A dual-processor multi-frequency implementation of the FINDS algorithm

This report presents a parallel processing implementation of the FINDS (Fault Inferring Nonlinear Detection System) algorithm on a dual processor configured target flight computer. First, a filter initialization scheme is presented which allows the no-fail filter (NFF) states to be initialized using the first iteration of the flight data. A modified failure isolation strategy, compatible with the new failure detection strategy reported earlier, is discussed and the performance of the new FDI algorithm is analyzed using flight recorded data from the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment. The results show that low level MLS, IMU, and IAS sensor failures are detected and isolated instantaneously, while accelerometer and rate gyro failures continue to take comparatively longer to detect and isolate. The parallel implementation is accomplished by partitioning the FINDS algorithm into two parts: one based on the translational dynamics and the other based on the rotational kinematics. Finally, a multi-rate implementation of the algorithm is presented yielding significantly low execution times with acceptable estimation and FDI performance

A preliminary design for flight testing the FINDS algorithm

This report presents a preliminary design for flight testing the FINDS (Fault Inferring Nonlinear Detection System) algorithm on a target flight computer. The FINDS software was ported onto the target flight computer by reducing the code size by 65%. Several modifications were made to the computational algorithms resulting in a near real-time execution speed. Finally, a new failure detection strategy was developed resulting in a significant improvement in the detection time performance. In particular, low level MLS, IMU and IAS sensor failures are detected instantaneously with the new detection strategy, while accelerometer and the rate gyro failures are detected within the minimum time allowed by the information generated in the sensor residuals based on the point mass equations of motion. All of the results have been demonstrated by using five minutes of sensor flight data for the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment

Changing World of the Commercial Real Estate Job Search Space

Successfully leveraging social media is now an essential part of any commercial real estate job seeker’s strategy. A recent study conducted by Reppler1, a social media consultancy, found that 91% of employers are now using social media to screen prospective applicants. Cornell University’s Baker Program in Real Estate and SelectLeaders have closely monitored changing trends in the real estate search space. Marc Torrey, Director of Global Sales at SelectLeaders, states that, “Where we see social media playing the biggest role in recruiting is on the screening end of the process. If I were looking for a job today I would assume that a recruiter was going to do a search and check on my online presence, what I consider to be someone’s online personal brand. Taking the time to make sure that your online personal brand conveys who you are and represents your best self should be a vital step in any job seekers process.”2 The resume may still be the single most important piece of an applicant’s arsenal in the recruiting process, but social media is beginning to render resumes obsolete. Phil Greenberg, Associate Director of Real Estate Career Services at Cornell University’s School of Hotel Administration, observes, “Now, there are dedicated boards such as SelectLeaders, which are very industry specific. The number of job postings and boards has proliferated extensively, and the ability to connect with people who have commonalities has similarly increased.”3 David Pollard of Monster.com states, “The next batch of workers to enter the workforce will shine on social media. Ultimately, it’s where they’ll pick up a tip for their next job. And so, talent management has to revamp its thinking toward one in which the resume is a piece (albeit an important one) of the puzzle.”

Design considerations for flight test of a fault inferring nonlinear detection system algorithm for avionics sensors

The modifications to the design of a fault inferring nonlinear detection system (FINDS) algorithm to accommodate flight computer constraints and the resulting impact on the algorithm performance are summarized. An overview of the flight data-driven FINDS algorithm is presented. This is followed by a brief analysis of the effects of modifications to the algorithm on program size and execution speed. Significant improvements in estimation performance for the aircraft states and normal operating sensor biases, which have resulted from improved noise design parameters and a new steady-state wind model, are documented. The aircraft state and sensor bias estimation performances of the algorithm's extended Kalman filter are presented as a function of update frequency of the piecewise constant filter gains. The results of a new detection system strategy and failure detection performance, as a function of gain update frequency, are also presented

Evaluation of a fault tolerant system for an integrated avionics sensor configuration with TSRV flight data

The performance analysis results of a fault inferring nonlinear detection system (FINDS) using sensor flight data for the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment is presented. First, a statistical analysis of the flight recorded sensor data was made in order to determine the characteristics of sensor inaccuracies. Next, modifications were made to the detection and decision functions in the FINDS algorithm in order to improve false alarm and failure detection performance under real modelling errors present in the flight data. Finally, the failure detection and false alarm performance of the FINDS algorithm were analyzed by injecting bias failures into fourteen sensor outputs over six repetitive runs of the five minute flight data. In general, the detection speed, failure level estimation, and false alarm performance showed a marked improvement over the previously reported simulation runs. In agreement with earlier results, detection speed was faster for filter measurement sensors soon as MLS than for filter input sensors such as flight control accelerometers

Healthcare Provider and Patient Knowledge, Attitudes and Practices (KAP) Regarding Zika Virus

