Accident investigation: Analysis of aircraft motions from ATC radar recordings

A technique was developed for deriving time histories of an aircraft's motion from air traffic control (ATC) radar records. This technique uses the radar range and azimuth data, along with the downlinked altitude data (from an onboard Mode-C transponder), to derive an expanded set of data which includes airspeed, lift, thrust-drag, attitude angles (pitch, roll, and heading), etc. This method of analyzing aircraft motions was evaluated through flight experiments which used the CV-990 research aircraft and recordings from both the enroute and terminal ATC radar systems. The results indicate that the values derived from the ATC radar records are for the most part in good agreement with the corresponding values obtained from airborne measurements. In an actual accident, this analysis of ATC radar records can complement the flight-data recorders, now onboard airliners, and provide a source of recorded information for other types of aircraft that are equipped with Mode-C transponders but not with onboard recorders

Parameter estimation of powered-lift STOL aircraft characteristics including turbulence and ground effects

The estimation of longitudinal aerodynamic coefficients from data recorded during flight tests of a powered-lift STOL aircraft is considered. First, a comparison is made between the coefficient values determined by the regression and quasilinearization identification techniques from records taken during elevator pulse maneuvers. The results show that for these tests the regression method provides less scatter in coefficient estimates and provides better correlation with the predicted values. Special techniques are then developed which allow identification of the coefficients from records taken during landing maneuvers in which the aircraft encounters turbulence while flying in ground effect. Flight test results are presented to illustrate the effects of air turbulence and ground proximity on the estimated coefficient values

Equations for determining aircraft motions for accident data

Procedures for determining a comprehensive accident scenario from a limited data set are reported. The analysis techniques accept and process data from either an Air Traffic Control radar tracking system or a foil flight data recorder. Local meteorological information at the time of the accident and aircraft performance data are also utilized. Equations for the desired aircraft motions and forces are given in terms of elements of the measurement set and certain of their time derivatives. The principal assumption made is that aircraft side force and side-slip angle are negligible. An estimation procedure is outlined for use with each data source. For the foil case, a discussion of exploiting measurement redundancy is given. Since either formulation requires estimates of measurement time derivatives, an algorithm for least squares smoothing is provided

Analysis of severe atmospheric disturbances from airline flight records

Advanced methods were developed to determine time varying winds and turbulence from digital flight data recorders carried aboard modern airliners. Analysis of several cases involving severe clear air turbulence encounters at cruise altitudes has shown that the aircraft encountered vortex arrays generated by destabilized wind shear layers above mountains or thunderstorms. A model was developed to identify the strength, size, and spacing of vortex arrays. This model is used to study the effects of severe wind hazards on operational safety for different types of aircraft. The study demonstrates that small remotely piloted vehicles and executive aircraft exhibit more violent behavior than do large airliners during encounters with high-altitude vortices. Analysis of digital flight data from the accident at Dallas/Ft. Worth in 1985 indicates that the aircraft encountered a microburst with rapidly changing winds embedded in a strong outflow near the ground. A multiple-vortex-ring model was developed to represent the microburst wind pattern. This model can be used in flight simulators to better understand the control problems in severe microburst encounters

Flight performance of a navigation, guidance, and control system concept for automatic approach and landing of space shuttle orbiter

Unpowered automatic approaches and landings were conducted to study navigation, guidance, and control problems associated with terminal area approach and landing for the space shuttle vehicle. The flight tests were performed in a Convair 990 aircraft equipped with a digital flight control computer connected to the aircraft control system and displays. The tests were designed to evaluate the performance of a navigation and guidance concept that utilized blended radio/inertial navigation with VOR, DME, and ILS as the ground navigation aids. Results from 36 automatic approaches and landings from 11,300 m (37,000 ft) to touchdown are presented. Preliminary results indicate that this concept may provide sufficient accuracy to accomplish automatic landing of the shuttle orbiter without air-breathing engines

The ASAC Air Carrier Investment Model (Second Generation)

