Stochastic Factors Research Articles

The Action Point Angle of Sight: A Traffic Generation Method for Driving Simulation, as a Small Step to Safe, Sustainable and Smart Cities

Computer simulations of traffic and driving provide essential solutions to reduce risk and cost in traffic-related studies and research. Through nearly 90 years of simulation development, many research projects have attempted to improve the various aspects of realism through the use of traffic theory, cameras, eye-tracking devices, sensors, etc. However, the previous studies still present limitations, such as not being able to simulate mixed and chaotic traffic flows, as well as limited integration/interoperability with 3D driving simulators. Thus, instead of reusing previous traffic simulators, in this paper, we define relevant concepts and describe the development and testing of a novel traffic generator. First, we introduce realistic aspects to improve traffic generation, including interactive physics (i.e., interactions based on physics among the vehicles, infrastructure, and weather) and natural traffic behaviors (e.g., road user behaviors and traffic rules), allowing the self-driving vehicle behaviors to mimic human behaviors under stochastic factors such as random vehicles and speed. Second, we gain experiences from the technical deficiencies of existing systems. Third, we propose methods for traffic generation based on the action point angle of sight (APAS) formula, which adheres to these constraints and is interoperable with modern driving simulators. We also conducted quantitative evaluations in two experiments (comprising 250 trials), in order to prove that the proposed solution can effectively simulate mixed traffic flows. Moreover, the approaches presented in this study can help self-driving cars to find their way at an intersection/T-junction, as well as allowing them to steer automatically after an accident occurs. The results indicate that traffic generation algorithms based on these new traffic theories can be effectively implemented and used in modern driving simulators and multi-driving simulators, outperforming previous traffic generators based on repurposed technologies.

The influence of time delay and Gaussian white noise on the dynamics of tobacco smoking model

This article analyses the influence of psychological and social addictions such as drug and tobacco consumption problems on humans by using an appropriate nonlinear computational formulation. We propose a mathematical model to simulate the multiple stages and behaviors of the smoking addiction process. Firstly, we present the dynamics of the local and global stability of the tobacco smoking model at existing equilibrium points and discuss the Hopf-Bifurcation analysis of the delayed model by regarding the time delay as a bifurcation parameter and derive specific formulas for the stability and direction of the Hopf bifurcation employing the normal form theory and centre manifold theorem. Then, we enhance our delayed model by considering the effects of the social environment. Precisely, we incorporate additive white noises into our delayed system to simulate the stochastic factors. Then, we analytically present some statistical properties of the perturbed system. Finally, we performed the sensitivity analysis and some numerical examples to discuss the feasibility of our theoretical findings.

Semi-global exponential stability of stochastic nonlinear functional sampling systems by emulation approach

In this paper, the semi-global exponential stability is studied for the stochastic nonlinear functional systems by emulation of sampled-data controller. In consideration of the stochastic factor, a novel definition of the right and upper Dini’s derivative of the constructed functional is given. Based on this novel definition, combining with stochastic analysis techniques and Lyapunov method, some sufficient criteria for the semi-global exponential stability of the stochastic nonlinear functional systems by suitably fast sampling are given. As a special case, a class of stochastic nonlinear functional systems with multiple time delays is studied and two coefficient type theorems that lead to the semi-global exponential stability of the sampling system are derived. Finally, a practical application about parallel active suspension systems with time delay and stochastic disturbance is discussed at length and the corresponding numerical example is given to illustrate the feasibility of the theoretical results.

Are some people more consistent? Examining the stability and underlying processes of personality profile consistency.

