A Systematic Review and Meta-Analysis Evaluating Antibiotic Prophylaxis in Dental Implants and Extraction Procedures

Background and objectives: The use of antibiotic prophylaxis in extraction and implant dentistry is still controversial, with varying opinions regarding their necessity. The overuse of antibiotics has led to widespread antimicrobial resistance and the emergence of multi drug resistant strains of bacteria. The main aim of this work was to determine whether there is a genuine need for antibiotic prophylaxis in two common dental procedures; dental implants and tooth extractions. Methods: Electronic searches were conducted across databases such as Cochrane Register of Controlled Trials, the UK National Health Service, Centre for reviews, Science Direct, PubMed and the British Dental Journal to identify clinical trials of either dental implants or tooth extractions, whereby the independent variable was systemic prophylactic antibiotics used as part of treatment in order to prevent postoperative complications such as implant failure or infection. Primary outcomes of interest were implant failure, and postoperative infections which include systemic bacteraemia and localised infections. The secondary outcome of interest was adverse events due to antibiotics. The Critical Appraisal Skills Programme tool was used to assess the risk of bias, extract outcomes of interest and to identify studies for inclusion in the meta-analysis. Results: Seven randomised clinical trials (RCTs) were included in the final review comprising n = 1368 patients requiring either tooth extraction(s) or dental implant(s). No statistically significant evidence was found to support the routine use of prophylactic antibiotics in reducing the risk of implant failure (p = 0.09, RR 0.43; 95% CI 0.16⁻1.14) or post-operative complications (p = 0.47, RR: 0.74; 95% CI 0.34⁻1.65) under normal conditions. Approximately 33 patients undergoing dental implant surgery need to receive antibiotics in order to prevent one implant failure from occurring. Conclusions: There is little conclusive evidence to suggest the routine use of antibiotic prophylaxis for third molar extractive surgery in healthy young adults. There was no statistical evidence for adverse events experienced for antibiotics vs. placebo. Based on our analysis, even if financially feasible, clinicians must carefully consider the appropriate use of antibiotics in dental implants and extraction procedures due to the risk of allergic reactions and the development of microbial drug resistance.Published versio

Load Balancing in SDN-Enabled WSNs Toward 6G IoE: Partial Cluster Migration Approach

The vision for the sixth-generation (6G) network involves the integration of communication and sensing capabilities in internet of everything (IoE), towards enabling broader interconnection in the devices of distributed wireless sensor networks (WSN). Moreover, the merging of SDN policies in 6G IoE-based WSNs i.e. SDN-enable WSN improves the network’s reliability and scalability via integration of sensing and communication (ISAC). It consists of multiple controllers to deploy the control services closer to the data plane for a speedy response through control messages. However, controller placement and load balancing are the major challenges in SDN-enabled WSNs due to the dynamic nature of data plane devices. To address the controller placement problem, an optimal number of controllers is identified using the articulation point method. Furthermore, a nature-inspired cheetah optimization algorithm is proposed for the efficient placement of controllers by considering the latency and synchronization overhead. Moreover, a load-sharing based control node migration (LS-CNM) method is proposed to address the challenges of controller load balancing dynamically. The LS-CNM identifies the overloaded controller and corresponding assistant controller with low utilization. Then, a suitable control node is chosen for partial migration in accordance with the load of the assistant controller. Subsequently, LS-CNM ensures dynamic load balancing by considering threshold loads, intelligent assistant controller selection, and real-time monitoring for effective partial load migration. The proposed LS-CNM scheme is executed on the open network operating system (ONOS) controller and the whole network is simulated in ns-3 simulator. The simulation results of the proposed LS-CNM outperform the state of the art in terms of frequency of controller overload, load variation of each controller, round trip time, and average delay

