Los tratados bilaterales de inversión y el arbitraje internacional: ¿en dirección al mejor funcionamiento de las instituciones domésticas? (Tema Central)

Los tratados bilaterales sobre promoción y protección recíproca de inversiones (TBIs) tienen dos grandes objetivos: uno concreto e inmediato, el otro vago y mediato. Primero, estos acuerdos brindan garantías al inversor extranjero respecto del tratamiento que el Estado receptor otorgará a sus proyectos. Segundo, la firma de estos tratados pretende atraer más inversión extranjera a los países signatarios. El esquema de los TBIs, por lo tanto, se sustenta en la creencia de que los flujos de capitales extranjeros son afectados por la incapacidad institucional de los potenciales estados receptores. Estos tratados servirían para remediar esta falencia. Desde una perspectiva de política económica, no obstante, los beneficios para los países receptores son motivo de grandes discusiones. El presente trabajo busca ampliar este debate, analizando en qué medida los TBIs ayudan a los estados receptores a desarrollar las instituciones adecuadas para sus democracias y sus economías de mercado.

Condiciones, no concesiones. Cooperación económicofinanciera China-Ecuador (Tema Central)

In the last decade, the presence of China in Latin America has been characterized by a model of economic cooperation based on pragmatic principles of complementarity and mutual benefits. Latin America is presented as a “paradise” of natural resources and expanding markets, while China stands as the main financier and investor in the region. In this scenario, particularly since 2009, Ecuador has become one of the top recipients of Chinese funding and investment, mainly in strategic sectors such as energy and infrastructure. The presence of China in the country has been the subject of extensive discussions about the true benefits and costs behind its model of economic cooperation.

Myocyte remodeling in response to hypertrophic stimuli requires nucleocytoplasmic shuttling of muscle LIM protein

CSRP3 or muscle LIM protein (MLP) is a nucleocytoplasmic shuttling protein and a mechanosensor in cardiac myocytes. MLP regulation and function was studied in cultured neonatal rat myocytes treated with pharmacological or mechanical stimuli. Either verapamil or BDM decreased nuclear MLP while phenylephrine and cyclic strain increased it. These results suggest that myocyte contractility regulates MLP subcellular localization. When RNA polymerase II was inhibited with alpha-amanitin, nuclear MLP was reduced by 30%. However, when both RNA polymerase I and II were inhibited with actinomycin D, there was a 90% decrease in nuclear MLP suggesting that its nuclear translocation is regulated by both nuclear and nucleolar transcriptional activity. Using cell permeable synthetic peptides containing the putative nuclear localization signal (NLS) of MLP, nuclear import of the protein in cultured rat neonatal myocytes was inhibited. The NLS of MLP also localizes to the nucleolus. Inhibition of nuclear translocation prevented the increased protein accumulation in response to phenylephrine. Furthermore, cyclic strain of myocytes after prior NLS treatment to remove nuclear MLP resulted in disarrayed sarcomeres. Increased protein synthesis and brain natriuretic peptide expression were also prevented suggesting that MLP is required for remodeling of the myo filaments and gene expression. These findings suggest that nucleocytoplasmic shuttling MLP plays an important role in the regulation of the myocyte remodeling and hypertrophy and is required for adaptation to hypertrophic stimuli. (C) 2009 Elsevier Inc. All rights reserved.

On simple adaptive momentum

Simple Adaptive Momentum [1] was introduced as a simple means of speeding the training of multi-layer perceptrons (MLPs) by changing the momentum term depending on the angle between the current and previous changes in the weights of the MLP. In the original paper. the weight changes of the whole network are used in determining this angle. This paper considers adapting the momentum term using certain subsets of these weights. This idea was inspired by the author's object oriented approach to programming MLPs. successfully used in teaching students: this approach is also described. It is concluded that the angle is best determined using the weight changes in each layer separately.

An introduction to radial basis functions for system identification: a comparison with other neural network methods

A look is taken at the use of radial basis functions (RBFs), for nonlinear system identification. RBFs are firstly considered in detail themselves and are subsequently compared with a multi-layered perceptron (MLP), in terms of performance and usage.

