Influência do Confucionismo e do Catolicismo na vida de chineses e portugueses: ensaio sobre a cultura do casamento

Dissertação de mestrado em Estudos Interculturais Português/Chinês: Tradução, Formação e Comunicação EmpresarialTanto para chineses como para portugueses, tanto antigamente como atualmente, o casamento é algo importante na vida de cada um e da sociedade em geral. Em ambas as sociedades há rituais e costumes matrimoniais que constituem elementos importantes da cultura e da estrutura social. Nas sociedades chinesa e portuguesa há perspetivas algo diferenciadas sobre esta matéria, motivadas por fontes culturais e circunstâncias sociais muito distintas. A presente dissertação ensaia uma análise comparativa da cultura do casamento nos dois países (costumes, rituais, valores, amor), bem como da sua evolução até aos nossos dias. Ou seja, proponho-me aprofundar as causas que estão a montante das diferenças e, acima de tudo, procuro identificar algumas tendências de mundança de mentalidades tanto em Portugal como na China, num quadro, respetivamente, do Catolicismo e do Confucionismo e da atual sociedade globalizada, onde diferentes tradições se encontram e se influenciam, verificando-se uma crescente abertura de rituais e cortumes tradicionais à modernidade, a uma certa indiferenciação, não deixando porém de se manterem diferenças significativas. Ainda bem.Both for Chinese and Portuguese, whether in ancient or in current society, marriage is always a very important issue in everyone’s life. Due to the different cultures and social backgrounds, people of the two countries hold different views towards marriage. Also, there are many customs and rituals with respect to marriage in these two societies, which constitute an important part of the social culture. Despite having this in common, there are also distinctions, motivated by different cultural foundations and social circumstances. This dissertation presents a comparative study about the culture of marriage in Portuguese and Chinese contexts: customs and rituals of wedding ceremonies, values of love and marriage, and changes in family values. The purpose of this study is to explore the causes behind these main differences and try to identify the changing trends of minds both in Portugal and China, which are mainly influenced by Catholicism and Confucianism. Nowadays, with the increasing economic and cultural contacts, new and modern rituals are causing the emergence of new customs in both societies. Values of love and marriage are more liberal and open minded, nevertheless some traditions are still deeply rooted. Despite these differences, both countries’ people have similarities in values of marriage, and they tend to draw nearer.无论对于中国人，还是葡萄牙人，无论在过去，还是现在，婚姻一直是每个 人一生中的重要事情，在两个国家都有很多文化习俗和婚姻有关。由于文化背景 和社会状态的不同，中葡两国人民的婚姻文化也存在着差异。本研究从传统的婚 礼习俗，婚姻观念及其发展变化入手，比较分析两个国家的婚姻文化，旨在探寻 其观念差异的文化和社会根源，即天主教和儒家思想对社会的影响，并对其观念 的变化趋势提出见解。当今社会，两国的联系日益密切，文化相互渗透，在习俗 上很多新鲜元素，在婚姻观上更加开放自由，但是仍然还保留着很多传统。与此 同时，两国人的婚姻文化表现出了明显的趋同形势

Hand and Arm Gesture-based Human-Robot Interaction: A Review

The study of Human-Robot Interaction (HRI) aims to create close and friendly communication between humans and robots. In the human-center HRI, an essential aspect of implementing a successful and effective HRI is building a natural and intuitive interaction, including verbal and nonverbal. As a prevalent nonverbally communication approach, hand and arm gesture communication happen ubiquitously in our daily life. A considerable amount of work on gesture-based HRI is scattered in various research domains. However, a systematic understanding of the works on gesture-based HRI is still lacking. This paper intends to provide a comprehensive review of gesture-based HRI and focus on the advanced finding in this area. Following the stimulus-organism-response framework, this review consists of: (i) Generation of human gesture(stimulus). (ii) Robot recognition of human gesture(organism). (iii) Robot reaction to human gesture(response). Besides, this review summarizes the research status of each element in the framework and analyze the advantages and disadvantages of related works. Toward the last part, this paper discusses the current research challenges on gesture-based HRI and provides possible future directions.Comment: 10 pages, 1 figure

A Sustainability Improvement Strategy of Interconnected Data Centers Based on Dispatching Potential of Electric Vehicle Charging Stations

With the rapid development of information technology, the electricity consumption of Internet Data Centers (IDCs) increases drastically, resulting in considerable carbon emissions that need to be reduced urgently. In addition to the introduction of Renewable Energy Sources (RES), the joint use of the spatial migration capacity of IDC workload and the temporal flexibility of the demand of Electric Vehicle Charging Stations (EVCSs) provides an important means to change the carbon footprint of the IDC. In this paper, a sustainability improvement strategy for the IDC carbon emission reduction was developed by coordinating the spatial-temporal dispatch flexibilities of the IDC workload and the EVCS demand. Based on the Minkowski sum algorithm, a generalized flexible load model of the EVCSs, considering traffic flow and Road Impedance (RI) was formulated. The case studies show that the proposed method can effectively increase the renewable energy consumption, reduce the overall carbon emissions of multi-IDCs, reduce the energy cost of the DCO, and utilize the EV dispatching potential. Discussions are also provided on the relationship between workload processing time delay and the renewable energy consumption rate

