An inverse analysis of fluid flow through granular media using differentiable lattice Boltzmann method

This study presents a method for the inverse analysis of fluid flow problems.The focus is put on accurately determining boundary conditions and characterizing the physical properties of granular media,such as permeability,and fluid components,like viscosity.The primary aim is to deduce either constant pressure head or pressure profiles,given the known velocity field at a steady-state flow through a conduit containing obstacles,including walls,spheres,and grains.The lattice Boltzmann method(LBM)combined with automatic differentiation(AD)(AD-LBM)is employed,with the help of the GPU-capable Taichi programming language.A lightweight tape is used to generate gradients for the entire LBM simulation,enabling end-to-end backpropagation.Our AD-LBM approach accurately estimates the boundary conditions for complex flow paths in porous media,leading to observed steady-state velocity fields and deriving macro-scale permeability and fluid viscosity.The method demonstrates significant advantages in terms of prediction accuracy and computational efficiency,making it a powerful tool for solving inverse fluid flow problems in various applications.

Enhanced Differentiable Architecture Search Based on Asymptotic Regularization

In differentiable search architecture search methods,a more efficient search space design can significantly improve the performance of the searched architecture,thus requiring people to carefully define the search space with different complexity according to various operations.Meanwhile rationalizing the search strategies to explore the well-defined search space will further improve the speed and efficiency of architecture search.With this in mind,we propose a faster and more efficient differentiable architecture search method,AllegroNAS.Firstly,we introduce a more efficient search space enriched by the introduction of two redefined convolution modules.Secondly,we utilize a more efficient architectural parameter regularization method,mitigating the overfitting problem during the search process and reducing the error brought about by gradient approximation.Meanwhile,we introduce a natural exponential cosine annealing method to make the learning rate of the neural network training process more suitable for the search procedure.Moreover,group convolution and data augmentation are employed to reduce the computational cost.Finally,through extensive experiments on several public datasets,we demonstrate that our method can more swiftly search for better-performing neural network architectures in a more efficient search space,thus validating the effectiveness of our approach.

A Set of Almost Automorphic Functions and Applications

For a set S of real numbers, we introduce the concept of S-almost automorphic functions valued in a Banach space. It generalizes in particular the space of Z-almost automorphic functions. Considering the space of S-almost automorphic functions, we give sufficient conditions of the existence and uniqueness of almost automorphic solutions of a differential equation with a piecewise constant argument of generalized type. This is done using the Banach fixed point theorem.

Astrocytic endothelin-1 overexpression impairs learning and memory ability in ischemic stroke via altered hippocampal neurogenesis and lipid metabolism

Vascular etiology is the second most prevalent cause of cognitive impairment globally.Endothelin-1,which is produced and secreted by endothelial cells and astrocytes,is implicated in the pathogenesis of stroke.However,the way in which changes in astrocytic endothelin-1 lead to poststroke cognitive deficits following transient middle cerebral artery occlusion is not well understood.Here,using mice in which astrocytic endothelin-1 was overexpressed,we found that the selective overexpression of endothelin-1 by astrocytic cells led to ischemic stroke-related dementia(1 hour of ischemia;7 days,28 days,or 3 months of reperfusion).We also revealed that astrocytic endothelin-1 overexpression contributed to the role of neural stem cell proliferation but impaired neurogenesis in the dentate gyrus of the hippocampus after middle cerebral artery occlusion.Comprehensive proteome profiles and western blot analysis confirmed that levels of glial fibrillary acidic protein and peroxiredoxin 6,which were differentially expressed in the brain,were significantly increased in mice with astrocytic endothelin-1 overexpression in comparison with wild-type mice 28 days after ischemic stroke.Moreover,the levels of the enriched differentially expressed proteins were closely related to lipid metabolism,as indicated by Kyoto Encyclopedia of Genes and Genomes pathway analysis.Liquid chromatography-mass spectrometry nontargeted metabolite profiling of brain tissues showed that astrocytic endothelin-1 overexpression altered lipid metabolism products such as glycerol phosphatidylcholine,sphingomyelin,and phosphatidic acid.Overall,this study demonstrates that astrocytic endothelin-1 overexpression can impair hippocampal neurogenesis and that it is correlated with lipid metabolism in poststroke cognitive dysfunction.

