Visual Servoing Approach to Autonomous UAV Landing on a Moving Vehicle.

Many aerial robotic applications require the ability to land on moving platforms, such as delivery trucks and marine research boats. We present a method to autonomously land an Unmanned Aerial Vehicle on a moving vehicle. A visual servoing controller approaches the ground vehicle using velocity commands calculated directly in image space. The control laws generate velocity commands in all three dimensions, eliminating the need for a separate height controller. The method has shown the ability to approach and land on the moving deck in simulation, indoor and outdoor environments, and compared to the other available methods, it has provided the fastest landing approach. Unlike many existing methods for landing on fast-moving platforms, this method does not rely on additional external setups, such as RTK, motion capture system, ground station, offboard processing, or communication with the vehicle, and it requires only the minimal set of hardware and localization sensors. The videos and source codes are also provided.

Drone flight data reveal energy and greenhouse gas emissions savings for very small package delivery.

Uncrewed aerial vehicles (UAVs) for last-mile deliveries will affect the energy productivity of delivery and require new methods to understand energy consumption and greenhouse gas (GHG) emissions. We combine empirical testing of 188 quadcopter flights across a range of speeds with a first-principles analysis to develop a usable energy model and a machine-learning algorithm to assess energy across takeoff, cruise, and landing. Our model shows that an electric quadcopter drone with a very small package (0.5 kg) would consume approximately 0.08 MJ/km and result in 70 g of CO2e per package in the United States. We compare drone delivery with other vehicles and show that energy per package delivered by drones (0.33 MJ/package) can be up to 94% lower than conventional transportation modes, with only electric cargo bicycles providing lower GHGs/package. Our open model and coefficients can assist stakeholders in understanding and improving the sustainability of small package delivery.

RGB-D SLAM in Dynamic Environments Using Point Correlations.

In this paper, a simultaneous localization and mapping (SLAM) method that eliminates the influence of moving objects in dynamic environments is proposed. This method utilizes the correlation between map points to separate points that are part of the static scene and points that are part of different moving objects into different groups. A sparse graph is first created using Delaunay triangulation from all map points. In this graph, the vertices represent map points, and each edge represents the correlation between adjacent points. If the relative position between two points remains consistent over time, there is correlation between them, and they are considered to be moving together rigidly. If not, they are considered to have no correlation and to be in separate groups. After the edges between the uncorrelated points are removed during point-correlation optimization, the remaining graph separates the map points of the moving objects from the map points of the static scene. The largest group is assumed to be the group of reliable static map points. Finally, motion estimation is performed using only these points. The proposed method was implemented for RGB-D sensors, evaluated with a public RGB-D benchmark, and tested in several additional challenging environments. The experimental results demonstrate that robust and accurate performance can be achieved by the proposed SLAM method in both slightly and highly dynamic environments. Compared with other state-of-the-art methods, the proposed method can provide competitive accuracy with good real-time performance.

In-flight positional and energy use data set of a DJI Matrice 100 quadcopter for small package delivery.

We autonomously directed a small quadcopter package delivery Uncrewed Aerial Vehicle (UAV) or "drone" to take off, fly a specified route, and land for a total of 209 flights while varying a set of operational parameters. The vehicle was equipped with onboard sensors, including GPS, IMU, voltage and current sensors, and an ultrasonic anemometer, to collect high-resolution data on the inertial states, wind speed, and power consumption. Operational parameters, such as commanded ground speed, payload, and cruise altitude, were varied for each flight. This large data set has a total flight time of 10 hours and 45 minutes and was collected from April to October of 2019 covering a total distance of approximately 65 kilometers. The data collected were validated by comparing flights with similar operational parameters. We believe these data will be of great interest to the research and industrial communities, who can use the data to improve UAV designs, safety, and energy efficiency, as well as advance the physical understanding of in-flight operations for package delivery drones.

Androgens and Anti-Müllerian Hormone in Infertile Patients.

