Search Results (1,415)

Microelectromechanical systems are being increasingly deployed in nuclear industry robotics, where their great sensitivity and mechanically stable silicon structures enable reliable sensing in radiation-exposed environments. An ultra-thin silicon strain gauge without an oxide substrate layer designed for robotic electronic skin is evaluated under Co-60 γ irradiation, representative of nuclear decommissioning conditions. The sensor performance is evaluated based on electrical measurements conducted before and after irradiation, focusing on cumulative radiation-induced effects. The results show that silicon strain gauge signal maintains a high linearity (R² > 0.99) under strain. Across an accumulated dose range up to approximately 15 Gy, only minor variations are observed, including a resistance increase within 1.3% and a reduction in gauge factor within 5% for most specimens. The radiation-induced resistance increases and sensitivity degradation results in a maximum strain estimation error of approximately 22.5 με (≈3.5%) within the tested operating range below 700 με. Full article

Carbonate mound–shoal complexes, despite their complex pore structures and pronounced heterogeneity, represent one of the most productive reservoir units within carbonate formations. Accurately predicting key physical properties—such as porosity, permeability, and flow zone index—from well log data remains a significant challenge for conventional empirical methods. This study investigates the application of machine learning algorithms for optimizing the prediction of reservoir properties in hill-and-plain carbonate bodies. Six machine learning approaches—Support Vector Machines (SVM), Backpropagation Neural Networks (BPNN), Long Short-Term Memory Networks (LSTM), K-Nearest Neighbors (KNN), Random Forests (RF), and Gaussian Process Regression (GPR)—are systematically evaluated and compared. The analysis employed flow zone indices, geological data, and well log curves to classify porosity–permeability types. Seven logging parameters were used as input features: spectral gamma ray (SGR), uranium-free gamma ray (CGR), photoelectric absorption cross-section index (PE), bulk density (RHOB), acoustic travel time (DT), neutron porosity (NPHI), and true resistivity (RT). These features were paired with measured physical property values to train and validate the predictive models. Results demonstrate distinct algorithmic advantages for specific properties. The RF model achieved superior performance in permeability prediction, yielding an R² of 0.6824, whereas the GPR model provided the highest accuracy for porosity estimation, with an R² of 0.7342 and an Accuracy Index (ACI) of 0.9699. Despite these improvements, machine learning models still face limitations in accurately characterizing low-permeability zones within highly heterogeneous hill–terrace reservoirs. To address this challenge, the study integrates geological prior knowledge into the machine learning framework and applies cross-validation techniques to optimize model parameters, thereby providing a practical and robust approach for detailed assessment of mound–hoal carbonate reservoirs. Full article

A structurally complex Paleozoic succession in southwestern Sinai hosts uranium and associated metals, and brittle deformation controls fluid flow and ore localization. The study integrates structural mapping with mineralogical, geochemical, and radiometric data to evaluate how fault architecture controls uranium and polymetallic mineral occurrences in the east Abu Zeneima area. Eleven representative samples were collected from major fault zones and host lithofacies, and 652 ground gamma-ray spectrometric measurements were acquired across mineralized localities and Paleozoic stratigraphic units. Heavy mineral separation, SEM–BSE/EDX, X-ray diffraction, and whole-rock geochemistry were used to identify ore and accessory phases and quantify their elemental composition. The middle carbonate member of the Um Bogma Formation is the primary host lithology and contains primary U dispersed within carbonaceous sandy dolostone and locally abundant secondary U phases coexisting with Cu–Fe–Mn phases and REE-bearing silicates and phosphates. Uranium enrichment (locally > 2900 ppm eU) in the targeted anomalous samples shows a positive association with P₂O₅ and a weaker positive association with ΣREEs. Together with SEM–BSE/EDX and XRD identification of uranyl phosphates and REE-bearing accessory minerals, these observations suggest that phosphate-bearing secondary phases and REE-rich accessories locally contributed to uranium hosting. Seventy-four radioactive anomalies are predominantly associated with normal faults and are concentrated along fault cores and highly fractured downthrown blocks, especially along a NW–SE trend that forms the main mineralized corridor. The study findings emphasize the importance of fault zone architecture for targeting new uranium resources in Paleozoic basins. Full article

