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Traditional text classification models have some drawbacks, such as the inability of the model to focus on important parts of the text contextual information in text processing. To solve this problem, we fuse the long and short-term memory network BiGRU with a convolutional neural network to receive text sequence input to reduce the dimensionality of the input sequence and to reduce the loss of text features based on the length and context dependency of the input text sequence. Considering the extraction of important features of the text, we choose the long and short-term memory network BiLSTM to capture the main features of the text and thus reduce the loss of features. Finally, we propose a BiGRU-CNN-BiLSTM model (DCRC model) based on CNN, GRU and LSTM, which is trained and validated on the THUCNews and Toutiao News datasets. The model outperformed the traditional model in terms of accuracy, recall and F1 score after experimental comparison.
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Recently, a lot of Chinese patients consult treatment plans through social networking platforms, but the Chinese medical text contains rich information, including a large number of medical nomenclatures and symptom descriptions. How to build an intelligence model to automatically classify the text information consulted by patients and recommend the correct department for patients is very important. In order to address the problem of insufficient feature extraction from Chinese medical text and low accuracy, this paper proposes a dual channel Chinese medical text classification model. The model extracts feature of Chinese medical text at different granularity, comprehensively and accurately obtains effective feature information, and finally recommends departments for patients according to text classification. One channel of the model focuses on medical nomenclatures, symptoms and other words related to hospital departments, gives different weights, calculates corresponding feature vectors with convolution kernels of different sizes, and then obtains local text representation. The other channel uses the BiGRU network and attention mechanism to obtain text representation, highlighting the important information of the whole sentence, that is, global text representation. Finally, the model uses full connection layer to combine the representation vectors of the two channels, and uses Softmax classifier for classification. The experimental results show that the accuracy, recall and F1-score of the model are improved by 10.65%, 8.94% and 11.62% respectively compared with the baseline models in average, which proves that our model has better performance and robustness.
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In the past decades, the field of cinema has undergone several transformations. The digital turn increasingly called for new forms of production, distribution, and exhibition, which imply different ways of thinking, doing, and experimenting cinema. These new forms also reduced the gap between cinema to other so-called visual arts. If cinema and visual arts were already in the process of merging, the last years forced the naturalization of thinking in similar theoretical grounds. This special issue aims to be a forum for the discussion of new practices of researching cinema, and the changes in cinema’s forms of experience and production.
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In southeast Asia, males of the Siamese fighting fish, Betta splendens, have been selected across centuries for winning paired staged fights and previous work has shown that males from fighter strains are more aggressive than wild-types. This strong directional selection for winners is likely to have targeted aggression-related endocrine systems, and a comparison between fighter and wild-type strains can bring into evidence the key hormones implicated in aggression. Here, we compared the plasma levels of the androgen 11-ketotestosterone (KT) and of the corticosteroid cortisol (F) in F2 males of a fighter and a wild-type strain raised under similar laboratory conditions. We show that F was generally lower in fighter as compared with wild-type males, while no overall differences in KT levels were detected between strains. When presented with a mirror-induced aggressive challenge, post-fight levels of F increased but more significantly so in wild-type males, while KT increased in males of both strains. After the challenge, fighter males had higher levels of KT as compared with wild-type males, while the pattern for F was opposite. As compared with animals in social groups, wild-type males placed under social isolation had lower F levels, while KT decreased for fighters. Taken together, this data suggests that while wild-type males responded to aggression with an increase in circulating levels of both androgens and corticosteroids, males selected for winning fights maintained a blunt F response, increasing only KT levels. These data agree with the hypothesis that a combination of high levels of androgens and low levels of corticosteroids is associated with high aggression. Overall, these results seem to indicate that selection for winning had a stronger impact in the hypothalamus-pituitary-interrenal axis than in the hypothalamus-pituitary–gonadal axis in B. splendens.
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Parental nutrient reserves are directly related to reproductive performance in sea cucumbers. This study focused on the lipid requirements of male and female sea cucumbers Apostichopus japonicus during the reproductive stage and analyzed their physiological responses to a high-fat diet (HFD). The intestinal lipid metabolites and microbiome profile changed significantly in animals fed with the HFD, as given by an upregulation of metabolites related to lipid metabolism and an increase in the predominance of Proteobacteria in the microbiome, respectively. The metabolic responses of male and female sea cucumbers to the HFD differed, which in turn could have triggered sex-related differences in the intestinal microbiome. These results suggest that the lipid content in diets can be differentially adjusted for male and female sea cucumbers to improve nutrition and promote reproduction. This data contributes to a better understanding of the reproductive biology and sex differences of sea cucumbers.
