Search Results (603)

Packed granular materials absorb sound. In previous studies, granular materials sized a few millimeters and samples of grain size as a powder were studied; however, the grain sizes in between have not been addressed. In this study, the sound absorption coefficients of materials ranging from granular materials with a grain size d = 4 mm to powder materials with d = 0.05 mm were analyzed theoretically and experimentally. In addition, five packing types were studied: four types of regular packing and random packing. For these packing structures, the propagation constants and characteristic impedances were substituted within a one-dimensional transfer matrix for sound wave propagation, from which the normal-incidence sound absorption coefficient was calculated. Furthermore, our analysis accounted for particle longitudinal vibrations due to sound pressure. According to analyses of cross-sectional CT images considering tortuosity, the theoretical values for random packing tended to be close to the experimental values for d = 0.8 mm and smaller. For random packing structures with d = 0.3 mm or smaller, the experimental values were closer to the theoretical values for simple cubic lattice than the theoretical values for random packing. Full article

A continuum model for describing pseudo-turbulent flows of a dispersed phase is developed using a statistical approach based on the kinetic equation for the probability density of particle velocity and temperature. The introduction of the probability density function enables a statistical description of the particle ensemble through equations for the first and second moments, replacing the dynamic description of individual particles derived from Langevin-type equations of motion and heat transfer. The lack of detailed dynamic information on individual particle behavior is compensated by a richer statistical characterization of the motion and heat transfer within the particle continuum. A numerical simulation of the unsteady flow of a gas–particle suspension generated by the interaction of a shock wave with a particle cloud is performed using an interpenetrating continua model and equations for the first and second moments of both gas and particles. Numerical methods for solving the two-phase gas dynamics equations—formulated using a two-velocity and two-temperature model—are discussed. Each phase is governed by conservation equations for mass, momentum, and energy, written in a conservative hyperbolic form. These equations are solved using a high-order Godunov-type numerical method, with time discretization performed by a third-order Runge–Kutta scheme. The study analyzes the influence of two-dimensional effects on the formation of shock-wave flow structures and explores the spatial and temporal evolution of particle concentration and other flow parameters. The results enable an estimation of shock wave attenuation by a granular backfill. The extended pressure relaxation region is observed behind the cloud of particles. Full article

In complex process systems, accurate real-time anomaly detection is essential to ensure operational safety and reliability. This study proposes a novel detection method that combines information granulation with kernel principal component analysis (KPCA). Here, information granulation is introduced as a general framework, with the principle of justifiable granularity (PJG) adopted as the specific implementation. Time series data are first granulated using PJG to extract compact features that preserve local dynamics. The KPCA model, equipped with a radial basis function kernel, is then applied to capture nonlinear correlations and construct monitoring statistics including $T^2$ and SPE. Thresholds are derived from training data and used for online anomaly detection. The method is evaluated on the Tennessee Eastman process and Continuous Stirred Tank Reactor datasets, covering various types of faults. Experimental results demonstrate that the proposed method achieves a near-zero false alarm rate below 1% and maintains a missed detection rate under 6%, highlighting its effectiveness and robustness across different fault scenarios and industrial datasets. Full article

This study aims to develop and characterize innovative geopolymer composites by incorporating activated carbon into a geopolymer matrix to create a novel, effective sorption material suitable for non-dusty or medium-temperature environmental applications. Specifically, it examines the impact of using a single source of activated carbon, both in its original granular form and milled form, at two different loading levels for each. The research focuses on evaluating how these variations influence the textural, adsorption, mechanical, and thermal properties of the resulting geopolymer composites, with particular attention to strength and thermal stability under operational conditions. The CO₂ adsorption capacity of the composites measured at 25 °C and pressure up to 0.1 MPa varied from 48.8 to 60.0 mg.g⁻¹, with the highest performance observed at a lower content of the granular form, while commercial pure activated carbon reached 120.8 mg.g⁻¹. However, incorporation of a granular form negatively affected thermal stability (approximately 20 wt.% weight loss) and significantly reduced compressive strength (below 45 MPa) due to increased material inhomogeneity. Despite these limitations, both types of composites show promising potential for environmental applications. However, further optimization is required to balance sorption capacity, strength, and thermal stability. Full article

