Initial evidence for the criterion-related and structural validity of the long versions of the direct and meta-perspectives of the Coach-Athlete Relationship Questionnaire

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2010 Taylor & Francis.The aim of the present study was to develop and initially validate a longer version of the direct (Jowett & Ntoumanis, 2004) and meta-perspectives (Jowett, 2009a, 2009b) of the Coach-Athlete Relationship Questionnaire (CART-Q). In Study 1, instruments (e.g. questionnaires, scales, and inventories) that have been used to assess relationship quality in the broader psychological literature were examined and items potentially relevant to the coach-athlete relationship were identified. The content validity of the identified items was then assessed using expert panels. A final questionnaire was subsequently prepared and administered to 693 participants (310 coaches and 383 athletes). Confirmatory factor analysis was employed to assess the multidimensional nature of the questionnaire based on the 3Cs (i.e. closeness, commitment, and complementarity) model of the coach-athlete relationship. The findings indicated that the direct and meta-perspective items of the long versions of the CART-Q approached an adequate data fit. Moreover, evidence for the internal consistency and criterion validity of the new instruments was also obtained. In Study 2, the newly developed measure was administered to an independent sample of 251 individuals (145 athletes and 106 coaches). Further statistical support was gained for the factorial validity and reliability of the longer version of the CART-Q

Explainable automated recognition of emotional states from canine facial expressions: the case of positive anticipation and frustration.

In animal research, automation of affective states recognition has so far mainly addressed pain in a few species. Emotional states remain uncharted territories, especially in dogs, due to the complexity of their facial morphology and expressions. This study contributes to fill this gap in two aspects. First, it is the first to address dog emotional states using a dataset obtained in a controlled experimental setting, including videos from (n = 29) Labrador Retrievers assumed to be in two experimentally induced emotional states: negative (frustration) and positive (anticipation). The dogs' facial expressions were measured using the Dogs Facial Action Coding System (DogFACS). Two different approaches are compared in relation to our aim: (1) a DogFACS-based approach with a two-step pipeline consisting of (i) a DogFACS variable detector and (ii) a positive/negative state Decision Tree classifier; (2) An approach using deep learning techniques with no intermediate representation. The approaches reach accuracy of above 71% and 89%, respectively, with the deep learning approach performing better. Secondly, this study is also the first to study explainability of AI models in the context of emotion in animals. The DogFACS-based approach provides decision trees, that is a mathematical representation which reflects previous findings by human experts in relation to certain facial expressions (DogFACS variables) being correlates of specific emotional states. The deep learning approach offers a different, visual form of explainability in the form of heatmaps reflecting regions of focus of the network's attention, which in some cases show focus clearly related to the nature of particular DogFACS variables. These heatmaps may hold the key to novel insights on the sensitivity of the network to nuanced pixel patterns reflecting information invisible to the human eye

Patterns of inflammation, microstructural alterations, and sodium accumulation define multiple sclerosis subtypes after 15 years from onset

INTRODUCTION: Conventional MRI is routinely used for the characterization of pathological changes in multiple sclerosis (MS), but due to its lack of specificity is unable to provide accurate prognoses, explain disease heterogeneity and reconcile the gap between observed clinical symptoms and radiological evidence. Quantitative MRI provides measures of physiological abnormalities, otherwise invisible to conventional MRI, that correlate with MS severity. Analyzing quantitative MRI measures through machine learning techniques has been shown to improve the understanding of the underlying disease by better delineating its alteration patterns. METHODS: In this retrospective study, a cohort of healthy controls (HC) and MS patients with different subtypes, followed up 15 years from clinically isolated syndrome (CIS), was analyzed to produce a multi-modal set of quantitative MRI features encompassing relaxometry, microstructure, sodium ion concentration, and tissue volumetry. Random forest classifiers were used to train a model able to discriminate between HC, CIS, relapsing remitting (RR) and secondary progressive (SP) MS patients based on these features and, for each classification task, to identify the relative contribution of each MRI-derived tissue property to the classification task itself. RESULTS AND DISCUSSION: Average classification accuracy scores of 99 and 95% were obtained when discriminating HC and CIS vs. SP, respectively; 82 and 83% for HC and CIS vs. RR; 76% for RR vs. SP, and 79% for HC vs. CIS. Different patterns of alterations were observed for each classification task, offering key insights in the understanding of MS phenotypes pathophysiology: atrophy and relaxometry emerged particularly in the classification of HC and CIS vs. MS, relaxometry within lesions in RR vs. SP, sodium ion concentration in HC vs. CIS, and microstructural alterations were involved across all tasks

Sterile neutrino production via active-sterile oscillations: the quantum Zeno effect

We study several aspects of the kinetic approach to sterile neutrino production via active-sterile mixing. We obtain the neutrino propagator in the medium including self-energy corrections up to $\mathcal{O}(G^2_F)$, from which we extract the dispersion relations and damping rates of the propagating modes. The dispersion relations are the usual ones in terms of the index of refraction in the medium, and the damping rates are $\Gamma_1(k) = \Gamma_{aa}(k) \cos^2\theta_m(k); \Gamma_2(k) = \Gamma_{aa}(k) \sin^2\theta_m(k)$ where $\Gamma_{aa}(k)\propto G^2_F k T^4$ is the active neutrino scattering rate and $\theta_m(k)$ is the mixing angle in the medium. We provide a generalization of the transition probability in the \emph{medium from expectation values in the density matrix}: $P_{a\to s}(t) = \frac{\sin^22\theta_m}{4}[e^{-\Gamma_1t} + e^{-\Gamma_2 t}-2e^{-{1/2}(\Gamma_1+\Gamma_2)t} \cos\big(\Delta E t\big)]$ and study the conditions for its quantum Zeno suppression directly in real time. We find the general conditions for quantum Zeno suppression, which for $m_s\sim \textrm{keV}$ sterile neutrinos with $\sin2\theta \lesssim 10^{-3}$ \emph{may only be} fulfilled near an MSW resonance. We discuss the implications for sterile neutrino production and argue that in the early Universe the wide separation of relaxation scales far away from MSW resonances suggests the breakdown of the current kinetic approach.Comment: version to appear in JHE

