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We determined experimentally the complex transient optical dielectric function of a well-characterized polyelectrolyte/gold-nanoparticle composite system over a broad spectral range upon short pulse laser excitation by simultaneously measuring the time-dependent reflectance and transmittance of white light pulses with femtosecond pump-probe spectroscopy. We extracted directly the ultrafast changes in the real and imaginary parts of the effective dielectric function, epsilon(eff)(r) (omega,t)and epsilon(eff)(i) (omega,t), from the experiment. This complete experimental set of information on the time-dependent complex dielectric function challenges theories modeling the transient dielectric function of gold particles and the effective medium.
Ground-based gamma-ray astronomy has had a major breakthrough with the impressive results obtained using systems of imaging atmospheric Cherenkov telescopes. Ground-based gamma-ray astronomy has a huge potential in astrophysics, particle physics and cosmology. CTA is an international initiative to build the next generation instrument, with a factor of 5-10 improvement in sensitivity in the 100 GeV-10 TeV range and the extension to energies well below 100 GeV and above 100 TeV. CTA will consist of two arrays (one in the north, one in the south) for full sky coverage and will be operated as open observatory. The design of CTA is based on currently available technology. This document reports on the status and presents the major design concepts of CTA.
We present the Potsdam Parallel Ice Sheet Model (PISM-PIK), developed at the Potsdam Institute for Climate Impact Research to be used for simulations of large-scale ice sheet-shelf systems. It is derived from the Parallel Ice Sheet Model (Bueler and Brown, 2009). Velocities are calculated by superposition of two shallow stress balance approximations within the entire ice covered region: the shallow ice approximation (SIA) is dominant in grounded regions and accounts for shear deformation parallel to the geoid. The plug-flow type shallow shelf approximation (SSA) dominates the velocity field in ice shelf regions and serves as a basal sliding velocity in grounded regions. Ice streams can be identified diagnostically as regions with a significant contribution of membrane stresses to the local momentum balance. All lateral boundaries in PISM-PIK are free to evolve, including the grounding line and ice fronts. Ice shelf margins in particular are modeled using Neumann boundary conditions for the SSA equations, reflecting a hydrostatic stress imbalance along the vertical calving face. The ice front position is modeled using a subgrid-scale representation of calving front motion (Albrecht et al., 2011) and a physically-motivated calving law based on horizontal spreading rates. The model is tested in experiments from the Marine Ice Sheet Model Intercomparison Project (MISMIP). A dynamic equilibrium simulation of Antarctica under present-day conditions is presented in Martin et al. (2011).
We present a dynamic equilibrium simulation of the ice sheet-shelf system on Antarctica with the Potsdam Parallel Ice Sheet Model (PISM-PIK). The simulation is initialized with present-day conditions for bed topography and ice thickness and then run to steady state with constant present-day surface mass balance. Surface temperature and sub-shelf basal melt distribution are parameterized. Grounding lines and calving fronts are free to evolve, and their modeled equilibrium state is compared to observational data. A physically-motivated calving law based on horizontal spreading rates allows for realistic calving fronts for various types of shelves. Steady-state dynamics including surface velocity and ice flux are analyzed for whole Antarctica and the Ronne-Filchner and Ross ice shelf areas in particular. The results show that the different flow regimes in sheet and shelves, and the transition zone between them, are captured reasonably well, supporting the approach of superposition of SIA and SSA for the representation of fast motion of grounded ice. This approach also leads to a natural emergence of sliding-dominated flow in stream-like features in this new 3-D marine ice sheet model.
A parameterization for the motion of ice-shelf fronts on a Cartesian grid in finite-difference land-ice models is presented. The scheme prevents artificial thinning of the ice shelf at its edge, which occurs due to the finite resolution of the model. The intuitive numerical implementation diminishes numerical dispersion at the ice front and enables the application of physical boundary conditions to improve the calculation of stress and velocity fields throughout the ice-sheet-shelf system. Numerical properties of this subgrid modification are assessed in the Potsdam Parallel Ice Sheet Model (PISM-PIK) for different geometries in one and two horizontal dimensions and are verified against an analytical solution in a flow-line setup.
Background Athlete's heart as an adaptation to long-time and intensive endurance training can vary considerably between individuals. Genetic polymorphisms in the cardiological relevant insulin-like growth factor 1 (IGF1) signalling pathway seem to have an essential influence on the extent of physiological hypertrophy.
Objective Analysis of polymorphisms in the genes of IGF1, IGF1 receptor (IGF1R) and the negative regulator of the cardiac IGF1 signalling pathway, myostatin (MSTN), and their relation to left ventricular mass (LVM) of endurance athletes.
Methods In 110 elite endurance athletes or athletes with a high amount of endurance training (75 males and 35 females) and 27 male controls, which were examined by echocardiographic imaging methods and ergometric exercise-testing, the genotypes of a cytosine-adenine repeat polymorphism in the promoter region of the IGF1 gene and a G/A substitution at position 3174 in the IGF1R gene were determined. Additionally, a mutation screen of the MSTN gene was performed.
Results The polymorphisms in the IGF1 and the IGF1R gene showed a significant relation to the LVM for male (IGF1: p=0.003; IGF1R: p=0.01), but not for female athletes. The same applies to a previously unnoticed polymorphism in the 1 intron of the MSTN gene, whose deletion allele (AAA -> AA) appears to increase the myostatic effect (p=0.015). Moreover, combinations of the polymorphisms showed significant synergistic effects on the LVM of the male athletes.
Conclusions The authors' results argue for the importance of polymorphisms in the IGF1 signalling pathway in combination with MSTN on the variant degree of physiological hypertrophy of male athletes.
We present a comprehensive study of X-ray emission by, and wind properties of, massive magnetic early B-type stars. Dedicated XMM-Newton observations were obtained for three early-type B-type stars, xi(1) CMa, V2052 Oph and zeta Cas, with recently discovered magnetic fields. We report the first detection of X-ray emission from V2052 Oph and zeta Cas. The latter is one the softest X-ray sources among the early-type stars, while the former is one of the X-ray faintest. The observations show that the X-ray spectra of our programme stars are quite soft with the bulk of X-ray emitting material having a temperature of about 1 MK. We compile the complete sample of early B-type stars with detected magnetic fields to date and existing X-ray measurements, in order to study whether the X-ray emission can be used as a general proxy for stellar magnetism. We find that the X-ray properties of early massive B-type magnetic stars are diverse, and that hard and strong X-ray emission does not necessarily correlate with the presence of a magnetic field, corroborating similar conclusions reached earlier for the classical chemically peculiar magnetic Bp-Ap stars.
We analyse the ultraviolet (UV) spectra of five non-supergiant B stars with magnetic fields (tau Sco, beta Cep, xi(1) CMa, V2052 Oph and zeta Cas) by means of non-local thermodynamic equilibrium (non-LTE) iron-blanketed model atmospheres. The latter are calculated with the Potsdam Wolf-Rayet (PoWR) code, which treats the photosphere as well as the wind, and also accounts for X-rays. With the exception of t Sco, this is the first analysis of these stars by means of stellar wind models. Our models accurately fit the stellar photospheric spectra in the optical and the UV. The parameters of X-ray emission, temperature and flux are included in the model in accordance with observations. We confirm the earlier findings that the filling factors of X-ray emitting material are very high.
Our analysis reveals that the magnetic early-type B stars studied here have weak winds with velocities not significantly exceeding upsilon(esc). The mass-loss rates inferred from the analysis of UV lines are significantly lower than predicted by hydrodynamically consistent models. We find that, although the X-rays strongly affect the ionization structure of the wind, this effect is not sufficient in reducing the total radiative acceleration. When the X-rays are accounted for at the intensity and temperatures observed, there is still sufficient radiative acceleration to drive a stronger mass-loss than we empirically infer from the UV spectral lines.
The Chandra Carina Complex contains 200 known O- and B-type stars. The Chandra survey detected 68 of the 70 O stars and 61 of 127 known B0-B3 stars. We have assembled a publicly available optical/X-ray database to identify OB stars that depart from the canonical L-X/L-bol relation or whose average X-ray temperatures exceed 1 keV. Among the single O stars with high kT we identify two candidate magnetically confined wind shock sources: Tr16-22, O8.5 V, and LS 1865, O8.5 V((f)). The O4 III(fc) star HD 93250 exhibits strong, hard, variable X-rays, suggesting that it may be a massive binary with a period of > 30 days. The visual O2 If* binary HD 93129A shows soft 0.6 keV and hard 1.9 keV emission components, suggesting embedded wind shocks close to the O2 If* Aa primary and colliding wind shocks between Aa and Ab. Of the 11 known O-type spectroscopic binaries, the long orbital-period systems HD 93343, HD 93403, and QZ Car have higher shock temperatures than short-period systems such as HD 93205 and FO 15. Although the X-rays from most B stars may be produced in the coronae of unseen, low-mass pre-main-sequence companions, a dozen B stars with high L-X cannot be explained by a distribution of unseen companions. One of these, SS73 24 in the Treasure Chest cluster, is a new candidate Herbig Be star.
We have developed lists of likely B3-A0 stars (called "late B" stars) in the young cluster Trumpler 16. The following criteria were used: location within 3' of eta Car, an appropriate V and B - V combination, and proper motion (where available). Color and magnitude cuts have been made assuming an E(B - V) = 0.55 mag +/- 0.1, which is a good approximation close to the center of Trumpler 16. These lists have been cross-correlated with X-ray sources found in the Chandra Carina Complex Project. Previous studies have shown that only very rarely (if at all) do late main-sequence B stars produce X-rays. We present evidence that the X-ray-detected sources are binaries with low-mass companions, since stars less massive than 1.4 M-circle dot are strong X-ray sources at the age of the cluster. Both the median X-ray energies and X-ray luminosities of these sources are in good agreement with values for typical low-mass coronal X-ray sources. We find that 39% of the late B stars based on a list with proper motions have low-mass companions. Similarly, 32% of a sample without proper motions have low-mass companions. We discuss the X-ray detection completeness. These results on low-mass companions of intermediate-mass stars are complementary to spectroscopic and interferometric results and probe new parameter space of low-mass companions at all separations. They do not support a steeply rising distribution of mass ratios to low masses for intermediate-mass (5 M-circle dot) primaries, such as would be found by random pairing from the initial mass function.
X-ray observations of the double-binary OB-star system QZ Car (HD 93206) obtained with the Chandra X-ray Observatory over a period of roughly 2 years are presented. The respective orbits of systems A (O9.7 I+b2 v, P-A = 21 days) and B (O8 III+o9 v, P-B = 6 days) are reasonably well sampled by the observations, allowing the origin of the X-ray emission to be examined in detail. The X-ray spectra can be well fitted by an attenuated three-temperature thermal plasma model, characterized by cool, moderate, and hot plasma components at kT similar or equal to 0.2, 0.7, and 2 keV, respectively, and a circumstellar absorption of similar or equal to 0.2 x 10(22) cm(-2). Although the hot plasma component could be indicating the presence of wind-wind collision shocks in the system, the model fluxes calculated from spectral fits, with an average value of similar or equal to 7x10(-13) erg s(-1) cm(-2), do not show a clear correlation with the orbits of the two constituent binaries. A semi-analytical model of QZ Car reveals that a stable momentum balance may not be established in either system A or B. Yet, despite this, system B is expected to produce an observed X-ray flux well in excess of the observations. If one considers the wind of the O8 III star to be disrupted by mass transfer, the model and observations are in far better agreement, which lends support to the previous suggestion of mass transfer in the O8 III+o9 v binary. We conclude that the X-ray emission from QZ Car can be reasonably well accounted for by a combination of contributions mainly from the single stars and the mutual wind-wind collision between systems A and B.
