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.

The Disintegration of a Floating Ferrofluid Layer into an Ordered Drop System in a Vertical Magnetic Field

Magnetic fluids,also known as ferrofluids,are versatile functional materials with a wide range of applications.These applications span from industrial uses such as vacuum seals,actuators,and acoustic devices to medical uses,including serving as contrast agents for magnetic resonance imaging(MRI),delivering medications to specific locations within the body,and magnetic hyperthermia for cancer treatment.The use of a non-wettable immiscible liquid substrate to support a layer of magnetic fluid opens up new possibilities for studying various fluid flows and related instabilities in multi-phase systems with both a free surface and an interface.The presence of two deformable boundaries within a ferrofluid layer significantly reduces the critical magnetic field strength required to transform the layer into an organized system of drops or polygonal figures evolving according to the intensity,frequency and direction of the considered magnetic field.This paper experimentally investigates this problem by assuming a uniform magnetic field perpendicular to the surface.This specific subject has not been previously explored experimentally.The critical magnetic field intensity required to destabilize the ferrofluid layer is determined based on the layer’s thickness and the fluid’s initial magnetic susceptibility.It is demonstrated that the critical magnetic field strength needed to disrupt the initially continuous ferrofluid layer increases with the layer’s thickness.Conversely,an increase in the ferrofluid’s magnetic susceptibility results in a decrease in the critical magnetic field strength.The emerging droplet structures are analyzed in terms of the number of drops,their size,and the periodicity of their arrangement.The number of droplets formed depends on the initial thickness of the layer,the presence or absence of a stable rupture in the upper layer,and the rate at which the magnetic field strength is increased to the critical value.A characteristic viscous time is proposed to evaluate the decomposition of the ferrofluid layer,which depends on the duration of the magnetic field’s application.The experimental data on the instability of a ferrofluid layer on a liquid substrate are compared with the theoretical results from the study of“magnetic fluid sandwich structures”conducted by Rannacher and Engel.This comparison highlights the similarities and differences between experimental observations and theoretical predictions,providing a deeper understanding of the behavior of ferrofluid layers under the influence of magnetic fields.

MULTIPLICITY OF NORMALIZED SOLUTIONS FOR THE FRACTIONAL SCHR?DINGER-POISSON SYSTEM WITH DOUBLY CRITICAL GROWTH

In this paper,we are concerned with solutions to the fractional Schrodinger-Poisson system■ with prescribed mass ∫_(R^(3))|u|^(2)dx=a^(2),where a> 0 is a prescribed number,μ> 0 is a paremeter,s ∈(0,1),2 <q <2_(s)^(*),and 2_(s)^(*)=6/(3-2s) is the fractional critical Sobolev exponent.In the L2-subcritical case,we show the existence of multiple normalized solutions by using the genus theory and the truncation technique;in the L^(2)-supercritical case,we obtain a couple of normalized solutions by developing a fiber map.Under both cases,to recover the loss of compactness of the energy functional caused by the doubly critical growth,we need to adopt the concentration-compactness principle.Our results complement and improve upon some existing studies on the fractional Schrodinger-Poisson system with a nonlocal critical term.

Synergizing Wind,Solar,and Biomass Power:Ranking Analysis of Off-Grid System for Different Weather Conditions of Iran

Nowadays,the use of renewable energies,especially wind,solar,and biomass,is essential as an effective solution to address global environmental and economic challenges.Therefore,the current study examines the energy-economic-environmental analysis of off-grid electricity generation systems using solar panels,wind turbines,and biomass generators in various weather conditions in Iran.Simulations over 25 years were conducted using HOMER v2.81 software,aiming to determine the potential of each region and find the lowest cost of electricity production per kWh.In the end,to identify the most suitable location,the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)method was employed to rank different stations based on simulation output parameters and some other influential factors.Considering the evaluation of various parameters,the stations in Yazd,Marand,and Dezful achieved the best results,while the stations in Ramsar,Shahrekord,and Gonbad presented the least favorable outcomes.In Yazd,the wind turbine is an economic priority,and a 100 kW wind turbine is utilized in the optimal system.In Yazd,where the simultaneous use of renewable energies is most prominent,the lowest pollutant production occurred with a quantity of 1174 kg/year.Annual energy losses are highest in Jask station and lowest in Yazd.