Toward Reliable Uptake Metrics in Large Vessel Vasculitis Studies

The aim of this study is to investigate the influence of sex, age, fat mass, fasting blood glucose level (FBGL), and estimated glomerular filtration rate (eGFR) on blood pool activity in patients with large vessel vasculitis (LVV). Blood pool activity was measured in the superior caval vein using mean, maximum, and peak standardized uptake values corrected for body weight (SUVs) and lean body mass (SULs) in 41 fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) scans of LVV patients. Sex influence on the blood pool activity was assessed with t-tests, while linear correlation analyses were used for age, fat mass, FBGL, and eGFR. Significantly higher SUVs were found in women compared with men, whereas SULs were similar between sexes. In addition, higher fat mass was associated with increased SUVs (r = 0.56 to 0.65; all p p > 0.05). Lower eGFR was associated with a higher FDG blood pool activity for all uptake values. In FDG-PET/CT studies with LVV patients, we recommend using SUL over SUV, while caution is advised in interpreting SUV and SUL measures when patients have impaired kidney function

Atmospheric Acetaldehyde: Importance of Air-Sea Exchange and a Missing Source in the Remote Troposphere.

We report airborne measurements of acetaldehyde (CH3CHO) during the first and second deployments of the National Aeronautics and Space Administration (NASA) Atmospheric Tomography Mission (ATom). The budget of CH3CHO is examined using the Community Atmospheric Model with chemistry (CAM-chem), with a newly-developed online air-sea exchange module. The upper limit of the global ocean net emission of CH3CHO is estimated to be 34 Tg a-1 (42 Tg a-1 if considering bubble-mediated transfer), and the ocean impacts on tropospheric CH3CHO are mostly confined to the marine boundary layer. Our analysis suggests that there is an unaccounted CH3CHO source in the remote troposphere and that organic aerosols can only provide a fraction of this missing source. We propose that peroxyacetic acid (PAA) is an ideal indicator of the rapid CH3CHO production in the remote troposphere. The higher-than-expected CH3CHO measurements represent a missing sink of hydroxyl radicals (and halogen radical) in current chemistry-climate models

X-ray Substructure Studies of Four Galaxy Clusters using XMM-Newton Data

Mahdavi et al. find that the degree of agreement between weak lensing and X-ray mass measurements is a function of cluster radius. Numerical simulations also point out that X-ray mass proxies do not work equally well at all radii. The origin of the effect is thought to be associated with cluster mergers. Recent work presenting the cluster maps showed an ability of X-ray maps to reveal and study cluster mergers in detail. Here we present a first attempt to use the study of substructure in assessing the systematics of the hydrostatic mass measurements using two-dimensional (2-D) X-ray diagnostics. The temperature map is uniquely able to identify the substructure in an almost relaxed cluster which would be unnoticed in the ICM electron number density and pressure maps. We describe the radial fluctuations in the 2-D maps by a cumulative/differential scatter profile relative to the mean profile within/at a given radius. The amplitude indicates ~10 fluctuations in the temperature, electron number density and entropy maps, and ~15 fluctuations in the pressure map. The amplitude of and the discontinuity in the scatter complement 2-D substructure diagnostics, e.g. indicating the most disturbed radial range. There is a tantalizing link between the substructure identified using the scatter of the entropy and pressure fluctuations and the hydrostatic mass bias relative to the expected mass based on the M-Yx and M-Mgas relations particularly at r500. XMM-Newton observations with ~120,000 source photons from the cluster are sufficient to apply our substructure diagnostics via the spectrally measured 2-D temperature, electron number density, entropy and pressure maps.Comment: 44 pages, 16 figures, 3 tables, including some language editing from ApJ, published in Ap

Dynamic changes in ear temperature in relation to separation distress in dogs

Highlights • Pet dogs were tested in a brief separation test and filmed remotely using thermography. • Temperature was analyzed from selected patches of both ear pinnae simultaneously. • Social isolation was associated with a significant decrease in ear pinnae temperature. • Temperature of the two ears did not differ significantly from each other. • Long distance thermography is a useful tool in non-invasive stress monitoring. Abstract Infrared thermography can visualize changes in body surface temperature that result from stress-induced physiological changes and alterations of blood flow patterns. Here we explored its use for remote stress monitoring (i.e. removing need for human presence) in a sample of six pet dogs. Dogs were tested in a brief separation test involving contact with their owner, a stranger, and social isolation for two one-minute-periods. Tests were filmed using a thermographic camera set up in a corner of the room, around 7 m from where the subjects spent most of the time. Temperature was measured from selected regions of both ear pinnae simultaneously. Temperatures of both ear pinnae showed a pattern of decrease during separation and increase when a person (either the owner or a stranger) was present, with no lateralized temperature differences between the two ears. Long distance thermographic measurement is a promising technique for non-invasive remote stress assessment, although there are some limitations related to dogs' hair structure over the ears, making it unsuitable for some subjects