Segmentation of Time Series: Parameter Dependence of Blake-Zisserman and Mumford-Shah Functionals and the Transition from Discrete to Continuous

The paper deals with variational approaches to the segmentation of time series into smooth pieces, but allowing for sharp breaks. In discrete time, the corresponding functionals are of Blake-Zisserman type. Their natural counterpart in continuous time are the Mumford-Shah functionals. Time series which minimise these functionals are proper estimates or representations of the signals behind recorded data. We focus on consistent behaviour of the functionals and the estimates, as parameters vary or as the sampling rate increases. For each time continuous time series $f\in L^2 (\lbrack 0,1\rbrack)$ we take conditional expectations w.r.t. to $\sigma$-algebras generated by finer and finer partitions of the time domain into intervals, and thereby construct a sequence $(f_n)_{n\in\N}$ of discrete time series. As $n$ increases this amounts to sampling the continuous time series with more and more accuracy. Our main result is consistent behaviour of segmentations w.r.t. to variation of parameters and increasing sampling rate

Consistencies and rates of convergence of jump-penalized least squares estimators

We study the asymptotics for jump-penalized least squares regression aiming at approximating a regression function by piecewise constant functions. Besides conventional consistency and convergence rates of the estimates in $L^2([0,1))$ our results cover other metrics like Skorokhod metric on the space of c\`{a}dl\`{a}g functions and uniform metrics on $C([0,1])$. We will show that these estimators are in an adaptive sense rate optimal over certain classes of "approximation spaces." Special cases are the class of functions of bounded variation (piecewise) H\"{o}lder continuous functions of order $0<\alpha\le1$ and the class of step functions with a finite but arbitrary number of jumps. In the latter setting, we will also deduce the rates known from change-point analysis for detecting the jumps. Finally, the issue of fully automatic selection of the smoothing parameter is addressed.Comment: Published in at http://dx.doi.org/10.1214/07-AOS558 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Anthropogenic perturbation of the carbon fluxes from land to ocean

A substantial amount of the atmospheric carbon taken up on land through photosynthesis and chemical weathering is transported laterally along the aquatic continuum from upland terrestrial ecosystems to the ocean. So far, global carbon budget estimates have implicitly assumed that the transformation and lateral transport of carbon along this aquatic continuum has remained unchanged since pre-industrial times. A synthesis of published work reveals the magnitude of present-day lateral carbon fluxes from land to ocean, and the extent to which human activities have altered these fluxes. We show that anthropogenic perturbation may have increased the flux of carbon to inland waters by as much as 1.0 Pg C yr-1 since pre-industrial times, mainly owing to enhanced carbon export from soils. Most of this additional carbon input to upstream rivers is either emitted back to the atmosphere as carbon dioxide (~0.4 Pg C yr-1) or sequestered in sediments (~0.5 Pg C yr-1) along the continuum of freshwater bodies, estuaries and coastal waters, leaving only a perturbation carbon input of ~0.1 Pg C yr-1 to the open ocean. According to our analysis, terrestrial ecosystems store ~0.9 Pg C yr-1 at present, which is in agreement with results from forest inventories but significantly differs from the figure of 1.5 Pg C yr-1 previously estimated when ignoring changes in lateral carbon fluxes. We suggest that carbon fluxes along the land–ocean aquatic continuum need to be included in global carbon dioxide budgets.Peer reviewe

Albiglutide and cardiovascular outcomes in patients with type 2 diabetes and cardiovascular disease (Harmony Outcomes): a double-blind, randomised placebo-controlled trial

