Cyclic shear behavior of en-echelon joints under constant normal stiffness conditions

To reveal the mechanism of shear failure of en-echelon joints under cyclic loading,such as during earthquakes,we conducted a series of cyclic shear tests of en-echelon joints under constant normal stiffness(CNS)conditions.We analyzed the evolution of shear stress,normal stress,stress path,dilatancy characteristics,and friction coefficient and revealed the failure mechanisms of en-echelon joints at different angles.The results show that the cyclic shear behavior of the en-echelon joints is closely related to the joint angle,with the shear strength at a positive angle exceeding that at a negative angle during shear cycles.As the number of cycles increases,the shear strength decreases rapidly,and the difference between the varying angles gradually decreases.Dilation occurs in the early shear cycles(1 and 2),while contraction is the main feature in later cycles(310).The friction coefficient decreases with the number of cycles and exhibits a more significant sensitivity to joint angles than shear cycles.The joint angle determines the asperities on the rupture surfaces and the block size,and thus determines the subsequent shear failure mode(block crushing and asperity degradation).At positive angles,block size is more greater and asperities on the rupture surface are smaller than at nonpositive angles.Therefore,the cyclic shear behavior is controlled by block crushing at positive angles and asperity degradation at negative angles.

Close relationship between mediators of inflammation and pancreatic cancer:Our experience

In this editorial,we focus specifically on the mechanisms by which pancreatic inflammation affects pancreatic cancer.Cancer of the pancreas remains one of the deadliest cancer types.The highest incidence and mortality rates of pancreatic cancer are found in developed countries.Trends of pancreatic cancer incidence and mortality vary considerably worldwide.A better understanding of the etiology and identification of the risk factors is essential for the primary prevention of this disease.Pancreatic tumors are characterized by a complex microenvironment that orchestrates metabolic alterations and supports a milieu of interactions among various cell types within this niche.In this editorial,we highlight the foundational studies that have driven our understanding of these processes.In our experimental center,we have carefully studied the mechanisms of that link pancreatic inflammation and pancreatic cancer.We focused on the role of mast cells(MCs).MCs contain pro-angiogenic factors,including tryptase,that are associated with increased angiogenesis in various tumors.In this editorial,we address the role of MCs in angiogenesis in both pancreatic ductal adenocarcinoma tissue and adjacent normal tissue.The assessment includes the density of c-Kit receptor-positive MCs,the density of tryptase-positive MCs,the area of tryptasepositive MCs,and angiogenesis in terms of microvascularization density.

主动脉缩窄后远端扩张可能性的血流动力学分析

目的动脉缩窄后远端扩张(PSD)是指在主动脉缩窄(COA)下游区域发生的局部扩张。已有研究分析主动脉缩窄后远端扩张的形成机制。然而,血流动力学的变化如何作用于血管壁使得PSD发生还需要进一步的探讨。本研究的主要目的是利用一系列不同缩窄和扩张程度下的COA和PSD模型揭示主动脉缩窄后远端扩张处的血流动力学差异,评估PSD的发生可能性和破裂风险。方法计算机断层扫描重建正常人主动脉(Normal)。为了分析PSD形成后的血流动力学差异,修改缩窄或(和)扩张区域获得COA和PSD模型。进行血流动力学模拟,计算出动压、涡度、横向壁面剪切应力(Trans WSS)等血流动力学参数。通过修改最小缩窄径、缩窄长度、最大扩张径获得不同缩窄和扩张程度的COA和PSD模型,评估不同程度COA和PSD患者远端(再)扩张的风险。结果高动压、高涡度和高Trans WSS出现并聚集在COA缩窄段远端的凸侧,且在PSD中均有所缓解。动压、涡度、横向壁面剪切应力在远端的均值的顺序均为:COA>PSD>Normal。最小缩窄径越小,均值越大。而不同缩窄长度的均值相差不大。结论缩窄段远端的凸侧受异常血流动力学的影响最大,是扩张形成的主要区域,其受到的高动压、高涡度和高Trans WSS是远端(再)扩张的风险因素。最小缩窄径越小,远端(再)扩张的风险越大。

Satellite Data-based Structural Mapping Reveals Active Panjal Traps Fault(PTF)in Kashmir,NW Himalaya

Exploring the evidence for unidentified earthquake-causing faults in the orogenic zones,and primarily the interior parts(Shah,2013),has been an ongoing quest for centuries(Willis,1923;Baker et al.,1988;Yeats et al.,1992;Wesnousky et al.,1999;Malik et al.,2010;Coudurier-Curveur et al.,2020;Shah et al.,2020).These faults are potentially dangerous due to their unknown risk and deformation budget,two of the most important aspects of mapping and understanding the vulnerability and hazards associated with active faults.

