Achieving high ductility and low in-plane anisotropy in magnesium alloy through a novel texture design strategy

Texture regulation is a prominent method to modify the mechanical properties and anisotropy of magnesium alloy.In this work,the Mg-1Al-0.3Ca-0.5Mn-0.2Gd(wt.%)alloy sheet with TD-tilted and circular texture was fabricated by unidirectional rolling(UR)and multidirectional rolling(MR)method,respectively.Unlike generating a strong in-plane mechanical anisotropy in conventional TD-tilted texture,the novel circular texture sample possessed a weak in-plane yield anisotropy.This can be rationalized by the similar proportion of soft grains with favorable orientation for basalslip and{10.12}tensile twinning during the uniaxial tension of circular-texture sample along different directions.Moreover,compared with the TD-tilted texture,the circular texture improved the elongation to failure both along the rolling direction(RD)and transverse direction(TD).By quasi-in-situ EBSD-assisted slip trace analysis,higher activation of basal slip was observed in the circular-texture sample during RD tension,contributing to its excellent ductility.When loading along the TD,the TD-tilted texture promoted the activation of{10.12}tensile twins significantly,thus providing nucleation sites for cracks and deteriorating the ductility.This research may shed new insights into the development of formable and ductile Mg alloy sheets by texture modification.

The Mechanism of Cube Texture Formation in Ni-7 at%W Substrate

In order to obtain the sharp cube texture,a new process,the intermediate annealing rolling technique,has been introduced to prepare the Ni7W substrate.In this paper,a cubic texture content up to 98.5%within 10°of the standard cubic orientation is obtained in the final substrate and the influence of this improved rolling technique on the cube texture formation has been discussed.The results show that the increased cube texture in the Ni7W substrate is caused by the optimized deformation texture and the increased nucleated fraction of the cube grains.

SDGNN: Symmetry-Preserving Dual-Stream Graph Neural Networks

Dear Editor,This letter proposes a symmetry-preserving dual-stream graph neural network(SDGNN) for precise representation learning to an undirected weighted graph(UWG). Although existing graph neural networks(GNNs) are influential instruments for representation learning to a UWG, they invariably adopt a unique node feature matrix for illustrating the sole node set of a UWG.

Privacy-Preserving Consensus-Based Distributed Economic Dispatch of Smart Grids via State Decomposition

This paper studies the privacy-preserving distributed economic dispatch(DED)problem of smart grids.An autonomous consensus-based algorithm is developed via local data exchange with neighboring nodes,which covers both the islanded mode and the grid-connected mode of smart grids.To prevent power-sensitive information from being disclosed,a privacy-preserving mechanism is integrated into the proposed DED algorithm by randomly decomposing the state into two parts,where only partial data is transmitted.Our objective is to develop a privacy-preserving DED algorithm to achieve optimal power dispatch with the lowest generation cost under physical constraints while preventing sensitive information from being eavesdropped.To this end,a comprehensive analysis framework is established to ensure that the proposed algorithm can converge to the optimal solution of the concerned optimization problem by means of the consensus theory and the eigenvalue perturbation approach.In particular,the proposed autonomous algorithm can achieve a smooth transition between the islanded mode and the grid-connected mode.Furthermore,rigorous analysis is given to show privacy-preserving performance against internal and external eavesdroppers.Finally,case studies illustrate the feasibility and validity of the developed algorithm.

Crystal plasticity finite element simulations on extruded Mg-10Gd rod with texture gradient

