Alpha-amylase, cortisol, and pupillary responses to social and non-social dynamic scenes in young children with autism spectrum disorder

The symptoms of Autism Spectrum Disorder (ASD) may manifest from deficits in attention/arousal; previous studies found altered autonomic and attentional responses in ASD. We found a larger tonic pupil size (Anderson & Colombo, 2009) and altered phasic pupillary responses to human faces (Anderson, Colombo, & Shaddy, 2006) in 2-5 year old children with ASD. Children (20 - 72 months of age) with ASD (n = 12), Down syndrome (DS; n = 9), and typical development (TD; n = 11) were presented with a social and a non-social video clip to examine pupil, salivary, and visual scanning measures. The ASD group had (a) a larger tonic pupil size, (b) lower tonic levels of AA, significantly related to tonic pupil size, and (c) increased phasic pupil responses to the social stimulus than controls. These findings provide replication and extension of our previous investigations; underlying pathology and early identification measures in ASD are discussed

Pupil and Salivary Indicators of Autonomic Dysfunction in Autism Spectrum Disorder

This is the peer reviewed version of the following article: Anderson, C. J., Colombo, J. and Unruh, K. E. (2013), Pupil and salivary indicators of autonomic dysfunction in autism spectrum disorder. Dev. Psychobiol., 55: 465–482. doi:10.1002/dev.21051, which has been published in final form at http://doi.org/10.1002/dev.21051. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.Dysregulated tonic pupil size has been reported in Autism Spectrum Disorder (ASD). Among the possible sources of this dysregulation are disruptions in the feedback loop between norepinephrine (NE) and hypothalamic systems. In the current study, we examined afternoon levels of salivary alpha-amylase (sAA, a putative correlate of NE) and cortisol (used to assess stress-based responses) in two independent samples of children with ASD. We found a larger pupil size and lower sAA levels in ASD, compared to typical and clinical age-matched controls. This was substantiated at the individual level, as sAA levels were strongly correlated with tonic pupil size. Relatively little diurnal variation in sAA taken in the home environment in the ASD group was also observed, while typical controls showed a significant linear increase throughout the day. Results are discussed in terms of potential early biomarkers and the elucidation of underlying neural dysfunction in ASD

Eye Tracking as a Measure of Receptive Vocabulary in Children with Autism Spectrum Disorders

This study examined the utility of eye tracking research technology to measure speech comprehension in 14 young boys with autism spectrum disorders (ASD) and 15 developmentally matched boys with typical development. Using eye tracking research technology, children were tested on individualized sets of known and unknown words, identified based on their performance on the Peabody Picture Vocabulary Test. Children in both groups spent a significantly longer amount of time looking at the target picture when previous testing indicated the word was known (known condition). Children with ASD spent similar amounts of time looking at the target and non-target pictures when previous testing indicated the word was unknown (unknown condition). However, children with typical development looked longer at the target pictures in the unknown condition as well, potentially suggesting emergent vocabulary knowledge

Earth Observations and Integrative Models in Support of Food and Water Security

Global food production depends upon many factors that Earth observing satellites routinely measure about water, energy, weather, and ecosystems. Increasingly sophisticated, publicly-available satellite data products can improve efficiencies in resource management and provide earlier indication of environmental disruption. Satellite remote sensing provides a consistent, long-term record that can be used effectively to detect large-scale features over time, such as a developing drought. Accuracy and capabilities have increased along with the range of Earth observations and derived products that can support food security decisions with actionable information. This paper highlights major capabilities facilitated by satellite observations and physical models that have been developed and validated using remotely-sensed observations. Although we primarily focus on variables relevant to agriculture, we also include a brief description of the growing use of Earth observations in support of aquaculture and fisheries

Service provision and barriers to care for homeless people with mental health problems across 14 European capital cities

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Carnegie Supernova Project-II: Extending the Near-Infrared Hubble Diagram for Type Ia Supernovae to z∼0.1z\sim0.1

The Carnegie Supernova Project-II (CSP-II) was an NSF-funded, four-year program to obtain optical and near-infrared observations of a "Cosmology" sample of $\sim100$ Type Ia supernovae located in the smooth Hubble flow ($0.03 \lesssim z \lesssim 0.10$). Light curves were also obtained of a "Physics" sample composed of 90 nearby Type Ia supernovae at $z \leq 0.04$ selected for near-infrared spectroscopic time-series observations. The primary emphasis of the CSP-II is to use the combination of optical and near-infrared photometry to achieve a distance precision of better than 5%. In this paper, details of the supernova sample, the observational strategy, and the characteristics of the photometric data are provided. In a companion paper, the near-infrared spectroscopy component of the project is presented.Comment: 43 pages, 10 figures, accepted for publication in PAS

