Thermodynamics of a class of non-asymptotically flat black holes in Einstein-Maxwell-Dilaton theory

We analyse in detail the thermodynamics in the canonical and grand canonical ensembles of a class of non-asymptotically flat black holes of the Einstein-(anti) Maxwell-(anti) Dilaton theory in 4D with spherical symmetry. We present the first law of thermodynamics, the thermodynamic analysis of the system through the geometrothermodynamics methods, Weinhold, Ruppeiner, Liu-Lu-Luo-Shao and the most common, that made by the specific heat. The geometric methods show a curvature scalar identically zero, which is incompatible with the results of the analysis made by the non null specific heat, which shows that the system is thermodynamically interacting, does not possess extreme case nor phase transition. We also analyse the local and global stability of the thermodynamic system, and obtain a local and global stability for the normal case for 0<\gamma<1 and for other values of \gamma, an unstable system. The solution where \gamma=0 separates the class of locally and globally stable solutions from the unstable ones.Comment: 18 pages, version accepted for publication in General Relativity and Gravitatio

Comparative study of nonlinear properties of EEG signals of a normal person and an epileptic patient

Background: Investigation of the functioning of the brain in living systems has been a major effort amongst scientists and medical practitioners. Amongst the various disorder of the brain, epilepsy has drawn the most attention because this disorder can affect the quality of life of a person. In this paper we have reinvestigated the EEGs for normal and epileptic patients using surrogate analysis, probability distribution function and Hurst exponent. Results: Using random shuffled surrogate analysis, we have obtained some of the nonlinear features that was obtained by Andrzejak \textit{et al.} [Phys Rev E 2001, 64:061907], for the epileptic patients during seizure. Probability distribution function shows that the activity of an epileptic brain is nongaussian in nature. Hurst exponent has been shown to be useful to characterize a normal and an epileptic brain and it shows that the epileptic brain is long term anticorrelated whereas, the normal brain is more or less stochastic. Among all the techniques, used here, Hurst exponent is found very useful for characterization different cases. Conclusions: In this article, differences in characteristics for normal subjects with eyes open and closed, epileptic subjects during seizure and seizure free intervals have been shown mainly using Hurst exponent. The H shows that the brain activity of a normal man is uncorrelated in nature whereas, epileptic brain activity shows long range anticorrelation.Comment: Keywords:EEG, epilepsy, Correlation dimension, Surrogate analysis, Hurst exponent. 9 page

Discovery of the peculiar supernova 1998bw in the error box of GRB980425

The discovery of X-ray, optical and radio afterglows of gamma-ray bursts (GRBs) and the measurements of the distances to some of them have established that these events come from Gpc distances and are the most powerful photon emitters known in the Universe, with peak luminosities up to 10^52 erg/s. We here report the discovery of an optical transient, in the BeppoSAX Wide Field Camera error box of GRB980425, which occurred within about a day of the gamma-ray burst. Its optical light curve, spectrum and location in a spiral arm of the galaxy ESO 184-G82, at a redshift z = 0.0085, show that the transient is a very luminous type Ic supernova, SN1998bw. The peculiar nature of SN1998bw is emphasized by its extraordinary radio properties which require that the radio emitter expand at relativistical speed. Since SN1998bw is very different from all previously observed afterglows of GRBs, our discovery raises the possibility that very different mechanisms may give rise to GRBs, which differ little in their gamma-ray properties.Comment: Under press embargo at Nature (submitted June 10, 1998

For which side the bell tolls: The laterality of approach-avoidance associative networks

The two hemispheres of the brain appear to play different roles in emotion and/or motivation. A great deal of previous research has examined the valence hypothesis (left hemisphere = positive; right = negative), but an increasing body of work has supported the motivational hypothesis (left hemisphere = approach; right = avoidance) as an alternative. The present investigation (N = 117) sought to provide novel support for the latter perspective. Left versus right hemispheres were briefly activated by neutral lateralized auditory primes. Subsequently, participants categorized approach versus avoidance words as quickly and accurately as possible. Performance in the task revealed that approach-related thoughts were more accessible following left-hemispheric activation, whereas avoidance-related thoughts were more accessible following right-hemispheric activation. The present results are the first to examine such lateralized differences in accessible motivational thoughts, which may underlie more “downstream” manifestations of approach and avoidance motivation such as judgments, decision making, and behavior

Long-range temporal correlations of broadband EEG oscillations for depressed subjects following different hemispheric cerebral infarction

