Padrão de especialização e saldo comercial da China com Estados Unidos, Europa e Ásia no início do Século XXI

The rise of China has been providing various effects on developed and developing countries, particularly its Asian neighbors which compete in third markets, such as the U.S., Europe and Japan this sense, the present study aimed to analyze the pattern of Chinese trade with two different groups of countries: the Asian neighbors (Asian Tigers and Dragons) and developed countries (United States, Europe and Japan) during the 2000s. To this end, this paper adopts the methodology of second breakdown of trade technological intensity proposed by Lall (2000). Furthermore, to analyze the intensity of trade between these economies as well as potential threats over their Chinese business partners close, we calculated the following indicators of trade: Trade Intensity Index (TII), Trade Orientation Index (TOI) , Intra-Industry Trade Index (ICII), Index Of Revealed Comparative Advantage (RCA), and, finally, the Contribution To The Balance Index (ICS). The main result achieved is the existence of China\'s trade patterns differ for each group of countries, according to the type of expertise of each partner.

Crescimento e poluição: a curva ambiental de Kuznets para o Brasil.

Este trabalho tem como objetivo verificar se no Brasil exista a relação da hipótese da curva ambiental de Kuznets, onde atividades que degradam o meio ambiente vão diminuindo após certo ponto de renda per capita atingido. Essa teoria será verificada através de um modelo estimado por mínimos quadrados ordinários com as variáveis de emissão de CO2 e a renda per capita e seus termos ao quadrado e ao cubo. Segundo os resultados obtidos, o Brasil ainda não apresenta este padrão de curva de Kuznets.

Efeito do consumo de farinha de linhaça (Linum usitatissimum) no crescimento de ratos Wistar e relação com a digestibilidade de globulinas e fatores antinutricionais protéicos

Linseed is an important oilseed consumed raw as nutritional supplement, that although represents a rich source of nutrients, its nutritional value could be impaired due to the presence of antinutritional factors. In this study, protein fractions from raw linseed flour were extracted and isolated being obtained 12% of albumins, 82% of globulins, 5% of glutelins and 1% of prolamins. These proteins were visualized by SDS-PAGE and albumins showed low molecular mass protein bands around 21 kDa and minor bands, similar to that of trypsin inhibitor; Globulins presented protein bands with high molecular masses, which possibly are constituents of multimeric proteins, such as legumins. After determination of the centesimal composition of raw linseed, it was used as exclusive protein source for young rats to evaluate its effect on animal growth. The results showed negative effects on rat growth (weight gain 73% less than the control group) and reduction of intestinal villus (35%), that could be related with in vitro and in vivo globulin digestibility and proteinaceous antinutritional factors (mammalian digestive enzymes inhibitors and lectins) in albumin fraction. Native globulins showed, by SDS-PAGE, low susceptibility in vitro to trypsin and chymotrypsin, however presented high degradation by pancreatin. Thermal treatment of globulins for 5 and 15 minutes at 100ºC improved considerably its digestibility by trypsin and pancreatin. Globulins presented 93.2% in vivo digestibility, similar to the control protein. Albumin fraction had high trypsin inhibition activity (100%) and chymotrypsin inhibition of 28.3%; haemagglutinating activity was not detected. The results of this study indicate the negative action of trypsin inhibitors on animal growth, but can not be discarded its combined action with other antinutritional factors, which could compromise the raw linseed utilization as an alternative food

CRESCIMENTO INICIAL E CONCENTRAÇÃO DE NUTRIENTES EM CLONES DE Eucalyptus urophylla x Eucalyptus grandis SOB INTERFERÊNCIA DE PLANTAS DANINHAS

