912 resultados para Cheminformatics, (Q)SAR, Cross-Validation, Visualization, 3D-Space


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Topological indices have been applied to build QSAR models for a set of 20 antimalarial cyclic peroxy cetals. In order to evaluate the reliability of the proposed linear models leave-n-out and Internal Test Sets (ITS) approaches have been considered. The proposed procedure resulted in a robust and consensued prediction equation and here it is shown why it is superior to the employed standard cross-validation algorithms involving multilinear regression models

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In order to extend previous SAR and QSAR studies, 3D-QSAR analysis has been performed using CoMFA and CoMSIA approaches applied to a set of 39 alpha-(N)-heterocyclic carboxaldehydes thiosemicarbazones with their inhibitory activity values (IC(50)) evaluated against ribonucleotide reductase (RNR) of H.Ep.-2 cells (human epidermoid carcinoma), taken from selected literature. Both rigid and field alignment methods, taking the unsubstituted 2-formylpyridine thiosemicarbazone in its syn conformation as template, have been used to generate multiple predictive CoMFA and CoMSIA models derived from training sets and validated with the corresponding test sets. Acceptable predictive correlation coefficients (Q(cv)(2) from 0.360 to 0.609 for CoMFA and Q(cv)(2) from 0.394 to 0.580 for CoMSIA models) with high fitted correlation coefficients (r` from 0.881 to 0.981 for CoMFA and r(2) from 0.938 to 0.993 for CoMSIA models) and low standard errors (s from 0.135 to 0.383 for CoMFA and s from 0.098 to 0.240 for CoMSIA models) were obtained. More precise CoMFA and CoMSIA models have been derived considering the subset of thiosemicarbazones (TSC) substituted only at 5-position of the pyridine ring (n=22). Reasonable predictive correlation coefficients (Q(cv)(2) from 0.486 to 0.683 for CoMFA and Q(cv)(2) from 0.565 to 0.791 for CoMSIA models) with high fitted correlation coefficients (r(2) from 0.896 to 0.997 for CoMFA and r(2) from 0.991 to 0.998 for CoMSIA models) and very low standard errors (s from 0.040 to 0.179 for CoMFA and s from 0.029 to 0.068 for CoMSIA models) were obtained. The stability of each CoMFA and CoMSIA models was further assessed by performing bootstrapping analysis. For the two sets the generated CoMSIA models showed, in general, better statistics than the corresponding CoMFA models. The analysis of CoMFA and CoMSIA contour maps suggest that a hydrogen bond acceptor near the nitrogen of the pyridine ring can enhance inhibitory activity values. This observation agrees with literature data, which suggests that the nitrogen pyridine lone pairs can complex with the iron ion leading to species that inhibits RNR. The derived CoMFA and CoMSIA models contribute to understand the structural features of this class of TSC as antitumor agents in terms of steric, electrostatic, hydrophobic and hydrogen bond donor and hydrogen bond acceptor fields as well as to the rational design of this key enzyme inhibitors.

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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.

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Nowadays, classifying proteins in structural classes, which concerns the inference of patterns in their 3D conformation, is one of the most important open problems in Molecular Biology. The main reason for this is that the function of a protein is intrinsically related to its spatial conformation. However, such conformations are very difficult to be obtained experimentally in laboratory. Thus, this problem has drawn the attention of many researchers in Bioinformatics. Considering the great difference between the number of protein sequences already known and the number of three-dimensional structures determined experimentally, the demand of automated techniques for structural classification of proteins is very high. In this context, computational tools, especially Machine Learning (ML) techniques, have become essential to deal with this problem. In this work, ML techniques are used in the recognition of protein structural classes: Decision Trees, k-Nearest Neighbor, Naive Bayes, Support Vector Machine and Neural Networks. These methods have been chosen because they represent different paradigms of learning and have been widely used in the Bioinfornmatics literature. Aiming to obtain an improvment in the performance of these techniques (individual classifiers), homogeneous (Bagging and Boosting) and heterogeneous (Voting, Stacking and StackingC) multiclassification systems are used. Moreover, since the protein database used in this work presents the problem of imbalanced classes, artificial techniques for class balance (Undersampling Random, Tomek Links, CNN, NCL and OSS) are used to minimize such a problem. In order to evaluate the ML methods, a cross-validation procedure is applied, where the accuracy of the classifiers is measured using the mean of classification error rate, on independent test sets. These means are compared, two by two, by the hypothesis test aiming to evaluate if there is, statistically, a significant difference between them. With respect to the results obtained with the individual classifiers, Support Vector Machine presented the best accuracy. In terms of the multi-classification systems (homogeneous and heterogeneous), they showed, in general, a superior or similar performance when compared to the one achieved by the individual classifiers used - especially Boosting with Decision Tree and the StackingC with Linear Regression as meta classifier. The Voting method, despite of its simplicity, has shown to be adequate for solving the problem presented in this work. The techniques for class balance, on the other hand, have not produced a significant improvement in the global classification error. Nevertheless, the use of such techniques did improve the classification error for the minority class. In this context, the NCL technique has shown to be more appropriated

