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This study examined the relationships between organizational justice, job satisfaction, and subjective well-being of medical doctors and nurses in Macao. It applied a quantitative methodology through a cross-sectional applying self-response questionnaires to 149 healthcare workers. Consistent with the group-engagement model (Tyler & Blader, 2003), findings indicate that organisational justice and job satisfaction improve subjective well-being. Yet, inconsistent with the model and our hypotheses, organizational justice did not affect work satisfaction. Finally, nurses experienced less positive justice perceptions than doctors. The study provides insights into the relationship between organizational justice, job satisfaction, and subjective well-being among healthcare professionals, which might help enhance working conditions. Healthcare organizations should prioritize promoting job satisfaction and justice perceptions to increase healthcare personnel's subjective well-being. The cross-sectional design limits causal inferences about variable relationships, and the self-reported data may have social desirability or response biases. Still, the originality and value of this paper lie in its contribution to the literature on the well-being of healthcare workers, particularly in the unique context of Macao. To our knowledge, this is the first study in Macao to examine the relationship between organizational justice, job satisfaction, and subjective well-being among healthcare workers

Due to the expansion of the Internet and advancements in technology, e-commerce has been frequently and widely used nowadays. The popularity of online shopping continues to develop and become increasingly common, yet, the concept of impulsive buying has consistently drawn significant attention over the years. In order to fit into the current shopping trend, recognizing the needs and wants of online shoppers as well as providing appropriate approaches are essential tasks for companies to achieve. The question of how to attract consumers to make purchases has been a concern for a long time, and in fact, it is necessary to explore consumers’ online purchase decisions in relation to their impulse buying behavior. In accordance with current academic knowledge, the main objective of this study is to investigate factors that influence consumers' online impulsive buying behavior based on external stimuli (such as sales promotions and websites characteristics) and the elements of marketing mix strategy (product, price, place, and promotion). According to the analysis, the promotion strategy has been identified as the most significant influence on consumers’ decision to make an online impulsive purchase. Therefore, the findings from this study are beneficial for companies and marketers to build a framework in order to develop suitable and effective strategies in order to encourage and stimulate consumers' desire for purchases. Furthermore, the research applies the qualitative methodology by conducting semi-structured interviews with 11 consumers who have previously experienced an online impulse buying

Continuous cardiac monitoring has been increasingly adopted to prevent heart diseases, especially the case of Chagas disease, a chronic condition that can degrade the heart condition, leading to sudden cardiac death. Unfortunately, a common challenge for these systems is the low-quality and high level of noise in ECG signal collection. Also, generic techniques to assess the ECG quality can discard useful information in these so-called chagasic ECG signals. To mitigate this issue, this work proposes a 1D CNN network to assess the quality of the ECG signal for chagasic patients and compare it to the state of art techniques. Segments of 10 s were extracted from 200 1-lead ECG Holter signals. Different feature extractions were considered such as morphological fiducial points, interval duration, and statistical features, aiming to classify 400 segments into four signal quality types: Acceptable ECG, Non-ECG, Wandering Baseline (WB), and AC Interference (ACI) segments. The proposed CNN architecture achieves a $$0.90 \pm 0.02$$accuracy in the multi-classification experiment and also $$0.94 \pm 0.01$$when considering only acceptable ECG against the other three classes. Also, we presented a complementary experiment showing that, after removing noisy segments, we improved morphological recognition (based on QRS wave) by 33% of the entire ECG data. The proposed noise detector may be applied as a useful tool for pre-processing chagasic ECG signals.

