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Modifications to minimum variance program for processing real data, including two-body problem solution, and modified Kalman filter with bias errors
An assembly of three major components is disclosed which included a wrist interface plate which is secured to the wrist joint of a robotic arm, a tool interface plate which is secured to each tool intended for use by the robotic arm, and a tool holster for each tool attached to the interface plate. The wrist interface plate and a selected tool interface plate are mutually connectable together through an opening or recess in the upper face of the interface plate by means of a notched tongue protruding from the front face of the wrist interface plate which engages a pair of spring-biased rotatable notched wheels located within the body of the tool interface plate. The tool holster captures and locks onto the tool interface plate by means of a pair of actuation claws including a locking tab and an unlocking wedge which operate respective actuation bosses on each of the notched wheels in response to a forward and backward motion of the tool interface plate as a result of motion of the robotic arm to either park the tool or use the tool.
A computational method to simulate unsteady flows involving moving rigid boundaries and interference has been developed. The method is used to solve inviscid equations governing the fluid flow and the dynamic equations governing the motion of rigid bodies. A second-order accurate, upwind-biased, and alterating-direction-implicit method is used to solve the governing equations of the flow. A kinematic domain decomposition (KDD) procedure is extended to treat 3D problems with a high degree of accuracy and generality. The method under consideration is applied to both transonic and supertransonic flows. Both cases involve flow past a cylinder which is forced to pitch sinusoidally near a vertical wall. Benefits of the proposed approach include accurate calculation of the flow around 3D moving multiple bodies with interference; reduction of a numerical error; in particular, the dispersion error which strongly affects wave propagation; and minimization of the phase error which is accumulated according to the time advance procedure.
A connector assembly includes releasably mateable plug and receptacle units. At least one socket is enclosed within the receptacle unit and is aligned with at least one permeable membrane disposed in the front end of the receptacle unit. The plug unit includes a body slidably mounted within a longitudinal bore therein. At least one pin extends from the front end of the body and is aligned with at least one permeable membrane disposed in the front end of the plug unit. The plug unit is biased toward a first, de-mate position in which the body is extended rearwardly such that the pin is enclosed with the plug unit and is slidable to a second, mate position in which the body is compressed forwardly such that the pin projects through the permeable membranes of the plug and receptacle units to electrically connect with the socket.
The increasing precision of cosmology data in the modern era is calling for methods to allow the extraction of non-Gaussian information using tools beyond two-point statistics. The marked power spectrum has the potential to extract beyond two-point information in a computationally efficient way while using much of the infrastructure already available for the power spectrum. In this work we explore the marked power spectrum from an analytical perspective. In particular, we explore a low-order polynomial for the mark that allows us to better control the theoretical uncertainties and we show that with minimal new degrees of freedom the analytical results match measurements from N-body simulations for both the matter field and biased tracers in redshift space. Finally, we show that even within the limited forms of mark that we consider, there are degeneracies that can be broken by inclusion of the marked auto-spectrum or the cross-spectrum with the unmarked field. I n conclusion, we discuss future theoretical developments that would enable us to apply this approach to survey data.
