8,238 research outputs found
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
RGIM: An Integrated Approach to Improve QoS in AODV, DSR and DSDV Routing Protocols for FANETS Using the Chain Mobility Model
Flying ad hoc networks (FANETs) are a collection of unmanned aerial vehicles that communicate without any predefined infrastructure. FANET, being one of the most researched topics nowadays, finds its scope in many complex applications like drones used for military applications, border surveillance systems and other systems like civil applications in traffic monitoring and disaster management. Quality of service (QoS) performance parameters for routing e.g. delay, packet delivery ratio, jitter and throughput in FANETs are quite difficult to improve. Mobility models play an important role in evaluating the performance of the routing protocols. In this paper, the integration of two selected mobility models, i.e. random waypoint and Gauss–Markov model, is implemented. As a result, the random Gauss integrated model is proposed for evaluating the performance of AODV (ad hoc on-demand distance vector), DSR (dynamic source routing) and DSDV (destination-Sequenced distance vector) routing protocols. The simulation is done with an NS2 simulator for various scenarios by varying the number of nodes and taking low- and high-node speeds of 50 and 500, respectively. The experimental results show that the proposed model improves the QoS performance parameters of AODV, DSR and DSDV protocol
Knowledge Services for eBusiness
Dynamic value chain activities and complex decisions require the transparent flow of information and seamless knowledge exchange among multiple value chain participants. Advances in semantic web-based technologies offer the means to integrate heterogeneous systems across organizations in a meaningful way by incorporating Ontology, a common, standard and shareable vocabulary used to represent the meaning of system entities; Knowledge Representation, with structured collections of information and sets of inference rules that can be used to conduct automated reasoning; and Intelligent Agents that collect content from diverse sources and exchange semantically enriched information. This research applies fundamental work done in semantic web technologies including ontologies, knowledge representation, multi-agent systems and the webservices architecture to develop a system architecture that enables semantically enriched collaborative eBusiness process. We describe the feasibility of the knowledge services architecture to enable the transparent exchange of information and knowledge among agents that manage eBusiness processes to enhance online processes in an eMarketplace
Measuring the maturity of Indian small and medium enterprises for unofficial readiness for capability maturity model integration-based software process improvement
Establishing the maturity levels of ‐ Small and Medium Enterprises (SMEs) without Capability Maturity Model Integration (CMMI) certification has always been regarded as an extremely challenging task. Software process improvement (SPI) has targeted to monitor and improve software processes, thereby improving the software business. Although there is scientific interest in SPI, little attention has been specifically given to the exploration of maturity levels for non‐CMMI SMEs. The goal is to explore the effect of time on process maturity and maturity levels achieved informally or unofficially by SMEs that are not otherwise CMMI certified. To find out the maturity levels achieved informally, a CMMI‐DEV v1.3 based survey questionnaire is administered to Indian software SMEs. Time of establishment of SMEs and follow‐up of CMMI‐based processes and practices unofficially are used as two important parameters to decide upon process maturity and achievement of specific CMMI level informally. This paper has been successful in ascertaining the effect of time of establishment of SMEs and follow‐up of CMMI‐based processes on process maturity using proposed RuleML that advocates adoption of more than 70% of CMMI‐DEV v1.3 process area‐specific practices for an SME to be unofficially ready for CMMI‐based SPI initiatives. The findings manifest multidimensional aspects of unofficial readiness of SMEs for CMMI‐based SPI that can be used by relevant authorities to select SMEs for funding for SPI initiatives. Finally, the proposed work has been validated statistically using t‐test for CMMI Level II and Level III
Digital device-based active learning approach using virtual community classroom during the COVID-19 pandemic
IoTPulse: machine learning-based enterprise health information system to predict alcohol addiction in Punjab (India) using IoT and fog computing
Characteristics of alpha projectile fragments emission in interaction of nuclei with emulsion
The properties of the relativistic alpha fragments produced in interactions
of 84^Kr at around 1 A GeV in nuclear emulsion are investigated. The
experimental results are compared with the similar results obtained from
various projectiles with emulsion interactions at different energies. The
total, partial nuclear cross-sections and production rates of alpha
fragmentation channels in relativistic nucleus-nucleus collisions and their
dependence on the mass number and initial energy of the incident projectile
nucleus are investigated. The yields of multiple alpha fragments emitted from
the interactions of projectile nuclei with the nuclei of light, medium and
heavy target groups of emulsion-detector are discussed and they indicate that
the projectile-breakup mechanism seems to be free from the target mass number.
It is found that the multiplicity distributions of alpha fragments are well
described by the Koba-Nielsen-Olesen (KNO) scaling presentation. The mean
multiplicities of the freshly produced newly created charged secondary
particles, normally known as shower and secondary particles associated with
target in the events where the emission of alpha fragments were accompanied by
heavy projectile fragments having Z value larger than 4 seem to be constant as
the alpha fragments multiplicity increases, and exhibit a behavior independent
of the alpha fragments multiplicity.Comment: 33 pages, 8 figures and 3 tables (in press
A drone-based networked system and methods for combating coronavirus disease (COVID-19) pandemic.
Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. It is similar to influenza viruses and raises concerns through alarming levels of spread and severity resulting in an ongoing pandemic worldwide. Within eight months (by August 2020), it infected 24.0 million persons worldwide and over 824 thousand have died. Drones or Unmanned Aerial Vehicles (UAVs) are very helpful in handling the COVID-19 pandemic. This work investigates the drone-based systems, COVID-19 pandemic situations, and proposes an architecture for handling pandemic situations in different scenarios using real-time and simulation-based scenarios. The proposed architecture uses wearable sensors to record the observations in Body Area Networks (BANs) in a push-pull data fetching mechanism. The proposed architecture is found to be useful in remote and highly congested pandemic areas where either the wireless or Internet connectivity is a major issue or chances of COVID-19 spreading are high. It collects and stores the substantial amount of data in a stipulated period and helps to take appropriate action as and when required. In real-time drone-based healthcare system implementation for COVID-19 operations, it is observed that a large area can be covered for sanitization, thermal image collection, and patient identification within a short period (2 KMs within 10 min approx.) through aerial route. In the simulation, the same statistics are observed with an addition of collision-resistant strategies working successfully for indoor and outdoor healthcare operations. Further, open challenges are identified and promising research directions are highlighted
An innovative two-stage data compression scheme using adaptive block merging technique
Test data has increased enormously owing to the rising on-chip complexity of integrated circuits. It further increases the test data transportation time and tester memory. The non-correlated test bits increase the issue of the test power. This paper presents a two-stage block merging based test data minimization scheme which reduces the test bits, test time and test power. A test data is partitioned into blocks of fixed sizes which are compressed using two-stage encoding technique. In stage one, successive blocks are merged to retain a representative block. In stage two, the retained pattern block is further encoding based on the existence of ten different subcases between the sub-block formed by splitting the retained pattern block into two halves. Non-compatible blocks are also split into two sub-blocks and tried for encoded using lesser bits. Decompression architecture to retrieve the original test data is presented. Simulation results obtained corresponding to different ISCAS′89 benchmarks circuits reflect its effectiveness in achieving better compression
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