Modelling the impacts of an invasive species across landscapes: a step-wise approach

We estimate the extent of ecological impacts of the invasive Asian paper wasp across different landscapes in New Zealand. We used: (i) a baseline distribution layer (modelled via MaxEnt); (ii) Asian paper wasp nest density (from >460 field plots, related to their preferences for specific land cover categories); and (iii) and their foraging intensity (rates of foraging success, and the time available to forage on a seasonal basis). Using geographic information systems this information is combined and modelled across different landscapes in New Zealand in a step-wise selection process. The highest densities of Asian paper wasps were in herbaceous saline vegetation, followed closely by built-up areas, and then scrub and shrubland. Nest densities of 34 per ha, and occupancy rates of 0.27 were recorded for herbaceous saline vegetation habitats. However, the extent of impacts of the Asian paper wasp remains relatively restricted because of narrow climate tolerances and spatial restriction of preferred habitats. A step-wise process based on geographic information systems and species distribution models, in combination with factors such as distribution, density, and predation, create a useful tool that allows the extent of impacts of invasive species to be assessed across large spatial scales. These models will be useful for conservation managers as they provide easy visual interpretation of results, and can help prioritise where direct conservation action or control of the invader are required

A novel co-locational and concurrent fNIRS/EEG measurement system: design and initial results.

We describe here the design, set-up and first time classification results of a novel co-locational functional Near- Infrared Spectroscopy/Electroencephalography (fNIRS/EEG) recording device suitable for brain computer interfacing applications using neural-hemodynamic signals. Our dual-modality system recorded both hemodynamic and electrical activity at seven sites over the motor cortex during an overt finger-tapping task. Data was collected from two subjects and classified offline using Linear Discriminant Analysis (LDA) and Leave-One-Out Cross-Validation (LOOCV). Classification of fNIRS features, EEG features and a combination of fNIRS/EEG features were performed separately. Results illustrate that classification of the combined fNIRS/EEG feature space offered average improved performance over classification of either feature space alone. The complementary nature of the physiological origin of the dual measurements offer a unique and information rich signal for a small measurement area of cortex. We feel this technology may be particularly useful in the design of BCI devices for the augmentation of neurorehabilitation therapy

Decolonial Dreamers and Dead Elephants

The 11 articles in this special themed issue examine the complexity of issues of power between individual researchers, between researchers and community organisations or higher education institutions, and between community organisations and institutions in relation to community-engaged research and scholarship. The articles uplift the pain and joy in community-engaged research, the harm and the benefits, the contradictions and tensions, and the true gifts and understanding gained in research with communities for the purpose of co-creating transformational change. We weave our own knowledge and experiences together with these individual articles as we seek ways to reimagine the future of community research and engagement. Specifically, we connect the near obliteration of African elephants and loss of Indigneous ways of knowing in Africa with the diverse communities, contexts and issues of power in community-engaged scholarship represented in this special volume. We, like the authors, hold a dream for the future of engaged scholarship that is more equitable, inclusive and morally just. We believe this dream is not only possible but achievable, as evidenced by the work of the authors in this volume. We present an African indigenous knowledge system, Ubuntu, whose principles, values and tenets simultaneously promote the conservation of the community as a whole and the harmonious existence of the individual within the community. We posit that the adaptation and adoption of this knowledge system within the scholarship and practice of community-university partnerships and community research relationships may enable the development of a mutuality and reciprocity that levels power hierarchies within the personal, organisational and societal arenas of community-university partnerships. We demonstrate that many of the cases described by contributors to this special volume resonate with this knowledge system, which itself has survived colonisation and its concomitant epistemicide. Together, the authors help paint a pathway for those who want to become decolonial dreamers (la paperson 2017) daring to reimagine the nature of power in research as we collectively find ways to dream bigger in order to uncover new and exciting possibilities for this work we call community-engaged scholarship

Invasive Impacts of the Asian Paper Wasp Across Different Landscapes

Dissertação de Mestrado em Evolução e Biologia Humanas, apresentada ao Departamento de Ciências da Vida da Faculdade de Ciências e Tecnologia da Universidade de Coimbr