Fuzzy Multi-Criteria Decision Support System for the Best Anti-Aging Treatment Selection Process through Normal Wiggly Hesitant Fuzzy Sets

This socialized environment among educated and developed people causes themto focusmore on their appearance and health,which turns them towards medical-related treatments,leading us to discuss anti-aging treatment methods for each age group,particularly for urban people who are interested in this.Some anti-aging therapies are used to address the alterations brought on by aging in human life without the need for surgery or negative effects.Five anti-aging therapies such as microdermabrasion or dermabrasion,laser resurfacing anti-aging skin treatments,chemical peels,dermal fillers for aged skin,and botox injections are considered in this study.Based on the criteria of safety risk,investment cost,customer happiness,and side effects,the optimal alternative is picked.As a result,a NormalWiggly Hesitant Pythagorean Fuzzy Set(NWHPFS)is constructed and used in Multi-Criteria Decision-Making(MCDM)using traditional wavy mathematical approaches.The entropy approach is utilized to determine weight values,and the Normal Wiggly Hesitant Pythagorean-VlseKriterijumska Optimizacija I Kompromisno Resenje(NWHPF-VIKOR)method is utilized to rank alternatives using MCDM methodologies.Sensitivity analysis and comparative analysis were performed to ensure the robustness and reliability of the proposed method.The smart final choice will undoubtedly assist Decision Makers(DM)in making the right judgments,and the MCDM approach will undoubtedly assist individuals in understanding the medicine.

Rheological Characterization of Systems with Plastic Flow Behavior

Model suspensions with plastic flow behavior were investigated rheologically.Shear stress and first normal stress difference were measured simultaneously with shear flow start-up experiments.After the shear deformation is stopped,the stress relaxation begins,residual shear stress can appear.The relative residual shear stressτRR is the ratio of the residual shear stress to the steady state shear stress.The relative residual shear stress is considered as a measure of the structure of the system.In the case ofτRR=0.98,we assume that an elastic to plastic deformation is occurred,which is the yield point.The system with 7.5%Aerosil 380 has achieved withτRR=0.95 in the first approximation the transition to plastic flow,this is the yield point for the system,with a yield stress of 23 Pa.This is the only one known system with yield point.The systems withτRR>0.30 andτRR<0.95 at the first point,have no transition from elastic to plastic flow,but the structure is strongly destroyed.Analogous to the above,the shear stress at this point will be called yield stress.One requirement is that the start-up experiment is determined with a very low shear rate¾0.00071/s or 0.000961/s.The associated normal stress to the yield stress is called normal yield stress.The dependence of the normal stress of the systems with Aerosil 380 on the shear stress reached,after a short increase/decrease in the values,the straight line of the normal stress/shear stress of the liquid phase M20000.A linear relationship between normal stress and shear stress was found in the systems with Bentone 27 in Araldite GY260.With a certain measured normal stress/shear stress point,you can draw a straight line with 45°in the double logarithmic plot¾a way to receive the normal stress/shear stress points.

Selection and Validation of Reference Genes for Normalization of RT-qPCR Analysis in Developing or Abiotic-Stressed Tissues of Loquat (Eriobotrya japonica)

Loquat(Eriobotrya japonica Lindl.)is a subtropical evergreen fruit tree that produces fruits with abundant nutrients and medicinal components.Confirming suitable reference genes for a set of loquat samples before qRT-PCR experiments is essential for the accurate quantification of gene expression.In this study,eight candidate reference genes were selected from our previously published RNA-seq data,and primers for each candidate reference gene were designed and evaluated.The Cq values of the candidate reference genes were calculated by RT-qPCR in 31 different loquat samples,including 12 subgroups of developing or abiotic-stressed tissues.Different combinations of stable reference genes were screened according to a comprehensive rank,which was synthesized from the results of four algorithms,including the geNorm,NormFinder,BestKeeper andΔCt methods.The screened reference genes were verified by normalizing EjLGA1 in each subgroup.The obtained suitable combinations of reference genes for accurate normalization were GAPDH,EF1αand ACT for floral development;GAPDH,UBCE and ACT for fruit setting;EF1α,GAPDH and eIF2B for fruit ripening;ACT,EF1αand UBCE for leaves under heat stress;eIF2B,UBCE and EF1αfor leaves under freezing stress;EF1α,TUA and UBCE for leaves under salt stress;ACT,EF1αand eIF2B for immature pulp under freezing stress;ACT,UBCE and eIF2B for immature seeds under freezing stress;EF1α,eIF2B and UBCE for both immature pulp and seeds under freezing stress;UBCE,TUB and TUA for red-fleshed fruits under cold-storage stress;eIF2B,RPS3 and TUB for white-fleshed fruits under coldstorage stress;and eIF2B,UBCE and RPS3 for both red-and white-fleshed fruits under cold-storage stress.This study obtained different combinations of stable reference genes for accurate normalization in twelve subgroups of developing or abiotic-stressed tissues in loquat.To our knowledge,this is the first report to obtain stable reference genes for normalizing gene expression of abiotic-stressed tissues in E.japonica.The use of the three most stable reference genes could increase the reliability of future quantification experiments.

