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This paper starts to address the affect and side-effects of social media on people’s live in a pure contemplation perspective. Social networks are revised and some issues regarding its impact on education was not forgotten such as the teacher role in the digital classroom, formal versus informal learning or Web 2.0 tools use. Since Moodle is the first Learning Management System whilst Facebook is the first social network in the world, a survey was accomplished with two independent classes of e-business students at University of Saint Joseph, Macao, China, on their attitudes toward both online services in a learning framework. In general, the results confirms to a certain extent others previous studies on the question of whether using Facebook as an educational tool is more effective than Moodle.

For a long time, Geography did not hold a specific mathematical approach for any interpretation of space and this was the key reason why Geography degrees covered a wide variety of subjects such as demography, geology or topography to fulfill its curriculum. Yet from the 90’s, Geography finally created its own research agenda to meet four vital questions of any true geographer: “Where is …?”, “Is there a general spatial pattern?”, “What are the anomalies?” and “Why do these phenomena pursue certain spatial distribution?” The present review article addresses ten different spatial (point, regression and event) issues for learning and teaching aim where statistics play a major background role on the outcomes of myGeoffice© free Web GIS platform. These include cluster analysis, geographically weighted regression (GWR), ordinary least squares (OLS) regression, path analysis, minimum spanning tree, linear regression, space-time clustering and point patterns, for instance. Although the technical viewpoint of the algorithms is not explained at fully, this review paper makes a rather strong emphasis on the result’s interpretation, their respective meaning and when these techniques should be applied in a learning/teaching context.

The knowledge of spatial distribution of grasshoppers can be very relevant for agricultural planning purposes. On the other hand, the comparison of spatial interpolators for efficiency and reliability reasons is also a key factor to understand interpolation maps outcomes (versus reality). At last, but not least, the use of open Web geographical tools to disseminate true spatial inferential methods to address spatial issues is still quite limited (if none) in high schools and universities, particularly in Geography subjects. If the latter can be addressed with myGeoffice©, the first issue will use the Utah, USA, dataset (58 samples) to layout the spatial distribution of grasshoppers and understand the counties that are more pro to this kind of agriculture infestation. Inverse Distance Weighted (IDW), Moving Average (MA), Multi-quadratic, Inverse Multi-quadratic and Nearest Neighbor (NN) will produce interpolated surfaces of grasshopper’s properties. Efficiency of spatial interpolators was assessed in this writing based on the prediction error’s statistics derived from the difference between the estimation and the real samples on a cross-validation procedure. Remarkably, results show that NN was the most accurate one when compared with the remaining deterministic approaches at sample’s locations.

Neuromarketing lies at the intersection of three main disciplines: psychology, neuroscience, and marketing, and it has been a successful neuroscientific approach for the study of real-life choices such as consumer behavior [1]. A current gap in the cosmetics field is the lack of published research studies, considering the marketing investment done yearly in this category. With the rapid economic expansion and the rise of social media in China, consumers' interest in beauty is growing. Even though the Chinese cosmetics sector is rapidly expanding, no studies have been done with Chinese consumers. This study aims to employ the same approach as previously done in consumer neuroscience studies to evaluate cosmetic brands' marketing strategy to understand better if immediate emotional responses can be measured using Electrodermal Activity (EDA). Here, we focus on cosmetics products advertisement as a model to understand consumer preference formation and choice. Eighteen Chinese female consumers were recruited between 19 and 37 years old. From the results obtained, it was understood that none of the participants have voted for the product advertisement for which they showed higher emotional arousal. However, it appears that the participants' preference is for the products for which the brand awareness is stronger since the product advertisements with more votes are the ones for the Korean brand used. The product advertisements with Asian faces were the ones with more votes, suggesting that Asian faces have engaged consumer preference. However, the product advertisements for the Brazilian brands, unknown to the Chinese public, were the ones with fewer votes, although, those product advertisements were the ones with more emotional arousal per minute. Those advertisements were also those with non-Asian faces, suggesting that this feature influenced voting decisions. From this study, it has been observed that Electrodermal Activity is a measure of emotional arousal that by itself cannot be translated into consumer engagement. Therefore, it is also proposed to evaluate brand awareness in future studies related to product advertisements. The physical features of the people included in the advertisements is also suggested to be further evaluated in future studies since a different cultural background seems to influence the consumers' engagement. Furthermore, using EDA to complement other neurophysiological tools like facial expression analysis is also suggested for future studies to have evidence about the nature of the emotions raised.

