The Experts below are selected from a list of 116853 Experts worldwide ranked by ideXlab platform
Amitrajeet A. Batabyal - One of the best experts on this subject based on the ideXlab platform.
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A note on common infections and the non-antibiotic treatment option
Stochastic Environmental Research and Risk Assessment, 2007Co-Authors: Amitrajeet A. BatabyalAbstract:Recently, Batabyal and Nijkamp (Environ Econ Policy Stud 7:39–51, 2005 ) have used a theoretical model of antibiotic use to study the relative merits of interventionist (antibiotics) and non-interventionist (no antibiotics) treatment options. A key assumption in their paper is that the default treatment option is the interventionist option. Because there are several instances in which this assumption is invalid, in this paper, we suppose that the default treatment option is the non-interventionist option. Specifically, we first derive the long run average cost of treating a common infection such as acute otitis media (AOM). Next, we show that there is a particular Tolerance Level and that when a physician uses this Tolerance Level to determine when to administer the non-antibiotic medicine, the long run average cost of treating the common infection under study is minimized.
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A Note on Common Infections and the Non-Antibiotic Treatment Option
Stochastic Environmental Research and Risk Assessment, 2007Co-Authors: Amitrajeet A. BatabyalAbstract:Recently, Batabyal and Nijkamp (2005) have used a theoretical model of antibiotic use to study the relative merits of interventionist (antibiotics) and non-interventionist (no antibiotics) treatment options. A key assumption in their paper is that the default treatment option is the interventionist option. Because there are several instances in which this assumption is invalid, in this paper, we suppose that the default treatment option is the non-interventionist option. Specifically, we first derive the long run average cost of treating a common infection such as acute otitis media (AOM). Next, we show that there is a particular Tolerance Level and that when a physician uses this Tolerance Level to determine when to administer the non-antibiotic medicine, the long run average cost of treating the common infection under study is minimized.
Jesus Mercadoblanco - One of the best experts on this subject based on the ideXlab platform.
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linking belowground microbial network changes to different Tolerance Level towards verticillium wilt of olive
Microbiome, 2020Co-Authors: Antonio Jose Fernandezgonzalez, Martina Cardoni, Carmen Gomezlama Cabanas, Antonio Valverdecorredor, Pablo J Villadas, Manuel Fernandezlopez, Jesus MercadoblancoAbstract:Verticillium wilt of olive (VWO) is caused by the soilborne fungal pathogen Verticillium dahliae. One of the best VWO management measures is the use of tolerant/resistant olive cultivars. Knowledge on the olive-associated microbiome and its potential relationship with Tolerance to biotic constraints is almost null. The aims of this work are (1) to describe the structure, functionality, and co-occurrence interactions of the belowground (root endosphere and rhizosphere) microbial communities of two olive cultivars qualified as tolerant (Frantoio) and susceptible (Picual) to VWO, and (2) to assess whether these communities contribute to their differential disease susceptibility Level. Minor differences in alpha and beta diversities of root-associated microbiota were detected between olive cultivars regardless of whether they were inoculated or not with the defoliating pathotype of V. dahliae. Nevertheless, significant differences were found in taxonomic composition of non-inoculated plants’ communities, “Frantoio” showing a higher abundance of beneficial genera in contrast to “Picual” that exhibited major abundance of potential deleterious genera. Upon inoculation with V. dahliae, significant changes at taxonomic Level were found mostly in Picual plants. Relevant topological alterations were observed in microbial communities’ co-occurrence interactions after inoculation, both at structural and functional Level, and in the positive/negative edges ratio. In the root endosphere, Frantoio communities switched to highly connected and low modularized networks, while Picual communities showed a sharply different behavior. In the rhizosphere, V. dahliae only irrupted in the microbial networks of Picual plants. The belowground microbial communities of the two olive cultivars are very similar and pathogen introduction did not provoke significant alterations in their structure and functionality. However, notable differences were found in their networks in response to the inoculation. This phenomenon was more evident in the root endosphere communities. Thus, a correlation between modifications in the microbial networks of this microhabitat and susceptibility/Tolerance to a soilborne pathogen was found. Moreover, V. dahliae irruption in the Picual microbial networks suggests a stronger impact on the belowground microbial communities of this cultivar upon inoculation. Our results suggest that changes in the co-occurrence interactions may explain, at least partially, the differential VWO susceptibility of the tested olive cultivars.
A Jamshidi - One of the best experts on this subject based on the ideXlab platform.
