Search Results (35)

The rapid expansion of high-protein dairy-based powders (HPDPs), including milk protein concentrates and isolates (MPC/MPI), whey protein concentrates and isolates (WPC/WPI), and micellar casein concentrates and isolates (MCC/MCI), has intensified the need to understand instability phenomena that emerge during processing and storage. These products are governed by protein-rich amorphous matrices, in which molecular mobility, interfacial composition, and mineral interactions dictate both physical stability and functional performance. Importantly, these physical instabilities are directly coupled with functional deterioration, particularly in terms of impaired wetting, dispersion, and dissolution during rehydration. This review presents an integrated mechanistic framework linking these instability phenomena across processing, storage, and reconstitution, thereby consolidating concepts that remain fragmented across the current literature on high-protein dairy matrices. Key controlling factors include glass transition temperature (Tg), water activity-induced plasticization, protein–protein and protein–mineral interactions, and surface compositional heterogeneity established during spray drying. These factors govern the progression from surface stickiness through uncontrolled agglomeration to caking, forming a consolidation continuum. In contrast to lactose-driven matrices, caking and agglomeration in HPDPs arise primarily from protein-mediated restructuring and inter-particle bonding, with lactose crystallization acting only as a secondary mechanism in mixed-composition grades. The review further distinguishes engineered agglomeration from storage-induced consolidation and evaluates advances in molecular mobility characterization and Tg-based stability mapping. Significant gaps remain in linking localized surface evolution, mineral redistribution, and inter-particle bridge chemistry under realistic environmental conditions. The review concludes by proposing a mobility-centered “stability-by-design” framework that integrates composition, processing, particle architecture, and storage conditions to guide the development of future HPDPs with improved physical stability and functional recovery. Full article

Intelligent caving mining requires not only equipment automation, but also the coordinated regulation of production timing, spatial structure, ore output, ore-flow quality, and energy consumption across the mining-processing chain. In caving mines, the state of broken ore flow, drawpoint activation, fragmentation distribution, dilution, ore loss, and ore-waste mixing affects not only underground production stability, but also downstream mineral processing performance, including feed-grade stability, particle-size distribution, pre-concentration potential, and the energy consumption of crushing, grinding, and separation. However, existing studies remain fragmented, with insufficient integration among production scheduling, spatial configuration, ore-flow and ore-output control, mineral-processing-oriented feed quality, and energy efficiency. To address this gap, this review systematically examines the time-space-quantity-energy collaborative feedback framework for intelligent caving mines. The four dimensions are defined as production timing, structural space, ore output and ore-flow quality and energy-consumption constraints, respectively. Recent advances are summarized in production rhythm analysis, spatial modeling, ore-flow and ore-output characterization, fragmentation recognition, energy monitoring and evaluation, digital-twin support, and intelligent control methods. On this basis, this review further reveals the coupling mechanisms by which time organization shapes spatial utilization, spatial structures constrain ore output and ore-flow quality, ore-output and ore-quality fluctuations affect energy-consumption evolution, and energy feedback reshapes production scheduling and spatial allocation. Key challenges are identified in multi-source data integration, mechanism modeling, evaluation methodology, and closed-loop execution. Future research directions are proposed toward digital twin-enabled, data-driven, mineral-processing-oriented, and human-machine collaborative regulation. Compared with existing reviews that discuss intelligent mining technologies, digital-twin architectures, ore-flow control, or underground production planning separately, this review clarifies their shared regulatory logic within a time-space-quantity-energy coupling framework oriented toward mining and processing. Overall, the unified time-space-quantity-energy framework provides a theoretical basis for transforming caving mines from isolated underground production optimization toward intelligent, efficient, low-energy, and mineral-processing-responsive collaborative operation. Full article

