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NMR and SEM fractal dimensions explore shale pore structure taking the Upper Paleozoic shale in Ordos Basin as an example

In this paper, the fractal dimension is calculated by extracting pore parameters from SEM images and NMR experimental data, the pore structure heterogeneity in plane and space is comprehensively discussed, and the relationship between the fractal dimension and shale composition and physical parameters is discussed, providing new ideas for the study of shale reservoirs heterogeneity. Fractal dimension analysis of SEM images reveals that the shale pores of the Shanxi Formation can be divided into organic pores, inter-granular pores and micro-fractures. The average diameter of nano-scale pores is 17.13 nm to 67.65 nm, the surface porosity is 5.75% to 9.37%, and the proportion of micro-fractures is 0.36% to 0.72%, with an average value of 0.53%. The ImageJ Weka Segmentation module in ImageJ software intelligently optimizes the degree of pore recognition in SEM images to ensure accurate extraction and characterization of pore structure features. The fractal dimension of the SEM image was calculated using the Dathe formula for the identified pores: Fractal dimension of bound fluid pore (0.4922 ~ 0.9396) and fractal dimension of movable fluid (2.9727 ~ 2.989), quartz content has a negative correlation with the fractal dimension of bound fluid pores, clay mineral content has a positive correlation with the fractal dimension of bound fluid pores, NMR fractal dimension has no obvious correlation with organic matter content and maturity, and NMR fractal dimension has a negative correlation with porosity, but has no obvious correlation with permeability: indicating that NMR fractal dimension is mainly affected by the composition of shale minerals; The Shanxi Formation shale has a high degree of evolution but the organic matter pores are not developed. The reservoirs space is mainly provided by inter-granular pores and micro-fractures; the inter-granular pores and micro-fractures have high heterogeneity and poor connectivity leads to low permeability.This paper attempts to use the ImageJ Weka Segmentation module to intelligently optimize the identification of pores, which improves the efficiency and accuracy of pore identification. At the same time, it combines the fractal dimension of SEM images and the fractal dimension of NMR images to characterize reservoir characteristics, which provides a basis for quantitatively describing the irregularity of shale pore morphology.

Diagnosis of trigeminal neuralgia based on plain skull radiography using convolutional neural network

Sotatercept and the Clinical Transformation of Pulmonary Arterial Hypertension

MFSD6 is an entry receptor for enterovirus D68

Kramers nodal lines in intercalated TaS2 superconductors

Abstract Kramers degeneracy is one fundamental embodiment of the quantum mechanical nature of particles with half-integer spin under time reversal symmetry. Under the chiral and noncentrosymmetric achiral crystalline symmetries, Kramers degeneracy emerges respectively as topological quasiparticles of Weyl fermions and Kramers nodal lines (KNLs), anchoring the Berry phase-related physics of electrons. However, an experimental demonstration for ideal KNLs well isolated at the Fermi level is lacking. Here, we establish a class of noncentrosymmetric achiral intercalated transition metal dichalcogenide superconductors with large Ising-type spin-orbit coupling, represented by In x TaS2, to host an ideal KNL phase. We provide evidence from angle-resolved photoemission spectroscopy with spin resolution, angle-dependent quantum oscillation measurements, and ab-initio calculations. Our work not only provides a realistic platform for realizing and tuning KNLs in layered materials, but also paves the way for exploring the interplay between KNLs and superconductivity, as well as applications pertaining to spintronics, valleytronics, and nonlinear transport.

Correction: ECP-IEM: Enhancing seasonal crop productivity with deep integrated models

An efficient dual-branch framework via implicit self-texture enhancement for arbitrary-scale histopathology image super-resolution

CEACAM1 as a mediator of B-cell receptor signaling in mantle cell lymphoma

Abstract B-cell receptor (BCR) signaling plays an important role in the pathogenesis of mantle cell lymphoma (MCL), but the detailed mechanisms are not fully understood. In this study, through a genome-wide loss-of-function screen, we identify carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) as an essential factor in a subset of MCL tumors. Our signal transduction studies reveal that CEACAM1 plays a critical role in BCR activation through involvement in two dynamic processes. First, following BCR engagement, CEACAM1 co-localizes to the membrane microdomains (lipid rafts) by anchoring to the F-actin cytoskeleton through the adaptor protein filamin A. Second, CEACAM1 recruits and increases the abundance of SYK in the BCR complex leading to BCR activation. These activities of CEACAM1 require its cytoplasmic tail and the N-terminal ectodomain. Considering that previous studies have extensively characterized CEACAM1 as an ITIM-bearing inhibitory receptor, our findings regarding its activating role are both surprising and context-dependent, which may have implications for BCR-targeting therapies.

