RESUMEN
Seed viability is essential to have a homogeneous plant population. The seed industry cannot adopt traditional procedures for seed viability evaluation since they are destructive, time-consuming, and need chemicals. This study aimed to investigate the potential of combining hyperspectral and color image features to differentiate viable and non-viable paddy seeds. The hyperspectral and color image of the 355 paddy seeds was captured and later used to examine their viability. An image processing algorithm was developed to extract features from color images of paddy seeds and investigated significant differences in the retrieved feature data using variance analysis. The spectra were extracted from the selected region of interest (ROI) of the hyperspectral paddy seed image and averaged. In the next step, the partial least square discrimination analysis (PLS-DA) model was developed to distinguish viable and non-viable paddy seeds. Initially, the PLS-DA model was developed using spectral data with different preprocessing techniques, and the result obtained an accuracy of 88.9 % in the calibration set and 86.1 % in the prediction set using Savitzky-Golay 2nd derivative preprocessed spectra. With the fusion of spectral and significant color image features, the model's accuracy improved to 93.3 % and 90.9 % in the calibration and prediction sets, respectively. Results also showed that the fusion of selected color image features with Savitzky-Golay 2nd derivative preprocessed spectra could achieve higher F1-score, recall, and precision values. The visualization map for the viable and non-viable paddy seeds was also developed utilizing the most effective predictive model. The results demonstrate the possibility of using the fusion of the hyperspectral and color image features to sort seeds according to viability, which may be applied in developing an online seed sorting method.
RESUMEN
This paper reports an investigation of the mechanical and microscopic properties of partially replaced banana leaf ash (BLA) concrete. In this research, the cement was partially replaced by BLA in two phases: Phase A (0%, 5%, 10%, 15%, 20%, 25% and 30%) and Phase B (0%, 10%, 20% and 30%). The consequence of partially replacing cement with BLA in concrete was investigated by the application of a range of tests, namely X-ray fluorescence (XRF), compressive strength, splitting tensile strength, flexure strength, ultrasonic pulse velocity and scanning electron microscopy (SEM) analysis. The properties were then correlated with the properties of a standard 100% Portland cement concrete of similar strength. The XRF result of the BLA identified a composition with 48.93% SiO2 and 3.48% Al2O3, which indicates that the material potentially possesses pozzolanic properties. The mechanical properties of the partially replaced BLA concrete noted minor strength loss, approximately 5% with 20% partial replacement. The nondestructive testing data showed enhanced performance up to 20% partial replacement, with ultrasonic pulse values above 3500 m/s. The scanning electron microscopy analysis illustrated that the morphology of BLA specimens contained increased microcracks compared with the control. The decrease in strength observed is attributed to the fibrous composition of the BLA. The mechanical, nondestructive testing and microscopic results highlight the potential to utilize BLA as a partial replacement for cement as a pozzolanic material in concrete at up to 20% by weight of cement.
RESUMEN
COVID-19 is caused by the SARS-CoV-2 virus, which is mainly transmitted directly between humans. However, it is observed that this disease can also be transmitted through an indirect route via environmental fomites. The development of appropriate and effective vaccines has allowed us to target and anticipate herd immunity. Understanding of the transmission dynamics and the persistence of the virus on environmental fomites and their resistive role on indirect transmission of the virus is an important scientific and public health challenge because it is essential to consider all possible transmission routes and route specific transmission strength to accurately quantify the herd immunity threshold. In this paper, we present a mathematical model that considers both direct and indirect transmission modes. Our analysis focuses on establishing the disease invasion threshold, investigating its sensitivity to both transmission routes and isolate route-specific transmission rate. Using the tau-leap algorithm, we perform a stochastic model simulation to address the invasion potential of both transmission routes. Our analysis shows that direct transmission has a higher invasion potential than that of the indirect transmission. As a proof of this concept, we fitted our model with early epidemic data from several countries to uniquely estimate the reproduction numbers associated with direct and indirect transmission upon confirming the identifiability of the parameters. As the indirect transmission possess lower invasion potential than direct transmission, proper estimation and necessary steps toward mitigating it would help reduce vaccination requirement.
Asunto(s)
COVID-19 , Inmunidad Colectiva , COVID-19/prevención & control , Humanos , Conceptos Matemáticos , Modelos Biológicos , SARS-CoV-2RESUMEN
ABSTRACT: Mathematical modeling of many physical systems leads to nonlinear evolution equations because most physical systems are inherently nonlinear in nature. The investigation of traveling wave solutions of nonlinear partial differential equations (NPDEs) plays a significant role in the study of nonlinear physical phenomena. In this article, we construct the traveling wave solutions of modified KDV-ZK equation and viscous Burgers equation by using an enhanced (G '/G) -expansion method. A number of traveling wave solutions in terms of unknown parameters are obtained. Derived traveling wave solutions exhibit solitary waves when special values are given to its unknown parameters. MATHEMATICS SUBJECT CLASSIFICATION: 35C07; 35C08; 35P99.