Parkinson’s Disease tremor classification – a comparison between Support Vector Machines and neural networks

Deep Brain Stimulation has been used in the study of and for treating Parkinson’s Disease (PD) tremor symptoms since the 1980s. In the research reported here we have carried out a comparative analysis to classify tremor onset based on intraoperative microelectrode recordings of a PD patient’s brain Local Field Potential (LFP) signals. In particular, we compared the performance of a Support Vector Machine (SVM) with two well known artificial neural network classifiers, namely a Multiple Layer Perceptron (MLP) and a Radial Basis Function Network (RBN). The results show that in this study, using specifically PD data, the SVM provided an overall better classification rate achieving an accuracy of 81% recognition.

Modulation of stretch-induced myocyte remodeling and gene expression by nitric oxide: a novel role for lipoma preferred partner in myofibrillogenesis

Prolonged hemodynamic load as a result of hypertension eventually leads to maladaptive cardiac adaptation and heart failure. The signalling pathways that underlie these changes are still poorly understood. The adaptive response to mechanical load is mediated by mechanosensors which convert the mechanical stimuli into a biological response. We examined the effect of cyclic mechanical stretch on myocyte adaptation using neonatal rat ventricular myocytes with 10% (adaptive) or 20% (maladaptive) maximum strain, 1Hz for 48 hours to mimic in vivo mechanical stress. Cells were also treated with and without L-NAME, a general nitric oxide synthase (NOS) inhibitor to suppress NO production. Maladaptive 20% mechanical stretch led to a significant loss of intact sarcomeres which was rescued by LNAME (P<0.05, n≥5 cultures). We hypothesized that the mechanism was through NOinduced alteration of myocyte gene expression. L-NAME up-regulated the mechanosensing proteins Muscle LIM protein (MLP (by 100%, p<0.05, n=4 cultures)) and lipoma preferred partner, a novel cardiac protein (LPP (by 80%, p<0.05, n=4 cultures)). L-NAME also significantly altered the subcellular localisation of LPP and MLP in a manner that favoured growth and adaptation. These findings suggest that NO participates in stretch-mediated adaptation. The use of isoform selective NOS inhibitors indicated a complex interaction between iNOS and nNOS isoforms regulate gene expression. LPP knockdown by siRNA led to formation of α-actinin aggregates and Z-bodies showing that myofibrillogenesis was impaired. There was an up-regulation of E3 ubiquitin ligase (MUL1) by 75% (P<0.05, n=5 cultures). This indicates that NO contributes to stretch-mediated adaptation via the upregulation of proteins associated mechansensing and myofibrillogenesis, thereby presenting potential therapeutic targets during the progression of heart failure. Keywords: Mechanotransduction, heart failure, stretch, heart, hypertrophy

Complex-valued b-spline neural networks for modelling and inverse of wiener systems

Communication signal processing applications often involve complex-valued (CV) functional representations for signals and systems. CV artificial neural networks have been studied theoretically and applied widely in nonlinear signal and data processing [1–11]. Note that most artificial neural networks cannot be automatically extended from the real-valued (RV) domain to the CV domain because the resulting model would in general violate Cauchy-Riemann conditions, and this means that the training algorithms become unusable. A number of analytic functions were introduced for the fully CV multilayer perceptrons (MLP) [4]. A fully CV radial basis function (RBF) nework was introduced in [8] for regression and classification applications. Alternatively, the problem can be avoided by using two RV artificial neural networks, one processing the real part and the other processing the imaginary part of the CV signal/system. A even more challenging problem is the inverse of a CV

Nuclear accumulation of myocyte muscle LIM protein is regulated by heme oxygenase 1 and correlates with cardiac function in the transition to failure

