946 resultados para Static-99
Resumo:
Mainstream IDEs such as Eclipse support developers in managing software projects mainly by offering static views of the source code. Such a static perspective neglects any information about runtime behavior. However, object-oriented programs heavily rely on polymorphism and late-binding, which makes them difficult to understand just based on their static structure. Developers thus resort to debuggers or profilers to study the system's dynamics. However, the information provided by these tools is volatile and hence cannot be exploited to ease the navigation of the source space. In this paper we present an approach to augment the static source perspective with dynamic metrics such as precise runtime type information, or memory and object allocation statistics. Dynamic metrics can leverage the understanding for the behavior and structure of a system. We rely on dynamic data gathering based on aspects to analyze running Java systems. By solving concrete use cases we illustrate how dynamic metrics directly available in the IDE are useful. We also comprehensively report on the efficiency of our approach to gather dynamic metrics.
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Maintaining object-oriented systems that use inheritance and polymorphism is difficult, since runtime information, such as which methods are actually invoked at a call site, is not visible in the static source code. We have implemented Senseo, an Eclipse plugin enhancing Eclipse's static source views with various dynamic metrics, such as runtime types, the number of objects created, or the amount of memory allocated in particular methods.
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The integration of the auditory modality in virtual reality environments is known to promote the sensations of immersion and presence. However it is also known from psychophysics studies that auditory-visual interaction obey to complex rules and that multisensory conflicts may disrupt the adhesion of the participant to the presented virtual scene. It is thus important to measure the accuracy of the auditory spatial cues reproduced by the auditory display and their consistency with the spatial visual cues. This study evaluates auditory localization performances under various unimodal and auditory-visual bimodal conditions in a virtual reality (VR) setup using a stereoscopic display and binaural reproduction over headphones in static conditions. The auditory localization performances observed in the present study are in line with those reported in real conditions, suggesting that VR gives rise to consistent auditory and visual spatial cues. These results validate the use of VR for future psychophysics experiments with auditory and visual stimuli. They also emphasize the importance of a spatially accurate auditory and visual rendering for VR setups.
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Static hedging of complicated payoff structures by standard instruments becomes increasingly popular in finance. The classical approach is developed for quite regular functions, while for less regular cases, generalized functions and approximation arguments are used. In this note, we discuss the regularity conditions in the classical decomposition formula due to P. Carr and D. Madan (in Jarrow ed, Volatility, pp. 417–427, Risk Publ., London, 1998) if the integrals in this formula are interpreted as Lebesgue integrals with respect to the Lebesgue measure. Furthermore, we show that if we replace these integrals by Lebesgue–Stieltjes integrals, the family of representable functions can be extended considerably with a direct approach.
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We review the determination of the strong coupling αs from the comparison of the perturbative expression for the Quantum Chromodynamics static energy with lattice data. Here, we collect all the perturbative expressions needed to evaluate the static energy at the currently known accuracy.
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We compare lattice data for the short-distance part of the static energy in 21 flavor quantum chromodynamics (QCD) with perturbative calculations, up to next-to-next-to-next-to leading-logarithmic accuracy. We show that perturbation theory describes very well the lattice data at short distances, and exploit this fact to obtain a determination of the product of the lattice scale r0 with the QCD scale ΛMS. With the input of the value of r0, this provides a determination of the strong coupling αs at the typical distance scale of the lattice data. We obtain αs1.5 GeV0.3260.019, which provides a novel determination of αs with three-loop accuracy (including resummation of the leading ultrasoft logarithms), and constitutes one of the few low-energy determinations of αs available. When this value is evolved to the Z-mass scale MZ, it corresponds to αsMZ0.11560.00220.0021.
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We obtain a determination of the strong coupling as in quantum chromodynamics, by comparing perturbative calculations for the short-distance part of the static energy with lattice computations. Our result reads as (1.5GeV) = 0.326±0.019, and when evolved to the scale MZ (the Z-boson mass) it corresponds to as (MZ) = 0.1156+0.0021 −0.0022.
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Comparing perturbative calculations with a lattice computation of the static energy in quantum chromodynamics at short distances, we obtain a determination of the strong coupling αS. Our determination is performed at a scale of around 1.5 GeV (the typical distance scale of the lattice data) and, when evolved to the Z-boson mass scale MZ, it corresponds to .