Diagnosis of poorly differentiated adenocarcinoma of the stomach by confocal laser endomicroscopy:A case report

BACKGROUND In recent years,confocal laser endomicroscopy(CLE)has become a new endoscopic imaging technology at the microscopic level,which is extensively performed for real-time in vivo histological examination.CLE can be performed to distinguish benign from malignant lesions.In this study,we diagnosed using CLE an asymptomatic patient with poorly differentiated gastric adenocarcinoma.CASE SUMMARY A 63-year-old woman was diagnosed with gastric mucosal lesions,which may be gastric cancer,in the small curvature of the stomach by gastroscopy.She consented to undergo CLE for morphological observation of the gastric mucosa.Through the combination of CLE diagnosis and postoperative pathology,the intraoperative CLE diagnosis was considered to be reliable.According to our experience,CLE can be performed as the first choice for the diagnosis of gastric cancer.CONCLUSION CLE has several advantages over pathological diagnosis.We believe that CLE has great potential in the diagnosis of benign and malignant gastric lesions.

Crosstalk between Wnt and bone morphogenetic protein signaling during osteogenic differentiati

Mesenchymal stem cells(MSCs)originate from many sources,including the bone marrow and adipose tissue,and differentiate into various cell types,such as osteoblasts and adipocytes.Recent studies on MSCs have revealed that many transcription factors and signaling pathways control osteogenic development.Osteogenesis is the process by which new bones are formed;it also aids in bone remodeling.Wnt/β-catenin and bone morphogenetic protein(BMP)signaling pathways are involved in many cellular processes and considered to be essential for life.Wnt/β-catenin and BMPs are important for bone formation in mammalian development and various regulatory activities in the body.Recent studies have indicated that these two signaling pathways contribute to osteogenic differen-tiation.Active Wnt signaling pathway promotes osteogenesis by activating the downstream targets of the BMP signaling pathway.Here,we briefly review the molecular processes underlying the crosstalk between these two pathways and explain their participation in osteogenic differentiation,emphasizing the canonical pathways.This review also discusses the crosstalk mechanisms of Wnt/BMP signaling with Notch-and extracellular-regulated kinases in osteogenic differentiation and bone development.

Spatial-temporal differentiation and influencing factors of rural settlements in mountainous areas: an example of Liangshan Yi Autonomous Prefecture, Southwestern China

Rural settlement is the basic spatial unit for compact communities in rural area. Scientific exploration of spatial-temporal differentiation and its influencing factors is the premise of spatial layout rationalization. Based on land use data of Liangshan Yi Autonomous Prefecture(hereinafter referred to as Liangshan Prefecture) in Sichuan Province, China from 1980 to 2020, compactness index, fractal dimension, imbalance index, location entropy and the optimal parameters-based geographical detector(OPGD) model are used to analyze the spatial-temporal evolution of the morphological characteristics of rural settlements, and to explore the influence of natural geographical factors, socioeconomic factors, and policy factors on the spatial differentiation of rural settlements. The results show that:(1) From 1980 to 2020, the rural settlements area in Liangshan Prefecture increased by 15.96 km^(2). In space, the rural settlements are generally distributed in a local aggregation, dense in the middle and sparse around the periphery. In 2015, the spatial density and expansion index of rural settlements reached the peak.(2) From 1980 to 2020, the compactness index decreased from 0.7636 to 0.7496, the fractal dimension increased from 1.0283 to 1.0314, and the fragmentation index decreased from 0.1183 to 0.1047. The spatial morphological structure of rural settlements tended to be loose, the shape contour tended to be complex, the degree of fragmentation decreased, and the spatial distribution was significantly imbalanced.(3) The results of OPGD detection in 2015 show that the influence of each factor is slope(0.2371) > traffic accessibility(0.2098) > population(0.1403) > regional GDP(0.1325) > elevation(0.0987) > poverty alleviation(0). The results of OPGD detection in 2020 show that the influence of each factor is slope(0.2339) > traffic accessibility(0.2198) > population(0.1432) > regional GDP(0.1219) > poverty alleviation(0.0992) > elevation(0.093). Natural geographical factors(slope and elevation) are the basic factors affecting the spatial distribution of rural settlements, and rural settlements are widely distributed in the river valley plain and the second half mountain area. Socioeconomic factors(traffic accessibility, population, and regional GDP) have a greater impact on the spatial distribution of rural settlements, which is an important factor affecting the spatial distribution of rural settlements. Policy factors such as poverty alleviation relocation have an indispensable impact on the spatial distribution of rural settlements. The research results can provide decisionmaking basis for the spatial arrangement of rural settlements in Liangshan Prefecture, and optimize the implementation of rural revitalization policies.