Introduction: Zika virus emergence in the western hemisphere has prompted the critical need for tailored risk counseling. Our team created a KAP survey in order to assess provider and patient awareness of Zika virus symptoms, transmission, treatment, and current and future concerns in order to inform local risk counseling efforts. Methods: The cross-sectional survey was issued in Medical Faculty Associates (MFA) clinics and via online link to healthcare providers and community members. The REDCap Data Collection tool was used to capture responses with subsequent SAS data analysis. Results: A total of 172 responses were collected. Most respondents (97%) were aware of a link between Zika virus and microcephaly. 89% think that a vaccine is important. 52% will restrict travel to Zika endemic regions. 51% will take mosquito protective measures in the US versus 91% in Zika endemic areas. 35% of pregnant women would abstain from sex if their partners traveled to a Zika endemic area whereas 25% would if they themselves were the traveler. 37% plan to delay pregnancy and 58% are concerned about eventually having a child with microcephaly. Of the healthcare providers sampled, about one-fifth could not identify Zika infection symptoms, 16% were unaware of symptom treatment options and 5.4% did not know that Zika virus could be passed transplacentally. 34% believed DEET to be unsafe in pregnancy and 52% were unsure about permethrin safety in pregnancy. Of the 172 survey respondents, most (97%) were aware of a link between Zika virus and microcephaly. 89% think that a vaccine is important. 52% would restrict travel to Zika endemic regions. 51% would practice mosquito safety in the US versus 91% in Zika endemic countries. 35% of pregnant women would abstain from intercourse if their partners traveled to Zika endemic areas whereas 25% would if they themselves were the traveler. 37% plan to delay pregnancy and 58% worry about future children with microcephaly. Of the healthcare providers, 20% could not identify Zika infection symptoms, 16% were unaware of symptom treatment options, 5% were unaware that Zika virus passes transplacentally, and 34% believed DEET to be unsafe in pregnancy. Conclusion: The survey results provide novel insight into the KAP of patients and healthcare providers regarding Zika virus. This data will be used to optimize information distribution to our community, address large knowledge gaps in both patients and providers, and prepare medical providers to offer needed counseling

A Screening Pipeline for Antiparasitic Agents Targeting Cryptosporidium Inosine Monophosphate Dehydrogenase

Persistent diarrhea is a leading cause of illness and death among impoverished children, and a growing share of this disease burden can be attributed to the parasite Cryptosporidium. There are no vaccines to prevent Cryptosporidium infection, and the treatment options are limited and unreliable. Critically, no effective treatment exists for children or adults suffering from AIDS. Cryptosporidium presents many technical obstacles for drug discovery; perhaps the most important roadblock is the difficulty of monitoring drug action. Here we have developed a set of methods to accelerate the drug discovery process for cryptosporidiosis. We exploit the opportunities for experimental manipulation in the related parasite Toxoplasma to genetically engineer a Cryptosporidium model. This new model parasite mirrors the metabolism of Cryptosporidium for a particularly promising drug target that supplies the building blocks for DNA and RNA. Drug effectiveness can be assayed through simple fluorescence measurements for many candidates. Using this assay as an initial filter, and adapting other assays to a high throughput format, we identify several novel chemical compounds that exhibit markedly improved anti-cryptosporidial activity and excellent selectivity

Pathogenetics of alveolar capillary dysplasia with misalignment of pulmonary veins.

Alveolar capillary dysplasia with misalignment of pulmonary veins (ACDMPV) is a lethal lung developmental disorder caused by heterozygous point mutations or genomic deletion copy-number variants (CNVs) of FOXF1 or its upstream enhancer involving fetal lung-expressed long noncoding RNA genes LINC01081 and LINC01082. Using custom-designed array comparative genomic hybridization, Sanger sequencing, whole exome sequencing (WES), and bioinformatic analyses, we studied 22 new unrelated families (20 postnatal and two prenatal) with clinically diagnosed ACDMPV. We describe novel deletion CNVs at the FOXF1 locus in 13 unrelated ACDMPV patients. Together with the previously reported cases, all 31 genomic deletions in 16q24.1, pathogenic for ACDMPV, for which parental origin was determined, arose de novo with 30 of them occurring on the maternally inherited chromosome 16, strongly implicating genomic imprinting of the FOXF1 locus in human lungs. Surprisingly, we have also identified four ACDMPV families with the pathogenic variants in the FOXF1 locus that arose on paternal chromosome 16. Interestingly, a combination of the severe cardiac defects, including hypoplastic left heart, and single umbilical artery were observed only in children with deletion CNVs involving FOXF1 and its upstream enhancer. Our data demonstrate that genomic imprinting at 16q24.1 plays an important role in variable ACDMPV manifestation likely through long-range regulation of FOXF1 expression, and may be also responsible for key phenotypic features of maternal uniparental disomy 16. Moreover, in one family, WES revealed a de novo missense variant in ESRP1, potentially implicating FGF signaling in the etiology of ACDMPV