Development of a takeoff performance monitoring system

The development and testing of a real-time takeoff performance monitoring system is discussed. The algorithm is madeup of two segments: a pretakeoff segment and a real-time segment. One-time inputs of ambient conditions and airplane configuration information are used in the pretakeoff segment to generate schedule performance data for that takeoff. The real-time segment uses the scheduled performance data generated in the pretakeoff segment, runway length data, and measured parameters to monitor the performance of the airplane throughout the takeoff roll. Airplane and engine performance deficiencies are detected and annunciated. An important feature of this algorithm is the one-time estimation of the runway rolling friction coefficient. The algorithm was tested using a six degree of freedom airplane model in a computer simulation. Results from a series of sensitivity analysis are also included

Development of a sensitivity analysis technique for multiloop flight control systems

This report presents the development and application of a sensitivity analysis technique for multiloop flight control systems. This analysis yields very useful information on the sensitivity of the relative-stability criteria of the control system, with variations or uncertainties in the system and controller elements. The sensitivity analysis technique developed is based on the computation of the singular values and singular-value gradients of a feedback-control system. The method is applicable to single-input/single-output as well as multiloop continuous-control systems. Application to sampled-data systems is also explored. The sensitivity analysis technique was applied to a continuous yaw/roll damper stability augmentation system of a typical business jet, and the results show that the analysis is very useful in determining the system elements which have the largest effect on the relative stability of the closed-loop system. As a secondary product of the research reported here, the relative stability criteria based on the concept of singular values were explored

Three-Dimensional Crystallographic Reconstruction for Atomic Resolution

Three-dimensional structures have recently been determined by electron crystallography at a resolution high enough to determine atomic arrangements in both protein and mineral specimens. The different nature of these two types of specimens produces some very significant differences in the way data is obtained and processed, although the principles are the same. The sensitivity of proteins to damage by the electron beam limits the signal-to-noise ratio in the image and the resolution to which data can be extracted from the image. A number of constraints, such as the amino acid sequence and the connectivity of atoms within amino acids, can be used in interpreting the limited image data. In materials samples, the relative insensitivity to damage allows obtaining resolution limited only by the microscope. In many samples, dynamical scattering and other non-linear effects limit the information in the image, but this limit can be circumvented by working in very thin areas of the specimen

Cognitive therapy and spirituality: the battleground and the blend

Includes bibliographical references

Improving Palliative Care with Deep Learning

Improving the quality of end-of-life care for hospitalized patients is a priority for healthcare organizations. Studies have shown that physicians tend to over-estimate prognoses, which in combination with treatment inertia results in a mismatch between patients wishes and actual care at the end of life. We describe a method to address this problem using Deep Learning and Electronic Health Record (EHR) data, which is currently being piloted, with Institutional Review Board approval, at an academic medical center. The EHR data of admitted patients are automatically evaluated by an algorithm, which brings patients who are likely to benefit from palliative care services to the attention of the Palliative Care team. The algorithm is a Deep Neural Network trained on the EHR data from previous years, to predict all-cause 3-12 month mortality of patients as a proxy for patients that could benefit from palliative care. Our predictions enable the Palliative Care team to take a proactive approach in reaching out to such patients, rather than relying on referrals from treating physicians, or conduct time consuming chart reviews of all patients. We also present a novel interpretation technique which we use to provide explanations of the model's predictions.Comment: IEEE International Conference on Bioinformatics and Biomedicine 201

Solar cell radiation handbook

The handbook to predict the degradation of solar cell electrical performance in any given space radiation environment is presented. Solar cell theory, cell manufacturing and how they are modeled mathematically are described. The interaction of energetic charged particles radiation with solar cells is discussed and the concept of 1 MeV equivalent electron fluence is introduced. The space radiation environment is described and methods of calculating equivalent fluences for the space environment are developed. A computer program was written to perform the equivalent fluence calculations and a FORTRAN listing of the program is included. Data detailing the degradation of solar cell electrical parameters as a function of 1 MeV electron fluence are presented

Community acceptance and implementation of HIV prevention interventions for injection drug users

In 1997, the National Institutes of Health (NIH) reviewed evidence of the effectiveness of HIV prevention programs for injection drug users (IDUs) and recommended that three types ofinterventions be implemented to prevent transmission of HIV among IDUs: 1) community-based outreach, 2) expanded syringe access (including needle exchange programs [NEP] and pharmacy sales), and 3) drug treatment. Progress on increasing the acceptance and feasibility of implementing these programs has been made at the national level, but their implementation has been varied at the local level.Understanding the conditions under which communities accept and implement interventions can help guide effective strategies to foster the implementation of these interventions in areas where programs do not currently exist