and snow removal. Full article

Unsaturated polyester resins (UPRs) represent challenging systems for reversible-deactivation radical polymerization (RDRP) because chain propagation, branching, and localized gelation may occur concurrently. This study systematically investigates the influence of the concentration of the RAFT agent 2-cyano-2-propyl dodecyl trithiocarbonate (CPDT), the chemical structure of the polyester prepolymer, and the nature of the acidic comonomer on the structural evolution of RAFT-modified unsaturated polyester copolymers. Three copolymer series synthesized at different CPDT concentrations were investigated: p-EGM:AA:[CPDT], p-EGM:MAA:[CPDT], and p-PGM:MAA:[CPDT]. Structural changes were characterized using H NMR, H–H COSY, UV–Vis spectroscopy, and gel permeation chromatography (GPC). Semi-quantitative analysis of normalized H NMR integral intensities was performed using Relative Vinyl Intensity (RVI), CPDT-associated methyl intensity (MI*), and normalized aliphatic intensity (AI*) to compare changes in selected proton environments among the investigated copolymer series. Increasing CPDT concentration was accompanied by a decrease in the normalized residual maleate vinyl signal, although the magnitude of this change depended strongly on copolymer composition. The most pronounced decrease in RVI was observed for the p-EGM:AA:[CPDT] series, from 0.6291 to 0.0528, whereas substantially smaller changes were observed for the p-EGM:MAA:[CPDT] series. The MI* and AI* profiles exhibited composition-dependent variations, reflecting changes in the relative contributions of CPDT-associated methyl and overlapping aliphatic proton environments, respectively. Because the aliphatic region used for AI* contains overlapping polymer- and CPDT-derived contributions, AI* is not interpreted as a quantitative measure of polymer-backbone branching. Overall, the combined NMR and GPC/SEC results reveal composition-dependent structural changes accompanying RAFT copolymerization and demonstrate that both the polyester matrix and the acidic comonomer influence the response of these heterogeneous unsaturated polyester systems to variations in CPDT concentration. Full article

With the rapid advancement of terahertz technology, electromagnetic interference has become a critical issue that compromises device performance, creating an urgent demand for high-performance terahertz absorbers. Three-dimensional (3D) printing, characterized by flexible structural design, monolithic fabrication, and mold-free processing, has emerged as a promising technique for producing terahertz absorbers. In this work, inspired by the structural and functional characteristics of deep-sea sponges, we propose a bioinspired absorber design that integrates a porous topology with 3D printing. By optimizing the rotation angle and the hollowed array, the absorber establishes multiple internal reflection paths, which, combined with the structural matrix and the graphene conductive coating, enable highly efficient dissipation of electromagnetic energy. Experimental results show that the fabricated sample achieves an absorptivity exceeding 99% over the 0.5–2.0 THz frequency range, while also exhibiting wide-angle absorption and polarization-insensitive performance. The influence of pore size and graphene concentration on the absorption properties is systematically revealed. This work further enhances the performance of 3D-printed terahertz absorbers and provides a novel technical pathway for the design and fabrication of high-performance terahertz absorbers. Full article

Campylobacter jejuni and Campylobacter coli are major foodborne pathogens whose accurate species-level discrimination is important for outbreak investigations as well as rapidly assessing putative antimicrobial resistance profiles and the pathogenic potential of the bacterium. To facilitate species differentiation, a novel assay that integrates the nucleic acid-sensing capability of the oligo-Alpha with the multiplexing capacity of the AlphaPlex bead chemistries was developed. This wash-free system (designated as oligo-Plex) enables the detection and differentiation of C. jejuni and C. coli within a single reaction and can be completed in approximately 75 min. It works by using custom oligonucleotides modified for bead attachment, which hybridize sequentially along Campylobacter’s glyA gene and ultimately bridge the donor and acceptor beads. Improvements in assay stringency were made by increasing incubation temperatures, thus allowing the resolution of target from non-target. Comparisons of FITC–europium and DIG–terbium labeling systems revealed superior performance by the FITC–europium pair and suggested that helical positioning and steric accessibility likely influence donor–acceptor efficiency. Maximized signal separation was seen when using terbium for the detection of C. coli and europium for the detection of C. jejuni. Testing was performed in a Tris-based buffer and milk to confirm matrix tolerance, with potential areas for further optimization identified. The oligo-Plex presented here establishes a streamlined, adaptable platform suitable for high-throughput screening of multiple nucleic acid analytes that is readily extendable to a diverse array of pathogens through appropriate oligo selection. Full article