279 research outputs found
Aircraft Anomaly Detection Using Performance Models Trained on Fleet Data
This paper describes an application of data mining technology called Distributed Fleet Monitoring (DFM) to Flight Operational Quality Assurance (FOQA) data collected from a fleet of commercial aircraft. DFM transforms the data into aircraft performance models, flight-to-flight trends, and individual flight anomalies by fitting a multi-level regression model to the data. The model represents aircraft flight performance and takes into account fixed effects: flight-to-flight and vehicle-to-vehicle variability. The regression parameters include aerodynamic coefficients and other aircraft performance parameters that are usually identified by aircraft manufacturers in flight tests. Using DFM, the multi-terabyte FOQA data set with half-million flights was processed in a few hours. The anomalies found include wrong values of competed variables, (e.g., aircraft weight), sensor failures and baises, failures, biases, and trends in flight actuators. These anomalies were missed by the existing airline monitoring of FOQA data exceedances
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Seasonal variability of atmospheric tides in the mesosphere and lower thermosphere: Meteor radar data and simulations
Thermal tides play an important role in the global atmospheric dynamics and provide a key mechanism for the forcing of thermosphere–ionosphere dynamics from below. A method for extracting tidal contributions, based on the adaptive filtering, is applied to analyse multi-year observations of mesospheric winds from ground-based meteor radars located in northern Germany and Norway. The observed seasonal variability of tides is compared to simulations with the Kühlungsborn Mechanistic Circulation Model (KMCM). It is demonstrated that the model provides reasonable representation of the tidal amplitudes, though substantial differences from observations are also noticed. The limitations of applying a conventionally coarse-resolution model in combination with parametrisation of gravity waves are discussed. The work is aimed towards the development of an ionospheric model driven by the dynamics of the KMCM
High-Fidelity Modeling for Health Monitoring in Honeycomb Sandwich Structures
High-Fidelity Model of the sandwich composite structure with real geometry is reported. The model includes two composite facesheets, honeycomb core, piezoelectric actuator/sensors, adhesive layers, and the impactor. The novel feature of the model is that it includes modeling of the impact and wave propagation in the structure before and after the impact. Results of modeling of the wave propagation, impact, and damage detection in sandwich honeycomb plates using piezoelectric actuator/sensor scheme are reported. The results of the simulations are compared with the experimental results. It is shown that the model is suitable for analysis of the physics of failure due to the impact and for testing structural health monitoring schemes based on guided wave propagation
Multifunctional nanoparticles for drug/gene delivery in nanomedicine
Multifunctional nanoparticles hold great promise for drug/gene delivery. Multilayered nanoparticles can act as nanomedical systems with on-board "molecular programming" to accomplish complex multi-step tasks. For example, the targeting process has only begun when the nanosystem has found the correct diseased cell of interest. Then it must pass the cell membrane and avoid enzymatic destruction within the endosomes of the cell. Since the nanosystem is only about one millionth the volume of a human cell, for it to have therapeutic efficacy with its contained package, it must deliver that drug or gene to the appropriate site within the living cell. The successive delayering of these nanosystems in a controlled fashion allows the system to accomplish operations that would be difficult or impossible to do with even complex single molecules. In addition, portions of the nanosystem may be protected from premature degradation or mistargeting to non-diseased cells. All of these problems remain major obstacles to successful drug delivery with a minimum of deleterious side effects to the patient. This paper describes some of the many components involved in the design of a general platform technology for nanomedical systems. The feasibility of most of these components has been demonstrated by our group and others. But the integration of these interacting sub-components remains a challenge. We highlight four components of this process as examples. Each subcomponent has its own sublevels of complexity. But good nanomedical systems have to be designed/engineered as a full nanomedical system, recognizing the need for the other components
