217 resultados para Cognitive flexibility
Resumo:
Density functional theory (DFT) calculations were performed to study the structural, mechanical, electrical, optical properties, and strain effects in single-layer sodium phosphidostannate(II) (NaSnP). We find the exfoliation of single-layer NaSnP from bulk form is highly feasible because the cleavage energy is comparable to graphite and MoS2. In addition, the breaking strain of the NaSnP monolayer is comparable to other widely studied 2D materials, indicating excellent mechanical flexibility of 2D NaSnP. Using the hybrid functional method, the calculated band gap of single-layer NaSnP is close to the ideal band gap of solar cell materials (1.5 eV), demonstrating great potential in future photovoltaic application. Furthermore, strain effect study shows that a moderate compression (2%) can trigger indirect-to-direct gap transition, which would enhance the ability of light absorption for the NaSnP monolayer. With sufficient compression (8%), the single-layer NaSnP can be tuned from semiconductor to metal, suggesting great applications in nanoelectronic devices based on strain engineering techniques.
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Cognitive scientists were not quick to embrace the functional neuroimaging technologies that emerged during the late 20th century. In this new century, cognitive scientists continue to question, not unreasonably, the relevance of functional neuroimaging investigations that fail to address questions of interest to cognitive science. However, some ultra-cognitive scientists assert that these experiments can never be of relevance to the study of cognition. Their reasoning reflects an adherence to a functionalist philosophy that arbitrarily and purposefully distinguishes mental information-processing systems from brain or brain-like operations. This article addresses whether data from properly conducted functional neuroimaging studies can inform and subsequently constrain the assumptions of theoretical cognitive models. The article commences with a focus upon the functionalist philosophy espoused by the ultra-cognitive scientists, contrasting it with the materialist philosophy that motivates both cognitive neuroimaging investigations and connectionist modelling of cognitive systems. Connectionism and cognitive neuroimaging share many features, including an emphasis on unified cognitive and neural models of systems that combine localist and distributed representations. The utility of designing cognitive neuroimaging studies to test (primarily) connectionist models of cognitive phenomena is illustrated using data from functional magnetic resonance imaging (fMRI) investigations of language production and episodic memory.
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Functional connectivity (FC) analyses of resting-state fMRI data allow for the mapping of large-scale functional networks, and provide a novel means of examining the impact of dopaminergic challenge. Here, using a double-blind, placebo-controlled design, we examined the effect of L-dopa, a dopamine precursor, on striatal resting-state FC in 19 healthy young adults.Weexamined the FC of 6 striatal regions of interest (ROIs) previously shown to elicit networks known to be associated with motivational, cognitive and motor subdivisions of the caudate and putamen (Di Martino et al., 2008). In addition to replicating the previously demonstrated patterns of striatal FC, we observed robust effects of L-dopa. Specifically, L-dopa increased FC in motor pathways connecting the putamen ROIs with the cerebellum and brainstem. Although L-dopa also increased FC between the inferior ventral striatum and ventrolateral prefrontal cortex, it disrupted ventral striatal and dorsal caudate FC with the default mode network. These alterations in FC are consistent with studies that have demonstrated dopaminergic modulation of cognitive and motor striatal networks in healthy participants. Recent studies have demonstrated altered resting state FC in several conditions believed to be characterized by abnormal dopaminergic neurotransmission. Our findings suggest that the application of similar experimental pharmacological manipulations in such populations may further our understanding of the role of dopaminergic neurotransmission in those conditions.
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Background: Magnetic resonance diffusion tensor imaging (DTI) shows promise in the early detection of microstructural pathophysiological changes in the brain. Objectives: To measure microstructural differences in the brains of participants with amnestic mild cognitive impairment (MCI) compared with an age-matched control group using an optimised DTI technique with fully automated image analysis tools and to investigate the correlation between diffusivity measurements and neuropsychological performance scores across groups. Methods: 34 participants (17 participants with MCI, 17 healthy elderly adults) underwent magnetic resonance imaging (MRI)-based DTI. To control for the effects of anatomical variation, diffusion images of all participants were registered to standard anatomical space. Significant statistical differences in diffusivity measurements between the two groups were determined on a pixel-by-pixel basis using gaussian random field theory. Results: Significantly raised mean diffusivity measurements (p<0.001) were observed in the left and right entorhinal cortices (BA28), posterior occipital-parietal cortex (BA18 and BA19), right parietal supramarginal gyrus (BA40) and right frontal precentral gyri (BA4 and BA6) in participants with MCI. With respect to fractional anisotropy, participants with MCI had significantly reduced measurements (p<0.001) in the limbic parahippocampal subgyral white matter, right thalamus and left posterior cingulate. Pearson's correlation coefficients calculated across all participants showed significant correlations between neuropsychological assessment scores and regional measurements of mean diffusivity and fractional anisotropy. Conclusions: DTI-based diffusivity measures may offer a sensitive method of detecting subtle microstructural brain changes associated with preclinical Alzheimer's disease.
