MODELING THE PROPERTIES OF GAS SENSOR MATERIALS BASED ON ORGANIC SEMICONDUCTORS

An approach has been developed for modeling the gas-sensitive and physicochemical properties of materials based on organic semiconductors. The approach is based on the use of various modeling methods: linear, nonlinear regression analysis and neural networks. The parameters of the technological process of the formation of materials were selected as external signals for modeling: the mass fraction of metal in the film-forming solution, the temperature and time of the first and second stages of annealing.

Investigation of the compact torus plasma motion in the KTX-CTI device based on circuit analyses

Compact torus (CT) injection is one of the most promising methods for the central fuelling of next-generation reactor-grade fusion devices due to its high density, high velocity, and self-contained magnetised structure. A newly compact torus injector (CTI) device in Keda Torus eXperiment (KTX), named KTX-CTI, was successfully developed and tested at the University of Science and Technology in China. In this study, first, we briefly introduce the basic principles and structure of KTX-CTI, and then, present an accurate circuit model that relies on nonlinear regression analysis (NRA) for studying the current waveform of the formation region. The current waveform, displacement, and velocity of CT plasma in the acceleration region are calculated using this NRA-based one-dimensional point model. The agreement between the model results and the experimental results is better than in the previous general model results estimated by the device dimensions in previous. The next-step upgrading reference scheme of the KTX-CTI device is preliminarily investigated using this NRA-based point model. This research can provide insights for the development of experiments and future upgrades of the device.

Comparison of [18F] NaF PET/CT dynamic analysis methods and a static analysis method including derivation of a semi-population input function for site-specific measurements of bone formation in a population with chronic kidney disease-mineral and bone disorder

Purpose The purpose of this study is to compare dynamic and static whole-body (WB) [18F]NaF PET/CT scan methods used for analysis of bone plasma clearance in patients with chronic kidney disease-mineral and bone disorder (CKD-MBD). Methods Seventeen patients with CKD-MBD underwent a 60-min dynamic scan followed by a 30-min static WB scan. Tracer kinetics in four thoracic vertebrae were analysed using nonlinear regression and Patlak analysis using image-derived arterial input functions. The static WB scan was analysed using a simplified Patlak method requiring only a single data point in combination with a fixed y-intercept value (V0), both obtained using a semi-population function. The semi-population function was constructed by combining a previously derived population input function in combination with data from venous blood samples. Static WB scan analysis data, obtained from the semi-population input functions, was compared with paired data obtained using dynamic input functions. Results Bone plasma clearance (Ki) from Patlak analyses correlated well with nonlinear regression analysis, but Ki results using Patlak analysis were lower than Ki results using nonlinear regression analysis. However, no significant difference was found between Ki obtained by static WB scans and Ki obtained by dynamic scans using nonlinear regression analysis (p = 0.29). Conclusion Bone plasma clearance measured from static WB scans correlates with clearance data measured by dynamic analysis. Static [18F]NaF PET/CT scans can be applied in future studies to measure Ki in patients with CKD-MBD, but the results should not be compared uncritically with results obtained by dynamic scan analysis.

Modeling the Effect of Temperature on Ginger and Turmeric Rhizome Sprouting

Ginger and turmeric are tropical plant species with medicinal, beverage, and edible uses. Both species are typically propagated using seed rhizomes that often lack uniformity when sprouting, ultimately affecting the transplant growth and quality. Our objectives were to (1) develop a model to predict the effect of temperature on rhizome sprouting and transplant growth and (2) characterize the morphological factors affecting the sprouting of ginger and turmeric rhizomes. Two experiments were conducted where the rhizomes were placed in plastic bags with a moist substrate inside dark incubator chambers. Five temperature treatments (21, 25, 27, 30, and 32 °C) were used for calibrating the model, and six temperature treatments (14, 20, 25, 30, 35, and 40 °C) were used in the validation phase. The number of days for rhizomes to develop 1- and 5-cm sprouts were counted; after which, the total number of sprouts, total leaf length, and root quality were measured. A nonlinear regression analysis was used to develop temperature–response curves. Ginger and turmeric had optimal sprouting temperatures of 27.5 and 30.1 °C, respectively. Temperatures close to the optimal reduced the time to sprout and to subsequently reach the transplant stage. No sprouting was observed at 14 °C, and the minimum temperature to develop 5-cm sprouts was estimated at slightly above 17 °C in both species. Temperatures above 32 °C resulted in tissue damage and rhizome loss. The results from this study show the potential to produce uniform ginger and turmeric transplants using temperature treatments that accelerate sprouting.

