Search Results (11,141)

To date, the grinding behavior of saprolite and lateritic overburden mixtures remains poorly understood. The Bond Work Index (BWI) is the principal indicator used to determine the specific energy consumption during the grinding process. To establish the F₈₀ and P₈₀ values, granulometric distribution models—Rosin–Rammler (RR), Gates–Gaudin–Schuhmann (GGS), and the Swebrec function (SWEF)—were evaluated. The mineral phases of the feed samples were analyzed by X-ray powder diffraction. This study provides evidence that the RR function is the most suitable for simulating the particle size distribution of the feed material, with residual errors below 6.30% and a coefficient of determination (R²) exceeding 97%. After the grinding equilibrium cycle is reached, the SWEF model proves to be the most appropriate, exhibiting residual errors under 3.50% and R² values above 98%. BWI reveals that saprolite is the most difficult ore to grind, with specific energy consumption increasing from 16.38 kWh/t to 25.50 kWh/t as the proportion of saprolite in the mixture rises. This reflects a clear upward trend, as confirmed by a fitted model with an R² of 98.54%. In contrast, the grindability index (Gbp) decreases, indicating that the material becomes increasingly resistant to grinding as the saprolite content increases. This may be attributed to inherent material properties, such as hardness, or to physical phenomena related to fragmentation. The declining Gbp further suggests that greater energy input is required to achieve additional particle size reduction. Overall, the findings demonstrate that saprolite is inherently difficult to grind and behaves according to its own grinding characteristics, regardless of whether it is processed alone or in combination with lateritic overburden. Full article

This paper presents an automatic system for the classification of musical instruments from audio recordings. The project leverages deep learning (DL) techniques to achieve its objective, exploring three different classification approaches based on distinct input representations. The first method involves the extraction of Mel-Frequency Cepstral Coefficients (MFCCs) from the audio files, which are then fed into a two-dimensional convolutional neural network (Conv2D). The second approach makes use of mel-spectrogram images as input to a similar Conv2D architecture. The third approach employs conventional machine learning (ML) classifiers, including Logistic Regression, K-Nearest Neighbors, and Random Forest, trained on MFCC-derived feature vectors. To gain insight into the behavior of the DL model, explainability techniques were applied to the Conv2D model using mel-spectrograms, allowing for a better understanding of how the network interprets relevant features for classification. Additionally, t-distributed stochastic neighbor embedding (t-SNE) was employed on the MFCC vectors to visualize how instrument classes are organized in the feature space. One of the main challenges encountered was the class imbalance within the dataset, which was addressed by assigning class-specific weights during training. The results, in terms of classification accuracy, were very satisfactory across all approaches, with the convolutional models and Random Forest achieving around 97–98%, and Logistic Regression yielding slightly lower performance. In conclusion, the proposed methods proved effective for the selected dataset, and future work may focus on further improving class balance techniques. Full article

This paper investigates the mechanical behavior of PBL shear connectors in UHPC during the elastic stage, utilizing push-out experiments and numerical simulation. This study simplifies the mechanical behavior of PBL shear connectors in UHPC under normal service conditions as a plane strain problem for the UHPC dowel and a Winkler’s Elastic foundation beam theory for the transverse reinforcement. The UHPC dowel is a thick-walled cylindrical shell subjected to non-axisymmetric loads inside and outside simultaneously in the plane-strain state. The stress solution is derived by assuming the contact stress distribution function and using the Airy stress function. The displacement solution is subsequently determined from the stresses by differentiating between elastic and rigid body displacements. By modeling the transverse reinforcement as an infinitely long elastic foundation beam, its displacement solution and stress solution are obtained. We obtain the load–slip curve calculation method by superimposing the displacement of UHPC with the transverse reinforcement in the direction of shear action. The proposed analytical solutions for stress and slip, as well as the method for calculating load–slip, are shown to be reliable by comparing them to the numerical simulation analysis results. Full article

The fashion industry, despite its global economic importance, is a major contributor to environmental degradation and social inequality. In response, sustainable fashion has emerged as a growing movement advocating ethical, ecological, and socially responsible practices. This study presents a comprehensive bibliometric analysis of 1134 peer-reviewed journal articles on sustainable fashion indexed in Scopus from 1986 to 2025. Results show an exponential rise in research output after 2015, with interdisciplinary contributions from social sciences, business, environmental science, and engineering. By applying performance analysis and science mapping techniques, the study identifies five major research themes: “Consumer Behavior,” “Design Ethics,” “Circular Economy,” “Innovation,” and “Digital Media.” The geographic distribution reveals strong outputs from both developed and emerging economies. This study provides an integrative overview of the intellectual landscape of sustainable fashion and serves as a roadmap for researchers, policymakers, and practitioners who are interested in the development of sustainable fashion. Full article

