Construction of a Computational Scheme for the Fuzzy HIV/AIDS Epidemic Model with a Nonlinear Saturated Incidence Rate

This work aimed to construct an epidemic model with fuzzy parameters.Since the classical epidemic model doesnot elaborate on the successful interaction of susceptible and infective people,the constructed fuzzy epidemicmodel discusses the more detailed versions of the interactions between infective and susceptible people.Thenext-generation matrix approach is employed to find the reproduction number of a deterministic model.Thesensitivity analysis and local stability analysis of the systemare also provided.For solving the fuzzy epidemic model,a numerical scheme is constructed which consists of three time levels.The numerical scheme has an advantage overthe existing forward Euler scheme for determining the conditions of getting the positive solution.The establishedscheme also has an advantage over existing non-standard finite difference methods in terms of order of accuracy.The stability of the scheme for the considered fuzzy model is also provided.From the plotted results,it can beobserved that susceptible people decay by rising interaction parameters.

On the Use of Monotonicity-Preserving Interpolatory Techniques in Multilevel Schemes for Balance Laws

Cost-effective multilevel techniques for homogeneous hyperbolic conservation laws are very successful in reducing the computational cost associated to high resolution shock capturing numerical schemes.Because they do not involve any special data structure,and do not induce savings in memory requirements,they are easily implemented on existing codes and are recommended for 1D and 2D simulations when intensive testing is required.The multilevel technique can also be applied to balance laws,but in this case,numerical errors may be induced by the technique.We present a series of numerical tests that point out that the use of monotonicity-preserving interpolatory techniques eliminates the numerical errors observed when using the usual 4-point centered Lagrange interpolation,and leads to a more robust multilevel code for balance laws,while maintaining the efficiency rates observed forhyperbolic conservation laws.

An Arbitrarily High Order and Asymptotic Preserving Kinetic Scheme in Compressible Fluid Dynamic

We present a class of arbitrarily high order fully explicit kinetic numerical methods in compressible fluid dynamics,both in time and space,which include the relaxation schemes by Jin and Xin.These methods can use the CFL number larger or equal to unity on regular Cartesian meshes for the multi-dimensional case.These kinetic models depend on a small parameter that can be seen as a"Knudsen"number.The method is asymptotic preserving in this Knudsen number.Also,the computational costs of the method are of the same order of a fully explicit scheme.This work is the extension of Abgrall et al.(2022)[3]to multidimensional systems.We have assessed our method on several problems for two-dimensional scalar problems and Euler equations and the scheme has proven to be robust and to achieve the theoretically predicted high order of accuracy on smooth solutions.

S-scheme heterojunction with ultrafast interfacial electron transfer for artificial photosynthesis

The rapid development of the global economy has led to the over-exploitation and burning of fossil fuels,causing a severe energy crisis and continuous CO_(2) emissions.Although solar energy is a clean and renewable resource,it faces significant diurnal and seasonal variations and is difficult to store[1-4].Converting solar energy into storable chemical energy through photocatalysis is an effective way to address both energy scarcity and environmental issues.Photocatalytic CO_(2) reduction,with the development of high-efficiency photocatalysts as the key,offers a clean and environmentally friendly method to convert CO_(2) into valuable hydrocarbon fuels,providing a viable solution to the global energy crisis and climate change[5,6].

Orbit Weighting Scheme in the Context of Vector Space Information Retrieval

This study introduces the Orbit Weighting Scheme(OWS),a novel approach aimed at enhancing the precision and efficiency of Vector Space information retrieval(IR)models,which have traditionally relied on weighting schemes like tf-idf and BM25.These conventional methods often struggle with accurately capturing document relevance,leading to inefficiencies in both retrieval performance and index size management.OWS proposes a dynamic weighting mechanism that evaluates the significance of terms based on their orbital position within the vector space,emphasizing term relationships and distribution patterns overlooked by existing models.Our research focuses on evaluating OWS’s impact on model accuracy using Information Retrieval metrics like Recall,Precision,InterpolatedAverage Precision(IAP),andMeanAverage Precision(MAP).Additionally,we assessOWS’s effectiveness in reducing the inverted index size,crucial for model efficiency.We compare OWS-based retrieval models against others using different schemes,including tf-idf variations and BM25Delta.Results reveal OWS’s superiority,achieving a 54%Recall and 81%MAP,and a notable 38%reduction in the inverted index size.This highlights OWS’s potential in optimizing retrieval processes and underscores the need for further research in this underrepresented area to fully leverage OWS’s capabilities in information retrieval methodologies.

