Walking on the bright side: Associations between affect, depression, and gait

Background Psychomotor change is a core symptom of depression and one of the criteria in diagnosing depressive disorders. Research suggests depressed individuals demonstrate deviations in gait, or walking, compared to non-depressed controls. However, studies are sparse, often limited to older adults and observational gait assessment. It is also unclear if gait changes are due to dysregulation of affect, a core feature of depression. The current study addressed this gap by investigating the relation between positive and negative affect, depressive symptom severity, and gait in young adults. Methods Using three-dimensional motion capture, gait parameters (velocity, stride length, and step time) were attained from 90 young adults during a task where they walked ten meters at their own pace overground in a laboratory for ten minutes. Self-report measures of mood and affect were collected. Results On average, the study population reported high negative and low positive affect. Contrary to our hypotheses, hierarchical regressions demonstrated no significant associations between gait parameters and affective or depressive symptoms (ps>.05). Conclusions Our findings do not support a relation between affective symptoms and gait parameters. The results may indicate age-dependent gait pathology or that other symptoms of depression may influence gait more strongly than affect. They may also reflect an observational bias of gait changes in depressed young adults, one that is unsupported by objective data. Replication is warranted to further examine whether affective symptomology is embodied via gait differences in young adults.

Demographics of Exoplanets in Binaries. I. Architecture of S-type Planetary Systems Revealed by the Radial-velocity Sample

Although the sample of exoplanets in binaries has been greatly expanded, the sample heterogeneity and observational bias are obstacles toward a clear figure of exoplanet demographics in the binary environment. To overcome the obstacles, we conduct a statistical study that focuses on S-type (circumstellar) planetary systems detected by the radial-velocity (RV) method. We try to account for observational biases by estimating, from available RV data, planet detection efficiencies for each individual system. Our main results are as follows. (1) Single (resp. multiple) planetary systems are mostly found in close (wide) binaries with separation a B < (>) ∼ 100–300 au. (2) In binaries, single and multiple-planet systems are similar in 1D distributions of mass and period as well as eccentricity (in contrast to the “eccentricity dichotomy” found in single star systems) but different in the 2D period-mass diagram. Specifically, there is a rectangular-shaped gap in the period-mass diagram of single-planet systems but not for multiples. This gap also depends on binary separation and is more prominent in close binaries. (3) There is a rising upper envelope in the period-mass diagram for planets in wide binaries as well as in single stars but not in close binaries. More specifically, there is a population of massive short-period planets in close binaries but almost absent in wide binaries or single stars. We suggest that enhanced planetary migration, collision and/or ejection in close binaries could be the potential underlying explanation for these three features.

Are Stripped Envelope Supernovae Really Deficient in 56Ni?

Recent works have indicated that the 56Ni masses estimated for stripped envelope supernovae (SESNe) are systematically higher than those estimated for SNe II. Although this may suggest a distinct progenitor structure between these types of SNe, the possibility remains that this may be caused by observational bias. One important possible bias is that SESNe with low 56Ni mass are dim, and therefore more likely to escape detection. By investigating the distributions of 56Ni mass and distance of the samples collected from the literature, we find that the current literature SESN sample indeed suffers from a significant observational bias, i.e., objects with low 56Ni mass—if they exist—will be missed, especially at larger distances. Note, however, that those distant objects in our sample are mostly SNe Ic-BL. We also conducted mock observations assuming that the 56Ni mass distribution for SESNe is intrinsically the same as that of SNe II. We find that the 56Ni mass distribution of the detected SESN samples moves toward higher mass than the assumed intrinsic distribution because of the difficulty in detecting the low-56Ni mass SESNe. These results could explain the general trend of the higher 56Ni mass distribution (than SNe II) of SESNe found thus far in the literature. However, further finding clear examples of low-56Ni mass SESNe (≤ 0.01 M ⊙) is required to strengthen this hypothesis. Also, objects with high 56Ni mass (≳ 0.2 M ⊙) are not explained by our model, which may require an additional explanation.