To investigate whether there is an association between androgens and ovarian reserve, expressed through anti-Mullerian hormone. This is a retrospective cross-sectional analysis of all consecutive women attending a tertiary fertility center, who presented with regular menstrual cycles. Patients had their AMH values measured with the same AMH assay (Immunotech (IOT) Beckmann Coulter assay), the same day in which androgens sampling was performed. Women with PCOS or other forms of androgen excess or untreated endocrine or metabolic disorders were excluded. A total of 942 women were included. Significant correlation was observed between total testosterone/free androgens index (FAI)/DHEAS and AMH (Spearman's r = 0.20/0.14/0.13, P value < 0.001, P value < 0.001, and P value < 0.001, respectively). After multiple linear regression analysis adjusting for confounders (age, BMI, cause of infertility, day of the menstrual cycle when the blood sample was performed), the regression slope in all participants for total testosterone predicting logAMH was 0.20 (P value < 0.001). Similarly, FAI was significantly associated with logAMH (regression coefficient = 0.04, P value = 0.04). In contrast, DHEAS was not significantly associated with logAMH. There was a significant, but weak relation between testosterone and AMH, while no significant association was observed between DHEAS and AMH. Future research is needed to elucidate whether testosterone supplementation may have any effect on ovarian function.

Feasibility of Discriminating UAV Propellers Noise from Distress Signals to Locate People in Enclosed Environments Using MEMS Microphone Arrays.

Detecting and finding people are complex tasks when visibility is reduced. This happens, for example, if a fire occurs. In these situations, heat sources and large amounts of smoke are generated. Under these circumstances, locating survivors using thermal or conventional cameras is not possible and it is necessary to use alternative techniques. The challenge of this work was to analyze if it is feasible the integration of an acoustic camera, developed at the University of Valladolid, on an unmanned aerial vehicle (UAV) to locate, by sound, people who are calling for help, in enclosed environments with reduced visibility. The acoustic array, based on MEMS (micro-electro-mechanical system) microphones, locates acoustic sources in space, and the UAV navigates autonomously by closed enclosures. This paper presents the first experimental results locating the angles of arrival of multiple sound sources, including the cries for help of a person, in an enclosed environment. The results are promising, as the system proves able to discriminate the noise generated by the propellers of the UAV, at the same time it identifies the angles of arrival of the direct sound signal and its first echoes reflected on the reflective surfaces.

Cryo-EM structures of the pore-forming A subunit from the Yersinia entomophaga ABC toxin.

ABC toxins are pore-forming virulence factors produced by pathogenic bacteria. YenTcA is the pore-forming and membrane binding A subunit of the ABC toxin YenTc, produced by the insect pathogen Yersinia entomophaga. Here we present cryo-EM structures of YenTcA, purified from the native source. The soluble pre-pore structure, determined at an average resolution of 4.4 Å, reveals a pentameric assembly that in contrast to other characterised ABC toxins is formed by two TcA-like proteins (YenA1 and YenA2) and decorated by two endochitinases (Chi1 and Chi2). We also identify conformational changes that accompany membrane pore formation by visualising YenTcA inserted into liposomes. A clear outward rotation of the Chi1 subunits allows for access of the protruding translocation pore to the membrane. Our results highlight structural and functional diversity within the ABC toxin subfamily, explaining how different ABC toxins are capable of recognising diverse hosts.

Image processing techniques for high-resolution structure determination from badly ordered 2D crystals.

2D electron crystallography can be used to study small membrane proteins in their native environment. Obtaining highly ordered 2D crystals is difficult and time-consuming. However, 2D crystals diffracting to only 10-12 Šcan be prepared relatively conveniently in most cases. We have developed image-processing algorithms allowing to generate a high resolution 3D structure from cryo-electron crystallography images of badly ordered crystals. These include movie-mode unbending, refinement over sub-tiles of the images in order to locally refine the sample tilt geometry, implementation of different CTF correction schemes, and an iterative method to apply known constraints in the real and reciprocal space to approximate amplitudes and phases in the so-called missing cone regions. These algorithms applied to a dataset of the potassium channel MloK1 show significant resolution improvements to better than 5 Å.

High-Resolution Cryoelectron Microscopy Structure of the Cyclic Nucleotide-Modulated Potassium Channel MloK1 in a Lipid Bilayer.

Eukaryotic cyclic nucleotide-modulated channels perform their diverse physiological roles by opening and closing their pores to ions in response to cyclic nucleotide binding. We here present a structural model for the cyclic nucleotide-modulated potassium channel homolog from Mesorhizobium loti, MloK1, determined from 2D crystals in the presence of lipids. Even though crystals diffract electrons to only ∼10 Å, using cryoelectron microscopy (cryo-EM) and recently developed computational methods, we have determined a 3D map of full-length MloK1 in the presence of cyclic AMP (cAMP) at ∼4.5 Å isotropic 3D resolution. The structure provides a clear picture of the arrangement of the cyclic nucleotide-binding domains with respect to both the pore and the putative voltage sensor domains when cAMP is bound, and reveals a potential gating mechanism in the context of the lipid-embedded channel.