Three key concepts will make up the pillars of this paper: second, foreign and heritage languages. Whenever appropriate “additional language” will be used as an umbrella term. A study of the domains of language use will be applied to these three different sociolinguistic contexts. To date, there are not many empirical studies on the domains of language and, more specifically, among young learners in different areal contexts, as it is the case of this study.

The aim of this study is to analyze the crisis management of Macao SAR and the extent to which the community were engaged in the COVID-19 pandemic prevention and control. There are some issues found that when the pandemic breaks out and after outbreaks, such as poor information communication, low efficiency of prevention and control work, unsatisfactory compliance of the public, lack of pandemic prevention materials which affect the government's control of the pandemic in the past study. In Macao SAR, densely residential areas and dense population are the main considerations for pandemic prevention and control. Communities, as the main first line of defense for pandemic prevention and control, are also the bridge for communication between the government and the residents. The community have the advantages of timely and accurate information collection and accurate implementation of prevention and control measures. In this study found that the involvement of the Macao community may not be the key to the success of epidemic prevention in Macao. Community participation also faces many challenges, such as uneven distribution of facilities and services, lack of medical expertise of community workers, shortage of manpower and other shortcomings of community participation. It is possible that the Macao community is not playing a key role in the COVID-19 pandemic prevention and control. Given this scenario, the government needs to give full play to social forces and the role of the community in pandemic prevention and control. Currently, there are few studies on community involvement in COVID-19 prevention and control. Through COVID-19, this study puts forward some ideas that the government needs to pay attention to community development and improve citizens' community awareness to promote the Macao community. Improving the Macao community is conducive to Macao in the future crisis and community cooperation

" Air pollution in Macau has become a serious problem following the Pearl River Delta’s (PRD) rapid industrialization that began in the 1990s. While there has been continual improvement in recent years, harmful air pollutant concentration levels are still common, impacting Macau residents' health and creating long-term medical costs to local society. With this in mind, Macau needs an air quality forecast system that accurately predicts pollutant concentration and an early alert system instead of only daily real-time reminders. Some scholars have previously carried out studies to develop an air quality forecast for Macau by successfully using statistical models. Therefore, pursuant to the outcomes of previous studies, this dissertation aims to build upon research results and explore further possibilities of building a better ML air quality forecast model based on the time series of air pollutants concentration and meteorological data. Four different state-of-the-art ML algorithms were used to create predictive models to forecast PM2.5, PM10, and carbon monoxide (CO) concentrations for the next 24 and 48-hour. These were Support Vector Machine (SVM), Artificial Neural Networks (ANN), Random Forest (RF), and Extreme Gradient Boosting (XGBoost). In addition, Multiple Linear Regression MLR, a standard ML model, was used for this dissertation as a baseline reference for performance comparison. The daily measurements of air quality data in Macau from 2016 to 2021 were collected for this dissertation. The 2020 and 2021 datasets were used for model testing while the four-year data prior to 2020 and 2021 were used to build and train the ML models. The results showed that SVM, ANN, RF, and XGBoost were able to provide a very good performance in building up a 24-hour forecast with higher R2 and lower RMSE, MAE, and BIAS. Meanwhile, all ML models in 48-hour forecasting performance were satisfactory enough to be accepted as a two-day continuous forecast even if the R2 value was lower than the 24-hour forecast. The 48-hour forecasting model could be further improved by proper feature selection based on the 24-hour dataset, using the SHAP value test, and the adjusted R2 value of the 48-hour forecasting model."

Virtual reality (VR), a computer-generated 3D environment, allows one to navigate and possibly interact, resulting in real-time simulation of one or more of the user’s five senses (M. Gutierrez et al., 2008; Vince, 2004). Despite its history through past decades, this technology has quickly developed recently. Virtual tours and spaces have been widely used in the education, arts, and rehabilitation industries. According to research, it has significant effects on mindfulness (improving mood), cognitive development (better learning ability), and embodiment (relieving pain and medical conditions). This thesis aims to identify the conditions for Macao's single-user experience to achieve mindfulness in virtual reality through immersion and interactivity. With their various definitions, this research uses the two spectrums on the levels of immersion and interactivity, conducts four experiment settings with Macao residents, and collects qualitative questionnaires and quantitative survey data. The four settings differ as they tackle different aspects: spiritual memory, historical memory, aesthetic appreciation, and meditation through concept. The analysed results were then evaluated to seek better conditions for the local community to achieve mindfulness by immersing themselves in virtual reality