The Compositional Aesthetic of Rodolfo Coelho de Souza in Paradise Station: an analysis

This article focuses on the compositional aesthetics of Rodolfo Coelho de Souza (1952-), a Brazilian fine art composer and active researcher, whose concerns surpasses the musical composition isolated from the social communication aspect. This is particularly evident in his piece Paradise Station, which, when analyzed, features the structural depth of its compositional process without disregarding the dialog with the listener and the Brazilian character, according to pitch, rhythm, texture, timbre and dynamics. The present analysis reveals a modular structure based on set classes, worked through a transformation network, which follows the David Lewin model.

Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data

Background: This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. Results: The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. Conclusions: We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.

Automatic aspect discrimination in data clustering

The attributes describing a data set may often be arranged in meaningful subsets, each of which corresponds to a different aspect of the data. An unsupervised algorithm (SCAD) that simultaneously performs fuzzy clustering and aspects weighting was proposed in the literature. However, SCAD may fail and halt given certain conditions. To fix this problem, its steps are modified and then reordered to reduce the number of parameters required to be set by the user. In this paper we prove that each step of the resulting algorithm, named ASCAD, globally minimizes its cost-function with respect to the argument being optimized. The asymptotic analysis of ASCAD leads to a time complexity which is the same as that of fuzzy c-means. A hard version of the algorithm and a novel validity criterion that considers aspect weights in order to estimate the number of clusters are also described. The proposed method is assessed over several artificial and real data sets.

Combinatorial-topological framework for the analysis of global dynamics

We discuss an algorithmic framework based on efficient graph algorithms and algebraic-topological computational tools. The framework is aimed at automatic computation of a database of global dynamics of a given m-parameter semidynamical system with discrete time on a bounded subset of the n-dimensional phase space. We introduce the mathematical background, which is based upon Conley's topological approach to dynamics, describe the algorithms for the analysis of the dynamics using rectangular grids both in phase space and parameter space, and show two sample applications. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4767672]

Germline mutation analysis of Tpit in Poodle dogs with ACTH-dependent hyperadrenocorticism

There is a high incidence of pituitary-dependent hyperadrenocorticism (PDH) in Poodle dogs, with family members being affected by the disease, suggesting a genetic involvement. Tpit is an obligate transcription factor for the expression of pro-opiomelanocortingene and for corticotroph terminal differentiation. The aim of the present study was to screen the Tpit gene for germline mutations in Poodles with PDH. Fifty Poodle dogs (33 female, 8.71 +/- 2.8 years) with PDH and 50 healthy Poodle dogs (32 females, 9.4241 2.8 years) were studied. Genomic DNA was isolated from peripheral blood, amplified by PCR and submitted to automatic sequence. No mutation in the coding region of Tpit was found, whereas the new single nucleotide polymorphism p.S343G, in heterozygous state, was found in the same frequency in both PDH and control groups. We concluded that Tpit gain-of-function mutations are not involved in the etiology of PDH in Poodle dogs.

Development of a high sensitive automatic setup for screening of microcystins in surface waters by employing a LED-based photometric detector

In this manuscript, an automatic setup for screening of microcystins in surface waters by employing photometric detection is described. Microcystins are toxins delivered by cyanobacteria within an aquatic environment, which have been considered strongly poisonous for humans. For that reason, the World Health Organization (WHO) has proposed a provisional guideline value for drinking water of 1 mu g L-1. In this work, we developed an automated equipment setup, which allows the screening of water for concentration of microcystins below 0.1 mu g V. The photometric method was based on the enzyme-linked immunosorbent assay (ELISA) and the analytical signal was monitored at 458 nm using a homemade LED-based photometer. The proposed system was employed for the detection of microcystins in rivers and lakes waters. Accuracy was assessed by processing samples using a reference method and applying the paired t-test between results. No significant difference at the 95% confidence level was observed. Other useful features including a linear response ranging from 0.05 up to 2.00 mu g L-1 (R-2 =0.999) and a detection limit of 0.03 mu g L-1 microcystins were achieved. (C) 2011 Elsevier B.V. All rights reserved.

