Assessment of the LC-2 Prelaunch Fatigue Spectra of the CM-to-SM Flange Weld

The pad stay and rollout components of the Ares I-X life cycle can generate cyclic stress oscillations to the vehicle that could initiate and grow fatigue cracks from weld defects. The Ares I-X Project requested that a study be performed to determine if stabilization of the vehicle is required to reduce the stresses that could initiate and grow fatigue cracks at the flange-to-skin weld of the Command Module (CM) and Service Module (SM) interface. A fatigue crack growth analysis was conducted that used loads (LC-2) and stress analyses developed by the Ares I-X Project and utilized material data and analysis methods developed by a critical initial flaw size (CIFS) analysis conducted by NASA Engineering and Safety Center (NESC) for the Upper Stage Simulator (USS) of the Ares I-X vehicle. A full CIFS analysis for the CM-to-SM flange-to-skin weld was not performed because the full flight spectrum was not provided and was not necessary to answer the question posed by the Ares I-X Project. Instead, an approach was developed to determine if the crack growth due to the pad stay and rollout components of the flight spectrum would adversely influence the CIFS. The approach taken used a number of conservative assumptions that eliminated the need for high-fidelity analyses and additional material testing, but still provided a bounding solution for the uncertainties of the problem. The results from this analysis indicate that the LC-2 pad stay and rollout spectrum components would not produce significant fatigue crack growth on the CM-to-SM flange-to-skin weld. Thus, from a fatigue crack growth standpoint, no stabilization is required to reduce the LC-2 pad stay and rollout cyclic stresses on the CM-to-SM flange-to-skin weld

Nystagmus during an acute Ménière's attack: From prodrome to recovery

OBJECTIVE: We are currently undertaking a clinical investigation to evaluate the diagnostic capability of a system for detecting periods of pathological dizziness. This article presents an analysis of the data captured during an acute attack of Ménière's disease. DESIGN: The Continuous Ambulatory Vestibular Assessment (CAVA) device is worn by patients in the community, and continuously records eye and head movement data (vestibular telemetry). STUDY SAMPLE: A 53-year-old lady with a fifteen-year history of left-sided unilateral Ménière's disease. RESULTS: The patient wore the device nearly continuously for thirty days. The data revealed a three-hour long attack of vertigo consisting of four separate phases of nystagmus. The duration, beat-direction and slow phase velocity of the nystagmus evolved through time. The first phase contained isolated nystagmus beats which preceded the patient's record of the vertigo attack onset but coincided with anticipation of an impending vertigo attack. CONCLUSIONS: CAVA provides a unique insight into the physiological parameters present during episodes of dizziness. Here, it has provided the first full example of an acute Ménière's attack, including a period of prodrome. These findings have implications for the prediction of vertigo attack onset, for the diagnosis of Ménière's disease and other diseases resulting in dizziness

1D convolutional neural networks for detecting nystagmus

Vertigo is a type of dizziness characterised by the subjective feeling of movement despite being stationary. One in four individuals in the community experience symptoms of dizziness at any given time, and it can be challenging for clinicians to diagnose the underlying cause. When dizziness is the result of a malfunction in the inner-ear, the eyes flicker and this is called nystagmus. In this article we describe the first use of Deep Neural Network architectures applied to detecting nystagmus. The data used in these experiments was gathered during a clinical investigation of a novel medical device for recording head and eye movements. We describe methods for training networks using very limited amounts of training data, with an average of 11 mins of nystagmus across four subjects, and less than 24 hours of data in total, per subject. Our methods work by replicating and modifying existing samples to generate new data. In a cross-fold validation experiment, we achieve an average F1 score of 0.59 (SD = 0.24) across all four folds, showing that the methods employed are capable of identifying periods of nystagmus with a modest degree of accuracy. Notably, we were also able to identify periods of pathological nystagmus produced by a patient during an acute attack of Ménière's Disease, despite training the network on nystagmus that was induced by different means

An investigation into the diagnostic accuracy, reliability, acceptability and safety of a novel device for Continuous Ambulatory Vestibular Assessment (CAVA)