Surface electromyography for analysis of heart rate variability in preterm infants.

OBJECTIVE: Characterizing heart rate variability (HRV) in neonates has gained increased attention and is helpful in quantifying maturation and risk of sepsis in preterm infants. Raw data used to derive HRV in a clinical setting commonly contain noise from motion artifacts. Thoracic surface electromyography (sEMG) potentially allows for pre-emptive removal of motion artifacts and subsequent detection of interbeat interval (IBI) of heart rate to calculate HRV. We tested the feasibility of sEMG in preterm infants to exclude noisy raw data and to derive IBI for HRV analysis. We hypothesized that a stepwise quality control algorithm can identify motion artifacts which influence IBI values, their distribution in the time domain, and outcomes of nonlinear time series analysis. APPROACH: This is a prospective observational study in preterm infants <6 days of age. We used 100 sEMG measurements from 24 infants to develop a semi-automatic quality control algorithm including synchronized video recording, threshold-based sEMG envelope curve, optimized QRS-complex detection, and final targeted visual inspection of raw data. MAIN RESULTS: Analysis of HRV from sEMG data in preterm infants is feasible. A stepwise algorithm to exclude motion artifacts and improve QRS detection significantly influenced data quality (34% of raw data excluded), distribution of IBI values in the time domain, and nonlinear time series analysis. The majority of unsuitable data (94%) were excluded by automated steps of the algorithm. SIGNIFICANCE: Thoracic sEMG is a promising method to assess motion artifacts and calculate HRV in preterm neonates.

A Multi-Sensor Fusion MAV State Estimation from Long-Range Stereo, IMU, GPS and Barometric Sensors.

State estimation is the most critical capability for MAV (Micro-Aerial Vehicle) localization, autonomous obstacle avoidance, robust flight control and 3D environmental mapping. There are three main challenges for MAV state estimation: (1) it can deal with aggressive 6 DOF (Degree Of Freedom) motion; (2) it should be robust to intermittent GPS (Global Positioning System) (even GPS-denied) situations; (3) it should work well both for low- and high-altitude flight. In this paper, we present a state estimation technique by fusing long-range stereo visual odometry, GPS, barometric and IMU (Inertial Measurement Unit) measurements. The new estimation system has two main parts, a stochastic cloning EKF (Extended Kalman Filter) estimator that loosely fuses both absolute state measurements (GPS, barometer) and the relative state measurements (IMU, visual odometry), and is derived and discussed in detail. A long-range stereo visual odometry is proposed for high-altitude MAV odometry calculation by using both multi-view stereo triangulation and a multi-view stereo inverse depth filter. The odometry takes the EKF information (IMU integral) for robust camera pose tracking and image feature matching, and the stereo odometry output serves as the relative measurements for the update of the state estimation. Experimental results on a benchmark dataset and our real flight dataset show the effectiveness of the proposed state estimation system, especially for the aggressive, intermittent GPS and high-altitude MAV flight.

Cholesteryl ester transfer between lipoproteins does not require a ternary tunnel complex with CETP.

The cholesteryl ester transfer protein (CETP) enables the transfer of cholesteryl ester (CE) from high-density lipoproteins (HDL) to low-density lipoproteins (LDL) in the plasma compartment. CETP inhibition raises plasma levels of HDL cholesterol; a ternary tunnel complex with CETP bridging HDL and LDL was suggested as a mechanism. Here, we test whether the inhibition of CETP tunnel complex formation is a promising approach to suppress CE transfer from HDL to LDL, for potential treatment of cardio-vascular disease (CVD). Three monoclonal antibodies against different epitopes of CETP are assayed for their potential to interfere with CE transfer between HDL and/or LDL. Surprisingly, antibodies that target the tips of the elongated CETP molecule, interaction sites sterically required to form the suggested transfer complexes, do not interfere with CETP activity, but an antibody binding to the central region does. We show that CETP interacts with HDL, but not with LDL. Our findings demonstrate that a ternary tunnel complex is not the mechanistic prerequisite to transfer CE among lipoproteins.

Structure and assembly of the mouse ASC inflammasome by combined NMR spectroscopy and cryo-electron microscopy.

