Carbon balance and crop residue management in dynamic equilibrium under a no-till system in Campos Gerais

The adoption of no-tillage systems (NT) and the maintenance of crop residues on the soil surface result in the long-term increase of carbon (C) in the system, promoting C sequestration and reducing C-CO2 emissions to the atmosphere. The purpose of this study was to evaluate the C sequestration rate and the minimum amount of crop residues required to maintain the dynamic C equilibrium (dC/dt = 0) of two soils (Typic Hapludox) with different textural classes. The experiment was arranged in a 2 x 2 x 2 randomized block factorial design. The following factors were analyzed: (a) two soil types: Typic Hapludox (Oxisol) with medium texture (LVTM) and Oxisol with clay texture (LVTA), (b) two sampling layers (0-5 and 5-20 cm), and (c) two sampling periods (P1 - October 2007; P2 - September 2008). Samples were collected from fields under a long-term (20 years) NT system with the following crop rotations: wheat/soybean/black oat + vetch/maize (LVTM) and wheat/maize/black oat + vetch/soybean (LVTA). The annual C sequestration rates were 0.83 and 0.76 Mg ha-1 for LVTM and LVTA, respectively. The estimates of the minimum amount of crop residues required to maintain a dynamic equilibrium (dC/dt = 0) were 7.13 and 6.53 Mg ha-1 year-1 for LVTM and LVTA, respectively. The C conversion rate in both studied soils was lower than that reported in other studies in the region, resulting in a greater amount of crop residues left on the soil surface.

Identification of Ligands for the Tau Exon 10 Splicing Regulatory Element RNA Using Dynamic Combinatorial Chemistry

We describe the use of dynamic combinatorial chemistry (DCC) to identify ligands for the stem-loop structure located at the exon 10-5'-intron junction of Tau pre-mRNA, which is involved in the onset of several tauopathies including frontotemporal dementia with Parkinsonism linked to chromosome 17 (FTDP-17). A series of ligands that combine the small aminoglycoside neamine and heteroaromatic moieties (azaquinolone and two acridines) have been identified by using DCC. These compounds effectively bind the stem-loop RNA target (the concentration required for 50% RNA response (EC(50)): 2-58 μM), as determined by fluorescence titration experiments. Importantly, most of them are able to stabilize both the wild-type and the +3 and +14 mutated sequences associated with the development of FTDP-17 without producing a significant change in the overall structure of the RNA (as analyzed by circular dichroism (CD) spectroscopy), which is a key factor for recognition by the splicing regulatory machinery. A good correlation has been found between the affinity of the ligands for the target and their ability to stabilize the RNA secondary structure.

Chemodiversity and molecular plasticity: recognition processes as explored by property spaces.

In the last few years, a need to account for molecular flexibility in drug-design methodologies has emerged, even if the dynamic behavior of molecular properties is seldom made explicit. For a flexible molecule, it is indeed possible to compute different values for a given conformation-dependent property and the ensemble of such values defines a property space that can be used to describe its molecular variability; a most representative case is the lipophilicity space. In this review, a number of applications of lipophilicity space and other property spaces are presented, showing that this concept can be fruitfully exploited: to investigate the constraints exerted by media of different levels of structural organization, to examine processes of molecular recognition and binding at an atomic level, to derive informative descriptors to be included in quantitative structure--activity relationships and to analyze protein simulations extracting the relevant information. Much molecular information is neglected in the descriptors used by medicinal chemists, while the concept of property space can fill this gap by accounting for the often-disregarded dynamic behavior of both small ligands and biomacromolecules. Property space also introduces some innovative concepts such as molecular sensitivity and plasticity, which appear best suited to explore the ability of a molecule to adapt itself to the environment variously modulating its property and conformational profiles. Globally, such concepts can enhance our understanding of biological phenomena providing fruitful descriptors in drug-design and pharmaceutical sciences.

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

Creating dynamic continuous improvement system for Larox Corporation

Today´s organizations must have the ability to react to rapid changes in the market. These rapid changes cause pressure to continuously find new efficient ways to organize work practices. Increased competition requires businesses to become more effective and to pay attention to quality of management and to make people to understand their work's impact on the final result. The fundamentals in continmuois improvement are systematic and agile tackling of indentified individual process constraints and the fact tha nothin finally improves without changes. Successful continuous improvement requires management commitment, education, implementation, measurement, recognition and regeneration. These ingredients form the foundation, both for breakthrough projects and small step ongoing improvement activities. One part of the organization's management system are the quality tools, which provide systematic methodologies for identifying problems, defining their root causes, finding solutions, gathering and sorting of data, supporting decision making and implementing the changes, and many other management tasks. Organizational change management includes processes and tools for managing the people in an organizational level change. These tools include a structured approach, which can be used for effective transition of organizations through change. When combined with the understanding of change management of individuals, these tools provide a framework for managing people in change,

