Quality of Processed Cheddar Cheese as a Function of Emulsifying Salt Replaced by κ-Carrageenan

Hydrocolloids act as stabilizer and thickening agents, thus able to replace emulsifying salts. The present study was planned to use к-carrageenan in the production of processed cheddar cheese and to explore its effect on physico-chemical and textural properties of processed cheddar cheeses. Different concentration of ?-carrageenan were used with gradual decrease in salt contents along with natural cheese, fat, and water to prepare processed cheddar cheese. The prepared samples were analyzed for physico-chemical and sensory attributes at storage interval of 45 days during and after 90 days. With the increase in hydrocolloid concentration, stiffer product was obtained and meltability of the samples decreased than control. Processed cheddar cheese samples having 0.15% к-carrageenan with 2% emulsifying salt (1.34% sodium citrate and 0.66% disodium phosphates) were found more acceptable in terms of physico-chemical and sensory attributes, but all sensory attributes got fewer score with the passage of storage time.     

Physiological and Nutraceutical Perspectives of Fructan

Functional and nutraceutical foods have captured the global market owing to trends and perceptions of consumers on the natural products and diet-health linkages. Health promoting potential of such foods has been attributed to the presence of essential bioactive moieties. Wheat, being staple food in many parts of the world, gained substantial attention of researchers particularly for the extraction of various functional components. Among these, fructan oligosaccharides in nature bestow quality of baked products and provide protection against various physiological disorders. Addition of fructan in various baked products enhances softness and color, especially in bread, and also imparts textural improvement. Moreover, fructans boost mineral absorption, hypocholesterolemic, and hypoglycemic perspectives, bifidogenic nature and controlling cancer insurgence. The benefits allied with fructan are mainly dose and time dependent. In this context, its industrial applications for vulnerable groups are increasing worldwide.     

Epoxidation reactions of unsaturated fatty esters with potassium peroxomonosulfate

Epoxidation of the double bond in methyl oleate, octadec-11E-en-9-ynoate, ricinoleate (12-hydroxy-octadec-9Z-enoate), iso-ricinoleate (9-hydroxy-octadec-12Z-enoate), and 12-oxo-octadec-9Z-enoate with potassium peroxomonosulfate (oxone, 2 KHSO₅.K₂SO₄) in the presence of trifluoroacetone or methyl pyruvate gave the corresponding monoepoxy derivatives. Reaction of Oxone^® with methyl linoleate and octadeca-9Z,11E-dienoate furnished the corresponding diepoxystearate derivative. Methyl 9,12-dioxo-octadec-10Z-enoate was obtained when a C₁₈ furanoid fatty ester (methyl 9,12-epoxy-9,11-octadecadienoate) was treated with Oxone^®. The yield of these reactions was very high (85–99%), and the epoxy derivatives were readily isolated by solvent extraction. The products were identified by spectroscopic methods.     

Forecasting Financial Time Series with Grammar‐Guided Feature Generation

The application of machine learning techniques to forecast financial time series is not a recent development, yet it continues to attract considerable attention because of the difficulty of the problem that is compounded by the nonlinear and nonstationary nature of the time series. The choice of an appropriate set of features is crucial to improve forecasting accuracy of machine learning techniques. In this article, we propose a systematic way for generating rich features using context‐free grammars. Our proposed methodology identifies potential candidates for new technical indicators that consistently improve forecasts compared with some well‐known indicators. The notion of grammar families as a compact representation to generate a rich class of features is exploited, and implementation issues are discussed in detail. The proposed methodology is tested on closing price data of major stock market indices, and the forecasting performance is compared with some standard techniques. A comparison with the conventional approach using standard technical indicators and naive approaches is shown.     

Estimation of heating time in tubular supercritical water reactors

Reactor efficiency and product distribution in supercritical water (SCW) reactors is greatly influenced by the design of the heating section of these reactors. However, little experimental or theoretical work is available to estimate the rate of heat transfer in such systems. In the present study, CFD modeling of the heat transfer in tubular SCW reactors has been performed. Effects of various operating parameters; i.e. reactor temperature and pressure, flow rate, reactor diameter, and the external heating mechanism, on the heating time constant, the temperature profile along the reactor, and reactor residence time are investigated. Based on numerical simulations, a semi-theoretical model is proposed to estimate the heating time constant as a function of reactor operating conditions. Results of this study provide useful insights for designing continuous supercritical water reactors as well as for the analysis of experimental data obtained from such systems.     