The mechanical properties of an extruded Mg-10Gd sample, specifically designed for vascular stents, are crucial for predicting its behavior under service conditions. Achieving homogeneous stresses in the hoop direction, essential for characterizing vascular stents, poses challenges in experimental testing based on standard specimens featuring a reduced cross section. This study utilizes an elasto-visco-plastic self-consistent polycrystal model(ΔEVPSC) with the predominant twinning reorientation(PTR) scheme as a numerical tool, offering an alternative to mechanical testing. For verification, various mechanical experiments, such as uniaxial tension, compression, notched-bar tension, three-point bending, and C-ring compression tests, were conducted. The resulting force vs. displacement curves and textures were then compared with those based on the ΔEVPSC model. The computational model's significance is highlighted by simulation results demonstrating that the differential hardening along with a weak strength differential effect observed in the Mg-10Gd sample is a result of the interplay between micromechanical deformation mechanisms and deformation-induced texture evolution. Furthermore, the study highlights that incorporating the axisymmetric texture from the as-received material incorporating the measured texture gradient significantly improves predictive accuracy on the strength in the hoop direction. Ultimately, the findings suggest that the ΔEVPSC model can effectively predict the mechanical behavior resulting from loading scenarios that are impossible to realize experimentally, emphasizing its valuable contribution as a digital twin.

A texture-modified dessert with high nutritional value designed for people with dysphagia:effect of refrigeration and frozen storage

Dysphagia is commonly associated with malnutrition and an increased choking risk.To overcome these complications,food designed for people with dysphagia should have an appropriate texture and a high nutritional value.In this study,six formulations of a strawberry dessert enriched in protein(calcium caseinate)and fiber(wheat dextrin or inulin)were developed using different hydrocolloids(xanthan gum,carboxymethyl cellulose or modified starch)to provide desirable texture and stability.Nutritional value was calculated and total phenolic content and antioxidant activity of the samples were analyzed.Back-extrusion test,rheological measurements and sensory analysis were performed in refrigerated and frozen samples to characterize their textural and viscoelastic properties.The high content in protein(14.7 g/100 g)and fiber(7.9-8.7 g/100 g)made possible to use the claims“high protein”and“high fiber”.Phytochemicals supplied by strawberries contributed to the antioxidant properties of the dessert.Loss tangent ranged 0.28-0.35 for all the formulations,indicating a weak gel behavior,which could be considered safe to swallow.The formulations with dextrin in combination with carboxymethyl cellulose or xanthan gum seemed to be less susceptible to structural changes during frozen storage.This work provides insights for the development of a nutrient-dense dessert that meets the requirements of people with dysphagia.

Evolution of microstructure and texture of AZ80 magnesium alloy under hot torsion with constant decreasing temperature rate

Hot torsion tests for AZ80 magnesium alloy were carried out in the temperature range of 380℃-260℃,with a constant decreasing temperature rate of 10℃/s in order to weaken the basal texture and refine the grains.The results indicated that the average grain sizes were refined forming gradient structure with increasing specimen radial position from center(12.2-5.4μm),and that the initial basal texture intensity of the extruded magnesium alloy was weakened from 46.2 to 8.3.Furthermore,the extension twins(ETs)could be disintegrated from the twins forming separated twins with smaller sizes.Interestingly,ETs with the same twin variant intersecting with each other could be coalesced forming grains with similar orientation,while ETs with different twin variants were separated by twins boundaries contributing to grain refinement.Moreover,in addition to the conventional continuous dynamic recrystallized(CDRX)grains with 30˚orientation rotated around C-axis of the parent grains,CDRXed grains with 30˚rotation around a-axis and random rotation axis were also discerned.Besides,the CDRX evolution induced twins were also elaborated,exhibiting the complex competition between CDRX and twining.Hot torsion deformation with constant decreasing temperatures rate is an effective way of grain refinement and texture modification.

Unveiling the rolling texture variations ofα-Mg phases in a dual-phase Mg-Li alloy

LZ91 Mg-Li alloy plates with three types of initial texture were rolled by 70%reduction at both room temperature and 200℃to explore the rolling texture formation ofα-Mg phase.The results showed that the rolling texture is largely affected by the initial texture.All the samples exhibited two main texture components as RD-split double peaks texture and TD-split double peaks texture after large strain rolling.The intensity of the two texture components was strongly influenced by the initial orientation and rolling temperature.Extension twinning altered the large-split non-basal orientation to a near basal one at low rolling strain.The basal orientation induced by twinning is unstable,which finally transmitted to the RD-split texture.The strong TD-split texture formed due to slip-induced orientation transition from its initial orientation.The competition between prismatic and basal slip determined the intensity and tilt angle of the TD-split texture.By increasing the rolling temperature,the TD-split texture component was enhanced in all three samples.Limitation of extension twinning behavior and the promotion of prismatic slip at elevated temperature are the main reasons for the difference in hot and cold rolling texture.