Meissner’s corpuscles are essential mechanoreceptors that detect low-frequency vibrations. However, the internal fluid dynamic processes that convert directional mechanical stimuli into neural signals are not yet fully understood. This study aims to clarify the direction-specific sensing mechanism by analyzing internal fluid flow and shear stress distribution under different vibration modes. A biomimetic microfluidic platform was developed and coupled with a dynamic mesh computational fluid dynamics (CFD) model to simulate the response of the corpuscle to 20 Hz normal and tangential vibrations. The simulation results showed clear differences in fluid behavior. Normal vibration produced localized vortices and peak wall shear stress greater than 0.0054 Pa along the short axis. In contrast, tangential vibration generated stable laminar flow with a lower average shear stress of about 0.0012 Pa along the long axis. These results suggest that the internal structure of the Meissner corpuscle is important for converting mechanical inputs from different directions into specific fluid patterns. This study provides a physical foundation for understanding mechanotransduction and supports the design of biomimetic sensors with improved directional sensitivity for use in smart skin and soft robotic systems. Full article

With the escalating global cyber threats, Distributed Denial of Service (DDoS) attacks have become one of the most disruptive and prevalent network attacks. Traditional DDoS detection systems face significant challenges due to the unpredictable nature, diverse protocols, and coupled behavioral patterns of attack traffic. To address this issue, this paper proposes a novel approach for DDoS attack detection by leveraging the Transformer architecture to model both temporal dependencies and behavioral patterns, significantly improving detection accuracy. We utilize the global attention mechanism of the Transformer to effectively capture long-range temporal correlations in network traffic, and the model’s ability to process multiple traffic features simultaneously enables it to identify nonlinear interactions. By reconstructing the CIC-DDoS2019 dataset, we strengthen the representation of attack behaviors, enabling the model to capture dynamic attack patterns and subtle traffic anomalies. This approach represents a key contribution by applying Transformer-based self-attention mechanisms to accurately model DDoS attack traffic, particularly in handling complex and dynamic attack patterns. Experimental results demonstrate that the proposed method achieves 99.9% accuracy, with 100% precision, recall, and F1 score, showcasing its potential for high-precision, low-false-alarm automated DDoS attack detection. This study provides a new solution for real-time DDoS detection and holds significant practical implications for cybersecurity systems. Full article

This paper introduces Exponentiated Inverse Exponential Distribution (EIED), a novel probability model developed within the power inverse exponential distribution framework. A distinctive feature of EIED is its highly flexible hazard rate function, which can exhibit increasing, decreasing, and reverse bathtub (upside-down bathtub) shapes, making it suitable for modeling diverse lifetime phenomena in reliability engineering, survival analysis, and risk assessment. We derived comprehensive statistical properties of the distribution, including the reliability and hazard functions, moments, characteristic and quantile functions, moment generating function, mean deviations, Lorenz and Bonferroni curves, and various entropy measures. The identifiability of the model parameters was rigorously established, and maximum likelihood estimation was employed for parameter inference. Through extensive simulation studies, we demonstrate the robustness of the estimation procedure across different parameter configurations. The practical utility of EIED was validated through applications to real-world datasets, where it showed superior performance compared to existing distributions. The proposed model offers enhanced flexibility for modeling complex lifetime data with varying hazard patterns, particularly in scenarios involving early failure periods, wear-in phases, and wear-out behaviors. Full article

In this study, the decarburization behavior in basic oxygen furnace (BOF) steelmaking was investigated based on the multi-zone reaction mechanism. The contributions of the main reaction zones to decarburization were clarified, and the effects of key factors—including the effective reaction amount in the main reaction zones, the post combustion ratio (PCR) in auxiliary reaction zones, and the carbon content of scrap steel—on decarburization behavior were quantitatively analyzed. The results indicate that decarburization predominantly occurs in the jet impact reaction zone (approximately 76% of the total decarburization), followed by the emulsion and metal droplet reaction zone (approximately 14%) and the bulk metal and slag reaction zone (approximately 10%). Variations in the effective reaction amount for the main reaction zones significantly affect both the decarburization rate and the endpoint carbon content, with the direct oxidation decarburization reaction in the jet impact reaction zone being the dominant factor. In addition, the PCR in the gas homogenization zone of the auxiliary reaction zones determines the distribution ratio of effective reaction oxygen, while the melting behavior of scrap steel in the metal homogenization zone plays a critical role in the precise control of the endpoint carbon content. This study provides a quantitative elucidation of the effects of different reaction zones on decarburization behavior, offering a foundation for the precise control of endpoint carbon content in BOF steelmaking. Full article

