Block-Transitive Designs in Affine Spaces

This paper deals with block-transitive $t$-$(v,k,\lambda)$ designs in affine spaces for large $t$, with a focus on the important index $\lambda=1$ case. We prove that there are no non-trivial 5-$(v,k,1)$ designs admitting a block-transitive group of automorphisms that is of affine type. Moreover, we show that the corresponding non-existence result holds for 4-$(v,k,1)$ designs, except possibly when the group is one-dimensional affine. Our approach involves a consideration of the finite 2-homogeneous affine permutation groups.Comment: 10 pages; to appear in: "Designs, Codes and Cryptography

Quantum subgroups of the Haagerup fusion categories

We answer three related questions concerning the Haagerup subfactor and its even parts, the Haagerup fusion categories. Namely we find all simple module categories over each of the Haagerup fusion categories (in other words, we find the `"quantum subgroups" in the sense of Ocneanu), we find all subfactors whose principal even part is one of the Haagerup fusion categories, and we compute the Brauer-Picard groupoid of Morita equivalences of the Haagerup fusion categories. In addition to the two even parts of the Haagerup subfactor, there is exactly one more fusion category which is Morita equivalent to each of them. This third fusion category has six simple objects and the same fusion rules as one of the even parts of the Haagerup subfactor, but has not previously appeared in the literature. We also find the full lattice of intermediate subfactors for every subfactor whose even part is one of these three fusion categories, and we discuss how our results generalize to Izumi subfactors.Comment: Final version. 40 pages, many figure

HRV and Treatment Outcomes

A substantial body of literature indicates that autonomic functioning, and heart rate dynamics specifically, is related to a range of psychiatric disorders (Alvares, Quintana, Hickie, & Guastella, 2015; Clamor et al., 2014; Kandola, Ashdown-Franks, Stubbs, Osborn, & Hayes, 2019; Kemp, Brunoni, et al., 2014; Kemp, Quintana, Quintana, Quinn, Hopkinson, & Harris, 2014; Latvala et al., 2016; Paulus, Argo, & Egge, 2013). Furthermore, recent research points toward associations between cardiac functioning with psychotherapy outcomes, which might be driven by bidirectional causal pathways (Angelovski et al., 2016; Blanck et al., 2019; Chalmers et al., 2014; Kemp et al., 2014). Resting heart rate (HR) and heart rate variability (HRV) or the changes in the time intervals between consecutive heart beats, have been conceptualized as transdiagnostic biomarkers for health and disease (Beauchaine & Thayer, 2015; Kemp & Quintana, 2013). Specifically, lower resting HR and higher resting HRV, reflected in greater variability in beat-to-beat heart rate dynamics, are cross-sectionally and prospectively associated with lower depressive and anxiety symptom severity (Chalmers et al., 2014; Latvala et al., 2016; Nelson et al., 2020). Moreover, higher resting HR and lower resting HRV are associated with unfavorable psychological and physical health outcomes as reflected in higher subsequent morbidity and mortality (Kemp & Quintana, 2013). HR and HRV are regulated by prefrontal and subcortical brain regions associated with cognition, affect, and emotion regulation (Lemogne et al., 2011; Mather & Thayer, 2018; Shaffer et al., 2014; Shaffer & Ginsberg, 2017; Thayer et al., 2009), indicating that they may be modifiable transdiagnostic biomarkers amenable to clinical interventions aimed at reducing depressive and anxiety symptoms. HRV has been classically assessed through several different sets of metrics, spanning the time, frequency, and non-linear domains, each of which may offer a unique lens through which to improve our understanding of the neurovascular networks underlying transdiagnostic symptom changes over time during treatment. Thus, the current study will examine whether wearable assessed resting HR and HRV are associated with exposure to treatment, whether they can predict depressive and anxiety trajectories as well as treatment outcomes during an evidence-based therapist-supported digital mental health intervention

Aging-related factors

This is a nonrandomized intent-to-treat study investigating age differences in engagement and clinical outcomes among people with depression and anxiety who participated in a digital mental health intervention

An introduction to the spatio-temporal analysis of satellite remote sensing data for geostatisticians

Satellite remote sensing data have become available in meteorology, agriculture, forestry, geology, regional planning, hydrology or natural environment sciences since several decades ago, because satellites provide routinely high quality images with different temporal and spatial resolutions. Joining, combining or smoothing these images for a better quality of information is a challenge not always properly solved. In this regard, geostatistics, as the spatiotemporal stochastic techniques of georeferenced data, is a very helpful and powerful tool not enough explored in this area yet. Here, we analyze the current use of some of the geostatistical tools in satellite image analysis, and provide an introduction to this subject for potential researchers.This research was supported by the Spanish Ministry of Economy, Industry and Competitiveness (Project MTM2017-82553-R), the Government of Navarra (Project PI015, 2016 and Project PI043 2017), and by the Fundación Caja Navarra-UNED Pamplona (2016 and 2017)