Miracle-dz/UniFAR-FTUs huggingface dataset:
Abundance study of the two solar-analogue CoRoT targets HD 42618 and HD 43587 from HARPS spectroscopy

We present a detailed abundance study based on spectroscopic data obtained with HARPS of two solar-analogue main targets for the asteroseismology programme of the CoRoT satellite: HD 42618 and HD 43587. The atmospheric parameters and chemical composition are accurately determined through a fully differential analysis with respect to the Sun observed with the same instrumental set-up. Several sources of systematic errors largely cancel out with this approach, which allows us to narrow down the 1-σ error bars to typically 20 K in effective temperature, 0.04 dex in surface gravity, and less than 0.05 dex in the elemental abundances. Although HD 42618 fulfils many requirements for being classified as a solar twin, its slight deficiency in metals and its possibly younger age indicate that, strictly speaking, it does not belong to this class of objects. On the other hand, HD 43587 is slightly more massive and evolved. In addition, marked differences are found in the amount of lithium present in the photospheres of these two stars, which might reveal different mixing properties in their interiors. These results will put tight constraints on the forthcoming theoretical modelling of their solar-like oscillations and contribute to increase our knowledge of the fundamental parameters and internal structure of stars similar to our Sun.
DNA microarrays in medicine: manufacturing techniques and potential applications

Since their first description in 1995, DNA microarrays have moved to centre stage in many areas of biomedical research and are now assuming an increasingly important role in diagnostics and in pharmacology. Such microarrays may be used to detect and quantify nucleic acid and to determine its sequence. In medicine, a major area of use is in detection of changes in the pattern of gene expression in conditions such as cancer. Other uses are in recognition of sequence variation and in the detection of infectious organisms. In the field of pharmacogenetics, microarrays are being used to monitor the presence of polymorphisms in genes encoding cytochromes and other proteins, in an attempt to reduce side effects and tailor treatment more effectively to the patient’s genetic background. Not surprisingly, these developments have been accompanied by a burst of patenting activity in all fields relating to DNA microarrays, including methods of manufacture, methods of detecting hybridisation, analysis of array data and concrete applications for use of microarrays in the diagnostic arena. This review will focus largely on manufacturing techniques.
The implications of dust for high-redshift protogalaxies and the formation of binary disks

Numerical simulations suggest that the first galaxies are formed in protogalactic halos with virial temperatures >= 10(4) K. It is likely that such halos are polluted with trace amounts of metals produced by the first generation of stars. The presence of dust can significantly change the chemistry and dynamics of early galaxies. In this article, we aim to assess the role of dust on the thermal and dynamical evolution of the first galaxies in the presence of a background UV flux, and its implications for the observability of Lyman-alpha emitters and sub-mm sources. We have performed high resolution cosmological simulations using the adaptive mesh refinement code FLASH to accomplish this goal. We have developed a chemical network appropriate for these conditions and coupled it with the FLASH code. The main ingredients of our chemical model include the formation of molecules (both in the gas phase and on dust grains), a multi-level treatment of atomic hydrogen, line trapping of Ly-alpha photons and, photoionization and photodissociation processes in a UV background. We found that the formation of molecules (H-2 and HD) is significantly enhanced in the presence of dust grains as compared to only gas phase reactions by up to two orders of magnitude. The presence of dust may thus establish a molecular ISM in high-redshift galaxies. The presence of a background UV flux strongly influences the formation of molecules by photodissociating them. We explore the evolution after a major merger, leading to the formation of a binary disk. These disks have gas masses of similar to 10(7) M-circle dot at a redshift of 5.4. Each disk lies in a separate subhalo as a result of the merger event. The disks are supported by turbulent pressure due to the highly supersonic turbulence present in the halo. For values of J(21) = 1000 (internal flux), we find that fragmentation may be enhanced due to thermal instabilities in the hot gas. The presence of dust does not significantly reduce the Ly-alpha emission. The emission of Ly-alpha is extended and originates from the envelope of the halo due to line trapping effects. We also find that dust masses of a few x10(8) M-circle dot are required to observe the dust continuum emission from z similar to 5 galaxies with ALMA.
Will it blend? Merging heterogeneous cores

