Properties Affecting the Reactivity of Lime

Lime reactivity is the most used identification parameter for lime quality. The reaction may vary in its rate and maximum reached temperature. In this study, the influence of the properties of limestone on the course of the reaction is studied. The samples are thoroughly examined from a geological point of view (geological age and origin, genesis and diagenesis) and their physicochemical properties are described (total porosity, limestone category, chemical analysis, insoluble residue). Different temperatures and isothermal loads were selected to study the effect of the burning process on the lime microstructure. The newly formed CaO is observed by scanning electron microscopy (SEM images). Lime reactivity analysis is performed, and different reaction courses are compared.

Biometric similarity Test of The Population of T. (Zaria) bantamensis tjicumpaensis with T. (Zaria) javana as a Form of Phylogeny And Evolutionary Proximity

Biometric aspects in the Turritellidae family need to be studied as an important identification parameter. Zaria, which is one of the sub genera in the Turritellidae family, deserves to be tested in order to determine the feasibility of the biometric aspect as an identification parameter. This paper aims to provide an overview of the benefits of the biometric aspect as an identification parameter. The method used to re-identify the biometric and morphological aspects of the T. (Zaria) bantamensis tjicumpaensis population with T. (Zaria) javana. The results of the identification were carried out by a T-Test on the biometric aspect to see the similarity of the biometric aspects of the two populations. Based on the results of the T-Test on the parameters of the Wsut: Wang and Wsut: L ratio, it shows that the two Zaria species are the same. Meanwhile, from the morphological aspect, there is a slight difference in the early growth peripherals.

Forecast of China’s Carbon Emissions Based on ARIMA Method

Global warming caused by carbon emissions has become increasingly prominent. As the world’s second-largest economy, China is under enormous pressure to cut down its carbon dioxide emissions. It is urgent to seek effective methods to forecast carbon emissions and put forward the pointed and effective measures to reduce emissions. In this paper, we first use the software Eviews to make an analysis of randomness on data of carbon emissions in the four representative provinces and city, Beijing, Henan, Guangdong, and Zhejiang, in terms of their carbon emissions data from 1997 to 2017. Then, according to their distinct characteristics, the methods of stationary processing of the difference, moving average, and substituting strong impact points, respectively, are adopted to perform the data preprocessing. Then, model identification, parameter estimation, and model test are carried out to establish the model of ARIMA( p , d, q) for the prediction of the carbon emissions of the four regions, respectively. Finally, the model is used to forecast the data and analyze their tendency for their carbon emissions in the next three years. The results can provide guidance for decision-makers to set reasonable carbon emission reduction targets and take appropriate energy conservation and emission reduction measures.

Evaluation of erosion characteristics of soils using the pinhole test

This paper investigates the erosion characteristics of soils using the pinhole test. The tests were conducted with two undisturbed clay samples and five disturbed sandy soil samples. Based on the pinhole test results, a process to analyze the critical shear stress and erosion rate was proposed. The result indicates that the particle size distribution and coefficient of uniformity of soils are significant factors that affect the erosion characteristics of the soil. Samples with a grain size ranging from 0.2 to 0.6 mm is most susceptible to soil erosion. The erosion coefficients can be used to distinguish between the low erodible soils (ND3 and ND4) and high erodible ones (D1 and D2). Furthermore, it is interesting to note that the critical shear stress might be used as an identification parameter for erosion characteristics of the soil: τc > 3.5 Pa (ND3), 3.0 Pa < τc < 3.5 Pa (D2), and τc < 3.0 Pa (D1).

Aplication of ARIMA Model for Forecasting Additional Positive Cases of Covid-19 in Jember Regency

The autoregressive integrated moving average (ARIMA) model is a popular method for forecasting univariate time series dataset. This method consists of four major stages, namely: identification, parameter assessment, diagnostic examination, and forecasting using the ARIMA model (p, d, q). ARIMA model can be applied in various fields, one of which is medical field. Currently, there had been a daily increase in the number of patients infected with Corona virus. Jember is one of the regencies in East Java with a high number of confirmed patients. On February 5, 2021, it was recorded that 5,872 patients were confirmed positive for Corona, 5,241 patients had been declared cured, and 352 patients were declared dead. Given the high number of confirmed cases of Covid-19 in Jember, the authors would like to conduct a prediction research on the increasing number of confirmed cases of Covid-19 in Jember Regency for the upcoming period using the ARIMA model (p,d,q). The research was conducted in the Jember Regency, East Java. The data were collected from March 28, 2020 to January 30, 2021. The study showed that the ARIMA model (1,2,3) was the best model for predicting the additional positive cases of Covid-19 per week in Jember, with the sum squared resid of 7.9496. The data forecast for the additional positive cases of Covid-19 for the next 6 periods is: 224,56 patients, 247,84 patients, 273,53 patients, 301,89 patients, 333,18 patients, and 367,72 patients. Received February 10, 2021Revised April 8, 2021Accepted April 22, 2021

Ion mobility spectrometry experiments should be carried out at high temperatures to reduce uncertainties in the measurement of reduced mobilities

In ion mobility spectrometry (IMS), reduced mobility (K0) is an identification parameter of gas-phase ions but, frequently, these values are different whether there is contamination with moisture and other volatile...

A STEP TOWARD DEVELOPMENT OF GENERIC FRAGILITY CURVES

A phenomenon (failure) is considered as the change of state of the system (structure) between the origin (hazard threshold) and the destination (failure) points. The survive and the lost ratios of the system characteristics (stiffness) are defined in this paper in terms of stiffness, and the survive and failure (phenomenon) functions. The phenomenon functions are defined (in turn) in terms of the system identification parameter (state variable) and two control parameters. These parameters were calibrated by mapping them on four selected key points including origin, quarter point, middle point and end points in the system behaviour space. The failure function was used as fragility function. The validity of the work was verified by comparing the results with the fragility curves of four nuclear power plant containment vessels.