Generalized Additive Models for Gigadata:Modeling the U.K. Black Smoke Network Daily Data

<p>We develop scalable methods for fitting penalized regression spline based generalized additive models with of the order of 10⁴ coefficients to up to 10⁸ data. Computational feasibility rests on: (i) a new iteration scheme for estimation of model coefficients and smoothing parameters, avoiding poorly scaling matrix operations; (ii) parallelization of the iteration’s pivoted block Cholesky and basic matrix operations; (iii) the marginal discretization of model covariates to reduce memory footprint, with efficient scalable methods for computing required crossproducts directly from the discrete representation. Marginal discretization enables much finer discretization than joint discretization would permit. We were motivated by the need to model four decades worth of daily particulate data from the U.K. Black Smoke and Sulphur Dioxide Monitoring Network. Although reduced in size recently, over 2000 stations have at some time been part of the network, resulting in some 10 million measurements. Modeling at a daily scale is desirable for accurate trend estimation and mapping, and to provide daily exposure estimates for epidemiological cohort studies. Because of the dataset size, previous work has focused on modeling time or space averaged pollution levels, but this is unsatisfactory from a health perspective, since it is often acute exposure locally and on the time scale of days that is of most importance in driving adverse health outcomes. If computed by conventional means our black smoke model would require a half terabyte of storage just for the model matrix, whereas we are able to compute with it on a desktop workstation. The best previously available reduced memory footprint method would have required three orders of magnitude more computing time than our new method. Supplementary materials for this article are available online.</p

A Spatial Model for the Needle Losses of Pine-Trees in the Forests of Baden-Württemberg: An Application of Bayesian Structured Additive Regression

Summary The data that are analysed are from a monitoring survey which was carried out in 1994 in the forests of Baden-Württemberg, a federal state in the south-western region of Germany. The survey is part of a large monitoring scheme that has been carried out since the 1980s at different spatial and temporal resolutions to observe the increase in forest damage. One indicator for tree vitality is tree defoliation, which is mainly caused by intrinsic factors, age and stand conditions, but also by biotic (e.g. insects) and abiotic stresses (e.g. industrial emissions). In the survey, needle loss of pine-trees and many potential covariates are recorded at about 580 grid points of a 4 km × 4 km grid. The aim is to identify a set of predictors for needle loss and to investigate the relationships between the needle loss and the predictors. The response variable needle loss is recorded as a percentage in 5% steps estimated by eye using binoculars and categorized into healthy trees (10% or less), intermediate trees (10–25%) and damaged trees (25% or more). We use a Bayesian cumulative threshold model with non-linear functions of continuous variables and a random effect for spatial heterogeneity. For both the non-linear functions and the spatial random effect we use Bayesian versions of P-splines as priors. Our method is novel in that it deals with several non-standard data requirements: the ordinal response variable (the categorized version of needle loss), non-linear effects of covariates, spatial heterogeneity and prediction with missing covariates. The model is a special case of models with a geoadditive or more generally structured additive predictor. Inference can be based on Markov chain Monte Carlo techniques or mixed model technology

Modeling sapling distribution over time using a functional predictor in a generalized additive model

[Key message], The effect of adult trees on sapling density distribution during the regeneration fellings is determined in a Pinus sylvestris L. Mediterranean forest using generalized additive models. [Context], Spatial pattern of adult trees determines the number of new individuals after regeneration fellings, which modify the light and air temperature under tree canopy. [Aims], We proposed a novel spatiotemporal model with a functional predictor in a generalized additive model framework to describe nonlinear relationships between the size of the adult trees and the number of saplings of P. sylvestris and to determine if the spatial pattern of the number of saplings remained constant or changed in time. [Methods], In 2001, two plots (0.5 ha) were set up in two phases of regeneration fellings under the group shelterwood method. We mapped the trees and saplings and measured their diameter and height. The inventories were repeated in 2006, 2010, and 2014. [Results], We found a negative association between the diameter of adult trees and number of saplings up to 7–8 m. Beyond these distances, the diameter of adult trees was not associated with the number of saplings. Our results indicate that the spatial pattern of the number of saplings remained quite constant in time. [Conclusion ], The generalized additive models are a flexible tool to determine the distance range of inhibition of saplings by adult trees

Modeling sapling distribution over time using a functional predictor in a generalized additive model

INTERLOCUTORY APPEAL FROM AN ORDER DENYING THE APPELLANTS MOTION TO SUPPRESS EVIDENCE MADE AND ENTERED BY THE SIXTH JUDICIAL DISTRICT COURT, IN AND FOR SEVIER COUNTY, STATE OF UTAH. THE HONORABLE DON V. TIBBS, PRESIDING

Modelling a response as a function of high frequency count data: the association between physical activity and fat mass

We present a new statistical modelling approach where the response is a function of high frequency count data. Our application is about investigating the relationship between the health outcome fat mass and physical activity (PA) measured by accelerometer. The accelerometer quantifies the intensity of physical activity as counts per epoch over a given period of time. We use data from the Avon longitudinal study of parents and children (ALSPAC) where accelerometer data is available as a time series of accelerometer counts per minute over seven days for a subset of children. In order to compare accelerometer profiles between individuals and to reduce the high dimension a functional summary of the profiles is used. We use the histogram as a functional summary due to its simplicity, suitability and ease of interpretation. Our model is an extension of generalised regression of scalars on functions or signal regression. It allows also multi-dimensional functional predictors and additive non-linear predictors for metric covariates. The additive multidimensional functional predictors allow investigating specific questions about whether the effect of PA varies over its intensity, by gender, by time of day or by day of the week. The key feature of the model is that it utilises the full profile of measured PA without requiring cut-points defining intensity levels for light, moderate and vigorous activity. We show that the (not necessarily causal) effect of PA is not linear and not constant over the activity intensity. Also, there is little evidence to suggest that the effect of PA intensity varies by gender or whether it happens on weekdays or on weekends