We investigate the connections between the magnetic fields and the X-ray emission from massive stars. Our study shows that the X-ray properties of known strongly magnetic stars are diverse: while some comply to the predictions of the magnetically confined wind model, others do not. We conclude that strong, hard, and variable X-ray emission may be a sufficient attribute of magnetic massive stars, but it is not a necessary one. We address the general properties of X-ray emission from "normal" massive stars, especially the long standing mystery about the correlations between the parameters of X-ray emission and fundamental stellar properties. The recent development in stellar structure modeling shows that small-scale surface magnetic fields may be common. We suggest a "hybrid" scenario which could explain the X-ray emission from massive stars by a combination of magnetic mechanisms on the surface and shocks in the stellar wind. The magnetic mechanisms and the wind shocks are triggered by convective motions in sub-photospheric layers. This scenario opens the door for a natural explanation of the well established correlation between bolometric and X-ray luminosities.
We have obtained spectropolarimetric observations of two Wolf-Rayet stars, WR 135 (WC8) and WR 136 (WN6), with the 6-m Russian telescope in July 2009 and July 2010. We have studied the He II 5412 angstrom line region, which contains also the C IV 5469 angstrom line (for WR 135 only). Our goals were to investigate the rapid line-profile variability (LPV) in WR star spectra and to search for magnetic fields. We find small amplitude emission peaks moving from the center of He II line to its wings during the night in spectra of both stars. These emission peaks are likely a signature of accelerating clumps in the stellar wind. We obtained upper limits of the magnetic field strength: approximate to 200G for WR 135 and approximate to 50G for WR 136. (C) 2011 WILEY-VCH Verlag GmbH&Co. KGaA, Weinheim
We report on the status of our spectropolarimetric observations of massive stars. During the last years, we have discovered magnetic fields in many objects of the upper main sequence, including Be stars, beta Cephei and Slowly Pulsating B stars, and a dozen O stars. Since the effects of those magnetic fields have been found to be substantial by recent models, we are looking into their impact on stellar rotation, pulsation, stellar winds, and chemical abundances. Accurate studies of the age, environment, and kinematic characteristics of the magnetic stars are also promising to give us new insight into the origin of the magnetic fields. Furthermore, longer time series of magnetic field measurements allow us to observe the temporal variability of the magnetic field and to deduce the stellar rotation period and the magnetic field geometry. Studies of the magnetic field in massive stars are indispensable to understand the conditions controlling the presence of those fields and their implications on the stellar physical parameters and evolution.
The star zeta Ophiuchi is one of the brightest massive stars in the northern hemisphere and was intensively studied in various wavelength domains. The currently available observational material suggests that certain observed phenomena are related to the presence of a magnetic field. We acquired spectropolarimetric observations of zeta Oph with FORS 1 mounted on the 8-m Kueyen telescope of the VLT to investigate if a magnetic field is indeed present in this star. Using all available absorption lines, we detect a mean longitudinal magnetic field < B(z)>(all) = 141 +/- 45 G, confirming the magnetic nature of this star. We review the X-ray properties of zeta Oph with the aim to understand whether the X-ray emission of zeta Oph is dominated by magnetic or by wind instability processes.
Biology has made great progress in identifying and measuring the building blocks of life. The availability of high-throughput methods in molecular biology has dramatically accelerated the growth of biological knowledge for various organisms. The advancements in genomic, proteomic and metabolomic technologies allow for constructing complex models of biological systems. An increasing number of biological repositories is available on the web, incorporating thousands of biochemical reactions and genetic regulations. Systems Biology is a recent research trend in life science, which fosters a systemic view on biology. In Systems Biology one is interested in integrating the knowledge from all these different sources into models that capture the interaction of these entities. By studying these models one wants to understand the emerging properties of the whole system, such as robustness. However, both measurements as well as biological networks are prone to considerable incompleteness, heterogeneity and mutual inconsistency, which makes it highly non-trivial to draw biologically meaningful conclusions in an automated way. Therefore, we want to promote Answer Set Programming (ASP) as a tool for discrete modeling in Systems Biology. ASP is a declarative problem solving paradigm, in which a problem is encoded as a logic program such that its answer sets represent solutions to the problem. ASP has intrinsic features to cope with incompleteness, offers a rich modeling language and highly efficient solving technology. We present ASP solutions, for the analysis of genetic regulatory networks, determining consistency with observed measurements and identifying minimal causes for inconsistency. We extend this approach for computing minimal repairs on model and data that restore consistency. This method allows for predicting unobserved data even in case of inconsistency. Further, we present an ASP approach to metabolic network expansion. This approach exploits the easy characterization of reachability in ASP and its various reasoning methods, to explore the biosynthetic capabilities of metabolic reaction networks and generate hypotheses for extending the network. Finally, we present the BioASP library, a Python library which encapsulates our ASP solutions into the imperative programming paradigm. The library allows for an easy integration of ASP solution into system rich environments, as they exist in Systems Biology.
Answer Set Programming (ASP) is an emerging paradigm for declarative programming, in which a computational problem is specified by a logic program such that particular models, called answer sets, match solutions. ASP faces a growing range of applications, demanding for high-performance tools able to solve complex problems. ASP integrates ideas from a variety of neighboring fields. In particular, automated techniques to search for answer sets are inspired by Boolean Satisfiability (SAT) solving approaches. While the latter have firm proof-theoretic foundations, ASP lacks formal frameworks for characterizing and comparing solving methods. Furthermore, sophisticated search patterns of modern SAT solvers, successfully applied in areas like, e.g., model checking and verification, are not yet established in ASP solving. We address these deficiencies by, for one, providing proof-theoretic frameworks that allow for characterizing, comparing, and analyzing approaches to answer set computation. For another, we devise modern ASP solving algorithms that integrate and extend state-of-the-art techniques for Boolean constraint solving. We thus contribute to the understanding of existing ASP solving approaches and their interconnections as well as to their enhancement by incorporating sophisticated search patterns. The central idea of our approach is to identify atomic as well as composite constituents of a propositional logic program with Boolean variables. This enables us to describe fundamental inference steps, and to selectively combine them in proof-theoretic characterizations of various ASP solving methods. In particular, we show that different concepts of case analyses applied by existing ASP solvers implicate mutual exponential separations regarding their best-case complexities. We also develop a generic proof-theoretic framework amenable to language extensions, and we point out that exponential separations can likewise be obtained due to case analyses on them. We further exploit fundamental inference steps to derive Boolean constraints characterizing answer sets. They enable the conception of ASP solving algorithms including search patterns of modern SAT solvers, while also allowing for direct technology transfers between the areas of ASP and SAT solving. Beyond the search for one answer set of a logic program, we address the enumeration of answer sets and their projections to a subvocabulary, respectively. The algorithms we develop enable repetition-free enumeration in polynomial space without being intrusive, i.e., they do not necessitate any modifications of computations before an answer set is found. Our approach to ASP solving is implemented in clasp, a state-of-the-art Boolean constraint solver that has successfully participated in recent solver competitions. Although we do here not address the implementation techniques of clasp or all of its features, we present the principles of its success in the context of ASP solving.
Building biological models by inferring functional dependencies from experimental data is an important issue in Molecular Biology. To relieve the biologist from this traditionally manual process, various approaches have been proposed to increase the degree of automation. However, available approaches often yield a single model only, rely on specific assumptions, and/or use dedicated, heuristic algorithms that are intolerant to changing circumstances or requirements in the view of the rapid progress made in Biotechnology. Our aim is to provide a declarative solution to the problem by appeal to Answer Set Programming (ASP) overcoming these difficulties. We build upon an existing approach to Automatic Network Reconstruction proposed by part of the authors. This approach has firm mathematical foundations and is well suited for ASP due to its combinatorial flavor providing a characterization of all models explaining a set of experiments. The usage of ASP has several benefits over the existing heuristic algorithms. First, it is declarative and thus transparent for biological experts. Second, it is elaboration tolerant and thus allows for an easy exploration and incorporation of biological constraints. Third, it allows for exploring the entire space of possible models. Finally, our approach offers an excellent performance, matching existing, special-purpose systems.
We introduce an approach to detecting inconsistencies in large biological networks by using answer set programming. To this end, we build upon a recently proposed notion of consistency between biochemical/genetic reactions and high-throughput profiles of cell activity. We then present an approach based on answer set programming to check the consistency of large-scale data sets. Moreover, we extend this methodology to provide explanations for inconsistencies by determining minimal representations of conflicts. In practice, this can be used to identify unreliable data or to indicate missing reactions.
Indoor position estimation constitutes a central task in home-based assisted living environments. Such environments often rely on a heterogeneous collection of low-cost sensors whose diversity and lack of precision has to be compensated by advanced techniques for localization and tracking. Although there are well established quantitative methods in robotics and neighboring fields for addressing these problems, they lack advanced knowledge representation and reasoning capacities. Such capabilities are not only useful in dealing with heterogeneous and incomplete information but moreover they allow for a better inclusion of semantic information and more general homecare and patient-related knowledge. We address this problem and investigate how state-of-the-art localization and tracking methods can be combined with Answer Set Programming, as a popular knowledge representation and reasoning formalism. We report upon a case-study and provide a first experimental evaluation of knowledge-based position estimation both in a simulated as well as in a real setting.
Preference handling and optimization are indispensable means for addressing nontrivial applications in Answer Set Programming (ASP). However, their implementation becomes difficult whenever they bring about a significant increase in computational complexity. As a consequence, existing ASP systems do not offer complex optimization capacities, supporting, for instance, inclusion-based minimization or Pareto efficiency. Rather, such complex criteria are typically addressed by resorting to dedicated modeling techniques, like saturation. Unlike the ease of common ASP modeling, however, these techniques are rather involved and hardly usable by ASP laymen. We address this problem by developing a general implementation technique by means of meta-prpogramming, thus reusing existing ASP systems to capture various forms of qualitative preferences among answer sets. In this way, complex preferences and optimization capacities become readily available for ASP applications.
Building biological models by inferring functional dependencies from experimental data is an important issue in Molecular Biology. To relieve the biologist from this traditionally manual process, various approaches have been proposed to increase the degree of automation. However, available approaches often yield a single model only, rely on specific assumptions, and/or use dedicated, heuristic algorithms that are intolerant to changing circumstances or requirements in the view of the rapid progress made in Biotechnology. Our aim is to provide a declarative solution to the problem by appeal to Answer Set Programming (ASP) overcoming these difficulties. We build upon an existing approach to Automatic Network Reconstruction proposed by part of the authors. This approach has firm mathematical foundations and is well suited for ASP due to its combinatorial flavor providing a characterization of all models explaining a set of experiments. The usage of ASP has several benefits over the existing heuristic algorithms. First, it is declarative and thus transparent for biological experts. Second, it is elaboration tolerant and thus allows for an easy exploration and incorporation of biological constraints. Third, it allows for exploring the entire space of possible models. Finally, our approach offers an excellent performance, matching existing, special-purpose systems.
We introduce an approach to detecting inconsistencies in large biological networks by using answer set programming. To this end, we build upon a recently proposed notion of consistency between biochemical/genetic reactions and high-throughput profiles of cell activity. We then present an approach based on answer set programming to check the consistency of large-scale data sets. Moreover, we extend this methodology to provide explanations for inconsistencies by determining minimal representations of conflicts. In practice, this can be used to identify unreliable data or to indicate missing reactions.
Preference handling and optimization are indispensable means for addressing nontrivial applications in Answer Set Programming (ASP). However, their implementation becomes difficult whenever they bring about a significant increase in computational complexity. As a consequence, existing ASP systems do not offer complex optimization capacities, supporting, for instance, inclusion-based minimization or Pareto efficiency. Rather, such complex criteria are typically addressed by resorting to dedicated modeling techniques, like saturation. Unlike the ease of common ASP modeling, however, these techniques are rather involved and hardly usable by ASP laymen. We address this problem by developing a general implementation technique by means of meta-prpogramming, thus reusing existing ASP systems to capture various forms of qualitative preferences among answer sets. In this way, complex preferences and optimization capacities become readily available for ASP applications.