Heap bioleaching is widely used to extract copper from low-grade sulfide ores thanks to its operational simplicity, low cost, and environmental sustainability. However, current control strategies rely primarily on single-factor optimization and often overlook the synergistic interactions of multiple key parameters, such as ore particle size, pore structure, pH, temperature, microbial activity, and oxygen transfer efficiency. As a result, issues such as low recovery rates, extended leaching periods, and high operational costs persist. Moreover, the “gray-box” nature of heap systems impedes real-time monitoring of internal physical, chemical, and biological processes. In addition, empirical multi-parameter optimization is time-consuming and inadequate for capturing complex interdependencies. This review was conducted to systematically examine the key factors influencing heap bioleaching efficiency and critically evaluate recent advances in numerical simulation and intelligent control strategies. As a result, we identified a major research gap: the existing models—including microscale shrinking core models (SCMs), mesoscale pore-network models based on CT reconstruction, and macroscale continuum models—have inherent limitations. SCMs assume idealized spherical particles with uniform mineral distribution while neglecting pore structure evolution and biofilm dynamics. Mesoscale models offer detailed pore characterization but lack robust multi-physics coupling (thermal–hydro–mechanical–chemical–biological, or THMCB). Macroscale models rely on homogenization assumptions that oversimplify spatial heterogeneity and temporal variations in permeability. This analysis covers the relevant literature from 1985 to 2025, with a focus on three methodological scales (micro, meso, and macro) and their integration with machine learning approaches. A notable finding is that hybrid neural network models (e.g., BP and RBF architectures) outperform purely physics-based models in predicting leaching kinetics under varying operational conditions. However, their accuracy depends heavily on high-quality field data—a limitation rarely addressed in prior reviews. By clearly delineating these model-specific limitations and scale-dependent trade-offs, this review makes two unique contributions: a structured framework for selecting and coupling numerical methods according to process requirements and a roadmap for integrating artificial neural networks with multi-physics simulations to achieve real-time intelligent control of heap bioleaching. The findings offer both theoretical guidance and practical references for optimizing the processing of low-grade copper sulfide ores. Full article

To investigate the mechanical characteristics of gravel-block soils in the cold regions, four large direct shear tests were designed under different coarse particle contents and three dry density conditions. The stress variations during shearing and the particle fragmentation rate after shearing were measured. The experimental results indicate that when p₅ (the proportion of particles larger than 5 mm) ≥ 40%, the samples exhibit strain hardening behavior, and the stress–strain curve does not exhibit a peak within the range of the tests. The rock fragment skeleton exhibits excellent deformation resistance. With increasing coarse particle content, the internal friction angle of the soil initially decreases and then increases, while the cohesion initially decreases and then increases. Moreover, with increasing initial dry density, both the cohesion and internal friction angle of the gravel-block soils gradually increase. The fractal dimension increases with the increase in the particle fragmentation rate, indicating that the fractal dimension can also represent the degree of particle fragmentation in the soil. The relative fractal dimension increases exponentially with the increase in coarse particle content, indicating that the coarse particle content has a significant impact on the degree of particle fragmentation of gravel-block soils. The higher the coarse particle content, the greater the degree of particle fragmentation of gravel-block soils. When the coarse particle content increases from 0% to 60%, the fractal dimension decreases from 2.825 to 2.555, and the shear strength of the gravel-block soils continuously improves. During the shear process, the gravel-block soils transition from poor grading to well grading, with coarse particles breaking and fine particles filling the gaps between the coarse particles, resulting in a reduction in soil porosity and an increase in particle fragmentation rate and fractal dimension. The research outcomes of this experimental study provide guidance for the study of debris-covered slope landslides in cold regions. Full article