FLUXNET comprises globally distributed eddy-covariance-based estimates of carbon fluxes between the biosphere and the atmosphere. Since eddy covariance flux towers have a relatively small footprint and are distributed unevenly across the world, upscaling the observations is necessary to obtain global-scale estimates of biosphere–atmosphere exchange. Based on cross-consistency checks with atmospheric inversions, sun-induced fluorescence (SIF) and dynamic global vegetation models (DGVMs), here we provide a systematic assessment of the latest upscaling efforts for gross primary production (GPP) and net ecosystem exchange (NEE) of the FLUXCOM initiative, where different machine learning methods, forcing data sets and sets of predictor variables were employed. Spatial patterns of mean GPP are consistent across FLUXCOM and DGVM ensembles (R 2 >0.94 at 1° spatial resolution) while the majority of DGVMs show, for 70 % of the land surface, values outside the FLUXCOM range. Global mean GPP magnitudes for 2008–2010 from FLUXCOM members vary within 106 and 130 PgC yr -1 with the largest uncertainty in the tropics. Seasonal variations in independent SIF estimates agree better with FLUXCOM GPP (mean global pixel-wise R 2 ~0.75) than with GPP from DGVMs (mean global pixel-wise R 2 ~0.6). Seasonal variations in FLUXCOM NEE show good consistency with atmospheric inversion-based net land carbon fluxes, particularly for temperate and boreal regions (R 2 >0.92). Interannual variability of global NEE in FLUXCOM is underestimated compared to inversions and DGVMs. The FLUXCOM version which also uses meteorological inputs shows a strong co-variation in interannual patterns with inversions (R 2 =0.87 for 2001–2010). Mean regional NEE from FLUXCOM shows larger uptake than inversion and DGVM-based estimates, particularly in the tropics with discrepancies of up to several hundred grammes of carbon per square metre per year. These discrepancies can only partly be reconciled by carbon loss pathways that are implicit in inversions but not captured by the flux tower measurements such as carbon emissions from fires and water bodies. We hypothesize that a combination of systematic biases in the underlying eddy covariance data, in particular in tall tropical forests, and a lack of site history effects on NEE in FLUXCOM are likely responsible for the too strong tropical carbon sink estimated by FLUXCOM. Furthermore, as FLUXCOM does not account for CO 2 fertilization effects, carbon flux trends are not realistic. Overall, current FLUXCOM estimates of mean annual and seasonal cycles of GPP as well as seasonal NEE variations provide useful constraints of global carbon cycling, while interannual variability patterns from FLUXCOM are valuable but require cautious interpretation. Exploring the diversity of Earth observation data and of machine learning concepts along with improved quality and quantity of flux tower measurements will facilitate further improvements of the FLUXCOM approach overall.
A satellite attitude control system is usable in the absence of any inertial yaw attitude reference, such as a gyroscope, and in the absence of a pitch bias momentum. Both the roll-yaw rigid body dynamics and the roll-yaw orbit kinematics are modelled. Pitch and roll attitude control are conventional. The model receives inputs from a roll sensor, and roll and yaw torques from reaction wheel monitors. The model produces estimated yaw which controls the spacecraft yaw attitude.
Samples of terrestrial atmospheric gasses from a free body of such gasses using a device characterized by a plurality of tubular bodies adapted to be mounted in side by side relation on a motorized highway vehicle in mutual parallelism with the axis of the normal path of travel for the vehicles. Each of the bodies is of a cylindrical configuration and has an axial opening at each of its opposite ends through which a linear flow path is defined. A pair of pivotally supported, spring-biased sealing caps is mounted adjacent to the ends of the body and continuously urged into a hermetic sealing relationship. A restraint for securing the caps against spring-urged pivotal displacement, includes a separable, normally tensioned line interconnecting the caps and an operable release mechanism for simultaneously releasing the caps for spring-urged displacement. A hot wire cutter is included for separating the line, whereby samples of air are trapped in the body as the caps are spring-driven to assume an hermetically sealed relation with the openings defined in each of the opposite ends of the body.
In this work, we study the ability of perturbative models with effective field theory contributions and infra-red resummation to model the redshift space clustering of biased tracers in models where the linear power spectrum has "features"- either imprinted during inflation or induced by non-standard expansion histories. We show that both Eulerian and Lagrangian perturbation theory are capable of reproducing the Fourier space two-point functions of halos up to the non-linear scale from a suite of 40963 particle N-body simulations. This is the first demonstration that perturbative models can accurately fit the redshift-space clustering of biased tracers in N-body simulations of such theories. By comparing different theoretical models and IR resummation schemes we assess the current theoretical uncertainty in predicting power spectra for models with features. Our results suggest that future surveys will be able to detect or tightly constrain features in the primordial spectrum below the one percent level across a wide range of scales.
