Development of a Real-Time, Secure and Reliable Automobile Service Center

Lack of ambition will prevent you from moving forward in life, as much like a car without petrol. The majority of people on earth isobsessed with automobiles. We have provided you with a web application for Real time automobile service that functions effectively on all the platforms. Occasionally, automobiles and other motorized vehicles require maintenance. They must be maintained clean, just as humans practice proper hygiene. They run on dirty streets and in polluted environment. They are subjected to loads that harm them since they travel on uneven roads with obstacles. Therefore, it is necessary to maintain automobiles and other motorized vehicles on a regular basis. This project aims to keep service centers running smoothly in terms of things like vehicle maintenance, customer quotation generation, vehicle servicing, spare parts sales, customer information, and customer feedback. The system is efficient at generating reports that will make service center routine maintenance easy.Additionally, it can handle car repairs, insurance, payments, delivery, etc. This project will be very helpful to customers who want to fix or repair their cars. As a result, we develop a software that is both compatible and unique

Overcoming Multidrug Resistance of Antibiotics via Nanodelivery Systems

Antibiotic resistance has become a threat to microbial therapies nowadays. The conventional approaches possess several limitations to combat microbial infections. Therefore, to overcome such complications, novel drug delivery systems have gained pharmaceutical scientists’ interest. Significant findings have validated the effectiveness of novel drug delivery systems such as polymeric nanoparticles, liposomes, metallic nanoparticles, dendrimers, and lipid-based nanoparticles against severe microbial infections and combating antimicrobial resistance. This review article comprises the specific mechanism of antibiotic resistance development in bacteria. In addition, the manuscript incorporated the advanced nanotechnological approaches with their mechanisms, including interaction with the bacterial cell wall, inhibition of biofilm formations, activation of innate and adaptive host immune response, generation of reactive oxygen species, and induction of intracellular effect to fight against antibiotic resistance. A section of this article demonstrated the findings related to the development of delivery systems. Lastly, the role of microfluidics in fighting antimicrobial resistance has been discussed. Overall, this review article is an amalgamation of various strategies to study the role of novel approaches and their mechanism to fight against the resistance developed to the antimicrobial therapies.</jats:p

Mycobacterium tuberculosis DosR Regulon Gene Rv0079 Encodes a Putative, ‘Dormancy Associated Translation Inhibitor (DATIN)’

Mycobacterium tuberculosis is a major human pathogen that has evolved survival mechanisms to persist in an immune-competent host under a dormant condition. The regulation of M. tuberculosis metabolism during latent infection is not clearly known. The dormancy survival regulon (DosR regulon) is chiefly responsible for encoding dormancy related functions of M. tuberculosis. We describe functional characterization of an important gene of DosR regulon, Rv0079, which appears to be involved in the regulation of translation through the interaction of its product with bacterial ribosomal subunits. The protein encoded by Rv0079, possibly, has an inhibitory role with respect to protein synthesis, as revealed by our experiments. We performed computational modelling and docking simulation studies involving the protein encoded by Rv0079 followed by in vitro translation and growth curve analysis experiments, involving recombinant E. coli and Bacille Calmette Guérin (BCG) strains that overexpressed Rv0079. Our observations concerning the interaction of the protein with the ribosomes are supportive of its role in regulation/inhibition of translation. We propose that the protein encoded by locus Rv0079 is a ‘dormancy associated translation inhibitor’ or DATIN

Concurrent Proinflammatory and Apoptotic Activity of a Helicobacter pylori Protein (HP986) Points to Its Role in Chronic Persistence

Helicobacter pylori induces cytokine mediated changes in gastroduodenal pathophysiology, wherein, the activated macrophages at the sub-mucosal space play a central role in mounting innate immune response against the antigens. The bacterium gains niche through persistent inflammation and local immune-suppression causing peptic ulcer disease or chronic gastritis; the latter being a significant risk factor for the development of gastric adenocarcinoma. What favors persistence of H. pylori in the gastric niches is not clearly understood. We report detailed characterization of a functionally unknown gene (HP986), which was detected in patient isolates associated with peptic ulcer and gastric carcinoma. Expression and purification of recombinant HP986 (rHP986) revealed a novel, ∼29 kDa protein in biologically active form which associates with significant levels of humoral immune responses in diseased individuals (p<0.001). Also, it induced significant levels of TNF-α and Interleukin-8 in cultured human macrophages concurrent to the translocation of nuclear transcription factor-κB (NF-κB). Further, the rHP986 induced apoptosis of cultured macrophages through a Fas mediated pathway. Dissection of the underlying signaling mechanism revealed that rHP986 induces both TNFR1 and Fas expression to lead to apoptosis. We further demonstrated interaction of HP986 with TNFR1 through computational and experimental approaches. Independent proinflammatory and apoptotic responses triggered by rHP986 as shown in this study point to its role, possibly as a survival strategy to gain niche through inflammation and to counter the activated macrophages to avoid clearance

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Deep contextual bandits for fast neighbor-aided initial access in mmWave cell-free networks

Abstract Access points (APs) in millimeter-wave (mmWave) user-centric (UC) networks will have sleep mode functionality. Initial access (IA) is a challenging problem in UC networks due to the coherent serving of the users. In this letter, a novel deep contextual bandit (DCB) learning-based instantaneous beam selection method is proposed as a complementary tool to current IA schemes. In the proposed approach, the DCB model at an AP uses beam selection information from the neighboring active APs as the input to solve the beam search problem of the host AP. The proposed fast beam selection scheme enables APs to be in energy-saving modes while maintaining the ability to serve users without any delay when restored. Simulations are carried out with realistic channel models generated using a ray-tracing tool. The results show that the proposed system with the 5G IA scheme can respond to dynamic throughput demands with negligible latency compared to the 5G IA scheme without the proposed scheme

Deep contextual bandits for fast initial access in mmWave based user-centric ultra-dense networks

Abstract Millimeter wave (mmWave) based multiple-input multiple-output (MIMO) capable user-centric (UC) ultra-dense (UD) networks are suggested to facilitate high throughput requirements of future networks. Due to the high blockage susceptibility of mmWave, the connections may drop frequently. Hence efficient and fast beam management in initial access (IA) is essential. Current cellular systems use beam sweeping based IA mechanisms. UC UD concept requires all of its access points (APs) to perform IA. This leads to a shortage of orthogonal radio resources. Nonorthogonal resource allocation causes interference which leads to a higher misdetection probability. In this paper, we propose a novel deep contextual bandit (DCB) based approach to perform fast and efficient IA in mmWave based UC UD networks. The DCB model uses one reference signal from the user to predict the IA beam. The reduced use of reference signals improves beam discovery delay and relaxes the requirement for radio resources. Ray-tracing and stochastic channel model-based simulations show that the suggested system outperforms its beam sweeping counterpart in terms of probability of beam misdetection and beam discovery delay in mmWave based UC UD networks