983 research outputs found
A hierarchical Bayesian model to infer PL(Z) relations using Gaia parallaxes
Aims. We aim at creating a Bayesian model to infer the coefficients of PL or
PLZ relations that propagates uncertainties in the observables in a rigorous
and well founded way. Methods. We propose a directed acyclic graph to encode
the conditional probabilities of the inference model that will allow us to
infer probability distributions for the PL and PL(Z) relations. We evaluate the
model with several semi-synthetic data sets and apply it to a sample of 200
fundamental mode and first overtone mode RR Lyrae stars for which Gaia DR1
parallaxes and literature Ks-band mean magnitudes are available. We define and
test several hyperprior probabilities to verify their adequacy and check the
sensitivity of the solution with respect to the prior choice. Results. The main
conclusion of this work is the absolute necessity of incorporating the existing
correlations between the observed variables (periods, metallicities and
parallaxes) in the form of model priors in order to avoid systematically biased
results, especially in the case of non-negligible uncertainties in the
parallaxes. The tests with the semi-synthetic data based on the data set used
in Gaia Collaboration et al. (2017) reveal the significant impact that the
existing correlations between parallax, metallicity and periods have on the
inferred parameters. The relation coefficients obtained here have been
superseded by those presented in Muraveva et al. (2018a), that incorporates the
findings of this work and the more recent Gaia DR2 measurements.Comment: 14 pages, 12 figures. Submitted to A&
Enhancing Genetic Improvement of Software with Regression Test Selection
Genetic improvement uses artificial intelligence to automatically improve software with respect to non-functional properties (AI for SE). In this paper, we propose the use of existing software engineering best practice to enhance Genetic Improvement (SE for AI). We conjecture that existing Regression Test Selection (RTS) techniques (which have been proven to be efficient and effective) can and should be used as a core component of the GI search process for maximising its effectiveness. To assess our idea, we have carried out a thorough empirical study assessing the use of both dynamic and static RTS techniques with GI to improve seven real-world software programs. The results of our empirical evaluation show that incorporation of RTS within GI significantly speeds up the whole GI process, making it up to 78% faster on our benchmark set, being still able to produce valid software improvements. Our findings are significant in that they can save hours to days of computational time, and can facilitate the uptake of GI in an industrial setting, by significantly reducing the time for the developer to receive feedback from such an automated technique. Therefore, we recommend the use of RTS in future test-based automated software improvement work. Finally, we hope this successful application of SE for AI will encourage other researchers to investigate further applications in this area
Dynamical two-mode squeezing of thermal fluctuations in a cavity opto-mechanical system
We report the experimental observation of two-mode squeezing in the
oscillation quadratures of a thermal micro-oscillator. This effect is obtained
by parametric modulation of the optical spring in a cavity opto-mechanical
system. In addition to stationary variance measurements, we describe the
dynamic behavior in the regime of pulsed parametric excitation, showing
enhanced squeezing effect surpassing the stationary 3dB limit. While the
present experiment is in the classical regime, our technique can be exploited
to produce entangled, macroscopic quantum opto-mechanical modes
Diversifying focused testing for unit testing
Software changes constantly because developers add new features or modifications. This directly affects the effectiveness of the testsuite associated with that software, especially when these new modifications are in a specific area that no test case covers. This paper tackles the problem of generating a high quality test suite to cover repeatedly a given point in a program, with the ultimate goal of exposing faults possibly affecting the given program point. Both search based software testing and constraint solving offer ready, but low quality, solutions to this: ideally a maximally diverse covering test set is required whereas search and constraint solving tend to generate test sets with biased distributions. Our approach, Diversified Focused Testing (DFT), uses a search strategy inspired by GödelTest. We artificially inject parameters into the code branching conditions and use a bi-objective search algorithm to find diverse inputs by perturbing the injected parameters, while keeping the path conditions still satisfiable. Our results demonstrate that our technique, DFT, is able to cover a desired point in the code at least 90% of the time. Moreover, adding diversity improves the bug detection and the mutation killing abilities of the test suites. We show that DFT achieves better results than focused testing, symbolic execution and random testing by achieving from 3% to 70% improvement in mutation score and up to 100% improvement in fault detection across 105 software subjects
