Ensemble-based data assimilation and the localisation problem

The “butterfly effect” is a popularly known paradigm; commonly it is said that when a butterfly flaps its wings in Brazil, it may cause a tornado in Texas. This essentially describes how weather forecasts can be extremely senstive to small changes in the given atmospheric data, or initial conditions, used in computer model simulations. In 1961 Edward Lorenz found, when running a weather model, that small changes in the initial conditions given to the model can, over time, lead to entriely different forecasts (Lorenz, 1963). This discovery highlights one of the major challenges in modern weather forecasting; that is to provide the computer model with the most accurately specified initial conditions possible. A process known as data assimilation seeks to minimize the errors in the given initial conditions and was, in 1911, described by Bjerkness as “the ultimate problem in meteorology” (Bjerkness, 1911).

Promotion carryover as a missing data problem

An important feature of agribusiness promotion programs is their lagged impact on consumption. Efficient investment in advertising requires reliable estimates of these lagged responses and it is desirable from both applied and theoretical standpoints to have a flexible method for estimating them. This note derives an alternative Bayesian methodology for estimating lagged responses when investments occur intermittently within a time series. The method exploits a latent-variable extension of the natural-conjugate, normal-linear model, Gibbs sampling and data augmentation. It is applied to a monthly time series on Turkish pasta consumption (1993:5-1998:3) and three, nonconsecutive promotion campaigns (1996:3, 1997:3, 1997:10). The results suggest that responses were greatest to the second campaign, which allocated its entire budget to television media; that its impact peaked in the sixth month following expenditure; and that the rate of return (measured in metric tons additional consumption per thousand dollars expended) was around a factor of 20.

In search of academic identity : physical education, sport science and the field of human movement studies

This thesis addresses the problem of the academic identity of the area traditionally referred to as physical education. The study is a critical examination of the argu ments for the justi cation of this area as an autonomous branch of knowledge. The investigation concentrates on a selected number of arguments. The data collection comprised articles books and proceedings of conferences. The preliminary assessment of these materials resulted in a classi cation of the arguments into three groups. The rst group comprises the arguments in favour of physical education as an academic discipline. The second includes the arguments supporting a science of sport. The third consists of the arguments in favour of to a eld of human movement study. The examination of these arguments produced the following results. (a) The area of physical education does not satisfy the conditions presupposed by the de nition of academic discipline. This is so because the area does not form an integrated system of scienti c theories. (b) The same di culty emerges from the examination of the ar guments for sport science. There is no science of sport because there is no integrated system of scienti c theories related to sport. (c) The arguments in favour of a eld of study yielded more productive results. However di culties arise from the de nition of human movement. The analysis of this concept showed that its limits are not well demarcated. This makes it problematic to take human movement as the focus of a eld of studies. These aspects led to the conclusion that such things as an academic discipline of physical education sport science and eld of human movement studies do not exist. At least there are not such things in the sense of autonomous branches of knowledge. This does not imply that a more integrated inquiry based on several disciplines is not possible and desirable. This would enable someone entering phys ical education to nd a more organised structure of knowledge with some generally accepted problem situations procedures and theories on which to base professional practice.

Laryngeal electromyography in movement disorders: Preliminary data

This study describes preliminary laryngeal electromyography (LEMG) data and botulinum toxin treatment in patients with dysphonia due to movement disorders. Twenty-five patients who had been clinically selected for botulinum toxin administration were examined, 19 with suspected laryngeal dystonia or spasmodic dysphonia (SD), 5 with vocal tremor, and 1 with Gilles de la Tourette syndrome (GTS). LEMG evaluations were performed before botulinum toxin administration using monopolar electrodes. Electromyography was consistent with dystonia in 14 patients and normal in 5, and differences in frequency suggesting essential tremor in 3 and Parkinson tremors in 2. The different LEMG patterns and significant improvement in our patients from botulinum toxin therapy has led us to perform laryngeal electromyography as a routine in UNICAMP movement disorders ambulatory.