Smart contracts empower many blockchain applications but are exposed to code-level defects. Existing methods do not scale to the evolving code, do not represent complex control and data flows, and lack granular and calibrated evidence. To address the above concerns, we present an across-graph corresponding contract-graph method for vulnerability detection: abstract syntax, control flow, and data flow are fused into a typed, directed contract-graph whose nodes are enriched with pre-code embeddings (GraphCodeBERT or CodeT5+). A Graph Matching Network (GMN) with cross-graph attention compares contract-graphs, aligns homologous sub-graphs associated with vulnerabilities, and supports the interpretation of statements at the level of balance between a broad structural coverage and a discriminative pairwise alignment. The evaluation follows a deployment-oriented protocol with thresholds fixed for validation, multi-seed averaging, and a conservative estimate of sensitivity under low-false-positive budgets. On SmartBugs Wild, the method consistently and markedly exceeds strong rule-based and learning baselines and maintains a higher sensitivity to matching false-positive rates; ablations track the gains to multi-graph fusion, pre-trained encoders, and cross-graph matching, stable through seeds. Full article

Smaller data environments with expert systems are generally driven by the need for interpretable reasoning frameworks, such as fuzzy rule-based systems (FRBS), which cannot often quantify epistemic uncertainty during decision-making. This study proposes a novel Layered Entropy Model (LEM) comprising three semantic layers: Membership Function Entropy (MFE), Rule Activation Entropy (RAE), and System Output Entropy (SOE). Shannon entropy is applied at each layer to enable granular diagnostic transparency throughout the inference process. The approach was evaluated using both synthetic simulations and a real-world case study on the PIMA Indian Diabetes dataset. In the real data experiment, the system produced sharp, fully confident decisions with zero entropy at all layers, yielding an Epistemic Confidence Index (ECI) of 1.0. The proposed framework maintains full compatibility with conventional Type-1 FRBS design while introducing a computationally efficient and fully interpretable uncertainty quantification capability. The results demonstrate that LEM can serve as a powerful tool for validating expert knowledge, auditing system transparency, and deployment in high-stakes, small-data decision domains, such as healthcare, safety, and finance. The model contributes directly to the goals of explainable artificial intelligence (XAI) by embedding uncertainty traceability within the reasoning process itself. Full article

With the rapid advancement of energy storage technologies, there is a growing demand for affordable, efficient, and environmentally benign battery systems. Sodium-ion batteries (SIBs) present a promising alternative to lithium-ion systems due to sodium’s high abundance and similar electrochemical properties. Particular attention is given to developing NASICON -sodium (Na) super ionic conductor, type cathode materials, especially Na3V2(PO4)3, which exhibits high thermal and structural stability. This study focuses on the sol–gel synthesis of Na₃V₂(PO₄)₃ using citric acid and ethylene glycol, as well as investigating the effect of annealing temperature (400–1000 °C) on its structural and electrochemical properties. Phase composition, morphology, textural characteristics, and electrochemical performance were systematically analyzed. Above 700 °C, a highly crystalline NASICON phase free of secondary impurities was formed, as confirmed by X-ray diffraction (XRD). Microstructural evolution revealed a transition from a loose amorphous structure to a dense granular morphology, accompanied by changes in specific surface area and porosity. The highest surface area (67.40 m²/g) was achieved at 700 °C, while increasing the temperature to 1000 °C caused pore collapse due to sintering. X-ray photoelectron spectroscopy (XPS) confirmed the predominant presence of V³⁺ ions and the formation of V⁴⁺ at the highest temperature. The optimal balance of high crystallinity, uniform elemental distribution, and stable texture was achieved at 900 °C. Electrochemical testing in a Na/NVP half-cell configuration delivered an initial capacity of 70 mAh/g, which decayed to 55 mAh/g by the 100th cycle, attributed to solid-electrolyte interphase (SEI) formation and irreversible Na⁺ trapping. These results demonstrate that the proposed approach yields high-quality Na₃V₂(PO₄)₃ cathode materials with promising potential for sodium-ion battery applications. Full article

