Effect of Thermal Treatment on Meat Proteins with Special Reference to Heterocyclic Aromatic Amines (HAAs)

Meat is one of the most imperative protein sources available with respect to its production and consumption. It is the richest source of some valuable nutrients like proteins, essential amino acids, polyunsaturated fatty acids, vitamins, and minerals like iron, zinc, and selenium. Thermal treatment produces conformational changes in protein structure as well as flavor, texture, and appearance, and chemical properties of the ingredients are also changed. Heterocyclic aromatic amines (HAAs), potent mutagens/carcinogens, are formed during the cooking of meat at high temperature. The review paper highlights the effects of various cooking methods, i.e., pan-frying, deep-frying, charcoal grilling, and roasting, on the formation of HAAs. The levels of HAAs produced in cooked meats vary depending upon the cooking method, time of cooking, and the type of meat being cooked. Metabolic behavior of HAAs is very unique, they interfere in the activity of many enzymes, modify the metabolic pathways, and lead to the adduct formation of DNA. The application of black pepper and several other spices during processing may reduce the formation of these (HAAs) mutagenic compounds.     

Analytical technique for the two-dimensional stress wave model of memory alloy dampers

In this paper vibration damping capacity of shape memory alloys (SMA) is studied which is based on two-dimensional Oberaigner, Fischer and Tanaka model. The thermodynamic based active and passive control paradigms in SMA are presented. The model solution is presented along with modification based on exact solution for the most general case of a set of conditions based upon general thermal regimes. For the particular cases, four examples of different thermal and mechanical loadings are given. This study incorporates the static thermal changes and dynamic thermal states.     

Nano-crystalline LaFeO3 powders synthesized by the citrate–gel method

A novel sol–gel process was developed for preparing nano-sized, perovskite-type LaFeO₃ powder by the thermal decomposition of the gel-complex of LaFe–(C₆H₈O₇·H₂O). The structural evolution has been systematically investigated by X-ray diffraction (XRD), differential thermal analysis (DTA) and thermogravimetric analysis (TGA). Perovskite powder of  25 nm size could be obtained at a temperature of  600 °C without formation of any secondary phases of La₂O₃ and Fe₂O₃ single oxides and no requirements of high temperature/vacuum/pH control etc. Analysis of the X-ray powder diffraction data showed a decrease in the value of lattice strains with increasing decomposition temperature, whereas the particle size increases with increasing decomposition temperature.     

Correction to: Do Energy Resources matter for Growth Level? The dynamic effects of different strategies of renewable energy,carbon emissions on sustainable economic growth

Clean Technologies and Environmental Policy -     

Addressing image and Poisson noise deconvolution problem using deep learning approaches

Digital images are more important in numerous contemporary applications, and the need for images in the technical field is also increasing drastically. It is used to recognize signatures and faces in many industries and is applicable for intelligent departments. The images are usually associated with the noise content; this may happen due to the instrument imperfections, troubleshooting while collecting data from the acquisition process, and another natural phenomenon. Poisson noise, also known as photon noise, is caused in the images due to the statistical essence of electromagnetic waves. X-ray, visible light, and gamma rays are electromagnetic waves. The enhancement of the convolution model in addressing images is challenging due to the various constituents such as optical aberrations, noise level, and optical setup. The modeling configuration of the image is attained using the point spread function (PSF), which is responsible for the system's impulse response. The quality image is retrieved by denoising and super-resolution (SR) methods; these methods simultaneously eliminate the noise content from the images. A Richardson–Lucy and alternating direction method of multipliers type of non-blind iterative algorithmic approaches associated with the PSF performance in addressing image is comparatively analyzed. The deep learning approach, convolutional neural networks (CNNs), is also employed to understand the nonlinear mapping relationship between the observed data and ground reality. The performance of the various network approaches is compared in this article. The result obtained shows that the deep learning CNNs achieved higher accuracy in producing denoising images. The goal of the proposed system model is to remove the interference noise in images. The high-resolution images are obtained by implementing a SR-based CNN model.     

Do Energy Resources matter for Growth Level? The dynamic effects of different strategies of renewable energy,carbon emissions on sustainable economic growth

Clean Technologies and Environmental Policy - This study examines the association between renewable energy strategies and carbon emissions on sustainable economic growth under affordable and clean...     

Development of Magnetocaloric Microstructures from Equiatomic Iron–Rhodium Nanoparticles through Laser Sintering

Pronounced magnetocaloric effects are typically observed in materials that often contain expensive and rare elements and are therefore costly to mass produce. However, they can rather be exploited on a small scale for miniaturized devices such as magnetic micro coolers, thermal sensors, and magnetic micropumps. Herein, a method is developed to generate magnetocaloric microstructures from an equiatomic iron–rhodium (FeRh) bulk target through a stepwise process. First, paramagnetic near-to-equiatomic solid-solution FeRh nanoparticles (NPs) are generated through picosecond (ps)-pulsed laser ablation in ethanol, which are then transformed into a printable ink and patterned using a continuous wave laser. Laser patterning not only leads to sintering of the NP ink but also triggers the phase transformation of the initial γ- to B2-FeRh. At a laser fluence of 246 J cm⁻², a partial (52%) phase transformation from γ- to B2-FeRh is obtained, resulting in a magnetization increase of 35 Am² kg⁻¹ across the antiferromagnetic to ferromagnetic phase transition. This represents a ca. sixfold enhancement compared to previous furnace-annealed FeRh ink. Finally, herein, the ability is demonstrated to create FeRh 2D structures with different geometries using laser sintering of magnetocaloric inks, which offers advantages such as micrometric spatial resolution, in situ annealing, and structure design flexibility.     

Comparative Effect of Foliar Application of Silicon,Titanium and Zinc Nanoparticles on the Performance of Vetiver- a Medicinal and Aromatic Plant

Silicon - In the agriculture sector, the use of nanoparticles (NPs) has become a centre of attraction for plant biological researchers. Several studies have been accomplished regarding the...