Evaluation of Bubble Formation and Break Up in Suppression Pools by Using Pattern Recognition Methods

During a possible loss of coolant accident in BWRs, a large amount of steam will be released from the reactor pressure vessel to the suppression pool. Steam will be condensed into the suppression pool causing dynamic and structural loads to the pool. The formation and break up of bubbles can be measured by visual observation using a suitable pattern recognition algorithm. The aim of this study was to improve the preliminary pattern recognition algorithm, developed by Vesa Tanskanen in his doctoral dissertation, by using MATLAB. Video material from the PPOOLEX test facility, recorded during thermal stratification and mixing experiments, was used as a reference in the development of the algorithm. The developed algorithm consists of two parts: the pattern recognition of the bubbles and the analysis of recognized bubble images. The bubble recognition works well, but some errors will appear due to the complex structure of the pool. The results of the image analysis were reasonable. The volume and the surface area of the bubbles were not evaluated. Chugging frequencies calculated by using FFT fitted well into the results of oscillation frequencies measured in the experiments. The pattern recognition algorithm works in the conditions it is designed for. If the measurement configuration will be changed, some modifications have to be done. Numerous improvements are proposed for the future 3D equipment.

Dynamic nature of human rights: Rawls's critique of moral universalism

Human rights do not represent an absolute truth. Otherwise, they would represent ideology, which is contradictory to the basic idea of human rights itself. Consequently, there is a need for redefinition of the main presuppositions of modern conception of human rights represented in the Universal Declaration of Human Rights. This paper argues that Rawls's conception of human rights is significant for the refiguration of human rights. It represents the path towards postmodern idea of human rights and the recognition of difference.

Nestmate recognition in the large carpenter bee, Xylocopa virginica /

Abstract Many species of social insects have the ability to recognize their nestmates. In bees, sociality is maintained by bees that recognize which individuals should be helped and which should be hanned in order to maximize fitness (either inclusive or individual) (Hamilton 1964; Lin and Michener 1972). Since female bees generally lay eggs in a single nest, it is highly likely that bees found cohabitating in the same nest are siblings. According to the kin selection hypothesis, individuals should cooperate and avoid aggression with same sex nestmates (Hamilton 1964). However, in opposite sex pairs that are likely kin, aggression should increase among nestmates as an expression of inbreeding avoidance (Lihoreau et al. 2007). Female bees often guard nest entrances, recognizing and excluding foreign conspecific females that threaten to steal nest resources (Breed and Page 1991). Conversely, males that aggressively guard territories should avoid aggression towards other males that are likely kin (Shellman-Reeve and Gamboa 1984). In order to test whether Xy/ocopa virginica can distinguish nestmates from non-nestmates, circle tube testing arenas were used. Measures of aggression, cooperation and tolerance were evaluated to detennine the presence of nestmate recognition in this species. The results of this study indicate that male and female X virginica have the ability to distinguish nestmates from non-nestmates. Individuals in same sex pairs demonstrated increased pushing, biting, and C-posturing when faced with non-nestmates. Males in same sex pairs also attempted to pass (unsuccessfully) nOIl-nestmates more often than ncstmates, suggesting that this behaviour may be an cxpression of dominancc in males. Increased cooperation exemplified by successful passes was not observed among nestmates. However, incrcased tolerance in the [onn of head-to-head touching was observed for nestmates in female same sex and opposite sex pairs. These results supported the kin selection hypothesis. Moreover, increased tolerance among opposite sex non-nestmates suggested that X virginica do not demonstrate inbreeding avoidance among nestmates. 3 The second part of this study was conducted to establish the presence and extent of drifting, or travelling to different nests, in a Xylocopa virgillica population. Drifting in flying Hymenoptera is reported to be the result of navigation error and guard bees erroneously admitting novel individuals into the nest (Michener 1966). Since bees in this study were individually marked and captured at nest entrances, the locations where individuals were caught allowed me to determine where and how often bees travelled from nest to nest. Ifbees were captured near their home nests, changing nests may have been deliberate or explained by navigational error. However, ifbees were found in nests further away from their homes, this provides stronger evidence that flying towards a novel nest may have been deliberate. Female bees are often faithful to their own nests (Kasuya 1981) and no drifting was expected in female X virginica because they raise brood and contribute to nest maintenance activities. Contrary to females, males were not expected to remain faithful to a single nest. Results showed that many more females drifted than expected and that they were most often recaptured in a single nest, either their home nest or a novel nest. There were some females that were never caught in the same nest twice. In addition, females drifted to further nests when population density was low (in 2007), suggesting they seek out and claim nesting spaces when they are available. Males, as expected, showed the opposite pattern and most males drifted from nest to nest, never recaptured in the same location. This pattern indicates that males may be nesting wherever space is available, or nesting in benches nearest to their territories. This study reveals that both female and male X virginica are capable of nestmate recognition and use this ability in a dynamic environment, where nest membership is not as stable as once thought.

