The relationship between compartment models and their stochastic counterparts:A comparative study with examples of the COVID-19 epidemic modeling

Deterministic compartment models(CMs)and stochastic models,including stochastic CMs and agent-based models,are widely utilized in epidemic modeling.However,the relationship between CMs and their corresponding stochastic models is not well understood.The present study aimed to address this gap by conducting a comparative study using the susceptible,exposed,infectious,and recovered(SEIR)model and its extended CMs from the coronavirus disease 2019 modeling literature.We demonstrated the equivalence of the numerical solution of CMs using the Euler scheme and their stochastic counterparts through theoretical analysis and simulations.Based on this equivalence,we proposed an efficient model calibration method that could replicate the exact solution of CMs in the corresponding stochastic models through parameter adjustment.The advancement in calibration techniques enhanced the accuracy of stochastic modeling in capturing the dynamics of epidemics.However,it should be noted that discrete-time stochastic models cannot perfectly reproduce the exact solution of continuous-time CMs.Additionally,we proposed a new stochastic compartment and agent mixed model as an alternative to agent-based models for large-scale population simulations with a limited number of agents.This model offered a balance between computational efficiency and accuracy.The results of this research contributed to the comparison and unification of deterministic CMs and stochastic models in epidemic modeling.Furthermore,the results had implications for the development of hybrid models that integrated the strengths of both frameworks.Overall,the present study has provided valuable epidemic modeling techniques and their practical applications for understanding and controlling the spread of infectious diseases.

Exploring mechanism of hidden,steep obliquely inclined bedding landslides using a 3DEC model:A case study of the Shanyang landslide in Shaanxi Province,China

Catastrophic geological disasters frequently occur on slopes with obliquely inclined bedding structures(also referred to as obliquely inclined bedding slopes),where the apparent dip sliding is not readily visible.This phenomenon has become a focal point in landslide research.Yet,there is a lack of studies on the failure modes and mechanisms of hidden,steep obliquely inclined bedding slopes.This study investigated the Shanyang landslide in Shaanxi Province,China.Using field investigations,laboratory tests of geotechnical parameters,and the 3DEC software,this study developed a numerical model of the landslide to analyze the failure process of such slopes.The findings indicate that the Shanyang landslide primarily crept along a weak interlayer under the action of gravity.The landslide,initially following a dip angle with the support of a stable inclined rock mass,shifted direction under the influence of argillization in the weak interlayer,moving towards the apparent dip angle.The slide resistance effect of the karstic dissolution zone was increasingly significant during this process,with lateral friction being the primary resistance force.A reduction in the lateral friction due to karstic dissolution made the apparent dip sliding characteristics of the Shanyang landslide more pronounced.Notably,deformations such as bending and uplift at the slope’s foot suggest that the main slide resistance shifts from lateral friction within the karstic dissolution zone to the slope foot’s resistance force,leading to the eventual buckling failure of the landslide.This study unveils a novel failure mode of apparent dip creep-buckling in the Shanyang landslide,highlighting the critical role of lateral friction from the karstic dissolution zone in its failure mechanism.These insights offer a valuable reference for mitigating risks and preventing disasters related to obliquely inclined bedding landslides.

Offshore Software Maintenance Outsourcing Process Model Validation:A Case Study Approach

The successful execution and management of Offshore Software Maintenance Outsourcing(OSMO)can be very beneficial for OSMO vendors and the OSMO client.Although a lot of research on software outsourcing is going on,most of the existing literature on offshore outsourcing deals with the outsourcing of software development only.Several frameworks have been developed focusing on guiding software systemmanagers concerning offshore software outsourcing.However,none of these studies delivered comprehensive guidelines for managing the whole process of OSMO.There is a considerable lack of research working on managing OSMO from a vendor’s perspective.Therefore,to find the best practices for managing an OSMO process,it is necessary to further investigate such complex and multifaceted phenomena from the vendor’s perspective.This study validated the preliminary OSMO process model via a case study research approach.The results showed that the OSMO process model is applicable in an industrial setting with few changes.The industrial data collected during the case study enabled this paper to extend the preliminary OSMO process model.The refined version of the OSMO processmodel has four major phases including(i)Project Assessment,(ii)SLA(iii)Execution,and(iv)Risk.

