ON CRACK PROBLEMS IN AN INFINITE PLANE CONSISTING OF THREE DIFFERENT MEDIA

The mathematical problem of an infinite elastic plane consisting of three different media with an arbitrary number of cracks is considered. It is reduced to singular integral equations along the interfaces and the cracks by a constructive method. Those along the interfaces are further reduced to Fredholm ones.

ONE－POT STEREOSELECTIVE SYNTHESIS OF FUSED RING SYSTEMS CONSISTING OF ISOXAZOLINE AND TETRAHYDRO－FURAN，－THIOPHENE，OR－PYRROLE VIA INTRAMOLECULAR CYCLOADDITION OF SILYL NITRONATES DERIVED FROM α－NITROALKENES

Michael condensations of α-nitroalkenes with heteroatom-centered nucleophiles bearing allyl group in the presence of a base followed by the addition of trimethylchlorosilane led to the stereoselective synthesis of isoxazoline fused tetrahydrofurans,tetrahydrothiophenes or tetrahydropyrroles via intramolecular silyl nitronates-olefin cycloadditions in onepot procedure with high yields.

Electron Donating Property and Catalytic Activity ofPerovskite-type Mixed Oxides (ABO_3) Consisting of Rare Earth and 3d Transition Metals

The catalytic activity of Perovskite-type mixed oxides (LaCoO3, PrCoO3 and SmCoO3) for the reduction of cyclohexanone to cyclohexanol with 2-propanol (Meerwein-PonndorfVerley reduction) has been studied. The data have been correlated with the surface electron donor properties of these mixed oxides

An Array Consisting of 10 High-Speed Side-Illuminated Evanescently Coupled Waveguide Photodetectors Each with a Bandwidth of 20 GHz

We design and fabricate a parallel system with 10 high speed side-illuminated evanescently coupled waveguide photodetectors （ECPDs）. The 10 ECPDs exhibit a uniform 3dB bandwidth of 20 GHz and low dark current of about i nA at 2 V reverse bias. The 10 ECPDs also exhibit uniform photo-responsivity of about 0.23A/W with an active region of 5 × 25μmS. The photodetector array has a total bandwidth of more than 200 GHz and can be integrated with other optoelectronic devices.

Electron impact total(elastic+inelastic) cross sections with simple molecules consisting of N & O atoms at 100-1600eV

A model complex optical potential rewritten by the conception of bonded atom, which considers the overlapping effect of electron cloud, is employed to calculate the total (elastic + inelastic) cross sections with simple molecules (N2, O2, NO2, NO, N2O) consisting of N & O atoms over an incident energy range of 100 - 1600 eV by the use of additivity rule at Roothaan-Hartree-Fock level. In the study, the complex optical potential composed of static, exchange, correlation polarization plus absorption contributions firstly uses bonded-atom conception. The qualitative results are compared with experimental data and other calculations wherever available and good agreement is obtained. The total cross sections of electron-molecule scattering above 100 eV can be successfully calculated.

Nonlinear Registration of Brain Magnetic Resonance Images with Cross Constraints of Intensity and Structure

Many deep learning-based registration methods rely on a single-stream encoder-decoder network for computing deformation fields between 3D volumes.However,these methods often lack constraint information and overlook semantic consistency,limiting their performance.To address these issues,we present a novel approach for medical image registration called theDual-VoxelMorph,featuring a dual-channel cross-constraint network.This innovative network utilizes both intensity and segmentation images,which share identical semantic information and feature representations.Two encoder-decoder structures calculate deformation fields for intensity and segmentation images,as generated by the dual-channel cross-constraint network.This design facilitates bidirectional communication between grayscale and segmentation information,enabling the model to better learn the corresponding grayscale and segmentation details of the same anatomical structures.To ensure semantic and directional consistency,we introduce constraints and apply the cosine similarity function to enhance semantic consistency.Evaluation on four public datasets demonstrates superior performance compared to the baselinemethod,achieving Dice scores of 79.9%,64.5%,69.9%,and 63.5%for OASIS-1,OASIS-3,LPBA40,and ADNI,respectively.

