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This thesis mainly discusses and compares the human rights situation and the problems in China, the USA and the UK. Also, the thesis will give the solution of how to make the world's human rights situation more fairly. Because we sometimes listen to these countries use cruel ways to suppress the opponents from the news. So I think this will be very suitable for understanding the current human rights situation, problems and movements in these countries. This thesis mainly uses the secondary data analysis method to collect and analyse the data. After analysing the data, three main issues affecting human rights were identified. These issues are race, religion, and network privacy. Other important factors still influence human rights, but this dissertation focused on the three issues identified. Finally, I will give two to three recommendations to practice human rights more fairly. Although the step will be very small, we can greatly improve the fair human rights in the future
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In the paper carried out by Wenjun et al. [Phys. Rev. A 95, 032124 (2017)], a generalization of the James effective dynamics theory based on a first version of the James method was presented. However, we contend that this is not a very rigorous way of deriving the effective third-order expansion for an interaction Hamiltonian with harmonic time-dependence. In fact, here we show that the third-order Hamiltonian obtained by Wenjun et al. is not Hermitian for general situations when we consider time dependence. Its non-Hermitian nature arises from the foundation of the theory itself. In this comment paper, the most general expression of the effective Hamiltonian expanded up to third order is obtained. Our derived effective Hamiltonian is Hermitian even in situations where we have time dependence.
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The continuous development of robust machine learning algorithms in recent years has helped to improve the solutions of many studies in many fields of medicine, rapid diagnosis and detection of high-risk patients with poor prognosis as the coronavirus disease 2019 (COVID-19) spreads globally, and also early prevention of patients and optimization of medical resources. Here, we propose a fully automated machine learning system to classify the severity of COVID-19 from electrocardiogram (ECG) signals. We retrospectively collected 100 5-minute ECGs from 50 patients in two different positions, upright and supine. We processed the surface ECG to obtain QRS complexes and HRV indices for RR series, including a total of 43 features. We compared 19 machine learning classification algorithms that yielded different approaches explained in a methodology session.
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COVID-19 is a respiratory disorder caused by CoronaVirus and SARS (SARS-CoV2). WHO declared COVID-19 a global pandemic in March 2020 and several nations’ healthcare systems were on the verge of collapsing. With that, became crucial to screen COVID-19-positive patients to maximize limited resources. NAATs and antigen tests are utilized to diagnose COVID-19 infections. NAATs reliably detect SARS-CoV-2 and seldom produce false-negative results. Because of its specificity and sensitivity, RT-PCR can be considered the gold standard for COVID-19 diagnosis. This test’s complex gear is pricey and time-consuming, using skilled specialists to collect throat or nasal mucus samples. These tests require laboratory facilities and a machine for detection and analysis. Deep learning networks have been used for feature extraction and classification of Chest CT-Scan images and as an innovative detection approach in clinical practice. Because of COVID-19 CT scans’ medical characteristics, the lesions are widely spread and display a range of local aspects. Using deep learning to diagnose directly is difficult. In COVID-19, a Transformer and Convolutional Neural Network module are presented to extract local and global information from CT images. This chapter explains transfer learning, considering VGG-16 network, in CT examinations and compares convolutional networks with Vision Transformers (ViT). Vit usage increased VGG-16 network F1-score to 0.94.
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The question of how to adequately integrate environment and labor provisions in free trade agreements is still a difficult one for both States and academicians. This article explores China’s approach to environment and labor issues in free trade agreements. For reference and comparison, it relies on the European Union’s and the United States’ approaches in their respective FTAs. The article identifies China’s preference for a case-by-case approach to the inclusion of environmental chapters in its FTAs. Additionally, in most FTAs it avoids to include provisions on labor standards. These two preferences represent major divergences from the European Union’s and the United States’ approaches, characterized by inclusion of chapters on environment and labor in all their modern FTAs. The article also finds that China’s FTAs rely solely on consultations and cooperation for the implementation of environmental and labor provisions, within the framework of Joint Committees and avoid the inclusion of civil society mechanisms. Moreover, resolution of disputes relies exclusively on consultations, in a diverse procedure than the one applicable to trade disputes. Despite alignment with the European Union model, this is another major point of divergence with the United States’ model, which applies the same enforcement mechanism for both environment and labor issues and trade issues and includes the possibility of applying sanctions. Finally, the article concludes that China’s options with regards to the treatment of environment and labor concerns in its free trade agreements aligns with both its domestic governance approach and its approach to international cooperation.
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This paper examines the extent to which China’s aid policies integrate poverty alleviation as a goal of their aid in general, particularly in Guinea. More specifically, the paper analyzed how aid donors focus on poverty alleviation and which policies and mechanisms are in place to address poverty in the countries receiving aid. Regarding the methodology, the author collected data from secondary sources, including government declarations of donors, policy documents at both the donor and recipient levels, as well as from scholarly publications. The following findings resulted from study: China’s aid policies have progressively incorporated poverty alleviationobjectives and identified sectors for intervention against poverty. However, the limitations of China approach to poverty is that China adopts a top-down approach to poverty reduction and lacks of an impact evaluation mechanism based on poverty alleviation.
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Macau, Macau Business, MAG, MB, MB Featured, Opinion | Many employers in Macau expect their employees to have received higher education (HE). This returns to the endless question of what HE is for; is it for job knowledge and skills acquisition, attitude development, thinking abilities, creativity, problem solving, how to learn, or what? What and whose knowledge?