Micro- and nanoplastics (MNPs) have now been detected in human blood, placenta, and arterial tissue, yet the oral cavity has received strikingly little mechanistic attention despite serving as a primary portal of environmental exposure and a local site of polymer generation from dental and oral-care materials. This narrative review addresses that gap from an environmental microbiology perspective, synthesizing recent literature on periodontal disease, chronic low-grade inflammation, oral biofilms, dental materials, microbial–plastic interactions, and systemic chronic disease risk. Unlike prior reviews, we apply an explicit three-tier evidentiary framework (established, plausible, unproven) that distinguishes what is directly demonstrated from what is biologically plausible but unproven, and we situate the periodontal environment specifically as a particle-retention and inflammatory-amplification niche. The strongest direct oral evidence shows that human dental calculus harbors at least 26 microplastic types, dominated by polyamide (41.4%), polyethylene (32.7%), and polyurethane (7.0%). Polyethylene isolated from calculus induces cytotoxicity, apoptosis, impaired migration, NF-κB activation, and upregulation of IL-1β and IL-6 in human gingival fibroblasts. From a microbiological standpoint, oral organisms actively degrade methacrylate dental polymers, and the degradation products of these polymers reciprocally modulate oral bacterial virulence gene expression. Across experimental systems, MNPs activate oxidative stress, inflammasome signaling, macrophage polarization, and barrier dysfunction, pathways that overlap extensively with periodontal pathobiology. Adjacent environmental microbiology demonstrates that plastic-associated biofilms enhance extracellular polymeric substance production, quorum sensing, pathogen persistence, and antibiotic resistance gene transfer, supporting a plausible but not yet validated oral plastisphere within plaque and calculus. We argue that periodontitis should be reconceptualized as a chronically inflamed particle-processing interface that may increase local MNP retention, cellular reactivity, and systemic inflammatory spillover, with implications for cardiovascular, metabolic, and other chronic disease risk pathways. Current evidence does not yet prove that environmental MNP exposure causes human periodontitis, and that evidentiary boundary is maintained throughout. A priority research agenda is proposed, centered on contamination-controlled subgingival biomonitoring stratified by periodontal status, spatially resolved multi-species biofilm models, polymer source attribution, and longitudinal clinical studies linking oral plastic burden to inflammatory and systemic outcomes. Full article

This study introduces a systematic and optimised methodology for designing Linear Variable Differential Transformer (LVDT) sensors and Voice Coil (VC) actuators, tailored for high-precision applications such as gravitational wave detectors and particle accelerators. Unlike prior studies, which focus primarily on industrial-grade LVDT design frameworks or isolated parameter studies, this work addresses the specific challenges of achieving both enhanced sensor response and actuation force within strict geometric and thermal constraints. Using a custom-developed simulation pipeline based on Finite Element Method Magnetics (FEMM), we evaluate the influence of key design parameters such as coil dimensions, radial gaps, and coil wire diameter on performance metrics such as response and linearity. The novelty of this work lies in its systematic exploration of design trade-offs, such as maximising performance while minimising heat dissipation, and its applicability to high-precision environments. In this work, particular emphasis is placed on the combination of the LVDT and VC functionalities in one unified sensor-and-actuator system designed for gravitational wave detectors. In addition, the methodology and simulation results are validated with experimental measurements of an optimised design, demonstrating a 2.8-fold increase in LVDT response and a 2.5-fold increase in VC actuation force compared to the initial configuration while preserving LVDT linearity and VC force stability. This work represents a significant advance over existing methodologies by offering a structured, scalable design process. Full article

Historically, the toxicological evaluation of poorly soluble low toxicity particles (PSLTs), such as titanium dioxide nanoparticles (TiO₂ NPs), distinct from conventional pigment-grade TiO₂, has focused on carcinogenicity and lung overload, leaving their pathological function in the development of pneumoconiosis undefined. In this study, we initiated a “Pneumoconiosis Renaissance”, redefining the human “Gold Standard” of pneumoconiosis pathology as a primarily interstitial “Dust Macule (DM) to Mixed Dust Fibrosis (MDF) axis”. In contrast, rats developed a species-specific “Airspace-Dominant Phenotype” (Pulmonary Dust Foci) driven by airspace stagnation. Integrating recent continuous inhalation exposure and recovery after inhalation exposure studies, we demonstrate that this overwhelming alveolar pathology in rats acts as a “Biological Mask”, physically superimposing upon and obscuring human-relevant interstitial sequestration. Crucially, however, extended recovery periods can unmask these interstitial events, revealing the true underlying pathology. We propose that future risk assessments and Adverse Outcome Pathways (AOPs) must incorporate spatial resolution. By rigorously segregating sensitive rat-specific airspace events from human-relevant interstitial remodeling, we can accurately bridge the interspecies gap. This review argues that rather than discarding the rat model, we must learn to decode it—using spatial distinctions to filter the airspace mask and evaluate the true interstitial risk of inhaled biodurable particles. Full article

