Effectiveness of mobile apps in teaching field-based identification skills

It has been suggested that few students graduate with the skills required for many ecological careers, as field-based learning is said to be in decline in academic institutions. Here, we asked if mobile technology could improve field-based learning, using ability to identify birds as the study metric. We divided a class of ninety-one undergraduate students into two groups for field-based sessions where they were taught bird identification skills. The first group has access to a traditional identification book and the second group were provided with an identification app. We found no difference between the groups in the ability of students to identify birds after three field sessions. Furthermore, we found that students using the traditional book were significantly more likely to identify novel species. Therefore, we find no evidence that mobile technology improved students’ ability to retain what they experienced in the field; indeed, there is evidence that traditional field guides were more useful to students as they attempted to identify new species. Nevertheless, students felt positively about using their own smartphone devices for learning, highlighting that while apps did not lead to an improvement in bird identification ability, they gave greater accessibility to relevant information outside allocated teaching times.

Conversations around homework: links to parental mental health, family characteristics and child psychological functioning

Parents are increasingly expected to supplement their children's school-based learning by providing support for children's homework. However, parents' capacities to provide such support may vary and may be limited by the experience of depression. This may have implications for child development. In the course of a prospective, longitudinal study of children of postnatally depressed and healthy mothers, we observed mothers (N = 88) and fathers (N = 78) at home during maths homework interactions with their 8-year-old children. The quality of parental communication was rated and analysed in relation to child functioning. The quality of communication of each of the parents was related to their mental state, social class and IQ. While postnatal depression was not directly related to child development, there was some evidence of the influence of maternal depression occurring in the child's school years. Different aspects of parental communication with the child showed specific associations with different child outcomes, over and above the influence of family characteristics. In particular, child school attainment and IQ were associated with parental strategies to encourage representational thinking and mastery motivation, whereas child behavioural adjustment at school and self-esteem were linked to the degree of parental emotional support and low levels of coercion. Notably, the influence of maternal homework support was more strongly related to child outcome than was paternal support, a pattern reflected in mothers' greater involvement in children's schools and school-related activities. Some parents may need guidance in how to support their children's homework if it is to be of benefit to child functioning.

Improvement of classification accuracy for stochastic discrimination - Multi-class classification

In this paper, an improved stochastic discrimination (SD) is introduced to reduce the error rate of the standard SD in the context of multi-class classification problem. The learning procedure of the improved SD consists of two stages. In the first stage, a standard SD, but with shorter learning period is carried out to identify an important space where all the misclassified samples are located. In the second stage, the standard SD is modified by (i) restricting sampling in the important space; and (ii) introducing a new discriminant function for samples in the important space. It is shown by mathematical derivation that the new discriminant function has the same mean, but smaller variance than that of standard SD for samples in the important space. It is also analyzed that the smaller the variance of the discriminant function, the lower the error rate of the classifier. Consequently, the proposed improved SD improves standard SD by its capability of achieving higher classification accuracy. Illustrative examples axe provided to demonstrate the effectiveness of the proposed improved SD.

On improvement of classification accuracy for stochastic discrimination

Stochastic discrimination (SD) depends on a discriminant function for classification. In this paper, an improved SD is introduced to reduce the error rate of the standard SD in the context of a two-class classification problem. The learning procedure of the improved SD consists of two stages. Initially a standard SD, but with shorter learning period is carried out to identify an important space where all the misclassified samples are located. Then the standard SD is modified by 1) restricting sampling in the important space, and 2) introducing a new discriminant function for samples in the important space. It is shown by mathematical derivation that the new discriminant function has the same mean, but with a smaller variance than that of the standard SD for samples in the important space. It is also analyzed that the smaller the variance of the discriminant function, the lower the error rate of the classifier. Consequently, the proposed improved SD improves standard SD by its capability of achieving higher classification accuracy. Illustrative examples are provided to demonstrate the effectiveness of the proposed improved SD.

State estimation using model order reduction for unstable systems

The problem of state estimation occurs in many applications of fluid flow. For example, to produce a reliable weather forecast it is essential to find the best possible estimate of the true state of the atmosphere. To find this best estimate a nonlinear least squares problem has to be solved subject to dynamical system constraints. Usually this is solved iteratively by an approximate Gauss–Newton method where the underlying discrete linear system is in general unstable. In this paper we propose a new method for deriving low order approximations to the problem based on a recently developed model reduction method for unstable systems. To illustrate the theoretical results, numerical experiments are performed using a two-dimensional Eady model – a simple model of baroclinic instability, which is the dominant mechanism for the growth of storms at mid-latitudes. It is a suitable test model to show the benefit that may be obtained by using model reduction techniques to approximate unstable systems within the state estimation problem.

