Numerical simulation of fluid flow and heat transfer in twin-screw extruders for non-Newtonian materials

A new simplified approach has been proposed for the numerical simulation of the thermal transport in corotating, tangential, and self-wiping twin-screw extruders. It is assumed that the flow domain in a twin-screw extruder can be divided into (i) the translation region (T-region), which represents a flow similar to that in a single-screw channel and (ii) the intermeshing region (I-region), which is located between the two screws. The two regions are simulated separately and then coupled for each screw section to model the overall transport in tangential and self-wiping twin-screw extruders. A finite difference method is employed for the developing flow and temperature fields in the T-region, in order to minimize the computing effort, while a finite element method is employed for determining the interchannel flow mixing and the thermal transport in the I-region. Results are obtained in terms of temperature, velocity, and pressure variations along the screw channels and mixing between the two screws.     

Physicochemical characterization of muscle proteins from different regions of mackerel (Rastrelliger kanagurta)

Physicochemical characteristics of proteins extracted from muscles excised from four distinct regions of mackerel were examined. Three regions were identified based on their fin position; namely anterior muscle, median muscle, posterior muscle and red muscles from beneath the lateral line. The biochemical characteristics like reactive sulphydryl groups, surface hydrophobicity, Ca²⁺ ATPase activity, turbidity, proximate composition and the functional characteristics such as viscosity, emulsion activity index (EAI) and emulsion stability (ES) were studied in the samples, from different regions. Sarcoplasmic protein (SPP) solubility was found to be higher in red muscles compared to that of white muscles, whereas myofibrillar protein (MFP) solubility was higher in white muscles particularly in the posterior portion. The MFP from posterior white muscles showed better viscosity, surface hydrophobicity and Ca²⁺ ATPase activity, which in turn contributed to the higher EAI and ES of this muscle portion. Variations in composition, electrophoretic pattern of proteins and selected functional properties (EAI) were noticed between red and white muscles, which may be of significance from the utilization point of the fish.     

FPGA based generic RO TRNG architecture for image confusion

Multimedia Tools and Applications - True Random Number Generator (TRNG) has become a central element of today’s secure communication. TRNGs developed through FPGA implementation have a...     

Chemoenzymatic Buta-1,3-diene Synthesis from Syngas Using Biological Decarboxylative Claisen Condensation and Zeolite-Based Dehydration

A method for producing buta-1,3-diene (1,3-BD) by an amalgamation of chemical and biological approaches with syngas as the carbon source is proposed. Syngas is converted to the central intermediate, acetyl-CoA, by microorganisms through a tetrahydrofolate metabolism pathway. Acetyl-CoA is subsequently converted to malonyl-CoA using a carbonyl donor in the presence of a carboxylase enzyme. A decarboxylative Claisen condensation of malonyl-CoA and acetaldehyde ensues in the presence of acyltransferases to form 3-hydroxybutyryl-CoA, which is subsequently reduced by aldehyde reductase to give butane-1,3-diol (1,3-BDO). An ensuing dehydration step converts 1,3-BDO to 1,3-BD in the presence of a chemical dehydrating reagent.     

Development of sensitive and specific multiplex PCR method for the detection of microcystin producing cyanobacteria in spirulina food supplements

Food Science and Biotechnology - Spirulina has emerged as the next-generation dietary supplement owing to its health benefits. Despite the advantages, there have been reports of contamination by...     

Effective Classification of Synovial Sarcoma Cancer Using Structure Features and Support Vectors

In this research work, we proposed a medical image analysis framework with two separate releases whether or not Synovial Sarcoma (SS) is the cell structure for cancer. Within this framework the histopathology images are decomposed into a third-level sub-band using a two-dimensional Discrete Wavelet Transform. Subsequently, the structure features (SFs) such as Principal Components Analysis (PCA), Independent Components Analysis (ICA) and Linear Discriminant Analysis (LDA) were extracted from this sub-band image representation with the distribution of wavelet coefficients. These SFs are used as inputs of the Support Vector Machine (SVM) classifier. Also, classification of PCA + SVM, ICA + SVM, and LDA + SVM with Radial Basis Function (RBF) kernel the efficiency of the process is differentiated and compared with the best classification results. Furthermore, data collected on the internet from various histopathological centres via the Internet of Things (IoT) are stored and shared on blockchain technology across a wide range of image distribution across secure data IoT devices. Due to this, the minimum and maximum values of the kernel parameter are adjusted and updated periodically for the purpose of industrial application in device calibration. Consequently, these resolutions are presented with an excellent example of a technique for training and testing the cancer cell structure prognosis methods in spindle shaped cell (SSC) histopathological imaging databases. The performance characteristics of cross-validation are evaluated with the help of the receiver operating characteristics (ROC) curve, and significant differences in classification performance between the techniques are analyzed. The combination of LDA + SVM technique has been proven to be essential for intelligent SS cancer detection in the future, and it offers excellent classification accuracy, sensitivity, specificity.     

Prognostic Kalman Filter Based Bayesian Learning Model for Data Accuracy Prediction

Data is always a crucial issue of concern especially during its prediction and computation in digital revolution. This paper exactly helps in providing efficient learning mechanism for accurate predictability and reducing redundant data communication. It also discusses the Bayesian analysis that finds the conditional probability of at least two parametric based predictions for the data. The paper presents a method for improving the performance of Bayesian classification using the combination of Kalman Filter and K-means. The method is applied on a small dataset just for establishing the fact that the proposed algorithm can reduce the time for computing the clusters from data. The proposed Bayesian learning probabilistic model is used to check the statistical noise and other inaccuracies using unknown variables. This scenario is being implemented using efficient machine learning algorithm to perpetuate the Bayesian probabilistic approach. It also demonstrates the generative function for Kalman-filer based prediction model and its observations. This paper implements the algorithm using open source platform of Python and efficiently integrates all different modules to piece of code via Common Platform Enumeration (CPE) for Python.     

A new asymmetric dual source multilevel inverter topology with reduced power switches

Multilevel inverters can synthesize a high-voltage staircase waveform with low- and medium-voltage components. A new multilevel inverter topology called Asymmetric Dual Source Multilevel Inverter (ADS-MLI) is proposed. When compared to the topologies found in the literature, it can produce multiple levels in the output voltage with fewer power switches. Most of the topologies found in the literature require cascading features to achieve asymmetric operation; but the ADS-MLI can operate without the need for cascading. A simulation prototype capable of synthesizing 13 levels is developed in MATLAB Simulink environment. Its performance is evaluated in the aspects of; number of switching components, efficiency, THD, switching voltage stress and common mode voltage. The simulated efficiency and power quality of the DS-MLI is validated using a 1 kW prototype fabricated using FGA25N120-ANTD controlled by FPGA-SPARTAN 6 processor. Further, the DS-MLI is field tested with a 1 kW solar PV unit and the results are presented.