Impaired mechanosensing leads to heart failure and we have previously shown that a decreased ratio of cytoplasmic to nuclear CSRP3/Muscle LIM protein (MLP ratio) is associated with a loss of mechanosensitivity. Here we tested whether passive or active stress/strain was important in modulating the MLP ratio and determined whether this correlated with heart function during the transition to failure. We exposed cultured neonatal rat myocytes to 10% cyclic mechanical stretch at 1 Hz, or electrically paced myocytes at 6.8 V (1 Hz) for 48 h. The MLP ratio decreased 50% (P < 0.05, n = 4) only in response to electrical pacing, suggesting impaired mechanosensitivity. Inhibition of contractility with 10 μM blebbistatin resulted in a ∼3 fold increase in the MLP ratio (n = 8, P < 0.05), indicating that myocyte contractility regulates nuclear MLP. Inhibition of histone deacetylase (HDAC) signaling with trichostatin A increased nuclear MLP following passive stretch, suggesting that HDACs block MLP nuclear accumulation. Inhibition of heme-oxygenase1 (HO-1) activity with PPZII blocked MLP nuclear accumulation. To examine how mechanosensitivity changes during the transition to heart failure, we studied a guinea pig model of angiotensin II infusion (400 ng/kg/min) over 12 weeks. Using subcellular fractionation we showed that the MLP ratio increased 88% (n = 4, P < 0.01) during compensated hypertrophy, but decreased significantly during heart failure (P < 0.001, n = 4). The MLP ratio correlated significantly with the E/A ratio (r = 0.71, P < 0.01 n = 12), a clinical measure of diastolic function. These data indicate for the first time that myocyte mechanosensitivity as indicated by the MLP ratio is regulated primarily by myocyte contractility via HO-1 and HDAC signaling.

A Road Following Approach Using Artificial Neural Networks Combinations

Navigation is a broad topic that has been receiving considerable attention from the mobile robotic community over the years. In order to execute autonomous driving in outdoor urban environments it is necessary to identify parts of the terrain that can be traversed and parts that should be avoided. This paper describes an analyses of terrain identification based on different visual information using a MLP artificial neural network and combining responses of many classifiers. Experimental tests using a vehicle and a video camera have been conducted in real scenarios to evaluate the proposed approach.

A neural networks study of quinone compounds with trypanocidal activity

This work investigates neural network models for predicting the trypanocidal activity of 28 quinone compounds. Artificial neural networks (ANN), such as multilayer perceptrons (MLP) and Kohonen models, were employed with the aim of modeling the nonlinear relationship between quantum and molecular descriptors and trypanocidal activity. The calculated descriptors and the principal components were used as input to train neural network models to verify the behavior of the nets. The best model for both network models (MLP and Kohonen) was obtained with four descriptors as input. The descriptors were T(5) (torsion angle), QTS1 (sum of absolute values of the atomic charges), VOLS2 (volume of the substituent at region B) and HOMO-1 (energy of the molecular orbital below HOMO). These descriptors provide information on the kind of interaction that occurs between the compounds and the biological receptor. Both neural network models used here can predict the trypanocidal activity of the quinone compounds with good agreement, with low errors in the testing set and a high correctness rate. Thanks to the nonlinear model obtained from the neural network models, we can conclude that electronic and structural properties are important factors in the interaction between quinone compounds that exhibit trypanocidal activity and their biological receptors. The final ANN models should be useful in the design of novel trypanocidal quinones having improved potency.

Automatic spiral analysis for objective assessment of motor symptoms in Parkinson's disease

