Enhancing the Thermal and Mechanical Properties of Organic-Inorganic Hybrid Nanocomposite Films Based on Poly Lactic Acid/OMMT Nano Clay

Abstract: Organic (PLA) inorganic (OMMT nano clay) hybrid nanocomposite films were fabricated using poly lactic acid (PLA) with various weight percentages (1-3wt%) of organically modified montmorillonite (OMMT) nano clay by means of one step solvent casting method. The thermal, mechanical and water absorption properties were determined as per standard testing methods to determine the optimum percentage of OMMT nano clay within the nanocomposite was investigated. The surface morphology of the organic-inorganic hybrid nanocomposite films was analyzed through XRD, SEM, and TEM surface analytical techniques. The incorporation of OMMT clay in to PLA matrix is found to have enhanced the thermo-mechanical properties. The water absorption and solubility test results also support the data from thermo-mechanical tests. The 2 wt % OMMT clay loaded PLA films showed the best results among all. The obtained results showed that the thermal, mechanical and water absorption properties could be increased significantly with the optimum incorporation of OMMT nano clay in a PLA matrix, in comparision wih the neat PLA

Cultivating Insight: Detecting Autism Spectrum Disorder through Residual Attention Network in Facial Image Analysis

Revolutionizing Autism Spectrum Disorder Identification through Deep Learning: Unveiling Facial Activation Patterns. In this study, our primary objective is to harness the power of deep learning algorithms for the precise identification of individuals with autism spectrum disorder (ASD) solely from facial image datasets. Our investigation centers around the utilization of face activation patterns, aiming to uncover novel insights into the distinctive facial features of ASD patients. To accomplish this, we meticulously examined facial imaging data from a global and multidisciplinary repository known as the Autism Face Imaging Data Exchange. Autism spectrum disorder is characterized by inherent social deficits and manifests in a spectrum of diverse symptomatic scenarios. Recent data from the Centers for Disease Control (CDC) underscores the significance of this disorder, indicating that approximately 1 in 54 children are impacted by ASD, according to estimations from the CDC's Autism and Developmental Disabilities Monitoring Network (ADDM). Our research delved into the intricate functional connectivity patterns that objectively distinguish ASD participants, focusing on their facial imaging data. Through this investigation, we aimed to uncover the latent facial patterns that play a pivotal role in the classification of ASD cases. Our approach introduces a novel module that enhances the discriminative potential of standard convolutional neural networks (CNNs), such as ResNet-50, thus significantly advancing the state-of-the-art. Our model achieved an impressive accuracy rate of 99% in distinguishing between ASD patients and control subjects within the dataset. Our findings illuminate the specific facial expression domains that contribute most significantly to the differentiation of ASD cases from typically developing individuals, as inferred from our deep learning methodology. To validate our approach, we conducted real-time video testing on diverse children, achieving an outstanding accuracy score of 99.90% and an F1 score of 99.67%. Through this pioneering work, we not only offer a cutting-edge approach to ASD identification but also contribute to the understanding of the underlying facial activation patterns that hold potential for transforming the diagnostic landscape of autism spectrum disorder

Fixed Points on Covariant and Contravariant Maps with an Application

Fixed-point results on covariant maps and contravariant maps in a (Formula presented.) -algebra-valued bipolar metric space are proved. Our results generalize and extend some recently obtained results in the existing literature. Our theoretical results in this paper are supported with suitable examples. We have also provided an application to find an analytical solution to the integral equation and the electrical circuit differential equation. © 2022 by the authors

Fixed point theorem on an orthogonal extended interpolative ψF-contraction

In this paper, we establish the fixed point results for an orthogonal extended interpolative Ciric Reich-Rus type $\psi\mathcal{F}$-contraction mapping on an orthogonal complete $\mathfrak{b}$-metric spaces and give an example to strengthen our main results. Furthermore, we present an application to fixed point results to find analytical solutions for functional equation

Glutathione de Novo Synthesis but Not Recycling Process Coordinates with Glutamine Catabolism to Control Redox Homeostasis and Directs Murine T Cell Differentiation

Upon antigen stimulation, T lymphocytes undergo dramatic changes in metabolism to fulfill the bioenergetic, biosynthetic and redox demands of proliferation and differentiation. Glutathione (GSH) plays an essential role in controlling redox balance and cell fate. While GSH can be recycled from Glutathione disulfide (GSSG), the inhibition of this recycling pathway does not impact GSH content and murine T cell fate. By contrast, the inhibition of the de novo synthesis of GSH, by deleting either the catalytic (Gclc) or the modifier (Gclm) subunit of glutamate–cysteine ligase (Gcl), dampens intracellular GSH, increases ROS, and impact T cell differentiation. Moreover, the inhibition of GSH de novo synthesis dampened the pathological progression of experimental autoimmune encephalomyelitis (EAE). We further reveal that glutamine provides essential precursors for GSH biosynthesis. Our findings suggest that glutamine catabolism fuels de novo synthesis of GSH and directs the lineage choice in T cells

Recent Strategy of Biodiesel Production from Waste Cooking Oil and Process Influencing Parameters: A Review

Cost of biodiesel produced from virgin vegetable oil through transesterification is higher than that of fossil fuel, because of high raw material cost. To minimize the biofuel cost, in recent days waste cooking oil was used as feedstock. Catalysts used in this process are usually acids, base, and lipase. Since lipase catalysts are much expensive, the usage of lipase in biodiesel production is limited. In most cases, NaOH is used as alkaline catalyst, because of its low cost and higher reaction rate. In the case of waste cooking oil containing high percentage of free fatty acid, alkaline catalyst reacts with free fatty acid and forms soap by saponification reaction. Also, it reduces the biodiesel conversions. In order to reduce the level of fatty acid content, waste cooking oil is pretreated with acid catalyst to undergo esterification reaction, which also requires high operating conditions. In this review paper, various parameters influencing the process of biofuel production such as reaction rate, catalyst concentration, temperature, stirrer speed, catalyst type, alcohol used, alcohol to oil ratio, free fatty acid content, and water content have been summarized