Time Series Analysis Forecasting and Control

CERN Document Server

Box, George E P; Reinsel, Gregory C

2011-01-01

A modernized new edition of one of the most trusted books on time series analysis. Since publication of the first edition in 1970, Time Series Analysis has served as one of the most influential and prominent works on the subject. This new edition maintains its balanced presentation of the tools for modeling and analyzing time series and also introduces the latest developments that have occurred n the field over the past decade through applications from areas such as business, finance, and engineering. The Fourth Edition provides a clearly written exploration of the key methods for building, cl

Use of Time-Series, ARIMA Designs to Assess Program Efficacy.

Science.gov (United States)

Braden, Jeffery P.; And Others

1990-01-01

Illustrates use of time-series designs for determining efficacy of interventions with fictitious data describing drug-abuse prevention program. Discusses problems and procedures associated with time-series data analysis using Auto Regressive Integrated Moving Averages (ARIMA) models. Example illustrates application of ARIMA analysis for…

Time-series-analysis techniques applied to nuclear-material accounting

International Nuclear Information System (INIS)

Pike, D.H.; Morrison, G.W.; Downing, D.J.

1982-05-01

This document is designed to introduce the reader to the applications of Time Series Analysis techniques to Nuclear Material Accountability data. Time series analysis techniques are designed to extract information from a collection of random variables ordered by time by seeking to identify any trends, patterns, or other structure in the series. Since nuclear material accountability data is a time series, one can extract more information using time series analysis techniques than by using other statistical techniques. Specifically, the objective of this document is to examine the applicability of time series analysis techniques to enhance loss detection of special nuclear materials. An introductory section examines the current industry approach which utilizes inventory differences. The error structure of inventory differences is presented. Time series analysis techniques discussed include the Shewhart Control Chart, the Cumulative Summation of Inventory Differences Statistics (CUSUM) and the Kalman Filter and Linear Smoother

On-line analysis of reactor noise using time-series analysis

International Nuclear Information System (INIS)

McGevna, V.G.

1981-10-01

A method to allow use of time series analysis for on-line noise analysis has been developed. On-line analysis of noise in nuclear power reactors has been limited primarily to spectral analysis and related frequency domain techniques. Time series analysis has many distinct advantages over spectral analysis in the automated processing of reactor noise. However, fitting an autoregressive-moving average (ARMA) model to time series data involves non-linear least squares estimation. Unless a high speed, general purpose computer is available, the calculations become too time consuming for on-line applications. To eliminate this problem, a special purpose algorithm was developed for fitting ARMA models. While it is based on a combination of steepest descent and Taylor series linearization, properties of the ARMA model are used so that the auto- and cross-correlation functions can be used to eliminate the need for estimating derivatives. The number of calculations, per iteration varies lineegardless of the mee 0.2% yield strength displayed anisotropy, with axial and circumferential values being greater than radial. For CF8-CPF8 and CF8M-CPF8M castings to meet current ASME Code S acid fuel cells

Improving Teachers' Knowledge of Functional Assessment-Based Interventions: Outcomes of a Professional Development Series

Science.gov (United States)

Lane, Kathleen Lynne; Oakes, Wendy Peia; Powers, Lisa; Diebold, Tricia; Germer, Kathryn; Common, Eric A.; Brunsting, Nelson

2015-01-01

This paper provides outcomes of a study examining the effectiveness of a year-long professional development training series designed to support in-service educators in learning a systematic approach to functional assessment-based interventions developed by Umbreit and colleagues (2007) that has met with demonstrated success when implemented with…

Law enforcement-applied tourniquets: a case series of life-saving interventions.

Science.gov (United States)

Callaway, David W; Robertson, Joshua; Sztajnkrycer, Matthew D

2015-01-01

Although the epidemiology of civilian trauma is distinct from that encountered in combat, in both settings, extremity hemorrhage remains a major preventable cause of potential mortality. The current paper describes the largest case series in the literature in which police officers arriving prior to emergency medical services applied commercially available field tourniquets to civilian victims of violent trauma. Although all 3 patients with vascular injury arrived at the receiving emergency department in extremis, they were successfully resuscitated and survived to discharge without major morbidity. While this outcome is likely multifactorial and highlights the exceptional care delivered by the modern trauma system, tourniquet application appears to have kept critically injured patients alive long enough to reach definitive trauma care. No patient had a tourniquet-related complication. This case series suggests that law enforcement officers can effectively identify indications for tourniquets and rapidly apply such life-saving interventions.

The foundations of modern time series analysis

CERN Document Server

Mills, Terence C

2011-01-01

This book develops the analysis of Time Series from its formal beginnings in the 1890s through to the publication of Box and Jenkins' watershed publication in 1970, showing how these methods laid the foundations for the modern techniques of Time Series analysis that are in use today.

Meta- and statistical analysis of single-case intervention research data: quantitative gifts and a wish list.

Science.gov (United States)

Kratochwill, Thomas R; Levin, Joel R

2014-04-01

In this commentary, we add to the spirit of the articles appearing in the special series devoted to meta- and statistical analysis of single-case intervention-design data. Following a brief discussion of historical factors leading to our initial involvement in statistical analysis of such data, we discuss: (a) the value added by including statistical-analysis recommendations in the What Works Clearinghouse Standards for single-case intervention designs; (b) the importance of visual analysis in single-case intervention research, along with the distinctive role that could be played by single-case effect-size measures; and (c) the elevated internal validity and statistical-conclusion validity afforded by the incorporation of various forms of randomization into basic single-case design structures. For the future, we envision more widespread application of quantitative analyses, as critical adjuncts to visual analysis, in both primary single-case intervention research studies and literature reviews in the behavioral, educational, and health sciences. Copyright © 2014 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Chernobyl effects on domestic and inbound tourism in Sweden. A time series analysis

International Nuclear Information System (INIS)

Hultkrantz, L.; Olsson, C.

1997-01-01

This paper estimates the impact of the Chernobyl nuclear accident on domestic and international tourism in Sweden. From ARIMA time series forecasts, outlier search, and intervention analysis based on regional monthly accommodation data from 1978-1989, no effect on domestic tourism is found. However, there is an enduring deterrence effect on incoming tourism. The loss of gross revenue from incoming tourism because of the Chernobyl accident, is estimated to 2.5 billion SEK. 5 figs., 7 tabs., 1 appendix, 27 refs

Chernobyl effects on domestic and inbound tourism in Sweden. A time series analysis

Energy Technology Data Exchange (ETDEWEB)

Hultkrantz, L. [Department of Economics, University of Uppsala, Uppsala (Sweden); Olsson, C. [Department of Economics, Umeaa University, Umeaa (Sweden)

1997-03-01

This paper estimates the impact of the Chernobyl nuclear accident on domestic and international tourism in Sweden. From ARIMA time series forecasts, outlier search, and intervention analysis based on regional monthly accommodation data from 1978-1989, no effect on domestic tourism is found. However, there is an enduring deterrence effect on incoming tourism. The loss of gross revenue from incoming tourism because of the Chernobyl accident, is estimated to 2.5 billion SEK. 5 figs., 7 tabs., 1 appendix, 27 refs.

Using machine learning to identify structural breaks in single-group interrupted time series designs.

Science.gov (United States)

Linden, Ariel; Yarnold, Paul R

2016-12-01

Single-group interrupted time series analysis (ITSA) is a popular evaluation methodology in which a single unit of observation is being studied, the outcome variable is serially ordered as a time series and the intervention is expected to 'interrupt' the level and/or trend of the time series, subsequent to its introduction. Given that the internal validity of the design rests on the premise that the interruption in the time series is associated with the introduction of the treatment, treatment effects may seem less plausible if a parallel trend already exists in the time series prior to the actual intervention. Thus, sensitivity analyses should focus on detecting structural breaks in the time series before the intervention. In this paper, we introduce a machine-learning algorithm called optimal discriminant analysis (ODA) as an approach to determine if structural breaks can be identified in years prior to the initiation of the intervention, using data from California's 1988 voter-initiated Proposition 99 to reduce smoking rates. The ODA analysis indicates that numerous structural breaks occurred prior to the actual initiation of Proposition 99 in 1989, including perfect structural breaks in 1983 and 1985, thereby casting doubt on the validity of treatment effects estimated for the actual intervention when using a single-group ITSA design. Given the widespread use of ITSA for evaluating observational data and the increasing use of machine-learning techniques in traditional research, we recommend that structural break sensitivity analysis is routinely incorporated in all research using the single-group ITSA design. © 2016 John Wiley & Sons, Ltd.

Time series analysis in the social sciences the fundamentals

CERN Document Server

Shin, Youseop

2017-01-01

Times Series Analysis in the Social Sciences is a practical and highly readable introduction written exclusively for students and researchers whose mathematical background is limited to basic algebra. The book focuses on fundamental elements of time series analysis that social scientists need to understand so they can employ time series analysis for their research and practice. Through step-by-step explanations and using monthly violent crime rates as case studies, this book explains univariate time series from the preliminary visual analysis through the modeling of seasonality, trends, and re

Elements of nonlinear time series analysis and forecasting

CERN Document Server

De Gooijer, Jan G

2017-01-01

This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications. Avoiding a “theorem-proof” format, it shows concrete applications on a variety of empirical time series. The book can be used in graduate courses in nonlinear time series and at the same time also includes interesting material for more advanced readers. Though it is largely self-contained, readers require an understanding of basic linear time series concepts, Markov chains and Monte Carlo simulation methods. The book covers time-domain and frequency-domain methods for the analysis of both univariate and multivariate (vector) time series. It makes a clear distinction between parametric models on the one hand, and semi- and nonparametric models/methods on the other. This offers the reader the option of concentrating exclusively on one of these nonlinear time series analysis methods. To make the book as user friendly as possible...

Twitter-Delivered Behavioral Weight-Loss Interventions: A Pilot Series.

Science.gov (United States)

Pagoto, Sherry L; Waring, Molly E; Schneider, Kristin L; Oleski, Jessica L; Olendzki, Effie; Hayes, Rashelle B; Appelhans, Bradley M; Whited, Matthew C; Busch, Andrew M; Lemon, Stephenie C

2015-10-23

Lifestyle interventions are efficacious at reducing risk for diabetes and cardiovascular disease but have not had a significant public health impact given high cost and patient and provider burden. Online social networks may reduce the burden of lifestyle interventions to the extent that they displace in-person visits and may enhance opportunities for social support for weight loss. We conducted an iterative series of pilot studies to evaluate the feasibility and acceptability of using online social networks to deliver a lifestyle intervention. In Study 1 (n=10), obese participants with depression received lifestyle counseling via 12 weekly group visits and a private group formed using the online social network, Twitter. Mean weight loss was 2.3 pounds (SD 7.7; range -19.2 to 8.2) or 1.2% (SD 3.6) of baseline weight. A total of 67% (6/9) of participants completing exit interviews found the support of the Twitter group at least somewhat useful. In Study 2 (n=11), participants were not depressed and were required to be regular users of social media. Participants lost, on average, 5.6 pounds (SD 6.3; range -15 to 0) or 3.0% (SD 3.4) of baseline weight, and 100% (9/9) completing exit interviews found the support of the Twitter group at least somewhat useful. To explore the feasibility of eliminating in-person visits, in Study 3 (n=12), we delivered a 12-week lifestyle intervention almost entirely via Twitter by limiting the number of group visits to one, while using the same inclusion criteria as that used in Study 2. Participants lost, on average, 5.4 pounds (SD 6.4; range -14.2 to 3.9) or 3.0% (SD 3.1) of baseline weight, and 90% (9/10) completing exit interviews found the support of the Twitter group at least somewhat useful. Findings revealed that a private Twitter weight-loss group was both feasible and acceptable for many patients, particularly among regular users of social media. Future research should evaluate the efficacy and cost-effectiveness of online

Case Series of a Knowledge Translation Intervention to Increase Upper Limb Exercise in Stroke Rehabilitation.

Science.gov (United States)

Connell, Louise A; McMahon, Naoimh E; Tyson, Sarah F; Watkins, Caroline L; Eng, Janice J

2016-12-01

Current approaches to upper limb rehabilitation are not sufficient to drive neural reorganization and maximize recovery after stroke. To address this evidence-practice gap, a knowledge translation intervention using the Behaviour Change Wheel was developed. The intervention involves collaboratively working with stroke therapy teams to change their practice and increase therapy intensity by therapists prescribing supplementary self-directed arm exercise. The purposes of this case series are: (1) to provide an illustrative example of how a research-informed process changed clinical practice and (2) to report on staff members' and patients' perceptions of the utility of the developed intervention. A participatory action research approach was used in 3 stroke rehabilitation units in the United Kingdom. The intervention aimed to change 4 therapist-level behaviors: (1) screening patients for suitability for supplementary self-directed arm exercise, (2) provision of exercises, (3) involving family and caregivers in assisting with exercises, and (4) monitoring and progressing exercises. Data on changes in practice were collected by therapy teams using a bespoke audit tool. Utility of the intervention was explored in qualitative interviews with patients and staff. Components of the intervention were successfully embedded in 2 of the 3 stroke units. At these sites, almost all admitted patients were screened for suitability for supplementary self-directed exercise. Exercises were provided to 77%, 70%, and 88% of suitable patients across the 3 sites. Involving family and caregivers and monitoring and progressing exercises were not performed consistently. This case series is an example of how a rigorous research-informed knowledge translation process resulted in practice change. Research is needed to demonstrate that these changes can translate into increased intensity of upper limb exercise and affect patient outcomes. © 2016 American Physical Therapy Association.

Analysis of Heavy-Tailed Time Series

DEFF Research Database (Denmark)

Xie, Xiaolei

This thesis is about analysis of heavy-tailed time series. We discuss tail properties of real-world equity return series and investigate the possibility that a single tail index is shared by all return series of actively traded equities in a market. Conditions for this hypothesis to be true...... are identified. We study the eigenvalues and eigenvectors of sample covariance and sample auto-covariance matrices of multivariate heavy-tailed time series, and particularly for time series with very high dimensions. Asymptotic approximations of the eigenvalues and eigenvectors of such matrices are found...... and expressed in terms of the parameters of the dependence structure, among others. Furthermore, we study an importance sampling method for estimating rare-event probabilities of multivariate heavy-tailed time series generated by matrix recursion. We show that the proposed algorithm is efficient in the sense...

Comparative efficacy of interventions to promote hand hygiene in hospital: systematic review and network meta-analysis

Science.gov (United States)

Hongsuwan, Maliwan; Limmathurotsakul, Direk; Lubell, Yoel; Lee, Andie S; Harbarth, Stephan; Day, Nicholas P J; Graves, Nicholas; Cooper, Ben S

2015-01-01

Objective To evaluate the relative efficacy of the World Health Organization 2005 campaign (WHO-5) and other interventions to promote hand hygiene among healthcare workers in hospital settings and to summarize associated information on use of resources. Design Systematic review and network meta-analysis. Data sources Medline, Embase, CINAHL, NHS Economic Evaluation Database, NHS Centre for Reviews and Dissemination, Cochrane Library, and the EPOC register (December 2009 to February 2014); studies selected by the same search terms in previous systematic reviews (1980-2009). Review methods Included studies were randomised controlled trials, non-randomised trials, controlled before-after trials, and interrupted time series studies implementing an intervention to improve compliance with hand hygiene among healthcare workers in hospital settings and measuring compliance or appropriate proxies that met predefined quality inclusion criteria. When studies had not used appropriate analytical methods, primary data were re-analysed. Random effects and network meta-analyses were performed on studies reporting directly observed compliance with hand hygiene when they were considered sufficiently homogeneous with regard to interventions and participants. Information on resources required for interventions was extracted and graded into three levels. Results Of 3639 studies retrieved, 41 met the inclusion criteria (six randomised controlled trials, 32 interrupted time series, one non-randomised trial, and two controlled before-after studies). Meta-analysis of two randomised controlled trials showed the addition of goal setting to WHO-5 was associated with improved compliance (pooled odds ratio 1.35, 95% confidence interval 1.04 to 1.76; I2=81%). Of 22 pairwise comparisons from interrupted time series, 18 showed stepwise increases in compliance with hand hygiene, and all but four showed a trend for increasing compliance after the intervention. Network meta-analysis indicated

Is Stacking Intervention Components Cost-Effective? An Analysis of the Incredible Years Program

Science.gov (United States)

Foster, E. Michael; Olchowski, Allison E.; Webster-Stratton, Carolyn H.

2007-01-01

The cost-effectiveness of delivering stacked multiple intervention components for children is compared to implementing single intervention by analyzing the Incredible Years Series program. The result suggests multiple intervention components are more cost-effective than single intervention components.

Mathematical foundations of time series analysis a concise introduction

CERN Document Server

Beran, Jan

2017-01-01

This book provides a concise introduction to the mathematical foundations of time series analysis, with an emphasis on mathematical clarity. The text is reduced to the essential logical core, mostly using the symbolic language of mathematics, thus enabling readers to very quickly grasp the essential reasoning behind time series analysis. It appeals to anybody wanting to understand time series in a precise, mathematical manner. It is suitable for graduate courses in time series analysis but is equally useful as a reference work for students and researchers alike.

The analysis of time series: an introduction

National Research Council Canada - National Science Library

Chatfield, Christopher

1989-01-01

.... A variety of practical examples are given to support the theory. The book covers a wide range of time-series topics, including probability models for time series, Box-Jenkins forecasting, spectral analysis, linear systems and system identification...

Trend analysis of time-series data: A novel method for untargeted metabolite discovery

NARCIS (Netherlands)

Peters, S.; Janssen, H.-G.; Vivó-Truyols, G.

2010-01-01

A new strategy for biomarker discovery is presented that uses time-series metabolomics data. Data sets from samples analysed at different time points after an intervention are searched for compounds that show a meaningful trend following the intervention. Obviously, this requires new data-analytical

Introduction to time series analysis and forecasting

CERN Document Server

Montgomery, Douglas C; Kulahci, Murat

2008-01-01

An accessible introduction to the most current thinking in and practicality of forecasting techniques in the context of time-oriented data. Analyzing time-oriented data and forecasting are among the most important problems that analysts face across many fields, ranging from finance and economics to production operations and the natural sciences. As a result, there is a widespread need for large groups of people in a variety of fields to understand the basic concepts of time series analysis and forecasting. Introduction to Time Series Analysis and Forecasting presents the time series analysis branch of applied statistics as the underlying methodology for developing practical forecasts, and it also bridges the gap between theory and practice by equipping readers with the tools needed to analyze time-oriented data and construct useful, short- to medium-term, statistically based forecasts.

Time Series Analysis of Insar Data: Methods and Trends

Science.gov (United States)

Osmanoglu, Batuhan; Sunar, Filiz; Wdowinski, Shimon; Cano-Cabral, Enrique

2015-01-01

Time series analysis of InSAR data has emerged as an important tool for monitoring and measuring the displacement of the Earth's surface. Changes in the Earth's surface can result from a wide range of phenomena such as earthquakes, volcanoes, landslides, variations in ground water levels, and changes in wetland water levels. Time series analysis is applied to interferometric phase measurements, which wrap around when the observed motion is larger than one-half of the radar wavelength. Thus, the spatio-temporal ''unwrapping" of phase observations is necessary to obtain physically meaningful results. Several different algorithms have been developed for time series analysis of InSAR data to solve for this ambiguity. These algorithms may employ different models for time series analysis, but they all generate a first-order deformation rate, which can be compared to each other. However, there is no single algorithm that can provide optimal results in all cases. Since time series analyses of InSAR data are used in a variety of applications with different characteristics, each algorithm possesses inherently unique strengths and weaknesses. In this review article, following a brief overview of InSAR technology, we discuss several algorithms developed for time series analysis of InSAR data using an example set of results for measuring subsidence rates in Mexico City.

Interrupted time series analysis in drug utilization research is increasing: systematic review and recommendations.

Science.gov (United States)

Jandoc, Racquel; Burden, Andrea M; Mamdani, Muhammad; Lévesque, Linda E; Cadarette, Suzanne M

2015-08-01

To describe the use and reporting of interrupted time series methods in drug utilization research. We completed a systematic search of MEDLINE, Web of Science, and reference lists to identify English language articles through to December 2013 that used interrupted time series methods in drug utilization research. We tabulated the number of studies by publication year and summarized methodological detail. We identified 220 eligible empirical applications since 1984. Only 17 (8%) were published before 2000, and 90 (41%) were published since 2010. Segmented regression was the most commonly applied interrupted time series method (67%). Most studies assessed drug policy changes (51%, n = 112); 22% (n = 48) examined the impact of new evidence, 18% (n = 39) examined safety advisories, and 16% (n = 35) examined quality improvement interventions. Autocorrelation was considered in 66% of studies, 31% reported adjusting for seasonality, and 15% accounted for nonstationarity. Use of interrupted time series methods in drug utilization research has increased, particularly in recent years. Despite methodological recommendations, there is large variation in reporting of analytic methods. Developing methodological and reporting standards for interrupted time series analysis is important to improve its application in drug utilization research, and we provide recommendations for consideration. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Nonlinear time series analysis of the human electrocardiogram

International Nuclear Information System (INIS)

Perc, Matjaz

2005-01-01

We analyse the human electrocardiogram with simple nonlinear time series analysis methods that are appropriate for graduate as well as undergraduate courses. In particular, attention is devoted to the notions of determinism and stationarity in physiological data. We emphasize that methods of nonlinear time series analysis can be successfully applied only if the studied data set originates from a deterministic stationary system. After positively establishing the presence of determinism and stationarity in the studied electrocardiogram, we calculate the maximal Lyapunov exponent, thus providing interesting insights into the dynamics of the human heart. Moreover, to facilitate interest and enable the integration of nonlinear time series analysis methods into the curriculum at an early stage of the educational process, we also provide user-friendly programs for each implemented method

What marketing scholars should know about time series analysis : time series applications in marketing

NARCIS (Netherlands)

Horváth, Csilla; Kornelis, Marcel; Leeflang, Peter S.H.

2002-01-01

In this review, we give a comprehensive summary of time series techniques in marketing, and discuss a variety of time series analysis (TSA) techniques and models. We classify them in the sets (i) univariate TSA, (ii) multivariate TSA, and (iii) multiple TSA. We provide relevant marketing

Introduction to time series analysis and forecasting

CERN Document Server

Montgomery, Douglas C; Kulahci, Murat

2015-01-01

Praise for the First Edition ""…[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics."" -MAA Reviews Thoroughly updated throughout, Introduction to Time Series Analysis and Forecasting, Second Edition presents the underlying theories of time series analysis that are needed to analyze time-oriented data and construct real-world short- to medium-term statistical forecasts.    Authored by highly-experienced academics and professionals in engineering statistics, the Second Edition features discussions on both

Time series evaluation of an intervention to increase statin tablet splitting by general practitioners.

Science.gov (United States)

Polinski, Jennifer M; Schneeweiss, Sebastian; Maclure, Malcolm; Marshall, Blair; Ramsden, Samuel; Dormuth, Colin

2011-02-01

Tablet splitting, in which a higher-dose tablet is split to get 2 doses, reduces patients' drug costs. Statins can be split safely. General practitioners (GPs) may not direct their patients to split statins because of safety concerns or unawareness of costs. Medical chart inserts provide cost-effective education to physicians. The aim of this study was to assess whether providing GPs with statin-splitting chart inserts would increase splitting rates, and to identify predictors of splitting. In 2005 and 2006, we faxed a statin chart insert to British Columbia GPs with a request for a telephone interview. Consenting GPs were mailed 3 statin chart inserts and interviewed by phone (the intervention). In an interrupted time series, we compared monthly rates of statin-splitting prescriptions among intervention and nonintervention GPs before, during, and after the intervention. In multivariate logistic regressions accounting for patient clustering, predictors of splitting included physician and patient demographics and the specific statin prescribed. Of 5051 GPs reached, 282 (6%) agreed to the intervention. Before the intervention, GPs' splitting rate was 2.6%; after intervention, GPs' splitting rate was 7.5%. The rate for the nonintervention GPs was 4.4%. Intervention GPs were 1.68 (95% CI, 1.12-2.53) times more likely to prescribe splitting after the intervention than were nonintervention GPs. Other predictors were a patient's female sex (odds ratio [OR] = 1.26; 95% CI, 1.18-1.34), lower patient income (OR = 1.33; 95% CI, 1.18-1.34), and a lack of drug insurance (OR = 1.89; 95% CI, 1.69-2.04). An inexpensive intervention was effective in producing a sustained increase in GPs' splitting rate during 22 months of observed follow-up. Expanding statin-splitting education to all GPs might reduce prescription costs for many patients and payors. Copyright © 2011 Elsevier HS Journals, Inc. All rights reserved.

A time series analysis of the effects of financial incentives and mandatory clinical applications as interventions to improve spontaneous adverse drug reaction reporting by hospital medical staff in China.

Science.gov (United States)

Chang, Feng; Xi, Yue; Zhao, Jie; Zhang, Xiaojian; Lu, Yun

2017-12-01

Spontaneous reporting of adverse drug reactions (ADRs) in hospitals is often under-reported, which may lead to problems in patient management. This study was aimed to assess the effectiveness of a financial intervention based on a fine and a bonus for improving spontaneous reporting of ADRs by physicians in a hospital setting. This study was conducted at the First Affiliated Hospital of Zhengzhou University (China). Starting in 2009, a bonus of 20 RMB (Chinese currency) was given for each spontaneous ADR report, and a fine of 50 RMB was given for any withheld ADR report. A time series analysis using autoregressive integrated moving average models was performed to assess the changes in the total number of spontaneous ADR reports between the preintervention period (2006-2008) and during the first (2009-2011) and second (2012-2014) intervention periods. The median number of reported ADRs per year increased from 29 (range 27-72) in the preintervention period to 277 (range 199-284) in the first intervention period and to 666 in the second (range 644-691). The monthly number of reported ADRs was stable during the 3 periods: 3.56 ± 3.60/month (95% confidence interval (CI), 2.42-4.75) during the preintervention period, 21 ± 13/month (95% CI, 16.97-25.80) in the first intervention period, and 56 ± 20/month (95% CI, 48.81-62.17) in the second intervention period. A financial incentive and ADR management regulations had a significant effect on the increase of reported ADRs. © 2017 John Wiley & Sons, Ltd.

Analysis of series resonant converter with series-parallel connection

Science.gov (United States)

Lin, Bor-Ren; Huang, Chien-Lan

2011-02-01

In this study, a parallel inductor-inductor-capacitor (LLC) resonant converter series-connected on the primary side and parallel-connected on the secondary side is presented for server power supply systems. Based on series resonant behaviour, the power metal-oxide-semiconductor field-effect transistors are turned on at zero voltage switching and the rectifier diodes are turned off at zero current switching. Thus, the switching losses on the power semiconductors are reduced. In the proposed converter, the primary windings of the two LLC converters are connected in series. Thus, the two converters have the same primary currents to ensure that they can supply the balance load current. On the output side, two LLC converters are connected in parallel to share the load current and to reduce the current stress on the secondary windings and the rectifier diodes. In this article, the principle of operation, steady-state analysis and design considerations of the proposed converter are provided and discussed. Experiments with a laboratory prototype with a 24 V/21 A output for server power supply were performed to verify the effectiveness of the proposed converter.

Nonlinear time series analysis with R

CERN Document Server

Huffaker, Ray; Rosa, Rodolfo

2017-01-01

In the process of data analysis, the investigator is often facing highly-volatile and random-appearing observed data. A vast body of literature shows that the assumption of underlying stochastic processes was not necessarily representing the nature of the processes under investigation and, when other tools were used, deterministic features emerged. Non Linear Time Series Analysis (NLTS) allows researchers to test whether observed volatility conceals systematic non linear behavior, and to rigorously characterize governing dynamics. Behavioral patterns detected by non linear time series analysis, along with scientific principles and other expert information, guide the specification of mechanistic models that serve to explain real-world behavior rather than merely reproducing it. Often there is a misconception regarding the complexity of the level of mathematics needed to understand and utilize the tools of NLTS (for instance Chaos theory). However, mathematics used in NLTS is much simpler than many other subjec...

Time series analysis time series analysis methods and applications

CERN Document Server

Rao, Tata Subba; Rao, C R

2012-01-01

The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments. The Handbook of Statistics is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with Volume 30 dealing with time series. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriented techniques, with the applied statistician in mind as the primary audience. Comprehensively presents the various aspects of statistical methodology Discusses a wide variety of diverse applications and recent developments Contributors are internationally renowened experts in their respect...

Time-Series Analysis: A Cautionary Tale

Science.gov (United States)

Damadeo, Robert

2015-01-01

Time-series analysis has often been a useful tool in atmospheric science for deriving long-term trends in various atmospherically important parameters (e.g., temperature or the concentration of trace gas species). In particular, time-series analysis has been repeatedly applied to satellite datasets in order to derive the long-term trends in stratospheric ozone, which is a critical atmospheric constituent. However, many of the potential pitfalls relating to the non-uniform sampling of the datasets were often ignored and the results presented by the scientific community have been unknowingly biased. A newly developed and more robust application of this technique is applied to the Stratospheric Aerosol and Gas Experiment (SAGE) II version 7.0 ozone dataset and the previous biases and newly derived trends are presented.

DIY Solar Market Analysis Webinar Series: Solar Resource and Technical

Science.gov (United States)

Series: Solar Resource and Technical Potential DIY Solar Market Analysis Webinar Series: Solar Resource and Technical Potential Wednesday, June 11, 2014 As part of a Do-It-Yourself Solar Market Analysis Potential | State, Local, and Tribal Governments | NREL DIY Solar Market Analysis Webinar

Allan deviation analysis of financial return series

Science.gov (United States)

Hernández-Pérez, R.

2012-05-01

We perform a scaling analysis for the return series of different financial assets applying the Allan deviation (ADEV), which is used in the time and frequency metrology to characterize quantitatively the stability of frequency standards since it has demonstrated to be a robust quantity to analyze fluctuations of non-stationary time series for different observation intervals. The data used are opening price daily series for assets from different markets during a time span of around ten years. We found that the ADEV results for the return series at short scales resemble those expected for an uncorrelated series, consistent with the efficient market hypothesis. On the other hand, the ADEV results for absolute return series for short scales (first one or two decades) decrease following approximately a scaling relation up to a point that is different for almost each asset, after which the ADEV deviates from scaling, which suggests that the presence of clustering, long-range dependence and non-stationarity signatures in the series drive the results for large observation intervals.

Entropic Analysis of Electromyography Time Series

Science.gov (United States)

Kaufman, Miron; Sung, Paul

2005-03-01

We are in the process of assessing the effectiveness of fractal and entropic measures for the diagnostic of low back pain from surface electromyography (EMG) time series. Surface electromyography (EMG) is used to assess patients with low back pain. In a typical EMG measurement, the voltage is measured every millisecond. We observed back muscle fatiguing during one minute, which results in a time series with 60,000 entries. We characterize the complexity of time series by computing the Shannon entropy time dependence. The analysis of the time series from different relevant muscles from healthy and low back pain (LBP) individuals provides evidence that the level of variability of back muscle activities is much larger for healthy individuals than for individuals with LBP. In general the time dependence of the entropy shows a crossover from a diffusive regime to a regime characterized by long time correlations (self organization) at about 0.01s.

The Statistical Analysis of Time Series

CERN Document Server

Anderson, T W

2011-01-01

The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists. Currently available in the Series: T. W. Anderson Statistical Analysis of Time Series T. S. Arthanari & Yadolah Dodge Mathematical Programming in Statistics Emil Artin Geometric Algebra Norman T. J. Bailey The Elements of Stochastic Processes with Applications to the Natural Sciences George

Time-series modeling of long-term weight self-monitoring data.

Science.gov (United States)

Helander, Elina; Pavel, Misha; Jimison, Holly; Korhonen, Ilkka

2015-08-01

Long-term self-monitoring of weight is beneficial for weight maintenance, especially after weight loss. Connected weight scales accumulate time series information over long term and hence enable time series analysis of the data. The analysis can reveal individual patterns, provide more sensitive detection of significant weight trends, and enable more accurate and timely prediction of weight outcomes. However, long term self-weighing data has several challenges which complicate the analysis. Especially, irregular sampling, missing data, and existence of periodic (e.g. diurnal and weekly) patterns are common. In this study, we apply time series modeling approach on daily weight time series from two individuals and describe information that can be extracted from this kind of data. We study the properties of weight time series data, missing data and its link to individuals behavior, periodic patterns and weight series segmentation. Being able to understand behavior through weight data and give relevant feedback is desired to lead to positive intervention on health behaviors.

Zoning and workstation analysis in interventional cardiology

International Nuclear Information System (INIS)

Degrange, J.P.

2009-01-01

As interventional cardiology can induce high doses not only for patients but also for the personnel, the delimitation of regulated areas (or zoning) and workstation analysis (dosimetry) are very important in terms of radioprotection. This paper briefly recalls methods and tools for the different steps to perform zoning and workstation analysis. It outlines the peculiarities of interventional cardiology, presents methods and tools adapted to interventional cardiology, and then discusses the same issues but for workstation analysis. It also outlines specific problems which can be met, and their possible adapted solutions

The Effectiveness of Cognitive Behavioral Therapy With Mindfulness and an Internet Intervention for Obesity: A Case Series

Directory of Open Access Journals (Sweden)

Keizaburo Ogata

2018-06-01

Full Text Available It is difficult for obese (body mass index of more than 30 and overweight (body mass index of 25–30 people to reduce and maintain their weight. The aim of this case series was to examine the effectiveness of a new cognitive behavioral therapy (CBT program that combines mindfulness exercises (e.g., the raisin exercise and breathing exercises and an online intervention to prevent dropout and subsequent weight gain in overweight participants. This case series included three participants, for whom previous weight reduction programs had been unsuccessful. All participants completed the program (60-min, group sessions provided weekly for 9 weeks and an 18-month follow-up assessment. Results showed that all participants succeeded in losing weight (loss ranged from 5.30 to 8.88% of their total body weight. Although rebound weight gain is commonly observed in the first year following initial weight loss, the follow-up assessment showed that participants achieved further weight loss during the 18-month follow-up period. These results suggest that a CBT program that comprises mindfulness and an online intervention may be an effective method for weight loss and maintenance, and may prevent dropout in obese and overweight individuals.Trial Registration: This case series was registered at www.umin.ac.jp with identifier UMIN000029664.

Stochastic time series analysis of hydrology data for water resources

Science.gov (United States)

Sathish, S.; Khadar Babu, S. K.

2017-11-01

The prediction to current publication of stochastic time series analysis in hydrology and seasonal stage. The different statistical tests for predicting the hydrology time series on Thomas-Fiering model. The hydrology time series of flood flow have accept a great deal of consideration worldwide. The concentration of stochastic process areas of time series analysis method are expanding with develop concerns about seasonal periods and global warming. The recent trend by the researchers for testing seasonal periods in the hydrologic flowseries using stochastic process on Thomas-Fiering model. The present article proposed to predict the seasonal periods in hydrology using Thomas-Fiering model.

Time averaging, ageing and delay analysis of financial time series

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Cherstvy, Andrey G.; Vinod, Deepak; Aghion, Erez; Chechkin, Aleksei V.; Metzler, Ralf

2017-06-01

We introduce three strategies for the analysis of financial time series based on time averaged observables. These comprise the time averaged mean squared displacement (MSD) as well as the ageing and delay time methods for varying fractions of the financial time series. We explore these concepts via statistical analysis of historic time series for several Dow Jones Industrial indices for the period from the 1960s to 2015. Remarkably, we discover a simple universal law for the delay time averaged MSD. The observed features of the financial time series dynamics agree well with our analytical results for the time averaged measurables for geometric Brownian motion, underlying the famed Black-Scholes-Merton model. The concepts we promote here are shown to be useful for financial data analysis and enable one to unveil new universal features of stock market dynamics.

Metagenomics meets time series analysis: unraveling microbial community dynamics

NARCIS (Netherlands)

Faust, K.; Lahti, L.M.; Gonze, D.; Vos, de W.M.; Raes, J.

2015-01-01

The recent increase in the number of microbial time series studies offers new insights into the stability and dynamics of microbial communities, from the world's oceans to human microbiota. Dedicated time series analysis tools allow taking full advantage of these data. Such tools can reveal periodic

Disease management with ARIMA model in time series.

Science.gov (United States)

Sato, Renato Cesar

2013-01-01

The evaluation of infectious and noninfectious disease management can be done through the use of a time series analysis. In this study, we expect to measure the results and prevent intervention effects on the disease. Clinical studies have benefited from the use of these techniques, particularly for the wide applicability of the ARIMA model. This study briefly presents the process of using the ARIMA model. This analytical tool offers a great contribution for researchers and healthcare managers in the evaluation of healthcare interventions in specific populations.

Applied time series analysis and innovative computing

CERN Document Server

Ao, Sio-Iong

2010-01-01

This text is a systematic, state-of-the-art introduction to the use of innovative computing paradigms as an investigative tool for applications in time series analysis. It includes frontier case studies based on recent research.

Multiresolution analysis of Bursa Malaysia KLCI time series

Science.gov (United States)

Ismail, Mohd Tahir; Dghais, Amel Abdoullah Ahmed

2017-05-01

In general, a time series is simply a sequence of numbers collected at regular intervals over a period. Financial time series data processing is concerned with the theory and practice of processing asset price over time, such as currency, commodity data, and stock market data. The primary aim of this study is to understand the fundamental characteristics of selected financial time series by using the time as well as the frequency domain analysis. After that prediction can be executed for the desired system for in sample forecasting. In this study, multiresolution analysis which the assist of discrete wavelet transforms (DWT) and maximal overlap discrete wavelet transform (MODWT) will be used to pinpoint special characteristics of Bursa Malaysia KLCI (Kuala Lumpur Composite Index) daily closing prices and return values. In addition, further case study discussions include the modeling of Bursa Malaysia KLCI using linear ARIMA with wavelets to address how multiresolution approach improves fitting and forecasting results.

Fourier analysis of time series an introduction

CERN Document Server

Bloomfield, Peter

2000-01-01

A new, revised edition of a yet unrivaled work on frequency domain analysis Long recognized for his unique focus on frequency domain methods for the analysis of time series data as well as for his applied, easy-to-understand approach, Peter Bloomfield brings his well-known 1976 work thoroughly up to date. With a minimum of mathematics and an engaging, highly rewarding style, Bloomfield provides in-depth discussions of harmonic regression, harmonic analysis, complex demodulation, and spectrum analysis. All methods are clearly illustrated using examples of specific data sets, while ample

Time series analysis of ozone data in Isfahan

Science.gov (United States)

Omidvari, M.; Hassanzadeh, S.; Hosseinibalam, F.

2008-07-01

Time series analysis used to investigate the stratospheric ozone formation and decomposition processes. Different time series methods are applied to detect the reason for extreme high ozone concentrations for each season. Data was convert into seasonal component and frequency domain, the latter has been evaluated by using the Fast Fourier Transform (FFT), spectral analysis. The power density spectrum estimated from the ozone data showed peaks at cycle duration of 22, 20, 36, 186, 365 and 40 days. According to seasonal component analysis most fluctuation was in 1999 and 2000, but the least fluctuation was in 2003. The best correlation between ozone and sun radiation was found in 2000. Other variables which are not available cause to this fluctuation in the 1999 and 2001. The trend of ozone is increasing in 1999 and is decreasing in other years.

Multivariate time series analysis with R and financial applications

CERN Document Server

Tsay, Ruey S

2013-01-01

Since the publication of his first book, Analysis of Financial Time Series, Ruey Tsay has become one of the most influential and prominent experts on the topic of time series. Different from the traditional and oftentimes complex approach to multivariate (MV) time series, this sequel book emphasizes structural specification, which results in simplified parsimonious VARMA modeling and, hence, eases comprehension. Through a fundamental balance between theory and applications, the book supplies readers with an accessible approach to financial econometric models and their applications to real-worl

Time series analysis methods and applications for flight data

CERN Document Server

Zhang, Jianye

2017-01-01

This book focuses on different facets of flight data analysis, including the basic goals, methods, and implementation techniques. As mass flight data possesses the typical characteristics of time series, the time series analysis methods and their application for flight data have been illustrated from several aspects, such as data filtering, data extension, feature optimization, similarity search, trend monitoring, fault diagnosis, and parameter prediction, etc. An intelligent information-processing platform for flight data has been established to assist in aircraft condition monitoring, training evaluation and scientific maintenance. The book will serve as a reference resource for people working in aviation management and maintenance, as well as researchers and engineers in the fields of data analysis and data mining.

Time series analysis and its applications with R examples

CERN Document Server

Shumway, Robert H

2017-01-01

The fourth edition of this popular graduate textbook, like its predecessors, presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty. The book is designed as a textbook for graduate level students in the physical, biological, and social sciences and as a graduate level text in statistics. Some parts may also serve as an undergraduate introductory course. Theory and methodology are separated to allow presentations on different levels. In addition to coverage of classical methods of time series regression, ARIMA models, spectral analysis and state-space models, the text includes modern developments including categorical time series analysis, multivariate spectral methods, long memory series, nonli...

Graphical Data Analysis on the Circle: Wrap-Around Time Series Plots for (Interrupted) Time Series Designs.

Science.gov (United States)

Rodgers, Joseph Lee; Beasley, William Howard; Schuelke, Matthew

2014-01-01

Many data structures, particularly time series data, are naturally seasonal, cyclical, or otherwise circular. Past graphical methods for time series have focused on linear plots. In this article, we move graphical analysis onto the circle. We focus on 2 particular methods, one old and one new. Rose diagrams are circular histograms and can be produced in several different forms using the RRose software system. In addition, we propose, develop, illustrate, and provide software support for a new circular graphical method, called Wrap-Around Time Series Plots (WATS Plots), which is a graphical method useful to support time series analyses in general but in particular in relation to interrupted time series designs. We illustrate the use of WATS Plots with an interrupted time series design evaluating the effect of the Oklahoma City bombing on birthrates in Oklahoma County during the 10 years surrounding the bombing of the Murrah Building in Oklahoma City. We compare WATS Plots with linear time series representations and overlay them with smoothing and error bands. Each method is shown to have advantages in relation to the other; in our example, the WATS Plots more clearly show the existence and effect size of the fertility differential.

Evaluation of Adherence to Nutritional Intervention Through Trajectory Analysis.

Science.gov (United States)

Sevilla-Villanueva, B; Gibert, K; Sanchez-Marre, M; Fito, M; Covas, M I

2017-05-01

Classical pre-post intervention studies are often analyzed using traditional statistics. Nevertheless, the nutritional interventions have small effects on the metabolism and traditional statistics are not enough to detect these subtle nutrient effects. Generally, this kind of studies assumes that the participants are adhered to the assigned dietary intervention and directly analyzes its effects over the target parameters. Thus, the evaluation of adherence is generally omitted. Although, sometimes, participants do not effectively adhere to the assigned dietary guidelines. For this reason, the trajectory map is proposed as a visual tool where dietary patterns of individuals can be followed during the intervention and can also be related with nutritional prescriptions. The trajectory analysis is also proposed allowing both analysis: 1) adherence to the intervention and 2) intervention effects. The analysis is made by projecting the differences of the target parameters over the resulting trajectories between states of different time-stamps which might be considered either individually or by groups. The proposal has been applied over a real nutritional study showing that some individuals adhere better than others and some individuals of the control group modify their habits during the intervention. In addition, the intervention effects are different depending on the type of individuals, even some subgroups have opposite response to the same intervention.

Transition of chaotic motion to a limit cycle by intervention of economic policy: an empirical analysis in agriculture.

Science.gov (United States)

Sakai, Kenshi; Managi, Shunsuke; Vitanov, Nikolay K; Demura, Katsuhiko

2007-04-01

This paper investigates the transition of dynamics observed in an actual real agricultural economic dataset. Lyapunov spectrum analysis is conducted on the data to distinguish deterministic chaos and the limit cycle. Chaotic and periodic oscillation were identified before and after the second oil crisis, respectively. The statitonarity of the time series is investigated using recurrence plots. This shows that government intervention might reduce market instability by removing a chaotic market's long-term unpredictability.

A taylor series approach to survival analysis

International Nuclear Information System (INIS)

Brodsky, J.B.; Groer, P.G.

1984-09-01

A method of survival analysis using hazard functions is developed. The method uses the well known mathematical theory for Taylor Series. Hypothesis tests of the adequacy of many statistical models, including proportional hazards and linear and/or quadratic dose responses, are obtained. A partial analysis of leukemia mortality in the Life Span Study cohort is used as an example. Furthermore, a relatively robust estimation procedure for the proportional hazards model is proposed. (author)

Forecast models for suicide: Time-series analysis with data from Italy.

Science.gov (United States)

Preti, Antonio; Lentini, Gianluca

2016-01-01

The prediction of suicidal behavior is a complex task. To fine-tune targeted preventative interventions, predictive analytics (i.e. forecasting future risk of suicide) is more important than exploratory data analysis (pattern recognition, e.g. detection of seasonality in suicide time series). This study sets out to investigate the accuracy of forecasting models of suicide for men and women. A total of 101 499 male suicides and of 39 681 female suicides - occurred in Italy from 1969 to 2003 - were investigated. In order to apply the forecasting model and test its accuracy, the time series were split into a training set (1969 to 1996; 336 months) and a test set (1997 to 2003; 84 months). The main outcome was the accuracy of forecasting models on the monthly number of suicides. These measures of accuracy were used: mean absolute error; root mean squared error; mean absolute percentage error; mean absolute scaled error. In both male and female suicides a change in the trend pattern was observed, with an increase from 1969 onwards to reach a maximum around 1990 and decrease thereafter. The variances attributable to the seasonal and trend components were, respectively, 24% and 64% in male suicides, and 28% and 41% in female ones. Both annual and seasonal historical trends of monthly data contributed to forecast future trends of suicide with a margin of error around 10%. The finding is clearer in male than in female time series of suicide. The main conclusion of the study is that models taking seasonality into account seem to be able to derive information on deviation from the mean when this occurs as a zenith, but they fail to reproduce it when it occurs as a nadir. Preventative efforts should concentrate on the factors that influence the occurrence of increases above the main trend in both seasonal and cyclic patterns of suicides.

Time series analysis as input for clinical predictive modeling: modeling cardiac arrest in a pediatric ICU.

Science.gov (United States)

Kennedy, Curtis E; Turley, James P

2011-10-24

Thousands of children experience cardiac arrest events every year in pediatric intensive care units. Most of these children die. Cardiac arrest prediction tools are used as part of medical emergency team evaluations to identify patients in standard hospital beds that are at high risk for cardiac arrest. There are no models to predict cardiac arrest in pediatric intensive care units though, where the risk of an arrest is 10 times higher than for standard hospital beds. Current tools are based on a multivariable approach that does not characterize deterioration, which often precedes cardiac arrests. Characterizing deterioration requires a time series approach. The purpose of this study is to propose a method that will allow for time series data to be used in clinical prediction models. Successful implementation of these methods has the potential to bring arrest prediction to the pediatric intensive care environment, possibly allowing for interventions that can save lives and prevent disabilities. We reviewed prediction models from nonclinical domains that employ time series data, and identified the steps that are necessary for building predictive models using time series clinical data. We illustrate the method by applying it to the specific case of building a predictive model for cardiac arrest in a pediatric intensive care unit. Time course analysis studies from genomic analysis provided a modeling template that was compatible with the steps required to develop a model from clinical time series data. The steps include: 1) selecting candidate variables; 2) specifying measurement parameters; 3) defining data format; 4) defining time window duration and resolution; 5) calculating latent variables for candidate variables not directly measured; 6) calculating time series features as latent variables; 7) creating data subsets to measure model performance effects attributable to various classes of candidate variables; 8) reducing the number of candidate features; 9

Lecture notes for Advanced Time Series Analysis

DEFF Research Database (Denmark)

Madsen, Henrik; Holst, Jan

1997-01-01

A first version of this notes was used at the lectures in Grenoble, and they are now extended and improved (together with Jan Holst), and used in Ph.D. courses on Advanced Time Series Analysis at IMM and at the Department of Mathematical Statistics, University of Lund, 1994, 1997, ...

AHRQ series on complex intervention systematic reviews-paper 7: PRISMA-CI elaboration and explanation.

Science.gov (United States)

Guise, Jeanne-Marie; Butler, Mary; Chang, Christine; Viswanathan, Meera; Pigott, Terri; Tugwell, Peter

2017-10-01

Complex interventions are widely used in health care, public health, education, criminology, social work, business, and welfare. They have increasingly become the subject of systematic reviews and are challenging to effectively report. The Complex Interventions Methods Workgroup developed an extension to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Complex Interventions (PRISMA-CI). Following the EQUATOR Network guidance for Preferred Reporting Items for Systematic Reviews and Meta-Analysis extensions, this Explanation and Elaboration (EE) document accompanies the PRISMA-CI checklist to promote consistency in reporting of systematic reviews of complex interventions. The EE document explains the meaning and rationale for each unique PRISMA-CI checklist item and provides examples to assist systematic review authors in operationalizing PRISMA-CI guidance. The Complex Interventions Workgroup developed PRISMA-CI as an important start toward increased consistency in reporting of systematic reviews of complex interventions. Because the field is rapidly expanding, the Complex Interventions Methods Workgroup plans to re-evaluate periodically for the need to add increasing specificity and examples as the field matures. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Multiscale multifractal multiproperty analysis of financial time series based on Rényi entropy

Science.gov (United States)

Yujun, Yang; Jianping, Li; Yimei, Yang

This paper introduces a multiscale multifractal multiproperty analysis based on Rényi entropy (3MPAR) method to analyze short-range and long-range characteristics of financial time series, and then applies this method to the five time series of five properties in four stock indices. Combining the two analysis techniques of Rényi entropy and multifractal detrended fluctuation analysis (MFDFA), the 3MPAR method focuses on the curves of Rényi entropy and generalized Hurst exponent of five properties of four stock time series, which allows us to study more universal and subtle fluctuation characteristics of financial time series. By analyzing the curves of the Rényi entropy and the profiles of the logarithm distribution of MFDFA of five properties of four stock indices, the 3MPAR method shows some fluctuation characteristics of the financial time series and the stock markets. Then, it also shows a richer information of the financial time series by comparing the profile of five properties of four stock indices. In this paper, we not only focus on the multifractality of time series but also the fluctuation characteristics of the financial time series and subtle differences in the time series of different properties. We find that financial time series is far more complex than reported in some research works using one property of time series.

Intervention analysis of introduction of rotavirus vaccine on hospital admissions rates due to acute diarrhea

Directory of Open Access Journals (Sweden)

Maria de Lourdes Teixeira Masukawa

2014-10-01

Full Text Available The aim of this study is to investigate the impact of rotavirus vaccine on hospitalization rates for acute diarrhea in children younger than 5 years old after the introduction of the vaccine in 2006. A descriptive analytical observational study was carried out of the hospitalization rates occurred between 2000 and 2011 in 22 Regional Health Centers of Paraná State, Brazil. The effect of the vaccine was assessed by applying the SARIMA/Box-Jenkins time series methodology of intervention analysis, which allows verifying the slopes of the series are different after the introduction of the vaccine and estimating the magnitude of these effects for children younger than five years of age, by age group, for each region center. It was verified a statistically significant reduction by center/month on hospitalization rates for children 1 year old and younger, with averages of 47% and 58%, respectively, in December 2011.

End-of-Life Care Interventions: An Economic Analysis.

Science.gov (United States)

Pham, B; Krahn, M

2014-01-01

The annual cost of providing care for patients in their last year of life is estimated to account for approximately 9% of the Ontario health care budget. Access to integrated, comprehensive support and pain/symptom management appears to be inadequate and inequitable. To evaluate the cost-effectiveness of end-of-life (EoL) care interventions included in the EoL care mega-analysis. Multiple sources were used, including systematic reviews, linked health administration databases, survey data, planning documents, expert input, and additional literature searches. We conducted a literature review of cost-effectiveness studies to inform the primary economic analysis. We conducted the primary economic analysis and budget impact analysis for an Ontario cohort of decedents and their families and included interventions pertaining to team-based models of care, patient care planning discussions, educational interventions for patients and caregivers, and supportive interventions for informal caregivers. The time horizon was the last year of life. Costs were in 2013 Canadian dollars. Effectiveness measures included days at home, percentage dying at home, and quality-adjusted life-days. We developed a Markov model; model inputs were obtained from a cohort of Ontario decedents assembled from Institute for Clinical Evaluative Sciences databases and published literature. In-home palliative team care was cost-effective; it increased the chance of dying at home by 10%, increased the average number of days at home (6 days) and quality-adjusted life-days (0.5 days), and it reduced costs by approximately $4,400 per patient. Expanding in-home palliative team care to those currently not receiving such services (approximately 45,000 per year, at an annual cost of $76-108 million) is likely to improve quality of life, reduce the use of acute care resources, and save $191-$385 million in health care costs. Results for the other interventions were uncertain. The cost-effectiveness analysis was

Multichannel biomedical time series clustering via hierarchical probabilistic latent semantic analysis.