2P3FL:A Novel Approach for Privacy Preserving in Financial Sectors Using Flower Federated Learning

The increasing data pool in finance sectors forces machine learning(ML)to step into new complications.Banking data has significant financial implications and is confidential.Combining users data from several organizations for various banking services may result in various intrusions and privacy leakages.As a result,this study employs federated learning(FL)using a flower paradigm to preserve each organization’s privacy while collaborating to build a robust shared global model.However,diverse data distributions in the collaborative training process might result in inadequate model learning and a lack of privacy.To address this issue,the present paper proposes the imple-mentation of Federated Averaging(FedAvg)and Federated Proximal(FedProx)methods in the flower framework,which take advantage of the data locality while training and guaranteeing global convergence.Resultantly improves the privacy of the local models.This analysis used the credit card and Canadian Institute for Cybersecurity Intrusion Detection Evaluation(CICIDS)datasets.Precision,recall,and accuracy as performance indicators to show the efficacy of the proposed strategy using FedAvg and FedProx.The experimental findings suggest that the proposed approach helps to safely use banking data from diverse sources to enhance customer banking services by obtaining accuracy of 99.55%and 83.72%for FedAvg and 99.57%,and 84.63%for FedProx.

A Cloud-Fog Enabled and Privacy-Preserving IoT Data Market Platform Based on Blockchain

The dynamic landscape of the Internet of Things(IoT)is set to revolutionize the pace of interaction among entities,ushering in a proliferation of applications characterized by heightened quality and diversity.Among the pivotal applications within the realm of IoT,as a significant example,the Smart Grid(SG)evolves into intricate networks of energy deployment marked by data integration.This evolution concurrently entails data interchange with other IoT entities.However,there are also several challenges including data-sharing overheads and the intricate establishment of trusted centers in the IoT ecosystem.In this paper,we introduce a hierarchical secure data-sharing platform empowered by cloud-fog integration.Furthermore,we propose a novel non-interactive zero-knowledge proof-based group authentication and key agreement protocol that supports one-to-many sharing sets of IoT data,especially SG data.The security formal verification tool shows that the proposed scheme can achieve mutual authentication and secure data sharing while protecting the privacy of data providers.Compared with previous IoT data sharing schemes,the proposed scheme has advantages in both computational and transmission efficiency,and has more superiority with the increasing volume of shared data or increasing number of participants.

On dry machining of AZ31B magnesium alloy using textured cutting tool inserts

Magnesium alloys have many advantages as lightweight materials for engineering applications,especially in the fields of automotive and aerospace.They undergo extensive cutting or machining while making products out of them.Dry cutting,a sustainable machining method,causes more friction and adhesion at the tool-chip interface.One of the promising solutions to this problem is cutting tool surface texturing,which can reduce tool wear and friction in dry cutting and improve machining performance.This paper aims to investigate the impact of dimple textures(made on the flank face of cutting inserts)on tool wear and chip morphology in the dry machining of AZ31B magnesium alloy.The results show that the cutting speed was the most significant factor affecting tool flank wear,followed by feed rate and cutting depth.The tool wear mechanism was examined using scanning electron microscope(SEM)images and energy dispersive X-ray spectroscopy(EDS)analysis reports,which showed that at low cutting speed,the main wear mechanism was abrasion,while at high speed,it was adhesion.The chips are discontinuous at low cutting speeds,while continuous at high cutting speeds.The dimple textured flank face cutting tools facilitate the dry machining of AZ31B magnesium alloy and contribute to ecological benefits.