Vertically Oriented and Interpenetrating CuSe Nanosheet Films with Open Channels for Flexible All-Solid-State Supercapacitors

As a p-type multifunctional semiconductor, CuSe nanostructures show great promise in optoelectronic, sensing, and photocatalytic fields. Although great progress has been achieved, controllable synthesis of CuSe nanosheets (NSs) with a desirable spacial orientation and open frameworks remains a challenge, and their use in supercapacitors (SCs) has not been explored. Herein, a highly vertically oriented and interpenetrating CuSe NS film with open channels is deposited on an Au-coated polyethylene terephthalate substrate. Such CuSe NS films exhibit high specific capacitance (209 F g–1) and can be used as a carbon black- and binder-free electrode to construct flexible, symmetric all-solid-state SCs, using polyvinyl alcohol–LiCl gel as the solid electrolyte. A device fabricated with such CuSe NS films exhibits high volumetric specific capacitance (30.17 mF cm–3), good cycling stability, excellent flexibility, and desirable mechanical stability. The excellent performance of such devices results from the vertically oriented and interpenetrating configuration of CuSe NS building blocks, which can increase the available surface and facilitate the diffusion of electrolyte ions. Moreover, as a prototype for application, three such solid devices in series can be used to light up a red light-emitting diode

MetaMHC: a meta approach to predict peptides binding to MHC molecules

As antigenic peptides binding to major histocompatibility complex (MHC) molecules is the prerequisite of cellular immune responses, an accurate computational predictor will be of great benefit to biologists and immunologists for understanding the underlying mechanism of immune recognition as well as facilitating the process of epitope mapping and vaccine design. Although various computational approaches have been developed, recent experimental results on benchmark data sets show that the development of improved predictors is needed, especially for MHC Class II peptide binding. To make the most of current methods and achieve a higher predictive performance, we developed a new web server, MetaMHC, to integrate the outputs of leading predictors by several popular ensemble strategies. MetaMHC consists of two components: MetaMHCI and MetaMHCII for MHC Class I peptide and MHC Class II peptide binding predictions, respectively. Experimental results by both cross-validation and using an independent data set show that the ensemble approaches outperform individual predictors, being statistically significant. MetaMHC is freely available at http://www.biokdd.fudan.edu.cn/Service/MetaMHC.html

Instantâneos do/no feminino: histórias de mulheres no conto português e chinês contemporâneo

Partindo do pressuposto de que a criação literária mantém complexas relações dialógicas com os sistemas culturais de que participa, o presente trabalho, que se inscreve no terreno dos estudos literários comparados luso-chineses, tem como objetivo desenvolver uma leitura crítico-comparativa das representações ficcionais da mulher patentes em contos contemporâneos portugueses e chineses de autoria feminina. Com base num corpus constituído por mais de cinquenta contos de oito autoras portuguesas e chinesas (Maria Isabel Barreno, Teolinda Gersão, Lídia Jorge, Maria Teresa Horta, Wang Anyi, Chen Ran, Tie Ning e Xu Kun), pretende-se, através de uma análise literária contrastiva das imagens da mulher veiculadas em cenários biográficos, familiares, geográficos, laborais, e psicoafetivos, esboçar uma sociologia literária comparada do feminino. Ao mesmo tempo, colocam-se em evidência os fatores de ordem política, socioeconómica e histórico-cultural que ajudaram a determinar a trajetória histórica recente da mulher na China e em Portugal.Based on the assumption that literary creation establishes complex dialogic relations with the cultural systems in which it takes part, this dissertation draws on the field of comparative Chinese and Portuguese literary studies, aiming to provide a contrastive analysis of the fictional images of women found in Portuguese and Chinese contemporary short stories by female authors. A close reading of over fifty short stories by eight Portuguese and Chinese authors (Maria Isabel Barreno, Teolinda Gersão, Lídia Jorge, Maria Teresa Horta, Wang Anyi, Chen Ran, Tie Ning, and Xu Kun) has been carried out, so as to shed some light on the multivarious images portrayed in these narratives, focusing on the biographical, family, geographical, labour, and psycho-affective contexts surrounding women. In line with a comparative socioliterary analysis of the fictional images of the feminine, we have moreover sought to highlight the political, socio-economic, historical, and cultural factors that helped to shape the recent historical trajectory of women in both Portugal and China.Programa Doutoral em Estudos Literário

