Planets opening dust gaps in gas disks

We investigate the interaction of gas and dust in a protoplanetary disk in the presence of a massive planet using a new two-fluid hydrodynamics code. In view of future observations of planet-forming disks we focus on the condition for gap formation in the dust fluid. While only planets more massive than 1 Jupiter mass (MJ) open up a gap in the gas disk, we find that a planet of 0.1 MJ already creates a gap in the dust disk. This makes it easier to find lower-mass planets orbiting in their protoplanetary disk if there is a significant population of mm-sized particles.Comment: 5 pages, 3 figures, accepted for publication in A&A Letter

Bounds on Quantum Correlations in Bell Inequality Experiments

Bell inequality violation is one of the most widely known manifestations of entanglement in quantum mechanics; indicating that experiments on physically separated quantum mechanical systems cannot be given a local realistic description. However, despite the importance of Bell inequalities, it is not known in general how to determine whether a given entangled state will violate a Bell inequality. This is because one can choose to make many different measurements on a quantum system to test any given Bell inequality and the optimization over measurements is a high-dimensional variational problem. In order to better understand this problem we present algorithms that provide, for a given quantum state, both a lower bound and an upper bound on the maximal expectation value of a Bell operator. Both bounds apply techniques from convex optimization and the methodology for creating upper bounds allows them to be systematically improved. In many cases these bounds determine measurements that would demonstrate violation of the Bell inequality or provide a bound that rules out the possibility of a violation. Examples are given to illustrate how these algorithms can be used to conclude definitively if some quantum states violate a given Bell inequality.Comment: 13 pages, 1 table, 2 figures. Updated version as published in PR

Multimodal Sleep Apnea Detection with Missing or Noisy Modalities

Polysomnography (PSG) is a type of sleep study that records multimodal physiological signals and is widely used for purposes such as sleep staging and respiratory event detection. Conventional machine learning methods assume that each sleep study is associated with a fixed set of observed modalities and that all modalities are available for each sample. However, noisy and missing modalities are a common issue in real-world clinical settings. In this study, we propose a comprehensive pipeline aiming to compensate for the missing or noisy modalities when performing sleep apnea detection. Unlike other existing studies, our proposed model works with any combination of available modalities. Our experiments show that the proposed model outperforms other state-of-the-art approaches in sleep apnea detection using various subsets of available data and different levels of noise, and maintains its high performance (AUROC>0.9) even in the presence of high levels of noise or missingness. This is especially relevant in settings where the level of noise and missingness is high (such as pediatric or outside-of-clinic scenarios)

Water Demand Management in England and Wales: constructions of the domestic water-user

YesMeasures to manage demand include implicit and explicit messages about domestic water-users which have important potential impacts on their perceptions and practices. Drawing on recent literature, this paper identifies three different ¿dimensions¿ along which demand management measures¿ constructions of the water-user may vary: these relate to whether the water user is passive or active, whether they are motivated by individual or common needs, and whether they perceive water as a right or a commodity. Demand management measures currently used in England and Wales are then discussed and analysed. The paper concludes by highlighting the importance of communications associated with demand management, and in particular, notes the need to consider the cumulative impact of messages and their interactions with people¿s existing understandings

Mining and Analyzing the Italian Parliament: Party Structure and Evolution

The roll calls of the Italian Parliament in the XVI legislature are studied by employing multidimensional scaling, hierarchical clustering, and network analysis. In order to detect changes in voting behavior, the roll calls have been divided in seven periods of six months each. All the methods employed pointed out an increasing fragmentation of the political parties endorsing the previous government that culminated in its downfall. By using the concept of modularity at different resolution levels, we identify the community structure of Parliament and its evolution in each of the considered time periods. The analysis performed revealed as a valuable tool in detecting trends and drifts of Parliamentarians. It showed its effectiveness at identifying political parties and at providing insights on the temporal evolution of groups and their cohesiveness, without having at disposal any knowledge about political membership of Representatives.Comment: 27 pages, 14 figure

What Provides Justification for Cheating:Producing or Observing Counterfactuals?

When people can profit financially by lying, they do so to the extent to which they can justify their lies. One type of justification is the observation and production of desirable counterfactual information. Here, we disentangle observing and producing of desired counterfactuals and test whether the mere observation is sufficient or whether one actually needs to produce the information in order to justify lying. By employing a modified version of the Die-Under-Cup task, we ask participants to privately roll a die three times and to report the outcome of the first die roll (with higher values corresponding to higher payoffs). In all three conditions, participants produce (roll the die) and observe the first die roll, which is relevant for pay. We manipulate whether participants produce and observe versus only observe the second and third die roll outcomes, which are both irrelevant for pay. Results reveal that people lie to the same extent—when producing and observing the counterfactuals, and when merely observing them. It seems that merely observing counterfactual information is sufficient to allow people to use this information to justify their lies. We further test whether creativity and moral disengagement are associated with dishonesty and replicate the finding showing that unethical behavior increases with creativity

Identification of compounds with anti-human cytomegalovirus activity that inhibit production of IE2 proteins

Using a high throughput screening methodology we surveyed a collection of largely uncharacterized validated or suspected kinase inhibitors for anti-human cytomegalovirus (HCMV) activity. From this screen we identified three structurally related 5-aminopyrazine compounds (XMD7-1, -2 and -27) that inhibited HCMV replication in virus yield reduction assays at low micromolar concentrations. Kinase selectivity assays indicated that each compound was a kinase inhibitor capable of inhibiting a range of cellular protein kinases. Western blotting and RNA sequencing demonstrated that treatment of infected cells with XMD7 compounds resulted in a defect in the production of the major HCMV transcriptional transactivator IE2 proteins (IE2-86, IE2-60 and IE2-40) and an overall reduction in transcription from the viral genome. However, production of certain viral proteins was not compromised by treatment with XMD7 compounds. Thus, these novel anti-HCMV compounds likely inhibited transcription from the viral genome and suppressed production of a subset of viral proteins by inhibiting IE2 protein production

A Parameterized Centrality Metric for Network Analysis

A variety of metrics have been proposed to measure the relative importance of nodes in a network. One of these, alpha-centrality [Bonacich, 2001], measures the number of attenuated paths that exist between nodes. We introduce a normalized version of this metric and use it to study network structure, specifically, to rank nodes and find community structure of the network. Specifically, we extend the modularity-maximization method [Newman and Girvan, 2004] for community detection to use this metric as the measure of node connectivity. Normalized alpha-centrality is a powerful tool for network analysis, since it contains a tunable parameter that sets the length scale of interactions. By studying how rankings and discovered communities change when this parameter is varied allows us to identify locally and globally important nodes and structures. We apply the proposed method to several benchmark networks and show that it leads to better insight into network structure than alternative methods.Comment: 11 pages, submitted to Physical Review