Aircraft empennage structural detail design

The purpose of this project is to provide an empennage structural assembly that will withstand the operational loads defined in FAR Part 23, as well as those specified in the statement of work, i.e. snow, rain, humidity, tiedown forces, etc. The goal is to provide a simple yet durable lightweight structure that will transfer the aerodynamic forces produced by the tail surfaces through the most efficient load path to the airframe. The structure should be simple and cost-effective to manufacture and repair. All structures meet or exceed loading and fatigue criteria. The structure provides for necessary stiffness and ease of maintenance

Evaluating the association of female obesity with the risk of live birth following IVF: Implications for clinical practice

Obesity is a well-established risk factor for infertility. Consequentially, women living with obesity may require fertility treatment to support them to conceive. Due to evidence suggesting obesity is also linked with poorer outcomes following in vitro fertilisation (IVF), local commissioning guidelines on assisted conception recommend a BMI of <30kg/m² before IVF can commence. However, it is currently unclear if these guidelines are evidence based. This commentary aims to critically appraise a recent systematic review by Sermondade et al, 2019 and expand upon the implications of the findings for clinical practice

The INTERSPEECH 2017 computational paralinguistics challenge:addressee, cold &amp; snoring

Abstract The INTERSPEECH 2017 Computational Paralinguistics Challenge addresses three different problems for the first time in research competition under well-defined conditions: In the Addressee sub-challenge, it has to be determined whether speech produced by an adult is directed towards another adult or towards a child; in the Cold sub-challenge, speech under cold has to be told apart from ‘healthy’ speech; and in the Snoring sub-challenge, four different types of snoring have to be classified. In this paper, we describe these sub-challenges, their conditions, and the baseline feature extraction and classifiers, which include data-learnt feature representations by end-to-end learning with convolutional and recurrent neural networks, and bag-of-audio-words for the first time in the challenge series