Science.gov (United States)

Wang, Jin; Sun, Xiangping; Nahavandi, Saeid; Kouzani, Abbas; Wu, Yuchuan; She, Mary

2014-11-01

Biomedical time series clustering that automatically groups a collection of time series according to their internal similarity is of importance for medical record management and inspection such as bio-signals archiving and retrieval. In this paper, a novel framework that automatically groups a set of unlabelled multichannel biomedical time series according to their internal structural similarity is proposed. Specifically, we treat a multichannel biomedical time series as a document and extract local segments from the time series as words. We extend a topic model, i.e., the Hierarchical probabilistic Latent Semantic Analysis (H-pLSA), which was originally developed for visual motion analysis to cluster a set of unlabelled multichannel time series. The H-pLSA models each channel of the multichannel time series using a local pLSA in the first layer. The topics learned in the local pLSA are then fed to a global pLSA in the second layer to discover the categories of multichannel time series. Experiments on a dataset extracted from multichannel Electrocardiography (ECG) signals demonstrate that the proposed method performs better than previous state-of-the-art approaches and is relatively robust to the variations of parameters including length of local segments and dictionary size. Although the experimental evaluation used the multichannel ECG signals in a biometric scenario, the proposed algorithm is a universal framework for multichannel biomedical time series clustering according to their structural similarity, which has many applications in biomedical time series management. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Time series analysis of barometric pressure data

International Nuclear Information System (INIS)

La Rocca, Paola; Riggi, Francesco; Riggi, Daniele

2010-01-01

Time series of atmospheric pressure data, collected over a period of several years, were analysed to provide undergraduate students with educational examples of application of simple statistical methods of analysis. In addition to basic methods for the analysis of periodicities, a comparison of two forecast models, one based on autoregression algorithms, and the other making use of an artificial neural network, was made. Results show that the application of artificial neural networks may give slightly better results compared to traditional methods.

A lifestyle intervention program for successfully addressing major cardiometabolic risks in persons with SCI: a three-subject case series.

Science.gov (United States)

Bigford, Gregory E; Mendez, Armando J; Betancourt, Luisa; Burns-Drecq, Patricia; Backus, Deborah; Nash, Mark S

2017-01-01

This study is a prospective case series analyzing the effects of a comprehensive lifestyle intervention program in three patients with chronic paraplegia having major risks for the cardiometabolic syndrome (CMS). Individuals underwent an intense 6-month program of circuit resistance exercise, nutrition using a Mediterranean diet and behavioral support, followed by a 6-month extension (maintenance) phase involving minimal support. The primary goal was a 7% reduction of body mass. Other outcomes analyzed insulin resistance using the HOMA-IR model, and plasma levels of fasting triglycerides and high-density lipoprotein cholesterol. All participants achieved the goal for 7% reduction of body mass and maintained the loss after the MP. Improvements were observed in 2/3 subjects for HOMA-IR and high-density lipoprotein cholesterol. All participants improved their risk for plasma triglycerides. We conclude, in a three-person case series of persons with chronic paraplegia, a lifestyle intervention program involving circuit resistance training, a calorie-restrictive Mediterranean-style diet and behavioral support, results in clinically significant loss of body mass and effectively reduced component risks for CMS and diabetes. These results were for the most part maintained after a 6-month MP involving minimal supervision.

Complexity analysis of the turbulent environmental fluid flow time series

Science.gov (United States)

Mihailović, D. T.; Nikolić-Đorić, E.; Drešković, N.; Mimić, G.

2014-02-01

We have used the Kolmogorov complexities, sample and permutation entropies to quantify the randomness degree in river flow time series of two mountain rivers in Bosnia and Herzegovina, representing the turbulent environmental fluid, for the period 1926-1990. In particular, we have examined the monthly river flow time series from two rivers (the Miljacka and the Bosnia) in the mountain part of their flow and then calculated the Kolmogorov complexity (KL) based on the Lempel-Ziv Algorithm (LZA) (lower-KLL and upper-KLU), sample entropy (SE) and permutation entropy (PE) values for each time series. The results indicate that the KLL, KLU, SE and PE values in two rivers are close to each other regardless of the amplitude differences in their monthly flow rates. We have illustrated the changes in mountain river flow complexity by experiments using (i) the data set for the Bosnia River and (ii) anticipated human activities and projected climate changes. We have explored the sensitivity of considered measures in dependence on the length of time series. In addition, we have divided the period 1926-1990 into three subintervals: (a) 1926-1945, (b) 1946-1965, (c) 1966-1990, and calculated the KLL, KLU, SE, PE values for the various time series in these subintervals. It is found that during the period 1946-1965, there is a decrease in their complexities, and corresponding changes in the SE and PE, in comparison to the period 1926-1990. This complexity loss may be primarily attributed to (i) human interventions, after the Second World War, on these two rivers because of their use for water consumption and (ii) climate change in recent times.

Handbook of Time Series Analysis Recent Theoretical Developments and Applications

CERN Document Server

Schelter, Björn; Timmer, Jens

2006-01-01

This handbook provides an up-to-date survey of current research topics and applications of time series analysis methods written by leading experts in their fields. It covers recent developments in univariate as well as bivariate and multivariate time series analysis techniques ranging from physics' to life sciences' applications. Each chapter comprises both methodological aspects and applications to real world complex systems, such as the human brain or Earth's climate. Covering an exceptionally broad spectrum of topics, beginners, experts and practitioners who seek to understand the latest de

Time-series analysis of Nigeria rice supply and demand: Error ...

African Journals Online (AJOL)

The study examined a time-series analysis of Nigeria rice supply and demand with a view to determining any long-run equilibrium between them using the Error Correction Model approach (ECM). The data used for the study represents the annual series of 1960-2007 (47 years) for rice supply and demand in Nigeria, ...

Time Series Factor Analysis with an Application to Measuring Money

NARCIS (Netherlands)

Gilbert, Paul D.; Meijer, Erik

2005-01-01

Time series factor analysis (TSFA) and its associated statistical theory is developed. Unlike dynamic factor analysis (DFA), TSFA obviates the need for explicitly modeling the process dynamics of the underlying phenomena. It also differs from standard factor analysis (FA) in important respects: the

A novel water quality data analysis framework based on time-series data mining.

Science.gov (United States)

Deng, Weihui; Wang, Guoyin

2017-07-01

The rapid development of time-series data mining provides an emerging method for water resource management research. In this paper, based on the time-series data mining methodology, we propose a novel and general analysis framework for water quality time-series data. It consists of two parts: implementation components and common tasks of time-series data mining in water quality data. In the first part, we propose to granulate the time series into several two-dimensional normal clouds and calculate the similarities in the granulated level. On the basis of the similarity matrix, the similarity search, anomaly detection, and pattern discovery tasks in the water quality time-series instance dataset can be easily implemented in the second part. We present a case study of this analysis framework on weekly Dissolve Oxygen time-series data collected from five monitoring stations on the upper reaches of Yangtze River, China. It discovered the relationship of water quality in the mainstream and tributary as well as the main changing patterns of DO. The experimental results show that the proposed analysis framework is a feasible and efficient method to mine the hidden and valuable knowledge from water quality historical time-series data. Copyright © 2017 Elsevier Ltd. All rights reserved.

Case Series.

Science.gov (United States)

Vetrayan, Jayachandran; Othman, Suhana; Victor Paulraj, Smily Jesu Priya

2017-01-01

To assess the effectiveness and feasibility of behavioral sleep intervention for medicated children with ADHD. Six medicated children (five boys, one girl; aged 6-12 years) with ADHD participated in a 4-week sleep intervention program. The main behavioral strategies used were Faded Bedtime With Response Cost (FBRC) and positive reinforcement. Within a case-series design, objective measure (Sleep Disturbance Scale for Children [SDSC]) and subjective measure (sleep diaries) were used to record changes in children's sleep. For all six children, significant decrease was found in the severity of children's sleep problems (based on SDSC data). Bedtime resistance and mean sleep onset latency were reduced following the 4-week intervention program according to sleep diaries data. Gains were generally maintained at the follow-up. Parents perceived the intervention as being helpful. Based on the initial data, this intervention shows promise as an effective and feasible treatment.

Spectral Unmixing Analysis of Time Series Landsat 8 Images

Science.gov (United States)

Zhuo, R.; Xu, L.; Peng, J.; Chen, Y.

2018-05-01

Temporal analysis of Landsat 8 images opens up new opportunities in the unmixing procedure. Although spectral analysis of time series Landsat imagery has its own advantage, it has rarely been studied. Nevertheless, using the temporal information can provide improved unmixing performance when compared to independent image analyses. Moreover, different land cover types may demonstrate different temporal patterns, which can aid the discrimination of different natures. Therefore, this letter presents time series K-P-Means, a new solution to the problem of unmixing time series Landsat imagery. The proposed approach is to obtain the "purified" pixels in order to achieve optimal unmixing performance. The vertex component analysis (VCA) is used to extract endmembers for endmember initialization. First, nonnegative least square (NNLS) is used to estimate abundance maps by using the endmember. Then, the estimated endmember is the mean value of "purified" pixels, which is the residual of the mixed pixel after excluding the contribution of all nondominant endmembers. Assembling two main steps (abundance estimation and endmember update) into the iterative optimization framework generates the complete algorithm. Experiments using both simulated and real Landsat 8 images show that the proposed "joint unmixing" approach provides more accurate endmember and abundance estimation results compared with "separate unmixing" approach.

Nonlinear Time Series Analysis via Neural Networks

Science.gov (United States)

Volná, Eva; Janošek, Michal; Kocian, Václav; Kotyrba, Martin

This article deals with a time series analysis based on neural networks in order to make an effective forex market [Moore and Roche, J. Int. Econ. 58, 387-411 (2002)] pattern recognition. Our goal is to find and recognize important patterns which repeatedly appear in the market history to adapt our trading system behaviour based on them.

Biological time series analysis using a context free language: applicability to pulsatile hormone data.

Directory of Open Access Journals (Sweden)

Dennis A Dean

Full Text Available We present a novel approach for analyzing biological time-series data using a context-free language (CFL representation that allows the extraction and quantification of important features from the time-series. This representation results in Hierarchically AdaPtive (HAP analysis, a suite of multiple complementary techniques that enable rapid analysis of data and does not require the user to set parameters. HAP analysis generates hierarchically organized parameter distributions that allow multi-scale components of the time-series to be quantified and includes a data analysis pipeline that applies recursive analyses to generate hierarchically organized results that extend traditional outcome measures such as pharmacokinetics and inter-pulse interval. Pulsicons, a novel text-based time-series representation also derived from the CFL approach, are introduced as an objective qualitative comparison nomenclature. We apply HAP to the analysis of 24 hours of frequently sampled pulsatile cortisol hormone data, which has known analysis challenges, from 14 healthy women. HAP analysis generated results in seconds and produced dozens of figures for each participant. The results quantify the observed qualitative features of cortisol data as a series of pulse clusters, each consisting of one or more embedded pulses, and identify two ultradian phenotypes in this dataset. HAP analysis is designed to be robust to individual differences and to missing data and may be applied to other pulsatile hormones. Future work can extend HAP analysis to other time-series data types, including oscillatory and other periodic physiological signals.

Growth And Export Expansion In Mauritius - A Time Series Analysis ...

African Journals Online (AJOL)

Growth And Export Expansion In Mauritius - A Time Series Analysis. ... RV Sannassee, R Pearce ... Using Granger Causality tests, the short-run analysis results revealed that there is significant reciprocal causality between real export earnings ...

Transition Icons for Time-Series Visualization and Exploratory Analysis.

Science.gov (United States)

Nickerson, Paul V; Baharloo, Raheleh; Wanigatunga, Amal A; Manini, Todd M; Tighe, Patrick J; Rashidi, Parisa

2018-03-01

The modern healthcare landscape has seen the rapid emergence of techniques and devices that temporally monitor and record physiological signals. The prevalence of time-series data within the healthcare field necessitates the development of methods that can analyze the data in order to draw meaningful conclusions. Time-series behavior is notoriously difficult to intuitively understand due to its intrinsic high-dimensionality, which is compounded in the case of analyzing groups of time series collected from different patients. Our framework, which we call transition icons, renders common patterns in a visual format useful for understanding the shared behavior within groups of time series. Transition icons are adept at detecting and displaying subtle differences and similarities, e.g., between measurements taken from patients receiving different treatment strategies or stratified by demographics. We introduce various methods that collectively allow for exploratory analysis of groups of time series, while being free of distribution assumptions and including simple heuristics for parameter determination. Our technique extracts discrete transition patterns from symbolic aggregate approXimation representations, and compiles transition frequencies into a bag of patterns constructed for each group. These transition frequencies are normalized and aligned in icon form to intuitively display the underlying patterns. We demonstrate the transition icon technique for two time-series datasets-postoperative pain scores, and hip-worn accelerometer activity counts. We believe transition icons can be an important tool for researchers approaching time-series data, as they give rich and intuitive information about collective time-series behaviors.

A likelihood-based time series modeling approach for application in dendrochronology to examine the growth-climate relations and forest disturbance history

Science.gov (United States)

A time series intervention analysis (TSIA) of dendrochronological data to infer the tree growth-climate-disturbance relations and forest disturbance history is described. Maximum likelihood is used to estimate the parameters of a structural time series model with components for ...

Time Series Analysis of Wheat Futures Reward in China

Institute of Scientific and Technical Information of China (English)

无

2005-01-01

Different from the fact that the main researches are focused on single futures contract and lack of the comparison of different periods, this paper described the statistical characteristics of wheat futures reward time series of Zhengzhou Commodity Exchange in recent three years. Besides the basic statistic analysis, the paper used the GARCH and EGARCH model to describe the time series which had the ARCH effect and analyzed the persistence of volatility shocks and the leverage effect. The results showed that compared with that of normal one,wheat futures reward series were abnormality, leptokurtic and thick tail distribution. The study also found that two-part of the reward series had no autocorrelation. Among the six correlative series, three ones presented the ARCH effect. By using of the Auto-regressive Distributed Lag Model, GARCH model and EGARCH model, the paper demonstrates the persistence of volatility shocks and the leverage effect on the wheat futures reward time series. The results reveal that on the one hand, the statistical characteristics of the wheat futures reward are similar to the aboard mature futures market as a whole. But on the other hand, the results reflect some shortages such as the immatureness and the over-control by the government in the Chinese future market.

Topological data analysis of financial time series: Landscapes of crashes

Science.gov (United States)

Gidea, Marian; Katz, Yuri

2018-02-01

We explore the evolution of daily returns of four major US stock market indices during the technology crash of 2000, and the financial crisis of 2007-2009. Our methodology is based on topological data analysis (TDA). We use persistence homology to detect and quantify topological patterns that appear in multidimensional time series. Using a sliding window, we extract time-dependent point cloud data sets, to which we associate a topological space. We detect transient loops that appear in this space, and we measure their persistence. This is encoded in real-valued functions referred to as a 'persistence landscapes'. We quantify the temporal changes in persistence landscapes via their Lp-norms. We test this procedure on multidimensional time series generated by various non-linear and non-equilibrium models. We find that, in the vicinity of financial meltdowns, the Lp-norms exhibit strong growth prior to the primary peak, which ascends during a crash. Remarkably, the average spectral density at low frequencies of the time series of Lp-norms of the persistence landscapes demonstrates a strong rising trend for 250 trading days prior to either dotcom crash on 03/10/2000, or to the Lehman bankruptcy on 09/15/2008. Our study suggests that TDA provides a new type of econometric analysis, which complements the standard statistical measures. The method can be used to detect early warning signals of imminent market crashes. We believe that this approach can be used beyond the analysis of financial time series presented here.

Time series analysis in astronomy: Limits and potentialities

DEFF Research Database (Denmark)

Vio, R.; Kristensen, N.R.; Madsen, Henrik

2005-01-01

In this paper we consider the problem of the limits concerning the physical information that can be extracted from the analysis of one or more time series ( light curves) typical of astrophysical objects. On the basis of theoretical considerations and numerical simulations, we show that with no a...

Multi-granular trend detection for time-series analysis

NARCIS (Netherlands)

van Goethem, A.I.; Staals, F.; Löffler, M.; Dykes, J.; Speckmann, B.

2017-01-01

Time series (such as stock prices) and ensembles (such as model runs for weather forecasts) are two important types of one-dimensional time-varying data. Such data is readily available in large quantities but visual analysis of the raw data quickly becomes infeasible, even for moderately sized data

ESTIMATING RELIABILITY OF DISTURBANCES IN SATELLITE TIME SERIES DATA BASED ON STATISTICAL ANALYSIS

Directory of Open Access Journals (Sweden)

Z.-G. Zhou

2016-06-01

Full Text Available Normally, the status of land cover is inherently dynamic and changing continuously on temporal scale. However, disturbances or abnormal changes of land cover — caused by such as forest fire, flood, deforestation, and plant diseases — occur worldwide at unknown times and locations. Timely detection and characterization of these disturbances is of importance for land cover monitoring. Recently, many time-series-analysis methods have been developed for near real-time or online disturbance detection, using satellite image time series. However, the detection results were only labelled with “Change/ No change” by most of the present methods, while few methods focus on estimating reliability (or confidence level of the detected disturbances in image time series. To this end, this paper propose a statistical analysis method for estimating reliability of disturbances in new available remote sensing image time series, through analysis of full temporal information laid in time series data. The method consists of three main steps. (1 Segmenting and modelling of historical time series data based on Breaks for Additive Seasonal and Trend (BFAST. (2 Forecasting and detecting disturbances in new time series data. (3 Estimating reliability of each detected disturbance using statistical analysis based on Confidence Interval (CI and Confidence Levels (CL. The method was validated by estimating reliability of disturbance regions caused by a recent severe flooding occurred around the border of Russia and China. Results demonstrated that the method can estimate reliability of disturbances detected in satellite image with estimation error less than 5% and overall accuracy up to 90%.

Time series analysis of nuclear instrumentation in EBR-II

International Nuclear Information System (INIS)

Imel, G.R.

1996-01-01

Results of a time series analysis of the scaler count data from the 3 wide range nuclear detectors in the Experimental Breeder Reactor-II are presented. One of the channels was replaced, and it was desired to determine if there was any statistically significant change (ie, improvement) in the channel's response after the replacement. Data were collected from all 3 channels for 16-day periods before and after detector replacement. Time series analysis and statistical tests showed that there was no significant change after the detector replacement. Also, there were no statistically significant differences among the 3 channels, either before or after the replacement. Finally, it was determined that errors in the reactivity change inferred from subcritical count monitoring during fuel handling would be on the other of 20-30 cents for single count intervals

Visualization of Time-Series Sensor Data to Inform the Design of Just-In-Time Adaptive Stress Interventions.

Science.gov (United States)

Sharmin, Moushumi; Raij, Andrew; Epstien, David; Nahum-Shani, Inbal; Beck, J Gayle; Vhaduri, Sudip; Preston, Kenzie; Kumar, Santosh

2015-09-01

We investigate needs, challenges, and opportunities in visualizing time-series sensor data on stress to inform the design of just-in-time adaptive interventions (JITAIs). We identify seven key challenges: massive volume and variety of data, complexity in identifying stressors, scalability of space, multifaceted relationship between stress and time, a need for representation at multiple granularities, interperson variability, and limited understanding of JITAI design requirements due to its novelty. We propose four new visualizations based on one million minutes of sensor data (n=70). We evaluate our visualizations with stress researchers (n=6) to gain first insights into its usability and usefulness in JITAI design. Our results indicate that spatio-temporal visualizations help identify and explain between- and within-person variability in stress patterns and contextual visualizations enable decisions regarding the timing, content, and modality of intervention. Interestingly, a granular representation is considered informative but noise-prone; an abstract representation is the preferred starting point for designing JITAIs.

Multivariate stochastic analysis for Monthly hydrological time series at Cuyahoga River Basin

Science.gov (United States)

zhang, L.

2011-12-01

Copula has become a very powerful statistic and stochastic methodology in case of the multivariate analysis in Environmental and Water resources Engineering. In recent years, the popular one-parameter Archimedean copulas, e.g. Gumbel-Houggard copula, Cook-Johnson copula, Frank copula, the meta-elliptical copula, e.g. Gaussian Copula, Student-T copula, etc. have been applied in multivariate hydrological analyses, e.g. multivariate rainfall (rainfall intensity, duration and depth), flood (peak discharge, duration and volume), and drought analyses (drought length, mean and minimum SPI values, and drought mean areal extent). Copula has also been applied in the flood frequency analysis at the confluences of river systems by taking into account the dependence among upstream gauge stations rather than by using the hydrological routing technique. In most of the studies above, the annual time series have been considered as stationary signal which the time series have been assumed as independent identically distributed (i.i.d.) random variables. But in reality, hydrological time series, especially the daily and monthly hydrological time series, cannot be considered as i.i.d. random variables due to the periodicity existed in the data structure. Also, the stationary assumption is also under question due to the Climate Change and Land Use and Land Cover (LULC) change in the fast years. To this end, it is necessary to revaluate the classic approach for the study of hydrological time series by relaxing the stationary assumption by the use of nonstationary approach. Also as to the study of the dependence structure for the hydrological time series, the assumption of same type of univariate distribution also needs to be relaxed by adopting the copula theory. In this paper, the univariate monthly hydrological time series will be studied through the nonstationary time series analysis approach. The dependence structure of the multivariate monthly hydrological time series will be

Time series analysis in chaotic diode resonator circuit

Energy Technology Data Exchange (ETDEWEB)

Hanias, M.P. [TEI of Chalkis, GR 34400, Evia, Chalkis (Greece)] e-mail: mhanias@teihal.gr; Giannaris, G. [TEI of Chalkis, GR 34400, Evia, Chalkis (Greece); Spyridakis, A. [TEI of Chalkis, GR 34400, Evia, Chalkis (Greece); Rigas, A. [TEI of Chalkis, GR 34400, Evia, Chalkis (Greece)

2006-01-01

A diode resonator chaotic circuit is presented. Multisim is used to simulate the circuit and show the presence of chaos. Time series analysis performed by the method proposed by Grasberger and Procaccia. The correlation and minimum embedding dimension {nu} and m {sub min}, respectively, were calculated. Also the corresponding Kolmogorov entropy was calculated.

Time series analysis in chaotic diode resonator circuit

International Nuclear Information System (INIS)

Hanias, M.P.; Giannaris, G.; Spyridakis, A.; Rigas, A.

2006-01-01

A diode resonator chaotic circuit is presented. Multisim is used to simulate the circuit and show the presence of chaos. Time series analysis performed by the method proposed by Grasberger and Procaccia. The correlation and minimum embedding dimension ν and m min , respectively, were calculated. Also the corresponding Kolmogorov entropy was calculated

Notes on economic time series analysis system theoretic perspectives

CERN Document Server

Aoki, Masanao

1983-01-01

In seminars and graduate level courses I have had several opportunities to discuss modeling and analysis of time series with economists and economic graduate students during the past several years. These experiences made me aware of a gap between what economic graduate students are taught about vector-valued time series and what is available in recent system literature. Wishing to fill or narrow the gap that I suspect is more widely spread than my personal experiences indicate, I have written these notes to augment and reor­ ganize materials I have given in these courses and seminars. I have endeavored to present, in as much a self-contained way as practicable, a body of results and techniques in system theory that I judge to be relevant and useful to economists interested in using time series in their research. I have essentially acted as an intermediary and interpreter of system theoretic results and perspectives in time series by filtering out non-essential details, and presenting coherent accounts of wha...

Correlation between detrended fluctuation analysis and the Lempel-Ziv complexity in nonlinear time series analysis

International Nuclear Information System (INIS)

Tang You-Fu; Liu Shu-Lin; Jiang Rui-Hong; Liu Ying-Hui

2013-01-01

We study the correlation between detrended fluctuation analysis (DFA) and the Lempel-Ziv complexity (LZC) in nonlinear time series analysis in this paper. Typical dynamic systems including a logistic map and a Duffing model are investigated. Moreover, the influence of Gaussian random noise on both the DFA and LZC are analyzed. The results show a high correlation between the DFA and LZC, which can quantify the non-stationarity and the nonlinearity of the time series, respectively. With the enhancement of the random component, the exponent a and the normalized complexity index C show increasing trends. In addition, C is found to be more sensitive to the fluctuation in the nonlinear time series than α. Finally, the correlation between the DFA and LZC is applied to the extraction of vibration signals for a reciprocating compressor gas valve, and an effective fault diagnosis result is obtained

A Markovian Entropy Measure for the Analysis of Calcium Activity Time Series.

Science.gov (United States)

Marken, John P; Halleran, Andrew D; Rahman, Atiqur; Odorizzi, Laura; LeFew, Michael C; Golino, Caroline A; Kemper, Peter; Saha, Margaret S

2016-01-01

Methods to analyze the dynamics of calcium activity often rely on visually distinguishable features in time series data such as spikes, waves, or oscillations. However, systems such as the developing nervous system display a complex, irregular type of calcium activity which makes the use of such methods less appropriate. Instead, for such systems there exists a class of methods (including information theoretic, power spectral, and fractal analysis approaches) which use more fundamental properties of the time series to analyze the observed calcium dynamics. We present a new analysis method in this class, the Markovian Entropy measure, which is an easily implementable calcium time series analysis method which represents the observed calcium activity as a realization of a Markov Process and describes its dynamics in terms of the level of predictability underlying the transitions between the states of the process. We applied our and other commonly used calcium analysis methods on a dataset from Xenopus laevis neural progenitors which displays irregular calcium activity and a dataset from murine synaptic neurons which displays activity time series that are well-described by visually-distinguishable features. We find that the Markovian Entropy measure is able to distinguish between biologically distinct populations in both datasets, and that it can separate biologically distinct populations to a greater extent than other methods in the dataset exhibiting irregular calcium activity. These results support the benefit of using the Markovian Entropy measure to analyze calcium dynamics, particularly for studies using time series data which do not exhibit easily distinguishable features.

A Markovian Entropy Measure for the Analysis of Calcium Activity Time Series.

Directory of Open Access Journals (Sweden)

John P Marken

Full Text Available Methods to analyze the dynamics of calcium activity often rely on visually distinguishable features in time series data such as spikes, waves, or oscillations. However, systems such as the developing nervous system display a complex, irregular type of calcium activity which makes the use of such methods less appropriate. Instead, for such systems there exists a class of methods (including information theoretic, power spectral, and fractal analysis approaches which use more fundamental properties of the time series to analyze the observed calcium dynamics. We present a new analysis method in this class, the Markovian Entropy measure, which is an easily implementable calcium time series analysis method which represents the observed calcium activity as a realization of a Markov Process and describes its dynamics in terms of the level of predictability underlying the transitions between the states of the process. We applied our and other commonly used calcium analysis methods on a dataset from Xenopus laevis neural progenitors which displays irregular calcium activity and a dataset from murine synaptic neurons which displays activity time series that are well-described by visually-distinguishable features. We find that the Markovian Entropy measure is able to distinguish between biologically distinct populations in both datasets, and that it can separate biologically distinct populations to a greater extent than other methods in the dataset exhibiting irregular calcium activity. These results support the benefit of using the Markovian Entropy measure to analyze calcium dynamics, particularly for studies using time series data which do not exhibit easily distinguishable features.

Sensitivity analysis of machine-learning models of hydrologic time series

Science.gov (United States)

O'Reilly, A. M.

2017-12-01

Sensitivity analysis traditionally has been applied to assessing model response to perturbations in model parameters, where the parameters are those model input variables adjusted during calibration. Unlike physics-based models where parameters represent real phenomena, the equivalent of parameters for machine-learning models are simply mathematical "knobs" that are automatically adjusted during training/testing/verification procedures. Thus the challenge of extracting knowledge of hydrologic system functionality from machine-learning models lies in their very nature, leading to the label "black box." Sensitivity analysis of the forcing-response behavior of machine-learning models, however, can provide understanding of how the physical phenomena represented by model inputs affect the physical phenomena represented by model outputs.As part of a previous study, hybrid spectral-decomposition artificial neural network (ANN) models were developed to simulate the observed behavior of hydrologic response contained in multidecadal datasets of lake water level, groundwater level, and spring flow. Model inputs used moving window averages (MWA) to represent various frequencies and frequency-band components of time series of rainfall and groundwater use. Using these forcing time series, the MWA-ANN models were trained to predict time series of lake water level, groundwater level, and spring flow at 51 sites in central Florida, USA. A time series of sensitivities for each MWA-ANN model was produced by perturbing forcing time-series and computing the change in response time-series per unit change in perturbation. Variations in forcing-response sensitivities are evident between types (lake, groundwater level, or spring), spatially (among sites of the same type), and temporally. Two generally common characteristics among sites are more uniform sensitivities to rainfall over time and notable increases in sensitivities to groundwater usage during significant drought periods.

Meta-Analysis of Workplace Physical Activity Interventions

Science.gov (United States)

Conn, Vicki S.; Hafdahl, Adam R.; Cooper, Pamela S.; Brown, Lori M.; Lusk, Sally L.

2009-01-01

Context Most adults do not achieve adequate physical activity. Despite the potential benefits of worksite health promotion, no previous comprehensive meta-analysis has summarized health and physical activity behavior outcomes from these programs. This comprehensive meta-analysis integrated the extant wide range of worksite physical activity intervention research. Evidence acquisition Extensive searching located published and unpublished intervention studies reported from 1969 through 2007. Results were coded from primary studies. Random-effects meta-analytic procedures, including moderator analyses, were completed in 2008. Evidence synthesis Effects on most variables were substantially heterogeneous because diverse studies were included. Standardized mean difference (d) effect sizes were synthesized across approximately 38,231 subjects. Significantly positive effects were observed for physical activity behavior (0.21), fitness (0.57), lipids (0.13), anthropometric measures (0.08), work attendance (0.19), and job stress (0.33). The significant effect size for diabetes risk (0.98) is more tentative given small sample sizes. Significant heterogeneity documents intervention effects varied across studies. The mean effect size for fitness corresponds to a difference between treatment minus control subjects' means on V02max of 3.5 mL/kg/min; for lipids, −0.2 on total cholesterol:HDL; and for diabetes risk, −12.6 mg/dL on fasting glucose. Conclusions These findings document that some workplace physical activity interventions can improve both health and important worksite outcomes. Effects were variable for most outcomes, reflecting the diversity of primary studies. Future primary research should compare interventions to confirm causal relationships and further explore heterogeneity. PMID:19765506

Radiation exposure in CT-guided interventions

Energy Technology Data Exchange (ETDEWEB)

Kloeckner, Roman, E-mail: Roman.Kloeckner@unimedizin-mainz.de [Department of Diagnostic and Interventional Radiology, Johannes Gutenberg-University, Langenbeckstraße 1, 55131 Mainz (Germany); Santos, Daniel Pinto dos; Schneider, Jens [Department of Diagnostic and Interventional Radiology, Johannes Gutenberg-University, Langenbeckstraße 1, 55131 Mainz (Germany); Kara, Levent [Department of Radiology, Inselspital Bern, Freiburgstraße 18, 3010 Bern (Switzerland); Dueber, Christoph; Pitton, Michael B. [Department of Diagnostic and Interventional Radiology, Johannes Gutenberg-University, Langenbeckstraße 1, 55131 Mainz (Germany)

2013-12-01

Purpose: To investigate radiation exposure in computed tomography (CT)-guided interventions, to establish reference levels for exposure, and to discuss strategies for dose reduction. Materials and methods: We analyzed 1576 consecutive CT-guided procedures in 1284 patients performed over 4.5 years, including drainage placements; biopsies of different organs; radiofrequency and microwave ablations (RFA/MWA) of liver, bone, and lung tumors; pain blockages, and vertebroplasties. Data were analyzed with respect to scanner settings, overall radiation doses, and individual doses of planning CT series, CT intervention, and control CT series. Results: Eighy-five percent of the total radiation dose was applied during the pre- and post-interventional CT series, leaving only 15% applied by the CT-guided intervention itself. Single slice acquisition was associated with lower doses than continuous CT-fluoroscopy (37 mGy cm vs. 153 mGy cm, p < 0.001). The third quartile of radiation doses varied considerably for different interventions. The highest doses were observed in complex interventions like RFA/MWA of the liver, followed by vertebroplasty and RFA/MWA of the lung. Conclusions: This paper suggests preliminary reference levels for various intervention types and discusses strategies for dose reduction. A multicenter registry of radiation exposure including a broader spectrum of scanners and intervention types is needed to develop definitive reference levels.

Mapping air temperature using time series analysis of LST : The SINTESI approach

NARCIS (Netherlands)

Alfieri, S.M.; De Lorenzi, F.; Menenti, M.

2013-01-01

This paper presents a new procedure to map time series of air temperature (Ta) at fine spatial resolution using time series analysis of satellite-derived land surface temperature (LST) observations. The method assumes that air temperature is known at a single (reference) location such as in gridded

Time Series Data Analysis of Wireless Sensor Network Measurements of Temperature.

Science.gov (United States)

Bhandari, Siddhartha; Bergmann, Neil; Jurdak, Raja; Kusy, Branislav

2017-05-26

Wireless sensor networks have gained significant traction in environmental signal monitoring and analysis. The cost or lifetime of the system typically depends on the frequency at which environmental phenomena are monitored. If sampling rates are reduced, energy is saved. Using empirical datasets collected from environmental monitoring sensor networks, this work performs time series analyses of measured temperature time series. Unlike previous works which have concentrated on suppressing the transmission of some data samples by time-series analysis but still maintaining high sampling rates, this work investigates reducing the sampling rate (and sensor wake up rate) and looks at the effects on accuracy. Results show that the sampling period of the sensor can be increased up to one hour while still allowing intermediate and future states to be estimated with interpolation RMSE less than 0.2 °C and forecasting RMSE less than 1 °C.

The physiology analysis system: an integrated approach for warehousing, management and analysis of time-series physiology data.

Science.gov (United States)

McKenna, Thomas M; Bawa, Gagandeep; Kumar, Kamal; Reifman, Jaques

2007-04-01

The physiology analysis system (PAS) was developed as a resource to support the efficient warehousing, management, and analysis of physiology data, particularly, continuous time-series data that may be extensive, of variable quality, and distributed across many files. The PAS incorporates time-series data collected by many types of data-acquisition devices, and it is designed to free users from data management burdens. This Web-based system allows both discrete (attribute) and time-series (ordered) data to be manipulated, visualized, and analyzed via a client's Web browser. All processes occur on a server, so that the client does not have to download data or any application programs, and the PAS is independent of the client's computer operating system. The PAS contains a library of functions, written in different computer languages that the client can add to and use to perform specific data operations. Functions from the library are sequentially inserted into a function chain-based logical structure to construct sophisticated data operators from simple function building blocks, affording ad hoc query and analysis of time-series data. These features support advanced mining of physiology data.

Mathematical methods in time series analysis and digital image processing

CERN Document Server

Kurths, J; Maass, P; Timmer, J

2008-01-01

The aim of this volume is to bring together research directions in theoretical signal and imaging processing developed rather independently in electrical engineering, theoretical physics, mathematics and the computer sciences. In particular, mathematically justified algorithms and methods, the mathematical analysis of these algorithms, and methods as well as the investigation of connections between methods from time series analysis and image processing are reviewed. An interdisciplinary comparison of these methods, drawing upon common sets of test problems from medicine and geophysical/enviromental sciences, is also addressed. This volume coherently summarizes work carried out in the field of theoretical signal and image processing. It focuses on non-linear and non-parametric models for time series as well as on adaptive methods in image processing.

Time-series modeling: applications to long-term finfish monitoring data

International Nuclear Information System (INIS)

Bireley, L.E.

1985-01-01

The growing concern and awareness that developed during the 1970's over the effects that industry had on the environment caused the electric utility industry in particular to develop monitoring programs. These programs generate long-term series of data that are not very amenable to classical normal-theory statistical analysis. The monitoring data collected from three finfish programs (impingement, trawl and seine) at the Millstone Nuclear Power Station were typical of such series and thus were used to develop methodology that used the full extent of the information in the series. The basis of the methodology was classic Box-Jenkins time-series modeling; however, the models also included deterministic components that involved flow, season and time as predictor variables. Time entered into the models as harmonic regression terms. Of the 32 models fitted to finfish catch data, 19 were found to account for more than 70% of the historical variation. The models were than used to forecast finfish catches a year in advance and comparisons were made to actual data. Usually the confidence intervals associated with the forecasts encompassed most of the observed data. The technique can provide the basis for intervention analysis in future impact assessments

Applied time series analysis

CERN Document Server

Woodward, Wayne A; Elliott, Alan C

2011-01-01

""There is scarcely a standard technique that the reader will find left out … this book is highly recommended for those requiring a ready introduction to applicable methods in time series and serves as a useful resource for pedagogical purposes.""-International Statistical Review (2014), 82""Current time series theory for practice is well summarized in this book.""-Emmanuel Parzen, Texas A&M University""What an extraordinary range of topics covered, all very insightfully. I like [the authors'] innovations very much, such as the AR factor table.""-David Findley, U.S. Census Bureau (retired)""…

Fractal analysis and nonlinear forecasting of indoor 222Rn time series

International Nuclear Information System (INIS)

Pausch, G.; Bossew, P.; Hofmann, W.; Steger, F.

1998-01-01

Fractal analyses of indoor 222 Rn time series were performed using different chaos theory based measurements such as time delay method, Hurst's rescaled range analysis, capacity (fractal) dimension, and Lyapunov exponent. For all time series we calculated only positive Lyapunov exponents which is a hint to chaos, while the Hurst exponents were well below 0.5, indicating antipersistent behaviour (past trends tend to reverse in the future). These time series were also analyzed with a nonlinear prediction method which allowed an estimation of the embedding dimensions with some restrictions, limiting the prediction to about three relative time steps. (orig.)

GPS Position Time Series @ JPL

Science.gov (United States)

Owen, Susan; Moore, Angelyn; Kedar, Sharon; Liu, Zhen; Webb, Frank; Heflin, Mike; Desai, Shailen

2013-01-01

Different flavors of GPS time series analysis at JPL - Use same GPS Precise Point Positioning Analysis raw time series - Variations in time series analysis/post-processing driven by different users. center dot JPL Global Time Series/Velocities - researchers studying reference frame, combining with VLBI/SLR/DORIS center dot JPL/SOPAC Combined Time Series/Velocities - crustal deformation for tectonic, volcanic, ground water studies center dot ARIA Time Series/Coseismic Data Products - Hazard monitoring and response focused center dot ARIA data system designed to integrate GPS and InSAR - GPS tropospheric delay used for correcting InSAR - Caltech's GIANT time series analysis uses GPS to correct orbital errors in InSAR - Zhen Liu's talking tomorrow on InSAR Time Series analysis

Using qualitative comparative analysis in a systematic review of a complex intervention.

Science.gov (United States)

Kahwati, Leila; Jacobs, Sara; Kane, Heather; Lewis, Megan; Viswanathan, Meera; Golin, Carol E

2016-05-04

Systematic reviews evaluating complex interventions often encounter substantial clinical heterogeneity in intervention components and implementation features making synthesis challenging. Qualitative comparative analysis (QCA) is a non-probabilistic method that uses mathematical set theory to study complex phenomena; it has been proposed as a potential method to complement traditional evidence synthesis in reviews of complex interventions to identify key intervention components or implementation features that might explain effectiveness or ineffectiveness. The objective of this study was to describe our approach in detail and examine the suitability of using QCA within the context of a systematic review. We used data from a completed systematic review of behavioral interventions to improve medication adherence to conduct two substantive analyses using QCA. The first analysis sought to identify combinations of nine behavior change techniques/components (BCTs) found among effective interventions, and the second analysis sought to identify combinations of five implementation features (e.g., agent, target, mode, time span, exposure) found among effective interventions. For each substantive analysis, we reframed the review's research questions to be designed for use with QCA, calibrated sets (i.e., transformed raw data into data used in analysis), and identified the necessary and/or sufficient combinations of BCTs and implementation features found in effective interventions. Our application of QCA for each substantive analysis is described in detail. We extended the original review findings by identifying seven combinations of BCTs and four combinations of implementation features that were sufficient for improving adherence. We found reasonable alignment between several systematic review steps and processes used in QCA except that typical approaches to study abstraction for some intervention components and features did not support a robust calibration for QCA. QCA was

Ultrasonic image analysis and image-guided interventions.

Science.gov (United States)

Noble, J Alison; Navab, Nassir; Becher, H

2011-08-06

The fields of medical image analysis and computer-aided interventions deal with reducing the large volume of digital images (X-ray, computed tomography, magnetic resonance imaging (MRI), positron emission tomography and ultrasound (US)) to more meaningful clinical information using software algorithms. US is a core imaging modality employed in these areas, both in its own right and used in conjunction with the other imaging modalities. It is receiving increased interest owing to the recent introduction of three-dimensional US, significant improvements in US image quality, and better understanding of how to design algorithms which exploit the unique strengths and properties of this real-time imaging modality. This article reviews the current state of art in US image analysis and its application in image-guided interventions. The article concludes by giving a perspective from clinical cardiology which is one of the most advanced areas of clinical application of US image analysis and describing some probable future trends in this important area of ultrasonic imaging research.

The Photoplethismographic Signal Processed with Nonlinear Time Series Analysis Tools

International Nuclear Information System (INIS)

Hernandez Caceres, Jose Luis; Hong, Rolando; Garcia Lanz, Abel; Garcia Dominguez, Luis; Cabannas, Karelia

2001-01-01

Finger photoplethismography (PPG) signals were submitted to nonlinear time series analysis. The applied analytical techniques were: (i) High degree polynomial fitting for baseline estimation; (ii) FFT analysis for estimating power spectra; (iii) fractal dimension estimation via the Higuchi's time-domain method, and (iv) kernel nonparametric estimation for reconstructing noise free-attractors and also for estimating signal's stochastic components

Multi-Scale Entropy Analysis as a Method for Time-Series Analysis of Climate Data

Directory of Open Access Journals (Sweden)

Heiko Balzter

2015-03-01

Full Text Available Evidence is mounting that the temporal dynamics of the climate system are changing at the same time as the average global temperature is increasing due to multiple climate forcings. A large number of extreme weather events such as prolonged cold spells, heatwaves, droughts and floods have been recorded around the world in the past 10 years. Such changes in the temporal scaling behaviour of climate time-series data can be difficult to detect. While there are easy and direct ways of analysing climate data by calculating the means and variances for different levels of temporal aggregation, these methods can miss more subtle changes in their dynamics. This paper describes multi-scale entropy (MSE analysis as a tool to study climate time-series data and to identify temporal scales of variability and their change over time in climate time-series. MSE estimates the sample entropy of the time-series after coarse-graining at different temporal scales. An application of MSE to Central European, variance-adjusted, mean monthly air temperature anomalies (CRUTEM4v is provided. The results show that the temporal scales of the current climate (1960–2014 are different from the long-term average (1850–1960. For temporal scale factors longer than 12 months, the sample entropy increased markedly compared to the long-term record. Such an increase can be explained by systems theory with greater complexity in the regional temperature data. From 1961 the patterns of monthly air temperatures are less regular at time-scales greater than 12 months than in the earlier time period. This finding suggests that, at these inter-annual time scales, the temperature variability has become less predictable than in the past. It is possible that climate system feedbacks are expressed in altered temporal scales of the European temperature time-series data. A comparison with the variance and Shannon entropy shows that MSE analysis can provide additional information on the

Time series analysis of gold production in Malaysia

Science.gov (United States)

Muda, Nora; Hoon, Lee Yuen

2012-05-01

Gold is a soft, malleable, bright yellow metallic element and unaffected by air or most reagents. It is highly valued as an asset or investment commodity and is extensively used in jewellery, industrial application, dentistry and medical applications. In Malaysia, gold mining is limited in several areas such as Pahang, Kelantan, Terengganu, Johor and Sarawak. The main purpose of this case study is to obtain a suitable model for the production of gold in Malaysia. The model can also be used to predict the data of Malaysia's gold production in the future. Box-Jenkins time series method was used to perform time series analysis with the following steps: identification, estimation, diagnostic checking and forecasting. In addition, the accuracy of prediction is tested using mean absolute percentage error (MAPE). From the analysis, the ARIMA (3,1,1) model was found to be the best fitted model with MAPE equals to 3.704%, indicating the prediction is very accurate. Hence, this model can be used for forecasting. This study is expected to help the private and public sectors to understand the gold production scenario and later plan the gold mining activities in Malaysia.

Meta-analysis of workplace physical activity interventions.

Science.gov (United States)

Conn, Vicki S; Hafdahl, Adam R; Cooper, Pamela S; Brown, Lori M; Lusk, Sally L

2009-10-01

Most adults do not achieve adequate physical activity levels. Despite the potential benefits of worksite health promotion, no previous comprehensive meta-analysis has summarized health and physical activity behavior outcomes from such programs. This comprehensive meta-analysis integrated the extant wide range of worksite physical activity intervention research. Extensive searching located published and unpublished intervention studies reported from 1969 through 2007. Results were coded from primary studies. Random-effects meta-analytic procedures, including moderator analyses, were completed in 2008. Effects on most variables were substantially heterogeneous because diverse studies were included. Standardized mean difference (d) effect sizes were synthesized across approximately 38,231 subjects. Significantly positive effects were observed for physical activity behavior (0.21); fitness (0.57); lipids (0.13); anthropometric measures (0.08); work attendance (0.19); and job stress (0.33). The significant effect size for diabetes risk (0.98) is less robust given small sample sizes. The mean effect size for fitness corresponds to a difference between treatment minus control subjects' means on VO2max of 3.5 mL/kg/min; for lipids, -0.2 on the ratio of total cholesterol to high-density lipoprotein; and for diabetes risk, -12.6 mg/dL on fasting glucose. These findings document that some workplace physical activity interventions can improve both health and important worksite outcomes. Effects were variable for most outcomes, reflecting the diversity of primary studies. Future primary research should compare interventions to confirm causal relationships and further explore heterogeneity.

Thankful for the little things: A meta-analysis of gratitude interventions.

Science.gov (United States)

Davis, Don E; Choe, Elise; Meyers, Joel; Wade, Nathaniel; Varjas, Kristen; Gifford, Allison; Quinn, Amy; Hook, Joshua N; Van Tongeren, Daryl R; Griffin, Brandon J; Worthington, Everett L

2016-01-01

A recent qualitative review by Wood, Froh, and Geraghty (2010) cast doubt on the efficacy of gratitude interventions, suggesting the need to carefully attend to the quality of comparison groups. Accordingly, in a series of meta-analyses, we evaluate the efficacy of gratitude interventions (ks = 4-18; Ns = 395-1,755) relative to a measurement-only control or an alternative-activity condition across 3 outcomes (i.e., gratitude, anxiety, psychological well-being). Gratitude interventions outperformed a measurement-only control on measures of psychological well-being (d = .31, 95% confidence interval [CI = .04, .58]; k = 5) but not gratitude (d = .20; 95% CI [-.04, .44]; k = 4). Gratitude interventions outperformed an alternative-activity condition on measures of gratitude (d = .46, 95% CI [.27, .64]; k = 15) and psychological well-being (d = .17, 95% CI [.09, .24]; k = 20) but not anxiety (d = .11, 95% CI [-.08, .31]; k = 5). More-detailed subdivision was possible on studies with outcomes assessing psychological well-being. Among these, gratitude interventions outperformed an activity-matched comparison (d = .14; 95% CI [.01, .27]; k = 18). Gratitude interventions performed as well as, but not better than, a psychologically active comparison (d = -.03, 95% CI [-.13, .07]; k = 9). On the basis of these findings, we summarize the current state of the literature and make suggestions for future applied research on gratitude. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Efficacy of computer technology-based HIV prevention interventions: a meta-analysis.

Science.gov (United States)

Noar, Seth M; Black, Hulda G; Pierce, Larson B

2009-01-02

To conduct a meta-analysis of computer technology-based HIV prevention behavioral interventions aimed at increasing condom use among a variety of at-risk populations. Systematic review and meta-analysis of existing published and unpublished studies testing computer-based interventions. Meta-analytic techniques were used to compute and aggregate effect sizes for 12 randomized controlled trials that met inclusion criteria. Variables that had the potential to moderate intervention efficacy were also tested. The overall mean weighted effect size for condom use was d = 0.259 (95% confidence interval = 0.201, 0.317; Z = 8.74, P partners, and incident sexually transmitted diseases. In addition, interventions were significantly more efficacious when they were directed at men or women (versus mixed sex groups), utilized individualized tailoring, used a Stages of Change model, and had more intervention sessions. Computer technology-based HIV prevention interventions have similar efficacy to more traditional human-delivered interventions. Given their low cost to deliver, ability to customize intervention content, and flexible dissemination channels, they hold much promise for the future of HIV prevention.

Patient doses in interventional cardiology

International Nuclear Information System (INIS)

Carrera, F.; Ojeda, C.; Ruiz-Cruces, R.; Francisco Diaz, J.; Sanchez, A.; Tort, I.

2001-01-01

Cardiovascular diseases are the first cause of death in Spain. The most usual procedures in interventional cardiology are coronariography and PTCA. The first is a diagnostic technique, and the second one is interventional. Our goal has been to study procedures made during the first six months in the Interventional Cardiology Unit of the Juan Ramon Jimenez Hospital (Huelva-Spain), taking into account radiation protection issues. We have studied 178 patients; 145 of them underwent coronariography, and 33 of the patients had PTCA too. Every case was analyzed taking into account technical and dosimetric parameters. We show parameters values gathered: Diagnostic techniques (valvular and non-valvular patients), and interventional techniques (coronariography and PTCA in different or in the same intervention). Higher doses were obtained with valvular patients, although the number of frames was similar. Attending to therapeutic procedures, the highest values were gotten with the 'double' interventions. Interventional procedures exceed in 60% doses gotten in diagnostic studies: this is because of the number of series and number of frames per series. Similar values obtained by other authors have been gotten. (author)

A manual physical therapy intervention for symptoms of knee osteoarthritis and associated fall risk: A case series of four patients.

Science.gov (United States)

Allen, Chris; Sheehan, Riley; Deyle, Gail; Wilken, Jason; Gill, Norman

2018-02-26

Patients with knee osteoarthritis (OA) are at an increased risk of falling. Further, the symptoms associated with knee OA are correlated with fall risk. A manual physical therapy (MPT) approach consisting of mobilizing techniques and reinforcing exercise improves the symptoms and functional limitations associated with knee OA. The purpose of this case series is to evaluate an MPT intervention of mobilization techniques and exercise for knee OA on improving symptoms and quantify the secondary benefit of improving stumble recovery. Four patients with symptomatic knee OA and four matched controls completed a fall risk assessment. Following 4 weeks of intervention, patients were reevaluated. Initial Western Ontario and McMaster Universities Arthritis Index (WOMAC) scores indicated notable symptoms and functional limitations in all patients. In addition, all patients displayed elevated fall risk and/or impaired stumble responses. Following 4 weeks of intervention, all patients reported meaningful reductions in all three WOMAC subscales and demonstrated improvements in at least two of the three fall risk measures. We identified potential connections between symptom relief in patients with knee OA, stumble response, and ultimately fall risk. The results suggest that MPT intervention designed to improve the signs and symptoms of knee OA may lead to a secondary benefit of improved gait stability and stumble response.

Analysis and implementation of LLC-T series parallel resonant ...

African Journals Online (AJOL)

A prototype 300 W, 100 kHz converter is designed and built to experimentally demonstrate, dynamic and steady state performance for the LLC-T series parallel resonant converter. A comparative study is performed between experimental results and the simulation studies. The analysis shows that the output of converter is ...

A non linear analysis of human gait time series based on multifractal analysis and cross correlations

International Nuclear Information System (INIS)

Munoz-Diosdado, A

2005-01-01

We analyzed databases with gait time series of adults and persons with Parkinson, Huntington and amyotrophic lateral sclerosis (ALS) diseases. We obtained the staircase graphs of accumulated events that can be bounded by a straight line whose slope can be used to distinguish between gait time series from healthy and ill persons. The global Hurst exponent of these series do not show tendencies, we intend that this is because some gait time series have monofractal behavior and others have multifractal behavior so they cannot be characterized with a single Hurst exponent. We calculated the multifractal spectra, obtained the spectra width and found that the spectra of the healthy young persons are almost monofractal. The spectra of ill persons are wider than the spectra of healthy persons. In opposition to the interbeat time series where the pathology implies loss of multifractality, in the gait time series the multifractal behavior emerges with the pathology. Data were collected from healthy and ill subjects as they walked in a roughly circular path and they have sensors in both feet, so we have one time series for the left foot and other for the right foot. First, we analyzed these time series separately, and then we compared both results, with direct comparison and with a cross correlation analysis. We tried to find differences in both time series that can be used as indicators of equilibrium problems

A non linear analysis of human gait time series based on multifractal analysis and cross correlations

Energy Technology Data Exchange (ETDEWEB)

Munoz-Diosdado, A [Department of Mathematics, Unidad Profesional Interdisciplinaria de Biotecnologia, Instituto Politecnico Nacional, Av. Acueducto s/n, 07340, Mexico City (Mexico)

2005-01-01

We analyzed databases with gait time series of adults and persons with Parkinson, Huntington and amyotrophic lateral sclerosis (ALS) diseases. We obtained the staircase graphs of accumulated events that can be bounded by a straight line whose slope can be used to distinguish between gait time series from healthy and ill persons. The global Hurst exponent of these series do not show tendencies, we intend that this is because some gait time series have monofractal behavior and others have multifractal behavior so they cannot be characterized with a single Hurst exponent. We calculated the multifractal spectra, obtained the spectra width and found that the spectra of the healthy young persons are almost monofractal. The spectra of ill persons are wider than the spectra of healthy persons. In opposition to the interbeat time series where the pathology implies loss of multifractality, in the gait time series the multifractal behavior emerges with the pathology. Data were collected from healthy and ill subjects as they walked in a roughly circular path and they have sensors in both feet, so we have one time series for the left foot and other for the right foot. First, we analyzed these time series separately, and then we compared both results, with direct comparison and with a cross correlation analysis. We tried to find differences in both time series that can be used as indicators of equilibrium problems.

