557 resultados para Ensembles


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This workshop focuses upon research about the qualities of community in music and of music in community facilitated by technologically supported relationships. Generative media systems present an opportunity for users to leverage computational systems to form new relationships through interactive and collaborative experiences. Generative music and art are a relatively new phenomenon that use procedural invention as a creative technique to produce music and visual media. Early systems have demonstrated the potential to provide access to collaborative ensemble experiences for users with little formal musical or artistic expertise. This workshop examines the relational affordances of these systems evidenced by selected field data drawn from the Network Jamming Project. These generative performance systems enable access to unique ensembles with very little musical knowledge or skill and offer the possibility of interactive relationships with artists and musical knowledge through collaborative performance. In this workshop we will focus on data that highlights how these simulated experiences might lead to understandings that may be of social benefit. Conference participants will be invited to jam in real time using virtual interfaces and to evaluate purposively selected video artifacts that demonstrate different kinds of interactive relationship with artists, peers, and community and that enrich the sense of expressive self. Theoretical insights about meaningful engagement drawn from the longitudinal and cross cultural experiences will underpin the discussion and practical presentation.

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Music making affects relationships with self and others by generating a sense of belonging to a culture or ideology (Bamford, 2006; Barovick, 2001; Dillon & Stewart, 2006; Fiske, 2000; Hallam, 2001). Whilst studies from arts education research present compelling examples of these relationships, others argue that they do not present sufficiently validated evidence of a causal link between music making experiences and cognitive or social change (Winner & Cooper, 2000; Winner & Hetland, 2000a, 2000b, 2001). I have suggested elsewhere that this disconnection between compelling evidence and observations of the effects of music making are in part due to the lack of rigor in research and the incapacity of many methods to capture these experiences in meaningful ways (Dillon, 2006). Part of the answer to these questions about rigor and causality lay in the creative use of new media technologies that capture the results of relationships in music artefacts. Crucially, it is the effective management of these artefacts within computer systems that allows researchers and practitioners to collect, organize, analyse and then theorise such music making experiences.

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Steady state entanglement in ensembles of harmonic oscillators with a common squeezed reservoir is studied. Under certain conditions the ensemble features genuine multipartite entanglement in the steady state. Several analytic results regarding the bipartite and multipartite entanglement properties of the system are derived. We also discuss a possible experimental implementation which may exhibit steady state genuine multipartite entanglement.

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Calls from 14 species of bat were classified to genus and species using discriminant function analysis (DFA), support vector machines (SVM) and ensembles of neural networks (ENN). Both SVMs and ENNs outperformed DFA for every species while ENNs (mean identification rate – 97%) consistently outperformed SVMs (mean identification rate – 87%). Correct classification rates produced by the ENNs varied from 91% to 100%; calls from six species were correctly identified with 100% accuracy. Calls from the five species of Myotis, a genus whose species are considered difficult to distinguish acoustically, had correct identification rates that varied from 91 – 100%. Five parameters were most important for classifying calls correctly while seven others contributed little to classification performance.

