How to Teach Entrepreneurship to Communication and Creative Industries Students

This handbook has been written as a result of work undertaken in the "CreBiz - Business Development Laboratory Study Module for Creative Industries" project. The objective of creating the study module is to enhance the business knowledge of undergraduate and graduate students of arts, humanities and media and communications, i.e. individuals, who have potential to be (self) employed after their graduation in the field of creative industries. Special focus in the study module is given to the latent entrepreneurial propensities, i.e. personal qualities and skills of the individual that would enable students to pursue an entrepreneurial career when given the opportunity or incentive to new venture creation

Affective recognition from EEG signals: an integrated data-mining approach

Emotions play an important role in human communication, interaction, and decision making processes. Therefore, considerable efforts have been made towards the automatic identification of human emotions, in particular electroencephalogram (EEG) signals and Data Mining (DM) techniques have been then used to create models recognizing the affective states of users. However, most previous works have used clinical grade EEG systems with at least 32 electrodes. These systems are expensive and cumbersome, and therefore unsuitable for usage during normal daily activities. Smaller EEG headsets such as the Emotiv are now available and can be used during daily activities. This paper investigates the accuracy and applicability of previous affective recognition methods on data collected with an Emotiv headset while participants used a personal computer to fulfill several tasks. Several features were extracted from four channels only (AF3, AF4, F3 and F4 in accordance with the 10–20 system). Both Support Vector Machine and Naïve Bayes were used for emotion classification. Results demonstrate that such methods can be used to accurately detect emotions using a small EEG headset during a normal daily activity

Validation of Noninvasive Measurements of Cardiac Output in Mice Using Echocardiography

Although multiple echocardiographic methods exist to calculate cardiac output (CO), they have not been validated in mice using a reference method. Echocardiographic and flow probe measurements of CO were obtained in mice before and after albumin infusion and inferior vena cava occlusions. Echocardiography was also performed before and after endotoxin injection. Cardiac output was calculated using LV volumes obtained from a M Mode or a 2D view, LV stroke volume calculated using the pulmonary flow, or estimated using pulmonary VTI. Close correlations were demonstrated between flow probe-measured CO and all echocardiographic measurements of CO. All echocardiographic-derived CO overestimated the flow-probe measured CO. 2D images-derived CO was associated with the smallest overestimation of CO. Interobserver variability was lowest for pulmonary VTI derived CO. In mice, CO calculated from 2D parasternal long axis images is most accurate when compared to flow probe measurements, however, pulmonary VTI-derived CO is subject to less variability

Reduced diversity and increased virulence-gene carriage in intestinal enterobacteria of coeliac children

<p>Abstract</p> <p>Background</p> <p>Coeliac disease is an immune-mediated enteropathology triggered by the ingestion of cereal gluten proteins. This disorder is associated with imbalances in the composition of the gut microbiota that could be involved in its pathogenesis. The aim of the present study was to determine whether intestinal <it>Enterobacteriaceae </it>populations of active and non-active coeliac patients and healthy children differ in diversity and virulence-gene carriage, so as to establish a possible link between the pathogenic potential of enterobacteria and the disease.</p> <p>Methods</p> <p><it>Enterobacteriaceae </it>clones were isolated on VRBD agar from faecal samples of 31 subjects (10 active coeliac patients, 10 symptom-free coeliac patients and 11 healthy controls) and identified at species level by the API 20E system. <it>Escherichia coli </it>clones were classified into four phylogenetic groups A, B1, B2 and D and the prevalence of eight virulence-associated genes (type-1 fimbriae [<it>fimA</it>], P fimbriae [<it>papC</it>], S fimbriae [<it>sfaD/E</it>], Dr haemagglutinin [<it>draA</it>], haemolysin [<it>hlyA</it>], capsule K1 [<it>neuB</it>], capsule K5 [<it>KfiC</it>] and aerobactin [<it>iutA</it>]) was determined by multiplex PCR.</p> <p>Results</p> <p>A total of 155 <it>Enterobacteriaceae </it>clones were isolated. Non-<it>E. coli </it>clones were more commonly isolated in healthy children than in coeliac patients. The four phylogenetic <it>E. coli </it>groups were equally distributed in healthy children, while in both coeliac patients most commensal isolates belonged to group A. Within the virulent groups, B2 was the most prevalent in active coeliac disease children, while D was the most prevalent in non-active coeliac patients. <it>E coli </it>clones of the virulent phylogenetic groups (B2+D) from active and non-active coeliac patients carried a higher number of virulence genes than those from healthy individuals. Prevalence of P fimbriae (<it>papC</it>), capsule K5 (<it>sfaD/E</it>) and haemolysin (<it>hlyA</it>) genes was higher in <it>E. coli </it>isolated from active and non-active coeliac children than in those from control subjects.</p> <p>Conclusion</p> <p>This study has demonstrated that virulence features of the enteric microbiota are linked to coeliac disease.</p

Testing the generality of above-ground biomass allometry across plant functional types at the continent scale

