A pitfall of piecewise-polytropic equation of state inference

The only messenger radiation in the Universe which one can use to statistically probe the Equation of State (EOS) of cold dense matter is that originating from the near-field vicinities of compact stars. Constraining gravitational masses and equatorial radii of rotating compact stars is a major goal for current and future telescope missions, with a primary purpose of constraining the EOS. From a Bayesian perspective it is necessary to carefully discuss prior definition; in this context a complicating issue is that in practice there exist pathologies in the general relativistic mapping between spaces of local (interior source matter) and global (exterior spacetime) parameters. In a companion paper, these issues were raised on a theoretical basis. In this study we reproduce a probability transformation procedure from the literature in order to map a joint posterior distribution of Schwarzschild gravitational masses and radii into a joint posterior distribution of EOS parameters. We demonstrate computationally that EOS parameter inferences are sensitive to the choice to define a prior on a joint space of these masses and radii, instead of on a joint space interior source matter parameters. We focus on the piecewise-polytropic EOS model, which is currently standard in the field of astrophysical dense matter study. We discuss the implications of this issue for the field.Comment: 16 pages, 9 figures. Accepted for publication in MNRA

Robustness Verification for Classifier Ensembles

We give a formal verification procedure that decides whether a classifier ensemble is robust against arbitrary randomized attacks. Such attacks consist of a set of deterministic attacks and a distribution over this set. The robustness-checking problem consists of assessing, given a set of classifiers and a labelled data set, whether there exists a randomized attack that induces a certain expected loss against all classifiers. We show the NP-hardness of the problem and provide an upper bound on the number of attacks that is sufficient to form an optimal randomized attack. These results provide an effective way to reason about the robustness of a classifier ensemble. We provide SMT and MILP encodings to compute optimal randomized attacks or prove that there is no attack inducing a certain expected loss. In the latter case, the classifier ensemble is provably robust. Our prototype implementation verifies multiple neural-network ensembles trained for image-classification tasks. The experimental results using the MILP encoding are promising both in terms of scalability and the general applicability of our verification procedure

Unraveling the senses of Phytophthora; leads to novel control strategies?

Oomycetes cause devastating diseases on plants and animals. They cause major yield losses in many crop plants and their control heavily depends on agrochemicals. This is certainly true for the potato late blight pathogen Phytophthora infestans. Strong concerns about adverse effects of agrochemicals on food safety and environment are incentives for the development of novel, environmental friendly control strategies preferably based on natural products. Cyclic lipopeptides (CLPs) were recently discovered as a new class of natural compounds with strong activities against oomycetes including Phytophthora. CLPs lyse zoospores, inhibit mycelial growth and effectively reduce late blight disease. In order to unravel how Phytophthora senses CLPs and other environmental signals we follow two approaches. On the one hand, we monitor genome wide changes in gene expression induced by CLPs with the aim to identify the cellular pathways targeted by CLPs. On the other hand, we analyse components of ubiquitous signal transduction pathways with the aim to identify features that are unique for Phytophthora or oomycetes and, hence, could be suitable targets for novel anti-oomycete agents. Mining and comparing whole genome sequences have revealed that Phytophthora harbours many novel phospholipid modifying enzymes, unique for oomycetes. They have aberrant combinations of catalytic and regulatory domains occasionally combined with transmembrane domains. The latter resemble receptors that might be activated by extracellular ligands. Phospholipids, the substrates of these enzymes, are structural membrane components that also function in signalling. Together these findings open new avenues of research aimed at target-discovery in oomycetes

Searching Spontaneous Conversational Speech

The ACM SIGIR Workshop on Searching Spontaneous Conversational Speech was held as part of the 2007 ACM SIGIR Conference in Amsterdam.\ud The workshop program was a mix of elements, including a keynote speech, paper presentations and panel discussions. This brief report describes the organization of this workshop and summarizes the discussions