Flow-Induced Clogging in Microfiltration Membranes: Numerical Modeling and Parametric Study

Microfiltration membrane technology has been widely used in various industries for solid-liquid separation. However, pore clogging remains a persistent challenge. This study employs (CFD) and discrete element method (DEM) models to enhance our understanding of microfiltration membrane clogging. The models were validated by comparing them to experimental data, demonstrating reasonable consistency. Subsequently, a parametric study was conducted on a cross-flow model, exploring the influence of key parameters on clogging. Findings show that clogging is a complex phenomenon affected by various factors. The mean inlet velocity and transmembrane flux were found to directly impact clogging, while the confinement ratio and cosine of the membrane pore entrance angle had an inverse relationship with it. Two clog types were identified: internal (inside the pore) and external (arching at the pore entrance), with the confinement ratio determining the type. This study introduced a dimensionless number as a quantitative clogging indicator based on transmembrane flux, Reynolds number, filtration time, entrance angle cosine, and confinement ratio. While this hypothesis held true in simulations, future studies should explore variations in clogging indicators, and improved modeling of clogging characteristics. Calibration between numerical and physical times and consideration of particle volume fraction will enhance understanding.

Analysis of an event study using the Fama–French five‑factor model:teaching approaches including spreadsheets and the R programming language

The current financial education framework has an increasing need to introduce tools that facilitate the application of theoretical models to real-world data and contexts.However,only a limited number of free tools are available for this purpose.Given this lack of tools,the present study provides two approaches to facilitate the implementa-tion of an event study.The first approach consists of a set of MS Excel files based on the Fama–French five-factor model,which allows the application of the event study methodology in a semi-automatic manner.The second approach is an open-source R-programmed tool through which results can be obtained in the context of an event study without the need for programming knowledge.This tool widens the calculus possibilities provided by the first approach and offers the option to apply not only the Fama–French five-factor model but also other models that are common in the finan-cial literature.It is a user-friendly tool that enables reproducibility of the analysis and ensures that the calculations are free of manipulation errors.Both approaches are freely available and ready-to-use.

Three-dimensional models of antigens with serodiagnostic potential for leprosy:An in silico study

BACKGROUND Leprosy is a disease caused by Mycobacterium leprae(M.leprae),an intracellular pathogen that has tropism and affects skin and nervous system cells.The disease has two forms of presentation:Paucibacillary and multibacillary,with different clinical and immunological manifestations.Unlike what occurs in the multibacillary form,the diagnostic tests for the paucibacillary form are nonspecific and not very sensitive,allowing the existence of infected individuals without treatment,which contributes to the spread of the pathogen in the population.To mitigate this contamination,more sensitive diagnostic tests capable of detecting paucibacillary patients are needed.AIM To predict the three-dimensional structure models of M.leprae antigens with serodiagnostic potential for leprosy.METHODS In this in silico study,satisfactory templates were selected in the Protein Data Bank(PDB)using Basic Local Alignment Search Tool to predict the structural templates of ML2038,ML0286,ML0050,and 85B antigens by comparative modeling.The templates were selected according to general criteria such as sequence identity,coverage,X-ray resolution,Global Model Quality Estimate value and phylogenetic relationship;Clustal X 2.1 software was used in this analysis.Molecular modeling was completed using the software Modeller 9v13.Visualization of the models was made using ViewerLite 4.2 and PyMol software,and analysis of the quality of the predicted models was performed using the QMEAN score and Z-score.Finally,the three-dimensional moels were validated using the MolProbity and Verify 3D platforms.RESULTS The three-dimensional structure models of ML2038,ML0286,ML0050,and 85B antigens of M.leprae were predicted using the templates PDB:3UOI(90.51%identity),PDB:3EKL(87.46%identity),PDB:3FAV(40.00%identity),and PDB:1F0N(85.21%identity),respectively.The QMEAN and Z-score values indicated the good quality of the structure models.These data refer to the monomeric units of antigens,since some of these antigens have quaternary structure.The validation of the models was performed with the final three-dimensional structure-monomer(ML0050 and 85B antigens)and quaternary structures(ML2038 and ML0286).The majority of amino acid residues were observed in favorable and allowed regions in the Ramachandran plot,indicating correct positioning of the side chain and absence of steric impediment.The MolProbity score value and Verify 3D results of all models indicated a satisfactory prediction.CONCLUSION The polarized immune response against M.leprae creates a problem in leprosy detection.The selection of immunodominant epitopes is essential for the development of more sensitive serodiagnostic tests,for this it is important to know the three-dimensional structure of the antigens,which can be predicted with bioinformatics tools.