Research on Pedestrian Detection Model and Compression Technology for UAV Images

The large view angle and complex background of UAV images bring many difficulties to the detection of small pedestrian targets in images, which are easy to be detected incorrectly or missed. In addition, the object detection models based on deep learning are usually complex and the high computational resource consumption limits the application scenarios. For small pedestrian detection in UAV images, this paper proposes an improved YOLOv5 method to improve the detection ability of pedestrians by introducing a new small object feature detection layer in the feature fusion layer, and experiments show that the improved method can improve the average precision by 4.4%, which effectively improves the pedestrian detection effect. To address the problem of high computational resource consumption, the model is compressed using channel pruning technology to reduce the consumption of video memory and computing power in the inference process. Experiments show that the model can be compressed to 11.2 MB and the GFLOPs of the model are reduced by 11.9% compared with that before compression under the condition of constant inference accuracy, which is significant for the deployment and application of the model

Short-Term Load Forecasting Using EMD with Feature Selection and TCN-Based Deep Learning Model

Short-term load forecasting (STLF) has a significant role in reliable operation and efficient scheduling of power systems. However, it is still a major challenge to accurately predict power load due to social and natural factors, such as temperature, humidity, holidays and weekends, etc. Therefore, it is very important for the efficient feature selection and extraction of input data to improve the accuracy of STLF. In this paper, a novel hybrid model based on empirical mode decomposition (EMD), a one-dimensional convolutional neural network (1D-CNN), a temporal convolutional network (TCN), a self-attention mechanism (SAM), and a long short-term memory network (LSTM) is proposed to fully decompose the input data and mine the in-depth features to improve the accuracy of load forecasting. Firstly, the original load sequence was decomposed into a number of sub-series by the EMD, and the Pearson correlation coefficient method (PCC) was applied for analyzing the correlation between the sub-series with the original load data. Secondly, to achieve the relationships between load series and external factors during an hour scale and the correlations among these data points, a strategy based on the 1D-CNN and TCN is proposed to comprehensively refine the feature extraction. The SAM was introduced to further enhance the key feature information. Finally, the feature matrix was fed into the long short-term memory (LSTM) for STLF. According to experimental results employing the North American New England Control Area (ISO-NE-CA) dataset, the proposed model is more accurate than 1D-CNN, LSTM, TCN, 1D-CNN–LSTM, and TCN–LSTM models. The proposed model outperforms the 1D-CNN, LSTM, TCN, 1D-CNN–LSTM, and TCN–LSTM by 21.88%, 51.62%, 36.44%, 42.75%, 16.67% and 40.48%, respectively, in terms of the mean absolute percentage error

Short-Term Load Forecasting Using EMD with Feature Selection and TCN-Based Deep Learning Model

Short-term load forecasting (STLF) has a significant role in reliable operation and efficient scheduling of power systems. However, it is still a major challenge to accurately predict power load due to social and natural factors, such as temperature, humidity, holidays and weekends, etc. Therefore, it is very important for the efficient feature selection and extraction of input data to improve the accuracy of STLF. In this paper, a novel hybrid model based on empirical mode decomposition (EMD), a one-dimensional convolutional neural network (1D-CNN), a temporal convolutional network (TCN), a self-attention mechanism (SAM), and a long short-term memory network (LSTM) is proposed to fully decompose the input data and mine the in-depth features to improve the accuracy of load forecasting. Firstly, the original load sequence was decomposed into a number of sub-series by the EMD, and the Pearson correlation coefficient method (PCC) was applied for analyzing the correlation between the sub-series with the original load data. Secondly, to achieve the relationships between load series and external factors during an hour scale and the correlations among these data points, a strategy based on the 1D-CNN and TCN is proposed to comprehensively refine the feature extraction. The SAM was introduced to further enhance the key feature information. Finally, the feature matrix was fed into the long short-term memory (LSTM) for STLF. According to experimental results employing the North American New England Control Area (ISO-NE-CA) dataset, the proposed model is more accurate than 1D-CNN, LSTM, TCN, 1D-CNN–LSTM, and TCN–LSTM models. The proposed model outperforms the 1D-CNN, LSTM, TCN, 1D-CNN–LSTM, and TCN–LSTM by 21.88%, 51.62%, 36.44%, 42.75%, 16.67% and 40.48%, respectively, in terms of the mean absolute percentage error

The complete chloroplast genome of Bougainvillea glabra

Bougainvillea glabra is one of the most popular ornamental and landscaping plants planted in tropical and subtropical regions. The brightly colored bracts, long florescence and strong stress resistance make B. glabra perfect ornamental horticulture plant. Bougainvillea plants have been frequently hybridized, resulting in more than 400 varieties. To investigate the chloroplast genome will help us to understand the biological diversity and stress resistance of Bougainvillea plants better. Here, we report the complete chloroplast genome of B. glabra, which is 154,542 bp in length, including a large single copy (LSC) region of 85,695 bp and a small single copy (SSC) region of 18,077 bp, separated by a pair of identical inverted repeat regions (IRs) of 25,385 bp each. A total of 128 genes were identified, including 83 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. Phylogenetic analysis based on 12 chloroplast genomes showed that B. glabra, accompanied with its sister species B. spectabilis, formed a base clade in Nyctaginaceae which was close to Pisonia aculeata. This study will be helpful for better understanding of the genetic diversity and stress resistance of Bougainvillea plants