Identifying the best common factor model via exploratory eactor analysis

Currently,there is no solid criterion for judging the quality of the estimators in factor analysis.This paper presents a new evaluation method for exploratory factor analysis that pinpoints an appropriate number of factors along with the best method for factor extraction.The proposed technique consists of two steps:testing the normality of the residuals from the fitted model via the Shapiro-Wilk test and using an empirical quantified index to judge the quality of the factor model.Examples are presented to demonstrate how the method is implemented and to verify its effectiveness.

VARIATIONAL ANALYSIS FOR THE MAXIMAL TIME FUNCTION IN NORMED SPACES

For a general normed vector space,a special optimal value function called a maximal time function is considered.This covers the farthest distance function as a special case,and has a close relationship with the smallest enclosing ball problem.Some properties of the maximal time function are proven,including the convexity,the lower semicontinuity,and the exact characterizations of its subdifferential formulas.

Research progress in tumor angiogenesis and drug resistance in breast cancer

Angiogenesis is considered a hallmark pathophysiological process in tumor development. Aberrant vasculature resulting from tumor angiogenesis plays a critical role in the development of resistance to breast cancer treatments, via exacerbation of tumor hypoxia, decreased effective drug concentrations within tumors, and immune-related mechanisms. Antiangiogenic therapy can counteract these breast cancer resistance factors by promoting tumor vascular normalization. The combination of antiangiogenic therapy with chemotherapy, targeted therapy, or immunotherapy has emerged as a promising approach for overcoming drug resistance in breast cancer. This review examines the mechanisms associated with angiogenesis and the interactions among tumor angiogenesis, the hypoxic tumor microenvironment, drug distribution, and immune mechanisms in breast cancer. Furthermore, this review provides a comprehensive summary of specific antiangiogenic drugs, and relevant studies assessing the reversal of drug resistance in breast cancer. The potential mechanisms underlying these interventions are discussed, and prospects for the clinical application of antiangiogenic therapy to overcome breast cancer treatment resistance are highlighted.

Spatial distribution characteristics of climate-induced landslides in the Eastern Himalayas

Climate warming is constantly causing hydro-meteorological perturbations,especially in high-altitude mountainous regions,which lead to the occurrences of landslides.The impact of climatic variables(i.e.,precipitation and temperature)on the distribution of landslides in the eastern regions of the Himalayas is poorly understood.To address this,the current study analyzes the relationship between the spatial distribution of landslide characteristics and climatic variables from 2013 to 2021.Google Earth Engine(GEE)was employed to make landslide inventories using satellite data.The results show that 2163,6927,and 9601 landslides were heterogeneously distributed across the study area in 2013,2017,and 2021,respectively.The maximum annual temperature was positively correlated with the distribution of landslides,whereas precipitation was found to have a non-significant impact on the landslide distribution.Spatially,most of the landslides occurred in areas with maximum annual precipitation ranging from 800 to 1600 mm and maximum annual temperature above 15℃.However,in certain regions,earthquake disruptions marginally affected the occurrence of landslides.Landslides were highly distributed in areas with elevations ranging between 3000 and 5000 m above sea level,and many landslides occurred near the lower permafrost limit and close to glaciers.The latter indicates that temperature change-induced freeze-thaw action influences landslides in the region.Temperature changes have shown a positive correlation with the number of landslides within elevations,indicating that temperature affects their spatial distribution.Various climate projections suggest that the region will experience further warming,which will increase the likelihood of landslides in the future.Thus,it is crucial to enhance ground observation capabilities and climate datasets to effectively monitor and mitigate landslide risks.