Effect of exercise on Fibroblast Growth Factor 21 levels in healthy males and females

Fibroblast growth factor 21 (FGF21) is a metabolic regulator that may increase in circulation following exercise. This study was undertaken to determine if changes to FGF21 post-exercise are dependent on biological sex and exercise modality. Secondary analyses were conducted to determine if the post-exercise rise in FGF21 was associated with upstream signaling factors (glucagon, epinephrine, glucose) and excess post-exercise oxygen consumption (EPOC) response. Following a randomized crossover design, male and female participants completed two, thirty minute exercise protocols – during the steady state (SS) protocol, participants cycled at 70% of VO2peak and during the sprint interval exercise (IE) protocol participants completed six, thirty second “all out” sprints against 7.5% of body weight with four and half minutes of active recovery between sprints. Blood samples were taken at baseline, immediately post-exercise (IPE), and 1-hour post-exercise. Oxygen consumption was monitored continuously throughout the trials. In males, FGF21 levels were increased at 1-hour post-exercise with no difference between conditions; in females, FGF21 levels were unchanged as a result of exercise. Comparison of the post-exercise FGF21 incremental area under the curve revealed that in the SS condition males had a greater FGF21 response than females and that within males the SS condition had a greater response than the IE condition. Exercise significantly increased FGF21 levels in males, but not in females. In males, FGF21 levels were greater in the SS condition than in the IE condition.

Evaluating statistical consistency for the ocean component of earth system models using physics informed convolutional autoencoder

Pharmacological and physiological activation of TGR5 in the NTS lowers food intake by enhancing leptin-STAT3 signaling

Systematic analysis of the global, regional, and national burden of subarachnoid hemorrhage from 1990 to 2021

Subarachnoid hemorrhage (SAH) is characterized by high rates of morbidity, mortality, and disability, which imposes a heavy disease burden on society and families. Incidence, mortality, disability-adjusted life years (DALYs) and their corresponding age-standardized rates (ASRs) and estimated annual percentage changes (EAPCs) of subarachnoid hemorrhage were analyzed by using GBD 2021 data in our study. Data were further stratified by age, sex, and region. Globally, in 2021, there were 697486 (95% UI, 614334795785) new cases of subarachnoid hemorrhage, 352,810 (309015401474) deaths, and 10.64 million (9.39 to 12.12) DALYs. The burden of subarachnoid hemorrhage showed substantial decline from 1990 to 2021. However, the decline in the age-standardized incidence rate was significantly smaller than the declines in the age-standardized mortality rate and age-standardized DALY rate, with the most pronounced downward trend in East Asia but an increase in sub-Saharan Africa, indicating that our prevention strategies require further refinement.

Effect of esketamine on postinduction hypotension in elderly patients undergoing elective noncardiac surgery: a secondary analysis of a randomized clinical trial

Design of circularly polarized phosphorescence materials guided by transfer learning

Is intergenerational elasticity (IGE) a misleading measure of wealth mobility?

Intergenerational elasticity (IGE) is a widely used measure of wealth mobility, represented as the slope in an AR(1) model. While intended to capture the extent of wealth mobility between generations, this paper identifies two key issues with its use. First, the IGE provides meaningful insights only when paired with the model’s convergence value, which is embedded in the intercept. A low IGE, often interpreted as high wealth mobility, does not necessarily imply that every subgroup of the population regresses to the same wealth level. Instead, it reflects the average rate at which the population converges toward the overall mean. Second, a comprehensive understanding of society’s wealth mobility requires a low variance of each parameter across subgroups. A high variance suggests that different subgroups converge to different wealth levels or at different rates. In order to use the IGE as a comparative measure across countries and time periods, we suggest examining both parameters and their variance. This way, a more nuanced and thorough assessment of intergenerational wealth mobility can be achieved.