Buildings Energy Efficiency: Interventions Analysis under a Smart Cities Approach

Directory of Open Access Journals (Sweden)

Gabriele Battista

2014-07-01

Full Text Available Most of the world’s population lives in urban areas and in inefficient buildings under the energy point of view. Starting from these assumptions, there is the need to identify methodologies and innovations able to improve social development and the quality of life of people living in cities. Smart cities can be a viable solution. The methodology traditionally adopted to evaluate building energy efficiency starts from the structure’s energy demands analysis and the demands reduction evaluation. Consequently, the energy savings is assessed through a cascade of interventions. Regarding the building envelope, the first intervention is usually related to the reduction of the thermal transmittance value, but there is also the need to emphasize the building energy savings through other parameters, such as the solar gain factor and dye solar absorbance coefficients. In this contribution, a standard building has been modeled by means of the well-known dynamic software, TRNSYS. This study shows a parametrical analysis through which it is possible to evaluate the effect of each single intervention and, consequently, its influence on the building energy demand. Through this analysis, an intervention chart has been carried out, aiming to assess the intervention efficiency starting from the percentage variation of energy demands.

Selection and Evaluation of Media for Behavioral Health Interventions Employing Critical Media Analysis.

Science.gov (United States)

Wilson, Patrick A; Cherenack, Emily M; Jadwin-Cakmak, Laura; Harper, Gary W

2018-01-01

Although a growing number of psychosocial health promotion interventions use the critical analysis of media to facilitate behavior change, no specific guidelines exist to assist researchers and practitioners in the selection and evaluation of culturally relevant media stimuli for intervention development. Mobilizing Our Voices for Empowerment is a critical consciousness-based health enhancement intervention for HIV-positive Black young gay/bisexual men that employs the critical analysis of popular media. In the process of developing and testing this intervention, feedback on media stimuli was collected from youth advisory board members (n = 8), focus group participants (n = 19), intervention participants (n = 40), and intervention facilitators (n = 6). A thematic analysis of qualitative data resulted in the identification of four key attributes of media stimuli and participants' responses to media stimuli that are important to consider when selecting and evaluating media stimuli for use in behavioral health interventions employing the critical analysis of media: comprehension, relevance, emotionality, and action. These four attributes are defined and presented as a framework for evaluating media, and adaptable tools are provided based on this framework to guide researchers and practitioners in the selection and evaluation of media for similar interventions.

Intervention Analysis of Nigeria's Foreign Exchange Rate ...

African Journals Online (AJOL)

ADOWIE PERE

to 2014:12 were used and a number of statistical tools are employed to verify this hypothesis. A useful approach is to ..... Conclusion: We have applied the intervention analysis to model ... Nigerian Journal of Economic and Social studies, Vol.

Game-based digital interventions for depression therapy: a systematic review and meta-analysis.

Science.gov (United States)

Li, Jinhui; Theng, Yin-Leng; Foo, Schubert

2014-08-01

The aim of this study was to review the existing literature on game-based digital interventions for depression systematically and examine their effectiveness through a meta-analysis of randomized controlled trials (RCTs). Database searching was conducted using specific search terms and inclusion criteria. A standard meta-analysis was also conducted of available RCT studies with a random effects model. The standard mean difference (Cohen's d) was used to calculate the effect size of each study. Nineteen studies were included in the review, and 10 RCTs (eight studies) were included in the meta-analysis. Four types of game interventions-psycho-education and training, virtual reality exposure therapy, exercising, and entertainment-were identified, with various types of support delivered and populations targeted. The meta-analysis revealed a moderate effect size of the game interventions for depression therapy at posttreatment (d=-0.47 [95% CI -0.69 to -0.24]). A subgroup analysis showed that interventions based on psycho-education and training had a smaller effect than those based on the other forms, and that self-help interventions yielded better outcomes than supported interventions. A higher effect was achieved when a waiting list was used as the control. The review and meta-analysis support the effectiveness of game-based digital interventions for depression. More large-scale, high-quality RCT studies with sufficient long-term data for treatment evaluation are needed.

The Benefits of Peer Review and a Multisemester Capstone Writing Series on Inquiry and Analysis Skills in an Undergraduate Thesis.

Science.gov (United States)

Weaver, K F; Morales, V; Nelson, M; Weaver, P F; Toledo, A; Godde, K

2016-01-01

This study examines the relationship between the introduction of a four-course writing-intensive capstone series and improvement in inquiry and analysis skills of biology senior undergraduates. To measure the impact of the multicourse write-to-learn and peer-review pedagogy on student performance, we used a modified Valid Assessment of Learning in Undergraduate Education rubric for Inquiry and Analysis and Written Communication to score senior research theses from 2006 to 2008 (pretreatment) and 2009 to 2013 (intervention). A Fisher-Freeman-Halton test and a two-sample Student's t test were used to evaluate individual rubric dimensions and composite rubric scores, respectively, and a randomized complete block design analysis of variance was carried out on composite scores to examine the impact of the intervention across ethnicity, legacy (e.g., first-generation status), and research laboratory. The results show an increase in student performance in rubric scoring categories most closely associated with science literacy and critical-thinking skills, in addition to gains in students' writing abilities. © 2016 K. F. Weaver et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Regression and regression analysis time series prediction modeling on climate data of quetta, pakistan

International Nuclear Information System (INIS)

Jafri, Y.Z.; Kamal, L.

2007-01-01

Various statistical techniques was used on five-year data from 1998-2002 of average humidity, rainfall, maximum and minimum temperatures, respectively. The relationships to regression analysis time series (RATS) were developed for determining the overall trend of these climate parameters on the basis of which forecast models can be corrected and modified. We computed the coefficient of determination as a measure of goodness of fit, to our polynomial regression analysis time series (PRATS). The correlation to multiple linear regression (MLR) and multiple linear regression analysis time series (MLRATS) were also developed for deciphering the interdependence of weather parameters. Spearman's rand correlation and Goldfeld-Quandt test were used to check the uniformity or non-uniformity of variances in our fit to polynomial regression (PR). The Breusch-Pagan test was applied to MLR and MLRATS, respectively which yielded homoscedasticity. We also employed Bartlett's test for homogeneity of variances on a five-year data of rainfall and humidity, respectively which showed that the variances in rainfall data were not homogenous while in case of humidity, were homogenous. Our results on regression and regression analysis time series show the best fit to prediction modeling on climatic data of Quetta, Pakistan. (author)

Time Series Imputation via L1 Norm-Based Singular Spectrum Analysis

Science.gov (United States)

Kalantari, Mahdi; Yarmohammadi, Masoud; Hassani, Hossein; Silva, Emmanuel Sirimal

Missing values in time series data is a well-known and important problem which many researchers have studied extensively in various fields. In this paper, a new nonparametric approach for missing value imputation in time series is proposed. The main novelty of this research is applying the L1 norm-based version of Singular Spectrum Analysis (SSA), namely L1-SSA which is robust against outliers. The performance of the new imputation method has been compared with many other established methods. The comparison is done by applying them to various real and simulated time series. The obtained results confirm that the SSA-based methods, especially L1-SSA can provide better imputation in comparison to other methods.

Analysis of historical series of industrial demand of energy; Analisi delle serie storiche dei consumi energetici dell`industria

Energy Technology Data Exchange (ETDEWEB)

Moauro, F. [ENEA, Centro Ricerche Casaccia, Rome (Italy). Dip. Energia

1995-03-01

This paper reports a short term analysis of the Italian demand for energy fonts and a check of a statistic model supposing the industrial demand for energy fonts as a function of prices and production, according to neoclassic neoclassic micro economic theory. To this pourpose monthly time series of industrial consumption of main energy fonts in 6 sectors, industrial production indexes in the same sectors and indexes of energy prices (coal, natural gas, oil products, electricity) have been used. The statistic methodology refers to modern analysis of time series and specifically to transfer function models. These ones permit rigorous identification and representation of the most important dynamic relations between dependent variables (production and prices), as relation of an input-output system. The results have shown an important positive correlation between energy consumption with prices. Furthermore, it has been shown the reliability of forecasts and their use as monthly energy indicators.

Time Series Analysis of Wheat flour Price Shocks in Pakistan: A Case Analysis

OpenAIRE

Asad Raza Abdi; Ali Hassan Halepoto; Aisha Bashir Shah; Faiz M. Shaikh

2013-01-01

The current research investigates the wheat flour Price Shocks in Pakistan: A case analysis. Data was collected by using secondary sources by using Time series Analysis, and data were analyzed by using SPSS-20 version. It was revealed that the price of wheat flour increases from last four decades, and trend of price shocks shows that due to certain market variation and supply and demand shocks also play a positive relationship in price shocks in the wheat prices. It was further revealed th...

Time series clustering analysis of health-promoting behavior

Science.gov (United States)

Yang, Chi-Ta; Hung, Yu-Shiang; Deng, Guang-Feng

2013-10-01

Health promotion must be emphasized to achieve the World Health Organization goal of health for all. Since the global population is aging rapidly, ComCare elder health-promoting service was developed by the Taiwan Institute for Information Industry in 2011. Based on the Pender health promotion model, ComCare service offers five categories of health-promoting functions to address the everyday needs of seniors: nutrition management, social support, exercise management, health responsibility, stress management. To assess the overall ComCare service and to improve understanding of the health-promoting behavior of elders, this study analyzed health-promoting behavioral data automatically collected by the ComCare monitoring system. In the 30638 session records collected for 249 elders from January, 2012 to March, 2013, behavior patterns were identified by fuzzy c-mean time series clustering algorithm combined with autocorrelation-based representation schemes. The analysis showed that time series data for elder health-promoting behavior can be classified into four different clusters. Each type reveals different health-promoting needs, frequencies, function numbers and behaviors. The data analysis result can assist policymakers, health-care providers, and experts in medicine, public health, nursing and psychology and has been provided to Taiwan National Health Insurance Administration to assess the elder health-promoting behavior.

Cost-Effectiveness Analysis in Practice: Interventions to Improve High School Completion

Science.gov (United States)

Hollands, Fiona; Bowden, A. Brooks; Belfield, Clive; Levin, Henry M.; Cheng, Henan; Shand, Robert; Pan, Yilin; Hanisch-Cerda, Barbara

2014-01-01

In this article, we perform cost-effectiveness analysis on interventions that improve the rate of high school completion. Using the What Works Clearinghouse to select effective interventions, we calculate cost-effectiveness ratios for five youth interventions. We document wide variation in cost-effectiveness ratios between programs and between…

Fractal time series analysis of postural stability in elderly and control subjects

Directory of Open Access Journals (Sweden)

Doussot Michel

2007-05-01

Full Text Available Abstract Background The study of balance using stabilogram analysis is of particular interest in the study of falls. Although simple statistical parameters derived from the stabilogram have been shown to predict risk of falls, such measures offer little insight into the underlying control mechanisms responsible for degradation in balance. In contrast, fractal and non-linear time-series analysis of stabilograms, such as estimations of the Hurst exponent (H, may provide information related to the underlying motor control strategies governing postural stability. In order to be adapted for a home-based follow-up of balance, such methods need to be robust, regardless of the experimental protocol, while producing time-series that are as short as possible. The present study compares two methods of calculating H: Detrended Fluctuation Analysis (DFA and Stabilogram Diffusion Analysis (SDA for elderly and control subjects, as well as evaluating the effect of recording duration. Methods Centre of pressure signals were obtained from 90 young adult subjects and 10 elderly subjects. Data were sampled at 100 Hz for 30 s, including stepping onto and off the force plate. Estimations of H were made using sliding windows of 10, 5, and 2.5 s durations, with windows slid forward in 1-s increments. Multivariate analysis of variance was used to test for the effect of time, age and estimation method on the Hurst exponent, while the intra-class correlation coefficient (ICC was used as a measure of reliability. Results Both SDA and DFA methods were able to identify differences in postural stability between control and elderly subjects for time series as short as 5 s, with ICC values as high as 0.75 for DFA. Conclusion Both methods would be well-suited to non-invasive longitudinal assessment of balance. In addition, reliable estimations of H were obtained from time series as short as 5 s.

Identifying Effective Components of Child Maltreatment Interventions: A Meta-analysis.

Science.gov (United States)

van der Put, Claudia E; Assink, Mark; Gubbels, Jeanne; Boekhout van Solinge, Noëlle F

2018-06-01

There is a lack of knowledge about specific components that make interventions effective in preventing or reducing child maltreatment. The aim of the present meta-analysis was to increase this knowledge by summarizing findings on effects of interventions for child maltreatment and by examining potential moderators of this effect, such as intervention components and study characteristics. Identifying effective components is essential for developing or improving child maltreatment interventions. A literature search yielded 121 independent studies (N = 39,044) examining the effects of interventions for preventing or reducing child maltreatment. From these studies, 352 effect sizes were extracted. The overall effect size was significant and small in magnitude for both preventive interventions (d = 0.26, p child maltreatment. For preventive interventions, larger effect sizes were found for short-term interventions (0-6 months), interventions focusing on increasing self-confidence of parents, and interventions delivered by professionals only. Further, effect sizes of preventive interventions increased as follow-up duration increased, which may indicate a sleeper effect of preventive interventions. For curative interventions, larger effect sizes were found for interventions focusing on improving parenting skills and interventions providing social and/or emotional support. Interventions can be effective in preventing or reducing child maltreatment. Theoretical and practical implications are discussed.

Bayesian near-boundary analysis in basic macroeconomic time series models

NARCIS (Netherlands)

M.D. de Pooter (Michiel); F. Ravazzolo (Francesco); R. Segers (René); H.K. van Dijk (Herman)

2008-01-01

textabstractSeveral lessons learnt from a Bayesian analysis of basic macroeconomic time series models are presented for the situation where some model parameters have substantial posterior probability near the boundary of the parameter region. This feature refers to near-instability within dynamic

A series of studies examining Internet treatment of obesity to inform Internet interventions for substance use and misuse.

Science.gov (United States)

Tate, Deborah F

2011-01-01

The feasibility and efficacy of Internet treatment programs for overweight and obese people have been demonstrated in a series of randomized trials. Initial studies examined various approaches to Internet behavioral treatment. Other studies have examined delivery of group behavioral counseling using Internet chat rooms, using the Internet for long-term maintenance of weight loss, and enhancing motivation in Internet programs. These interventions have produced weight losses of 4-7 kg over 6 months to 1 year when support via e-mail, automated messages, or chat rooms is provided. Outcomes and lessons learned with application to the treatment of substance use and misuse are provided.

Interrupted time-series analysis of regulations to reduce paracetamol (acetaminophen poisoning.

Directory of Open Access Journals (Sweden)

Oliver W Morgan

2007-04-01

Full Text Available Paracetamol (acetaminophen poisoning is the leading cause of acute liver failure in Great Britain and the United States. Successful interventions to reduced harm from paracetamol poisoning are needed. To achieve this, the government of the United Kingdom introduced legislation in 1998 limiting the pack size of paracetamol sold in shops. Several studies have reported recent decreases in fatal poisonings involving paracetamol. We use interrupted time-series analysis to evaluate whether the recent fall in the number of paracetamol deaths is different to trends in fatal poisoning involving aspirin, paracetamol compounds, antidepressants, or nondrug poisoning suicide.We calculated directly age-standardised mortality rates for paracetamol poisoning in England and Wales from 1993 to 2004. We used an ordinary least-squares regression model divided into pre- and postintervention segments at 1999. The model included a term for autocorrelation within the time series. We tested for changes in the level and slope between the pre- and postintervention segments. To assess whether observed changes in the time series were unique to paracetamol, we compared against poisoning deaths involving compound paracetamol (not covered by the regulations, aspirin, antidepressants, and nonpoisoning suicide deaths. We did this comparison by calculating a ratio of each comparison series with paracetamol and applying a segmented regression model to the ratios. No change in the ratio level or slope indicated no difference compared to the control series. There were about 2,200 deaths involving paracetamol. The age-standardised mortality rate rose from 8.1 per million in 1993 to 8.8 per million in 1997, subsequently falling to about 5.3 per million in 2004. After the regulations were introduced, deaths dropped by 2.69 per million (p = 0.003. Trends in the age-standardised mortality rate for paracetamol compounds, aspirin, and antidepressants were broadly similar to paracetamol

International Work-Conference on Time Series

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Pomares, Héctor; Valenzuela, Olga

2017-01-01

This volume of selected and peer-reviewed contributions on the latest developments in time series analysis and forecasting updates the reader on topics such as analysis of irregularly sampled time series, multi-scale analysis of univariate and multivariate time series, linear and non-linear time series models, advanced time series forecasting methods, applications in time series analysis and forecasting, advanced methods and online learning in time series and high-dimensional and complex/big data time series. The contributions were originally presented at the International Work-Conference on Time Series, ITISE 2016, held in Granada, Spain, June 27-29, 2016. The series of ITISE conferences provides a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting.  It focuses on interdisciplinary and multidisciplinary rese arch encompassing the disciplines of comput...

Functional analysis-based interventions for challenging behaviour in dementia.

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Moniz Cook, Esme D; Swift, Katie; James, Ian; Malouf, Reem; De Vugt, Marjolein; Verhey, Frans

2012-02-15

Functional analysis (FA) for the management of challenging behaviour is a promising behavioural intervention that involves exploring the meaning or purpose of an individual's behaviour. It extends the 'ABC' approach of behavioural analysis, to overcome the restriction of having to derive a single explanatory hypothesis for the person's behaviour. It is seen as a first line alternative to traditional pharmacological management for agitation and aggression. FA typically requires the therapist to develop and evaluate hypotheses-driven strategies that aid family and staff caregivers to reduce or resolve a person's distress and its associated behavioural manifestations. To assess the effects of functional analysis-based interventions for people with dementia (and their caregivers) living in their own home or in other settings. We searched ALOIS: the Cochrane Dementia and Cognitive Improvement Group's Specialized Register on 3 March 2011 using the terms: FA, behaviour (intervention, management, modification), BPSD, psychosocial and Dementia. Randomised controlled trials (RCTs) with reported behavioural outcomes that could be associated with functional analysis for the management of challenging behaviour in dementia. Four reviewers selected trials for inclusion. Two reviewers worked independently to extract data and assess trial quality, including bias. Meta-analyses for reported incidence, frequency, severity of care recipient challenging behaviour and mood (primary outcomes) and caregiver reaction, burden and mood were performed. Details of adverse effects were noted. Eighteen trials are included in the review. The majority were in family care settings. For fourteen studies, FA was just one aspect of a broad multi-component programme of care. Assessing the effect of FA was compromised by ill-defined protocols for the duration of component parts of these programmes (i.e. frequency of the intervention or actual time spent). Therefore, establishing the real effect of the

A Meta-Analysis of Treatment Interventions for Internet Addiction Among Korean Adolescents.

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Chun, JongSerl; Shim, HaiSun; Kim, Soyoun

2017-04-01

This study comprehensively examined the effects of treatment interventions for Internet addiction among adolescents in South Korea through a meta-analysis. We analyzed 70 domestic master's theses and journal articles that reported on controlled studies and involved pre- and post-test analyses in the design. The dates of these publications fall between 2000 and 2015. The total effect size, calculated by random-effect analysis (g), revealed that interventions for the treatment of Internet addiction were effective (ES = 1.838). Meta-ANOVAs revealed differences between groups based on a theoretical model, intervention group size, and intervention duration. Integrative therapy produced larger effect sizes (ES = 2.794) compared to other treatment models such as cognitive behavioral therapy and reality therapy. Effect sizes for interventions, including nine to 12 people (ES = 2.178), were larger than those of interventions including more or fewer participants. Finally, treatment interventions that lasted 8 or more weeks revealed larger effect sizes (ES = 2.294) compared to shorter interventions. The study findings suggest directions for the development and effective operation of future Internet addiction interventions among Korean adolescents. Increasing the effectiveness of these interventions requires an integrative theoretical model, an intervention group size of nine to 12 participants, and a long-term intervention.

Physical and cognitive task analysis in interventional radiology

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Johnson, S [School of Psychology, University of Liverpool, Liverpool (United Kingdom); Healey, A [Royal Liverpool University Hospital, Liverpool (United Kingdom); Evans, J [Royal Liverpool University Hospital, Liverpool (United Kingdom); Murphy, M [Royal Liverpool University Hospital, Liverpool (United Kingdom); Crawshaw, M [Department of Psychology, University of Hull, Hull (United Kingdom); Gould, D [Royal Liverpool University Hospital, Liverpool (United Kingdom)

2006-01-15

AIM: To identify, describe and detail the cognitive thought processes, decision-making, and physical actions involved in the preparation and successful performance of core interventional radiology procedures. MATERIALS AND METHODS: Five commonly performed core interventional radiology procedures were selected for cognitive task analysis. Several examples of each procedure being performed by consultant interventional radiologists were videoed. The videos of those procedures, and the steps required for successful outcome, were analysed by a psychologist and an interventional radiologist. Once a skeleton algorithm of the procedures was defined, further refinement was achieved using individual interview techniques with consultant interventional radiologists. Additionally a critique of each iteration of the established algorithm was sought from non-participating independent consultant interventional radiologists. RESULTS: Detailed task descriptions and decision protocols were developed for five interventional radiology procedures (arterial puncture, nephrostomy, venous access, biopsy-using both ultrasound and computed tomography, and percutaneous transhepatic cholangiogram). Identical tasks performed within these procedures were identified and standardized within the protocols. CONCLUSIONS: Complex procedures were broken down and their constituent processes identified. This might be suitable for use as a training protocol to provide a universally acceptable safe practice at the most fundamental level. It is envisaged that data collected in this way can be used as an educational resource for trainees and could provide the basis for a training curriculum in interventional radiology. It will direct trainees towards safe practice of the highest standard. It will also provide performance objectives of a simulator model.

Physical and cognitive task analysis in interventional radiology

International Nuclear Information System (INIS)

Johnson, S.; Healey, A.; Evans, J.; Murphy, M.; Crawshaw, M.; Gould, D.

2006-01-01

AIM: To identify, describe and detail the cognitive thought processes, decision-making, and physical actions involved in the preparation and successful performance of core interventional radiology procedures. MATERIALS AND METHODS: Five commonly performed core interventional radiology procedures were selected for cognitive task analysis. Several examples of each procedure being performed by consultant interventional radiologists were videoed. The videos of those procedures, and the steps required for successful outcome, were analysed by a psychologist and an interventional radiologist. Once a skeleton algorithm of the procedures was defined, further refinement was achieved using individual interview techniques with consultant interventional radiologists. Additionally a critique of each iteration of the established algorithm was sought from non-participating independent consultant interventional radiologists. RESULTS: Detailed task descriptions and decision protocols were developed for five interventional radiology procedures (arterial puncture, nephrostomy, venous access, biopsy-using both ultrasound and computed tomography, and percutaneous transhepatic cholangiogram). Identical tasks performed within these procedures were identified and standardized within the protocols. CONCLUSIONS: Complex procedures were broken down and their constituent processes identified. This might be suitable for use as a training protocol to provide a universally acceptable safe practice at the most fundamental level. It is envisaged that data collected in this way can be used as an educational resource for trainees and could provide the basis for a training curriculum in interventional radiology. It will direct trainees towards safe practice of the highest standard. It will also provide performance objectives of a simulator model

Identifying effective components of child maltreatment interventions: A meta-analysis

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van der Put, C.E.; Assink, M.; Gubbels, J.; Boekhout van Solinge, N.F.

There is a lack of knowledge about specific components that make interventions effective in preventing or reducing child maltreatment. The aim of the present meta-analysis was to increase this knowledge by summarizing findings on effects of interventions for child maltreatment and by examining

Cost effective management of duodenal ulcers in Uganda: interventions based on a series of seven cases.

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Nzarubara, Gabriel R

2005-03-01

Our understanding of the cause and treatment of peptic ulcer disease has changed dramatically over the last couple of decades. It was quite common some years ago to treat chronic ulcers surgically. These days, the operative treatment is restricted to the small proportion of ulcer patients who have complications such as perforation. The author reports seven cases of perforated duodenal ulcers seen in a surgical clinic between 1995 and 2001. Recommendations on the criteria for selecting the appropriate surgical intervention for patients with perforated duodenal ulcer are given. To decide on the appropriate surgical interventions for patients with perforated duodenal ulcer. These are case series of 7 patients who presented with perforated duodenal ulcers without a history of peptic ulcer disease. Seven patients presented with perforated duodenal ulcer 72 hours after perforation in a specialist surgical clinic in Kampala were analyzed. Appropriate management based on these patients is suggested. These patients were initially treated in upcountry clinics for acute gastritis from either alcohol consumption or suspected food poisoning. There was no duodenal ulcer history. As a result, they came to specialist surgical clinic more than 72 hours after perforation. Diagnosis of perforated duodenal ulcer was made and they were operated using the appropriate surgical intervention. Diagnosis of hangovers and acute gastritis from alcoholic consumption or suspected food poisoning should be treated with suspicion because the symptoms and signs may mimic perforated peptic ulcer in "silent" chronic ulcers. The final decision on the appropriate surgical intervention for patients with perforated duodenal ulcer stratifies them into two groups: The previously fit patients who have relatively mild physiological compromise imposed on previously healthy organ system by the perforation can withstand the operative stress of definitive procedure. The Second category includes patients who are

Arab drama series content analysis from a transnational Arab identity perspective

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Joelle Chamieh

2016-04-01

Full Text Available The scientific contribution in deciphering drama series falls under the discipline of understanding the narratology of distinctive cultures and traditions within specific contexts of certain societies. This article spells out the interferences deployed by the provocations that are induced through the functions of values in modeling societies which are projected through the transmission of media. The proposed operational model consists of providing an à priori design of common Arab values assimilated into an innovative grid analysis code book that has enabled the execution of a systematic and reliable approach to the quantitative content analysis performance. Additionally, a more thorough qualitative content analysis has been implemented in terms of narratolgy where actions have been evaluated based on the grid analysis code book for a clearer perception of Arab values depicted in terms of their context within the Arab drama milieu. This approach has been deployed on four Arab drama series covering the transnational/national and non-divisive/divisive media aspects in the intention of extracting the transmitted values from a common identity perspective for cause of divulging Arab people’s expectancies.

Visibility graph analysis on quarterly macroeconomic series of China based on complex network theory

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Wang, Na; Li, Dong; Wang, Qiwen

2012-12-01

The visibility graph approach and complex network theory provide a new insight into time series analysis. The inheritance of the visibility graph from the original time series was further explored in the paper. We found that degree distributions of visibility graphs extracted from Pseudo Brownian Motion series obtained by the Frequency Domain algorithm exhibit exponential behaviors, in which the exponential exponent is a binomial function of the Hurst index inherited in the time series. Our simulations presented that the quantitative relations between the Hurst indexes and the exponents of degree distribution function are different for different series and the visibility graph inherits some important features of the original time series. Further, we convert some quarterly macroeconomic series including the growth rates of value-added of three industry series and the growth rates of Gross Domestic Product series of China to graphs by the visibility algorithm and explore the topological properties of graphs associated from the four macroeconomic series, namely, the degree distribution and correlations, the clustering coefficient, the average path length, and community structure. Based on complex network analysis we find degree distributions of associated networks from the growth rates of value-added of three industry series are almost exponential and the degree distributions of associated networks from the growth rates of GDP series are scale free. We also discussed the assortativity and disassortativity of the four associated networks as they are related to the evolutionary process of the original macroeconomic series. All the constructed networks have “small-world” features. The community structures of associated networks suggest dynamic changes of the original macroeconomic series. We also detected the relationship among government policy changes, community structures of associated networks and macroeconomic dynamics. We find great influences of government

Flood Frequency Analysis For Partial Duration Series In Ganjiang River Basin

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zhangli, Sun; xiufang, Zhu; yaozhong, Pan

2016-04-01

Accurate estimation of flood frequency is key to effective, nationwide flood damage abatement programs. The partial duration series (PDS) method is widely used in hydrologic studies because it considers all events above a certain threshold level as compared to the annual maximum series (AMS) method, which considers only the annual maximum value. However, the PDS has a drawback in that it is difficult to define the thresholds and maintain an independent and identical distribution of the partial duration time series; this drawback is discussed in this paper. The Ganjiang River is the seventh largest tributary of the Yangtze River, the longest river in China. The Ganjiang River covers a drainage area of 81,258 km2 at the Wanzhou hydrologic station as the basin outlet. In this work, 56 years of daily flow data (1954-2009) from the Wanzhou station were used to analyze flood frequency, and the Pearson-III model was employed as the hydrologic probability distribution. Generally, three tasks were accomplished: (1) the threshold of PDS by percentile rank of daily runoff was obtained; (2) trend analysis of the flow series was conducted using PDS; and (3) flood frequency analysis was conducted for partial duration flow series. The results showed a slight upward trend of the annual runoff in the Ganjiang River basin. The maximum flow with a 0.01 exceedance probability (corresponding to a 100-year flood peak under stationary conditions) was 20,000 m3/s, while that with a 0.1 exceedance probability was 15,000 m3/s. These results will serve as a guide to hydrological engineering planning, design, and management for policymakers and decision makers associated with hydrology.

Cluster analysis of activity-time series in motor learning

DEFF Research Database (Denmark)

Balslev, Daniela; Nielsen, Finn Å; Futiger, Sally A

2002-01-01

Neuroimaging studies of learning focus on brain areas where the activity changes as a function of time. To circumvent the difficult problem of model selection, we used a data-driven analytic tool, cluster analysis, which extracts representative temporal and spatial patterns from the voxel......-time series. The optimal number of clusters was chosen using a cross-validated likelihood method, which highlights the clustering pattern that generalizes best over the subjects. Data were acquired with PET at different time points during practice of a visuomotor task. The results from cluster analysis show...

Time Series in Education: The Analysis of Daily Attendance in Two High Schools

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Koopmans, Matthijs

2011-01-01

This presentation discusses the use of a time series approach to the analysis of daily attendance in two urban high schools over the course of one school year (2009-10). After establishing that the series for both schools were stationary, they were examined for moving average processes, autoregression, seasonal dependencies (weekly cycles),…

Implementation and impact of an audit and feedback antimicrobial stewardship intervention in the orthopaedics department of a tertiary-care hospital: a controlled interrupted time series study.

Science.gov (United States)

Tavares, Margarida; Carvalho, Ana Cláudia; Almeida, José Pedro; Andrade, Paulo; São-Simão, Ricardo; Soares, Pedro; Alves, Carlos; Pinto, Rui; Fontanet, Arnaud; Watier, Laurence

2018-06-01

A prospective audit and feedback antimicrobial stewardship intervention conducted in the Orthopaedics Department of a university hospital in Portugal was evaluated by comparing an interrupted time series in the intervention group with a non-intervention (control) group. Monthly antibiotic use (except cefazolin) was measured as the World Health Organization's Anatomical Therapeutic Chemical defined daily doses (ATC-DDD) from January 2012 to September 2016, excluding the 6-month phase of intervention implementation starting on 1 January 2015. Compared with the control group, the intervention group had a monthly decrease in the use of fluoroquinolones by 2.3 DDD/1000 patient-days [95% confidence interval (CI) -3.97 to -0.63]. An increase in the use of penicillins by 103.3 DDD/1000 patient-days (95% CI 47.42 to 159.10) was associated with intervention implementation, followed by a decrease during the intervention period (slope = -5.2, 95% CI -8.56 to -1.82). In the challenging scenario of treatment of osteoarticular and prosthetic joint infections, an audit and feedback intervention reduced antibiotic exposure and spectrum. Copyright © 2018 Elsevier B.V. and International Society of Chemotherapy. All rights reserved.

A Reception Analysis on the Youth Audiences of TV Series in Marivan

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Omid Karimi

2014-03-01

Full Text Available The aim of this article is to describe the role of foreign media as the agitators of popular culture. For that with reception analysis it’s pay to describe decoding of youth audiences about this series. Globalization theory and Reception in Communication theory are formed the theoretical system of current article. The methodology in this research is qualitative one, and two techniques as in-depth interview and observation are used for data collection. The results show different people based on individual features, social and cultural backgrounds have inclination toward special characters and identify with them. This inclination so far the audience fallow the series because of his/her favorite character. Also there is a great compatibility between audience backgrounds and their receptions. A number of audience have criticized the series and point out the negative consequences on its society. However, seeing the series continue; really they prefer watching series enjoying to risks of it.

Time series analysis of monthly pulpwood use in the Northeast

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James T. Bones

1980-01-01

Time series analysis was used to develop a model that depicts pulpwood use in the Northeast. The model is useful in forecasting future pulpwood requirements (short term) or monitoring pulpwood-use activity in relation to past use patterns. The model predicted a downturn in use during 1980.

Time Series Analysis Based on Running Mann Whitney Z Statistics

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A sensitive and objective time series analysis method based on the calculation of Mann Whitney U statistics is described. This method samples data rankings over moving time windows, converts those samples to Mann-Whitney U statistics, and then normalizes the U statistics to Z statistics using Monte-...

Time Series Analysis of 3D Coordinates Using Nonstochastic Observations

NARCIS (Netherlands)

Velsink, H.

2016-01-01

Adjustment and testing of a combination of stochastic and nonstochastic observations is applied to the deformation analysis of a time series of 3D coordinates. Nonstochastic observations are constant values that are treated as if they were observations. They are used to formulate constraints on

Time Series Analysis of 3D Coordinates Using Nonstochastic Observations

NARCIS (Netherlands)

Hiddo Velsink

2016-01-01

From the article: Abstract Adjustment and testing of a combination of stochastic and nonstochastic observations is applied to the deformation analysis of a time series of 3D coordinates. Nonstochastic observations are constant values that are treated as if they were observations. They are used to

Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

Science.gov (United States)

Donges, Jonathan; Heitzig, Jobst; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik; Marwan, Norbert; Dijkstra, Henk; Kurths, Jürgen

2016-04-01

We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis, recurrence networks, visibility graphs, and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology. pyunicorn is available online at https://github.com/pik-copan/pyunicorn. Reference: J.F. Donges, J. Heitzig, B. Beronov, M. Wiedermann, J. Runge, Q.-Y. Feng, L. Tupikina, V. Stolbova, R.V. Donner, N. Marwan, H.A. Dijkstra, and J. Kurths, Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package, Chaos 25, 113101 (2015), DOI: 10.1063/1.4934554, Preprint: arxiv.org:1507.01571 [physics.data-an].

Time series analysis of temporal networks

Science.gov (United States)

Sikdar, Sandipan; Ganguly, Niloy; Mukherjee, Animesh

2016-01-01

A common but an important feature of all real-world networks is that they are temporal in nature, i.e., the network structure changes over time. Due to this dynamic nature, it becomes difficult to propose suitable growth models that can explain the various important characteristic properties of these networks. In fact, in many application oriented studies only knowing these properties is sufficient. For instance, if one wishes to launch a targeted attack on a network, this can be done even without the knowledge of the full network structure; rather an estimate of some of the properties is sufficient enough to launch the attack. We, in this paper show that even if the network structure at a future time point is not available one can still manage to estimate its properties. We propose a novel method to map a temporal network to a set of time series instances, analyze them and using a standard forecast model of time series, try to predict the properties of a temporal network at a later time instance. To our aim, we consider eight properties such as number of active nodes, average degree, clustering coefficient etc. and apply our prediction framework on them. We mainly focus on the temporal network of human face-to-face contacts and observe that it represents a stochastic process with memory that can be modeled as Auto-Regressive-Integrated-Moving-Average (ARIMA). We use cross validation techniques to find the percentage accuracy of our predictions. An important observation is that the frequency domain properties of the time series obtained from spectrogram analysis could be used to refine the prediction framework by identifying beforehand the cases where the error in prediction is likely to be high. This leads to an improvement of 7.96% (for error level ≤20%) in prediction accuracy on an average across all datasets. As an application we show how such prediction scheme can be used to launch targeted attacks on temporal networks. Contribution to the Topical Issue

Time-series panel analysis (TSPA): multivariate modeling of temporal associations in psychotherapy process.

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Ramseyer, Fabian; Kupper, Zeno; Caspar, Franz; Znoj, Hansjörg; Tschacher, Wolfgang

2014-10-01

Processes occurring in the course of psychotherapy are characterized by the simple fact that they unfold in time and that the multiple factors engaged in change processes vary highly between individuals (idiographic phenomena). Previous research, however, has neglected the temporal perspective by its traditional focus on static phenomena, which were mainly assessed at the group level (nomothetic phenomena). To support a temporal approach, the authors introduce time-series panel analysis (TSPA), a statistical methodology explicitly focusing on the quantification of temporal, session-to-session aspects of change in psychotherapy. TSPA-models are initially built at the level of individuals and are subsequently aggregated at the group level, thus allowing the exploration of prototypical models. TSPA is based on vector auto-regression (VAR), an extension of univariate auto-regression models to multivariate time-series data. The application of TSPA is demonstrated in a sample of 87 outpatient psychotherapy patients who were monitored by postsession questionnaires. Prototypical mechanisms of change were derived from the aggregation of individual multivariate models of psychotherapy process. In a 2nd step, the associations between mechanisms of change (TSPA) and pre- to postsymptom change were explored. TSPA allowed a prototypical process pattern to be identified, where patient's alliance and self-efficacy were linked by a temporal feedback-loop. Furthermore, therapist's stability over time in both mastery and clarification interventions was positively associated with better outcomes. TSPA is a statistical tool that sheds new light on temporal mechanisms of change. Through this approach, clinicians may gain insight into prototypical patterns of change in psychotherapy. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Effects of Interventions Based in Behavior Analysis on Motor Skill Acquisition: A Meta-Analysis

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Alstot, Andrew E.; Kang, Minsoo; Alstot, Crystal D.

2013-01-01

Techniques based in applied behavior analysis (ABA) have been shown to be useful across a variety of settings to improve numerous behaviors. Specifically within physical activity settings, several studies have examined the effect of interventions based in ABA on a variety of motor skills, but the overall effects of these interventions are unknown.…

The Critical Analysis of the Intervention Basis and Evolution in Agriculture

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Włodzimierz Rembisz

2010-12-01

Full Text Available The principles and evolution of intervention in agriculture are critically analyzed from the perspective of the economics and economic of agriculture theories. The allocation and returns aspects of economics are used as references in the analysis. The assumptions and outcomes of a triple factors production function, first aspect, are usually used as a justification for intervention support. That type of production function explains, as is believed, the lover possibilities of labor productivity growth in agriculture compared to non- farm labor employment. That affects, as assumed, income disparities between farm and non-farm labor. The analysis also disputes the politically, institutionally and administratively based justifications for the intervention. The evolution of intervention measures from price support towards direct payments and subsequently more market, are subject of review as well.

Trend analysis and change point detection of annual and seasonal temperature series in Peninsular Malaysia

Science.gov (United States)

Suhaila, Jamaludin; Yusop, Zulkifli

2017-06-01

Most of the trend analysis that has been conducted has not considered the existence of a change point in the time series analysis. If these occurred, then the trend analysis will not be able to detect an obvious increasing or decreasing trend over certain parts of the time series. Furthermore, the lack of discussion on the possible factors that influenced either the decreasing or the increasing trend in the series needs to be addressed in any trend analysis. Hence, this study proposes to investigate the trends, and change point detection of mean, maximum and minimum temperature series, both annually and seasonally in Peninsular Malaysia and determine the possible factors that could contribute to the significance trends. In this study, Pettitt and sequential Mann-Kendall (SQ-MK) tests were used to examine the occurrence of any abrupt climate changes in the independent series. The analyses of the abrupt changes in temperature series suggested that most of the change points in Peninsular Malaysia were detected during the years 1996, 1997 and 1998. These detection points captured by Pettitt and SQ-MK tests are possibly related to climatic factors, such as El Niño and La Niña events. The findings also showed that the majority of the significant change points that exist in the series are related to the significant trend of the stations. Significant increasing trends of annual and seasonal mean, maximum and minimum temperatures in Peninsular Malaysia were found with a range of 2-5 °C/100 years during the last 32 years. It was observed that the magnitudes of the increasing trend in minimum temperatures were larger than the maximum temperatures for most of the studied stations, particularly at the urban stations. These increases are suspected to be linked with the effect of urban heat island other than El Niño event.

Endovascular Versus Open Surgical Intervention in Patients with Takayasu's Arteritis: A Meta-analysis.

Science.gov (United States)

Jung, Jae Hyun; Lee, Young Ho; Song, Gwan Gyu; Jeong, Han Saem; Kim, Jae-Hoon; Choi, Sung Jae

2018-06-01

Although medical treatment has advanced, surgical treatment is needed to control symptoms of Takayasu's arteritis (TA), such as angina, stroke, hypertension, or claudication. Endovascular or open surgical intervention is performed; however, there are few comparative studies on these methods. This meta-analysis and systematic review aimed to examine the outcome of surgical treatment of TA. A meta-analysis comparing outcomes of endovascular and open surgical intervention was performed using MEDLINE and Embase. This meta-analysis included only observational studies, and the evidence level was low to moderate. Data were pooled and analysed using a fixed or random effects model with the I 2 statistic. The included studies involved a total of 770 patients and 1363 lesions, with 389 patients treated endovascularly and 420 treated by surgical revascularization. Restenosis was more common with endovascular than open surgical intervention (odds ratio [OR] 5.18, 95% confidence interval [CI] 2.78-9.62; p open surgical intervention patients in the coronary artery, supra-aortic branches, and renal artery. In both the active and inactive stages, restenosis was more common in those treated endovascularly than in those treated by open surgery. However, stroke occurred less often with endovascular intervention than with open surgical intervention (OR 0.33, 95% CI 0.12-0.90; p = .003). Mortality and complications other than stroke and mortality did not differ between endovascular and open surgical intervention. This meta-analysis has shown a lower risk of restenosis with open surgical intervention than with endovascular intervention. Stroke was generally more common with open surgical intervention than with endovascular intervention. However, there were differences according to the location of the lesion, and the risk of stroke in open surgery is higher when the supra-aortic branches are involved rather than the renal arteries. Copyright © 2018 European Society for Vascular

The Timeseries Toolbox - A Web Application to Enable Accessible, Reproducible Time Series Analysis

Science.gov (United States)

Veatch, W.; Friedman, D.; Baker, B.; Mueller, C.

2017-12-01

The vast majority of data analyzed by climate researchers are repeated observations of physical process or time series data. This data lends itself of a common set of statistical techniques and models designed to determine trends and variability (e.g., seasonality) of these repeated observations. Often, these same techniques and models can be applied to a wide variety of different time series data. The Timeseries Toolbox is a web application designed to standardize and streamline these common approaches to time series analysis and modeling with particular attention to hydrologic time series used in climate preparedness and resilience planning and design by the U. S. Army Corps of Engineers. The application performs much of the pre-processing of time series data necessary for more complex techniques (e.g. interpolation, aggregation). With this tool, users can upload any dataset that conforms to a standard template and immediately begin applying these techniques to analyze their time series data.

On statistical inference in time series analysis of the evolution of road safety.

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Commandeur, Jacques J F; Bijleveld, Frits D; Bergel-Hayat, Ruth; Antoniou, Constantinos; Yannis, George; Papadimitriou, Eleonora

2013-11-01

Data collected for building a road safety observatory usually include observations made sequentially through time. Examples of such data, called time series data, include annual (or monthly) number of road traffic accidents, traffic fatalities or vehicle kilometers driven in a country, as well as the corresponding values of safety performance indicators (e.g., data on speeding, seat belt use, alcohol use, etc.). Some commonly used statistical techniques imply assumptions that are often violated by the special properties of time series data, namely serial dependency among disturbances associated with the observations. The first objective of this paper is to demonstrate the impact of such violations to the applicability of standard methods of statistical inference, which leads to an under or overestimation of the standard error and consequently may produce erroneous inferences. Moreover, having established the adverse consequences of ignoring serial dependency issues, the paper aims to describe rigorous statistical techniques used to overcome them. In particular, appropriate time series analysis techniques of varying complexity are employed to describe the development over time, relating the accident-occurrences to explanatory factors such as exposure measures or safety performance indicators, and forecasting the development into the near future. Traditional regression models (whether they are linear, generalized linear or nonlinear) are shown not to naturally capture the inherent dependencies in time series data. Dedicated time series analysis techniques, such as the ARMA-type and DRAG approaches are discussed next, followed by structural time series models, which are a subclass of state space methods. The paper concludes with general recommendations and practice guidelines for the use of time series models in road safety research. Copyright © 2012 Elsevier Ltd. All rights reserved.

The Fourier decomposition method for nonlinear and non-stationary time series analysis.

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Singh, Pushpendra; Joshi, Shiv Dutt; Patney, Rakesh Kumar; Saha, Kaushik

2017-03-01

for many decades, there has been a general perception in the literature that Fourier methods are not suitable for the analysis of nonlinear and non-stationary data. In this paper, we propose a novel and adaptive Fourier decomposition method (FDM), based on the Fourier theory, and demonstrate its efficacy for the analysis of nonlinear and non-stationary time series. The proposed FDM decomposes any data into a small number of 'Fourier intrinsic band functions' (FIBFs). The FDM presents a generalized Fourier expansion with variable amplitudes and variable frequencies of a time series by the Fourier method itself. We propose an idea of zero-phase filter bank-based multivariate FDM (MFDM), for the analysis of multivariate nonlinear and non-stationary time series, using the FDM. We also present an algorithm to obtain cut-off frequencies for MFDM. The proposed MFDM generates a finite number of band-limited multivariate FIBFs (MFIBFs). The MFDM preserves some intrinsic physical properties of the multivariate data, such as scale alignment, trend and instantaneous frequency. The proposed methods provide a time-frequency-energy (TFE) distribution that reveals the intrinsic structure of a data. Numerical computations and simulations have been carried out and comparison is made with the empirical mode decomposition algorithms.

HIV/STI prevention interventions: A systematic review and meta-analysis

Directory of Open Access Journals (Sweden)

Globerman Jason

2017-12-01

Full Text Available Behavioral interventions can prevent the transmission of HIV and sexually transmitted infections. This systematic review and meta-analysis assesses the effectiveness and quality of available evidence of HIV prevention interventions for people living with HIV in high-income settings. Searches were conducted in MEDLINE, EMBASE, PsycINFO, and CDC Compendium of Effective Interventions. Interventions published between January, 1998 and September, 2015 were included. Quality of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE. Forty-six articles and 63 datasets involving 14,096 individuals met inclusion criteria. Included articles were grouped by intervention type, comparison group and outcome. Few of these had high or moderate quality of evidence and statistically significant effects. One intervention type, group-level health education interventions, were effective in reducing HIV/STI incidence when compared to attention controls. A second intervention type, comprehensive risk counseling and services, was effective in reducing sexual risk behaviors when compared to both active and attention controls. All other intervention types showed no statistically significant effect or had low or very low quality of evidence. Given that the majority of interventions produced low or very low quality of evidence, researchers should commit to rigorous evaluation and high quality reporting of HIV intervention studies.

The impact of national-level interventions to improve hygiene on the incidence of irritant contact dermatitis in healthcare workers: changes in incidence from 1996 to 2012 and interrupted times series analysis.

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Stocks, S J; McNamee, R; Turner, S; Carder, M; Agius, R M

2015-07-01

Reducing healthcare-associated infections (HCAI) has been a priority in the U.K. over recent decades and this has been reflected in interventions focusing on improving hygiene procedures. To evaluate whether these interventions coincided with an increased incidence of work-related irritant contact dermatitis (ICD) attributed to hand hygiene or/and other hygiene measures in healthcare workers (HCWs). A quasi-experimental (interrupted time series) design was used to compare trends in incidence of ICD in HCWs attributed to hygiene before and after interventions to reduce HCAI with trends in the same periods in control groups (ICD in other workers). Cases of ICD reported to a U.K. surveillance scheme from 1996 to 2012 were analysed. The time periods compared were defined objectively based on the dates of the publication of national evidence-based guidelines, the U.K. Health Act 2006 and the Cleanyourhands campaign. The reported incidence of ICD in HCWs attributed to hygiene has increased steadily from 1996 to 2012 [annual incidence rate ratio (95% confidence interval): hand hygiene only 1.10 (1.07-1.12); all hygiene 1.05 (1.03-1.07)], whereas the incidence in other workers is declining. An increase in incidence of ICD in HCWs attributed to hand hygiene was observed at the beginning of the Cleanyourhands campaign. The increasing incidence of ICD in HCWs combined with the popularity of interventions to reduce HCAI warrants increased efforts towards identifying products and implementing practices posing the least risk of ICD. © 2015 British Association of Dermatologists.

Time series analysis of wind speed using VAR and the generalized impulse response technique

Energy Technology Data Exchange (ETDEWEB)

Ewing, Bradley T. [Area of Information Systems and Quantitative Sciences, Rawls College of Business and Wind Science and Engineering Research Center, Texas Tech University, Lubbock, TX 79409-2101 (United States); Kruse, Jamie Brown [Center for Natural Hazard Research, East Carolina University, Greenville, NC (United States); Schroeder, John L. [Department of Geosciences and Wind Science and Engineering Research Center, Texas Tech University, Lubbock, TX (United States); Smith, Douglas A. [Department of Civil Engineering and Wind Science and Engineering Research Center, Texas Tech University, Lubbock, TX (United States)

2007-03-15

This research examines the interdependence in time series wind speed data measured in the same location at four different heights. A multiple-equation system known as a vector autoregression is proposed for characterizing the time series dynamics of wind. Additionally, the recently developed method of generalized impulse response analysis provides insight into the cross-effects of the wind series and their responses to shocks. Findings are based on analysis of contemporaneous wind speed time histories taken at 13, 33, 70 and 160 ft above ground level with a sampling rate of 10 Hz. The results indicate that wind speeds measured at 70 ft was the most variable. Further, the turbulence persisted longer at the 70-ft measurement than at the other heights. The greatest interdependence is observed at 13 ft. Gusts at 160 ft led to the greatest persistence to an 'own' shock and led to greatest persistence in the responses of the other wind series. (author)

Evaluating the impact of flexible alcohol trading hours on violence: an interrupted time series analysis.

Directory of Open Access Journals (Sweden)

David K Humphreys

Full Text Available On November 24(th 2005, the Government of England and Wales removed regulatory restrictions on the times at which licensed premises could sell alcohol. This study tests availability theory by treating the implementation of Licensing Act (2003 as a natural experiment in alcohol policy.An interrupted time series design was employed to estimate the Act's immediate and delayed impact on violence in the City of Manchester (Population 464,200. We collected police recorded rates of violence, robbery, and total crime between the 1st of February 2004 and the 31st of December 2007. Events were aggregated by week, yielding a total of 204 observations (95 pre-, and 109 post-intervention. Secondary analysis examined changes in daily patterns of violence. Pre- and post-intervention events were separated into four three-hour segments 18∶00-20∶59, 21∶00-23.59, 00∶00-02∶59, 03∶00-05∶59.Analysis found no evidence that the Licensing Act (2003 affected the overall volume of violence. However, analyses of night-time violence found a gradual and permanent shift of weekend violence into later parts of the night. The results estimated an initial increase of 27.5% between 03∶00 to 06∶00 (ω = 0.2433, 95% CI = 0.06, 0.42, which increased to 36% by the end of the study period (δ = -0.897, 95% CI = -1.02, -0.77.This study found no evidence that a national policy increasing the physical availability of alcohol affected the overall volume of violence. There was, however, evidence suggesting that the policy may be associated with changes to patterns of violence in the early morning (3 a.m. to 6 a.m..