Multiple Uplift and Exhumation of the Southeastern Tibetan Plateau:Evidence from Low-Temperature Thermochronology

Since the Cenozoic,the Tibetan Plateau has experienced large-scale uplift and outgrowth due to the India-Asia collision.However,the mechanism and timing of these tectonic processes still remain debated.Here,using apatite fission track dating and inverse thermal modeling,we explore the mechanism of different phases of rapid cooling for different batholiths and intrusions in the southeastern Tibetan Plateau.In contrast to previous views,we find that the coeval granitic batholith exposed in the same tectonic zone experienced differential fast uplift in different sites,indicating that the present Tibetan Plateau was the result of differential uplift rather than the entire lithosphere uplift related to lithospheric collapse during Cenozoic times.In addition,we also suggest that the 5-2 Ma mantle-related magmatism should be regarded as the critical trigger for the widely coeval cooling event in the southeastern Tibetan Plateau,because it led to the increase in atmospheric CO_(2)level and a hotter upper crust than before,which are efficient for suddenly fast rock weathering and erosion.Finally,we propose that the current landform of the southeastern Tibetan Plateau was the combined influences of tectonic and climate.

Transcriptional regulation in the development and dysfunction of neocortical projection neurons

Glutamatergic projection neurons generate sophisticated excitatory circuits to integrate and transmit information among different cortical areas,and between the neocortex and other regions of the brain and spinal cord.Appropriate development of cortical projection neurons is regulated by certain essential events such as neural fate determination,proliferation,specification,differentiation,migration,survival,axonogenesis,and synaptogenesis.These processes are precisely regulated in a tempo-spatial manner by intrinsic factors,extrinsic signals,and neural activities.The generation of correct subtypes and precise connections of projection neurons is imperative not only to support the basic cortical functions(such as sensory information integration,motor coordination,and cognition)but also to prevent the onset and progression of neurodevelopmental disorders(such as intellectual disability,autism spectrum disorders,anxiety,and depression).This review mainly focuses on the recent progress of transcriptional regulations on the development and diversity of neocortical projection neurons and the clinical relevance of the failure of transcriptional modulations.

Risk stratification for radioactive iodine refractoriness using molecular alterations in distant metastatic differentiated thyroid cancer

Objective: Patients with radioactive iodine-refractory differentiated thyroid cancer(RAIR-DTC) are often diagnosed with delay and constrained to limited treatment options. The correlation between RAI refractoriness and the underlying genetic characteristics has not been extensively studied.Methods: Adult patients with distant metastatic DTC were enrolled and assigned to undergo next-generation sequencing of a customized 26-gene panel(Thyro Lead). Patients were classified into RAIR-DTC or non-RAIR groups to determine the differences in clinicopathological and molecular characteristics. Molecular risk stratification(MRS) was constructed based on the association between molecular alterations identified and RAI refractoriness, and the results were classified as high, intermediate or low MRS.Results: A total of 220 patients with distant metastases were included, 63.2% of whom were identified as RAIRDTC. Genetic alterations were identified in 90% of all the patients, with BRAF(59.7% vs. 17.3%), TERT promoter(43.9% vs. 7.4%), and TP53 mutations(11.5% vs. 3.7%) being more prevalent in the RAIR-DTC group than in the non-RAIR group, except for RET fusions(15.8% vs. 39.5%), which had the opposite pattern. BRAF and TERT promoter are independent predictors of RAIR-DTC, accounting for 67.6% of patients with RAIR-DTC. MRS was strongly associated with RAI refractoriness(P<0.001), with an odds ratio(OR) of high to low MRS of 7.52 [95%confidence interval(95% CI), 3.96-14.28;P<0.001] and an OR of intermediate to low MRS of 3.20(95% CI,1.01-10.14;P=0.041).Conclusions: Molecular alterations were associated with RAI refractoriness, with BRAF and TERT promoter mutations being the predominant contributors, followed by TP53 and DICER1 mutations. MRS might serve as a valuable tool for both prognosticating clinical outcomes and directing precision-based therapeutic interventions.