A micro-crosslinked amphoteric hydrophobic association copolymer as high temperature-and salt-resistance fluid loss reducer for water-based drilling fluids

During ultradeep oil and gas drilling,fluid loss reducers are highly important for water-based drilling fluids,while preparing high temperature-and salt-resistance fluid loss reducers with excellent rheology and filtration performance remains a challenge.Herein,a micro-crosslinked amphoteric hydrophobic association copolymer(i.e.,DADC)was synthesized using N,N-dimethyl acrylamide,diallyl dimethyl ammonium chloride,2-acrylamido-2-methylpropane sulfonic acid,hydrophobic monomer,and pentaerythritol triallyl ether crosslinker.Due to the synergistic effects of hydrogen bonds,electrostatic interaction,hydrophobic association,and micro-crosslinking,the DADC copolymer exhibited outstanding temperature-and salt-resistance.The rheological experiments have shown that the DADC copolymer had excellent shear dilution performance and a certain degree of salt-responsive viscosity-increasing performance.The DADC copolymer could effectively adsorb on the surface of bentonite particles through electrostatic interaction and hydrogen bonds,which bring more negative charge to the bentonite,thus improving the hydration and dispersion of bentonite particles as well as the colloidal stability of the drilling fluids.Moreover,the drilling fluids constructed based on the DADC copolymer exhibited satisfactory rheological and filtration properties(FLHTHP=12 m L)after aging at high temperatures(up to200℃)and high salinity(saturated salt)environments.Therefore,this work provided new insights into designing and fabricating high-performance drilling fluid treatment agents,demonstrating good potential applications in deep and ultradeep drilling engineering.

Distribution and dynamics of niche and interspecific association of dominant phytoplankton species in the Feiyun River basin,Zhejiang,China

To investigate the dominant species and interspecific association in the phytoplankton community of the Feiyun River basin in Zhejiang Province,East China,the main stream and the Shanxi Zhaoshandu Reservoir in the downstream were chosen as the study area,for which 22 sampling sites were designated.Sampling was conducted in September 2021,January,May,and July 2022.Phytoplankton species were identified from both quantitative samples and in-vivo observations.Phytoplankton was quantified by direct counting.Results show that there were 98 species belonging to 6 phyla and 78 genera.In addition,to clarify the niches of the dominant phytoplankton species and their interspecific association,the dominance index was calculated,and a comprehensive analysis was conducted including niche width,niche overlap value,ecological response rate,overall association,chi-square test,and the stability.The phytoplankton community exhibited characteristics of a Cyanobacteria-Chlorophyta-Diatom type community,showing higher diversity in spring and lower diversity in summer.Among 11 dominants phytoplankton species from 3 phyla,both frequency and dominance degree varied seasonally,of which Microcystis sp.was the dominant species in Spring,Autumn,and Winter.The niche widths of the dominant species ranged from 0.234 to 0.933,and were categorized into three groups.The niche overlap values of the 11 dominant species ranged from 0.359 to 0.959,exhibiting significant seasonal differences-highest in winter followed by autumn,spring,and summer in turn.The overall correlation among dominant species in all four seasons revealed a non-significant negative association,resulting in an unstable community structure.A significant portion(84.2%)of species pairs displayed positive associations,suggesting a successional pattern where Diatoms dominated while other dominant species shared resources and space.Despite this pattern,stability measurements indicated that the dominant species community remained unstable.Therefore,careful monitoring is recommended for potential water environment issues arising from abnormal proliferation of dominant species in the watershed during winter.This research built a theoretical foundation with a data support to the early warning of eutrophication and provided a reference for water resources management in similar watersheds along the eastern coast of China.