Seepage-induced internal erosion occurs when the hydraulic forces are sufficient to detach fine particles and transport them out of the structure, leading to notable changes in soil characteristics such as particle size distribution, pore size distribution, and pore structure, which will, in turn, have significant influences on the mechanical properties of soil. In this study, three approaches were utilized to model the erosion-induced loss of fine particles, i.e., deleting fine particles randomly (RM), by contact force (CF), and by coordination number (CN) using the discrete element method (DEM). The impact of each fine particle removal mode on both micro- and macro-mechanical soil properties, including peak strength, dilation, critical state characteristics, average particle coordination number, and contact force distribution, is comprehensively analyzed and compared. The results demonstrate that residual strength was insensitive to removal method, whereas at 10% fines loss, peak strength decreased by up to 17% and the secant stiffness E₅₀ decreased by nearly 48%. This work provides a foundation for simulating the internal erosion of gap-graded soils. Full article

Background and objectives: Antibiotic resistance in Cutibacterium acnes is undermining topical macrolides and clindamycin, prompting renewed interest in zinc oxide nanoparticles (ZnO-NPs) as non-antibiotic alternatives. We aimed to (i) determine the antimicrobial and anti-inflammatory performance of topical ZnO-NP formulations across in vitro, animal and early human models; (ii) identify physicochemical parameters that modulate potency and tolerance; and (iii) delineate translational gaps and priority design elements for randomised trials. Methods: We systematically searched PubMed, Scopus and Web of Science until 1 June 2025 for in vitro, animal and human studies that evaluated ≤100 nm ZnO-NPs applied topically to C. acnes cultures, extracting data on bacterial load, lesion counts, biophysical skin parameters and acute toxicity. Eight eligible investigations (five in vitro, two animal, one exploratory human) analysed particles 20–50 nm in diameter carrying mildly anionic zeta potentials. Results: Hyaluronic acid-coated ZnO-NPs achieved a sixteen-fold higher selective kill ratio over Staphylococcus epidermidis at 32 µg mL¹, while centrifugally spun polyvinyl alcohol dressings reduced C. acnes burden by 3.1 log₁₀ on porcine skin within 24 h, and plant-derived nanogels generated inhibition zones that were 11% wider than benzoyl-peroxide’s 5%. In human subjects, twice-daily 0.5% hyaluronic–ZnO nanogel cut inflammatory-lesion counts by 58% at week four and lowered transepidermal water loss without erythema. Preclinical safety was reassuring, zero mortality among animals at 100 µg mL¹ and no irritation among patients, although high-dose sunscreen-grade ZnO (20 nm) delayed rat wound closure by 38%, highlighting dose-dependent differences. Conclusions: Collectively, the evidence indicates that nanoscale reformulation markedly augments zinc’s antibacterial and anti-inflammatory performance while maintaining favourable acute tolerance, supporting progression to rigorously designed, adequately powered randomised trials that will benchmark ZnO-NPs against benzoyl peroxide and retinoids, optimise dosing for efficacy versus phototoxicity, and establish long-term dermatological safety. Full article