Objective: To develop a method for objective quantification of PD motor symptoms related to Off episodes and peak dose dyskinesias, using spiral data gathered by using a touch screen telemetry device. The aim was to objectively characterize predominant motor phenotypes (bradykinesia and dyskinesia), to help in automating the process of visual interpretation of movement anomalies in spirals as rated by movement disorder specialists. Background: A retrospective analysis was conducted on recordings from 65 patients with advanced idiopathic PD from nine different clinics in Sweden, recruited from January 2006 until August 2010. In addition to the patient group, 10 healthy elderly subjects were recruited. Upper limb movement data were collected using a touch screen telemetry device from home environments of the subjects. Measurements with the device were performed four times per day during week-long test periods. On each test occasion, the subjects were asked to trace pre-drawn Archimedean spirals, using the dominant hand. The pre-drawn spiral was shown on the screen of the device. The spiral test was repeated three times per test occasion and they were instructed to complete it within 10 seconds. The device had a sampling rate of 10Hz and measured both position and time-stamps (in milliseconds) of the pen tip. Methods: Four independent raters (FB, DH, AJ and DN) used a web interface that animated the spiral drawings and allowed them to observe different kinematic features during the drawing process and to rate task performance. Initially, a number of kinematic features were assessed including ‘impairment’, ‘speed’, ‘irregularity’ and ‘hesitation’ followed by marking the predominant motor phenotype on a 3-category scale: tremor, bradykinesia and/or choreatic dyskinesia. There were only 2 test occasions for which all the four raters either classified them as tremor or could not identify the motor phenotype. Therefore, the two main motor phenotype categories were bradykinesia and dyskinesia. ‘Impairment’ was rated on a scale from 0 (no impairment) to 10 (extremely severe) whereas ‘speed’, ‘irregularity’ and ‘hesitation’ were rated on a scale from 0 (normal) to 4 (extremely severe). The proposed data-driven method consisted of the following steps. Initially, 28 spatiotemporal features were extracted from the time series signals before being presented to a Multilayer Perceptron (MLP) classifier. The features were based on different kinematic quantities of spirals including radius, angle, speed and velocity with the aim of measuring the severity of involuntary symptoms and discriminate between PD-specific (bradykinesia) and/or treatment-induced symptoms (dyskinesia). A Principal Component Analysis was applied on the features to reduce their dimensions where 4 relevant principal components (PCs) were retained and used as inputs to the MLP classifier. Finally, the MLP classifier mapped these components to the corresponding visually assessed motor phenotype scores for automating the process of scoring the bradykinesia and dyskinesia in PD patients whilst they draw spirals using the touch screen device. For motor phenotype (bradykinesia vs. dyskinesia) classification, the stratified 10-fold cross validation technique was employed. Results: There were good agreements between the four raters when rating the individual kinematic features with intra-class correlation coefficient (ICC) of 0.88 for ‘impairment’, 0.74 for ‘speed’, 0.70 for ‘irregularity’, and moderate agreements when rating ‘hesitation’ with an ICC of 0.49. When assessing the two main motor phenotype categories (bradykinesia or dyskinesia) in animated spirals the agreements between the four raters ranged from fair to moderate. There were good correlations between mean ratings of the four raters on individual kinematic features and computed scores. The MLP classifier classified the motor phenotype that is bradykinesia or dyskinesia with an accuracy of 85% in relation to visual classifications of the four movement disorder specialists. The test-retest reliability of the four PCs across the three spiral test trials was good with Cronbach’s Alpha coefficients of 0.80, 0.82, 0.54 and 0.49, respectively. These results indicate that the computed scores are stable and consistent over time. Significant differences were found between the two groups (patients and healthy elderly subjects) in all the PCs, except for the PC3. Conclusions: The proposed method automatically assessed the severity of unwanted symptoms and could reasonably well discriminate between PD-specific and/or treatment-induced motor symptoms, in relation to visual assessments of movement disorder specialists. The objective assessments could provide a time-effect summary score that could be useful for improving decision-making during symptom evaluation of individualized treatment when the goal is to maximize functional On time for patients while minimizing their Off episodes and troublesome dyskinesias.

Machine Learning Algorithms in Heavy Process Manufacturing

In a global economy, manufacturers mainly compete with cost efficiency of production, as the price of raw materials are similar worldwide. Heavy industry has two big issues to deal with. On the one hand there is lots of data which needs to be analyzed in an effective manner, and on the other hand making big improvements via investments in cooperate structure or new machinery is neither economically nor physically viable. Machine learning offers a promising way for manufacturers to address both these problems as they are in an excellent position to employ learning techniques with their massive resource of historical production data. However, choosing modelling a strategy in this setting is far from trivial and this is the objective of this article. The article investigates characteristics of the most popular classifiers used in industry today. Support Vector Machines, Multilayer Perceptron, Decision Trees, Random Forests, and the meta-algorithms Bagging and Boosting are mainly investigated in this work. Lessons from real-world implementations of these learners are also provided together with future directions when different learners are expected to perform well. The importance of feature selection and relevant selection methods in an industrial setting are further investigated. Performance metrics have also been discussed for the sake of completion.