A quantitative approach to evolution of music and philosophy

The development of new statistical and computational methods is increasingly making it possible to bridge the gap between hard sciences and humanities. In this study, we propose an approach based on a quantitative evaluation of attributes of objects in fields of humanities, from which concepts such as dialectics and opposition are formally defined mathematically. As case studies, we analyzed the temporal evolution of classical music and philosophy by obtaining data for 8 features characterizing the corresponding fields for 7 well-known composers and philosophers, which were treated with multivariate statistics and pattern recognition methods. A bootstrap method was applied to avoid statistical bias caused by the small sample data set, with which hundreds of artificial composers and philosophers were generated, influenced by the 7 names originally chosen. Upon defining indices for opposition, skewness and counter-dialectics, we confirmed the intuitive analysis of historians in that classical music evolved according to a master apprentice tradition, while in philosophy changes were driven by opposition. Though these case studies were meant only to show the possibility of treating phenomena in humanities quantitatively, including a quantitative measure of concepts such as dialectics and opposition, the results are encouraging for further application of the approach presented here to many other areas, since it is entirely generic.

cDNA-AFLP analysis of Psidium guajava L. cultivars under water stress and mechanical injury: methodological implications

Studies involving amplified fragment length polymorphism (cDNA-AFLP) have often used polyacrylamide gels with radiolabeled primers in order to establish best primer combinations, to analyze, and to recover transcript-derived fragments. Use of automatic sequencer to establish best primer combinations is convenient, because it saves time, reduces costs and risks of contamination with radioactive material and acrylamide, and allows objective band-matching and more precise evaluation of transcript-derived fragments intensities. This study aimed at examining the gene expression of commercial cultivars of P. guajava subjected to water and mechanical injury stresses, combining analyses by automatic sequencer and fluorescent kits for polyacrylamide gel electrophoresis. Firstly, 64 combinations of EcoRI and MseI primers were tested. Ten combinations with higher number of polymorphic fragments were then selected for transcript-derived fragments recovering and cluster analysis, involving 45 saplings of P. guajava. Two groups were obtained, one composed by the control samplings, and another formed by samplings undergoing stress, with no clear distinction between stress treatments. The results revealed the convenience of using a combination of automatic sequencer and fluorescent kits for polyacrylamide gel electrophoreses to examine gene expression profiles. The Unweighted Pair Group Method with Arithmetic Mean analysis using Euclidean distances points out a similar induced response mechanism of P. guajava undergoing water stress and mechanical injury.

The meccano method for automatic 3-d triangulation and volume parametrization of complex solids

[EN]In this paper we review the novel meccano method. We summarize the main stages (subdivision, mapping, optimization) of this automatic tetrahedral mesh generation technique and we concentrate the study to complex genus-zero solids. In this case, our procedure only requires a surface triangulation of the solid. A crucial consequence of our method is the volume parametrization of the solid to a cube. We construct volume T-meshes for isogeometric analysis by using this result. The efficiency of the proposed technique is shown with several examples. A comparison between the meccano method and standard mesh generation techniques is introduced.-1…

Statistical methods for biomedical signal analysis and processing

Statistical modelling and statistical learning theory are two powerful analytical frameworks for analyzing signals and developing efficient processing and classification algorithms. In this thesis, these frameworks are applied for modelling and processing biomedical signals in two different contexts: ultrasound medical imaging systems and primate neural activity analysis and modelling. In the context of ultrasound medical imaging, two main applications are explored: deconvolution of signals measured from a ultrasonic transducer and automatic image segmentation and classification of prostate ultrasound scans. In the former application a stochastic model of the radio frequency signal measured from a ultrasonic transducer is derived. This model is then employed for developing in a statistical framework a regularized deconvolution procedure, for enhancing signal resolution. In the latter application, different statistical models are used to characterize images of prostate tissues, extracting different features. These features are then uses to segment the images in region of interests by means of an automatic procedure based on a statistical model of the extracted features. Finally, machine learning techniques are used for automatic classification of the different region of interests. In the context of neural activity signals, an example of bio-inspired dynamical network was developed to help in studies of motor-related processes in the brain of primate monkeys. The presented model aims to mimic the abstract functionality of a cell population in 7a parietal region of primate monkeys, during the execution of learned behavioural tasks.