Background/Objectives: Fungal keratitis remains a vision-threatening infection, and current amphotericin B (AmphB) eye drops suffer from low corneal residence time, poor aqueous solubility, and the need for frequent dosing. This study develops electrospun nanofiber-based ophthalmic inserts combining polyvinyl alcohol (PVA), gamma-cyclodextrin (γ-CD), and sodium taurocholate (STC) to enhance AmphB solubility and provide a non-invasive, rapidly dissolving ophthalmic dosage form. Methods: γ-CD and STC-enhanced AmphB-loaded PVA nanofiber-based ophthalmic inserts with varying γ-CD and STC concentrations were prepared by electrospinning and characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD). Drug content, in vitro release (Weibull modeling), antifungal activity against Candida albicans, Fusarium solani, and Aspergillus fumigatus, ocular cytocompatibility using the Hen’s Egg Test on Chorioallantoic Membrane (HET-CAM), and accelerated stability (40 ± 2 °C, 75 ± 5% relative humidity, 4 weeks) were evaluated. Results: Bead-free nanofibers with mean diameters between 216 ± 33 nm and 310 ± 35 nm were obtained, and XRD confirmed complete amorphization of AmphB within the PVA nanofiber matrix, forming an amorphous solid dispersion. All formulations showed rapid and nearly complete AmphB release (≈100% within 60 min), with Weibull β values < 0.75, indicating Fickian diffusion-controlled release. AmphB-loaded PVA nanofiber-based ophthalmic inserts produced inhibition zones and broth susceptibility profiles comparable to AmphB in dimethyl sulfoxide (DMSO), demonstrating preserved antifungal activity. HET-CAM scores (0–0.9) classified the inserts as practically non-irritant, and SEM/FTIR after accelerated storage showed no relevant morphological or physicochemical changes. Conclusions: These γ-CD and STC-enhanced AmphB-loaded PVA nanofiber-based ophthalmic inserts provide a non-invasive, rapidly dissolving ophthalmic dosage form that combines amorphous AmphB, immediate drug availability, and good ocular tolerance, supporting their further development as a patient-friendly treatment option for fungal keratitis. Full article

Real-time coal–rock identification is essential for intelligent mining, enabling hazard prevention and geological modeling. However, existing methods often suffer from unclear bit–rock interaction mechanisms, signal distortion, sensor remoteness, or delayed data acquisition, limiting their effectiveness in continuous operations. This study proposes a novel approach for real-time coal–rock identification based on multi-source near-bit drilling data. A near-bit data acquisition system was developed and positioned directly behind the drill bit, integrating sensors to capture high-fidelity parameters—including weight on bit (WOB), torque, rotational speed, rate of penetration (ROP), natural gamma ray, and borehole trajectory—thereby eliminating frictional interference from the drill string. A data-driven theoretical model was established to derive a near-bit drillability index (NDI) for rock strength and to correlate gamma ray responses with lithology. Field trials were conducted in a coal mine in northern Shaanxi, involving over 30 boreholes and systematic core validation. The results demonstrate that the method enables continuous, high-resolution identification of coal–rock interfaces and strength variations along the borehole trajectory, with interpreted results aligning well with core logs and achieving approximately 85% accuracy in strength estimation. By ensuring compatibility with conventional drilling rigs and supporting real-time data transmission and 3D geological updating, this study offers a practical and robust technical pathway for achieving geological transparency and real-time steering in underground coal mining. Full article

The jet structure plays an important role in both the prompt and afterglow emission phases of gamma-ray bursts (GRBs). Whether GRB jets are better described by uniform (top-hat) or structured models remains an open question. We use the afterglowpy Python package to numerically model the late X-ray afterglow light curves of a large sample of long and short GRBs, and apply the Bayesian Information Criterion (BIC) to compare the performance of top-hat and Gaussian structured jet models. Within our adopted modeling framework, we find that the top-hat model is preferred by the BIC for ∼78.9% (150/190) of long GRBs and 70% (7/10) of short GRBs. GRB 180205A and GRB 140515A exhibit $\Delta$BIC < 2 for all three model comparisons, indicating that top-hat, Gaussian, and power-law jets provide equivalent fits to their afterglow light curves. This large-sample analysis suggests that uniform jets may be more common than structured jets in the observed GRB population, although this conclusion is subject to the limitations of our model assumptions and the BIC-based model selection criterion. Furthermore, we find that the best-fit distributions of observer angle ${\theta }_{\mathrm{obs}}$, electron energy fraction ${ϵ}_e$, and isotropic equivalent energy $E_0$ differ significantly between the top-hat and Gaussian jet models, with ${\theta }_{\mathrm{obs}}$ showing the most pronounced distinction. Full article

