Preliminary structure-activity relationship studies on some novel s-substituted aliphatic analogues of 5-{1-[(4- chlorophenyl) sulfonyl]-3-piperidinyl}-1, 3, 4-oxadiazol-2-yl sulfide

Purpose: To study the structure-activity relationships of synthetic multifunctional sulfides through evaluation of lipoxygenase and anti-bacterial activities.Methods: S-substituted derivatives of the parent compound 5-(1-(4- chlorophenylsulfonyl) piperidin-3- yl)-1, 3, 4-oxadiazole-2-thiol were synthesized through reaction with different saturated and unsaturated alkyl halides in DMF medium, with NaH catalyst. Spectral characterization of each derivative was carried out with respect to IR, 1H - NMR, 13C - NMR and EI - MS. The lipoxygenase inhibitory and antibacterial activities of the derivatives were determined using standard procedures.Results: Compound 5e exhibited higher lipoxygenase inhibitory potential than the standard (Baicalein®), with % inhibition of 94.71 ± 0.45 and IC50 of 20.72 ± 0.34 μmoles/L. Compound 5b showed significant antibacterial potential against all the bacterial strains with % inhibition ranging from 62.04 ± 2.78, 69.49 ± 0.41, 63.38 ± 1.97 and 59.70 ± 3.70 to 78.32 ± 0.41, while MIC ranged from 8.18 ± 2.00, 10.60 ± 1.83, 10.84 ± 3.00, 9.81 ± 1.86 and 11.73 ± 5.00 μmoles/L for S. typhi, E. coli, P. aeruginosa, B. subtilis and S. aureus, respectively. Compounds 5d, 5e and 5g showed good antibacterial activity against S. typhi and B. subtilis bacterial strains.Conclusion: The results suggest that compound 5e bearing n-pentyl group is a potent lipoxygenase inhibitor, while compound 5b with n-propyl substitution is a strong antibacterial agent. In addition, compounds 5d, 5e and 5g bearing n-butyl, n-pentyl and n-octyl groups, respectively, are good antibacterial agents against S. typhi and B. subtilis.Keywords: Sulfides, Antibacterial activity, Lipoxygenase activity, Spectral analysi

A transfer learning based approach for brain tumor classification

In order to improve patient outcomes, brain tumors—which are notorious for their catastrophic effects and short life expectancy, particularly in higher grades—need to be diagnosed accurately and treated with care. Patient survival chances may be hampered by incorrect medical procedures brought on by a brain tumor misdiagnosis. CNNs and computer-aided tumor detection systems have demonstrated promise in revolutionizing brain tumor diagnostics through the application of ML techniques. One issue in the field of brain tumor detection and classification is the dearth of non-invasive indication support systems, which is compounded by data scarcity. Conventional neural networks may cause problems such as overfitting and gradient vanishing when they use uniform filters in different visual settings. Moreover, these methods incur time and computational complexity as they train the model from scratch and extract the pertinent characteristics. This paper presents an InceptionV4 neural network architecture-based Transfer Learning-based methodology to address the shortcomings in brain tumor classification methods. The goal is to deliver precise diagnostic assistance while minimizing calculation time and improving accuracy. The model makes use of a dataset that contains 7022 MRI images that were obtained from figshare, the SARTAJ dataset, and Br35H, among other sites. The suggested InceptionV4 architecture improves its ability to categorize brain tumors into three groups and normal brain images by utilizing transfer learning approaches. The suggested InceptionV4 model achieves an accuracy rate of 98.7% in brain tumor classification, indicating the model’s remarkable performance. This suggests a noteworthy progression in the precision of diagnosis and computational effectiveness to support practitioners making decisions

Augmenting the Robustness and Efficiency of Violence Detection Systems for Surveillance and Non-Surveillance Scenarios

Violence detection holds immense significance in ensuring public safety, security, and law enforcement in various domains. With the increasing availability of video data from surveillance cameras and social media platforms, the need for accurate and efficient violence detection algorithms has become paramount. Automated violence detection systems can aid law enforcement agencies in identifying and responding to violent incidents promptly, thereby preventing potential threats and ensuring public protection. This research focuses on violence detection in large video databases, proposing two keyframe-based models named DeepkeyFrm and AreaDiffKey. The keyframes selection process is critical in violence detection systems, as it reduces computational complexity and enhances accuracy. EvoKeyNet and KFCRNet are the proposed classification models that leverage feature extraction from optimal keyframes. EvoKeyNet utilizes an evolutionary algorithm to select optimal feature attributes, while KFCRNet employs an ensemble of LSTM, Bi-LSTM, and GRU models with a voting scheme. Our key contributions include the development of efficient keyframes selection methods and classification models, addressing the challenge of violence detection in dynamic surveillance scenarios. The proposed models outperform existing methods in terms of accuracy and computational efficiency, with accuracy results as follows: 98.98% (Hockey Fight), 99.29% (Violent Flow), 99% (RLVS), 91% (UCF-Crime), and 91% (ShanghaiTech). The ANOVA and Tukey tests were performed to validate the statistical significance of the differences among all models. The proposed approaches, supported by the statistical tests, pave the way for more effective violence detection systems, holding immense promise for a safer and secure future. As violence detection technology continues to evolve, our research stands as a crucial stepping stone towards achieving improved public safety and security in the face of dynamic challenges

A lightweight and robust authentication scheme for the healthcare system using public cloud server