Accounting for Selection Bias and Redshift Evolution in GRB Radio Afterglow Data

Gamma-ray Bursts (GRBs) are highly energetic events that can be observed at extremely high redshift. However, inherent bias in GRB data due to selection effects and redshift evolution can significantly skew any subsequent analysis. We correct for important variables related to the GRB emission, such as the burst duration, T90*, the prompt isotropic energy, Eiso, the rest-frame end time of the plateau emission, Ta,radio*, and its correspondent luminosity La,radio, for radio afterglow. In particular, we use the Efron–Petrosian method presented in 1992 for the correction of our variables of interest. Specifically, we correct Eiso and T90* for 80 GRBs, and La,radio and Ta,radio* for a subsample of 18 GRBs that present a plateau-like flattening in their light curve. Upon application of this method, we find strong evolution with redshift in most variables, particularly in La,radio, with values similar to those found in past and current literature in radio, X-ray and optical wavelengths, indicating that these variables are susceptible to observational bias. This analysis emphasizes the necessity of correcting observational data for evolutionary effects to obtain the intrinsic behavior of correlations to use them as discriminators among the most plausible theoretical models and as reliable cosmological tools.

Observational bias within a hospital-wide hand hygiene program

We assessed the extent to which healthcare workers report more favorable hand hygiene rates when observing members of their own professional group versus other groups’ observations of them. Healthcare workers consistently reported higher compliance rates for their own group compared to others’ observations of them (97 vs 92%; P ≤ .001).

Deep learning ferroelectric polarization distributions from STEM data via with and without atom finding

Over the last decade, scanning transmission electron microscopy (STEM) has emerged as a powerful tool for probing atomic structures of complex materials with picometer precision, opening the pathway toward exploring ferroelectric, ferroelastic, and chemical phenomena on the atomic scale. Analyses to date extracting a polarization signal from lattice coupled distortions in STEM imaging rely on discovery of atomic positions from intensity maxima/minima and subsequent calculation of polarization and other order parameter fields from the atomic displacements. Here, we explore the feasibility of polarization mapping directly from the analysis of STEM images using deep convolutional neural networks (DCNNs). In this approach, the DCNN is trained on the labeled part of the image (i.e., for human labelling), and the trained network is subsequently applied to other images. We explore the effects of the choice of the descriptors (centered on atomic columns and grid-based), the effects of observational bias, and whether the network trained on one composition can be applied to a different one. This analysis demonstrates the tremendous potential of the DCNN for the analysis of high-resolution STEM imaging and spectral data and highlights the associated limitations.

Spectral properties of near-Earth objects with low-Jovian Tisserand invariant

ABSTRACT The near-Earth objects with low-Jovian Tisserand invariant (TJ) represent about 9 per cent of the known objects orbiting in the near-Earth space, being subject of numerous planetary encounters and large temperature variations. We aim to make a spectral characterization for a large sample of NEOs with TJ ≤ 3.1. Consequently, we can estimate the fraction of bodies with a cometary origin. We report new spectral observations for 26 low-TJ NEOs. The additional spectra, retrieved from different public data bases, allowed us to perform the analysis over a catalogue of 150 objects. We classified them with respect to Bus-DeMeo taxonomic system. The results are discussed regarding their orbital parameters. The taxonomic distribution of low-TJ NEOs differs from the entire NEOs population. Consequently, TJ ∼ 3 can act as a composition border too. We found that 56.2 per cent of low-TJ NEOs have comet-like spectra and they become abundant (79.7 per cent) for TJ ≤ 2.8. 16 D-type objects have been identified in this population, distributed on orbits with an average TJ = 2.65 ± 0.6. Using two dynamical criteria, together with the comet-like spectral classification as an identification method and by applying an observational bias correction, we estimate that the fraction of NEOs with a cometary nature and H ∈ (14, 21) mag has the lower and upper bounds (1.5 ± 0.15) and (10.4 ± 2.2) per cent. Additionally, our observations show that all extreme cases of low-perihelion asteroids (q ≤ 0.3 au) belong to S-complex.

