Pig as a Favorable Animal for Taenia Saginata Asiatica Infection

The epidemiology of Taenia saginata in some parts of Asia is confusing, in that beef does not appear to be the source of infection. In some areas, beef is either not available or not eaten raw, whereas pork at times is eaten uncooked. In light of this situation, we have exposed pigs and other animals to infection with strains of T. saginata to establish their ability to serve as intermediate hosts. Eggs of Taiwan Taenia, Korea Taenia, Indonesia Taenia, Thailand Taenia, Philippines Taenia, Ethiopia Taenia, and Madagascar Taenia were fed to 83 pigs of three strains: 43 Small-Ear Miniature (SEM), 34 Landrace Small-Ear Miniature (L-SEM), and 6 Duroc-Yorkshire-Landrace (DYL). We also fed the eggs to 10 Holstein calves, 17 Sannean goats, and 4 monkeys (Macaca cyclopis). We succeeded in infecting SEM (infection rate 88%, cysticercus recovery rate 19.1%), L-SEM (83%, 1.1%), and DYL (100%, 0.3%) pigs with Taiwan Taenia; SEM (100%, 1.7%), L-SEM (100%, 5.6%), and DYL (100%, 0.06%) pigs with Korea Taenia; SEM (100%, 22%) and L-SEM (100%, 1.6%) pigs with Indonesia Taenia; SEM (75%, 0.06%) pigs with Thailand Taenia SEM (100%, 11%) pigs with Philippines Taenia; SEM (80%, 0.005%) pigs with Ethiopia Taenia; SEM (100%, 0.2%) pigs with Madagascar Taenia. Holstein calves became infected with Taenia from Taiwan (100%, 1.1%), Korea (100%, 0.03%), Thailand (100%, 0.2%), and the Philippines (100%, 6%); however, the cysticerci of Taenia from Korea, Thailand, and the Philippines were degenerated and/or calcified. Sannean goats became infected with Taenia from Taiwan (33%, 0.01%) and Korea (50%, 0.02%), while monkeys became infected with Taenia from Taiwan (50%, 0.01%). However, the cysticerci were degenerated and/or calcified. Therefore, these strains of pig seem to be favorable animal models for experimental studies of T. saginata-like tapeworms, with the SEM pig the most favorable

Improving the Performance of Online Neural Transducer Models

Having a sequence-to-sequence model which can operate in an online fashion is important for streaming applications such as Voice Search. Neural transducer is a streaming sequence-to-sequence model, but has shown a significant degradation in performance compared to non-streaming models such as Listen, Attend and Spell (LAS). In this paper, we present various improvements to NT. Specifically, we look at increasing the window over which NT computes attention, mainly by looking backwards in time so the model still remains online. In addition, we explore initializing a NT model from a LAS-trained model so that it is guided with a better alignment. Finally, we explore including stronger language models such as using wordpiece models, and applying an external LM during the beam search. On a Voice Search task, we find with these improvements we can get NT to match the performance of LAS

IMAGE-BASED MEASUREMENT AND BIOMECHANICAL ANALYSIS OF THE KNEE JOINT DURING FUNCTIONAL ACTIVITIES

A new approach based on the integration of medical image-based measurement techniques, infrared stereophotogrammetry and finite element modelling (FEM) was developed for comprehensive subject-specific biomechanical analyses of the knee joint during weight-bearing functional activities including cycling. The medical image-based methods include digitally reconstructed radiograph (DRR) based 3D fluoroscopy methods, and a new slice-to-volume registration method using FLASH MRI for the real-time measurement of the 3D kinematics of the knee in vivo. With the new approach, the soft tissue artefacts associated with skin marker-based stereophotogrammetry and their effects on the calculated biomechanical variables were also investigated

Differential Harnack inequalities for nonlinear heat equations with potentials under the Ricci flow

We prove several differential Harnack inequalities for positive solutions to nonlinear backward heat equations with different potentials coupled with the Ricci flow. We also derive an interpolated Harnack inequality for the nonlinear heat equation under the $\varepsilon$-Ricci flow on a closed surface. These new Harnack inequalities extend the previous differential Harnack inequalities for linear heat equations with potentials under the Ricci flow.Comment: 17 pages. New explanations added; Final versio

Improved Noisy Student Training for Automatic Speech Recognition

Recently, a semi-supervised learning method known as "noisy student training" has been shown to improve image classification performance of deep networks significantly. Noisy student training is an iterative self-training method that leverages augmentation to improve network performance. In this work, we adapt and improve noisy student training for automatic speech recognition, employing (adaptive) SpecAugment as the augmentation method. We find effective methods to filter, balance and augment the data generated in between self-training iterations. By doing so, we are able to obtain word error rates (WERs) 4.2%/8.6% on the clean/noisy LibriSpeech test sets by only using the clean 100h subset of LibriSpeech as the supervised set and the rest (860h) as the unlabeled set. Furthermore, we are able to achieve WERs 1.7%/3.4% on the clean/noisy LibriSpeech test sets by using the unlab-60k subset of LibriLight as the unlabeled set for LibriSpeech 960h. We are thus able to improve upon the previous state-of-the-art clean/noisy test WERs achieved on LibriSpeech 100h (4.74%/12.20%) and LibriSpeech (1.9%/4.1%).Comment: 5 pages, 5 figures, 4 tables; v2: minor revisions, reference adde