European Economies in the First Epoch of Imperialism and Mercantilism. 1415-1846.

The costs and benefits of European Imperialism from the conquest of Ceuta, 1415, to the Treaty of Lusaka, 1974.Twelfth International Economic History Congress. Madrid, 1998.Patrick K. O'Brien and Leandro Prados de la Escosura (eds.)Editada en la Fundación Empresa PúblicaJorge M. Pedreira. «To Have and To Have not». The Economic Consequences of Empire: Portugal (1415-1822).-- Bartolomé Yun-Casalilla. The American Empire and the Spanish Economy: An Institutional and Regional Perspective.-- Pieter C. Emmer. The Economic Impact of the Dutch Expansion Overseas, 1570-1870.-- Paul Butel and François Crouzet. Empire and Economic Growth: the Case of 18th Century France.-- Stanley L. Engerman. British Imperialism in a Mercantilist Age, 1492-1849: Conceptual Issues and Empirical Problems.Publicad

TCANet for Domain Adaptation of Hyperspectral Images

The use of Convolutional Neural Networks (CNNs) to solve Domain Adaptation (DA) image classification problems in the context of remote sensing has proven to provide good results but at high computational cost. To avoid this problem, a deep learning network for DA in remote sensing hyperspectral images called TCANet is proposed. As a standard CNN, TCANet consists of several stages built based on convolutional filters that operate on patches of the hyperspectral image. Unlike the former, the coefficients of the filter are obtained through Transfer Component Analysis (TCA). This approach has two advantages: firstly, TCANet does not require training based on backpropagation, since TCA is itself a learning method that obtains the filter coefficients directly from the input data. Second, DA is performed on the fly since TCA, in addition to performing dimensional reduction, obtains components that minimize the difference in distributions of data in the different domains corresponding to the source and target images. To build an operating scheme, TCANet includes an initial stage that exploits the spatial information by providing patches around each sample as input data to the network. An output stage performing feature extraction that introduces sufficient invariance and robustness in the final features is also included. Since TCA is sensitive to normalization, to reduce the difference between source and target domains, a previous unsupervised domain shift minimization algorithm consisting of applying conditional correlation alignment (CCA) is conditionally applied. The results of a classification scheme based on CCA and TCANet show that the DA technique proposed outperforms other more complex DA techniquesThis work was supported in part by Consellería de Educación, Universidade e Formación Profesional [grant numbers GRC2014/008, ED431C 2018/19, and ED431G/08] and Ministerio de Economía y Empresa, GovernmentofSpain[grantnumberTIN2016-76373-P].Allareco–fundedbytheEuropeanRegionalDevelopment Fund (ERDF). This work received financial support from the Xunta de Galicia and the European Union (European Social Fund - ESF)S

A hybrid CUDA, OpenMP, and MPI parallel TCA-based domain adaptation for classification of very high-resolution remote sensing images

Domain Adaptation (DA) is a technique that aims at extracting information from a labeled remote sensing image to allow classifying a different image obtained by the same sensor but at a different geographical location. This is a very complex problem from the computational point of view, specially due to the very high-resolution of multispectral images. TCANet is a deep learning neural network for DA classification problems that has been proven as very accurate for solving them. TCANet consists of several stages based on the application of convolutional filters obtained through Transfer Component Analysis (TCA) computed over the input images. It does not require backpropagation training, in contrast to the usual CNN-based networks, as the convolutional filters are directly computed based on the TCA transform applied over the training samples. In this paper, a hybrid parallel TCA-based domain adaptation technique for solving the classification of very high-resolution multispectral images is presented. It is designed for efficient execution on a multi-node computer by using Message Passing Interface (MPI), exploiting the available Graphical Processing Units (GPUs), and making efficient use of each multicore node by using Open Multi-Processing (OpenMP). As a result, an accurate DA technique from the point of view of classification and with high speedup values over the sequential version is obtained, increasing the applicability of the technique to real problemsOpen Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work was supported in part by the Ministerio de Ciencia e Innovación, Government of Spain (grant numbers PID2019-104834GB-I00 and TED2021-130367B-I00), the Consellería de Educación, Universidade e Formación Profesional (grant number 2019–2022 ED431G-2019/04 and 2021–2024 ED431C 2022/16), and by the Junta de Castilla y León (project VA226P20 (PROPHET II Project)). All are co-funded by the European Regional Development Fund (ERDF)S

Psicología de la Salud cubana: apuntes históricos y proyecciones en los inicios del siglo XXI

