Estimating the Mosquito Density in Guangzhou city, China

Mosquito is a vector of many diseases. Predicting the trend of mosquito density is important for early warning and control of mosquito diseases. In this paper, we fit a discrete time mosquito model developed by Gong et al. in 2011, which considers the immature and adult stages, and weather dependent model parameters, to the Breteau Index and Bite Index data for Aedes aegypti in Guangzhou city, China in 2014, as well as the weather data for average temperature, precipitation, evaporation and daylight for the same period. We estimated the model parameters using the Markov Chain Monte-Carlo (MCMC) method. We find that many parameters are not identifiable. We revise and simplify the model so that the parameters of our new model are identifiable. Our results indicate that the model predicted mosquito prevalence agrees well with data. We then use the fitted parameter values against the Breteau Index and Bite Index data for Guangzhou city in 2017 and 2018, and show that the estimated parameter values are applicable for other seasons.

Improved model for predicting the hydraulic conductivity of soils based on the Kozeny–Carman equation

The saturated hydraulic conductivity of soils is a critical concept employed in basic calculation in the geotechnical engineering field. The Kozeny–Carman equation, as a well-known relationship between hydraulic conductivity and the properties of soils, is considered to apply to sands but not to clays. To solve this problem, a new formula was established based on Hagen–Poiseuille's law. To explain the influence on the seepage channel surface caused by the interaction of soil particles and partially viscous fluid, the surface area ratio was introduced. A modified framework for determining the hydraulic radius was also proposed. Next, the relationship between the effective void ratio and the total void ratio was established for deriving the correlation of hydraulic conductivity and total void ratio. The improved equation was validated using abundant experimental results from clays, silts, and sands. According to the results, the accuracies of the proposed model with two fitted multipliers for clays, silts, and sands are 94.6, 96.6, and 100%, respectively, but with only one fitted parameter, the accuracies are 97.1, 91.5, and 100%, respectively. The proposed model can be considered to have a satisfactory capability to predict hydraulic conductivity for a wide variety of soils, ranging from clays to sands.

Testing dissipative dark matter in causal thermodynamics

In this paper we study the consistency of a cosmological model representing a universe filled with a one-component dissipative dark matter fluid, in the framework of the causal Israel–Stewart theory, where a general expression arising from perturbation analysis for the relaxation time [Formula: see text] is used. This model is described by an exact analytic solution recently found in [N. Cruz, E. González and G. Palma, Gen. Relat. Gravit. 52, 62 (2020), which depends on several model parameters as well as integration constants, allowing the use of Type Ia Supernovae and Observational Hubble data to perform by an astringent observational tests. The constraint regions found for the parameters of the solution allow the existence of an accelerated expansion of the universe at late times, after the domination era of the viscous pressure, which holds without the need of including a cosmological constant. Nevertheless, the fitted parameter values lead to drawbacks as a very large non-adiabatic contribution to the speed of sound, and some inconsistencies, not totally conclusive, with the description of the dissipative dark matter as a fluid, which is nevertheless a common feature of these kind of models.

Evaluation of Different Objective Functions Used in the SUFI-2 Calibration Process of SWAT-CUP on Water Balance Analysis: A Case Study of the Pursat River Basin, Cambodia

Many calibration techniques have been developed for the Soil and Water Assessment Tool (SWAT). Among them, the SWAT calibration and uncertainty program (SWAT-CUP) with sequential uncertainty fitting 2 (SUFI-2) algorithm is widely used and several objective functions have been implemented in its calibration process. In this study, eight different objective functions were used in a calibration of stream flow of the Pursat River Basin of Cambodia, a tropical monsoon and forested watershed, to examine their influences on the calibration results, parameter optimizations, and water resources estimations. As results, many objective functions performed better than satisfactory in calibrating the SWAT model. However, different objective functions defined different fitted values and sensitivity rank of the calibrated parameters, except Nash–Sutcliffe efficiency (NSE) and ratio of standard deviation of observations to root mean square error (RSR) which are equivalent and produced quite identical simulation results including parameter sensitivity and fitted parameter values, leading to the same water balance components and water yields estimations. As they generated reasonable fitted parameter values, either NSE or RSR gave better estimation results of annual average water yield and other water balance components such as annual average evapotranspiration, groundwater flow, surface runoff, and lateral flow according to the characteristics of the river basin and the results and data of previous studies. Moreover, either of them was also better in calibrating base flow, falling limb, and overall the entire flow phases of the hydrograph in this area.

RSFit3000: A MATLAB GUI-based program for determining rate and state frictional parameters from experimental data

We present a MATLAB graphical user interface (GUI) software package for analyzing rate and state friction experiments. Called RSFit3000, the software allows users to easily determine frictional parameters by fitting velocity-step and slide-hold-slide events using the aging- and slip-law forms for state variable evolution. RSFit3000 includes features for removing strain hardening or weakening trends from the data, and provides options for using two state variables, applying a weighting function, and treating stiffness as a fitting parameter. Completed fits are conveniently saved in MATLAB structure arrays that contain fitted parameter values with their error intervals, and all information required to reproduce a given fit. The GUI makes the program simple to use, as all fitting tasks are completed via interaction with the interface. Here we describe how to use the software, and illustrate its flexibility and utility by analyzing two sets of synthetic friction data, as well as some previously published experimental data. Although descriptions of rate and state friction fitting routines have been published in the past, RSFit3000 marks the first time a software package for analyzing friction experiments has been described in the literature.