"Adult neurogenesis, i.e., the production of new neurons in the adult brain, has been studied intensively in the past years, both in humans and in animal models, as the understanding of this process can have major clinical implications. The study of neurogenesis in fish has been receiving more attention as, unlike mammals, they possess remarkably high levels of adult neurogenesis and a high capability for neuronal regeneration and replacement where neuronal death has occurred. Less is known, however, on the importance of adult neurogenesis for behavioural plasticity, i.e., for the capacity to change behaviour according to context. As a product of the brain, behaviour relies on functional neuronal networks and it may be expected that more permanent changes in behavioural states imply structural reorganization of neuronal circuits, with the integration of new neurons. Interestingly, the high level of brain plasticity of fish is paralleled by a high degree of behavioural plasticity, with many examples of species that change, either reversibly or irreversibly, their behavioural phenotype during their lifetime, as illustrated by species with functional sex-change and alternative reproductive phenotypes. Flexibility in behaviour may thus require a reorganization of neuronal networks underlying these behaviours with recruitment of new neurons. In this thesis, the link between brain and behavioural plasticity was studied in a small marine fish that inhabits the Mediterranean and adjacent Atlantic coasts, the peacock blenny Salaria pavo. In this species, males adopt nests in rock crevices and attract females into the nest for egg laying, with the male taking care of the eggs until hatching. In some populations, a scarcity of nest sites drives smaller and young males to adopt an alternative reproductive tactic to reproduce. These “sneaker” males mimic the females’ morphology and reproductive behaviour in order to illude the larger nesting males and parasitically fertilize eggs during mating events. Sneaker males later transition into the nesting male phenotype, and this major behavioural transformation in the same animal, first courting males and afterwards courting females, may imply significant reorganization of brain areas associated with reproductive behaviour. During the study, a brain atlas for the species was developed and the main cell proliferation regions, i.e. niches of stem cells birth that may differentiate into cells of the nervous system, characterized. Proliferative areas were observed throughout the whole brain and paralleled the pattern described for other teleosts. Proliferative cells were abundant namely in areas like the olfactory bulbs (granular and glomerular), the anterior subdivision of the dorsomedial telencephalon (DMa), the dorsal and ventral part of the ventral subdivision of the dorsomedial telencephalon (DMvd and DMvv), the dorsal part of the dorsal subdivision of the dorsomedial telencephalon (DMdd), the posterior subdivision of the dorsolateral telencephalon (DLp), the posterior zone of the dorsal telencephalic area (DP), the preoptic area (POA), the dorsal, supracommissural and ventral nucleus of the ventral telencephalic area (Vd, Vs and Vv), the optic tectum and its periventricular grey zone (TeO and PGZ), the ventral zone of the periventricular hypothalamus (Hv), the cerebellum, mainly the molecular layer (CCeM) and the caudal lobe (LCa). A study of the brain nuclei activated during female courtship events using immediate early-genes suggested that some of the areas of the social behaviour network (SBN), a set of brain nuclei underlying the expression of social behaviour across vertebrates, are implicated in female courtship, in particular nuclei in the ventral telencephalic regions. This was followed by an experiment to investigate the possible link between cell proliferation and male tactic switch. Nest availability was manipulated to allow a fraction of sneaker males to adopt a nest and start the transition to nesting males. Ten days after the experiment, some of the smaller males had indeed started switching into nesting males, adopting a nest and starting to develop male secondary sexual characters. The pattern of brain proliferation was studied in these fish to try to confirm that the irreversible behavioural transition would be associated with the reorganization of brain nuclei, assuming that cell proliferation relates to neurogenesis and structural reorganization. Transitional males had elevated cell proliferation levels, as compared to males that remained sneakers, in the dorsolateral anterior and posterior telencephalic regions, thought to be homologous to the hippocampus in mammals. Cell proliferation levels were generally elevated in ventral and ventromedial telencephalic nuclei in both sneakers and transitional males, as compared with nesting males and females, areas considered to be homologous to nuclei of the amygdaloid complex of mammals. There was large variation in proliferation levels within transitional males, and in particular one male more advanced in the transition had higher numbers of BrdU-positive cells than the others. This suggests that a longer time-window for detecting the peak in brain cell proliferation associated with tactic transition in some fish may have been needed. Overall, the study supports the hypothesis that behavioural transition in males of this species is paralleled by an increase in cell proliferation in nuclei potentially relevant for the expression of reproductive behaviours, and establishes the peacock blenny as a new relevant model for the study of neuronal plasticity in vertebrates."