Developing an Observing Air–Sea Interactions Strategy (OASIS) for the global ocean

The Observing Air–Sea Interactions Strategy (OASIS) is a new United Nations Decade of Ocean Science for Sustainable Development programme working to develop a practical, integrated approach for observing air–sea interactions globally for improved Earth system (including ecosystem) forecasts, CO2 uptake assessments called for by the Paris Agreement, and invaluable surface ocean information for decision makers. Our “Theory of Change” relies upon leveraged multi-disciplinary activities, partnerships, and capacity strengthening. Recommendations from >40 OceanObs’19 community papers and a series of workshops have been consolidated into three interlinked Grand Ideas for creating #1: a globally distributed network of mobile air–sea observing platforms built around an expanded array of long-term time-series stations; #2: a satellite network, with high spatial and temporal resolution, optimized for measuring air–sea fluxes; and #3: improved representation of air–sea coupling in a hierarchy of Earth system models. OASIS activities are organized across five Theme Teams: (1) Observing Network Design & Model Improvement; (2) Partnership & Capacity Strengthening; (3) UN Decade OASIS Actions; (4) Best Practices & Interoperability Experiments; and (5) Findable–Accessible–Interoperable–Reusable (FAIR) models, data, and OASIS products. Stakeholders, including researchers, are actively recruited to participate in Theme Teams to help promote a predicted, safe, clean, healthy, resilient, and productive ocean.publishedVersio

A comparison of univariate, vector, bilinear autoregressive, and band power features for brain–computer interfaces

Selecting suitable feature types is crucial to obtain good overall brain–computer interface performance. Popular feature types include logarithmic band power (logBP), autoregressive (AR) parameters, time-domain parameters, and wavelet-based methods. In this study, we focused on different variants of AR models and compare performance with logBP features. In particular, we analyzed univariate, vector, and bilinear AR models. We used four-class motor imagery data from nine healthy users over two sessions. We used the first session to optimize parameters such as model order and frequency bands. We then evaluated optimized feature extraction methods on the unseen second session. We found that band power yields significantly higher classification accuracies than AR methods. However, we did not update the bias of the classifiers for the second session in our analysis procedure. When updating the bias at the beginning of a new session, we found no significant differences between all methods anymore. Furthermore, our results indicate that subject-specific optimization is not better than globally optimized parameters. The comparison within the AR methods showed that the vector model is significantly better than both univariate and bilinear variants. Finally, adding the prediction error variance to the feature space significantly improved classification results

Carnegie Supernova Project-I and -II: Measurements of H0H_0 using Cepheid, TRGB, and SBF Distance Calibration to Type Ia Supernovae

We present an analysis of Type Ia Supernovae (SNe~Ia) from both the Carnegie Supernova Project~I (CSP-I) and II (CSP-II), and extend the Hubble diagram from the optical to the near-infrared wavelengths ($uBgVriYJH$). We calculate the Hubble constant, $H_0$, using various distance calibrators: Cepheids, Tip of the Red Giant Branch (TRGB), and Surface Brightness Fluctuations (SBF). Combining all methods of calibrations, we derive $\rm H_0=71.76 \pm 0.58 \ (stat) \pm 1.19 \ (sys) \ km \ s^{-1} \ Mpc^{-1}$from$B$-band, and$\rm H_0=73.22 \pm 0.68 \ (stat) \pm 1.28 \ (sys) \ km \ s^{-1} \ Mpc^{-1}$from$H$-band. By assigning equal weight to the Cepheid, TRGB, and SBF calibrators, we derive the systematic errors required for consistency in the first rung of the distance ladder, resulting in a systematic error of$1.2\sim 1.3 \rm \ km \ s^{-1} \ Mpc^{-1}$in$H_0$. As a result, relative to the statistics-only uncertainty, the tension between the late-time$H_0$we derive by combining the various distance calibrators and the early-time$H_0$from the Cosmic Microwave Background is reduced. The highest precision in SN~Ia luminosity is found in the$Y$band ($0.12\pm0.01$mag), as defined by the intrinsic scatter ($\sigma_{int}$). We revisit SN~Ia Hubble residual-host mass correlations and recover previous results that these correlations do not change significantly between the optical and the near-infrared wavelengths. Finally, SNe~Ia that explode beyond 10 kpc from their host centers exhibit smaller dispersion in their luminosity, confirming our earlier findings. Reduced effect of dust in the outskirt of hosts may be responsible for this effect.Comment: Revised calculations are made. Will be resubmitted to Ap