A Comparative Study on Factors Influencing Food Security in China and India

This paper analyzes and compares the key factors influencing food security in two populous countries(China and India),and cate-gorizes them into three types:agricultural production,economic development and income level,and income distribution.Using the prevalence of undernourishment as an indicator of food security,the paper empirically tests the degree of impact of various factors on food security in both countries using Tobit regression and Newey regression methods.The study finds that improving the level of economic development can significantly enhance food security in both countriesꎻreducing the Gini coefficient has a significant impact on India,but not on Chinaꎻincreasing the agricultural production per capita has a much greater effect on China than on India.Therefore,both countries should take measures that are both similar and different according to their national conditions to improve their food security level.

Considerations of rock dilation on modeling failure and deformation of hard rocks-a case study of the mine-by test tunnel in Canada

For the compressive stress-induced failure of tunnels at depth, rock fracturing process is often closely associated with the generation of surface parallel fractures in the initial stage, and shear failure is likely to occur in the final process during the formation of shear bands, breakouts or V-shaped notches close to the excavation boundaries. However, the perfectly elastoplastic, strain-softening and elasto-brittle-plastic models cannot reasonably describe the brittle failure of hard rock tunnels under high in-situ stress conditions. These approaches often underestimate the depth of failure and overestimate the lateral extent of failure near the excavation. Based on a practical case of the mine-by test tunnel at an underground research laboratory (URL) in Canada, the influence of rock mass dilation on the depth and extent of failure and deformation is investigated using a calibrated cohesion weakening and frictional strengthening (CWFS) model. It can be found that, when modeling brittle failure of rock masses, the calibrated CWFS model with a constant dilation angle can capture the depth and extent of stress-induced brittle failure in hard rocks at a low confinement if the stress path is correctly represented, as demonstrated by the failure shape observed in the tunnel. However, using a constant dilation angle cannot simulate the nonlinear deformation behavior near the excavation boundary accurately because the dependence of rock mass dilation on confinement and plastic shear strain is not considered. It is illustrated from the numerical simulations that the proposed plastic shear strain and confinement-dependent dilation angle model in combination with the calibrated CWFS model implemented in FLAC can reasonably reveal both rock mass failure and displacement distribution in vicinity of the excavation simultaneously. The simulation results are in good agreement with the field observations and displacement measurement data.

Prediction model of in-hospital mortality in elderly patients with acute heart failure based on retrospective study

Objectives The aim of this study was to develop a clinical risk model that is predictive of in-hospital mortality in elderly patients hos- pitalized with acute heart failure （AHF）. Methods 2486 patients who were 60 years and older from intensive care units of Cardiology De- partment in the hospital were analyzed. Independent risk factors for in-hospital mortality were obtained by binary logistic regression and then used to establish the risk prediction score system （RPSS）. The area under the curve （AUC） of receiver operator characteristic and C-statistic test were adopted to assess the performance of RPSS and to compare with previous get with the guidelines-heart failure （GWTG-HF）. Re- sults By binary logistic regression analysis, heart rate （OR： 1.043, 95% CI： 1.030-1.057, P 〈 0.001）, left ventricular ejection fraction （OR： 0.918, 95% CI： 0.833~）.966, P 〈 0.001）, pH value （OR： 0.001, 95% CI： 0.000-0.002, P 〈 0.001）, renal dysfunction （OR： 0.120, 95% CI： 0.066M）.220, P 〈 0.001） and NT-pro BNP （OR： 3.463, 95% CI： 1.870-6.413, P 〈 0.001） were independent risk factors of in-hospital mortal- ity for elderly AHF patients. Additionally, RPSS, which was composed of all the above-mentioned parameters, provided a better risk predic- tion than GWTG-THF （AUC： 0.873 vs. 0.818, P = 0.016）. Conclusions Our risk prediction model, RPSS, provided a good prediction for in-hospital mortality in elderly patients with A/IF.