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Air pollution in Macau has become a serious problem following the Pearl River Delta’s (PRD) rapid industrialization that began in the 1990s. With this in mind, Macau needs an air quality forecast system that accurately predicts pollutant concentration during the occurrence of pollution episodes to warn the public ahead of time. Five different state-of-the-art machine learning (ML) algorithms were applied to create predictive models to forecast PM2.5, PM10, and CO concentrations for the next 24 and 48 h, which included artificial neural networks (ANN), random forest (RF), extreme gradient boosting (XGBoost), support vector machine (SVM), and multiple linear regression (MLR), to determine the best ML algorithms for the respective pollutants and time scale. The diurnal measurements of air quality data in Macau from 2016 to 2021 were obtained for this work. The 2020 and 2021 datasets were used for model testing, while the four-year data before 2020 and 2021 were used to build and train the ML models. Results show that the ANN, RF, XGBoost, SVM, and MLR models were able to provide good performance in building up a 24-h forecast with a higher coefficient of determination (R2) and lower root mean square error (RMSE), mean absolute error (MAE), and biases (BIAS). Meanwhile, all the ML models in the 48-h forecasting performance were satisfactory enough to be accepted as a two-day continuous forecast even if the R2 value was lower than the 24-h forecast. The 48-h forecasting model could be further improved by proper feature selection based on the 24-h dataset, using the Shapley Additive Explanations (SHAP) value test and the adjusted R2 value of the 48-h forecasting model. In conclusion, the above five ML algorithms were able to successfully forecast the 24 and 48 h of pollutant concentration in Macau, with the RF and SVM models performing the best in the prediction of PM2.5 and PM10, and CO in both 24 and 48-h forecasts.
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Employees work long hours in an environment where the ambient air quality is poor, directly affecting their work efficiency. The concentration of particulate matters (PM) produced by the interior renovation of shopping malls has not received particular attention in Macao. Therefore, this study will investigate the indoor air quality (IAQ), in particular of PM2.5, in large-scale shopping mall renovation projects. This study collected on-site PM data with low-cost portable monitoring equipment placed temporarily at specific locations to examine whether the current control measures are appropriate and propose some improvements. Prior to this study, there were no measures being implemented, and on-site monitoring to assess the levels of PM2.5 concentrations was non-existent. The results show the highest level of PM2.5 recorded in this study was 559.00 μg/m3. Moreover, this study may provide a reference for decision-makers, management, construction teams, design consultant teams, and renovation teams of large-scale projects. In addition, the monitoring of IAQ can ensure a comfortable environment for employees and customers. This study concluded that the levels of PM2.5 concentration have no correlation with the number of on-site workers, but rather were largely influenced by the processes being performed on-site.
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This study, focusing on the China's Yao minority community, investigates the feasibility to create a generative computational method to replicate the diversity of the existing Yao traditional wood buildings, addressing the critical issues currently facing computational design methods, in the attempt to adapt genetic-generative algorithms to the study of local ancient architecture. The project develops a computational tool to generate a network of three-dimensional prototypes, or building structures, derived from traditional wood frame village houses. It studies possible housing structures that illustrate some of the key working methods available in digital systems such as ‘generating' and ‘compositing' taking as a starting point computational strategies oriented towards geometry and where a set of local variables play a decisive role: available local technologies, use of raw materials, and the dimensioning of timber components based on data collected from Yao architecture.
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Mangroves are a unique group of plants growing along tropical and sub-tropical coastlines, with the ability to remove several types of contaminants such as heavy metals and other persistent organic compounds in coastal waters. However, little attention has been given to the possible role of mangroves in the removal of organochlorinated pesticides (OCPs) from the environment. Used worldwide, these pesticides were banned in the late 80s, withal they can still be quantified in aquatic environments due to their high stability. Moreover, as persistent and lipophilic compounds, OCPs are known for their tendency to bioaccumulate and biomagnify through the food chain, affecting local ecosystems, and potentially human health. This work aimed to investigate the potential benefits of mangrove ecosystems as OCP phytoremediators. For this purpose, a total of seventy-three articles from non-mangrove and mangrove areas around the world were gathered, integrated and re-analysed as a whole. These data include information from four different matrices (water, sediment, benthic fauna and mangrove plants). A common trend of less pesticide contamination in mangrove areas was observed for all the selected matrices. As a complement, average concentrations were discussed considering International Directives, such as the European legislation 2013/39/EU for water policy and the Dutch List together with the International Sediment Quality Guideline, for sediments. Additionally, theoretical risk assessments were also included. Since information regarding OCPs in mangroves ecosystem is very scarce compared to non-mangrove areas, this review provides valuable insights regarding these environments, and the importance of preserving them as a relevant remediation unit.