A presença de plantas daninhas em plantios de eucalipto, especialmente nos dois primeiros anos, pode acarretar grandes prejuízos à produtividade, pois reduz a eficiência de aproveitamento dos recursos de crescimento pela cultura. Assim, objetivou-se com este trabalho avaliar os efeitos da interferência de plantas daninhas sobre o crescimento inicial de dois clones de Eucalyptus urophylla x Eucalyptus grandis e a concentração foliar de nutrientes na cultura e nas plantas daninhas. O experimento foi instalado em esquema fatorial 2 x 5 + 7, sendo dois clones de híbridos de Eucalyptus urophylla x Eucalyptus grandis, identificados como CNB001 e CNB016, em competição com cinco plantas daninhas Urochloa decumbens (capim-braquiária), Ipomoea nil (corda-de-viola), Commelina diffusa (trapoeraba), Spermacoce latifolia (erva-quente) e Panicum maximum (capim-colonião). Adicionalmente, foram cultivados os dois clones de eucalipto e as cinco plantas daninhas em monocultivo como padrão de comparação, no delineamento inteiramente casualizado, com quatro repetições. Foram avaliados eucalipto através da altura de plantas, o diâmetro do coleto, o número de ramos, a área foliar, a matéria seca e, o teor foliar de nutrientes do eucalipto, bem como o teor de nutrientes nas folhas das plantas daninhas. O clone CNB001 apresentou crescimento inicial superior ao clone CNB016, no entanto, livre da interferência de plantas daninhas, verificaram-se teores foliares semelhantes para a maioria dos nutrientes em ambos os genótipos. O clone CNB016 mostrou maior sensibilidade à interferência negativa das plantas daninhas que o clone CNB001, sendo seu crescimento inicial mais afetado por Ipomoea nil e a concentração de nutrientes reduzida pelas espécies Panicum maximum, Urochloa decumbens e Commelina diffusa. Panicum maximum apresentou maior interferência com o clone CNB001, enquanto Ipomoea nil pouco influenciou o crescimento e o teor de nutrientes deste híbrido. As plantas daninhas apresentaram elevada capacidade de extrair nutrientes do solo, mesmo em convivência com os clones de Eucalyptus urophylla x Eucalyptus grandis. A interferência imposta à cultura é dependente da espécie infestante e do genótipo de eucalipto.

Periodicidade do crescimento de espécies arbóreas da Floresta Estacional Semidecidual no Sul do Brasil.

Embora a sazonalidade climática seja menos evidente nas regiões tropicais que nas temperadas, muitas espécies tropicais apresentam crescimento rítmico. A avaliação do crescimento em circunferência do tronco (CCT) permitirá obter informações sobre o desenvolvimento dos indivíduos de espécies arbóreas desta região. Esse estudo teve como objetivo avaliar o CCT de 11 espécies arbóreas de uma floresta estacional semidecidual no sul do Brasil, visando testar duas hipóteses: (i) existe sazonalidade no CCT das árvores e este crescimento está relacionado às variações climáticas da região de estudo; (ii) as características dos indivíduos (posição sociológica, altura da árvore, grau de ocupação por lianas, deciduidade e diâmetro à altura do peito) influenciam no incremento acumulado em circunferência. Para detectar a periodicidade do CCT foram implantadas faixas dendrométricas permanentes no tronco (altura do DAP) de 156 indivíduos. O acompanhamento do crescimento foi realizado mensalmente por um período de 18 meses. Foram feitas correlações do CCT mensal com a precipitação, temperatura e fotoperíodo para verificar a influencia dos fatores ambientais e análise de covariância para averiguar se as características dos indivíduos também interferiram no incremento acumulado em circunferência do tronco. As espécies apresentaram um padrão sazonal de CCT, com as maiores taxas de crescimento de outubro a dezembro, sendo que os parâmetros ambientais avaliados atuaram em conjunto - principalmente o fotoperíodo e a temperatura - promovendo essa sazonalidade e confirmando a primeira hipótese. Considerando as características dos indivíduos, somente o diâmetro do tronco correlacionou-se negativamente com o incremento acumulado em circunferência (b = -0,32; p = 0,02), aceitando parcialmente a segunda hipótese.