To meet its objective of assisting the U.S. aviation industry with the technological challenges of the future, NASA must identify research areas that have the greatest potential for improving the operation of the air transportation system. To accomplish this, NASA is building an Aviation System Analysis Capability (ASAC). The ASAC differs from previous NASA modeling efforts in that the economic behavior of buyers and sellers in the air transportation and aviation industries is central to its conception. To link the economics of flight with the technology of flight, ASAC requires a parametrically based mode with extensions that link airline operations and investments in aircraft with aircraft characteristics. This model also must provide a mechanism for incorporating air travel demand and profitability factors into the airlines' investment decisions. Finally, the model must be flexible and capable of being incorporated into a wide-ranging suite of economic and technical models that are envisioned for ASAC. We describe a second-generation Air Carrier Investment Model that meets these requirements. The enhanced model incorporates econometric results from the supply and demand curves faced by U.S.-scheduled passenger air carriers. It uses detailed information about their fleets in 1995 to make predictions about future aircraft purchases. It enables analysts with the ability to project revenue passenger-miles flown, airline industry employment, airline operating profit margins, numbers and types of aircraft in the fleet, and changes in aircraft manufacturing employment under various user-defined scenarios

Study protocol: a randomised controlled trial investigating the effect of exercise training on peripheral blood gene expression in patients with stable angina

Background: Exercise training has been shown to reduce angina and promote collateral vessel development in patients with coronary artery disease. However, the mechanism whereby exercise exerts these beneficial effects is unclear. There has been increasing interest in the use of whole genome peripheral blood gene expression in a wide range of conditions to attempt to identify both novel mechanisms of disease and transcriptional biomarkers. This protocol describes a study in which we will assess the effect of a structured exercise programme on peripheral blood gene expression in patients with stable angina, and correlate this with changes in angina level, anxiety, depression, and exercise capacity. Methods/Design: Sixty patients with stable angina will be recruited and randomised 1: 1 to exercise training or conventional care. Patients randomised to exercise training will attend an exercise physiology laboratory up to three times weekly for supervised aerobic interval training sessions of one hour in total duration. Patients will undergo assessments of angina, anxiety, depression, and peripheral blood gene expression at baseline, after six and twelve weeks of training, and twelve weeks after formal exercise training ceases. Discussion: This study will provide comprehensive data on the effect of exercise training on peripheral blood gene expression in patients with angina. By correlating this with improvement in angina status we will identify candidate peripheral blood transcriptional markers predictive of improvements in angina level in response to exercise training

Trajectories of depression and anxiety symptom severity during psychological therapy for common mental health problems

BACKGROUND: There is substantial variation in patient symptoms following psychological therapy for depression and anxiety. However, reliance on endpoint outcomes ignores additional interindividual variation during therapy. Knowing a patient's likely symptom trajectories could guide clinical decisions. We aimed to identify latent classes of patients with similar symptom trajectories over the course of psychological therapy and explore associations between baseline variables and trajectory class. METHODS: Patients received high-intensity psychological treatment for common mental health problems at National Health Service Improving Access to Psychological Therapies services in South London (N = 16 258). To identify trajectories, we performed growth mixture modelling of depression and anxiety symptoms over 11 sessions. We then ran multinomial regressions to identify baseline variables associated with trajectory class membership. RESULTS: Trajectories of depression and anxiety symptoms were highly similar and best modelled by four classes. Three classes started with moderate-severe symptoms and showed (1) no change, (2) gradual improvement, and (3) fast improvement. A final class (4) showed initially mild symptoms and minimal improvement. Within the moderate-severe baseline symptom classes, patients in the two showing improvement as opposed to no change tended not to be prescribed psychotropic medication or report a disability and were in employment. Patients showing fast improvement additionally reported lower baseline functional impairment on average. CONCLUSIONS: Multiple trajectory classes of depression and anxiety symptoms were associated with baseline characteristics. Identifying the most likely trajectory for a patient at the start of treatment could inform decisions about the suitability and continuation of therapy, ultimately improving patient outcomes

Development of a blood-based gene expression algorithm for assessment of obstructive coronary artery disease in non-diabetic patients