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Environmental education (EE) has long been practiced worldwide, while Nature-based solutions (NBS) is a relatively new concept. This chapter aims to provide an overview of the EE and NBS practices in East Asia and evaluate how these two valuable applications can be used concurrently. East Asia has a well developed environmental education (EE) programs and activities, both in formal and informal education. These ranges from developing green schools and campuses to establishing policies and acts. While EE has been actively practiced for decades in the region, the adoption of NBS to address environmental and societal challenges is limited. The educational benefits and opportunities from NBS are also lacking. Although there are some projects that can be classified as NBS, like the use of wetlands for wastewater treatment, they are not clearly categorized as one. These projects are also not integrated into environmental education programs. Considering this, the region should develop innovative environmental education programs for schools, universities and communities, that integrate NBS projects. Integrating the two together will boost the effectiveness of environmental education in raising environmental awareness and changing the environmental attitude and behavior of people, which will also help address societal issues.
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Genotoxic effects of dicofol on the edible clam Meretrix meretrix were investigated through a mesocosm experiment. Individuals of M. meretrix, were exposed to environmental concentration (D1 = 50 ng/L) and supra-environmental concentration (D2 = 500 ng/L) of dicofol for 15 days, followed by the same depuration period. DNA damage (i.e., strand breaks and alkali-labile sites) was evaluated at day 1, 7 and 15, during uptake and depuration, using Comet assay (alkaline version) and nuclear abnormalities (NAs) as genotoxicity biomarkers. The protective effects of dicofol against DNA damage induced by ex vivo hydrogen peroxide (H2O2) exposure were also assessed. Comet assay results revealed no significant DNA damages under dicofol exposure, indicating 1) apparent lack of genotoxicity of dicofol to the tested conditions and/or 2) resistance of the animals due to optimal adaptation to stress conditions. Moreover, ex vivo H2O2 exposure showed an increase in the DNA damage in all the treatments without significant differences between them. However, considering only the DNA damage induced by H2O2 during uptake phase, D1 animals had significantly lower DNA damage than those from other treatments, revealing higher protection against a second stressor. NAs data showed a decrease in the % of cells with polymorphic, kidney shape, notched or lobbed nucleus, along the experiment. The combination of these results supports the idea that the clams used in the experiment were probably collected from a stressful environment (in this case Pearl River Delta region) which could have triggered some degree of adaptation to those environmental conditions, explaining the lack of DNA damages and highlighting the importance of organisms’ origin and the conditions that they were exposed during their lives.
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The extraction of 21 insecticides and 5 metabolites was performed using an optimized and validated QuEChERS protocol that was further used for the quantification (GC–MS/MS) in several seafood matrices (crustaceans, bivalves, and fish-mudskippers). Seven species, acquired from Hong Kong and Macao wet markets (a region so far poorly monitored), were selected based on their commercial importance in the Indo-Pacific region, market abundance, and affordable price. Among them, mussels from Hong Kong, together with mudskippers from Macao, presented the highest insecticide concentrations (median values of 30.33 and 23.90 ng/g WW, respectively). Residual levels of fenobucarb, DDTs, HCHs, and heptachlors were above the established threshold (10 ng/g WW) for human consumption according to the European and Chinese legislations: for example, in fish-mudskippers, DDTs, fenobucarb, and heptachlors (5-, 20- and tenfold, respectively), and in bivalves, HCHs (fourfold) had higher levels than the threshold. Risk assessment revealed potential human health effects (e.g., neurotoxicity), especially through fish and bivalve consumption (non-carcinogenic risk; ΣHQLT > 1), and a potential concern of lifetime cancer risk development through the consumption of fish, bivalves, and crustaceans collected from these markets (carcinogenic risk; ΣTCR > 10–4). Since these results indicate polluted regions, where the seafood is collected/produced, a strict monitoring framework should be implemented in those areas to improve food quality and safety of seafood products.
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