976 resultados para Set-Valued Functions
Resumo:
The kinematics of the anatomical shoulder are analysed and modelled as a parallel mechanism similar to a Stewart platform. A new method is proposed to describe the shoulder kinematics with minimal coordinates and solve the indeterminacy. The minimal coordinates are defined from bony landmarks and the scapulothoracic kinematic constraints. Independent from one another, they uniquely characterise the shoulder motion. A humanoid mechanism is then proposed with identical kinematic properties. It is then shown how minimal coordinates can be obtained for this mechanism and how the coordinates simplify both the motion-planning task and trajectory-tracking control. Lastly, the coordinates are also shown to have an application in the field of biomechanics where they can be used to model the scapulohumeral rhythm.
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L'ARN polymérase 3 transcrit un petit groupe de gènes fortement exprimés et impliqués dans plusieurs mécanismes moléculaires. Les ARNs de transfert ou ARNt représentent plus ou moins la moitié du transcriptome de l'ARN polymérase 3. Ils sont directement impliqués dans la traduction des protéines en agissant comme transporteurs d'acides aminés qui sont incorporés à la chaîne naissante de polypeptides. Chez des levures cultivées dans un milieu jusqu'à épuisement des nutriments, Maf1 réprime la transcription par l'ARN polymérase 3, favorisant ainsi l'économie énergétique cellulaire. Dans un modèle de cellules de mammifères, MAF1 réprime aussi la transcription de l'ARN polymérase 3 dans des conditions de stress, cependant il n'existe aucune donnée quant à son rôle chez un mammifère vivant. Pendant mon doctorat, j'ai utilisé une souris délétée pour le gène Maf1 afin de connaître les effets de ce gène chez un mammifère. Etonnamment, la souris Maf1-‐/-‐ est résistante à l'obésité même si celle-‐ci est nourrie avec une nourriture riche en matières grasses. Des études moléculaires et de métabolomiques ont montré qu'il existe des cycles futiles de production et dégradation des lipides et des ARNt, ce qui entraîne une augmentation de la dépense énergique et favorise la résistance à l'obésité. En plus de la caractérisation de la souris Maf1-‐/-‐, pendant ma thèse j'ai également développé une méthode afin de normaliser les données de ChIP-‐sequencing. Cette méthode est fondée sur l'utilisation d'un contrôle interne, représenté ici par l'ajout d'une quantité fixe de chromatine provenant d'un organisme différent de celui étudié. La méthode a amélioré considérablement la reproductibilité des valeurs entre réplicas biologiques. Elle a aussi révélé des différences entre échantillons issus de conditions différentes. Une occupation supérieure de l'ARN polymérase 3 sur les gènes Pol 3 chez les souris Maf1 KO entraîne une augmentation du niveau de précurseurs d'ARNt, ayant pour effet probable la saturation de la machinerie de maturation des ARNt. En effet, chez les souris Maf1 KO, le pourcentage d'ARNt modifiés est plus faible que chez les souris type sauvage. Ce déséquilibre entre le niveau de précurseurs et d'ARNt matures entraîne une diminution de la traduction protéique. Ces résultats ont permis d'identifier de nouvelles fonctions pour la protéine MAF1, comme étant une protéine régulatrice à la fois de la transcription mais aussi de la traduction et en étant un cible potentielle au traitement à l'obésité. -- RNA polymerase III (Pol 3) transcribes a small set of highly expressed genes involved in different molecular mechanisms. tRNAs account for almost half of the Pol 3 transcriptome and are involved in translation, bringing a new amino into the nascent polypeptide chain. In yeast, under nutrient deprivation, Maf1 acts for cell energetic economy by repressing Pol 3 transcription. In mammalian cells, MAF1 also represses Pol 3 activity under conditions of serum deprivation or DNA damages but nothing is known about its role in a mammalian organism. During my thesis studies, I used a Maf1 KO mouse model to characterize the effects of Maf1 deletion in a living animal. Surprisingly, the MAF1 KO mouse developed an unexpected phenotype, being resistant to high fat diet-‐induced obesity and displaying an extended lifespan. Molecular and metabolomics characterizations revealed futile cycles of lipids and tRNAs, which are produced and immediately degraded, which increases energy consumption in the Maf1 KO mouse and probably explains in part the protection to obesity. Additionally to the mouse characterization, I also developed a method to normalize ChIP-‐seq data, based on the addition of a foreign chromatin to be used as an internal control. The method improved reproducibility between replicates and revealed differences of Pol 3 occupancy between WT and Maf1 KO samples that were not seen without normalization to the internal control. I then established that increased Pol 3 occupancy in the Maf1 KO mouse liver was associated with increased levels of tRNA precursor but not of mature tRNAs, the effective molecules involved in translation. The overproduction of precursor tRNAs associated with the deletion of Maf1 apparently overwhelms the tRNA processing machinery as the Maf1 KO mice have lower levels of fully modified tRNAs. This maturation defect directly impacts on translation efficiency as polysomic fractions and newly synthetized protein levels were reduced in the liver of the Maf1 KO mouse. Altogether, these results indicate new functions for MAF1, a regulator of both transcription and translation as well as a potential target for obesity treatment.
