A Federated Consensus for Proof of Authority in IoT-Blockchain Applications

The growing adoption of Internet of Things (IoT) devices and the need for secure and scalable blockchain applications pose significant challenges in the realm of consensus protocols. This paper proposes a novel consensus mechanism called Federated Consensus for Proof of Authority (Fed-PoA), which combines the advantages of Proof of Authority (PoA) and federated learning to achieve secure and scalable IoT-Blockchain applications. The Fed-PoA ensures efficient data sharing, privacy preservation, and decentralized operation. Performance evaluation of this model in a simulated environment demonstrates superior convergence and memory usage compared to a representative work in this context

Synthesis of Newly Formulated Aluminium Composite through Powder Metallurgy using Waste Bone Material

The increasing concern for sustainable materials and waste management has led to innovative approaches in material science. This study explores the potential benefit of aggregate waste in the production of aluminum composites practicing powder metallurgy techniques. The aim is to investigate the feasibility of incorporating bone material into aluminium matrices to enhance the composite’s mechanical properties. The research involves several key steps. Firstly, waste bone material is collected and processed to obtain a fine powder suitable for powder metallurgy. Various techniques such as grinding, milling, or pulverization are employed to achieve the desired particle size distribution. Next, the bone powder is mixed with aluminium powder in predetermined ratios to create composite blends. The composite blends are then subjected to compaction using powder metallurgy techniques, including cold pressing and sintering. The compaction process aims to consolidate the powders and facilitate the formation of a solid composite structure. The aluminum composites mechanical characteristics are then assessed. The effects of incorporating bone material are assessed using tests on tensile strength, ductility, hardness, and other relevant mechanical properties. Comparative analysis is performed between the composites with bone material and traditional aluminium composites to assess any improvements or changes in performance

Correlation between body weight and postural control in healthy individuals using sway meter

BACKGROUND: Postural control is critical for ensuring a safety activity of daily living. Individuals with poor stability are more prone to fall while doing activities of daily living. A certain level of sway is essentially present due to small perturbation within the body during shifting body weight from one to other foot, breathing, etc. The purpose of this study was to analyze the correlation between body mass and postural control in normal, lean and obese individual. AIMS: to analyze the correlation between body mass and postural control in healthy individuals using sway meter. MATERIALS AND METHODS: This is an observational study done with 75 participants. Both male and female healthy individuals between 18-23 years were included in this study. Individuals with any musculoskeletal injuries, neurological conditions, peripheral artery disease and pregnant women were excluded from the study. BMI of each participant was calculated and assigned into three groups. Group A-lean, group B-normal and group C-obese. Postural control was analyzed for each group by using sway meter; level of postural sway was compared between groups A, B & C. RESULTS: On comparing mean values of groups A, B and C there was a positive association and strong correlation between body mass index and postural control with eye open and eye closed in anterior, posterior and postural sway towards left between the groups at (P ≤ 0.05). However, there was a negative association and weak correlation between BMI and postural control with eye open & eye closed in postural sway towards right between the groups at (P ≥ 0.05). CONCLUSIONS: This study reveals that there is strong correlation between BMI and postural control. Subjects in eyes closed and eyes opened conditions showed sway in anterior, posterior and left directions but there was less sway towards right side direction

Molecular characterization of extended spectrum β -lactamases enterobacteriaceae causing lower urinary tract infection among pediatric population.

The β-lactam antibiotics have traditionally been the main treatment of Enterobacteriaceae infections, nonetheless, the emergence of species producing β- Lactamases has rendered this class of antibiotics largely ineffective. There are no published data on etiology of urinary tract infections (UTI) and antimicrobial resistance profile of uropathogens among children in Qatar. The aim of this study is to determine the phenotypic and genotypic profiles of antimicrobial resistant Enterobacteriaceae among children with UTI in Qatar. Bacteria were isolated from 727 urine positive cultures, collected from children with UTI between February and June 2017 at the Pediatric Emergency Center, Doha, Qatar. Isolated bacteria were tested for antibiotic susceptibility against sixteen clinically relevant antibiotics using phoenix and Double Disc Synergy Test (DDST) for confirmation of extended-spectrum beta-lactamase (ESBL) production. Existence of genes encoding ESBL production were identified using polymerase chain reaction (PCR). Statistical analysis was done using non-parametric Kappa statistics, Pearson chi-square test and Jacquard's coefficient. 201 (31.7%) of samples were confirmed as Extended Spectrum β -Lactamases (ESBL) Producing Enterobacteriaceae. The most dominant pathogen was 166 (83%) followed by 22 (11%). Resistance was mostly encoded by CTX-M (59%) genes, primarily CTX-MG1 (89.2%) followed by CTX-MG9 (7.7%). 37% of isolated bacteria were harboring multiple genes (2 genes or more). isolates were categorized into 11 clusters, while were grouped into five clonal clusters according to the presence and absence of seven genes namely TEM, SHV, CTX-MG1, CTX-MG2, CTX-MG8 CTX-MG9 CTX-MG25. Our data indicates an escalated problem of ESBL in pediatrics with UTI, which mandates implementation of regulatory programs to reduce the spread of ESBL producing Enterobacteriaceae in the community. The use of cephalosporins, aminoglycosides (gentamicin) and trimethoprim/sulfamethoxazole is compromised in Qatar among pediatric population with UTI, leaving carbapenems and amikacin as the therapeutic option for severe infections caused by ESBL producers