Lack of association between genetic markers on chromosome 16q22-Q24 and type 1 diabetes in Russian affected families
Aim To evaluate whether the T1D susceptibility locus on chromosome 16q contributes to the genetic susceptibility to T1D in Russian patients. Method Thirteen microsatellite markers, spanning a 47-centimorgan genomic region on 16q22-q24 were evaluated for linkage to T1D in 98 Russian multiplex families. Multipoint logarithm of odds (LOD) ratio (MLS) and nonparametric LOD (NPL) values were computed for each marker, using GENEHUNTER 2.1 software. Four microsatellites (D16S422, D16S504, D16S3037, and D16S3098) and 6 biallelic markers in 2 positional candidate genes, ICSBP1 and NQO1, were additionally tested for association with T1D in 114 simplex families, using transmission disequilibrium test (TDT). Results A peak of linkage (MLS = 1.35, NPL = 0.91) was shown for marker D16S750, but this was not significant (P = 0.18). The subsequent linkage analysis in the subset of 46 multiplex families carrying a common risk HLA-DR4 haplotype increased peak MLS and NPL values to 1.77 and 1.22, respectively, but showed no significant linkage (P = 0.11) to T1D in the 16q22-q24 genomic region. TDT analysis failed to find significant association between these markers and disease, even after the conditioning for the predisposing HLA-DR4 haplotype. Conclusion Our results did not support the evidence for the susceptibility locus to T1D on chromosome 16q22-24 in the Russian family data set. The lack of association could reflect genetic heterogeneity of type 1 diabetes in diverse ethnic groups
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Electrophysiological Guidance of Epidural Electrode Array Implantation over the Human Lumbosacral Spinal Cord to Enable Motor Function after Chronic Paralysis.
Epidural electrical stimulation (EES) of the spinal cord has been shown to restore function after spinal cord injury (SCI). Characterization of EES-evoked motor responses has provided a basic understanding of spinal sensorimotor network activity related to EES-enabled motor activity of the lower extremities. However, the use of EES-evoked motor responses to guide EES system implantation over the spinal cord and their relation to post-operative EES-enabled function in humans with chronic paralysis attributed to SCI has yet to be described. Herein, we describe the surgical and intraoperative electrophysiological approach used, followed by initial EES-enabled results observed in 2 human subjects with motor complete paralysis who were enrolled in a clinical trial investigating the use of EES to enable motor functions after SCI. The 16-contact electrode array was initially positioned under fluoroscopic guidance. Then, EES-evoked motor responses were recorded from select leg muscles and displayed in real time to determine electrode array proximity to spinal cord regions associated with motor activity of the lower extremities. Acceptable array positioning was determined based on achievement of selective proximal or distal leg muscle activity, as well as bilateral muscle activation. Motor response latencies were not significantly different between intraoperative recordings and post-operative recordings, indicating that array positioning remained stable. Additionally, EES enabled intentional control of step-like activity in both subjects within the first 5 days of testing. These results suggest that the use of EES-evoked motor responses may guide intraoperative positioning of epidural electrodes to target spinal cord circuitry to enable motor functions after SCI
Depressive symptoms in spouses of older patients with severe sepsis
OBJECTIVE:
To examine whether spouses of patients with severe sepsis are at increased risk for depression independent of the spouse's presepsis history, whether this risk differs by sex, and is associated with a sepsis patient's disability after hospitalization.
DESIGN:
Prospective longitudinal cohort study.
SETTING:
Population-based cohort of U.S. adults over 50 yrs old interviewed as part of the Health and Retirement Study (1993-2008).
PATIENTS:
Nine hundred twenty-nine patient-spouse dyads comprising 1,212 hospitalizations for severe sepsis.