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SU-E-T-586: Optimal Determination of Tolerance Level for Radiation Dose Delivery Verification in An in Vivo Dosimetry System
Medical Physics, 2015Co-Authors: Y Chen, S Souri, G Gill, A Rea, A Kuruvilla, Adam C. Riegel, Y Cao, A JamshidiAbstract:Purpose: To statistically determine the optimal Tolerance Level in the verification of delivery dose compared to the planned dose in an in vivo dosimetry system in radiotherapy. Methods: The LANDAUER MicroSTARii dosimetry system with screened nanoDots (optically stimulated luminescence dosimeters) was used for in vivo dose measurements. Ideally, the measured dose should match with the planned dose and falls within a normal distribution. Any deviation from the normal distribution may be redeemed as a mismatch, therefore a potential sign of the dose misadministration. Randomly mis-positioned nanoDots can yield a continuum background distribution. A percentage difference of the measured dose to its corresponding planned dose (ΔD) can be used to analyze combined data sets for different patients. A model of a Gaussian plus a flat function was used to fit the ΔD distribution. Results: Total 434 nanoDot measurements for breast cancer patients were collected across a period of three months. The fit yields a Gaussian mean of 2.9% and a standard deviation (SD) of 5.3%. The observed shift of the mean from zero is attributed to the machine output bias and calibration of the dosimetry system. A pass interval of −2SD to +2SD was applied and a mismatch background was estimatedmore » to be 4.8%. With such a Tolerance Level, one can expect that 99.99% of patients should pass the verification and at most 0.011% might have a potential dose misadministration that may not be detected after 3 times of repeated measurements. After implementation, a number of new start breast cancer patients were monitored and the measured pass rate is consistent with the model prediction. Conclusion: It is feasible to implement an optimal Tolerance Level in order to maintain a low limit of potential dose misadministration while still to keep a relatively high pass rate in radiotherapy delivery verification.« less
Blaise Conrard - One of the best experts on this subject based on the ideXlab platform.
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Fault Tolerance Level assessment of a wireless communication link in a system of systems concept modeled using bond graph
2015 International Conference on Advances in Biomedical Engineering (ICABME), 2015Co-Authors: Ahmad Koubeissi, Mohammad Ayache, Mahmoud Abbas, Rochdi Merzouki, Blaise ConrardAbstract:The main focus of this paper is on graphical modeling of wireless link of a System of Systems (SoS) for the purpose of Fault Tolerance Level Assessment. Having used hypergraphs previously for modeling the structural organization of SoS, it's now important to introduce another graphical tool for modeling the wireless communication channel (WCL) between component systems of SoS, namely Bond Graph, and to evaluate at the same time, the fault Tolerance Level of each WCL so that we are able to compare various SoS configurations in terms of communication reliability and robustness. We perform an experiment on cooperative behavior of NAO humanoids forming an SoS to exploit model benefits at microscopic Level and at macroscopic Level, by developing a simulator that demonstrates how we can assess the fault Tolerance Level of each WCL in SoS.
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SoSE - Bond graph model-based for fault Tolerance Level assessment of a wireless communication link in a system of systems concept
2015 10th System of Systems Engineering Conference (SoSE), 2015Co-Authors: Ahmad Koubeissi, Mohammad Ayache, Rochdi Merzouki, Blaise ConrardAbstract:The main focus of this paper is on graphical modeling of wireless link of a System of Systems (SoS) for the purpose of Fault Tolerance Level Assessment. Having used hypergraphs previously for modeling the structural organization of SoS, it's now important to introduce another graphical tool for modeling the wireless communication channel (WCL) between component systems of SoS, namely Bond Graph, and to evaluate at the same time, the fault Tolerance Level of each WCL so that we are able to compare various SoS configurations in terms of communication reliability and robustness. We perform an experiment on cooperative behavior of NAO humanoids forming an SoS to exploit model benefits at microscopic Level and at macroscopic Level, by developing a simulator that demonstrates how we can assess the fault Tolerance Level of each WCL in SoS.
Xubin Pan - One of the best experts on this subject based on the ideXlab platform.
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Calculation of sampling size for non-zero Tolerance Level
Global Ecology and Conservation, 2020Co-Authors: Xubin PanAbstract:Abstract The Tolerance Level of 0 and the confidence Level of 0.95 are widely applied in current investigation and sampling strategies for the crime, food, environment, and biodiversity fields. Although some researchers recommend the non-zero Tolerance Level, few relevant sampling plans have been proposed. In this report, I used the binomial distribution as an example to show the estimate of sampling size, considering different detection efficacies, proportion of concerned units, and confidence Level. The results indicate that the required sampling size based on non-zero Tolerance is larger than that based on zero Tolerance when other parameters are the same. High detection efficacy and high proportion of concerned units can decrease the sampling size. Especially, large sampling size can not only increase the confidence Level, but also decrease the proportion of concerned regulated units with effective policy measurement.
