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Background and objective Intrauterine Growth Restriction (IUGR) is a condition in which a fetus does not grow to the expected weight during pregnancy. There are several well documented causes in the literature for this issue, such as maternal disorder, and genetic influences. Nevertheless, besides the risk during pregnancy and labour periods, in a long term perspective, the impact of IUGR condition during the child development is an area of research itself. The main objective of this work is to propose a machine learning solution to identify the most significant features of importance based on physiological, clinical or socioeconomic factors correlated with previous IUGR condition after 10 years of birth. Methods In this work, 41 IUGR (18 male) and 34 Non-IUGR (22 male) children were followed up 9 years after the birth, in average (9.1786 ± 0.6784 years old). A group of machine learning algorithms is proposed to classify children previously identified as born under IUGR condition based on 24-hours monitoring of ECG (Holter) and blood pressure (ABPM), and other clinical and socioeconomic attributes. In additional, an algorithm of relevance determination based on the classifier is also proposed, to determine the level of importance of the considered features. Results The proposed classification solution achieved accuracy up to 94.73%, and better performance than seven state-of-the-art machine learning algorithms. Also, relevant latent factors related to HRV and BP monitoring are proposed, such as: day-time heart rate (day-time HR), day-night systolic blood pressure (day-night SBP), 24-hour standard deviation (SD) of SBP, dropped, morning cortisol creatinine, 24-hour mean of SDs of all NN intervals for each 5 minutes segment (24-hour SDNNi), among others. Conclusion With outstanding accuracy of our proposed solutions, the classification system and the indication of relevant attributes may support medical teams on the clinical monitoring of IUGR children during their childhood development.
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This paper aims to report a case study of exploring the effect of ?assessment for learning? on improving student learning and facilitating teachers? professional development in the examination-oriented context of Hong Kong. By adopting Variation Theory of the Lesson Study approach, data were collected through pre- and post-tests, interviews with students and teacher participants and observation field-notes in order to help diagnose students? learning difficulties and provide evidence for teachers to refine their teaching strategies to enhance students? learning effectiveness. The students? improvement in learning performance informed the teacher participants of the usefulness of ?assessment for learning? in the classroom.
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Education for learners with special education needs has become one of the major concerns of education policies in every corner of the world. In Macau, however, the transformation of schools into inclusive environments is reported to be slow because many teachers in Macau have not accepted the key values of inclusive education and possess little knowledge of their responsibilities as inclusive education teachers. Despite being nonempirical, the aim of this article is twofold: to inform inclusive education teachers, especially those in Macau and other developing regions, of the necessary knowledge, skills and strategies of working collaboratively with parents of children with SEN and provide policy makers concerned with practical ideas of designing effective professional development programmes for teachers working in the inclusive environment. The ultimate aim is to ensure that children with SEN benefit from an education process that includes quality learning opportunities.
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The objective of this case study is to analyze how two groups of parents, a group who have newly arrived in Macau from Mainland China and the other who have resided in Macau for more than three decades, interact with the class teachers at the levels of ?two-way communication,? ?supervision of children at home,? and ?participating in decision making? in a secondary school. The findings will redound to the benefits of school leaders, teachers, and indirectly the parents in a sense that looking closely at the ethnic and cultural differences between parents can promote effective cooperation between parents and teachers.
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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.
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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.
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One of the purposes of this study is to evaluate how the choice of teaching method can be assisted by knowledge of a student’s personality type and learning style. The present research is undertaken in the context of Web 2.0 tools use within the Portuguese literature subject at Escola Portuguesa de Macao (EPM). The Felder-Soloman index of learning style (ILS) and the Myers-Briggs Type Indicator (MBTI) based upon Jung’s theory of psychological nature were used as measures of learning style and personality type with 8th grade EPM students. Descriptive and chi-squared correlation statistical results of the associations between personality and learners types are presented. These results are discussed positing that the knowledge of student’s personality traits and learning styles together may have a notable implication for teaching methods.
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Complexity theory (CT) has had a meteoric rise in management literature and the social sciences. Its fledgling importation into school leadership and management raises several questions and concerns. This article takes one view of CT and argues that, though its key elements have much to offer school leadership and management, caution has to be exercised in accepting CT too readily, as it: (1) is unclear on its own novelty, nature and status; (2) can be regarded as disguised ideology in conflating description and prescription; (3) confuses explanation with prediction; (4) is relativist, undermining its own status; (5) contains problems in its advocacy of self-organization; (6) neglects the ethical and emotional dimensions of leadership and management; and (7) risks exonerating school leaders and managers from reasonable expectations of accountability and responsibility. The article concludes that there are questions to CT at the levels of theory, ontology, deontology and ethics, but that it offers useful challenges for school leadership and management.
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