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This project was developed as a partnership between the Laboratory of Stratigraphical Analyses of the Geology Department of UFRN and the company Millennium Inorganic Chemicals Mineração Ltda. This company is located in the north end of the paraiban coast, in the municipal district of Mataraca. Millennium has as main prospected product, heavy minerals as ilmenita, rutilo and zircon presents in the sands of the dunes. These dunes are predominantly inactive, and overlap the superior portion of Barreiras Formation rocks. The mining happens with the use of a dredge that is emerged at an artificial lake on the dunes. This dredge removes sand dunes of the bottom lake (after it disassembles of the lake borders with water jets) and directs for the concentration plant, through piping where the minerals are then separate. The present work consisted in the acquisition external geometries of the dunes, where in the end a 3D Static Model could be set up of these sedimentary deposits with emphasis in the behavior of the structural top of Barreiras Formation rocks (inferior limit of the deposit). The knowledge of this surface is important in the phase of the plowing planning for the company, because a calculation mistake can do with that the dredge works too close of this limit, taking the risk that fragments can cause obstruction in the dredge generating a financial damage so much in the equipment repair as for the stopped days production. During the field stages (accomplished in 2006 and 2007) topographical techniques risings were used with Total Station and Geodesic GPS as well as shallow geophysical acquisitions with GPR (Ground Penetrating Radar). It was acquired almost 10,4km of topography and 10km of profiles GPR. The Geodesic GPS was used for the data geopositioning and topographical rising of a traverse line with 630m of extension in the stage of 2007. The GPR was shown a reliable method, ecologically clean, fast acquisition and with a low cost in relation to traditional methods as surveys. The main advantage of this equipment is obtain a continuous information to superior surface Barreiras Formation rocks. The static models 3D were elaborated starting from the obtained data being used two specific softwares for visualization 3D: GoCAD 2.0.8 and Datamine. The visualization 3D allows a better understanding of the Barreiras surface behavior as well as it makes possible the execution of several types of measurements, favoring like calculations and allowing that procedures used for mineral extraction is used with larger safety

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Objective: To identify potential prognostic factors for pulmonary thromboembolism (PTE), establishing a mathematical model to predict the risk for fatal PTE and nonfatal PTE.Method: the reports on 4,813 consecutive autopsies performed from 1979 to 1998 in a Brazilian tertiary referral medical school were reviewed for a retrospective study. From the medical records and autopsy reports of the 512 patients found with macroscopically and/or microscopically,documented PTE, data on demographics, underlying diseases, and probable PTE site of origin were gathered and studied by multiple logistic regression. Thereafter, the jackknife method, a statistical cross-validation technique that uses the original study patients to validate a clinical prediction rule, was performed.Results: the autopsy rate was 50.2%, and PTE prevalence was 10.6%. In 212 cases, PTE was the main cause of death (fatal PTE). The independent variables selected by the regression significance criteria that were more likely to be associated with fatal PTE were age (odds ratio [OR], 1.02; 95% confidence interval [CI], 1.00 to 1.03), trauma (OR, 8.5; 95% CI, 2.20 to 32.81), right-sided cardiac thrombi (OR, 1.96; 95% CI, 1.02 to 3.77), pelvic vein thrombi (OR, 3.46; 95% CI, 1.19 to 10.05); those most likely to be associated with nonfatal PTE were systemic arterial hypertension (OR, 0.51; 95% CI, 0.33 to 0.80), pneumonia (OR, 0.46; 95% CI, 0.30 to 0.71), and sepsis (OR, 0.16; 95% CI, 0.06 to 0.40). The results obtained from the application of the equation in the 512 cases studied using logistic regression analysis suggest the range in which logit p > 0.336 favors the occurrence of fatal PTE, logit p < - 1.142 favors nonfatal PTE, and logit P with intermediate values is not conclusive. The cross-validation prediction misclassification rate was 25.6%, meaning that the prediction equation correctly classified the majority of the cases (74.4%).Conclusions: Although the usefulness of this method in everyday medical practice needs to be confirmed by a prospective study, for the time being our results suggest that concerning prevention, diagnosis, and treatment of PTE, strict attention should be given to those patients presenting the variables that are significant in the logistic regression model.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Many psychophysical studies suggest that target depth and direction during reaches are processed independently, but the neurophysiological support to this view is so far limited. Here, we investigated the representation of reach depth and direction by single neurons in an area of the medial posterior parietal cortex (V6A). Single-unit activity was recorded from V6A in two Macaca fascicularis monkeys performing a fixation-to-reach task to targets at different depths and directions. We found that in a substantial percentage of V6A neurons depth and direction signals jointly influenced fixation, planning and arm movement-related activity in 3D space. While target depth and direction were equally encoded during fixation, depth tuning became stronger during arm movement planning, execution and target holding. The spatial tuning of fixation activity was often maintained across epochs, and this occurred more frequently in depth. These findings support for the first time the existence of a common neural substrate for the encoding of target depth and direction during reaching movements in the posterior parietal cortex. Present results also highlight the presence in V6A of several types of cells that process independently or jointly eye position and arm movement planning and execution signals in order to control reaches in 3D space. It is possible that depth and direction influence also the metrics of the reach action and that this effect on the reach kinematic variables can account for the spatial tuning we found in V6A neural activity. For this reason, we recorded and analyzed behavioral data when one monkey performed reaching movements in 3-D space. We evaluated how the target spatial position, in particular target depth and target direction, affected the kinematic parameters and trajectories describing the motor action properties.

