Your search
Results 411 resources
-
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.
-
In a context of a new transnational division of labour, temporary international labour mobility is on the rise in Europe. In particular, recent decades have seen considerably more women seeking work experience abroad. Observers have been concerned with how such mobility is related to individualization, and in particular how it may challenge collective institutions, communities and families. The aim of this study is to explore such issues among women and men with international work experience. Using data from European Social Survey, the paper investigates previously mobile workers in terms of their current working and living conditions. Across genders, we consider different forms of individualization that may be associated with transnational labour mobility. While both women and men with transnational work experience generally feature strong strategic individualization, this is most pronounced among men. Hence, men's mobility is among other things associated with increased autonomy in working life, while – in contrast to women – it does not seem to hamper their integration in the sphere of social reproduction.
-
Distinct patterns of gene expression often underlie intra- and intersexual differences, and the study of this set of coregulated genes is essential to understand the emergence of complex behavioural phenotypes. Here, we describe the development of a de novo transcriptome and brain gene expression profiles of wild-caught peacock blenny, Salaria pavo, an intertidal fish with sex-role reversal in courtship behaviour (i.e., females are the courting sex) and sequential alternative reproductive tactics in males (i.e., larger and older nest-holder males and smaller and younger sneaker males occur). Sneakers mimic both female's courtship behaviour and nuptial coloration to get access to nests and sneak fertilizations, and later in life transition into nest-holder males. Thus, this species offers the unique opportunity to study how the regulation of gene expression can contribute to intersex phenotypes and to the sequential expression of male and female behavioural phenotypes by the same individual. We found that at the whole brain level, expression of the sneaker tactic was paralleled by broader and divergent gene expression when compared to either females or nest-holder males, which were more similar between themselves. When looking at sex-biased transcripts, sneaker males are intersex rather than being either nest-holder or female-like, and their transcriptome is simultaneously demasculinized for nest-holder-biased transcripts and feminized for female-biased transcripts. These results indicate that evolutionary changes in reproductive plasticity can be achieved through regulation of gene expression, and in particular by varying the magnitude of expression of sex-biased genes, throughout the lifetime of the same individual.
-
<abstract><p>About 6.5 million people are infected with Chagas disease (CD) globally, and WHO estimates that $ > million people worldwide suffer from ChHD. Sudden cardiac death (SCD) represents one of the leading causes of death worldwide and affects approximately 65% of ChHD patients at a rate of 24 per 1000 patient-years, much greater than the SCD rate in the general population. Its occurrence in the specific context of ChHD needs to be better exploited. This paper provides the first evidence supporting the use of machine learning (ML) methods within non-invasive tests: patients' clinical data and cardiac restitution metrics (CRM) features extracted from ECG-Holter recordings as an adjunct in the SCD risk assessment in ChHD. The feature selection (FS) flows evaluated 5 different groups of attributes formed from patients' clinical and physiological data to identify relevant attributes among 57 features reported by 315 patients at HUCFF-UFRJ. The FS flow with FS techniques (variance, ANOVA, and recursive feature elimination) and Naive Bayes (NB) model achieved the best classification performance with 90.63% recall (sensitivity) and 80.55% AUC. The initial feature set is reduced to a subset of 13 features (4 Classification; 1 Treatment; 1 CRM; and 7 Heart Tests). The proposed method represents an intelligent diagnostic support system that predicts the high risk of SCD in ChHD patients and highlights the clinical and CRM data that most strongly impact the final outcome.</p></abstract>
-
We critically review studies of subjective wellbeing conducted in China by the International Wellbeing Group, and we evaluate the International Wellbeing Index (IWI), a new instrument they developed. Subjective wellbeing was positive and similar in studies across China, and conformed to the normative range. Its resilience (PWI = 61.2–67.1) mirrors survey findings conducted in Western countries, in agreement with Subjective Wellbeing Homeostasis. Reliability, validity and psychometric analyses support the utility of the IWI as a measure of subjective wellbeing. Our conclusions have implications for research and social development in China, discussed further in this review.
-
Statistical methods such as multiple linear regression (MLR) and classification and regression tree (CART) analysis were used to build prediction models for the levels of pollutant concentrations in Macao using meteorological and air quality historical data to three periods: (i) from 2013 to 2016, (ii) from 2015 to 2018, and (iii) from 2013 to 2018. The variables retained by the models were identical for nitrogen dioxide (NO2), particulate matter (PM10), PM2.5, but not for ozone (O3) Air pollution data from 2019 was used for validation purposes. The model for the 2013 to 2018 period was the one that performed best in prediction of the next-day concentrations levels in 2019, with high coefficient of determination (R2), between predicted and observed daily average concentrations (between 0.78 and 0.89 for all pollutants), and low root mean square error (RMSE), mean absolute error (MAE), and biases (BIAS). To understand if the prediction model was robust to extreme variations in pollutants concentration, a test was performed under the circumstances of a high pollution episode for PM2.5 and O3 during 2019, and the low pollution episode during the period of implementation of the preventive measures for COVID-19 pandemic. Regarding the high pollution episode, the period of the Chinese National Holiday of 2019 was selected, in which high concentration levels were identified for PM2.5 and O3, with peaks of daily concentration exceeding 55 μg/m3 and 400 μg/m3, respectively. The 2013 to 2018 model successfully predicted this high pollution episode with high coefficients of determination (of 0.92 for PM2.5 and 0.82 for O3). The low pollution episode for PM2.5 and O3 was identified during the 2020 COVID-19 pandemic period, with a low record of daily concentration for PM2.5 levels at 2 μg/m3 and O3 levels at 50 μg/m3, respectively. The 2013 to 2018 model successfully predicted the low pollution episode for PM2.5 and O3 with a high coefficient of determination (0.86 and 0.84, respectively). Overall, the results demonstrate that the statistical forecast model is robust and able to correctly reproduce extreme air pollution events of both high and low concentration levels.