<p>Abstract</p> <p>Background</p> <p>Alterations in gene expression in peripheral blood cells have been shown to be sensitive to the presence and extent of coronary artery disease (CAD). A non-invasive blood test that could reliably assess obstructive CAD likelihood would have diagnostic utility.</p> <p>Results</p> <p>Microarray analysis of RNA samples from a 195 patient Duke CATHGEN registry case:control cohort yielded 2,438 genes with significant CAD association (p < 0.05), and identified the clinical/demographic factors with the largest effects on gene expression as age, sex, and diabetic status. RT-PCR analysis of 88 CAD classifier genes confirmed that diabetic status was the largest clinical factor affecting CAD associated gene expression changes. A second microarray cohort analysis limited to non-diabetics from the multi-center PREDICT study (198 patients; 99 case: control pairs matched for age and sex) evaluated gene expression, clinical, and cell population predictors of CAD and yielded 5,935 CAD genes (p < 0.05) with an intersection of 655 genes with the CATHGEN results. Biological pathway (gene ontology and literature) and statistical analyses (hierarchical clustering and logistic regression) were used in combination to select 113 genes for RT-PCR analysis including CAD classifiers, cell-type specific markers, and normalization genes.</p> <p>RT-PCR analysis of these 113 genes in a PREDICT cohort of 640 non-diabetic subject samples was used for algorithm development. Gene expression correlations identified clusters of CAD classifier genes which were reduced to meta-genes using LASSO. The final classifier for assessment of obstructive CAD was derived by Ridge Regression and contained sex-specific age functions and 6 meta-gene terms, comprising 23 genes. This algorithm showed a cross-validated estimated AUC = 0.77 (95% CI 0.73-0.81) in ROC analysis.</p> <p>Conclusions</p> <p>We have developed a whole blood classifier based on gene expression, age and sex for the assessment of obstructive CAD in non-diabetic patients from a combination of microarray and RT-PCR data derived from studies of patients clinically indicated for invasive angiography.</p> <p>Clinical trial registration information</p> <p>PREDICT, Personalized Risk Evaluation and Diagnosis in the Coronary Tree, <url>http://www.clinicaltrials.gov</url>, <a href="http://www.clinicaltrials.gov/ct2/show/NCT00500617">NCT00500617</a></p

Hyperuricaemia and the metabolic syndrome in type 2 DM

<p>Abstract</p> <p>Background</p> <p>Elevated serum uric acid levels (SUA) have been associated with an increased risk of cardiovascular diseases and the metabolic syndrome (MetS) and are often reported to be higher in females than in males. The aim of this report is to determine the prevalence and clinical correlates of hyperuricaemia and also to evaluate associations with the MetS in people with type 2 diabetes mellitus (DM).</p> <p>Methods</p> <p>This was a cross-sectional study conducted in people with type 2 DM in Lagos, Nigeria. Hyperuricaemia was defined by cut-off values of > 7 mg/dl for men and > 6 mg/dl for women. The diagnosis of MetS was made using the new definition by the American Heart Association and other related bodies. Clinical and biochemical parameters were compared between subjects with hyperuricaemia and normouricaemia. Statistical analysis included usage of Student's t test, Pearson correlation coefficients, multivariate regression analysis and chi square.</p> <p>Results</p> <p>601 patients with type 2 DM aged between 34-91 years were recruited for the study. The prevalence rates of hyperuricaemia and the MetS were 25% and 60% respectively. The frequency of occurrence of hyperuricaemia was comparable in both genders (59% vs 41%, p = 0.3). Although, the prevalence of the MetS in subjects with hyperuricaemia and normouricaemia was comparable (61 vs 56%, p = 0.1), a higher proportion of hyperuricaemic subjects had 3 or more components of the Mets compared with normouricaemic subjects. Possible predictors of hyperuricaemia include central obesity, smoking and elevated serum triglycerides (TG). SUA levels were found to be positively and significantly associated with serum TG (r = 0.2, p = 0.0001) and total cholesterol (r = 13, p = 0.001).</p> <p>Conclusion</p> <p>The prevalence of hyperuricaemia in subjects with type 2 DM is comparable in both genders and possible predictors of hyperuricaemia are potentially modifiable. SUA is positively and significantly associated with serum TG and total cholesterol.</p