Segmental dataset and whole body expression data do not support the hypothesis that non-random movement is an intrinsic property of Drosophila retrogenes

Background: Several studies in Drosophila have shown excessive movement of retrogenes from the X chromosome to autosomes, and that these genes are frequently expressed in the testis. This phenomenon has led to several hypotheses invoking natural selection as the process driving male-biased genes to the autosomes. Metta and Schlotterer (BMC Evol Biol 2010, 10:114) analyzed a set of retrogenes where the parental gene has been subsequently lost. They assumed that this class of retrogenes replaced the ancestral functions of the parental gene, and reported that these retrogenes, although mostly originating from movement out of the X chromosome, showed female-biased or unbiased expression. These observations led the authors to suggest that selective forces (such as meiotic sex chromosome inactivation and sexual antagonism) were not responsible for the observed pattern of retrogene movement out of the X chromosome. Results: We reanalyzed the dataset published by Metta and Schlotterer and found several issues that led us to a different conclusion. In particular, Metta and Schlotterer used a dataset combined with expression data in which significant sex-biased expression is not detectable. First, the authors used a segmental dataset where the genes selected for analysis were less testis-biased in expression than those that were excluded from the study. Second, sex-biased expression was defined by comparing male and female whole-body data and not the expression of these genes in gonadal tissues. This approach significantly reduces the probability of detecting sex-biased expressed genes, which explains why the vast majority of the genes analyzed (parental and retrogenes) were equally expressed in both males and females. Third, the female-biased expression observed by Metta and Schltterer is mostly found for parental genes located on the X chromosome, which is known to be enriched with genes with female-biased expression. Fourth, using additional gonad expression data, we found that autosomal genes analyzed by Metta and Schlotterer are less up regulated in ovaries and have higher chance to be expressed in meiotic cells of spermatogenesis when compared to X-linked genes. Conclusions: The criteria used to select retrogenes and the sex-biased expression data based on whole adult flies generated a segmental dataset of female-biased and unbiased expressed genes that was unable to detect the higher propensity of autosomal retrogenes to be expressed in males. Thus, there is no support for the authors' view that the movement of new retrogenes, which originated from X-linked parental genes, was not driven by selection. Therefore, selection-based genetic models remain the most parsimonious explanations for the observed chromosomal distribution of retrogenes.

The Problem of Data

Jahnke and Asher explore workflows and methodologies at a variety of academic data curation sites, and Keralis delves into the academic milieu of library and information schools that offer instruction in data curation. Their conclusions point to the urgent need for a reliable and increasingly sophisticated professional cohort to support data-intensive research in our colleges, universities, and research centers.

A New Approach for Automatic Removal of Movement Artifacts in Near-Infrared Spectroscopy Time Series by Means of Acceleration Data

Abstract: Near-infrared spectroscopy (NIRS) enables the non-invasive measurement of changes in hemodynamics and oxygenation in tissue. Changes in light-coupling due to movement of the subject can cause movement artifacts (MAs) in the recorded signals. Several methods have been developed so far that facilitate the detection and reduction of MAs in the data. However, due to fixed parameter values (e.g., global threshold) none of these methods are perfectly suitable for long-term (i.e., hours) recordings or were not time-effective when applied to large datasets. We aimed to overcome these limitations by automation, i.e., data adaptive thresholding specifically designed for long-term measurements, and by introducing a stable long-term signal reconstruction. Our new technique (“acceleration-based movement artifact reduction algorithm”, AMARA) is based on combining two methods: the “movement artifact reduction algorithm” (MARA, Scholkmann et al. Phys. Meas. 2010, 31, 649–662), and the “accelerometer-based motion artifact removal” (ABAMAR, Virtanen et al. J. Biomed. Opt. 2011, 16, 087005). We describe AMARA in detail and report about successful validation of the algorithm using empirical NIRS data, measured over the prefrontal cortex in adolescents during sleep. In addition, we compared the performance of AMARA to that of MARA and ABAMAR based on validation data.