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Alueellisten ilmastomallien vaakasuuntainen erottelukyky on globaaleja malleja huomattavasti tarkempi, minkä vuoksi niillä on useita käyttökohteita ilmastonmuutoksen vaikutusten arvioinnissa. Tässä Pro Gradu – työssä tutkittiin alueellisten ilmastomallien tuottamia sademääräsimulaatioita sekä sadehavaintoaineistoja Euroopassa. Aineistona käytettiin ENSEMBLES-hankkeen tarjoamia 10 alueellista ilmastosimulaatiota, kahta hilamuotoista havaintoaineistoa sekä Ilmatieteen laitoksen sadeasemahavaintoja. Aineisto oli päiväkohtaista. Vuositasolla ilmastomallit ovat pääsääntöisesti sademäärää yliennustavia, mutta harha vaihtelee alueiden ja vuodenaikojen kesken. Osa tästä harhasta selittyy kuitenkin sillä, että havaintoaineistoihin sisältyy tyypillisesti sademäärän mittaustapahtumasta aiheutuva virhe. Alueellisten simulaatioiden harha pyritään minimoimaan kun halutaan kvantifioida tulevaisuuden sademääriä ilmastomallitulosten avulla. Tutkimuksessa sovellettiin tähän tarkoitettua empiiristä korjausmenetelmää tapauskohtaisella testialueella Suomessa. Korjausmenetelmä huomioi sadetapahtumien harhan niiden intensiteetin mukaan, jolloin se periaatteessa soveltuu paremmin myös rankkasateiden korjaamiseen. Korjausmenetelmässä harhan riippuvuus sadetapahtuman intensiteetistä oletetaan skenaariojaksolla samaksi kuin vertailujaksolla. Edellytyksenä korjausmenetelmän käytölle on se, että sadetapahtumien intensiteettijakauma simulaatioaineistoissa on kohtuullisen lähellä havaittua jakaumaa. Korjausmenetelmä parantaa sademäärän vuodenaikaiskeskiarvoja tarkastelualueella vertailujaksolla, vuoden kokonaissadekertymän harhan suuruus aineiston keskiarvossa on vain 7 mm. Koska sadetapahtumien intensiteettijakauma muuttuu simulaatioissa vertailu- ja skenaariojaksojen välillä, korjausmenetelmä vaikuttaa kuitenkin sademäärän muutoksen suuruuteen. Lisäksi menetelmän vaikutus sademäärän muutokseen jakautuu epätasaisesti sadetapahtuman intensiteetistä riippuen: menetelmä pienentää rankkasateiden kertymien muutosta, mutta kasvattaa sitä tavallisten sadetapahtumien osalta. Rankkasadetapahtumien erilliskäsittely korjausmenetelmässä aiheuttaa sen, että korjatusta sadetapahtumien intensiteettijakaumasta tulee epäjatkuva riippumatta siitä, mikä tarkastelujakso on kyseessä. Tässä työssä käytetty korjausmenetelmä ei ole ainoa laatuaan, perinteisesti mallitulosten korjaamiseen on käytetty vakiokertoimiin perustuvaa menetelmää kaikille sadetapahtumille. Korjausmenetelmien testaaminen on monien sovellusten kannalta tärkeää, mutta parhaan menetelmän löytäminen ei ole yksiselitteisen helppoa. Globaaleihin malleihin verrattuna alueellisten ilmastomallien ja korjausmenetelmien käyttö aiheuttavat molemmat ylimääräisen epävarmuuslähteen ilmastosimulaatioihin.

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In this article, we present a novel application of a quantum clustering (QC) technique to objectively cluster the conformations, sampled by molecular dynamics simulations performed on different ligand bound structures of the protein. We further portray each conformational population in terms of dynamically stable network parameters which beautifully capture the ligand induced variations in the ensemble in atomistic detail. The conformational populations thus identified by the QC method and verified by network parameters are evaluated for different ligand bound states of the protein pyrrolysyl-tRNA synthetase (DhPylRS) from D. hafniense. The ligand/environment induced re-distribution of protein conformational ensembles forms the basis for understanding several important biological phenomena such as allostery and enzyme catalysis. The atomistic level characterization of each population in the conformational ensemble in terms of the re-orchestrated networks of amino acids is a challenging problem, especially when the changes are minimal at the backbone level. Here we demonstrate that the QC method is sensitive to such subtle changes and is able to cluster MD snapshots which are similar at the side-chain interaction level. Although we have applied these methods on simulation trajectories of a modest time scale (20 ns each), we emphasize that our methodology provides a general approach towards an objective clustering of large-scale MD simulation data and may be applied to probe multistate equilibria at higher time scales, and to problems related to protein folding for any protein or protein-protein/RNA/DNA complex of interest with a known structure.