Estudo, proposta e previsão de desempenho de um filtro de energia para experimentos com alta resolução de comprimento de onda em fontes pulsantes de nêutrons

Em fontes de nêutrons por spallation para pesquisa de materiais, o comprimento de onda dos nêutrons é geralmente determinado pelos tempos de percurso (TOF) dos nêutrons desde a fonte até o detector. A precisão atingível é limitada pelo fato de o tempo de emissão do pulso característico do sistema alvo/moderador ser diferente de zero (a situação ideal fictícia seria a emissão se ocorresse na forma de um impulso). “Moderadores acoplados” (elementos usados para produzir feixes de alta intensidade com nêutrons de baixa energia) apresentam um decaimento de intensidade em função do tempo muito longo, ao longo de todo o espectro usado nos experimentos. Por este motivo, “moderadores desacoplados”, os quais produzem feixes com intensidade mais reduzida, são freqüentemente usados para instrumentos que requerem alta resolução. Neste trabalho, propusemos e analisamos uma nova técnica de filtragem dinâmica de feixes de nêutrons polarizados de baixa energia para experimentos que utilizam TOF na determinação do comprimento de onda. O dispositivo consiste de um sistema ótico polarizador/analisador e um inversor de spin seletivo em energia, o qual funciona por ressonância espacial do spin. Variando a condição de ressonância em sincronia com a estrutura temporal do pulso de nêutrons (através do controle de campos magnéticos), o filtro pode ajustar a resolução de energia (ou de comprimento de onda) de pulsos de banda larga em tais experimentos, separando os nêutrons com a correta relação “TOF/comprimento de onda” dos demais Um método para o cálculo de desempenho do sistema foi apresentado em um Trabalho Individual (TI) (PARIZZI et al., 2002 - i), do qual se fará aqui uma breve revisão além de amplo uso na otimização dos parâmetros a serem ajustados para o projeto do filtro. Os resultados finais mostram que ganhos consideráveis em resolução podem ser obtidos com a aplicação desta técnica em experimentos de reflectometria por tempo de percurso, sem que para tal seja necessário comprometer a intensidade do feixe usado pelo mesmo instrumento quando operado em um modo de baixa resolução, dando ao usuário do instrumento a opção de escolher a relação ótima entre intensidade e resolução para seu experimento. Como parte da conclusão desta dissertação, é apresentada uma proposta de parâmetros para a construção deste tipo de filtro e previsão de desempenho da configuração proposta, baseada no software de modelamento desenvolvido.

Caracterização de escoamentos turbulentos transientes usando a transformada de ondaletas

Este trabalho apresenta a aplicação da transformada de ondaletas, como ferramenta de análise para o estudo de escoamentos turbulentos transientes e não homogêneos que podem ocorrer nas situações reais de engenharia, onde fenômenos transientes e não contínuos estão normalmente presentes. O estudo experimental da turbulência em túnel de vento habitualmente pressupõe que o escoamento seja estacionário; assim, fenômenos transientes são estudados como uma sucessão de situações estacionárias intermediárias. Isto é necessário porque a ferramenta clássica para o estudo experimental da turbulência, a análise de Fourier, só se aplica a fenômenos estacionários, pois seus resultados se referem a comportamentos de conjunto e as singularidades do sinal não aparecem na análise. Para estes escoamentos onde a transformada de Fourier não se aplica ou não apresenta resultados satisfatórios, a transformada de ondaletas, entre outras possibilidades, é a ferramenta matemática que vem sendo mais freqüentemente utilizada a partir da última década. São apresentados os fundamentos matemáticos, bem como uma breve história da transformada de ondaletas, da transformada de Fourier e da estatística aplicada á turbulência. Para estudar a transformada de ondaletas e buscar a melhor forma de aplicá-la ao estudo da turbulência, foram analisados três escoamentos distintos: na esteira de um cilindro, em turbulência homogênea e em um banco de tubos de configuração quadrangular. Os resultados experimentais foram obtidos por anemometria de fio quente. As medições foram feitas em um túnel de vento, partindo do repouso até atingir o regime permanente. Os dados experimentais obtidos foram analisados utilizando técnicas de ondaletas, usando várias ondaletas e várias transformadas de ondaletas diferentes. Os resultados são comparados entre si e com a transformada de Fourier. Também foram realizados ensaios em regime permanente para várias velocidades do escoamento entre o repouso e a velocidade nominal do ventilador, com o auxílio de um inversor de freqüência. Os resultados para a variação do número de Strouhal com a velocidade, obtidos da análise destes dados pela transformada de Fourier mostraram boa concordância com os obtidos da análise de ondaletas das aquisições transientes. Os resultados mostram que a transformada de ondaletas é uma ferramenta valiosa para a análise dos dados experimentais obtidos nos problemas investigados, qualificando e complementando a análise de Fourier onde esta se aplica e substituindo-a quando o fenômeno for não estacionário.