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Copyright of Journal of Taibah University Medical Sciences is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper delves into the transformative role of machine learning (ML) techniques in revolutionizing the security of electric and flying vehicles (EnFVs). By exploring key domains such as predictive maintenance, cyberattack detection, and intelligent decision-making, the study uncovers pivotal insights that will shape the future of this technology. From a theoretical perspective, ML emerges as a cornerstone for fortifying EnFV safety, offering real-time threat detection, predictive maintenance capabilities, and enhanced anomaly detection. In practical terms, ML-based solutions are envisioned as instrumental in preventing cyberattacks, reducing downtime, and improving overall safety. The research contributions of this study encompass a comprehensive overview of ML applications in EnFV security, identification of challenges, and paving the way for future research directions. While acknowledging research limitations, particularly the need for real-world implementation, the study emphasizes the crucial yet underexplored ethical considerations in ML for EnFV security. Future research suggestions focus on Explainable AI techniques, real-time ML algorithms for resource-constrained environments, and privacy-preserving ML techniques, aiming for a transparent, efficient, and privacy-aware integration of ML in EnFV security. By addressing key security challenges, ML can potentially revolutionize the EnFV domain, paving the way for a future of efficient, sustainable, and connected transportation systems. [ABSTRACT FROM AUTHOR]

Highlights • Stall-fed goats reared mainly on cereal rich concentrate mixture can develop fibrous osteodystrophy (FO). • Decreased Ca:P ratio and elevated ALP activity in view of clinical signs are diagnostic markers of FO in goats. • Biochemical analysis along with radiological examination could confirm FO in goats. Abstract Fibrous osteodystrophy (FO), a metabolic bone disorder, has been reported in different animal species with variable susceptibility. Albeit, it is commonly reported in horses, the clinical disease is also recorded globally in goats. Diagnosis of fibrous osteodystrophy is mainly based on various clinical examination methods including biochemical alterations which can be adopted as routine diagnostic method. Therefore, the present study was aimed to investigate calcium: phosphorus (Ca:P) ratio and alkaline phosphatase (ALP) activity as biochemical diagnostic markers in goats diagnosed for fibrous osteodystrophy by clinical and radiological examinations. Blood samples were obtained from 11 goats diagnosed to have clinical fibrous osteodystrophy and 10 healthy goats, and used for harvesting serum. Goats with fibrous osteodystrophy revealed markedly elevated serum phosphorus level and ALP activity, and lowered calcium level in comparison to healthy goats. Remarkably lower serum Ca:P ratio was also observed in diseased goats. Radiological examination of skull of diseased goats revealed radio-lucent areas on the mandible as well as the upper jaw. In conclusion, marked reduction in Ca:P ratio and elevation in ALP activity could be promising biochemical diagnostic marker of fibrous osteodystrophy in goats. [ABSTRACT FROM AUTHOR]

A novel acrylonitrile embedded benzimidazole-based probe 3 has been designed and synthesized by conjugating anthraquinone with 2-(1H-benzo[d]imidazol-2-yl)acetonitrile. The probe 3 potentially detects CN − ions in H 2 O/CH 3 CN (1:9; v/v), solid state, and plasma-like solution via chromo and fluorometric approach. The probe 3 displayed an absorption redshift from 415 nm to 472 nm and emission redshift from 510 nm to 610 nm in the presence of CN − ions, in H 2 O/CH 3 CN (1:9; v/v). The probe 3 displayed colour change from yellow to orange along with red emission in the presence of CN − ions. The probe 3 showed very low detection limit of 37 × 10 −9  M. Furthermore, probe 3 is also utilized as a portable paper strip for on-site detection of CN − ions. The 1 H NMR and mass spectrometry analysis confirmed the nucleophilic addition of CN − ions to probe 3 . [ABSTRACT FROM AUTHOR]