Internal Finishing of Aluminium Tube with Sintered Magnetic Abrasive

There has been a rapid growth in the development of harder and complex shapes to machine metals and alloys during the last few years. Conventional edged tool machining is difficult and uneconomical for such materials and degree of surface finish attainable is poor. In view of the seriousness of this problem, recently new non-conventional fine machining processes like Magnetic Abrasive Polishing, Magnetic Abrasive Flow Machining (MAFM), Magnetic Float Machining (MFM) and Magnetic Abrasive Machining (MAM), Magneto ndashRheological Machining (MRM), Chemo-Mechanical Polishing (CMP) have been developed. Among these processes lsquoMagnetic Abrasive Finishing processes are widely used for obtaining quality finish on metallic (ferrous and non ferrous) as well as non metallic (ceramics) components. MAF process has been recently used in its variant forms such as Magnetic float polishing, Magneto-rheological machining, Electrolytic magnetic polishing but the problem of development of magnetic abrasive powders is still present and efforts are in continuous progress at global to remove this problem.nbspIn the MAF method, a magnetic field is used to generate cutting force to treat the surface of a machined part. The magnetic field helps to form a flexible magnetic abrasives brush for finishing of surface.nbsp Finishing force can be controlled with magnetic field and a low surface temperature is generated during finishing operations. Magnetic abrasives are not easily available. Very few studies have been reported till date on the development of alternative magnetic abrasives. The aim of study is to evaluate the performance of developed sintered magnetic abrasives for internal finishing of aluminium tubes using MAF process. PISF is calculated nbspconsidering different variables like speed (rpm) , quantity of abrasive and gap of magnetic pole and work piece.nbsp Preparation of sintered magnetic abrasive was difficult and time consuming. The best result came at 425 rpm and quantity of abrasive used 6 gm. PISF value obtained in present case was 84 % . nbs

Placement analysis of combined renewable and conventional distributed energy resources within a radial distribution network

System islanding, relay tripping, and reverse power flow-like issues in the distribution network are all caused by randomly placed distributed energy resources. To minimize such problems, distributed energy resource (DER) optimal placement in the radial distribution network (RDN) is essential to reduce power loss and enhance the voltage profile. When placing DERs, consideration of constraints like size, location, number, type, and power factor (PF) should be considered. For optimal placement, renewable and nonrenewable DERs are considered. The effects of different types and PFs of DER placements have been tested on the IEEE 33 bus RDN to satisfy all limitations. Using various intelligent techniques, distributed energy resource units of optimal type, PF, size, quantity, and position were placed in the IEEE 33 bus RDN. These intelligent strategies for minimizing power loss, enhancing the voltage profile, and increasing the convergence rate are based on an adaptive neuro-fuzzy inference system, a genetic algorithm, and enhanced particle swarm optimization.publishedVersio

AI-Based Sustainable and Intelligent Offloading Framework for IIoT in Collaborative Cloud-Fog Environments

The cloud paradigm is one of the most trending areas in today’s era due to its rich profusion of services. However, it fails to serve the latency-sensitive Industrial Internet of Things (IIoT) applications associated with automotives, robotics, oil and gas, smart communications, Industry 5.0, etc. Hence, to strengthen the capabilities of IIoT, fog computing has emerged as a promising solution for latency-aware IIoT tasks. However, the resource-constrained nature of fog nodes puts forth another substantial issue of offloading decisions in resource management. Therefore, we propose an Artificial Intelligence (AI)-enabled intelligent and sustainable framework for an optimized multi-layered integrated cloud fog-based environment where real-time offloading decisions are accomplished as per the demand of IIoT applications and analyzed by a fuzzy based offloading controller. Moreover, an AI based Whale Optimization Algorithm (WOA) has been incorporated into a framework that promises to search for the best possible resources and make accurate decisions to ameliorate various Quality-of-Service (QoS) parameters. The experimental results show an escalation in makespan time up to 37.17%, energy consumption up to 27.32%, and execution cost up to 13.36% in comparison to benchmark offloading and allocation schemes

Assessment on performance and variability in different sweet orange (Citrus sinensis Obseck) cultivars under Punjab conditions

Based on morphological characterization, the performance of eighteen sweet orange, (Citrus sinensis Obseck) cultivars were evaluated. On the basis of two year data, the maximum mean fruit weight (316.25 gm) was recorded in Moro, while the maximum mean fruit diameter and mean fruit length was recorded in Mosambi and Olinda Valencia (87.32 mm and 81.33 mm, respectively). Albedo thickness was recorded maximum in Ruby Nucellar (3.42 mm). Highest total soluble solids was recorded in cultivar Moro (11.450 brix), while the titratable acidity was recorded maximum in Valencia Calizonida (1.21 %). Fruit axis diameter and Fruit rind thickness were recorded maximum in Rhode Red Valencia and Vernia (15.12 mm and 8.11 mm, respectively). In the variability studies, the maximum genotypic coefficient of variance (GCV) and phenotypic coefficient of variance (PCV) was recorded maximum for titratable acidity (27.88 and 27.94, respectively) followed by albedo thickness (23.77 and 23.78, respectively) and fruit weight (21.52 and 21.67, respectively). Genetic advance per cent of mean was recorded for titratable acidity (57.31%) followed by albedo thickness (48.96 %) and fruit weight (44.03 %) suggesting that further selection will be effective for improvement in these traits