Seepage erosion around sheet pile walls represents a critical failure mechanism in geotechnical engineering, yet the underlying mechanisms governing the onset of erosion remain poorly understood. This study presents a comprehensive multi-scale investigation employing a coupled computational fluid dynamics (CFD)-discrete element method (DEM) to elucidate the onset mechanisms of seepage erosion in gap-graded soils with varying the fines content under different hydraulic gradients. The results demonstrate that increasing the fines content enhances the overall erosion resistance, as evidenced by reduced particle mobilization and eroded mass ratio. Particle tracking analysis reveals that the fines content fundamentally influences the spatial distribution of the erosion. Specimens with low fines content exhibit distributed erosion throughout the domain, while specimens with higher fines content show concentrated erosion around the sheet pile wall and downstream regions. Micromechanical analysis of local contact fabric and contact forces indicates that this spatial heterogeneity stems from the mechanical coordination number and mechanical redundancy, characterized by the reduced magnitudes of these parameters for the region with lower erosion resistance. These findings establish that the fines content governs both global erosion resistance and spatial erosion patterns, providing essential insights for optimizing soil gradation design and advancing fundamental understanding of seepage erosion mechanisms. Full article

Synchronous grouting slurry is widely used in shield tunnel construction to fill the gaps between stratum and shield tail segments. However, as grout is nearly liquid in the initial stages, the tunnel lining segments recently separated from the shield tail are easily affected by the upward buoyancy generated by grout, causing issues such as longitudinal misalignment and opening of ring joints. Therefore, studying the upward buoyancy characteristics of synchronous grout is crucial. In this study, floating characterisation parameters of grout were investigated using buoyancy model tests, orthogonal tests, and comprehensive tests. The floating characterisation parameters are affected by distribution ratio and types of each grout component. The relationship between the floating characterisation parameters of grout and buoyancy was established. The results show that density, flow index, and shear strength can be used as the floating characterisation parameters. Binder–sand and water–binder ratios have the largest impact on the density. The bentonite–water ratio exerts a primary influence on the flow index, while the water–binder ratio contributes a secondary effect. In addition, bentonite–water and binder–sand ratios have the greatest effect on the shear strength. Furthermore, the particle size of sand and type of bentonite considerably influence the flow index and shear strength. A high-shear grout using well-graded fine sand and a high mesh of sodium bentonite was considered in this study. When the content of bentonite exceeds 7% (P2.2), Archimedes’ law is not applicable for calculating the upward buoyancy of grout. Buoyancy supply rate exhibits gradual enhancement with flow index elevation, yet with diminishing growth rates. Full article

Cyclic hydraulic loading frequently affects embankment dams during reservoir regulation, tidal fluctuations, and intense rainfall. It potentially worsens fine particle migration during internal erosion and increases dam failure risks. This study is the first to systematically explore the influence of cyclic hydraulic loading on the critical hydraulic gradient (i_cr) of gap-graded soils, providing new insights into suffusion behavior. Transparent soil experiments, which enable direct observation of soil structural evolution, are combined with coupled DEM–Darcy simulations that offer microscopic mechanical insights, marking the first integrated use of these two approaches to investigate suffusion behavior. To quantify fine particle migration, we propose a novel modified grayscale threshold segmentation (MGTS) method for analyzing cross-sectional images captured during transparent soil experiments. The results from both methods show consistency in fine particle migration, clogging formation, and failure, with differences in permeability and i_cr remaining within acceptable limits. Fine particle content significantly influences the post-cyclic i_cr of internally unstable soils. For soils with lower fine particle content (15%), i_cr increases after cyclic hydraulic loading and rises with the mean hydraulic gradient during cycling. Conversely, soils with higher fine particle content (20%) exhibit a decrease in post-cyclic i_cr. This behavior is explained by changes in the average contact force between fine particles (F_ff) observed in DEM simulations. Full article