Efeito do consumo de farinha de linhaça (Linum usitatissimum) no crescimento de ratos Wistar e relação com a digestibilidade de globulinas e fatores antinutricionais protéicos

Linseed is an important oilseed consumed raw as nutritional supplement, that although represents a rich source of nutrients, its nutritional value could be impaired due to the presence of antinutritional factors. In this study, protein fractions from raw linseed flour were extracted and isolated being obtained 12% of albumins, 82% of globulins, 5% of glutelins and 1% of prolamins. These proteins were visualized by SDS-PAGE and albumins showed low molecular mass protein bands around 21 kDa and minor bands, similar to that of trypsin inhibitor; Globulins presented protein bands with high molecular masses, which possibly are constituents of multimeric proteins, such as legumins. After determination of the centesimal composition of raw linseed, it was used as exclusive protein source for young rats to evaluate its effect on animal growth. The results showed negative effects on rat growth (weight gain 73% less than the control group) and reduction of intestinal villus (35%), that could be related with in vitro and in vivo globulin digestibility and proteinaceous antinutritional factors (mammalian digestive enzymes inhibitors and lectins) in albumin fraction. Native globulins showed, by SDS-PAGE, low susceptibility in vitro to trypsin and chymotrypsin, however presented high degradation by pancreatin. Thermal treatment of globulins for 5 and 15 minutes at 100ºC improved considerably its digestibility by trypsin and pancreatin. Globulins presented 93.2% in vivo digestibility, similar to the control protein. Albumin fraction had high trypsin inhibition activity (100%) and chymotrypsin inhibition of 28.3%; haemagglutinating activity was not detected. The results of this study indicate the negative action of trypsin inhibitors on animal growth, but can not be discarded its combined action with other antinutritional factors, which could compromise the raw linseed utilization as an alternative food

An application of fractal image-set coding in facial recognition

Faces are complex patterns that often differ in only subtle ways. Face recognition algorithms have difficulty in coping with differences in lighting, cameras, pose, expression, etc. We propose a novel approach for facial recognition based on a new feature extraction method called fractal image-set encoding. This feature extraction method is a specialized fractal image coding technique that makes fractal codes more suitable for object and face recognition. A fractal code of a gray-scale image can be divided in two parts – geometrical parameters and luminance parameters. We show that fractal codes for an image are not unique and that we can change the set of fractal parameters without significant change in the quality of the reconstructed image. Fractal image-set coding keeps geometrical parameters the same for all images in the database. Differences between images are captured in the non-geometrical or luminance parameters – which are faster to compute. Results on a subset of the XM2VTS database are presented.

Selecting, optimizing and fusing ‘salient’ Gabor features for facial expression recognition

This paper describes a novel framework for facial expression recognition from still images by selecting, optimizing and fusing ‘salient’ Gabor feature layers to recognize six universal facial expressions using the K nearest neighbor classifier. The recognition comparisons with all layer approach using JAFFE and Cohn-Kanade (CK) databases confirm that using ‘salient’ Gabor feature layers with optimized sizes can achieve better recognition performance and dramatically reduce computational time. Moreover, comparisons with the state of the art performances demonstrate the effectiveness of our approach.

Facial feature detection for in-car environment

Acoustically, vehicles are extremely noisy environments and as a consequence audio-only in-car voice recognition systems perform very poorly. Seeing that the visual modality is immune to acoustic noise, using the visual lip information from the driver is seen as a viable strategy in circumventing this problem. However, implementing such an approach requires a system being able to accurately locate and track the driver’s face and facial features in real-time. In this paper we present such an approach using the Viola-Jones algorithm. Using this system, we present our results which show that using the Viola-Jones approach is a suitable method of locating and tracking the driver’s lips despite the visual variability of illumination and head pose.