Personality traits are relatively consistent across time, as indicated by test-retest correlations. However, ipsative consistency approaches suggest there are individual differences in this consistency. Despite this, it is unknown whether these differences are due to person-level characteristics (i.e., some people are just more consistent) or exogenous forces (i.e., lack of consistency is due to environmental changes). Moreover, it is unclear whether the processes promoting long-term consistency are the same across people. We examine these two questions using item-level profile correlations across four to nine waves of data with four data sets (N = 21,616) with multilevel asymptotic growth models. Results indicated that there were, on average, high levels of profile consistency. However, there were notable individual differences in initial profile correlation values as well as in changes in levels of consistency across time, indicating that some people are more stably consistent than others. Moreover, the directions of people's trajectories across increasing time intervals suggest that the mechanisms responsible for reinforcing personality consistency vary across people. These effects were typically moderated by age at 30 years old, maturity-related traits, and education level. Overall, findings indicate some people are more consistent than others, such that this stable level of (in)consistency is a dispositional factor. Additionally, individual differences in profile consistency are shaped by different levels of three processes. On average, stochastic factors are not impactful for most individuals, and transactional processes have an important role in increasing consistency for a sizable amount of people-nuances not previously revealed when focusing on rank-order stability. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Evolutionary dynamics of influenza A/H1N1 virus circulating in India from 2011 to 2021

Influenza A viruses (IAV) are fast-evolving pathogens with a very high mutation rate (2.0×10-6 to 2.0×10-4) compared to the influenza B (IBV) and influenza C (ICV) viruses. Generally, the tropical regions are considered as the reservoir for the IAV's genetic and antigenic evolutionary modification to be reintroduced into the temperate region. Therefore, in connection to the above facts, the present study emphasized on the evolutionary dynamic of the pandemic-2009 H1N1 (pdmH1N1) influenza virus in India. A total of Ninety-two whole genome sequences of pdmH1N1 viruses circulating in India during the 2009 post-pandemic era were analysed. The temporal signal of the study, indicating strict molecular clock evolutionary process and the overall substitution rate is 2.21×10-3/site/year. We are using the nonparametric Bayesian Skygrid coalescent model to estimates the effective past population dynamic or size over time. The study exhibits a strong relation between the genetic distances and collection dates of the Indian pdmH1N1 strain. The skygrid plot represents the highest exponential growth of IAV in rainy and winter seasons. All the genes of Indian pdmH1N1 were under purifying selective pressure. The Bayesian time-imprinted phylogenetic tree represents the following clade distributions in the country within the last 10years; I) clade 6, 6C, and 7 were co-circulating between the 2011 to 2012 flu season; II) the clade 6B was introduced into circulation in the late seasons of 2012; III) lastly, the clade 6B remain existing in the circulation and segregated into subclade 6B.1 with five different subgroup (6B.1A, 6B.1A.1, 6B.1A.5a, 6B.1A.5a.2, 6B.1A.7). The recent circulating strain of Indian H1N1 strain represent the insertion of basic-amino acid arginine (R) in the cleavage site (325/K-R) of HA protein and amino acid mutation (314/I-M) on the lateral head surface domain of NA protein. Moreover, the study indicates the sporadic presence of the oseltamivir-resistant (275/H-Y) H1N1 variant in circulation. The present study suggests the purifying selective pressure and stochastic ecological factors for the existence and adaptation of a certain clade 6B in the host populations and additional information on the emergence of mutated strains in the circulation.

V2V Energy Trading in Residential Microgrids Considering Multiple Constraints via Bayesian Game

The V2V (vehicle-to-vehicle) energy swapping strategy provides an alternative charging for electric vehicles (EVs) to alleviate the problem of overload caused by the un-coordinately charges in residential microgrids (MGs) during the peak. However, stochastic factors of EVs and neglected network losses cause inflexibility and impracticality of the existing methods. Focused on the stochastic factors of energy trading caused by EVs and network constraints in residential MGs scenario, a V2V Energy Trading in Residential Microgrids (VETRM) considering multiple constraints via Bayesian game model is proposed. Frist, the Bayesian game modeled types of players by information including the stochastic characteristics of EVs, which results in uncertainties that the game participants determine the roles of seller or buyer that depends on the states of power surplus or lack. Then, utility functions based on the sensitivity analysis to the impact of V2V transactions on the network and to guarantee the exchange of energies to inviolate network constraints are established. The solution of model based on game equilibrium has been rigorously derived. Two scenarios fulfill the comparisons of existing models and proposed model for simulation including IEEE 33 and IEEE 123 bus system that the proposed model improve the revenues of EV in reducing energy loss and smoothing the peak of the power system to demonstrate the effectiveness of the VETRM model.