Neutron gamma density (NGD) plays an increasingly important role in petroleum exploration and development. However, current NGD logging fails to obtain reliable results in anomalous mineral formations (such as anhydrite, halite and coal). To address these issues, the application of NGD logging in anomalous minerals has been studied in this paper. Studies have shown that, compared to the standard formations (dolomite, limestone and sandstone), halite, anhydrite and coal have additional influence on inelastic gamma rays, epithermal neutron distribution, and thermal neutron distribution. This causes additional errors when the gamma and neutron information is used for density calculation. In addition, since the influence mechanisms of different minerals on NGD logging are different, it is necessary to determine the mineral type before conducting NGD correction. Compared to other minerals, halite can be easily distinguished by its very high sigma (thermal neutron capture cross-section) and low apparent density; anhydrite by its high sigma, high density and low neutron porosity; and coal by its very low density and zero neutron porosity. Furthermore, for a given anomalous mineral, the density error of NGD logging has a clear linear relationship with the apparent density, which can be used for density correction. By using the corresponding correction algorithm, the density error of NGD logging can be controlled within 0.025 g/cm³ in anomalous mineral formations. This study can provide guidance for the application of NGD technology in mineral exploration. Full article

Wood ash from biomass power plants and coarse, low-grade sheep wool from farming are underutilized biowastes that are often landfilled. Their valorization could reduce waste and emissions, decrease reliance on virgin materials, and support the circular economy and European Green Deal targets. However, both materials may contain naturally occurring radionuclides, primarily ⁴⁰K, as well as trace uranium and thorium isotopes, with higher concentrations typically found in wood ash due to combustion processes. Assessing their activity concentrations and bioavailability is therefore essential to ensure regulatory compliance and protect public health. This study quantified radionuclide levels in wood ash and sheep wool samples collected in Croatia and evaluated their suitability for agricultural applications. Natural radionuclides (⁴⁰K, ²³²Th, ²³⁸U, ²¹⁴Pb, ²¹⁴Bi, ²²⁶Ra, ²¹⁰Pb, ²¹⁰Po) and ¹³⁷Cs were determined using high-resolution gamma-ray and alpha spectrometry. The influence of different factors on radionuclide content was discussed, and transfer factors within the soil–hay–wool pathway were calculated to assess bioavailability. Measured activity concentrations were consistently low, and transfer factors indicated minimal radionuclide mobility. The results support the safe agricultural reuse of these materials and provide baseline data for radiological safety assessments in sustainable waste management practices. Full article

Lorentz invariance violation (LIV) can alter the group velocity of photons by modifying their dispersion relation, manifesting as differences in the arrival times of photons with different energies. This effect can accumulate over long propagation distances, making gamma-ray bursts (GRBs) a key tool for probing Lorentz invariance violation. By analyzing spectral lag data from 360 measurements across 90 GRBs using Markov Chain Monte Carlo (MCMC) sampling, and under the assumption that all GRBs share a common intrinsic time delay function, we report a maximum a posteriori value of the energy scale of quantum gravity at linear order $E_{QG}=8.96\times {10}^{14}$ GeV, though the data are also compatible with Lorentz invariance ($E_{\mathrm{QG}}=\infty$) to within $2.8\sigma$. Furthermore, we are $95\%$ confident that $E_{QG}\ge 6.67\times {10}^{14}$ GeV. Full article