Historical aspects of the development of Cuban Health Psychology have been s ystematised for more than 42 years, since their incorporation in the National Health System, focusing o n three groups of determinants. In the first group the appearance of a new way of thinking is combined with th e recognition of the bio-psychosocial model following the change from the old biomedical model, the new concept ualization of the health-illness process, and the growing knowledge of psychological and social factors asso ciated with this process, the transition in the epidemiological profiles, the impact of the concepts of wellbeing and health-related quality of life, the incorporation of primary health care as a fundamental scenario for many health-related actions, and the importance of working in interdisciplinary teams. A second group covers th e social changes that occurred in Cuba after the decade of 60s, which gave shape to these new conception s with a preventive approach with a social perspective. The third group of determinants is related to the devel opment of Psychology itself, with specific fields of action. In addition, the immediate tasks for Cuban Health Psychology are being determined for the present time, as well as the formulation of its basic perspecti ve in the context of world trends in this discipline for the future.Se sistematizan aspectos históricos del desarrollo de la Psicología de la Sal ud cubana a lo largo de más de 42 años de su inserción en el Sistema Nacional de Salud, considerando tres grupos de determinantes: en el primer grupo, se combina la aparición de una nueva forma de pensamiento con el recon ocimiento del modelo biopsicosocial tras la transformación del viejo modelo biomédico, la nu eva conceptualización del proceso salud-enfermedad y el conocimiento creciente de factores psicológicos y sociales aso ciados a este proceso, la transición en los perfiles epidemiológicos, la irrupción de los con ceptos de bienestar y calidad de vida relacionada con la salud, la incorporación de la atención primaria como ámbito f undamental para muchas acciones de salud y la importancia del trabajo en equipos interdisciplin arios. El segundo, está relacionado con los cambios sociales ocurridos en Cuba después de la década de los 60 y que materializaron estas nuevas concepciones con un enfoque preventivo, de proyección social. El tercero, vincul a el desarrollo mismo de la Psicología con campos específicos de actuación. Además, se intentan identif icar las tareas prioritarias para la Psicología de la salud cubana en el presente y formular sus proyecciones básicas , para los próximos años en el contexto de las tendencias mundiales en esta disciplina.São sistematizados aspectos históricos no desenvolvimento da Psicologia d a saúde cubana ao longo de mais de 42 anos da sua inserção no Sistema Nacional de Saúde, considerando três gru pos de determinantes. No primeiro grupo são combinados a aparição de uma nova forma de pensamento, com o recon hecimento do modelo biopsicossocial depois da transformação do velho modelo biomédico , a nova conceptualização do processo saúde-doença e o conhecimento crescente de fatores psicológico e sociais associados a este processo, a transição nos perfis epidemiológicos, a irrupção dos conceitos de bem-estar e qualidade de vida relacionada com a saúde, a incorporação da atenção primaria como âmbito fundamental para muitas ações de saúde e a importância do trabalho em equipes interdisciplinares. Um segundo grupo est á relacionado com as mudanças sociais ocorridos na Cuba depois da década dos sessenta e que materializaram estas novas conceições com um enfoque preventivo, de projeção social. No terceiro grupo de determinantes vin cula o desenvolvimento mesmo da psicologia com campos específicos de atuação. Além, intentou-se identi ficar as tarefas prioritárias para a psicologia da saúde cubana no presente e formular suas projeções básicas n o contexto das tendências mundiais em esta disciplina para os próximos anos

Feed withdrawal periods in the quality of broilers meat raised in the conventional system