A partial dependence factorial analysis to deal with selection bias in observational studis

This thesis presents a creative and practical approach to dealing with the problem of selection bias. Selection bias may be the most important vexing problem in program evaluation or in any line of research that attempts to assert causality. Some of the greatest minds in economics and statistics have scrutinized the problem of selection bias, with the resulting approaches – Rubin’s Potential Outcome Approach(Rosenbaum and Rubin,1983; Rubin, 1991,2001,2004) or Heckman’s Selection model (Heckman, 1979) – being widely accepted and used as the best fixes. These solutions to the bias that arises in particular from self selection are imperfect, and many researchers, when feasible, reserve their strongest causal inference for data from experimental rather than observational studies. The innovative aspect of this thesis is to propose a data transformation that allows measuring and testing in an automatic and multivariate way the presence of selection bias. The approach involves the construction of a multi-dimensional conditional space of the X matrix in which the bias associated with the treatment assignment has been eliminated. Specifically, we propose the use of a partial dependence analysis of the X-space as a tool for investigating the dependence relationship between a set of observable pre-treatment categorical covariates X and a treatment indicator variable T, in order to obtain a measure of bias according to their dependence structure. The measure of selection bias is then expressed in terms of inertia due to the dependence between X and T that has been eliminated. Given the measure of selection bias, we propose a multivariate test of imbalance in order to check if the detected bias is significant, by using the asymptotical distribution of inertia due to T (Estadella et al. 2005) , and by preserving the multivariate nature of data. Further, we propose the use of a clustering procedure as a tool to find groups of comparable units on which estimate local causal effects, and the use of the multivariate test of imbalance as a stopping rule in choosing the best cluster solution set. The method is non parametric, it does not call for modeling the data, based on some underlying theory or assumption about the selection process, but instead it calls for using the existing variability within the data and letting the data to speak. The idea of proposing this multivariate approach to measure selection bias and test balance comes from the consideration that in applied research all aspects of multivariate balance, not represented in the univariate variable- by-variable summaries, are ignored. The first part contains an introduction to evaluation methods as part of public and private decision process and a review of the literature of evaluation methods. The attention is focused on Rubin Potential Outcome Approach, matching methods, and briefly on Heckman’s Selection Model. The second part focuses on some resulting limitations of conventional methods, with particular attention to the problem of how testing in the correct way balancing. The third part contains the original contribution proposed , a simulation study that allows to check the performance of the method for a given dependence setting and an application to a real data set. Finally, we discuss, conclude and explain our future perspectives.

Statistical methods for analysis and processing of medical ultrasound: applications to segmentation and restoration

In this thesis two major topics inherent with medical ultrasound images are addressed: deconvolution and segmentation. In the first case a deconvolution algorithm is described allowing statistically consistent maximum a posteriori estimates of the tissue reflectivity to be restored. These estimates are proven to provide a reliable source of information for achieving an accurate characterization of biological tissues through the ultrasound echo. The second topic involves the definition of a semi automatic algorithm for myocardium segmentation in 2D echocardiographic images. The results show that the proposed method can reduce inter- and intra observer variability in myocardial contours delineation and is feasible and accurate even on clinical data.

Strategy as a matter of beliefs: the recorded music industry reinventing itself by rethinking itself

Managerial and organizational cognition studies the ways cognitions of managers in groups, organizations and industries shape their strategies and actions. Cognitions refer to simplified representations of managers’ internal and external environments, necessary to cope with the rich, ambiguous information requirements that characterize strategy making. Despite the important achievements in the field, many unresolved puzzles remain as to this process, particular as to the cognitive factors that condition actors in framing a response to a discontinuity, how actors can change their models in the face of a discontinuity, and the reciprocal relation between cognition and action. I leverage on the recent case of the recorded music industry in the face of the digital technology to study these issues, through a strategy-oriented study of the way early response to the discontinuity was constructed and of the subsequent evolution of this response. Through a longitudinal historical and cognitive analysis of actions and cognitions at both the industry and firm-level during the period in which the response took place (1999-2010), I gain important insights on the way historical beliefs in the industry shaped early response to the digital disruption, on the role of outsiders in promoting change through renewed vision about important issues, and on the reciprocal relationship between cognitive and strategic change.