Heterogeneous processors allow different performance/power operation points by pairing high performance Outof-Order (OoO) cores with small energy efficient In-Order cores. Timely switching between the cores types allows the system to tailor to energy budget and performance constraints. Each core migration incurs a penalty though, which is caused by the necessary transfer of state between cores. Heterogeneous systems are kept from further increasing performance through more frequent migrations, as the benefits are suppressed by these overheads. Sharing some of the components between cores can reduce the transfer overheads and potentially overcome this problem. However, multiplexing core components can have also an adverse effect on performance when done without taking into consideration the extra latency. For this reason, it is critical to strike a balance between component sharing and complexity. In our work, we show that sharing the translation mechanism and the level 2 caches capture most of the potential benefits for in-order cores, while the branch predictor state is most critical for Out-of-Order cores. Finally, even under a best case scenario, on average 10% of applications could transfer to an OoO core to gain extra performance, while 6% of execution could migrate to In-Order cores saving significant energy, without incurring any penalty to the system. Under a more relaxed trade-off policy, benefits increase significantly as, on average, for 66% of the time executed a migration to the opposite core to improve the energy delay product.
Chimeric Protein , IE 1-pp 65 Donors by Using a Soluble Recombinant Cytomegalovirus-Seropositive Blood Blood Mononuclear Cells of Human T Cells from Peripheral + and CD 8 + CD 4 Ex Vivo Stimulation and Expansion of both

10.1128/JVI.75. 17.7840-7847.2001. 2001, 75(17):7840. DOI: J. Virol. Betbeder, Jean-Luc Davignon and Christian Davrinche Céline Jacquier, Nicolas Gibert, Emmanuelle Le Roy, Didier Jocelyn Vaz-Santiago, Jacqueline Lulé, Pierre Rohrlich, Chimeric Protein, IE1-pp65 Donors by Using a Soluble Recombinant Cytomegalovirus-Seropositive Blood Blood Mononuclear Cells of Human T Cells from Peripheral + and CD8 + CD4 Ex Vivo Stimulation and Expansion of both
Antioxidant capacity and chemical composition of Carum copticum under PEG treatment.

Drought stress is one of the main non-biological factors limiting the growth and yield of plants in dry and semi-dry regions of the world. Plants are the source of much chemicals derived from secondary metabolism. Carum copticum is a plant from the Apiaceae family with the seeds containing 2-4% the essential oil which are rich in monoterpenes such as thymol and are widely used as an antibacterial agent. This experiment was conducted in order to evaluate the effects of drought stress on physiological parameters and essential oil properties of seedlings and callus of C. copticum. For this purpose, seeds ofC. copticum were cultured in Murashige and Skoog medium containing 0, 2, 4, 6, and 8% PEG. Also,calluses cultured were in MS medium containing 0.25 mg.L-1 2, 4-Dichlorophenoxyacetic acid, and 1 mg.L-1 benzyl amino purine and different levels of PEG. After PEG treatment for 4 weeks, results showed that drought stress decreased chlorophylls and carotenoids contents while it increased anthocyanin, phenolic compounds, protein contents, and CAT and APX activities. Unlike CAT and APX, water deficit induced a significant reduction in superoxide dismutase activity. The content of reducing sugars and proline increased progressively when drought stress increased. Furthermore, PEG changed the essential-oil composition in shoots and calluses. Drought stress increased thymol and p-cymene concentration, though it decreased γ-terpinene. In general, these results showed the high tolerance of C. copticum to drought stress and also revealed positive effects of drought on the antioxidant activities and essential oil composition.
Neurobehavioural Activity In Albino Wistar Rats In The Open Field Maze Following Long Term Tobacco Diet Ingestion