Associative brain centers, such as the insect mushroom body, need to represent sensory information in an efficient manner. In Drosophila melanogaster, the Kenyon cells of the mushroom body integrate inputs from a random set of olfactory projection neurons, but some projection neurons—namely those activated by a few ethologically meaningful odors—connect to Kenyon cells more frequently than others. This biased and random connectivity pattern is conceivably advantageous, as it enables the mushroom body to represent a large number of odors as unique activity patterns while prioritizing the representation of a few specific odors. How this connectivity pattern is established remains largely unknown. Here, we test whether the mechanisms patterning the connections between Kenyon cells and projection neurons depend on sensory activity or whether they are hardwired. We mapped a large number of mushroom body input connections in partially anosmic flies—flies lacking the obligate odorant co-receptor Orco—and in wild-type flies. Statistical analyses of these datasets reveal that the random and biased connectivity pattern observed between Kenyon cells and projection neurons forms normally in the absence of most olfactory sensory activity. Finally, this finding supports the idea that even comparatively subtle, population-level patterns of neuronal connectivity can be encoded by fixed genetic programs and are likely to be the result of evolved prioritization of ecologically and ethologically salient stimuli.
Spatial transformations of the vestibular-optokinetic system must account for changes in head position with respect to gravity in order to produce compensatory oculomotor responses. The purpose of this experiment was to study the influence of gravity on the vestibulo-ocular reflex (VOR) in darkness and on visual-vestibular interaction in the pitch plane in human subjects using two different comparisons: (1) Earth-horizontal axis (EHA) rotation about an upright versus a supine body orientation, and (2) Earth-horizontal versus Earth-vertical (EVA) rotation axes. Visual-vestibular responses (VVR) were evaluated by measuring the slow phase velocity of nystagmus induced during sinusoidal motion of the body in the pitch plane (at 0.2 Hz and 0.8 Hz) combined with a constant-velocity vertical optokinetic stimulation (at +/- 36 degrees/s). The results showed no significant effect on the gain or phase of the VOR in darkness or on the VVR responses at 0.8 Hz between EHA upright and EHA supine body orientations. However, there was a downward shift in the VOR bias in darkness in the supine orientation. There were systematic changes in VOR and VVR between EHA and EVA for 0.2 Hz, including a reduced modulation gain, increased phase lead, and decreased bias during EVA rotation. The same trend was also observed at 0.8 Hz, but at a lesser extent, presumably due to the effects of eccentric rotation in our EVA condition and/or to the different canal input across frequencies. The change in the bias at 0.2 Hz between rotation in darkness and rotation with an optokinetic stimulus was greater than the optokinetic responses without rotation. During EHA, changes in head position relative to gravity preserve graviceptor input to the VVR regardless of body orientation. However, the modifications in VVR gain and phase when the rotation axis is aligned with gravity indicate that this graviceptive information is important for providing compensatory eye movements during visual-vestibular interaction in the pitch plane.
This work is part of a series establishing the redshift framework for the 3 × 2 pt analysis of the Dark Energy Survey Year 6 (DES Y6). For DES Y6, photometric redshift distributions are estimated using self-organizing maps (SOMs), calibrated with spectroscopic and many-band photometric data. To overcome limitations from color-redshift degeneracies and incomplete spectroscopic coverage, we enhance this approach by incorporating clustering-based redshift constraints (clustering-z, or WZ) from angular cross-correlations with BOSS and eBOSS galaxies and eBOSS quasar samples. We define a WZ likelihood and apply importance sampling to a large ensemble of SOM-derived 𝑛(𝑧) realizations, selecting those consistent with the clustering measurements to produce a posterior sample for each lens and source bin. The analysis uses angular scales corresponding to 1.5–5 Mpc to optimize signal-to-noise ratio while mitigating modeling uncertainties and marginalizes over redshift-dependent galaxy bias and other systematics informed by the N-body simulation CARDINAL . While a sparser spectroscopic reference sample limits WZ constraining power at 𝑧 >1.1, particularly for source bins, we demonstrate that combining SOM with WZ improves redshift accuracy and enhances the overall cosmological constraining power of DES Y6. As a result, we estimate an improvement in 𝑆 8 of approximately 10% for cosmic shear and 3 ×2pt analysis, primarily due to the WZ calibration of the source samples.