Cloud computing is vital in various applications, such as healthcare, transportation, governance, and mobile computing. When using a public cloud server, it is mandatory to be secured from all known threats because a minor attacker’s disturbance severely threatens the whole system. A public cloud server is posed with numerous threats; an adversary can easily enter the server to access sensitive information, especially for the healthcare industry, which offers services to patients, researchers, labs, and hospitals in a flexible way with minimal operational costs. It is challenging to make it a reliable system and ensure the privacy and security of a cloud-enabled healthcare system. In this regard, numerous security mechanisms have been proposed in past decades. These protocols either suffer from replay attacks, are completed in three to four round trips or have maximum computation, which means the security doesn’t balance with performance. Thus, this work uses a fuzzy extractor method to propose a robust security method for a cloud-enabled healthcare system based on Elliptic Curve Cryptography (ECC). The proposed scheme’s security analysis has been examined formally with BAN logic, ROM and ProVerif and informally using pragmatic illustration and different attacks’ discussions. The proposed security mechanism is analyzed in terms of communication and computation costs. Upon comparing the proposed protocol with prior work, it has been demonstrated that our scheme is 33.91% better in communication costs and 35.39% superior to its competitors in computation costs

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication

Reliable Path Selection Packet Forwarding Routing Protocol for Vehicular Adhoc Networks

Vehicular Adhoc Networks (VANETs) have earned a gigantic consideration in the recent era. Wide deployment of VANETs for enhancing traffic safety, traffic management, and assisting drivers through elegant transportation system is facing several research challenges that need to be addressed. One of the crucial issues comprise of the design of scalable routing algorithms that are robust to rapid topology changes and frequent link disconnections caused by high mobility of vehicles. The objective of this research is to develop an optimal and reliable multi-hop routing approach for accomplishing effective vehicular communication in VANETs. First of all, a detailed technical analysis, comparison, and drawbacks of the existing state of the art routing protocols are given. Then, a novel routing scheme called a Reliable Path Selection Packet Forwarding Routing Protocol (RPSPF) is proposed. The novelty of the proposed protocol comes from the fact that firstly it establishes an optimal route for vehicles to send packets towards their respective destinations by considering connectivity and shortest optimal distance based on multiple intersections. Secondly, it uses a novel reliable packet forwarding technique in-between intersections that avoids packet loss while forwarding packet due to occurrence of sudden link ruptures. The performance of the protocol is assessed through GloMoSim and VanetMobiSim simulators. According to the simulation analysis, RPSPF protocol exhibits higher packet delivery ratio by 40%, 30%, 25% and 18%. It also experiences much lower end to end delay by 50%, 40%, 25% and 20% as compared to the state of the art routing protocols like Greedy Perimeter Stateless Routing (GPSR), Directional Greedy Source Routing (DGSR), Enhanced Greedy Traffic Aware Routing Directional (E-GyTARD), and Traffic Flow Oriented Routing (TFOR) respectively. It also experiences very lower routing overhead as compared to aforementioned protocols. The proposed routing protocol has significantly enhanced network performance by incorporating the routing challenges in effective manners. The scheme is envisaged to function well for various kinds of vehicular communication applications by assuring user connectivity. These applications consist of road safety services such as coordinated communication of two vehicles, managing flows of traffic, triggering driving related alerts such as traffic congestion alerts, road situation alerts, and accident warnings. Other applications include finding locations of petrol stations and restaurants, accessing internet, downloading music, and playing games

A review of vehicle to vehicle communication protocols for VANETs in the urban environment

Vehicular Ad-hoc Networks (VANETs) have been gaining significant attention from the research community due to their increasing importance for building an intelligent transportation system. The characteristics of VANETs, such as high mobility, network partitioning, intermittent connectivity and obstacles in city environments, make routing a challenging task. Due to these characteristics of VANETs, the performance of a routing protocol is degraded. The position-based routing is considered to be the most significant approach in VANETs. In this paper, we present a brief review of most significant position based unicast routing protocols designed for vehicle to vehicle communications in the urban environment. We provide them with their working features for exchanging information between vehicular nodes. We describe their pros and cons. This study also provides a comparison of the vehicle to vehicle communication based routing protocols. The comparative study is based on some significant factors such as mobility, traffic density, forwarding techniques and method of junction selection mechanism, and strategy used to handle a local optimum situation. It also provides the simulation based study of existing dynamic junction selection routing protocols and a static junction selection routing protocol. It provides a profound insight into the routing techniques suggested in this area and the most valuable solutions to advance VANETs. More importantly, it can be used as a source of references to other researchers in finding literature that is relevant to routing in VANETs. © 2018 by the author

A Review of Vehicle to Vehicle Communication Protocols for VANETs in the Urban Environment

Vehicular Ad-hoc Networks (VANETs) have been gaining significant attention from the research community due to their increasing importance for building an intelligent transportation system. The characteristics of VANETs, such as high mobility, network partitioning, intermittent connectivity and obstacles in city environments, make routing a challenging task. Due to these characteristics of VANETs, the performance of a routing protocol is degraded. The position-based routing is considered to be the most significant approach in VANETs. In this paper, we present a brief review of most significant position based unicast routing protocols designed for vehicle to vehicle communications in the urban environment. We provide them with their working features for exchanging information between vehicular nodes. We describe their pros and cons. This study also provides a comparison of the vehicle to vehicle communication based routing protocols. The comparative study is based on some significant factors such as mobility, traffic density, forwarding techniques and method of junction selection mechanism, and strategy used to handle a local optimum situation. It also provides the simulation based study of existing dynamic junction selection routing protocols and a static junction selection routing protocol. It provides a profound insight into the routing techniques suggested in this area and the most valuable solutions to advance VANETs. More importantly, it can be used as a source of references to other researchers in finding literature that is relevant to routing in VANETs