Tracing Anthropogenic Aerosol Trace Metal Sources in the North Atlantic Ocean Using Pb, Ni and Zn Isotopes
Xingchao ZhangNolwenn LemaitreJörg RickliTim Jesper SuhrhoffRachel ShelleyAli BenhraMohamed Ahmed JeyidDerek Vance
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Stable-isotope tracing is a method to measure intracellular metabolic pathway utilization by feeding a cellular system a stable-isotope-labeled tracer nutrient. The power of the method to resolve differential pathway utilization is derived from the enrichment of metabolites in heavy isotopes that are synthesized from the tracer nutrient. However, the readout is complicated by the presence of naturally occurring heavy isotopes that are not derived from the tracer nutrient. Herein we present an algorithm, and a tool that applies it (PolyMID-Correct, part of the PolyMID software package), to computationally remove the influence of naturally occurring heavy isotopes. The algorithm is applicable to stable-isotope tracing data collected on low- and high- mass resolution mass spectrometers. PolyMID-Correct is open source and available under an MIT license.
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Unlimited program flow trace is used for performance analysis on function level and for debugging of sporadic effects. Trace output via an affordable and robust tool interface like Infineon's two pin DAP [1] requires a very high trace compression. With a novel approach the required compression is achieved by tracing just calls and returns of functions and by filtering out completely very short functions, which do not call any other function.
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Tracing and performance analysis tools are an important component in the development of high performance applications. Tracing parallel programs with current tracing tools, however, easily leads to large trace files with hundreds of Megabytes. The storage, visualization, and analysis of such trace files is often difficult. We propose a trace-scaling agent for tracing parallel applications, which learns the application behavior in runtime and achieves a small, easy to handle trace. The agent dynamically identifies the amount of information needed to capture the application behavior. This knowledge acquired at runtime allows recording only the non-iterative trace information, which drastically reduces the size of the trace file.
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This paper introduces an intelligent trace-keeping handcart design based on the AT89S51 single chip microcomputer.Nowadays,there are so many intelligent trace-keeping handcart designs.Which design can embody the tracing function of an intelligent trace-keeping handcart? After argument,comparison and experiment,the author has made the tracing circuit system of the intelligent trace-keeping handcart.The system was based on the mechanical structure on common toy cars and it can stably trace the black track on road and run.
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[Context and motivation] Trace matrices are lynch pins for the development of mission- and safety-critical software systems and are useful for all software systems, yet automated methods for recovering trace links are far from perfect. This limitation makes the job of human analysts who must vet recovered trace links more difficult. [Question/Problem] Earlier studies suggested that certain analyst behaviors when performing trace recovery tasks lead to decreased accuracy of recovered trace relationships. We propose a three-step experimental study to: (a) determine if there really are behaviors that lead to errors of judgment for analysts, (b) enhance the requirements tracing software to curtail such behaviors, and (c) determine if curtailing such behaviors results in increased accuracy. [Principal ideas/results] We report on a preliminary study we undertook in which we modified the user interface of this http URL to curtail two behaviors indicated by the earlier work. We report on observed results. [Contributions] We describe and discuss a major study of potentially unwanted analyst behaviors and present results of a preliminary study toward determining if curbing these behaviors with enhancements to tracing software leads to fewer human errors.
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[Context and motivation] Trace matrices are lynch pins for the development of mission- and safety-critical software systems and are useful for all software systems, yet automated methods for recovering trace links are far from perfect. This limitation makes the job of human analysts who must vet recovered trace links more difficult. [Question/Problem] Earlier studies suggested that certain analyst behaviors when performing trace recovery tasks lead to decreased accuracy of recovered trace relationships. We propose a three-step experimental study to: (a) determine if there really are behaviors that lead to errors of judgment for analysts, (b) enhance the requirements tracing software to curtail such behaviors, and (c) determine if curtailing such behaviors results in increased accuracy. [Principal ideas/results] We report on a preliminary study we undertook in which we modified the user interface of RETRO.NET to curtail two behaviors indicated by the earlier work. We report on observed results. [Contributions] We describe and discuss a major study of potentially unwanted analyst behaviors and present results of a preliminary study toward determining if curbing these behaviors with enhancements to tracing software leads to fewer human errors.
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Abstract Many areas of computer performance analysis require detailed traces of events that occur during a program's execution. Collecting traces is expensive. The additional code required to record events greatly slows a program's execution. In addition, the resulting trace files can grow unmanageably large. This paper describes a technique called abstract execution that alleviates both problems. Abstract execution records a small set of events during the traced program's execution. These events serve as input to an abstract version of the program that generates a full trace by re‐executing selected portions of the original program. This process greatly reduces both the cost of tracing the original program and the size of the trace files. The cost of regenerating a trace is insignificant in comparison to the cost of applications that use it. This paper also describes a system called AE that implements Abstract Execution. The paper contains measurements that demonstrate that AE can efficiently trace large programs.
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