This paper describes a methodology for accurate and flight-calibrated determination of the on-times of the Cassini spacecraft Reaction Control System (RCS) thrusters, without any form of dynamic simulation, for the reaction wheel biases. The hydrazine usage and the delta V vector in body frame are also computed from the respective thruster on-times. The Cassini spacecraft, the largest and most complex interplanetary spacecraft ever built, continues to undertake ambitious and unique scientific observations of planet Saturn, Titan, Enceladus, and other moons of Saturn. In order to maintain a stable attitude during the course of its mission, this three-axis stabilized spacecraft uses two different control systems: the RCS and the reaction wheel assembly control system. The RCS is used to execute a commanded spacecraft slew, to maintain three-axis attitude control, control spacecraft's attitude while performing science observations with coarse pointing requirements, e.g. during targeted low-altitude Titan and Enceladus flybys, bias the momentum of reaction wheels, and to perform RCS-based orbit trim maneuvers. The use of RCS often imparts undesired delta V on the spacecraft. The Cassini navigation team requires accurate predictions of the delta V in spacecraft coordinates and inertial frame resulting from slews using RCS thrusters and more importantly from reaction wheel bias events. It is crucial for the Cassini spacecraft attitude control and navigation teams to be able to, quickly but accurately, predict the hydrazine usage and delta V for various reaction wheel bias events without actually having to spend time and resources simulating the event in flight software-based dynamic simulation or hardware-in-the-loop simulation environments. The methodology described in this paper, and the ground software developed thereof, are designed to provide just that. This methodology assumes a priori knowledge of thrust magnitudes and thruster pulse rise and tail-off time constants for eight individual attitude control thrusters, the spacecraft's wet mass and its center of mass location, and a few other key parameters.
Internet data can be used to improve infectious disease models. However, the representativeness and individual-level validity of internet-derived measures are largely unexplored as this requires ground truth data for study. This study sought to identify relationships between Web-based behaviors and/or conversation topics and health status using a ground truth, survey-based dataset. This study leveraged a unique dataset of self-reported surveys, microbiological laboratory tests, and social media data from the same individuals toward understanding the validity of individual-level constructs pertaining to influenza-like illness in social media data. Logistic regression models were used to identify illness in Twitter posts using user posting behaviors and topic model features extracted from users’ tweets. Of 396 original study participants, only 81 met the inclusion criteria for this study. Of these participants’ tweets, we identified only two instances that were related to health and occurred within 2 weeks (before or after) of a survey indicating symptoms. It was not possible to predict when participants reported symptoms using features derived from topic models (area under the curve [AUC]=0.51; P=.38), though it was possible using behavior features, albeit with a very small effect size (AUC=0.53; P≤.001). Individual symptoms were also generally not predictable either. The study sample and a random sample from Twitter are predictably different on held-out data (AUC=0.67; P≤.001), meaning that the content posted by people who participated in this study was predictably different from that posted by random Twitter users. Individuals in the random sample and the GoViral sample used Twitter with similar frequencies (similar @ mentions, number of tweets, and number of retweets; AUC=0.50; P=.19). To our knowledge, this is the first instance of an attempt to use a ground truth dataset to validate infectious disease observations in social media data. The lack of signal, the lack of predictability among behaviors or topics, and the demonstrated volunteer bias in the study population are important findings for the large and growing body of disease surveillance using internet-sourced data.