Tailoring the texture and mechanical properties of 3%Y_(2)O_(3)p/ZGK200 composites fabricated by unidirectional and cross rolling followed by annealing

3%Y_(2)O_(3)p/ZGK200 composites were subjected to unidirectional rolling(UR)and cross rolling(CR)at 400℃and 350℃followed by annealing at 300℃for 1 h.The microstructure,texture and mechanical properties of rolled and annealed composites were systematically studied.The rolled composites exhibited a heterogeneous microstructure,consisting of deformed grains elongated along rolling direction(RD)and Y_(2)O_(3)particles bands distributed along RD.After annealing,static recrystallization(SRX)occurred and most deformed grains transformed into equiaxed grains.A non-basal texture with two strong T-texture components was obtained after UR while a non-basal elliptical/circle texture with circle multi-peaks was obtained after CR,indicating that rolling path had great influences on texture of the composites.After annealing process,R-texture component disappeared or weakened,as results,a non-basal texture with double peaks tilting from normal direction(ND)to transverse direction(TD)and a more random non-basal texture with circle multi-peaks were obtained for UR and CR composites,respectively.The yield strength of rolled composites after UR showed obvious anisotropy along RD and TD while a low anisotropic yield strength was obtained after CR.Some Y_(2)O_(3)particles broke during rolling.The fracture of the composites was attributed to the existence of Y_(2)O_(3)clusters and interfacial debonding between particles and matrix during tension,as a result,the ductility was not as superior as matrix alloy.

Automatic area estimation of algal blooms in water bodies from UAV images using texture analysis

Algal blooms,the spread of algae on the surface of water bodies,have adverse effects not only on aquatic ecosystems but also on human life.The adverse effects of harmful algal blooms(HABs)necessitate a convenient solution for detection and monitoring.Unmanned aerial vehicles(UAVs)have recently emerged as a tool for algal bloom detection,efficiently providing on-demand images at high spatiotemporal resolutions.This study developed an image processing method for algal bloom area estimation from the aerial images(obtained from the internet)captured using UAVs.As a remote sensing method of HAB detection,analysis,and monitoring,a combination of histogram and texture analyses was used to efficiently estimate the area of HABs.Statistical features like entropy(using the Kullback-Leibler method)were emphasized with the aid of a gray-level co-occurrence matrix.The results showed that the orthogonal images demonstrated fewer errors,and the morphological filter best detected algal blooms in real time,with a precision of 80%.This study provided efficient image processing approaches using on-board UAVs for HAB monitoring.

Effect of forging on the microstructure and texture of a high Nb containing γ-TiAl alloy

The effect of forging on the microstructure and texture evolution of a high Nb containing Ti-45Al-7Nb-0.3W(at.%)alloy was investigated by X-ray diffractometer(XRD),scanning electron microscopy(SEM),and transmission electron microscopy(TEM).The results show that the as-cast alloy is mainly composed of α_(2)/γ lamellar colonies with a mean size of 70μm,but the hot-forged pancake displays a near duplex microstructure(DP).Kinking and bending of lamellar colonies,deformation twinning and dynamic recrystallization(DRX)occur during hot forging.Meanwhile,dense dislocations in theβphase after forging suggest that the high-temperature β phase with a disordered structure is favorable for improving the hot-workability of the alloy.Unlike the common TiAl casting texture,the solidification process of the investigated as-cast alloy with high Nb content is completely via the β phase region,resulting in the formation of a<110>γ fiber texture where the<110>γ aligns parallel to the heat-flow direction.In comparison,the relatively strong<001>and weak<302>texture components in the as-forged alloy are attributed to the deformation twinning.After annealing,static recrystallization occurs at the twin boundary and intersections,which weakens the deformation texture.