Examining the impact of trait anxiety on the recognition of facial emotional expressions

Question : Cette thèse comporte deux articles portant sur l’étude d’expressions faciales émotionnelles. Le processus de développement d’une nouvelle banque de stimuli émotionnels fait l’objet du premier article, alors que le deuxième article utilise cette banque pour étudier l’effet de l’anxiété de trait sur la reconnaissance des expressions statiques. Méthodes : Un total de 1088 clips émotionnels (34 acteurs X 8 émotions X 4 exemplaire) ont été alignés spatialement et temporellement de sorte que les yeux et le nez de chaque acteur occupent le même endroit dans toutes les vidéos. Les vidéos sont toutes d’une durée de 500ms et contiennent l’Apex de l’expression. La banque d’expressions statiques fut créée à partir de la dernière image des clips. Les stimuli ont été soumis à un processus de validation rigoureux. Dans la deuxième étude, les expressions statiques sont utilisées conjointement avec la méthode Bubbles dans le but d’étudier la reconnaissance des émotions chez des participants anxieux. Résultats : Dans la première étude, les meilleurs stimuli ont été sélectionnés [2 (statique & dynamique) X 8 (expressions) X 10 (acteurs)] et forment la banque d’expressions STOIC. Dans la deuxième étude, il est démontré que les individus présentant de l'anxiété de trait utilisent préférentiellement les basses fréquences spatiales de la région buccale du visage et ont une meilleure reconnaissance des expressions de peur. Discussion : La banque d’expressions faciales STOIC comporte des caractéristiques uniques qui font qu’elle se démarque des autres. Elle peut être téléchargée gratuitement, elle contient des vidéos naturelles et tous les stimuli ont été alignés, ce qui fait d’elle un outil de choix pour la communauté scientifique et les cliniciens. Les stimuli statiques de STOIC furent utilisés pour franchir une première étape dans la recherche sur la perception des émotions chez des individus présentant de l’anxiété de trait. Nous croyons que l’utilisation des basses fréquences est à la base des meilleures performances de ces individus, et que l’utilisation de ce type d’information visuelle désambigüise les expressions de peur et de surprise. Nous pensons également que c’est la névrose (chevauchement entre l'anxiété et la dépression), et non l’anxiété même qui est associée à de meilleures performances en reconnaissance d’expressions faciales de la peur. L’utilisation d’instruments mesurant ce concept devrait être envisagée dans de futures études.

Effectiveness Of Feature Detection Operators On The Performance Of Iris Biometric Recognition System

Iris Recognition is a highly efficient biometric identification system with great possibilities for future in the security systems area.Its robustness and unobtrusiveness, as opposed tomost of the currently deployed systems, make it a good candidate to replace most of thesecurity systems around. By making use of the distinctiveness of iris patterns, iris recognition systems obtain a unique mapping for each person. Identification of this person is possible by applying appropriate matching algorithm.In this paper, Daugman’s Rubber Sheet model is employed for irisnormalization and unwrapping, descriptive statistical analysis of different feature detection operators is performed, features extracted is encoded using Haar wavelets and for classification hammingdistance as a matching algorithm is used. The system was tested on the UBIRIS database. The edge detection algorithm, Canny, is found to be the best one to extract most of the iris texture. The success rate of feature detection using canny is 81%, False Accept Rate is 9% and False Reject Rate is 10%.

k-NN based On-Line Handwritten Character recognition system

On-line handwriting recognition has been a frontier area of research for the last few decades under the purview of pattern recognition. Word processing turns to be a vexing experience even if it is with the assistance of an alphanumeric keyboard in Indian languages. A natural solution for this problem is offered through online character recognition. There is abundant literature on the handwriting recognition of western, Chinese and Japanese scripts, but there are very few related to the recognition of Indic script such as Malayalam. This paper presents an efficient Online Handwritten character Recognition System for Malayalam Characters (OHR-M) using K-NN algorithm. It would help in recognizing Malayalam text entered using pen-like devices. A novel feature extraction method, a combination of time domain features and dynamic representation of writing direction along with its curvature is used for recognizing Malayalam characters. This writer independent system gives an excellent accuracy of 98.125% with recognition time of 15-30 milliseconds