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This paper describes informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography (GCxGC) and high-resolution mass spectrometry (HRMS). GCxGC-HRMS analysis produces large data sets that are rich with information, but highly complex. The size of the data and volume of information requires automated processing for comprehensive cross-sample analysis, but the complexity poses a challenge for developing robust methods. The approach developed here analyzes GCxGC-HRMS data from multiple samples to extract a feature template that comprehensively captures the pattern of peaks detected in the retention-times plane. Then, for each sample chromatogram, the template is geometrically transformed to align with the detected peak pattern and generate a set of feature measurements for cross-sample analyses such as sample classification and biomarker discovery. The approach avoids the intractable problem of comprehensive peak matching by using a few reliable peaks for alignment and peak-based retention-plane windows to define comprehensive features that can be reliably matched for cross-sample analysis. The informatics are demonstrated with a set of 18 samples from breast-cancer tumors, each from different individuals, six each for Grades 1-3. The features allow classification that matches grading by a cancer pathologist with 78% success in leave-one-out cross-validation experiments. The HRMS signatures of the features of interest can be examined for determining elemental compositions and identifying compounds.

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Nitazoxanide (2-acetolyloxy-N-(5-nitro 2-thiazolyl) benzamide; NTZ) represents the parent compound of a novel class of broad-spectrum anti-parasitic compounds named thiazolides. NTZ is active against a wide variety of intestinal and tissue-dwelling helminths, protozoa, enteric bacteria and a number of viruses infecting animals and humans. While potent, this poses a problem in practice, since this obvious non-selectivity can lead to undesired side effects in both humans and animals. In this study, we used real time PCR to determine the in vitro activities of 29 different thiazolides (NTZ-derivatives), which carry distinct modifications on both the thiazole- and the benzene moieties, against the tachyzoite stage of the intracellular protozoan Neospora caninum. The goal was to identify a highly active compound lacking the undesirable nitro group, which would have a more specific applicability, such as in food animals. By applying self-organizing molecular field analysis (SOMFA), these data were used to develop a predictive model for future drug design. SOMFA performs self-alignment of the molecules, and takes into account the steric and electrostatic properties, in order to determine 3D-quantitative structure activity relationship models. The best model was obtained by overlay of the thiazole moieties. Plotting of predicted versus experimentally determined activity produced an r2 value of 0.8052 and cross-validation using the "leave one out" methodology resulted in a q2 value of 0.7987. A master grid map showed that large steric groups at the R2 position, the nitrogen of the amide bond and position Y could greatly reduce activity, and the presence of large steric groups placed at positions X, R4 and surrounding the oxygen atom of the amide bond, may increase the activity of thiazolides against Neospora caninum tachyzoites. The model obtained here will be an important predictive tool for future development of this important class of drugs.

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Immersive virtual environments (IVEs) have the potential to afford natural interaction in the three-dimensional (3D) space around a user. However, interaction performance in 3D mid-air is often reduced and depends on a variety of ergonomics factors, the user's endurance, muscular strength, as well as fitness. In particular, in contrast to traditional desktop-based setups, users often cannot rest their arms in a comfortable pose during the interaction. In this article we analyze the impact of comfort on 3D selection tasks in an immersive desktop setup. First, in a pre-study we identified how comfortable or uncomfortable specific interaction positions and poses are for users who are standing upright. Then, we investigated differences in 3D selection task performance when users interact with their hands in a comfortable or uncomfortable body pose, while sitting on a chair in front of a table while the VE was displayed on a headmounted display (HMD). We conducted a Fitts' Law experiment to evaluate selection performance in different poses. The results suggest that users achieve a significantly higher performance in a comfortable pose when they rest their elbow on the table.

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Morphogenesis occurs in 3D space over time and is guided by coordinated gene expression programs. Here we use postembryonic development in Arabidopsis plants to investigate the genetic control of growth. We demonstrate that gene expression driving the production of the growth-stimulating hormone gibberellic acid and downstream growth factors is first induced within the radicle tip of the embryo. The center of cell expansion is, however, spatially displaced from the center of gene expression. Because the rapidly growing cells have very different geometry from that of those at the tip, we hypothesized that mechanical factors may contribute to this growth displacement. To this end we developed 3D finite-element method models of growing custom-designed digital embryos at cellular resolution. We used this framework to conceptualize how cell size, shape, and topology influence tissue growth and to explore the interplay of geometrical and genetic inputs into growth distribution. Our simulations showed that mechanical constraints are sufficient to explain the disconnect between the experimentally observed spatiotemporal patterns of gene expression and early postembryonic growth. The center of cell expansion is the position where genetic and mechanical facilitators of growth converge. We have thus uncovered a mechanism whereby 3D cellular geometry helps direct where genetically specified growth takes place.

