Search Results (1,483)

In this paper, synchronous mechanical and optical measurements are proposed using the dual cantilever mode of dynamic mechanical analysis (DMA). It was demonstrated that this mode enables the detection of phase transitions in both the core and cladding materials of polymer optical fibers (POFs), with corresponding changes in optical signal intensity observed across different light wavelengths. In dual cantilever mode DMA, an increase in optical transmission was recorded between the two detected glass transition temperatures. The initial increase in transmission is attributed to cladding softening and the consequent reduction in internal stresses in the POF, while the maximum in optical transmission coincides with the beginning of the phase transition in the core material. To compare and interpret the optical and thermo-mechanical results, Differential scanning calorimetry (DSC) and Fourier transform infrared (FTIR) measurements were carried out on POF pieces, as well as separately on the core and cladding materials. This integrated technique yields quantitative data on a material’s viscoelasticity and light-transmission changes, making it valuable for quality control and for predicting the long-term behavior of advanced POFs in various applications. Full article

Background: Ovarian cancer (OC) is the second most common gynecologic malignancy in the United States and remains the leading cause of death among cancers of the female reproductive system. Alarmingly, mortality rates have risen disproportionately among women of African ancestry compared to those of European or Asian descent. Identifying microRNA (miRNA) signatures that contribute to these disparities may enhance prognostic accuracy and inform personalized therapeutic strategies. Methods: In this study, we identified prognostic markers of overall survival in serous ovarian cancer (SOC) using data from The Cancer Genome Atlas (TCGA) and the Human Protein Atlas. Integrative bioinformatic analyses revealed three key prognostic genes—TIMP3 (Tissue Inhibitor of Metalloproteinases-3), BRAF (v-raf murine sarcoma viral oncogene homolog B), and ITGB1 (Integrin Beta-1)—as critical molecular determinants associated with survival in patients with SOC. Candidate miRNAs regulating these genes were predicted using TargetScanHuman v8.0, identifying a core regulatory set comprising miR-192, miR-30d, miR-16-5p, miR-143-3p, and miR-20a-5p. To validate their clinical relevance, formalin-fixed, paraffin-embedded (FFPE) and fresh SOC tumor samples were obtained from African American and Caucasian patients who underwent surgery at Loma Linda University (LLU) between 2010 and 2023. Results and Discussion: Among all these, ITGB1 (p = 0.00033), TIMP3 (p = 0.0035), and BRAF (p = 0.026) emerged as statistically significant predictors. Following total RNA extraction, cDNA synthesis, and quantitative reverse transcription PCR (qRT-PCR), the expression levels of these miRNAs and their target genes were quantified. In the LLU cohort, ITGB1 and TIMP3 were significantly upregulated in African American patients compared to Caucasian patients (p < 0.01 and p < 0.02, respectively). Among the miRNAs, miR-192-5p was particularly noteworthy, showing marginally differential expression in LLU samples (p = 0.0712) but strong statistical significance in the TCGA cohort (p = 0.00013), where elevated expression correlated with poorer overall survival (p = 0.021). Pathway enrichment and gene ontology analyses (miRTargetLink2.0, Enrichr) revealed interconnected regulatory networks linking miR-192, miR-16-5p, miR-143-3p, and miR-20a-5p to ITGB1; miR-143-3p/miR-145-5p to BRAF; and miR-16-5p and miR-30c/d to TIMP3. Conclusions: Collectively, these findings identify distinct miRNA–mRNA regulatory signatures—particularly the miR-192-5p–ITGB1/TIMP3 axis—as potential clinically relevant biomarkers that may contribute to racial disparities and disease progression in ovarian cancer. Full article