Manufacturing and Modeling of Hybrid Polymer Composites by Using Multiple-nonlinear Regression Analysis

In this study, artichoke stem particles (AS) and wollastonite mineral (W) were used as an organic and inorganic fillers in order to improve the mechanical properties of polypropylene (PP). In this regard, PP-based composites containing AS and W were produced as non-hybrid and hybrid materials using a high-speed thermokinetic mixer. Mechanical properties of polymer composites were investigated by the tensile test. Experimental results reveal that the highest elastic modulus for PP-W and the highest tensile strength for PP were obtained while the lowest ultimate strain value was gained using PP-W-A. Then, multiple nonlinear regression analysis was employed to determine the effect of weight ratios of wollastonite mineral and artichoke stem particles in polypropylene on elastic modulus, tensile strength and ultimate strain. Experimental results were expressed second order (tensile strength), third order (elastic modulus) and fourth order (ultimate strain) mathematical models. The results show that the proposed models have well fitted with the experimental results. The coefficient of determination (R2) values were found between 0.95 and 1 in all models. Also, boundedness check control of the proposed models which gives information about whether models are realistic or not was carried out by calculating the maximum and minimum values produced by the relevant model.

Research on the Longitudinal Section of River Restoration Using Probabilistic Theory

Since the 1960s, many rivers have been destroyed as a consequence of the process of rapid urbanization. As accurate figures are important to repair rivers, there have been many research reports on methods to obtain the exact river slope and elevation. Until now, many research efforts have analyzed the river using measured river topographic factors, but when the flow velocity changes rapidly, such as during a flood, surveying is not easy; and due to cost, frequent measurements are difficult. Previous research has focused on the cross section of the river, so the information on the river longitudinal profile is insufficient. In this research, using informational entropy theory, equations are presented that can calculate the average river slope, river slope, and river longitudinal elevation for a river basin in real time. The applicability was analyzed through a comparison with the measured data of river characteristic factors obtained from the river plan. The parameters were calculated using informational entropy theory and nonlinear regression analysis using actual data, and then the longitudinal elevation entropy equation for each river and the average river slope were calculated. As a result of analyzing the applicability of the equations presented in this study by R2 and Root Mean Square Error, all R2 values were over 0.80, while RMSE values were analyzed to be between 0.54 and 2.79. Valid results can be obtained by calculating river characteristic factors.

EXPERIMENTAL STUDY OF FLOW THROUGH TRAPEZOIDAL WEIR CONTROLLED UNDER A SEMI-CIRCULAR GATE

Different parameters of a weir model have a great effect on the discharge coefficient. In this experimental study the effect of varying angle of a trapezoidal weir coupled with a below semi-circular gate is determined. The result showed that the higher the value of the higher the coefficient of discharge. The respective average discharge coefficient of the block model and the trapezoidal weir models are; 0.48031,0.48880, 0.49565, 0.49647, 0.49892 and 0.49934. As such the trapezoidal weir with has the highest value of average discharge coefficient =0.49934. Hence the most efficient. Linear and nonlinear regression analysis were used to generate mathematical equations that can be used to predict the flow rate Q for the combined weir-gate structure and the discharge coefficient of the most efficient model with respectively. The discharge coefficient for the most efficient weir model was found to be 3.81% more than that of the block model (with rectangular weir). The predicted coefficient of discharge for the most efficient model was also found to be in good agreement with the observed discharge coefficient with a percentage error in the range of 0.4%