The Clinical Value of Ultrasound Image Texture Analysis in the Diagnosis of Uterine Adhesions

Purpose: This review examines the diagnostic value of transvaginal 3D ultrasound image texture analysis for the diagnosis of uterine adhesions. Materials and Methods: The total clinical data of 53 patients with uterine adhesions diagnosed by hysteroscopy and the imaging data of transvaginal three-dimensional ultrasound from the Second Affiliated Hospital of Chongqing Medical University from June 2022 to August 2023 were retrospectively analysed. Based on hysteroscopic surgical records, patients were divided into two independent groups: normal endometrium and uterine adhesion sites. The samples were divided into a training set and a test set, and the transvaginal 3D ultrasound was used to outline the region of interest (ROI) and extract texture features for normal endometrium and uterine adhesions based on hysteroscopic surgical recordings, the training set data were feature screened and modelled using lasso regression and cross-validation, and the diagnostic efficacy of the model was assessed by applying the subjects’ operating characteristic (ROC) curves. Results: For each group, 290 texture feature parameters were extracted and three higher values were screened out, and the area under the curve of the constructed ultrasonographic scoring model was 0.658 and 0.720 in the training and test sets, respectively. Conclusion Relative clinical value of transvaginal three-dimensional ultrasound image texture analysis for the diagnosis of uterine adhesions.

Privacy-Preserving Healthcare and Medical Data Collaboration Service System Based on Blockchain and Federated Learning

As the volume of healthcare and medical data increases from diverse sources,real-world scenarios involving data sharing and collaboration have certain challenges,including the risk of privacy leakage,difficulty in data fusion,low reliability of data storage,low effectiveness of data sharing,etc.To guarantee the service quality of data collaboration,this paper presents a privacy-preserving Healthcare and Medical Data Collaboration Service System combining Blockchain with Federated Learning,termed FL-HMChain.This system is composed of three layers:Data extraction and storage,data management,and data application.Focusing on healthcare and medical data,a healthcare and medical blockchain is constructed to realize data storage,transfer,processing,and access with security,real-time,reliability,and integrity.An improved master node selection consensus mechanism is presented to detect and prevent dishonest behavior,ensuring the overall reliability and trustworthiness of the collaborative model training process.Furthermore,healthcare and medical data collaboration services in real-world scenarios have been discussed and developed.To further validate the performance of FL-HMChain,a Convolutional Neural Network-based Federated Learning(FL-CNN-HMChain)model is investigated for medical image identification.This model achieves better performance compared to the baseline Convolutional Neural Network(CNN),having an average improvement of 4.7%on Area Under Curve(AUC)and 7%on Accuracy(ACC),respectively.Furthermore,the probability of privacy leakage can be effectively reduced by the blockchain-based parameter transfer mechanism in federated learning between local and global models.

Application of texture signatures based on multiparameter-magnetic resonance imaging for predicting microvascular invasion in hepatocellular carcinoma:Retrospective study

BACKGROUND Despite continuous changes in treatment methods,the survival rate for advanced hepatocellular carcinoma(HCC)patients remains low,highlighting the importance of diagnostic methods for HCC.AIM To explore the efficacy of texture analysis based on multi-parametric magnetic resonance(MR)imaging(MRI)in predicting microvascular invasion(MVI)in preoperative HCC.METHODS This study included 105 patients with pathologically confirmed HCC,categorized into MVI-positive and MVI-negative groups.We employed Original Data Analysis,Principal Component Analysis,Linear Discriminant Analysis(LDA),and Non-LDA(NDA)for texture analysis using multi-parametric MR images to predict preoperative MVI.The effectiveness of texture analysis was determined using the B11 program of the MaZda4.6 software,with results expressed as the misjudgment rate(MCR).RESULTS Texture analysis using multi-parametric MRI,particularly the MI+PA+F dimensionality reduction method combined with NDA discrimination,demonstrated the most effective prediction of MVI in HCC.Prediction accuracy in the pulse and equilibrium phases was 83.81%.MCRs for the combination of T2-weighted imaging(T2WI),arterial phase,portal venous phase,and equilibrium phase were 22.86%,16.19%,20.95%,and 20.95%,respectively.The area under the curve for predicting MVI positivity was 0.844,with a sensitivity of 77.19%and specificity of 91.67%.CONCLUSION Texture analysis of arterial phase images demonstrated superior predictive efficacy for MVI in HCC compared to T2WI,portal venous,and equilibrium phases.This study provides an objective,non-invasive method for preoperative prediction of MVI,offering a theoretical foundation for the selection of clinical therapy.