Spatial scale affects the importance of deterministic and stochastic factors in the structuring of tadpole assemblages in Brazilian Cerrado

Many factors influence the structure of natural assemblages. Species interaction and environmental factors may generate deterministic patterns, whereas dispersal and ecological drift may generate stochastic patterns. We used pond systems to understand how deterministic and stochastic factors interact and influence tadpole assemblages at different spatial scales. We used variation partitioning and a co-occurrence analysis to evaluate how local environment heterogeneity, species interaction, and spatial variables affected species composition at local and regional scales in Brazilian savanna. Both deterministic and stochastic processes were important to explain tadpole distribution at regional scale, but with a greater contribution of stochastic factors. At local scales, environmental and niche traits were more important to explain tadpole distribution into the habitats. We demonstrate that in Brazilian Cerrado, species composition can be explained by the "MacArthur paradox", in which niche processes are important at local scales, whereas dispersal constraints and population processes lead to stochastic patterns in species distribution at large spatial scales.

Effect of the bacterial community assembly process on the microbial remediation of petroleum hydrocarbon-contaminated soil.

The accumulation of petroleum hydrocarbons (PHs) in the soil can reduce soil porosity, hinder plant growth, and have a serious negative impact on soil ecology. Previously, we developed PH-degrading bacteria and discovered that the interaction between microorganisms may be more important in the degradation of PHs than the ability of exogenous-degrading bacteria. Nevertheless, the role of microbial ecological processes in the remediation process is frequently overlooked. This study established six different surfactant-enhanced microbial remediation treatments on PH-contaminated soil using a pot experiment. After 30 days, the PHs removal rate was calculated; the bacterial community assembly process was also determined using the R language program, and the assembly process and the PHs removal rate were correlated. The rhamnolipid-enhanced Bacillus methylotrophicus remediation achieved the highest PHs removal rate, and the bacterial community assembly process was impacted by deterministic factors, whereas the bacterial community assembly process in other treatments with low removal rates was affected by stochastic factors. When compared to the stochastic assembly process and the PHs removal rate, the deterministic assembly process and the PHs removal rate were found to have a significant positive correlation, indicating that the deterministic assembly process of bacterial communities may mediate the efficient removal of PHs. Therefore, this study recommends that when using microorganisms to remediate contaminated soil, care should be taken to avoid strong soil disturbance because directional regulation of bacterial ecological functions can also contribute to efficient removal of pollutants.

A Comprehensive Methodology for Investment Project Assessment Based on Monte Carlo Simulation

This article presents a methodology for assessing investment projects representing the sequence of steps necessary for a comprehensive assessment and optimization of an investment project. The assessment process starts with the quantitative forecasting of stochastic input factors, with the selection of risk factors and the definition of their uncertainty. That is followed by the design of a mathematical model for calculating the criterion of economic efficiency of investment, its calculation mathematically, and forecasting by Monte Carlo simulation. The simulation output is assessed from the point of view of risk, and in case of an unacceptable result, the possibilities for project optimization are proposed. Finally, the proposed methodology was applied to an investment project model, where individual principles are practically demonstrated.