Leveraging technology-driven strategies to untangle omics big data: circumventing roadblocks in clinical facets of oral cancer

Oral cancer is one of the 19most rapidly progressing cancers associated with significant mortality, owing to its extreme degree of invasiveness and aggressive inclination. The early occurrences of this cancer can be clinically deceiving leading to a poor overall survival rate. The primary concerns from a clinical perspective include delayed diagnosis, rapid disease progression, resistance to various chemotherapeutic regimens, and aggressive metastasis, which collectively pose a substantial threat to prognosis. Conventional clinical practices observed since antiquity no longer offer the best possible options to circumvent these roadblocks. The world of current cancer research has been revolutionized with the advent of state-of-the-art technology-driven strategies that offer a ray of hope in confronting said challenges by highlighting the crucial underlying molecular mechanisms and drivers. In recent years, bioinformatics and Machine Learning (ML) techniques have enhanced the possibility of early detection, evaluation of prognosis, and individualization of therapy. This review elaborates on the application of the aforesaid techniques in unraveling potential hints from omics big data to address the complexities existing in various clinical facets of oral cancer. The first section demonstrates the utilization of omics data and ML to disentangle the impediments related to diagnosis. This includes the application of technology-based strategies to optimize early detection, classification, and staging via uncovering biomarkers and molecular signatures. Furthermore, breakthrough concepts such as salivaomics-driven non-invasive biomarker discovery and omics-complemented surgical interventions are articulated in detail. In the following part, the identification of novel disease-specific targets alongside potential therapeutic agents to confront oral cancer via omics-based methodologies is presented. Additionally, a special emphasis is placed on drug resistance, precision medicine, and drug repurposing. In the final section, we discuss the research approaches oriented toward unveiling the prognostic biomarkers and constructing prediction models to capture the metastatic potential of the tumors. Overall, we intend to provide a bird’s eye view of the various omics, bioinformatics, and ML approaches currently being used in oral cancer research through relevant case studies

Identification of plasmid-mediated quinolone resistance genes qnrA1, qnrB1 and aac(6')-1b-cr in a multiple drug-resistant isolate of Klebsiella pneumoniae from Chennai

Purpose: Resistance to fluoroquinolones, a commonly prescribed antimicrobial for Gram-negative and Gram-positive microorganisms, is of importance in therapy. The purpose of this study was to screen for the presence of Plasmid-Mediated Quinolone Resistance (PMQR) determinants in clinical isolates of Klebsiella pneumoniae . Materials and Methods: Extended-Spectrum Beta-Lactamase (ESBL) isolates of K. pneumoniae collected during October 2009 were screened by the antimicrobial susceptibility test. The plasmids from these isolates were analysed by specific Polymerase chain Reaction (PCR) for qnrA, qnrB and aac(6′)-1b. The amplified products were sequenced to confirm the allele. Results: Our analysis showed that 61% out of the 23 ESBL K. pneumoniae isolates were resistant to ciprofloxacin and 56% to levofloxacin. The PMQR was demonstrated by transforming the plasmids from two isolates P12 and P13 into E. coli JM109. The PMQR gene qnrA was found in 16 isolates and qnrB in 11 isolates. The plasmid pKNMGR13 which conferred an minimum inhibitory concentration (MIC) of more than 240 ΅g/ml in sensitive E. coli was found to harbour the qnrA1 and qnrB1 allele. Furthermore, the gene aac(6′)-1b-cr encoding a variant aminoglycoside 6′-N Acetyl transferase which confers resistance to fluoroquinolones was found in the same plasmid. Conclusions: Our report shows the prevalence of PMQR mediated by qnrA and qnrB in multidrug-resistant K. pneumoniae isolates from Chennai. A multidrug-resistant plasmid conferring high resistance to ciprofloxacin was found to harbour another PMQR gene, aac(6′)-1b-cr mutant gene. This is the first report screening for PMQR in K. pneumoniae isolates from India

The design and implementation of folded adaptive lattice filter structures in FPGA for ECG signals

An adaptive filter is the utmost essential filter castoff in statistical signal dealing. The fine-tuning of the filter factor in relation to the response signal is the adaptive filter's key feature due to fewer calculations, Least Mean Square (LMS) adaptive filters are widely used to remove noise from Electrocardiograms (ECG). The adaptive filters are realized as signal processing algorithms in Digital Signal Processors (DSPs) or in VLSI Signal Processors (VSPs). The technique provides a way to create a folded adaptive lattice LMS filter, which requires less hardware than an adaptive lattice filter. Folding is an algorithm that uses a time scheduling technique that combines arithmetic operations into one operation which reduces Register and silicon chip areas. The design and implementation of a folded lattice adaptive filter remove Power Line Interference (PLI) noise from ECG signals. The MATLAB Xilinx System Generator tool is used to design the Adaptive Lattice LMS Filter and Folded Adaptive Lattice LMS Filter with Folding Order K = 2 and K = 4 and realized in the Virtex 5 FPGA KIT. The results of the folded architecture show that the area is reduced for K = 2 and K = 4 by 82.60% and 91.05%, respectively compared with a normal adaptive lattice filter