Exploring visual features through Gabor representations for facial expression detection

Gabor representations have been widely used in facial analysis (face recognition, face detection and facial expression detection) due to their biological relevance and computational properties. Two popular Gabor representations used in literature are: 1) Log-Gabor and 2) Gabor energy filters. Even though these representations are somewhat similar, they also have distinct differences as the Log-Gabor filters mimic the simple cells in the visual cortex while the Gabor energy filters emulate the complex cells, which causes subtle differences in the responses. In this paper, we analyze the difference between these two Gabor representations and quantify these differences on the task of facial action unit (AU) detection. In our experiments conducted on the Cohn-Kanade dataset, we report an average area underneath the ROC curve (A`) of 92.60% across 17 AUs for the Gabor energy filters, while the Log-Gabor representation achieved an average A` of 96.11%. This result suggests that small spatial differences that the Log-Gabor filters pick up on are more useful for AU detection than the differences in contours and edges that the Gabor energy filters extract.

Temporal-based support vector machines for facial expression recognition

When classifying a signal, ideally we want our classifier to trigger a large response when it encounters a positive example and have little to no response for all other examples. Unfortunately in practice this does not occur with responses fluctuating, often causing false alarms. There exists a myriad of reasons why this is the case, most notably not incorporating the dynamics of the signal into the classification. In facial expression recognition, this has been highlighted as one major research question. In this paper we present a novel technique which incorporates the dynamics of the signal which can produce a strong response when the peak expression is found and essentially suppresses all other responses as much as possible. We conducted preliminary experiments on the extended Cohn-Kanade (CK+) database which shows its benefits. The ability to automatically and accurately recognize facial expressions of drivers is highly relevant to the automobile. For example, the early recognition of “surprise” could indicate that an accident is about to occur; and various safeguards could immediately be deployed to avoid or minimize injury and damage. In this paper, we conducted initial experiments on the extended Cohn-Kanade (CK+) database which shows its benefits.

Person-independent facial expression detection using constrained local models

In automatic facial expression detection, very accurate registration is desired which can be achieved via a deformable model approach where a dense mesh of 60-70 points on the face is used, such as an active appearance model (AAM). However, for applications where manually labeling frames is prohibitive, AAMs do not work well as they do not generalize well to unseen subjects. As such, a more coarse approach is taken for person-independent facial expression detection, where just a couple of key features (such as face and eyes) are tracked using a Viola-Jones type approach. The tracked image is normally post-processed to encode for shift and illumination invariance using a linear bank of filters. Recently, it was shown that this preprocessing step is of no benefit when close to ideal registration has been obtained. In this paper, we present a system based on the Constrained Local Model (CLM) which is a generic or person-independent face alignment algorithm which gains high accuracy. We show these results against the LBP feature extraction on the CK+ and GEMEP datasets.

Toward a more robust facial expression recognition in occluded images using randomly sampled Gabor based templates

Occlusion is a big challenge for facial expression recognition (FER) in real-world situations. Previous FER efforts to address occlusion suffer from loss of appearance features and are largely limited to a few occlusion types and single testing strategy. This paper presents a robust approach for FER in occluded images and addresses these issues. A set of Gabor based templates is extracted from images in the gallery using a Monte Carlo algorithm. These templates are converted into distance features using template matching. The resulting feature vectors are robust to occlusion. Occluded eyes and mouth regions and randomly places occlusion patches are used for testing. Two testing strategies analyze the effects of these occlusions on the overall recognition performance as well as each facial expression. Experimental results on the Cohn-Kanade database confirm the high robustness of our approach and provide useful insights about the effects of occlusion on FER. Performance is also compared with previous approaches.

Automatically detecting pain in video through facial action units

In a clinical setting, pain is reported either through patient self-report or via an observer. Such measures are problematic as they are: 1) subjective, and 2) give no specific timing information. Coding pain as a series of facial action units (AUs) can avoid these issues as it can be used to gain an objective measure of pain on a frame-by-frame basis. Using video data from patients with shoulder injuries, in this paper, we describe an active appearance model (AAM)-based system that can automatically detect the frames in video in which a patient is in pain. This pain data set highlights the many challenges associated with spontaneous emotion detection, particularly that of expression and head movement due to the patient's reaction to pain. In this paper, we show that the AAM can deal with these movements and can achieve significant improvements in both the AU and pain detection performance compared to the current-state-of-the-art approaches which utilize similarity-normalized appearance features only.