Evaluation of coughing and nasal discharge as early indicators for an increased risk to develop equine recurrent airway obstruction (RAO).

BACKGROUND It is often assumed that horses with mild respiratory clinical signs, such as mucous nasal discharge and occasional coughing, have an increased risk of developing recurrent airway obstruction (RAO). HYPOTHESIS Compared to horses without any clinical signs of respiratory disease, those with occasional coughing, mucous nasal discharge, or both have an increased risk of developing signs of RAO (frequent coughing, increased breathing effort, exercise intolerance, or a combination of these) as characterized by the Horse Owner Assessed Respiratory Signs Index (HOARSI 1-4). ANIMALS Two half-sibling families descending from 2 RAO-affected stallions (n = 65 and n = 47) and an independent replication population of unrelated horses (n = 88). METHODS In a retrospective cohort study, standardized information on occurrence and frequency of coughing, mucous nasal discharge, poor performance, and abnormal breathing effort-and these factors combined in the HOARSI-as well as management factors were collected at intervals of 1.3-5 years. RESULTS Compared to horses without clinical signs of respiratory disease (half-siblings 7%; unrelated horses 3%), those with mild respiratory signs developed clinical signs of RAO more frequently: half-siblings with mucous nasal discharge 35% (P < .001, OR: 7.0, sensitivity: 62%, specificity: 81%), with mucous nasal discharge and occasional coughing 43% (P < .001, OR: 9.9, sensitivity: 55%, specificity: 89%); unrelated horses with occasional coughing: 25% (P = .006, OR = 9.7, sensitivity: 75%, specificity: 76%). CONCLUSIONS AND CLINICAL IMPORTANCE Occasional coughing and mucous nasal discharge might represent an increased risk of developing RAO.

A systematized workflow for assessing land resources using readily available spatial datasets

Land degradation as well as land conservation maps at a (sub-) national scale are critical for pro-ject planning for sustainable land management. It has long been recognized that online accessible and low-cost raster data sets (e.g. Landsat imagery, SRTM-DEM’s) provide a readily available basis for land resource assessments for developing countries. However, choice of spatial, tempo-ral and spectral resolution of such data is often limited. Furthermore, while local expert knowl-edge on land degradation processes is abundant, difficulties are often encountered when linking existing knowledge with modern approaches including GIS and RS. The aim of this study was to develop an easily applicable, standardized workflow for preliminary spatial assessments of land degradation and conservation, which also allows the integration of existing expert knowledge. The core of the developed method consists of a workflow for rule-based land resource assess-ment. In a systematic way, this workflow leads from predefined land degradation and conserva-tion classes to field indicators, to suitable spatial proxy data, and finally to a set of rules for clas-sification of spatial datasets. Pre-conditions are used to narrow the area of interest. Decision tree models are used for integrating the different rules. It can be concluded that the workflow presented assists experts from different disciplines in col-laboration GIS/RS specialists in establishing a preliminary model for assessing land degradation and conservation in a spatially explicit manner. The workflow provides support when linking field indicators and spatial datasets, and when determining field indicators for groundtruthing.

Founder, Academic, or Employee? A Nuanced Study of Career Choice Intentions

We add novel insights to the debate about why individuals choose to start their own firm by comparing entrepreneurial intentions to the intentions to work at a university as an academic and to be employed in a private firm. To model this more complex set of career choices, we examine novel multiplicative aspects of the theory of planned behavior (TPB) and test our hypotheses on survey data of 15,866 students from 13 European countries. Multinomial logistic regression analyses reveal how the different TPB elements influence career preferences and demonstrate the moderating effects of perceived controllability and desirability.