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.

Federated Learning Model for Auto Insurance Rate Setting Based on Tweedie Distribution

In the assessment of car insurance claims,the claim rate for car insurance presents a highly skewed probability distribution,which is typically modeled using Tweedie distribution.The traditional approach to obtaining the Tweedie regression model involves training on a centralized dataset,when the data is provided by multiple parties,training a privacy-preserving Tweedie regression model without exchanging raw data becomes a challenge.To address this issue,this study introduces a novel vertical federated learning-based Tweedie regression algorithm for multi-party auto insurance rate setting in data silos.The algorithm can keep sensitive data locally and uses privacy-preserving techniques to achieve intersection operations between the two parties holding the data.After determining which entities are shared,the participants train the model locally using the shared entity data to obtain the local generalized linear model intermediate parameters.The homomorphic encryption algorithms are introduced to interact with and update the model intermediate parameters to collaboratively complete the joint training of the car insurance rate-setting model.Performance tests on two publicly available datasets show that the proposed federated Tweedie regression algorithm can effectively generate Tweedie regression models that leverage the value of data fromboth partieswithout exchanging data.The assessment results of the scheme approach those of the Tweedie regressionmodel learned fromcentralized data,and outperformthe Tweedie regressionmodel learned independently by a single party.

Amend:An integrated platform of retracted papers and concerned papers

Purpose:The notable increase in retraction papers has attracted considerable attention from diverse stakeholders.Various sources are now offering information related to research integrity,including concerns voiced on social media,disclosed lists of paper mills,and retraction notices accessible through journal websites.However,despite the availability of such resources,there remains a lack of a unified platform to consolidate this information,thereby hindering efficient searching and cross-referencing.Thus,it is imperative to develop a comprehensive platform for retracted papers and related concerns.This article aims to introduce“Amend,”a platform designed to integrate information on research integrity from diverse sources.Design/methodology/approach:The Amend platform consolidates concerns and lists of problematic articles sourced from social media platforms(e.g.,PubPeer,For Better Science),retraction notices from journal websites,and citation databases(e.g.,Web of Science,CrossRef).Moreover,Amend includes investigation and punishment announcements released by administrative agencies(e.g.,NSFC,MOE,MOST,CAS).Each related paper is marked and can be traced back to its information source via a provided link.Furthermore,the Amend database incorporates various attributes of retracted articles,including citation topics,funding details,open access status,and more.The reasons for retraction are identified and classified as either academic misconduct or honest errors,with detailed subcategories provided for further clarity.Findings:Within the Amend platform,a total of 32,515 retracted papers indexed in SCI,SSCI,and ESCI between 1980 and 2023 were identified.Of these,26,620(81.87%)were associated with academic misconduct.The retraction rate stands at 6.64 per 10,000 articles.Notably,the retraction rate for non-gold open access articles significantly differs from that for gold open access articles,with this disparity progressively widening over the years.Furthermore,the reasons for retractions have shifted from traditional individual behaviors like falsification,fabrication,plagiarism,and duplication to more organized large-scale fraudulent practices,including Paper Mills,Fake Peer-review,and Artificial Intelligence Generated Content(AIGC).Research limitations:The Amend platform may not fully capture all retracted and concerning papers,thereby impacting its comprehensiveness.Additionally,inaccuracies in retraction notices may lead to errors in tagged reasons.Practical implications:Amend provides an integrated platform for stakeholders to enhance monitoring,analysis,and research on academic misconduct issues.Ultimately,the Amend database can contribute to upholding scientific integrity.Originality/value:This study introduces a globally integrated platform for retracted and concerning papers,along with a preliminary analysis of the evolutionary trends in retracted papers.

Dynamic behaviors of water-saturated and frozen sandstone subjected to freeze-thaw cycles