The invention of neuroscience has benefited medical practitioners and businesses in improving their management and leadership. Neuromarketing, a field that combines neuroscience and marketing, helps businesses understand consumer behaviour and how they respond to advertising stimuli. This study aims to investigate the consumer purchase intention and preferences to improve the marketing management of the brand, based on neuroscientific tools such as emotional arousal using Galvanic Skin Response (GSR) sensors, eye-tracking, and emotion analysis through facial expressions classification. The stimuli for the experiment are two advertisement videos from the Macau tea brand “Guanding Teahouse” followed by a survey. The experiment was conducted on 40 participants. 76.2% of participants that chose the same product in the first survey responded with the same choice of products in the second survey. The GSR peaks in video ad 1 measured a total of 60. On the other hand, video ad 2 counted a total of 55 GSR peaks. The emotions in ad1 and ad2 have similar responses, with an attention percentage of 76%. The results showed that ad1 has a higher engagement time of 11.1% and ad2 has 9.6%, but only 19 of the respondent’s conducted engagement in video ad1, and 31 showed engagement in video ad2. The results demonstrated that although ad 1 has higher engagement rates, the respondents are more attracted to video ad 2. Therefore, ad2 has better marketing power than ad 1. Overall, this study bridges the gap of no previous research on measuring tea brand advertisements with the neuroscientific method. The results provide valuable insights for marketers to develop better advertisements and marketing campaigns and understand consumer preferences by personalising and targeting advertisements based on consumers' emotional responses and behaviour of consumers' purchase intentions. Future research could explore advertisements targeting different demographics.

This research aims to evaluate a Macau tea brand's social media advertising effectiveness with neuromarketing tools, including physiological monitoring that can measure emotional arousal. This research bridges the gap of social media marketing on Instagram for brands through the neuromarketing method. Data from 40 respondents were collected with iMotions software using neuroscientific tools. This research uses the stimuli of Guanding Teahouse, a newly established Macau tea brand, to evaluate social media advertising effectiveness. The neuroscientific tools – Galvanic Skin Response (GSR) sensors, Eye-tracking, Facial Expression Analysis (FEA) and emotion analysis are used to do the experiment. The data analysis was drawn from one representative respondent to measure the emotions and attention on the Instagram advertisements. Video 1 recorded 9 GSR peaks and Video 2 recorded 12 GSR peaks, both videos attention is ranging between 96-98 indexes. Results show that advertising videos should focus more on the products than the model. Moreover, the participant is more interested in Video 2, but the effectiveness of advertising is showing a lower focus on the brand and the tea. Future studies should consider comparing the video advertising effectiveness of Instagram stories and Instagram reels to prevent disruption of video on the stories ad.

Consumers' selections and decision-making processes are some of the most exciting and challenging topics in neuromarketing, sales, and branding. From a global perspective, multicultural influences and societal conditions are crucial to consider. Neuroscience applications in international marketing and consumer behavior is an emergent and multidisciplinary field aiming to understand consumers' thoughts, reactions, and selection processes in branding and sales. This study focuses on real-time monitoring of different physiological signals using eye-tracking, facial expressions recognition, and Galvanic Skin Response (GSR) acquisition methods to analyze consumers' responses, detect emotional arousal, measure attention or relaxation levels, analyze perception, consciousness, memory, learning, motivation, preference, and decision-making. This research aimed to monitor human subjects' reactions to these signals during an experiment designed in three phases consisting of different branding advertisements. The nonadvertisement exposition was also monitored while gathering survey responses at the end of each phase. A feature extraction module with a data analytics module was implemented to calculate statistical metrics and decision-making supporting tools based on Principal Component Analysis (PCA) and Feature Importance (FI) determination based on the Random Forest technique. The results indicate that when compared to image ads, video ads are more effective in attracting consumers' attention and creating more emotional arousal.

Human emotions can be associated with decision-making, and emotions can generate behaviors. Due to the fact that it could be biased and exhaustively complex to examine how human beings make choices, it is necessary to consider relevant groups of study, such as stock traders and non-traders in finance. This work aims to analyze the connection between emotions and the decision-making process of investors and non-investors submitted to the same set of stimuli to understand how emotional arousal might dictate the decision process. Neuroscience monitoring tools such as Real-Time Facial Expression Analysis (AFFDEX), Eye-Tracking, and Galvanic Skin Response (GSR) were adopted to monitor the related experiments of this paper and its accompanying analysis process. Thirty-seven participants attended the study, 24 were classified as stock traders, and 13 were non-traders; the mean age for the groups was 35 and 25, respectively. The designed experiment initially disclosed a thought-provoking result between the two groups under the certainty and risk-seeking prospect theory; there were more risk-takers among non-investors at 75%, while investors were inclined toward certainty at 79.17%. The implication could be that the non-investing individuals were less complex in thought and therefore pursued higher returns besides a high probability of losing the game. In addition, the automatic emotion classification system indicates that when non-investors confronted a stock trending chart beyond their acquaintance or knowledge, they were psychologically exposed to fear, anger, sadness, and surprise. On the contrary, investors were detected with disgust, joy, contempt, engagement, sadness, and surprise, where sadness and surprise overlapped in both parties. Under time pressure conditions, 54.05% of investors or non-investors tend to make decisions after the peak(s) of emotional arousal. Variations were found in the deciding points of the slopes: 2.70% were decided right after the peak(s), 37.84% waited until the emotions turned stable, and 13.51% were determined as the emotional indicators started to slide downwards. Several combinations of emotional responses were associated with decisions. For example, negative emotions could induce passive decision-making, in this case, to sell the stock; nevertheless, it was also examined that as the slope slipped downwards to a particular horizontal point, the individuals became more optimistic and selected the "BUY" option. Future works may consider expanding the study to larger sample size, different demographic groups, and other biometrics for further analysis and conclusions.