Strengthening Active Aging through Older People’s Association and Economic Activity of the Older People in Nepal

Aging is a natural lifelong process ending in death. Many older people are living in poverty. Older people are generally considered dependent on others as they grow older. The purpose of this article is to explore the entrepreneurship activities of Nepalese older adults. Data for this study were collected from the project Help Age International (HAI) implemented in Nepal. Qualitative data observations and interviews were used to collect data. The findings of this study show the formation of the Older People’s Association (OPA) has supported many older people to participate outside the home in various social activities. Moreover, regular deposits through OPAs offer little help. OPAs support older people in their need of financial support to implement minor entrepreneurship. Older people who received support were pleased and were actively involved in their activities and also regularly deposited money in them. Subsequently, older people’s participation in social activities has increased and also helped to lower elderly abuse, loneliness, and depression. Local governments should promote such activities which will help with healthy aging.

THAPE: A Tunable Hybrid Associative Predictive Engine Approach for Enhancing Rule Interpretability in Association Rule Learning for the Retail Sector

Association rule learning(ARL)is a widely used technique for discovering relationships within datasets.However,it often generates excessive irrelevant or ambiguous rules.Therefore,post-processing is crucial not only for removing irrelevant or redundant rules but also for uncovering hidden associations that impact other factors.Recently,several post-processing methods have been proposed,each with its own strengths and weaknesses.In this paper,we propose THAPE(Tunable Hybrid Associative Predictive Engine),which combines descriptive and predictive techniques.By leveraging both techniques,our aim is to enhance the quality of analyzing generated rules.This includes removing irrelevant or redundant rules,uncovering interesting and useful rules,exploring hidden association rules that may affect other factors,and providing backtracking ability for a given product.The proposed approach offers a tailored method that suits specific goals for retailers,enabling them to gain a better understanding of customer behavior based on factual transactions in the target market.We applied THAPE to a real dataset as a case study in this paper to demonstrate its effectiveness.Through this application,we successfully mined a concise set of highly interesting and useful association rules.Out of the 11,265 rules generated,we identified 125 rules that are particularly relevant to the business context.These identified rules significantly improve the interpretability and usefulness of association rules for decision-making purposes.

Deployment Dynamic Modeling and Driving Schemes for a Ring-Truss Deployable Antenna

Mesh reflector antennas are widely used in space tasks owing to their light weight,high surface accuracy,and large folding ratio.They are stowed during launch and then fully deployed in orbit to form a mesh reflector that transmits signals.Smooth deployment is essential for duty services;therefore,accurate and efficient dynamic modeling and analysis of the deployment process are essential.One major challenge is depicting time-varying resistance of the cable network and capturing the cable-truss coupling behavior during the deployment process.This paper proposes a general dynamic analysis methodology for cable-truss coupling.Considering the topological diversity and geometric nonlinearity,the cable network's equilibrium equation is derived,and an explicit expression of the time-varying tension of the boundary cables,which provides the main resistance in truss deployment,is obtained.The deployment dynamic model is established,which considers the coupling effect between the soft cables and deployable truss.The effects of the antenna's driving modes and parameters on the dynamic deployment performance were investigated.A scaled prototype was manufactured,and the deployment experiment was conducted to verify the accuracy of the proposed modeling method.The proposed methodology is suitable for general cable antennas with arbitrary topologies and parameters,providing theoretical guidance for the dynamic performance evaluation of antenna driving schemes.

Improvement and security analysis of multi-ring discrete modulation continuous variable quantum secret sharing scheme

In order to avoid the complexity of Gaussian modulation and the problem that the traditional point-to-point communication DM-CVQKD protocol cannot meet the demand for multi-user key sharing at the same time, we propose a multi-ring discrete modulation continuous variable quantum key sharing scheme(MR-DM-CVQSS). In this paper, we primarily compare single-ring and multi-ring M-symbol amplitude and phase-shift keying modulations. We analyze their asymptotic key rates against collective attacks and consider the security key rates under finite-size effects. Leveraging the characteristics of discrete modulation, we improve the quantum secret sharing scheme. Non-dealer participants only require simple phase shifters to complete quantum secret sharing. We also provide the general design of the MR-DM-CVQSS protocol.We conduct a comprehensive analysis of the improved protocol's performance, confirming that the enhancement through multi-ring M-PSK allows for longer-distance quantum key distribution. Additionally, it reduces the deployment complexity of the system, thereby increasing the practical value.