Cereal contamination by mycotoxins represents a major food safety concern. This study aimed to assess the co-occurrence of 15 mycotoxins in 50 couscous samples marketed in Algeria using HPLC/FLD and LC-MS/MS techniques. The samples included various couscous types, differing in ingredients, production method (organic or conventional), processing operations, and granularity. The most frequently detected mycotoxins were tentoxin (76%), deoxynivalenol (74%), tenuazonic acid (72%), and ochratoxin A (54%). For the regulated mycotoxins, none of the concentrations exceeded the maximum levels set by the European Union. In contrast, tenuazonic acid and tentoxin, which are not yet regulated, were the most common compounds detected. Contamination with multiple mycotoxins was commonly observed: 90% of the samples contained at least two mycotoxins, with some containing up to seven. The most frequent combination involved tenuazonic acid-tentoxin-ochratoxin A. These findings highlight the need for frequent and systematic monitoring of couscous and other processed cereal-based products. Full article

The ultrastructural organization of different cell types involved in homeostatic growth in the cerebellum of juvenile chum salmon (Oncorhynchus keta) was investigated using transmission and scanning electron microscopy. The organization of astrocytes, oligodendrocytes, dark cells, adult-type glial and non-glial progenitors, stellate neurons, and eurydendroid cells (EDCs) in the molecular and granular layers and granular eminences was characterized. The organization of dendritic bouquets of Purkinje cells and climbing fibers was studied for the first time at the ultrastructural level, and the ultrastructural features of mossy fibers and the rosettes they form were characterized. Scanning electron microscopy (SEM) revealed the presence of single and paired adult-type neural stem/progenitor cells (aNSPCs) on the cerebellar surface and stromal clusters of aNSPCs outside the dorsal matrix zone (DMZ). Immunohistochemical (IHC) verification of proliferating cell nuclear antigen (PCNA) revealed five types of proliferating cells in the cerebellum of juvenile chum salmon: neuroepithelial cells (NECs), glial aNSPCs, and non-glial aNSPCs. A glial fibrillary acidic protein-positive (GFAP) complex consisting of radial glial fibers and aNSPCs was detected in the DMZ. At the same time, a complex of GFAP+ cerebellar afferents, consisting of differentiating mossy and climbing fibers, was found to develop in the cerebellum of juvenile chum salmon. Nestin+ non-glial aNSPCs and small nestin+ resident cells were detected in the dorsal, lateral, and basal areas, as well as in the granular layer (GrL) and granular eminences (GrEm). These cell types may contribute to the homeostatic growth of the cerebellum by acting as both active participants (PCNA+) and resident (silent) aNSPCs. Studying vimentin-positive systems in the cerebellum revealed a widespread presence of proliferating glial aNSPCs that actively contribute to homeostatic growth, as well as small resident immunopositive cells throughout the cerebellum of juvenile chum salmon. Immunolocalization of the neuronal RNA-binding protein marker (HuCD) was detected in numerous molecular layer (ML) cells at the early stages of neuronal differentiation in the dorsal and lateral regions of the cerebellum of juvenile chum salmon. HuCD + EDCs were detected for the first time in the dorsal (DZ) and basal (BZ) zones, forming broad axonal arborization. Immunolabeling of HuCD in combination with transmission electron microscopy (TEM) allowed EDCs to be characterized in the cerebellum of juvenile chum salmon for the first time. Full article