Abnormal long-range temporal correlation (LRTC) in EEG oscillation has been observed in several brain pathologies and mental disorders. This study examined the relationship between the LRTC of broadband EEG oscillation and depression following cerebral infarction with different hemispheric lesions to provide a novel insight into such depressive disorders. Resting EEGs of 16 channels in 18 depressed (9 left and 9 right lesions) and 21 non-depressed (11 left and 10 right lesions) subjects following cerebral infarction and 19 healthy control subjects were analysed by means of detrended fluctuation analysis, a quantitative measurement of LRTC. The difference among groups and the correlation between the severity of depression and LRTC in EEG oscillation were investigated by statistical analysis. The results showed that LRTC of broadband EEG oscillations in depressive subjects was still preserved but attenuated in right hemispheric lesion subjects especially in left pre-frontal and right inferior frontal and posterior temporal regions. Moreover, an association between the severity of psychiatric symptoms and the attenuation of the LRTC was found in frontal, central and temporal regions for stroke subjects with right lesions. A high discriminating ability of the LRTC in the frontal and central regions to distinguish depressive from non-depressive subjects suggested potential feasibility for LRTC as an assessment indicator for depression following right hemispheric cerebral infarction. Different performance of temporal correlation in depressed subjects following the two hemispheric lesions implied complex association between depression and stroke lesion location.</p

Honey bee foraging distance depends on month and forage type

To investigate the distances at which honey bee foragers collect nectar and pollen, we analysed 5,484 decoded waggle dances made to natural forage sites to determine monthly foraging distance for each forage type. Firstly, we found significantly fewer overall dances made for pollen (16.8 %) than for non-pollen, presumably nectar (83.2 %; P < 2.2 × 10−23). When we analysed distance against month and forage type, there was a significant interaction between the two factors, which demonstrates that in some months, one forage type is collected at farther distances, but this would reverse in other months. Overall, these data suggest that distance, as a proxy for forage availability, is not significantly and consistently driven by need for one type of forage over the other

Integrative Genomics Viewer

Author Manuscript 2012 May 07.To the Editor: Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.National Institute of General Medical Sciences (U.S.) (R01GM074024)National Cancer Institute (U.S.) (R21CA135827)National Human Genome Research Institute (U.S.) (U54HG003067

Validation of the SCID-hu Thy/Liv mouse model with four classes of licensed antiretrovirals.

BackgroundThe SCID-hu Thy/Liv mouse model of HIV-1 infection is a useful platform for the preclinical evaluation of antiviral efficacy in vivo. We performed this study to validate the model with representatives of all four classes of licensed antiretrovirals.Methodology/principal findingsEndpoint analyses for quantification of Thy/Liv implant viral load included ELISA for cell-associated p24, branched DNA assay for HIV-1 RNA, and detection of infected thymocytes by intracellular staining for Gag-p24. Antiviral protection from HIV-1-mediated thymocyte depletion was assessed by multicolor flow cytometric analysis of thymocyte subpopulations based on surface expression of CD3, CD4, and CD8. These mice can be productively infected with molecular clones of HIV-1 (e.g., the X4 clone NL4-3) as well as with primary R5 and R5X4 isolates. To determine whether results in this model are concordant with those found in humans, we performed direct comparisons of two drugs in the same class, each of which has known potency and dosing levels in humans. Here we show that second-generation antiretrovirals were, as expected, more potent than their first-generation predecessors: emtricitabine was more potent than lamivudine, efavirenz was more potent than nevirapine, and atazanavir was more potent than indinavir. After interspecies pharmacodynamic scaling, the dose ranges found to inhibit viral replication in the SCID-hu Thy/Liv mouse were similar to those used in humans. Moreover, HIV-1 replication in these mice was genetically stable; treatment of the mice with lamivudine did not result in the M184V substitution in reverse transcriptase, and the multidrug-resistant NY index case HIV-1 retained its drug-resistance substitutions.ConclusionGiven the fidelity of such comparisons, we conclude that this highly reproducible mouse model is likely to predict clinical antiviral efficacy in humans

Data quality problems in discrete event simulation of manufacturing operations

High-quality input data are a necessity for successful discrete event simulation (DES) applications, and there are available methodologies for data collection in DES projects. However, in contrast to standalone projects, using DES as a daily manufacturing engineering tool requires high-quality production data to be constantly available. In fact, there has been a major shift in the application of DES in manufacturing from production system design to daily operations, accompanied by a stream of research on automation of input data management and interoperability between data sources and simulation models. Unfortunately, this research stream rests on the assumption that the collected data are already of high quality,and there is a lack of in-depth understanding of simulation data quality problems from a practitioners’ perspective.Therefore, a multiple-case study within the automotive industry was used to provide empirical descriptions of simulation data quality problems, data production processes, and relations between these processes and simulation data quality problems. These empirical descriptions are necessary to extend the present knowledge on data quality in DES in a practical real-world manufacturing context, which is a prerequisite for developing practical solutions for solving data quality problems such as limited accessibility, lack of data on minor stoppages, and data sources not being designed for simulation. Further, the empirical and theoretical knowledge gained throughout the study was used to propose a set of practical guidelines that can support manufacturing companies in improving data quality in DES