Demography and Socio-Economic Aspects on Irrigated Smallholder Agricultural Enterprises and Their Association with the Cultivation of Maize (Zea mays L.) as a Selected Field Crop

The purpose of this study is to correlate demography and socio-economic aspects at Irrigated Smallholder Agricultural Enterprises and their association with the Cultivation of Maize in order to determine its positive impacts at irrigated smallholders’ agricultural entrepreneurs’ household. Chi-square test was used as descriptive analysis method. The Fischer Exact tests were employed to test demography (gender, age, education, and income) in winter and summer production season of irrigated smallholder agricultural enterprises and their association with the cultivation of selected field crop (i.e. maize). The results show that gender results were not being statistically significant, as measured by the Phi measure of effect size, φ = 0.149, p = 0.011, and φ = 0.05, p = 0.392 in summer. As far as age is concern, it appears to be a statistically significant association between cultivating maize and age in winter, φ = 0.046, p = 0.730 in winter and φ = 0.172, p = 0.013. Education winter result not being statistically significant, the effect size showed a weak association, as measured by the Phi measure of effect size, φ = 0.112, p = 0.305 and φ = 0.035, p = 0.948 in summer. Income result not being statistically significant, as measured by the Phi measure of effect size, φ = 0.049, p = 0.399 and φ = 0.081, p = 0.166 in summer. In conclusion, the study shows that the development of best management practices must be based on a comprehensive analysis of the livelihoods and irrigated smallholder agricultural enterprise farming styles of participating irrigated smallholder agricultural entrepreneurs.

A Non-Parametric Scheme for Identifying Data Characteristic Based on Curve Similarity Matching

For accurately identifying the distribution charac-teristic of Gaussian-like noises in unmanned aerial vehicle(UAV)state estimation,this paper proposes a non-parametric scheme based on curve similarity matching.In the framework of the pro-posed scheme,a Parzen window(kernel density estimation,KDE)method on sliding window technology is applied for roughly esti-mating the sample probability density,a precise data probability density function(PDF)model is constructed with the least square method on K-fold cross validation,and the testing result based on evaluation method is obtained based on some data characteristic analyses of curve shape,abruptness and symmetry.Some com-parison simulations with classical methods and UAV flight exper-iment shows that the proposed scheme has higher recognition accuracy than classical methods for some kinds of Gaussian-like data,which provides better reference for the design of Kalman filter(KF)in complex water environment.

Epistasis-aware genome-wide association studies provide insights into the efficient breeding of high-yield and high-quality rice

Marker-assisted selection(MAS)and genomic selection(GS)breeding have greatly improved the efficiency of rice breeding.Due to the influences of epistasis and gene pleiotropy,ensuring the actual breeding effect of MAS and GS is still a difficult challenge to overcome.In this study,113 indica rice varieties(V)and their 565 testcross hybrids(TC)were used as the materials to investigate the genetic basis of 12 quality traits and nine agronomic traits.The original traits and general combining ability of the parents,as well as the original traits and midparent heterosis of TC,were subjected to genome-wide association analysis.In total,381 primary significantly associated loci(SAL)and 1,759 secondary SALs that had epistatic interactions with these primary SALs were detected.Among these loci,322 candidate genes located within or nearby the SALs were screened,204 of which were cloned genes.A total of 39 MAS molecular modules that are beneficial for trait improvement were identified by pyramiding the superior haplotypes of candidate genes and desirable epistatic alleles of the secondary SALs.All the SALs were used to construct genetic networks,in which 91 pleiotropic loci were investigated.Additionally,we estimated the accuracy of genomic prediction in the parent V and TC by incorporating either no SALs,primary SALs,secondary SALs or epistatic effect SALs as covariates.Although the prediction accuracies of the four models were generally not significantly different in the TC dataset,the incorporation of primary SALs,secondary SALs,and epistatic effect SALs significantly improved the prediction accuracies of 5(26%),3(16%),and 11(58%)traits in the V dataset,respectively.These results suggested that SALs and epistatic effect SALs identified based on an additive genotype can provide considerable predictive power for the parental lines.They also provide insights into the genetic basis of complex traits and valuable information for molecular breeding in rice.