Locally and globally uniform approximations for ruin probabilities of a nonstandard bidimensional risk model with subexponential claims

Consider a nonstandard continuous-time bidimensional risk model with constant force of interest,in which the two classes of claims with subexponential distributions satisfy a general dependence structure and each pair of the claim-inter-arrival times is arbitrarily dependent.Under some mild conditions,we achieve a locally uniform approximation of the finite-time ruin probability for all time horizon within a finite interval.If we further assume that each pair of the claim-inter-arrival times is negative quadrant dependent and the two classes of claims are consistently-varying-tailed,it shows that the above obtained approximation is also globally uniform for all time horizon within an infinite interval.

Decoding the inconsistency of six cropland maps in China

Accurate cropland information is critical for agricultural planning and production,especially in foodstressed countries like China.Although widely used medium-to-high-resolution satellite-based cropland maps have been developed from various remotely sensed data sources over the past few decades,considerable discrepancies exist among these products both in total area and in spatial distribution of croplands,impeding further applications of these datasets.The factors influencing their inconsistency are also unknown.In this study,we evaluated the consistency and accuracy of six cropland maps widely used in China in circa 2020,including three state-of-the-art 10-m products(i.e.,Google Dynamic World,ESRI Land Cover,and ESA WorldCover)and three 30-m ones(i.e.,GLC_FCS30,GlobeLand 30,and CLCD).We also investigated the effects of landscape fragmentation,climate,and agricultural management.Validation using a ground-truth sample revealed that the 10-m-resolution WorldCover provided the highest accuracy(92.3%).These maps collectively overestimated Chinese cropland area by up to 56%.Up to 37%of the land showed spatial inconsistency among the maps,concentrated mainly in mountainous regions and attributed to the varying accuracy of cropland maps,cropland fragmentation and management practices such as irrigation.Our work shed light on the promotion of future cropland mapping efforts,especially in highly inconsistent regions.

A Dual Discriminator Method for Generalized Zero-Shot Learning

Zero-shot learning enables the recognition of new class samples by migrating models learned from semanticfeatures and existing sample features to things that have never been seen before. The problems of consistencyof different types of features and domain shift problems are two of the critical issues in zero-shot learning. Toaddress both of these issues, this paper proposes a new modeling structure. The traditional approach mappedsemantic features and visual features into the same feature space;based on this, a dual discriminator approachis used in the proposed model. This dual discriminator approach can further enhance the consistency betweensemantic and visual features. At the same time, this approach can also align unseen class semantic features andtraining set samples, providing a portion of information about the unseen classes. In addition, a new feature fusionmethod is proposed in the model. This method is equivalent to adding perturbation to the seen class features,which can reduce the degree to which the classification results in the model are biased towards the seen classes.At the same time, this feature fusion method can provide part of the information of the unseen classes, improvingits classification accuracy in generalized zero-shot learning and reducing domain bias. The proposed method isvalidated and compared with othermethods on four datasets, and fromthe experimental results, it can be seen thatthe method proposed in this paper achieves promising results.

Identifying Brand Consistency by Product Differentiation Using CNN

This paper presents a new method of using a convolutional neural network(CNN)in machine learning to identify brand consistency by product appearance variation.In Experiment 1,we collected fifty mouse devices from the past thirty-five years from a renowned company to build a dataset consisting of product pictures with pre-defined design features of their appearance and functions.Results show that it is a challenge to distinguish periods for the subtle evolution of themouse devices with such traditionalmethods as time series analysis and principal component analysis(PCA).In Experiment 2,we applied deep learning to predict the extent to which the product appearance variation ofmouse devices of various brands.The investigation collected 6,042 images ofmouse devices and divided theminto the Early Stage and the Late Stage.Results show the highest accuracy of 81.4%with the CNNmodel,and the evaluation score of brand style consistency is 0.36,implying that the brand consistency score converted by the CNN accuracy rate is not always perfect in the real world.The relationship between product appearance variation,brand style consistency,and evaluation score is beneficial for predicting new product styles and future product style roadmaps.In addition,the CNN heat maps highlight the critical areas of design features of different styles,providing alternative clues related to the blurred boundary.The study provides insights into practical problems for designers,manufacturers,and marketers in product design.It not only contributes to the scientific understanding of design development,but also provides industry professionals with practical tools and methods to improve the design process and maintain brand consistency.Designers can use these techniques to find features that influence brand style.Then,capture these features as innovative design elements and maintain core brand values.