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Aim: To examine the concordance rates of common medical conditions and neurocognitive performance in monozygotic (MZ) and dizygotic (DZ) older twins. Methods: Twins aged ≥65 years and living in the three Eastern states of Australia were recruited through the Australian Twin Registry and underwent detailed neuropsychological and medical assessment. Results: Assessments were conducted on 113 MZ and 96 DZ twin pairs, with a mean age of 70.5 years. MZ twins were more concordant than DZ twins for hypertension and asthma. MZ twins had higher correlations than DZ twins on most neuropsychological tests, with the exception of some tests related to processing speed. The concordance rate for mild cognitive impairment or dementia was 76.2% in MZ twins and 42.9% in DZ twins, a non-significant difference. Conclusions: Except for some aspects of processing speed, most cognitive functions in older individuals show significant heritability. The heritability of neurocognitive disorders is, however, low.
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Modal flexibility is a widely accepted technique to detect structural damage using vibration characteristics. Its application to detect damage in long span large diameter cables such as those used in suspension bridge main cables has not received much attention. This paper uses the modal flexibility method incorporating two damage indices (DIs) based on lateral and vertical modes to localize damage in such cables. The competency of those DIs in damage detection is tested by the numerically obtained vibration characteristics of a suspended cable in both intact and damaged states. Three single damage cases and one multiple damage case are considered. The impact of random measurement noise in the modal data on the damage localization capability of these two DIs is next examined. Long span large diameter cables are characterized by the two critical cable parameters named bending stiffness and sag-extensibility. The influence of these parameters in the damage localization capability of the two DIs is evaluated by a parametric study with two single damage cases. Results confirm that the damage index based on lateral vibration modes has the ability to successfully detect and locate damage in suspended cables with 5% noise in modal data for a range of cable parameters. This simple approach therefore can be extended for timely damage detection in cables of suspension bridges and thereby enhance their service during their life spans.
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This cross-sectional study assessed intellect, cognition, academic function, behaviour, and emotional health of long-term survivors after childhood liver transplantation. Eligible children were >5 yr post-transplant, still attending school, and resident in Queensland. Hearing and neurocognitive testing were performed on 13 transplanted children and six siblings including two twin pairs where one was transplanted and the other not. Median age at testing was 13.08 (range 6.52-16.99) yr; time elapsed after transplant 10.89 (range 5.16-16.37) yr; and age at transplant 1.15 (range 0.38-10.00) yr. Mean full-scale IQ was 97 (81-117) for transplanted children and 105 (87-130) for siblings. No difficulties were identified in intellect, cognition, academic function, and memory and learning in transplanted children or their siblings, although both groups had reduced mathematical ability compared with normal. Transplanted patients had difficulties in executive functioning, particularly in self-regulation, planning and organization, problem-solving, and visual scanning. Thirty-one percent (4/13) of transplanted patients, and no siblings, scored in the clinical range for ADHD. Emotional difficulties were noted in transplanted patients but were not different from their siblings. Long-term liver transplant survivors exhibit difficulties in executive function and are more likely to have ADHD despite relatively intact intellect and cognition.
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Within online learning communities, receiving timely and meaningful insights into the quality of learning activities is an important part of an effective educational experience. Commonly adopted methods – such as the Community of Inquiry framework – rely on manual coding of online discussion transcripts, which is a costly and time consuming process. There are several efforts underway to enable the automated classification of online discussion messages using supervised machine learning, which would enable the real-time analysis of interactions occurring within online learning communities. This paper investigates the importance of incorporating features that utilise the structure of on-line discussions for the classification of "cognitive presence" – the central dimension of the Community of Inquiry framework focusing on the quality of students' critical thinking within online learning communities. We implemented a Conditional Random Field classification solution, which incorporates structural features that may be useful in increasing classification performance over other implementations. Our approach leads to an improvement in classification accuracy of 5.8% over current existing techniques when tested on the same dataset, with a precision and recall of 0.630 and 0.504 respectively.