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El present treball és un estudi sobre l'estigma social en la malaltia mental i la representació d'aquest al cinema. Aquesta anàlisi s'ha portat a terme a partir de dues línies de treball. Per una banda amb l'anàlisi interpretativa de dotze pel·lícules utilitzant els indicadors de 'perillositat'; 'incapacitat per a la vida'; 'incurabilitat'; 'pèrdua de rols socials'; 'por al rebuig i/o por a les relacions socials'; i per l'altra banda a partir d'un grup de discussió, en el qual s'han visionat fragments de cinc pel·lícules amb set estudiants del Grau d'Educació Social de la Universitat de Vic. Dels resultats obtinguts es desprèn que la pel·lícula és un mitjà de comunicació mitjançant el qual els estereotips són usats en favor de l'espectacle, estigmatitzant així les persones diagnosticades de malaltia mental. Aquest és un dels motius que fan valorar el cinema com un recurs educatiu a considerar tant en la formació d'educadors i educadores socials com en els projectes d'intervenció socioeducativa.
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Previous functional MRI (fMRI) studies have associated anterior hippocampus with imagining and recalling scenes, imagining the future, recalling autobiographical memories and visual scene perception. We have observed that this typically involves the medial rather than the lateral portion of the anterior hippocampus. Here, we investigated which specific structures of the hippocampus underpin this observation. We had participants imagine novel scenes during fMRI scanning, as well as recall previously learned scenes from two different time periods (one week and 30 min prior to scanning), with analogous single object conditions as baselines. Using an extended segmentation protocol focussing on anterior hippocampus, we first investigated which substructures of the hippocampus respond to scenes, and found both imagination and recall of scenes to be associated with activity in presubiculum/parasubiculum, a region associated with spatial representation in rodents. Next, we compared imagining novel scenes to recall from one week or 30 min before scanning. We expected a strong response to imagining novel scenes and 1-week recall, as both involve constructing scene representations from elements stored across cortex. By contrast, we expected a weaker response to 30-min recall, as representations of these scenes had already been constructed but not yet consolidated. Both imagination and 1-week recall of scenes engaged anterior hippocampal structures (anterior subiculum and uncus respectively), indicating possible roles in scene construction. By contrast, 30-min recall of scenes elicited significantly less activation of anterior hippocampus but did engage posterior CA3. Together, these results elucidate the functions of different parts of the anterior hippocampus, a key brain area about which little is definitely known.
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We propose a new kernel estimation of the cumulative distribution function based on transformation and on bias reducing techniques. We derive the optimal bandwidth that minimises the asymptotic integrated mean squared error. The simulation results show that our proposed kernel estimation improves alternative approaches when the variable has an extreme value distribution with heavy tail and the sample size is small.