Schur Forms and Normal-Nilpotent Decompositions

Real and complex Schur forms have been receiving increasing attention from the fluid mechanics community recently,especially related to vortices and turbulence.Several decompositions of the velocity gradient tensor,such as the triple decomposition of motion(TDM)and normal-nilpotent decomposition(NND),have been proposed to analyze the local motions of fluid elements.However,due to the existence of different types and non-uniqueness of Schur forms,as well as various possible definitions of NNDs,confusion has spread widely and is harming the research.This work aims to clean up this confusion.To this end,the complex and real Schur forms are derived constructively from the very basics,with special consideration for their non-uniqueness.Conditions of uniqueness are proposed.After a general discussion of normality and nilpotency,a complex NND and several real NNDs as well as normal-nonnormal decompositions are constructed,with a brief comparison of complex and real decompositions.Based on that,several confusing points are clarified,such as the distinction between NND and TDM,and the intrinsic gap between complex and real NNDs.Besides,the author proposes to extend the real block Schur form and its corresponding NNDs for the complex eigenvalue case to the real eigenvalue case.But their justification is left to further investigations.

Nonlinear constitutive models of rock structural plane and their applications

Structural planes play an important role in controlling the stability of rock engineering,and the influence of structural planes should be considered in the design and construction process of rock engineering.In this paper,mechanical properties,constitutive theory,and numerical application of structural plane are studied by a combination method of laboratory tests,theoretical derivation,and program development.The test results reveal the change laws of various mechanical parameters under different roughness and normal stress.At the pre-peak stage,a non-stationary model of shear stiffness is established,and threedimensional empirical prediction models for initial shear stiffness and residual stage roughness are proposed.The nonlinear constitutive models are established based on elasto-plastic mechanics,and the algorithms of the models are developed based on the return mapping algorithm.According to a large number of statistical analysis results,empirical prediction models are proposed for model parameters expressed by structural plane characteristic parameters.Finally,the discrete element method(DEM)is chosen to embed the constitutive models for practical application.The running programs of the constitutive models have been compiled into the discrete element model library.The comparison results between the proposed model and the Mohr-Coulomb slip model show that the proposed model can better describe nonlinear changes at different stages,and the predicted shear strength,peak strain and shear stiffness are closer to the test results.The research results of the paper are conducive to the accurate evaluation of structural plane in rock engineering.

A novel mitigation measure for normal fault-induced deformations on pile-raft systems

Evidence from recent earthquakes has shown destructive consequences of fault-induced permanent ground movement on structures.Such observations have increased the demand for improvements in the design of structures that are dramatically vulnerable to surface fault ruptures.In this study a novel connection between the raft and the piles is proposed to mitigate the hazards associated with a normal fault on pile-raft systems by means of 3D finite element(FE)modeling.Before embarking on the parametric study,the strain-softening constitutive law used for numerical modeling of the sand has been validated against centrifuge test results.The exact location of the fix-head and unconnected pile-raft systems relative to the outcropping fault rupture in the free-field is parametrically investigated,revealing different failure mechanisms.The performance of the proposed connection for protecting the pile-raft system against normal fault-induced deformations is assessed by comparing the geotechnical and structural responses of both types of foundation.The results indicate that the pocket connection can relatively reduce the cap rotation and horizontal and vertical displacements of the raft in most scenarios.The proposed connection decreases the bending moment response of the piles to their bending moment capacity,verging on a fault offset of 0.6 m at bedrock.

On calculating glacial isostatic adjustment

Modeling the earth's fluid and elastic response to the melting of the glaciers of the last ice age is the most direct way to infer the earth's radial viscosity profile.Here,we compare two methods for calculating the viscoelastic response to surface loading.In one,the elastic equation of motion is converted to a viscoelastic equation using the Correspondence Principle.In the other,elastic deformation is added to the viscous flow as isostatic adjustment proceeds.The two modeling methods predict adjustment histories that are different enough to potentially impact the interpretation of the observed glacial isostatic adjustment(GIA).The differences arise from buoyancy and whether fluid displacements are subjected to hydrostatic pre-stress.The methods agree if they use the same equations and boundary conditions.The origin of the differences is determined by varying the boundary conditions and pre-stress application.

Understanding the combustion behavior of electric bicycle batteries and unveiling its relationship with fire extinguishing

In this study,a detailed analysis of the combustion behaviors of the lithium iron phosphate(LFP)and lithium manganese oxide(LMO)batteries used in electric bicycles was conducted.This research included quantitative measurements of the combustion duration,flame height,combustion temperature,heat release rate,and total heat release.The results indicated that LMO batteries exhibited higher combustion temperatures of 600–700°C,flame heights of 70–75 cm,a significantly higher heat release rate of40.1 k W(12 Ah),and a total heat release of 1.04 MJ(12 Ah)compared to LFP batteries with the same capacity.Based on these experimental results,a normalized total heat release(NORTHR)parameter was proposed,demonstrating good universality for batteries with different capacities.Utilizing this parameter,quantitative calculations and optimization of the extinguishing agent dosage were conducted for fires involving these two types of batteries,and the method was validated by extinguishing fires for these two types of battery packs with water-based extinguishing fluids.