A Neural-network-based Alternative Scheme to Include Nonhydrostatic Processes in an Atmospheric Dynamical Core

Here,a nonhydrostatic alternative scheme(NAS)is proposed for the grey zone where the nonhydrostatic impact on the atmosphere is evident but not large enough to justify the necessity to include an implicit nonhydrostatic solver in an atmospheric dynamical core.The NAS is designed to replace this solver,which can be incorporated into any hydrostatic models so that existing well-developed hydrostatic models can effectively serve for a longer time.Recent advances in machine learning(ML)provide a potential tool for capturing the main complicated nonlinear-nonhydrostatic relationship.In this study,an ML approach called a neural network(NN)was adopted to select leading input features and develop the NAS.The NNs were trained and evaluated with 12-day simulation results of dry baroclinic-wave tests by the Weather Research and Forecasting(WRF)model.The forward time difference of the nonhydrostatic tendency was used as the target variable,and the five selected features were the nonhydrostatic tendency at the last time step,and four hydrostatic variables at the current step including geopotential height,pressure in two different forms,and potential temperature,respectively.Finally,a practical NAS was developed with these features and trained layer by layer at a 20-km horizontal resolution,which can accurately reproduce the temporal variation and vertical distribution of the nonhydrostatic tendency.Corrected by the NN-based NAS,the improved hydrostatic solver at different horizontal resolutions can run stably for at least one month and effectively reduce most of the nonhydrostatic errors in terms of system bias,anomaly root-mean-square error,and the error of the wave spatial pattern,which proves the feasibility and superiority of this scheme.

Association between Placental Malaria and Severe Pre-Eclampsia in Two University Hospitals of Yaounde City

Context: Pre-eclampsia and placental malaria, are two diseases that share pathophysiological similarities, such as placental ischemia, endothelial dysfunction and production of pro-inflammatory cytokines. Objective: The objective of our study was to investigate the association between placental malaria lesions and severe pre-eclampsia. Methodology: We conducted a prospective analytical cross-sectional study in two University Hospitals in the city of Yaounde (Yaounde Central Hospital and the Gynaecological Obstetrics and Paediatrics Hospital), and in the laboratory of the Centre Pasteur in Yaounde over an eight-month period (1st January 2021 – 1st September 2021). All patients with pre-eclampsia diagnosed according to the criteria of the International Society for the Study of Hypertension (ISSHP) and free of chronic metabolic or infectious pathology were included in this study. The patients were divided into two groups: group 1 (mild pre-eclampsia) and group 2: severe pre-eclampsia. Socio-demographic, clinical and histopathological characteristics specific to pre-eclampsia and placental malaria were investigated. Statistical analysis was performed with SPSS 23.0 software, Chi 2 was used to compare categorical variables, Student t-test was used to compare means, and logistic regression was used to assess the association between placental malaria lesions and PES. Results: The mean age of our study population was 29.93 ± 7.36 years versus 28.28 ± 7.18 years in patients with mild and severe pre-eclampsia respectively. Pre-eclampsia placental lesions (accelerated villous maturation, infarction) were significantly greater in patients with severe pre-eclampsia (p Conclusion: Placental malaria lesions were significantly associated with severe pre-eclampsia and increased the risk of developing severe pre-eclampsia placental lesions by a factor of 10.

Leveraging the potential of big genomic and phenotypic data for genome-wide association mapping in wheat

Genome-wide association mapping studies(GWAS)based on Big Data are a potential approach to improve marker-assisted selection in plant breeding.The number of available phenotypic and genomic data sets in which medium-sized populations of several hundred individuals have been studied is rapidly increasing.Combining these data and using them in GWAS could increase both the power of QTL discovery and the accuracy of estimation of underlying genetic effects,but is hindered by data heterogeneity and lack of interoperability.In this study,we used genomic and phenotypic data sets,focusing on Central European winter wheat populations evaluated for heading date.We explored strategies for integrating these data and subsequently the resulting potential for GWAS.Establishing interoperability between data sets was greatly aided by some overlapping genotypes and a linear relationship between the different phenotyping protocols,resulting in high quality integrated phenotypic data.In this context,genomic prediction proved to be a suitable tool to study relevance of interactions between genotypes and experimental series,which was low in our case.Contrary to expectations,fewer associations between markers and traits were found in the larger combined data than in the individual experimental series.However,the predictive power based on the marker-trait associations of the integrated data set was higher across data sets.Therefore,the results show that the integration of medium-sized to Big Data is an approach to increase the power to detect QTL in GWAS.The results encourage further efforts to standardize and share data in the plant breeding community.