O objetivo desta pesquisa foi avaliar o efeito de diferentes períodos de jejum alimentar (três, seis, nove, 12, 15 e 18 horas) na perda de peso da ave viva, rendimento da carcaça quente e fria (antes e após o resfriamento no chiller). Os atributos de qualidade da carne de peito de frango criados no sistema convencional tais como cor, capacidade de retenção de água (CRA), pH, força de cisalhamento e perda por cozimento foram avaliados. Neste experimento foram utilizados frangos de corte da linhagem Ross com 46 dias de idade. Os resultados mostraram que períodos prolongados de jejum alimentar teve efeito estatístico (P<0,05) na perda de peso das aves vivas. Essa perda foi de 2,27% para três horas a 7,51% para 18 horas de jejum alimentar. A queda no rendimento da carcaça a quente começou às nove horas de jejum (P<0,05) com rendimento de 67,4% após três horas a 66,2 % após nove horas de jejum alimentar. O rendimento da carcaça resfriada diminuiu de 74,8% após três horas a 73,2% após seis horas de jejum (P<0,05). Os maiores rendimentos de carcaça foram obtidos com os frangos de corte submetidos aos períodos entre 3 e 6 horas de jejum (carcaça quente) e três horas (carcaça resfriada). Não foram observadas diferenças estatísticas (P>0,05) para o valor de L*, a* e b*, CRA, pH e perda por cozimento da carne de peito devido aos diferentes períodos de jejum alimentar. Os valores da correlação de Pearson mostraram uma correlação negativa (P<0,001) tanto entre o pH e o valor de L* quanto entre o valor de L* e a CRA nos diferentes períodos de jejum.This research was aimed at evaluating the effect of different feed withdrawal (FW) periods (3, 6, 9, 12, 15 and 18 hours) on the live bird weight loss, dressed and chilled carcass yield (before and after of water chilling). The attributes of chilled breast meat quality of broilers raised in the conventional system were also evaluated, such as color, water holding capacity (WHC), pH, shear force and cooking loss. In this experiment, 46-day-old Ross broilers were used. The results of this study indicated that prolonged FW periods have a significant effect (P<0.05) on live broiler weight losses, from 2.27% for 3 hours FW to 7.51% for 18 hours FW. The reduction in dressed carcass yields became statistically significant after 9 hours of FW, ranging from carcass yield of 67.4% after 3hours to 66.2% after 9 hours FW. Chilled carcass yields dropped from 74.8% after 3 hours to 73.2% after 6 hours FW (P<0.05). The highest carcass yields were observed for broilers submitted to FW periods between 3 and 6 hours (dressed carcass yield) and 3 hours (chilled carcass yield). No statistical differences (P>0.05) were observed for L*, a* and b values, WHC, pH, cooking losses and pH of the breast meat submitted to different FW periods. Pearson correlation values showed a negative (P<0.001) correlation between pH and L* value, and between L* value and WHC, which varied with FW periods

Watershed Monitoring in Galicia from UAV Multispectral Imagery Using Advanced Texture Methods

Watershed management is the study of the relevant characteristics of a watershed aimed at the use and sustainable management of forests, land, and water. Watersheds can be threatened by deforestation, uncontrolled logging, changes in farming systems, overgrazing, road and track construction, pollution, and invasion of exotic plants. This article describes a procedure to automatically monitor the river basins of Galicia, Spain, using five-band multispectral images taken by an unmanned aerial vehicle and several image processing algorithms. The objective is to determine the state of the vegetation, especially the identification of areas occupied by invasive species, as well as the detection of man-made structures that occupy the river basin using multispectral images. Since the territory to be studied occupies extensive areas and the resulting images are large, techniques and algorithms have been selected for fast execution and efficient use of computational resources. These techniques include superpixel segmentation and the use of advanced texture methods. For each one of the stages of the method (segmentation, texture codebook generation, feature extraction, and classification), different algorithms have been evaluated in terms of speed and accuracy for the identification of vegetation and natural and artificial structures in the Galician riversides. The experimental results show that the proposed approach can achieve this goal with speed and precisionThis work was supported in part by the Civil Program UAVs Initiative, promoted by the Xunta de Galicia and developed in partnership with the Babcock company to promote the use of unmanned technologies in civil services. We also have to acknowledge the support by the Ministerio de Ciencia e Innovación, Government of Spain (grant number PID2019-104834GB-I00), and Consellería de Educación, Universidade e Formación Profesional (grant number ED431C 2018/19, and accreditation 2019–2022 ED431G-2019/04). All are co-funded by the European Regional Development Fund (ERDF)S

HypeRvieW: an open source desktop application for hyperspectral remote-sensing data processing

In this article, we present a desktop application for the analysis, reference data generation, registration, and supervised spatial-spectral classification of hyperspectral remote-sensing images through a simple and intuitive interface. Regarding the classification ability, the different classification schemes are implemented by using a chain structure as a base. It consists of five configurable stages that must be executed in a fixed order: preprocessing, spatial processing, pixel-wise classification, combination, and post-processing. The modular implementation makes its extension easy by adding new algorithms for each stage or new classification chains. The tool has been designed as a platform that is open to the incorporation of algorithms by the users interested in comparing classification schemes. As an example of use, a classification scheme based on the Quick Shift (QS) algorithm for segmentation and on Extreme Learning Machines (ELMs) or Support Vector Machines (SVMs) for classification is also proposed. The application is license-free, runs on the Linux operating system, and was developed in C language using the GTK library, as well as other free libraries to build the graphical user interfaces (GUIs)This work was supported by the Xunta de Galicia, Programme for Consolidation of Competitive Research Groups [2014/008]; Ministry of Science and Innovation, Government of Spain, cofounded by the FEDER funds of European Union [TIN2013-41129-P]S