Brain connectivity in preterm infants

Preterm infants are at increased risk for neurological disabilities and cognitive dysfunction at later age. Electroencephalography (EEG) is a useful method for assessing neurological function and prognosis. In the very preterm infant (below 32 weeks gestation), the EEG background activity is characterized by discontinuity, instability and fragmentation. With advancing age this background becomes more continuous. EEG spectral power analyses in very preterm infants show a maturational change from high-amplitude low-frequency waves to low-amplitude high-frequency waves. The frequency spectrum of an EEG is divided in ?newborn(0-2 Hz), ?newborn (2-6 Hz), ?newborn (6-13 Hz) and ?newborn (13-30 Hz) band. Hence, in preterm infants EEG spectral power decreases with age, with a shift from the lower (delta) to the higher frequency (alpha, beta) content of the EEG. During normal maturation different developmental processes occur in the anatomy, e.g. myelination and formation of interneural connections. The main anatomical structures enabling connections between the hemispheres are the corpus callosum (the direct highway between left and right hemispheres) and thalamo-cortical connections (the local secondary roadmap between the hemispheres with subcortical deeper brain structures as interface). Increased anatomical connectivity between brain areas may result in more functional connectivity, assessed by EEG signal shape similarity between brain regions. The goal of this thesis was to quantify the neuronal connectivity as a function of postmenstrual age (PMA). EEG cross-correlation analyses between homologous channels of brain hemispheres were calculated to study the peak correlation value and corresponding lag time as function of PMA.In this study 36 preterm neonates with appropriate weight for gestation and a normal follow-up at the age of five years were included. For comparison a set of 9 preterm infants with abnormal neurological follow-up was included. Beside these infants, two infants were studied with no interhemispherical connection between the hemispheres, a condition known as agenesis of the corpus callosum.The neonatal EEGs were obtained by the end of the first week of life. The reduced 10-20 EEG montage system was used for measuring the EEGs. Five bipolar channels at homologous positions on both brain hemispheres were used for the cross-correlation analysis. Each EEG recording was divided into 8 second epochs, in which for every epoch, the maximum correlation value and corresponding lag time was determined. In each EEG recording, the median correlation and time lag value was calculated from the 8 second epochs. Linear regression analysis was used to study the influence of postmenstrual age on the time domain parameters. The correlation values significantly decreased with increasing PMA for all the channels. With increasing PMA, three of the five bipolar channels showed a significant change in lag time. The frontal-temporal channel showed an increase, while the other temporal channels showed a decrease as a function of PMA. Cross-correlation analysis showed no difference in preterm infants with normal and abnormal follow-up. Correlation values and lag time of the two infants with corpus callosum agenesis were comparable with the other subjects. For all spectral power frequency, the correlation values decreased with PMA. For higher frequency bands the correlation values were lower. The observed trend for the burst showed a similar trend as the whole EEG. We observed a significant decrease of the correlation values for all channels, indicating a loss of similarity in signal shape. No uniform change was observed for the corresponding time lag, indicating no uniform changes in signal conductivity. No distinction could be made between infants with an intact or absent corpus callosum. This may indicate that interhemispherical EEG cross-correlation is not influenced by the presence of a corpus callosum and that other circuitries are involved. Head growth (increasing electrode position) only partially explains the lag time changes we observed. A limitation of the methodology is the low spatial resolution in EEG electrode position. We speculate that the complex process of maturation in preterm infants, including myelination, increasing interneural connections, development excitatory and inhibitory circuitries lead to a complex signal feedback system that may be more important than just the direct interhemispherical connection. Preterm infants are at increased risk for neurological disabilities and cognitive dysfunction at later age. Electroencephalography (EEG) is a useful method for assessing neurological function and prognosis. In the very preterm infant (below 32 weeks gestation), the EEG background activity is characterized by discontinuity, instability and fragmentation. With advancing age this background becomes more continuous. EEG spectral power analyses in very preterm infants show a maturational change from high-amplitude low-frequency waves to low-amplitude high-frequency waves. The frequency spectrum of an EEG is divided in ?newborn(0-2 Hz), ?newborn (2-6 Hz), ?newborn (6-13 Hz) and ?newborn (13-30 Hz) band. Hence, in preterm infants EEG spectral power decreases with age, with a shift from the lower (delta) to the higher frequency (alpha, beta) content of the EEG. During normal maturation different developmental processes occur in the anatomy, e.g. myelination and formation of interneural connections. The main anatomical structures enabling connections between the hemispheres are the corpus callosum (the direct highway between left and right hemispheres) and thalamo-cortical connections (the local secondary roadmap between the hemispheres with subcortical deeper brain structures as interface). Increased anatomical connectivity between brain areas may result in more functional connectivity, assessed by EEG signal shape similarity between brain regions. The goal of this thesis was to quantify the neuronal connectivity as a function of postmenstrual age (PMA). EEG cross-correlation analyses between homologous channels of brain hemispheres were calculated to study the peak correlation value and corresponding lag time as function of PMA.In this study 36 preterm neonates with appropriate weight for gestation and a normal follow-up at the age of five years were included. For comparison a set of 9 preterm infants with abnormal neurological follow-up was included. Beside these infants, two infants were studied with no interhemispherical connection between the hemispheres, a condition known as agenesis of the corpus callosum.The neonatal EEGs were obtained by the end of the first week of life. The reduced 10-20 EEG montage system was used for measuring the EEGs. Five bipolar channels at homologous positions on both brain hemispheres were used for the cross-correlation analysis. Each EEG recording was divided into 8 second epochs, in which for every epoch, the maximum correlation value and corresponding lag time was determined. In each EEG recording, the median correlation and time lag value was calculated from the 8 second epochs. Linear regression analysis was used to study the influence of postmenstrual age on the time domain parameters. The correlation values significantly decreased with increasing PMA for all the channels. With increasing PMA, three of the five bipolar channels showed a significant change in lag time. The frontal-temporal channel showed an increase, while the other temporal channels showed a decrease as a function of PMA. Cross-correlation analysis showed no difference in preterm infants with normal and abnormal follow-up. Correlation values and lag time of the two infants with corpus callosum agenesis were comparable with the other subjects. For all spectral power frequency, the correlation values decreased with PMA. For higher frequency bands the correlation values were lower. The observed trend for the burst showed a similar trend as the whole EEG. We observed a significant decrease of the correlation values for all channels, indicating a loss of similarity in signal shape. No uniform change was observed for the corresponding time lag, indicating no uniform changes in signal conductivity. No distinction could be made between infants with an intact or absent corpus callosum. This may indicate that interhemispherical EEG cross-correlation is not influenced by the presence of a corpus callosum and that other circuitries are involved. Head growth (increasing electrode position) only partially explains the lag time changes we observed. A limitation of the methodology is the low spatial resolution in EEG electrode position. We speculate that the complex process of maturation in preterm infants, including myelination, increasing interneural connections, development excitatory and inhibitory circuitries lead to a complex signal feedback system that may be more important than just the direct interhemispherical connection