An all-purpose dispersive multiconductor interconnect modelcompatible with PRIMA

This paper describes a new, transmission line-based discrete model for interconnects with per-unit-length, frequency-dependent resistance and inductance. The proposed model is developed in such a manner that the resulting discrete form of Telegrapher's equations constitutes a passive system, and is compatible with passive, reduced-order macromodeling algorithms. The validity of the proposed model is demonstrated through numerical examples     

Aflatoxins: Biosynthesis,Occurrence, Toxicity,and Remedies

Food contagion with aflatoxins is the modern concern and has received a great awareness during the last few decades. The intermittent incidence of these toxins in agricultural commodities has negative role on the economy of the affected regions where harvest and postharvest techniques for the prevention of mold growth, are seldom practiced. Aflatoxins are difuranocoumarin derivatives produced by a polyketide pathway by the fungus Aspergillus flavus and Aspergillus parasiticus via polyketide pathway which are highly hepatotoxic, hepatocarcinogenic, teratogenic, and mutagenic in nature and contaminate a wide variety of important agricultural commodities before, during, and after harvest in various environmental conditions. The production of aflatoxins in innate substrates depends upon the various factors, that is, type of substrate, fungal species, moisture contents of the substrate, minerals, humidity, temperature, and physical damage of the kernels. These toxins cause several ailments such as cancer, hepatitis, mutation abnormalities, and reproduction disorders. Minimization and inactivation of aflatoxins contaminants through proper crop management at farm level and with physical, chemical, and biological techniques are the limelight of the article.     

Controlled Forging of a Nb Containing Microalloyed Steel for Automotive Applications

Controlled forging of microalloyed steels is a viable economical process for the manufacture of automotive parts. Ferrite grain refinement and precipitation hardening are the major microstructural parameters to enhance the mechanical properties of the forged components. In the current study, a modified thermomechanical treatment for additional ferrite grain refinement is developed by exploiting the effect of Nb in increasing the T _NR (no recrystallization temperature) and via phase transformation from a pancaked austenite. This is accomplished by performing the final passes of forging below the T _NR temperature followed by a controlled cooling stage to produce a mixture of fine grained ferrite, small scaled acicular ferrite as well as a limited amount of martensite. The effect of processing parameters in terms of forging strain, cooling rate and aging condition on the microstructure and mechanical properties of a medium carbon, Nb containing microalloyed steel is investigated. An attempt is made to identify a suitable microstructure that provides a proper combination of high strength and good impact toughness. The processing-microstructure relationships for the proposed novel forging procedure are discussed, and directions for further improvements are outlined.     

Optimal Deep Hybrid Boltzmann Machine Based Arabic Corpus Classification Model

Natural Language Processing (NLP) for the Arabic language has gained much significance in recent years. The most commonly-utilized NLP task is the ‘Text Classification’ process. Its main intention is to apply the Machine Learning (ML) approaches for automatically classifying the textual files into one or more pre-defined categories. In ML approaches, the first and foremost crucial step is identifying an appropriate large dataset to test and train the method. One of the trending ML techniques, i.e., Deep Learning (DL) technique needs huge volumes of different types of datasets for training to yield the best outcomes. The current study designs a new Dice Optimization with a Deep Hybrid Boltzmann Machine-based Arabic Corpus Classification (DODHBM-ACC) model in this background. The presented DODHBM-ACC model primarily relies upon different stages of pre-processing and the word2vec word embedding process. For Arabic text classification, the DHBM technique is utilized. This technique is a hybrid version of the Deep Boltzmann Machine (DBM) and Deep Belief Network (DBN). It has the advantage of learning the decisive intention of the classification process. To adjust the hyperparameters of the DHBM technique, the Dice Optimization Algorithm (DOA) is exploited in this study. The experimental analysis was conducted to establish the superior performance of the proposed DODHBM-ACC model. The outcomes inferred the better performance of the proposed DODHBM-ACC model over other recent approaches.