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With the rapid urban development, Macao SAR has become one of regions with the with highest population density in the world, characterized by high traffic flow and dense building aggregations. Noise has become one of the major environmental problems in Macao. Besides having an impact on human health and wellbeing, noise pollution is known to impact ecological systems and the image of a place. Before proposing a plan to reduce noise pollution, it is necessary to have a general understanding of the current noise levels in Macao, how they have changed over time and the main noise pollution sources and environmental concerns. This dissertation relies on the publicly available data from DSPA (Macao Environmental Protection Bureau) monitoring stations concerning noise levels over the past decade. The main research goals were: 1) Characterize changes in noise levels from 2010 to 2021 during daytime, nighttime, and full-day from multiple noise stations located in Macao, Taipa, and Coloane Peninsula; and 2) associate changes in noise levels with potential factors such as location, number of residents/tourists, number of vehicles, among others. This work provides an important framework for future studies concerning noise monitoring and mitigation strategies
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This Practice Note considers challenges to the jurisdiction of arbitral tribunals under the Macau Arbitration Law, the scope of challenge before national courts and tribunals.
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Macao is a city of culture, and history and culture are the wealth of Macao. Over the centuries, the exchange and transmutation of Chinese and Western cultures have given Macao a unique cultural charm, and have also formed and preserved a considerable amount of cultural heritage. Cultural heritage has received increasing attention from all sectors of the community in the tourism industry in Macao, the promotion of the preservation and transmission of cultural heritage through tourism development has become a new issue in the tourism sector. As an independent art form in the urban public space, tile painting has both practical and aesthetic functions, and is a special vehicle for the convergence of multiple cultures in the urban cultural ecology. It is also a medium through which the city's cultural message can be fully disseminated. The paper presents a detailed analysis of the strengths, weaknesses, opportunities and challenges of the development of Macao's cultural heritage tile murals, based on an introduction to the existing status of Macao's cultural heritage tile murals, using the SWOT analysis method, which provides a reference for Macao's cultural heritage tourism
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Over the past several decades, the dichotomy between traditional and emerging donors has been based upon the notion that emerging donors (such as China) support authoritarian regimes and use foreign aid to pursue their economic interests at the expense of the poor in the recipient countries. Accordingly, Western donors, media, and scholars portray Chinese aid as non-poverty-focused. This study aims to review and analyze whether the dichotomy between traditional and emerging donors is still relevant in the current aid system and to propose a new and rigorous criterion for recategorizing donors. In terms of methodology, this study relies on secondary data, including scholarly works on traditional and emerging donors and foreign aid policy documents. Conclusions based on the research indicate that the divide between traditional donors and (re)emerging donors is becoming more ambiguous. The literature review indicates that the two donors’ aids had a mixed impact and that their approaches were similar. This paper highlights the importance of developing different recategorization criteria depending on the impact of aid.
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The phenomenon of burnout has been recognised as a worldwide occupational health issue after being vastly studied for decades. Trait Emotional Intelligence (trait EI) and resilience have been identified as personal protective factors (Gutierrez & Mullen, 2016; Listopad et al., 2021), while organisational socialisation is suggested to be an organisational factor in helping people in preventing burnout (Taormina & Law, 2000). With the purpose of 1) investigating the phenomenon in the counselling profession, as well as 2) exploring how trait EI and resilience are related to burnout and whether organisational socialisation might impose moderating effects in between, the present study examined 115 counselling professionals currently employed and working in organisational settings in Macau by snowball sampling, using a quantitative and cross-sectional approach through self-reported online questionnaires. From the data obtained, different burnout patterns were observed according to job titles and work settings, indicating that counselling professionals with different specialties and work in different settings have unique sources of stress, which resulting in differences in their burnout patterns. No between-group differences were observed in age and work experience, while male participants have a higher burnout perception than female participants in the current study. On the other hand, current results suggested trait EI and four components of resilience (determination, endurance, adaptability and recuperability) are negatively correlated to counselling professionals’ burnout perception, providing supportive evidence that trait EI and resilience are protective factors against burnout. Moderation analysis results revealed that organisational socialisation has some moderating effects on the relationship between trait EI, resilience and burnout. However, differences in direction and intensity indicated that the moderating effects of organisational socialisation might be influenced by individual differences. Further studies are needed to better the understanding of the moderating effect of organisational socialisation. Limitations of the current research and implications for counselling professionals and organisations were also discussed in the study
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This dissertation aims to research the need and viability of creating a digital platform that assists the creative processes naturally linked to Visual Merchandising. Through the proposal of a digital platform that works as a co-creative tool for display archives and a co-creative tool for display set-ups through mood boards, we will aim at improving the teamwork in retail and provide a unique, fast-forward platform for information sharing and input under the direction of Visual Departments. Building on rich source materials such as bibliography, scientific papers, news, and articles, and interviewing Visual Merchandisers actively working in the field, we will show the importance of creativity in Luxury Retail and what are the most common challenges in the field that we will propose a solution to. We will focus on the study of concepts, reviewing digital application tools being used by professionals and their best features and improvement opportunities. By gathering this information, we hope to provide accurate insights and information that proves the viability of this proposal and understand what features could serve best the target audience. Finally, we will present a conceptual idea in the form of sketches with functions of this digital application tool to be fully developed in the future and hopefully build a consistent well, designed commercial web-based application
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The following Arbitration practice note provides comprehensive and up to date legal information on Arbitration as a dispute resolution method in Macau
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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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