Guiding severely anisotropic twinning bands in Magnesium: An in situ investigation by full-field microscopic image correlation

A critical issue for lightweight Magnesium alloys is their propensity for strain localization at the component scale, linked to the peculiar twinning phenomenon. For the (c-axes-aligned) rolling texture, highly compact coordinated twinning bands (CTBs) form that, uniquely, have a singular plane of shear. Normally, where these bands emerge, and progress are up to stochastic factors. Here, a cross-notched sample design is nominated to guide the bands of conjugate orientations into predetermined diagonal corridors and enforce their overlap at a prefixed location. The deformation fields in the Magnesium AZ31 sample are in situ monitored with an advanced microscopic image correlation (micro-DIC) variant that has a unique combination of extreme field coverage (∼1.5 ×105 grains), intragranular resolution (∼102 data points per grain) and very high time-step resolution (0.05–0.1% nominal strain increments over the twin plateau). The latter allows investigating the emergence, advance, lateral growth, and interaction of CTBs with extreme detail over absolute and sequential micro-DIC strain maps. The sample design is successful in guiding the CTB formations into the designated corridors. Seed segments of CTBs first make a cross connection across the sample, followed by lateral expansion that proceeds until the corridor is roughly filled. This happens sequentially for the two diagonal corridors, forcing the second band to pass through the first. The band strain is reduced by about 25% at the enforced overlap compared to the characteristic intensity it exhibits outside it (around 2.3%)—a direct measurement of the dilution of the strain activity of a CTB as it crosses another CTB. The uniqueness of this application in guiding severely anisotropic bands is contrasted with the micro-DIC fields of a transversely isotropic sample of the same material that is analogously put under a twin-dominated deformation.

A Prediction-Based Approach for Online Dynamic Appointment Scheduling: A Case Study in Radiotherapy Treatment

Patient scheduling is a difficult task involving stochastic factors, such as the unknown arrival times of patients. Similarly, the scheduling of radiotherapy for cancer treatments needs to handle patients with different urgency levels when allocating resources. High-priority patients may arrive at any time, and there must be resources available to accommodate them. A common solution is to reserve a flat percentage of treatment capacity for emergency patients. However, this solution can result in overdue treatments for urgent patients, a failure to fully exploit treatment capacity, and delayed treatments for low-priority patients. This problem is especially severe in large and crowded hospitals. In this paper, we propose a prediction-based approach for online dynamic radiotherapy scheduling that dynamically adapts the present scheduling decision based on each incoming patient and the current allocation of resources. Our approach is based on a regression model trained to recognize the links between patients’ arrival patterns and their ideal waiting time in optimal off-line solutions when all future arrivals are known in advance. When our prediction-based approach is compared with flat-reservation policies, it does a better job of preventing overdue treatments for emergency patients and also maintains comparable waiting times for the other patients. We also demonstrate how our proposed approach supports explainability and interpretability in scheduling decisions using Shapley additive explanation values. History: Accepted by Erwin Pesch, Area Editor for Heuristic Search & Approximation Algorithms. Funding: Mitacs Accélération IT26995 and Canada Research Chair in Analytics and Logistics in Healthcare (HANALOG). Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.1289 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2021.0342 ) at ( http://dx.doi.org/10.5281/zenodo.7579533 ).

Effective sampling for drift mitigation in machine learning using scenario selection: A microgrid case study

Predictive modeling is pervasive across a variety of industries (e.g., driving patterns in insurance, fraud detection in finance, and forecasting in energy). However, the deterioration of prediction accuracy for most machine learning (ML) models due to the drift is inevitable despite having acceptable performance in a test setting. Drift is a natural occurrence as cumulative information changes over time but should be regulated to ensure an ML model’s prediction remains relevant in real-time when decisions are being made. This study proposes a drift mitigation framework (DMF) to obtain an effective sample size in a scalable and unbiased manner for sustainable predictive performance from ML models using microgrids (MGs) as a testbed. Scenario selection was used as an alternative sampling technique to obtain an effective sample from historical data contributing to probability theory. These scenarios were evaluated using a quantile-quantile (Q-Q) plot, Welch’s T-test, and relative entropy measures to ensure the obtained sample effectively captures the general population behavior. The results showed two of the three climate factors used in our experiment formed a nearly straight line on their Q-Q plots, suggesting the effective sample retained comparable statistical properties to theoretical distributions fitted to the original population and complete training data. At an alpha equal to 0.05, a hypothesis test was conducted with the null hypothesis claiming the means of reduced and complete data were statistically equivalent for ambient temperature, solar irradiance, and wind speed. The p-values obtained for each stochastic climate factor were 1.01, 0.296, and 4.13 suggesting insufficient evidence to reject the null hypothesis. Similarly, the resulting population stability index (PSI) values for each stochastic climate factor were 0.175, 0.352, and 0.023 respectively. Hence, there was no significant shift between the population data and the effective sample across each factor.