Extracting more out of relocation data: building movement models as mixtures of random walks

We present a framework for fitting multiple random walks to animal movement paths consisting of ordered sets of step lengths and turning angles. Each step and turn is assigned to one of a number of random walks, each characteristic of a different behavioral state. Behavioral state assignments may be inferred purely from movement data or may include the habitat type in which the animals are located. Switching between different behavioral states may be modeled explicitly using a state transition matrix estimated directly from data, or switching probabilities may take into account the proximity of animals to landscape features. Model fitting is undertaken within a Bayesian framework using the WinBUGS software. These methods allow for identification of different movement states using several properties of observed paths and lead naturally to the formulation of movement models. Analysis of relocation data from elk released in east-central Ontario, Canada, suggests a biphasic movement behavior: elk are either in an "encamped" state in which step lengths are small and turning angles are high, or in an "exploratory" state, in which daily step lengths are several kilometers and turning angles are small. Animals encamp in open habitat (agricultural fields and opened forest), but the exploratory state is not associated with any particular habitat type.

The movement toward patient safety: State action related to reporting and disclosure of healthcare-associated infections

Increasing attention has been given to the problem of medical errors over the past decade. Included within that focused attention has been a strong interest in reducing the occurrence of healthcare-associated infections (HAIs). Acting concurrently with federal initiatives, the majority of U.S. states have statutorily required reporting and public disclosure of HAI data. Although the occurrence of these state statutory enactments and other state initiatives represent a recognition of the strong concern pertaining to HAIs, vast differences in each state’s HAI reporting and public disclosure requirements creates a varied and unequal response to what has become a national problem.^ The purpose of this research was to explore the variations in state HAI legal requirements and other state mandates. State actions, including statutory enactments, regulations, and other initiatives related to state reporting and public disclosure mechanisms were compared, discussed, and analyzed in an effort to illustrate the impact of the lack of uniformity as a public health concern.^ The HAI statutes, administrative requirements, and other mandates of each state and two U.S. territories were reviewed to answer the following seven research questions: How far has the state progressed in its HAI initiative? If the state has a HAI reporting requirement, is it mandatory or voluntary? What healthcare entities are subject to the reporting requirements? What data collection system is utilized? What measures are required to be reported? What is the public disclosure mechanism? How is the underlying reported information protected from public disclosure or other legal release?^ Secondary publicly available data, including state statutes, administrative rules, and other initiatives, were utilized to examine the current HAI-related legislative and administrative activity of the study subjects. The information was reviewed and analyzed to determine variations in HAI reporting and public disclosure laws. Particular attention was given to the seven key research questions.^ The research revealed that considerable progress has been achieved in state HAI initiatives since 2004. Despite this progress, however, when reviewing the state laws and HAI programs comparatively, considerable variations were found to exist with regards to the type of reporting requirements, healthcare facilities subject to the reporting laws, data collection systems utilized, reportable measures, public disclosure requirements, and confidentiality and privilege provisions. The wide variations in state statutes, administrative rules, and other agency directives create a fragmented and inconsistent approach to addressing the nationwide occurrence of HAIs in the U.S. healthcare system. ^

An improvement of a SLAM RGB-D method with movement prediction derived from a study of visual features

This paper presents a method for the fast calculation of a robot’s egomotion using visual features. The method is part of a complete system for automatic map building and Simultaneous Location and Mapping (SLAM). The method uses optical flow to determine whether the robot has undergone a movement. If so, some visual features that do not satisfy several criteria are deleted, and then egomotion is calculated. Thus, the proposed method improves the efficiency of the whole process because not all the data is processed. We use a state-of-the-art algorithm (TORO) to rectify the map and solve the SLAM problem. Additionally, a study of different visual detectors and descriptors has been conducted to identify which of them are more suitable for the SLAM problem. Finally, a navigation method is described using the map obtained from the SLAM solution.

Handling the Problem of Unbalanced Data Sets in the Classification of Technical Equipment States

Questions of handling unbalanced data considered in this article. As models for classification, PNN and MLP are used. Problem of estimation of model performance in case of unbalanced training set is solved. Several methods (clustering approach and boosting approach) considered as useful to deal with the problem of input data.

An analysis of mopeds as a potential safety problem in the United States. Volume II: data analysis and usage and accident projections. Final report.

National Highway Traffic Safety Administration, Washington, D.C.