Cross-Modal Consistency with Aesthetic Similarity for Multimodal False Information Detection

With the explosive growth of false information on social media platforms, the automatic detection of multimodalfalse information has received increasing attention. Recent research has significantly contributed to multimodalinformation exchange and fusion, with many methods attempting to integrate unimodal features to generatemultimodal news representations. However, they still need to fully explore the hierarchical and complex semanticcorrelations between different modal contents, severely limiting their performance detecting multimodal falseinformation. This work proposes a two-stage detection framework for multimodal false information detection,called ASMFD, which is based on image aesthetic similarity to segment and explores the consistency andinconsistency features of images and texts. Specifically, we first use the Contrastive Language-Image Pre-training(CLIP) model to learn the relationship between text and images through label awareness and train an imageaesthetic attribute scorer using an aesthetic attribute dataset. Then, we calculate the aesthetic similarity betweenthe image and related images and use this similarity as a threshold to divide the multimodal correlation matrixinto consistency and inconsistencymatrices. Finally, the fusionmodule is designed to identify essential features fordetectingmultimodal false information. In extensive experiments on four datasets, the performance of the ASMFDis superior to state-of-the-art baseline methods.

A Combined Antenna Array Deployment with High Positioning Accuracy and Low Angular Measurement Error

In this paper,an antenna array composed of circular array and orthogonal linear array is proposed by using the design of long and short baseline“orthogonal linear array”and the circular array ambiguity resolution design of multi-group baseline clustering.The effectiveness of the antenna array in this paper is verified by sufficient simulation and experiment.After the system deviation correction work,it is found that in the L/S/C/X frequency bands,the ambiguity resolution probability is high,and the phase difference system error between each channel is basically the same.The angle measurement error is less than 0.5°,and the positioning error is less than 2.5 km.Notably,as the center frequency increases,calibration consistency improves,and the calibration frequency points become applicable over a wider frequency range.At a center frequency of 11.5 GHz,the calibration frequency point bandwidth extends to 1200 MHz.This combined antenna array deployment holds significant promise for a wide range of applications in contemporary wireless communication systems.

Reproducibility study of intravoxel incoherent motion and apparent diffusion coefficient parameters in normal pancreas

BACKGROUND The consistency of pancreatic apparent diffusion coefficient(ADC)values and intravoxel incoherent motion(IVIM)parameter values across different magnetic resonance imaging(MRI)devices significantly impacts the patient’s diagnosis and treatment.AIM To explore consistency in image quality,ADC values,and IVIM parameter values among different MRI devices in pancreatic examinations.METHODS This retrospective study was approved by the local ethics committee,and informed consent was obtained from all participants.In total,22 healthy volunteers(10 males and 12 females)aged 24-61 years(mean,28.9±2.3 years)underwent pancreatic diffusion-weighted imaging using 3.0T MRI equipment from three vendors.Two independent observers subjectively scored image quality and measured the pancreas’s overall ADC values and signal-to-noise ratios(SNRs).Subsequently,regions of interest(ROIs)were delineated for the IVIM parameters(true diffusion coefficient,pseudo-diffusion coefficient,and perfusion fraction)using post-processing software.These ROIs were on the head,body,and tail of the pancrease.The subjective image ratings were assessed using the kappa consistency test.Intraclass correlation coefficients(ICCs)and mixed linear models were used to evaluate each device’s quantitative parameter values.Finally,a pairwise analysis of IVIM parameter values across each device was performed using Bland-Altman plots.RESULTS The Kappa value for the subjective ratings of the different observers was 0.776(P<0.05).The ICC values for interobserver and intra-observer agreements for the quantitative parameters were 0.803[95% confidence interval(CI):0.684-0.880]and 0.883(95%CI:0.760-0.945),respectively(P<0.05).The ICCs for the SNR between different devices was comparable(P>0.05),and the ICCs for the ADC values from different devices were 0.870,0.707,and 0.808,respectively(P<0.05).Notably,only a few statistically significant inter-device agreements were observed for different IVIM parameters,and among those,the ICC values were generally low.The mixed linear model results indicated differences(P<0.05)in the f-value for the pancreas head,D-value for the pancreas body,and D-value for the pancreas tail obtained using different MRI machines.The Bland-Altman plots showed significant variability at some data points.CONCLUSION ADC values are consistent among different devices,but the IVIM parameters’repeatability is moderate.Therefore,the variability in the IVIM parameter values may be associated with using different MRI machines.Thus,caution should be exercised when using IVIM parameter values to assess the pancreas.