A comparative study of green growth efficiency in Yangtze River Economic Belt and Yellow River Basin between 2010 and 2020

The Yangtze River Economic Belt and the Yellow River Basin are important economic regions and ecological barriers in China. Promoting the development of the Yangtze River Economic Belt and promoting ecological protection and high-quality development in the Yellow River Basin are major regional strategies implemented by the Chinese government, and the green growth of the two regions is important for the high-quality sustainable development of the whole China. To investigate the regional differences in green growth efficiency of the same type of geographical units, this paper measures the green growth efficiency and decomposition indicators of the Yangtze River Economic Belt and the Yellow River Basin from 2010 to 2020 using a three-stage DEA model and the Malmquist index method and establishes a panel Tobit model to identify the influencing factors of green growth efficiency. The results show that: ①After using the three-stage DEA model to remove the influence of external environment and stochastic factors, the mean values of green growth efficiency of Yangtze River Economic Zone and Yellow River Basin from 2010 to 2020 are 0.996 and 1.089, respectively. The change of green growth efficiency of Yangtze River Economic Zone is slightly higher than that of Yellow River Basin. ②The Malmquist indexes of the Yangtze River Economic Belt and the Yellow River Basin have generally increased, with the Technological Progress Index, which characterizes technological innovation, being the main endogenous driver of green growth efficiency in the Yellow River Basin, while the technical efficiency index, which characterizes factor mix and management level, is more significant in the Yangtze River Economic Belt. ③The Tobit model regression results show that the factors influencing green growth efficiency are also different in the two regions. Among them, the urbanization rate has a significantly positive effect on the two regions, while the effects of environmental regulation and research intensity are not significant. External openness has a suppressive effect on green growth efficiency in the Yangtze River Economic Belt, while the level of financial development and human capital negatively affect green growth efficiency in the Yellow River Basin. Therefore, green development in the new era should pay attention to the differences between different regions, and make appropriate development policies according to the local conditions of the development status of different regions.

CERN's sanctions regime against Russian science: nature, features and consequences

The subject of the article is the process of forming the CERN sanctions regime regarding Russia's participation in global scientific megaprojects in the field of theoretical physics. The purpose of the article is to reveal the content and organizational mechanism of CERN sanctions aimed at ending institutional cooperation with Russia. The objectives of the study include determining the algorithm of the long-term bilateral strategic partnership between Russia and CERN; revealing the grounds and logic of CERN's unilateral termination of promising cooperation with Russia, as well as predicting the negative consequences of sanctions. The authors pay special attention to testing the research hypothesis that CERN's anti–Russian sanctions policy is based on a combination of, on the one hand, politicized principles, and, on the other, extreme prudence, which resulted in the "stretching" of the measures taken over time and their focus on taking into account the current geopolitical situation. This indicates the incompleteness of the transition from the logic of scientific diplomacy to the rigid logic of sanctions, which makes it possible to predict the preservation of some elements of scientific diplomacy in relations between CERN and Russia. The methodological base of the research includes traditional methods and approaches (analysis and synthesis, abstraction and generalization; modeling; forecasting; the general scientific principle of dialectical development; a systematic approach), as well as new methods (meta-analysis, discursive analysis, stochastic factor analysis). It is concluded that CERN's sanctions policy, based on an appeal to value motivations, is characterized by flexible consideration of the current geopolitical situation and the gradual nature of the restrictive measures taken. The research hypothesis about the preservation of a certain potential of scientific diplomacy in relations between CERN and Russia has been confirmed in the work. This is reflected in the continuation of cooperation and fulfillment of obligations under existing bilateral agreements. It is proved that, by their nature, CERN sanctions belong to an independent category of sanctions against Russian science, which are imposed by international structures operating in the field of megascience. The novelty of the research lies in the actualization of the need to develop a special direction of Russian scientific and technical policy aimed at mitigating the consequences of sanctions complications in relations with international organizational structures in the field of megascience.

