Auto-tuning for high performance autopilot design

A novel auto-tuning method for the RIDE controller algorithm is presented. The RIDE controller is applied to a high performance aircraft model. The tuner utilises a constrained genetic algorithm to automate the tuning process. The results of the tuner are compared with that of another tuning method which utilises unconstrained optimisation so as to highlight the efficacy of constrained optimisation for this application. It is shown from the results that the constrained genetic algorithm optimisation scheme offers a highly effective tuning solution which can be used to attain safe and high performance control with the RIDE control algorithm

Motion-Compensation Techniques in Neonatal and Fetal MR Imaging

Fetal and neonatal MR imaging is increasingly used as a complementary diagnostic tool to sonography. MR imaging is an ideal technique for imaging fetuses and neonates because of the absence of ionizing radiation, the superior contrast of soft tissues compared with sonography, the availability of different contrast options, and the increased FOV. Motion in the normally mobile fetus and the unsettled, sleeping, or sedated neonate during a long acquisition will decrease image quality in the form of motion artifacts, hamper image interpretation, and often necessitate a repeat MR imaging to establish a diagnosis. This article reviews current techniques of motion compensation in fetal and neonatal MR imaging, including the following: 1) motion-prevention strategies (such as adequate patient preparation, patient coaching, and sedation, when required), 2) motion-artifacts minimization methods (such as fast imaging protocols, data undersampling, and motion-resistant sequences), and 3) motion-detection/correction schemes (such as navigators and self-navigated sequences, external motion-tracking devices, and postprocessing approaches) and their application in fetal and neonatal brain MR imaging. Additionally some background on the repertoire of motion of the fetal and neonatal patient and the resulting artifacts will be presented, as well as insights into future developments and emerging techniques of motion compensation

Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET

The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR

Relationship of edge localized mode burst times with divertor flux loop signal phase in JET

A phase relationship is identified between sequential edge localized modes (ELMs) occurrence times in a set of H-mode tokamak plasmas to the voltage measured in full flux azimuthal loops in the divertor region. We focus on plasmas in the Joint European Torus where a steady H-mode is sustained over several seconds, during which ELMs are observed in the Be II emission at the divertor. The ELMs analysed arise from intrinsic ELMing, in that there is no deliberate intent to control the ELMing process by external means. We use ELM timings derived from the Be II signal to perform direct time domain analysis of the full flux loop VLD2 and VLD3 signals, which provide a high cadence global measurement proportional to the voltage induced by changes in poloidal magnetic flux. Specifically, we examine how the time interval between pairs of successive ELMs is linked to the time-evolving phase of the full flux loop signals. Each ELM produces a clear early pulse in the full flux loop signals, whose peak time is used to condition our analysis. The arrival time of the following ELM, relative to this pulse, is found to fall into one of two categories: (i) prompt ELMs, which are directly paced by the initial response seen in the flux loop signals; and (ii) all other ELMs, which occur after the initial response of the full flux loop signals has decayed in amplitude. The times at which ELMs in category (ii) occur, relative to the first ELM of the pair, are clustered at times when the instantaneous phase of the full flux loop signal is close to its value at the time of the first ELM

Discovery and functional prioritization of Parkinson's disease candidate genes from large-scale whole exome sequencing.

BACKGROUND: Whole-exome sequencing (WES) has been successful in identifying genes that cause familial Parkinson's disease (PD). However, until now this approach has not been deployed to study large cohorts of unrelated participants. To discover rare PD susceptibility variants, we performed WES in 1148 unrelated cases and 503 control participants. Candidate genes were subsequently validated for functions relevant to PD based on parallel RNA-interference (RNAi) screens in human cell culture and Drosophila and C. elegans models. RESULTS: Assuming autosomal recessive inheritance, we identify 27 genes that have homozygous or compound heterozygous loss-of-function variants in PD cases. Definitive replication and confirmation of these findings were hindered by potential heterogeneity and by the rarity of the implicated alleles. We therefore looked for potential genetic interactions with established PD mechanisms. Following RNAi-mediated knockdown, 15 of the genes modulated mitochondrial dynamics in human neuronal cultures and four candidates enhanced α-synuclein-induced neurodegeneration in Drosophila. Based on complementary analyses in independent human datasets, five functionally validated genes-GPATCH2L, UHRF1BP1L, PTPRH, ARSB, and VPS13C-also showed evidence consistent with genetic replication. CONCLUSIONS: By integrating human genetic and functional evidence, we identify several PD susceptibility gene candidates for further investigation. Our approach highlights a powerful experimental strategy with broad applicability for future studies of disorders with complex genetic etiologies

Powering of Devices

Patent for a method of powering devices

Perinatal cortical growth and childhood neurocognitive abilities

Objective: This observational cohort study addressed the hypothesis that after preterm delivery brain growth between 24 and 44 weeks postmenstrual age (PMA) is related to global neurocognitive ability in later childhood. Methods: Growth rates for cerebral volume and cortical surface area were estimated in 82 infants without focal brain lesions born before 30 weeks PMA by using 217 magnetic resonance images obtained between 24 and 44 weeks PMA. Abilities were assessed at 2 years using the Griffiths Mental Development Scale and at 6 years using the Wechsler Preschool and Primary Scale of Intelligence–Revised (WPPSI-R), the Developmental Neuropsychological Assessment (NEPSY), and the Movement Assessment Battery for Children (MABC). Analysis was by generalized least-squares regression. Results: Mean test scores approximated population averages. Cortical growth was directly related to the Griffiths Developmental Quotient (DQ), the WPPSI-R full-scale IQ, and a NEPSY summary score but not the MABC score and in exploration of subtests to attention, planning, memory, language, and numeric and conceptual abilities but not motor skills. The mean (95% confidence interval) estimated reduction in cortical surface area at term corrected age associated with a 1 SD fall in test score was as follows: DQ 7.0 (5.8–8.5); IQ 6.0 (4.9–7.3); and NEPSY 9.1 (7.5–11.0) % · SD−1. Total brain volume growth was not correlated with any test score. Conclusions: The rate of cerebral cortical growth between 24 and 44 weeks PMA predicts global ability in later childhood, particularly complex cognitive functions but not motor functions. During late fetal life, brain growth is rapid, particularly in the cerebral cortex. In infants born preterm, the reduced growth of the cortical surface area relative to total brain volume correlates with lower postmenstrual age (PMA) at birth and a lower Griffiths Developmental Quotient (DQ) at 2 years of age.1 Preterm birth also leads to local changes in brain volume2 and perhaps to a reduction in total brain volume, although this is controversial.3,4 These data raised the hypothesis that brain growth in the perinatal period, particularly of the cerebral cortex, predicts later neurocognitive function in infants born preterm. To address this, we examined childhood abilities in a cohort of infants in whom growth of the cortical surface area and cerebral volume between 24 and 44 weeks PMA had been measured