In this study, Fe₂O₃–TiO₂ nanocomposites with different TiO₂ contents (1–50%) were synthesized via a solvothermal method using pre-formed α-Fe₂O₃ nanoparticles as cores. We systematically evaluated the influence of TiO₂ loading on the nanocomposites’ structural, morphological, optical, and photocatalytic properties. X-ray diffraction revealed the coexistence of hematite and anatase phases, with an increase in TiO₂ content inducing reduced crystallite size, enhanced dislocation density, and microstrain, indicating interfacial lattice distortion. Scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) showed a uniform elemental distribution at low TiO₂ contents, evolving into irregular agglomerates at higher loadings. Fourier-transform infrared (FTIR) spectra indicated the suppression of Fe–O vibrations and the appearance of hydroxyl-related bands with TiO₂ enrichment. Diffuse reflectance spectroscopy (DRS) analysis confirmed the simultaneous presence of hematite (~2.0 eV) and anatase (3.2–3.35 eV) absorption edges, with a slight blue shift in the TiO₂ band gap at higher concentrations. Photocatalytic activity, assessed using methylene blue degradation under xenon lamp irradiation, demonstrated a strong dependence on the TiO₂ fraction. The composite containing 33% TiO₂ achieved the best performance, with 98% dye removal and a pseudo-first-order rate constant of 0.045 min⁻¹, outperforming both pure hematite and commercial P25 TiO₂. These results highlight that intermediate TiO₂ content (~33%) provides an optimal balance between structural integrity and photocatalytic efficiency, making Fe₂O₃–TiO₂ heterostructures promising candidates for water purification under simulated solar irradiation. Full article

Low-permeability glutenite reservoirs in the Qaidam Basin, NW China, exhibit intricate pore networks and strong heterogeneity that hinder effective hydrocarbon development. Here, we integrate thin-section petrography, scanning electron microscopy (SEM), mercury injection capillary pressure (MICP), and nuclear magnetic resonance (NMR) to characterize pore types and establish quantitative links between fractal dimension and petrophysical properties. The reservoirs are mainly pebbly sandstones and sandy conglomerates with 15–23% quartz, 27–37% feldspar, and 2–20% carbonate/muddy matrix. Helium porosity ranges from 5.12% to 18.11% (mean 9.39%) and air permeability from 60 to 3270 mD (mean 880 mD). Fine pores (1–10 μm) dominate, throats are short and poorly connected, and illite (up to 16.76%) lines pore walls, further reducing permeability. Fractal analysis yields weighted-average dimensions of 2.55, 2.50, and 2.15 for macro-, meso-, and micropores, respectively, giving an overall dimension of 2.52. Higher dimensions correlate negatively with porosity and permeability. Empirical models (quadratic for porosity and exponential for permeability) predict core data within 0.86% and 5.4% error, validated by six blind wells. Reservoirs are classified as Class I (>12%, >1.0 mD), Class II (8–12%, 0.5–1.0 mD), and Class III (<8%, <0.5 mD), providing a robust tool for stimulation design and numerical simulation. Full article

Conical screw compressors are increasingly used in applications that require quiet operation and reduced dimensions. One of the important problems in the case of these compressors is the profiling of the active elements, which are conical screws, with constant or variable pitch. This problem can be solved using programs that allow for the creation of a virtual solid that represents the trace left by a body during its movement. In this paper, the profiling of the outer rotor of a conical screw compressor, with variable pitch, is pro-posed by numerical modeling of the space swept by the inner rotor while rotating. After obtaining the numerical model, a physical replica of it was made by 3D printing. The obtained part was scanned using an ATOS Core 500 video measurement system. Subsequently, the model obtained by scanning was compared with the numerical model of the rotor. The numerical model was obtained first using a part with known shape and dimensions. Since the helical–conical surface has variable pitch, it is possible to analyze the influence of the helix inclination angle on the modeling accuracy in parallel with the analysis of the contact between the two rotors. Full article

As a core wear-prone component of coal mining equipment, the wear resistance of cutting picks directly affects mining efficiency and operating costs. This study addresses the premature failure of traditional hard alloy cutting picks caused by impact fatigue and abrasive wear under complex geological conditions. By introducing WC powder, the research aims to enhance the quality of the laser cladding coating on cobalt-based reinforced cutting picks and to investigate the variation in optimal process parameters with an increasing WC ratio. Five sets of L9 orthogonal experiments were conducted using the Taguchi method. Combined with the analysis of the signal-to-noise ratio (SNR), the optimal parameters under each material ratio were obtained and experimentally verified. The errors were all within 10%, which proves the reliability and repeatability of the optimization results. Subsequently, the effects of laser power, powder feeding rate and scanning speed on coating quality were systematically evaluated. Scanning speed had the most significant effect on microhardness, while laser power predominantly influenced dilution rate. For low WC content, powder feeding rate had a greater impact on porosity; as WC content increased, laser power became the main factor affecting porosity. Grey Relational Analysis (GRA) was subsequently applied to integrate the three response targets into a single grey relational grade (GRG), optimizing the parameters for each WC ratio. And the law of mutual influence between different material ratios and their process parameters was found. Wear tests on the optimized cladding layer showed that, compared with the original and pure cobalt-based picks, wear resistance increased by 45% and 80%, respectively. These results indicate a clear correlation between WC content, process parameter optimization, and improved coating performance. Full article