Secrecy sum-rate analysis of massive MIMO systems under dual-threat attacks using normalization methods

Massive Multiple Input Multiple Output(MIMO)has been considered as an emerging technology to enhance the spectral and energy efficiency for the upcoming wireless communication systems.This paper derives a closedform approximation for the Ergodic Achievable Secrecy Sum-Rate(EASSR)by considering the joint impact of eavesdroppers and jammers.Two widely used linear precoding techniques,Zero-Forcing(ZF)and Maximum Ratio Transmission(MRT),were used in conjunction with matrix and vector normalization to analyze the secrecy performance.Closed-form expressions are used to explain how the secrecy performance is affected when using the ZF and MRT precoding in the eavesdropping and jamming attack models.We also analyze and compare the performances of different combinations of normalization method and precoding technique in various scenarios.From the analytical expressions and simulation results,we observe that the vector and matrix normalization perform better for the ZF precoding than for the MRT precoding in high Signal-to-Noise Ratio(SNR)scenarios.However,in low SNR,the MRT with matrix normalization outperforms the ZF with vector normalization regardless of the number of users in the system.Further,we observe that the MRT fails to serve more than two users in high SNR scenario.Numerical results obtained from Monte Carlo simulation are used to corroborate the accuracy of the asymptotic secrecy analysis.

A REVERSED-FRAME NORMALIZATION DESIGN OF ROBUST FLIGHT CONTROL SYSTEM

In this paper, a discussion is devoted to the theory and method of a reversed-frame normalization design to robust flight control system. The robust stability theory of the normal transfer function matrix with the same characteristic gain loci is proved. An example of flight control system design shows the application and advantage of this method.

Robust Radiometric Normalization of the near Equatorial Satellite Images Using Feature Extraction and Remote Sensing Analysis

Relative radiometric normalization (RRN) minimizes radiometric differences among images caused by inconsistencies of acquisition conditions rather than changes in surface. Scale invariant feature transform (SIFT) has the ability to automatically extract control points (CPs) and is commonly used for remote sensing images. However, its results are mostly inaccurate and sometimes contain incorrect matching caused by generating a small number of false CP pairs. These CP pairs have high false alarm matching. This paper presents a modified method to improve the performance of SIFT CPs matching by applying sum of absolute difference (SAD) in a different manner for the new optical satellite generation called near-equatorial orbit satellite and multi-sensor images. The proposed method, which has a significantly high rate of correct matches, improves CP matching. The data in this study were obtained from the RazakSAT satellite a new near equatorial satellite system. The proposed method involves six steps: 1) data reduction, 2) applying the SIFT to automatically extract CPs, 3) refining CPs matching by using SAD algorithm with empirical threshold, and 4) calculation of true CPs intensity values over all image’ bands, 5) preforming a linear regression model between the intensity values of CPs locate in reverence and sensed image’ bands, 6) Relative radiometric normalization conducting using regression transformation functions. Different thresholds have experimentally tested and used in conducting this study (50 and 70), by followed the proposed method, and it removed the false extracted SIFT CPs to be from 775, 1125, 883, 804, 883 and 681 false pairs to 342, 424, 547, 706, 547, and 469 corrected and matched pairs, respectively.