Neutral point clamped inverter for enhanced grid connected PV system performance based on hexagonal space vector modulation

It’s high TIM-3 for armored CAR-T therapy for B-ALL

Visualizing hot carrier dynamics by nonlinear optical spectroscopy at the atomic length scale

Abstract Probing and manipulating the spatiotemporal dynamics of hot carriers in nanoscale metals is crucial to a plethora of applications ranging from nonlinear nanophotonics to single-molecule photochemistry. The direct investigation of these highly non-equilibrium carriers requires the experimental capability of high energy-resolution (~ meV) broadband femtosecond spectroscopy. When considering the ultimate limits of atomic-scale structures, this capability has remained out of reach until date. Using a two-color femtosecond pump-probe spectroscopy, we present here the real-time tracking of hot carrier dynamics in a well-defined plasmonic picocavity, formed in the tunnel junction of a scanning tunneling microscope (STM). The excitation of hot carriers in the picocavity enables ultrafast all-optical control over the broadband (~ eV) anti-Stokes electronic resonance Raman scattering (ERRS) and the four-wave mixing (FWM) signals generated at the atomic length scale. By mapping the ERRS and FWM signals from a single graphene nanoribbon (GNR), we demonstrate that both signals are more efficiently generated along the edges of the GNR — a manifestation of atomic-scale nonlinear optical microscopy.

MCF-Net: Personnel and machinery detection model for complex downhole drilling environments

Detection of personnel and machinery in the drilling environment of underground coal mines is crucial to the safe production of coal. However, the existing detection models seriously affect the accuracy of the detection models due to the problems of insufficient light and mutual occlusion in the underground. To address these problems, this study proposes a lightweight downhole personnel and machinery detection model (MCF-Net), which aims to solve the above problems while improving the detection accuracy and speed of the model. In this study, YOLOv10 is used as the baseline model, and the PSA module in the backbone network is replaced by designing a lightweight attention mechanism MLBAM, which improves the model’s multi-scale feature extraction capability, enhances the model’s detection performance of mutually occluded objects and reduces the model’s complexity. In the neck network, C2f is reconstructed to get C2f-DualConv based on DualConv, and the group convolution technique is used to extract downhole image features, which can effectively overcome the influence of interference factors such as insufficient illumination in the downhole. Finally, Focaler-CIoU is introduced to reconstruct the IoU loss function, which can accurately locate the downhole objects. In addition, this study conducts experiments on a real downhole borehole dataset, and the results show that compared with the baseline model, MCF-Net improves the accuracy by 0.013 for mAP @ 0.5 and 0.046 for mAP @ 0.5:0.95, reduces the model complexity by 2.27MB for Params and 8.4 for GLOPs, and improves the inference speed by FPS is improved by 11.83 f/s.

Association between post-stroke cognitive impairment and gut microbiota in patients with ischemic stroke

Abstract More than half of stroke survivors have post-stroke cognitive impairment (PSCI). The role of gut microbiota, which can communicate with the brain through the gut-brain axis and affect inflammation, has been receiving increased attention. This cross-sectional study aimed to investigate the association of PSCI, gut microbiota, and inflammatory markers. Patients with first ischemic stroke and complete 3-month and 1-year follow-up data were included and divided into PSCI and non-PSCI groups according to the Montreal Cognitive Assessment (MoCA) score at the above time points. PSCI was defined as having a MoCA less than 23 at either 3 months or 1 year, or a decrease of more than 2 points at both time points. Gut microbiota was assessed by 16 S rRNA gene sequencing and Next Generation Sequencing analysis. The inflammatory markers included interleukins (ILs), eotaxin, G-CSF, TNF-α, IFNγ, sCD40L, and MCP-1. There were 95 ischemic stroke patients (mean age, 60.5 ± 12.1 years; male, 68.4%), including 30 with PSCI and 65 with non-PSCI. In gut microbiota analysis, the PSCI group had a higher abundance of Bacteroidaceae and Clostridiaceae, and the non-PSCI group had a higher abundance of Prevotellaceae, Ruminococcaceae, Oscillibacter, and Faecalibacterium. Ruminococcaceae family under the Oscillospirales order remains significantly different in the two groups in logistic regression model adjusting confounding variables (p = 0.044). In an analysis of inflammatory markers, the plasma levels of eotaxin (p = 0.041) and IL-12p40 (p = 0.031) were significantly higher in the PSCI group than those in the non-PSCI group, and the plasma level of eotaxin was significantly positively correlated with the amount of Clostridiaceae (rho = 0.389, p = 0.045). The study found that PSCI was associated with certain gut microbiota, and these gut microbiotas correlated with the pro-inflammatory marker eotaxin. This suggests that gut microbiota might play a role in the development of cognitive impairment after ischemic stroke.