Accurate ground-based estimation of the carbon stored in terrestrial ecosystems is critical to quantifying the global carbon budget. Allometric models provide cost-effective methods for biomass prediction. But do such models vary with ecoregion or plant functional type? We compiled 15,054 measurements of individual tree or shrub biomass from across Australia to examine the generality of allometric models for prediction above-ground biomass. This provided a robust case study because Australia includes ecoregions ranging from arid shrublands to tropical rainforests, and has a rich history of biomass research, particularly in planted forests. Regardless of ecoregion, for five broad categories of plant functional type (shrubs; multi-stemmed trees; trees of the genus Eucalyptus and closely related genera; other trees of high wood density; and other trees of low wood density), relationships between biomass and stem diameter were generic. Simple power-law models explained 84-95% of the variation in biomass, with little improvement in model performance when other plant variables (height, bole wood density), or site characteristics (climate, age, management) were included. Predictions of stand-based biomass from allometric models of varying levels of generalisation (species-specific, plant functional type) were validated using whole-plot harvest data from 17 contrasting stands (range: 9 to 356 Mg ha(-1) ). Losses in efficiency of prediction were &lt; 1% if generalised models were used in place of species-specific models. Furthermore, application of generalised multi-species models did not introduce significant bias in biomass prediction in 92% of the 53 species tested. Further, overall efficiency of stand-level biomass prediction was 99%, with a mean absolute prediction error of only 13%. Hence, for cost-effective prediction of biomass across a wide range of stands, we recommend use of generic allometric models based on plant functional types. Development of new species-specific models is only warranted when gains in accuracy of stand-based predictions are relatively high (e.g. high-value monocultures). This article is protected by copyright. All rights reserved

Forest types outpaced tree species in centroid-based range shifts under global change

IntroductionMounting evidence suggests that geographic ranges of tree species worldwide are shifting under global environmental changes. Little is known, however, about if and how these species’ range shifts may trigger the range shifts of various types of forests. Markowitz’s portfolio theory of investment and its broad application in ecology suggest that the range shift of a forest type could differ substantially from the range shifts of its constituent tree species.MethodsHere, we tested this hypothesis by comparing the range shifts of forest types and the mean of their constituent species between 1970–1999 and 2000–2019 across Alaska, Canada, and the contiguous United States using continent-wide forest inventory data. We first identified forest types in each period using autoencoder neural networks and K-means cluster analysis. For each of the 43 forest types that were identified in both periods, we systematically compared historical range shifts of the forest type and the mean of its constituent tree species based on the geographic centroids of interpolated distribution maps.ResultsWe found that forest types shifted at 86.5 km·decade-1 on average, more than three times as fast as the average of constituent tree species (28.8 km·decade-1). We showed that a predominantly positive covariance of the species range and the change of species relative abundance triggers this marked difference.DiscussionOur findings provide an important scientific basis for adaptive forest management and conservation, which primarily depend on individual species assessment, in mitigating the impacts of rapid forest transformation under climate change

Dominance and rarity in tree communities across the globe: Patterns, predictors and threats

Aim: Ecological and anthropogenic factors shift the abundances of dominant and rare tree species within local forest communities, thus affecting species composition and ecosystem functioning. To inform forest and conservation management it is important to understand the drivers of dominance and rarity in local tree communities. We answer the following research questions: (1) What are the patterns of dominance and rarity in tree communities? (2) Which ecological and anthropogenic factors predict these patterns? And (3) what is the extinction risk of locally dominant and rare tree species? Location: Global. Time period: 1990–2017. Major taxa studied: Trees. Methods: We used 1.2 million forest plots and quantified local tree dominance as the relative plot basal area of the single most dominant species and local rarity as the percentage of species that contribute together to the least 10% of plot basal area. We mapped global community dominance and rarity using machine learning models and evaluated the ecological and anthropogenic predictors with linear models. Extinction risk, for example threatened status, of geographically widespread dominant and rare species was evaluated. Results: Community dominance and rarity show contrasting latitudinal trends, with boreal forests having high levels of dominance and tropical forests having high levels of rarity. Increasing annual precipitation reduces community dominance, probably because precipitation is related to an increase in tree density and richness. Additionally, stand age is positively related to community dominance, due to stem diameter increase of the most dominant species. Surprisingly, we find that locally dominant and rare species, which are geographically widespread in our data, have an equally high rate of elevated extinction due to declining populations through large‐scale land degradation. Main conclusions: By linking patterns and predictors of community dominance and rarity to extinction risk, our results suggest that also widespread species should be considered in large‐scale management and conservation practices

Positive biodiversity-productivity relationship predominant in global forests

The biodiversity-productivity relationship (BPR) is foundational to our understanding of the global extinction crisis and its impacts on ecosystem functioning. Understanding BPR is critical for the accurate valuation and effective conservation of biodiversity. Using ground-sourced data from 777,126 permanent plots, spanning 44 countries and most terrestrial biomes, we reveal a globally consistent positive concave-down BPR, showing that continued biodiversity loss would result in an accelerating decline in forest productivity worldwide. The value of biodiversity in maintaining commercial forest productivity alone - US$166 billion to 490 billion per year according to our estimation - is more than twice what it would cost to implement effective global conservation. This highlights the need for a worldwide reassessment of biodiversity values, forest management strategies, and conservation priorities.Peer Reviewe