MEASUREMENTS AND MAIN RESULTS:
Severe sepsis was identified using a validated algorithm in Medicare claims. Depression was assessed with a modified version of the Center for Epidemiologic Studies Depression Scale. All analyses were stratified by gender. The prevalence of substantial depressive symptoms in wives of patients with severe sepsis increased by 14 percentage points at the time of severe sepsis (from 20% at a median of 1.1 yrs presepsis to 34% at a median of 1 yr postsepsis) with an odds ratio of 3.74 (95% confidence interval: 2.20, 6.37), in multivariable regression. Husbands had an 8 percentage point increase in the prevalence of substantial depressive symptoms, which was not significant in multivariable regression (odds ratio 1.90, 95% confidence interval 0.75, 4.71). The increase in depression was not explained by bereavement; women had greater odds of substantial depressive symptoms even when their spouse survived a severe sepsis hospitalization (odds ratio 2.86, 95% confidence interval 1.06, 7.73). Wives of sepsis survivors who were disabled were more likely to be depressed (odds ratio 1.35 per activities of daily living limitation of sepsis survivor, 95% confidence interval 1.12, 1.64); however, controlling for patient disability only slightly attenuated the association between sepsis and wives' depression (odds ratio 2.61, 95% confidence interval 0.93, 7.38).
CONCLUSIONS:
Older women may be at greater risk for depression if their spouse is hospitalized for severe sepsis. Spouses of patients with severe sepsis may benefit from greater support and depression screening, both when their loved one dies and when their loved one survives.NIH K08 HL091249/HL/NHLBI NIH HHS/United States
KL2 RR025015-05/RR/NCRR NIH HHS/United States
R01 AG030155/AG/NIA NIH HHS/United States
U01 AG09740/AG/NIA NIH HHS/United StatesPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93628/1/12.Davydow.CCM.Sepsis.Spouses.pd
A Toolchain Architecture for Condition Monitoring Using the Eclipse Arrowhead Framework
Condition Monitoring is one of the most critical applications of the Internet of Things (IoT) within the context of Industry 4.0. Current deployments typically present interoperability and management issues, requiring human intervention along the engineering process of the systems; in addition, the fragmentation of the IoT landscape, and the adoption of poor architectural solutions often make it difficult to integrate third-party devices in a seamless way. In this paper, we tackle these issues by proposing a tool-driven architecture that supports heterogeneous sensor management through well-established interoperability solutions for the IoT domain, i.e. the Eclipse Arrowhead framework and the recent Web of Things (WoT) standard released by the W3C working group. We deploy the architecture in a real Structural Health Monitoring (SHM) scenario, which validates each developed tool and demonstrates the increased automation derived from their combined usage
A genetic locus complements resistance to Bordetella pertussis-induced histamine sensitization.
Histamine plays pivotal role in normal physiology and dysregulated production of histamine or signaling through histamine receptors (HRH) can promote pathology. Previously, we showed that Bordetella pertussis or pertussis toxin can induce histamine sensitization in laboratory inbred mice and is genetically controlled by Hrh1/HRH1. HRH1 allotypes differ at three amino acid residues with
Inferring neutral winds in the ionospheric transition region from atmospheric-gravity-wave traveling-ionospheric-disturbance (AGW-TID) observations with the EISCAT VHF radar and the Nordic Meteor Radar Cluster
Atmospheric gravity waves and traveling ionospheric disturbances can be observed in the neutral atmosphere and the ionosphere at a wide range of spatial and temporal scales. Especially at medium scales, these oscillations are often not resolved in general circulation models and are parameterized. We show that ionospheric disturbances forced by upward-propagating atmospheric gravity waves can be simultaneously observed with the EISCAT very high frequency incoherent scatter radar and the Nordic Meteor Radar Cluster. From combined multi-static measurements, both vertical and horizontal wave parameters can be determined by applying a specially developed Fourier filter analysis method. This method is demonstrated using the example of a strongly pronounced wave mode that occurred during the EISCAT experiment on 7 July 2020. Leveraging the developed technique, we show that the wave characteristics of traveling ionospheric disturbances are notably impacted by the fall transition of the mesosphere and lower thermosphere. We also demonstrate the application of using the determined wave parameters to infer the thermospheric neutral wind velocities. Applying the dissipative anelastic gravity wave dispersion relation, we obtain vertical wind profiles in the lower thermosphere.</p
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