The key empirical property of the X-ray emission from O stars is a strong correlation between the bolometric and X-ray luminosities. In the framework of the Chandra Carina Complex Project, 129 O and B stars have been detected as X-ray sources; 78 of those, all with spectral type earlier than B3, have enough counts for at least a rough X-ray spectral characterization. This leads to an estimate of the L-X-L-BOL ratio for an exceptional number of 60 O stars belonging to the same region and triples the number of Carina massive stars studied spectroscopically in X-rays. The derived log(L-X/L-BOL) is -7.26 for single objects, with a dispersion of only 0.21 dex. Using the properties of hot massive stars listed in the literature, we compare the X-ray luminosities of different types of objects. In the case of O stars, the L-X-L-BOL ratios are similar for bright and faint objects, as well as for stars of different luminosity classes or spectral types. Binaries appear only slightly harder and slightly more luminous in X-rays than single objects; the differences are not formally significant (at the 1% level), except for the L-X-L-BOL ratio in the medium (1.0-2.5 keV) energy band. Weak-wind objects have similar X-ray luminosities but they display slightly softer spectra compared with "normal" O stars with the same bolometric luminosity. Discarding three overluminous objects, we find a very shallow trend of harder emission in brighter objects. The properties of the few B stars bright enough to yield some spectral information appear to be different overall (constant X-ray luminosities, harder spectra), hinting that another mechanism for producing X-rays, besides wind shocks, might be at work. However, it must be stressed that the earliest and X-ray brightest among these few detected objects are similar to the latest O stars, suggesting a possibly smooth transition between the two processes.
The Great Nebula in Carina provides an exceptional view into the violent massive star formation and feedback that typifies giant H II regions and starburst galaxies. We have mapped the Carina star-forming complex in X-rays, using archival Chandra data and a mosaic of 20 new 60 ks pointings using the Chandra X-ray Observatory's Advanced CCD Imaging Spectrometer, as a testbed for understanding recent and ongoing star formation and to probe Carina's regions of bright diffuse X-ray emission. This study has yielded a catalog of properties of > 14,000 X-ray point sources;> 9800 of them have multiwavelength counterparts. Using Chandra's unsurpassed X-ray spatial resolution, we have separated these point sources from the extensive, spatially-complex diffuse emission that pervades the region; X-ray properties of this diffuse emission suggest that it traces feedback from Carina's massive stars. In this introductory paper, we motivate the survey design, describe the Chandra observations, and present some simple results, providing a foundation for the 15 papers that follow in this special issue and that present detailed catalogs, methods, and science results.
We address the problem of Finite Model Computation (FMC) of first-order theories and show that FMC can efficiently and transparently be solved by taking advantage of a recent extension of Answer Set Programming (ASP), called incremental Answer Set Programming (iASP). The idea is to use the incremental parameter in iASP programs to account for the domain size of a model. The FMC problem is then successively addressed for increasing domain sizes until an answer set, representing a finite model of the original first-order theory, is found. We implemented a system based on the iASP solver iClingo and demonstrate its competitiveness by showing that it slightly outperforms the winner of the FNT division of CADE's 2009 Automated Theorem Proving (ATP) competition on the respective benchmark collection.
We present XMM-Newton and Chandra observations of the born-again planetary nebula A 30. These X-ray observations reveal a bright unresolved source at the position of the central star whose X-ray luminosity exceeds by far the model expectations for photospheric emission and for shocks within the stellar wind. We suggest that a “born-again hot bubble” may be responsible for this X-ray emission. Diffuse X-ray emission associated with the petal-like features and one of the H-poor knots seen in the optical is also found. The weakened emission of carbon lines in the spectrum of the diffuse emission can be interpreted as the dilution of stellar wind by mass-loading or as the detection of material ejected during a very late thermal pulse.