Human emotions can be meticulously associated with decision-making, and emotion can generate behaviours. Due to the fact that it could be bias and exhaustively complex to examine how human beings make choices, important groups of study in finance are stock traders and non-traders. The objective of this work is to analyze the connection between emotions and the decision-making process of investors and non-investors to understand how emotional arousal might dictate the process of deciding policy. As facial expressions are fleeting, neuroscience tools such as AFFDEX (Real-Time Facial Expression Analysis), Eye-Tracking, and GSR (galvanic skin response) were adopted to facilitate the experiment and its accompanying analysis process. Thirty-seven participants attended the study, ranging from 18 to 72 years old; the distribution of investors and non-investors was twenty-four and thirteen, respectively. The experiment initially disclosed a thought-provoking result between the two groups under the certainty and risk-seeking prospect theory; there were more risk-takers among non-investors at 75%, while investors were inclined toward certainty at 79.17%. The implication could be that the non-investing individuals were less complex in thought and therefore pursued higher returns besides a high probability of losing the game. In addition, the automatic emotion classification system indicates that when non-investors confronted a stock trending chart beyond their acquaintance or knowledge, they were psychologically exposed to fear, anger, sadness, and surprise. Investors, on the contrary, were detected with disgust, joy, contempt, engagement, sadness, and surprise, where sadness and surprise overlapped in both parties. Under time pressure conditions, 54.05% of investors or non-investors tend to make decisions after the peak(s) of emotional arousal. Variations were found in the deciding points of the slopes: 2.70% were decided right after the peak(s), 37.84% waited until the emotions turned stable, and 13.51% were determined as the emotional indicators started to slide downwards. Several combinations of emotional responses were associated with decisions. For example, negative emotions could induce passive decision-making, in this case, to sell the stock; nevertheless, it was also examined that as the slope slipped downwards to a particular horizontal point, the individuals became more optimistic and selected the "BUY" option. The support of physiological monitoring tools makes it possible to capture the individuals' responses and discover the science of decision-making. Future works may consider expanding the study to more significant demographic populations for further discoveries

The inundation problem in Macao is getting more attention recently, especially after the destructive impacts of typhoons Hato (2017) and Mangkut (2019). The inundation caused by storm surges is getting more severe with the rapid sea-level rise in Macao. Moreover, the potential threat of a tsunami in Macao, may be enhanced with rising sea-level. This research evaluated the risk of coastal hazards in Macao by analyzing the local meteorological data. The results of the analysis indicate a rising trend in the tropical cyclone intensity and more severe storm surges are expected to occur in the future. Moreover, this research explores the potential of Nature-based Solutions (NbS), particularly mangroves, to address the inundation problem in Macao. The study included a preliminary laboratory-based experiment and the application of local mangroves data in numerical models. The results of the experiment and numerical models demonstrate the ability of mangroves to attenuate waves. These findings, although preliminary, indicate that mangroves could be a promising NbS to address inundation issues in Macao. To effectively implement this NbS, further field investigations are needed to measure attenuation in-situ, as well as determine optimal locations for mangrove restoration projects

