Massive Stellar Content of the Galactic Supershell GSH 305+01-24

The distribution of OB stars along with that of H$\alpha$, $^{12}$CO, dust infrared emission, and neutral hydrogen is carried out in order to provide a more complete picture of interactions of the young massive stars and the observed supershell GSH 305+01-24. The studied field is located between $299^\circ \le l \le 311^\circ$ and $-5^\circ \le b \le 7^\circ$. The investigation is based on nearly 700 O-B9 stars with $uvby\beta$ photometry currently available. The derived stellar physical parameters were used to establish a homogeneous scale for the distances and extinction of light for major apparent groups and layers of foreground and background stars in Centaurus and study the interaction with the surrounding interstellar medium. The distance to the entire Centaurus star-forming complex is revised and a maximum of the OB-star distance distribution is found at 1.8$\pm$0.4 (r.m.s) kpc. The massive star component of GSH 305+01-24 is identified at about 85-90 % completeness up to 11.5-12 mag. The projected coincidence of the OB stars with the shell and the similarities between the shell's morphology and the OB-star distribution indicate a strong interaction of the stellar winds with the superbubble material. We demonstrate that these stars contribute a sufficient wind injection energy in order to explain the observed size and expansion velocity of the supershell. The derived stellar ages suggest an age gradient over the Coalsack Loop. A continuous star-formation might be taking place within the shell with the youngest stars located at its periphery and the open cluster NGC 4755 being the oldest. A layer of very young stars at 1 kpc is detected and its connection to both GSH 305+01-24 and the foreground GSH 304-00-12 H I shells is investigated.Comment: Accepted for publication in A&A. Paper consists of 11 pages, 3 tables and 9 figures. Table 1 and Table 3 will only be available from CD

Unlabeled sample compression schemes and corner peelings for ample and maximum classes

We examine connections between combinatorial notions that arise in machine learning and topological notions in cubical/simplicial geometry. These connections enable to export results from geometry to machine learning. Our first main result is based on a geometric construction by Tracy Hall (2004) of a partial shelling of the cross-polytope which can not be extended. We use it to derive a maximum class of VC dimension 3 that has no corners. This refutes several previous works in machine learning from the past 11 years. In particular, it implies that all previous constructions of optimal unlabeled sample compression schemes for maximum classes are erroneous. On the positive side we present a new construction of an unlabeled sample compression scheme for maximum classes. We leave as open whether our unlabeled sample compression scheme extends to ample (a.k.a. lopsided or extremal) classes, which represent a natural and far-reaching generalization of maximum classes. Towards resolving this question, we provide a geometric characterization in terms of unique sink orientations of the 1-skeletons of associated cubical complexes

Characterisation of materials through x-ray mapping

Scanning electron microscopy (SEM) energy dispersive spectroscopy (EDS, wavelength dispersive spectroscopy (WDS) and the conbination of these techniques through x-ray mapping (XRM) have become excellent tool for characterising the distribution of elements and phases in materials. Quantitative x-ray mapping (QXRM) enables reliable quantitative results that cna be an order of magnitude better than traditional analysis and is also far superior to regions of interest x-ray maps(ROIM) where low levels of an element overlaps are present

Low noise high performance 50nm T-gate metamorphic HEMT with cut-off frequency f_T of 440 GHz for millimeterwave imaging receivers applications

The 50 nm m-HEMT exhibits extremely high f<sub>T</sub>, of 440GHz, low F<sub>min</sub> of 0.7 dB, associated gain of 13 dB at 26 GHz with an exceptionally high Id of 200 mA/mm and gm of 950 ms/mm at low noise biased point

Hypothesis Testing in Feedforward Networks with Broadcast Failures

Consider a countably infinite set of nodes, which sequentially make decisions between two given hypotheses. Each node takes a measurement of the underlying truth, observes the decisions from some immediate predecessors, and makes a decision between the given hypotheses. We consider two classes of broadcast failures: 1) each node broadcasts a decision to the other nodes, subject to random erasure in the form of a binary erasure channel; 2) each node broadcasts a randomly flipped decision to the other nodes in the form of a binary symmetric channel. We are interested in whether there exists a decision strategy consisting of a sequence of likelihood ratio tests such that the node decisions converge in probability to the underlying truth. In both cases, we show that if each node only learns from a bounded number of immediate predecessors, then there does not exist a decision strategy such that the decisions converge in probability to the underlying truth. However, in case 1, we show that if each node learns from an unboundedly growing number of predecessors, then the decisions converge in probability to the underlying truth, even when the erasure probabilities converge to 1. We also derive the convergence rate of the error probability. In case 2, we show that if each node learns from all of its previous predecessors, then the decisions converge in probability to the underlying truth when the flipping probabilities of the binary symmetric channels are bounded away from 1/2. In the case where the flipping probabilities converge to 1/2, we derive a necessary condition on the convergence rate of the flipping probabilities such that the decisions still converge to the underlying truth. We also explicitly characterize the relationship between the convergence rate of the error probability and the convergence rate of the flipping probabilities

Long-Range Temporal Correlations in Resting State Beta Oscillations are Reduced in Schizophrenia

Symptoms of schizophrenia (SCZ) are likely to be generated by genetically mediated synaptic dysfunction, which contribute to large-scale functional neural dysconnectivity. Recent electrophysiological studies suggest that this dysconnectivity is present not only at a spatial level but also at a temporal level, operationalized as long-range temporal correlations (LRTCs). Previous research suggests that alpha and beta frequency bands have weaker temporal stability in people with SCZ. This study sought to replicate these findings with high-density electroencephalography (EEG), enabling a spatially more accurate analysis of LRTC differences, and to test associations with characteristic SCZ symptoms and cognitive deficits. A 128-channel EEG was used to record eyes-open resting state brain activity of 23 people with SCZ and 24 matched healthy controls (HCs). LRTCs were derived for alpha (8–12 Hz) and beta (13–25 Hz) frequency bands. As an exploratory analysis, LRTC was source projected using sLoreta. People with SCZ showed an area of significantly reduced beta-band LRTC compared with HCs over bilateral posterior regions. There were no between-group differences in alpha-band activity. Individual symptoms of SCZ were not related to LRTC values nor were cognitive deficits. The study confirms that people with SCZ have reduced temporal stability in the beta frequency band. The absence of group differences in the alpha band may be attributed to the fact that people had, in contrast to previous studies, their eyes open in the current study. Taken together, our study confirms the utility of LRTC as a marker of network instability in people with SCZ and provides a novel empirical perspective for future examinations of network dysfunction salience in SCZ research