The decline in the injectivity of injection wells is a serious problem in geothermal systems. In this article, we analyse the mechanisms responsible for the reduction in permeability in Lower Jurassic sandstones during the injection of cooled formation brine. Flow experiments were conducted on rock cores using three types of brines with varying degrees of contamination. The studies included microscopic analysis, scanning electron microscopy (SEM) and mercury intrusion capillary pressure (MICP) before and after the experiments. The results showed that the main factor in the decrease in permeability is the formation of a filter cake from secondary iron minerals on the front surface of the core. Filter cake formation was observed in all samples, with ferrous sediment penetrating to a maximum depth of 1.5 cm from the core front. In addition, the mobilisation of clay particles was observed, which accumulate in pore constrictions, causing additional flow restriction. Mercury porosimetry revealed significant increases in hysteresis values in the front zone (from 16.5 to 42%), indicating complex pore connectivity changes without substantial porosity reduction. The rate of injectivity decline correlates strongly with the fluid flow velocity. The results of the study provide a scientific basis for optimising reinjection processes in geothermal systems and developing strategies to prevent formation damage. Full article

LiDAR technology has undergone significant advancement in recent years, establishing itself as a technique for long-range, high-precision detection. As its use expands into more intricate scenarios, the need to overcome blind spots in the scanning field and enhance system stability has become increasingly critical. This paper introduces a novel coaxial LiDAR system featuring a double-clad optical fiber-based receiver which consists of a single-mode fiber core for the emission of the laser beam and a multimode inner cladding for the collection and transmission of the back-reflected beam. The real-time system is specifically engineered to measure distances in both near and far fields, eliminating blind spots. Experimental evaluations demonstrate that our system achieves a detection range of 0.2–70.7 m, with a distance accuracy of 3.4 cm and an angular resolution of 0.018°. Compared with conventional LiDAR systems, our approach eliminates the need for complex optical pathway designs and algorithmic compensation. It offers a simplified structure, enhanced stability, and high accuracy. Full article

The shell liner is a core component of Semi-Autogenous Grinding (SAG) mills, suffering severe wear from ore impact and friction, and its shape directly affects grinding efficiency and maintenance costs. In this study, the Finnie wear model in EDEM2022 software was improved to predict the wear morphology evolution of shell liners. A Python-based coupled simulation of the Discrete Element Method (DEM, EDEM) and Finite Element Method (FEM, ABAQUS) was established to analyze liner wear mechanisms, stress states, and mill service performance (wear resistance, grinding efficiency, and stress distribution). The simulated wear profile showed high consistency with laser three-dimensional scanning (LTDS) results, confirming the improved Finnie-DEM model’s effectiveness in reproducing liner wear evolution. Shearing in crushing/grinding zones was the main wear cause, with additional contributions from relative sliding among ore, grinding balls, and liners in grinding/discharge zones. DEM-FEM coupling revealed two circumferential instantaneous wear extremes (Max^a > Max^b) and two lifter wear rate peaks (M^a > M^b). In the grinding zone, liner stress distribution matched wear distribution, with maximum instantaneous stress at characteristic points A and B—stress at A reflects liner impact degree, while stress at B indicates mill ore-crushing capacity. Optimizing flat liner shape adjusted wear rate peaks (M^a, M^b), improving overall liner wear. This optimization significantly affected stresses at A/B and ore normal collision but had little impact on mill energy efficiency. Full article