Analysis of cyclical behavior in time series of stock market returns

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Stratimirović, Djordje; Sarvan, Darko; Miljković, Vladimir; Blesić, Suzana

2018-01-01

In this paper we have analyzed scaling properties and cyclical behavior of the three types of stock market indexes (SMI) time series: data belonging to stock markets of developed economies, emerging economies, and of the underdeveloped or transitional economies. We have used two techniques of data analysis to obtain and verify our findings: the wavelet transform (WT) spectral analysis to identify cycles in the SMI returns data, and the time-dependent detrended moving average (tdDMA) analysis to investigate local behavior around market cycles and trends. We found cyclical behavior in all SMI data sets that we have analyzed. Moreover, the positions and the boundaries of cyclical intervals that we found seam to be common for all markets in our dataset. We list and illustrate the presence of nine such periods in our SMI data. We report on the possibilities to differentiate between the level of growth of the analyzed markets by way of statistical analysis of the properties of wavelet spectra that characterize particular peak behaviors. Our results show that measures like the relative WT energy content and the relative WT amplitude of the peaks in the small scales region could be used to partially differentiate between market economies. Finally, we propose a way to quantify the level of development of a stock market based on estimation of local complexity of market's SMI series. From the local scaling exponents calculated for our nine peak regions we have defined what we named the Development Index, which proved, at least in the case of our dataset, to be suitable to rank the SMI series that we have analyzed in three distinct groups.

Development of analysis software for radiation time-series data with the use of visual studio 2005

International Nuclear Information System (INIS)

Hohara, Sin-ya; Horiguchi, Tetsuo; Ito, Shin

2008-01-01

Time-Series Analysis supplies a new vision that conventional analysis methods such as energy spectroscopy haven't achieved ever. However, application of time-series analysis to radiation measurements needs much effort in software and hardware development. By taking advantage of Visual Studio 2005, we developed an analysis software, 'ListFileConverter', for time-series radiation measurement system called as 'MPA-3'. The software is based on graphical user interface (GUI) architecture that enables us to save a large amount of operation time in the analysis, and moreover to make an easy-access to special file structure of MPA-3 data. In this paper, detailed structure of ListFileConverter is fully explained, and experimental results for counting capability of MPA-3 hardware system and those for neutron measurements with our UTR-KINKI reactor are also given. (author)

A systematic review of case-series studies on the effectiveness of interventions to reduce polypharmacy and its adverse consequences in the elderly.

Directory of Open Access Journals (Sweden)

Maria Benedetta Michelazzo

2017-03-01

Full Text Available Background. Aging is frequently accompanied by chronic diseases; as a consequence, older people are often exposed to polypharmacy that has been associated with negative health-consequences. The aim of this study is to conduct a systematic review of the literature reporting on the effectiveness of different approaches to reduce polypharmacy in the elderly. Methods. We conducted a comprehensive literature search of MEDLINE, Scopus and ISI Web of Knowledge databases. Eligible studies were case-series reporting outcomes of interventions aimed at reducing polypharmacy and its consequences in the elderly. A quality appraisal of the studies included was performed. Results. Nineteen studies were included, of which six conducted in community setting, seven in hospital setting, and six in nursing homes. Seventeen of them were judged as moderate quality, and two of them as poor quality. The majority of the interventions were carried out by pharmacists, alone (35% or with other professionals (40%. Interventions consisted in pharmacotherapy reviews based on various tools and software; in some cases educational interventions were performed for review-performers and patients. Studies conducted in community-setting provided also a feedback to primary care physician. The outcomes included five categories: therapy’s characteristics (e.g. number of drugs, appropriate prescriptions, quality of life, health-related outcomes, costs, healthcare services’ utilization. Therapy-related outcomes were those more affected by all types of interventions. Conclusion. Interventions aimed at reviewing patients’ therapy are effective in optimizing the use of drugs, and could be considered also  in improving quality of life, healthcare costs, services’ utilization, and health-related outcomes.

A Filtering of Incomplete GNSS Position Time Series with Probabilistic Principal Component Analysis

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Gruszczynski, Maciej; Klos, Anna; Bogusz, Janusz

2018-04-01

For the first time, we introduced the probabilistic principal component analysis (pPCA) regarding the spatio-temporal filtering of Global Navigation Satellite System (GNSS) position time series to estimate and remove Common Mode Error (CME) without the interpolation of missing values. We used data from the International GNSS Service (IGS) stations which contributed to the latest International Terrestrial Reference Frame (ITRF2014). The efficiency of the proposed algorithm was tested on the simulated incomplete time series, then CME was estimated for a set of 25 stations located in Central Europe. The newly applied pPCA was compared with previously used algorithms, which showed that this method is capable of resolving the problem of proper spatio-temporal filtering of GNSS time series characterized by different observation time span. We showed, that filtering can be carried out with pPCA method when there exist two time series in the dataset having less than 100 common epoch of observations. The 1st Principal Component (PC) explained more than 36% of the total variance represented by time series residuals' (series with deterministic model removed), what compared to the other PCs variances (less than 8%) means that common signals are significant in GNSS residuals. A clear improvement in the spectral indices of the power-law noise was noticed for the Up component, which is reflected by an average shift towards white noise from - 0.98 to - 0.67 (30%). We observed a significant average reduction in the accuracy of stations' velocity estimated for filtered residuals by 35, 28 and 69% for the North, East, and Up components, respectively. CME series were also subjected to analysis in the context of environmental mass loading influences of the filtering results. Subtraction of the environmental loading models from GNSS residuals provides to reduction of the estimated CME variance by 20 and 65% for horizontal and vertical components, respectively.

Time series analysis for psychological research: examining and forecasting change.

Science.gov (United States)

Jebb, Andrew T; Tay, Louis; Wang, Wei; Huang, Qiming

2015-01-01

Psychological research has increasingly recognized the importance of integrating temporal dynamics into its theories, and innovations in longitudinal designs and analyses have allowed such theories to be formalized and tested. However, psychological researchers may be relatively unequipped to analyze such data, given its many characteristics and the general complexities involved in longitudinal modeling. The current paper introduces time series analysis to psychological research, an analytic domain that has been essential for understanding and predicting the behavior of variables across many diverse fields. First, the characteristics of time series data are discussed. Second, different time series modeling techniques are surveyed that can address various topics of interest to psychological researchers, including describing the pattern of change in a variable, modeling seasonal effects, assessing the immediate and long-term impact of a salient event, and forecasting future values. To illustrate these methods, an illustrative example based on online job search behavior is used throughout the paper, and a software tutorial in R for these analyses is provided in the Supplementary Materials.

Time series analysis for psychological research: examining and forecasting change

Science.gov (United States)

Jebb, Andrew T.; Tay, Louis; Wang, Wei; Huang, Qiming

2015-01-01

Psychological research has increasingly recognized the importance of integrating temporal dynamics into its theories, and innovations in longitudinal designs and analyses have allowed such theories to be formalized and tested. However, psychological researchers may be relatively unequipped to analyze such data, given its many characteristics and the general complexities involved in longitudinal modeling. The current paper introduces time series analysis to psychological research, an analytic domain that has been essential for understanding and predicting the behavior of variables across many diverse fields. First, the characteristics of time series data are discussed. Second, different time series modeling techniques are surveyed that can address various topics of interest to psychological researchers, including describing the pattern of change in a variable, modeling seasonal effects, assessing the immediate and long-term impact of a salient event, and forecasting future values. To illustrate these methods, an illustrative example based on online job search behavior is used throughout the paper, and a software tutorial in R for these analyses is provided in the Supplementary Materials. PMID:26106341

Cognitive-Based Interventions to Improve Mobility: A Systematic Review and Meta-analysis.

Science.gov (United States)

Marusic, Uros; Verghese, Joe; Mahoney, Jeannette R

2018-06-01

A strong relation between cognition and mobility has been identified in aging, supporting a role for enhancement mobility through cognitive-based interventions. However, a critical evaluation of the consistency of treatment effects of cognitive-based interventions is currently lacking. The objective of this study was 2-fold: (1) to review the existing literature on cognitive-based interventions aimed at improving mobility in older adults and (2) to assess the clinical effectiveness of cognitive interventions on gait performance. A systematic review of randomized controlled trials (RCT) of cognitive training interventions for improving simple (normal walking) and complex (dual task walking) gait was conducted in February 2018. Older adults without major cognitive, psychiatric, neurologic, and/or sensory impairments were included. Random effect meta-analyses and a subsequent meta-regression were performed to generate overall cognitive intervention effects on single- and dual-task walking conditions. Ten RCTs met inclusion criteria, with a total of 351 participants included in this meta-analysis. Cognitive training interventions revealed a small effect of intervention on complex gait [effect size (ES) = 0.47, 95% confidence interval (CI) 0.13 to 0.81, P = .007, I 2  = 15.85%], but not simple gait (ES = 0.35, 95% CI -0.01 to 0.71, P = .057, I 2  = 57.32%). Moreover, a meta-regression analysis revealed that intervention duration, training frequency, total number of sessions, and total minutes spent in intervention were not significant predictors of improvement in dual-task walking speed, though there was a suggestive trend toward a negative association between dual-task walking speed improvements and individual training session duration (P = .067). This meta-analysis provides support for the fact that cognitive training interventions can improve mobility-related outcomes, especially during challenging walking conditions requiring higher-order executive

Phase correction and error estimation in InSAR time series analysis

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Zhang, Y.; Fattahi, H.; Amelung, F.

2017-12-01

During the last decade several InSAR time series approaches have been developed in response to the non-idea acquisition strategy of SAR satellites, such as large spatial and temporal baseline with non-regular acquisitions. The small baseline tubes and regular acquisitions of new SAR satellites such as Sentinel-1 allows us to form fully connected networks of interferograms and simplifies the time series analysis into a weighted least square inversion of an over-determined system. Such robust inversion allows us to focus more on the understanding of different components in InSAR time-series and its uncertainties. We present an open-source python-based package for InSAR time series analysis, called PySAR (https://yunjunz.github.io/PySAR/), with unique functionalities for obtaining unbiased ground displacement time-series, geometrical and atmospheric correction of InSAR data and quantifying the InSAR uncertainty. Our implemented strategy contains several features including: 1) improved spatial coverage using coherence-based network of interferograms, 2) unwrapping error correction using phase closure or bridging, 3) tropospheric delay correction using weather models and empirical approaches, 4) DEM error correction, 5) optimal selection of reference date and automatic outlier detection, 6) InSAR uncertainty due to the residual tropospheric delay, decorrelation and residual DEM error, and 7) variance-covariance matrix of final products for geodetic inversion. We demonstrate the performance using SAR datasets acquired by Cosmo-Skymed and TerraSAR-X, Sentinel-1 and ALOS/ALOS-2, with application on the highly non-linear volcanic deformation in Japan and Ecuador (figure 1). Our result shows precursory deformation before the 2015 eruptions of Cotopaxi volcano, with a maximum uplift of 3.4 cm on the western flank (fig. 1b), with a standard deviation of 0.9 cm (fig. 1a), supporting the finding by Morales-Rivera et al. (2017, GRL); and a post-eruptive subsidence on the same

Recurrence Density Enhanced Complex Networks for Nonlinear Time Series Analysis

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Costa, Diego G. De B.; Reis, Barbara M. Da F.; Zou, Yong; Quiles, Marcos G.; Macau, Elbert E. N.

We introduce a new method, which is entitled Recurrence Density Enhanced Complex Network (RDE-CN), to properly analyze nonlinear time series. Our method first transforms a recurrence plot into a figure of a reduced number of points yet preserving the main and fundamental recurrence properties of the original plot. This resulting figure is then reinterpreted as a complex network, which is further characterized by network statistical measures. We illustrate the computational power of RDE-CN approach by time series by both the logistic map and experimental fluid flows, which show that our method distinguishes different dynamics sufficiently well as the traditional recurrence analysis. Therefore, the proposed methodology characterizes the recurrence matrix adequately, while using a reduced set of points from the original recurrence plots.

A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis.

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Hayashi, Hideaki; Shibanoki, Taro; Shima, Keisuke; Kurita, Yuichi; Tsuji, Toshio

2015-12-01

This paper proposes a probabilistic neural network (NN) developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model with a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into an NN, which is named a time-series discriminant component network (TSDCN), so that parameters of dimensionality reduction and classification can be obtained simultaneously as network coefficients according to a backpropagation through time-based learning algorithm with the Lagrange multiplier method. The TSDCN is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. The validity of the TSDCN is demonstrated for high-dimensional artificial data and electroencephalogram signals in the experiments conducted during the study.

A systematic review and meta-analysis of mobile devices and weight loss with an intervention content analysis.

Science.gov (United States)

Lyzwinski, Lynnette Nathalie

2014-06-30

Overweight and obesity constitute leading global public health challenges. Tackling overweight and obesity by influencing human behaviour is a complex task, requiring novel emerging health psychology interventions. The aims of this review will be to determine whether mobile devices induce weight loss and improvements in diet and physical activity levels when compared with standard controls without a weight loss intervention or controls allocated to non-mobile device weight loss interventions. A systematic review on mobile devices and weight loss was conducted. The inclusion criteria were all randomized controlled trials with baseline and post-intervention weight measures in adult subjects >18 years of age without pre-specified co-morbidities. Mobile device specifications included modern, portable devices in the form of smartphones, PDAs, iPods, and Mp3 players. Cohen's d for standardized differences in mean weight loss was calculated. A random effects meta-analysis was generated using Comprehensive meta-analysis software. Theories and intervention content were coded and analysed. A total of 17 studies were identified, of which 12 were primary trials and 5 were secondary analyses. The meta-analysis generated a medium significant effect size of 0.430 (95% CI 0.252-0.609) (p-value ≤ 0.01), favouring mobile interventions. Throughout the systematic review, mobile devices were found to induce weight loss relative to baseline weight. When comparing them with standard no intervention controls as well as controls receiving non-mobile weight loss interventions, results favoured mobile devices for weight loss. Reductions in Body mass index, waist circumference, and percentage body fat were also found in the review. Improvements in the determinants of weight loss in the form of improved dietary intake and physical activity levels were also found. Theory appears to largely inform intervention design, with the most common theories being Social Cognitive Theory, Elaboration

A combined teamwork training and work standardisation intervention in operating theatres: controlled interrupted time series study.

Science.gov (United States)

Morgan, Lauren; Pickering, Sharon P; Hadi, Mohammed; Robertson, Eleanor; New, Steve; Griffin, Damian; Collins, Gary; Rivero-Arias, Oliver; Catchpole, Ken; McCulloch, Peter

2015-02-01

Teamwork training and system standardisation have both been proposed to reduce error and harm in surgery. Since the approaches differ markedly, there is potential for synergy between them. Controlled interrupted time series with a 3 month intervention and observation phases before and after. Operating theatres conducting elective orthopaedic surgery in a single hospital system (UK Hospital Trust). Teamwork training based on crew resource management plus training and follow-up support in developing standardised operating procedures. Focus of subsequent standardisation efforts decided by theatre staff. Paired observers watched whole procedures together. We assessed non-technical skills using NOTECHS II, technical performance using glitch rate and compliance with WHO checklist using a simple quality tool. We measured complication and readmission rates and hospital stay using hospital administrative records. Before/after change was compared in the active and control groups using two-way ANOVA and regression models. 1121 patients were operated on before and 1100 after intervention. 44 operations were observed before and 50 afterwards. Non-technical skills (p=0.002) and WHO compliance (pteamwork and system improvement causes marked improvements in team behaviour and WHO performance, but not technical performance or outcome. These findings are consistent with the synergistic hypothesis, but larger controlled studies with a strong implementation strategy are required to test potential outcome effects. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Bioelectric signal classification using a recurrent probabilistic neural network with time-series discriminant component analysis.

Science.gov (United States)

Hayashi, Hideaki; Shima, Keisuke; Shibanoki, Taro; Kurita, Yuichi; Tsuji, Toshio

2013-01-01

This paper outlines a probabilistic neural network developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower-dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model that incorporates a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into a neural network so that parameters can be obtained appropriately as network coefficients according to backpropagation-through-time-based training algorithm. The network is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. In the experiments conducted during the study, the validity of the proposed network was demonstrated for EEG signals.

Innovative Technology-Based Interventions for Autism Spectrum Disorders: A Meta-Analysis

Science.gov (United States)

Grynszpan, Ouriel; Weiss, Patrice L.; Perez-Diaz, Fernando; Gal, Eynat

2014-01-01

This article reports the results of a meta-analysis of technology-based intervention studies for children with autism spectrum disorders. We conducted a systematic review of research that used a pre-post design to assess innovative technology interventions, including computer programs, virtual reality, and robotics. The selected studies provided…

Interventions to reduce stress in university students: a review and meta-analysis.

Science.gov (United States)

Regehr, Cheryl; Glancy, Dylan; Pitts, Annabel

2013-05-15

Recent research has revealed concerning rates of anxiety and depression among university students. Nevertheless, only a small percentage of these students receive treatment from university health services. Universities are thus challenged with instituting preventative programs that address student stress and reduce resultant anxiety and depression. A systematic review of the literature and meta-analysis was conducted to examine the effectiveness of interventions aimed at reducing stress in university students. Studies were eligible for inclusion if the assignment of study participants to experimental or control groups was by random allocation or parallel cohort design. Retrieved studies represented a variety of intervention approaches with students in a broad range of programs and disciplines. Twenty-four studies, involving 1431 students were included in the meta-analysis. Cognitive, behavioral and mindfulness interventions were associated with decreased symptoms of anxiety. Secondary outcomes included lower levels of depression and cortisol. Included studies were limited to those published in peer reviewed journals. These studies over-represent interventions with female students in Western countries. Studies on some types of interventions such as psycho-educational and arts based interventions did not have sufficient data for inclusion in the meta-analysis. This review provides evidence that cognitive, behavioral, and mindfulness interventions are effective in reducing stress in university students. Universities are encouraged to make such programs widely available to students. In addition however, future work should focus on developing stress reduction programs that attract male students and address their needs. Copyright © 2012 Elsevier B.V. All rights reserved.

EFFICACY OF PHYSIOTHERAPY INTERVENTIONS LATE AFTER STROKE: A META-ANALYSIS

OpenAIRE

Ferrarello , Francesco; Baccini , Marco; Rinaldi , Lucio Antonio; Cavallini , Maria Chiara; Mossello , Enrico; Masotti , Giulio; Marchionni , Niccolò; Di Bari , Mauro

2010-01-01

Abstract Objective. Physiotherapy is usually provided only in the first few months after stroke, while its effectiveness and appropriateness in the chronic phase are uncertain. We conducted a systematic review and meta-analysis of randomized clinical trials (RCT) to evaluate the efficacy of physiotherapy interventions on motor and functional outcomes late after stroke. Methods. We searched published studies where participants were randomized to an active physiotherapy intervention,...

Extended local similarity analysis (eLSA) of microbial community and other time series data with replicates.

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Xia, Li C; Steele, Joshua A; Cram, Jacob A; Cardon, Zoe G; Simmons, Sheri L; Vallino, Joseph J; Fuhrman, Jed A; Sun, Fengzhu

2011-01-01

The increasing availability of time series microbial community data from metagenomics and other molecular biological studies has enabled the analysis of large-scale microbial co-occurrence and association networks. Among the many analytical techniques available, the Local Similarity Analysis (LSA) method is unique in that it captures local and potentially time-delayed co-occurrence and association patterns in time series data that cannot otherwise be identified by ordinary correlation analysis. However LSA, as originally developed, does not consider time series data with replicates, which hinders the full exploitation of available information. With replicates, it is possible to understand the variability of local similarity (LS) score and to obtain its confidence interval. We extended our LSA technique to time series data with replicates and termed it extended LSA, or eLSA. Simulations showed the capability of eLSA to capture subinterval and time-delayed associations. We implemented the eLSA technique into an easy-to-use analytic software package. The software pipeline integrates data normalization, statistical correlation calculation, statistical significance evaluation, and association network construction steps. We applied the eLSA technique to microbial community and gene expression datasets, where unique time-dependent associations were identified. The extended LSA analysis technique was demonstrated to reveal statistically significant local and potentially time-delayed association patterns in replicated time series data beyond that of ordinary correlation analysis. These statistically significant associations can provide insights to the real dynamics of biological systems. The newly designed eLSA software efficiently streamlines the analysis and is freely available from the eLSA homepage, which can be accessed at http://meta.usc.edu/softs/lsa.

Identification of human operator performance models utilizing time series analysis

Science.gov (United States)

Holden, F. M.; Shinners, S. M.

1973-01-01

The results of an effort performed by Sperry Systems Management Division for AMRL in applying time series analysis as a tool for modeling the human operator are presented. This technique is utilized for determining the variation of the human transfer function under various levels of stress. The human operator's model is determined based on actual input and output data from a tracking experiment.

Bibliometric analysis of interventions with batterers in Spain

Directory of Open Access Journals (Sweden)

Victoria A. Ferrer Perez

2015-01-01

Full Text Available This study analyse the evolution and characteristics of scientific production on intervention programmes with gender violence perpetrators performed in Spain. The standard bibliometric indicators were applied to 148 studies identified. The greatest productivity is focused between 2008 and 2010 and the largest number of records corresponds to articles in specialised scientific journals. As far as authorship is concerned, an analysis of the number of studies per person indicates that the results obtained are only initially consistent with Lotka’s Law, that is, there are a majority of not very productive authors and a minority who publish frequently, but the data do not fit this law. An analysis of collaboration between authors enables us to determine the existence of one “Social Circle” or “Invisible College”, at least. Most of the records analysed focus on the description of one or several intervention programmes with men who abuse their partner. Results show that there are progressively more evidence based studies on batterers and their treatment.

The application of complex network time series analysis in turbulent heated jets

International Nuclear Information System (INIS)

Charakopoulos, A. K.; Karakasidis, T. E.; Liakopoulos, A.; Papanicolaou, P. N.

2014-01-01

In the present study, we applied the methodology of the complex network-based time series analysis to experimental temperature time series from a vertical turbulent heated jet. More specifically, we approach the hydrodynamic problem of discriminating time series corresponding to various regions relative to the jet axis, i.e., time series corresponding to regions that are close to the jet axis from time series originating at regions with a different dynamical regime based on the constructed network properties. Applying the transformation phase space method (k nearest neighbors) and also the visibility algorithm, we transformed time series into networks and evaluated the topological properties of the networks such as degree distribution, average path length, diameter, modularity, and clustering coefficient. The results show that the complex network approach allows distinguishing, identifying, and exploring in detail various dynamical regions of the jet flow, and associate it to the corresponding physical behavior. In addition, in order to reject the hypothesis that the studied networks originate from a stochastic process, we generated random network and we compared their statistical properties with that originating from the experimental data. As far as the efficiency of the two methods for network construction is concerned, we conclude that both methodologies lead to network properties that present almost the same qualitative behavior and allow us to reveal the underlying system dynamics

Properties of Asymmetric Detrended Fluctuation Analysis in the time series of RR intervals

Science.gov (United States)

Piskorski, J.; Kosmider, M.; Mieszkowski, D.; Krauze, T.; Wykretowicz, A.; Guzik, P.

2018-02-01

Heart rate asymmetry is a phenomenon by which the accelerations and decelerations of heart rate behave differently, and this difference is consistent and unidirectional, i.e. in most of the analyzed recordings the inequalities have the same directions. So far, it has been established for variance and runs based types of descriptors of RR intervals time series. In this paper we apply the newly developed method of Asymmetric Detrended Fluctuation Analysis, which so far has mainly been used with economic time series, to the set of 420 stationary 30 min time series of RR intervals from young, healthy individuals aged between 20 and 40. This asymmetric approach introduces separate scaling exponents for rising and falling trends. We systematically study the presence of asymmetry in both global and local versions of this method. In this study global means "applying to the whole time series" and local means "applying to windows jumping along the recording". It is found that the correlation structure of the fluctuations left over after detrending in physiological time series shows strong asymmetric features in both magnitude, with α+ physiological data after shuffling or with a group of symmetric synthetic time series.

A Comparison of Missing-Data Procedures for Arima Time-Series Analysis

Science.gov (United States)

Velicer, Wayne F.; Colby, Suzanne M.

2005-01-01

Missing data are a common practical problem for longitudinal designs. Time-series analysis is a longitudinal method that involves a large number of observations on a single unit. Four different missing-data methods (deletion, mean substitution, mean of adjacent observations, and maximum likelihood estimation) were evaluated. Computer-generated…

Multi-complexity ensemble measures for gait time series analysis: application to diagnostics, monitoring and biometrics.

Science.gov (United States)

Gavrishchaka, Valeriy; Senyukova, Olga; Davis, Kristina

2015-01-01

Previously, we have proposed to use complementary complexity measures discovered by boosting-like ensemble learning for the enhancement of quantitative indicators dealing with necessarily short physiological time series. We have confirmed robustness of such multi-complexity measures for heart rate variability analysis with the emphasis on detection of emerging and intermittent cardiac abnormalities. Recently, we presented preliminary results suggesting that such ensemble-based approach could be also effective in discovering universal meta-indicators for early detection and convenient monitoring of neurological abnormalities using gait time series. Here, we argue and demonstrate that these multi-complexity ensemble measures for gait time series analysis could have significantly wider application scope ranging from diagnostics and early detection of physiological regime change to gait-based biometrics applications.

Meta-Analysis of Parent-Mediated Interventions for Young Children with Autism Spectrum Disorder

Science.gov (United States)

Nevill, Rose E.; Lecavalier, Luc; Stratis, Elizabeth A.

2018-01-01

A number of studies of parent-mediated interventions in autism spectrum disorder have been published in the last 15 years. We reviewed 19 randomized clinical trials of parent-mediated interventions for children with autism spectrum disorder between the ages of 1 and 6 years and conducted a meta-analysis on their efficacy. Meta-analysis outcomes…

A cost-effectiveness threshold analysis of a multidisciplinary structured educational intervention in pediatric asthma.

Science.gov (United States)

Rodriguez-Martinez, Carlos E; Sossa-Briceño, Monica P; Castro-Rodriguez, Jose A

2018-05-01

Asthma educational interventions have been shown to improve several clinically and economically important outcomes. However, these interventions are costly in themselves and could lead to even higher disease costs. A cost-effectiveness threshold analysis would be helpful in determining the threshold value of the cost of educational interventions, leading to these interventions being cost-effective. The aim of the present study was to perform a cost-effectiveness threshold analysis to determine the level at which the cost of a pediatric asthma educational intervention would be cost-effective and cost-saving. A Markov-type model was developed in order to estimate costs and health outcomes of a simulated cohort of pediatric patients with persistent asthma treated over a 12-month period. Effectiveness parameters were obtained from a single uncontrolled before-and-after study performed with Colombian asthmatic children. Cost data were obtained from official databases provided by the Colombian Ministry of Health. The main outcome was the variable "quality-adjusted life-years" (QALYs). A deterministic threshold sensitivity analysis showed that the asthma educational intervention will be cost-saving to the health system if its cost is under US$513.20. Additionally, the analysis showed that the cost of the intervention would have to be below US$967.40 in order to be cost-effective. This study identified the level at which the cost of a pediatric asthma educational intervention will be cost-effective and cost-saving for the health system in Colombia. Our findings could be a useful aid for decision makers in efficiently allocating limited resources when planning asthma educational interventions for pediatric patients.

A Systematic Review and Meta-Analysis of Mobile Devices and Weight Loss with an Intervention Content Analysis

Science.gov (United States)

Lyzwinski, Lynnette Nathalie

2014-01-01

Introduction: Overweight and obesity constitute leading global public health challenges. Tackling overweight and obesity by influencing human behaviour is a complex task, requiring novel emerging health psychology interventions. The aims of this review will be to determine whether mobile devices induce weight loss and improvements in diet and physical activity levels when compared with standard controls without a weight loss intervention or controls allocated to non-mobile device weight loss interventions. Methods: A systematic review on mobile devices and weight loss was conducted. The inclusion criteria were all randomized controlled trials with baseline and post-intervention weight measures in adult subjects >18 years of age without pre-specified co-morbidities. Mobile device specifications included modern, portable devices in the form of smartphones, PDAs, iPods, and Mp3 players. Cohen’s d for standardized differences in mean weight loss was calculated. A random effects meta-analysis was generated using Comprehensive meta-analysis software. Theories and intervention content were coded and analysed. Results: A total of 17 studies were identified, of which 12 were primary trials and 5 were secondary analyses. The meta-analysis generated a medium significant effect size of 0.430 (95% CI 0.252–0.609) (p-value ≤ 0.01), favouring mobile interventions. Throughout the systematic review, mobile devices were found to induce weight loss relative to baseline weight. When comparing them with standard no intervention controls as well as controls receiving non-mobile weight loss interventions, results favoured mobile devices for weight loss. Reductions in Body mass index, waist circumference, and percentage body fat were also found in the review. Improvements in the determinants of weight loss in the form of improved dietary intake and physical activity levels were also found. Theory appears to largely inform intervention design, with the most common theories being

A Systematic Review and Meta-Analysis of Mobile Devices and Weight Loss with an Intervention Content Analysis

Directory of Open Access Journals (Sweden)

Lynnette Nathalie Lyzwinski

2014-06-01

Full Text Available Introduction: Overweight and obesity constitute leading global public health challenges. Tackling overweight and obesity by influencing human behaviour is a complex task, requiring novel emerging health psychology interventions. The aims of this review will be to determine whether mobile devices induce weight loss and improvements in diet and physical activity levels when compared with standard controls without a weight loss intervention or controls allocated to non-mobile device weight loss interventions. Methods: A systematic review on mobile devices and weight loss was conducted. The inclusion criteria were all randomized controlled trials with baseline and post-intervention weight measures in adult subjects >18 years of age without pre-specified co-morbidities. Mobile device specifications included modern, portable devices in the form of smartphones, PDAs, iPods, and Mp3 players. Cohen’s d for standardized differences in mean weight loss was calculated. A random effects meta-analysis was generated using Comprehensive meta-analysis software. Theories and intervention content were coded and analysed. Results: A total of 17 studies were identified, of which 12 were primary trials and 5 were secondary analyses. The meta-analysis generated a medium significant effect size of 0.430 (95% CI 0.252–0.609 (p-value ≤ 0.01, favouring mobile interventions. Throughout the systematic review, mobile devices were found to induce weight loss relative to baseline weight. When comparing them with standard no intervention controls as well as controls receiving non-mobile weight loss interventions, results favoured mobile devices for weight loss. Reductions in Body mass index, waist circumference, and percentage body fat were also found in the review. Improvements in the determinants of weight loss in the form of improved dietary intake and physical activity levels were also found. Theory appears to largely inform intervention design, with the most common

Analysis of Land Subsidence Monitoring in Mining Area with Time-Series Insar Technology

Science.gov (United States)

Sun, N.; Wang, Y. J.

2018-04-01

Time-series InSAR technology has become a popular land subsidence monitoring method in recent years, because of its advantages such as high accuracy, wide area, low expenditure, intensive monitoring points and free from accessibility restrictions. In this paper, we applied two kinds of satellite data, ALOS PALSAR and RADARSAT-2, to get the subsidence monitoring results of the study area in two time periods by time-series InSAR technology. By analyzing the deformation range, rate and amount, the time-series analysis of land subsidence in mining area was realized. The results show that InSAR technology could be used to monitor land subsidence in large area and meet the demand of subsidence monitoring in mining area.

Qualitative analysis of an educational intervention with HIV-discordant heterosexual Latino couples.

Science.gov (United States)

Pérez-Jiménez, David; Orengo-Aguayo, Rosaura E

2011-12-01

This qualitative analysis elucidates the potential elements of the intervention that may be effective in terms of a) increasing knowledge about HIV/ AIDS in the members of this population; b) increasing the use of male condoms and the practice of mutual masturbation; and c) changing opinions toward male condom use and mutual masturbation. Five heterosexual HIV-discordant couples participated in the adapted intervention, which consisted of four three-hour-long sessions. One month after the intervention, we conducted a qualitative semi-structured interview with every participant to evaluate issues related to the process and content of the activities comprising the intervention, the impact of the intervention, logistics, and recruitment and retention as well as to make a more general evaluation. The information was submitted to qualitative content analysis. After the intervention, participants reported having better attitudes regarding safer sex, particularly in terms of condom use. A reason given by the participants to feel more positive toward condom use and mutual masturbation was that these practices could prevent the infection of the HIV-negative partner. This study provides important evidence of an intervention that promises to be efficacious in preventing some high-risk sexual behaviors among Latino HIV-discordant heterosexual couples. The evidence presented seems to suggest that an intervention that includes basic relevant information about HIV/AIDS, that explains the benefits of condom use and other safer sex options, and that provides effective negotiation and communication strategies could significantly reduce HIV transmission among these couples.

Definition of distance for nonlinear time series analysis of marked point process data

Energy Technology Data Exchange (ETDEWEB)

Iwayama, Koji, E-mail: koji@sat.t.u-tokyo.ac.jp [Research Institute for Food and Agriculture, Ryukoku Univeristy, 1-5 Yokotani, Seta Oe-cho, Otsu-Shi, Shiga 520-2194 (Japan); Hirata, Yoshito; Aihara, Kazuyuki [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan)

2017-01-30

Marked point process data are time series of discrete events accompanied with some values, such as economic trades, earthquakes, and lightnings. A distance for marked point process data allows us to apply nonlinear time series analysis to such data. We propose a distance for marked point process data which can be calculated much faster than the existing distance when the number of marks is small. Furthermore, under some assumptions, the Kullback–Leibler divergences between posterior distributions for neighbors defined by this distance are small. We performed some numerical simulations showing that analysis based on the proposed distance is effective. - Highlights: • A new distance for marked point process data is proposed. • The distance can be computed fast enough for a small number of marks. • The method to optimize parameter values of the distance is also proposed. • Numerical simulations indicate that the analysis based on the distance is effective.

On the Use of Running Trends as Summary Statistics for Univariate Time Series and Time Series Association

OpenAIRE

Trottini, Mario; Vigo, Isabel; Belda, Santiago

2015-01-01

Given a time series, running trends analysis (RTA) involves evaluating least squares trends over overlapping time windows of L consecutive time points, with overlap by all but one observation. This produces a new series called the “running trends series,” which is used as summary statistics of the original series for further analysis. In recent years, RTA has been widely used in climate applied research as summary statistics for time series and time series association. There is no doubt that ...

CROSAT: A digital computer program for statistical-spectral analysis of two discrete time series

International Nuclear Information System (INIS)

Antonopoulos Domis, M.

1978-03-01

The program CROSAT computes directly from two discrete time series auto- and cross-spectra, transfer and coherence functions, using a Fast Fourier Transform subroutine. Statistical analysis of the time series is optional. While of general use the program is constructed to be immediately compatible with the ICL 4-70 and H316 computers at AEE Winfrith, and perhaps with minor modifications, with any other hardware system. (author)

Application of Time Series Analysis in Determination of Lag Time in Jahanbin Basin

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Seied Yahya Mirzaee

2005-11-01

    One of the important issues that have significant role in study of hydrology of basin is determination of lag time. Lag time has significant role in hydrological studies. Quantity of rainfall related lag time depends on several factors, such as permeability, vegetation cover, catchments slope, rainfall intensity, storm duration and type of rain. Determination of lag time is important parameter in many projects such as dam design and also water resource studies. Lag time of basin could be calculated using various methods. One of these methods is time series analysis of spectral density. The analysis is based on fouries series. The time series is approximated with Sinuous and Cosines functions. In this method harmonically significant quantities with individual frequencies are presented. Spectral density under multiple time series could be used to obtain basin lag time for annual runoff and short-term rainfall fluctuation. A long lag time could be due to snowmelt as well as melting ice due to rainfalls in freezing days. In this research the lag time of Jahanbin basin has been determined using spectral density method. The catchments is subjected to both rainfall and snowfall. For short term rainfall fluctuation with a return period  2, 3, 4 months, the lag times were found 0.18, 0.5 and 0.083 month, respectively.

Sleep, School Performance, and a School-Based Intervention among School-Aged Children: A Sleep Series Study in China

Science.gov (United States)

Li, Shenghui; Arguelles, Lester; Jiang, Fan; Chen, Wenjuan; Jin, Xingming; Yan, Chonghuai; Tian, Ying; Hong, Xiumei; Qian, Ceng; Zhang, Jun; Wang, Xiaobin; Shen, Xiaoming

2013-01-01

Background Sufficient sleep during childhood is essential to ensure a transition into a healthy adulthood. However, chronic sleep loss continues to increase worldwide. In this context, it is imperative to make sleep a high-priority and take action to promote sleep health among children. The present series of studies aimed to shed light on sleep patterns, on the longitudinal association of sleep with school performance, and on practical intervention strategy for Chinese school-aged children. Methods and Findings A serial sleep researches, including a national cross-sectional survey, a prospective cohort study, and a school-based sleep intervention, were conducted in China from November 2005 through December 2009. The national cross-sectional survey was conducted in 8 cities and a random sample of 20,778 children aged 9.0±1.61 years participated in the survey. The five-year prospective cohort study included 612 children aged 6.8±0.31 years. The comparative cross-sectional study (baseline: n = 525, aged 10.80±0.41; post-intervention follow-up: n = 553, aged 10.81±0.33) was undertaken in 6 primary schools in Shanghai. A battery of parent and teacher reported questionnaires were used to collect information on children’s sleep behaviors, school performance, and sociodemographic characteristics. The mean sleep duration was 9.35±0.77 hours. The prevalence of daytime sleepiness was 64.4% (sometimes: 37.50%; frequently: 26.94%). Daytime sleepiness was significantly associated with impaired attention, learning motivation, and particularly, academic achievement. By contrast, short sleep duration only related to impaired academic achievement. After delaying school start time 30 minutes and 60 minutes, respectively, sleep duration correspondingly increased by 15.6 minutes and 22.8 minutes, respectively. Moreover, intervention significantly improved the sleep duration and daytime sleepiness. Conclusions Insufficient sleep and daytime sleepiness commonly existed and

Sleep, school performance, and a school-based intervention among school-aged children: a sleep series study in China.

Science.gov (United States)

Li, Shenghui; Arguelles, Lester; Jiang, Fan; Chen, Wenjuan; Jin, Xingming; Yan, Chonghuai; Tian, Ying; Hong, Xiumei; Qian, Ceng; Zhang, Jun; Wang, Xiaobin; Shen, Xiaoming

2013-01-01

Sufficient sleep during childhood is essential to ensure a transition into a healthy adulthood. However, chronic sleep loss continues to increase worldwide. In this context, it is imperative to make sleep a high-priority and take action to promote sleep health among children. The present series of studies aimed to shed light on sleep patterns, on the longitudinal association of sleep with school performance, and on practical intervention strategy for Chinese school-aged children. A serial sleep researches, including a national cross-sectional survey, a prospective cohort study, and a school-based sleep intervention, were conducted in China from November 2005 through December 2009. The national cross-sectional survey was conducted in 8 cities and a random sample of 20,778 children aged 9.0±1.61 years participated in the survey. The five-year prospective cohort study included 612 children aged 6.8±0.31 years. The comparative cross-sectional study (baseline: n = 525, aged 10.80±0.41; post-intervention follow-up: n = 553, aged 10.81±0.33) was undertaken in 6 primary schools in Shanghai. A battery of parent and teacher reported questionnaires were used to collect information on children's sleep behaviors, school performance, and sociodemographic characteristics. The mean sleep duration was 9.35±0.77 hours. The prevalence of daytime sleepiness was 64.4% (sometimes: 37.50%; frequently: 26.94%). Daytime sleepiness was significantly associated with impaired attention, learning motivation, and particularly, academic achievement. By contrast, short sleep duration only related to impaired academic achievement. After delaying school start time 30 minutes and 60 minutes, respectively, sleep duration correspondingly increased by 15.6 minutes and 22.8 minutes, respectively. Moreover, intervention significantly improved the sleep duration and daytime sleepiness. Insufficient sleep and daytime sleepiness commonly existed and positively associated with the impairment of

Sleep, school performance, and a school-based intervention among school-aged children: a sleep series study in China.

Directory of Open Access Journals (Sweden)

Shenghui Li

Full Text Available BACKGROUND: Sufficient sleep during childhood is essential to ensure a transition into a healthy adulthood. However, chronic sleep loss continues to increase worldwide. In this context, it is imperative to make sleep a high-priority and take action to promote sleep health among children. The present series of studies aimed to shed light on sleep patterns, on the longitudinal association of sleep with school performance, and on practical intervention strategy for Chinese school-aged children. METHODS AND FINDINGS: A serial sleep researches, including a national cross-sectional survey, a prospective cohort study, and a school-based sleep intervention, were conducted in China from November 2005 through December 2009. The national cross-sectional survey was conducted in 8 cities and a random sample of 20,778 children aged 9.0±1.61 years participated in the survey. The five-year prospective cohort study included 612 children aged 6.8±0.31 years. The comparative cross-sectional study (baseline: n = 525, aged 10.80±0.41; post-intervention follow-up: n = 553, aged 10.81±0.33 was undertaken in 6 primary schools in Shanghai. A battery of parent and teacher reported questionnaires were used to collect information on children's sleep behaviors, school performance, and sociodemographic characteristics. The mean sleep duration was 9.35±0.77 hours. The prevalence of daytime sleepiness was 64.4% (sometimes: 37.50%; frequently: 26.94%. Daytime sleepiness was significantly associated with impaired attention, learning motivation, and particularly, academic achievement. By contrast, short sleep duration only related to impaired academic achievement. After delaying school start time 30 minutes and 60 minutes, respectively, sleep duration correspondingly increased by 15.6 minutes and 22.8 minutes, respectively. Moreover, intervention significantly improved the sleep duration and daytime sleepiness. CONCLUSIONS: Insufficient sleep and daytime sleepiness

The Analysis Of Personality Disorder On Two Characters In The Animation Series Black Rock Shooter

OpenAIRE

Ramadhana, Rizki Andrian

2015-01-01

The title of this thesis is The Analysis of Personality Disorder on Two Characters in the Animation Series “Black Rock Shooter” which discusses about the personality disorder of two characters from this series; they are Kagari Izuriha and Yomi Takanashi. The animation series Black Rock Shooter is chosen as the source of data because this animation has psychological genre and represents the complexity of human relationship, especially when build up a friendship. It is because human is a social...

Investigation of interfacial wave structure using time-series analysis techniques

International Nuclear Information System (INIS)

Jayanti, S.; Hewitt, G.F.; Cliffe, K.A.

1990-09-01

The report presents an investigation into the interfacial structure in horizontal annular flow using spectral and time-series analysis techniques. Film thickness measured using conductance probes shows an interesting transition in wave pattern from a continuous low-frequency wave pattern to an intermittent, high-frequency one. From the autospectral density function of the film thickness, it appears that this transition is caused by the breaking up of long waves into smaller ones. To investigate the possibility of the wave structure being represented as a low order chaotic system, phase portraits of the time series were constructed using the technique developed by Broomhead and co-workers (1986, 1987 and 1989). These showed a banded structure when waves of relatively high frequency were filtered out. Although these results are encouraging, further work is needed to characterise the attractor. (Author)

Impact of STROBE statement publication on quality of observational study reporting: interrupted time series versus before-after analysis.

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Sylvie Bastuji-Garin

Full Text Available In uncontrolled before-after studies, CONSORT was shown to improve the reporting of randomised trials. Before-after studies ignore underlying secular trends and may overestimate the impact of interventions. Our aim was to assess the impact of the 2007 STROBE statement publication on the quality of observational study reporting, using both uncontrolled before-after analyses and interrupted time series.For this quasi-experimental study, original articles reporting cohort, case-control, and cross-sectional studies published between 2004 and 2010 in the four dermatological journals having the highest 5-year impact factors (≥ 4 were selected. We compared the proportions of STROBE items (STROBE score adequately reported in each article during three periods, two pre STROBE period (2004-2005 and 2006-2007 and one post STROBE period (2008-2010. Segmented regression analysis of interrupted time series was also performed.Of the 456 included articles, 187 (41% reported cohort studies, 166 (36.4% cross-sectional studies, and 103 (22.6% case-control studies. The median STROBE score was 57% (range, 18%-98%. Before-after analysis evidenced significant STROBE score increases between the two pre-STROBE periods and between the earliest pre-STROBE period and the post-STROBE period (median score2004-05 48% versus median score2008-10 58%, p<0.001 but not between the immediate pre-STROBE period and the post-STROBE period (median score2006-07 58% versus median score2008-10 58%, p = 0.42. In the pre STROBE period, the six-monthly mean STROBE score increased significantly, by 1.19% per six-month period (absolute increase 95%CI, 0.26% to 2.11%, p = 0.016. By segmented analysis, no significant changes in STROBE score trends occurred (-0.40%; 95%CI, -2.20 to 1.41; p = 0.64 in the post STROBE statement publication.The quality of reports increased over time but was not affected by STROBE. Our findings raise concerns about the relevance of uncontrolled before

Detrended partial cross-correlation analysis of two nonstationary time series influenced by common external forces

Science.gov (United States)

Qian, Xi-Yuan; Liu, Ya-Min; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene

2015-06-01

When common factors strongly influence two power-law cross-correlated time series recorded in complex natural or social systems, using detrended cross-correlation analysis (DCCA) without considering these common factors will bias the results. We use detrended partial cross-correlation analysis (DPXA) to uncover the intrinsic power-law cross correlations between two simultaneously recorded time series in the presence of nonstationarity after removing the effects of other time series acting as common forces. The DPXA method is a generalization of the detrended cross-correlation analysis that takes into account partial correlation analysis. We demonstrate the method by using bivariate fractional Brownian motions contaminated with a fractional Brownian motion. We find that the DPXA is able to recover the analytical cross Hurst indices, and thus the multiscale DPXA coefficients are a viable alternative to the conventional cross-correlation coefficient. We demonstrate the advantage of the DPXA coefficients over the DCCA coefficients by analyzing contaminated bivariate fractional Brownian motions. We calculate the DPXA coefficients and use them to extract the intrinsic cross correlation between crude oil and gold futures by taking into consideration the impact of the U.S. dollar index. We develop the multifractal DPXA (MF-DPXA) method in order to generalize the DPXA method and investigate multifractal time series. We analyze multifractal binomial measures masked with strong white noises and find that the MF-DPXA method quantifies the hidden multifractal nature while the multifractal DCCA method fails.

Interventional chest procedures in pregnancy.

LENUS (Irish Health Repository)

Morgan, Ross K

2011-03-01

Interventional pulmonology encompasses diagnostic and therapeutic bronchoscopic procedures, and pleural interventions. In the last 10 years older techniques have been refined and exciting new technologies have extended the reach and application of the instruments used. The main areas within pulmonary medicine for which these interventions have a role are malignant and nonmalignant airway disease, pleural effusion, pneumothorax, and artificial airways. There are no data from well-designed prospective trials to guide recommendations for interventional pulmonary procedures in pregnancy. The recommendations provided in this article are based on critical review of reported case series, opinion from recognized experts, and personal observations.

Interventional chest procedures in pregnancy.

LENUS (Irish Health Repository)

Morgan, Ross K

2012-02-01

Interventional pulmonology encompasses diagnostic and therapeutic bronchoscopic procedures, and pleural interventions. In the last 10 years older techniques have been refined and exciting new technologies have extended the reach and application of the instruments used. The main areas within pulmonary medicine for which these interventions have a role are malignant and nonmalignant airway disease, pleural effusion, pneumothorax, and artificial airways. There are no data from well-designed prospective trials to guide recommendations for interventional pulmonary procedures in pregnancy. The recommendations provided in this article are based on critical review of reported case series, opinion from recognized experts, and personal observations.

Comparative Cost Analysis of Four Interventions to Prevent HIV Transmission in Bandung, Indonesia

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Eveline J.M. Verstraaten

2017-11-01

Full Text Available Background: the costs of HIV/AIDS interventions in Indonesia are largely unknown. Knowing these costs is an important input for policy makers in the decision-making of setting priorities among HIV/AIDS interventions. The aim of this analysis is to determine the costs of four HIV/AIDS interventions in Bandung, Indonesia in 2015, to inform the local AIDS commission. Methods: data on utilization and costs of the different interventions were collected in a sexual transmitted infections (STI-clinic and the KPA, the local HIV/AIDS commission, for the period of January 2015-December 2015. The costs were estimated from a societal perspective, using a micro-costing approach. Results: the total annualized costs for condom distribution, mobile voluntary counselling and testing (VCT, religious based information, communication, and education (IEC and STI services equalled US$56,926, US$2,985, US$1,963 and US$5,865, respectively. Conclusion: this analysis has provided cost estimates of four different HIV/AIDS interventions in Bandung, Indonesia. Additionally, it has estimated the costs of scaling up these interventions. Together, this provides important information for policy makers vis-à-vis the implementation of these interventions. However, an evaluation of the effectiveness of these interventions is needed to estimate the cost-effectiveness.

State intervention causing inefficiency: an empirical analysis of the Norwegian Continental Shelf

International Nuclear Information System (INIS)

Kashani, Hossein A.

2005-01-01

State intervention in the Norwegian Continental Shelf started with the establishment of Statoil as the medium of state ownership over the found petroleum and as a tool to monitor oil companies' procurement behaviour. This paper tests the extent to which the state intervention created inefficiencies in the Norwegian Continental Shelf (NCS) activities, as measured by data envelopment analysis, stochastic frontier analysis, Malmquist Indices, and standard regression analysis. Our results confirm such inefficiencies. Accordingly, the results provide an important insight into NCS production techniques and, more generally, into governments' abilities to influence private sector behaviour through contracts and tendering

Healthcare provider-led interventions to support medication adherence following ACS: a meta-analysis.

Science.gov (United States)

Crawshaw, Jacob; Auyeung, Vivian; Ashworth, Lucy; Norton, Sam; Weinman, John

2017-01-01

We conducted a systematic review and meta-analysis to determine the effectiveness of healthcare provider-led (HCPs) interventions to support medication adherence in patients with acute coronary syndrome (ACS). A systematic search of Cochrane Library, Medline, EMBASE, PsycINFO, Web of Science, IPA, CINAHL, ASSIA, OpenGrey, EthOS, WorldCat and PQDT was undertaken. Interventions were deemed eligible if they included adult ACS patients, were HCP-led, measured medication adherence and randomised participants to parallel groups. Intervention content was coded using the Behaviour Change Technique (BCT) Taxonomy and data were pooled for analysis using random-effects models. Our search identified 8870 records, of which 27 were eligible (23 primary studies). A meta-analysis (n=9735) revealed HCP-led interventions increased the odds of medication adherence by 54% compared to control interventions (k=23, OR 1.54, 95% CI 1.26 to 1.88, I 2 =57.5%). After removing outliers, there was a 41% increase in the odds of medication adherence with moderate heterogeneity (k=21, OR 1.41, 95% CI 1.21 to 1.65, I 2 =35.3%). Interventions that included phone contact yielded (k=12, OR 1.63, 95% CI 1.25 to 2.12, I 2 =32.0%) a larger effect compared to those delivered exclusively in person. A total of 32/93 BCTs were identified across interventions (mean=4.7, SD=2.2) with 'information about health consequences' (BCT 5.1) (19/23) the most common. HCP-led interventions for ACS patients appear to have a small positive impact on medication adherence. While we were able to identify BCTs among interventions, data were insufficient to determine the impact of particular BCTs on study effectiveness. CRD42016037706.

Short-term and sustained effects of a health system strengthening intervention to improve mortality trends for paediatric severe malnutrition in rural South African hospitals: An interrupted time series design

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M Muzigaba

2017-04-01

Full Text Available Background. Case fatality rates for childhood severe acute malnutrition (SAM remain high in some resource-limited facilities in South Africa (SA, despite the widespread availability of the World Health Organization treatment guidelines. There is a need to develop reproducible interventions that reinforce the implementation of these guidelines and assess their effect and sustainability. Objectives. To assess the short-term and sustained effects of a health system strengthening intervention on mortality attributable to SAM in two hospitals located in the Eastern Cape Province of SA. Methods. This was a theory-driven evaluation conducted in two rural hospitals in SA over a 69-month period (2009 - 2014. In both facilities, a health system strengthening intervention was implemented within the first 32 months, and thereafter discontinued. Sixty-nine monthly data series were collected on: (i monthly total SAM case fatality rate (CFR; (ii monthly SAM CFR within 24 hours of admission; and (iii monthly SAM CFR among HIV-positive cases, to determine the intervention’s effect within the first 32 months and sustainability over the remaining 37 months. The data were analysed using Linden’s method for analysing interrupted time series data. Results. The study revealed that the intervention was associated with a statistically significant decrease of up to 0.4% in monthly total SAM CFR, a non-statistically significant decrease of up to 0.09% in monthly SAM CFR within 24 hours of admission and a non-statistically significant decrease of up to 0.11% in monthly SAM CFR among HIV-positive cases. The decrease in mortality trends for both outcomes was only slightly reversed upon the discontinuation of the intervention. No autocorrelation was detected in the regression models generated during data analyses. Conclusion. The study findings suggest that although the intervention was designed to be self-sustaining, this may not have been the case. A qualitative enquiry

Network structure of multivariate time series.

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Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

2015-10-21

Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail.

Theory of planned behavior interventions for reducing heterosexual risk behaviors: A meta-analysis.