In high-altitude cold areas,freeze-thaw(F-T)cycles induced by day-night and seasonal temperature changes cause numerous rock mass slope engineering disasters.To investigate the dynamic properties of rock in the natural environment of a high-altitude cold area,standard specimens were drilled from the slope of the Jiama copper mine in Tibet,and dynamic compression tests were performed on watersaturated and frozen sandstone with different numbers of F-T cycles(0,10,20,30,and 40)by the split Hopkinson pressure bar(SHPB)system with a cryogenic control system.The influence of water-saturated and frozen conditions on the dynamic performance of sandstone was investigated.The following conclusions are drawn:(1)With increasing strain rate,the attenuation factor(la)of water-saturated sandstone and the intensifying factor(li)of frozen sandstone linearly increase.As the number of F-T cycles increases,the dependence factor(ld)of water-saturated sandstone linearly decreases,whereas the ld of frozen sandstone linearly increases.(2)The prediction equation of the dynamic compressive strength of water-saturated and frozen sandstone is obtained,which can be used to predict the dynamic compressive strength of sandstone after various F-T cycles based on the strain rate.(3)The mesoscopic mechanism of water-saturated and frozen sandstone’s dynamic compressive strength evolution is investigated.The water softening effect causes the dynamic compressive strength of water-saturated sandstone to decrease,whereas the strengthening effect of pore ice causes it to increase.(4)The decrease in the relative dynamic compressive strength of water-saturated sandstone and the increase in the relative dynamic compressive strength of frozen sandstone can be attributed to the increased porosity.

Effects of transient temperature gradient on frost heave of saturated silty clay in an open system

Frost heave in seasonally frozen regions is a one-dimensional process that could severely damage infrastructure subgrades.Stress state,temperature and water migration are important factors for frost heave.This work investigated the effects of soil temperature and volumetric water content on the transient frost heave ratio during the freezing of saturated silty clay in an open system and analyzed the relationships between the transient frost heave ratio and freezing rate and between temperature gradient and frost heave rate.The results show that the frost heave ratio,frost heave rate,and freezing rate are positively correlated with the temperature gradient since the temperature gradient drives the water migration during freezing,indicating the transient temperature gradient could be used to evaluate the frost heave of saturated silty clay.The transient freezing rate and transient frost heave ratio are logarithmically related to the transient frost heave ratio and transient temperature gradient,respectively.The effects of transient temperature gradient on frost heave are the principal mechanism responsible for different frost heave characteristics and uneven frost heave along a subgrade of the same soil type.

Strength characteristics of dry and saturated rock at different strain rates

The strength of rock materials is largely affected by water and loading conditions, but there are few studies on mechanical properties of saturated rocks at high strain rates. Through compressive tests on dry and saturated sandstone specimens, it was found that the dynamic compressive strength of both dry and saturated sandstone specimens increased with the increase of strain rates. The saturated rock specimens showed stronger rate dependence than the dry ones. The water affecting factor （WAF）, as the ratio of the strength under dry state to that under saturated state, was introduced to describe the influence of water on the compressive strength at different strain rates. The WAF under static load was close to 1.38, and decreased with the increase of strain rate. When the strain rate reached 190 s^-1, the WAF reduced to 0.98. It indicates that the compressive strength of saturated specimens can be higher than that of dry ones when the strain rate is high enough. Furthermore, the dual effects of water and strain rate on the strength of rock were discussed based on sliding crack model, which provided a good explanation for the experimental results.

Impact of stretching-segment on saturated flow rate of signalized intersection using cellular automation

In order to analyze the impact of stretching-segment on the saturated flow rate of signalized intersection approach, an improved cellular automation model was proposed to estimate its saturated flow rate. The NaSch model was improved by adding different slow probabilities, turning deceleration rules and modified lane changing rules. The relationship between the saturated flow rate of stretching-segments and adjacent lanes was tested in numerical simulation. The length of stretching-segment, cycle length and green time were selected as impact factors of the cellular automation model. The simulation result indicates that the geometrics design of stretching-segment and the traffic signal timing scenario have major effects on the saturated flow rate of the intersection approach. The saturated flow rate will continually increase with increasing stretching-segment length until it reaches a threshold. After reaching the threshold, the stretching-segment can be treated as a separate lane. The green time is approximately linearly related to the threshold length of the stretching-segment. An optimum cycle length exists when the length of the stretching-segment is not long enough, and it is approximately linearly related to the length of stretching-segment.

Pulse rate estimation based on facial videos:an evaluation and optimization of the classical methods using both self-constructed and public datasets

