Inverse Correlation between Vitamin D and C-Reactive Protein in Newborns

Some studies suggested that adequate vitamin D might reduce inflammation in adults. However, little is known about this association in early life. We aimed to determine the relationship between cord blood 25-hydroxyvitamin D (25(OH)D) and C-reactive protein (CRP) in neonates. Cord blood levels of 25(OH)D and CRP were measured in 1491 neonates in Hefei, China. Potential confounders including maternal sociodemographic characteristics, perinatal health status, lifestyle, and birth outcomes were prospectively collected. The average values of cord blood 25(OH)D and CRP were 39.43 nmol/L (SD = 20.35) and 6.71 mg/L (SD = 3.07), respectively. Stratified by 25(OH)D levels, per 10 nmol/L increase in 25(OH)D, CRP decreased by 1.42 mg/L (95% CI: 0.90, 1.95) among neonates with 25(OH)D <25.0 nmol/L, and decreased by 0.49 mg/L (95% CI: 0.17, 0.80) among neonates with 25(OH)D between 25.0 nmol/L and 49.9 nmol/L, after adjusting for potential confounders. However, no significant association between 25(OH)D and CRP was observed among neonates with 25(OH)D ≥50 nmol/L. Cord blood 25(OH)D and CRP levels showed a significant seasonal trend with lower 25(OH)D and higher CRP during winter-spring than summer-autumn. Stratified by season, a significant linear association of 25(OH)D with CRP was observed in neonates born in winter-spring (adjusted β = −0.11, 95% CI: −0.13, −0.10), but not summer-autumn. Among neonates born in winter-spring, neonates with 25(OH)D <25 nmol/L had higher risk of CRP ≥10 mg/L (adjusted OR = 3.06, 95% CI: 2.00, 4.69), compared to neonates with 25(OH)D ≥25 nmol/L. Neonates with vitamin D deficiency had higher risk of exposure to elevated inflammation at birth.

Integrating ePsychology into practice and research: A guide for early career psychologists

The ever expanding availability of technology-based mental health services and resources has opened up new areas of psychological practice and research. There are many reasons to embrace this technology movement, whether specialising in providing e-mental health services, conducting research on e-mental health or using technology to assist you in your work in other fields of psychology. e-mental health services not only offer more treatment choices for clients but they provide health professionals with an array of free and comprehensive resources that can help streamline their face-to-face work. This growth in ePsychology (the application of e-mental health by psychologists) also opens up an exciting range of research and teaching possibilities. In this article we cover what ePsychology can offer the early career psychologist.

Personality in sport and exercise psychology: Integrating a whole person perspective

This paper draws on contemporary views in personality psychology as a means for understanding people participating in sport and physical activity. Specifically, we focus on McAdams’ integrative framework [McAdams (2013). The psychological self as actor, agent, and author. Perspectives on Psychological Science, 8, 272–295; McAdams & Pals (2006). A new big five: Fundamental principles for an integrative science of personality. American Psychologist, 61, 204–217] and suggest this framework as potentially generative in the field of sport and exercise psychology. McAdams indicates that people can be defined through three layers of understanding, incorporating (a) dispositional traits, (b) characteristic adaptations, and (c) narrative identities. Together these layers provide a vision of the whole person – a perspective of personality rarely adopted by the sport and exercise community. The aim of this paper is to introduce scholars and practitioners to the potential benefits of embracing this whole person outlook, and to discuss the opportunities and challenges McAdams’ framework may have for advancing scholarship in sport and exercise psychology.

Integrating and evaluating neural word embeddings in information retrieval

Recent advances in neural language models have contributed new methods for learning distributed vector representations of words (also called word embeddings). Two such methods are the continuous bag-of-words model and the skipgram model. These methods have been shown to produce embeddings that capture higher order relationships between words that are highly effective in natural language processing tasks involving the use of word similarity and word analogy. Despite these promising results, there has been little analysis of the use of these word embeddings for retrieval. Motivated by these observations, in this paper, we set out to determine how these word embeddings can be used within a retrieval model and what the benefit might be. To this aim, we use neural word embeddings within the well known translation language model for information retrieval. This language model captures implicit semantic relations between the words in queries and those in relevant documents, thus producing more accurate estimations of document relevance. The word embeddings used to estimate neural language models produce translations that differ from previous translation language model approaches; differences that deliver improvements in retrieval effectiveness. The models are robust to choices made in building word embeddings and, even more so, our results show that embeddings do not even need to be produced from the same corpus being used for retrieval.

Application of inverse filtering technique in power system studies

This paper demonstrates the application of inverse filtering technique for power systems. In order to implement this method, the control objective should be based on a system variable that needs to be set on a specific value for each sampling time. A control input is calculated to generate the desired output of the plant and the relationship between the two is used design an auto-regressive model. The auto-regressive model is converted to a moving average model to calculate the control input based on the future values of the desired output. Therefore, required future values to construct the output are predicted to generate the appropriate control input for the next sampling time.

A novel concept for airport terminal design integrating flexibility

The current research proposed a conceptual design framework for airports to obtain flexible departure layouts based on passenger activity analysis obtained from Business Process Models (BPM). BPMs available for airport terminals were used as a design tool in the current research to uncover the relationships existing between spatial layout and corresponding passenger activities. An algorithm has been developed that demonstrates the applicability of the proposed design framework by obtaining relative spatial layouts based on passenger activity analysis. The generated relative spatial layout assists architects in achieving suitable alternative layouts to meet the changing needs of an airport terminal.

Integrating urban ecosystem sustainability assessment into policy-making: Insights from the Gold Coast City

This paper introduces a policy-making support tool called ‘Micro-level Urban ecosystem Sustainability IndeX (MUSIX)’. The index serves as a sustainability assessment model that monitors six aspects of urban ecosystems, hydrology, ecology, pollution, location, design, and efficiency based on parcel-scale indicators. This index is applied in a case study investigation in the Gold Coast City, Queensland, Australia. The outcomes reveal that there are major environmental problems caused by increased impervious surfaces from growing urban development in the study area. The findings suggest that increased impervious surfaces are linked to increased surface runoff, car dependency, transport-related pollution, poor public transport accessibility, and unsustainable built environment. This paper presents how the MUSIX outputs can be used to guide policy-making through the evaluation of existing policies.

A model eliciting framework for integrating mathematics and robotics learning

Robotics is taught in many Australian ICT classrooms, in both primary and secondary schools. Robotics activities, including those developed using the LEGO Mindstorms NXT technology, are mathematics-rich and provide a fertile round for learners to develop and extend their mathematical thinking. However, this context for learning mathematics is often under-exploited. In this paper a variant of the model construction sequence (Lesh, Cramer, Doerr, Post, & Zawojewski, 2003) is proposed, with the purpose of explicitly integrating robotics and mathematics teaching and learning. Lesh et al.’s model construction sequence and the model eliciting activities it embeds were initially researched in primary mathematics classrooms and more recently in university engineering courses. The model construction sequence involves learners working collaboratively upon product-focussed tasks, through which they develop and expose their conceptual understanding. The integrating model proposed in this paper has been used to design and analyse a sequence of activities in an Australian Year 4 classroom. In that sequence more traditional classroom learning was complemented by the programming of LEGO-based robots to ‘act out’ the addition and subtraction of simple fractions (tenths) on a number-line. The framework was found to be useful for planning the sequence of learning and, more importantly, provided the participating teacher with the ability to critically reflect upon robotics technology as a tool to scaffold the learning of mathematics.