Rotorcraft Flight Dynamics and Control in Wind for Autonomous Sampling of Spatiotemporal Processes

In recent years, there has been significant effort put into the design and use small, autonomous, multi-agent, aerial teams for a variety of military and commercial applications. In particular, small multi-rotor systems have been shown to be especially useful for carrying sensors as they have the ability to rapidly transit between locations as well as hover in place. This dissertation seeks to use multi-agent teams of autonomous rotorcraft to sample spatiotemporal fields in windy conditions. For many sampling objectives, there is the problem of how to accomplish the sampling objective in the presence of strong wind fields caused by external means or by other rotorcraft flying in close proximity. This dissertation develops several flight control strategies for both wind compensation, using nonlinear control techniques, and wind avoidance, using artificial potential-based control. To showcase the utility of teams of unmanned rotorcraft for spatiotemporal sampling, optimal algorithms are developed for two sampling objectives: (1) sampling continuous spatiotemporal fields modeled as Gaussian processes, and (2) optimal motion planning for coordinated target detection, which is an example of a discrete spatiotemporal field. All algorithms are tested in simulation and several are tested in a motion capture based experimental testbed

Experimental validation of the influence of white matter anisotropy on the intracranial EEG forward solution

Forward solutions with different levels of complexity are employed for localization of current generators, which are responsible for the electric and magnetic fields measured from the human brain. The influence of brain anisotropy on the forward solution is poorly understood. The goal of this study is to validate an anisotropic model for the intracranial electric forward solution by comparing with the directly measured ‘gold standard’. Dipolar sources are created at known locations in the brain and intracranial electroencephalogram (EEG) is recorded simultaneously. Isotropic models with increasing level of complexity are generated along with anisotropic models based on Diffusion tensor imaging (DTI). A Finite Element Method based forward solution is calculated and validated using the measured data. Major findings are (1) An anisotropic model with a linear scaling between the eigenvalues of the electrical conductivity tensor and water self-diffusion tensor in brain tissue is validated. The greatest improvement was obtained when the stimulation site is close to a region of high anisotropy. The model with a global anisotropic ratio of 10:1 between the eigenvalues (parallel: tangential to the fiber direction) has the worst performance of all the anisotropic models. (2) Inclusion of cerebrospinal fluid as well as brain anisotropy in the forward model is necessary for an accurate description of the electric field inside the skull. The results indicate that an anisotropic model based on the DTI can be constructed non-invasively and shows an improved performance when compared to the isotropic models for the calculation of the intracranial EEG forward solution

Transcriptional regulatory networks underlying gene expression changes in Huntington's disease

Abstract Transcriptional changes occur presymptomatically and throughout Huntington's disease (HD), motivating the study of transcriptional regulatory networks (TRNs) in HD. We reconstructed a genome‐scale model for the target genes of 718 transcription factors (TFs) in the mouse striatum by integrating a model of genomic binding sites with transcriptome profiling of striatal tissue from HD mouse models. We identified 48 differentially expressed TF‐target gene modules associated with age‐ and CAG repeat length‐dependent gene expression changes in Htt CAG knock‐in mouse striatum and replicated many of these associations in independent transcriptomic and proteomic datasets. Thirteen of 48 of these predicted TF‐target gene modules were also differentially expressed in striatal tissue from human disease. We experimentally validated a specific model prediction that SMAD3 regulates HD‐related gene expression changes using chromatin immunoprecipitation and deep sequencing (ChIP‐seq) of mouse striatum. We found CAG repeat length‐dependent changes in the genomic occupancy of SMAD3 and confirmed our model's prediction that many SMAD3 target genes are downregulated early in HD

Dynamic control of autonomous quadrotor flight in an estimated wind field

Abstract — We present a nonlinear, dynamic controller for a 6DOF quadrotor operating in an estimated, spatially varying, turbulent wind field. The quadrotor dynamics include the aerodynamic effects of drag, rotor blade flapping, and induced thrust due to translational velocity and external wind fields. To control the quadrotor we use a dynamic input/output feedback linearization controller that estimates a parametric model of the wind field using a recursive Bayesian filter. Each rotor experiences a possibly different wind field, which introduces moments that are accounted for in the controller and allows flight in wind fields that vary over the length of the vehicle. We add noise to the wind field in the form of Dryden turbulence to simulate the algorithm in two applications: autonomous ship landing and quadrotor proximity flight. I

Postprocedural Interpretation of Endoscopic Retrograde Cholangiopancreatography by Radiology

BACKGROUND: With the increase in the use of endoscopic retrograde cholangiopancreatography (ERCP) (necessitating real-time interpretation), it is unknown whether post-ERCP radiologist reporting is still necessary or helpful

Additional file 4 of Mapping age- and sex-specific HIV prevalence in adults in sub-Saharan Africa, 2000–2018

Additional file 4: Supplemental results.1. README. 2. Prevalence range across districts. 3. Prevalence range between sexes. 4. Prevalence range between ages. 5. Age-specific district ranges