Lifecycle analysis for surgery instruments at a hospital

Gli strumenti chirurgici sono importanti “devices” utilizzati come supporto indi-spensabile nella cura di pazienti negli ospedali. Essi sono caratterizzati da un intero ciclo di vita che inizia convenzionalmente nello “Store”, dove gli strumenti sterilizzati sono prelevati per essere utilizzati all’interno delle sale operatorie, e termina nuovamente nello “Store”, dove gli strumenti vengono immagazzinati per essere riutilizzati in un nuovo ciclo. Può accadere che le singole fasi del ciclo subiscano ritardi rispetto ai tempi previ-sti, non assicurando, pertanto, nelle sale operatorie, il corretto numero degli stru-menti secondo i tempi programmati. Il progetto che vado ad illustrare ha come obiettivo l’ottimizzazione del ciclo degli strumenti chirurgici all’interno di un nuovo ospedale, applicando i principi della Lean philosophy ed in particolare i metodi: “Poke Yoke, 5S e tracciabilità”. Per raggiungere tale scopo, il progetto è stato articolato come segue. In un primo momento si è osservato l’intero ciclo di vita degli strumenti nei due principali ospedali di Copenhagen (Hervel e Gentofte hospital). Ciò ha permesso di rilevare gli steps del ciclo, nonché di riscontrare sul campo i principali problemi relativi al ciclo stesso quali: bassa flessiblità, decentramento dei differenti reparti di cleaning e di store rispetto alle operation theatres ed un problema nel solleva-mento degli strumenti pesanti. Raccolte le dovute informazioni, si è passati alla fase sperimentale, in cui sono stati mappati due cicli di vita differenti, utilizzando tre strumenti di analisi: • Idef0 che consente di avere una visione gerarchica del ciclo; • Value stream Mapping che permette di evidenziare i principali sprechi del ciclo; • Simulator Tecnomatix che favorisce un punto di vista dinamico dell’analisi. Il primo ciclo mappato è stato creato con il solo scopo di mettere in risalto gli steps del ciclo e alcuni problemi rincontrati all’interno degli ospedali visitati. Il secondo ciclo, invece, è stato creato in ottica Lean al fine di risolvere alcuni tra i principali problemi riscontrati nei due ospedali e ottimizzare il primo ciclo. Si ricordi, infatti, che nel secondo ciclo le principali innovazioni introdotte sono state: l’utilizzo del Barcode e Rfid Tag per identificare e tracciare la posizione degli items, l’uso di un “Automatic and Retrievial Store” per minimizzare i tempi di inserimento e prelievo degli items e infine l’utilizzo di tre tipologie di carrello, per consentire un flessibile servizio di cura. Inoltre sono state proposte delle solu-zioni “Poke-Yoke” per risolvere alcuni problemi manuali degli ospedali. Per evidenziare il vantaggio del secondo ciclo di strumenti, è stato preso in consi-derazione il parametro “Lead time”e le due simulazioni, precedentemente create, sono state confrontate. Tale confronto ha evidenziato una radicale riduzione dei tempi (nonché dei costi associati) della nuova soluzione rispetto alla prima. Alla presente segue la trattazione in lingua inglese degli argomenti oggetto di ri-cerca. Buona lettura.

Query rewriting in information retrieval: automatic context extraction from local user documents to improve query results

The central objective of research in Information Retrieval (IR) is to discover new techniques to retrieve relevant information in order to satisfy an Information Need. The Information Need is satisfied when relevant information can be provided to the user. In IR, relevance is a fundamental concept which has changed over time, from popular to personal, i.e., what was considered relevant before was information for the whole population, but what is considered relevant now is specific information for each user. Hence, there is a need to connect the behavior of the system to the condition of a particular person and his social context; thereby an interdisciplinary sector called Human-Centered Computing was born. For the modern search engine, the information extracted for the individual user is crucial. According to the Personalized Search (PS), two different techniques are necessary to personalize a search: contextualization (interconnected conditions that occur in an activity), and individualization (characteristics that distinguish an individual). This movement of focus to the individual's need undermines the rigid linearity of the classical model overtaken the ``berry picking'' model which explains that the terms change thanks to the informational feedback received from the search activity introducing the concept of evolution of search terms. The development of Information Foraging theory, which observed the correlations between animal foraging and human information foraging, also contributed to this transformation through attempts to optimize the cost-benefit ratio. This thesis arose from the need to satisfy human individuality when searching for information, and it develops a synergistic collaboration between the frontiers of technological innovation and the recent advances in IR. The search method developed exploits what is relevant for the user by changing radically the way in which an Information Need is expressed, because now it is expressed through the generation of the query and its own context. As a matter of fact the method was born under the pretense to improve the quality of search by rewriting the query based on the contexts automatically generated from a local knowledge base. Furthermore, the idea of optimizing each IR system has led to develop it as a middleware of interaction between the user and the IR system. Thereby the system has just two possible actions: rewriting the query, and reordering the result. Equivalent actions to the approach was described from the PS that generally exploits information derived from analysis of user behavior, while the proposed approach exploits knowledge provided by the user. The thesis went further to generate a novel method for an assessment procedure, according to the "Cranfield paradigm", in order to evaluate this type of IR systems. The results achieved are interesting considering both the effectiveness achieved and the innovative approach undertaken together with the several applications inspired using a local knowledge base.