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Radiomics is the high-throughput extraction and analysis of quantitative image features. For non-small cell lung cancer (NSCLC) patients, radiomics can be applied to standard of care computed tomography (CT) images to improve tumor diagnosis, staging, and response assessment. The first objective of this work was to show that CT image features extracted from pre-treatment NSCLC tumors could be used to predict tumor shrinkage in response to therapy. This is important since tumor shrinkage is an important cancer treatment endpoint that is correlated with probability of disease progression and overall survival. Accurate prediction of tumor shrinkage could also lead to individually customized treatment plans. To accomplish this objective, 64 stage NSCLC patients with similar treatments were all imaged using the same CT scanner and protocol. Quantitative image features were extracted and principal component regression with simulated annealing subset selection was used to predict shrinkage. Cross validation and permutation tests were used to validate the results. The optimal model gave a strong correlation between the observed and predicted shrinkages with . The second objective of this work was to identify sets of NSCLC CT image features that are reproducible, non-redundant, and informative across multiple machines. Feature sets with these qualities are needed for NSCLC radiomics models to be robust to machine variation and spurious correlation. To accomplish this objective, test-retest CT image pairs were obtained from 56 NSCLC patients imaged on three CT machines from two institutions. For each machine, quantitative image features with concordance correlation coefficient values greater than 0.90 were considered reproducible. Multi-machine reproducible feature sets were created by taking the intersection of individual machine reproducible feature sets. Redundant features were removed through hierarchical clustering. The findings showed that image feature reproducibility and redundancy depended on both the CT machine and the CT image type (average cine 4D-CT imaging vs. end-exhale cine 4D-CT imaging vs. helical inspiratory breath-hold 3D CT). For each image type, a set of cross-machine reproducible, non-redundant, and informative image features was identified. Compared to end-exhale 4D-CT and breath-hold 3D-CT, average 4D-CT derived image features showed superior multi-machine reproducibility and are the best candidates for clinical correlation.

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Objective: This research is focused in the creation and validation of a solution to the inverse kinematics problem for a 6 degrees of freedom human upper limb. This system is intended to work within a realtime dysfunctional motion prediction system that allows anticipatory actuation in physical Neurorehabilitation under the assisted-as-needed paradigm. For this purpose, a multilayer perceptron-based and an ANFIS-based solution to the inverse kinematics problem are evaluated. Materials and methods: Both the multilayer perceptron-based and the ANFIS-based inverse kinematics methods have been trained with three-dimensional Cartesian positions corresponding to the end-effector of healthy human upper limbs that execute two different activities of the daily life: "serving water from a jar" and "picking up a bottle". Validation of the proposed methodologies has been performed by a 10 fold cross-validation procedure. Results: Once trained, the systems are able to map 3D positions of the end-effector to the corresponding healthy biomechanical configurations. A high mean correlation coefficient and a low root mean squared error have been found for both the multilayer perceptron and ANFIS-based methods. Conclusions: The obtained results indicate that both systems effectively solve the inverse kinematics problem, but, due to its low computational load, crucial in real-time applications, along with its high performance, a multilayer perceptron-based solution, consisting in 3 input neurons, 1 hidden layer with 3 neurons and 6 output neurons has been considered the most appropriated for the target application.

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Esta tesis doctoral se enmarca dentro del campo de los sistemas embebidos reconfigurables, redes de sensores inalámbricas para aplicaciones de altas prestaciones, y computación distribuida. El documento se centra en el estudio de alternativas de procesamiento para sistemas embebidos autónomos distribuidos de altas prestaciones (por sus siglas en inglés, High-Performance Autonomous Distributed Systems (HPADS)), así como su evolución hacia el procesamiento de alta resolución. El estudio se ha llevado a cabo tanto a nivel de plataforma como a nivel de las arquitecturas de procesamiento dentro de la plataforma con el objetivo de optimizar aspectos tan relevantes como la eficiencia energética, la capacidad de cómputo y la tolerancia a fallos del sistema. Los HPADS son sistemas realimentados, normalmente formados por elementos distribuidos conectados o no en red, con cierta capacidad de adaptación, y con inteligencia suficiente para llevar a cabo labores de prognosis y/o autoevaluación. Esta clase de sistemas suele formar parte de sistemas más complejos llamados sistemas ciber-físicos (por sus siglas en inglés, Cyber-Physical Systems (CPSs)). Los CPSs cubren un espectro enorme de aplicaciones, yendo desde aplicaciones médicas, fabricación, o aplicaciones aeroespaciales, entre otras muchas. Para el diseño de este tipo de sistemas, aspectos tales como la confiabilidad, la definición de modelos de computación, o el uso de metodologías y/o herramientas que faciliten el incremento de la escalabilidad y de la gestión de la complejidad, son fundamentales. La primera parte de esta tesis doctoral se centra en el estudio de aquellas plataformas existentes en el estado del arte que por sus características pueden ser aplicables en el campo de los CPSs, así como en la propuesta de un nuevo diseño de plataforma de altas prestaciones que se ajuste mejor a los nuevos y más exigentes requisitos de las nuevas aplicaciones. Esta primera parte incluye descripción, implementación y validación de la plataforma propuesta, así como conclusiones sobre su usabilidad y sus limitaciones. Los principales objetivos para el diseño de la plataforma propuesta se enumeran a continuación: • Estudiar la viabilidad del uso de una FPGA basada en RAM como principal procesador de