We propose a new semantics for shared-memory parallel programs that gives strong guarantees even in the presence of data races. Our local data race freedom property guarantees that all data-race-free portions of progr...
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Oval squids are polyandrous, with one female mating with multiple males during the spawning season. There are two alternative male mating tactics used by Sepioteuthis lessoniana. Larger males place spermatophores at t...
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Oval squids are polyandrous, with one female mating with multiple males during the spawning season. There are two alternative male mating tactics used by Sepioteuthis lessoniana. Larger males place spermatophores at the opening of the oviduct using a male-parallel mating posture, whereas smaller males attach spermatophores around the female buccal membrane using a male-upturned mating posture. If the route of egg transportation is taken into consideration, male-parallel mating would be expected to result in higher fertilization success than male-upturned mating. Although these male mating tactics are largely dependent on the body size of the male relative to that of the female, it is unclear how female choice affects the male's mating tactics and his mating success. Squids are highly visual animals, and they communicate through dynamic body patterning. In the present study, we observed that smaller male squids in captivity would attempt to mate with a larger female using the male-parallel tactic repeatedly, but they failed to be successful most of the time because of a rejection signal by the female. In contrast, when the males switched to the male-upturned tactic, the mating success rate was increased significantly, with much less female rejection signal. This finding suggests that female squids signal their mating receptivity visually and that male squids alter their mating tactics accordingly. This is the evidence to support the hypothesis that the switch in male mating tactics depends on female choice in oval squids and that this is transmitted via visual communication.
Recent trends in nuclear reactor performance and safety analyses increasingly rely on multiscale multiphysics computer simulations to enhance predictive capabilities by replacing conventional methods that are largely ...
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Recent trends in nuclear reactor performance and safety analyses increasingly rely on multiscale multiphysics computer simulations to enhance predictive capabilities by replacing conventional methods that are largely empirically based with a more scientifically based methodology. Through this approach, one addresses the issue of traditionally employing a suite of stand-alone codes that independently simulate various physical phenomena that were previously disconnected. Multiple computer simulations of different phenomena must exchange data during runtime to address these interdependencies. Previously, recommendations have been made regarding various approaches for piloting different design options of data coupling for multiphysics systems (Seydaliev and Caswell, 2014, "CORBA and MPI Based "Backbone" for Coupling Advanced Simulation Tools,"AECL Nucl. Rev., 3(2), pp. 83-90). This paper describes progress since the initial pilot study that outlined the implementation and execution of a new distribution framework, referred to as "Backbone," to provide the necessary runtime exchange of data between different codes. The Backbone, currently under development at the Canadian Nuclear Laboratories (CNL), is a hybrid design using both common object request broker architecture (CORBA) and message passing interface (MPI) systems. This paper also presents two preliminary cases for coupling existing nuclear performance and safety analysis codes used for simulating fuel behavior, fission product release, thermal hydraulics, and neutron transport through the Backbone. Additionally, a pilot study presents a few strategies of a new time step controller (TSC) to synchronize the codes coupled through the Backbone. A performance and fidelity comparison is presented between a simple heuristic method for determining time step length and a more advanced third-order method, which was selected to maximize configurability and effectiveness of temporal integration, saving time steps and reducin
A series of estimates of the total mortality rate (Z) can be obtained by using the Beverton-Holt nonequilibrium-based approach of Gedamke and Hoenig (2006) on observations of population mean length over time (ML model...
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A series of estimates of the total mortality rate (Z) can be obtained by using the Beverton-Holt nonequilibrium-based approach of Gedamke and Hoenig (2006) on observations of population mean length over time (ML model). In contrast, only relative mortality rates (not absolute values) can be obtained from a time series of catch rates. We derived the transitional behavior of the catch rate following a change in total mortality in the population. From this derivation, we developed a new-method to estimate Z that utilizes both mean lengths and catch rates (MLCR model). Both theML model and the MLCR model assume constant recruitment in the population. We used a simulation study to test performance when recruitment is variable. Simulations over various scenarios of Z and recruitment variability showed that there may be correlated residuals in the mean lengths and catch rates arising from fluctuations in recruitment. However, the root mean square errors of the Z estimates and the change point (i.e., the year when mortality changed) were smaller in the MLCR model than in the ML model, indicating that the MLCR model can better account for variable recruitment. Both methods were then applied to Mutton Snapper Lutjanus analis in Puerto Rico to illustrate their potential application to assess data-limited stocks. The ML model estimated an increase in Z, but the MLCR model also estimated a subsequent reduction in Z when the catch rate data were considered.