Chemicals with behavioral activity are delivered to users when tobacco products are ingested. Nicotine in tobacco causes depression of locomotor activity in rats; but, tolerance to this activity develops following chronic administration. However there is a controversy in the way rodents differ in their sensitivity and direction of the effect (increased or decreased activity) of nicotine. This study aims to determine such a status in the albino Wistar rats. The open field maze (arena) was used to study locomotor, exploratory and anxiety related behaviors in 32 albino Wistar rats weighing between 180g – 230g. The rats were grouped into 4 consisting of 8 rats each. Group 1 animals which served as control had free access to normal rat chow and clean drinking water. Group 2 animals received 15% w/w tobacco diet; group 3 animals received 24% w/w tobacco diet; while group 4 animals received 30% w/w tobacco diet. Each animal was tested in the open maze for 5 minutes and behaviors scored. ANOVA and post-hoc t-test were employed for statistical analysis and p<. 05, accepted as significant. Our results revealed changes in behaviour that may likely result from the total constituents of tobacco as against reported effects of nicotine alone.
TUTORIAL IN BIOSTATISTICS GENETIC MAPPING OF COMPLEX TRAITS

Statistical genetic mapping methods are powerful tools for "nding genes that contribute to complex human traits. Mapping methods combine knowledge of the biological mechanisms of inheritance and the randomness inherent in those mechanisms to locate, with increasing precision, trait genes on the human genome. We provide an overview of the two major classes of mapping methods, genetic linkage analysis and linkage disequilibrium analysis, and related concepts of genetic inheritance. Copyright ( 1999 John Wiley & Sons, Ltd.
Serum Fatty Acid Binding Protein 4 ( FABP 4 ) Predicts Pre-eclampsia in Women with Type

Publisher rights © 2016 by the American Diabetes Association. This is an author-created, uncopyedited electronic version of an article accepted for publication in Diabetes Care. The American Diabetes Association (ADA), publisher of Diabetes Care, is not responsible for any errors or omissions in this version of the manuscript or any version derived from it by third parties. The definitive publisher-authenticated version will be available in a future issue of Diabetes Care in print and online at http://care.diabetesjournals. org/content/39/10/1827
An Efficient Community Question Answer (CQA) using the Metadata Rating

Community Question Answering (CQA) is the question answering process. Question Answering (QA) is the field of information retrieval and Natural language Processing (NLP). In this paper we mainly focus on lexical gap and word embedding problem. Here, the CQA aims to find the existing question which is equivalent to queried question. The other existing system of this paper is two novel category powered models. That is basic category powered model called as MB-NET and enhanced category powered model called as ME-NET. They are used to learn about the lexical gap and word embedding problem. The proposed system of this paper is to extend the metadata information easily using user ratings, like signals and Poll and Survey signals, into the learning process to obtain more powerful word representations.
Equilibrium formulae for transverse magnetotransport of strongly correlated metals

Exact formulas for the Hall coefficient [A. Auerbach, Phys. Rev. Lett. 121, 066601 (2018). ], modified Nernst coefficient, and thermal Hall coefficient of metals are derived from the Kubo formula. These coefficients depend exclusively on equilibrium susceptibilities, which are significantly easier to compute than conductivities. For weak isotropic scattering, Boltzmann theory is recovered. For strong scattering, well-controlled methods for thermodynamic functions are available. As an example, the Hall sign reversals of lattice bosons near the Mott insulator phases are determined. Appendices include mathematical supplements and instructions for calculating the coefficients.
Distributed Systems Report Series LDBC Graphalytics : A Benchmark for Large-Scale Graph Analysis on Parallel and Distributed Platforms , a Technical Report