Adipose tissue plays a crucial role in the tumor microenvironment (TME), where its secreted extracellular vesicles (EVs) are involved in the complex signaling between tumor cells and surrounding stromal components. This study aims to unravel the mechanisms through which adipocyte-derived EVs influence breast cancer (BC) progression. Human mesenchymal stem cells (hMSCs) were differentiated into adipocytes following a 21-day induction protocol that led to significant accumulation of lipid droplets within the cells. EVs were isolated from the conditioned medium of both hMSC-derived adipocytes and BC cells. Particle size distribution, morphology, and uptake into the recipient cell were investigated via nanoparticle tracking analysis, transmission electron microscopy, and fluorescence microscopy, respectively. Our results show that BC-derived EVs notably impaired cell viability and modulated the expression of key genes involved in apoptosis resistance within stromal cells. On the other hand, stromal-derived EVs significantly altered tumor cell behavior, indicating a dynamic, bidirectional exchange of bioactive signals. These findings underscore the pivotal role of EV-mediated communication in the tumor-stroma interplay, suggesting that adipocyte-cancer cell EV crosstalk contributes to the remodeling of the TME, potentially facilitating tumor progression. Full article

Ionic rare earths are extracted from primary sources by the in situ chemical leaching method, where the type and concentration of leaching agents significantly affect the mechanical properties and microstructure of the ore body. In this study, MgSO₄ and Al₂(SO₄)₃ solutions of varying concentrations were used as leaching agents to investigate the evolution of shear strength, the characteristics of Duncan–Chang hyperbolic model parameters, and the changes in microstructural pore characteristics of rare earth samples under different leaching conditions. The results show that the stress–strain curves of all samples consistently exhibit strain-hardening behavior under all leaching conditions, and shear strength is jointly influenced by confining pressure and the chemical interaction between the leaching solution and the soil. The samples leached with MgSO₄ exhibited higher shear strength than those treated with water. The samples leached with 3% and 6% Al₂(SO₄)₃ showed increased strength, while 9% Al₂(SO₄)₃ caused a slight decrease. With increasing leaching agent concentration, the cohesion of the samples significantly declined, whereas the internal friction angle remained relatively stable. The Duncan–Chang model accurately described the nonlinear deformation behavior of the rare earth samples, with the model parameter b markedly decreasing as confining pressure increased, indicating that confining stress plays a dominant role in governing the nonlinear response. Under the coupled effects of chemical leaching and mechanical stress, the number and size distribution of pores of the rare earth samples underwent a complex multiscale co-evolution. These results provide theoretical support for the green, efficient, and safe exploitation of ionic rare earth ores. Full article

Compression of clayey sediments not only causes land subsidence but also results in geogenic high fluoride groundwater. The distribution characteristics and enrichment mechanisms of fluoride in alluvial−lacustrine facies clayey sediments in the land subsidence area of Cangzhou Plain, China, were investigated using sample collection, mineralogical research, and hydrogeochemical and isotopic analysis. The results show that F⁻ concentration of groundwater samples ranged from 0.31 to 5.54 mg/L in aquifers. The total fluoride content of clayey sediments ranged from 440 to 792 mg/kg and porewater F⁻ concentration ranged from 0.77 to 4.18 mg/L. Clay minerals containing fine particles, such as muscovite, facilitate the enrichment of fluoride in clayey sediments, resulting in higher total fluoride levels than those in sandy sediments. The clay porewater F⁻ predominantly originated from the dissolution of water-soluble F and the desorption of exchangeable F from sediments. The F⁻ concentration in porewater was further influenced by ionic interactions such as cation exchange. The stable sedimentary environment and intense compression promoted the dissolution of F–bearing minerals and the desorption of adsorbed F in deep clayey sediments. The similar composition feature of δ²H−δ¹⁸O in deep groundwater and clay porewater samples suggests a significant mixing effect. These findings highlight the joint effects of hydrogeochemical and mineralogical processes on F behavior in clayey sediments. Full article

This work thoroughly investigated the compound 4-(2,5-Dimethoxyphenyl)-3,4-dihydrobenzo[g]chromene-2,5,10-trione (DMDCT) using molecular docking, quantum chemical analysis, and vibrational spectroscopy methodology. The medicinal chemistry group has been particularly interested in chromene and benzochromene derivatives due to their wide range of pharmacological actions, including anticancer, antibacterial, anti-inflammatory, antioxidant, antiviral, and neuroprotective capabilities. In this connection, DMDCT has been explored to evaluate its biological, electrical, and structural properties. DFT using the B3LYP functional and 6–31G basis was established to conduct theoretical computations with the Gaussian 09 program. The findings from these computations provide insight into the following topics: NBO interactions, optimal molecular geometry, Mulliken charge distribution, frontier molecular orbitals, and MEP. Second-order perturbation theory has been used to assess stabilization energies arising from donor–acceptor interactions. Furthermore, general features such as chemical hardness, softness, and electronegativity were studied. The results suggest that DMDCT has stable electronic configurations and biologically relevant active sites. This integrated experimental and theoretical study supports the potential of DMDCT as a practical scaffold for future therapeutic applications and contributes valuable information regarding its vibrational and electronic behavior. Full article