This research examines the otolith microchemical characteristics of the critically endangered kunming snout trout (Schizothorax grahami) collected from the sources section endemic to the Chishui River, China, a tributary of the upper Yangtze River, and the metal concentrations in the water of fish habitats. Among the analyzed elements, strontium (Sr) exhibited consistent distribution patterns across otolith rings, as observed through face-scan imagery (scanning the polished surface of the otolith cut), with a relatively low coefficient of variation. Statistical analysis using a paired two-tailed t-test revealed significant differences in Sr:Ca ratios among samples from the three river sections. Notably, magnesium (Mg) levels in the otolith core during the early life stages of the fish were notably higher compared to non-core regions. Similarly, Mg concentrations of water were elevated in the spawning grounds relative to non-spawning areas. This suggests that otolith Mg content may be influenced by the specific water conditions of the spawning grounds. Furthermore, Mg:Ca ratios in the otolith core displayed significant variation among samples from U3, L2, and other sites, implying that the fish in these samples originated from distinct spawning locations. These findings demonstrate that strontium and magnesium in otoliths can serve as effective markers for reconstructing the life history of S. grahami in the Chishui River and can contribute to the management of different fish stocks. Full article

An integrated analysis including total organic carbon (TOC), X-ray diffraction (XRD), scanning electron microscopy (SEM), and gas adsorption experiments was conducted on core samples from the deep Wufeng–Longmaxi (WF-LMX) Formation in the Zigong area to characterize its lithofacies and reservoir characteristics and their influencing factors. The results suggest that eight distinct lithofacies are distinguished and argillaceous/calcareous mixed siliceous shale lithofacies (S-1) is the most optimal lithofacies. The pore surface fractal dimension (D) was derived by applying the Frenkel–Halsey–Hil (FHH) model to low-temperature N₂ adsorption (LTNA) data. The meso-macropore regime shows higher heterogeneity than the micropore regime (since D₂ > D₁). Both D₁ and D₂ show a significant positive relation with TOC and carbonate content, a slight negative correlation with quartz content, and no clear link with clay content. In the initial depositional stage of the LMX Formation, a low-energy, stagnant, and strongly reducing environment facilitated the accumulation of siliceous biogenic sediments, leading to the formation of siliceous shale characterized by high paleoproductivity. In the middle to late stages of LMX Formation deposition, increased input of terrigenous clastic material, shallower water depths, and the gradual disruption of the anoxic conditions resulted in diminished paleoproductivity, causing a transition from siliceous shale to a mixed shale lithofacies. Increased TOC and carbonate content enhance pore heterogeneity, with TOC predominantly influencing micropores and carbonates controlling macropores. In contrast, higher quartz content inhibits pore development. Full article

This study focuses on first-generation crystalline silicon photovoltaic (PV) cells, which remain the core of the PV industry. It outlines the structure and operation of single-junction cells, distinguishing between monocrystalline and polycrystalline technologies. A literature review was conducted using databases such as Web of Science and Scopus to identify research trends and inform future research directions. PV cell classification by generation is also presented based on production methods and materials. The experimental section includes both electrical and structural characterisation of crystalline silicon solar cells, with particular emphasis on the influence of the number and geometry of front-side busbars on metal-semiconductor contact resistance and electrical properties. Additionally, the paper highlights the use of dedicated laboratory equipment—such as a solar simulator (for determining photovoltaic cell parameters from current-voltage characteristics) and Corescan equipment (for determining layer parameters using the single-tip probe method)—in evaluating PV cell properties. This equipment is part of the Photovoltaics and Electrical Properties Laboratory at the Silesian University of Technology. The findings demonstrate clear structural correlations that can contribute to optimising the performance and longevity of silicon-based PV cells. Full article