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Tyson, Mandy; Covey, Judith; Rosenthal, Harriet E S

2014-12-01

The meta-analysis reported here examined interventions informed by the theory of planned behavior (TPB) or theory of reasoned action (TRA) aimed at reducing heterosexual risk behaviors (prevention of STDs and unwanted pregnancy). Studies were eligible for inclusion if they were either randomized control trials or quasi-experimental studies that compared the TPB-based intervention against a control group. Search strategy consisted of articles identified in previous reviews, keyword search through search engines, examination of key journals, and contacting key experts. Forty-seven intervention studies were included in the meta-analysis. Random effects models revealed that pooled effect sizes for TPB-based interventions had small but significant effects on behavior and other secondary outcomes (i.e., knowledge, attitudes, normative beliefs, perceived behavioral control, and intentions). Significant heterogeneity found between effect sizes was explored using metaregression. Larger effects were found for interventions that provided opportunities for social comparison. The TPB provides a valuable framework for designing interventions to change heterosexual risk behaviors. However, effect sizes varied quite substantially between studies, and further research is needed to explore the reasons why.

The Effects of Expressive Writing Interventions for Patients With Cancer: A Meta-Analysis.

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Oh, Pok-Ja; Kim, Soo Hyun

2016-07-01

To evaluate the effects of expressive writing (EW) interventions in patients with cancer.
. Electronic databases searched included both international and Korean databases through January 2015.
. Of the 20 trials that met the eligibility criteria of this review, a meta-analysis was conducted of 14 articles involving 13 randomized and 1 nonrandomized trials with 1,718 patients with cancer. EW interventions were compared with a neutral writing intervention or usual care (no writing). A significant small effect was noted on relieving cancer symptoms; however, the effects on psychological and cognitive outcomes were not significant. When subgroup analysis by control condition was performed, a significant effect on health-related quality of life was found between the EW intervention group and the usual care group. 
. EW had significant small effects only on cancer symptoms. The findings suggest that the traditional EW intervention protocol may need to be intensified to confirm its effect on patients with cancer.
. Current evidence for EW as a nursing intervention for improving physical, psychological, and cognitive outcomes among patients with cancer is promising, but not conclusive.

Time series analysis of soil Radon-222 recorded at Kutch region, Gujarat, India

International Nuclear Information System (INIS)

Madhusudan Rao, K.; Rastogi, B.K.; Barman, Chiranjib; Chaudhuri, Hirok

2013-01-01

Kutch region in Gujarat lies in a seismic vulnerable zone (seismic zone-v). After the devastating Bhuj earthquake (7.7M) of January 26, 2001 in the Kutch region several researcher focused their attention to monitor geophysical and geochemical precursors for earthquakes in the region. In order to find out the possible geochemical precursory signals for earthquake events, we monitored radioactive gas radon-222 in sub surface soil gas at Kutch region. We have analysed the recorded soil radon-222 time series by means of nonlinear techniques such as FFT power spectral analysis, empirical mode decomposition, multi-fractal analysis along with other linear statistical methods. Some fascinating and fruitful results originated out the nonlinear analysis of the said time series have been discussed in the present paper. The entire analytical method aided us to recognize the nature and pattern of soil radon-222 emanation process. Moreover the recording and statistical and non-linear analysis of soil radon data at Kutch region will assist us to understand the preparation phase of an imminent seismic event in the region. (author)

Physiotherapy intervention in Parkinson's disease: systematic review and meta-analysis.

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Tomlinson, Claire L; Patel, Smitaa; Meek, Charmaine; Herd, Clare P; Clarke, Carl E; Stowe, Rebecca; Shah, Laila; Sackley, Catherine; Deane, Katherine H O; Wheatley, Keith; Ives, Natalie

2012-08-06

To assess the effectiveness of physiotherapy compared with no intervention in patients with Parkinson's disease. Systematic review and meta-analysis of randomised controlled trials. Literature databases, trial registries, journals, abstract books, and conference proceedings, and reference lists, searched up to the end of January 2012. Randomised controlled trials comparing physiotherapy with no intervention in patients with Parkinson's disease were eligible. Two authors independently abstracted data from each trial. Standard meta-analysis methods were used to assess the effectiveness of physiotherapy compared with no intervention. Tests for heterogeneity were used to assess for differences in treatment effect across different physiotherapy interventions used. Outcome measures were gait, functional mobility and balance, falls, clinician rated impairment and disability measures, patient rated quality of life, adverse events, compliance, and economic analysis outcomes. 39 trials of 1827 participants met the inclusion criteria, of which 29 trials provided data for the meta-analyses. Significant benefit from physiotherapy was reported for nine of 18 outcomes assessed. Outcomes which may be clinically significant were speed (0.04 m/s, 95% confidence interval 0.02 to 0.06, P<0.001), Berg balance scale (3.71 points, 2.30 to 5.11, P<0.001), and scores on the unified Parkinson's disease rating scale (total score -6.15 points, -8.57 to -3.73, P<0.001; activities of daily living subscore -1.36, -2.41 to -0.30, P=0.01; motor subscore -5.01, -6.30 to -3.72, P<0.001). Indirect comparisons of the different physiotherapy interventions found no evidence that the treatment effect differed across the interventions for any outcomes assessed, apart from motor subscores on the unified Parkinson's disease rating scale (in which one trial was found to be the cause of the heterogeneity). Physiotherapy has short term benefits in Parkinson's disease. A wide range of physiotherapy techniques

On the Impact of a Quadratic Acceleration Term in the Analysis of Position Time Series

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Bogusz, Janusz; Klos, Anna; Bos, Machiel Simon; Hunegnaw, Addisu; Teferle, Felix Norman

2016-04-01

The analysis of Global Navigation Satellite System (GNSS) position time series generally assumes that each of the coordinate component series is described by the sum of a linear rate (velocity) and various periodic terms. The residuals, the deviations between the fitted model and the observations, are then a measure of the epoch-to-epoch scatter and have been used for the analysis of the stochastic character (noise) of the time series. Often the parameters of interest in GNSS position time series are the velocities and their associated uncertainties, which have to be determined with the highest reliability. It is clear that not all GNSS position time series follow this simple linear behaviour. Therefore, we have added an acceleration term in the form of a quadratic polynomial function to the model in order to better describe the non-linear motion in the position time series. This non-linear motion could be a response to purely geophysical processes, for example, elastic rebound of the Earth's crust due to ice mass loss in Greenland, artefacts due to deficiencies in bias mitigation models, for example, of the GNSS satellite and receiver antenna phase centres, or any combination thereof. In this study we have simulated 20 time series with different stochastic characteristics such as white, flicker or random walk noise of length of 23 years. The noise amplitude was assumed at 1 mm/y-/4. Then, we added the deterministic part consisting of a linear trend of 20 mm/y (that represents the averaged horizontal velocity) and accelerations ranging from minus 0.6 to plus 0.6 mm/y2. For all these data we estimated the noise parameters with Maximum Likelihood Estimation (MLE) using the Hector software package without taken into account the non-linear term. In this way we set the benchmark to then investigate how the noise properties and velocity uncertainty may be affected by any un-modelled, non-linear term. The velocities and their uncertainties versus the accelerations for

Do Instructional Interventions Influence College Students' Critical Thinking Skills? A Meta-Analysis

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Niu, Lian; Behar-Horenstein, Linda S.; Garvan, Cyndi W.

2013-01-01

Promoting students' critical thinking skills is an important task of higher education. Colleges and universities have designed various instructional interventions to enhance students' critical thinking skills. Empirical studies have yielded inconsistent results in terms of the effects of such interventions. This meta-analysis presents a synthesis…

[Analysis of researchers' implication in a research-intervention in the Stork Network: a tool for institutional analysis].

Science.gov (United States)

Fortuna, Cinira Magali; Mesquita, Luana Pinho de; Matumoto, Silvia; Monceau, Gilles

2016-09-19

This qualitative study is based on institutional analysis as the methodological theoretical reference with the objective of analyzing researchers' implication during a research-intervention and the interferences caused by this analysis. The study involved researchers from courses in medicine, nursing, and dentistry at two universities and workers from a Regional Health Department in follow-up on the implementation of the Stork Network in São Paulo State, Brazil. The researchers worked together in the intervention and in analysis workshops, supported by an external institutional analysis. Two institutions stood out in the analysis: the research, established mainly with characteristics of neutrality, and management, with Taylorist characteristics. Differences between researchers and difficulties in identifying actions proper to network management and research were some of the interferences that were identified. The study concludes that implication analysis is a powerful tool for such studies.

Qualitative Analysis of an Educational Intervention with HIV-Discordant Heterosexual Latino Couples

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Pérez-Jiménez, David; Orengo-Aguayo, Rosaura E.

2012-01-01

Objective This qualitative analysis elucidates the potential elements of the intervention that may be effective in terms of a) increasing knowledge about HIV/AIDS in the members of this population; b) increasing the use of male condoms and the practice of mutual masturbation; and c) changing opinions toward male condom use and mutual masturbation. Methods Five heterosexual HIV-discordant couples participated in the adapted intervention, which consisted of four three-hour-long sessions. One month after the intervention, we conducted a qualitative semi-structured interview with every participant to evaluate issues related to the process and content of the activities comprising the intervention, the impact of the intervention, logistics, and recruitment and retention as well as to make a more general evaluation. The information was submitted to qualitative content analysis. Results After the intervention, participants reported having better attitudes regarding safer sex, particularly in terms of condom use. A reason given by the participants to feel more positive toward condom use and mutual masturbation was that these practices could prevent the infection of the HIV-negative partner. Conclusion This study provides important evidence of an intervention that promises to be efficacious in preventing some high-risk sexual behaviors among Latino HIV-discordant heterosexual couples. The evidence presented seems to suggest that an intervention that includes basic relevant information about HIV/AIDS, that explains the benefits of condom use and other safer sex options, and that provides effective negotiation and communication strategies could significantly reduce HIV transmission among these couples. PMID:22263299

Impact of lean interventions on time buffer reduction in a hospital setting

NARCIS (Netherlands)

Roemeling, Oskar P.; Land, Martin J.; Ahaus, Kees; Slomp, Jannes; van den Bijllaardt, Wouter

2017-01-01

This paper focuses on performance changes stemming from a series of lean interventions in a medical laboratory. This research is one of the first to link a series of lean interventions and performance over time. In a mixed-method case study, six years of patient-related throughput data, retrieved

SERI Wind Energy Program

Energy Technology Data Exchange (ETDEWEB)

Noun, R. J.

1983-06-01

The SERI Wind Energy Program manages the areas or innovative research, wind systems analysis, and environmental compatibility for the U.S. Department of Energy. Since 1978, SERI wind program staff have conducted in-house aerodynamic and engineering analyses of novel concepts for wind energy conversion and have managed over 20 subcontracts to determine technical feasibility; the most promising of these concepts is the passive blade cyclic pitch control project. In the area of systems analysis, the SERI program has analyzed the impact of intermittent generation on the reliability of electric utility systems using standard utility planning models. SERI has also conducted methodology assessments. Environmental issues related to television interference and acoustic noise from large wind turbines have been addressed. SERI has identified the causes, effects, and potential control of acoustic noise emissions from large wind turbines.

Time Series Analysis, Modeling and Applications A Computational Intelligence Perspective

CERN Document Server

Chen, Shyi-Ming

2013-01-01

Temporal and spatiotemporal data form an inherent fabric of the society as we are faced with streams of data coming from numerous sensors, data feeds, recordings associated with numerous areas of application embracing physical and human-generated phenomena (environmental data, financial markets, Internet activities, etc.). A quest for a thorough analysis, interpretation, modeling and prediction of time series comes with an ongoing challenge for developing models that are both accurate and user-friendly (interpretable). The volume is aimed to exploit the conceptual and algorithmic framework of Computational Intelligence (CI) to form a cohesive and comprehensive environment for building models of time series. The contributions covered in the volume are fully reflective of the wealth of the CI technologies by bringing together ideas, algorithms, and numeric studies, which convincingly demonstrate their relevance, maturity and visible usefulness. It reflects upon the truly remarkable diversity of methodological a...

Statistical attribution analysis of the nonstationarity of the annual runoff series of the Weihe River.

Science.gov (United States)

Xiong, Lihua; Jiang, Cong; Du, Tao

2014-01-01

Time-varying moments models based on Pearson Type III and normal distributions respectively are built under the generalized additive model in location, scale and shape (GAMLSS) framework to analyze the nonstationarity of the annual runoff series of the Weihe River, the largest tributary of the Yellow River. The detection of nonstationarities in hydrological time series (annual runoff, precipitation and temperature) from 1960 to 2009 is carried out using a GAMLSS model, and then the covariate analysis for the annual runoff series is implemented with GAMLSS. Finally, the attribution of each covariate to the nonstationarity of annual runoff is analyzed quantitatively. The results demonstrate that (1) obvious change-points exist in all three hydrological series, (2) precipitation, temperature and irrigated area are all significant covariates of the annual runoff series, and (3) temperature increase plays the main role in leading to the reduction of the annual runoff series in the study basin, followed by the decrease of precipitation and the increase of irrigated area.

Chaotic time series analysis in economics: Balance and perspectives

International Nuclear Information System (INIS)

Faggini, Marisa

2014-01-01

The aim of the paper is not to review the large body of work concerning nonlinear time series analysis in economics, about which much has been written, but rather to focus on the new techniques developed to detect chaotic behaviours in economic data. More specifically, our attention will be devoted to reviewing some of these techniques and their application to economic and financial data in order to understand why chaos theory, after a period of growing interest, appears now not to be such an interesting and promising research area

Chaotic time series analysis in economics: Balance and perspectives

Energy Technology Data Exchange (ETDEWEB)

Faggini, Marisa, E-mail: mfaggini@unisa.it [Dipartimento di Scienze Economiche e Statistiche, Università di Salerno, Fisciano 84084 (Italy)

2014-12-15

The aim of the paper is not to review the large body of work concerning nonlinear time series analysis in economics, about which much has been written, but rather to focus on the new techniques developed to detect chaotic behaviours in economic data. More specifically, our attention will be devoted to reviewing some of these techniques and their application to economic and financial data in order to understand why chaos theory, after a period of growing interest, appears now not to be such an interesting and promising research area.

Predicting the Market Potential Using Time Series Analysis

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Halmet Bradosti

2015-12-01

Full Text Available The aim of this analysis is to forecast a mini-market sales volume for the period of twelve months starting August 2015 to August 2016. The study is based on the monthly sales in Iraqi Dinar for a private local mini-market for the month of April 2014 to July 2015. As revealed on the graph and of course if the stagnant economic condition continues, the trend of future sales is down-warding. Based on time series analysis, the business may continue to operate and generate small revenues until August 2016. However, due to low sales volume, low profit margin and operating expenses, the revenues may not be adequate enough to produce positive net income and the business may not be able to operate afterward. The principal question rose from this is the forecasting sales in the region will be difficult where the business cycle so dynamic and revolutionary due to systematic risks and unforeseeable future.

Inorganic chemical analysis of environmental materials—A lecture series

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Crock, J.G.; Lamothe, P.J.

2011-01-01

At the request of the faculty of the Colorado School of Mines, Golden, Colorado, the authors prepared and presented a lecture series to the students of a graduate level advanced instrumental analysis class. The slides and text presented in this report are a compilation and condensation of this series of lectures. The purpose of this report is to present the slides and notes and to emphasize the thought processes that should be used by a scientist submitting samples for analyses in order to procure analytical data to answer a research question. First and foremost, the analytical data generated can be no better than the samples submitted. The questions to be answered must first be well defined and the appropriate samples collected from the population that will answer the question. The proper methods of analysis, including proper sample preparation and digestion techniques, must then be applied. Care must be taken to achieve the required limits of detection of the critical analytes to yield detectable analyte concentration (above "action" levels) for the majority of the study's samples and to address what portion of those analytes answer the research question-total or partial concentrations. To guarantee a robust analytical result that answers the research question(s), a well-defined quality assurance and quality control (QA/QC) plan must be employed. This QA/QC plan must include the collection and analysis of field and laboratory blanks, sample duplicates, and matrix-matched standard reference materials (SRMs). The proper SRMs may include in-house materials and/or a selection of widely available commercial materials. A discussion of the preparation and applicability of in-house reference materials is also presented. Only when all these analytical issues are sufficiently addressed can the research questions be answered with known certainty.

A Cost-Benefit Analysis of Early Childhood Hygiene Interventions in Uzbekistan

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Raushan ATANIYAZOVA

2014-11-01

Full Text Available This paper applies cost-benefit analysis (CBA technique to estimate the effectiveness of hand hygiene and oral health interventions in Uzbekistan for children of kindergarten age (3-6 years old. Our primary objective in this study is to apply CBA framework to investigate economic viability of hand hygiene and oral health interventions on respiratory diseases (influenza, bronchitis, pneumonia, intestinal diseases (diarrhea, hepatitis A, and helminthiasis, and dental caries and stomatitis. Though it is often difficult to attribute a specific hygiene intervention to a reduction in specific illness, our study shows that prevention of disease through hygiene promotion is cost-effective. To be the most effective, however, hygiene interventions should be accompanied by education and awareness-raising of teachers, parents and children.

Housefly population density correlates with shigellosis among children in Mirzapur, Bangladesh: a time series analysis.

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Tamer H Farag

Full Text Available BACKGROUND: Shigella infections are a public health problem in developing and transitional countries because of high transmissibility, severity of clinical disease, widespread antibiotic resistance and lack of a licensed vaccine. Whereas Shigellae are known to be transmitted primarily by direct fecal-oral contact and less commonly by contaminated food and water, the role of the housefly Musca domestica as a mechanical vector of transmission is less appreciated. We sought to assess the contribution of houseflies to Shigella-associated moderate-to-severe diarrhea (MSD among children less than five years old in Mirzapur, Bangladesh, a site where shigellosis is hyperendemic, and to model the potential impact of a housefly control intervention. METHODS: Stool samples from 843 children presenting to Kumudini Hospital during 2009-2010 with new episodes of MSD (diarrhea accompanied by dehydration, dysentery or hospitalization were analyzed. Housefly density was measured twice weekly in six randomly selected sentinel households. Poisson time series regression was performed and autoregression-adjusted attributable fractions (AFs were calculated using the Bruzzi method, with standard errors via jackknife procedure. FINDINGS: Dramatic springtime peaks in housefly density in 2009 and 2010 were followed one to two months later by peaks of Shigella-associated MSD among toddlers and pre-school children. Poisson time series regression showed that housefly density was associated with Shigella cases at three lags (six weeks (Incidence Rate Ratio = 1.39 [95% CI: 1.23 to 1.58] for each log increase in fly count, an association that was not confounded by ambient air temperature. Autocorrelation-adjusted AF calculations showed that a housefly control intervention could have prevented approximately 37% of the Shigella cases over the study period. INTERPRETATION: Houseflies may play an important role in the seasonal transmission of Shigella in some developing

A comparative analysis of spectral exponent estimation techniques for 1/f(β) processes with applications to the analysis of stride interval time series.

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Schaefer, Alexander; Brach, Jennifer S; Perera, Subashan; Sejdić, Ervin

2014-01-30

The time evolution and complex interactions of many nonlinear systems, such as in the human body, result in fractal types of parameter outcomes that exhibit self similarity over long time scales by a power law in the frequency spectrum S(f)=1/f(β). The scaling exponent β is thus often interpreted as a "biomarker" of relative health and decline. This paper presents a thorough comparative numerical analysis of fractal characterization techniques with specific consideration given to experimentally measured gait stride interval time series. The ideal fractal signals generated in the numerical analysis are constrained under varying lengths and biases indicative of a range of physiologically conceivable fractal signals. This analysis is to complement previous investigations of fractal characteristics in healthy and pathological gait stride interval time series, with which this study is compared. The results of our analysis showed that the averaged wavelet coefficient method consistently yielded the most accurate results. Class dependent methods proved to be unsuitable for physiological time series. Detrended fluctuation analysis as most prevailing method in the literature exhibited large estimation variances. The comparative numerical analysis and experimental applications provide a thorough basis for determining an appropriate and robust method for measuring and comparing a physiologically meaningful biomarker, the spectral index β. In consideration of the constraints of application, we note the significant drawbacks of detrended fluctuation analysis and conclude that the averaged wavelet coefficient method can provide reasonable consistency and accuracy for characterizing these fractal time series. Copyright © 2013 Elsevier B.V. All rights reserved.

A comparative analysis of spectral exponent estimation techniques for 1/fβ processes with applications to the analysis of stride interval time series

Science.gov (United States)

Schaefer, Alexander; Brach, Jennifer S.; Perera, Subashan; Sejdić, Ervin

2013-01-01

Background The time evolution and complex interactions of many nonlinear systems, such as in the human body, result in fractal types of parameter outcomes that exhibit self similarity over long time scales by a power law in the frequency spectrum S(f) = 1/fβ. The scaling exponent β is thus often interpreted as a “biomarker” of relative health and decline. New Method This paper presents a thorough comparative numerical analysis of fractal characterization techniques with specific consideration given to experimentally measured gait stride interval time series. The ideal fractal signals generated in the numerical analysis are constrained under varying lengths and biases indicative of a range of physiologically conceivable fractal signals. This analysis is to complement previous investigations of fractal characteristics in healthy and pathological gait stride interval time series, with which this study is compared. Results The results of our analysis showed that the averaged wavelet coefficient method consistently yielded the most accurate results. Comparison with Existing Methods: Class dependent methods proved to be unsuitable for physiological time series. Detrended fluctuation analysis as most prevailing method in the literature exhibited large estimation variances. Conclusions The comparative numerical analysis and experimental applications provide a thorough basis for determining an appropriate and robust method for measuring and comparing a physiologically meaningful biomarker, the spectral index β. In consideration of the constraints of application, we note the significant drawbacks of detrended fluctuation analysis and conclude that the averaged wavelet coefficient method can provide reasonable consistency and accuracy for characterizing these fractal time series. PMID:24200509

Effectiveness of Non-Pharmacological Interventions to Prevent Falls in Older People: A Systematic Overview. The SENATOR Project ONTOP Series

Science.gov (United States)

Rimland, Joseph M.; Abraha, Iosief; Dell’Aquila, Giuseppina; Cruz-Jentoft, Alfonso; Soiza, Roy; Gudmusson, Adalsteinn; Petrovic, Mirko; O’Mahony, Denis; Todd, Chris; Cherubini, Antonio

2016-01-01

Background Falls are common events in older people, which cause considerable morbidity and mortality. Non-pharmacological interventions are an important approach to prevent falls. There are a large number of systematic reviews of non-pharmacological interventions, whose evidence needs to be synthesized in order to facilitate evidence-based clinical decision making. Objectives To systematically examine reviews and meta-analyses that evaluated non-pharmacological interventions to prevent falls in older adults in the community, care facilities and hospitals. Methods We searched the electronic databases Pubmed, the Cochrane Database of Systematic Reviews, EMBASE, CINAHL, PsycINFO, PEDRO and TRIP from January 2009 to March 2015, for systematic reviews that included at least one comparative study, evaluating any non-pharmacological intervention, to prevent falls amongst older adults. The quality of the reviews was assessed using AMSTAR and ProFaNE taxonomy was used to organize the interventions. Results Fifty-nine systematic reviews were identified which consisted of single, multiple and multifactorial non-pharmacological interventions to prevent falls in older people. The most frequent ProFaNE defined interventions were exercises either alone or combined with other interventions, followed by environment/assistive technology interventions comprising environmental modifications, assistive and protective aids, staff education and vision assessment/correction. Knowledge was the third principle class of interventions as patient education. Exercise and multifactorial interventions were the most effective treatments to reduce falls in older adults, although not all types of exercise were equally effective in all subjects and in all settings. Effective exercise programs combined balance and strength training. Reviews with a higher AMSTAR score were more likely to contain more primary studies, to be updated and to perform meta-analysis. Conclusions The aim of this overview of

Duality between Time Series and Networks

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Campanharo, Andriana S. L. O.; Sirer, M. Irmak; Malmgren, R. Dean; Ramos, Fernando M.; Amaral, Luís A. Nunes.

2011-01-01

Studying the interaction between a system's components and the temporal evolution of the system are two common ways to uncover and characterize its internal workings. Recently, several maps from a time series to a network have been proposed with the intent of using network metrics to characterize time series. Although these maps demonstrate that different time series result in networks with distinct topological properties, it remains unclear how these topological properties relate to the original time series. Here, we propose a map from a time series to a network with an approximate inverse operation, making it possible to use network statistics to characterize time series and time series statistics to characterize networks. As a proof of concept, we generate an ensemble of time series ranging from periodic to random and confirm that application of the proposed map retains much of the information encoded in the original time series (or networks) after application of the map (or its inverse). Our results suggest that network analysis can be used to distinguish different dynamic regimes in time series and, perhaps more importantly, time series analysis can provide a powerful set of tools that augment the traditional network analysis toolkit to quantify networks in new and useful ways. PMID:21858093

Meta-analysis evaluating music interventions for anxiety and pain in surgery.

Science.gov (United States)

Kühlmann, A Y R; de Rooij, A; Kroese, L F; van Dijk, M; Hunink, M G M; Jeekel, J

2018-06-01

This study aimed to evaluate anxiety and pain following perioperative music interventions compared with control conditions in adult patients. Eleven electronic databases were searched for full-text publications of RCTs investigating the effect of music interventions on anxiety and pain during invasive surgery published between 1 January 1980 and 20 October 2016. Results and data were double-screened and extracted independently. Random-effects meta-analysis was used to calculate effect sizes as standardized mean differences (MDs). Heterogeneity was investigated in subgroup analyses and metaregression analyses. The review was registered in the PROSPERO database as CRD42016024921. Ninety-two RCTs (7385 patients) were included in the systematic review, of which 81 were included in the meta-analysis. Music interventions significantly decreased anxiety (MD -0·69, 95 per cent c.i. -0·88 to -0·50; P < 0·001) and pain (MD -0·50, -0·66 to -0·34; P < 0·001) compared with controls, equivalent to a decrease of 21 mm for anxiety and 10 mm for pain on a 100-mm visual analogue scale. Changes in outcome corrected for baseline were even larger: MD -1·41 (-1·89 to -0·94; P < 0·001) for anxiety and -0·54 (-0·93 to -0·15; P = 0·006) for pain. Music interventions provided during general anaesthesia significantly decreased pain compared with that in controls (MD -0·41, -0·64 to -0·18; P < 0·001). Metaregression analysis found no significant association between the effect of music interventions and age, sex, choice and timing of music, and type of anaesthesia. Risk of bias in the studies was moderate to high. Music interventions significantly reduce anxiety and pain in adult surgical patients. © 2018 The Authors. BJS published by John Wiley & Sons Ltd on behalf of BJS Society Ltd.

Data imputation analysis for Cosmic Rays time series

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Fernandes, R. C.; Lucio, P. S.; Fernandez, J. H.

2017-05-01

The occurrence of missing data concerning Galactic Cosmic Rays time series (GCR) is inevitable since loss of data is due to mechanical and human failure or technical problems and different periods of operation of GCR stations. The aim of this study was to perform multiple dataset imputation in order to depict the observational dataset. The study has used the monthly time series of GCR Climax (CLMX) and Roma (ROME) from 1960 to 2004 to simulate scenarios of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80% and 90% of missing data compared to observed ROME series, with 50 replicates. Then, the CLMX station as a proxy for allocation of these scenarios was used. Three different methods for monthly dataset imputation were selected: AMÉLIA II - runs the bootstrap Expectation Maximization algorithm, MICE - runs an algorithm via Multivariate Imputation by Chained Equations and MTSDI - an Expectation Maximization algorithm-based method for imputation of missing values in multivariate normal time series. The synthetic time series compared with the observed ROME series has also been evaluated using several skill measures as such as RMSE, NRMSE, Agreement Index, R, R2, F-test and t-test. The results showed that for CLMX and ROME, the R2 and R statistics were equal to 0.98 and 0.96, respectively. It was observed that increases in the number of gaps generate loss of quality of the time series. Data imputation was more efficient with MTSDI method, with negligible errors and best skill coefficients. The results suggest a limit of about 60% of missing data for imputation, for monthly averages, no more than this. It is noteworthy that CLMX, ROME and KIEL stations present no missing data in the target period. This methodology allowed reconstructing 43 time series.

Time series analysis of reference crop evapotranspiration for Bokaro District, Jharkhand, India

Directory of Open Access Journals (Sweden)

Gautam Ratnesh

2016-09-01

Full Text Available Evapotranspiration is the one of the major role playing element in water cycle. More accurate measurement and forecasting of Evapotranspiration would enable more efficient water resources management. This study, is therefore, particularly focused on evapotranspiration modelling and forecasting, since forecasting would provide better information for optimal water resources management. There are numerous techniques of evapotranspiration forecasting that include autoregressive (AR and moving average (MA, autoregressive moving average (ARMA, autoregressive integrated moving average (ARIMA, Thomas Feiring, etc. Out of these models ARIMA model has been found to be more suitable for analysis and forecasting of hydrological events. Therefore, in this study ARIMA models have been used for forecasting of mean monthly reference crop evapotranspiration by stochastic analysis. The data series of 102 years i.e. 1224 months of Bokaro District were used for analysis and forecasting. Different order of ARIMA model was selected on the basis of autocorrelation function (ACF and partial autocorrelation (PACF of data series. Maximum likelihood method was used for determining the parameters of the models. To see the statistical parameter of model, best fitted model is ARIMA (0, 1, 4 (0, 1, 112.

Caring for family caregivers: An analysis of a family-centered intervention

Directory of Open Access Journals (Sweden)

Carme Ferré-Grau

2014-08-01

Full Text Available Objective To assess the effectiveness of Problem-Solving Therapy (PST on family caregivers through the use of scales to measure anxiety, depression and emotional distress; and to explore facilitating factors and obstacles for its use based on the narrative of nurses. Method A clinical trial and an exploratory focus group with the use of mixed analysis methodology. The study was conducted in a primary health care center in Tarragona, Spain, and the sample consisted of 122 family caregivers who were included in the home care service, and 10 nurses who participated in the intervention group. Family caregivers with evident symptoms of anxiety, depression and emotional distress received PST in the intervention group. The intervention group also consisted of a discussion with eight nurses, which was transcribed and submitted to content analysis. Conclusion Problem-Solving Therapy proved to be effective in reducing perceived anxiety, depression and emotional distress. We identified its strong points and obstacles as described by nurses.

Analysis of rainfall and temperature time series to detect long-term climatic trends and variability over semi-arid Botswana

Science.gov (United States)

Byakatonda, Jimmy; Parida, B. P.; Kenabatho, Piet K.; Moalafhi, D. B.

2018-03-01

Arid and semi-arid environments have been identified with locations prone to impacts of climate variability and change. Investigating long-term trends is one way of tracing climate change impacts. This study investigates variability through annual and seasonal meteorological time series. Possible inhomogeneities and years of intervention are analysed using four absolute homogeneity tests. Trends in the climatic variables were determined using Mann-Kendall and Sen's Slope estimator statistics. Association of El Niño Southern Oscillation (ENSO) with local climate is also investigated through multivariate analysis. Results from the study show that rainfall time series are fully homogeneous with 78.6 and 50% of the stations for maximum and minimum temperature, respectively, showing homogeneity. Trends also indicate a general decrease of 5.8, 7.4 and 18.1% in annual, summer and winter rainfall, respectively. Warming trends are observed in annual and winter temperature at 0.3 and 1.5% for maximum temperature and 1.7 and 6.5% for minimum temperature, respectively. Rainfall reported a positive correlation with Southern Oscillation Index (SOI) and at the same time negative association with Sea Surface Temperatures (SSTs). Strong relationships between SSTs and maximum temperature are observed during the El Niño and La Niña years. These study findings could facilitate planning and management of agricultural and water resources in Botswana.

Characterization of Land Transitions Patterns from Multivariate Time Series Using Seasonal Trend Analysis and Principal Component Analysis

Directory of Open Access Journals (Sweden)

Benoit Parmentier

2014-12-01

Full Text Available Characterizing biophysical changes in land change areas over large regions with short and noisy multivariate time series and multiple temporal parameters remains a challenging task. Most studies focus on detection rather than the characterization, i.e., the manner by which surface state variables are altered by the process of changes. In this study, a procedure is presented to extract and characterize simultaneous temporal changes in MODIS multivariate times series from three surface state variables the Normalized Difference Vegetation Index (NDVI, land surface temperature (LST and albedo (ALB. The analysis involves conducting a seasonal trend analysis (STA to extract three seasonal shape parameters (Amplitude 0, Amplitude 1 and Amplitude 2 and using principal component analysis (PCA to contrast trends in change and no-change areas. We illustrate the method by characterizing trends in burned and unburned pixels in Alaska over the 2001–2009 time period. Findings show consistent and meaningful extraction of temporal patterns related to fire disturbances. The first principal component (PC1 is characterized by a decrease in mean NDVI (Amplitude 0 with a concurrent increase in albedo (the mean and the annual amplitude and an increase in LST annual variability (Amplitude 1. These results provide systematic empirical evidence of surface changes associated with one type of land change, fire disturbances, and suggest that STA with PCA may be used to characterize many other types of land transitions over large landscape areas using multivariate Earth observation time series.

Music-based interventions to reduce internalizing symptoms in children and adolescents: A meta-analysis.

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Geipel, Josephine; Koenig, Julian; Hillecke, Thomas K; Resch, Franz; Kaess, Michael

2018-01-01

Existing systematic reviews provide evidence that music therapy is an effective intervention in the treatment of children and adolescents with psychopathology. The objective of the present review was to systematically review and quantify the effects of music-based interventions in reducing internalizing symptoms (i.e., depression and anxiety) in children and adolescents using a meta-analytical approach. Databases and journals were systematically screened for studies eligible for inclusion in meta-analysis on the effects of music-based interventions in reducing internalizing symptoms. A random-effect meta-analysis using standardized mean differences (SMD) was conducted. Five studies were included. Analysis of data from (randomized) controlled trials, yielded a significant main effect (Hedge's g = -0.73; 95%CI [-1.42;-0.04], Z = 2.08, p = 0.04, k = 5), indicating a greater reduction of internalizing symptoms in youth receiving music-based interventions (n = 100) compared to different control group interventions (n = 95). The existing evidence is limited to studies of low power and methodological quality. Included studies were highly heterogeneous with respect to the nature of the intervention, the measurements applied, the samples studied, and the study design. Findings indicate that music-based interventions may be efficient in reducing the severity of internalizing symptoms in children and adolescents. While these results are encouraging with respect to the application of music-based intervention, rigorous research is necessary to replicate existing findings and provide a broader base of evidence. More research adopting well controlled study designs of high methodological quality is needed. Copyright © 2017 Elsevier B.V. All rights reserved.

TIME SERIES ANALYSIS ON STOCK MARKET FOR TEXT MINING CORRELATION OF ECONOMY NEWS

Directory of Open Access Journals (Sweden)

Sadi Evren SEKER

2014-01-01

Full Text Available This paper proposes an information retrieval methodfor the economy news. Theeffect of economy news, are researched in the wordlevel and stock market valuesare considered as the ground proof.The correlation between stock market prices and economy news is an already ad-dressed problem for most of the countries. The mostwell-known approach is ap-plying the text mining approaches to the news and some time series analysis tech-niques over stock market closing values in order toapply classification or cluster-ing algorithms over the features extracted. This study goes further and tries to askthe question what are the available time series analysis techniques for the stockmarket closing values and which one is the most suitable? In this study, the newsand their dates are collected into a database and text mining is applied over thenews, the text mining part has been kept simple with only term frequency – in-verse document frequency method. For the time series analysis part, we havestudied 10 different methods such as random walk, moving average, acceleration,Bollinger band, price rate of change, periodic average, difference, momentum orrelative strength index and their variation. In this study we have also explainedthese techniques in a comparative way and we have applied the methods overTurkish Stock Market closing values for more than a2 year period. On the otherhand, we have applied the term frequency – inversedocument frequency methodon the economy news of one of the high-circulatingnewspapers in Turkey.

Meta-Analysis of Single-Case Design Research on Self-Regulatory Interventions for Academic Performance

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Perry, Valerie; Albeg, Loren; Tung, Catherine

2012-01-01

The current study examined the effects of self-regulatory interventions on reading, writing, and math by conducting a meta-analysis of single-case design research. Self-regulatory interventions have promise as an effective approach that is both minimally invasive and involves minimal resources. Effects of the interventions were analyzed by…

Social network analysis of character interaction in the Stargate and Star Trek television series

Science.gov (United States)

Tan, Melody Shi Ai; Ujum, Ephrance Abu; Ratnavelu, Kuru

This paper undertakes a social network analysis of two science fiction television series, Stargate and Star Trek. Television series convey stories in the form of character interaction, which can be represented as “character networks”. We connect each pair of characters that exchanged spoken dialogue in any given scene demarcated in the television series transcripts. These networks are then used to characterize the overall structure and topology of each series. We find that the character networks of both series have similar structure and topology to that found in previous work on mythological and fictional networks. The character networks exhibit the small-world effects but found no significant support for power-law. Since the progression of an episode depends to a large extent on the interaction between each of its characters, the underlying network structure tells us something about the complexity of that episode’s storyline. We assessed the complexity using techniques from spectral graph theory. We found that the episode networks are structured either as (1) closed networks, (2) those containing bottlenecks that connect otherwise disconnected clusters or (3) a mixture of both.

Multifractal detrended cross-correlation analysis on gold, crude oil and foreign exchange rate time series

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Pal, Mayukha; Madhusudana Rao, P.; Manimaran, P.

2014-12-01

We apply the recently developed multifractal detrended cross-correlation analysis method to investigate the cross-correlation behavior and fractal nature between two non-stationary time series. We analyze the daily return price of gold, West Texas Intermediate and Brent crude oil, foreign exchange rate data, over a period of 18 years. The cross correlation has been measured from the Hurst scaling exponents and the singularity spectrum quantitatively. From the results, the existence of multifractal cross-correlation between all of these time series is found. We also found that the cross correlation between gold and oil prices possess uncorrelated behavior and the remaining bivariate time series possess persistent behavior. It was observed for five bivariate series that the cross-correlation exponents are less than the calculated average generalized Hurst exponents (GHE) for q0 and for one bivariate series the cross-correlation exponent is greater than GHE for all q values.

Therapeutic intervention for internalized stigma of severe mental illness: A systematic review and meta-analysis.

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Tsang, Hector W H; Ching, S C; Tang, K H; Lam, H T; Law, Peggy Y Y; Wan, C N

2016-05-01

Internalized stigma can lead to pervasive negative effects among people with severe mental illness (SMI). Although prevalence of internalized stigma is high, there is a dearth of interventions and meanwhile a lack of evidence as to their effectiveness. This study aims at unraveling the existence of different therapeutic interventions and the effectiveness internalized stigma reduction in people with SMI via a systematic review and meta-analysis. Five electronic databases were searched. Studies were included if they (1) involved community or hospital based interventions on internalized stigma, (2) included participants who were given a diagnosis of SMI>50%, and (3) were empirical and quantitative in nature. Fourteen articles were selected for extensive review and five for meta-analysis. Nine studies showed significant decrease in internalized stigma and two showed sustainable effects. Meta-analysis showed that there was a small to moderate significant effect in therapeutic interventions (SMD=-0.43; p=0.003). Among the intervention elements, four studies suggested a favorable effect of psychoeducation. Meta-analysis showed that there was small to moderate significant effect (SMD=-0.40; p=0.001). Most internalized stigma reduction programs appear to be effective. This systematic review cannot make any recommendation on which intervention is more effective although psychoeducation seems most promising. More Randomized Controlled Trials (RCT) on particular intervention components using standard outcome measures are recommended in future studies. Copyright © 2016. Published by Elsevier B.V.

Stepping Stones and Creating Futures intervention: shortened interrupted time series evaluation of a behavioural and structural health promotion and violence prevention intervention for young people in informal settlements in Durban, South Africa.

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Jewkes, Rachel; Gibbs, Andrew; Jama-Shai, Nwabisa; Willan, Samantha; Misselhorn, Alison; Mushinga, Mildred; Washington, Laura; Mbatha, Nompumelelo; Skiweyiya, Yandisa

2014-12-29

Gender-based violence and HIV are highly prevalent in the harsh environment of informal settlements and reducing violence here is very challenging. The group intervention Stepping Stones has been shown to reduce men's perpetration of violence in more rural areas, but violence experienced by women in the study was not affected. Economic empowerment interventions with gender training can protect older women from violence, but microloan interventions have proved challenging with young women. We investigated whether combining a broad economic empowerment intervention and Stepping Stones could impact on violence among young men and women. The intervention, Creating Futures, was developed as a new generation of economic empowerment intervention, which enabled livelihood strengthening though helping participants find work or set up a business, and did not give cash or make loans. We piloted Stepping Stones with Creating Futures in two informal settlements of Durban with 232 out of school youth, mostly aged 18-30 and evaluated with a shortened interrupted time series of two baseline surveys and at 28 and 58 weeks post-baseline. 94/110 men and 111/122 women completed the last assessment, 85.5% and 90.2% respectively of those enrolled. To determine trend, we built random effects regression models with each individual as the cluster for each variable, and measured the slope of the line across the time points. Men's mean earnings in the past month increased by 247% from R411 (~$40) to R1015 (~$102, and women's by 278% R 174 (~$17) to R 484 (about $48) (trend test, p < 0.0001). There was a significant reduction in women's experience of the combined measure of physical and/or sexual IPV in the prior three months from 30.3% to 18.9% (p = 0.037). This was not seen for men. However both men and women scored significantly better on gender attitudes and men significantly reduced their controlling practices in their relationship. The prevalence of moderate or severe depression

Health coaching interventions for persons with chronic conditions: a systematic review and meta-analysis protocol.

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Boehmer, Kasey R; Barakat, Suzette; Ahn, Sangwoo; Prokop, Larry J; Erwin, Patricia J; Murad, M Hassan

2016-09-01

Chronic conditions are increasingly more common and negatively impact quality of life, disability, morbidity, and mortality. Health coaching has emerged as a possible intervention to help individuals with chronic conditions adopt health supportive behaviors that improve both quality of life and health outcomes. We planned a systematic review and meta-analysis of the contemporary health coaching literature published in the last decade to evaluate the effect of health coaching on clinically important, disease-specific, functional, and behavioral outcomes. We will include randomized controlled trials or quasi-experimental studies that compared health coaching to alternative interventions or usual care. To enable adoption of effective interventions, we aim to explore how the effect of intervention is modified by the intervention components, delivering personnel (i.e., health professionals vs trained lay or peer persons), dose, frequency, and setting. Analysis of intervention outcomes will be reported and classified using an existing theoretical framework, the Theory of Patient Capacity, to identify the areas of patients' capacity to access and use healthcare and enact self-care where coaching may be an effective intervention. This systematic review and meta-analysis will identify and synthesize evidence to inform the practice of health coaching by providing evidence on components and characteristics of the intervention essential for success in individuals with chronic health conditions. PROSPERO CRD42016039730.

Connected to TV series: Quantifying series watching engagement.

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Tóth-Király, István; Bőthe, Beáta; Tóth-Fáber, Eszter; Hága, Győző; Orosz, Gábor

2017-12-01

Background and aims Television series watching stepped into a new golden age with the appearance of online series. Being highly involved in series could potentially lead to negative outcomes, but the distinction between highly engaged and problematic viewers should be distinguished. As no appropriate measure is available for identifying such differences, a short and valid measure was constructed in a multistudy investigation: the Series Watching Engagement Scale (SWES). Methods In Study 1 (N Sample1  = 740 and N Sample2  = 740), exploratory structural equation modeling and confirmatory factor analysis were used to identify the most important facets of series watching engagement. In Study 2 (N = 944), measurement invariance of the SWES was investigated between males and females. In Study 3 (N = 1,520), latent profile analysis (LPA) was conducted to identify subgroups of viewers. Results Five factors of engagement were identified in Study 1 that are of major relevance: persistence, identification, social interaction, overuse, and self-development. Study 2 supported the high levels of equivalence between males and females. In Study 3, three groups of viewers (low-, medium-, and high-engagement viewers) were identified. The highly engaged at-risk group can be differentiated from the other two along key variables of watching time and personality. Discussion The present findings support the overall validity, reliability, and usefulness of the SWES and the results of the LPA showed that it might be useful to identify at-risk viewers before the development of problematic use.

Simultaneous determination of radionuclides separable into natural decay series by use of time-interval analysis

International Nuclear Information System (INIS)

Hashimoto, Tetsuo; Sanada, Yukihisa; Uezu, Yasuhiro

2004-01-01

A delayed coincidence method, time-interval analysis (TIA), has been applied to successive α-α decay events on the millisecond time-scale. Such decay events are part of the 220 Rn→ 216 Po (T 1/2 145 ms) (Th-series) and 219 Rn→ 215 Po (T 1/2 1.78 ms) (Ac-series). By using TIA in addition to measurement of 226 Ra (U-series) from α-spectrometry by liquid scintillation counting (LSC), two natural decay series could be identified and separated. The TIA detection efficiency was improved by using the pulse-shape discrimination technique (PSD) to reject β-pulses, by solvent extraction of Ra combined with simple chemical separation, and by purging the scintillation solution with dry N 2 gas. The U- and Th-series together with the Ac-series were determined, respectively, from alpha spectra and TIA carried out immediately after Ra-extraction. Using the 221 Fr→ 217 At (T 1/2 32.3 ms) decay process as a tracer, overall yields were estimated from application of TIA to the 225 Ra (Np-decay series) at the time of maximum growth. The present method has proven useful for simultaneous determination of three radioactive decay series in environmental samples. (orig.)

Analysis of time series and size of equivalent sample

International Nuclear Information System (INIS)

Bernal, Nestor; Molina, Alicia; Pabon, Daniel; Martinez, Jorge

2004-01-01

In a meteorological context, a first approach to the modeling of time series is to use models of autoregressive type. This allows one to take into account the meteorological persistence or temporal behavior, thereby identifying the memory of the analyzed process. This article seeks to pre-sent the concept of the size of an equivalent sample, which helps to identify in the data series sub periods with a similar structure. Moreover, in this article we examine the alternative of adjusting the variance of the series, keeping in mind its temporal structure, as well as an adjustment to the covariance of two time series. This article presents two examples, the first one corresponding to seven simulated series with autoregressive structure of first order, and the second corresponding to seven meteorological series of anomalies of the air temperature at the surface in two Colombian regions

Radial artery pulse waveform analysis based on curve fitting using discrete Fourier series.

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Jiang, Zhixing; Zhang, David; Lu, Guangming

2018-04-19

Radial artery pulse diagnosis has been playing an important role in traditional Chinese medicine (TCM). For its non-invasion and convenience, the pulse diagnosis has great significance in diseases analysis of modern medicine. The practitioners sense the pulse waveforms in patients' wrist to make diagnoses based on their non-objective personal experience. With the researches of pulse acquisition platforms and computerized analysis methods, the objective study on pulse diagnosis can help the TCM to keep up with the development of modern medicine. In this paper, we propose a new method to extract feature from pulse waveform based on discrete Fourier series (DFS). It regards the waveform as one kind of signal that consists of a series of sub-components represented by sine and cosine (SC) signals with different frequencies and amplitudes. After the pulse signals are collected and preprocessed, we fit the average waveform for each sample using discrete Fourier series by least squares. The feature vector is comprised by the coefficients of discrete Fourier series function. Compared with the fitting method using Gaussian mixture function, the fitting errors of proposed method are smaller, which indicate that our method can represent the original signal better. The classification performance of proposed feature is superior to the other features extracted from waveform, liking auto-regression model and Gaussian mixture model. The coefficients of optimized DFS function, who is used to fit the arterial pressure waveforms, can obtain better performance in modeling the waveforms and holds more potential information for distinguishing different psychological states. Copyright © 2018 Elsevier B.V. All rights reserved.

Discontinuous conduction mode analysis of phase-modulated series ...

Indian Academy of Sciences (India)

modulated dc–dc series resonant converter (SRC) operating in discontinuous conduction mode (DCM). The conventional fundamental harmonic approximation technique is extended for a non-ideal series resonant tank to clarify the limitations of ...

Effects of a Sedentary Intervention on Cognitive Function.

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Edwards, Meghan K; Loprinzi, Paul D

2018-03-01

To examine the effects of a free-living, sedentary-inducing intervention on cognitive function. Randomized controlled, parallel group intervention. University campus. Thirty-three young adults (n = 23 intervention; n = 10 control). The intervention group was asked to eliminate all exercise and minimize steps to ≤5000 steps/day for 1 week, whereas the control group was asked to continue normal physical activity (PA) levels for 1 week. Both groups completed a series of 8 cognitive function assessments (assessing multiple parameters of cognition) preintervention and immediately postintervention. The intervention group was asked to resume normal PA levels for 1 week postintervention and completed the cognitive assessments for a third time at 2 weeks postintervention. Split-plot repeated-measures analysis of variance. The results of our statistical analyses showed that the group × time interaction effect was not significant ( P > .05) for any of the evaluated cognitive parameters. These findings demonstrate the need for future experimental investigations of sedentary behavior to better understand its effects on cognitive function. However, although previous work has demonstrated favorable effects of acute and chronic PA on cognitive function, our findings suggest that a 1-week period of reduced PA does not detrimentally affect cognitive function, which may have encouraging implications for individuals going through a temporary relapse in PA.

International Work-Conference on Time Series

CERN Document Server

Pomares, Héctor

2016-01-01

This volume presents selected peer-reviewed contributions from The International Work-Conference on Time Series, ITISE 2015, held in Granada, Spain, July 1-3, 2015. It discusses topics in time series analysis and forecasting, advanced methods and online learning in time series, high-dimensional and complex/big data time series as well as forecasting in real problems. The International Work-Conferences on Time Series (ITISE) provide a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing the disciplines of computer science, mathematics, statistics and econometrics.

Evaluation of a complex, population-based injury claims management intervention for improving injury outcomes: study protocol

Science.gov (United States)

Collie, Alex; Gabbe, Belinda; Fitzharris, Michael

2015-01-01

Introduction Injuries resulting from road traffic crashes are a substantial cause of disability and death worldwide. Injured persons receiving compensation have poorer recovery and return to work than those with non-compensable injury. Case or claims management is a critical component of injury compensation systems, and there is now evidence that claims management can have powerful positive impacts on recovery, but can also impede recovery or exacerbate mental health concerns in some injured people. This study seeks to evaluate the impact of a population-based injury claims management intervention in the State of Victoria, Australia, on the health of those injured in motor vehicle crashes, their experience of the compensation process, and the financial viability of the compensation system. Methods and analysis Evaluation of this complex intervention involves a series of linked but stand-alone research projects to assess the anticipated process changes, impacts and outcomes of the intervention over a 5-year time frame. Linkage and analysis of routine administrative and health system data is supplemented with a series of primary studies collecting new information. Additionally, a series of ‘action’ research projects will be undertaken to inform the implementation of the intervention. A program logic model designed by the state government Transport Accident Commission in conjunction with the research team provides the evaluation framework. Ethics and dissemination Relatively few studies have comprehensively examined the impact of compensation system processes on the health of injured persons, their satisfaction with systems processes, and impacts on the financial performance of the compensation scheme itself. The wholesale, population-based transformation of an injury claims management model is a rare opportunity to document impacts of system-level policy change on outcomes of injured persons. Findings will contribute to the evidence base of information on the

The Real-time Frequency Spectrum Analysis of Neutron Pulse Signal Series

International Nuclear Information System (INIS)

Tang Yuelin; Ren Yong; Wei Biao; Feng Peng; Mi Deling; Pan Yingjun; Li Jiansheng; Ye Cenming

2009-01-01

The frequency spectrum analysis of neutron pulse signal is a very important method in nuclear stochastic signal processing Focused on the special '0' and '1' of neutron pulse signal series, this paper proposes new rotation-table and realizes a real-time frequency spectrum algorithm under 1G Hz sample rate based on PC with add, address and SSE. The numerical experimental results show that under the count rate of 3X10 6 s -1 , this algorithm is superior to FFTW in time-consumption and can meet the real-time requirement of frequency spectrum analysis. (authors)

Statistical tools for analysis and modeling of cosmic populations and astronomical time series: CUDAHM and TSE

Science.gov (United States)

Loredo, Thomas; Budavari, Tamas; Scargle, Jeffrey D.

2018-01-01

This presentation provides an overview of open-source software packages addressing two challenging classes of astrostatistics problems. (1) CUDAHM is a C++ framework for hierarchical Bayesian modeling of cosmic populations, leveraging graphics processing units (GPUs) to enable applying this computationally challenging paradigm to large datasets. CUDAHM is motivated by measurement error problems in astronomy, where density estimation and linear and nonlinear regression must be addressed for populations of thousands to millions of objects whose features are measured with possibly complex uncertainties, potentially including selection effects. An example calculation demonstrates accurate GPU-accelerated luminosity function estimation for simulated populations of $10^6$ objects in about two hours using a single NVIDIA Tesla K40c GPU. (2) Time Series Explorer (TSE) is a collection of software in Python and MATLAB for exploratory analysis and statistical modeling of astronomical time series. It comprises a library of stand-alone functions and classes, as well as an application environment for interactive exploration of times series data. The presentation will summarize key capabilities of this emerging project, including new algorithms for analysis of irregularly-sampled time series.