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Dieting and non-dieting are two contrasting approaches to the management of overweight/obesity, but less is known about why people follow non-dieting approaches and how these approaches are associated with health and nutrition status indicators. This thesis enables a greater understanding of why dieting and non-dieting approaches are adopted and provides insight into whether one approach is more favourably associated with nutrition and health status indicators. The findings of this thesis will be useful for clinicians who wish to encourage dieting or non-dieting approaches in their clients and for researchers wishing to understand how best to address overweight and obesity.
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This study describes the results of a controlled clinical trial involving 44 7- to 14-year-old children with recurrent abdominal pain who were randomly allocated to either cognitive-behavioral family intervention (CBFI) or standard pediatric care (SPC). Both treatment conditions resulted in significant improvements on measures of pain intensity and pain behavior. However, the children receiving CBFI had a higher rate of complete elimination of pain, lower levels of relapse at 6- and 12-month follow-up, and lower levels of interference with their activities as a result of pain and parents reported a higher level of satisfaction with the treatment than children receiving SPC. After controlling for pretreatment levels of pain, children's active self-coping and mothers' caregiving strategies were significant independent predictors of pain behavior at posttreatment.
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Sleepiness remains a primary cause of road crashes, the major cause of death in young adults. Light is known to produce a direct alerting effect, but little is known about its effects on sleepy drivers. This study aimed to compare the effect of blue-green light and caffeine on young drivers’ cognitive performance after chronic-partial sleep loss.
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Pharmaceutical Care is defined as “the responsible provision of drug therapy for the purpose of achieving definite outcomes that improve a patient’s quality of life”. One of the fundamental concepts in understanding needs for pharmaceutical care are Drug-Related Problems (DRPs). As the complexity of medication treatment increases, identification of drug-related problems (DRPs) by healthcare professionals remains vital to patient safety and Quality Use of Medicines(QUM). DRPs have been used by many researchers to evaluate the QUM in different settings. DRPs present, however, a list of potential problems not a strategic framework for assessing a medication regimen.
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Doctoral training is strongly focused on honing research skills at the expense of developing teaching competency. As a result, emerging academics are unprepared for the pedagogical requirements of their early-career academic roles. Employing an action research approach, this study investigates the effectiveness of a competency-based teaching development intervention that aims to improve the teaching self-efficacy of doctoral candidates. To conduct this research, we apply the theoretical framework of Cognitive Apprenticeship Theory, a theory of social learning that requires learners to participate in a community of inquiry. Participants report significantly higher levels of teaching self-efficacy and a stronger sense of connectedness to the wider academic community.
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In recent years more and more complex humanoid robots have been developed. On the other hand programming these systems has become more difficult. There is a clear need for such robots to be able to adapt and perform certain tasks autonomously, or even learn by themselves how to act. An important issue to tackle is the closing of the sensorimotor loop. Especially when talking about humanoids the tight integration of perception with actions will allow for improved behaviours, embedding adaptation on the lower-level of the system.
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In this paper, we present the results of an exploratory study that examined the problem of automating content analysis of student online discussion transcripts. We looked at the problem of coding discussion transcripts for the levels of cognitive presence, one of the three main constructs in the Community of Inquiry (CoI) model of distance education. Using Coh-Metrix and LIWC features, together with a set of custom features developed to capture discussion context, we developed a random forest classification system that achieved 70.3% classification accuracy and 0.63 Cohen's kappa, which is significantly higher than values reported in the previous studies. Besides improvement in classification accuracy, the developed system is also less sensitive to overfitting as it uses only 205 classification features, which is around 100 times less features than in similar systems based on bag-of-words features. We also provide an overview of the classification features most indicative of the different phases of cognitive presence that gives an additional insights into the nature of cognitive presence learning cycle. Overall, our results show great potential of the proposed approach, with an added benefit of providing further characterization of the cognitive presence coding scheme.