la plataforma en cuanto a consumo energético y capacidad de cómputo. • Propuesta de técnicas de gestión del consumo de energía en cada etapa del perfil de trabajo de la plataforma. •Propuestas para la inclusión de reconfiguración dinámica y parcial de la FPGA (por sus siglas en inglés, Dynamic Partial Reconfiguration (DPR)) de forma que sea posible cambiar ciertas partes del sistema en tiempo de ejecución y sin necesidad de interrumpir al resto de las partes. Evaluar su aplicabilidad en el caso de HPADS. Las nuevas aplicaciones y nuevos escenarios a los que se enfrentan los CPSs, imponen nuevos requisitos en cuanto al ancho de banda necesario para el procesamiento de los datos, así como en la adquisición y comunicación de los mismos, además de un claro incremento en la complejidad de los algoritmos empleados. Para poder cumplir con estos nuevos requisitos, las plataformas están migrando desde sistemas tradicionales uni-procesador de 8 bits, a sistemas híbridos hardware-software que incluyen varios procesadores, o varios procesadores y lógica programable. Entre estas nuevas arquitecturas, las FPGAs y los sistemas en chip (por sus siglas en inglés, System on Chip (SoC)) que incluyen procesadores embebidos y lógica programable, proporcionan soluciones con muy buenos resultados en cuanto a consumo energético, precio, capacidad de cómputo y flexibilidad. Estos buenos resultados son aún mejores cuando las aplicaciones tienen altos requisitos de cómputo y cuando las condiciones de trabajo son muy susceptibles de cambiar en tiempo real. La plataforma propuesta en esta tesis doctoral se ha denominado HiReCookie. La arquitectura incluye una FPGA basada en RAM como único procesador, así como un diseño compatible con la plataforma para redes de sensores inalámbricas desarrollada en el Centro de Electrónica Industrial de la Universidad Politécnica de Madrid (CEI-UPM) conocida como Cookies. Esta FPGA, modelo Spartan-6 LX150, era, en el momento de inicio de este trabajo, la mejor opción en cuanto a consumo y cantidad de recursos integrados, cuando además, permite el uso de reconfiguración dinámica y parcial. Es importante resaltar que aunque los valores de consumo son los mínimos para esta familia de componentes, la potencia instantánea consumida sigue siendo muy alta para aquellos sistemas que han de trabajar distribuidos, de forma autónoma, y en la mayoría de los casos alimentados por baterías. Por esta razón, es necesario incluir en el diseño estrategias de ahorro energético para incrementar la usabilidad y el tiempo de vida de la plataforma. La primera estrategia implementada consiste en dividir la plataforma en distintas islas de alimentación de forma que sólo aquellos elementos que sean estrictamente necesarios permanecerán alimentados, cuando el resto puede estar completamente apagado. De esta forma es posible combinar distintos modos de operación y así optimizar enormemente el consumo de energía. El hecho de apagar la FPGA para ahora energía durante los periodos de inactividad, supone la pérdida de la configuración, puesto que la memoria de configuración es una memoria volátil. Para reducir el impacto en el consumo y en el tiempo que supone la reconfiguración total de la plataforma una vez encendida, en este trabajo, se incluye una técnica para la compresión del archivo de configuración de la FPGA, de forma que se consiga una reducción del tiempo de configuración y por ende de la energía consumida. Aunque varios de los requisitos de diseño pueden satisfacerse con el diseño de la plataforma HiReCookie, es necesario seguir optimizando diversos parámetros tales como el consumo energético, la tolerancia a fallos y la capacidad de procesamiento. Esto sólo es posible explotando todas las posibilidades ofrecidas por la arquitectura de procesamiento en la FPGA. Por lo tanto, la segunda parte de esta tesis doctoral está centrada en el diseño de una arquitectura reconfigurable denominada ARTICo3 (Arquitectura Reconfigurable para el Tratamiento Inteligente de Cómputo, Confiabilidad y Consumo de energía) para la mejora de estos parámetros por medio de un uso dinámico de recursos. ARTICo3 es una arquitectura de procesamiento para FPGAs basadas en RAM, con comunicación tipo bus, preparada para dar soporte para la gestión dinámica de los recursos internos de la FPGA en tiempo de ejecución gracias a la inclusión de reconfiguración dinámica y parcial. Gracias a esta capacidad de reconfiguración parcial, es posible adaptar los niveles de capacidad de procesamiento, energía consumida o tolerancia a fallos para responder a las demandas de la aplicación, entorno, o métricas internas del dispositivo mediante la adaptación del número de recursos asignados para cada tarea. Durante esta segunda parte de la tesis se detallan el diseño de la arquitectura, su implementación en la plataforma HiReCookie, así como en otra familia de FPGAs, y su validación por medio de diferentes pruebas y demostraciones. Los principales objetivos que se plantean la arquitectura son los siguientes: • Proponer una metodología basada en un enfoque multi-hilo, como las propuestas por CUDA (por sus siglas en inglés, Compute Unified Device Architecture) u Open CL, en la cual distintos kernels, o unidades de ejecución, se ejecuten en un numero variable de aceleradores hardware sin necesidad de cambios en el código de aplicación. • Proponer un diseño y proporcionar una arquitectura en la que las condiciones de trabajo cambien de forma dinámica dependiendo bien de parámetros externos o bien de parámetros que indiquen el estado de la plataforma. Estos cambios en el punto de trabajo de la arquitectura serán posibles gracias a la reconfiguración dinámica y parcial de aceleradores hardware en tiempo real. • Explotar las posibilidades de procesamiento concurrente, incluso en una arquitectura basada en bus, por medio de la optimización de las transacciones en ráfaga de datos hacia los aceleradores. •Aprovechar las ventajas ofrecidas por la aceleración lograda por módulos puramente hardware para conseguir una mejor eficiencia energética. • Ser capaces de cambiar los niveles de redundancia de hardware de forma dinámica según las necesidades del sistema en tiempo real y sin cambios para el código de aplicación. • Proponer una capa de abstracción entre el código de aplicación y el uso dinámico de los recursos de la FPGA. El diseño en FPGAs permite la utilización de módulos hardware específicamente creados para una aplicación concreta. De esta forma es posible obtener rendimientos mucho mayores