Four areas in the Kongo Central Province, western Democratic Republic of the Congo, with unexploited phosphate deposits were investigated to assess the composition of phosphatic materials and to evaluate pollution hazards, including radiological hazards arising from naturally occurring radionuclides. In those areas, phosphate rocks were sampled and analyzed for P₂O₅ content (by ED-XRF), and for the naturally occurring radionuclides ²³⁸U, ²²⁶Ra, ²³²Th, ⁴⁰K (by gamma-ray spectrometry). Phosphate rocks displayed P₂O₅ content ranging from 1.06 to 24.42% (dry weight) and exceptionally high ²³⁸U and ²²⁶Ra activity concentrations (up to 3069 and 2273 Bq kg⁻¹, respectively), significantly exceeding global averages in soils. Radiological hazard indices, including the radium equivalent (RaEq), annual effective dose and lifetime cancer risk, confirmed potential health risks associated with phosphate-rich rocks. With the upcoming development of phosphate deposits in DRC, such phosphate materials might become future sources of both geochemical contamination and radiological exposure, emphasizing the need for suitable radiation monitoring and waste management plans prior to and during mineral resource exploitation. Full article

Oil and gas exploration conducted in the main fault zone of the Fuman Oilfield has yielded large-scale and high-production results. Against this background, the non-fault zone has emerged as a new domain for oil exploration endeavors. Nevertheless, the establishment of a unified sequence division scheme for the study area remains unachieved, primarily constrained by two key factors: first, the high costs associated with ultra-deep high-density coring operations; and second, the inconspicuous response characteristics exhibited by logging curves. This absence of a standardized scheme has further impeded the progress of oil and gas exploration in the non-main fault inter-region within the study area. Consequently, the present study is based on multi-source data, including seismic data, logging data, and field outcrop data. Magnetic susceptibility measurements from the cement plant section and natural gamma-ray logging data from the Yangjikan section were systematically analyzed to establish cyclostratigraphic frameworks. A sedimentary noise model (SNM) was employed to reconstruct Holocene sea-level fluctuations, enabling precise sequence stratigraphic subdivision within the Fuman Area. Results demonstrate that the Middle-Lower Ordovician Yijianfang–Penglaiba Formations retain robust astronomical cyclicity, validated by high-fidelity orbital forcing signals. Notably, the DYNOT (Dynamic Noise After Orbital Tuning) model effectively decouples orbital-driven sea-level oscillations from local depositional noise, offering a novel approach for sequence boundary identification. This methodology reveals a hierarchical sequence architecture comprising four third-order sequences and 11 fourth-order sequences within the Yijianfang–Penglaiba Formations. Such a framework provides critical insights into facies distribution patterns and non-fault-controlled exploration potential in the Fuman Basin. Full article

Background: Patients with latent tuberculosis infection are mainly asymptomatic, but they still carry a notable risk of developing active TB, particularly when the host becomes immunosuppressed. Hence, appropriate diagnosis and management for LTBI are essential. Tuberculin skin test (TST) and interferon-gamma release assays (IGRAs) are among the most commonly utilized methods for detecting LTBI. Until now, no agreement has been established regarding the most effective diagnostic test, either TST or IGRA, so our study aims to evaluate the diagnostic utility of TST versus IGRA in detecting LTBI. Methods: An extensive literature search was executed in several databases from inception till June 2024. We included all the available studies that compared TST versus IGRA concurrently applied to the same study participants, utilizing one of the following proxy reference standards: previous contact with a tuberculosis patient, tuberculosis history, chest x-ray suggestive of tuberculosis, or a combination of them. The sensitivity (SN) and specificity (SP) were imputed with their 95% confidence interval (CI). A bivariate random-effects model within the OpenMeta-Analyst software was utilized for data analysis. Results: We included 39 studies, and our primary analysis regarding LTBI revealed that TST has an SN of 0.320 (95% CI [0.254–0.393]) and an SP of 0.808 (95% CI [0.752–0.854]). Nevertheless, the IGRA exhibited a higher SN estimated at 0.362 (95% CI [0.295–0.434]) and a lower SP estimated at 0.758 (95% CI [0.700–0.808]). Regarding the adult population, TST consistently showed a lower SN and a higher SP relative to IGRA. However, within the pediatric population, TST showed higher SN and lower SP when compared to IGRA. Furthermore, TST also showed a lower SN and a higher SP within hemodialysis and organ transplant patients than IGRA. Conclusions: Our diagnostic test meta-analysis revealed that TST was associated with a lower SN and a higher SP than IGRA. Clinicians should interpret these findings with caution, considering the substantial heterogeneity observed across the included studies, the reliance on proxy reference standards, the potential influence of BCG vaccination status, and the considerable overlap in confidence intervals between TST and IGRA estimates across most analyses. Full article