Endothelial Wnt/β-catenin signaling inhibits glioma angiogenesis and normalizes tumor blood vessels by inducing PDGF-B expression

Endothelial Wnt/β-catenin signaling is necessary for angiogenesis of the central nervous system and blood–brain barrier (BBB) differentiation, but its relevance for glioma vascularization is unknown. In this study, we show that doxycycline-dependent Wnt1 expression in subcutaneous and intracranial mouse glioma models induced endothelial Wnt/β-catenin signaling and led to diminished tumor growth, reduced vascular density, and normalized vessels with increased mural cell attachment. These findings were corroborated in GL261 glioma cells intracranially transplanted in mice expressing dominant-active β-catenin specifically in the endothelium. Enforced endothelial β-catenin signaling restored BBB characteristics, whereas inhibition by Dkk1 (Dickkopf-1) had opposing effects. By overactivating the Wnt pathway, we induced the Wnt/β-catenin–Dll4/Notch signaling cascade in tumor endothelia, blocking an angiogenic and favoring a quiescent vascular phenotype, indicated by induction of stalk cell genes. We show that β-catenin transcriptional activity directly regulated endothelial expression of platelet-derived growth factor B (PDGF-B), leading to mural cell recruitment thereby contributing to vascular quiescence and barrier function. We propose that reinforced Wnt/β-catenin signaling leads to inhibition of angiogenesis with normalized and less permeable vessels, which might prove to be a valuable therapeutic target for antiangiogenic and edema glioma therapy

Novel polyomaviruses in mammals from multiple orders and reassessment of polyomavirus evolution and taxonomy

As the phylogenetic organization of mammalian polyomaviruses is complex and currently incompletely resolved, we aimed at a deeper insight into their evolution by identifying polyomaviruses in host orders and families that have either rarely or not been studied. Sixteen unknown and two known polyomaviruses were identified in animals that belong to 5 orders, 16 genera, and 16 species. From 11 novel polyomaviruses, full genomes could be determined. Splice sites were predicted for large and small T antigen (LTAg, STAg) coding sequences (CDS) and examined experimentally in transfected cell culture. In addition, splice sites of seven published polyomaviruses were analyzed. Based on these data, LTAg and STAg annotations were corrected for 10/86 and 74/86 published polyomaviruses, respectively. For 25 polyomaviruses, a spliced middle T CDS was observed or predicted. Splice sites that likely indicate expression of additional, alternative T antigens, were experimentally detected for six polyomaviruses. In contrast to all other mammalian polyomaviruses, three closely related cetartiodactyl polyomaviruses display two introns within their LTAg CDS. In addition, the VP2 of Glis glis (edible dormouse) polyomavirus 1 was observed to be encoded by a spliced transcript, a unique experimental finding within the Polyomaviridae family. Co-phylogenetic analyses based on LTAg CDS revealed a measurable signal of codivergence when considering all mammalian polyomaviruses, most likely driven by relatively recent codivergence events. Lineage duplication was the only other process whose influence on polyomavirus evolution was unambiguous. Finally, our analyses suggest that an update of the taxonomy of the family is required, including the creation of novel genera of mammalian and non-mammalian polyomaviruses.info:eu-repo/semantics/publishedVersio

Characteristics of adults with type 1 diabetes and treatment-resistant problematic hypoglycaemia: a baseline analysis from the HARPdoc RCT

Aims/hypothesis Problematic hypoglycaemia still complicates insulin therapy for some with type 1 diabetes. This study describes baseline emotional, cognitive and behavioural characteristics in participants in the HARPdoc trial, which evaluates a novel intervention for treatment-resistant problematic hypoglycaemia. Methods We documented a cross-sectional baseline description of 99 adults with type 1 diabetes and problematic hypoglycaemia despite structured education in flexible insulin therapy. The following measures were included: Hypoglycaemia Fear Survey II (HFS-II); Attitudes to Awareness of Hypoglycaemia questionnaire (A2A); Hospital Anxiety and Depression Index; and Problem Areas In Diabetes. k-mean cluster analysis was applied to HFS-II and A2A factors. Data were compared with a peer group without problematic hypoglycaemia, propensity-matched for age, sex and diabetes duration (n = 81). Results The HARPdoc cohort had long-duration diabetes (mean ± SD 35.8 ± 15.4 years), mean ± SD Gold score 5.3 ± 1.2 and a median (IQR) of 5.0 (2.0–12.0) severe hypoglycaemia episodes in the previous year. Most individuals had been offered technology and 49.5% screened positive for anxiety (35.0% for depression and 31.3% for high diabetes distress). The cohort segregated into two clusters: in one (n = 68), people endorsed A2A cognitive barriers to hypoglycaemia avoidance, with low fear on HFS-II factors; in the other (n = 29), A2A factor scores were low and HFS-II high. Anxiety and depression scores were significantly lower in the comparator group. Conclusions/interpretation The HARPdoc protocol successfully recruited people with treatment-resistant problematic hypoglycaemia. The participants had high anxiety and depression. Most of the cohort endorsed unhelpful health beliefs around hypoglycaemia, with low fear of hypoglycaemia, a combination that may contribute to persistence of problematic hypoglycaemia and may be a target for adjunctive psychological therapies

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie