The Forest Service: A Study in Public Land Management. By Glen O. Robinson

  This report will provide an overview of climate modeling from a mathematical perspective, particularly with respect to the use of partial differential equations. A visit to the Swedish Meterological and Hydrological Institute's Rossby Center for climate research in Norrkoping, Sweden, is at the foundation of our investigations. An introduction and a brief history section will be followed by a description of the Navier-Stokes equations, which are at the heart of climate-related mathematics, as well as a survey of many of the popular approximations and modeling techniques in use by climate researchers today. Subsequently, a boundary value problem based on the one dimensional compressible Euler equations will be discussed from an analytical as well as a numerical point of view, especially with concern to the well-posedness of the same.

The Self-Employment of Immigrants and Natives in Sweden

Earlier studies on entrepreneurship and self-employment among immigrants call attention to the fact that also the "market" for self-employment or entrepreneurs consists of a supply and demand side as well as the interaction between these two. More recent research suggests that a mix of personal resources, the surrounding structural context of markets, competition and the current political and economic environment, all acting together are seen as determining factors affecting self-employment by immigrants. However, few studies have been able to quantify the importance of these different aspects that determine ethnic self-employment. The central aim of this paper is therefore, by using multilevel regression, to quantify the role the country of birth respectively labour market area plays for understanding individual differences in self-employment. Using register data on individuals for the year of 2007 for the entire Swedish population we have in this study a unique opportunity to quantify the relative importance of the self-employers embeddedness in the social and ethnic networks (country of birth) and the regional business and public regulatory framework (labour market areas) measured. Our results suggest that of the total variation in individual differences in self-employment can 14 % (men) respectively 16 % (women) be attributed to the ethnic group and the labour market area. Furthermore, the ethnical groups accounted for 70 % (men) and 78 % (women) of this higher level variance. These results show that the social and ethnical context (measured by country of birth) and the economic environment (measured by local labour market areas) played a minor role for understanding individual differences in self-employment. These results can have important implications when planning interventions or other actions focusing on self-employment. Focusing only on ethnical groups/labour market areas might be inefficient as approximately 85 % of the variation is not explained by ethnical groups/labour market areas. Instead more general approaches or interventions focusing on other groups that capture a larger part of the variation might be more efficient.immigrants, self-employment, integration, entrepreneurship, multilevel logistic regression

Predictive Modeling of Equine Activity Budgets Using a 3D Skeleton Reconstructed from Surveillance Recordings

In this work, we present a pipeline to reconstruct the 3D pose of a horse from 4 simultaneous surveillance camera recordings. Our environment poses interesting challenges to tackle, such as limited field view of the cameras and a relatively closed and small environment. The pipeline consists of training a 2D markerless pose estimation model to work on every viewpoint, then applying it to the videos and performing triangulation. We present numerical evaluation of the results (error analysis), as well as show the utility of the achieved poses in downstream tasks of selected behavioral predictions. Our analysis of the predictive model for equine behavior showed a bias towards pain-induced horses, which aligns with our understanding of how behavior varies across painful and healthy subjects.Comment: 3rd Workshop on CV4Animals: Computer Vision for Animal Behavior Tracking and Modeling (in conjunction with CVPR 2023) [POSTER

Dynamics are Important for the Recognition of Equine Pain in Video

A prerequisite to successfully alleviate pain in animals is to recognize it, which is a great challenge in non-verbal species. Furthermore, prey animals such as horses tend to hide their pain. In this study, we propose a deep recurrent two-stream architecture for the task of distinguishing pain from non-pain in videos of horses. Different models are evaluated on a unique dataset showing horses under controlled trials with moderate pain induction, which has been presented in earlier work. Sequential models are experimentally compared to single-frame models, showing the importance of the temporal dimension of the data, and are benchmarked against a veterinary expert classification of the data. We additionally perform baseline comparisons with generalized versions of state-of-the-art human pain recognition methods. While equine pain detection in machine learning is a novel field, our results surpass veterinary expert performance and outperform pain detection results reported for other larger non-human species.Comment: CVPR 2019: IEEE Conference on Computer Vision and Pattern Recognitio

Sharing Pain: Using Pain Domain Transfer for Video Recognition of Low Grade Orthopedic Pain in Horses

Orthopedic disorders are common among horses, often leading to euthanasia, which often could have been avoided with earlier detection. These conditions often create varying degrees of subtle long-term pain. It is challenging to train a visual pain recognition method with video data depicting such pain, since the resulting pain behavior also is subtle, sparsely appearing, and varying, making it challenging for even an expert human labeller to provide accurate ground-truth for the data. We show that a model trained solely on a dataset of horses with acute experimental pain (where labeling is less ambiguous) can aid recognition of the more subtle displays of orthopedic pain. Moreover, we present a human expert baseline for the problem, as well as an extensive empirical study of various domain transfer methods and of what is detected by the pain recognition method trained on clean experimental pain in the orthopedic dataset. Finally, this is accompanied with a discussion around the challenges posed by real-world animal behavior datasets and how best practices can be established for similar fine-grained action recognition tasks. Our code is available at https://github.com/sofiabroome/painface-recognition

Integration pågår

Medan unga malmöbor ofta möts över kulturgränser, träffar knappt varannan sjuttioåring någon från en annan kultur. Även om utrymmet för mångfald tycks ha sina gränser och attityderna är polariserade, får ytterligheterna allt svagare stöd