Pulse rate is one of the important characteristics of traditional Chinese medicine pulse diagnosis,and it is of great significance for determining the nature of cold and heat in diseases.The prediction of pulse rate based on facial video is an exciting research field for getting palpation information by observation diagnosis.However,most studies focus on optimizing the algorithm based on a small sample of participants without systematically investigating multiple influencing factors.A total of 209 participants and 2,435 facial videos,based on our self-constructed Multi-Scene Sign Dataset and the public datasets,were used to perform a multi-level and multi-factor comprehensive comparison.The effects of different datasets,blood volume pulse signal extraction algorithms,region of interests,time windows,color spaces,pulse rate calculation methods,and video recording scenes were analyzed.Furthermore,we proposed a blood volume pulse signal quality optimization strategy based on the inverse Fourier transform and an improvement strategy for pulse rate estimation based on signal-to-noise ratio threshold sliding.We found that the effects of video estimation of pulse rate in the Multi-Scene Sign Dataset and Pulse Rate Detection Dataset were better than in other datasets.Compared with Fast independent component analysis and Single Channel algorithms,chrominance-based method and plane-orthogonal-to-skin algorithms have a more vital anti-interference ability and higher robustness.The performances of the five-organs fusion area and the full-face area were better than that of single sub-regions,and the fewer motion artifacts and better lighting can improve the precision of pulse rate estimation.

The Probability Density Function Related to Shallow Cumulus Entrainment Rate and Its Influencing Factors in a Large-Eddy Simulation

The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds.Accurately obtaining the entrainment rate(λ)is particularly important for its parameterization within the overall cumulus parameterization scheme.In this study,an improved bulk-plume method is proposed by solving the equations of two conserved variables simultaneously to calculateλof cumulus clouds in a large-eddy simulation.The results demonstrate that the improved bulk-plume method is more reliable than the traditional bulk-plume method,becauseλ,as calculated from the improved method,falls within the range ofλvalues obtained from the traditional method using different conserved variables.The probability density functions ofλfor all data,different times,and different heights can be well-fitted by a log-normal distribution,which supports the assumed stochastic entrainment process in previous studies.Further analysis demonstrate that the relationship betweenλand the vertical velocity is better than other thermodynamic/dynamical properties;thus,the vertical velocity is recommended as the primary influencing factor for the parameterization ofλin the future.The results of this study enhance the theoretical understanding ofλand its influencing factors and shed new light on the development ofλparameterization.

Prediction model for corrosion rate of low-alloy steels under atmospheric conditions using machine learning algorithms

This work constructed a machine learning(ML)model to predict the atmospheric corrosion rate of low-alloy steels(LAS).The material properties of LAS,environmental factors,and exposure time were used as the input,while the corrosion rate as the output.6 dif-ferent ML algorithms were used to construct the proposed model.Through optimization and filtering,the eXtreme gradient boosting(XG-Boost)model exhibited good corrosion rate prediction accuracy.The features of material properties were then transformed into atomic and physical features using the proposed property transformation approach,and the dominant descriptors that affected the corrosion rate were filtered using the recursive feature elimination(RFE)as well as XGBoost methods.The established ML models exhibited better predic-tion performance and generalization ability via property transformation descriptors.In addition,the SHapley additive exPlanations(SHAP)method was applied to analyze the relationship between the descriptors and corrosion rate.The results showed that the property transformation model could effectively help with analyzing the corrosion behavior,thereby significantly improving the generalization ability of corrosion rate prediction models.

Experimental study on the effect of unloading rate on gneiss rockburst

Rockburst are often encountered in tunnel construction due to the complex geological conditions.To study the influence of unloading rate on rockburst,gneiss rockburst experiments were conducted under three groups of unloading rates.A high-speed photography system and acoustic emission(AE)system were used to monitor the entire process of rockburst process in real-time.The results show that the intensity of gneiss rockburst decreases with decrease of unloading rate,which is manifested as the reduction of AE energy and fragments ejection velocity.The mechanisms are proposed to explain this effect:(i)The reduction of unloading rate changes the crack propagation mechanism in the process of rockburst.This makes the rockbursts change from the tensile failure mechanism at high unloading rate to the tension-shear mixed failure mechanism at low unloading rate,and more energy released in the form of shear crack propagation.Then,less strain energy is converted into kinetic energy of fragments ejection.(ii)Less plate cracking degree of gneiss has taken shape due to decrease of unloading rate,resulting in the destruction of rockburst incubation process.The enlightenments of reducing the unloading rate for the project are also described quantitatively.The rockburst magnitude is reduced from the medium magnitude at the unloading rate of 0.1 MPa/s to the slight magnitude at the unloading rate of 0.025 MPa/s,which was judged by the ejection velocity.

