Safety, tolerability, pharmacodynamics and pharmacokinetics of the soluble guanylyl cyclase activator BI 685509 in patients with diabetic kidney disease:A randomized trial

Aims: Albuminuria is associated with abnormalities in the nitric oxide (NO)–soluble guanylyl cyclase (sGC)–cyclic guanosine monophosphate pathway. We assessed safety and efficacy of the NO-independent sGC activator BI 685509 in patients with diabetic kidney disease and albuminuria. Materials and methods: In this Phase Ib trial (NCT03165227), we randomized patients with type 1 or 2 diabetes, estimated glomerular filtration rate (eGFR) 20–75 mL/min/1.73 m2 and urinary albumin:creatinine ratio (UACR) 200–3500 mg/g to oral BI 685509 (1 mg three times daily, n = 20; 3 mg once daily, n = 19; 3 mg three times daily, n = 20, after final titration) or placebo (n = 15) for 28 days. Changes from baseline in UACR in first morning void (UACRFMV) and 10-hour (UACR10h) urine (3 mg once daily/three times daily only) were assessed. Results: Baseline median eGFR and UACR were 47.0 mL/min/1.73 m2 and 641.5 mg/g, respectively. Twelve patients had drug-related adverse events (AEs; 16.2%: BI 685509, n = 9; placebo, n = 3), most frequently hypotension (4.1%: BI 685509, n = 2; placebo, n = 1) and diarrhoea (2.7%: BI 685509, n = 2; placebo, n = 0). Four patients experienced AEs leading to study discontinuation (5.4%: BI 685509, n = 3; placebo, n = 1). Placebo-corrected mean UACRFMV decreased from baseline in the 3-mg once-daily (28.8%, P = 0.23) and three-times-daily groups (10.2%, P = 0.71) and increased in the 1-mg three-times-daily group (6.6%, P = 0.82); changes were not significant. UACR10h decreased by 35.3% (3 mg once daily, P = 0.34) and 56.7% (3 mg three times daily, P = 0.09); ≥50.0% of patients (UACR10h 3 mg once daily/three times daily) responded (≥20% UACR decrease from baseline). Conclusions: BI 685509 was generally well tolerated. Effects on UACR lowering merit further investigation.</p

Combined kyphoplasty and intraoperative radiotherapy (Kypho-IORT) versus external beam radiotherapy (EBRT) for painful vertebral metastases - a randomized phase III study

Background: The spine is the most frequent location of bone metastases. Local treatment aims at palliation of pain and, given the increased likelihood of long-term cancer survival, at local control. Kyphoplasty and intraoperative radiotherapy (Kypho-IORT) provided instantaneous pain relief in 70% of patients at the first day after the intervention and resulted in local control rates of &gt; 93% at 1 year in a recently conducted phase I/II trial. To assess its clinical value, we designed a phase III trial which tests Kypho-IORT against the most widespread standard-of-care, external beam radiotherapy (EBRT), in patients with painful vertebral metastases. Methods: This phase III study includes patients ≥50 years of age with up to 4 vertebral metastases and a pain score of at least 3/10 points on the visual/numeric analogy scale (VAS). Patients randomized into the experimental arm (A) will undergo Kypho-IORT (Kyphoplasty plus IORT with 8 Gy prescribed to 13 mm depth). Patients randomized into the control arm (B) will receive EBRT with either 30 Gy in 10 fractions or 8 Gy as a single dose. The primary end point is pain reduction defined as at least − 3 points on the VAS compared to baseline at day 1. Assuming that 40% of patients in the Kypho-IORT arm and 5% of patients in the control arm will achieve this reduction and 20% will drop out, a total of 54 patients will have to be included to reach a power of 0.817 with a two-sided alpha of 0.05. Secondary endpoints are evaluation of the percentage of patients with a pain reduction of at least 3 points at 2 and 6 weeks, local tumor control, frequency of re-intervention, secondary fractures/sintering, complication rates, skin toxicity/wound healing, progression-free survival (PFS), overall survival (OS) and quality of life. Discussion: This trial will generate level 1 evidence on the clinical value of a one-stop procedure which may provide instantaneous pain relief, long-term control and shortened intervals to further adjuvant (systemic) therapies in patients with spinal metastases. Trial registration Registered with ClinicalTrials.gov, number: NCT02773966. Registration date: 05/16/2016