A commercial Zirconium alloy was subjected to different thickness reductions (20%, 40% and 60%) by cold rolling. A through-thickness gradient in microstructure, crystallographic texture and residual stress was observed. This gradient was till 1/8th of the specimen thickness, and implied a corresponding anisotropy in the imposed strain state. An elasto-plastic FE (finite element) model was developed to capture such through thickness deformation gradients. A reasonably good agreement was observed between the experimental and predicted residual stress distributions when the material anisotropy was accounted for. Through-thickness residual stress evolution was shown to be significantly affected by material anisotropy and to a lesser extent by the rolling parameters (coefficient of friction and rotational speed). [ABSTRACT FROM AUTHOR]

Modern vehicles are increasingly getting connected within the vehicles, with other systems, leading to more concerns about security. Controller area network (CAN) has become a de-facto standard for connecting internal vehicles' components. However, it lacks security features. Conventional security mechanisms fail to protect in-vehicle networks from attacks, requiring the development of an effective intrusion detection system (IDS). This work develops an IDS for in-vehicle networks called IDS-IVN based on a compact representation of location invariant and time-variant traffic features using deep learning. The IDS-IVN uses convolutional neural and long–short-term memory networks as encoder/decoder functions of autoencoder networks to extract features from raw data and classify them using latent space representation into intrusive and non-intrusive classes. A benchmark real-time ROAD dataset is used to demonstrate the IDS-IVN's performance compared to the existing methods. IDS-IVN reports 99% accuracy with a 0.32% low false-positive rate for detecting intrusions. [ABSTRACT FROM AUTHOR]

The rice Hybrid Proline Rich Protein (HyPRP) encoding gene, OsHyPRP16 expression exhibit early upregulation in response to Magnaporthe oryzae inoculation. Here, we functionally characterized the OsHyPRP16 promoter through deletion analysis in transgenic Arabidopsis using GUS (β-glucuronidase) reporter assay. The promoter fragments, sequentially deleted from the 5′ end could induce differential GUS activity in response to stresses induced by different hormones and abiotic stress conditions. In addition, a strong GUS induction was observed in M. oryzae inoculated transgenic Arabidopsis. Based on the insilico and stress-inducibility of D1 promoter fragment against various phytohormones and rice blast fungus, and with no basal activity under control conditions, we rationally selected D1 promoter fragment to drive the expression of a major rice blast resistance gene; Pi54 in the genetic background of blast susceptible TP309 rice line. The D1 promoter fragment was able to induce the expression of Pi54 at immediate-early stages of M. oryzae infection in transgenic rice. The transgenic plants with Pi54 under the control of D1 promoter fragment displayed complete resistance against M. oryzae infection as compared to control plants. The present study suggests that the D1 fragment of OsHyPRP16 promoter is a valuable tool for breeding and development of rice lines with early-inducible and pathogen-responsive enhanced disease resistance. • Functional characterization of rice HyPRP16 promoter was performed. • Deletion fragment (D1) exhibits distinct stress-response with no basal activity. • D1 driven R gene (Pi54) induce early upon M. oryzae infection in transgenic rice. • Early induction of Pi54 impart resistance against rice blast disease. [ABSTRACT FROM AUTHOR]

Apple is one of the most important fruit crops and the availability of recently sequenced genome facilitates research on gene–trait relationship. Quantitative real-time PCR (qRT-PCR) is a sensitive technique to study gene expression, but its accuracy largely depends on stability of reference gene used for data normalization. Therefore, present study was aimed to identify and validate suitable reference gene in apple. Expression stabilities of 10 housekeeping genes, which are commonly used as reference genes in qRT-PCR studies were evaluated in samples of different developmental stages, various tissue types and under diverse biotic stress conditions in apple. The PCR efficiency of all the genes was found to be ranging between 94–107.6%. Analysis using geNorm, NormFinder and Bestkeeper programs demonstrated that their expression stabilities vary among sample sets. However, protein phosphatase 2A ( PP2A ), ribosomal protein L2 ( RPL2 ) and glyceraldehyde-3-phosphate dehydrogenase ( GAPDH ) were found to be suitable reference genes across all the tissue types and under different biotic stress conditions, while 18S ribosomal RNA ( 18S ), β-tubulin ( TUB ) and ubiquitin ( UBQ ) were found to be the least stable genes. Moreover, a combination of different reference genes was suggested for different sample sets. These, results suggest that selection of suitable reference gene depends on the tissue type and development stage or disease condition. Further, use of more than one reference genes in respective tissue types of apple is suggested to accurately normalize qRT-PCR data, in future. [ABSTRACT FROM AUTHOR]