NORMALIZED SOLUTIONS FOR THE GENERAL KIRCHHOFF TYPE EQUATIONS

In the present paper,we prove the existence,non-existence and multiplicity of positive normalized solutions(λ_(c),u_(c))∈R×H^(1)(R^(N))to the general Kirchhoff problem-M■,satisfying the normalization constraint f_(R)^N u^2dx=c,where M∈C([0,∞))is a given function satisfying some suitable assumptions.Our argument is not by the classical variational method,but by a global branch approach developed by Jeanjean et al.[J Math Pures Appl,2024,183:44–75]and a direct correspondence,so we can handle in a unified way the nonlinearities g(s),which are either mass subcritical,mass critical or mass supercritical.

Shear mechanical properties and frictional sliding responses of rough joint surfaces under dynamic normal displacement conditions

A comprehensive understanding of the dynamic frictional characteristics in rock joints under high normal load and strong confinement is essential for ensuring the safety of deep engineering construction and mitigating geological disasters.This study conducted shear experiments on rough rock joints under displacement-controlled dynamic normal loads,investigating the shear behaviors of joints across varying initial normal loads,normal loading frequencies,and normal loading amplitudes.Experimental results showed that the peak/valley shear force values increased with initial normal loads and normal loading frequencies but showed an initial increase followed by a decrease with normal loading amplitudes.Dynamic normal loading can either increase or decrease shear strength,while this study demonstrates that higher frequencies lead to enhanced friction.Increased initial normal loading and normal loading frequency result in a gradual decrease in joint roughness coefficient(JRC)values of joint surfaces after shearing.Positive correlations existed between frictional energy dissipation and peak shear forces,while post-shear joint surface roughness exhibited a negative correlation with peak shear forces through linear regression analysis.This study contributes to a better understanding of the sliding responses and shear mechanical characteristics of rock joints under dynamic disturbances.

Effect of lateral stress on frictional properties of a fracture in sandstone

The injection of large volumes of natural gas into geological formations,as is required for underground gas storage,leads to alterations in the effective stress exerted on adjacent faults.This increases the potential for their reactivation and subsequent earthquake triggering.Most measurements of the frictional properties of rock fractures have been conducted under normal and shear stresses.However,faults in gas storage facilities exist within a true three-dimensional(3D)stress state.A double-direct shear experiment on rock fractures under both lateral and normal stresses was conducted using a true triaxial loading system.It was observed that the friction coefficient increases with increasing lateral stress,but decreases with increasing normal stress.The impact of lateral and normal stresses on the response is primarily mediated through their influence on the initial friction coefficient.This allows for an empirical modification of the rate-state friction model that considers the influence of lateral and normal stresses.The impact of lateral and normal stresses on observed friction coefficients is related to the propensity for the production of wear products on the fracture surfaces.Lateral stresses enhance the shear strength of rock(e.g.Mogi criterion).This reduces asperity breakage and the generation of wear products,and consequently augments the friction coefficient of the surface.Conversely,increased normal stresses inhibit dilatancy on the fracture surface,increasing the breakage of asperities and the concomitant production of wear products that promote rolling deformation.This ultimately reduces the friction coefficient.

Extraction of Acoustic Normal Mode Depth Functions Using Range-Difference Method with Vertical Linear Array Data

Data-derived normal mode extraction is an effective method for extracting normal mode depth functions in the absence of marine environmental data.However,when the corresponding singular vectors become nonunique when two or more singular values obtained from the cross-spectral density matrix diagonalization are nearly equal,this results in unsatisfactory extraction outcomes for the normal mode depth functions.To address this issue,we introduced in this paper a range-difference singular value decomposition method for the extraction of normal mode depth functions.We performed the mode extraction by conducting singular value decomposition on the individual frequency components of the signal's cross-spectral density matrix.This was achieved by using pressure and its range-difference matrices constructed from vertical line array data.The proposed method was validated using simulated data.In addition,modes were successfully extracted from ambient noise.