We aim to elucidate the sedimentary cyclicity of the Middle Jurassic Bath–Bajocian Formation in the northern S Oilfield of the West Siberian Basin, address the lack of high-resolution Milankovitch cycle research in this region, and support hydrocarbon exploration and development. This study employs the gamma-ray (GR) logging data of Well 79 as the primary dataset. Using Acycle V2.8 software implemented on the MATLAB 2020b platform, we conducted a systematic astrochronological analysis. After improving data quality through preprocessing procedures—including outlier removal, linear interpolation, and detrending—we identified significant cyclic signals via spectral analysis. These cyclicities were subsequently validated using multitaper spectral analysis (MTM), sliding spectral analysis, COCO correlation testing, and wavelet analysis. Band-pass filtering was then applied to facilitate sequence subdivision and sedimentation rate estimation. The results reveal well-preserved Milankovitch cyclicity in the Bath–Bajocian Formation of Well 79. The observed cycle thicknesses corresponding to the 405 kyr long eccentricity, 100 kyr short eccentricity, 41 kyr obliquity, and 20 kyr precession are 34.57 m, 8.26 m, 3.44 m, and 1.73 m, respectively, with thickness ratios deviating by less than 5% from the theoretical 20:5:2:1 proportion. Sliding spectral analysis indicates an alternating pattern of increasing and decreasing sedimentation rates. Based on the identified orbital signals, 12 fourth-order sequences and 52 fifth-order cycles were recognized. Sedimentation rates among the three wells range from 6.49 to 12.08 cm/kyr, averaging 9.29 cm/kyr, and exhibit a decreasing trend from west to east. These findings provide a robust astrostratigraphic framework for refined stratigraphic division and reservoir prediction in the study area. Full article

GWASs have successfully identified numerous genetic variants linked to complex traits, but traditional univariate approaches often fail to capture shared genetic architecture across multiple phenotypes. As the scale of genomic data continues to increase, the demand for more efficient multi-phenotype analysis methods has become particularly critical. In addition, the issue of population structure must also be properly addressed to ensure robust and unbiased results. Multivariate methods for multi-phenotype analysis, such as GAMMA, address this by combining linear mixed models with multivariate distance matrix regression to account for population structure; however, since these methods utilize computationally intensive models, developing efficient implementations is essential for practical analysis. Although GAMMA is a well-designed and effective tool, its original implementation relies on multiple programming environments and requires frequent data exchanges between components. These factors increase computational burden and complicate installation and execution for users unfamiliar with programming, making practical applications, particularly for high-dimensional datasets, challenging. Here, we present GAMMA-RAY, a high-performance C++ implementation that streamlines the computational pipeline, leverages parallel processing, and employs efficient matrix operations to achieve substantial reductions in runtime and memory usage. GAMMA-RAY provides both a user-friendly web-based interface for non-programmers and a standalone version for secure local execution. We further applied GAMMA-RAY to a yeast dataset and identified putative trans-eQTLs, in which several variants overlapped with previously reported cis- and trans-eQTLs. In addition, functional enrichment analysis revealed that the associated trans-eGenes are enriched, a conclusion consistently supported by biological annotation resources and underscoring the biological significance of these results. Full article

Pulsar wind nebulae (PWNe), formed when the wind originating from a rapidly rotating neutron star flows out into its surroundings, have now been observed across the electromagnetic spectrum from the radio to the PeV gamma-ray regime. For most of these sources, leptonic processes, where electrons interacting with background photon fields produce high-energy photons through inverse Compton scattering, are believed to be the origin of associated very-high-energy gamma-ray emission. As such, these objects cannot contribute significantly to the galactic hadronic cosmic ray flux at ∼TeV-PeV energies. However, in a handful of cases, the possibility for an energetically sub-dominant hadron population being accelerated and producing very to ultra-high energy gamma-rays through pion decay has not yet been comprehensively excluded. Such scenarios have received renewed attention in the light of recent results from the Large High Altitude Air Shower Observatory (LHAASO). In this review, we explore the theoretical background positing hadronic acceleration in galactic PWNe, considering cases where the hadrons escape from the pulsar surface and/or are accelerated in the wind, as well as potential ‘shock mixing’ scenarios. We also explore current and future possible constraints on a hadronic component to PWNe from observations. Full article