Cell replacement with stem cell-derived retinal ganglion cells from different protocols

Glaucoma,characterized by a degenerative loss of retinal ganglion cells,is the second leading cause of blindness worldwide.There is currently no cure for vision loss in glaucoma because retinal ganglion cells do not regenerate and are not replaced after injury.Human stem cell-derived retinal ganglion cell transplant is a potential therapeutic strategy for retinal ganglion cell degenerative diseases.In this review,we first discuss a 2D protocol for retinal ganglion cell differentiation from human stem cell culture,including a rapid protocol that can generate retinal ganglion cells in less than two weeks and focus on their transplantation outcomes.Next,we discuss using 3D retinal organoids for retinal ganglion cell transplantation,comparing cell suspensions and clusters.This review provides insight into current knowledge on human stem cell-derived retinal ganglion cell differentiation and transplantation,with an impact on the field of regenerative medicine and especially retinal ganglion cell degenerative diseases such as glaucoma and other optic neuropathies.

Metabolic and proteostatic differences in quiescent and active neural stem cells

Adult neural stem cells are neurogenesis progenitor cells that play an important role in neurogenesis.Therefore,neural regeneration may be a promising target for treatment of many neurological illnesses.The regenerative capacity of adult neural stem cells can be chara cterized by two states:quiescent and active.Quiescent adult neural stem cells are more stable and guarantee the quantity and quality of the adult neural stem cell pool.Active adult neural stem cells are chara cterized by rapid proliferation and differentiation into neurons which allow for integration into neural circuits.This review focuses on diffe rences between quiescent and active adult neural stem cells in nutrition metabolism and protein homeostasis.Furthermore,we discuss the physiological significance and underlying advantages of these diffe rences.Due to the limited number of adult neural stem cells studies,we refe rred to studies of embryonic adult neural stem cells or non-mammalian adult neural stem cells to evaluate specific mechanisms.

Novel Investigation of Stochastic Fractional Differential Equations Measles Model via the White Noise and Global Derivative Operator Depending on Mittag-Leffler Kernel

Because of the features involved with their varied kernels,differential operators relying on convolution formulations have been acknowledged as effective mathematical resources for modeling real-world issues.In this paper,we constructed a stochastic fractional framework of measles spreading mechanisms with dual medication immunization considering the exponential decay and Mittag-Leffler kernels.In this approach,the overall population was separated into five cohorts.Furthermore,the descriptive behavior of the system was investigated,including prerequisites for the positivity of solutions,invariant domain of the solution,presence and stability of equilibrium points,and sensitivity analysis.We included a stochastic element in every cohort and employed linear growth and Lipschitz criteria to show the existence and uniqueness of solutions.Several numerical simulations for various fractional orders and randomization intensities are illustrated.

Construction of an immune-related gene signature for overall survival prediction and immune infiltration in gastric cancer