III/V semiconductor quantum dots (QD) are in the focus of optoelectronics research for about 25 years now. Most of the work has been done on InAs QD on GaAs substrate. But, e.g., Ga(As)Sb (antimonide) QD on GaAs subst...
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III/V semiconductor quantum dots (QD) are in the focus of optoelectronics research for about 25 years now. Most of the work has been done on InAs QD on GaAs substrate. But, e.g., Ga(As)Sb (antimonide) QD on GaAs substrate/buffer have also gained attention for the last 12 years. There is a scientific dispute on whether there is a wetting layer before antimonide QD formation, as commonly expected for Stransky-Krastanov growth, or not. Usually ex situ photoluminescence (PL) and atomic force microscope (AFM) measurements are performed to resolve similar issues. In this contribution, we show that reflectance anisotropy/difference spectroscopy (RAS/RDS) can be used for the same purpose as an in situ, real-time monitoring technique. It can be employed not only to identify QD growth via a distinct RAS spectrum, but also to get information on the existence of a wetting layer and its thickness. The data suggest that for antimonide QD growth the wetting layer has a thickness of 1 ML (one monolayer) only.
Machine learning (ML) refers to a set of automatic pattern recognition methods that have been successfully applied across various problem domains, including biomedical image analysis. This review focuses on ML applica...
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Machine learning (ML) refers to a set of automatic pattern recognition methods that have been successfully applied across various problem domains, including biomedical image analysis. This review focuses on ML applications for image analysis in light microscopy experiments with typical tasks of segmenting and tracking individual cells, and modelling of reconstructed lineage trees. After describing a typical image analysis pipeline and highlighting challenges of automatic analysis (for example, variability in cell morphology, tracking in presence of clutters) this review gives a brief historical outlook of ML, followed by basic concepts and definitions required for understanding examples. This article then presents several example applications at various image processing stages, including the use of supervised learning methods for improving cell segmentation, and the application of active learning for tracking. The review concludes with remarks on parameter setting and future directions.
Software engineers can find vulnerabilities with less effort if they are directed towards code that might contain more vulnerabilities. HARMLESS is an incremental support vector machine tool that builds a vulnerabilit...
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Termination is an important but undecidable program property, which has led to a large body of work on static methods for conservatively predicting or enforcing termination. One such method is the size-change terminat...
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This paper develops an operational semantics for a release-acquire fragment of the C11 memory model with relaxed accesses. We show that the semantics is both sound and complete with respect to the axiomatic model. The...
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We present the implementation of a 2D stencil computation on Cyclone V SoC Field Programmable Gate Array (FPGA). The heat equation is chosen as a study case for the 2D stencil problem. To reduce the development time i...
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ISBN:
(纸本)9781538665206;9781538665190
We present the implementation of a 2D stencil computation on Cyclone V SoC Field Programmable Gate Array (FPGA). The heat equation is chosen as a study case for the 2D stencil problem. To reduce the development time in FPGA programming, OpenCL programming language is employed to develop the kernel for the stencil computation. OpenCL is a framework to develop the kernel that can be executed in heterogeneous platforms such as CPU, DSP, GPU, and FPGA. In the study, we compare the execution time and power consumption between core i5 4300U CPU and Cyclone V FPGA. The experiment shows that the Cyclone V SoC FPGA is faster than a single core i5 4300U CPU in executing the 2D stencil computation. The research also shows that the FPGA consumes low power.
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