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Vaatimusten määrittelyn tarkoitus on kartoittaa tietojärjestelmän käyttäjien työtehtäviä ja niihin liittyviä järjestelmän toiminnallisia ja ei-toiminnallisia vaatimuksia. Todellinen asiakasnäkökulma tulee esille yrityksen itse käynnistämässä vaatimusten määrittelyssä. Nykytilan selvittäminen ja kriittisten toimintojen havaitseminen käynnistävät kohdeyksikössä käytävän keskinäisen keskustelun, mikä on edellytyksenä järjestelmävaatimusten havaitsemiseen. Tämän työn teoriaosuudessa lähestytään eri näkökulmia vaatimustenmäärittelyyn. Tämän jälkeen esitellään muutamia asiakasyritykselle sopivia määrittelymenetelmiä, joita voidaan hyödyntää valmisohjelmistohankeen määrittelyssä. Työssä esitetään myös toiminnanohjaukseen ja tietovarastointiin tarkoitettujen järjestelmien tapaa kerätä taloudellista informaatiota ja luoda raportteja johdolle päätöksenteon tueksi. Työn empiirisessä osassa selvitetään mitkä ovat Lappeenrannan Energia Oy:n asettamat liiketoiminnalliset tarpeet ja vaatimukset uudelle talousohjauksen tietojärjestelmälle.
Resumo:
This thesis studies the properties and usability of operators called t-norms, t-conorms, uninorms, as well as many valued implications and equivalences. Into these operators, weights and a generalized mean are embedded for aggregation, and they are used for comparison tasks and for this reason they are referred to as comparison measures. The thesis illustrates how these operators can be weighted with a differential evolution and aggregated with a generalized mean, and the kinds of measures of comparison that can be achieved from this procedure. New operators suitable for comparison measures are suggested. These operators are combination measures based on the use of t-norms and t-conorms, the generalized 3_-uninorm and pseudo equivalence measures based on S-type implications. The empirical part of this thesis demonstrates how these new comparison measures work in the field of classification, for example, in the classification of medical data. The second application area is from the field of sports medicine and it represents an expert system for defining an athlete's aerobic and anaerobic thresholds. The core of this thesis offers definitions for comparison measures and illustrates that there is no actual difference in the results achieved in comparison tasks, by the use of comparison measures based on distance, versus comparison measures based on many valued logical structures. The approach has been highly practical in this thesis and all usage of the measures has been validated mainly by practical testing. In general, many different types of operators suitable for comparison tasks have been presented in fuzzy logic literature and there has been little or no experimental work with these operators.
Resumo:
Statistical mechanics Monte Carlo simulation is reviewed as a formalism to study thermodynamic properties of liquids. Considering the importance of free energy changes in chemical processes, the thermodynamic perturbation theory implemented in the Monte Carlo method is discussed. The representation of molecular interaction by the Lennard-Jones and Coulomb potential functions is also discussed. Charges derived from quantum molecular electrostatic potential are also discussed as an useful methodology to generate an adequate set of partial charges to be used in liquid simulation.