In this paper we introduce LDBC Graphalytics, a new industrial-grade benchmark for graph analysis platforms. It consists of six deterministic algorithms, standard datasets, synthetic dataset generators, and reference output, that enable the objective comparison of graph analysis platforms. Its test harness produces deep metrics that quantify multiple kinds of system scalability, such as horizontal/vertical and weak/strong, and of robustness, such as failures and performance variability. The benchmark comes with opensource software for generating data and monitoring performance. We describe and analyze six implementations of the benchmark (three from the community, three from the industry), providing insights into the strengths and weaknesses of the platforms. Key to our contribution, vendors perform the tuning and benchmarking of their platforms. Date Version Changes 2016-Mar-18 1.0 First submission for peer review. 2016-Jun-07 1.1 Second submission for camera-ready version. 2017-Jan-16 1.2 Figure 7’s horizontal axis changed from kE(V )PS to E(V )PS. This does not affect the analysis of the results. More datasets and systems added to main plots. More polishing of the document text. 2017-Jan-16 1.3 Update list of figures and tables.
C V ] 1 0 N ov 2 01 8 Multi-label Object Attribute Classification using a Convolutional Neural Network

Objects of different classes can be described using a limited number of attributes such as color, shape, pattern, and texture. Learning to detect object attributes instead of only detecting objects can be helpful in dealing with a priori unknown objects. With this inspiration, a deep convolutional neural network for low-level object attribute classification, called the Deep Attribute Network (DAN), is proposed. Since object features are implicitly learned by object recognition networks, one such existing network is modified and fine-tuned for developing DAN. The performance of DAN is evaluated on the ImageNet Attribute and aPascal datasets. Experiments show that in comparison with state-of-theart methods, the proposed model achieves better results.
Learning Flocking Control in an Artificial Swarm

In this paper, we introduce a control strategy for artificial swarms that leverages a small number of trained leaders to influence the trajectory of the flock in spatial navigation tasks. Artificial swarms have potential to solve spatially distributed realworld problems, such as search and rescue, monitoring, and cleanup tasks, because they are robust and scalable with decentralized control. However, controlling the trajectory of a swarm requires communicating navigational goals to the swarm agents, which is infeasible for large swarms or agents that have limited sensing and communication abilities. We address this challenge with a biologically-inspired approach, where informed individuals that are able to exert influence over their peers steer the group towards its destination. Deriving a control strategy for these leaders is a challenging problem, because artificial swarms have complex emergent behaviors that are difficult to model and predict. Our key contribution is a neuroevolutionary learning-based control method in which a subset of swarm agents are trained to strategically influence the behavior of other agents. We apply this control method in increasingly complex navigational tasks, observing that its effectiveness depends on the proportion of leaders in the swarm, and that a learning-based approach may outperform a simple heading bias policy with a sufficient proportion of leaders. 1
Neural discrimination of speech sound changes in a variable context occurs irrespective of attention and explicit awareness

To process complex stimuli like language, our auditory system must tolerate large acoustic variance, like speaker variability, and still be sensitive enough to discriminate between phonemes and to detect complex sound relationships in, e.g., prosodic cues. Our study determined discrimination of speech sounds in input mimicking natural speech variability, and detection of deviations in regular pitch relationships (rule violations) between speech sounds. We investigated the automaticity and the influence of attention and explicit awareness on these changes by recording the neurophysiological mismatch negativity (MMN) and P3a as well as task performance from 21 adults. The results showed neural discrimination of phonemes and rule violations as indicated by MMN and P3a, regardless of whether the sounds were attended or not, even when participants could not explicitly describe the rule. While small sample size precluded statistical analysis of some outcomes, we still found preliminary associations between the MMN amplitudes, task performance, and emerging explicit awareness of the rule. Our results highlight the automaticity of processing complex aspects of speech as a basis for the emerging conscious perception and explicit awareness of speech properties. While MMN operates at the implicit processing level, P3a appears to work at the borderline of implicit and explicit.
Effect of Brea Gum on the characteristics of wheat bread at different storage times