Standard setting in Australian medical schools

Background: Standard setting of assessment is critical in quality assurance of medical programs. The aims of this study were to identify and compare the impact of methods used to establish the passing standard by the 13 medical schools who participated in the 2014 Australian Medical Schools Assessment Collaboration (AMSAC). Methods: A survey was conducted to identify the standard setting procedures used by participating schools. Schools standard setting data was collated for the 49 multiple choice items used for benchmarking by AMSAC in 2014. Analyses were conducted for nine schools by their method of standard setting and key characteristics of 28 panel members from four schools. Results: Substantial differences were identified between AMSAC schools that participated in the study, in both the standard setting methods and how particular techniques were implemented. The correlation between the item standard settings data by school ranged from − 0.116 to 0.632. A trend was identified for panel members to underestimate the difficulty level of hard items and overestimate the difficulty level of easy items for all methods. The median derived cut-score standard across schools was 55% for the 49 benchmarking questions. Although, no significant differences were found according to panel member standard setting experience or clinicians versus scientists, panel members with a high curriculum engagement generally had significantly lower expectations of borderline candidates (p = 0.044). Conclusion: This study used a robust assessment framework to demonstrate that several standard setting techniques are used by Australian medical schools, which in some cases use different techniques for different stages of their program. The implementation of the most common method, the Modified Angoff standard setting approach was found to vary markedly. The method of standard setting used had an impact on the distribution of expected minimally competent student performance by item and overall, with the passing standard varying by up to 10%. This difference can be attributed to the method of standard setting because the ASMSAC items have been shown over time to have consistent performance levels reflecting similar cohort ability. There is a need for more consistency in the method of standard setting used by medical schools in Australia

Using Gaussian Process Models for Near-Infrared Spectroscopy Data Interpolation

Gaussian Process (GP) model interpolation is used extensively in geostatistics. We investigated the effectiveness of using GP model interpolation to generate maps of cortical activity as measured by Near Infrared Spectroscopy (NIRS). GP model interpolation also produces a variability map, which indicates the reliability of the interpolated data. For NIRS, cortical hemodynamic activity is spatially sampled. When generating cortical activity maps, the data must be interpolated. Popular NIRS imaging software HomER uses Photon Migration Imaging (PMI) and Diffuse Optical Imaging (DOI) techniques based on models of light behaviour to generate activity maps. Very few non-parametric methods of NIRS imaging exist and none of them indicate the reliability of the interpolated data. Our GP model interpolation algorithm and HomER produced activity maps based on data generated from typical functional NIRS responses. Image results in HomER were taken as the bench mark as the images produced are commonly considered to be representative of the true underlying hemodynamic spatial response. The output from the GP approach was then compared to these on a qualitative basis. The GP model interpolation appears to produce less structured image maps of hemodynamic activity compared to those produced by HomER, however a broadly similar spatial response is compelling evidence of the utility of GP models for such applications. The additional generation of a variability map which is produced by the GP method may have some utility for functional NIRS as such information is not explicitly available from standard approaches. GP model interpolation can produce spatial activity maps from coarsely sampled NIRS data sets without any knowledge of the system being modelled. While the images produced do not appear to have the same feature resolution as photonic model-based methods the technique is worthy of further investigation due to its relative simplicity and, most intriguingly, its generation of ancillary information in the form of the variability map. This additional data may have some utility in NIRS optode design or perhaps it may have application as additional input for response classification purposes. This GP technique may also be of use where model information is inadequate for DOI techniques

Combining fNIRS and EEG to improve motor cortex activity classification during an imagined movement-based task

Included in Presentatio

Combining fNIRS and EEG to improve motor cortex activity classification during an imagined movement-based task

This work serves as an initial investigation into improvements to classification accuracy of an imagined movement-based Brain Computer Interface (BCI) by combining the feature spaces of two unique measurement modalities: functional near infrared spectroscopy (fNIRS) and electroencephalography (EEG). Our dual-modality system recorded concurrent and co-locational hemodynamic and electrical responses in the motor cortex during an imagined movement task, participated in by two subjects. Offline analysis and classification of fNIRS and EEG data was performed using leave-one-out cross-validation (LOOCV) and linear discriminant analysis (LDA). Classification of 2-dimensional fNIRS and EEG feature spaces was performed separately and then their feature spaces were combined for further classification. Results of our investigation indicate that by combining feature spaces, modest gains in classification accuracy of an imagined movement-based BCI can be achieved by employing a supplemental measurement modality. It is felt that this technique may be particularly useful in the design of BCI devices for the augmentation of rehabilitation therapy