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Tietojärjestelmien strateginen kehittäminen on ollut niin liike-elämän kiinnostuksen kuin akateemisen tutkimuksenkin kohteena jo pitkään. Aihe on edelleen ajankohtainen, eikä ajankohtaisuus osoita laantumisen merkkejä. Valtaosa tutkimuksesta on kohdistunut suuryrityksiin ja jonkin verran pk-yrityksiin yhtenä ryhmänä. Tutkimus on kohdistunut aiheeseen tarkastelemalla onko tietojärjestelmien ja liiketoimintastrategian välillä yhteyttä, ja jos, onko sillä merkitystä yrityksen menestykselle. Tämän tutkimuksen tavoitteena oli pureutua syvemmälle siihen tapaan, jolla yritys kytkee liiketoimintastrategiansa tietojärjestelmähankintaan. Kohdetietojärjestelmäksi tutkimuksessa valittiin toiminnanohjausjärjestelmät ja yrityskooksi keskisuuret yritykset. Toiminnanohjausjärjestelmän valintaa voidaan perustella sen kattavuudella yrityksen toiminnassa eri sidosryhmien suunnasta katsottaessa. Keskisuuret yritykset valittiin osittain sen vuoksi, koska niistä ei ole paljoakaan omaa tutkimusta, osittain sen vuoksi, että niiden luonne kehityspolun epäjatkumokohdassa haluttiin nostaa esille. Tutkimuksen empiirinen osa pohjautuu kolmeen tutkimustapaukseen, kolmen keskisuuren yrityksen toiminnanohjaushankkeeseen. Tapausyritysten liiketoiminta- ja ITjohtoa haastateltiin, ja lisäksi käytettiin kaikkea saataville ollutta kirjallista arkistoaineistoa. Tutkimuksen päämenetelmä oli Grounded Theory (GT). Tutkimustavassa ei, poiketen useista muista laadullisista tutkimustavoista, ole ennalta määrättyä viitekehystä, vaan tutkimus lähtee liikkeelle ns. puhtaalta pöydältä ilman esioletuksia luoden tutkimusprosessin kuluessa uutta teoriaa. Tutkimustavan etuna voidaan pitää ennakkoluulottomuutta. Aikaisemman tutkimuksen rooli tässä tutkimuksessa oli ensinnäkin kartoittaa tutkimusaluetta ja olla johdantona tutkimukselle, toisaalta tuloksia vertailtiin aikaisempaan tutkimukseen. Tutkimusaineisto analysoitiin tarkasti. Ensin aineisto käytiin läpi koodaamalla se aineistosta esille nousseiden käsitteiden alle. Seuraavaksi saatu tulos luokiteltiin aineistosta nousseisiin luokkiin sekä muodostettiin käsitteiden ja luokkien väliset yhteydet. Lopuksi muodostumassa oleva teoria konkretisoitiin 18 hypoteesin ja hypoteesit yhdistävän mallin avulla. Tutkimuksessa saatiin uutta tietoa siitä, miten vaatimusprosessi etenee ja miten keskisuuren yrityksen ominaispiirteet vaikuttavat vaatimusprosessiin. Lisäksi saatiin uutta tietoa siitä, mitkä ovat kriittisiä menestystekijöitä keskisuuren yrityksen toiminnanohjaushankkeessa. Keskisuuretyritykset näyttävät tämän tutkimuksen aineiston perusteella osaavan asettaa vaatimuksia toiminnanohjausjärjestelmälle liiketoimintastrategian, prosessikuvausten ja toiminnanohjausjärjestelmien tarjoamien mahdollisuuksien suunnista. Vaatimusten toteutumisenarviointi on keskisuurilla yrityksillä epäsystemaattista, kuten aikaisemmassa tutkimuksessa on todettu olevan myös suurilla yrityksillä. Resurssivaje vaikeuttaa toiminnanohjausjärjestelmän liiketoimintastrategisten vaatimusten toteutumista. Tutkimusaineiston perusteella voidaan päätellä, että keskisuurissa yrityksissä – huolimatta siitä, että niissä on olemassa prosessikuvaukset – ei ole varsinaista prosessiajattelua tai prosessijohtamista. Keskisuuret yritykset eivät tämän tutkimuksen aineiston perusteella näytä muodostavan poikkeusta, vaan mittariston käyttö on epäkypsää, eikä mittaristoa pystytä hyödyntämään tietojärjestelmähankkeen tukena. Tulosten pohjalta voidaan arvioida, että strategisen johtamisen komponentit ovat keskisuuressa yrityksessä toisistaan irrallisia. Vaikka toiminnanohjaushankkeen vaatimuksia asetettaessa liiketoimintastrategia on vahvasti mukana, jää vaatimuksenasettelu karkealle tasolle, eikä konkretisoidu prosesseihin ja mittarointiin. Sen seurauksena toiminnanohjausjärjestelmästä ei saada kaikkea sitä hyötyä ja tukea liiketoimintastrategialle, mikä olisi mahdollista. Tutkimuksessa tuli myös esille resurssi- ja osaamispuutteen haittavaikutuksia keskisuurten yritysten toiminnanohjaushankkeiden vaatimusprosessissa. Puutteet yhdistettynä hajallaan oleviin strategisen johtamisen komponentteihin muodostavat yhdessä vaikean lähtökohdan strategiselle toiminnanohjaushankkeelle.