High-Order DG Schemes with Subcell Limiting Strategies for Simulations of Shocks,Vortices and Sound Waves in Materials Science Problems

Shock waves,characterized by abrupt changes in pressure,temperature,and density,play a significant role in various materials science processes involving fluids.These high-energy phenomena are utilized across multiple fields and applications to achieve unique material properties and facilitate advanced manufacturing techniques.Accurate simulations of these phenomena require numerical schemes that can represent shock waves without spurious oscillations and simultaneously capture acoustic waves for a wide range of wavelength scales.This work suggests a high-order discontinuous Galerkin(DG)method with a finite volume(FV)subcell limiting strategies to achieve better subcell resolution and lower numerical diffusion properties.By switching to the FV discretization on an embedded sub-cell grid,the method displays advantages with respect to both DG accuracy and FV shock-capturing ability.The FV scheme utilizes a class of high-fidelity schemes that are built upon the boundary variation diminishing(BVD)reconstruction paradigm.The method is therefore able to resolve discontinuities and multi-scale structures on the subcell level,while preserving the favorable properties of the high-order DG scheme.We have tested the present DG method up to the 6th-order accuracy for both smooth and discontinuous noise problems.

Verifiable quantum secret sharing scheme based on orthogonal product states

In the domain of quantum cryptography,the implementation of quantum secret sharing stands as a pivotal element.In this paper,we propose a novel verifiable quantum secret sharing protocol using the d-dimensional product state and Lagrange interpolation techniques.This protocol is initiated by the dealer Alice,who initially prepares a quantum product state,selected from a predefined set of orthogonal product states within the C~d■C~d framework.Subsequently,the participants execute unitary operations on this product state to recover the underlying secret.Furthermore,we subject the protocol to a rigorous security analysis,considering both eavesdropping attacks and potential dishonesty from the participants.Finally,we conduct a comparative analysis of our protocol against existing schemes.Our scheme exhibits economies of scale by exclusively employing quantum product states,thereby realizing significant cost-efficiency advantages.In terms of access structure,we adopt a(t, n)-threshold architecture,a strategic choice that augments the protocol's practicality and suitability for diverse applications.Furthermore,our protocol includes a rigorous integrity verification mechanism to ensure the honesty and reliability of the participants throughout the execution of the protocol.

Tree mycorrhizal associations determine how biodiversity,large trees,and environmental factors drive aboveground carbon stock in temperate forests

Biodiversity,large trees,and environmental conditions such as climate and soil have important effects on forest carbon stocks.However,recent studies in temperate forests suggest that the relative importance of these factors depends on tree mycorrhizal associations,whereby large-tree effects may be driven by ectomycorrhizal(EM)trees,diversity effects may be driven by arbuscular mycorrhizal(AM)trees,and environment effects may depend on differential climate and soil preferences of AM and EM trees.To test this hypothesis,we used forest-inventory data consisting of over 80,000 trees from 631 temperate-forest plots(30 m×30 m)across Northeast China to examine how biodiversity(species diversity and ecological uniqueness),large trees(top 1%of tree diameters),and environmental factors(climate and soil nutrients)differently regulate aboveground carbon stocks of AM trees,EM trees,and AM and EM trees combined(i.e.total aboveground carbon stock).We found that large trees had a positive effect on both AM and EM tree carbon stocks.However,biodiversity and environmental factors had opposite effects on AM vs.EM tree carbon stocks.Specifically,the two components of biodiversity had positive effects on AM tree carbon stocks,but negative effects on EM tree carbon stocks.Environmental heterogeneity(mean annual temperature and soil nutrients)also exhibited contrasting effects on AM and EM tree carbon stocks.Consequently,for the total carbon stock,the positive large-tree effect far surpasses the diversity and environment effect.This is mainly because when integrating AM and EM tree carbon stock into total carbon stock,the opposite diversity-effect(also environment-effect)on AM vs.EM tree carbon stock counteracts each other while the consistent positive large-tree effect on AM and EM tree carbon stock is amplified.In summary,this study emphasized a mycorrhizal viewpoint to better understand the determinants of overarching aboveground carbon profile across regional forests.