Moving Horizon Estimation of Air Data Parameters for UAVs

Local wind velocities, angle of attack and lift coefficients of a fixed-wing unmanned aerial vehicle (UAV) are estimated by fusing kinematic, aerodynamic and stochastic wind models with data from an inertial measurement unit, a global navigation satellite system receiver and a pitot-static tube in a Moving Horizon Estimator. Experimental validation with two different UAVs and two sensor sets of different quality, show promising results for both wind velocity and angle of attack estimation

Real-Time Moving Horizon Estimation of Air Data Parameters and Wind Velocities for fixed-wing UAVs

We present a real-time implementation of an estimation algorithm for angle of attack, airspeed and wind velocities estimation on a single board computer. The estimator uses only sensor data from a standard fixed-wing UAV autopilot, which consists of a Global Navigation Satellite System receiver, an inertial measurement unit and a pitot-static tube. This sensor data is fused with a combination of kinematic, aerodynamic and stochstic wind models in a nonlinear moving horizon estimator using numerical optimization. An algorithmic differentiation toolbox and automatic code generation is used to create a realtime capable estimator which is able to run within a UAV on an on-board computer. Hardware in the Loop simulation results show that the latency of the estimator is significantly below the expected wind gust period and gives low root-mean-square estimation errors for angle of attack (0.29◦ ) , airspeed (0.21m/s) and wind velocities (0.44m/s)

Icing Detection for Small Fixed Wing UAVs using Inflight Aerodynamic Coefficient Estimation

In cold and humid environments, airfoil icing is a major hindrance to UAV operations. Airfoil icing increases the aerodynamic drag coefficient, while reducing the maximum lift coefficient and the stall angle. This results in degraded endurance and safety of an UAV. Recently de-icing solutions for fixed-wing UAVs have been developed. These solutions use resistive heating in order to melt the ice on the wings. However, since this requires a high amount of energy it is desirable to only heat the wings if significant icing occurs. In this paper, a method for automatic icing detection is presented. A moving horizon estimator (MHE) is used, which combines aerodynamic, kinematic and stochastic wind models with data from a typical autopilot sensor suite to estimate angle of attack and lift coefficients. The sensor suite consists of an inertial measurement unit (IMU), a global navigation satellite system (GNSS) receiver, a heading reference and a pitot-static tube. Within the MHE an Unscented Kalman Filter (UKF) is used for arrival cost approximation. FENSAP icing simulations show that in severe icing conditions, both the offset and the gradient of the lift coefficient change. Based on these icing simulations an UAV flight simulator that can simulate icing has been used. Simulation results show that the MHE is capable of monitoring changes in offset and gradient of the lift coefficient due to icing. A faster convergence to the estimated coefficient values could be achieved when using an external trigger signal, i.e. from a temperature and humidity sensor, to reset the covariance matrix of the arrival cost. We also investigate the effect on convergence speed resulting from an altitude change giving additional excitation. The estimation results show angle of attack estimation errors below 1 degree. These estimates can be used to limit the angle of attack and adjust the commanded airspeed in the autopilot in order to avoid stall

Combining model-free and model-based angle of attack estimation for small fixed-wing UAVs using a standard sensor suite

We propose to estimate steady and turbulent wind velocities and aerodynamic coefficients of a fixed-wing Unmanned Aerial Vehicle (UAV) by using frequency separation as well as kinematic, aerodynamic and wind models combined in an Extended Kalman Filter (EKF). With these estimates it is possible to calculate the angle of attack and the magnitude of the airspeed. Avoiding the need for prior knowledge of UAV parameters, the proposed method utilizes only sensor information that is part of a standard sensor suite, which consists of a Global Navigation Satellite System (GNSS), an Inertial Measurement Unit (IMU) and a pitot-static tube, and attitude information obtained from these sensors. An observability analysis shows that attitude changes are necessary during the initialization phase and from time to time during the flight. Simulation results indicate that, with typical sensor accuracy, the estimates are close to the reference values of the aerodynamic coefficients and wind velocities and is capable of estimating the Angle of Attack with an Root Mean Square Error (RMSE) of 0.33°, the Sideslip Angle with an RMSE of 3.21° and the airspeed with an RMSE of 0.23 m/s