Parameters Calibration of the GISSMO Failure Model for SUS301L-MT

With the development of the rail transit industry,more attention has been paid to the passive safety of rail vehicles.Structural damage is one of the main failure behaviors in a rail vehicle collision,but it has been paid little attention to in past research.In this paper,the quasi-static fracture experiments of SUS301L-MT under different stress states were carried out.The mechanical fracture properties of this material were studied,and the corresponding finite element simulation accuracy was improved to guide the design of vehicle crashworthiness.Through the tests,the fracture behavior of materials with wide stress triaxiality was obtained,and each specimen’s fracture locations and fracture strains were determined.Parameters of a generalized incremental stress state dependent damage model(GISSMO)of the material were calibrated,and the model’s accuracy was verified with test results from a 45°shear specimen.The GISSMO failure model accurately reflected the fracture characteristics of the material.The mesh dependency of this model was modified and discussed.The results show that the simulation agrees well with experimental data for the force-displacement curve after correction,but the strain distribution needs to be further studied and improved.

Theoretical and Experimental Study on the Performance of Hermetic Diaphragm Squeeze Film Dampers for Gas-Lubricated Bearings

Low damping characteristics have always been a key sticking points in the development of gas bearings.The application of squeeze film dampers can significantly improve the damping performance of gas lubricated bearings.This paper proposed a novel hermetic diaphragm squeeze film damper(HDSFD)for oil-free turbomachinery supported by gas lubricated bearings.Several types of HDSFDs with symmetrical structure were proposed for good damping performance.By considering the compressibility of the damper fluid,based on hydraulic fluid mechanics theory,a dynamic model of HDSFDs under medium is proposed,which successfully reflects the frequency dependence of force coefficients.Based on the dynamic model,the effects of damper fluid viscosity,bulk modulus of damper fluid,thickness of damper fluid film and plunger thickness on the dynamic stiffness and damping of HDSFDs were analyzed.An experimental test rig was assembled and series of experimental studies on HDSFDs were conducted.The damper fluid transverse flow is added to the existing HDSFD concept,which aims to make the dynamic force coefficients independent of frequency.Although the force coefficient is still frequency dependent,the damping coefficient at high frequency excitation with damper fluid supply twice as that without damper fluid supply.The results serve as a benchmark for the calibration of analytical tools under development.

ON INFORMATION THEORY METHOD FOR RELIABILITY ASSESSMENT OF SYSTEMS CONSISTING OF DIFFERENT SUCCESS FAILURE MODEL UNITS

Using the characteristic of addition of information quantity and the principle of equivalence of information quantity, this paper derives the general conversion formulae of the formation theory method conversion (synthesis) on the systems consisting of different success failure model units. According to the fundamental method of the unit reliability assessment, the general models of system reliability approximate lower limits are given. Finally, this paper analyses the application of the assessment method by examples, the assessment results are neither conservative nor radical and very satisfactory. The assessment method can be popularized to the systems which have fixed reliability structural models.

Comparative study of HFACS and the 24Model accident causation models

A comparative study is conducted to compare the theory and application effect of two accident causation models, the human factors analysis and classification system（HFACS） and the accident causation ＂2-4＂ model（24 Model）, as well as to provide a reference for safety researchers and accident investigators to select an appropriate accident analysis method. The two models are compared in terms of their theoretical foundations, cause classifications, accident analysis processes, application ranges, and accident prevention strategies. A coal and gas outburst accident is then analyzed using both models, and the application results are compared. This study shows that both the 24 Model and HFACS have strong theoretical foundations, and they can each be applied in various domains. In addition, the cause classification in HFACS is more practical, and its accident analysis process is more convenient. On the other hand, the 24 Model includes external factors, which makes the cause analysis more systematic and comprehensive. Moreover, the 24 Model puts forward more corresponding measures to prevent accidents.

Application of in vitro and in vivo models in the study of food allergy

Food allergy is one of the most important food safety problems that has attracted increasing attention.The food allergy experimental models provide not only the accurate allergen detection and evaluation methods but also the powerful approaches for mechanism investigations.In this paper,we reviewed the common food allergy cell models including mast cell,basophil granulocyte and basophil,as well as the animal models of BALB/c mouse,C3H/HeJ mouse,and BN rat.We also introduced zebrafish,a promising model organism for investigating immunity though lacking direct applications in food allergy to date,and focused on traumatic inflammation,bacterial infection and viral infection models.In addition,we also summarized the clinical diagnostic research methods for food allergy.The elucidation of these topics will help researchers to understand the characteristics and mechanisms of various models and thus select the proper models for particular study,so as to support further investigations of food allergy.

Snow and sea ice thermodynamics in the Arctic:Model validation and sensitivity study against SHEBA data

Evolution of the Arctic sea ice and its snow cover during the SHEBA year were simulated by applying a high-resolution thermodynamic snow/ice model （HIGHTSI）. Attention was paid to the impact of albedo on snow and sea ice mass balance, effect of snow on total ice mass balance, and the model vertical resolution. The SHEBA annual simulation was made applying the best possible external forcing data set created by the Sea Ice Model Intercomparison Project. The HIGHTSI control run reasonably reproduced the observed snow and ice thickness. A number of albedo schemes were incorporated into HIGHTSI to study the feedback processes between the albedo and snow and ice thickness. The snow thickness turned out to be an essential variable in the albedo parameterization. Albedo schemes dependent on the surface temperature were liable to excessive positive feedback effects generated by errors in the modelled surface temperature. The superimposed ice formation should be taken into account for the annual Arctic sea ice mass balance.

A CLOUD-RESOLVING MODELING STUDY OF SURFACE RAINFALL PROCESSES ASSOCIATED WITH LANDFALLING TYPHOON KAEMI(2006)

The detailed surface rainfall processes associated with landfalling typhoon Kaemi（2006） are investigated based on hourly data from a two-dimensional cloud-resolving model simulation. The model is integrated for 6 days with imposed large-scale vertical velocity, zonal wind, horizontal temperature and vapor advection from National Center for Environmental Prediction （NCEP） / Global Data Assimilation System （GDAS） data. The simulation data are validated with observations in terms of surface rain rate. The Root-Mean-Squared （RMS） difference in surface rain rate between the simulation and the gauge observations is 0.660 mm h^-1, which is smaller than the standard deviations of both the simulated rain rate （0.753 mm h^-1） and the observed rain rate （0.833 mm h^-1）. The simulation data are then used to study the physical causes associated with the detailed surface rainfall processes during the landfall. The results show that time averaged and model domain-mean Ps mainly comes from large-scale convergence （QWVF） and local vapor loss （positive QWVT）. Large underestimation （about 15%） of Ps will occur if QWVT and QCM （cloud source/sink） are not considered as contributors to Ps ,QWVF accounts for the variation of P during most of the integration time, while it is not always a contributor to Ps,Sometimes surface rainfall could occur when divergence is dominant with local vapor loss to be a contributor to Ps - Surface rainfall is a result ofmulti-timescale interactions. QWVE possesses the longest time scale and the lowest frequeney the second and QCM of variation with time and may exert impact on P on longer time scales. QWVF possesses longest time scale and lowest frequency and can explain most of the variation of Ps. QWVT possess shorter time scales and higher frequencies, which can explain more detailed variations in Ps. Partitioning analysis shows that stratiform rainfall is dominant from the morning of 26 July till the late night of 27 July. After that, convective rainfall dominates till about 1000 LST 28 July. Before 28 July, the variations of QWVT in rainfall-free regions contribute less to that of the domain-mean QWVT while after that they contribute much, which is consistent to the corresponding variations in their fractional coverage. The variations of QWVF in rainfall regions are the main contributors to that of the domain-mean QWVF, then the main contributors to the surface rain rate before the afternoon of 28 July.

Model updating of a bridge structure using vibration test data based on GMPSO and BPNN:case study

Model updating issues with high-dimensional and strong-nonlinear optimization processes are still unsolved by most optimization methods.In this study,a hybrid methodology that combines the Gaussian-white-noise-mutation particle swarm optimization(GMPSO),back-propagation neural network(BPNN)and Latin hypercube sampling(LHS)technique is proposed.In this approach,as a meta-heuristic algorithm with the least modification to the standard PSO,GMPSO simultaneously offers convenient programming and good performance in optimization.The BPNN with LHS establishes the meta-models for FEM to accelerate efficiency during the updating process.A case study of the model updating of an actual bridge with no distribution but bounded parameters was carried out using this methodology with two different objective functions.One considers only the frequencies of the main girder and the other considers both the frequencies and vertical displacements of typical points.The updating results show that the methodology is a sound approach to solve an actual complex bridge structure and offers good agreement in the frequencies and mode shapes of the updated model and test data.Based on the shape comparison of the main girder at the finished state with different objective functions,it is emphasized that both the dynamic and static responses should be taken into consideration during the model updating process.

A sensitivity study of the WRF model in offshore wind modeling over the Baltic Sea

Accurate wind modeling is important for wind resources assessment and wind power forecasting. To improve the WRF model configuration for the offshore wind modeling over the Baltic Sea, this study performed a sensitivity study of the WRF model to multiple model configurations, including domain setup,grid resolution, sea surface temperature, land surface data, and atmosphere-wave coupling. The simulated offshore wind was evaluated against LiDAR observations under different wind directions, atmospheric stabilities, and sea status. Generally, the simulated wind profiles matched observations, despite systematic underestimations. Strengthening the forcing from the reanalysis data through reducing the number of nested domains played the largest role in improving wind modeling. Atmosphere-wave coupling further improved the simulated wind, especially under the growing and mature sea conditions.Increasing the vertical resolution, and updating the sea surface temperature and the land surface information only had a slight impact, mainly visible during very stable conditions. Increasing the horizontal resolution also only had a slight impact, most visible during unstable conditions. Our study can help to improve the wind resources assessment and wind power forecasting over the Baltic Sea.

Numerical simulation study of the failure evolution process and failure mode of surrounding rock in deep soft rock roadways

Based on the safety coefficient method,which assigns rock failure criteria to calculate the rock mass unit,the safety coefficient contour of surrounding rock is plotted to judge the distribution form of the fractured zone in the roadway.This will provide the basis numerical simulation to calculate the surrounding rock fractured zone in a roadway.Using the single factor and multi-factor orthogonal test method,the evolution law of roadway surrounding rock displacements,plastic zone and stress distribution under different conditions is studied.It reveals the roadway surrounding rock burst evolution process,and obtains five kinds of failure modes in deep soft rock roadway.Using the fuzzy mathematics clustering analysis method,the deep soft surrounding rock failure model in Zhujixi mine can be classified and patterns recognized.Compared to the identification results and the results detected by geological radar of surrounding rock loose circle,the reliability of the results of the pattern recognition is verified and lays the foundations for the support design of deep soft rock roadways.

A Sensitivity Study on Parameterization Scheme of Snow Internal and Interfacial Processes in Snow Model

In order to develop a seasonal snow model of land surface process as accurately as possible for climatic study. it is necessary to fully understand the effects of important snow internal processes and interaction with air and to get an insight into influence of several relevant parameterization schemes with parameters' uncertainty to some degree. Using the snow model (SAST) developed by first author and other one and some useful field observation data, this paper has conducted a series of sensitivity studies on the parameterization schemes. They are relative to compaction process, snow thermal conduction, methodology of layering snow pack and to key parameters such as snow albedo, water holding capacity. Then, based on the results from the sensitivity studies, some useful conclusions for snow cover model improvement are obtained from the analysis of the results.