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Purpose: To investigate the dosimetric properties of an electronic portal imaging device (EPID) for electron beam detection and to evaluate its potential for quality assurance (QA) of modulated electron radiotherapy (MERT). Methods: A commercially available EPID was used to detect electron beams shaped by a photon multileaf collimator (MLC) at a source-surface distance of 70 cm. The fundamental dosimetric properties such as reproducibility, dose linearity, field size response, energy response, and saturation were investigated for electron beams. A new method to acquire the flood-field for the EPID calibration was tested. For validation purpose, profiles of open fields and various MLC fields (square and irregular) were measured with a diode in water and compared to the EPID measurements. Finally, in order to use the EPID for QA of MERT delivery, a method was developed to reconstruct EPID two-dimensional (2D) dose distributions in a water-equivalent depth of 1.5 cm. Comparisons were performed with film measurement for static and dynamic monoenergy fields as well as for multienergy fields composed by several segments of different electron energies. Results: The advantageous EPID dosimetric properties already known for photons as reproducibility, linearity with dose, and dose rate were found to be identical for electron detection. The flood-field calibration method was proven to be effective and the EPID was capable to accurately reproduce the dose measured in water at 1.0 cm depth for 6 MeV, 1.3 cm for 9 MeV, and 1.5 cm for 12, 15, and 18 MeV. The deviations between the output factors measured with EPID and in water at these depths were within ±1.2% for all the energies with a mean deviation of 0.1%. The average gamma pass rate (criteria: 1.5%, 1.5 mm) for profile comparison between EPID and measurements in water was better than 99% for all the energies considered in this study. When comparing the reconstructed EPID 2D dose distributions at 1.5 cm depth to film measurements, the gamma pass rate (criteria: 2%, 2 mm) was better than 97% for all the tested cases. Conclusions: This study demonstrates the high potential of the EPID for electron dosimetry, and in particular, confirms the possibility to use it as an efficient verification tool for MERT delivery.
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Background: The cerebral network that is active during rest and is deactivated during goal-oriented activity is called the default mode network (DMN). It appears to be involved in self-referential mental activity. Atypical functional connectivity in the DMN has been observed in schizophrenia. One hypothesis suggests that pathologically increased DMN connectivity in schizophrenia is linked with a main symptom of psychosis, namely, misattribution of thoughts. Methods: A resting-state pseudocontinuous arterial spin labeling (ASL) study was conducted to measure absolute cerebral blood flow (CBF) in 34 schizophrenia patients and 27 healthy controls. Using independent component analysis (ICA), the DMN was extracted from ASL data. Mean CBF and DMN connectivity were compared between groups using a 2-sample t test. Results: Schizophrenia patients showed decreased mean CBF in the frontal and temporal regions (P < .001). ICA demonstrated significantly increased DMN connectivity in the precuneus (x/y/z = -16/-64/38) in patients than in controls (P < .001). CBF was not elevated in the respective regions. DMN connectivity in the precuneus was significantly correlated with the Positive and Negative Syndrome Scale scores (P < .01). Conclusions: In schizophrenia patients, the posterior hub-which is considered the strongest part of the DMN-showed increased DMN connectivity. We hypothesize that this increase hinders the deactivation of the DMN and, thus, the translation of cognitive processes from an internal to an external focus. This might explain symptoms related to defective self-monitoring, such as auditory verbal hallucinations or ego disturbances.
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It is well known that sufficiently regular, one-dimensional payoff functions have an explicit static hedge by bonds, forward contracts, and options in a continuum of strikes. An easy and natural extension of the corresponding representation leads to static hedges based on the same instruments along with traffic light options, which have recently been introduced in the market. It is well known that the second strike derivative of non-discounted prices of vanilla options is related to the risk-neutral density of the underlying asset price in the corresponding absolutely continuous settings. Similar statements hold for traffic light options in sufficiently regular, bivariate settings.
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We present an update of our determination of the strong coupling αs from the quantum chromodynamics static energy. This updated analysis includes new lattice data, at smaller lattice spacings and reaching shorter distances, the use of better suited perturbative expressions to compare with data in a wider distance range, and a comprehensive and detailed estimate of the error sources that contribute to the uncertainty of the final result. Our updated value for αs at the Z-mass scale, MZ, is αs(MZ)=0.1166+0.0012−0.0008, which supersedes our previous result.