Simulating actuator energy consumption for trajectory optimisation

This work aims to construct a high-speed simulation tool which is used to quantify the dynamic actuator power consumption of an aircraft in flight, for use within trajectory optimisation packages. The purpose is to evaluate the energy penalties of the flight control actuation system as an aircraft manoeuvre along any arbitrary trajectory. The advantage is that the approximations include major transient properties which previous steady state techniques could not capture. The output can be used to provide feedback to a trajectory optimisation process to help it compute the aircraft level optimality of any given flight path. The tool features a six degree of freedom dynamic model of an aircraft which is combined with low frequency functional electro-mechanical actuator models in order to estimate the major transient power demands. The actuator models interact with the aircraft using an aerodynamic load estimator which generates load forces on the actuators that vary as a function of flight condition and control surface demands. A total energy control system is applied for longitudinal control and a total heading control system is implemented to manage the lateral motion. The outer loop is closed using a simple waypoint following guidance system with turn anticipation and variable turn radius control. To test the model, a simple trajectory analysis is undertaken which quantifies a heading change executed with four different turn rates. The tool shows that the actuation system requires 12.8 times more electrical energy when performing a 90° turn with a radius of 400 m compared to 1000 m. A second test is performed to verify the model’s ability to track a longer trajectory under windy conditions

High loading of polygenic risk for ADHD in children with comorbid aggression

Objective: Although attention deficit hyperactivity disorder (ADHD) is highly heritable, genome-wide association studies (GWAS) have not yet identified any common genetic variants that contribute to risk. There is evidence that aggression or conduct disorder in children with ADHD indexes higher genetic loading and clinical severity. The authors examine whether common genetic variants considered en masse as polygenic scores for ADHD are especially enriched in children with comorbid conduct disorder. Method: Polygenic scores derived from an ADHD GWAS meta-analysis were calculated in an independent ADHD sample (452 case subjects, 5,081 comparison subjects). Multivariate logistic regression analyses were employed to compare polygenic scores in the ADHD and comparison groups and test for higher scores in ADHD case subjects with comorbid conduct disorder relative to comparison subjects and relative to those without comorbid conduct disorder. Association with symptom scores was tested using linear regression. Results: Polygenic risk for ADD, derived from the meta-analysis, was higher in the independent ADHD group than in the comparison group. Polygenic score was significantly higher in ADHD case subjects with conduct disorder relative to ADHD case subjects without conduct disorder. ADHD polygenic score showed significant association with comorbid conduct disorder symptoms. This relationship was explained by,the aggression items. Conclusions: Common genetic variation is relevant to ADHD, especially in individuals with comorbid aggression. The findings suggest that the previously published ADHD GWAS meta-analysis contains weak but true associations with common variants, support for which falls below genome-wide significance levels. The findings also highlight the fact that aggression in ADHD indexes genetic as well as clinical severity

Value of ADC measurements for nodal staging after chemoradiation in locally advanced rectal cancer—a per lesion validation study

OBJECTIVES: To evaluate the performance of diffusion-weighted MRI (DWI) in addition to T2-weighted (T2W) MRI for nodal restaging after chemoradiation in rectal cancer. METHODS: Thirty patients underwent chemoradiation followed by MRI (1.5 T) and surgery. Imaging consisted of T2W-MRI and DWI (b0, 500, 1000). On T2W-MRI, nodes were scored as benign/malignant by two independent readers (R1, R2). Mean apparent diffusion coefficient (ADC) was measured for each node. Diagnostic performance was compared for T2W-MRI, ADC and T2W+ADC, using a per lesion histological validation. RESULTS: ADC was higher for the malignant nodes (1.43 +/- 0.38 vs 1.19 +/- 0.27 *10(-3) mm(2)/s, p < 0.001). Area under the ROC curve/sensitivity/specificity were 0.88/65%/93% (R1) and 0.95/71%/91% (R2) using T2W-MRI; 0.66/53%/82% using ADC (mean of two readers); and 0.91/56%/98% (R1) and 0.96/56%/99% (R2) using T2W+ADC. There was no significant difference between T2W-MRI and T2W+ADC. Interobserver reproducibility was good for T2W-MRI (kappa0.73) and ADC (intraclass correlation coefficient 0.77). CONCLUSIONS: After chemoradiation, ADC measurements may have potential for nodal characterisation, but DWI on its own is not reliable. Addition of DWI to T2W-MRI does not improve accuracy and T2W-MRI is already sufficiently accurate