In this paper, we show a deep learning model for bot detection, named as DeBot, for industrial network traffic. DeBot uses a novel Cascade Forward Back Propagation Neural Network (CFBPNN) model with a subset of features using the Correlation-based Feature Selection (CFS) technique. A time series-based Nonlinear Auto-regressive Network with eXogenous inputs (NARX) technique analyzes the factors having a higher impact on the target variable and predict the behavioral pattern. To the best of our knowledge, we pioneer the use of optimal feature selection and integration with the cascading model of deep learning in bot detection of IIoTs. We conduct a thorough set of experiments on five popular bot datasets: NF-UNSW-NB15, NF-ToN-IoT, NF-BoT-IoT, NF-CSE-CIC-IDS2018, and ToN-IoT-Windows. We compare CFBPNN with other existing neural network models. We observe that CFBPNN in DeBot shows 100% accuracy in all the datasets with subset evaluation and obtains optimum F1-score and zero precision. [Display omitted] • We address the multi-layered network model with IIoT features to enable bot attack detection. • Our DeBot model evaluates the subset with optimal features with high impact on attack class and predict the risk factor. • We pioneer the implementation of time series-based Nonlinear Auto-Regressive eXogenous (NARX) model to predict the risk in the specified time gap. • We introduce a new cascading model with recurrent feature to preserve the relationship between input and output variables. [ABSTRACT FROM AUTHOR]

[Display omitted] • "Nature-to-new" as a medicinal chemistry strategy. • Iterative Scaffold-hopping to identify new chemotype. • Organocatalysed Umpolung Chemistry to construct Arylidene heterocyclic-fused imidazolone scaffold. • Polyphosphoric acid-mediated ester-lactam exchange. • In silico study reveals good drug-like properties. A strategy of "Nature-to-new" with iterative scaffold-hopping was considered for investigation of privileged ring/functional motif-elaborated analogs of natural aurones. An organocatalyzed umpolung chemistry based method was established for molecular-diversity feasible synthesis of title class of chemotypes i.e. (Z)-2-Arylideneimidazo[1,2– a ]pyridinones and (Z)-2-Arylidenebenzo[ d ]imidazo[2,1–b]thiazol-3-ones. Various biophysical experiments indicated their important biological properties. The analogs showed characteristic anticancer activities with efficiency more than an anticancer drug. The compounds induced apoptosis with arrest in the S phase of the cell cycle regulation. The compounds' significant effect in up/down-regulation of various apoptotic proteins, an apoptosis cascade, and the inhibition of topoisomerases-mediated DNA relaxation process was identified. The analysis of the structure-activity relationship, interference with biological events and the drug-likeness physicochemical properties of the compounds in the acceptable window indicated distinctive medicinal molecule-to-properties of the investigated chemotypes. [ABSTRACT FROM AUTHOR]

Abstract: Present study investigates the cultivable diversity of root-associated bacteria from a medicinal plant Ajuga bracteosa in the Kangra valley, in order to determine their plant growth promoting (PGP) and biotechnological potential. The plant was found to exhibit a positive rhizosphere effect of 1.3–1.5. A total of 123 morphologically different bacteria were isolated from the rhizospheric soil and roots of the plant. Medium composition was found to have significant effect on the composition of isolated bacterial populations. Majority of the rhizospheric soil isolates belonged to α- and γ-Proteobacteria, with Pseudomonas constituting the most dominant species. Endophytic bacterial community, on other hand, consisted almost exclusively of Firmicutes. Majority of the isolates showed PGP activity by producing siderophores and indole acetic acid. Several isolates were found to exhibit very high antioxidant activity in the culture medium. A significant proportion of isolates also demonstrated other ecologically important activities like phosphate solubilization, nitrogen fixation, and production of hydrolytic enzymes including amylase, protease, lipase, chitinase, cellulase, pectinase and phosphatase. Firmicutes were found to be metabolically the most versatile group and performed multiple enzyme activities. This is the first systematic study of culturable bacterial community from the rhizosphere of A. bracteosa, particularly in the Kangra valley region. [Copyright &y& Elsevier]

