Radio variability of 1st 3-months Fermi blazars at 5 GHz: affected by interstellar scintillation?

Blazars from the first-three-months Fermi-AGN list were observed with the Urumqi 25m radio telescope at 5GHz in IDV (Intra-Day Variability) mode and inter-month observation mode. A significant correlation between the flux density at 5GHz and the gamma-ray intensity for the Fermi-LAT detected blazars is seen. There is a higher IDV detection rate in Fermi detected blazars than those reported for other samples. Stronger variability appears at lower Galactic latitudes; IDV appears to be stronger in weaker sources, indicating that the variability is affected by interstellar scintillation.Comment: 4 pages, 4 figures, in proceedings of 'Multiwavelength Variability of Blazars' in Guangzhou Uni. of China, 22-24, Sep. 2010, to appear in JA

Luteinizing hormone and androstendione are independent predictors of ovulation after laparoscopic ovarian drilling: a retrospective cohort study

<p>Abstract</p> <p>Background</p> <p>Our objective was to investigate luteinizing hormone, follicle-stimulating hormone, testosterone, and androstenedione as predicitve markers for ovulation after laparoscopic ovarian drilling.</p> <p>Methods</p> <p>We retrospectively analyzed 100 clompihen-resistant patients with the polycystic ovary syndrome who underwent laparoscopic ovarian drilling at our department. The main outcome measure was spontaneous postoperative ovulation within three months after laparoscopic ovarian drilling. In order to predict spontaneous ovulation, we tested the following parameters by use of a univariate followed by a multivariate regression model: Preoperative serum levels of LH, FSH, testosterone, and androstenedione as well as patients' age and body mass index. In addition, we focused on pregnancy and life birth rates.</p> <p>Results</p> <p>Spontaneous ovulation was documented in 71/100 patients (71.0%). In a univariate and multivariate analysis, luteinizing hormone (OR 1.58, 95%CI: 1.30-1.92) and androstenedione (OR 3.03, 95%CI: 1.20-7.67), but not follicle-stimulating hormone and testosterone were independent predictors of ovulation. Using a cut-off for luteinizing hormone and androstenedione of 12.1 IU/l and 3.26 ng/ml, respectively, spontaneous ovulation was observed in 63/70 (90.0%) and 36/42 patients (85.7%) with elevated and in 8/30 (26.7%) and 35/58 (60.3%) patients with low luteinizing hormone and androstenedione levels, respectively. The sensitivity, specificity, positive and negatvie predictive values for luteinizing hormone and androstendione as predictors of spontaneous ovulation after ovarian drilling were 88.7% (95%CI: 79.0-95.0%), 75.9% (95%CI: 56.5-89.7%), 90.0% (95%CI: 80.5-95.8%), and 73.3% (95%CI: 54.1-87.7%) for luteinizing hormone, and 50.7% (95%CI: 38.6-62.8%), 79.3% (95%CI: 60.3-92.0%), 85.7% (95%CI: 71.5-94.6%), and 39.7% (95%CI: 27.0-53.4%) for androstenedione, respectively. Complete one-year follow-up was available for 74/100 patients (74%). We observed a one-year pregnancy rate and a resulting life-birth rate of 61% and 51%, respectively.</p> <p>Conclusions</p> <p>Luteinizing hormone and androstenedione prior to laparoscopic ovarian drilling are independent predictors of spontaneous ovulation within three months of surgery. We suggest to preferentially performing laparoscopic ovarian drilling in patients with high luteinizing hormone and androstenedione levels.</p

Microbiological Lessons Learned from the Space Shuttle

After 30 years of being the centerpiece of NASA s human spacecraft, the Space Shuttle will retire. This highly successful program provided many valuable lessons for the International Space Station (ISS) and future spacecraft. Major microbiological risks to crewmembers include food, water, air, surfaces, payloads, animals, other crewmembers, and ground support personnel. Adverse effects of microorganisms are varied and can jeopardize crew health and safety, spacecraft systems, and mission objectives. Engineering practices and operational procedures can minimize the negative effects of microorganisms. To minimize problems associated with microorganisms, appropriate steps must begin in the design phase of new spacecraft or space habitats. Spacecraft design must include requirements to control accumulation of water including humidity, leaks, and condensate on surfaces. Materials used in habitable volumes must not contribute to microbial growth. Use of appropriate materials and the implementation of robust housekeeping that utilizes periodic cleaning and disinfection will prevent high levels of microbial growth on surfaces. Air filtration can ensure low levels of bioaerosols and particulates in the breathing air. The use of physical and chemical steps to disinfect drinking water coupled with filtration can provide safe drinking water. Thorough preflight examination of flight crews, consumables, and the environment can greatly reduce pathogens in spacecraft. The advances in knowledge of living and working onboard the Space Shuttle formed the foundation for environmental microbiology requirements and operations for the International Space Station (ISS) and future spacecraft. Research conducted during the Space Shuttle Program resulted in an improved understanding of the effects of spaceflight on human physiology, microbial properties, and specifically the host-microbe interactions. Host-microbe interactions are substantially affected by spaceflight. Astronaut immune functions were found to be altered. Selected microorganisms were found to become more virulent during spaceflight. The increased knowledge gained on the Space Shuttle resulted in further studies of the host-microbe interactions on the ISS to determine if countermeasures were necessary. Lessons learned from the Space Shuttle Program were integrated into the ISS resulting in the safest space habitat to date