Efficacy and tolerability of chitin-glucan combined with simethicone(GASTRAP^(■)DIRECT)in irritable bowel syndrome:A prospective,open-label,multicenter study

BACKGROUND Irritable bowel syndrome(IBS),defined according to the Rome IV diagnostic criteria,is a chronic functional gastrointestinal disorder characterized by recurrent abdominal pain related to altered bowel habits.First-line recommended treatments are limited to combining drugs targeting predominant symptoms,particularly pain(antispasmodics),constipation(laxatives),and diarrhea(loperamide),yielding only a limited therapeutic gain.GASTRAP^(■)DIRECT is a class IIa medical formulation composed of a combination of chitin-glucan and simethicone indicated for the symptomatic treatment of gas-related gastrointestinal disorders by combining different mechanisms of action.AIM To evaluate the efficacy,tolerability,and safety of 4-week GASTRAP^(■)DIRECT treatment in patients with IBS.METHODS In this prospective,multicenter,open-label trial,120 patients with IBS received three sticks of GASTRAP^(■)DIRECT(1.5 g/d of chitin-glucan and 0.75 mg/d of simethicone)per day for 4 weeks.The primary endpoint was the responder rate,defined as the number of patients whose abdominal pain score decreased by≥30%from baseline to week(W)4.The analysis was performed using the per-protocol set.Cardinal symptoms,impact of global symptoms on daily life,change in stool consistency,and improvement in defecatory disorders were evaluated.RESULTS Overall,100 patients were evaluated.At W4,67%(95%CI:57-75)showed improvement in abdominal pain(score:5.8±2.4 vs 2.9±2.0,P<0.0001).Similar improvements were observed for bloating[8.0±1.7 vs 4.7±2.9,P<0.0001;60%(95%CI:50-70)responders],abdominal distension[7.2±2.1 vs 4.4±3.1,P<0.0001;53%(95%CI:43-63)responders],and impact of global symptoms on daily life[7.1±2.0 vs 4.6±2.9,P<0.0001;54%(95%CI:44-64)responders].Stool consistency improved in most patients(90%and 57%for patients with liquid and hard stools,respectively).Overall,42%of patients with defecatory disorders reported very much/considerable improvements by W2.No severe adverse event occurred,and tolerability was rated“good”or“very good”by 93%of patients.CONCLUSION GASTRAP^(■)DIRECT is safe and well tolerated,alleviating IBS symptoms rapidly in 2 weeks.This open-label study suggests that the combination of chitin-glucan and simethicone could be beneficial in patients with IBS.

An Eighth Order A-Stable Rational Integrator

In this work we derived and analyzed the stability structure of an order eight rational integrator wherein our numerator and denominator is 4 (i.e. m = n = 4) for the solution of problems in ordinary differential equations. The integrator was observed to be A-stable and also L-stable.

Decentralized Semi-Supervised Learning for Stochastic Configuration Networks Based on the Mean Teacher Method

The aim of this paper is to broaden the application of Stochastic Configuration Network (SCN) in the semi-supervised domain by utilizing common unlabeled data in daily life. It can enhance the classification accuracy of decentralized SCN algorithms while effectively protecting user privacy. To this end, we propose a decentralized semi-supervised learning algorithm for SCN, called DMT-SCN, which introduces teacher and student models by combining the idea of consistency regularization to improve the response speed of model iterations. In order to reduce the possible negative impact of unsupervised data on the model, we purposely change the way of adding noise to the unlabeled data. Simulation results show that the algorithm can effectively utilize unlabeled data to improve the classification accuracy of SCN training and is robust under different ground simulation environments.

Tunable fiber laser based on a cascaded structure consisting of in-line MZI and traditional MZI

A tunable erbium-doped fiber(EDF) laser with a cascaded structure consisting of in-line Mach-Zehnder interferometer(MZI) and traditional MZI is proposed. The transmission spectrum of the in-line MZI is modulated by the traditional MZI, which determines the period of the cascaded structure, while the in-line MZI's transmission spectrum is the outer envelope curve of the cascaded structure's transmission spectrum. A stable single-wavelength lasing operation is obtained at 1 527.14 nm. The linewidth is less than 0.07 nm with a side-mode suppression ratio(SMSR) over 48 d B. Fixing the in-line MZI structure on a furnace, when the temperature changes from 30 °C to 230 °C, the central wavelength can be tuned within the range of 12.4 nm.