This study explored the effect of communication (i.e., among staff, and between staff and clients) and of cultural diversity on job satisfaction (i.e., intrinsic, extrinsic, and general) and perceived service quality of formal caregivers working in elderly services in Macao. We applied a quantitative methodology, based on a cross-sectional design using a self-response questionnaire to 162 staff in six elderly centres in Macao. Based on an extensive review of the literature, we proposed that: H1) cultural diversity is negatively related to (a) intrinsic job satisfaction, (b) extrinsic job satisfaction, (c) general job satisfaction, and (H5) negatively related to perceived competence and service quality; (H2) communication (a) among staff and (b) between staff and clients is positively related to intrinsic job satisfaction (H3) extrinsic job satisfaction, (H4) general job satisfaction, and (H6) perceived service quality; and finally that (H7) intrinsic, (H8) extrinsic, and (H9) general job satisfaction mediate the relationship between (a) cultural diversity, (b) communication among staff and (c) communication between staff and clients, and perceived service quality. We found that more communication among staff was related to higher intrinsic, extrinsic and general job satisfaction, and perceived competence and service quality. And intrinsic job satisfaction mediated the positive effect of communication among staff on perceived service quality. Opposite to predicted communication between staff and clients was related to lower levels of job satisfaction. And cultural diversity was positively related to satisfaction, as well as perceived competence and service quality. The theoretical and practical implications of findings, as well as limitations and suggestions for future research were discussed

Road transportation is one of the main sources of air pollution in Macao. This study mainly explores four major roadside locations with high traffic flow in Macao from March to May 2022 and measures their pollutant concentrations (PM10 and PM2.5), traffic flow and their fuel type, as well as considering the meteorological parameters and pollutant concentration of SMG Macao to analyze the relationship between traffic flow and pollutants on roadside locations. Under the measuring distance between 3 and 6 meters, showing that the four locations had a good correlation with the roadside station data provided by SMG on both weekdays and weekends/holidays (PM2.5: R2 is 0.59 to 0.81 on weekdays and 0.79 to 0.88 on weekends/holidays, p<0.01; PM10: R2 is 0.33 to 0.82 on weekdays and 0.30 to 0.58 on weekends/holidays, p<0.05), the overall PM2.5 is 41 to 86% higher than that of the same period of Macao roadside station (SMG), and 68 to 186% higher than that of Taipa Ambient (SMG), indicating that it is more harmful to daily pedestrians. The overall relationship between PM concentration and traffic flow is small on the long-term scale (PM2.5: R2 is 0.01 to 0.13; PM10: R2 is 0.00 to 0.02). This study also analyzed air quality on EBL, the overall PM2.5 and PM10 decreased by 12.3% to 24.8% compared with non-EBL during the period, so that is indeed beneficial to the reduction of pollutant concentrations. In addition, narrower roads were overall higher when road widths added for comparison. Lastly, meteorological data added for comparison, except for relative humidity, it can be found that there is a significant correlation with long-term pollutants (p<0.05). While previous studies have found that single-day traffic flow is related to the increase in PM concentration, this paper is more inclined to their two-way effect when exploring their long-term relationship

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.

Technology is an essential and valuable tool nowadays. New technology and innovations are introduced to the public day by day. Metaverse will be a new trend, as the Macau government has been trying to promote this technology since the COVID-19 pandemic is still here. Before this technology goes deeply to the public, this paper attempts to examine the consumer’s perspective of Metaverse and understand the cognition of Macau people about Metaverse. And bring out what factors and conditions will make them accept this technology. A qualitative research method will address the questions and problem to understand consumer perspectives towards this technology. Entrepreneurs, managers, and professionals will be invited to take part in this research. Ten interviews will be carried out in this research for data analysis, which may provide a board overview of this technology in Macau and give recommendations to local entrepreneurs. In conclusion, consumers think it is still not a well-developed technology and is not globally used at this stage. In contrast, if this technology is ready-to-use, it will be a helpful assistant in their businesses. They expect the metaverse to be fully developed in ten or more years

Fast and efficient malaria diagnostics are essential in efforts to detect and treat the disease in a proper time. The standard approach to diagnose malaria is a microscope exam, which is submitted to a subjective interpretation. Thus, the automating of the diagnosis process with the use of an intelligent system capable of recognizing malaria parasites could aid in the early treatment of the disease. Usually, laboratories capture a minimum set of images in low quality using a system of microscopes based on mobile devices. Due to the poor quality of such data, conventional algorithms do not process those images properly. This paper presents the application of deep learning techniques to improve the accuracy of malaria plasmodium detection in the presented context. In order to increase the number of training sets, deep convolutional generative adversarial networks (DCGAN) were used to generate reliable training data that were introduced in our deep learning model to improve accuracy. A total of 6 experiments were performed and a synthesized dataset of 2.200 images was generated by the DCGAN for the training phase. For a real image database with 600 blood smears with malaria plasmodium, the proposed Deep Learning architecture obtained the accuracy of 100% for the plasmodium detection. The results are promising and the solution could be employed to support a mass medical diagnosis system.