The Experts below are selected from a list of 3303 Experts worldwide ranked by ideXlab platform
Yaron Ilan - One of the best experts on this subject based on the ideXlab platform.
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Overcoming Randomness does not rule out the importance of Inherent Randomness for functionality.
Journal of biosciences, 2019Co-Authors: Yaron IlanAbstract:Randomness is intrinsic to many natural processes. It is also clear that, under certain conditions, disorders are not associated with functionality. Several examples in which overcoming, suppressing, or combining both Randomness and non-Randomness is required are drawn from various fields. However, the need to suppress or overcome Randomness does not negate its importance under certain conditions and its significance in valid processes and organ functions. Randomness should be acknowledged rather than ignored or suppressed; it can be viewed, at worst, as a disturbing disorder that may be treated to produce order, or, at best, as a ‘beneficial disorder’ that can be considered as a higher level of functionality.
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Personalized Inherent Randomness of the immune system is manifested by an individualized response to immune triggers and immunomodulatory therapies: a novel platform for designing personalized immunotherapies
Immunologic Research, 2019Co-Authors: Dimitri Kanovitch, Yaron IlanAbstract:The considerable variability of responses amongst subjects to disease triggers and immunotherapies is a major obstacle to designing better immune-based therapies. Therefore, development of patient-tailored precision medicine that improves the efficacy of immunomodulatory drugs is necessary. The individualized response to disease triggers and immunomodulatory therapies was studied using the concanavalin A (ConA) immune-mediated hepatitis model and the oral administration of anti CD3 or β-glucosylceramide (GC). Mice were treated with anti-CD3 antibodies or GC followed by an injection of ConA. The effects of these treatments on liver damage and the immune profile were then analyzed. An individualized response to ConA and orally administered immunomodulatory agents was observed in eight consecutive experiments. While alleviation of the immune-mediated liver injury, as measured by serum levels of liver enzymes, was seen, and high intra-group and inter-experimental variabilities were detected. A similar individualized response was observed for the effect on serum levels of IFN-γ, TNF-α, and IL-10 and on CD4+CD25+, CD8+CD25+, and CD3+NK1.1+ lymphocytes. A personalized form of Inherent Randomness in an isolated system was documented, which may underlie the variability in responses to immune triggers and immunomodulatory therapies. The data support the use of personalized Randomness-based platforms for improving the response to chronic therapies.
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Randomness in microtubule dynamics an error that requires correction or an Inherent plasticity required for normal cellular function
Cell Biology International, 2019Co-Authors: Yaron IlanAbstract:Microtubules (MTs) play roles in regulating the mechanical structure and dynamics of cells. While MTs appear to be highly ordered structures, recent data suggest some Randomness in their structure and dynamics. Part of this Inherent Randomness is attributed to errors and correction mechanisms are being investigated to overcome these 'mistakes.' However, this Randomness may also be part of the normal intracellular function of MTs. It is possible that random events in MT structure and dynamics may contribute to their normal function and may even be part of an improved efficacy mechanism. An alternative view, wherein MT and kinetochore errors are part of required cell plasticity, is also discussed. These data may further support the concept of Randomness in biological pathways as part of self-organization or accurate and enhanced function.
Abel Brodeur - One of the best experts on this subject based on the ideXlab platform.
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Terrorism and Voting Behavior: Evidence from the United States:
Research & Politics, 2021Co-Authors: Leonardo Baccini, Abel Brodeur, Sean Nossek, Eran ShorAbstract:This article examines the impact of terrorism on voting behavior in the United States. We rely on an exhaustive list of terror attacks over the period 1970–2016 and exploit the Inherent Randomness ...
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The Effect of Terrorism on Employment and Consumer Sentiment: Evidence from Successful and Failed Terror Attacks
American Economic Journal: Applied Economics, 2018Co-Authors: Abel BrodeurAbstract:This paper examines the economic consequences of terror attacks by exploiting the Inherent Randomness in the success or failure of terror attacks. The findings suggest that successful attacks, in comparison to failed attacks, reduce the number of jobs and total earnings in targeted counties by approximately 2 percent in the years following the attack. Analyzing the channels, I find that successful attacks affect, in particular, specific industries such as housing. Last, I show that successful attacks receive more media coverage and increase levels of consumer pessimism in terms of business conditions and buying conditions.
Qinghua Zhou - One of the best experts on this subject based on the ideXlab platform.