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Neural Networks are a set of mathematical methods and computer programs designed to simulate the information process and the knowledge acquisition of the human brain. In last years its application in chemistry is increasing significantly, due the special characteristics for model complex systems. The basic principles of two types of neural networks, the multi-layer perceptrons and radial basis functions, are introduced, as well as, a pruning approach to architecture optimization. Two analytical applications based on near infrared spectroscopy are presented, the first one for determination of nitrogen content in wheat leaves using multi-layer perceptrons networks and second one for determination of BRIX in sugar cane juices using radial basis functions networks.
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Conservation laws in physics are numerical invariants of the dynamics of a system. In cellular automata (CA), a similar concept has already been defined and studied. To each local pattern of cell states a real value is associated, interpreted as the “energy” (or “mass”, or . . . ) of that pattern.The overall “energy” of a configuration is simply the sum of the energy of the local patterns appearing on different positions in the configuration. We have a conservation law for that energy, if the total energy of each configuration remains constant during the evolution of the CA. For a given conservation law, it is desirable to find microscopic explanations for the dynamics of the conserved energy in terms of flows of energy from one region toward another. Often, it happens that the energy values are from non-negative integers, and are interpreted as the number of “particles” distributed on a configuration. In such cases, it is conjectured that one can always provide a microscopic explanation for the conservation laws by prescribing rules for the local movement of the particles. The onedimensional case has already been solved by Fuk´s and Pivato. We extend this to two-dimensional cellular automata with radius-0,5 neighborhood on the square lattice. We then consider conservation laws in which the energy values are chosen from a commutative group or semigroup. In this case, the class of all conservation laws for a CA form a partially ordered hierarchy. We study the structure of this hierarchy and prove some basic facts about it. Although the local properties of this hierarchy (at least in the group-valued case) are tractable, its global properties turn out to be algorithmically inaccessible. In particular, we prove that it is undecidable whether this hierarchy is trivial (i.e., if the CA has any non-trivial conservation law at all) or unbounded. We point out some interconnections between the structure of this hierarchy and the dynamical properties of the CA. We show that positively expansive CA do not have non-trivial conservation laws. We also investigate a curious relationship between conservation laws and invariant Gibbs measures in reversible and surjective CA. Gibbs measures are known to coincide with the equilibrium states of a lattice system defined in terms of a Hamiltonian. For reversible cellular automata, each conserved quantity may play the role of a Hamiltonian, and provides a Gibbs measure (or a set of Gibbs measures, in case of phase multiplicity) that is invariant. Conversely, every invariant Gibbs measure provides a conservation law for the CA. For surjective CA, the former statement also follows (in a slightly different form) from the variational characterization of the Gibbs measures. For one-dimensional surjective CA, we show that each invariant Gibbs measure provides a conservation law. We also prove that surjective CA almost surely preserve the average information content per cell with respect to any probability measure.
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Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.
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An extensive literature suggests a link between executive functions and aggressive behavior in humans, pointing mostly to an inverse relationship, i.e., increased tendencies toward aggression in individuals scoring low on executive function tests. This literature is limited, though, in terms of the groups studied and the measures of executive functions. In this paper, we present data from two studies addressing these issues. In a first behavioral study, we asked whether high trait aggressiveness is related to reduced executive functions. A sample of over 600 students performed in an extensive behavioral test battery including paradigms addressing executive functions such as the Eriksen Flanker task, Stroop task, n-back task, and Tower of London (TOL). High trait aggressive participants were found to have a significantly reduced latency score in the TOL, indicating more impulsive behavior compared to low trait aggressive participants. No other differences were detected. In an EEG-study, we assessed neural and behavioral correlates of error monitoring and response inhibition in participants who were characterized based on their laboratory-induced aggressive behavior in a competitive reaction time task. Participants who retaliated more in the aggression paradigm and had reduced frontal activity when being provoked did not, however, show any reduction in behavioral or neural correlates of executive control compared to the less aggressive participants. Our results question a strong relationship between aggression and executive functions at least for healthy, high-functioning people.