Thermal emission from WASP-24b at 3.6 and 4.5 {\mu}m

Aims. We observe occultations of WASP-24b to measure brightness temperatures and to determine whether or not its atmosphere exhibits a thermal inversion (stratosphere). Methods. We observed occultations of WASP-24b at 3.6 and 4.5 {\mu}m using the Spitzer Space Telescope. It has been suggested that there is a correlation between stellar activity and the presence of inversions, so we analysed existing HARPS spectra in order to calculate log R'HK for WASP-24 and thus determine whether or not the star is chromospherically active. We also observed a transit of WASP-24b in the Str\"{o}mgren u and y bands, with the CAHA 2.2-m telescope. Results. We measure occultation depths of 0.159 \pm 0.013 per cent at 3.6 {\mu}m and 0.202 \pm 0.018 per cent at 4.5 {\mu}m. The corresponding planetary brightness temperatures are 1974 \pm 71 K and 1944 \pm 85 K respectively. Atmosphere models with and without a thermal inversion fit the data equally well; we are unable to constrain the presence of an inversion without additional occultation measurements in the near-IR. We find log R'HK = -4.98 \pm 0.12, indicating that WASP-24 is not a chromospherically active star. Our global analysis of new and previously-published data has refined the system parameters, and we find no evidence that the orbit of WASP-24b is non-circular. Conclusions. These results emphasise the importance of complementing Spitzer measurements with observations at shorter wavelengths to gain a full understanding of hot Jupiter atmospheres.Comment: 7 pages, 4 figures, 3 tables. Accepted for publication in A&

Hybrid Approach for Resource Allocation in Cloud Infrastructure Using Random Forest and Genetic Algorithm

In cloud computing, the virtualization technique is a significant technology to optimize the power consumption of the cloud data center. In this generation, most of the services are moving to the cloud resulting in increased load on data centers. As a result, the size of the data center grows and hence there is more energy consumption. To resolve this issue, an efficient optimization algorithm is required for resource allocation. In this work, a hybrid approach for virtual machine allocation based on genetic algorithm (GA) and the random forest (RF) is proposed which belongs to a class of supervised machine learning techniques. The aim of the work is to minimize power consumption while maintaining better load balance among available resources and maximizing resource utilization. The proposed model used a genetic algorithm to generate a training dataset for the random forest model and further get a trained model. The real-time workload traces from PlanetLab are used to evaluate the approach. The results showed that the proposed GA-RF model improves energy consumption, execution time, and resource utilization of the data center and hosts as compared to the existing models. The work used power consumption, execution time, resource utilization, average start time, and average finish time as performance metrics

Intelligent Fault-Tolerant Mechanism for Data Centers of Cloud Infrastructure

Fault tolerance in cloud computing is considered as one of the most vital issues to deliver reliable services. Checkpoint/restart is one of the methods used to enhance the reliability of the cloud services. However, many existing methods do not focus on virtual machine (VM) failure that occurs due to the higher response time of a node, byzantine fault, and performance fault, and existing methods also ignore the optimization during the recovery phase. This paper proposes a checkpoint/restart mechanism to enhance reliability of cloud services. Our work is threefold: (1) we design an algorithm to identify virtual machine failure due to several faults; (2) an algorithm to optimize the checkpoint interval time is designed; (3) lastly, the asynchronous checkpoint/restart with log-based recovery mechanism is used to restart the failed tasks. The valuation results obtained using a real-time dataset shows that the proposed model reduces power consumption and improves the performance with a better fault tolerance solution compared to the nonoptimization method

Effect of inducers against tobamovirus infection in tomato and bell Pepper

Tomato and bell pepper seeds were treated with salicylic acid (50 mM), neem oil (5%) and Pseudomonas fluorescens (slurry). The seedlings were sprayed with salicylic acid (50 mM) and neem oil (5%). The concentration of Tomato mosaic tobamovirus (ToMV) and Tobacco mosaic tobamovirus (TMV) was assessed based on the number of local lesions on Nicotiana glutinosa. The results showed that the seed/seedling treatment with inducers reduced the number of local lesions when compared to untreated ones. Salicylic acid was an effective inducer

Hyperfast pulsars as the remnants of massive stars ejected from young star clusters

Recent proper motion and parallax measurements for the pulsar PSR B1508+55 indicate a transverse velocity of ~1100 km/s, which exceeds earlier measurements for any neutron star. The spin-down characteristics of PSR B1508+55 are typical for a non-recycled pulsar, which implies that the velocity of the pulsar cannot have originated from the second supernova disruption of a massive binary system. The high velocity of PSR B1508+55 can be accounted for by assuming that it received a kick at birth or that the neutron star was accelerated after its formation in the supernova explosion. We propose an explanation for the origin of hyperfast neutron stars based on the hypothesis that they could be the remnants of a symmetric supernova explosion of a high-velocity massive star which attained its peculiar velocity (similar to that of the pulsar) in the course of a strong dynamical three- or four-body encounter in the core of dense young star cluster. To check this hypothesis we investigated three dynamical processes involving close encounters between: (i) two hard massive binaries, (ii) a hard binary and an intermediate-mass black hole, and (iii) a single star and a hard binary intermediate-mass black hole. We find that main-sequence O-type stars cannot be ejected from young massive star clusters with peculiar velocities high enough to explain the origin of hyperfast neutron stars, but lower mass main-sequence stars or the stripped helium cores of massive stars could be accelerated to hypervelocities. Our explanation for the origin of hyperfast pulsars requires a very dense stellar environment of the order of 10^6 -10^7 stars pc^{-3}. Although such high densities may exist during the core collapse of young massive star clusters, we caution that they have never been observed.Comment: 11 pages, 6 figures, 1 table, accepted to MNRA