Moisture Recovery – A Dynamic Modelling Approach

With rising insulation standards, the use of mechanical ventilation, especially in non-residential buildings, is becoming increasingly relevant. To ensure thermal comfort and avoid health problems for people in the room, cost- and energy-intensive humidification of the supply air is necessary. The use of moisture recovery systems can thus significantly reduce the energy consumption of ventilation systems. Despite this energy-saving potential, moisture recovery systems are rarely used in ventilation systems. To forecast the efficiency of moisture recovery systems in partial load operation and under different climatic conditions, a dynamic model of a membrane-based enthalpy exchanger was developed in the object-oriented modelling language Modelica. The model is based on the solution diffusion model, a quite common approach. In contrast to the models found in the literature, the sorption process is not assumed to be in equilibrium state. Rather, as a first approach the membrane’s permeance, consisting of the solubility and diffusion coefficient, is modelled with a linear dependency on the moisture difference between the two incoming airflows. A parameter fitting has been carried out with experimental data to determine the unknown material parameters. The model containing the fitted parameter set was validated using different experimental data.

Sequential regression measurement error models with application

Sequential regression approaches can be used to analyze processes in which covariates are revealed in stages. Such processes occur widely, with examples including medical intervention, sports contests and political campaigns. The naïve sequential approach involves fitting regression models using the covariates revealed by the end of the current stage, but this is only practical if the number of covariates is not too large. An alternative approach is to incorporate the score (linear predictor) from the model developed at the previous stage as a covariate at the current stage. This score takes into account the history of the process prior to the stage under consideration. However, the score is a function of fitted parameter estimates and, therefore, contains measurement error. In this article, we propose a novel technique to account for error in the score. The approach is demonstrated with application to the sprint event in track cycling and is shown to reduce bias in the estimated effect of the score and avoid unrealistically extreme predictions.

Modelling the fill rate of pit latrines in Ifakara, Tanzania

A model of the rate at which pit latrines fill was developed and compared with actual fill rates measured in latrines in Ifakara, Tanzania. Model parameters were derived primarily from data collected during the field study in Tanzania, with one fitted parameter. Although the model did not accurately simulate the fill rate of individual pits, it provided a good simulation of the average fill rate of the pits and aided the identification of pits that were performing poorly. Laboratory experiments conducted on samples of sludge from the pits were used to identify the average hydrolysis constant for biodegradation of the organic material. The average hydrolysis constant (0.046 day−1) was higher than that identified in another modelling study (0.0015 day−1), conducted in South Africa. The higher hydrolysis constant provided a simulation of the profile of volatile solids with lower root mean square error in 17/24 of the pits, however, for the other pits a lower hydrolysis constant was more appropriate. A sensitivity study of the model indicated that the pit fill rates were particularly sensitive to the parameter that quantified water accumulation in the pit, as such quantifying water flow through the pit is a priority for future research.

Importance of Nonperturbative QCD Parameters for Bottom Mesons

The importance of nonperturbative quantum chromodynamics (QCD) parameters is discussed in context to the predicting power for bottom meson masses and isospin splitting. In the framework of heavy quark effective theory, the work presented here focuses on the different allowed values of the two nonperturbative QCD parameters used in heavy quark effective theory formula, and using the best fitted parameter, masses of the excited bottom meson states injp=1/2+doublet in strange and nonstrange sectors are calculated here. The calculated masses are found to be matching well with experiments and other phenomenological models. The mass splitting and hyperfine splitting have also been analyzed for both strange and nonstrange heavy mesons with respect to spin and flavor symmetries.

The rheology of suspensions of solid particles

We present data for the rheology of suspensions of monodisperse particles of varying aspect ratio, from oblate to prolate, and covering particle volume fractions ϕ from dilute to highly concentrated. Rheology is characterized by fitting the experimental data to the model of Herschel & Bulkley (Herschel & Bulkley 1926 Kolloid Z. 39 , 291–300 ( doi:10.1007/BF01432034 )) yielding three rheometric parameters: consistency K (cognate with viscosity); flow index n (a measure of shear-thinning); yield stress τ 0 . The consistency K of suspensions of particles of arbitrary aspect ratio can be accurately predicted by the model of Maron & Pierce (Maron & Pierce 1956 J. Colloid Sci. 11 , 80–95 ( doi:10.1016/0095-8522(56)90023-X )) with the maximum packing fraction ϕ m as the only fitted parameter. We derive empirical relationships for ϕ m and n as a function of average particle aspect ratio r p and for τ 0 as a function of ϕ m and a fitting parameter τ *. These relationships can be used to predict the rheology of suspensions of prolate particles from measured ϕ and r p . By recasting our data in terms of the Einstein coefficient, we relate our rheological observations to the underlying particle motions via Jeffery’s (Jeffery 1922 Proc. R. Soc. Lond. A 102 , 161–179 ( doi:10.1098/rspa.1922.0078 )) theory. We extend Jeffery’s work to calculate, numerically, the Einstein coefficient for a suspension of many, initially randomly oriented particles. This provides a physical, microstructural explanation of our observations, including transient oscillations seen during run start-up and changes of rheological regime as ϕ increases.