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Ultimate Boundedness of Stochastic Hopfield Neural Networks
Journal of Convergence Information Technology, 2011Co-Authors: Li Wan, Qinghua ZhouAbstract:Abstract Hopfield neural networks with nonlinear and delay-type template elements have been extensively studied in past years and found many applications for solving a number of problems in various scientific disciplines. Although ultimate boundedness of several classes of neural networks with constant delays was studied by some researchers, the Inherent Randomness associated with signal transmission was not taken account into these networks. So far there are not any results on ultimate boundedness of stochastic neural networks with delays. This paper investigates ultimate boundedness of stochastic Hopfield neural networks with delays and establishs some sufficient criteria on stochasitc ultimate boundedness by employing Lyapunov method. One example is given to demonstrate our criteria.
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Ultimate Boundedness of Stochastic Neural Networks with Delays
Advanced Materials Research, 2011Co-Authors: Li Wan, Qinghua ZhouAbstract:Although ultimate boundedness of several classes of neural networks with constant delays was studied by some researchers, the Inherent Randomness associated with signal transmission was not taken account into these networks. At present, few authors study ultimate boundedness of stochastic neural networks and no related papers are reported. In this paper, by using Lyapunov functional and linear matrix inequality, some sufficient conditions ensuring the ultimate boundedness of stochastic neural networks with time-varying delays are established. Our criteria are easily tested by Matlab LMI Toolbox. One example is given to demonstrate our criteria.
Stephen D Brown - One of the best experts on this subject based on the ideXlab platform.
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difficulty of predicting interconnect delay in a timing driven fpga cad flow
System-Level Interconnect Prediction, 2006Co-Authors: Valavan Manohararajah, Gordon R. Chiu, Deshanand Singh, Stephen D BrownAbstract:This paper studies the difficulty of predicting interconnect delay in an industrial setting. Fifty industrial circuits, Altera's Quartus II CAD software, and Altera's Stratix and Stratix II FPGA architectures were used in the study. We show that there is a large amount of Inherent Randomness in a state-of-the-art FPGA placement algorithm. Thus, it is impossible to predict interconnect delay with a high degree of accuracy. Futhermore, we show that a simple timing model can be used to predict some aspects of interconnect timing with just as much accuracy as predictions obtained by running the placement tool itself. Finally, we examine the benefits of using the simple timing model in a timing driven physical synthesis flow, and attempt to establish an upper bound on these possible gains, given the difficulty of interconnect delay prediction.
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SLIP - Difficulty of predicting interconnect delay in a timing driven FPGA CAD flow
Proceedings of the international workshop on System-level interconnect prediction - SLIP'06, 2006Co-Authors: Valavan Manohararajah, Gordon R. Chiu, Deshanand Singh, Stephen D BrownAbstract:This paper studies the difficulty of predicting interconnect delay in an industrial setting. Fifty industrial circuits, Altera's Quartus II CAD software, and Altera's Stratix and Stratix II FPGA architectures were used in the study. We show that there is a large amount of Inherent Randomness in a state-of-the-art FPGA placement algorithm. Thus, it is impossible to predict interconnect delay with a high degree of accuracy. Futhermore, we show that a simple timing model can be used to predict some aspects of interconnect timing with just as much accuracy as predictions obtained by running the placement tool itself. Finally, we examine the benefits of using the simple timing model in a timing driven physical synthesis flow, and attempt to establish an upper bound on these possible gains, given the difficulty of interconnect delay prediction.
Stefan Slesazeck - One of the best experts on this subject based on the ideXlab platform.
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Random Number Generation Based on Ferroelectric Switching
IEEE Electron Device Letters, 2018Co-Authors: Halid Mulaosmanovic, Thomas Mikolajick, Stefan SlesazeckAbstract:Hafnium oxide-based ferroelectric field-effect transistors (FeFETs) have a great potential for fast nonvolatile memory due to their high performance, fully CMOS compatible integration, and low-power operation. The aggressive scaling of these devices has revealed novel features, such as the multilevel storage capability and abrupt switching, which, however, appears to be a stochastic process. In this letter, we propose a path for true random number generation based on the statistical switching in a single FeFET device. It relies on an Inherent Randomness of the polarization reversal of ferroelectric domains in the gate stack. The bit sequence is generated by repeatedly programming an FeFET at a calibrated voltage and pulse width, and features random and equiprobable “ones” and “zeros,” which are separated by orders of magnitude in drain current. This simple yet reliable operation provides a compact one-transistor solution for the unbiased random number generation.