Inflammasomes are multiprotein complexes that control the innate immune response by activating caspase-1, thus promoting the secretion of cytokines in response to invading pathogens and endogenous triggers. Assembly of inflammasomes is induced by activation of a receptor protein. Many inflammasome receptors require the adapter protein ASC [apoptosis-associated speck-like protein containing a caspase-recruitment domain (CARD)], which consists of two domains, the N-terminal pyrin domain (PYD) and the C-terminal CARD. Upon activation, ASC forms large oligomeric filaments, which facilitate procaspase-1 recruitment. Here, we characterize the structure and filament formation of mouse ASC in vitro at atomic resolution. Information from cryo-electron microscopy and solid-state NMR spectroscopy is combined in a single structure calculation to obtain the atomic-resolution structure of the ASC filament. Perturbations of NMR resonances upon filament formation monitor the specific binding interfaces of ASC-PYD association. Importantly, NMR experiments show the rigidity of the PYD forming the core of the filament as well as the high mobility of the CARD relative to this core. The findings are validated by structure-based mutagenesis experiments in cultured macrophages. The 3D structure of the mouse ASC-PYD filament is highly similar to the recently determined human ASC-PYD filament, suggesting evolutionary conservation of ASC-dependent inflammasome mechanisms.

Structure of the type VI secretion system contractile sheath.

Bacteria use rapid contraction of a long sheath of the type VI secretion system (T6SS) to deliver effectors into a target cell. Here, we present an atomic-resolution structure of a native contracted Vibrio cholerae sheath determined by cryo-electron microscopy. The sheath subunits, composed of tightly interacting proteins VipA and VipB, assemble into a six-start helix. The helix is stabilized by a core domain assembled from four ß strands donated by one VipA and two VipB molecules. The fold of inner and middle layers is conserved between T6SS and phage sheaths. However, the structure of the outer layer is distinct and suggests a mechanism of interaction of the bacterial sheath with an accessory ATPase, ClpV, that facilitates multiple rounds of effector delivery. Our results provide a mechanistic insight into assembly of contractile nanomachines that bacteria and phages use to translocate macromolecules across membranes.

2dx_automator: implementation of a semiautomatic high-throughput high-resolution cryo-electron crystallography pipeline.

The introduction of direct electron detectors (DED) to cryo-electron microscopy has tremendously increased the signal-to-noise ratio (SNR) and quality of the recorded images. We discuss the optimal use of DEDs for cryo-electron crystallography, introduce a new automatic image processing pipeline, and demonstrate the vast improvement in the resolution achieved by the use of both together, especially for highly tilted samples. The new processing pipeline (now included in the software package 2dx) exploits the high SNR and frame readout frequency of DEDs to automatically correct for beam-induced sample movement, and reliably processes individual crystal images without human interaction as data are being acquired. A new graphical user interface (GUI) condenses all information required for quality assessment in one window, allowing the imaging conditions to be verified and adjusted during the data collection session. With this new pipeline an automatically generated unit cell projection map of each recorded 2D crystal is available less than 5 min after the image was recorded. The entire processing procedure yielded a three-dimensional reconstruction of the 2D-crystallized ion-channel membrane protein MloK1 with a much-improved resolution of 5Å in-plane and 7Å in the z-direction, within 2 days of data acquisition and simultaneous processing. The results obtained are superior to those delivered by conventional photographic film-based methodology of the same sample, and demonstrate the importance of drift-correction.

Single particle 3D reconstruction for 2D crystal images of membrane proteins.

In cases where ultra-flat cryo-preparations of well-ordered two-dimensional (2D) crystals are available, electron crystallography is a powerful method for the determination of the high-resolution structures of membrane and soluble proteins. However, crystal unbending and Fourier-filtering methods in electron crystallography three-dimensional (3D) image processing are generally limited in their performance for 2D crystals that are badly ordered or non-flat. Here we present a single particle image processing approach, which is implemented as an extension of the 2D crystallographic pipeline realized in the 2dx software package, for the determination of high-resolution 3D structures of membrane proteins. The algorithm presented, addresses the low single-to-noise ratio (SNR) of 2D crystal images by exploiting neighborhood correlation between adjacent proteins in the 2D crystal. Compared with conventional single particle processing for randomly oriented particles, the computational costs are greatly reduced due to the crystal-induced limited search space, which allows a much finer search space compared to classical single particle processing. To reduce the considerable computational costs, our software features a hybrid parallelization scheme for multi-CPU clusters and computer with high-end graphic processing units (GPUs). We successfully apply the new refinement method to the structure of the potassium channel MloK1. The calculated 3D reconstruction shows more structural details and contains less noise than the map obtained by conventional Fourier-filtering based processing of the same 2D crystal images.