que en el caso de las arquitecturas de propósito general. Además, algunas FPGAs permiten la reconfiguración dinámica y parcial de ciertas partes de su lógica en tiempo de ejecución, lo cual dota al diseño de una gran flexibilidad. Los fabricantes de FPGAs ofrecen arquitecturas predefinidas con la posibilidad de añadir bloques prediseñados y poder formar sistemas en chip de una forma más o menos directa. Sin embargo, la forma en la que estos módulos hardware están organizados dentro de la arquitectura interna ya sea estática o dinámicamente, o la forma en la que la información se intercambia entre ellos, influye enormemente en la capacidad de cómputo y eficiencia energética del sistema. De la misma forma, la capacidad de cargar módulos hardware bajo demanda, permite añadir bloques redundantes que permitan aumentar el nivel de tolerancia a fallos de los sistemas. Sin embargo, la complejidad ligada al diseño de bloques hardware dedicados no debe ser subestimada. Es necesario tener en cuenta que el diseño de un bloque hardware no es sólo su propio diseño, sino también el diseño de sus interfaces, y en algunos casos de los drivers software para su manejo. Además, al añadir más bloques, el espacio de diseño se hace más complejo, y su programación más difícil. Aunque la mayoría de los fabricantes ofrecen interfaces predefinidas, IPs (por sus siglas en inglés, Intelectual Property) comerciales y plantillas para ayudar al diseño de los sistemas, para ser capaces de explotar las posibilidades reales del sistema, es necesario construir arquitecturas sobre las ya establecidas para facilitar el uso del paralelismo, la redundancia, y proporcionar un entorno que soporte la gestión dinámica de los recursos. Para proporcionar este tipo de soporte, ARTICo3 trabaja con un espacio de soluciones formado por tres ejes fundamentales: computación, consumo energético y confiabilidad. De esta forma, cada punto de trabajo se obtiene como una solución de compromiso entre estos tres parámetros. Mediante el uso de la reconfiguración dinámica y parcial y una mejora en la transmisión de los datos entre la memoria principal y los aceleradores, es posible dedicar un número variable de recursos en el tiempo para cada tarea, lo que hace que los recursos internos de la FPGA sean virtualmente ilimitados. Este variación en el tiempo del número de recursos por tarea se puede usar bien para incrementar el nivel de paralelismo, y por ende de aceleración, o bien para aumentar la redundancia, y por lo tanto el nivel de tolerancia a fallos. Al mismo tiempo, usar un numero óptimo de recursos para una tarea mejora el consumo energético ya que bien es posible disminuir la potencia instantánea consumida, o bien el tiempo de procesamiento. Con el objetivo de mantener los niveles de complejidad dentro de unos límites lógicos, es importante que los cambios realizados en el hardware sean totalmente transparentes para el código de aplicación. A este respecto, se incluyen distintos niveles de transparencia: • Transparencia a la escalabilidad: los recursos usados por una misma tarea pueden ser modificados sin que el código de aplicación sufra ningún cambio. • Transparencia al rendimiento: el sistema aumentara su rendimiento cuando la carga de trabajo aumente, sin cambios en el código de aplicación. • Transparencia a la replicación: es posible usar múltiples instancias de un mismo módulo bien para añadir redundancia o bien para incrementar la capacidad de procesamiento. Todo ello sin que el código de aplicación cambie. • Transparencia a la posición: la posición física de los módulos hardware es arbitraria para su direccionamiento desde el código de aplicación. • Transparencia a los fallos: si existe un fallo en un módulo hardware, gracias a la redundancia, el código de aplicación tomará directamente el resultado correcto. • Transparencia a la concurrencia: el hecho de que una tarea sea realizada por más o menos bloques es transparente para el código que la invoca. Por lo tanto, esta tesis doctoral contribuye en dos líneas diferentes. En primer lugar, con el diseño de la plataforma HiReCookie y en segundo lugar con el diseño de la arquitectura ARTICo3. Las principales contribuciones de esta tesis se resumen a continuación. • Arquitectura de la HiReCookie incluyendo: o Compatibilidad con la plataforma Cookies para incrementar las capacidades de esta. o División de la arquitectura en distintas islas de alimentación. o Implementación de los diversos modos de bajo consumo y políticas de despertado del nodo. o Creación de un archivo de configuración de la FPGA comprimido para reducir el tiempo y el consumo de la configuración inicial. • Diseño de la arquitectura reconfigurable para FPGAs basadas en RAM ARTICo3: o Modelo de computación y modos de ejecución inspirados en el modelo de CUDA pero basados en hardware reconfigurable con un número variable de bloques de hilos por cada unidad de ejecución. o Estructura para optimizar las transacciones de datos en ráfaga proporcionando datos en cascada o en paralelo a los distinto módulos incluyendo un proceso de votado por mayoría y operaciones de reducción. o Capa de abstracción entre el procesador principal que incluye el código de aplicación y los recursos asignados para las diferentes tareas. o Arquitectura de los módulos hardware reconfigurables para mantener la escalabilidad añadiendo una la interfaz para las nuevas funcionalidades con un simple acceso a una memoria RAM interna. o Caracterización online de las tareas para proporcionar información a un módulo de gestión de recursos para mejorar la operación en términos de energía y procesamiento cuando además se opera entre distintos nieles de tolerancia a fallos. El documento está dividido en dos partes principales formando un total de cinco capítulos. En primer lugar, después de motivar la necesidad de nuevas plataformas para cubrir las nuevas aplicaciones, se detalla el diseño de la plataforma HiReCookie, sus partes, las posibilidades para bajar el consumo energético y se muestran casos de uso de la plataforma así como pruebas de validación del diseño. La segunda parte del documento describe la arquitectura reconfigurable, su implementación en varias FPGAs, y pruebas de validación en términos de capacidad de procesamiento y consumo energético, incluyendo cómo estos aspectos se ven afectados por el nivel de tolerancia a fallos elegido. Los capítulos a lo largo del documento son los siguientes: El capítulo 1 analiza los principales objetivos, motivación y aspectos teóricos necesarios