Thermal emission at 3.6-8 micron from WASP-19b: a hot Jupiter without a stratosphere orbiting an active star

We report detection of thermal emission from the exoplanet WASP-19b at 3.6, 4.5, 5.8 and 8.0 micron. We used the InfraRed Array Camera on the Spitzer Space Telescope to observe two occultations of WASP-19b by its host star. We combine our new detections with previous measurements of WASP-19b's emission at 1.6 and 2.09 micron to construct a spectral energy distribution of the planet's dayside atmosphere. By comparing this with model-atmosphere spectra, we find that the dayside atmosphere of WASP-19b lacks a strong temperature inversion. As WASP-19 is an active star (log RHK = -4.50 +/- 0.03), this finding supports the hypothesis of Knutson, Howard & Isaacson (2010) that inversions are suppressed in hot Jupiters orbiting active stars. The available data are unable to differentiate between a carbon-rich and an oxygen-rich atmosphere.Comment: As accepted for publication in MNRAS. 12 pages, 5 figures, 3 table

The GTC exoplanet transit spectroscopy survey IX. Detection of haze, Na, K, and Li in the super-Neptune WASP-127b

Exoplanets with relatively clear atmospheres are prime targets for detailed studies of chemical compositions and abundances in their atmospheres. Alkali metals have long been suggested to exhibit broad wings due to pressure broadening, but most of the alkali detections only show very narrow absorption cores, probably because of the presence of clouds. We report the strong detection of the pressure-broadened spectral profiles of Na, K, and Li absorption in the atmosphere of the super-Neptune WASP-127b, at 4.1$\sigma$, 5.0$\sigma$, and 3.4$\sigma$, respectively. We performed a spectral retrieval modeling on the high-quality optical transmission spectrum newly acquired with the 10.4 m Gran Telescopio Canarias (GTC), in combination with the re-analyzed optical transmission spectrum obtained with the 2.5 m Nordic Optical Telescope (NOT). By assuming a patchy cloudy model, we retrieved the abundances of Na, K, and Li, which are super-solar at 3.7$\sigma$ for K and 5.1$\sigma$ for Li (and only 1.8$\sigma$ for Na). We constrained the presence of haze coverage to be around 52%. We also found a hint of water absorption, but cannot constrain it with the global retrieval owing to larger uncertainties in the probed wavelengths. WASP-127b will be extremely valuable for atmospheric characterization in the era of James Webb Space Telescope

Characterizing Exoplanets in the Visible and Infrared: A Spectrometer Concept for the EChO Space Mission

Transit-spectroscopy of exoplanets is one of the key observational techniques to characterize the extrasolar planet and its atmosphere. The observational challenges of these measurements require dedicated instrumentation and only the space environment allows an undisturbed access to earth-like atmospheric features such as water or carbon-dioxide. Therefore, several exoplanet-specific space missions are currently being studied. One of them is EChO, the Exoplanet Characterization Observatory, which is part of ESA's Cosmic Vision 2015-2025 program, and which is one of four candidates for the M3 launch slot in 2024. In this paper we present the results of our assessment study of the EChO spectrometer, the only science instrument onboard this spacecraft. The instrument is a multi-channel all-reflective dispersive spectrometer, covering the wavelength range from 400 nm to 16 microns simultaneously with a moderately low spectral resolution. We illustrate how the key technical challenge of the EChO mission - the high photometric stability - influences the choice of spectrometer concept and drives fundamentally the instrument design. First performance evaluations underline the fitness of the elaborated design solution for the needs of the EChO mission.Comment: 20 pages, 8 figures, accepted for publication in the Journal of Astronomical Instrumentatio

Exoplanet Atmosphere Measurements from Transmission Spectroscopy and other Planet-Star Combined Light Observations

It is possible to learn a great deal about exoplanet atmospheres even when we cannot spatially resolve the planets from their host stars. In this chapter, we overview the basic techniques used to characterize transiting exoplanets - transmission spectroscopy, emission and reflection spectroscopy, and full-orbit phase curve observations. We discuss practical considerations, including current and future observing facilities and best practices for measuring precise spectra. We also highlight major observational results on the chemistry, climate, and cloud properties of exoplanets.Comment: Accepted review chapter; Handbook of Exoplanets, eds. Hans J. Deeg and Juan Antonio Belmonte (Springer-Verlag). 22 pages, 6 figure

A review on a deep learning perspective in brain cancer classification

AWorld Health Organization (WHO) Feb 2018 report has recently shown that mortality rate due to brain or central nervous system (CNS) cancer is the highest in the Asian continent. It is of critical importance that cancer be detected earlier so that many of these lives can be saved. Cancer grading is an important aspect for targeted therapy. As cancer diagnosis is highly invasive, time consuming and expensive, there is an immediate requirement to develop a non-invasive, cost-effective and efficient tools for brain cancer characterization and grade estimation. Brain scans using magnetic resonance imaging (MRI), computed tomography (CT), as well as other imaging modalities, are fast and safer methods for tumor detection. In this paper, we tried to summarize the pathophysiology of brain cancer, imaging modalities of brain cancer and automatic computer assisted methods for brain cancer characterization in a machine and deep learning paradigm. Another objective of this paper is to find the current issues in existing engineering methods and also project a future paradigm. Further, we have highlighted the relationship between brain cancer and other brain disorders like stroke, Alzheimer’s, Parkinson’s, andWilson’s disease, leukoriaosis, and other neurological disorders in the context of machine learning and the deep learning paradigm