Linking Brief Functional Analysis to Intervention Design in General Education Settings

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Ishuin, Tifanie

2009-01-01

This study focused on the utility and applicability of brief functional analysis in general education settings. The purpose of the study was to first identify the environmental variables maintaining noncompliance through a brief functional analysis, and then to design and implement a functionally equivalent intervention. The participant exhibited…

Antigravity treadmill training during the early rehabilitation phase following unicompartmental knee arthroplasty: A case series.

Science.gov (United States)

Huang, Chun-Hao; Schroeder, E Todd; Powers, Christopher

2018-02-26

Patients who have undergone unicompartmental knee arthroplasty (UKA) have been reported to exhibit altered gait 19-25 months post-surgery. The most common gait impairment in this population is inadequate knee flexion and a corresponding decrease in the knee extensor moment during loading response (i.e., quadriceps avoidance). The purpose of this case series was to determine whether incorporation of antigravity treadmill training into a standard physical therapy program can eliminate quadriceps avoidance gait during the early rehabilitation phase following UKA. Four females who underwent UKA were recruited for this study. Participants completed antigravity treadmill training three times per week for 12 weeks in addition to their standard physical therapy program. Instrumented gait analysis was performed at baseline (pre-intervention), week 6 (mid-intervention), and week 12 (post-intervention). We found that peak knee flexion and the peak knee extensor moment during the weight acceptance phase of gait increased to normal values following the 12-week intervention period (14.1 ± 6.5° to 20.6 ± 1.5° and 0.4 ± 0.3 to 0.7 ± 0.2 Nm/kg respectively). The findings of this case series suggest that a standard physical therapy program that incorporates early gait training using an antigravity treadmill may be beneficial in eliminating "quadriceps avoidance" during the early rehabilitation phase following UKA.

Hybrid Wavelet De-noising and Rank-Set Pair Analysis approach for forecasting hydro-meteorological time series

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WANG, D.; Wang, Y.; Zeng, X.

2017-12-01

Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, Wavelet De-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series.

Application of the Allan Variance to Time Series Analysis in Astrometry and Geodesy: A Review.

Science.gov (United States)

Malkin, Zinovy

2016-04-01

The Allan variance (AVAR) was introduced 50 years ago as a statistical tool for assessing the frequency standards deviations. For the past decades, AVAR has increasingly been used in geodesy and astrometry to assess the noise characteristics in geodetic and astrometric time series. A specific feature of astrometric and geodetic measurements, as compared with clock measurements, is that they are generally associated with uncertainties; thus, an appropriate weighting should be applied during data analysis. In addition, some physically connected scalar time series naturally form series of multidimensional vectors. For example, three station coordinates time series X, Y, and Z can be combined to analyze 3-D station position variations. The classical AVAR is not intended for processing unevenly weighted and/or multidimensional data. Therefore, AVAR modifications, namely weighted AVAR (WAVAR), multidimensional AVAR (MAVAR), and weighted multidimensional AVAR (WMAVAR), were introduced to overcome these deficiencies. In this paper, a brief review is given of the experience of using AVAR and its modifications in processing astrogeodetic time series.

Correlation and multifractality in climatological time series

International Nuclear Information System (INIS)

Pedron, I T

2010-01-01

Climate can be described by statistical analysis of mean values of atmospheric variables over a period. It is possible to detect correlations in climatological time series and to classify its behavior. In this work the Hurst exponent, which can characterize correlation and persistence in time series, is obtained by using the Detrended Fluctuation Analysis (DFA) method. Data series of temperature, precipitation, humidity, solar radiation, wind speed, maximum squall, atmospheric pressure and randomic series are studied. Furthermore, the multifractality of such series is analyzed applying the Multifractal Detrended Fluctuation Analysis (MF-DFA) method. The results indicate presence of correlation (persistent character) in all climatological series and multifractality as well. A larger set of data, and longer, could provide better results indicating the universality of the exponents.

Implementation of targeted medication adherence interventions within a community chain pharmacy practice: The Pennsylvania Project.

Science.gov (United States)

Bacci, Jennifer L; McGrath, Stephanie Harriman; Pringle, Janice L; Maguire, Michelle A; McGivney, Melissa Somma

2014-01-01

To identify facilitators and barriers to implementing targeted medication adherence interventions in community chain pharmacies, and describe adaptations of the targeted intervention and organizational structure within each individual pharmacy practice. Qualitative study. Central and western Pennsylvania from February to April 2012. Rite Aid pharmacists staffed at the 118 Pennsylvania Project intervention sites. Qualitative analysis of pharmacists' perceptions of facilitators and barriers experienced, targeted intervention and organizational structure adaptations implemented, and training and preparation prior to implementation. A total of 15 key informant interviews were conducted from February to April 2012. Ten pharmacists from "early adopter" practices and five pharmacists from "traditionalist" practices were interviewed. Five themes emerged regarding the implementation of targeted interventions, including all pharmacists' need to understand the relationship of patient care programs to their corporation's vision; providing individualized, continual support and mentoring to pharmacists; anticipating barriers before implementation of patient care programs; encouraging active patient engagement; and establishing best practices regarding implementation of patient care services. This qualitative analysis revealed that there are a series of key steps that can be taken before the execution of targeted interventions that may promote successful implementation of medication therapy management in community chain pharmacies.

Comparative performance analysis of shunt and series passive filter for LED lamp

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Sarwono, Edi; Facta, Mochammad; Handoko, Susatyo

2018-03-01

Light Emitting Diode lamp or LED lamp nowadays is widely used by consumers as a new innovation in the lighting technologies due to its energy saving for low power consumption lamps for brighter light intensity. How ever, the LED lamp produce an electric pollutant known as harmonics. The harmonics is generated by rectifier as part of LED lamp circuit. The present of harmonics in current or voltage has made the source waveform from the grid is distorted. This distortion may cause inacurrate measurement, mall function, and excessive heating for any element at the grid. This paper present an analysis work of shunt and series filters to suppress the harmonics generated by the LED lamp circuit. The work was initiated by conducting several tests to investigate the harmonic content of voltage and currents. The measurements in this work were carried out by using HIOKI Power Quality Analyzer 3197. The measurement results showed that the harmonics current of tested LED lamps were above the limit of IEEE standard 519-2014. Based on the measurement results shunt and series filters were constructed as low pass filters. The bode analysis were appled during construction and prediction of the filters performance. Based on experimental results, the application of shunt filter at input side of LED lamp has reduced THD current up to 88%. On the other hand, the series filter has significantly reduced THD current up to 92%.

Time series analysis of pressure fluctuation in gas-solid fluidized beds

Directory of Open Access Journals (Sweden)

C. Alberto S. Felipe

2004-09-01

Full Text Available The purpose of the present work was to study the differentiation of states of typical fluidization (single bubble, multiple bubble and slugging in a gas-solid fluidized bed, using spectral analysis of pressure fluctuation time series. The effects of the method of measuring (differential and absolute pressure fluctuations and the axial position of the probes in the fluidization column on the identification of each of the regimes studied were evaluated. Fast Fourier Transform (FFT was the mathematic tool used to analysing the data of pressure fluctuations, which expresses the behavior of a time series in the frequency domain. Results indicated that the plenum chamber was a place for reliable measurement and that care should be taken in measurement in the dense phase. The method allowed fluid dynamic regimes to be differentiated by their dominant frequency characteristics.

Activity-based cost analysis in catheter-based angiography and interventional radiology

International Nuclear Information System (INIS)

Rautio, R.; Keski-Nisula, L.; Paakkala, T.

2003-01-01

The aim of this study was to analyse the costs of the interventional radiology unit and to identify the cost factors in the different activities of catheter-based angiographies and interventional radiology. In 1999 the number of procedures in the interventional radiological unit at Tampere University Hospital was 2968; 1601 of these were diagnostic angiographies, 526 endovascular and 841 nonvascular interventions. The costs were analysed by using Activity Based Cost (ABC) analysis. The budget of the interventional unit was approximately 1.8 million Euro. Material costs accounted for 67%, personnel costs for 17%, equipment costs for 14% and premises costs for 2% of this. The most expensive products were endografting of aortic aneurysms, with a mean price of 5291 Euro and embolizations of cerebral aneurysms (4472 Euro). Endografts formed 87.3% of the total costs in endografting and Guglielmi detachable coils accounted for 63.3% of the total costs in embolizations. The material costs formed the majority of the costs, especially in the newest and most complicated endovascular treatments. Despite the high cost of angiography equipment, its share of the costs is minor. In our experience ABC system is suitable for analysing costs in interventional radiology. (orig.)

Wet tropospheric delays forecast based on Vienna Mapping Function time series analysis

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Rzepecka, Zofia; Kalita, Jakub

2016-04-01

It is well known that the dry part of the zenith tropospheric delay (ZTD) is much easier to model than the wet part (ZTW). The aim of the research is applying stochastic modeling and prediction of ZTW using time series analysis tools. Application of time series analysis enables closer understanding of ZTW behavior as well as short-term prediction of future ZTW values. The ZTW data used for the studies were obtained from the GGOS service hold by Vienna technical University. The resolution of the data is six hours. ZTW for the years 2010 -2013 were adopted for the study. The International GNSS Service (IGS) permanent stations LAMA and GOPE, located in mid-latitudes, were admitted for the investigations. Initially the seasonal part was separated and modeled using periodic signals and frequency analysis. The prominent annual and semi-annual signals were removed using sines and consines functions. The autocorrelation of the resulting signal is significant for several days (20-30 samples). The residuals of this fitting were further analyzed and modeled with ARIMA processes. For both the stations optimal ARMA processes based on several criterions were obtained. On this basis predicted ZTW values were computed for one day ahead, leaving the white process residuals. Accuracy of the prediction can be estimated at about 3 cm.

Assessing Spontaneous Combustion Instability with Nonlinear Time Series Analysis

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Eberhart, C. J.; Casiano, M. J.

2015-01-01

Considerable interest lies in the ability to characterize the onset of spontaneous instabilities within liquid propellant rocket engine (LPRE) combustion devices. Linear techniques, such as fast Fourier transforms, various correlation parameters, and critical damping parameters, have been used at great length for over fifty years. Recently, nonlinear time series methods have been applied to deduce information pertaining to instability incipiency hidden in seemingly stochastic combustion noise. A technique commonly used in biological sciences known as the Multifractal Detrended Fluctuation Analysis has been extended to the combustion dynamics field, and is introduced here as a data analysis approach complementary to linear ones. Advancing, a modified technique is leveraged to extract artifacts of impending combustion instability that present themselves a priori growth to limit cycle amplitudes. Analysis is demonstrated on data from J-2X gas generator testing during which a distinct spontaneous instability was observed. Comparisons are made to previous work wherein the data were characterized using linear approaches. Verification of the technique is performed by examining idealized signals and comparing two separate, independently developed tools.

Recurrent epidemic cycles driven by intervention in a population of two susceptibility types

International Nuclear Information System (INIS)

Juanico, Drandreb Earl O

2014-01-01

Epidemics have been known to persist in the form of recurrence cycles. Despite intervention efforts through vaccination and targeted social distancing, infectious diseases like influenza continue to appear intermittently over time. I have undertaken an analysis of a stochastic epidemic model to explore the hypothesis that intervention efforts actually drive epidemic cycles. Time series from simulations of the model reveal oscillations exhibiting a similar temporal signature as influenza epidemics. The power-spectral density indicates a resonant frequency, which approximately corresponds to the apparent annual seasonality of influenza in temperate zones. Asymptotic solution to the backward Kolmogorov equation of the dynamics corresponds to an exponentially-decaying mean-exit time as a function of the intervention rate. Intervention must be implemented at a sufficiently high rate to extinguish the infection. The results demonstrate that intervention efforts can induce epidemic cycles, and that the temporal signature of cycles can provide early warning of imminent outbreaks

Most probable dimension value and most flat interval methods for automatic estimation of dimension from time series

International Nuclear Information System (INIS)

Corana, A.; Bortolan, G.; Casaleggio, A.

2004-01-01

We present and compare two automatic methods for dimension estimation from time series. Both methods, based on conceptually different approaches, work on the derivative of the bi-logarithmic plot of the correlation integral versus the correlation length (log-log plot). The first method searches for the most probable dimension values (MPDV) and associates to each of them a possible scaling region. The second one searches for the most flat intervals (MFI) in the derivative of the log-log plot. The automatic procedures include the evaluation of the candidate scaling regions using two reliability indices. The data set used to test the methods consists of time series from known model attractors with and without the addition of noise, structured time series, and electrocardiographic signals from the MIT-BIH ECG database. Statistical analysis of results was carried out by means of paired t-test, and no statistically significant differences were found in the large majority of the trials. Consistent results are also obtained dealing with 'difficult' time series. In general for a more robust and reliable estimate, the use of both methods may represent a good solution when time series from complex systems are analyzed. Although we present results for the correlation dimension only, the procedures can also be used for the automatic estimation of generalized q-order dimensions and pointwise dimension. We think that the proposed methods, eliminating the need of operator intervention, allow a faster and more objective analysis, thus improving the usefulness of dimension analysis for the characterization of time series obtained from complex dynamical systems

Evaluation of Internet-Based Interventions on Waist Circumference Reduction: A Meta-Analysis.

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Seo, Dong-Chul; Niu, Jingjing

2015-07-21

Internet-based interventions are more cost-effective than conventional interventions and can provide immediate, easy-to-access, and individually tailored support for behavior change. Waist circumference is a strong predictor of an increased risk for a host of diseases, such as hypertension, diabetes, and dyslipidemia, independent of body mass index. To date, no study has examined the effect of Internet-based lifestyle interventions on waist circumference change. This study aimed to systematically review the effect of Internet-based interventions on waist circumference change among adults. This meta-analysis reviewed randomized controlled trials (N=31 trials and 8442 participants) that used the Internet as a main intervention approach and reported changes in waist circumference. Internet-based interventions showed a significant reduction in waist circumference (mean change -2.99 cm, 95% CI -3.68 to -2.30, I(2)=93.3%) and significantly better effects on waist circumference loss (mean loss 2.38 cm, 95% CI 1.61-3.25, I(2)=97.2%) than minimal interventions such as information-only groups. Meta-regression results showed that baseline waist circumference, gender, and the presence of social support in the intervention were significantly associated with waist circumference reduction. Internet-based interventions have a significant and promising effect on waist circumference change. Incorporating social support into an Internet-based intervention appears to be useful in reducing waist circumference. Considerable heterogeneity exists among the effects of Internet-based interventions. The design of an intervention may have a significant impact on the effectiveness of the intervention.

Introduction to Time Series Modeling

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Kitagawa, Genshiro

2010-01-01

In time series modeling, the behavior of a certain phenomenon is expressed in relation to the past values of itself and other covariates. Since many important phenomena in statistical analysis are actually time series and the identification of conditional distribution of the phenomenon is an essential part of the statistical modeling, it is very important and useful to learn fundamental methods of time series modeling. Illustrating how to build models for time series using basic methods, "Introduction to Time Series Modeling" covers numerous time series models and the various tools f

Spatial analysis of precipitation time series over the Upper Indus Basin

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Latif, Yasir; Yaoming, Ma; Yaseen, Muhammad

2018-01-01

The upper Indus basin (UIB) holds one of the most substantial river systems in the world, contributing roughly half of the available surface water in Pakistan. This water provides necessary support for agriculture, domestic consumption, and hydropower generation; all critical for a stable economy in Pakistan. This study has identified trends, analyzed variability, and assessed changes in both annual and seasonal precipitation during four time series, identified herein as: (first) 1961-2013, (second) 1971-2013, (third) 1981-2013, and (fourth) 1991-2013, over the UIB. This study investigated spatial characteristics of the precipitation time series over 15 weather stations and provides strong evidence of annual precipitation by determining significant trends at 6 stations (Astore, Chilas, Dir, Drosh, Gupis, and Kakul) out of the 15 studied stations, revealing a significant negative trend during the fourth time series. Our study also showed significantly increased precipitation at Bunji, Chitral, and Skardu, whereas such trends at the rest of the stations appear insignificant. Moreover, our study found that seasonal precipitation decreased at some locations (at a high level of significance), as well as periods of scarce precipitation during all four seasons. The observed decreases in precipitation appear stronger and more significant in autumn; having 10 stations exhibiting decreasing precipitation during the fourth time series, with respect to time and space. Furthermore, the observed decreases in precipitation appear robust and more significant for regions at high elevation (>1300 m). This analysis concludes that decreasing precipitation dominated the UIB, both temporally and spatially including in the higher areas.

RECONSTRUCTION OF PRECIPITATION SERIES AND ANALYSIS OF CLIMATE CHANGE OVER PAST 500 YEARS IN NORTHERN CHINA

Institute of Scientific and Technical Information of China (English)

RONG Yan-shu; TU Qi-pu

2005-01-01

It is important and necessary to get a much longer precipitation series in order to research features of drought/flood and climate change.Based on dryness and wetness grades series of 18 stations in Northern China of 533 years from 1470 to 2002, the Moving Cumulative Frequency Method (MCFM) was developed, moving average precipitation series from 1499 to 2002 were reconstructed by testing three kinds of average precipitation, and the features of climate change and dry and wet periods were researched by using reconstructed precipitation series in the present paper.The results showed that there were good relationship between the reconstructed precipitation series and the observation precipitation series since 1954 and their relative root-mean-square error were below 1.89%, that the relation between reconstructed series and the dryness and wetness grades series were nonlinear and this nonlinear relation implied that reconstructed series were reliable and could became foundation data for researching evolution of the drought and flood.Analysis of climate change upon reconstructed precipitation series revealed that although drought intensity of recent dry period from middle 1970s of 20th century until early 21st century was not the strongest in historical climate of Northern China, intensity and duration of wet period was a great deal decreasing and shortening respectively, climate evolve to aridification situation in Northern China.

Adventures in Modern Time Series Analysis: From the Sun to the Crab Nebula and Beyond

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Scargle, Jeffrey

2014-01-01

With the generation of long, precise, and finely sampled time series the Age of Digital Astronomy is uncovering and elucidating energetic dynamical processes throughout the Universe. Fulfilling these opportunities requires data effective analysis techniques rapidly and automatically implementing advanced concepts. The Time Series Explorer, under development in collaboration with Tom Loredo, provides tools ranging from simple but optimal histograms to time and frequency domain analysis for arbitrary data modes with any time sampling. Much of this development owes its existence to Joe Bredekamp and the encouragement he provided over several decades. Sample results for solar chromospheric activity, gamma-ray activity in the Crab Nebula, active galactic nuclei and gamma-ray bursts will be displayed.

Multimodal Counseling Interventions: Effect on Human Papilloma Virus Vaccination Acceptance

Directory of Open Access Journals (Sweden)

Oroma Nwanodi

2017-11-01

Full Text Available Human papilloma virus (HPV vaccine was developed to reduce HPV-attributable cancers, external genital warts (EGW, and recurrent respiratory papillomatosis. Adolescent HPV vaccination series completion rates are less than 40% in the United States of America, but up to 80% in Australia and the United Kingdom. Population-based herd immunity requires 80% or greater vaccination series completion rates. Pro-vaccination counseling facilitates increased vaccination rates. Multimodal counseling interventions may increase HPV vaccination series non-completers’ HPV-attributable disease knowledge and HPV-attributable disease prophylaxis (vaccination acceptance over a brief 14-sentence counseling intervention. An online, 4-group, randomized controlled trial, with 260 or more participants per group, found that parents were more likely to accept HPV vaccination offers for their children than were childless young adults for themselves (68.2% and 52.9%. A combined audiovisual and patient health education handout (PHEH intervention raised knowledge of HPV vaccination purpose, p = 0.02, and HPV vaccination acceptance for seven items, p < 0.001 to p = 0.023. The audiovisual intervention increased HPV vaccination acceptance for five items, p < 0.001 to p = 0.006. That HPV causes EGW, and that HPV vaccination prevents HPV-attributable diseases were better conveyed by the combined audiovisual and PHEH than the control 14-sentence counseling intervention alone.

Vision and Relevant Risk Factor Interventions for Preventing Falls among Older People: A Network Meta-analysis.

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Zhang, Xin-Yi; Shuai, Jian; Li, Li-Ping

2015-05-28

Our study objective was to determine the effect of vision intervention and combinations of different intervention components on preventing falls and fall-related injuries among older people. Six electronic databases were searched to identify seven articles published before May, 2014. We conducted a systematic review of data from seven randomized controlled trails and identified eight regimens: vision intervention alone (V), vision plus exercise (referred to as physical exercise) interventions (V + E), vision plus home hazard interventions (V + HH), vision plus exercise plus home hazard interventions (V + E + HH), vision plus exercise plus sensation interventions (V + E + S), vision plus hearing interventions (V + H), vision plus various risk factor assessment and interventions (V + VRF), and the control group (C, no intervention group). The main outcome was the incidence of falls during the follow-up period. Seven papers included 2723 participants. Network meta-analysis of seven trials, using pairwise comparisons between each intervention, indicated there was no significant difference. However, there was a trend in which intervention incorporating V + VRF had more advantages than any other combination of interventions. In conclusion, V + VRF proves to be more effective than other V combination interventions in preventing falls in older people (≥65 years of age). V alone appears less effective in our network meta-analysis.

Cost-Effectiveness Analysis Comparing Pre-Diagnosis Autism Spectrum Disorder (ASD)-Targeted Intervention with Ontario's Autism Intervention Program

Science.gov (United States)

Penner, Melanie; Rayar, Meera; Bashir, Naazish; Roberts, S. Wendy; Hancock-Howard, Rebecca L.; Coyte, Peter C.

2015-01-01

Novel management strategies for autism spectrum disorder (ASD) propose providing interventions before diagnosis. We performed a cost-effectiveness analysis comparing the costs and dependency-free life years (DFLYs) generated by pre-diagnosis intensive Early Start Denver Model (ESDM-I); pre-diagnosis parent-delivered ESDM (ESDM-PD); and the Ontario…

Systematic review and meta-analysis of music interventions in hypertension treatment: a quest for answers.

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Kühlmann, Anne Y R; Etnel, Jonathan R G; Roos-Hesselink, Jolien W; Jeekel, Johannes; Bogers, Ad J J C; Takkenberg, Johanna J M

2016-04-19

Adverse effects, treatment resistance and high costs associated with pharmacological treatment of hypertension have led to growing interest in non-pharmacological complementary therapies such as music interventions. This meta-analysis aims to provide an overview of reported evidence on the efficacy of music interventions in the treatment of hypertension. A systematic literature search was conducted for publications on the effect of music interventions on blood pressure in adult hypertensive subjects published between January 1990-June 2014. Randomized controlled trials with a follow-up duration ≥28 days were included. Blood pressure measures were pooled using inverse variance weighting. Of the 1689 abstracts reviewed, 10 randomized controlled trials were included. Random-effects pooling of the music intervention groups showed a trend toward a decrease in mean systolic blood pressure (SBP) from 144 mmHg(95 % CI:137-152) to 134 mmHg(95 % CI:124-144), and in mean diastolic blood pressure (DBP) from 84 mmHg(95 % CI:78-89) to 78 mmHg(95 % CI:73-84). Fixed-effect analysis of a subgroup of 3 trials with valid control groups showed a significant decrease in pooled mean SBP and DBP in both intervention and control groups. A comparison between music intervention groups and control groups was not possible due to unavailable measures of dispersion. This systematic review and meta-analysis revealed a trend towards a decrease in blood pressure in hypertensive patients who received music interventions, but failed to establish a cause-effect relationship between music interventions and blood pressure reduction. Considering the potential value of this safe, low-cost intervention, well-designed, high quality and sufficiently powered randomized studies assessing the efficacy of music interventions in the treatment of hypertension are warranted.

Family-Based Interventions in Preventing Children and Adolescents from Using Tobacco: A Systematic Review and Meta-Analysis.

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Thomas, Roger E; Baker, Philip R A; Thomas, Bennett C

2016-07-01

Tobacco is the main preventable cause of death and disease worldwide. Adolescent smoking is increasing in many countries with poorer countries following the earlier experiences of affluent countries. Preventing adolescents from starting smoking is crucial to decreasing tobacco-related illness. To assess effectiveness of family-based interventions alone and combined with school-based interventions to prevent children and adolescents from initiating tobacco use. Fourteen bibliographic databases and the Internet, journals hand-searched, and experts consulted. Randomized controlled trials (RCTs) with children or adolescents and families, interventions to prevent starting tobacco use, and follow-up ≥6 months. Abstracts/titles independently assessed and data independently entered by 2 authors. Risk of bias was assessed with the Cochrane Risk-of-Bias tool. Twenty-seven RCTs were included. Nine trials of never-smokers compared with a control provided data for meta-analysis. Family intervention trials had significantly fewer students who started smoking. Meta-analysis of 2 RCTs of combined family and school interventions compared with school only, showed additional significant benefit. The common feature of effective high-intensity interventions was encouraging authoritative parenting. Only 14 RCTs provided data for meta-analysis (approximately a third of participants). Of the 13 RCTs that did not provide data for meta-analysis 8 compared a family intervention with no intervention and 1 reported significant effects, and 5 compared a family combined with school intervention with a school intervention only and none reported additional significant effects. There is moderate-quality evidence that family-based interventions prevent children and adolescents from starting to smoke. Copyright © 2016 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.

Motivating People To Be Physically Active. Physical Activity Intervention Series.

Science.gov (United States)

Marcus, Bess H.; Forsyth, LeighAnn H.

This book describes proven methods for helping people change from inactive to active living. The behavior change methods are useful for healthy adults as well as individuals with chronic physical and psychological conditions. The book describes intervention programs for individuals and groups and for workplace and community settings. Part 1,…

A Descriptive Analysis of Tactical Casualty Care Interventions Performed by Law Enforcement Personnel in the State of Wisconsin, 2010-2015.

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Stiles, Chad M; Cook, Christopher; Sztajnkrycer, Matthew D

2017-06-01

Introduction Based upon military experience, law enforcement has developed guidelines for medical care during high-threat conditions. The purpose of the current study was to provide a descriptive analysis of reported outcomes of law enforcement medical interventions. This was a descriptive analysis of a convenience sample of cases submitted to the Wisconsin Tactical Medicine Initiative (Wisconsin USA), after the provision of successful patient care, between January 2010 and December 2015. The study was reviewed by the Mayo Foundation Institutional Review Board (Rochester, Minnesota USA) and deemed exempt. Nineteen agencies submitted information during the study period. Of the 56 episodes of care reported, four (7.1%) cases involved care provided to injured officers while 52 (92.9%) involved care to injured civilians, including suspects. In at least two cases, on-going threats existed during the provision of medical care to an injured civilian. Law enforcement rendered care prior to Emergency Medical Services (EMS) arrival in all but two cases. The current case series demonstrates the life-saving potential for law enforcement personnel trained and equipped under current Tactical Combat Casualty Care (TCCC)/ Committee on Tactical Emergency Casualty Care (C-TECC) tactical casualty care guidelines. Although originally developed to save the lives of wounded combat personnel, in the civilian sector, the training appears more likely to save victims rather than law enforcement personnel. Stiles CM , Cook C , Sztajnkrycer MD . A descriptive analysis of tactical casualty care interventions performed by law enforcement personnel in the State of Wisconsin, 2010-2015. Prehosp Disaster Med. 2017;32(3):284-288.

Causality as a Rigorous Notion and Quantitative Causality Analysis with Time Series

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Liang, X. S.

2017-12-01

Given two time series, can one faithfully tell, in a rigorous and quantitative way, the cause and effect between them? Here we show that this important and challenging question (one of the major challenges in the science of big data), which is of interest in a wide variety of disciplines, has a positive answer. Particularly, for linear systems, the maximal likelihood estimator of the causality from a series X2 to another series X1, written T2→1, turns out to be concise in form: T2→1 = [C11 C12 C2,d1 — C112 C1,d1] / [C112 C22 — C11C122] where Cij (i,j=1,2) is the sample covariance between Xi and Xj, and Ci,dj the covariance between Xi and ΔXj/Δt, the difference approximation of dXj/dt using the Euler forward scheme. An immediate corollary is that causation implies correlation, but not vice versa, resolving the long-standing debate over causation versus correlation. The above formula has been validated with touchstone series purportedly generated with one-way causality that evades the classical approaches such as Granger causality test and transfer entropy analysis. It has also been applied successfully to the investigation of many real problems. Through a simple analysis with the stock series of IBM and GE, an unusually strong one-way causality is identified from the former to the latter in their early era, revealing to us an old story, which has almost faded into oblivion, about "Seven Dwarfs" competing with a "Giant" for the computer market. Another example presented here regards the cause-effect relation between the two climate modes, El Niño and Indian Ocean Dipole (IOD). In general, these modes are mutually causal, but the causality is asymmetric. To El Niño, the information flowing from IOD manifests itself as a propagation of uncertainty from the Indian Ocean. In the third example, an unambiguous one-way causality is found between CO2 and the global mean temperature anomaly. While it is confirmed that CO2 indeed drives the recent global warming

Multiple Indicator Stationary Time Series Models.

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Sivo, Stephen A.

2001-01-01

Discusses the propriety and practical advantages of specifying multivariate time series models in the context of structural equation modeling for time series and longitudinal panel data. For time series data, the multiple indicator model specification improves on classical time series analysis. For panel data, the multiple indicator model…

Workplace interventions to improve work ability: A systematic review and meta-analysis of their effectiveness.

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Oakman, Jodi; Neupane, Subas; Proper, Karin I; Kinsman, Natasha; Nygård, Clas-Håkan

2018-03-01

Objective Extended working lives due to an ageing population will necessitate the maintenance of work ability across the life course. This systematic review aimed to analyze whether workplace interventions positively impact work ability. Methods We searched Medline, PsycINFO, CINAHL and Embase databases using relevant terms. Work-based interventions were those focused on individuals, the workplace, or multilevel (combination). Work ability - measured using the work ability index (WAI) or the single-item work ability score (WAS) - was the outcome measure. Grading of Recommendations Assessment, Development & Evaluation (GRADE) criteria was used to assess evidence quality, and impact statements were developed to synthesize the results. Meta-analysis was undertaken where appropriate. Results We reviewed 17 randomized control trials (comprising 22 articles). Multilevel interventions (N=5) included changes to work arrangements and liaisons with supervisors, whilst individual-focused interventions (N=12) involved behavior change or exercise programs. We identified only evidence of a moderate quality for either individual or multilevel interventions aiming to improve work ability. The meta-analysis of 13 studies found a small positive significant effect for interventions on work ability [overall pooled mean 0.12, 95% confidence interval (CI) 0.03-0.21] with no heterogeneity for the effect size (Chi 2 =11.28, P=0.51; I 2 =0%). Conclusions The meta-analysis showed a small positive effect, suggesting that workplace interventions might improve work ability. However, the quality of the evidence base was only moderate, precluding any firm conclusion. Further high quality studies are require to establish the role of interventions on work ability.

An Interactive Analysis of Hyperboles in a British TV Series: Implications For EFL Classes

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Sert, Olcay

2008-01-01

This paper, part of an ongoing study on the analysis of hyperboles in a British TV series, reports findings drawing upon a 90,000 word corpus. The findings are compared to the ones from CANCODE (McCarthy and Carter 2004), a five-million word corpus of spontaneous speech, in order to identify similarities between the two. The analysis showed that…

100 classic papers of interventional radiology: A citation analysis

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Crockett, Matthew T; Browne, Ronan FJ; MacMahon, Peter J; Lawler, Leo

2015-01-01

AIM: To define the 100 citation classic papers of interventional radiology. METHODS: Using the database of Journal Citation Reports the 40 highest impact factor radiology journals were chosen. From these journals the 100 most cited interventional radiology papers were chosen and analysed. RESULTS: The top paper received 2497 citations and the 100th paper 200 citations. The average number of citations was 320. Dates of publication ranged from 1953 - 2005. Most papers originated in the United States (n = 67) followed by Italy (n = 20) and France (n = 10). Harvard University (n = 18) and Osped Civile (n = 11) were the most prolific institutions. Ten journals produced all of the top 100 papers with “Radiology” and “AJR” making up the majority. SN Goldberg and T Livraghi were the most prolific authors. Nearly two thirds of the papers (n = 61) were published after 1990. CONCLUSION: This analysis identifies many of the landmark interventional radiology papers and provides a fascinating insight into the changing discourse within the field. It also identifies topics, authors and institutions which have impacted greatly on the specialty. PMID:25918585

100 classic papers of interventional radiology: A citation analysis.

Science.gov (United States)

Crockett, Matthew T; Browne, Ronan Fj; MacMahon, Peter J; Lawler, Leo

2015-04-28

To define the 100 citation classic papers of interventional radiology. Using the database of Journal Citation Reports the 40 highest impact factor radiology journals were chosen. From these journals the 100 most cited interventional radiology papers were chosen and analysed. The top paper received 2497 citations and the 100(th) paper 200 citations. The average number of citations was 320. Dates of publication ranged from 1953 - 2005. Most papers originated in the United States (n = 67) followed by Italy (n = 20) and France (n = 10). Harvard University (n = 18) and Osped Civile (n = 11) were the most prolific institutions. Ten journals produced all of the top 100 papers with "Radiology" and "AJR" making up the majority. SN Goldberg and T Livraghi were the most prolific authors. Nearly two thirds of the papers (n = 61) were published after 1990. This analysis identifies many of the landmark interventional radiology papers and provides a fascinating insight into the changing discourse within the field. It also identifies topics, authors and institutions which have impacted greatly on the specialty.

Work-related accidents among the Iranian population: a time series analysis, 2000-2011.

Science.gov (United States)

Karimlou, Masoud; Salehi, Masoud; Imani, Mehdi; Hosseini, Agha-Fatemeh; Dehnad, Afsaneh; Vahabi, Nasim; Bakhtiyari, Mahmood

2015-01-01

Work-related accidents result in human suffering and economic losses and are considered as a major health problem worldwide, especially in the economically developing world. To introduce seasonal autoregressive moving average (ARIMA) models for time series analysis of work-related accident data for workers insured by the Iranian Social Security Organization (ISSO) between 2000 and 2011. In this retrospective study, all insured people experiencing at least one work-related accident during a 10-year period were included in the analyses. We used Box-Jenkins modeling to develop a time series model of the total number of accidents. There was an average of 1476 accidents per month (1476·05±458·77, mean±SD). The final ARIMA (p,d,q) (P,D,Q)s model for fitting to data was: ARIMA(1,1,1)×(0,1,1)12 consisting of the first ordering of the autoregressive, moving average and seasonal moving average parameters with 20·942 mean absolute percentage error (MAPE). The final model showed that time series analysis of ARIMA models was useful for forecasting the number of work-related accidents in Iran. In addition, the forecasted number of work-related accidents for 2011 explained the stability of occurrence of these accidents in recent years, indicating a need for preventive occupational health and safety policies such as safety inspection.

How can interventions increase motivation for physical activity? A systematic review and meta-analysis

OpenAIRE

Crutzen, Rik; Nurmi, Johanna; Beattie, Marguerite; Dombrowski, Stephan; Knittle, Keegan; Hankonen, Nelli

2018-01-01

Motivation is a proximal determinant of behavior in many psychological theories, and increasing motivation is central to most behavior change interventions. This systematic review and meta-analysis sought to fill a gap in the literature by identifying features of behavior change interventions associated with favorable changes in three prominent motivational constructs: intention, stage of change and autonomous motivation. A systematic literature search identified 88 intervention studies (N = ...

Interventions for vaginismus.

Science.gov (United States)

Melnik, Tamara; Hawton, Keith; McGuire, Hugh

2012-12-12

Vaginismus is an involuntary contraction of the vaginal muscles which makes sexual intercourse difficult or impossible. It is one of the more common female psychosexual problems. Various therapeutic strategies for vaginismus, such as sex therapy and desensitisation, have been proposed, and uncontrolled case series appear promising. To assess the effects of different interventions for vaginismus. We searched the Cochrane Depression, Anxiety and Neurosis Group's Specialised Register (CCDANCTR-Studies and CCDANCTR-References) to August 2012. This register contains relevant randomised controlled trials from: The Cochrane Library (all years), EMBASE (1974 to date), MEDLINE (1950 to date) and PsycINFO (1967 to date). We searched reference lists and conference abstracts. We contacted experts in the field regarding unpublished material. Controlled trials comparing treatments for vaginismus with another treatment, a placebo treatment, treatment as usual or waiting list control. The review authors extracted data which we verified with the trial investigator where possible. Five studies were included, of which four with a total of 282 participants provided data. No meta-analysis was possible due to heterogeneity of comparisons within included studies as well as inadequate reporting of data. All studies were considered to be at either moderate or high risk of bias. The results of this systematic review indicate that there is no clinical or statistical difference between systematic desensitisation and any of the control interventions (either waiting list control, systematic desensitisation combined with group therapy or in vitro (with women under instruction by the therapist) desensitisation) for the treatment of vaginismus. The drop-out rates were higher in the waiting list groups. A clinically relevant effect of systematic desensitisation when compared with any of the control interventions cannot be ruled out. None of the included trials compared other behaviour therapies (e

Remote-Sensing Time Series Analysis, a Vegetation Monitoring Tool

Science.gov (United States)

McKellip, Rodney; Prados, Donald; Ryan, Robert; Ross, Kenton; Spruce, Joseph; Gasser, Gerald; Greer, Randall

2008-01-01

The Time Series Product Tool (TSPT) is software, developed in MATLAB , which creates and displays high signal-to- noise Vegetation Indices imagery and other higher-level products derived from remotely sensed data. This tool enables automated, rapid, large-scale regional surveillance of crops, forests, and other vegetation. TSPT temporally processes high-revisit-rate satellite imagery produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by other remote-sensing systems. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution. To improve cloud statistics, the TSPT combines MODIS data from multiple satellites (Aqua and Terra). The TSPT produces MODIS products as single time-frame and multitemporal change images, as time-series plots at a selected location, or as temporally processed image videos. Using the TSPT program, MODIS metadata is used to remove and/or correct bad and suspect data. Bad pixel removal, multiple satellite data fusion, and temporal processing techniques create high-quality plots and animated image video sequences that depict changes in vegetation greenness. This tool provides several temporal processing options not found in other comparable imaging software tools. Because the framework to generate and use other algorithms is established, small modifications to this tool will enable the use of a large range of remotely sensed data types. An effective remote-sensing crop monitoring system must be able to detect subtle changes in plant health in the earliest stages, before the effects of a disease outbreak or other adverse environmental conditions can become widespread and devastating. The integration of the time series analysis tool with ground-based information, soil types, crop types, meteorological data, and crop growth models in a Geographic Information System, could provide the foundation for a large-area crop-surveillance system that could identify

The effect of the late 2000s financial crisis on suicides in Spain: an interrupted time-series analysis.

Science.gov (United States)

Lopez Bernal, James A; Gasparrini, Antonio; Artundo, Carlos M; McKee, Martin

2013-10-01

The current financial crisis is having a major impact on European economies, especially that of Spain. Past evidence suggests that adverse macro-economic conditions exacerbate mental illness, but evidence from the current crisis is limited. This study analyses the association between the financial crisis and suicide rates in Spain. An interrupted time-series analysis of national suicides data between 2005 and 2010 was used to establish whether there has been any deviation in the underlying trend in suicide rates associated with the financial crisis. Segmented regression with a seasonally adjusted quasi-Poisson model was used for the analysis. Stratified analyses were performed to establish whether the effect of the crisis on suicides varied by region, sex and age group. The mean monthly suicide rate in Spain during the study period was 0.61 per 100 000 with an underlying trend of a 0.3% decrease per month. We found an 8.0% increase in the suicide rate above this underlying trend since the financial crisis (95% CI: 1.009-1.156; P = 0.03); this was robust to sensitivity analysis. A control analysis showed no change in deaths from accidental falls associated with the crisis. Stratified analyses suggested that the association between the crisis and suicide rates is greatest in the Mediterranean and Northern areas, in males and amongst those of working age. The financial crisis in Spain has been associated with a relative increase in suicides. Males and those of working age may be at particular risk of suicide associated with the crisis and may benefit from targeted interventions.

Nonparametric factor analysis of time series

OpenAIRE

Rodríguez-Poo, Juan M.; Linton, Oliver Bruce

1998-01-01

We introduce a nonparametric smoothing procedure for nonparametric factor analaysis of multivariate time series. The asymptotic properties of the proposed procedures are derived. We present an application based on the residuals from the Fair macromodel.

A Trend Analysis of Participant and Setting Characteristics in Autism Intervention Research

Science.gov (United States)

Crosland, Kimberly A.; Clarke, Shelley; Dunlap, Glen

2013-01-01

The current trend analysis was conducted to empirically document the characteristics of individuals with autism who participated in intervention research published between 1995 and 2009 in three journals ("Journal of Applied Behavior Analysis," "Journal of Autism and Developmental Disorders," and "Focus on Autism and Other…

Operation Analysis of the Series-Parallel Resonant Converter Working above Resonance Frequency

Directory of Open Access Journals (Sweden)

Peter Dzurko

2006-01-01

Full Text Available The present article deals with theoretical analysis of operation of a series-parallel converter working above resonance frequency. Derived are principal equations for individual operation intervals. Based on these made out are waveforms of individual quantities during both the inverter operation at load and no-load operation. The waveforms may be utilised at designing the inverter individual parts.

Decoding divergent series in nonparaxial optics.

Science.gov (United States)

Borghi, Riccardo; Gori, Franco; Guattari, Giorgio; Santarsiero, Massimo

2011-03-15

A theoretical analysis aimed at investigating the divergent character of perturbative series involved in the study of free-space nonparaxial propagation of vectorial optical beams is proposed. Our analysis predicts a factorial divergence for such series and provides a theoretical framework within which the results of recently published numerical experiments concerning nonparaxial propagation of vectorial Gaussian beams find a meaningful interpretation in terms of the decoding operated on such series by the Weniger transformation.

Effectiveness of E-self-help interventions for curbing adult problem drinking: A meta-analysis.

NARCIS (Netherlands)

Riper, H.; Spek, V.; Boon, B.; Conijn, B.; Kramer, J.; Martin-Abello, K.; Smit, H.F.E.

2011-01-01

Background: Self-help interventions without professional contact to curb adult problem drinking in the community are increasingly being delivered via the Internet. Objective: The objective of this meta-analysis was to assess the overall effectiveness of these eHealth interventions. Methods: In all,

Time-series analysis to study the impact of an intersection on dispersion along a street canyon.

Science.gov (United States)

Richmond-Bryant, Jennifer; Eisner, Alfred D; Hahn, Intaek; Fortune, Christopher R; Drake-Richman, Zora E; Brixey, Laurie A; Talih, M; Wiener, Russell W; Ellenson, William D

2009-12-01

This paper presents data analysis from the Brooklyn Traffic Real-Time Ambient Pollutant Penetration and Environmental Dispersion (B-TRAPPED) study to assess the transport of ultrafine particulate matter (PM) across urban intersections. Experiments were performed in a street canyon perpendicular to a highway in Brooklyn, NY, USA. Real-time ultrafine PM samplers were positioned on either side of an intersection at multiple locations along a street to collect time-series number concentration data. Meteorology equipment was positioned within the street canyon and at an upstream background site to measure wind speed and direction. Time-series analysis was performed on the PM data to compute a transport velocity along the direction of the street for the cases where background winds were parallel and perpendicular to the street. The data were analyzed for sampler pairs located (1) on opposite sides of the intersection and (2) on the same block. The time-series analysis demonstrated along-street transport, including across the intersection when background winds were parallel to the street canyon and there was minimal transport and no communication across the intersection when background winds were perpendicular to the street canyon. Low but significant values of the cross-correlation function (CCF) underscore the turbulent nature of plume transport along the street canyon. The low correlations suggest that flow switching around corners or traffic-induced turbulence at the intersection may have aided dilution of the PM plume from the highway. This observation supports similar findings in the literature. Furthermore, the time-series analysis methodology applied in this study is introduced as a technique for studying spatiotemporal variation in the urban microscale environment.

Behavioural interventions for urinary incontinence in community-dwelling seniors: an evidence-based analysis.

Science.gov (United States)

2008-01-01

In early August 2007, the Medical Advisory Secretariat began work on the Aging in the Community project, an evidence-based review of the literature surrounding healthy aging in the community. The Health System Strategy Division at the Ministry of Health and Long-Term Care subsequently asked the secretariat to provide an evidentiary platform for the ministry's newly released Aging at Home Strategy.After a broad literature review and consultation with experts, the secretariat identified 4 key areas that strongly predict an elderly person's transition from independent community living to a long-term care home. Evidence-based analyses have been prepared for each of these 4 areas: falls and fall-related injuries, urinary incontinence, dementia, and social isolation. For the first area, falls and fall-related injuries, an economic model is described in a separate report.Please visit the Medical Advisory Secretariat Web site, http://www.health.gov.on.ca/english/providers/program/mas/mas_about.html, to review these titles within the Aging in the Community series.AGING IN THE COMMUNITY: Summary of Evidence-Based AnalysesPrevention of Falls and Fall-Related Injuries in Community-Dwelling Seniors: An Evidence-Based AnalysisBehavioural Interventions for Urinary Incontinence in Community-Dwelling Seniors: An Evidence-Based AnalysisCaregiver- and Patient-Directed Interventions for Dementia: An Evidence-Based AnalysisSocial Isolation in Community-Dwelling Seniors: An Evidence-Based AnalysisThe Falls/Fractures Economic Model in Ontario Residents Aged 65 Years and Over (FEMOR) OBJECTIVE: To assess the effectiveness of behavioural interventions for the treatment and management of urinary incontinence (UI) in community-dwelling seniors. TARGET POPULATION AND CONDITION Urinary incontinence defined as "the complaint of any involuntary leakage of urine" was identified as 1 of the key predictors in a senior's transition from independent community living to admission to a long-term care

Multimodal Counseling Interventions: Effect on Human Papilloma Virus Vaccination Acceptance.

Science.gov (United States)

Nwanodi, Oroma; Salisbury, Helen; Bay, Curtis

2017-11-06

Human papilloma virus (HPV) vaccine was developed to reduce HPV-attributable cancers, external genital warts (EGW), and recurrent respiratory papillomatosis. Adolescent HPV vaccination series completion rates are less than 40% in the United States of America, but up to 80% in Australia and the United Kingdom. Population-based herd immunity requires 80% or greater vaccination series completion rates. Pro-vaccination counseling facilitates increased vaccination rates. Multimodal counseling interventions may increase HPV vaccination series non-completers' HPV-attributable disease knowledge and HPV-attributable disease prophylaxis (vaccination) acceptance over a brief 14-sentence counseling intervention. An online, 4-group, randomized controlled trial, with 260 or more participants per group, found that parents were more likely to accept HPV vaccination offers for their children than were childless young adults for themselves (68.2% and 52.9%). A combined audiovisual and patient health education handout (PHEH) intervention raised knowledge of HPV vaccination purpose, p = 0.02, and HPV vaccination acceptance for seven items, p HPV vaccination acceptance for five items, p HPV causes EGW, and that HPV vaccination prevents HPV-attributable diseases were better conveyed by the combined audiovisual and PHEH than the control 14-sentence counseling intervention alone.

TIME SERIES CHARACTERISTIC ANALYSIS OF RAINFALL, LAND USE AND FLOOD DISCHARGE BASED ON ARIMA BOX-JENKINS MODEL

Directory of Open Access Journals (Sweden)

Abror Abror

2014-01-01

Full Text Available Indonesia located in tropic area consists of wet season and dry season. However, in last few years, in river discharge in dry season is very little, but in contrary, in wet season, frequency of flood increases with sharp peak and increasingly great water elevation. The increased flood discharge may occur due to change in land use or change in rainfall characteristic. Both matters should get clarity. Therefore, a research should be done to analyze rainfall characteristic, land use and flood discharge in some watershed area (DAS quantitatively from time series data. The research was conducted in DAS Gintung in Parakankidang, DAS Gung in Danawarih, DAS Rambut in Cipero, DAS Kemiri in Sidapurna and DAS Comal in Nambo, located in Tegal Regency and Pemalang Regency in Central Java Province. This research activity consisted of three main steps: input, DAS system and output. Input is DAS determination and selection and searching secondary data. DAS system is early secondary data processing consisting of rainfall analysis, HSS GAMA I parameter, land type analysis and DAS land use. Output is final processing step that consisting of calculation of Tadashi Tanimoto, USSCS effective rainfall, flood discharge, ARIMA analysis, result analysis and conclusion. Analytical calculation of ARIMA Box-Jenkins time series used software Number Cruncher Statistical Systems and Power Analysis Sample Size (NCSS-PASS version 2000, which result in time series characteristic in form of time series pattern, mean square errors (MSE, root mean square ( RMS, autocorrelation of residual and trend. Result of this research indicates that composite CN and flood discharge is proportional that means when composite CN trend increase then flood discharge trend also increase and vice versa. Meanwhile, decrease of rainfall trend is not always followed with decrease in flood discharge trend. The main cause of flood discharge characteristic is DAS management characteristic, not change in

Cost analysis in interventional radiology-A tool to optimize management costs

International Nuclear Information System (INIS)

Clevert, D.-A.; Stickel, M.; Jung, E.M.; Reiser, M.; Rupp, N.

2007-01-01

Objective: The objective of the study was to analyze the methods to reduce cost in interventional radiology departments by reorganizing procurement. Materials and methods: All products used in Department of Interventional Radiology were inventoried. An ABC-analysis was completed and A-products (high-value and high turnover products) underwent a XYZ-analysis which predicted demand on the basis of ordering frequency. Then criteria for a procurement strategy for the different material categories were fixed. The net working capital (NWC) was calculated using an interest rate of 8%/year. Results: Total annual material turnover was 353,000 Euro . The value of all A-products determined by the inventory was 260,000 Euro . Changes in the A-product procurement strategy tapped a cost reduction potential of 14,500/year Euro . The resulting total saving was 17,200 Euro . Improved stores management added another 37,500 Euro. The total cost cut of 52,000 Euro is equivalent to 14.7% of annual expenses. Conclusion: A flexible procurement strategy helps to reduce the storage and capital tie-up costs of A-products in interventional radiology without affecting the quality of service provided to patients

Adult Craniopharyngioma: Case Series, Systematic Review, and Meta-Analysis.

Science.gov (United States)

Dandurand, Charlotte; Sepehry, Amir Ali; Asadi Lari, Mohammad Hossein; Akagami, Ryojo; Gooderham, Peter

2017-12-18

The optimal therapeutic approach for adult craniopharyngioma remains controversial. Some advocate for gross total resection (GTR), while others advocate for subtotal resection followed by adjuvant radiotherapy (STR + XRT). To conduct a systematic review and meta-analysis assessing the rate of recurrence in the follow-up of 3 yr in adult craniopharyngioma stratified by extent of resection and presence of adjuvant radiotherapy. MEDLINE (1946-July 1, 2016) and EMBASE (1980-June 30, 2016) were systematically reviewed. From1975 to 2013, 33 patients were treated with initial surgical resection for adult onset craniopharyngioma at our center and were reviewed for inclusion in this study. Data from 22 patients were available for inclusion as a case series in the systematic review. Eligible studies (n = 21) were identified from the literature in addition to a case series of our institutional experience. Three groups were available for analysis: GTR, STR + XRT, and STR. The rates of recurrence were 17%, 27%, and 45%, respectively. The risk of developing recurrence was significant for GTR vs STR (odds ratio [OR]: 0.24, 95% confidence interval [CI]: 0.15-0.38) and STR + XRT vs STR (OR: 0.20, 95% CI: 0.10-0.41). Risk of recurrence after GTR vs STR + XRT did not reach significance (OR: 0.63, 95% CI: 0.33-1.24, P = .18). This is the first and largest systematic review focusing on the rate of recurrence in adult craniopharyngioma. Although the rates of recurrence are favoring GTR, difference in risk of recurrence did not reach significance. This study provides guidance to clinicians and directions for future research with the need to stratify outcomes per treatment modalities. Copyright © 2017 by the Congress of Neurological Surgeons

Application of time series analysis on molecular dynamics simulations of proteins: a study of different conformational spaces by principal component analysis.

Science.gov (United States)

Alakent, Burak; Doruker, Pemra; Camurdan, Mehmet C

2004-09-08

Time series analysis is applied on the collective coordinates obtained from principal component analysis of independent molecular dynamics simulations of alpha-amylase inhibitor tendamistat and immunity protein of colicin E7 based on the Calpha coordinates history. Even though the principal component directions obtained for each run are considerably different, the dynamics information obtained from these runs are surprisingly similar in terms of time series models and parameters. There are two main differences in the dynamics of the two proteins: the higher density of low frequencies and the larger step sizes for the interminima motions of colicin E7 than those of alpha-amylase inhibitor, which may be attributed to the higher number of residues of colicin E7 and/or the structural differences of the two proteins. The cumulative density function of the low frequencies in each run conforms to the expectations from the normal mode analysis. When different runs of alpha-amylase inhibitor are projected on the same set of eigenvectors, it is found that principal components obtained from a certain conformational region of a protein has a moderate explanation power in other conformational regions and the local minima are similar to a certain extent, while the height of the energy barriers in between the minima significantly change. As a final remark, time series analysis tools are further exploited in this study with the motive of explaining the equilibrium fluctuations of proteins. Copyright 2004 American Institute of Physics

Multifractal analysis of visibility graph-based Ito-related connectivity time series.