Background: Glucagon-like peptide 1 receptor agonists differ in chemical structure, duration of action, and in their effects on clinical outcomes. The cardiovascular effects of once-weekly albiglutide in type 2 diabetes are unknown. We aimed to determine the safety and efficacy of albiglutide in preventing cardiovascular death, myocardial infarction, or stroke. Methods: We did a double-blind, randomised, placebo-controlled trial in 610 sites across 28 countries. We randomly assigned patients aged 40 years and older with type 2 diabetes and cardiovascular disease (at a 1:1 ratio) to groups that either received a subcutaneous injection of albiglutide (30–50 mg, based on glycaemic response and tolerability) or of a matched volume of placebo once a week, in addition to their standard care. Investigators used an interactive voice or web response system to obtain treatment assignment, and patients and all study investigators were masked to their treatment allocation. We hypothesised that albiglutide would be non-inferior to placebo for the primary outcome of the first occurrence of cardiovascular death, myocardial infarction, or stroke, which was assessed in the intention-to-treat population. If non-inferiority was confirmed by an upper limit of the 95% CI for a hazard ratio of less than 1·30, closed testing for superiority was prespecified. This study is registered with ClinicalTrials.gov, number NCT02465515. Findings: Patients were screened between July 1, 2015, and Nov 24, 2016. 10 793 patients were screened and 9463 participants were enrolled and randomly assigned to groups: 4731 patients were assigned to receive albiglutide and 4732 patients to receive placebo. On Nov 8, 2017, it was determined that 611 primary endpoints and a median follow-up of at least 1·5 years had accrued, and participants returned for a final visit and discontinuation from study treatment; the last patient visit was on March 12, 2018. These 9463 patients, the intention-to-treat population, were evaluated for a median duration of 1·6 years and were assessed for the primary outcome. The primary composite outcome occurred in 338 (7%) of 4731 patients at an incidence rate of 4·6 events per 100 person-years in the albiglutide group and in 428 (9%) of 4732 patients at an incidence rate of 5·9 events per 100 person-years in the placebo group (hazard ratio 0·78, 95% CI 0·68–0·90), which indicated that albiglutide was superior to placebo (p&lt;0·0001 for non-inferiority; p=0·0006 for superiority). The incidence of acute pancreatitis (ten patients in the albiglutide group and seven patients in the placebo group), pancreatic cancer (six patients in the albiglutide group and five patients in the placebo group), medullary thyroid carcinoma (zero patients in both groups), and other serious adverse events did not differ between the two groups. There were three (&lt;1%) deaths in the placebo group that were assessed by investigators, who were masked to study drug assignment, to be treatment-related and two (&lt;1%) deaths in the albiglutide group. Interpretation: In patients with type 2 diabetes and cardiovascular disease, albiglutide was superior to placebo with respect to major adverse cardiovascular events. Evidence-based glucagon-like peptide 1 receptor agonists should therefore be considered as part of a comprehensive strategy to reduce the risk of cardiovascular events in patients with type 2 diabetes. Funding: GlaxoSmithKline

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Consistencies and Rates of Convergence of Jump-PenalizedLeast Squares Estimators

Abstract We study the asymptotics for jump-penalized least squares regression aiming at approx-imating a regression function by piecewise constant functions. Besides conventional consistency and convergence rates of the estimates in L2([0, 1)) our results cover other metricslike Skorokhod metric on the space of c`adl`ag functions and uniform metrics on C([0, 1]) aswell as convergence of the scale spaces, the family of estimates under varying smoothing parameter. We will show that the estimates used are in an adaptive sense rate optimal overthe class of functions of bounded variation, (piecewise) H&amp;quot;older continuous functions of order 1&gt; = a&gt; 0 and the class of step functions. In the latter setting, we will also deduce therates known from changepoint analysis for detecting the jumps. 1 Introduction We consider regression models of the form Y ni = f ni + xni, (i = 1,..., n) (1) where xni are independent zero-mean sub-gaussian random variables and f ni is the mean valueof a square integrable function f 2 L

and Mathematical Geophysics ‡

We propose a new approach for model selection in mathematical statistics that is based not on the probability but on the ‘waiting time ’ of a sample. By waiting time of a sample we understand the average time of the first appearance of the sample in a sequence of independent identically distributed random variables. In the paper we consider a few simple examples to illustrate the main idea and further mathematical problems related to the new approach. Key words: mathematical statistics, sample, model selection

Imitation of binary random textures on the basis of Gaussian numerical models

We present a method for binary texture synthesis based on thresholds of Gaussian random fields. The method enables us to reproduce the average value and correlation function of the observed texture. The method is comparatively simple, and it seems to be effective for a wide class of random binary textures. In the paper we discuss properties of the method and illustrate its performance in the statistically homogeneous and isotropic case. Key words: texture analysis and synthesis, binary texture simulation, numerical modeling of random fields, Gaussian threshold models