A new era of mutation rate analyses: Concepts and methods

The mutation rate is a pivotal biological characteristic,intricately governed by natural selection and historically garnering considerable attention.Recent advances in high-throughput sequencing and analytical methodologies have profoundly transformed our understanding in this domain,ushering in an unprecedented era of mutation rate research.This paper aims to provide a comprehensive overview of the key concepts and methodologies frequently employed in the study of mutation rates.It examines various types of mutations,explores the evolutionary dynamics and associated theories,and synthesizes both classical and contemporary hypotheses.Furthermore,this review comprehensively explores recent advances in understanding germline and somatic mutations in animals and offers an overview of experimental methodologies,mutational patterns,molecular mechanisms,and driving forces influencing variations in mutation rates across species and tissues.Finally,it proposes several potential research directions and pressing questions for future investigations.

Effects of microwave pretreatment on zinc extraction from spent catalyst saturated with zinc acetate

A new technology for microwave pretreatment of spent catalyst on Zn extraction by HCl leaching was proposed and the temperature-change curve of spent catalyst under microwave irradiation was measured.The influence of microwave pretreatment temperature and microwave irradiation time on zinc extraction was investigated and the mechanism of microwave pretreatment for spent catalyst was analyzed.The results show that microwave pretreatment can greatly enhance the leaching rate of Zn.The Zn extraction reaches 96.58%under the conditions of microwave pretreatment temperature of 950℃and the microwave irradiation time of 12 min.The blocked pores of spent catalyst can be opened through microwave pretreatment,increasing the contact area of leaching reagent and zinc.

Dynamic tensile strength and failure mechanisms of thermally treated sandstone under dry and water-saturated conditions

To study the tensile strength and failure mechanisms of rock with hydro-thermal coupling damage under different loading rates,a series of static and dynamic splitting tests were conducted on thermally treated sandstone under dry and water-saturated conditions.Experimental results showed that high temperatures effectively weakened the tensile strength of sandstone specimens,and the P-wave velocity declined with increasing temperature.Overall,thermal damage of rock increased gradually with increasing temperature,but obvious negative damage appeared at the temperature of 100℃.The water-saturated sandstone specimens had lower indirect tensile strength than the dry ones,which indicated that water-rock interaction led to secondary damage in heat-treated rock.Under both dry and water-saturated conditions,the dynamic tensile strength of sandstone increased with the increase of strain rate.The water-saturated rock specimens showed stronger rate dependence than the dry ones,but the loading rate sensitivity of thermally treated rock decreased with increasing treatment temperature.With the help of scanning electron microscopy technology,the thermal fractures of rock,caused by extreme temperature,were analyzed.Hydro-physical mechanisms of sandstone under different loading rate conditions after heat treatment were further discussed.

Omega-3 polyunsaturated fatty acids promote liver regeneration after 90% hepatectomy in rats

AIM:To evaluate the effectiveness of omega-3 polyunsaturated fatty acid(ω-3 PUFA) administration on liver regeneration after 90% partial hepatectomy(PH) in rats.METHODS:ω-3 PUFAs were intravenously injected in the ω-3 PUFA group before PH surgery.PH,sparing only the caudate lobe,was performed in both the control and the ω-3 PUFA group.Survival rates,liver weight/body weight ratios,liver weights,HE staining,transmission electron microscope imaging,nuclearassociated antigen Ki-67,enzyme-linked immunosorbent assay and signal transduction were evaluated to analyze liver regeneration.RESULTS:All rats in the control group died within 30 h after hepatectomy.Survival rates in the ω-3 PUFA group were 20/20 at 30 h and 4/20 1 wk after PH.Liver weight/body weight ratios and liver weights increased significantly in the ω-3 PUFA group.The structure of sinusoidal endothelial cells and space of Disse was greatly restored in the ω-3 PUFA group compared to the control group after PH.In the ω-3 PUFA group,interleukin(IL)-4 and IL-10 levels were significantly increased whereas IL-6 and tumor necrosis factor-levels were dramatically decreased.In addition,activation of protein kinase B(Akt) and of signal transducer and activator of transcription 3 signaling pathway were identified at an earlier time after PH in the ω-3 PUFA group.CONCLUSION:Omega-3 polyunsaturated fatty acids may prevent acute liver failure and promote liver regeneration after 90% hepatectomy in rats.