Shear band evolution and acoustic emission characteristics of sandstone containing non-persistent flaws

Direct shear tests were conducted on sandstone specimens under different constant normal stresses to study the coalescence of cracks between non-persistent flaws and the shear sliding characteristics of the shear-formed fault.Digital image correlation and acoustic emission(AE)techniques were used to monitor the evolution of shear bands at the rock bridge area and microcracking behaviors.The experimental results revealed that the shear stresses corresponding to the peak and sub-peak in the stressdisplacement curve are significantly affected by the normal stress.Strain localization bands emerged at both the tip of joints and the rock bridge,and their extension and interaction near the peak stress caused a surge in the AE hit rate and a significant decrease in the AE b value.Short and curvilinear strain bands were detected at low normal stress,while high normal stress generally led to more microcracking events and longer coplanar cracks at the rock bridge area.Furthermore,an increase in normal stress resulted in a higher AE count rate and more energetic AE events during friction sliding along the shearformed fault.It was observed that the elastic energy released during the crack coalescence at the prepeak stage was much greater than that released during friction sliding at the post-peak stage.More than 75%of AE events were located in the low-frequency band(0e100 kHz),and this proportion continued to rise with increasing normal stress.Moreover,more AE events of low AF value and high RA value were observed in specimens subjected to high normal stress,indicating that greater normal stress led to more microcracks of shear nature.

A Deep Learning Framework for Mass-Forming Chronic Pancreatitis and Pancreatic Ductal Adenocarcinoma Classification Based on Magnetic Resonance Imaging

Pancreatic diseases, including mass-forming chronic pancreatitis (MFCP) and pancreatic ductal adenocarcinoma(PDAC), present with similar imaging features, leading to diagnostic complexities. Deep Learning (DL) methodshave been shown to perform well on diagnostic tasks. Existing DL pancreatic lesion diagnosis studies basedon Magnetic Resonance Imaging (MRI) utilize the prior information to guide models to focus on the lesionregion. However, over-reliance on prior information may ignore the background information that is helpful fordiagnosis. This study verifies the diagnostic significance of the background information using a clinical dataset.Consequently, the Prior Difference Guidance Network (PDGNet) is proposed, merging decoupled lesion andbackground information via the Prior Normalization Fusion (PNF) strategy and the Feature Difference Guidance(FDG) module, to direct the model to concentrate on beneficial regions for diagnosis. Extensive experiments inthe clinical dataset demonstrate that the proposed method achieves promising diagnosis performance: PDGNetsbased on conventional networks record an ACC (Accuracy) and AUC (Area Under the Curve) of 87.50% and89.98%, marking improvements of 8.19% and 7.64% over the prior-free benchmark. Compared to lesion-focusedbenchmarks, the uplift is 6.14% and 6.02%. PDGNets based on advanced networks reach an ACC and AUC of89.77% and 92.80%. The study underscores the potential of harnessing background information in medical imagediagnosis, suggesting a more holistic view for future research.

Enhancing Mild Cognitive Impairment Detection through Efficient Magnetic Resonance Image Analysis

Neuroimaging has emerged over the last few decades as a crucial tool in diagnosing Alzheimer’s disease(AD).Mild cognitive impairment(MCI)is a condition that falls between the spectrum of normal cognitive function and AD.However,previous studies have mainly used handcrafted features to classify MCI,AD,and normal control(NC)individuals.This paper focuses on using gray matter(GM)scans obtained through magnetic resonance imaging(MRI)for the diagnosis of individuals with MCI,AD,and NC.To improve classification performance,we developed two transfer learning strategies with data augmentation(i.e.,shear range,rotation,zoom range,channel shift).The first approach is a deep Siamese network(DSN),and the second approach involves using a cross-domain strategy with customized VGG-16.We performed experiments on the Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset to evaluate the performance of our proposed models.Our experimental results demonstrate superior performance in classifying the three binary classification tasks:NC vs.AD,NC vs.MCI,and MCI vs.AD.Specifically,we achieved a classification accuracy of 97.68%,94.25%,and 92.18%for the three cases,respectively.Our study proposes two transfer learning strategies with data augmentation to accurately diagnose MCI,AD,and normal control individuals using GM scans.Our findings provide promising results for future research and clinical applications in the early detection and diagnosis of AD.