Australian Catholic University

About: Australian Catholic University is a education organization based out in Brisbane, Queensland, Australia. It is known for research contribution in the topics: Population & Poison control. The organization has 2721 authors who have published 10013 publications receiving 215248 citations. The organization is also known as: ACU & ACU National.

Empirical research on teaching and learning of mathematical modelling: a survey on the current state-of-the-art

Abstract: The teaching and learning of mathematical modelling is an important research field all over the world. In this paper we present a survey of the state-of-the-art on empirical studies in this field. We analyse the development of studies focusing on cognitive aspects of the promotion of modelling, i.e. the promotion of modelling abilities resp. skills, or in newer terminology, modelling competencies. Furthermore, we provide a literature search on the role of empirical research in important mathematics education journals and point out that this topic is only seldom treated in these journals. In addition, Proceedings of the conference series on the teaching and learning of mathematical modelling and applications were analysed in order to identify the role of empirical research in this important series and the kind of topics which are examined. The literature research points out the dominance of case study approaches and cognitively oriented studies compared to studies which used quantitative research methods or focused on affect-related issues. Finally, the papers in this special issue are described and developments and future prospects are identified.

Effect of standing posture during whole body vibration training on muscle morphology and function in older adults: A randomised controlled trial

Abstract: Background Whole body vibration (WBV) is a novel modality of exercise shown to improve musculoskeletal function. This study aims to examine the effects of standing posture during low magnitude WBV training on muscle function and muscle morphology in older adults.