Effects of temperature-dependent viscosity variation on entropy generation, heat and fluid flow through a porous-saturated duct of rectangular cross-section

Effect of temperature-dependent viscosity on fully developed forced convection in a duct of rectangular cross-section occupied by a fluid-saturated porous medium is investigated analytically. The Darcy flow model is applied and the viscosity-temperature relation is assumed to be an inverse-linear one. The case of uniform heat flux on the walls, i.e. the H boundary condition in the terminology of Kays and Crawford [12], is treated. For the case of a fluid whose viscosity decreases with temperature, it is found that the effect of the variation is to increase the Nusselt number for heated walls. Having found the velocity and the temperature distribution, the second law of thermodynamics is invoked to find the local and average entropy generation rate. Expressions for the entropy generation rate, the Bejan number, the heat transfer irreversibility, and the fluid flow irreversibility are presented in terms of the Brinkman number, the Péclet number, the viscosity variation number, the dimensionless wall heat flux, and the aspect ratio （width to height ratio）. These expressions let a parametric study of the problem based on which it is observed that the entropy generated due to flow in a duct of square cross-section is more than those of rectangular counterparts while increasing the aspect ratio decreases the entropy generation rate similar to what previously reported for the clear flow case by Ratts and Rant [14].

Stability Analysis of SIQS Epidemic Model with Saturated Incidence Rate

A SIQS epidemic model with saturated incidence rate is studied. Two equilibrium points exist for the system, disease-free and endemic equilibrium. The stability of the disease-free equilibrium and endemic equilibrium exists when the basic reproduction number R0, is less or greater than unity respectively. The global stability of the disease-free and endemic equilibrium is proved using Lyapunov functions and Poincare-Bendixson theorem plus Dulac’s criterion respectively.

Adaptive Retransmission Design for Wireless Federated Edge Learning

As a popular distributed machine learning framework,wireless federated edge learning(FEEL)can keep original data local,while uploading model training updates to protect privacy and prevent data silos.However,since wireless channels are usually unreliable,there is no guarantee that the model updates uploaded by local devices are correct,thus greatly degrading the performance of the wireless FEEL.Conventional retransmission schemes designed for wireless systems generally aim to maximize the system throughput or minimize the packet error rate,which is not suitable for the FEEL system.A novel retransmission scheme is proposed for the FEEL system to make a tradeoff between model training accuracy and retransmission latency.In the proposed scheme,a retransmission device selection criterion is first designed based on the channel condition,the number of local data,and the importance of model updates.In addition,we design the air interface signaling under this retransmission scheme to facilitate the implementation of the proposed scheme in practical scenarios.Finally,the effectiveness of the proposed retransmission scheme is validated through simulation experiments.

Intrusion Detection Using Federated Learning for Computing

The integration of clusters,grids,clouds,edges and other computing platforms result in contemporary technology of jungle computing.This novel technique has the aptitude to tackle high performance computation systems and it manages the usage of all computing platforms at a time.Federated learning is a collaborative machine learning approach without centralized training data.The proposed system effectively detects the intrusion attack without human intervention and subsequently detects anomalous deviations in device communication behavior,potentially caused by malicious adversaries and it can emerge with new and unknown attacks.The main objective is to learn overall behavior of an intruder while performing attacks to the assumed target service.Moreover,the updated system model is send to the centralized server in jungle computing,to detect their pattern.Federated learning greatly helps the machine to study the type of attack from each device and this technique paves a way to complete dominion over all malicious behaviors.In our proposed work,we have implemented an intrusion detection system that has high accuracy,low False Positive Rate(FPR)scalable,and versatile for the jungle computing environment.The execution time taken to complete a round is less than two seconds,with an accuracy rate of 96%.

Covert Communication in Integrated High Altitude Platform Station Terrestrial Networks

In recent years,Internet of Things(IoT)technology has emerged and gradually sprung up.As the needs of largescale IoT applications cannot be satisfied by the fifth generation(5G)network,wireless communication network needs to be developed into the sixth generation(6G)network.However,with the increasingly prominent security problems of wireless communication networks such as 6G,covert communication has been recognized as one of the most promising solutions.Covert communication can realize the transmission of hidden information between both sides of communication to a certain extent,which makes the transmission content and transmission behavior challenging to be detected by noncooperative eavesdroppers.In addition,the integrated high altitude platform station(HAPS)terrestrial network is considered a promising development direction because of its flexibility and scalability.Based on the above facts,this article investigates the covert communication in an integrated HAPS terrestrial network,where a constant power auxiliary node is utilized to send artificial noise(AN)to realize the covert communication.Specifically,the covert constraint relationship between the transmitting and auxiliary nodes is derived.Moreover,the closed-form expressions of outage probability(OP)and effective covert communication rate are obtained.Finally,numerical results are provided to verify our analysis and reveal the impacts of critical parameters on the system performance.