In this study, we report the synthesis, characterization, and performance evaluation of a series of bimetallic Pt_xRh_y/C electrocatalysts with systematically varied Rh content for glycerol electrooxidation in acidic and alkaline media. The catalysts were prepared via a polyol reduction method using ethylene glycol as both a solvent and reducing agent, with prior functionalization of Vulcan XC-72 carbon to enhance nanoparticles (NPs) dispersion. High-resolution transmission electron microscopy (HRTEM), energy-dispersive X-ray spectroscopy (EDS), and X-ray diffraction (XRD) analyses indicated the spatial co-location of Rh atoms alongside Pt atoms. Electrochemical studies revealed strong composition-dependent behavior, with Pt₉₅Rh₅/C exhibiting the highest activity toward glycerol oxidation. To elucidate the origin of raised results, density functional tight binding (DFTB) simulations were conducted to model atomic distributions and evaluate energetic parameters. The results showed that Rh atoms preferentially segregate to the surface at higher concentrations due to their lower surface energy, while at low concentrations, they remain confined within the Pt lattice. Among the series, Pt₉₅Rh₅/C exhibited a distinctively higher excess energy and less favorable binding energy, rationalizing its lower thermodynamic stability. These findings reveal a clear trade-off between catalytic activity and structural durability, highlighting the critical role of the composition and nanoscale architecture in optimizing Pt-based electrocatalysts for alcohol oxidation reactions. Full article

Electrochemical CO₂ reduction reaction (CO₂RR) is a key technology for achieving carbon neutrality and efficient utilization of renewable energy, capable of converting CO₂ into high-value-added carbon-based fuels and chemicals. Copper (Cu)-based catalysts have attracted significant attention due to their unique performance in generating multi-carbon (C₂₊) products such as ethylene and ethanol; however, there are still many controversies regarding their complex reaction mechanisms, active sites, and the dynamic evolution of intermediates. In situ Raman spectroscopy, with its high surface sensitivity, applicability in aqueous environments, and precise detection of molecular vibration modes, has become a powerful tool for studying the structural evolution of Cu catalysts and key reaction intermediates during CO₂RR. This article reviews the principles of electrochemical in situ Raman spectroscopy and its latest developments in the study of CO₂RR on Cu-based catalysts, focusing on its applications in monitoring the dynamic structural changes of the catalyst surface (such as Cu⁺, Cu⁰, and Cu²⁺ oxide species) and identifying key reaction intermediates (such as *CO, *OCCO(*O=C-C=O), *COOH, etc.). Numerous studies have shown that Cu-based oxide precursors undergo rapid reduction and surface reconstruction under CO₂RR conditions, resulting in metallic Cu nanoclusters with unique crystal facets and particle size distributions. These oxide-derived active sites are considered crucial for achieving high selectivity toward C₂₊ products. Time-resolved Raman spectroscopy and surface-enhanced Raman scattering (SERS) techniques have further revealed the dynamic characteristics of local pH changes at the electrode/electrolyte interface and the adsorption behavior of intermediates, providing molecular-level insights into the mechanisms of selectivity control in CO₂RR. However, technical challenges such as weak signal intensity, laser-induced damage, and background fluorescence interference, and opportunities such as coupling high-precision confocal Raman technology with in situ X-ray absorption spectroscopy or synchrotron radiation Fourier transform infrared spectroscopy in researching the mechanisms of CO₂RR are also put forward. Full article

The arrival of tracers at boundaries with defined distances from the origin of their motion in stochastically fluctuating advection processes is investigated. The advection model is a stationary one-dimensional integrated stochastic process with an arbitrary a priori known correlation and with possible mean drift. The current (direction-sensitive), the total flux (direction-insensitive) of tracers through a non-absorbing boundary, and the first-passage times of the tracers at an absorbing boundary are derived depending on the correlation function of the carrying flow velocity. While the general derivations are universal with respect to the distribution function of the advection’s increments, the current and the total flux are explicitly derived for a Gaussian distribution. The first-passage time is derived implicitly through an integral that is solved numerically in the present study. No approximations or restrictions to special cases of the advection process are used. One application is one-dimensional Gaussian turbulence, where the one-dimensional random velocity carries tracer particles through space. Finally, subdiffusive or superdiffusive behavior can temporarily be reached by such a stochastic process with an adequately designed correlation function. Full article