The effect of Brea Gum (BG) addition on a basic bread formulation is described. The aim of the study was to investigate the effect of BG on the characteristics of wheat bread in terms of changes in moisture, texture, retrogradation of amylopectin, and microstructure. Bread quality was assessed by the physical parameters (volume, specific volume index, width/height ratio, crumb moisture, color, and hardness) and crumb grain structure (total cell number, total cell area, average size of cells, and number of cells per unit area). The effect of BG on the characteristics of the crumb during 24, 48, and 72 hours of storage was determined according to changes in moisture, hardness, and amylopectin retrogradation. Furthermore, the microstructure of the crumb was analyzed by scanning electron microscopy (SEM). The results show the ability of BG to retain moisture in the bread crumb, which was expressed by the lower hardness of the bread crumbs with the addition of the hydrocolloid at 48 and 72 hours of storage. This effect was also evident in the microstructure.
Requirements for General Intelligence : A Case Study in Trustworthy Cumulative Learning for Air Traffic Control

While many evaluation procedures have been proposed in past research for artificial general intelligence (AGI), few take the time to carefully list the (minimum, general) requirements that an AGIaspiring (cognitive) control architecture is intended to eventually meet. Such requirements could guide the design process and help evaluate the potential of an architecture to become generally intelligent— not through measuring the performance of a running AI system, but through a white-box, offline evaluation of what requirements have been met to what degree. Rather than providing our estimate of what features are necessary to achieve AGI, we analyze a concrete task from the air traffic control (ATC) domain to come up with a crisp set of requirements that AGI would need to meet as well. To avoid major disruptions to proven workflows in safety-critical domains, a trustworthy, robust and adaptable AI system must work side-by-side with a human operator and cumulatively learn new tasks that can gradually be introduced into the operator’s complex workflow. Our analysis results in a set of minimal/necessary requirements that can guide the development of AGI-aspiring architectures. We conclude the paper with an evaluation of the degree to which several common AI approaches and architectures meet these requirements.
Understanding and improving the relation between interaction simplicity and expressivity for producing illustrations

This thesis is interested in the relationship between expres- sivity and simplicity in the context of illustrations production. More precisely, it focuses on the design of systems and workflows allowing novice users to produce illustrations in an easier and faster way with a high level of expressivity while still allowing experts users to boost their production performance.
Multi-agent distributed optimization algorithms for partition-based linear programming (LP) problems

The paper addresses the problem of multi-agent distributed solutions for a class of linear programming (LP) problems which include box constraints on the decision variables and inequality constraints. The major difference with existing literature on distributed solution of LP problems is that each agent is expected to compute only a single or few entries of the global minimizer vector, often referred as a partition-based optimization. This class of LP problems isrelevant in different applications such as optimal power transfer in remotely powered battery-less wireless sensor networks, minimum energy LED luminaries control in smart offices, and optimal temperature control in start buildings. Via a suitable approximation of the originalLP problem, we propose three different primal-dual distributed algorithms based on dual gradient ascent, on the methods of multipliers and on the Alternating Direction Methods of Multipliers.We discuss the computational and communication requirements of these methods and we provide numerical comparisons.
A unified treatment of the non-relativistic and relativistic hydrogen atom: III. The reduced Green functions

For pt.I see ibid p.79-94. This is the second in a series of three papers in which it is shown how the radial part of non-relativistic and relativistic hydrogenic bound-state calculations involving the Green functions can be presented in a unified manner. In this paper the nonrelativistic Green function is examined in detail; new functional forms are presented and a clear mathematical progression is shown to link these and most other known forms. A linear transformation of the four radial parts of the relativistic Green function is given which allows for the presentation of this function as a simple generalization of the non-relativistic Green function. Thus, many properties of the non-relativistic Green function are shown to have simple relativistic generalizations. In particular, new recursion relations of the radial parts of both the non-relativistic and relativistic Green functions are presented, along with new expressions for the double Laplace transforms and recursion relations between the radial matrix elements. A novel proof of the Sturmian form of the radial Green functions is given in an appendix.