Wanted dead or alive : high diversity of macroinvertebrates associated with living and ’dead’ Posidonia oceanica matte

The Mediterranean endemic seagrass Posidonia oceanica forms beds characterised by a dense leaf canopy and a thick root-rhizome ‘matte’. Death of P. oceanica shoots leads to exposure of the underlying matte, which can persist for many years, and is termed ‘dead’ matte. Traditionally, dead matte has been regarded as a degraded habitat. To test whether this assumption was true, the motile macroinvertebrates of adjacent living (with shoots) and dead (without shoots) matte of P. oceanica were sampled in four different plots located at the same depth (5–6 m) in Mellieha Bay, Malta (central Mediterranean). The total number of species and abundance were significantly higher (ANOVA; P<0.05 and P<0.01, respectively) in the dead matte than in living P. oceanica matte, despite the presence of the foliar canopy in the latter. Multivariate analysis (MDS) clearly showed two main groups of assemblages, corresponding to the two matte types. The amphipods Leptocheirus guttatus and Maera grossimana, and the polychaete Nereis rava contributed most to the dissimilarity between the two different matte types. Several unique properties of the dead matte contributing to the unexpected higher number of species and abundance of motile macroinvertebrates associated with this habitat are discussed. The findings have important implications for the conservation of bare P. oceanica matte, which has been generally viewed as a habitat of low ecological value.peer-reviewe

Readability estimates for commonly used health-related quality of life surveys

To estimate readability of seven commonly used health-related quality of life instruments: SF-36, HUI, EQ-5D, QWB-SA, HALex, Minnesota Living with Heart Failure Questionnaire (MLHFQ), and the NEI-VFQ-25. The Flesch–Kincaid (F–K) and Flesch Reading Ease (FRE) formulae were used to estimate readability for every item in each measure. The percentage of items that require more than 5 years of formal schooling according to F–K was 50 for the EQ-5D, 53 for the SF-36, 80 for the VFQ-25, 85 for the QWB-SA, 100 for the HUI, HALex, and the MLHFQ. The percentage of items deemed harder than “easy” according to FRE was 50 for the SF-36, 67 for the EQ-5D, 79 for the QWB-SA, 80 for the VFQ-25, 100 for the HUI, HALex, and the MLHFQ. All seven surveys have a substantial number of items with high readability levels that may not be appropriate for the general population

Quantum Criticality in Heavy Fermion Metals

Quantum criticality describes the collective fluctuations of matter undergoing a second-order phase transition at zero temperature. Heavy fermion metals have in recent years emerged as prototypical systems to study quantum critical points. There have been considerable efforts, both experimental and theoretical, which use these magnetic systems to address problems that are central to the broad understanding of strongly correlated quantum matter. Here, we summarize some of the basic issues, including i) the extent to which the quantum criticality in heavy fermion metals goes beyond the standard theory of order-parameter fluctuations, ii) the nature of the Kondo effect in the quantum critical regime, iii) the non-Fermi liquid phenomena that accompany quantum criticality, and iv) the interplay between quantum criticality and unconventional superconductivity.Comment: (v2) 39 pages, 8 figures; shortened per the editorial mandate; to appear in Nature Physics. (v1) 43 pages, 8 figures; Non-technical review article, intended for general readers; the discussion part contains more specialized topic