The presence of toxic elements in drinking water poses important risks to human health. Among the diverse methodologies available to remove these elements from water, adsorption methods are among the most effective; however, many adsorbent materials are either costly, not widely available, or difficult to handle. This work focuses on the application of a new natural geologic material, named “V” material, to prepare an adsorbent substrate applied to water treatment, using its adsorption properties to remove metallic species from aqueous media. The geologic material is a thermally and mechanically resistant material, composed basically of quartz, iron and aluminum oxides, with amphoteric properties. A granular medium or substrate was prepared via thermal treatment using three granulometric fractions of the material: the smaller fraction, less than 250 μm, named the fine fraction, VFF; from 250 μm to 425 μm, named the medium fraction, VMF; and from 425 μm to 1200 μm, named the gross fraction, VGF. The experiments were carried out on both alkaline-treated and non-treated substrates, named activated and non-activated substrates, respectively. The BET and external surface, as well as the pore volume, increased significantly after the calcination process. The adsorption isotherms pointed to a strong interaction between metallic ions and activated substrates, in contrast to the non-activated substrate, which showed much less affinity. This type of isotherm is associated with specific adsorption, where the adsorption occurs chemically between Cu²⁺ ions and the substrate surface, basically composed of amphoteric metallic oxides. The adsorption data fit fairly well to the Freundlich and Langmuir models, where the K values are higher for activated substrates. According to the Freundlich K values, the copper adsorptions on the activated substrates were higher: 5.0395, 3.9814 and 4.2165 mg/g, compared with 0.3622, 1.8843 and 0.4544 mg/g on non-activated substrates. The pH measurements showed the production of 0.56 and 0.10 μmol H⁺ during the adsorption reaction on the activated substrate, following the theoretical model for the chemisorption of transitional metals on amphoteric oxides. These results show the potential applicability of this kind of substrate in retaining transitional metals from polluted drinkable water at low cost. It is environmentally friendly, non-toxic, and available for rural media and mining-impacted regions. Full article

Addressing the inefficiency, subjective errors, and limited adaptability of existing methods for surveying complex ancient structures, this study presents an intelligent hierarchical algorithm for generating line drawings guided by structured architectural features. Leveraging point cloud data, our approach integrates prior semantic and structural knowledge of ancient buildings to establish a multi-granularity feature extraction framework encompassing local geometric features (normal vectors, curvature, Simplified Point Feature Histograms-SPFH), component-level semantic features (utilizing enhanced PointNet++ segmentation and geometric graph matching for specialized elements), and structural relationships (adjacency analysis, hierarchical support inference). This framework autonomously achieves intelligent layer assignment, line type/width selection based on component semantics, vectorization optimization via orthogonal and hierarchical topological constraints, and the intelligent generation of sectional views and symbolic annotations. We implemented an algorithmic toolchain using the AutoCAD Python API (pyautocad version 0.5.0) within the AutoCAD 2023 environment. Validation on point cloud datasets from two representative ancient structures—Guanchang No. 11 (Luoyuan County, Fujian) and Li Tianda’s Residence (Langxi County, Anhui)—demonstrates the method’s effectiveness in accurately identifying key components (e.g., columns, beams, Dougong brackets), generating engineering-standard line drawings with significantly enhanced efficiency over traditional approaches, and robustly handling complex architectural geometries. This research delivers an efficient, reliable, and intelligent solution for digital preservation, restoration design, and information archiving of ancient architectural heritage. Full article

This paper demonstrates the comprehensive research of the target Middle Eastern carbonate oilfield on waterflooding technologies, including geological characteristics, integrated research, and principal development techniques. Geological research reveals that the Mishrif Formation in the B Oilfield is a gentle-sloping carbonate platform, with granular limestone serving as the primary reservoir rock and micrite limestone serving as the secondary reservoir rock. In addition, based on understandings drawn from geological characteristics and numerical simulation, the water flooding mode of IBPT, which can take full use of the gravity effect, has been proven to yield better sweep efficiency in the context of a thick and heterogeneous reservoir. Furthermore, a large-scale physical model experiment is designed to investigate the fluid migration between the producer and injector and indicates that the injected water migration is mainly divided into four phases, including a two-peak advance phase, a gravitational differentiation phase, a secondary bottom water phase, and a wellbore water coning phase. Subsequently, the principal techniques and corresponding optimized production responses of water flooding development are systematically illustrated, which consist of well type optimization, differentiated water injection strategies, injection pattern conversion, unstable water injection, selective well perforation, as well as tracer surveillance methodology. The outcomes of this study are directly derived from field performances and could provide concrete practical experiences for water flooding technology in the Middle East. Full article