The influence of lipid-extraction on theδ^(13)C of mesopelagic and demersal fish in the South China Sea:modification and application of lipid normalization models

Mesopelagic fish,the most important daily vertically migrating community in the oceans,are characterized by high lipid content which may obscure the interpretation of stable isotopes analysis.Demersal fish,which are important consumers in the food web dominated by mesopelagic fish,also have a high lipid content.Here we collected 127 fish samples from the South China Sea and evaluated the effect of lipid contents on△δ^(13)C of mesopelagic and demersal fish.In lipid-extracted mesopelagic fish,the C/N content ratio(<5.5)shows a clear correlation withΔδ^(13)C(the offset of bulk and lipid-extractedδ^(13)C values),especially in non-migratory and semi-migratory species;these values were less correlation in demersal fish.Based on our results,we suggest that mesopelagic and demersal fish in different regions of the South China Sea should be studied separately using appropriate correction models and less fit for the traditional model.Moreover,the C/N content ratio should be used cautiously for establishing the lipid normalization model,especially for the fish in migratory mesopelagic fish and demersal fish.Our results also reveal that mesopelagic fish across nearby regions could be analyzed together.The new models described here can be applied in future studies of mesopelagic and demersal fish in the South China Sea.

Supervised Feature Learning for Offline Writer Identification Using VLAD and Double Power Normalization

As an indispensable part of identity authentication,offline writer identification plays a notable role in biology,forensics,and historical document analysis.However,identifying handwriting efficiently,stably,and quickly is still challenging due to the method of extracting and processing handwriting features.In this paper,we propose an efficient system to identify writers through handwritten images,which integrates local and global features from similar handwritten images.The local features are modeled by effective aggregate processing,and global features are extracted through transfer learning.Specifically,the proposed system employs a pre-trained Residual Network to mine the relationship between large image sets and specific handwritten images,while the vector of locally aggregated descriptors with double power normalization is employed in aggregating local and global features.Moreover,handwritten image segmentation,preprocessing,enhancement,optimization of neural network architecture,and normalization for local and global features are exploited,significantly improving system performance.The proposed system is evaluated on Computer Vision Lab(CVL)datasets and the International Conference on Document Analysis and Recognition(ICDAR)2013 datasets.The results show that it represents good generalizability and achieves state-of-the-art performance.Furthermore,the system performs better when training complete handwriting patches with the normalization method.The experimental result indicates that it’s significant to segment handwriting reasonably while dealing with handwriting overlap,which reduces visual burstiness.

THE EXISTENCE OF GROUND STATE NORMALIZED SOLUTIONS FOR CHERN-SIMONS-SCHRODINGER SYSTEMS

In this paper,we study normalized solutions of the Chern-Simons-Schrödinger system with general nonlinearity and a potential in H^(1)(ℝ^(2)).When the nonlinearity satisfies some general 3-superlinear conditions,we obtain the existence of ground state normalized solutions by using the minimax procedure proposed by Jeanjean in[L.Jeanjean,Existence of solutions with prescribed norm for semilinear elliptic equations,Nonlinear Anal.(1997)].

基于TZ Normalization规整的话者确认阈值选取

针对说话人确认中,各目标话者模型输出评分分布不一致而导致系统确认阈值设置的困难,本文采取了通过评分规整确定系统最小检测代价函数(DCF)确认阈值的方法。在分析了已有的两种评分规整方法Z norm a l-ization和T norm a lization的基础上,提出了一种结合两者优点的组合规整方法——TZ norm a lization,并据此给出了一种阈值动态修正方法,有效地提高了系统的性能和阈值选取的鲁棒性。对历年的N IST(手机电话语音)评测语料库进行了实验,表明了该方法的有效性。

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。

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.

Characteristics of laser-induced breakdown spectroscopy of liquid slag

Rapid online analysis of liquid slag is essential for optimizing the quality and energy efficiency of steel production. To investigate the key factors that affect the online measurement of refined slag using laser-induced breakdown spectroscopy(LIBS), this study examined the effects of slag composition and temperature on the intensity and stability of the LIBS spectra. The experimental temperature was controlled at three levels: 1350℃, 1400℃, and 1450℃. The results showed that slag composition and temperature significantly affected the intensity and stability of the LIBS spectra. Increasing the Fe content and temperature in the slag reduces its viscosity, resulting in an enhanced intensity and stability of the LIBS spectra. Additionally, 42 refined slag samples were quantitatively analyzed for Fe, Si, Ca, Mg, Al, and Mn at 1350℃, 1400℃, and 1450℃.The normalized full spectrum combined with partial least squares(PLS) quantification modeling was used, using the Ca Ⅱ 317.91 nm spectral line as an internal standard. The results show that using the internal standard normalization method can significantly reduce the influence of spectral fluctuations. Meanwhile, a temperature of 1450℃ has been found to yield superior results compared to both 1350℃ and 1400℃, and it is advantageous to conduct a quantitative analysis of the slag when it is in a “water-like” state with low viscosity.

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.