-
The levels of air pollution in Macao often exceeded the levels recommended by WHO. In order for the population to take precautionary measures and avoid further health risks under high pollutant exposure, it is important to develop a reliable air quality forecast. Statistical models based on multiple regression (MR) analysis were developed successfully for Macao to predict the next day concentrations of PM10, PM2.5, and NO2. All the developed models were statistically significantly valid with a 95% confidence level with high coefficients of determination (from 0.89 to 0.92) for all pollutants. The models utilized meteorological and air quality variables based on five years of historical data, from 2013 to 2017. The data from 2013 to 2016 were used to develop the statistical models and data from 2017 were used for validation purposes. A wide range of meteorological and air quality variables were identified, and only some were selected as significant dependent variables. Meteorological variables were selected from an extensive list of variables, including geopotential height, relative humidity, atmospheric stability, and air temperature at different vertical levels. Air quality variables translate the resilience of the recent past concentrations of each pollutant and usually are maximum and/or the average of latest 24-hour levels. The models were applied in forecasting the next day average daily concentrations for PM10, PM2.5, and NO2 for the air quality monitoring stations. The results are expected to be an operational air quality forecast for Macao.
-
The concept of Soundscape was initially proposed to study the relationship between humans and their sonic environment. It has gathered momentum from academia to environmentalists and policymakers throughout the years. The study and characterisation of Soundscapes can be complex as it tries to take a holistic and qualitative approach rather than simply quantifying sound pressure levels. This paper introduces a comprehensive Soundscape study process in an ongoing research project in Macao (China), a small territory (32.9 km2) and one of the most densely populated areas in the world. The paper seeks to show a first version of a technical solution to systematically capture the local soundscape, analyse it, classify it, and ultimately deliver a dataset library and the intangible qualities of the environmental sound. This implementation, including technical documentation, code, and sound library with strong labelling, is presented under an open-source license to encourage future collaborative research. Finally, the paper offers suggestions on further developing the apparatus to reach a systematic and near real-time soundscape analysis with the development of a machine learning system.
-
Hydrology modeling became a relevant topic for the Cidade da Praia, Cabo Verde, Africa, due to negative impact risk to local population and its assets. The modeling via Geographical Information Systems (GIS) can help the decision-making process of space occupation and characterization for this type of risk. Under the municipalities of Praia, the phenomenon of flash flood is common, causing soil erosion and landslide. This constitutes a risk for the local habitat, particularly in districts with a lack of strong human infrastructures. To simulate, analyze and generate risk maps using GIS to help this county governance authorities for decision-making, thus, becomes the main aim of this article.
-
Alternative reproductive tactics (ARTs) evolve when there is strong intra-sexual competition between conspecifics for access to mates. Typically, larger “bourgeois” males reproduce by securing the access to reproductive resources while smaller “parasitic” males reproduce by stealing fertilizations from larger males. A number of factors can influence the reproductive success of each tactic, including intrinsic (e.g. size) and extrinsic (e.g. tactic relative frequency) variables. An example where plastic ARTs occur is the peacock blenny Salaria pavo, with large males reproducing by defending nests and attracting females (bourgeois tactic) and small males reproducing by achieving sneaked fertilizations (parasitic tactic). In this study, we conducted field observations on individually tagged animals to determine their social network and collected eggs from 11 nests to determine the fertilization success of each male tactic. Paternity estimates for 550 offspring indicated an average fertilization success for nest-holder males of 95%. Nest-holder male morphological traits and social network parameters were tested as predictors of fertilization success, but only the number of sneakers present in the nest-holder’s social networks was found to be a predictor of paternity loss. Although male morphological traits had been previously found to be strongly correlated with reproductive success of nest-holder males, as measured by the number of eggs collected in the male’s nest, no correlation was found between any of the measured morphological traits and fertilization success for these males. The results suggest a stronger influence of the social environment than of morphological variables in the proportion of lost fertilizations by nest-holder males of this species.
Explore
Academic Units
- Faculty of Arts and Humanities (79)
- Faculty of Business and Law (85)
- Faculty of Health Sciences (34)
- Faculty of Religious Studies and Philosophy (47)
- Institute for Data Engineering and Sciences (14)
- Institute of Science and Environment (77)
- Library (2)
- Macau Ricci Institute (7)
- School of Education (73)
Resource type
United Nations SDGs
- 01 - No Poverty (1)
- 02 - Zero Hunger (1)
- 03 - Good Health and Well-being (10)
- 04 - Quality Education (5)
- 05 - Gender Equality (1)
- 07 - Affordable and Clean Energy (1)
- 08 - Decent Work and Economic Growth (3)
- 09 - Industry, Innovation and Infrastructure (11)
- 10 - Reduced Inequalities (1)
- 11 - Sustainable Cities and Communities (5)
- 12 - Responsable Consumption and Production (2)
- 13 - Climate Action (2)
- 14 - Life Below Water (12)
- 15 - Life on Land (4)
- 16 - Peace, Justice and Strong Institutions (1)