The accurate modeling of dynamic soil–structure interaction processes under impact loading is critical for advancing the design of soil-embedded barrier systems. Full-scale crash testing remains the benchmark for evaluating barrier performance; however, such tests are costly, logistically demanding, and subject to variability that limits repeatability. Recent advancements in computational methods, particularly the development of large-deformation numerical schemes, such as the multi-material arbitrary Lagrangian–Eulerian (MM-ALE) and smoothed particle hydrodynamics (SPH) approaches, offer viable alternatives for simulating soil behavior under impact loading. These methods have enabled a more realistic representation of granular soil dynamics, particularly that of the Manual for Assessing Safety Hardware (MASH) strong soil, a well-graded gravelly soil commonly used in crash testing of soil-embedded barriers and safety features. This soil exhibits complex mechanical responses governed by inter-particle friction, dilatancy, confining pressure, and moisture content. Nonetheless, the predictive fidelity of these simulations is governed by the selection and implementation of soil constitutive models, which must capture the nonlinear, dilatant, and pressure-sensitive behavior of granular materials under high strain rate loading. This review critically examines the theoretical foundations and practical applications of a range of soil constitutive models embedded in the LS-DYNA hydrocode, including elastic, elastoplastic, elasto-viscoplastic, and multi-yield surface formulations. Emphasis is placed on the unique behaviors of MASH strong soil, such as confining-pressure dependence, limited elastic range, and strong dilatancy, which must be accurately represented to model the soil’s transition between solid-like and fluid-like states during impact loading. This paper addresses existing gaps in the literature by offering a structured basis for selecting and evaluating constitutive models in simulations of high-energy vehicular impact events involving soil–structure systems. This framework supports researchers working to improve the numerical analysis of impact-induced responses in soil-embedded structural systems. Full article

Concrete-like composites are widely used in the building of civil engineering applications such as houses, dams, and roads. Mesoscale modeling is a powerful tool for the physical and mechanical analysis of concrete-like composites. A novel discrete element method (DEM)-enhanced external force-free method for multi-phase concrete-like composite modeling with an interface transition zone (ITZ) is presented in this paper. Firstly, randomly distributed particles with arbitrary shapes are generated based on a grading curve. Then, a Minkowski sum operation for particles is implemented to control the minimum gap between adjacent particles. Secondly, a transition from particles to clumps is realized using the overlapping discrete element cluster (ODEC) method and is randomly placed into a specific space. Thirdly, the DEM simulation with a simple linear contact model is employed to separate the overlapped clumps. Meanwhile, the initial position, displacement, and rotation of clumps are recorded. Finally, the mesoscale model is reconstructed based on the displacement and rotation information. The results show that this method can efficiently generate multi-phase composites with arbitrary particle shapes, high volume fractions, an overlapped ITZ, and a periodic structure. This study proposes a novel, efficient tool for analyzing and designing composite materials in resilient civil infrastructure. Full article

Crumb rubber (CR) obtained from end-of-life tyres (ELT) has gained significant attention in the sustainable design of asphalt pavements in recent years, showing a promising perspective in the enhancement of pavement performance related to its structural and functional properties. Existing research on CR influence on pavement performance mostly focused on peculiarities of asphalt mixture modification procedures—dry and wet processes, CR content in the mixture and CR particle size. In this study, a laboratory-based experimental investigation of CR effect on two different mixture gradations, namely dense-graded and gap-graded mixtures with three different binder contents, was performed. CR was added in mixtures through binder modification, with a constant CR content of 18% by binder weight in all mixtures. Volumetric properties—maximum mixture density, bulk density and void characteristics, alongside mechanical properties determined by the Marshall test method—were determined on unmodified and modified mixtures. The goal was to evaluate the influence of CR modification with respect to three different binder contents. The results showed that gap-graded mixtures are more sensitive to change in CR modified binder content in comparison to dense-graded mixtures in terms of air voids content. Furthermore, the mechanical properties of CR-modified mixtures were slightly enhanced in gap-graded mixtures, showing a promising potential of CR modification for pavement performance. However, the choice of optimal binder content in CR-modified mixtures was shown to be a critical mixture design parameter due to the increased sensitivity of binder content change to the analysed voids properties and permanent deformations. Full article