Two-stage dynamic recrystallization and texture evolution in Al-7Mg alloy during hot torsion

Hot torsion tests were performed on the Al-7Mg alloy at the temperature ranging from 300 to 500℃ and strain rates between 0.05 and 5 s^(-1) to explore the progressive dynamic recrystallization(DRX)and texture behaviors.The DRX behavior of the alloy manifested two distinct stages:Stage 1 at strain of≤2 and Stage 2 at strains of≥2.In Stage 1,there was a slight increase in the DRXed grain fraction(X_(DRX))with predominance of discontinuous DRX(DDRX),followed by a modest change in X_(DRX) until the transition to Stage 2.Stage 2 was marked by an accelerated rate of DRX,culminating in a substantial final X_(DRX) of~0.9.Electron backscattered diffraction(EBSD)analysis on a sample in Stage 2 revealed that continuous DRX(CDRX)predominantly occurred within the(121)[001]grains,whereas the(111)[110]grains underwent a geometric DRX(GDRX)evolution without a noticeable sub-grain structure.Furthermore,a modified Avrami’s DRX kinetics model was utilized to predict the microstructural refinement in the Al-7Mg alloy during the DRX evolution.Although this kinetics model did not accurately capture the DDRX behavior in Stage 1,it effectively simulated the DRX rate in Stage 2.The texture index was employed to assess the evolution of the texture isotropy during hot-torsion test,demonstrating significant improvement(>75%)in texture randomness before the commencement of Stage 2.This initial texture evolution is attributed to the rotation of parent grains and the substructure evolution,rather than to an increase in X_(DRX).

Thermal and textural properties of extruded rice affect its cooking performances and the texture of the steamed extruded rice

Extruded rice has increasingly gained popularity in the market due to its convenience and acceptable texture.The objective of this study was to understand how the physicochemical,thermal,and textural properties of the extruded rice affected its cooking properties and texture of the cooked one.It was found that air trapped in the grains during extrusion reduced the transparency of extruded rice.More air trapped in the grains reduced the true density of the extruded rice,which in turn decreased the hardness of extruded rice.A looser internal structure of extruded rice grain,as indicated by the lower true density,resulted in a faster hydration and shorter optimum cooking time.Extruded rices showed two thermal-transition peaks,with peak 1 from 93.3℃ to 112.8℃ and peak 2 from 107.5℃ to 132.5℃.The increased hardness of extruded rice led to increases in its thermaltransition temperatures,longer optimum steaming time,and decreases in its water absorption and cooking loss,which resulted in an increase in the hardness and a reduction in the adhesiveness of the steamed one.This study provides insights into the key factors determining the eating quality of extruded rice,which is beneficial for food scientists in developing premium extruded rice.

A new two-step variational model for multiplicative noise removal with applications to texture images

Multiplicative noise removal problems have attracted much attention in recent years.Unlike additive noise,multiplicative noise destroys almost all information of the original image,especially for texture images.Motivated by the TV-Stokes model,we propose a new two-step variational model to denoise the texture images corrupted by multiplicative noise with a good geometry explanation in this paper.In the first step,we convert the multiplicative denoising problem into an additive one by the logarithm transform and propagate the isophote directions in the tangential field smoothing.Once the isophote directions are constructed,an image is restored to fit the constructed directions in the second step.The existence and uniqueness of the solution to the variational problems are proved.In these two steps,we use the gradient descent method and construct finite difference schemes to solve the problems.Especially,the augmented Lagrangian method and the fast Fourier transform are adopted to accelerate the calculation.Experimental results show that the proposed model can remove the multiplicative noise efficiently and protect the texture well.