Dizziness is a common condition that is responsible for a significant degree of material morbidity and burden on health services. It is usually episodic and short-lived, so when a patient presents to their clinician, examination is normal. The CAVA (Continuous Ambulatory Vestibular Assessment) device has been developed to provide continuous monitoring of eye-movements, allowing insight into the physiological parameters present during a dizziness attack. This article describes the first clinical investigation into the medical and technical aspects of this new diagnostic system. Seventeen healthy subjects wore the device near continuously for up to thirty days, artificially inducing nystagmus on eight occasions. 405 days’ worth of data was captured, comprising around four billion data points. A computer algorithm developed to detect nystagmus demonstrated a sensitivity of 99.1% (95% CI: 95.13% to 99.98%) and a specificity of 98.6% (95% CI: 96.54% to 99.63%). Eighty-two percent of participants wore the device for a minimum of eighty percent of each day. Adverse events were self-limiting and mostly the consequence of skin stripping from the daily replacement of the electrodes. The device was shown to operate effectively as an ambulatory monitor, allowing the reliable detection of artificially induced nystagmus

Parameter identifiability in a class of random graph mixture models

We prove identifiability of parameters for a broad class of random graph mixture models. These models are characterized by a partition of the set of graph nodes into latent (unobservable) groups. The connectivities between nodes are independent random variables when conditioned on the groups of the nodes being connected. In the binary random graph case, in which edges are either present or absent, these models are known as stochastic blockmodels and have been widely used in the social sciences and, more recently, in biology. Their generalizations to weighted random graphs, either in parametric or non-parametric form, are also of interest in many areas. Despite a broad range of applications, the parameter identifiability issue for such models is involved, and previously has only been touched upon in the literature. We give here a thorough investigation of this problem. Our work also has consequences for parameter estimation. In particular, the estimation procedure proposed by Frank and Harary for binary affiliation models is revisited in this article

Bacterial Respiration of Arsenate and Its Significance in the Environment

Although arsenic is a trace element in terms of its natural abundance, it nonetheless has a common presence within the earth's crust. Because it is classified as a group VB element in the periodic table, it shares many chemical and biochemical properties in common with its neighbors phosphorus and nitrogen. Indeed, in the case of this element's most oxidized (+5) oxidation state, arsenate [HAsO_4^(2-) or As (V)], its toxicity is based on its action as an analog of phosphate. Hence, arsenate ions uncouple the oxidative phosphorylation normally associated with the enzyme glyceraldehyde 3-phosphate dehydrogenase, thereby preventing the formation ofphosphoglyceroyl phosphate, a key high-energy intermediate in glycolysis. To guard against this, a number of bacteria possess a detoxifying arsenate reductase pathway (the arsC system) whereby cytoplasmic enzymes remove internal pools of arsenate by achieving its reduction to arsenite [H_2AsO_3- or As (III)]. However, because the arsenite product binds with internal sulfhydryl groups that render it even more toxic than the original arsenate, efficient arsenite efflux from the cell is also required and is achieved by an active ion ''pumping'' system (1). The details of this bacterial arsenic detoxification phenomenon have been well established in the literature, and Chapter 10 in this volume provided a thorough review. Here, we discuss bacterial respiration of arsenate and its significance in the environment. As a biological phenomenon, respiratory growth on arsenate is quite remarkable, given the toxicity of the element. Moreover, the consequences of microbial arsenate respiration may, at times, have a significant impact on environmental chemistry

Method for repairing cracks in structures

A first material with a known maximum temperature of operation is coated with a second material on at least one surface of the first material. The coating has a melting temperature that is greater than the maximum temperature of operation of the first material. The coating is heated to its melting temperature until the coating flows into any cracks in the first material's surface

Replica-Based Crack Inspection

Surface replication has been proposed as a method for crack detection in space shuttle main engine flowliner slots. The results of a feasibility study show that examination of surface replicas with a scanning electron microscope can result in the detection of cracks as small as 0.005 inch, and surface flaws as small as 0.001 inch, for the flowliner material