para seguir el resto del documento. El capítulo 2 está centrado en el diseño de la plataforma HiReCookie y sus posibilidades para disminuir el consumo de energía. El capítulo 3 describe la arquitectura reconfigurable ARTICo3. El capítulo 4 se centra en las pruebas de validación de la arquitectura usando la plataforma HiReCookie para la mayoría de los tests. Un ejemplo de aplicación es mostrado para analizar el funcionamiento de la arquitectura. El capítulo 5 concluye esta tesis doctoral comentando las conclusiones obtenidas, las contribuciones originales del trabajo y resultados y líneas futuras. ABSTRACT This PhD Thesis is framed within the field of dynamically reconfigurable embedded systems, advanced sensor networks and distributed computing. The document is centred on the study of processing solutions for high-performance autonomous distributed systems (HPADS) as well as their evolution towards High performance Computing (HPC) systems. The approach of the study is focused on both platform and processor levels to optimise critical aspects such as computing performance, energy efficiency and fault tolerance. HPADS are considered feedback systems, normally networked and/or distributed, with real-time adaptive and predictive functionality. These systems, as part of more complex systems known as Cyber-Physical Systems (CPSs), can be applied in a wide range of fields such as military, health care, manufacturing, aerospace, etc. For the design of HPADS, high levels of dependability, the definition of suitable models of computation, and the use of methodologies and tools to support scalability and complexity management, are required. The first part of the document studies the different possibilities at platform design level in the state of the art, together with description, development and validation tests of the platform proposed in this work to cope with the previously mentioned requirements. The main objectives targeted by this platform design are the following: • Study the feasibility of using SRAM-based FPGAs as the main processor of the platform in terms of energy consumption and performance for high demanding applications. • Analyse and propose energy management techniques to reduce energy consumption in every stage of the working profile of the platform. • Provide a solution with dynamic partial and wireless remote HW reconfiguration (DPR) to be able to change certain parts of the FPGA design at run time and on demand without interrupting the rest of the system. • Demonstrate the applicability of the platform in different test-bench applications. In order to select the best approach for the platform design in terms of processing alternatives, a study of the evolution of the state-of-the-art platforms is required to analyse how different architectures cope with new more demanding applications and scenarios: security, mixed-critical systems for aerospace, multimedia applications, or military environments, among others. In all these scenarios, important changes in the required processing bandwidth or the complexity of the algorithms used are provoking the migration of the platforms from single microprocessor architectures to multiprocessing and heterogeneous solutions with more instant power consumption but higher energy efficiency. Within these solutions, FPGAs and Systems on Chip including FPGA fabric and dedicated hard processors, offer a good trade of among flexibility, processing performance, energy consumption and price, when they are used in demanding applications where working conditions are very likely to vary over time and high complex algorithms are required. The platform architecture proposed in this PhD Thesis is called HiReCookie. It includes an SRAM-based FPGA as the main and only processing unit. The FPGA selected, the Xilinx Spartan-6 LX150, was at the beginning of this work the best choice in terms of amount of resources and power. Although, the power levels are the lowest of these kind of devices, they can be still very high for distributed systems that normally work powered by batteries. For that reason, it is necessary to include different energy saving possibilities to increase the usability of the platform. In order to reduce energy consumption, the platform architecture is divided into different power islands so that only those parts of the systems that are strictly needed are powered on, while the rest of the islands can be completely switched off. This allows a combination of different low power modes to decrease energy. In addition, one of the most important handicaps of SRAM-based FPGAs is that they are not alive at power up. Therefore, recovering the system from a switch-off state requires to reload the FPGA configuration from a non-volatile memory device. For that reason, this PhD Thesis also proposes a methodology to compress the FPGA configuration file in order to reduce time and energy during the initial configuration process. Although some of the requirements for the design of HPADS are already covered by the design of the HiReCookie platform, it is necessary to continue improving energy efficiency, computing performance and fault tolerance. This is only possible by exploiting all the opportunities provided by the processing architectures configured inside the FPGA. Therefore, the second part of the thesis details the design of the so called ARTICo3 FPGA architecture to enhance the already intrinsic capabilities of the FPGA. ARTICo3 is a DPR-capable bus-based virtual architecture for multiple HW acceleration in SRAM-based FPGAs. The architecture provides support for dynamic resource management in real time. In this way, by using DPR, it will be possible to change the levels of computing performance, energy consumption and fault tolerance on demand by increasing or decreasing the amount of resources used by the different tasks. Apart from the detailed design of the architecture and its implementation in different FPGA devices, different validation tests and comparisons are also shown. The main objectives targeted by this FPGA architecture are listed as follows: • Provide a method based on a multithread approach such as those offered by CUDA (Compute Unified Device Architecture) or OpenCL kernel executions, where kernels are executed in a variable number of HW accelerators without requiring application code changes. • Provide an architecture to dynamically adapt working points according to either self-measured or external parameters in terms of energy consumption, fault tolerance and computing performance. Taking advantage of DPR capabilities, the architecture must provide support for a dynamic use of resources in real time. • Exploit concurrent processing capabilities in a standard bus-based system by optimizing data transactions to and from HW accelerators. • Measure the advantage of HW acceleration as a technique to boost performance to improve processing times and save energy by reducing active times for distributed embedded systems. • Dynamically change the levels of HW redundancy to adapt fault tolerance in real time. • Provide HW abstraction from SW application design. FPGAs give the possibility of designing specific HW blocks for every required task to optimise performance while some of them include the possibility of including DPR. Apart from the possibilities provided by manufacturers, the way these HW modules are organised, addressed and multiplexed in area and time can improve computing performance and energy consumption. At the same time, fault tolerance and security techniques can also be dynamically included using DPR. However, the inherent complexity of designing new HW modules for every application is not negligible. It does not only consist of the HW description, but also the design of drivers and interfaces with the rest of the system, while the design space is widened and more complex to define and program. Even though the tools provided by the majority of manufacturers already include predefined bus interfaces, commercial IPs, and templates to ease application prototyping, it is necessary to improve these capabilities. By adding new architectures on top of them, it is possible to take advantage of parallelization and HW redundancy while providing a framework to ease the use of dynamic resource management. ARTICo3 works within a solution space where working points change at run time in a 3D space defined by three different axes: Computation, Consumption, and Fault Tolerance. Therefore, every working point is found as a trade-off solution among these three axes. By means of DPR, different accelerators can be multiplexed so that the amount of available resources for any application is virtually unlimited. Taking advantage of DPR capabilities and a novel way of transmitting data to the reconfigurable HW accelerators, it is possible to dedicate a dynamically-changing number of resources for a given task in order to either boost computing speed or adding HW redundancy and a voting process to increase fault-tolerance levels. At the same time, using an optimised amount of resources for a given task reduces energy consumption by reducing instant power or computing time. In order to keep level complexity under certain limits, it is important that HW changes are transparent for the application code. Therefore, different levels of transparency are targeted by the system: • Scalability transparency: a task must be able to expand its resources without changing the system structure or application algorithms. • Performance transparency: the system must reconfigure itself as load changes. • Replication transparency: multiple instances of the same task are loaded to increase reliability and performance. • Location transparency: resources are accessed with no knowledge of their location by the application code. • Failure transparency: task must be completed despite a failure in some components. • Concurrency transparency: different tasks will work in a concurrent way transparent to the application code. Therefore, as it can be seen, the Thesis is contributing in two different ways. First with the design of the HiReCookie platform and, second with the design of the ARTICo3 architecture. The main contributions of this PhD Thesis are then listed below: • Architecture of the HiReCookie platform including: o Compatibility of the processing layer for high performance applications with the Cookies Wireless Sensor Network platform for fast prototyping and implementation. o A division of the architecture in power islands. o All the different low-power modes. o The creation of the partial-initial bitstream together with the wake-up policies of the node. • The design of the reconfigurable architecture for SRAM FPGAs: ARTICo3: o A model of computation and execution modes inspired in CUDA but based on reconfigurable HW with a dynamic number of thread blocks per kernel. o A structure to optimise burst data transactions providing coalesced or parallel data to HW accelerators, parallel voting process and reduction operation. o The abstraction provided to the host processor with respect to the operation of the kernels in terms of the number of replicas, modes of operation, location in the reconfigurable area and addressing. o The architecture of the modules representing the thread blocks to make the system scalable by adding functional units only adding an access to a BRAM port. o The online characterization of the kernels to provide information to a scheduler or resource manager in terms of energy consumption and processing time when changing among different fault-tolerance levels, as well as if a kernel is expected to work in the memory-bounded or computing-bounded areas. The document of the Thesis is divided into two main parts with a total of five chapters. First, after motivating the need for new platforms to cover new more demanding applications, the design of the HiReCookie platform, its parts and several partial tests are detailed. The design of the platform alone does not cover all the needs of these applications. Therefore, the second part describes the architecture inside the FPGA, called ARTICo3, proposed in this PhD Thesis. The architecture and its implementation are tested in terms of energy consumption and computing performance showing different possibilities to improve fault tolerance and how this impact in energy and time of processing. Chapter 1 shows the main goals of this PhD Thesis and the technology background required to follow the rest of the document. Chapter 2 shows all the details about the design of the FPGA-based platform HiReCookie. Chapter 3 describes the ARTICo3 architecture. Chapter 4 is focused on the validation tests of the ARTICo3 architecture. An application for proof of concept is explained where typical kernels related to image processing and encryption algorithms are used. Further experimental analyses are performed using these kernels. Chapter 5 concludes the document analysing conclusions, comments about the contributions of the work, and some possible future lines for the work.