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Network theory applied to protein structures provides insights into numerous problems of biological relevance. The explosion in structural data available from PDB and simulations establishes a need to introduce a standalone-efficient program that assembles network concepts/parameters under one hood in an automated manner. Herein, we discuss the development/application of an exhaustive, user-friendly, standalone program package named PSN-Ensemble, which can handle structural ensembles generated through molecular dynamics (MD) simulation/NMR studies or from multiple X-ray structures. The novelty in network construction lies in the explicit consideration of side-chain interactions among amino acids. The program evaluates network parameters dealing with topological organization and long-range allosteric communication. The introduction of a flexible weighing scheme in terms of residue pairwise cross-correlation/interaction energy in PSN-Ensemble brings in dynamical/chemical knowledge into the network representation. Also, the results are mapped on a graphical display of the structure, allowing an easy access of network analysis to a general biological community. The potential of PSN-Ensemble toward examining structural ensemble is exemplified using MD trajectories of an ubiquitin-conjugating enzyme (UbcH5b). Furthermore, insights derived from network parameters evaluated using PSN-Ensemble for single-static structures of active/inactive states of 2-adrenergic receptor and the ternary tRNA complexes of tyrosyl tRNA synthetases (from organisms across kingdoms) are discussed. PSN-Ensemble is freely available from http://vishgraph.mbu.iisc.ernet.in/PSN-Ensemble/psn_index.html.

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Conformational changes in proteins are extremely important for their biochemical functions. Correlation between inherent conformational variations in a protein and conformational differences in its homologues of known structure is still unclear. In this study, we have used a structural alphabet called Protein Blocks (PBs). PBs are used to perform abstraction of protein 3-D structures into a 1-D strings of 16 alphabets (a-p) based on dihedral angles of overlapping pentapeptides. We have analyzed the variations in local conformations in terms of PBs represented in the ensembles of 801 protein structures determined using NMR spectroscopy. In the analysis of concatenated data over all the residues in all the NMR ensembles, we observe that the overall nature of inherent local structural variations in NMR ensembles is similar to the nature of local structural differences in homologous proteins with a high correlation coefficient of .94. High correlation at the alignment positions corresponding to helical and beta-sheet regions is only expected. However, the correlation coefficient by considering only the loop regions is also quite high (.91). Surprisingly, segregated position-wise analysis shows that this high correlation does not hold true to loop regions at the structurally equivalent positions in NMR ensembles and their homologues of known structure. This suggests that the general nature of local structural changes is unique; however most of the local structural variations in loop regions of NMR ensembles do not correlate to their local structural differences at structurally equivalent positions in homologues.

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Using numerical diagonalization we study the crossover among different random matrix ensembles (Poissonian, Gaussian orthogonal ensemble (GOE), Gaussian unitary ensemble (GUE) and Gaussian symplectic ensemble (GSE)) realized in two different microscopic models. The specific diagnostic tool used to study the crossovers is the level spacing distribution. The first model is a one-dimensional lattice model of interacting hard-core bosons (or equivalently spin 1/2 objects) and the other a higher dimensional model of non-interacting particles with disorder and spin-orbit coupling. We find that the perturbation causing the crossover among the different ensembles scales to zero with system size as a power law with an exponent that depends on the ensembles between which the crossover takes place. This exponent is independent of microscopic details of the perturbation. We also find that the crossover from the Poissonian ensemble to the other three is dominated by the Poissonian to GOE crossover which introduces level repulsion while the crossover from GOE to GUE or GOE to GSE associated with symmetry breaking introduces a subdominant contribution. We also conjecture that the exponent is dependent on whether the system contains interactions among the elementary degrees of freedom or not and is independent of the dimensionality of the system.

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Quantum ensembles form easily accessible architectures for studying various phenomena in quantum physics, quantum information science and spectroscopy. Here we review some recent protocols for measurements in quantum ensembles by utilizing ancillary systems. We also illustrate these protocols experimentally via nuclear magnetic resonance techniques. In particular, we shall review noninvasive measurements, extracting expectation values of various operators, characterizations of quantum states and quantum processes, and finally quantum noise engineering.