To understand the evolution and morphology of planetary nebulae, a detailed knowledge of their central stars is required. Central stars that exhibit emission lines in their spectra, indicating stellar mass-loss allow to study the evolution of planetary nebulae in action. Emission line central stars constitute about 10 % of all central stars. Half of them are practically hydrogen-free Wolf-Rayet type central stars of the carbon sequence, [WC], that show strong emission lines of carbon and oxygen in their spectra. In this contribution we address the weak emission-lines central stars (wels). These stars are poorly analyzed and their hydrogen content is mostly unknown. We obtained optical spectra, that include the important Balmer lines of hydrogen, for four weak emission line central stars. We present the results of our analysis, provide spectral classification and discuss possible explanations for their formation and evolution.
Identification of a novel heteroglycan-interacting protein, HIP 1.3, from Arabidopsis thaliana
(2011)
Plastidial degradation of transitory starch yields mainly maltose and glucose. Following the export into the cytosol, maltose acts as donor for a glucosyl transfer to cytosolic heteroglycans as mediated by a cytosolic transglucosidase (DPE2; EC 2.4.1.25) and the second glucosyl residue is liberated as glucose. The cytosolic phosphorylase (Pho2/PHS2; EC 2.4.1.1) also interacts with heteroglycans using the same intramolecular sites as DPE2. Thus, the two glucosyl transferases interconnect the cytosolic pools of glucose and glucose 1-phosphate. Due to the complex monosaccharide pattern, other heteroglycan-interacting proteins (Hips) are expected to exist.
Identification of those proteins was approached by using two types of affinity chromatography. Heteroglycans from leaves of Arabidopsis thaliana (Col-0) covalently bound to Sepharose served as ligands that were reacted with a complex mixture of buffer-soluble proteins from Arabidopsis leaves. Binding proteins were eluted by sodium chloride. For identification, SDS-PAGE, tryptic digestion and MALDI-TOF analyses were applied. A strongly interacting polypeptide (approximately 40 kDa; designated as HIP1.3) was observed as product of locus At1g09340. Arabidopsis mutants deficient in HIP1.3 were reduced in growth and contained heteroglycans displaying an altered monosaccharide pattern. Wild type plants express HIP1.3 most strongly in leaves. As revealed by immuno fluorescence, HIP1.3 is located in the cytosol of mesophyll cells but mostly associated with the cytosolic surface of the chloroplast envelope membranes. In an HIP1.3-deficient mutant the immunosignal was undetectable. Metabolic profiles from leaves of this mutant and wild type plants as well were determined by GC-MS. As compared to the wild type control, more than ten metabolites, such as ascorbic acid, fructose, fructose bisphosphate, glucose, glycine, were elevated in darkness but decreased in the light. Although the biochemical function of HIP1.3 has not yet been elucidated, it is likely to possess an important function in the central carbon metabolism of higher plants.
Maturation of fleshy fruits such as tomato (Solanum lycopersicum) is subject to tight genetic control. Here we describe the development of a quantitative real-time PCR platform that allows accurate quantification of the expression level of approximately 1000 tomato transcription factors. In addition to utilizing this novel approach, we performed cDNA microarray analysis and metabolite profiling of primary and secondary metabolites using GC-MS and LC-MS, respectively. We applied these platforms to pericarp material harvested throughout fruit development, studying both wild-type Solanum lycopersicum cv. Ailsa Craig and the hp1 mutant. This mutant is functionally deficient in the tomato homologue of the negative regulator of the light signal transduction gene DDB1 from Arabidopsis, and is furthermore characterized by dramatically increased pigment and phenolic contents. We choose this particular mutant as it had previously been shown to have dramatic alterations in the content of several important fruit metabolites but relatively little impact on other ripening phenotypes. The combined dataset was mined in order to identify metabolites that were under the control of these transcription factors, and, where possible, the respective transcriptional regulation underlying this control. The results are discussed in terms of both programmed fruit ripening and development and the transcriptional and metabolic shifts that occur in parallel during these processes.