Transient analysis using conical shell elements

The use of the NASTRAN conical shell element in static, eigenvalue, and direct transient analyses is demonstrated. The results of a NASTRAN static solution of an externally pressurized ring-stiffened cylinder agree well with a theoretical discontinuity analysis. Good agreement is also obtained between the NASTRAN direct transient response of a uniform cylinder to a dynamic end load and one-dimensional solutions obtained using a method of characteristics stress wave code and a standing wave solution. Finally, a NASTRAN eigenvalue analysis is performed on a hydroballistic model idealized with conical shell elements

Impact 2001

Index Competitive Agricultural Systems in a Global Economy ............................................................. 1 Safe and Secure Food and Fiber Systems ............................................................. 20 Healthy, Well-Nourished Population ............................................................. 28 Greater Harmony Between Agriculture and the Environment ............................................................. 38 Economic Development and Quality of Life for People and Communities ............................................................. 46 Society-Ready Graduates ............................................................. 5

Impact 2001

Index Competitive Agricultural Systems in a Global Economy ............................................................. 1 Safe and Secure Food and Fiber Systems ............................................................. 20 Healthy, Well-Nourished Population ............................................................. 28 Greater Harmony Between Agriculture and the Environment ............................................................. 38 Economic Development and Quality of Life for People and Communities ............................................................. 46 Society-Ready Graduates ............................................................. 5

Deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction: an international multicentre study

BACKGROUND: Atherosclerotic plaque quantification from coronary CT angiography (CCTA) enables accurate assessment of coronary artery disease burden and prognosis. We sought to develop and validate a deep learning system for CCTA-derived measures of plaque volume and stenosis severity. METHODS: This international, multicentre study included nine cohorts of patients undergoing CCTA at 11 sites, who were assigned into training and test sets. Data were retrospectively collected on patients with a wide range of clinical presentations of coronary artery disease who underwent CCTA between Nov 18, 2010, and Jan 25, 2019. A novel deep learning convolutional neural network was trained to segment coronary plaque in 921 patients (5045 lesions). The deep learning network was then applied to an independent test set, which included an external validation cohort of 175 patients (1081 lesions) and 50 patients (84 lesions) assessed by intravascular ultrasound within 1 month of CCTA. We evaluated the prognostic value of deep learning-based plaque measurements for fatal or non-fatal myocardial infarction (our primary outcome) in 1611 patients from the prospective SCOT-HEART trial, assessed as dichotomous variables using multivariable Cox regression analysis, with adjustment for the ASSIGN clinical risk score. FINDINGS: In the overall test set, there was excellent or good agreement, respectively, between deep learning and expert reader measurements of total plaque volume (intraclass correlation coefficient [ICC] 0·964) and percent diameter stenosis (ICC 0·879; both p<0·0001). When compared with intravascular ultrasound, there was excellent agreement for deep learning total plaque volume (ICC 0·949) and minimal luminal area (ICC 0·904). The mean per-patient deep learning plaque analysis time was 5·65 s (SD 1·87) versus 25·66 min (6·79) taken by experts. Over a median follow-up of 4·7 years (IQR 4·0–5·7), myocardial infarction occurred in 41 (2·5%) of 1611 patients from the SCOT-HEART trial. A deep learning-based total plaque volume of 238·5 mm(3) or higher was associated with an increased risk of myocardial infarction (hazard ratio [HR] 5·36, 95% CI 1·70–16·86; p=0·0042) after adjustment for the presence of deep learning-based obstructive stenosis (HR 2·49, 1·07–5·50; p=0·0089) and the ASSIGN clinical risk score (HR 1·01, 0·99–1·04; p=0·35). INTERPRETATION: Our novel, externally validated deep learning system provides rapid measurements of plaque volume and stenosis severity from CCTA that agree closely with expert readers and intravascular ultrasound, and could have prognostic value for future myocardial infarction

Cognition based bTBI mechanistic criteria; a tool for preventive and therapeutic innovations

Blast-induced traumatic brain injury has been associated with neurodegenerative and neuropsychiatric disorders. To date, although damage due to oxidative stress appears to be important, the specific mechanistic causes of such disorders remain elusive. Here, to determine the mechanical variables governing the tissue damage eventually cascading into cognitive deficits, we performed a study on the mechanics of rat brain under blast conditions. To this end, experiments were carried out to analyse and correlate post-injury oxidative stress distribution with cognitive deficits on a live rat exposed to blast. A computational model of the rat head was developed from imaging data and validated against in vivo brain displacement measurements. The blast event was reconstructed in silico to provide mechanistic thresholds that best correlate with cognitive damage at the regional neuronal tissue level, irrespectively of the shape or size of the brain tissue types. This approach was leveraged on a human head model where the prediction of cognitive deficits was shown to correlate with literature findings. The mechanistic insights from this work were finally used to propose a novel helmet design roadmap and potential avenues for therapeutic innovations against blast traumatic brain injury

An lntegrated Growth and Analysis System for In-Situ XAS Studies of Metal- Semiconductor Interactions

A UHV system for in-situ studies of metal-semiconductor interactions has been designed and assembled at North Carolina State University and recently installed and tested at the NSLS. The UHV system consists of interconnected deposition and analysis chambers, each of which is capable of maintaining a base pressure of approximately 1 x 10-10 Torr. Up to three materials can be co-deposited on 25 mm wafers by electron-beam evaporation. Substrate temperature can be controlled in the range 30-900 °C during deposition, and the growth process may be monitored with RHEED. The deposited materials and their reaction products can be studied in-situ with a variety of technique: XAFS, AES, XPS, UPS and ARXPS/UPS. We describe the capabilities of the system and present our first EXAFS results on the stabilization of Co + 2 Si films co-deposited on Si0.8Ge0.2 alloys. Preliminary results indicate that Co + 2Si forms a stable film on Si0.8Ge0.2 with a "CoSi2-like" reaction path. As is tie case with Co/Si0.8Ge0.2, silicide formation is complete at 700 °C. However, the Co+2Si/0.8Ge0.2 system does not undergo a CoSi→ CoSi2 transition when annealed at 500-700 °C, and exhibits only weak CoSi features in this.temperature range

Coherent electromagnetic field imaging through Fourier transform heterodyne

The authors present a detection process capable of directly imaging the transverse amplitude, phase, and if desired, Doppler shift of coherent electromagnetic fields. Based on coherent detection principles governing conventional heterodyned RADAR/LIDAR systems, Fourier Transform Heterodyne (FTH) incorporates transverse spatial encoding of the local oscillator for image capture. Appropriate selection of spatial encoding functions, or basis set, allows image retrieval by way of classic Fourier manipulations. Of practical interest: (1) imaging is accomplished on a single element detector requiring no additional scanning or moving components, and (2) a wide variety of appropriate spatial encoding functions exist that may be adaptively configured in real-time for applications requiring optimal detection. In this paper, they introduce the underlying principles governing FTH imaging, followed by demonstration of concept via a simple experimental setup based on a HeNe laser and a 69 element spatial phase modulator