SHIELD: Comparing Gas and Star Formation in Low Mass Galaxies

We analyze the relationships between atomic, neutral hydrogen (HI) and star formation (SF) in the 12 low-mass SHIELD galaxies. We compare high spectral (~0.82 km/s/channel) and spatial resolution (physical resolutions of 170 pc - 700 pc) HI imaging from the VLA with H\alpha and far-ultraviolet imaging. We quantify the degree of co-spatiality between star forming regions and regions of high HI column densities. We calculate the global star formation efficiencies (SFE, $\Sigma_{\rm SFR}$ / $\Sigma_{\rm HI}$), and examine the relationships among the SFE and HI mass, HI column density, and star formation rate (SFR). The systems are consuming their cold neutral gas on timescales of order a few Gyr. While we derive an index for the Kennicutt-Schmidt relation of N ~ 0.68 $\pm$ 0.04 for the SHIELD sample as a whole, the values of N vary considerably from system to system. By supplementing SHIELD results with those from other surveys, we find that HI mass and UV-based SFR are strongly correlated over five orders of magnitude. Identification of patterns within the SHIELD sample allows us to bin the galaxies into three general categories: 1) mainly co-spatial HI and SF regions, found in systems with highest peak HI column densities and highest total HI masses, 2) moderately correlated HI and SF regions, found in systems with moderate HI column densities, and 3) obvious offsets between HI and SF peaks, found in systems with the lowest total HI masses. SF in these galaxies is dominated by stochasticity and random fluctuations in their ISM

The challenge for genetic epidemiologists: how to analyze large numbers of SNPs in relation to complex diseases

Genetic epidemiologists have taken the challenge to identify genetic polymorphisms involved in the development of diseases. Many have collected data on large numbers of genetic markers but are not familiar with available methods to assess their association with complex diseases. Statistical methods have been developed for analyzing the relation between large numbers of genetic and environmental predictors to disease or disease-related variables in genetic association studies. In this commentary we discuss logistic regression analysis, neural networks, including the parameter decreasing method (PDM) and genetic programming optimized neural networks (GPNN) and several non-parametric methods, which include the set association approach, combinatorial partitioning method (CPM), restricted partitioning method (RPM), multifactor dimensionality reduction (MDR) method and the random forests approach. The relative strengths and weaknesses of these methods are highlighted. Logistic regression and neural networks can handle only a limited number of predictor variables, depending on the number of observations in the dataset. Therefore, they are less useful than the non-parametric methods to approach association studies with large numbers of predictor variables. GPNN on the other hand may be a useful approach to select and model important predictors, but its performance to select the important effects in the presence of large numbers of predictors needs to be examined. Both the set association approach and random forests approach are able to handle a large number of predictors and are useful in reducing these predictors to a subset of predictors with an important contribution to disease. The combinatorial methods give more insight in combination patterns for sets of genetic and/or environmental predictor variables that may be related to the outcome variable. As the non-parametric methods have different strengths and weaknesses we conclude that to approach genetic association studies using the case-control design, the application of a combination of several methods, including the set association approach, MDR and the random forests approach, will likely be a useful strategy to find the important genes and interaction patterns involved in complex diseases

Kinetic temperature of massive star-forming molecular clumps measured with formaldehyde IV. The ALMA view of N113 and N159W in the LMC

We mapped the kinetic temperature structure of two massive star-forming regions, N113 and N159W, in the Large Magellanic Cloud (LMC). We have used ~1.′′6 (~0.4 pc) resolution measurements of the para-H2CO JKaKc = 303–202, 322–221, and 321–220 transitions near 218.5 GHz to constrain RADEX non local thermodynamic equilibrium models of the physical conditions. The gas kinetic temperatures derived from the para-H2CO line ratios 322–221/303–202 and 321–220/303–202 range from 28 to 105 K in N113 and 29 to 68 K in N159W. Distributions of the dense gas traced by para-H2CO agree with those of the 1.3 mm dust and Spitzer 8.0 μm emission, but they do not significantly correlate with the Hα emission. The high kinetic temperatures (Tkin ≳ 50 K) of the dense gas traced by para-H2CO appear to be correlated with the embedded infrared sources inside the clouds and/or young stellar objects in the N113 and N159W regions. The lower temperatures (Tkin < 50 K) were measured at the outskirts of the H2CO-bearing distributions of both N113 and N159W. It seems that the kinetic temperatures of the dense gas traced by para-H2CO are weakly affected by the external sources of the Hα emission. The non thermal velocity dispersions of para-H2CO are well correlated with the gas kinetic temperatures in the N113 region, implying that the higher kinetic temperature traced by para-H2CO is related to turbulence on a ~0.4 pc scale. The dense gas heating appears to be dominated by internal star formation activity, radiation, and/or turbulence. It seems that the mechanism heating the dense gas of the star-forming regions in the LMC is consistent with that in Galactic massive star-forming regions located in the Galactic plane