Advances in Robustness of Image-based Malware Detection

In recent years, deep learning has emerged as a powerful tool for image classification tasks. However, the performance of individual deep learning models can be limited by their architecture and training data. In this project, various Convolutional Neural Network (CNN) architectures are proposed to train the malware data for feature extraction for various color coordinates such as L, CMYK, RGB, RGBA, and YCbCr. Different optimization techniques like Stochastic Gradient Descent, Root Mean Square Propagation, Ada Delta, Adam, and Adaptive Gradient are used to minimize errors in the trained data, leading to enhanced accuracy. The proposed ensemble deep learning model for image classification, combining strengths from popular CNN architectures like LeNet, AlexNet, VGG, ResNet, and GoogleNet, is utilized for feature extraction. This model employs a weighted average of predictions from each model to make the final classification decision. The performance of the proposed model is evaluated using several benchmark datasets, and the experimental results demonstrate that the ensemble model achieves higher accuracy and robustness compared to individual models and other state-of-the-art ensemble methods. Ablation studies were conducted to analyze the contribution of each model to the ensemble performance. The results reveal that each model contributes differently, and the combination of all models achieves the best performance. The proposed ensemble deep learning model, incorporating AlexNet, LeNet, VGG, ResNet, and GoogleNet architectures, attains state-of-the-art performance across several benchmark datasets. This versatile model can be applied to various image classification tasks, including object recognition, scene understanding, and medical image analysis

Computational screening, ensemble docking and pharmacophore analysis of potential gefitinib analogues against epidermal growth factor receptor

<p>The observable mutated isoforms of epidermal growth factor receptor (EGFR) are important considerable therapeutic benchmarks in moderating the non-small cell lung cancer (NSCLC). Recently, quinazoline-based ATP competitive inhibitors have been developed against the EGFR; however, these imply the mutation probabilities, which contribute to the discovery of high probable novel inhibitors for EGFR mutants. Therefore, SAR-based bioactivity analysis, molecular docking and computational toxicogenomics approaches were performed to identify and evaluate new analogs of gefitinib against the ligand-binding domain of the EGFR double-mutated model. From the diverse groups of molecular clustering and molecular screening strategies, top high-binding gefitinib-analogues were identified and studied against EGFR core cavity through three-phase ensemble docking approach. Resulted high possible leads showed good binding orientations than gefitinib (positive control) thus they were subjected to pharmacophore analysis that possesses possible molecular assets to tight binding with EGFR domain. Residues Ser720, Arg841 and Trp880 were observed as novel hot spots and involved in H-bonds, pi-stacking and π-cation interactions that contribute additional electrostatic potency to sustain stability and complexity of protein-ligand complexes, thus they have ability to profoundly adopted by pharmacophoric features. Furthermore, lead molecules have an inhibition percent probability, anticancer potency, toxic impacts, flexible pharmacokinetics, potential gene-chemical interactions towards EGFR were revealed by computational systems biology tools. Our multiple screening strategies confirmed that the druggable sub-pocket was crucial to strong EGFR-ligand binding. The essential pharmacophoric features of ligands provided viewpoints for new inhibitors envisaging, and predicted scaffolds could used as anticancer agents against selected EGFR mutated isoforms.</p

Recovery of Prenatal Baicalein Exposure Perturbed Reproduction by Postnatal Exposure of Testosterone in Male Mice

Baicalein (BC), a flavonoid, which lacks the qualities of reproductive health and shows adverse effects, is tested in this study. Inseminated mice were injected with 30, 60, and 90 mg BC/Kg body weight on gestation days 11, 13, 15, and 17. The F1 BC-exposed males of each dosage were divided into six groups. First three groups (n = 6 from each BC dosage) were used for assessment of reproductive performance, the others (n = 4 from each BC dosage) were administered with testosterone 4.16 mg/kg body weight on postnatal days 21, 31, and 41. The reproductive health of adult F1 males at the age of 55 and 60 was tested. Prenatal BC exposure showed reduced fertility after cohabitation with control females. The BC exposure significantly reduced the body weight, tissue indices, and sperm parameters (motility, count, viability, and daily sperm count) and altered the sperm membrane in a hypoosmotic swelling test. A downward trend was observed in testicular steroidogenic marker enzymes (3β- and 17β-steroid dehydrogenases) and serum testosterone, whereas increase in serum titers of FSH and LH along with altered the testicular histology. Conversely, testosterone (4.16 mg/kg body weight) partially recovered reduced male reproductive health by BC. BC impaired male reproductive health due to low levels of testosterone is reverted by external testosterone is evidenced in this study

Fluoranthene-based derivatives for multimodal anti-counterfeiting and detection of nitroaromatics

In this study, we developed two novel sky blue fluorescent fluorophores comprising ethyl alcohol (FOH) and ethanethiol (FSH) units appended to fluoranthene at the periphery. Single Crystal X-Ray Diffraction (SC-XRD) studies reveal that the molecular flexibility of alkyl chains leads to distinct diagonal (FOH) and ladder (FSH) shaped supramolecular arrangements in the crystal lattices. Detailed photophysical and DFT studies showed that FOH and FSH demonstrate high sensitivity and selectivity towards the detection of trinitrophenol (TNP). FSH exhibits high quenching efficiency (similar to 84%), a rate constant of KSV = 1.1 x 104 M-1 with a limit of detection of similar to 97 ppm in THF, and similar to 76 ppm in river water. Mechanistic investigation through NMR and SC-XRD of the FSH adduct with 1,3-dinitrobenzene (DNB) reveal strong pi-pi interactions (3.518 angstrom). Furthermore, photoinduced electron transfer occurs from the fluorophores to the nitro analytes and leads to strong intermolecular interactions using the static quenching mechanism. Both fluorophores were employed in advanced surveillance to identify finger marks on a wide range of substrates (glass, cellophane tape, aluminium foil and floor tiles) with different resolutions to provide an unadorned and lucrative method for viewing the latent fingerprints (LFPs) with exceptionally consistent evidence of up to level 3 and without the requirement for post-treatments, leading to promising applications for onsite forensic analysis. Furthermore, FOH and FSH were evaluated in 72 hpf zebrafish larvae/embryos to demonstrate the non-toxicological behaviour and fluorescence imaging/tracking. Two novel fluoranthene ensembles with ethyl alcohol (FOH) and ethanethiol (FSH) functionality with distinct diagonal and ladder arrangements in the crystal lattices were developed for Latent Fingerprints (LFPs) towards analysis of explosives.Web of Science4236270625