Constraint‐induced movement therapy in children with unilateral cerebral palsy

Abstract: Background Unilateral cerebral palsy (CP) is a condition that affects muscle control and function on one side of the body. Children with unilateral CP experience difficulties using their hands together secondary to disturbances that occur in the developing fetal or infant brain. Often, the more affected limb is disregarded. Constraint-induced movement therapy (CIMT) aims to increase use of the more affected upper limb and improve bimanual performance. CIMT is based on two principles: restraining the use of the less affected limb (for example, using a splint, mitt or sling) and intensive therapeutic practice of the more affected limb. Objectives To evaluate the effect of constraint-induced movement therapy (CIMT) in the treatment of the more affected upper limb in children with unilateral CP. Search methods In March 2018 we searched CENTRAL, MEDLINE, Embase, CINAHL, PEDro, OTseeker, five other databases and three trials registers. We also ran citation searches, checked reference lists, contacted experts, handsearched key journals and searched using Google Scholar. Selection criteria Randomised controlled trials (RCTs), cluster-RCTs or clinically controlled trials implemented with children with unilateral CP, aged between 0 and 19 years, where CIMT was compared with a different form of CIMT, or a low dose, high-dose or dose-matched alternative form of upper-limb intervention such as bimanual intervention. Primarily, outcomes were bimanual performance, unimanual capacity and manual ability. Secondary outcomes included measures of self-care, body function, participation and quality of life. Data collection and analysis Two review authors independently screened titles and abstracts to eliminate ineligible studies. Five review authors were paired to extract data and assess risk of bias in each included study. GRADE assessments were undertaken by two review authors. Main results We included 36 trials (1264 participants), published between 2004 and 2018. Sample sizes ranged from 11 to 105 (mean 35). Mean age was 5.96 years (standard deviation (SD) 1.82), range three months to 19.8 years; 53% male and 47% participants had left hemiplegia. Fifty-seven outcome measures were used across studies. Average length of CIMT programs was four weeks (range one to 10 weeks). Frequency of sessions ranged from twice weekly to seven days per week. Duration of intervention sessions ranged from 0.5 to eight hours per day. The mean total number of hours of CIMT provided was 137 hours (range 20 to 504 hours). The most common constraint devices were a mitt/glove or a sling (11 studies each).We judged the risk of bias as moderate to high across the studies. Key results Primary outcomes at primary endpoint (immediately after intervention)CIMT versus low-dose comparison (e.g. occupational therapy)We found low-quality evidence that CIMT was more effective than a low-dose comparison for improving bimanual performance (mean difference (MD) 5.44 Assisting Hand Assessment (AHA) units, 95% confidence interval (CI) 2.37 to 8.51).CIMT was more effective than a low-dose comparison for improving unimanual capacity (Quality of upper extremity skills test (QUEST) - Dissociated movement MD 5.95, 95% CI 2.02 to 9.87; Grasps; MD 7.57, 95% CI 2.10 to 13.05; Weight bearing MD 5.92, 95% CI 2.21 to 9.6; Protective extension MD 12.54, 95% CI 8.60 to 16.47). Three studies reported adverse events, including frustration, constraint refusal and reversible skin irritations from casting.CIMT versus high-dose comparison (e.g. individualised occupational therapy, bimanual therapy)When compared with a high-dose comparison, CIMT was not more effective for improving bimanual performance (MD -0.39 AHA Units, 95% CI -3.14 to 2.36). There was no evidence that CIMT was more effective than a high-dose comparison for improving unimanual capacity in a single study using QUEST (Dissociated movement MD 0.49, 95% CI -10.71 to 11.69; Grasp MD -0.20, 95% CI -11.84 to 11.44). Two studies reported that some children experienced frustration participating in CIMT.CIMT versus dose-matched comparison (e.g. Hand Arm Bimanual Intensive Therapy, bimanual therapy, occupational therapy)There was no evidence of differences in bimanual performance between groups receiving CIMT or a dose-matched comparison (MD 0.80 AHA units, 95% CI -0.78 to 2.38).There was no evidence that CIMT was more effective than a dose-matched comparison for improving unimanual capacity (Box and Blocks Test MD 1.11, 95% CI -0.06 to 2.28; Melbourne Assessment MD 1.48, 95% CI -0.49 to 3.44; QUEST Dissociated movement MD 6.51, 95% CI -0.74 to 13.76; Grasp, MD 6.63, 95% CI -2.38 to 15.65; Weightbearing MD -2.31, 95% CI -8.02 to 3.40) except for the Protective extension domain (MD 6.86, 95% CI 0.14 to 13.58).There was no evidence of differences in manual ability between groups receiving CIMT or a dose-matched comparison (ABILHAND-Kids MD 0.74, 95% CI 0.31 to 1.18). From 15 studies, two children did not tolerate CIMT and three experienced difficulty. Authors' conclusions The quality of evidence for all conclusions was low to very low. For children with unilateral CP, there was some evidence that CIMT resulted in improved bimanual performance and unimanual capacity when compared to a low-dose comparison, but not when compared to a high-dose or dose-matched comparison. Based on the evidence available, CIMT appears to be safe for children with CP.

Stock trading with cycles

Abstract: Research highlights? Reinforcement learning is used to formalize an automated process for determining stock cycles by tuningthe momentum and the average periods. ? The secondary and tertiary trends or short-term wave cycles are eliminated by a smoothing technique. ? The use of reinforcement learning (RL) as a non-arbitrage algorithmic trading system. ? Our study attempts to identify the change of a primary trend or a broad movement. ? Dynamic asset switching based on the detection of peaks and troughs within a portfolio of stock counters. Based on the principles of technical analysis, this paper proposes an artificial intelligence model, which employs the Adaptive Network Fuzzy Inference System (ANFIS) supplemented by the use of reinforcement learning (RL) as a non-arbitrage algorithmic trading system. The novel intelligent trading system is capable of identifying a change in a primary trend for trading and investment decisions. It dynamically determines the periods for momentum and moving averages using the RL paradigm and also appropriately shifting the cycle using ANFIS-RL to address the delay in the predicted cycle. This is used as a proxy to determine the best point in time to go LONG and visa versa for SHORT. When this is coupled with a group of stocks, we derive a simple form of "riding the cycles - waves". These are the derived features of the underlying stock movement. It provides a learning framework to trade on cycles. Initial experimental results are encouraging. Firstly, the proposed framework is able to outperform DENFIS and RSPOP in terms of true error and correlation. Secondly, based on the test trading with five US stocks, the proposed trading system is able to beat the market by about 50 percentage points over a period of 13years.