Computational Modeling of Reaction-Diffusion COVID-19 Model Having Isolated Compartment

Cases of COVID-19 and its variant omicron are raised all across the world.The most lethal form and effect of COVID-19 are the omicron version,which has been reported in tens of thousands of cases daily in numerous nations.Following WHO(World health organization)records on 30 December 2021,the cases of COVID-19 were found to be maximum for which boarding individuals were found 1,524,266,active,recovered,and discharge were found to be 82,402 and 34,258,778,respectively.While there were 160,989 active cases,33,614,434 cured cases,456,386 total deaths,and 605,885,769 total samples tested.So far,1,438,322,742 individuals have been vaccinated.The coronavirus or COVID-19 is inciting panic for several reasons.It is a new virus that has affected the whole world.Scientists have introduced certain ways to prevent the virus.One can lower the danger of infection by reducing the contact rate with other persons.Avoiding crowded places and social events withmany people reduces the chance of one being exposed to the virus.The deadly COVID-19 spreads speedily.It is thought that the upcoming waves of this pandemicwill be evenmore dreadful.Mathematicians have presented severalmathematical models to study the pandemic and predict future dangers.The need of the hour is to restrict the mobility to control the infection from spreading.Moreover,separating affected individuals from healthy people is essential to control the infection.We consider the COVID-19 model in which the population is divided into five compartments.The present model presents the population’s diffusion effects on all susceptible,exposed,infected,isolated,and recovered compartments.The reproductive number,which has a key role in the infectious models,is discussed.The equilibrium points and their stability is presented.For numerical simulations,finite difference(FD)schemes like nonstandard finite difference(NSFD),forward in time central in space(FTCS),and Crank Nicolson(CN)schemes are implemented.Some core characteristics of schemes like stability and consistency are calculated.

Modeling the hydration,viscosity and ultrasonic property evolution of class G cement up to 90℃ and 200 MPa by a scale factor method

A comprehensive experimental program has been performed to characterize the hydration and engineering property evolution of a class G oil well cement under various curing temperatures from 30 to 90℃.The progress of hydration was monitored by isothermal calorimetry(atmospheric pressure);the viscosity evolution was measured using a high temperature and high pressure consistometer(up to 200 MPa);the ultrasonic property development was evaluated by an ultrasonic cement analyzer(up to 100 MPa).Test results indicate that the influences of curing temperature and pressure on the hydration,viscosity and ultrasonic property development can be modeled by a scale factor method that is similar to the maturity method used in the concrete industry.However,the key parameters of the scale factor model,namely the apparent activation energy and the apparent activation volume of cement showed obvious variations with test method and curing condition.The test results indicate that the curing temperature has a stronger effect on cement hydration rate than viscosity and ultrasonic property development rate,while the curing pressure has a much stronger influence on cement slurry properties before setting(viscosity)than after setting(ultrasonic property).

A Nonstandard Computational Investigation of SEIR Model with Fuzzy Transmission, Recovery and Death Rates

In this article,a Susceptible-Exposed-Infectious-Recovered(SEIR)epidemic model is considered.The equilibrium analysis and reproduction number are studied.The conventional models have made assumptions of homogeneity in disease transmission that contradict the actual reality.However,it is crucial to consider the heterogeneity of the transmission rate when modeling disease dynamics.Describing the heterogeneity of disease transmission mathematically can be achieved by incorporating fuzzy theory.A numerical scheme nonstandard,finite difference(NSFD)approach is developed for the studied model and the results of numerical simulations are presented.Simulations of the constructed scheme are presented.The positivity,convergence and consistency of the developed technique are investigated using mathematical induction,Jacobean matrix and Taylor series expansions respectively.The suggested scheme preserves all these essential characteristics of the disease dynamical models.The numerical and simulation results reveal that the proposed NSFD method provides an adequate representation of the dynamics of the disease.Moreover,the obtained method generates plausible predictions that can be used by regulators to support the decision-making process to design and develop control strategies.Effects of the natural immunity on the infected class are studied which reveals that an increase in natural immunity can decrease the infection and vice versa.