Science.gov (United States)

Czechowski, Zbigniew; Lovallo, Michele; Telesca, Luciano

2016-02-01

In this study, we investigate multifractal properties of connectivity time series resulting from the visibility graph applied to normally distributed time series generated by the Ito equations with multiplicative power-law noise. We show that multifractality of the connectivity time series (i.e., the series of numbers of links outgoing any node) increases with the exponent of the power-law noise. The multifractality of the connectivity time series could be due to the width of connectivity degree distribution that can be related to the exit time of the associated Ito time series. Furthermore, the connectivity time series are characterized by persistence, although the original Ito time series are random; this is due to the procedure of visibility graph that, connecting the values of the time series, generates persistence but destroys most of the nonlinear correlations. Moreover, the visibility graph is sensitive for detecting wide "depressions" in input time series.

Influence of exercise intervention on gestational diabetes mellitus: a systematic review and meta-analysis.

Science.gov (United States)

Zheng, J; Wang, H; Ren, M

2017-10-01

Exercise intervention might be a promising approach to prevent gestational diabetes mellitus. However, the results remained controversial. We conducted a systematic review and meta-analysis to explore the effect of exercise intervention on gestational diabetes mellitus. PubMed, EMbase, Web of science, EBSCO, and Cochrane library databases were systematically searched. Randomized controlled trials (RCTs) assessing the effect of exercise intervention on gestational diabetes mellitus were included. Two investigators independently searched articles, extracted data, and assessed the quality of included studies. The primary outcome was the incidence of gestational diabetes mellitus, preterm birth, and gestational age at birth. Meta-analysis was performed using random-effect model. Five RCTs involving 1872 patients were included in the meta-analysis. Overall, compared with control intervention, exercise intervention was found to significantly reduce the risk of gestational diabetes mellitus (std. mean difference 0.62; 95% CI 0.43-0.89; P = 0.01), but demonstrated no influence on preterm birth (OR 0.93; 95% CI 0.44-1.99; P = 0.86), gestational age at birth (std. mean difference -0.03; 95% CI -0.12 to 0.07; P = 0.60), glucose 2-h post-OGTT (std. mean difference -1.02; 95% CI -2.75 to 0.71; P = 0.25), birth weight (std. mean difference -0.10; 95% CI -0.25 to 0.04; P = 0.16), Apgar score less than 7 (OR 0.78; 95% CI 0.21-2.91; P = 0.71), and preeclampsia (OR 1.05; 95% CI 0.53-2.07; P = 0.88). Compared to control intervention, exercise intervention was found to significantly reduce the incidence of gestational diabetes mellitus, but had no significant influence on preterm birth, gestational age at birth, glucose 2-h post-OGTT, birth weight, Apgar score less than 7, and preeclampsia.

Humanitarian Interventions: Western Imperialism or a Responsibility to Protect?--An Analysis of the Humanitarian Interventions in Darfur

Science.gov (United States)

Damboeck, Johanna

2012-01-01

Purpose: The aim of this article is to provide an analysis of the features that have shaped the state's decision-making process in the United Nations, with regard to the humanitarian intervention in Darfur from 2003 onwards. Design/methodology/approach: The methodological approach to the study is a review of political statement papers grounded in…

Analysis of Foreign Exchange Interventions by Intervention Agent with an Artificial Market Approach

Science.gov (United States)

Matsui, Hiroki; Tojo, Satoshi

We propose a multi-agent system which learns intervention policies and evaluates the effect of interventions in an artificial foreign exchange market. Izumi et al. had presented a system called AGEDASI TOF to simulate artificial market, together with a support system for the government to decide foreign exchange policies. However, the system needed to fix the amount of governmental intervention prior to the simulation, and was not realistic. In addition, the interventions in the system did not affect supply and demand of currencies; thus we could not discuss the effect of intervention correctly. First, we improve the system so as to make much of the weights of influential factors. Thereafter, we introduce an intervention agent that has the role of the central bank to stabilize the market. We could show that the agent learned the effective intervention policies through the reinforcement learning, and that the exchange rate converged to a certain extent in the expected range. We could also estimate the amount of intervention, showing the efficacy of signaling. In this model, in order to investigate the aliasing of the perception of the intervention agent, we introduced a pseudo-agent who was supposed to be able to observe all the behaviors of dealer agents; with this super-agent, we discussed the adequate granularity for a market state description.

Feasibility of a cognitive strategy training intervention for people with Parkinson's disease.

Science.gov (United States)

Foster, Erin R; Spence, Daniel; Toglia, Joan

2018-05-01

To investigate the feasibility of a novel client-centered cognitive strategy training intervention for people with Parkinson's disease (PD). This was a case series of seven people with PD without dementia but with subjective cognitive decline. The intervention involved ≥5 treatment sessions at the participant's home. Participant acceptance and engagement were assessed by the Credibility/Expectancy Questionnaire (CEQ), Client Satisfaction Questionnaire (CSQ), enjoyment and effort ratings, and homework completion. Logistical information was tracked, and the Canadian Occupational Performance Measure (COPM) was an exploratory outcome measure. Data analysis was descriptive. CEQ scores were positive and increased over time. CSQ scores were high (M = 30.8, SD = 0.75), with all participants rating all items positively. Almost all (95%) effort and enjoyment ratings were ≥3 (Much), and homework completion rates averaged 84% (SD = 18). Intervention duration was 6-15 weeks (M = 9.2, SD = 2.8), with treatment sessions averaging 1.7 h (SD = 0.5). Group and most individual COPM ratings improved ≥2 points. These findings support the feasibility of the intervention for people with PD. It was acceptable, engaging, and promising in terms of its effect on self-identified functional cognitive problems. Implications for Rehabilitation People with Parkinson's disease (PD) without dementia can experience cognitive decline that negatively impacts function and quality of life. Strategy-based interventions that explicitly train for transfer may mitigate the negative functional consequences of cognitive decline in this population. We developed a client-centered cognitive strategy training intervention for people with PD. This small case series supports its feasibility, indicating that it is acceptable and engaging for people with PD and promising in terms of its effect on self-identified functional cognitive problems.

The "Chaos Theory" and nonlinear dynamics in heart rate variability analysis: does it work in short-time series in patients with coronary heart disease?

Science.gov (United States)

Krstacic, Goran; Krstacic, Antonija; Smalcelj, Anton; Milicic, Davor; Jembrek-Gostovic, Mirjana

2007-04-01

Dynamic analysis techniques may quantify abnormalities in heart rate variability (HRV) based on nonlinear and fractal analysis (chaos theory). The article emphasizes clinical and prognostic significance of dynamic changes in short-time series applied on patients with coronary heart disease (CHD) during the exercise electrocardiograph (ECG) test. The subjects were included in the series after complete cardiovascular diagnostic data. Series of R-R and ST-T intervals were obtained from exercise ECG data after sampling digitally. The range rescaled analysis method determined the fractal dimension of the intervals. To quantify fractal long-range correlation's properties of heart rate variability, the detrended fluctuation analysis technique was used. Approximate entropy (ApEn) was applied to quantify the regularity and complexity of time series, as well as unpredictability of fluctuations in time series. It was found that the short-term fractal scaling exponent (alpha(1)) is significantly lower in patients with CHD (0.93 +/- 0.07 vs 1.09 +/- 0.04; P chaos theory during the exercise ECG test point out the multifractal time series in CHD patients who loss normal fractal characteristics and regularity in HRV. Nonlinear analysis technique may complement traditional ECG analysis.

Interventions prioritaires en Afrique de l'ouest pour l'estimation des ...

African Journals Online (AJOL)

For this to be achieved a list of 37 interventions from health and non-health sector were elaborated based on lancet series 2008 and on WHO proposed nutrition interventions. The list was then submitted to West Africa countries' team of nutrition and agriculture resource persons for selection. The interventions were ...

Independent component analysis: A new possibility for analysing series of electron energy loss spectra

International Nuclear Information System (INIS)

Bonnet, Nogl; Nuzillard, Danielle

2005-01-01

A complementary approach is proposed for analysing series of electron energy-loss spectra that can be recorded with the spectrum-line technique, across an interface for instance. This approach, called blind source separation (BSS) or independent component analysis (ICA), complements two existing methods: the spatial difference approach and multivariate statistical analysis. The principle of the technique is presented and illustrations are given through one simulated example and one real example

AHRQ series on complex intervention systematic reviews-paper 6: PRISMA-CI extension statement and checklist.

Science.gov (United States)

Guise, Jeanne-Marie; Butler, Mary E; Chang, Christine; Viswanathan, Meera; Pigott, Terri; Tugwell, Peter

2017-10-01

Complex interventions are widely used in health systems, public health, education, and communities and are increasingly the subject of systematic reviews. Oversimplification and inconsistencies in reporting about complex interventions can limit the usability of review findings. Although guidance exists to ensure that reports of individual studies and systematic reviews adhere to accepted scientific standards, their design-specific focus leaves important reporting gaps relative to complex interventions in health care. This paper provides a stand-alone extension to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting tool for complex interventions-PRISMA-CI-to help authors, publishers, and readers understand and apply to systematic reviews of complex interventions. PRISMA-CI development followed the Enhancing the QUAlity and Transparency Of health Research Network guidance for extensions and focused on adding or modifying only essential items that are truly unique to complex interventions and are not covered by broader interpretation of current PRISMA guidance. PRISMA-CI provides an important structure and guidance for systematic reviews and meta-analyses for the highly prevalent and dynamic field of complex interventions. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Mediation Analysis of an Adolescent HIV/STI/Pregnancy Prevention Intervention

Science.gov (United States)

Glassman, Jill R.; Franks, Heather M.; Baumler, Elizabeth R.; Coyle, Karin K.

2014-01-01

Most interventions designed to prevent HIV/STI/pregnancy risk behaviours in young people have multiple components based on psychosocial theories (e.g. social cognitive theory) dictating sets of mediating variables to influence to achieve desired changes in behaviours. Mediation analysis is a method for investigating the extent to which a variable…

The effectiveness of different interventions to promote poison prevention behaviours in households with children: a network meta-analysis.

Science.gov (United States)

Achana, Felix A; Sutton, Alex J; Kendrick, Denise; Wynn, Persephone; Young, Ben; Jones, David R; Hubbard, Stephanie J; Cooper, Nicola J

2015-01-01

There is evidence from 2 previous meta-analyses that interventions to promote poison prevention behaviours are effective in increasing a range of poison prevention practices in households with children. The published meta-analyses compared any intervention against a "usual care or no intervention" which potentially limits the usefulness of the analysis to decision makers. We aim to use network meta-analysis to simultaneously evaluate the effectiveness of different interventions to increase prevalence of safe storage of i) Medicines only, ii) Other household products only, iii) Poisons (both medicines and non-medicines), iv) Poisonous plants; and v) Possession of poison control centre (PCC) telephone number in households with children. Data on the effectiveness of poison prevention interventions was extracted from primary studies identified in 2 newly-undertaken systematic reviews. Effect estimates were pooled across studies using a random effects network meta-analysis model. 28 of the 47 primary studies identified were included in the analysis. Compared to usual care intervention, the intervention with education and low cost/free equipment elements was most effective in promoting safe storage of medicines (odds ratio 2.51, 95% credible interval 1.01 to 6.00) while interventions with education, low cost/free equipment, home safety inspection and fitting components were most effective in promoting safe storage of other household products (2.52, 1.12 to 7.13), safe storage of poisons (11.10, 1.60 to 141.50) and possession of PCC number (38.82, 2.19 to 687.10). No one intervention package was more effective than the others in promoting safe storage of poisonous plants. The most effective interventions varied by poison prevention practice, but education alone was not the most effective intervention for any poison prevention practice. Commissioners and providers of poison prevention interventions should tailor the interventions they commission or provide to the poison

Principal components and iterative regression analysis of geophysical series: Application to Sunspot number (1750 2004)

Science.gov (United States)

Nordemann, D. J. R.; Rigozo, N. R.; de Souza Echer, M. P.; Echer, E.

2008-11-01

We present here an implementation of a least squares iterative regression method applied to the sine functions embedded in the principal components extracted from geophysical time series. This method seems to represent a useful improvement for the non-stationary time series periodicity quantitative analysis. The principal components determination followed by the least squares iterative regression method was implemented in an algorithm written in the Scilab (2006) language. The main result of the method is to obtain the set of sine functions embedded in the series analyzed in decreasing order of significance, from the most important ones, likely to represent the physical processes involved in the generation of the series, to the less important ones that represent noise components. Taking into account the need of a deeper knowledge of the Sun's past history and its implication to global climate change, the method was applied to the Sunspot Number series (1750-2004). With the threshold and parameter values used here, the application of the method leads to a total of 441 explicit sine functions, among which 65 were considered as being significant and were used for a reconstruction that gave a normalized mean squared error of 0.146.

Seasonal and annual precipitation time series trend analysis in North Carolina, United States

Science.gov (United States)

Sayemuzzaman, Mohammad; Jha, Manoj K.

2014-02-01

The present study performs the spatial and temporal trend analysis of the annual and seasonal time-series of a set of uniformly distributed 249 stations precipitation data across the state of North Carolina, United States over the period of 1950-2009. The Mann-Kendall (MK) test, the Theil-Sen approach (TSA) and the Sequential Mann-Kendall (SQMK) test were applied to quantify the significance of trend, magnitude of trend, and the trend shift, respectively. Regional (mountain, piedmont and coastal) precipitation trends were also analyzed using the above-mentioned tests. Prior to the application of statistical tests, the pre-whitening technique was used to eliminate the effect of autocorrelation of precipitation data series. The application of the above-mentioned procedures has shown very notable statewide increasing trend for winter and decreasing trend for fall precipitation. Statewide mixed (increasing/decreasing) trend has been detected in annual, spring, and summer precipitation time series. Significant trends (confidence level ≥ 95%) were detected only in 8, 7, 4 and 10 nos. of stations (out of 249 stations) in winter, spring, summer, and fall, respectively. Magnitude of the highest increasing (decreasing) precipitation trend was found about 4 mm/season (- 4.50 mm/season) in fall (summer) season. Annual precipitation trend magnitude varied between - 5.50 mm/year and 9 mm/year. Regional trend analysis found increasing precipitation in mountain and coastal regions in general except during the winter. Piedmont region was found to have increasing trends in summer and fall, but decreasing trend in winter, spring and on an annual basis. The SQMK test on "trend shift analysis" identified a significant shift during 1960 - 70 in most parts of the state. Finally, the comparison between winter (summer) precipitations with the North Atlantic Oscillation (Southern Oscillation) indices concluded that the variability and trend of precipitation can be explained by the

Time series analysis in road safety research uisng state space methods

OpenAIRE

BIJLEVELD, FD

2008-01-01

In this thesis we present a comprehensive study into novel time series models for aggregated road safety data. The models are mainly intended for analysis of indicators relevant to road safety, with a particular focus on how to measure these factors. Such developments may need to be related to or explained by external influences. It is also possible to make forecasts using the models. Relevant indicators include the number of persons killed permonth or year. These statistics are closely watch...

Impact of a Family Empowerment Intervention on Delinquent Behavior: A Latent Growth Model Analysis.

Science.gov (United States)

Dembo, Richard; Schmeidler, James; Wothke, Werner

2003-01-01

Analysis indicated that reported frequency of involvement in delinquency declined more over time for families receiving Family Empowerment Intervention (FEI) as opposed to those receiving Extended Services Intervention (ESI). Results provide support for the impact of FEI services on reported frequency of delinquent behavior over a 36-month…

A cost analysis of implementing a behavioral weight loss intervention in community mental health settings: Results from the ACHIEVE trial.

Science.gov (United States)

Janssen, Ellen M; Jerome, Gerald J; Dalcin, Arlene T; Gennusa, Joseph V; Goldsholl, Stacy; Frick, Kevin D; Wang, Nae-Yuh; Appel, Lawrence J; Daumit, Gail L

2017-06-01

In the ACHIEVE randomized controlled trial, an 18-month behavioral intervention accomplished weight loss in persons with serious mental illness who attended community psychiatric rehabilitation programs. This analysis estimates costs for delivering the intervention during the study. It also estimates expected costs to implement the intervention more widely in a range of community mental health programs. Using empirical data, costs were calculated from the perspective of a community psychiatric rehabilitation program delivering the intervention. Personnel and travel costs were calculated using time sheet data. Rent and supply costs were calculated using rent per square foot and intervention records. A univariate sensitivity analysis and an expert-informed sensitivity analysis were conducted. With 144 participants receiving the intervention and a mean weight loss of 3.4 kg, costs of $95 per participant per month and $501 per kilogram lost in the trial were calculated. In univariate sensitivity analysis, costs ranged from $402 to $725 per kilogram lost. Through expert-informed sensitivity analysis, it was estimated that rehabilitation programs could implement the intervention for $68 to $85 per client per month. Costs of implementing the ACHIEVE intervention were in the range of other intensive behavioral weight loss interventions. Wider implementation of efficacious lifestyle interventions in community mental health settings will require adequate funding mechanisms. © 2017 The Obesity Society.

Geomechanical time series and its singularity spectrum analysis

Czech Academy of Sciences Publication Activity Database

Lyubushin, Alexei A.; Kaláb, Zdeněk; Lednická, Markéta

2012-01-01

Roč. 47, č. 1 (2012), s. 69-77 ISSN 1217-8977 R&D Projects: GA ČR GA105/09/0089 Institutional research plan: CEZ:AV0Z30860518 Keywords : geomechanical time series * singularity spectrum * time series segmentation * laser distance meter Subject RIV: DC - Siesmology, Volcanology, Earth Structure Impact factor: 0.347, year: 2012 http://www.akademiai.com/content/88v4027758382225/fulltext.pdf

Personal identity narratives of therapeutic songwriting participants following Spinal Cord Injury: A case series analysis.

Science.gov (United States)

Roddy, Chantal; Rickard, Nikki; Tamplin, Jeanette; Baker, Felicity Anne

2018-07-01

Spinal Cord Injury (SCI) patients face unique identity challenges associated with physical limitations, higher comorbid depression, increased suicidality and reduced subjective well-being. Post-injury identity is often unaddressed in subacute rehabilitation environments where critical physical and functional rehabilitation goals are prioritized. Therapeutic songwriting has demonstrated prior efficacy in promoting healthy adjustment and as a means of expression for post-injury narratives. The current study sought to examine the identity narratives of therapeutic songwriting participants. Case-series analysis of the individual identity trajectories of eight individuals. Subacute rehabilitation facility, Victoria, Australia. Eight individuals with an SCI; 7 males and 1 female. Six-week therapeutic songwriting intervention facilitated by a music therapist to promote identity rehabilitation. Identity, subjective well-being and distress, emotional state. Three participants demonstrated positive trajectories and a further three showed negative trajectories; remaining participants were ambiguous in their response. Injury severity differentiated those with positive trajectories from those with negative trajectories, with greater injury severity apparent for those showing negative trends. Self-concept also improved more in those with positive trajectories. Core demographic variables did not however meaningfully predict the direction of change in core identity or wellbeing indices. Identity-focused songwriting holds promise as a means of promoting healthy identity reintegration. Further research on benefits for those with less severe spinal injuries is warranted.

Dynamic factor analysis in the frequency domain: causal modeling of multivariate psychophysiological time series

NARCIS (Netherlands)

Molenaar, P.C.M.

1987-01-01

Outlines a frequency domain analysis of the dynamic factor model and proposes a solution to the problem of constructing a causal filter of lagged factor loadings. The method is illustrated with applications to simulated and real multivariate time series. The latter applications involve topographic

Time-Series Analysis of Remotely-Sensed SeaWiFS Chlorophyll in River-Influenced Coastal Regions

Science.gov (United States)

Acker, James G.; McMahon, Erin; Shen, Suhung; Hearty, Thomas; Casey, Nancy

2009-01-01

The availability of a nearly-continuous record of remotely-sensed chlorophyll a data (chl a) from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission, now longer than ten years, enables examination of time-series trends for multiple global locations. Innovative data analysis technology available on the World Wide Web facilitates such analyses. In coastal regions influenced by river outflows, chl a is not always indicative of actual trends in phytoplankton chlorophyll due to the interference of colored dissolved organic matter and suspended sediments; significant chl a timeseries trends for coastal regions influenced by river outflows may nonetheless be indicative of important alterations of the hydrologic and coastal environment. Chl a time-series analysis of nine marine regions influenced by river outflows demonstrates the simplicity and usefulness of this technique. The analyses indicate that coastal time-series are significantly influenced by unusual flood events. Major river systems in regions with relatively low human impact did not exhibit significant trends. Most river systems with demonstrated human impact exhibited significant negative trends, with the noteworthy exception of the Pearl River in China, which has a positive trend.

Phase synchronization based minimum spanning trees for analysis of financial time series with nonlinear correlations

Science.gov (United States)

Radhakrishnan, Srinivasan; Duvvuru, Arjun; Sultornsanee, Sivarit; Kamarthi, Sagar

2016-02-01

The cross correlation coefficient has been widely applied in financial time series analysis, in specific, for understanding chaotic behaviour in terms of stock price and index movements during crisis periods. To better understand time series correlation dynamics, the cross correlation matrices are represented as networks, in which a node stands for an individual time series and a link indicates cross correlation between a pair of nodes. These networks are converted into simpler trees using different schemes. In this context, Minimum Spanning Trees (MST) are the most favoured tree structures because of their ability to preserve all the nodes and thereby retain essential information imbued in the network. Although cross correlations underlying MSTs capture essential information, they do not faithfully capture dynamic behaviour embedded in the time series data of financial systems because cross correlation is a reliable measure only if the relationship between the time series is linear. To address the issue, this work investigates a new measure called phase synchronization (PS) for establishing correlations among different time series which relate to one another, linearly or nonlinearly. In this approach the strength of a link between a pair of time series (nodes) is determined by the level of phase synchronization between them. We compare the performance of phase synchronization based MST with cross correlation based MST along selected network measures across temporal frame that includes economically good and crisis periods. We observe agreement in the directionality of the results across these two methods. They show similar trends, upward or downward, when comparing selected network measures. Though both the methods give similar trends, the phase synchronization based MST is a more reliable representation of the dynamic behaviour of financial systems than the cross correlation based MST because of the former's ability to quantify nonlinear relationships among time

Measuring Quality Improvement in Acute Ischemic Stroke Care: Interrupted Time Series Analysis of Door-to-Needle Time

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Anne Margreet van Dishoeck

2014-06-01

Full Text Available Background: In patients with acute ischemic stroke, early treatment with recombinant tissue plasminogen activator (rtPA improves functional outcome by effectively reducing disability and dependency. Timely thrombolysis, within 1 h, is a vital aspect of acute stroke treatment, and is reflected in the widely used performance indicator ‘door-to-needle time' (DNT. DNT measures the time from the moment the patient enters the emergency department until he/she receives intravenous rtPA. The purpose of the study was to measure quality improvement from the first implementation of thrombolysis in stroke patients in a university hospital in the Netherlands. We further aimed to identify specific interventions that affect DNT. Methods: We included all patients with acute ischemic stroke consecutively admitted to a large university hospital in the Netherlands between January 2006 and December 2012, and focused on those treated with thrombolytic therapy on admission. Data were collected routinely for research purposes and internal quality measurement (the Erasmus Stroke Study. We used a retrospective interrupted time series design to study the trend in DNT, analyzed by means of segmented regression. Results: Between January 2006 and December 2012, 1,703 patients with ischemic stroke were admitted and 262 (17% were treated with rtPA. Patients treated with thrombolysis were on average 63 years old at the time of the stroke and 52% were male. Mean age (p = 0.58 and sex distribution (p = 0.98 did not change over the years. The proportion treated with thrombolysis increased from 5% in 2006 to 22% in 2012. In 2006, none of the patients were treated within 1 h. In 2012, this had increased to 81%. In a logistic regression analysis, this trend was significant (OR 1.6 per year, CI 1.4-1.8. The median DNT was reduced from 75 min in 2006 to 45 min in 2012 (p Conclusion and Implications: The DNT steadily improved from the first implementation of thrombolysis. Specific

Hispanic mothers’ beliefs regarding HPV vaccine series completion in their adolescent daughters

Science.gov (United States)

Roncancio, A. M.; Ward, K. K.; Carmack, C. C.; Mu�oz, B. T.; Cribbs, F. L.

2017-01-01

Abstract Rates of human papillomavirus (HPV) vaccine series completion among adolescent Hispanic females in Texas in 2014 (∼39%) lag behind the Healthy People 2020 goal (80%). This qualitative study identifies Hispanic mothers’ salient behavioral, normative and control beliefs regarding having their adolescent daughters complete the vaccine series. Thirty-two mothers of girls (aged 11–17) that had received at least one dose of the HPV vaccine, completed in-depth interviews. Six girls had received one dose of the HPV vaccine, 10 girls had received two doses, and 16 girls had received all three doses. The questions elicited salient: (i) experiential and instrumental attitudes (behavioral beliefs); (ii) supporters and non-supporters (normative beliefs) and (iii) facilitators and barriers (control beliefs). Directed content analysis was employed to select the most salient beliefs. Mothers: (i) expressed salient positive feelings (e.g. good, secure, happy and satisfied); (ii) believed that completing the series resulted in positive effects (e.g. protection, prevention); (iii) believed that the main supporters were themselves, their daughter’s father and doctor with some of their friends not supporting series completion and (iv) believed that vaccine affordability, information, transportation, ease of scheduling and keeping vaccination appointments and taking their daughter’s immunization card to appointments were facilitators. This study represents the first step in building theory-based framework of vaccine series completion for this population. The beliefs identified provide guidance for health care providers and intervention developers. PMID:28088755

Analysis of Data from a Series of Events by a Geometric Process Model

Institute of Scientific and Technical Information of China (English)

Yeh Lam; Li-xing Zhu; Jennifer S. K. Chan; Qun Liu

2004-01-01

Geometric process was first introduced by Lam[10,11]. A stochastic process {Xi, i = 1, 2,…} is called a geometric process (GP) if, for some a > 0, {ai-1Xi, i = 1, 2,…} forms a renewal process. In thispaper, the GP is used to analyze the data from a series of events. A nonparametric method is introduced forthe estimation of the three parameters in the GP. The limiting distributions of the three estimators are studied.Through the analysis of some real data sets, the GP model is compared with other three homogeneous andnonhomogeneous Poisson models. It seems that on average the GP model is the best model among these fourmodels in analyzing the data from a series of events.

Protective Effect of Dual-Strain Probiotics in Preterm Infants: A Multi-Center Time Series Analysis

Science.gov (United States)

Schwab, Frank; Garten, Lars; Geffers, Christine; Gastmeier, Petra; Piening, Brar

2016-01-01

Objective To determine the effect of dual-strain probiotics on the development of necrotizing enterocolitis (NEC), mortality and nosocomial bloodstream infections (BSI) in preterm infants in German neonatal intensive care units (NICUs). Design A multi-center interrupted time series analysis. Setting 44 German NICUs with routine use of dual-strain probiotics on neonatal ward level. Patients Preterm infants documented by NEO-KISS, the German surveillance system for nosocomial infections in preterm infants with birth weights below 1,500 g, between 2004 and 2014. Intervention Routine use of dual-strain probiotics containing Lactobacillus acidophilus and Bifidobacterium spp. (Infloran) on the neonatal ward level. Main outcome measures Incidences of NEC, overall mortality, mortality following NEC and nosocomial BSI. Results Data from 10,890 preterm infants in 44 neonatal wards was included in this study. Incidences of NEC and BSI were 2.5% (n = 274) and 15.0%, (n = 1631), respectively. Mortality rate was 6.1% (n = 665). The use of dual-strain probiotics significantly reduced the risk of NEC (HR = 0.48; 95% CI = 0.38–0.62), overall mortality (HR = 0.60, 95% CI = 0.44–0.83), mortality after NEC (HR = 0.51, 95% CI = 0.26–0.999) and nosocomial BSI (HR = 0.89, 95% CI = 0.81–0.98). These effects were even more pronounced in the subgroup analysis of preterm infants with birth weights below 1,000 g. Conclusion In order to reduce NEC and mortality in preterm infants, it is advisable to add routine prophylaxis with dual-strain probiotics to clinical practice in neonatal wards. PMID:27332554

Is there sufficient evidence regarding signage-based stair use interventions? A sequential meta-analysis.

Science.gov (United States)

Bauman, Adrian; Milton, Karen; Kariuki, Maina; Fedel, Karla; Lewicka, Mary

2017-11-28

The proliferation of studies using motivational signs to promote stair use continues unabated, with their oft-cited potential for increasing population-level physical activity participation. This study examined all stair use promotional signage studies since 1980, calculating pre-estimates and post-estimates of stair use. The aim of this project was to conduct a sequential meta-analysis to pool intervention effects, in order to determine when the evidence base was sufficient for population-wide dissemination. Using comparable data from 50 stair-promoting studies (57 unique estimates) we pooled data to assess the effect sizes of such interventions. At baseline, median stair usage across interventions was 8.1%, with an absolute median increase of 2.2% in stair use following signage-based interventions. The overall pooled OR indicated that participants were 52% more likely to use stairs after exposure to promotional signs (adjusted OR 1.52, 95% CI 1.37 to 1.70). Incremental (sequential) meta-analyses using z-score methods identified that sufficient evidence for stair use interventions has existed since 2006, with recent studies providing no further evidence on the effect sizes of such interventions. This analysis has important policy and practice implications. Researchers continue to publish stair use interventions without connection to policymakers' needs, and few stair use interventions are implemented at a population level. Researchers should move away from repeating short-term, small-scale, stair sign interventions, to investigating their scalability, adoption and fidelity. Only such research translation efforts will provide sufficient evidence of external validity to inform their scaling up to influence population physical activity. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Exercise Interventions for Preventing Falls Among Older People in Care Facilities: A Meta-Analysis.

Science.gov (United States)

Lee, Seon Heui; Kim, Hee Sun

2017-02-01

Falls in older people are a common problem, often leading to considerable morbidity. However, the overall effect of exercise interventions on fall prevention in care facilities remains controversial. To evaluate the effectiveness of exercise interventions on the rate of falls and number of fallers in care facilities. A meta-analysis was conducted of randomized controlled trials published up to December 2014. Eight databases were searched including Ovid-Medline, Embase, CINAHL, Cochrane Library, KoreaMed, KMbase, KISS, and KisTi. Two investigators independently extracted data and assessed study quality. Twenty-one studies were selected, that included 5,540 participants. Fifteen studies included exercise as a single intervention, whereas the remaining six included exercise combined with two or more fall interventions tailored to each resident's fall risk (i.e., medication review, environmental modification or staff education). Meta-analysis showed that exercise had a preventive effect on the rate of falls (risk ratio [RR] 0.81, 95% CI 0.68-0.97). This effect was stronger when exercise combined with other fall interventions on the rate of falls (RR 0.61, 95% CI 0.52-0.72) and on the number of fallers (RR 0.85, 95% CI 0.77-0.95). Exercise interventions including balance training (i.e., gait, balance, and functional training; or balance and strength) resulted in reduced the rate of falls. Sensitivity analyses indicated that exercise interventions resulted in reduced numbers of recurrent fallers (RR 0.71, 95% CI 0.53-0.97). This review provides an important basis for developing evidence-based exercise intervention protocols for older people living in care facilities. Exercise programs, which are combined with tailored other fall interventions and challenge balance training to improve balance skills, should be applied to frail older people with functional limitations in institutional settings. © 2016 Sigma Theta Tau International.

Single event time series analysis in a binary karst catchment evaluated using a groundwater model (Lurbach system, Austria).

Science.gov (United States)

Mayaud, C; Wagner, T; Benischke, R; Birk, S

2014-04-16

The Lurbach karst system (Styria, Austria) is drained by two major springs and replenished by both autogenic recharge from the karst massif itself and a sinking stream that originates in low permeable schists (allogenic recharge). Detailed data from two events recorded during a tracer experiment in 2008 demonstrate that an overflow from one of the sub-catchments to the other is activated if the discharge of the main spring exceeds a certain threshold. Time series analysis (autocorrelation and cross-correlation) was applied to examine to what extent the various available methods support the identification of the transient inter-catchment flow observed in this binary karst system. As inter-catchment flow is found to be intermittent, the evaluation was focused on single events. In order to support the interpretation of the results from the time series analysis a simplified groundwater flow model was built using MODFLOW. The groundwater model is based on the current conceptual understanding of the karst system and represents a synthetic karst aquifer for which the same methods were applied. Using the wetting capability package of MODFLOW, the model simulated an overflow similar to what has been observed during the tracer experiment. Various intensities of allogenic recharge were employed to generate synthetic discharge data for the time series analysis. In addition, geometric and hydraulic properties of the karst system were varied in several model scenarios. This approach helps to identify effects of allogenic recharge and aquifer properties in the results from the time series analysis. Comparing the results from the time series analysis of the observed data with those of the synthetic data a good agreement was found. For instance, the cross-correlograms show similar patterns with respect to time lags and maximum cross-correlation coefficients if appropriate hydraulic parameters are assigned to the groundwater model. The comparable behaviors of the real and the

A novel model for Time-Series Data Clustering Based on piecewise SVD and BIRCH for Stock Data Analysis on Hadoop Platform

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Ibgtc Bowala

2017-06-01

Full Text Available With the rapid growth of financial markets, analyzers are paying more attention on predictions. Stock data are time series data, with huge amounts. Feasible solution for handling the increasing amount of data is to use a cluster for parallel processing, and Hadoop parallel computing platform is a typical representative. There are various statistical models for forecasting time series data, but accurate clusters are a pre-requirement. Clustering analysis for time series data is one of the main methods for mining time series data for many other analysis processes. However, general clustering algorithms cannot perform clustering for time series data because series data has a special structure and a high dimensionality has highly co-related values due to high noise level. A novel model for time series clustering is presented using BIRCH, based on piecewise SVD, leading to a novel dimension reduction approach. Highly co-related features are handled using SVD with a novel approach for dimensionality reduction in order to keep co-related behavior optimal and then use BIRCH for clustering. The algorithm is a novel model that can handle massive time series data. Finally, this new model is successfully applied to real stock time series data of Yahoo finance with satisfactory results.

Empirical mode decomposition and long-range correlation analysis of sunspot time series

International Nuclear Information System (INIS)

Zhou, Yu; Leung, Yee

2010-01-01

Sunspots, which are the best known and most variable features of the solar surface, affect our planet in many ways. The number of sunspots during a period of time is highly variable and arouses strong research interest. When multifractal detrended fluctuation analysis (MF-DFA) is employed to study the fractal properties and long-range correlation of the sunspot series, some spurious crossover points might appear because of the periodic and quasi-periodic trends in the series. However many cycles of solar activities can be reflected by the sunspot time series. The 11-year cycle is perhaps the most famous cycle of the sunspot activity. These cycles pose problems for the investigation of the scaling behavior of sunspot time series. Using different methods to handle the 11-year cycle generally creates totally different results. Using MF-DFA, Movahed and co-workers employed Fourier truncation to deal with the 11-year cycle and found that the series is long-range anti-correlated with a Hurst exponent, H, of about 0.12. However, Hu and co-workers proposed an adaptive detrending method for the MF-DFA and discovered long-range correlation characterized by H≈0.74. In an attempt to get to the bottom of the problem in the present paper, empirical mode decomposition (EMD), a data-driven adaptive method, is applied to first extract the components with different dominant frequencies. MF-DFA is then employed to study the long-range correlation of the sunspot time series under the influence of these components. On removing the effects of these periods, the natural long-range correlation of the sunspot time series can be revealed. With the removal of the 11-year cycle, a crossover point located at around 60 months is discovered to be a reasonable point separating two different time scale ranges, H≈0.72 and H≈1.49. And on removing all cycles longer than 11 years, we have H≈0.69 and H≈0.28. The three cycle-removing methods—Fourier truncation, adaptive detrending and the

Functional Technology for Individuals with Intellectual Disabilities: Meta-Analysis of Mobile Device-Based Interventions

Science.gov (United States)

Kim, Jemma; Kimm, Christina H.

2017-01-01

This study employs a meta-analysis of single-subject design research to investigate the efficacy of mobile device-based interventions for individuals with intellectual disabilities (ID) and to further examine possible variables that may moderate the intervention outcomes. A total of 23 studies, 78 participants, and 140 observed cases that met the…

Economic Analysis in Series-Distillation Desalination

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Mirna Rahmah Lubis

2010-06-01

Full Text Available The ability to produce potable water economically is the primary purpose of seawater desalination research. Reverse osmosis (RO and multi-stage flash (MSF cost more than potable water produced from fresh water resources. Therefore, this research investigates a high-efficiency mechanical vapor-compression distillation system that employs an improved water flow arrangement. The incoming salt concentration was 0.15% salt for brackish water and 3.5% salt for seawater, whereas the outgoing salt concentration was 1.5% and 7%, respectively. Distillation was performed at 439 K and 722 kPa for both brackish water feed and seawater feed. Water costs of the various conditions were calculated for brackish water and seawater feeds using optimum conditions considered as 25 and 20 stages, respectively. For brackish water at a temperature difference of 0.96 K, the energy requirement is 2.0 kWh/m3. At this condition, the estimated water cost is $0.39/m3 achieved with 10,000,000 gal/day distillate, 30-year bond, 5% interest rate, and $0.05/kWh electricity. For seawater at a temperature difference of 0.44 K, the energy requirement is 3.97 kWh/m3 and the estimated water cost is $0.61/m3. Greater efficiency of the vapor compression system is achieved by connecting multiple evaporators in series, rather than the traditional parallel arrangement. The efficiency results from the gradual increase of salinity in each stage of the series arrangement in comparison to parallel. Calculations using various temperature differences between boiling brine and condensing steam show the series arrangement has the greatest improvement at lower temperature differences. Keywords: desalination, dropwise condensation, mechanical-vapor compression

Track Irregularity Time Series Analysis and Trend Forecasting

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Jia Chaolong

2012-01-01

Full Text Available The combination of linear and nonlinear methods is widely used in the prediction of time series data. This paper analyzes track irregularity time series data by using gray incidence degree models and methods of data transformation, trying to find the connotative relationship between the time series data. In this paper, GM (1,1 is based on first-order, single variable linear differential equations; after an adaptive improvement and error correction, it is used to predict the long-term changing trend of track irregularity at a fixed measuring point; the stochastic linear AR, Kalman filtering model, and artificial neural network model are applied to predict the short-term changing trend of track irregularity at unit section. Both long-term and short-term changes prove that the model is effective and can achieve the expected accuracy.

Effectiveness of multi-component non-pharmacologic delirium interventions: A Meta-analysis

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Hshieh, Tammy T.; Yue, Jirong; Oh, Esther; Puelle, Margaret; Dowal, Sarah; Travison, Thomas; Inouye, Sharon K.

2015-01-01

Importance Delirium, an acute disorder with high morbidity and mortality, is often preventable through multi-component non-pharmacologic strategies. The efficacy of these strategies for preventing subsequent adverse outcomes has been limited to small studies. Objective Evaluate available evidence on multi-component non-pharmacologic delirium interventions in reducing incident delirium and preventing poor outcomes associated with delirium. Data Sources PubMed, Google Scholar, ScienceDirect and Cochrane Database of Systematic Reviews from January 1, 1999–December 31, 2013. Study Selection Studies examining the following outcomes were included: delirium incidence, falls, length of stay, rate of discharge to a long-term care institution, change in functional or cognitive status. Data Extraction and Synthesis Two experienced physician reviewers independently and blindly abstracted data on outcome measures using a standardized approach. The reviewers conducted quality ratings based on the Cochrane Risk of Bias criteria for each study. Main Outcomes and Measures We identified 14 interventional studies. Results for outcomes of delirium, falls, length of stay and institutionalization data were pooled for meta-analysis but heterogeneity limited meta-analysis of results for outcomes of functional and cognitive decline. Overall, eleven studies demonstrated significant reductions in delirium incidence (Odds Ratio 0.47, 95% Confidence Interval 0.38–0.58). The four randomized or matched (RMT) studies reduced delirium incidence by 44% (95% CI 0.42–0.76). Rate of falls decreased significantly among intervention patients in four studies (OR 0.38, 95% CI 0.25–0.60); in the two RMTs, the fall rate was reduced by 64% (95% CI 0.22–0.61). Lengths of stay and institutionalization rates also trended towards decreases in the intervention groups, mean difference −0.16 days shorter (95% CI −0.97–0.64) and odds of institutionalization 5% lower (OR 0.95, 95% CI 0.71–1

Work-related accidents among the Iranian population: a time series analysis, 2000–2011

Science.gov (United States)

Karimlou, Masoud; Imani, Mehdi; Hosseini, Agha-Fatemeh; Dehnad, Afsaneh; Vahabi, Nasim; Bakhtiyari, Mahmood

2015-01-01

Background Work-related accidents result in human suffering and economic losses and are considered as a major health problem worldwide, especially in the economically developing world. Objectives To introduce seasonal autoregressive moving average (ARIMA) models for time series analysis of work-related accident data for workers insured by the Iranian Social Security Organization (ISSO) between 2000 and 2011. Methods In this retrospective study, all insured people experiencing at least one work-related accident during a 10-year period were included in the analyses. We used Box–Jenkins modeling to develop a time series model of the total number of accidents. Results There was an average of 1476 accidents per month (1476·05±458·77, mean±SD). The final ARIMA (p,d,q) (P,D,Q)s model for fitting to data was: ARIMA(1,1,1)×(0,1,1)12 consisting of the first ordering of the autoregressive, moving average and seasonal moving average parameters with 20·942 mean absolute percentage error (MAPE). Conclusions The final model showed that time series analysis of ARIMA models was useful for forecasting the number of work-related accidents in Iran. In addition, the forecasted number of work-related accidents for 2011 explained the stability of occurrence of these accidents in recent years, indicating a need for preventive occupational health and safety policies such as safety inspection. PMID:26119774

Applied behavior analysis as intervention for autism: definition, features and philosophical concepts

Directory of Open Access Journals (Sweden)

Síglia Pimentel Höher Camargo

2013-11-01

Full Text Available Autism spectrum disorder (ASD is a lifelong pervasive developmental disorder with no known causes and cure. However, educational and behavioral interventions with a foundation in applied behavior analysis (ABA have been shown to improve a variety of skill areas such as communication, social, academic, and adaptive behaviors of individuals with ASD. The goal of this work is to present the definition, features and philosophical concepts that underlie ABA and make this science an effective intervention method for people with autism.

Mass media interventions for preventing smoking in young people.

Science.gov (United States)

Carson, Kristin V; Ameer, Faisal; Sayehmiri, Kourosh; Hnin, Khin; van Agteren, Joseph Em; Sayehmiri, Fatemeh; Brinn, Malcolm P; Esterman, Adrian J; Chang, Anne B; Smith, Brian J

2017-06-02

campaigns, one of which is new for this update. Seven of the studies used a controlled trial design and one an interrupted time-series analysis. Risks of bias were high across all included studies and there was considerable heterogeneity in study design, intervention and population being assessed.Three studies (n = 17,385), one of which compared a mass media intervention to no intervention and two of which evaluated mass media interventions as adjuncts to school-based interventions, found that the mass media interventions reduced the smoking behaviour of young people. The remaining five studies (n = 72,740) did not detect a significant effect on smoking behaviour. These included three studies comparing a mass media intervention to no intervention, one study evaluating a mass media intervention as an adjunct to a school-based intervention, and one interrupted time-series study of a social media intervention. The three campaigns which found a significant effect described their theoretical basis, used formative research in designing the campaign messages, and used message broadcast of reasonable intensity over extensive periods of time. However, some of the campaigns which did not detect an effect also exhibited these characteristics. Effective campaigns tended to last longer (minimum 3 years) and were more intense (more contact time) for both school-based lessons (minimum eight lessons per grade) and media spots (minimum four weeks' duration across multiple media channels with between 167 and 350 TV and radio spots). Implementation of combined school-based components (e.g. school posters) and the use of repetitive media messages delivered by multiple channels (e.g. newspapers, radio, television) appeared to contribute to successful campaigns. Certainty about the effects of mass media campaigns on smoking behaviour in youth is very low, due to inconsistency between studies in both design and results, and due to methodological issues amongst the included studies. It would

Time Series Analysis of Onchocerciasis Data from Mexico: A Trend towards Elimination

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Pérez-Rodríguez, Miguel A.; Adeleke, Monsuru A.; Orozco-Algarra, María E.; Arrendondo-Jiménez, Juan I.; Guo, Xianwu

2013-01-01

Background In Latin America, there are 13 geographically isolated endemic foci distributed among Mexico, Guatemala, Colombia, Venezuela, Brazil and Ecuador. The communities of the three endemic foci found within Mexico have been receiving ivermectin treatment since 1989. In this study, we predicted the trend of occurrence of cases in Mexico by applying time series analysis to monthly onchocerciasis data reported by the Mexican Secretariat of Health between 1988 and 2011 using the software R. Results A total of 15,584 cases were reported in Mexico from 1988 to 2011. The data of onchocerciasis cases are mainly from the main endemic foci of Chiapas and Oaxaca. The last case in Oaxaca was reported in 1998, but new cases were reported in the Chiapas foci up to 2011. Time series analysis performed for the foci in Mexico showed a decreasing trend of the disease over time. The best-fitted models with the smallest Akaike Information Criterion (AIC) were Auto-Regressive Integrated Moving Average (ARIMA) models, which were used to predict the tendency of onchocerciasis cases for two years ahead. According to the ARIMA models predictions, the cases in very low number (below 1) are expected for the disease between 2012 and 2013 in Chiapas, the last endemic region in Mexico. Conclusion The endemic regions of Mexico evolved from high onchocerciasis-endemic states to the interruption of transmission due to the strategies followed by the MSH, based on treatment with ivermectin. The extremely low level of expected cases as predicted by ARIMA models for the next two years suggest that the onchocerciasis is being eliminated in Mexico. To our knowledge, it is the first study utilizing time series for predicting case dynamics of onchocerciasis, which could be used as a benchmark during monitoring and post-treatment surveillance. PMID:23459370

Cost-Effectiveness Analysis Comparing Pre-diagnosis Autism Spectrum Disorder (ASD)-Targeted Intervention with Ontario's Autism Intervention Program.

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Penner, Melanie; Rayar, Meera; Bashir, Naazish; Roberts, S Wendy; Hancock-Howard, Rebecca L; Coyte, Peter C

2015-09-01

Novel management strategies for autism spectrum disorder (ASD) propose providing interventions before diagnosis. We performed a cost-effectiveness analysis comparing the costs and dependency-free life years (DFLYs) generated by pre-diagnosis intensive Early Start Denver Model (ESDM-I); pre-diagnosis parent-delivered ESDM (ESDM-PD); and the Ontario Status Quo (SQ). The analyses took government and societal perspectives to age 65. We assigned probabilities of Independent, Semi-dependent or Dependent living based on projected IQ. Costs per person (in Canadian dollars) were ascribed to each living setting. From a government perspective, the ESDM-PD produced an additional 0.17 DFLYs for $8600 less than SQ. From a societal perspective, the ESDM-I produced an additional 0.53 DFLYs for $45,000 less than SQ. Pre-diagnosis interventions targeting ASD symptoms warrant further investigation.

Interventions to improve gross motor performance in children with neurodevelopmental disorders: a meta-analysis.

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Lucas, Barbara R; Elliott, Elizabeth J; Coggan, Sarah; Pinto, Rafael Z; Jirikowic, Tracy; McCoy, Sarah Westcott; Latimer, Jane

2016-11-29

Gross motor skills are fundamental to childhood development. The effectiveness of current physical therapy options for children with mild to moderate gross motor disorders is unknown. The aim of this study was to systematically review the literature to investigate the effectiveness of conservative interventions to improve gross motor performance in children with a range of neurodevelopmental disorders. A systematic review with meta-analysis was conducted. MEDLINE, EMBASE, AMED, CINAHL, PsycINFO, PEDro, Cochrane Collaboration, Google Scholar databases and clinical trial registries were searched. Published randomised controlled trials including children 3 to ≤18 years with (i) Developmental Coordination Disorder (DCD) or Cerebral Palsy (CP) (Gross Motor Function Classification System Level 1) or Developmental Delay or Minimal Acquired Brain Injury or Prematurity (gross motor outcomes obtained using a standardised assessment tool. Meta-analysis was performed to determine the pooled effect of intervention on gross motor function. Methodological quality and strength of meta-analysis recommendations were evaluated using PEDro and the GRADE approach respectively. Of 2513 papers, 9 met inclusion criteria including children with CP (n = 2) or DCD (n = 7) receiving 11 different interventions. Only two of 9 trials showed an effect for treatment. Using the least conservative trial outcomes a large beneficial effect of intervention was shown (SMD:-0.8; 95% CI:-1.1 to -0.5) with "very low quality" GRADE ratings. Using the most conservative trial outcomes there is no treatment effect (SMD:-0.1; 95% CI:-0.3 to 0.2) with "low quality" GRADE ratings. Study limitations included the small number and poor quality of the available trials. Although we found that some interventions with a task-orientated framework can improve gross motor outcomes in children with DCD or CP, these findings are limited by the very low quality of the available evidence. High quality intervention

Supporting the running and analysis of trials of web-based behavioural interventions: the LifeGuide

OpenAIRE

Yang, Yang; Osmond, Adrian; Chen, Xiaoyu; Weal, Mark; Wills, Gary; De Roure, David; Joseph, Judith; Yardley, Lucy

2009-01-01

Behavioural interventions - packages of advice and support for behaviour change - are one of the most important methodologies and technologies employed by social scientists for understanding and changing behaviour. A typical web-based behavioural intervention study includes the designing, deploying, piloting and trialling of the intervention as well as data analysis. We have developed a research environment named LifeGuide, which covers the full scope of this process, enabling social scientis...

Modeling activity patterns of wildlife using time-series analysis.

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Zhang, Jindong; Hull, Vanessa; Ouyang, Zhiyun; He, Liang; Connor, Thomas; Yang, Hongbo; Huang, Jinyan; Zhou, Shiqiang; Zhang, Zejun; Zhou, Caiquan; Zhang, Hemin; Liu, Jianguo

2017-04-01

The study of wildlife activity patterns is an effective approach to understanding fundamental ecological and evolutionary processes. However, traditional statistical approaches used to conduct quantitative analysis have thus far had limited success in revealing underlying mechanisms driving activity patterns. Here, we combine wavelet analysis, a type of frequency-based time-series analysis, with high-resolution activity data from accelerometers embedded in GPS collars to explore the effects of internal states (e.g., pregnancy) and external factors (e.g., seasonal dynamics of resources and weather) on activity patterns of the endangered giant panda ( Ailuropoda melanoleuca ). Giant pandas exhibited higher frequency cycles during the winter when resources (e.g., water and forage) were relatively poor, as well as during spring, which includes the giant panda's mating season. During the summer and autumn when resources were abundant, pandas exhibited a regular activity pattern with activity peaks every 24 hr. A pregnant individual showed distinct differences in her activity pattern from other giant pandas for several months following parturition. These results indicate that animals adjust activity cycles to adapt to seasonal variation of the resources and unique physiological periods. Wavelet coherency analysis also verified the synchronization of giant panda activity level with air temperature and solar radiation at the 24-hr band. Our study also shows that wavelet analysis is an effective tool for analyzing high-resolution activity pattern data and its relationship to internal and external states, an approach that has the potential to inform wildlife conservation and management across species.

Phytotherapy management: a new intervention for nursing intervention classification.

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Paloma, Echevarria; Ovidio, Céspedes; Jessica, Rojas; Francisca, Sánchez Ayllón; Isabel, Morales; Maravillas, Gimenez

2014-01-01

We present a new nurse intervention: "Phytotherapy Management," which has been accepted by the editorial board of the Nursing Interventions Classification for inclusion in the 7th edition of the Nursing Intervention Classification. This could have implications for nursing practice and research. Content analysis, extensive search in the literature.