FOXP1 Haploinsufficiency Contributes to the Development of Congenital Diaphragmatic Hernia.

FOXP1 encodes a transcription factor involved in tissue regulation and cell-type-specific functions. Haploinsufficiency of FOXP1 is associated with a neurodevelopmental disorder: autosomal dominant mental retardation with language impairment with or without autistic features. More recently, heterozygous FOXP1 variants have also been shown to cause a variety of structural birth defects including central nervous system (CNS) anomalies, congenital heart defects, congenital anomalies of the kidney and urinary tract, cryptorchidism, and hypospadias. In this report, we present a previously unpublished case of an individual with congenital diaphragmatic hernia (CDH) who carries an approximately 3.8 Mb deletion. Based on this deletion, and deletions previously reported in two other individuals with CDH, we define a CDH critical region on chromosome 3p13 that includes FOXP1 and four other protein-coding genes. We also provide detailed clinical descriptions of two previously reported individuals with CDH who carry de novo, pathogenic variants in FOXP1 that are predicted to trigger nonsense-mediated mRNA decay. A subset of individuals with putatively deleterious FOXP4 variants has also been shown to develop CDH. Since FOXP proteins function as homo- or heterodimers and the homologs of FOXP1 and FOXP4 are expressed at the same time points in the embryonic mouse diaphragm, they may function together as a dimer, or in parallel as homodimers, to regulate gene expression during diaphragm development. Not all individuals with heterozygous, loss-of-function changes in FOXP1 develop CDH. Hence, we conclude that FOXP1 acts as a susceptibility factor that contributes to the development of CDH in conjunction with other genetic, epigenetic, environmental, and/or stochastic factors.

Do ecological protection approaches affect total factor productivity change of cropland production in Sweden?

Ecological protection approaches are important in achieving sustainable productivity growth in agriculture. Based on an unbalanced panel dataset for 2010–2016, we used stochastic frontier analysis-based Malmquist total factor productivity index to estimate total factor productivity change of Swedish crop production and its components (efficiency change, technical change, scale change). We then examined the effect of ecological protection approaches on total factor productivity change. The empirical results demonstrated that ecological protection approaches such as organic farming, mixed cropping or integrated farming could hamper total factor productivity growth. The results also indicated that average total factor productivity change in the study period was positive and average technical efficiency of the Swedish crop production was 71%. Among the components of total factor productivity change, average scale change was positive. Average technical efficiency change and average technical change were both negative. If technical efficiency and technological progress can be improved, that would increase the positive change in total factor productivity. This suggests that policies on compensation or insurance against productivity loss are required to encourage mainstreaming of ecological protection approaches among farmers.

Present-Day Crustal Velocity Field in Ecuador from cGPS Position Time Series

The present study analyzes the GNSS time series obtained between the years 2017 and 2022 for the calculation of absolute and residual rates of Ecuador in 10 stations (ABEC, CUEC, ECEC, EPEC, FOEC, GZEC, MUEC, PLEC, RIOP, SEEC, TPC) of the continuous monitoring REGME network. Considering that the latest studies refer to periods 2012-2014 and Ecuador is located in an area of high seismic activity, it is important to update the GNSS rates. The RINEX data were provided by the Military Geographic Institute of Ecuador, the governing institution of geoinformation in that country; for processing, GipsyX scientific software was used with a PPP mode, considering 24 h sessions, and high precision was achieved. For the analysis of time series, the SARI platform was used. The series was modeled using a least-squares adjustment, which delivered the velocities for each station in the three local topocentric components. The results were contrasted with other studies, obtaining interesting conclusions as the presence of abnormal post-seismic rates stands out due to the high rate of seismic occurrence in Ecuador, and reaffirms the idea of a constant update of velocities for the Ecuadorian territory and the inclusion of the stochastic factor in the analysis of GNSS time series, since it can affect the ability to obtain the final GNSS velocities.

