Unveiling the frontiers of deep learning: innovations shaping diverse domains

Deep learning (DL) enables the development of computer models that are capable of learning, visualizing, optimizing, refining, and predicting data. In recent years, DL has been applied in a range of fields, including audio-visual data processing, agriculture, transportation prediction, natural language, biomedicine, disaster management, bioinformatics, drug design, genomics, face recognition, and ecology. To explore the current state of deep learning, it is necessary to investigate the latest developments and applications of deep learning in these disciplines. However, the literature is lacking in exploring the applications of deep learning in all potential sectors. This paper thus extensively investigates the potential applications of deep learning across all major fields of study as well as the associated benefits and challenges. As evidenced in the literature, DL exhibits accuracy in prediction and analysis, makes it a powerful computational tool, and has the ability to articulate itself and optimize, making it effective in processing data with no prior training. Given its independence from training data, deep learning necessitates massive amounts of data for effective analysis and processing, much like data volume. To handle the challenge of compiling huge amounts of medical, scientific, healthcare, and environmental data for use in deep learning, gated architectures like LSTMs and GRUs can be utilized. For multimodal learning, shared neurons in the neural network for all activities and specialized neurons for particular tasks are necessary.Comment: 64 pages, 3 figures, 3 table

Navigating the IoT landscape: Unraveling forensics, security issues, applications, research challenges, and future

Given the exponential expansion of the internet, the possibilities of security attacks and cybercrimes have increased accordingly. However, poorly implemented security mechanisms in the Internet of Things (IoT) devices make them susceptible to cyberattacks, which can directly affect users. IoT forensics is thus needed for investigating and mitigating such attacks. While many works have examined IoT applications and challenges, only a few have focused on both the forensic and security issues in IoT. Therefore, this paper reviews forensic and security issues associated with IoT in different fields. Future prospects and challenges in IoT research and development are also highlighted. As demonstrated in the literature, most IoT devices are vulnerable to attacks due to a lack of standardized security measures. Unauthorized users could get access, compromise data, and even benefit from control of critical infrastructure. To fulfil the security-conscious needs of consumers, IoT can be used to develop a smart home system by designing a FLIP-based system that is highly scalable and adaptable. Utilizing a blockchain-based authentication mechanism with a multi-chain structure can provide additional security protection between different trust domains. Deep learning can be utilized to develop a network forensics framework with a high-performing system for detecting and tracking cyberattack incidents. Moreover, researchers should consider limiting the amount of data created and delivered when using big data to develop IoT-based smart systems. The findings of this review will stimulate academics to seek potential solutions for the identified issues, thereby advancing the IoT field.Comment: 77 pages, 5 figures, 5 table

Anti-inflammatory, thrombolytic and hair-growth promoting activity of the n-hexane fraction of the methanol extract of Leea indica leaves

The anti-inflammatory, thrombolytic, and hair growth-promoting activity of the n-hexane fraction from the methanol extract of Leea indica (NFLI) leaves was investigated. NFLI showed significant inhibition of hemolysis and protein denaturation, and exhibited a concentration-dependent thrombolytic activity. When applied topically to mice at concentrations of 10, 1, 0.1%, NFLI demonstrated a significant increase in average hair length (p < 0.001) compared with untreated animals. NFLI (1% concentration) exhibited the highest percentage of hair regrowth on day 7, 14 and 21 (81.24, 65.60, and 62.5%, respectively). An in silico study was further conducted to predict the binding affinity of phytochemicals previously reported in L. indica towards PGD2 synthase (PDB ID: 2VD1), an enzyme that catalyses the isomerisation of prostaglandin H2 to PGD2 which is involved in hair loss. Phthalic acid, farnesol, n-tricosane, n-tetracosane, and n-heptacosane showed the best ligand efficiencies towards PGD2 synthase and their intermolecular interactions were visualised using BIOVIA Discovery Studio Visualizer. Our results indicate that L. indica could represent a promising natural alternative to tackle alopecia

Insightful valorization of the biological activities of Pani Heloch leaves through experimental and computer-aided mechanisms

Pani heloch (Antidesma montanum) is traditionally used to treat innumerable diseases and is a source of wild vegetables for the management of different pathological conditions. The present study explored the qualitative phytochemicals; quantitative phenol and flavonoid contents; in vitro antioxidant, anti-inflammatory, and thrombolytic effects; and in vivo antipyretic and analgesic properties of the methanol extract of A. montanum leaves in different experimental models. The extract exhibited secondary metabolites including alkaloids, flavonoids, flavanols, phytosterols, cholesterols, phenols, terpenoids, glycosides, fixed oils, emodines, coumarins, resins, and tannins. Besides, Pani heloch showed strong antioxidant activity (IC50 = 99.00 µg/mL), while a moderate percentage of clot lysis (31.56%) in human blood and significant anti-inflammatory activity (p < 0.001) was achieved with the standard. Moreover, the analgesic and antipyretic properties appeared to trigger a significant response (p < 0.001) relative to in the control group. Besides, an in silico study of carpusin revealed favorable protein-binding affinities. Furthermore, the absorption, distribution, metabolism, excretion, and toxicity analysis and toxicological properties of all isolated compounds adopted Lipinski’s rule of five for drug-like potential and level of toxicity. Our research unveiled that the methanol extract of A. montanum leaves exhibited secondary metabolites that are a good source for managing inflammation, pyrexia, pain, and cellular toxicity. Computational approaches and further studies are required to identify the possible mechanism which responsible for the biological effects

Biological evaluation, DFT calculations and molecular docking studies on the antidepressant and cytotoxicity activities of Cycas pectinata buch.-ham. compounds

Cycas pectinata Buch.-Ham. is commonly used in folk medicine against various disorders. The present study investigated the antidepressant and cytotoxicity activity of methanol extract of C. pectinata (MECP) along with quantitative phytochemical analysis by GC-MS method. Here, the GC-MS study of MECP presented 41 compounds, among which most were fatty acids, esters, terpenoids and oximes. The antidepressant activity was assessed by the forced swimming test (FST) and tail suspension test (TST) models. In contrast, MECP (200 and 400 mg/kg) exhibited a significant and dose-dependent manner reduction in immobility comparable with fluoxetine (10 mg/kg) and phenelzine (20 mg/kg). MECP showed a weak toxicity level in the brine shrimp lethality bioassay (ED50: 358.65 µg/mL) comparable to the standard drug vincristine sulfate (ED50: 2.39 µg/mL). Three compounds from the GC-MS study were subjected to density functional theory (DFT) calculations, where only cyclopentadecanone oxime showed positive and negative active binding sites. Cyclopentadecanone oxime also showed a good binding interaction in suppressing depression disorders by blocking monoamine oxidase and serotonin receptors with better pharmacokinetic and toxicological properties. Overall, the MECP exhibited a significant antidepressant activity with moderate toxicity, which required further advance studies to identify the mechanism.Centro de Investigación y Publicación (CRP) | Ref. IRG 180111Universidad Islámica Internacional de Chittagong (IIUC