Abstract: A new series of 8-(substituted-phenyl)xanthines have been synthesized and compounds were evaluated for their affinity for A1 and A2 adenosine receptors (AR) using radioligand binding assays. The effects of varying the positions of 8-phenyl substituents on affinity and selectivity at A1 and A2A adenosine receptors have been studied. Isovanilloid 1,3-dimethyl-8-[4-methoxy-3-(2-morpholin-4-ylethoxy)phenylxanthine (9d) displayed the highest affinity and selectivity towards A2A AR subtypes with K i =100nM over A1 receptors (Ki>100mM). It has been observed that substitution pattern on 8-phenyl group greatly affects the affinity and selectivity at adenosine receptors, with A2A tolerating bulkier substituents than did A1 receptors. [Copyright &y& Elsevier]

The fiber optic communication is the one where the wired and the wireless communication systems are integrated to have high bandwidth, low cost, and high data rate with high user density. The RoF technology brings about high-performance network and the guaranteed quality of service for the increased demand for multimedia services. The RoF faces problems like distortion and chromatic dispersion in the RoF link, reducing the quality of the signal at receiver. To enhance the quality of the signal at the receiver side, several techniques have been reported. Those techniques concentrated on the RoF link and the modulation schemes used in the technology. This article reviews the complete RoF technology, which includes the challenges that limit the RoF network along with its compensation scheme and the RoF in the PON services with security. Along with that, the comparative study on the problems faced by the RoF and its mitigation schemes, such as linearization techniques and compensation for chromatic dispersion, are discussed. The linearization schemes will analyze the different pre-distortion circuits used to linearize the transmitting signal such that the signal received by the mobile unit is free of distortion. When these problems are reduced, the RoF with PON has faced another major problem of insecure transmission. Hence the performance of the existing encryption schemes is compared. [ABSTRACT FROM AUTHOR]

• Merging of value chain and supply chain into a single transparent blockchain-based solution. • The use of blockchain for e-commerce with the start from product development to customer acquisition. • Lattice-based cryptography usage in blockchain signcryption process. • Introduction of proof-of-accomplishment as an extension of smart contract in heterogeneous stakeholder environment. A distributed and transparent ledger system is considered for various e-commerce products including health medicines, electronics, security appliances, food products and many more to ensure technological and e-commerce sustainability. This solution, named as 'PRODCHAIN', is a generic blockchain framework with lattice-based cryptographic processes for reducing the complexity for tracing the e-commerce products. Moreover, we have introduced a rating based consensus process called Proof of Accomplishment (PoA). The solution has been analyzed and experimental studies are performed on Ethereum network. The results are discussed in terms of latency and throughput which prove the efficiency of PRODCHAIN in e-commerce products and services. The presented solution is beneficial for improving the traceability of the products ensuring the social and financial sustainability. This work will help the researchers to gain knowledge about the blockchain implications for supply chain possibilities in future developments for society. [ABSTRACT FROM AUTHOR]

Sericite sample having potash (K 2 O) content ~9% is evaluated as a source of potash. The mineralogical studies revealed the fine grain structure of sericite containing muscovite, orthoclase and phlogopite as the major potash bearing phases. The feed sample directly leached in different lixiviants yielded low potash dissolution values. Planetary ball milling was carried out to liberate the potash values from silicate matrix. Leaching was adopted to assess the liberated K values and within milling time of 10–12 h almost 90% potash was leached out. Based on XRD analysis, orthoclase and phlogopite were found to be the toughest potash – bearing phase in terms of dissociation. Compared to other processes, mechanical activation process adopted in this work is simple, environment-friendly and minimal waste generation without using the chemical additive. Unlabelled Image • Sericite sample is evaluated as potash source. • Planetary ball milling liberated the potash values from silicate matrix. • ~90% potash values recovered within milling time of 10 h. • Process adopted is simple, environment friendly and minimal waste generation. [ABSTRACT FROM AUTHOR]