Combining model-free and model-based angle of attack estimation for small fixed-wing UAVs using a standard sensor suite

We propose to estimate steady and turbulent wind velocities and aerodynamic coefficients of a fixed-wing Unmanned Aerial Vehicle (UAV) by using frequency separation as well as kinematic, aerodynamic and wind models combined in an Extended Kalman Filter (EKF). With these estimates it is possible to calculate the angle of attack and the magnitude of the airspeed. Avoiding the need for prior knowledge of UAV parameters, the proposed method utilizes only sensor information that is part of a standard sensor suite, which consists of a Global Navigation Satellite System (GNSS), an Inertial Measurement Unit (IMU) and a pitot-static tube, and attitude information obtained from these sensors. An observability analysis shows that attitude changes are necessary during the initialization phase and from time to time during the flight. Simulation results indicate that, with typical sensor accuracy, the estimates are close to the reference values of the aerodynamic coefficients and wind velocities and is capable of estimating the Angle of Attack with an Root Mean Square Error (RMSE) of 0.33°, the Sideslip Angle with an RMSE of 3.21° and the airspeed with an RMSE of 0.23 m/s

Impact of Atmospheric Icing on UAV Aerodynamic Performance

This paper presents a first assessment on the impact of atmospheric icing on the aerodynamic performance of fixed-wing UAVs. Numerical simulations were performed in order to evaluate the impact on lift and drag on a 2D airfoil for UAVs. The results show clear evidence that icing increases drag while decreasing lift and the maximum angle of attack. All these effects have negative impact on the maneuverability, stall behavior, range and general operational capabilities of UAVs. Additionally, these results were used in a flight simulator in order to allow the simulation of UAV flights in icing conditions and to study the impact of icing on energy consumption and autopilot responses. Results from the flight simulator show higher angles of attack and higher energy consumption when flying in icing conditions. This flight simulator provides a testbed for further research into in-flight ice detection for fixed-wing UAVs

Impact of atmospheric icing on UAV aerodynamic performance

This paper presents a first assessment on the impact of atmospheric icing on the aerodynamic performance of fixed-wing UAVs. Numerical simulations were performed in order to evaluate the impact on lift and drag on a 2D airfoil for UAVs. The results show clear evidence that icing increases drag while decreasing lift and the maximum angle of attack. All these effects have negative impact on the maneuverability, stall behavior, range and general operational capabilities of UAVs. Additionally, these results were used in a flight simulator in order to allow the simulation of UAV flights in icing conditions and to study the impact of icing on energy consumption and autopilot responses. Results from the flight simulator show higher angles of attack and higher energy consumption when flying in icing conditions. This flight simulator provides a testbed for further research into in-flight ice detection for fixed-wing UAVs

Propulsion System Modeling for Small Fixed Wing UAVs

This paper presents a model of an electrical propulsion system typically used for small fixed wing unmanned aerial vehicles (UAVs). Such systems consist of a power source, an electronic speed controller and a brushless DC motor which drives a propeller. The electrical, mechanical and aerodynamic subsystems are modeled separately and then combined into one system model, aiming at bridging the gap between the more complex models used in manned aviation and the simpler models typically used for UAVs. Such a model allows not only the prediction of thrust but also of the propeller speed and consumed current. This enables applications such as accurate range and endurance estimation, UAV simulation and model-based control, in-flight aerodynamic drag estimation and propeller icing detection. Wind tunnel experiments are carried out to validate the model, which is also compared to two UAV propulsion models found in the literature. The experimental results show that the model is able to predict thrust well, with a root mean square error (RMSE) of 2.20 percent of max thrust when RPM measurements are available, and an RMSE of 4.52 percent without