BACKGROUND Treatment options for patients with gastric cancer(GC)continue to improve,but the overall prognosis is poor.The use of PD-1 inhibitors has also brought benefits to patients with advanced GC and has gradually become the new standard treatment option at present,and there is an urgent need to identify valuable biomarkers to classify patients with different characteristics into subgroups.AIM To determined the effects of differentially expressed immune-related genes(DEIRGs)on the development,prognosis,tumor microenvironment(TME),and treatment response among GC patients with the expectation of providing new biomarkers for personalized treatment of GC populations.METHODS Gene expression data and clinical pathologic information were downloaded from The Cancer Genome Atlas(TCGA),and immune-related genes(IRGs)were searched from ImmPort.DEIRGs were extracted from the intersection of the differentially-expressed genes(DEGs)and IRGs lists.The enrichment pathways of key genes were obtained by analyzing the Kyoto Encyclopedia of Genes and Genomes(KEGGs)and Gene Ontology(GO)databases.To identify genes associated with prognosis,a tumor risk score model based on DEIRGs was constructed using Least Absolute Shrinkage and Selection Operator and multivariate Cox regression.The tumor risk score was divided into high-and lowrisk groups.The entire cohort was randomly divided into a 2:1 training cohort and a test cohort for internal validation to assess the feasibility of the risk model.The infiltration of immune cells was obtained using‘CIBERSORT,’and the infiltration of immune subgroups in high-and low-risk groups was analyzed.The GC immune score data were obtained and the difference in immune scores between the two groups was analyzed.RESULTS We collected 412 GC and 36 adjacent tissue samples,and identified 3627 DEGs and 1311 IRGs.A total of 482 DEIRGs were obtained.GO analysis showed that DEIRGs were mainly distributed in immunoglobulin complexes,receptor ligand activity,and signaling receptor activators.KEGG pathway analysis showed that the top three DEIRGs enrichment types were cytokine-cytokine receptors,neuroactive ligand receptor interactions,and viral protein interactions.We ultimately obtained an immune-related signature based on 10 genes,including 9 risk genes(LCN1,LEAP2,TMSB15A mRNA,DEFB126,PI15,IGHD3-16,IGLV3-22,CGB5,and GLP2R)and 1 protective gene(LGR6).Kaplan-Meier survival analysis,receiver operating characteristic curve analysis,and risk curves confirmed that the risk model had good predictive ability.Multivariate COX analysis showed that age,stage,and risk score were independent prognostic factors for patients with GC.Meanwhile,patients in the low-risk group had higher tumor mutation burden and immunophenotype,which can be used to predict the immune checkpoint inhibitor response.Both cytotoxic T lymphocyte antigen4+and programmed death 1+patients with lower risk scores were more sensitive to immunotherapy.CONCLUSION In this study a new prognostic model consisting of 10 DEIRGs was constructed based on the TME.By providing risk factor analysis and prognostic information,our risk model can provide new directions for immunotherapy in GC patients.

How mesenchymal stem cells transform into adipocytes:Overview of the current understanding of adipogenic differentiation

Mesenchymal stem cells(MSCs)are stem/progenitor cells capable of self-renewal and differentiation into osteoblasts,chondrocytes and adipocytes.The transformation of multipotent MSCs to adipocytes mainly involves two subsequent steps from MSCs to preadipocytes and further preadipocytes into adipocytes,in which the process MSCs are precisely controlled to commit to the adipogenic lineage and then mature into adipocytes.Previous studies have shown that the master transcription factors C/enhancer-binding protein alpha and peroxisome proliferation activator receptor gamma play vital roles in adipogenesis.However,the mechanism underlying the adipogenic differentiation of MSCs is not fully understood.Here,the current knowledge of adipogenic differentiation in MSCs is reviewed,focusing on signaling pathways,noncoding RNAs and epigenetic effects on DNA methylation and acetylation during MSC differentiation.Finally,the relationship between maladipogenic differentiation and diseases is briefly discussed.We hope that this review can broaden and deepen our understanding of how MSCs turn into adipocytes.

Characteristics and control factors of feldspar dissolution in gravity flow sandstone of Chang 7 Member,Triassic Yanchang Formation,Ordos Basin,NW China

To clarify the formation and distribution of feldspar dissolution pores and predict the distribution of high-quality reservoir in gravity flow sandstone of the 7^(th) member of Triassic Yanchang Formation(Chang 7 Member)in the Ordos Basin,thin sections,scanning electron microscopy,energy spectrum analysis,X-ray diffraction whole rock analysis,and dissolution experiments are employed in this study to investigate the characteristics and control factors of feldspar dissolution pores.The results show that:(1)Three types of diagenetic processes are observed in the feldspar of Chang 7 sandstone in the study area:secondary overgrowth of feldspar,replacement by clay and calcite,and dissolution of detrital feldspar.(2)The feldspar dissolution of Chang 7 tight sandstone is caused by organic acid,and is further affected by the type of feldspar,the degree of early feldspar alteration,and the buffering effect of mica debris on organic acid.(3)Feldspars have varying degrees of dissolution.Potassium feldspar is more susceptible to dissolution than plagioclase.Among potassium feldspar,orthoclase is more soluble than microcline,and unaltered feldspar is more soluble than early kaolinized or sericitized feldspar.(4)The dissolution experiment demonstrated that the presence of mica can hinder the dissolution of feldspar.Mica of the same mass has a significantly stronger capacity to consume organic acids than feldspar.(5)Dissolution pores in feldspar of Chang 7 Member are more abundant in areas with low mica content,and they improve the reservoir physical properties,while in areas with high mica content,the number of feldspar dissolution pores decreases significantly.