Artifact for Enhancing Genetic Improvement of Software with Regression Test Selection
We present in this document the basic information needed to download, unpack, and then interpret the instructions we provide as requested in the ICSE 2021 Artifact Submission Guidelines. The artifact contains all the subject programs, scripts, tools, results, and a series of guidelines on how to use them. We aim at obtaining the badges of Available and Reusable. In order to do so, we have added all the components needed for the full execution of the experiments and analyses as we originally did during the writing of our paper, making it readily available. Furthermore, we have included instructions to the INSTALL file on how to add new programs to the experiments and analyses, making it reusable for the next researchers that intend to replicate or extend our experiments
Control of Recoil Losses in Nanomechanical SiN Membrane Resonators
In the context of a recoil damping analysis, we have designed and produced a
membrane resonator equipped with a specific on-chip structure working as a
"loss shield" for a circular membrane. In this device the vibrations of the
membrane, with a quality factor of , reach the limit set by the intrinsic
dissipation in silicon nitride, for all the modes and regardless of the modal
shape, also at low frequency. Guided by our theoretical model of the loss
shield, we describe the design rationale of the device, which can be used as
effective replacement of commercial membrane resonators in advanced
optomechanical setups, also at cryogenic temperatures
mTOR pathway inhibition as a new therapeutic strategy in epilepsy and epileptogenesis.
Several preclinical and some clinical studies have revealed that the mammalian target of rapamycin (mTOR) signaling pathway is involved in both genetic and acquired epilepsy syndromes. Excessive activation of mTOR signaling, as a consequence of loss-of-function of genes encoding for tuberous sclerosis complex (TSC) 1 and 2, is linked to the development of cortical malformations and epilepsy. This mTOR hyperactivation is associated with different epileptogenic conditions under the term of 'mTORopathies' such as tuberous sclerosis, focal cortical dysplasia, hemimegalencephaly and ganglioglioma. mTOR overactivation produces brain abnormalities that include dysplastic neurons, abnormal cortical organization and astrogliosis. mTOR inhibitors (e.g. rapamycin) have consistent protective effects in various genetic (e.g. TSC models and WAG/Rij rats) and acquired (e.g. kainate or pilocarpine post-status epilepticus) epilepsy animal models. Furthermore, clinical studies in patients with TSC and cortical dysplasia (CD) have confirmed the effectiveness of mTOR inhibitors also in epileptic patients. Therefore, mTOR is currently a very good candidate as a target for epilepsy and epileptogenesis. This review describes the relevance of the mTOR pathway to epileptogenesis and its potential as a therapeutic target in epilepsy treatment by presenting the most recent findings on mTOR inhibitors
Calibrated quantum thermometry in cavity optomechanics
Cavity optomechanics has achieved the major breakthrough of the preparation
and observation of macroscopic mechanical oscillators in peculiarly quantum
states. The development of reliable indicators of the oscillator properties in
these conditions is important also for applications to quantum technologies. We
compare two procedures to infer the oscillator occupation number, minimizing
the necessity of system calibrations. The former starts from homodyne spectra,
the latter is based on the measurement of the motional sidebands asymmetry in
heterodyne spectra. Moreover, we describe and discuss a method to control the
cavity detuning, that is a crucial parameter for the accuracy of the latter,
intrinsically superior procedure
Refining Fitness Functions for Search-Based Automated Program Repair: A Case Study with ARJA and ARJA-e
Several tools support code templates as a means to specify searches within a program’s source code. Despite their ubiquity, code templates can often prove difficult to specify, and may produce too many or too few match results. In this paper, we present a search-based approach to support developers in specifying templates. This approach uses a suite of mutation operators to recommend changes to a given template, such that it matches with a desired set of code snippets. We evaluate our approach on the problem of inferring a code template that matches all instances of a design pattern, given one instance as a starting template
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