Rhizosphere Fungal Dynamics in Sugarcane during Different Growth Stages

Understanding the normal variation of the sugarcane rhizosphere fungal community throughout its life cycle is essential for the development of agricultural practices for fungal and ecological health associated with the microbiota. Therefore, we performed high-throughput sequencing of 18S rDNA of soil samples using the Illumina sequencing platform for correlation analysis of rhizosphere fungal community time series, covering information from 84 samples in four growth periods. The results revealed that the sugarcane rhizosphere fungi possessed the maximum fungal richness in Tillering. Rhizosphere fungi were closely associated with sugarcane growth, including Ascomycota, Basidiomycota, and Chytridiomycota, which showed high abundance in a stage-specific manner. Through the Manhattan plots, 10 fungal genera showed a decreasing trend throughout the sugarcane growth, and two fungal genera were significantly enriched at three stages of sugarcane growth (p < 0.05) including Pseudallescheria (Microascales, Microascaceae) and Nectriaceae (Hypocreales, Nectriaceae). In addition, soil pH, soil temperature, total nitrogen, and total potassium were critical drivers of fungal community structure at different stages of sugarcane growth. We also found that sugarcane disease status showed a significant and strong negative effect on selected soil properties by using structural equation modeling (SEM), suggesting that poor soil increases the likelihood of sugarcane disease. In addition, the assembly of sugarcane rhizosphere fungal community structure was mainly influenced by stochastic factors, but after the sugarcane root system became stable (Maturity), the stochastic contribution rate decreased to the lowest value. Our work provides a more extensive and solid basis for the biological control of sugarcane potential fungal diseases.

Theoretical and experimental investigation on teeth impacts between the inner hub and the friction plate of the planetary transmission system's clutch

When the friction plate and the steel plate of a planetary transmission system's clutch are detached, there will be continuous teeth impacts between the clutch friction plate and the inner hub (i.e. the floating ring gear). These impacts exhibit strong nonlinear and stochastic characteristics, especially under variable operating conditions, which have significant effects on the reliability of the friction plate. In this paper, an original dynamic impact model considering the coupling of several stochastic factors (backlash, eccentricity, impact position, etc.) is established to study the impact characteristics between the mating teeth of the clutch friction plate and the inner hub. The changes in impact features such as the total number and position of impact teeth, and the impact force are discussed by the coupling effect between different parameters such as backlash, speed fluctuation amplitude and speed fluctuation frequency. A friction plate impact test bench is designed to measure the dynamic impact force, which is directly compared to the simulation results to verify the proposed dynamic impact model. The analysis results of this study can provide a theoretical basis for improving the service performance and life of the friction plate of the planetary transmission system's clutch.

EPIGUI: Graphical User Interface for Simulating Epidemics on Networks

This paper presents a graphical interface called EPIGUI, which allows the study of the dynamics of an infectious disease spread using compartmental models in combination with complex networks. This interface aims at considering stochastic factors that govern the evolution of an infection in a network. Moreover, it provides simple tools to create networks of agents and to define the epidemiological parameters of outbreaks. There are six common infectious disease models (SI, SIS, SIR, SIRS, SEIR, and SEIRS) or a user can provide another model, combining compartments. Moreover, in the simulations the user can either include a synthetic network generated according to a network model (random, small-world, scale-free, modular, or hierarchical) or a real network. This approach can help understand the paths followed by outbreaks in a given community and design new strategies to prevent and to control them.