Information Exchange and Fusion in Dynamic and Heterogeneous Distributed Environments

Context awareness, dynamic reconfiguration at runtime and heterogeneity are key characteristics of future distributed systems, particularly in ubiquitous and mobile computing scenarios. The main contributions of this dissertation are theoretical as well as architectural concepts facilitating information exchange and fusion in heterogeneous and dynamic distributed environments. Our main focus is on bridging the heterogeneity issues and, at the same time, considering uncertain, imprecise and unreliable sensor information in information fusion and reasoning approaches. A domain ontology is used to establish a common vocabulary for the exchanged information. We thereby explicitly support different representations for the same kind of information and provide Inter-Representation Operations that convert between them. Special account is taken of the conversion of associated meta-data that express uncertainty and impreciseness. The Unscented Transformation, for example, is applied to propagate Gaussian normal distributions across highly non-linear Inter-Representation Operations. Uncertain sensor information is fused using the Dempster-Shafer Theory of Evidence as it allows explicit modelling of partial and complete ignorance. We also show how to incorporate the Dempster-Shafer Theory of Evidence into probabilistic reasoning schemes such as Hidden Markov Models in order to be able to consider the uncertainty of sensor information when deriving high-level information from low-level data. For all these concepts we provide architectural support as a guideline for developers of innovative information exchange and fusion infrastructures that are particularly targeted at heterogeneous dynamic environments. Two case studies serve as proof of concept. The first case study focuses on heterogeneous autonomous robots that have to spontaneously form a cooperative team in order to achieve a common goal. The second case study is concerned with an approach for user activity recognition which serves as baseline for a context-aware adaptive application. Both case studies demonstrate the viability and strengths of the proposed solution and emphasize that the Dempster-Shafer Theory of Evidence should be preferred to pure probability theory in applications involving non-linear Inter-Representation Operations.

Dynamic Injection of Scribble Features into Graphical Diagram Editors

Almost everyone sketches. People use sketches day in and day out in many different and heterogeneous fields, to share their thoughts and clarify ambiguous interpretations, for example. The media used to sketch varies from analog tools like flipcharts to digital tools like smartboards. Whereas analog tools are usually affected by insufficient editing capabilities like cut/copy/paste, digital tools greatly support these scenarios. Digital tools can be grouped into informal and formal tools. Informal tools can be understood as simple drawing environments, whereas formal tools offer sophisticated support to create, optimize and validate diagrams of a certain application domain. Most digital formal tools force users to stick to a concrete syntax and editing workflow, limiting the user’s creativity. For that reason, a lot of people first sketch their ideas using the flexibility of analog or digital informal tools. Subsequently, the sketch is "portrayed" in an appropriate digital formal tool. This work presents Scribble, a highly configurable and extensible sketching framework which allows to dynamically inject sketching features into existing graphical diagram editors, based on Eclipse GEF. This allows to combine the flexibility of informal tools with the power of formal tools without any effort. No additional code is required to augment a GEF editor with sophisticated sketching features. Scribble recognizes drawn elements as well as handwritten text and automatically generates the corresponding domain elements. A local training data library is created dynamically by incrementally learning shapes, drawn by the user. Training data can be shared with others using the WebScribble web application which has been created as part of this work.

Attentional Selection in Object Recognition

A key problem in object recognition is selection, namely, the problem of identifying regions in an image within which to start the recognition process, ideally by isolating regions that are likely to come from a single object. Such a selection mechanism has been found to be crucial in reducing the combinatorial search involved in the matching stage of object recognition. Even though selection is of help in recognition, it has largely remained unsolved because of the difficulty in isolating regions belonging to objects under complex imaging conditions involving occlusions, changing illumination, and object appearances. This thesis presents a novel approach to the selection problem by proposing a computational model of visual attentional selection as a paradigm for selection in recognition. In particular, it proposes two modes of attentional selection, namely, attracted and pay attention modes as being appropriate for data and model-driven selection in recognition. An implementation of this model has led to new ways of extracting color, texture and line group information in images, and their subsequent use in isolating areas of the scene likely to contain the model object. Among the specific results in this thesis are: a method of specifying color by perceptual color categories for fast color region segmentation and color-based localization of objects, and a result showing that the recognition of texture patterns on model objects is possible under changes in orientation and occlusions without detailed segmentation. The thesis also presents an evaluation of the proposed model by integrating with a 3D from 2D object recognition system and recording the improvement in performance. These results indicate that attentional selection can significantly overcome the computational bottleneck in object recognition, both due to a reduction in the number of features, and due to a reduction in the number of matches during recognition using the information derived during selection. Finally, these studies have revealed a surprising use of selection, namely, in the partial solution of the pose of a 3D object.