We measure the correspondence between the distribution of galaxies and matter around troughs and peaks in the projected galaxy density, by comparing redMaGiC galaxies (0.15 < z < 0.65) to weak lensing mass maps from the Dark Energy Survey (DES) Y3 data release. We obtain stacked profiles, as a function of angle θ, of the galaxy density contrast δ g and the weak lensing convergence κ, in the vicinity of these identified troughs and peaks, referred to as ‘void’ and ‘cluster’ superstructures. The ratio of the profiles depend mildly on θ, indicating good consistency between the profile shapes. We model the amplitude of this ratio using a function $F(\boldsymbol{\eta }, \theta )$ that depends on cosmological parameters $\boldsymbol{\eta }$, scaled by the galaxy bias. We construct templates of $F(\boldsymbol{\eta }, \theta )$ using a suite of N-body (‘Gower Street’) simulations forward-modelled with DES Y3-like noise and systematics. We discuss and quantify the caveats of using a linear bias model to create galaxy maps from the simulation dark matter shells. We measure the galaxy bias in three lens tomographic bins (near to far): $2.32^{+0.86}_{-0.27}, 2.18^{+0.86}_{-0.23}, 1.86^{+0.82}_{-0.23}$ for voids, and $2.46^{+0.73}_{-0.27}, 3.55^{+0.96}_{-0.55}, 4.27^{+0.36}_{-1.14}$ for clusters, assuming the best-fit Planck cosmology. Similar values with ∼0.1σ shifts are obtained assuming the mean DES Y3 cosmology. The biases from troughs and peaks are broadly consistent, although a larger bias is derived for peaks, which is also larger than those measured from the DES Y3 3 × 2-point analysis. This method shows an interesting avenue for measuring field-level bias that can be applied to future lensing surveys.
The capture efficiency describes the capability of a sink, such as a grain boundary (GB), dislocation, and void, to absorb point defects (PDs). The bias defines the difference in capture efficiency between the absorption of a vacancy and dumbbell at a sink. Complete kinetic information on PDs, including diffusion barriers and diffusion orientations, as well as accurate saddle points, are needed to determine the capture efficiency and bias at a sink accurately, which is computationally demanding. Here, in the present study, the Self-Evolving Atomistic Kinetic Monte Carlo (SEAKMC) method was used to investigate the defect dynamics of PDs near different types of grain boundaries (GBs) (with both $\langle$100$\rangle$ and $\langle$110$\rangle$ families) accurately in body-centered cubic (BCC) iron (Fe). The capture efficiency, sink strength, and bias factor of different types of GBs were determined in Fe, which, different from traditional rate theory estimation, showed a distinct capture efficiency, sink strength, and bias in different GBs. The results demonstrate a strong positive correlation between the capture efficiency and the GB strain width, instead of the GB misorientation, GB energy, or GB-PD binding energy, which have been investigated previously. This work provides valuable insight into the radiation-induced microstructural evolution of GBs.
A solution adaption capability for curvilinear near-body grids has been implemented in the OVERFLOW overset grid computational fluid dynamics code. The approach follows closely that used for the Cartesian off-body grids, but inserts refined grids in the computational space of original near-body grids. Refined curvilinear grids are generated using parametric cubic interpolation, with one-sided biasing based on curvature and stretching ratio of the original grid. Sensor functions, grid marking, and solution interpolation tasks are implemented in the same fashion as for off-body grids. A goal-oriented procedure, based on largest error first, is included for controlling growth rate and maximum size of the adapted grid system. The adaption process is almost entirely parallelized using MPI, resulting in a capability suitable for viscous, moving body simulations. Two- and three-dimensional examples are presented.
Magnetic high entropy alloys (HEAs) consisting of 3 d transition metals offer an exciting platform to explore novel magnetic phases as they often house competing exchange interactions in combination with random site disorders. In this work, a sensitive and tunable magnetic order is demonstrated in sputtered single-layer FeCoNiMnAl x films, as a function of non-magnetic Al addition, along with an unexpected exchange bias effect. Thin films of 50 nm FeCoNiMn exhibit a face-centered-cubic ( fcc ) phase, reentrant spin glass (SG) transition near 100 K, and a large exchange bias of over 500 Oe after field-cooling to 5 K. The exchange bias is increased to 930 Oe through a small addition of 5 at.% Al. Further Al addition to 12 at.% results in a body-centered-cubic ( bcc ) phase, coinciding with a large increase in the saturation magnetization, decrease of exchange bias to 50 Oe, and suppression of SG behavior. The change in magnetic order across the Al-induced structural transformation is mediated by the switching of Mn ground state from AF to FM, which is supported by first-principles calculations and experimentally confirmed via X-ray magnetic circular dichroism. These results open up new HEA strategies for explorations of novel magnetic phases.