Effects of pramipexole on the processing of rewarding and aversive taste stimuli

Rationale: Pramipexole, a D2/D3 dopamine receptor agonist, has been implicated in the development of impulse control disorders in patients with Parkinson's disease. Investigation of single doses of pramipexole in healthy participants in reward-based learning tasks has shown inhibition of the neural processing of reward, presumptively through stimulation of dopamine autoreceptors. Objectives: This study aims to examine the effects of pramipexole on the neural response to the passive receipt of rewarding and aversive sight and taste stimuli. Methods: We used functional magnetic resonance imaging to examine the neural responses to the sight and taste of pleasant (chocolate) and aversive (mouldy strawberry) stimuli in 16 healthy volunteers who received a single dose of pramipexole (0.25 mg) and placebo in a double-blind, within-subject, design. Results: Relative to placebo, pramipexole treatment reduced blood oxygen level-dependent activation to the chocolate stimuli in the areas known to play a key role in reward, including the ventromedial prefrontal cortex, the orbitofrontal cortex, striatum, thalamus and dorsal anterior cingulate cortex. Pramipexole also reduced activation to the aversive condition in the dorsal anterior cingulate cortex. There were no effects of pramipexole on the subjective ratings of the stimuli. Conclusions: Our results are consistent with an ability of acute, low-dose pramipexole to diminish dopamine-mediated responses to both rewarding and aversive taste stimuli, perhaps through an inhibitory action of D2/3 autoreceptors on phasic burst activity of midbrain dopamine neurones. The ability of pramipexole to inhibit aversive processing might potentiate its adverse behavioural effects and could also play a role in its proposed efficacy in treatment-resistant depression.

Societal transformation in response to global environmental change: a review of emerging concepts

The study of societal transformation in response to environmental change has become established, yet little consensus exists regarding the conceptual basis of transformation. This paper aims to provide structure to the dialog on transformation, and to reflect on the challenges of social research in this area. Concepts of transformation are identified through a literature review, and examined using four analytical criteria. It is found that the term ‘transformation’ is frequently used merely as a metaphor. When transformation is not used as a metaphor, eight concepts are most frequently employed. They differ with respect to (i) system conceptualization, (ii) notions of social consciousness (deliberate/emergent), and (iii) outcome (prescriptive/descriptive). Problem-based research tends to adopt concepts of deliberate transformation with prescriptive outcome, while concepts of emergent transformation with no prescriptive outcome tend to inform descriptive-analytical research. Dialog around the complementarities of different concepts and their empirical testing are priorities for future research.

Discontinuous Galerkin methods for the p-biharmonic equation from a discrete variational perspective

We study discontinuous Galerkin approximations of the p-biharmonic equation for p∈(1,∞) from a variational perspective. We propose a discrete variational formulation of the problem based on an appropriate definition of a finite element Hessian and study convergence of the method (without rates) using a semicontinuity argument. We also present numerical experiments aimed at testing the robustness of the method.

Dystrophin analysis using a panel of anti-dystrophin antibodies in Duchenne and Becker muscular dystrophy.

Dystrophin, the protein product of the Duchenne muscular dystrophy (DMD) gene, was studied in 19 patients with Xp21 disorders and in 25 individuals with non-Xp21 muscular dystrophy. Antibodies raised to seven different regions spanning most of the protein were used for immunocytochemistry. In all patients specific dystrophin staining anomalies were detected and correlated with clinical severity and also gene deletion. In patients with Becker muscular dystrophy (BMD) the anomalies detected ranged from inter- and intra-fibre variation in labelling intensity with the same antibody or several antibodies to general reduction in staining and discontinuous staining. In vitro evidence of abnormal dystrophin breakdown was observed reanalysing the muscle of patients, with BMD and not that of non-Xp21 dystrophies, after it has been stored for several months. A number of patients with DMD showed some staining but this did not represent a diagnostic problem. Based on the data presented, it was concluded that immunocytochemistry is a powerful technique in the prognostic diagnosis of Xp21 muscular dystrophies.