DNA methylation in poultry:a review

As an important epigenetic modification,DNA methylation is involved in many biological processes such as animal cell differentiation,embryonic development,genomic imprinting and sex chromosome inactivation.As DNA methylation sequencing becomes more sophisticated,it becomes possible to use it to solve more zoological problems.This paper reviews the characteristics of DNA methylation,with emphasis on the research and application of DNA methylation in poultry.

A solution method for decomposing vector fields in Hamilton energy

Hamilton energy,which reflects the energy variation of systems,is one of the crucial instruments used to analyze the characteristics of dynamical systems.Here we propose a method to deduce Hamilton energy based on the existing systems.This derivation process consists of three steps:step 1,decomposing the vector field;step 2,solving the Hamilton energy function;and step 3,verifying uniqueness.In order to easily choose an appropriate decomposition method,we propose a classification criterion based on the form of system state variables,i.e.,type-I vector fields that can be directly decomposed and type-II vector fields decomposed via exterior differentiation.Moreover,exterior differentiation is used to represent the curl of low-high dimension vector fields in the process of decomposition.Finally,we exemplify the Hamilton energy function of six classical systems and analyze the relationship between Hamilton energy and dynamic behavior.This solution provides a new approach for deducing the Hamilton energy function,especially in high-dimensional systems.

ED-Ged:Nighttime Image Semantic Segmentation Based on Enhanced Detail and Bidirectional Guidance

Semantic segmentation of driving scene images is crucial for autonomous driving.While deep learning technology has significantly improved daytime image semantic segmentation,nighttime images pose challenges due to factors like poor lighting and overexposure,making it difficult to recognize small objects.To address this,we propose an Image Adaptive Enhancement(IAEN)module comprising a parameter predictor(Edip),multiple image processing filters(Mdif),and a Detail Processing Module(DPM).Edip combines image processing filters to predict parameters like exposure and hue,optimizing image quality.We adopt a novel image encoder to enhance parameter prediction accuracy by enabling Edip to handle features at different scales.DPM strengthens overlooked image details,extending the IAEN module’s functionality.After the segmentation network,we integrate a Depth Guided Filter(DGF)to refine segmentation outputs.The entire network is trained end-to-end,with segmentation results guiding parameter prediction optimization,promoting self-learning and network improvement.This lightweight and efficient network architecture is particularly suitable for addressing challenges in nighttime image segmentation.Extensive experiments validate significant performance improvements of our approach on the ACDC-night and Nightcity datasets.

Nested Saturated Control of Uncertain Complex Cascade Systems Using Mixed Saturation Levels

This study addresses the problem of global asymptotic stability for uncertain complex cascade systems composed of multiple integrator systems and non-strict feedforward nonlinear systems. To tackle the complexity inherent in such structures, a novel nested saturated control design is proposed that incorporates both constant saturation levels and state-dependent saturation levels. Specifically, a modified differentiable saturation function is proposed to facilitate the saturation reduction analysis of the uncertain complex cascade systems under the presence of mixed saturation levels. In addition, the design of modified differentiable saturation function will help to construct a hierarchical global convergence strategy to improve the robustness of control design scheme. Through calculation of relevant inequalities, time derivative of boundary surface and simple Lyapunov function,saturation reduction analysis and convergence analysis are carried out, and then a set of explicit parameter conditions are provided to ensure global asymptotic stability in the closed-loop systems. Finally, a simplified system of the mechanical model is presented to validate the effectiveness of the proposed method.