This paper introduces a novel ratio-based framework for analyzing how consumer heterogeneity translates into product differentiation in vertically structured monopoly markets. We consider a monopolist facing a continuum of consumers and a strictly convex production cost function and identify conditions under which the heterogeneity of preferences, measured by the length of the consumer type interval, maps into a corresponding range of offered qualities. The analysis shows that this mapping depends on the curvature of the marginal cost function: under linear costs, the relationship is proportional; under convex costs, heterogeneity expands faster than segmentation; and under concave costs, the reverse occurs. These findings offer a new lens for understanding endogenous market granularity in monopoly settings and have potential applicability in markets with vertically differentiated goods. We also show that under partial market coverage, this proportionality breaks down - even in the linear case - revealing a critical asymmetry in equilibrium structure. Full article

The volumetric Hirst method is considered a golden standard in aerobiology for determining particle number concentrations of bioaerosols. Using Hirst-type pollen and spore traps on mobile platforms (i.e., aircraft, cars, motorbikes, bicycles or carried by pedestrians) is anticipated to significantly enhance the spatial and temporal granularity of data for bioaerosol monitoring. Mobile sampling promises to enhance our understanding of bioaerosol dynamics, ecological interactions and the impact of human activities on airborne biological particles. In this article, we present the design and test of an airborne Hirst-type volumetric sampler. We followed a structured approach and incorporated the fundamental principles of the original design, while optimizing for size, weight, power and cost. Our portable Hirst-type volumetric sampler (FlyHirst) was attached to an ultralight aircraft, together with complementing instrumentation, and was tested for collection of atmospheric concentrations of pollen, fungal spores and hyphae. By linking the temporal resolution of the samples with the spatial position of the aircraft, using flight time, we calculated the spatial resolution of our measurements in 3D. In six summer flights over Denmark, our study revealed that the diversity of the recorded spores corresponded to the seasonal expectance. Urtica pollen was recorded up to 1300 m above ground (a.g.l.), and fungal spores up to 2100 m a.g.l. We suggest that, based on this proof-of-concept, FlyHirst can be applied on other mobile platforms or as a personal sampler. Full article

Lupus nephritis (LN) is a serious complication of systemic lupus erythematosus that is associated with long-term morbidity and mortality. Pathomorphological findings of LN are broadly divided into proliferative lupus nephritis (PLN) and membranous lupus nephritis (MLN). PLN is characterized by diffuse global or segmental proliferative glomerulonephritis with significant infiltration of inflammatory cells. Type 1 T-helper (Th1) cells, which predominate under inflammatory conditions, and NETosis, as the process of forming neutrophil extracellular traps (NETs), are key factors in the development of PLN. Meanwhile, MLN is characterized by diffuse membranous nephropathy (MN) with global granular subepithelial immune deposits. MLN patients usually experience massive proteinuria, and occasionally show an unfavorable renal prognosis despite aggressive treatment, similar to PLN patients. Intriguingly, in some instances, MLN patients do not show the general immunoserological characteristics of SLE, such as low serum complement and elevated anti-DNA antibody titers. Several reports have indicated an association between Th2 cell dominance and the development of MLN. Moreover, exostosin 1 (EXT1) and exostosin 2 (EXT2) on the glomerular basement membrane have recently been discovered as novel putative antigens for secondary MN, and have been shown to be up-regulated in patients with MLN. To date, many studies have focused on the dissimilarities between PLN and MLN. However, the reason for two polar morphological forms existing within the same disease is not completely clear. The present review addresses published observations on this topic in addition to providing our assertion regarding characteristic NETosis and glomerular EXT1/EXT2 expressions between PLN and MLN. Full article