Japanese quails (Coturnix Japonica) show keel bone damage during the laying period-a radiography study.

Keel bone damage is an important welfare issue in laying hens and can occur with a high prevalence of up to 100% of hens within one flock. Affected hens suffer from pain. Although multiple factors contribute to the prevalence and severity of keel bone damage, selection for high laying performance appears to play a key role. With up to 300 eggs/year, Japanese quails show a high laying performance, too, and, thus, may also show keel bone damage. However, to our knowledge, there are no scientific results on keel bone damage in Japanese quails to date. Therefore, the aim of this study was to assess whether keel bone fractures and deviations occur in Japanese quails and to obtain more detailed information about the development of their keel bone during the production cycle. A group of 51 female quails were radiographed at 8, 10, 15, 19, and 23 weeks of age. The X-rays were used to detect fractures and deviations and to measure the lateral surface area, length, and radiographic density of the keel bone. In addition, the length of the caudal cartilaginous part of the keel bone was measured to learn more about the progress of ossification. At 23 weeks of age, quails were euthanized and their macerated keel bones assessed for fractures and deviations. Both keel bone deviations and keel bone fractures were detected in the Japanese quails. In the 23rd week of age, 82% of the quails had a deviated keel bone as assessed after maceration. Furthermore, there was a decrease in radiographic density, lateral surface area, and length of the keel bone between weeks of age 8 and 19. This could indicate a general loss of bone substance and/or demineralization of the keel bone. Our study shows that keel bone damage is not only a problem in laying hens but also affects female Japanese quails.

Pseudo-document simulation for comparing LDA, GSDMM and GPM topic models on short and sparse text using Twitter data.

Topic models are a useful and popular method to find latent topics of documents. However, the short and sparse texts in social media micro-blogs such as Twitter are challenging for the most commonly used Latent Dirichlet Allocation (LDA) topic model. We compare the performance of the standard LDA topic model with the Gibbs Sampler Dirichlet Multinomial Model (GSDMM) and the Gamma Poisson Mixture Model (GPM), which are specifically designed for sparse data. To compare the performance of the three models, we propose the simulation of pseudo-documents as a novel evaluation method. In a case study with short and sparse text, the models are evaluated on tweets filtered by keywords relating to the Covid-19 pandemic. We find that standard coherence scores that are often used for the evaluation of topic models perform poorly as an evaluation metric. The results of our simulation-based approach suggest that the GSDMM and GPM topic models may generate better topics than the standard LDA model.