The decay of photoexcited quantum systems: a description within the statistical scattering model

The decay of photoexcited quantum systems (examples are photodissociation of molecules and autoionization of atoms) can be viewed as a half-collision process (an incoming photon excites the system which subsequently decays by dissociation or autoionization). For this reason, the standard statistical approach to quantum scattering, originally developed to describe nuclear compound reactions, is not directly applicable. Using an alternative approach, correlations and fluctuations of observables characterizing this process were first derived in [Fyodorov YV and Alhassid Y 1998 Phys. Rev. A 58, R3375]. Here we show how the results cited above, and more recent results incorporating direct decay processes, can be obtained from the standard statistical scattering approach by introducing one additional channel.Comment: 7 pages, 2 figure

Learning Musical Contour on a Tabletop

Many successful tabletop applications for music making have been developed, and the technology has been investigated from different perspectives. Yet, to date, despite optimistic claims regarding their potential as learning tools, their role in helping people to explore, acquire, and rea- son about musical concepts has been sparsely researched. We have developed an exploratory study around a simple tabletop application that allows people to make music using a visual representation of melodic contour. Our aim is to understand whether and how such system might help peo- ple to reason about music in terms of contour while at the same time affording an enjoyable music making experience to musically untrained people. Our findings suggest that the system has potential as a learning tool, especially for beginners, but tutoring is still necessary to acquire, use, and express concepts precisely

MULTI-TOUCH INTERACTION PRINCIPLES FOR COLLABORATIVE REAL-TIME MUSIC ACTIVITIES: TOWARDS A PATTERN LANGUAGE

In this paper we give an analysis of the literature on a set of problems that can arise when undertaking the interaction design of multi-touch applications for collaborative real-time music activities, which are designed for multi-touch technologies (e.g. smartphones, tablets, interactive tabletops, among others). Each problem is described, and a candidate design pattern (CDP) is suggested in the form of a short sentence and a diagram—an approach inspired by Christopher Alexander’s A Pattern Language. These solutions relate to the fundamental collaborative principles of democratic relationships, identities and collective interplay. We believe that this approach might disseminate forms of best design practice for collaborative music applications, in order to produce real-time musical systems which are collaborative and expressive

Genome-wide association study identifies 30 loci associated with bipolar disorder.

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder

Integrated Bayesian analysis of rare exonic variants to identify risk genes for schizophrenia and neurodevelopmental disorders.

Background: Integrating rare variation from trio family and case-control studies has successfully implicated specific genes contributing to risk of neurodevelopmental disorders (NDDs) including autism spectrum disorders (ASD), intellectual disability (ID), developmental disorders (DDs), and epilepsy (EPI). For schizophrenia (SCZ), however, while sets of genes have been implicated through the study of rare variation, only two risk genes have been identified. Methods: We used hierarchical Bayesian modeling of rare-variant genetic architecture to estimate mean effect sizes and risk-gene proportions, analyzing the largest available collection of whole exome sequence data for SCZ (1,077 trios, 6,699 cases, and 13,028 controls), and data for four NDDs (ASD, ID, DD, and EPI; total 10,792 trios, and 4,058 cases and controls). Results: For SCZ, we estimate there are 1,551 risk genes. There are more risk genes and they have weaker effects than for NDDs. We provide power analyses to predict the number of risk-gene discoveries as more data become available. We confirm and augment prior risk gene and gene set enrichment results for SCZ and NDDs. In particular, we detected 98 new DD risk genes at FDR 0.55), but low between SCZ and the NDDs (ρ<0.3). An in-depth analysis of 288 NDD genes shows there is highly significant protein-protein interaction (PPI) network connectivity, and functionally distinct PPI subnetworks based on pathway enrichment, single-cell RNA-seq cell types, and multi-region developmental brain RNA-seq. Conclusions: We have extended a pipeline used in ASD studies and applied it to infer rare genetic parameters for SCZ and four NDDs ( https://github.com/hoangtn/extTADA ). We find many new DD risk genes, supported by gene set enrichment and PPI network connectivity analyses. We find greater similarity among NDDs than between NDDs and SCZ. NDD gene subnetworks are implicated in postnatally expressed presynaptic and postsynaptic genes, and for transcriptional and post-transcriptional gene regulation in prenatal neural progenitor and stem cells

Issues and techniques for collaborative music making on multi-touch surfaces

A range of systems exist for collaborative music making on multi-touch surfaces. Some of them have been highly successful, but currently there is no systematic way of designing them, to maximize collaboration for a particular user group. We are particularly interested in systems that will engage novices and experts. We designed a simple application in an initial attempt to clearly analyse some of the issues. Our application allows groups of users to express themselves in collaborative music making using pre-composed materials. User studies were video recorded and analysed using two techniques derived from Grounded Theory and Content Analysis. A questionnaire was also conducted and evaluated. Findings suggest that the application affords engaging interaction. Enhancements for collaborative music making on multi-touch surfaces are discussed. Finally, future work on the prototype is proposed to maximise engagement. © 2010 Robin Laney et al

A Subsumption Agent for Collaborative Free Improvisation

This paper discusses the design and evaluation of an artificial agent for collaborative musical free improvisation. The agent provides a means to investigate the underpinnings of improvisational interaction. In connection with this general goal, the system is also used here to explore the implementation of a collaborative musical agent using a specific robotics architecture, Subsumption. The architecture of the system is explained, and its evaluation in an empirical study with expert improvisors is discussed. A follow-up study using a second iteration of the system is also presented. The system design and connected studies bring together Subsumption robotics, ecological psychology, and musical improvisation, and contribute to an empirical grounding of an ecological theory of improvisation

mTADA is a framework for identifying risk genes from de novo mutations in multiple traits

Joint analysis of multiple traits can result in the identification of associations not found through the analysis of each trait in isolation. Studies of neuropsychiatric disorders and congenital heart disease (CHD) which use de novo mutations (DNMs) from parent-offspring trios have reported multiple putatively causal genes. However, a joint analysis method designed to integrate DNMs from multiple studies has yet to be implemented. We here introduce multiple-trait TADA (mTADA) which jointly analyzes two traits using DNMs from non-overlapping family samples. We first demonstrate that mTADA is able to leverage genetic overlaps to increase the statistical power of risk-gene identification. We then apply mTADA to large datasets of &gt;13,000 trios for five neuropsychiatric disorders and CHD. We report additional risk genes for schizophrenia, epileptic encephalopathies and CHD. We outline some shared and specific biological information of intellectual disability and CHD by conducting systems biology analyses of genes prioritized by mTADA