Using big data from long-form recordings to study development and optimize societal impact

Big data are everywhere. In this chapter, we focus on one source: long-form, child-centered recordings collected using wearable technologies. Because these recordings are simultaneously unobtrusive and encompassing, they may be a break-through technology for clinicians and researchers from several diverse fields. We demonstrate this possibility by outlining three applications for the recordings---clinical treatment, large-scale interventions, and language documentation---where we see the greatest potential. We argue that incorporating these recordings into basic and applied research will result in more equitable treatment of patients, more reliable measurements of the effects of interventions on real-world behavior, and deeper scientific insights with less observational bias. We conclude by outlining a proposal for a semi-structured online platform where vast numbers of long-form recordings could be hosted and more representative, less biased algorithms could be trained.

IMF BX and Dipole Tilt Dependence on Transpolar Arcs

&lt;p&gt;Transpolar arcs (TPAs) are predicted by many models to appear in both hemispheres, as so-called conjugate TPAs. However, some observations have suggested that this is not always the case, and that there is an IMF B&lt;sub&gt;x&lt;/sub&gt; dependence on whether TPAs appear on both hemispheres or not. Specifically, it has been suggested that TPAs only appear on the northern hemisphere for negative IMF B&lt;sub&gt;X&lt;/sub&gt; and vice versa for positive IMF B&lt;sub&gt;X&lt;/sub&gt;. Furthermore, a positive Earth dipole tilt is predicted to have a similar effect on TPA occurrences as a negative IMF B&lt;sub&gt;X&lt;/sub&gt; and vice versa. It is also known that TPAs appear on different locations on the auroral oval, i.e., dawn-, dusk- or both sides of the oval, depending on IMF B&lt;sub&gt;Y&lt;/sub&gt;. However, the role of IMF B&lt;sub&gt;X&lt;/sub&gt; and IMF B&lt;sub&gt;Z&lt;/sub&gt; for the TPA location remains unclear, with some previous observations suggesting a correlation with IMF B&lt;sub&gt;X&lt;/sub&gt;.&lt;/p&gt;&lt;p&gt;In this study, we investigate the influence of IMF B&lt;sub&gt;X&lt;/sub&gt; and dipole tilt on TPAs by statistically analyzing observational data. We analyze TPA datasets from four previous studies, as well as our own TPA dataset, created from DMSP satellite measurements. At first glance, the data suggests that there is a strong correlation between both IMF B&lt;sub&gt;X&lt;/sub&gt; and dipole tilt, and TPA observations in a specific hemisphere. However, when normalizing the data to the solar wind distribution and when taking observational bias into account, this correlation disappears. We therefore conclude that there is no clear correlation between neither IMF B&lt;sub&gt;X&lt;/sub&gt; nor dipole tilt and in which hemisphere a TPA appears. We further analyze four of the five datasets with respect to dawn-dusk appearances of TPAs and its correlation to IMF B&lt;sub&gt;X&lt;/sub&gt;, B&lt;sub&gt;Y&lt;/sub&gt; and B&lt;sub&gt;Z&lt;/sub&gt;. Here, the results for the datasets mostly agree with previous observations. Finally, we discuss the potential causes for the few non-conjugate TPAs, by studying our own TPA dataset in further detail.&lt;/p&gt;

Improving sampling and calibration of GRBs as distance indicators

We present a sample of 74 Gamma-Ray Bursts (GRBs) from the Fermi-GBM catalogue for which we compute the distance moduli and use them to constrain effective dark energy models. To overcome the circularity problem affecting GRBs as distance indicators, we calibrate the Amati relation of our sample with a cosmology-independent technique. Specifically, we use the latest observational Hubble parameter data, including associated systematics, to approximate the cosmic expansion through a Bezier parametric curve. We subsequently obtain the distance moduli of the GRBs and include the data in a suite of recent cosmological observations of the expansion history (Planck Compressed 2018, 2012 BOSS release of BAO data and Pantheon SNIa), to compute Bayesian posterior constraints for the standard cosmological model ΛCDM, as well as ωCDM, and the CPL parametrization. Throughout the analysis we strive to keep under control the error propagation and limit our GRBs sample to avoid observational bias. As a result, we find no evidence in favour of the alternatives to ΛCDM model. The latter agrees very well with our calibrated sample of GRBs and presently available luminosity distance probes.