Objectives: Kidneytumors, particularly renal cell carcinoma (RCC), represent a critical public health concern due to their prevalence and the severe consequences of late diagnosis. Traditional diagnostic techniques, though widely used, are often limited by human error, inter-observer variability, and delayed recognition of malignant subtypes, underscoring the urgent need for automated, accurate, and reproducible solutions. Methods: To address these challenges, this study introduces a hierarchical, AI-driven framework for early detection and precise classification of kidney tumors from CT scans. At its core, the framework uses a specialized encoder, RAD-DINO-MAIRA-2, to extract highly discriminative imaging features, which are subsequently processed through multiple machine learning classifiers tailored to distinct hierarchical levels of diagnosis. Results: Using benchmark kidney tumor datasets, the framework was rigorously validated across 25 independent trials. Performance was assessed using accuracy, reproducibility, and robustness metrics, with results revealing a maximum accuracy of 98.29% and a mean accuracy of 94.72%. Notably, the Gaussian Process classifier achieved perfect performance in tumor type classification, while the MLP classifier attained flawless results in malignant subtype differentiation. Comparative analyses demonstrate that our hierarchical approach outperforms conventional DL-based pipelines by reducing sensitivity to dataset variability and providing a clinically viable path for integration into diagnostic workflows. Combining state-of-the-art feature extraction with hierarchical classification, the proposed framework delivers a robust and interpretable tool with substantial promise for improving patient outcomes in real-world clinical practice. Full article

Perfluorooctanesulfonate (PFOS) is a typical persistent organic pollutant, which presents a significant risk to the ecosystem and human health. Therefore, the development of a highly sensitive and effective detection technique for PFOS has aroused wide concern. In this study, for the mesoporous metal–organic frameworks (MOFs), Cr-MIL-101 were used as the precursor. And the poly(3,4-ethylenedioxythiophene) (PEDOT) using as molecularly imprinted polymers (MIPs) was loaded on Cr-MIL-101 to form a core–shell structure. The obtained Cr-MIL-101@PEDOT/MIP composites integrate the high specific surface area of Cr-MIL-101 and the specific recognition capability of PEDOT/MIP. The glassy carbon electrode (GCE) interface modified by them can specifically adsorb PFOS through electrostatic interactions, coordination by Cr metal nodes, hydrophobic interaction, and hydrogen bonding, etc. The adsorbed PFOS molecules could block the active sites at the electrode interface, causing the current decay of the redox probe. Following the quantitative analysis of peak current decay values using the Langmuir model and the Freundlich–Langmuir model, a wide detection range (0.1–200 nM) and a low detection limit (0.025 nM) were obtained. Characterization techniques including scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET), X-ray photoelectron spectroscopy (XPS), and electrochemical methods were employed to validate the fabrication of the composites. Moreover, Cr-MIL-101@PEDOT/MIP/GCE showed satisfactory stability, repeatability, and selectivity, providing an effective method for the detection of PFOS in practical samples, showing a wide prospective application. Full article

The in situ conversion of oil shale with air injection has the advantage of self-generated heat. The fragmentation degree of oil shale affects the oxidative pyrolysis process. In this paper, the basic properties of oil shale were analyzed, and weight loss observation and high-pressure TGA-DSC (thermogravimetric analysis and differential scanning calorimetry) tests in an air atmosphere were conducted using the cores and particles. The oil shale’s oxidative pyrolysis characteristics and the effect of its particle sizes were evaluated. The results show that the porosity and permeability conditions, TOC (total organic carbon), and inorganic mineral composition of oil shale are highly heterogeneous, with higher permeability and greater TOC along the bedding direction. The derivative of the TGA curve shows a single peak, and the heat flow curve shows a double peak that can be used to determine the oil shale’s oxidation type. The oxidative pyrolysis stage of organic matter can be divided into three temperature ranges, of which the medium temperature range is where the most combustion weight loss and heat release occurs. The activation energy of oxidative pyrolysis, which is affected by factors such as particle size, organic matter content, and pyrolysis temperature, is 46.92–248.11 kJ/mol, indicating the varying degrees of difficulty in initiating the reaction under different conditions. The pre-exponential factor is 3.15 × 10²–6.27 × 10¹¹ 1/s, and the enthalpy value is 2.575–4.045 kJ/g. The combustion indexes and reaction enthalpy under different particle sizes are more correlated with their own organic matter content. As oil shale particle size decreases, the variation law of the activation energy and pre-exponential factor changes with temperature from an initial continuous increase to a decrease, then increases again with the smallest kinetic parameters in the medium temperature zone. A small particle size, high organic matter content, and high pressure are more conducive to initiating the oxidative pyrolysis reaction to achieve in situ conversion of organic matter. Full article