A cost-effect analysis of an intervention against radon in homes

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Hein Stigum

2009-10-01

Full Text Available Background  Key words  : Radon exposure, lung cancer, cost-effect analysis, attributable risk, models-mathematical: Radon is a radioactive gas that may leak into buildings from the ground. Radon exposure is a risk factor for lung cancer. An intervention against radon exposure in homes may consist of locating homes with high radon exposure (above 200 Bq m-3 and improving these, and of protecting future houses. The purpose of this paper is to calculate the costs and the effects of this intervention. Methods: We performed a cost-effect analysis from the perspective of the society, followed by an uncertainty and sensitivity analysis. The distribution of radon levels in Norwegian homes is lognormal with mean=74.5 Bq/m3, and 7.6% above 200 Bq/m3. Results: The preventable attributable fraction of radon on lung cancer was 3.8% (95% uncertainty interval: 0.6%, 8.3%. In cumulative present values the intervention would cost $238 (145, 310 million and save 892 (133, 1981 lives, each life saved costs $0.27 (0.09, 0.9 million. The cost-effect ratio was sensitive to the radon risk, the radon exposure distribution, and the latency period of lung cancer. Together these three parameters explained 90% of the variation in the cost-effect ratio. Conclusions: Reducing the radon concentration in present and future homes to below 200 Bq/m3 will cost $0.27 (0.09, 0.9 million per life saved. The uncertainty in the estimated cost per life is large, mainly due to uncertainty in the risk of lung cancer from radon. Based on estimates from road construction, the Norwegian society has been willing to pay $1 million to save a life. We therefore conclude that the intervention against radon in homes is justifiable. The willingness to pay is also larger that the upper uncertainty limit of the cost per life. Our conclusion is therefore robust against the uncertainties in the parameters.

case series

African Journals Online (AJOL)

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Key words: Case report, case series, concept analysis, research design. African Health Sciences 2012; (4): 557 - 562 http://dx.doi.org/10.4314/ahs.v12i4.25. PO Box 17666 .... According to the latest version of the Dictionary of. Epidemiology ...

Operation States Analysis of the Series-Parallel resonant Converter Working Above Resonance Frequency

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Peter Dzurko

2007-01-01

Full Text Available Operation states analysis of a series-parallel converter working above resonance frequency is described in the paper. Principal equations are derived for individual operation states. On the basis of them the diagrams are made out. The diagrams give the complex image of the converter behaviour for individual circuit parameters. The waveforms may be utilised at designing the inverter individual parts.

Systematic review and meta-analysis of educational interventions designed to improve medication administration skills and safety of registered nurses.

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Härkänen, Marja; Voutilainen, Ari; Turunen, Elina; Vehviläinen-Julkunen, Katri

2016-06-01

The aim of this study is to evaluate the nature, quality and effectiveness of educational interventions designed to increase the medication administration skills and safety of registered nurses working in hospitals. A systematic review with meta-analysis. Intervention studies designed to increase the medication administration skills and safety of nurses, indexed in one or more databases (CINAHL, PubMed, Scopus, Cochrane, PsycInfo, or Medic), and published in peer-reviewed journals between January 2000 and April 2015. The nature of the interventions was evaluated by narrative analysis, the quality of studies was assessed using the Effective Public Health Practise Project Quality Assessment Tool and the effectiveness of the interventions was ascertained by calculating effect sizes and conducting a meta-analysis. A total of 755 studies were identified and 14 intervention studies were reviewed. Interventions differed by their nature, including traditional classroom training, simulation, e-learning, slide show presentations, interactive CD-ROM programme, and the use of posters and pamphlets. All interventions appeared to improve medication administration safety and skills based on original p-values. Only five studies reached strong (n=1) or moderate (n=4) quality ratings and one of them had to be omitted from the meta-analysis due unclear measures of dispersion. The meta-analysis favoured the interventions, the pooled effect size (Hedges' g) was large, 1.06. The most effective interventions were a blended learning programme including e-learning and a 60-min PowerPoint presentation. The least effective educational intervention, an interactive internet-based e-learning course, was reported in the study that achieved the only strong quality rating. It is challenging to recommend any specific intervention, because all educational interventions seem to have a positive effect, although the size of the effect greatly varies. In the future, studies sharing similar contents and

Mindfulness-based interventions for binge eating: a systematic review and meta-analysis.

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Godfrey, Kathryn M; Gallo, Linda C; Afari, Niloofar

2015-04-01

Mindfulness-based interventions are increasingly used to treat binge eating. The effects of these interventions have not been reviewed comprehensively. This systematic review and meta-analysis sought to summarize the literature on mindfulness-based interventions and determine their impact on binge eating behavior. PubMED, Web of Science, and PsycINFO were searched using keywords binge eating, overeating, objective bulimic episodes, acceptance and commitment therapy, dialectical behavior therapy, mindfulness, meditation, mindful eating. Of 151 records screened, 19 studies met inclusion criteria. Most studies showed effects of large magnitude. Results of random effects meta-analyses supported large or medium-large effects of these interventions on binge eating (within-group random effects mean Hedge's g = -1.12, 95 % CI -1.67, -0.80, k = 18; between-group mean Hedge's g = -0.70, 95 % CI -1.16, -0.24, k = 7). However, there was high statistical heterogeneity among the studies (within-group I(2) = 93 %; between-group I(2) = 90 %). Limitations and future research directions are discussed.

Cost-benefit analysis of a socio-technical intervention in a Brazilian footwear company.

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Guimarães, L B de M; Ribeiro, J L D; Renner, J S

2012-09-01

This article presents a costs-benefits analysis of a macroergonomic intervention in a Brazilian footwear company. Comparing results of a pilot line (composed by 100 multiskilled workers organized in teams) with eight traditional lines (still working in a one human being/one task model) the intervention showed to be worth pursuing since achieved gains were higher than intervention costs: there was a reduction in human resource costs (80% reduction in industrial accidents, 100% reduction in work-related musculoskeletal disorders or WMSD, medical consultations and turnover, and a 45.65% reduction in absenteeism) and production improvement (productivity increased in 3% and production waste decrease to less than 1%). The net intervention value of the intervention was around U$ 430,000 with a benefit-to-cost ratio of 7.2. Moreover, employees who worked in the pilot line understood that their quality of work life improved, compensating the anxiety brought up by the radical changes implemented. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

BiGGEsTS: integrated environment for biclustering analysis of time series gene expression data

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Madeira Sara C

2009-07-01

Full Text Available Abstract Background The ability to monitor changes in expression patterns over time, and to observe the emergence of coherent temporal responses using expression time series, is critical to advance our understanding of complex biological processes. Biclustering has been recognized as an effective method for discovering local temporal expression patterns and unraveling potential regulatory mechanisms. The general biclustering problem is NP-hard. In the case of time series this problem is tractable, and efficient algorithms can be used. However, there is still a need for specialized applications able to take advantage of the temporal properties inherent to expression time series, both from a computational and a biological perspective. Findings BiGGEsTS makes available state-of-the-art biclustering algorithms for analyzing expression time series. Gene Ontology (GO annotations are used to assess the biological relevance of the biclusters. Methods for preprocessing expression time series and post-processing results are also included. The analysis is additionally supported by a visualization module capable of displaying informative representations of the data, including heatmaps, dendrograms, expression charts and graphs of enriched GO terms. Conclusion BiGGEsTS is a free open source graphical software tool for revealing local coexpression of genes in specific intervals of time, while integrating meaningful information on gene annotations. It is freely available at: http://kdbio.inesc-id.pt/software/biggests. We present a case study on the discovery of transcriptional regulatory modules in the response of Saccharomyces cerevisiae to heat stress.

Health Facility Utilisation Changes during the Introduction of Community Case Management of Malaria in South Western Uganda: An Interrupted Time Series Approach.

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Sham Lal

Full Text Available Malaria endemic countries have scaled-up community health worker (CHW interventions, to diagnose and treat malaria in communities with limited access to public health systems. The evaluations of these programmes have centred on CHW's compliance to guidelines, but the broader changes at public health centres including utilisation and diagnoses made, has received limited attention.This analysis was conducted during a CHW-intervention for malaria in Rukungiri District, Western Uganda. Outpatient department (OPD visit data were collected for children under-5 attending three health centres one year before the CHW-intervention started (pre-intervention period and for 20 months during the intervention (intervention-period. An interrupted time series analysis with segmented regression models was used to compare the trends in malaria, non-malaria and overall OPD visits during the pre-intervention and intervention-period.The introduction of a CHW-intervention suggested the frequency of diagnoses of diarrhoeal diseases, pneumonia and helminths increased, whilst the frequency of malaria diagnoses declined at health centres. In May 2010 when the intervention began, overall health centre utilisation decreased by 63% compared to the pre-intervention period and the health centres saw 32 fewer overall visits per month compared to the pre-intervention period (p<0.001. Malaria visits also declined shortly after the intervention began and there were 27 fewer visits per month during the intervention-period compared with the pre-intervention period (p<0.05. The declines in overall and malaria visits were sustained for the entire intervention-period. In contrast, there were no observable changes in trends of non-malarial visits between the pre-intervention and intervention-period.This analysis suggests introducing a CHW-intervention can reduce the number of child malaria visits and change the profile of cases presenting at health centres. The reduction in workload of

Visualization of time series statistical data by shape analysis (GDP ratio changes among Asia countries)

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Shirota, Yukari; Hashimoto, Takako; Fitri Sari, Riri

2018-03-01

It has been very significant to visualize time series big data. In the paper we shall discuss a new analysis method called “statistical shape analysis” or “geometry driven statistics” on time series statistical data in economics. In the paper, we analyse the agriculture, value added and industry, value added (percentage of GDP) changes from 2000 to 2010 in Asia. We handle the data as a set of landmarks on a two-dimensional image to see the deformation using the principal components. The point of the analysis method is the principal components of the given formation which are eigenvectors of its bending energy matrix. The local deformation can be expressed as the set of non-Affine transformations. The transformations give us information about the local differences between in 2000 and in 2010. Because the non-Affine transformation can be decomposed into a set of partial warps, we present the partial warps visually. The statistical shape analysis is widely used in biology but, in economics, no application can be found. In the paper, we investigate its potential to analyse the economic data.

Non-parametric characterization of long-term rainfall time series

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Tiwari, Harinarayan; Pandey, Brij Kishor

2018-03-01

The statistical study of rainfall time series is one of the approaches for efficient hydrological system design. Identifying, and characterizing long-term rainfall time series could aid in improving hydrological systems forecasting. In the present study, eventual statistics was applied for the long-term (1851-2006) rainfall time series under seven meteorological regions of India. Linear trend analysis was carried out using Mann-Kendall test for the observed rainfall series. The observed trend using the above-mentioned approach has been ascertained using the innovative trend analysis method. Innovative trend analysis has been found to be a strong tool to detect the general trend of rainfall time series. Sequential Mann-Kendall test has also been carried out to examine nonlinear trends of the series. The partial sum of cumulative deviation test is also found to be suitable to detect the nonlinear trend. Innovative trend analysis, sequential Mann-Kendall test and partial cumulative deviation test have potential to detect the general as well as nonlinear trend for the rainfall time series. Annual rainfall analysis suggests that the maximum changes in mean rainfall is 11.53% for West Peninsular India, whereas the maximum fall in mean rainfall is 7.8% for the North Mountainous Indian region. The innovative trend analysis method is also capable of finding the number of change point available in the time series. Additionally, we have performed von Neumann ratio test and cumulative deviation test to estimate the departure from homogeneity. Singular spectrum analysis has been applied in this study to evaluate the order of departure from homogeneity in the rainfall time series. Monsoon season (JS) of North Mountainous India and West Peninsular India zones has higher departure from homogeneity and singular spectrum analysis shows the results to be in coherence with the same.

Multidimensional scaling analysis of financial time series based on modified cross-sample entropy methods

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He, Jiayi; Shang, Pengjian; Xiong, Hui

2018-06-01

Stocks, as the concrete manifestation of financial time series with plenty of potential information, are often used in the study of financial time series. In this paper, we utilize the stock data to recognize their patterns through out the dissimilarity matrix based on modified cross-sample entropy, then three-dimensional perceptual maps of the results are provided through multidimensional scaling method. Two modified multidimensional scaling methods are proposed in this paper, that is, multidimensional scaling based on Kronecker-delta cross-sample entropy (MDS-KCSE) and multidimensional scaling based on permutation cross-sample entropy (MDS-PCSE). These two methods use Kronecker-delta based cross-sample entropy and permutation based cross-sample entropy to replace the distance or dissimilarity measurement in classical multidimensional scaling (MDS). Multidimensional scaling based on Chebyshev distance (MDSC) is employed to provide a reference for comparisons. Our analysis reveals a clear clustering both in synthetic data and 18 indices from diverse stock markets. It implies that time series generated by the same model are easier to have similar irregularity than others, and the difference in the stock index, which is caused by the country or region and the different financial policies, can reflect the irregularity in the data. In the synthetic data experiments, not only the time series generated by different models can be distinguished, the one generated under different parameters of the same model can also be detected. In the financial data experiment, the stock indices are clearly divided into five groups. Through analysis, we find that they correspond to five regions, respectively, that is, Europe, North America, South America, Asian-Pacific (with the exception of mainland China), mainland China and Russia. The results also demonstrate that MDS-KCSE and MDS-PCSE provide more effective divisions in experiments than MDSC.

Harmonic Analysis of a Nonstationary Series of Temperature Paleoreconstruction for the Central Part of Greenland

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T.E. Danova

2016-06-01

Full Text Available The results of the investigations of a transformed series of reconstructed air temperature data for the central part of Greenland with an increment of 30 years have been presented. Stationarization of a ~ 50,000-years’ series of the reconstructed air temperature in the central part of Greenland according to ice core data has been performed using mathematical expectation. To obtain mathematical expectation estimation, the smoothing procedure by the methods of moving average and wavelet analysis has been carried out. Fourier’s transformation has been applied repeatedly to the stationarized series with changing the averaging time in the process of smoothing. Three averaging time values have been selected for the investigations: ~ 400–500 years, ~ 2,000 years, and ~ 4,000 years. Stationarization of the reconstructed temperature series with the help of wavelet transformation showed the best results when applying the averaging time of ~ 400 and ~ 2000 years, the trends well characterize the initial temperature series, there-by revealing the main patterns of its dynamics. Using the period with the averaging time of ~ 4,000 years showed the worst result: significant events of the main temperature series were lost in the process of averaging. The obtained results well correspond to cycling known to be inherent to the climatic system of the planet; the detected modes of 1,470 ± 500 years are comparable to the Dansgaard–Oeschger and Bond oscillations.

Firecracker eye injuries during Deepavali festival: A case series

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Kumar Ravi

2010-01-01

Full Text Available We report a large series of ocular injuries caused by fire-crackers. This study was a hospital-based, singlecenter, retrospective case series in which the records of 51 patients with ocular injuries were analyzed. Injuries were classified according to Birmingham eye trauma terminology system (BETTS. Visual outcomes before and after the intervention were recorded. Ten patients were admitted for further management. As ocular firecracker injuries result in significant morbidity, public education regarding proper use of firecrackers may help in reducing the incidence of ocular injuries.

Studies in Astronomical Time Series Analysis. VI. Bayesian Block Representations

Science.gov (United States)

Scargle, Jeffrey D.; Norris, Jay P.; Jackson, Brad; Chiang, James

2013-01-01

This paper addresses the problem of detecting and characterizing local variability in time series and other forms of sequential data. The goal is to identify and characterize statistically significant variations, at the same time suppressing the inevitable corrupting observational errors. We present a simple nonparametric modeling technique and an algorithm implementing it-an improved and generalized version of Bayesian Blocks [Scargle 1998]-that finds the optimal segmentation of the data in the observation interval. The structure of the algorithm allows it to be used in either a real-time trigger mode, or a retrospective mode. Maximum likelihood or marginal posterior functions to measure model fitness are presented for events, binned counts, and measurements at arbitrary times with known error distributions. Problems addressed include those connected with data gaps, variable exposure, extension to piece- wise linear and piecewise exponential representations, multivariate time series data, analysis of variance, data on the circle, other data modes, and dispersed data. Simulations provide evidence that the detection efficiency for weak signals is close to a theoretical asymptotic limit derived by [Arias-Castro, Donoho and Huo 2003]. In the spirit of Reproducible Research [Donoho et al. (2008)] all of the code and data necessary to reproduce all of the figures in this paper are included as auxiliary material.

STUDIES IN ASTRONOMICAL TIME SERIES ANALYSIS. VI. BAYESIAN BLOCK REPRESENTATIONS

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Scargle, Jeffrey D. [Space Science and Astrobiology Division, MS 245-3, NASA Ames Research Center, Moffett Field, CA 94035-1000 (United States); Norris, Jay P. [Physics Department, Boise State University, 2110 University Drive, Boise, ID 83725-1570 (United States); Jackson, Brad [The Center for Applied Mathematics and Computer Science, Department of Mathematics, San Jose State University, One Washington Square, MH 308, San Jose, CA 95192-0103 (United States); Chiang, James, E-mail: jeffrey.d.scargle@nasa.gov [W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305 (United States)

2013-02-20

This paper addresses the problem of detecting and characterizing local variability in time series and other forms of sequential data. The goal is to identify and characterize statistically significant variations, at the same time suppressing the inevitable corrupting observational errors. We present a simple nonparametric modeling technique and an algorithm implementing it-an improved and generalized version of Bayesian Blocks-that finds the optimal segmentation of the data in the observation interval. The structure of the algorithm allows it to be used in either a real-time trigger mode, or a retrospective mode. Maximum likelihood or marginal posterior functions to measure model fitness are presented for events, binned counts, and measurements at arbitrary times with known error distributions. Problems addressed include those connected with data gaps, variable exposure, extension to piecewise linear and piecewise exponential representations, multivariate time series data, analysis of variance, data on the circle, other data modes, and dispersed data. Simulations provide evidence that the detection efficiency for weak signals is close to a theoretical asymptotic limit derived by Arias-Castro et al. In the spirit of Reproducible Research all of the code and data necessary to reproduce all of the figures in this paper are included as supplementary material.

River catchment rainfall series analysis using additive Holt-Winters method

Science.gov (United States)

Puah, Yan Jun; Huang, Yuk Feng; Chua, Kuan Chin; Lee, Teang Shui

2016-03-01

Climate change is receiving more attention from researchers as the frequency of occurrence of severe natural disasters is getting higher. Tropical countries like Malaysia have no distinct four seasons; rainfall has become the popular parameter to assess climate change. Conventional ways that determine rainfall trends can only provide a general result in single direction for the whole study period. In this study, rainfall series were modelled using additive Holt-Winters method to examine the rainfall pattern in Langat River Basin, Malaysia. Nine homogeneous series of more than 25 years data and less than 10% missing data were selected. Goodness of fit of the forecasted models was measured. It was found that seasonal rainfall model forecasts are generally better than the monthly rainfall model forecasts. Three stations in the western region exhibited increasing trend. Rainfall in southern region showed fluctuation. Increasing trends were discovered at stations in the south-eastern region except the seasonal analysis at station 45253. Decreasing trend was found at station 2818110 in the east, while increasing trend was shown at station 44320 that represents the north-eastern region. The accuracies of both rainfall model forecasts were tested using the recorded data of years 2010-2012. Most of the forecasts are acceptable.

STUDIES IN ASTRONOMICAL TIME SERIES ANALYSIS. VI. BAYESIAN BLOCK REPRESENTATIONS

International Nuclear Information System (INIS)

Scargle, Jeffrey D.; Norris, Jay P.; Jackson, Brad; Chiang, James

2013-01-01

This paper addresses the problem of detecting and characterizing local variability in time series and other forms of sequential data. The goal is to identify and characterize statistically significant variations, at the same time suppressing the inevitable corrupting observational errors. We present a simple nonparametric modeling technique and an algorithm implementing it—an improved and generalized version of Bayesian Blocks—that finds the optimal segmentation of the data in the observation interval. The structure of the algorithm allows it to be used in either a real-time trigger mode, or a retrospective mode. Maximum likelihood or marginal posterior functions to measure model fitness are presented for events, binned counts, and measurements at arbitrary times with known error distributions. Problems addressed include those connected with data gaps, variable exposure, extension to piecewise linear and piecewise exponential representations, multivariate time series data, analysis of variance, data on the circle, other data modes, and dispersed data. Simulations provide evidence that the detection efficiency for weak signals is close to a theoretical asymptotic limit derived by Arias-Castro et al. In the spirit of Reproducible Research all of the code and data necessary to reproduce all of the figures in this paper are included as supplementary material.

Analysis of radiation-induced microchemical evolution in 300 series stainless steel

International Nuclear Information System (INIS)

Brager, H.R.; Garner, F.A.

1980-03-01

The irradiation of 300 series stainless steel by fast neutrons leads to an evolution of alloy microstructures that involves not only the formation of voids and dislocations, but also an extensive repartitioning of elements between various phases. This latter evolution has been shown to be the primary determinant of the alloy behavior in response to the large number of variables which influence void swelling and irradiation creep. The combined use of scanning transmission electron microscopy and energy-dispersive x-ray analysis has been the key element in the study of this phenomenon. Problems associated with the analysis of radioactive specimens are resolved by minor equipment modifications. Problems associated with spatial resolution limitations and the complexity and heterogeneity of the microchemical evolution have been overcome by using several data acquisition techniques. These include the measurement of compositional profiles near sinks, the use of foil-edge analysis, and the statistical sampling of many matrix and precipitate volumes

Analysis of JET ELMy time series

International Nuclear Information System (INIS)

Zvejnieks, G.; Kuzovkov, V.N.

2005-01-01

Full text: Achievement of the planned operational regime in the next generation tokamaks (such as ITER) still faces principal problems. One of the main challenges is obtaining the control of edge localized modes (ELMs), which should lead to both long plasma pulse times and reasonable divertor life time. In order to control ELMs the hypothesis was proposed by Degeling [1] that ELMs exhibit features of chaotic dynamics and thus a standard chaos control methods might be applicable. However, our findings which are based on the nonlinear autoregressive (NAR) model contradict this hypothesis for JET ELMy time-series. In turn, it means that ELM behavior is of a relaxation or random type. These conclusions coincide with our previous results obtained for ASDEX Upgrade time series [2]. [1] A.W. Degeling, Y.R. Martin, P.E. Bak, J. B.Lister, and X. Llobet, Plasma Phys. Control. Fusion 43, 1671 (2001). [2] G. Zvejnieks, V.N. Kuzovkov, O. Dumbrajs, A.W. Degeling, W. Suttrop, H. Urano, and H. Zohm, Physics of Plasmas 11, 5658 (2004)

A Detailed Analysis of Prehospital Interventions in Common Medical Priority Dispatch System Determinants

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Sporer, Karl A

2011-02-01

Full Text Available Background: Medical Priority Dispatch System (MPDS is a type of Emergency Medical Dispatch (EMD system used to prioritize 9-1-1 calls and optimize resource allocation. Dispatchers use a series of scripted questions to assign determinants to calls based on chief complaint and acuity.Objective: We analyzed the prehospital interventions performed on patients with MPDS determinants for breathing problems, chest pain, unknown problem (man down, seizures, fainting (unconscious and falls for transport status and interventions.Methods: We matched all prehospital patients in complaint-based categories for breathing problems, chest pain, unknown problem (man down, seizures, fainting (unconscious and falls from January 1, 2004, to December 31, 2006, with their prehospital record. Calls were queried for the following prehospital interventions: Basic Life Support care only, intravenous line placement only, medication given, procedures or non-transport. We defined Advanced Life Support (ALS interventions as the administration of a medication or a procedure.Results: Of the 77,394 MPDS calls during this period, 31,318 (40% patients met inclusion criteria. Breathing problems made up 12.2%, chest pain 6%, unknown problem 1.4%, seizures 3%, falls 9% and unconscious/fainting 9% of the total number of MPDS calls. Patients with breathing problem had a low rate of procedures (0.7% and cardiac arrest medications (1.6% with 38% receiving some medication. Chest pain patients had a similar distribution; procedures (0.5%, cardiac arrest medication (1.5% and any medication (64%. Unknown problem: procedures (1%, cardiac arrest medication (1.3%, any medication (18%. Patients with Seizures had a low rate of procedures (1.1% and cardiac arrest medications (0.6% with 20% receiving some medication. Fall patients had a lower rate of severe illness with more medication, mostly morphine: procedures (0.2%, cardiac arrest medication (0.2%, all medications (28%. Unconscious

Time series analysis of infrared satellite data for detecting thermal anomalies: a hybrid approach

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Koeppen, W. C.; Pilger, E.; Wright, R.

2011-07-01

We developed and tested an automated algorithm that analyzes thermal infrared satellite time series data to detect and quantify the excess energy radiated from thermal anomalies such as active volcanoes. Our algorithm enhances the previously developed MODVOLC approach, a simple point operation, by adding a more complex time series component based on the methods of the Robust Satellite Techniques (RST) algorithm. Using test sites at Anatahan and Kīlauea volcanoes, the hybrid time series approach detected ~15% more thermal anomalies than MODVOLC with very few, if any, known false detections. We also tested gas flares in the Cantarell oil field in the Gulf of Mexico as an end-member scenario representing very persistent thermal anomalies. At Cantarell, the hybrid algorithm showed only a slight improvement, but it did identify flares that were undetected by MODVOLC. We estimate that at least 80 MODIS images for each calendar month are required to create good reference images necessary for the time series analysis of the hybrid algorithm. The improved performance of the new algorithm over MODVOLC will result in the detection of low temperature thermal anomalies that will be useful in improving our ability to document Earth's volcanic eruptions, as well as detecting low temperature thermal precursors to larger eruptions.

Comparison of correlation analysis techniques for irregularly sampled time series

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K. Rehfeld

2011-06-01

Full Text Available Geoscientific measurements often provide time series with irregular time sampling, requiring either data reconstruction (interpolation or sophisticated methods to handle irregular sampling. We compare the linear interpolation technique and different approaches for analyzing the correlation functions and persistence of irregularly sampled time series, as Lomb-Scargle Fourier transformation and kernel-based methods. In a thorough benchmark test we investigate the performance of these techniques.

All methods have comparable root mean square errors (RMSEs for low skewness of the inter-observation time distribution. For high skewness, very irregular data, interpolation bias and RMSE increase strongly. We find a 40 % lower RMSE for the lag-1 autocorrelation function (ACF for the Gaussian kernel method vs. the linear interpolation scheme,in the analysis of highly irregular time series. For the cross correlation function (CCF the RMSE is then lower by 60 %. The application of the Lomb-Scargle technique gave results comparable to the kernel methods for the univariate, but poorer results in the bivariate case. Especially the high-frequency components of the signal, where classical methods show a strong bias in ACF and CCF magnitude, are preserved when using the kernel methods.

We illustrate the performances of interpolation vs. Gaussian kernel method by applying both to paleo-data from four locations, reflecting late Holocene Asian monsoon variability as derived from speleothem δ¹⁸O measurements. Cross correlation results are similar for both methods, which we attribute to the long time scales of the common variability. The persistence time (memory is strongly overestimated when using the standard, interpolation-based, approach. Hence, the Gaussian kernel is a reliable and more robust estimator with significant advantages compared to other techniques and suitable for large scale application to paleo-data.

Cost analysis of radiological interventional procedures and reimbursement within a clinic

International Nuclear Information System (INIS)

Strotzer, M.; Voelk, M.; Lenhart, M.; Fruend, R.; Feuerbach, S.

2002-01-01

Purpose: Analysis of costs for vascular radiological interventions on a per patient basis and comparison with reimbursement based on GOAe(Gebuehrenordnung fuer Aerzte) and DKG-NT (Deutsche Krankenhausgesellschaft-Nebenkostentarif). Material and Methods: The ten procedures most frequently performed within 12 months were evaluated. Personnel costs were derived from precise costs per hour and estimated procedure time for each intervention. Costs for medical devices were included. Reimbursement based on GOAewas calculated using the official conversion factor of 0.114 DM for each specific relative value unit and a multiplication factor of 1.0. The corresponding conversion factor for DKG-NT, determined by the DKG, was 0.168 DM. Results: A total of 832 interventional procedures were included. Marked differences between calculated costs and reimbursement rates were found. Regarding the ten most frequently performed procedures, there was a deficit of 1.06 million DM according GOAedata (factor 1.0) and 0.787 million DM according DKG-NT. The percentage of reimbursement was only 34.2 (GOAe; factor 1.0) and 51.3 (DKG-NT), respectively. Conclusion: Reimbursement of radiological interventional procedures based on GOAeand DKG-NT data is of limited value for economic controlling purposes within a hospital. (orig.) [de

Teaching Children to Write: A Meta-analysis of Writing Intervention Research

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Monica Koster

2015-10-01

Full Text Available It has been established that in the Netherlands, as in other countries, a majority of students do not attain the desired level of writing skills at the end of elementary school. Time devoted to writing is limited, and only a minority of schools succeed in effectively teaching writing. An improvement in the way writing is taught in elementary school is clearly required. In order to identify effective instructional practices we conducted a meta-analysis of writing intervention studies aimed at grade 4 to 6 in a regular school setting. Average effect sizes were calculated for ten intervention categories: strategy instruction, text structure instruction, pre-writing activities, peer assistance, grammar instruction, feedback, evaluation, process approach, goal setting, and revision. Five of these categories yielded statistically significant results. Pairwise comparison of these categories revealed that goal setting (ES = 2.03 is the most effective intervention to improve students’ writing performance, followed by strategy instruction (ES = .96, text structure instruction (ES = .76, peer assistance (ES = .59, and feedback (ES = .88 respectively. Further research is needed to examine how these interventions can be implemented effectively in classrooms to improve elementary students’ writing performance.

Physical activity interventions differentially affect exercise task and barrier self-efficacy: a meta-analysis.

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Higgins, Torrance J; Middleton, Kathryn R; Winner, Larry; Janelle, Christopher M

2014-08-01

Researchers have yet to establish how interventions to increase physical activity influence specific self-efficacy beliefs. The current study sought to quantify the effect of interventions to increase physical activity among healthy adults on exercise task (EXSE) and barrier self-efficacy (BSE) via meta-analysis. Intervention characteristics associated with self-efficacy and physical activity changes were also identified. A systematic database search and manual searches through reference lists of related publications were conducted for articles on randomized, controlled physical activity interventions. Published intervention studies reporting changes in physical activity behavior and either EXSE or BSE in healthy adults were eligible for inclusion. Of the 1,080 studies identified, 20 were included in the meta-analyses. Interventions had a significant effect of g = 0.208, 95% confidence interval (CI) [0.027, 0.388], p exercise sessions effectively increased EXSE and physical activity, whereas long interventions improved BSE. Interventions that did not provide support increased BSE and physical activity levels. Further, interventions that did not require the use of daily exercise logs improved EXSE and physical activity behavior. Interventions designed to increase physical activity differentially influenced EXSE and BSE. EXSE appeared to play a more significant role during exercise adoption, whereas BSE was involved in the maintenance of exercise behavior. Recommendations are offered for the design of future interventions.

Pooled Analysis of Six Pharmacologic and Nonpharmacologic Interventions for Vasomotor Symptoms

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Guthrie, Katherine A.; LaCroix, Andrea Z.; Ensrud, Kristine E.; Joffe, Hadine; Newton, Katherine M.; Reed, Susan D.; Caan, Bette; Carpenter, Janet S.; Cohen, Lee S.; Freeman, Ellen W.; Larson, Joseph C.; Manson, JoAnn E.; Rexrode, Kathy; Skaar, Todd C.; Sternfeld, Barbara; Anderson, Garnet L.

2015-01-01

Objective To describe the effects of six interventions for menopausal vasomotor symptoms relative to control in a pooled analysis, facilitating translation of the results for clinicians and symptomatic women. The MsFLASH (Menopause Strategies: Finding Lasting Answers for Symptoms and Health) network tested these interventions in three randomized clinical trials (RCTs). Methods An analysis of pooled individual-level data from three RCTs is presented. Participants were 899 peri- and postmenopausal women with at least 14 bothersome vasomotor symptoms/week. Interventions included escitalopram 10–20 mg/day, non-aerobic yoga, aerobic exercise, 1.8 g/day omega-3 fatty acid supplementation, low-dose oral 17-beta-estradiol 0.5-mg/day, and low-dose venlafaxine XR 75-mg/day. The main outcome measures were changes from baseline in mean daily vasomotor symptoms frequency and bother during 8–12 weeks of treatment. Linear regression models estimated differences in outcomes between each intervention and corresponding control group, adjusted for baseline characteristics. Models included trial-specific intercepts, effects of the baseline outcome measure, and time. Results The 8-week reduction in vasomotor symptoms frequency from baseline relative to placebo was similar for escitalopram at −1.4/day (95% CI: −2.7 to −0.2), low-dose estradiol at −2.4 (95% CI: −3.4 to −1.3), and venlafaxine at −1.8 (95% CI: −2.8 to −0.8); vasomotor symptoms bother reduction was minimal and did not vary across these three pharmacologic interventions (means −0.2 to −0.3 relative to placebo). No effects on vasomotor symptoms frequency or bother were seen with aerobic exercise, yoga or omega-3 supplements. Conclusions These analyses suggest that escitalopram, low-dose estradiol, and venlafaxine provide comparable, modest reductions in vasomotor symptoms frequency and bother among women with moderate hot flushes. Clinical Trial Registration ClinicalTrials.gov, www

Time series modeling, computation, and inference

CERN Document Server

Prado, Raquel

2010-01-01

The authors systematically develop a state-of-the-art analysis and modeling of time series. … this book is well organized and well written. The authors present various statistical models for engineers to solve problems in time series analysis. Readers no doubt will learn state-of-the-art techniques from this book.-Hsun-Hsien Chang, Computing Reviews, March 2012My favorite chapters were on dynamic linear models and vector AR and vector ARMA models.-William Seaver, Technometrics, August 2011… a very modern entry to the field of time-series modelling, with a rich reference list of the current lit

Effect of nocturnal sound reduction on the incidence of delirium in intensive care unit patients: An interrupted time series analysis.

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van de Pol, Ineke; van Iterson, Mat; Maaskant, Jolanda

2017-08-01

Delirium in critically-ill patients is a common multifactorial disorder that is associated with various negative outcomes. It is assumed that sleep disturbances can result in an increased risk of delirium. This study hypothesized that implementing a protocol that reduces overall nocturnal sound levels improves quality of sleep and reduces the incidence of delirium in Intensive Care Unit (ICU) patients. This interrupted time series study was performed in an adult mixed medical and surgical 24-bed ICU. A pre-intervention group of 211 patients was compared with a post-intervention group of 210 patients after implementation of a nocturnal sound-reduction protocol. Primary outcome measures were incidence of delirium, measured by the Intensive Care Delirium Screening Checklist (ICDSC) and quality of sleep, measured by the Richards-Campbell Sleep Questionnaire (RCSQ). Secondary outcome measures were use of sleep-inducing medication, delirium treatment medication, and patient-perceived nocturnal noise. A significant difference in slope in the percentage of delirium was observed between the pre- and post-intervention periods (-3.7% per time period, p=0.02). Quality of sleep was unaffected (0.3 per time period, p=0.85). The post-intervention group used significantly less sleep-inducing medication (psound-reduction protocol. However, reported sleep quality did not improve. Copyright © 2017. Published by Elsevier Ltd.

Dietary interventions to prevent and manage diabetes in worksite settings: a meta-analysis

OpenAIRE

Shrestha, Archana; Karmacharya, Biraj Man; Khudyakov, Polyna; Weber, Mary Beth; Spiegelman, Donna

2017-01-01

Objectives: The translation of lifestyle intervention to improve glucose tolerance into the workplace has been rare. The objective of this meta-analysis is to summarize the evidence for the effectiveness of dietary interventions in worksite settings on lowering blood sugar levels. Methods: We searched for studies in PubMed, Embase, Econlit, Ovid, Cochrane, Web of Science, and Cumulative Index to Nursing and Allied Health Literature. Search terms were as follows: (1) Exposure-based: nutrition/...

A Time Series Analysis to Asymmetric Marketing Competition Within a Market Structure

OpenAIRE

Francisco F. R. Ramos

1996-01-01

As a complementary to the existing studies of competitive market structure analysis, the present paper proposed a time series methodology to provide a more detailed picture of marketing competition in relation to competitive market structure. Two major hypotheses were tested as part of this project. First, it was found that some significant cross- lead and lag effects of marketing variables on sales between brands existed even between differents submarkets. second, it was found that high qual...

On-line condition monitoring of nuclear systems via symbolic time series analysis

International Nuclear Information System (INIS)

Rajagopalan, V.; Ray, A.; Garcia, H. E.

2006-01-01

This paper provides a symbolic time series analysis approach to fault diagnostics and condition monitoring. The proposed technique is built upon concepts from wavelet theory, symbolic dynamics and pattern recognition. Various aspects of the methodology such as wavelet selection, choice of alphabet and determination of depth of D-Markov Machine are explained in the paper. The technique is validated with experiments performed in a Machine Condition Monitoring (MCM) test bed at the Idaho National Laboratory. (authors)

Detrended fluctuation analysis based on higher-order moments of financial time series

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Teng, Yue; Shang, Pengjian

2018-01-01

In this paper, a generalized method of detrended fluctuation analysis (DFA) is proposed as a new measure to assess the complexity of a complex dynamical system such as stock market. We extend DFA and local scaling DFA to higher moments such as skewness and kurtosis (labeled SMDFA and KMDFA), so as to investigate the volatility scaling property of financial time series. Simulations are conducted over synthetic and financial data for providing the comparative study. We further report the results of volatility behaviors in three American countries, three Chinese and three European stock markets by using DFA and LSDFA method based on higher moments. They demonstrate the dynamics behaviors of time series in different aspects, which can quantify the changes of complexity for stock market data and provide us with more meaningful information than single exponent. And the results reveal some higher moments volatility and higher moments multiscale volatility details that cannot be obtained using the traditional DFA method.

Economic feasibility of biogas production in swine farms using time series analysis

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Felipe Luis Rockenbach

2016-07-01

Full Text Available ABSTRACT: This study aimed to measure the economic feasibility and the time needed to return capital invested for the installation of a swine manure treatment system, these values originated the sale of carbon credits and/or of compensation of electric energy in swine farms, using the Box-Jenkins forecast models. It was found that the use of biogas is a viable option in a large scale with machines that operate daily for 10h or more, being the return period between 70 to 80 months. Time series analysis models are important to anticipate the series under study behavior, providing the swine breeder/investor means to reduce the financial investment risk as well as helping to decrease the production costs. Moreover, this process can be seen as another source of income and enable the breeder to be self-sufficient in the continuous supply of electric energy, which is very valuable nowadays considering that breeders are now increasingly using various technologies.

A prospective interrupted time series study of interventions to improve the quality, rating, framing and structure of goal-setting in community-based brain injury rehabilitation.

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Hassett, Leanne; Simpson, Grahame; Cotter, Rachel; Whiting, Diane; Hodgkinson, Adeline; Martin, Diane

2015-04-01

To investigate whether the introduction of an electronic goals system followed by staff training improved the quality, rating, framing and structure of goals written by a community-based brain injury rehabilitation team. Interrupted time series design. Two interventions were introduced six months apart. The first intervention comprised the introduction of an electronic goals system. The second intervention comprised a staff goal training workshop. An audit protocol was devised to evaluate the goals. A random selection of goal statements from the 12 months prior to the interventions (Time 1 baseline) were compared with all goal statements written after the introduction of the electronic goals system (Time 2) and staff training (Time 3). All goals were de-identified for client and time-period, and randomly ordered. A total of 745 goals (Time 1 n = 242; Time 2 n = 283; Time 3 n = 220) were evaluated. Compared with baseline, the introduction of the electronic goals system alone significantly increased goal rating, framing and structure (χ(2) tests 144.7, 18.9, 48.1, respectively, p goal quality, which was only a trend at Time 2, was statistically significant at Time 3 (χ(2) 15.0, p ≤ 001). The training also led to a further significant increase in the framing and structuring of goals over the electronic goals system (χ(2) 11.5, 12.5, respectively, p ≤ 0.001). An electronic goals system combined with staff training improved the quality, rating, framing and structure of goal statements. © The Author(s) 2014.

Short-term forecasting of meteorological time series using Nonparametric Functional Data Analysis (NPFDA)

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Curceac, S.; Ternynck, C.; Ouarda, T.

2015-12-01

Over the past decades, a substantial amount of research has been conducted to model and forecast climatic variables. In this study, Nonparametric Functional Data Analysis (NPFDA) methods are applied to forecast air temperature and wind speed time series in Abu Dhabi, UAE. The dataset consists of hourly measurements recorded for a period of 29 years, 1982-2010. The novelty of the Functional Data Analysis approach is in expressing the data as curves. In the present work, the focus is on daily forecasting and the functional observations (curves) express the daily measurements of the above mentioned variables. We apply a non-linear regression model with a functional non-parametric kernel estimator. The computation of the estimator is performed using an asymmetrical quadratic kernel function for local weighting based on the bandwidth obtained by a cross validation procedure. The proximities between functional objects are calculated by families of semi-metrics based on derivatives and Functional Principal Component Analysis (FPCA). Additionally, functional conditional mode and functional conditional median estimators are applied and the advantages of combining their results are analysed. A different approach employs a SARIMA model selected according to the minimum Akaike (AIC) and Bayessian (BIC) Information Criteria and based on the residuals of the model. The performance of the models is assessed by calculating error indices such as the root mean square error (RMSE), relative RMSE, BIAS and relative BIAS. The results indicate that the NPFDA models provide more accurate forecasts than the SARIMA models. Key words: Nonparametric functional data analysis, SARIMA, time series forecast, air temperature, wind speed

Physical activity interventions differentially affect exercise task and barrier self-efficacy: A meta-analysis

Science.gov (United States)

Higgins, Torrance J.; Middleton, Kathryn R.; Winner, Larry; Janelle, Christopher M.; Middleton, Kathryn R.

2014-01-01

Objective Researchers have yet to establish how interventions to increase physical activity influence specific self-efficacy beliefs. The current study sought to quantify the effect of interventions to increase physical activity among healthy adults on exercise task (EXSE) and barrier self-efficacy (BSE) via meta-analysis. Intervention characteristics associated with self-efficacy and physical activity changes were also identified. Methods A systematic database search and manual searches through reference lists of related publications were conducted for articles on randomized, controlled physical activity interventions. Published intervention studies reporting changes in physical activity behavior and either EXSE or BSE in healthy adults were eligible for inclusion. Results Of the 1,080 studies identified, 20 were included in the meta-analyses. Interventions had a significant effect of g = 0.208, 95% confidence interval (CI) [0.027, 0.388], p physical activity. Moderator analyses indicated shorter interventions that did not include structured exercise sessions effectively increased EXSE and physical activity, whereas long interventions improved BSE. Interventions that did not provide support increased BSE and physical activity levels. Further, interventions that did not require the use of daily exercise logs improved EXSE and physical activity behavior. Conclusion Interventions designed to increase physical activity differentially influenced EXSE and BSE. EXSE appeared to play a more significant role during exercise adoption, whereas BSE was involved in the maintenance of exercise behavior. Recommendations are offered for the design of future interventions. PMID:23957904

Interventions for addressing low balance confidence in older adults: a systematic review and meta-analysis.

Science.gov (United States)

Rand, Debbie; Miller, William C; Yiu, Jeanne; Eng, Janice J

2011-05-01

low balance confidence is a major health problem among older adults restricting their participation in daily life. to determine what interventions are most effective in increasing balance confidence in older adults. systematic review with meta-analysis of randomised controlled trials including at least one continuous end point of balance confidence. Studies, including adults 60 years or older without a neurological condition, were included in our study. the standardised mean difference (SMD) of continuous end points of balance confidence was calculated to estimate the pooled effect size with random-effect models. Methodological quality of trials was assessed using the Physical Therapy Evidence Database (PEDro) Scale. thirty studies were included in this review and a meta-analysis was conducted for 24 studies. Interventions were pooled into exercise (n = 9 trials, 453 subjects), Tai Chi (n = 5 trials, 468 subjects), multifactorial intervention (n = 10 trials, 1,233 subjects). Low significant effects were found for exercise and multifactorial interventions (SMD 0.22-0.31) and medium (SMD 0.48) significant effects were found for Tai Chi. Tai chi interventions are the most beneficial in increasing the balance confidence of older adults.

Effect of Exercise Intervention on Flow-Mediated Dilation in Overweight and Obese Adults: Meta-Analysis

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Younsun Son

2017-01-01

Full Text Available The objective of this meta-analysis is to summarize the effect of exercise intervention on flow-mediated dilatation (FMD in overweight and obese adults. We searched four electronic databases (PubMed/Medline, Scopus, and CINAHL through June 2016 for relevant studies pertaining to the effectiveness of exercise intervention on FMD. Seventeen of the 91 studies identified met the inclusion criteria. Comprehensive Meta-Analysis software (version 3 was used to compute the standardized mean difference effect size (ES and 95% CI using a random effects model. We calculated 34 ESs. We found that exercise intervention had medium and positive effects on FMD, with an overall ES of 0.522 (95% CI = 0.257, 0.786. Heterogeneity of ESs was observed (Qb=239, p≤0.001, I2 = 86.19, and the effect was moderated by comorbidity (Qb = 6.39, df = 1, p=0.011. A large ES for the combination exercise, low intensity exercise, and comorbidity subgroups (ES = 0.82~1.24 was found. We conclude that while exercise intervention significantly improves FMD in overweight and obese adults, the effect may depend on the different characteristics of exercise intervention and on participants’ demographics.

The Prediction of Teacher Turnover Employing Time Series Analysis.

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Costa, Crist H.

The purpose of this study was to combine knowledge of teacher demographic data with time-series forecasting methods to predict teacher turnover. Moving averages and exponential smoothing were used to forecast discrete time series. The study used data collected from the 22 largest school districts in Iowa, designated as FACT schools. Predictions…

Saltelli Global Sensitivity Analysis and Simulation Modelling to Identify Intervention Strategies to Reduce the Prevalence of Escherichia coli O157 Contaminated Beef Carcasses.

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Victoria J Brookes

Full Text Available Strains of Shiga-toxin producing Escherichia coli O157 (STEC O157 are important foodborne pathogens in humans, and outbreaks of illness have been associated with consumption of undercooked beef. Here, we determine the most effective intervention strategies to reduce the prevalence of STEC O157 contaminated beef carcasses using a modelling approach.A computational model simulated events and processes in the beef harvest chain. Information from empirical studies was used to parameterise the model. Variance-based global sensitivity analysis (GSA using the Saltelli method identified variables with the greatest influence on the prevalence of STEC O157 contaminated carcasses. Following a baseline scenario (no interventions, a series of simulations systematically introduced and tested interventions based on influential variables identified by repeated Saltelli GSA, to determine the most effective intervention strategy.Transfer of STEC O157 from hide or gastro-intestinal tract to carcass (improved abattoir hygiene had the greatest influence on the prevalence of contaminated carcases. Due to interactions between inputs (identified by Saltelli GSA, combinations of interventions based on improved abattoir hygiene achieved a greater reduction in maximum prevalence than would be expected from an additive effect of single interventions. The most effective combination was improved abattoir hygiene with vaccination, which achieved a greater than ten-fold decrease in maximum prevalence compared to the baseline scenario.Study results suggest that effective interventions to reduce the prevalence of STEC O157 contaminated carcasses should initially be based on improved abattoir hygiene. However, the effect of improved abattoir hygiene on the distribution of STEC O157 concentration on carcasses is an important information gap-further empirical research is required to determine whether reduced prevalence of contaminated carcasses is likely to result in reduced

Cost-Effectiveness Analysis of Breast Cancer Control Interventions in Peru

Science.gov (United States)

Zelle, Sten G.; Vidaurre, Tatiana; Abugattas, Julio E.; Manrique, Javier E.; Sarria, Gustavo; Jeronimo, José; Seinfeld, Janice N.; Lauer, Jeremy A.; Sepulveda, Cecilia R.; Venegas, Diego; Baltussen, Rob

2013-01-01

Objectives In Peru, a country with constrained health resources, breast cancer control is characterized by late stage treatment and poor survival. To support breast cancer control in Peru, this study aims to determine the cost-effectiveness of different breast cancer control interventions relevant for the Peruvian context. Methods We performed a cost-effectiveness analysis (CEA) according to WHO-CHOICE guidelines, from a healthcare perspective. Different screening, early detection, palliative, and treatment interventions were evaluated using mathematical modeling. Effectiveness estimates were based on observational studies, modeling, and on information from Instituto Nacional de Enfermedades Neoplásicas (INEN). Resource utilizations and unit costs were based on estimates from INEN and observational studies. Cost-effectiveness estimates are in 2012 United States dollars (US$) per disability adjusted life year (DALY) averted. Results The current breast cancer program in Peru ($8,426 per DALY averted) could be improved through implementing triennial or biennial screening strategies. These strategies seem the most cost-effective in Peru, particularly when mobile mammography is applied (from $4,125 per DALY averted), or when both CBE screening and mammography screening are combined (from $4,239 per DALY averted). Triennially, these interventions costs between $63 million and $72 million per year. Late stage treatment, trastuzumab therapy and annual screening strategies are the least cost-effective. Conclusions Our analysis suggests that breast cancer control in Peru should be oriented towards early detection through combining fixed and mobile mammography screening (age 45-69) triennially. However, a phased introduction of triennial CBE screening (age 40-69) with upfront FNA in non-urban settings, and both CBE (age 40-49) and fixed mammography screening (age 50-69) in urban settings, seems a more feasible option and is also cost-effective. The implementation of this

Online Interventions for Social Marketing Health Behavior Change Campaigns: A Meta-Analysis of Psychological Architectures and Adherence Factors

Science.gov (United States)

Thelwall, Mike; Dawes, Phil

2011-01-01

Background Researchers and practitioners have developed numerous online interventions that encourage people to reduce their drinking, increase their exercise, and better manage their weight. Motivations to develop eHealth interventions may be driven by the Internet’s reach, interactivity, cost-effectiveness, and studies that show online interventions work. However, when designing online interventions suitable for public campaigns, there are few evidence-based guidelines, taxonomies are difficult to apply, many studies lack impact data, and prior meta-analyses are not applicable to large-scale public campaigns targeting voluntary behavioral change. Objectives This meta-analysis assessed online intervention design features in order to inform the development of online campaigns, such as those employed by social marketers, that seek to encourage voluntary health behavior change. A further objective was to increase understanding of the relationships between intervention adherence, study adherence, and behavioral outcomes. Methods Drawing on systematic review methods, a combination of 84 query terms were used in 5 bibliographic databases with additional gray literature searches. This resulted in 1271 abstracts and papers; 31 met the inclusion criteria. In total, 29 papers describing 30 interventions were included in the primary meta-analysis, with the 2 additional studies qualifying for the adherence analysis. Using a random effects model, the first analysis estimated the overall effect size, including groupings by control conditions and time factors. The second analysis assessed the impacts of psychological design features that were coded with taxonomies from evidence-based behavioral medicine, persuasive technology, and other behavioral influence fields. These separate systems were integrated into a coding framework model called the communication-based influence components model. Finally, the third analysis assessed the relationships between intervention adherence

Web-Based Interventions Supporting Adolescents and Young People With Depressive Symptoms: Systematic Review and Meta-Analysis.

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Välimäki, Maritta; Anttila, Katriina; Anttila, Minna; Lahti, Mari

2017-12-08

Although previous studies on information and communication technology (ICT)-based intervention on mental health among adolescents with depressive symptoms have already been combined in a number of systematic reviews, coherent information is still missing about interventions used, participants' engagement of these interventions, and how these interventions work. We conducted a systematic review and meta-analysis of trials to describe the effectiveness of Web-based interventions to support adolescents with depression or depressive symptoms, anxiety, and stress. We also explored the content of the interventions, as there has previously been a lack of coherent understanding of the detailed content of the Web-based interventions for these purposes. We included parallel randomized controlled trials targeted at adolescents, or young people in the age range of 10 and 24 years, with symptoms or diagnoses of depression and anxiety. The interventions were from original studies aimed to support mental health among adolescents, and they were delivered via Web-based information and communication technology. Out of 2087 records identified, 27 papers (22 studies) met the inclusion criteria. On the basis of a narrative analysis of 22 studies, a variety of Web-based interventions were found; the most commonly used intervention was based on cognitive behavioral therapy. Meta-analysis was further conducted with 15 studies (4979 participants). At the end of the intervention, a statistically significant improvement was found in the intervention group (10 studies) regarding depressive symptoms (P=.02, median 1.68, 95% CI 3.11-0.25) and after 6 months (3 studies; P=.01, median 1.78, 95% CI 3.20-0.37). Anxiety symptoms (8 studies; Pstress scores. However, adolescents in the intervention group left the study early more often, both in short-term studies (11 studies; P=.007, median 1.31, 95% CI 1.08-1.58) and mid-term studies (3 studies; P=.02, median 1.65, 95% CI 1.09-2.49). We did not find

Economic analysis of an internet-based depression prevention intervention.

Science.gov (United States)

Ruby, Alexander; Marko-Holguin, Monika; Fogel, Joshua; Van Voorhees, Benjamin W

2013-09-01

-based interventions like CATCH-IT appears economically viable in the context of an Accountable Care Organization. Furthermore, while the cost of implementing an effective safety protocol is proportionally high for this intervention, CATCH-IT is still significantly cheaper to implement than current treatment options. Limitations of this research included diminished participation in follow-up surveys assessing willingness-to-pay. IMPLICATIONS FOR HEALTH CARE PROVISION AND USE AND HEALTH POLICIES: This research emphasizes that preventive interventions have the potential to be cheaper to implement than treatment protocols, even before taking into account lost productivity due to illness. Research such as this business application analysis of the CATCH-IT program highlights the importance of supporting preventive medical interventions as the healthcare system already does for treatment interventions. This research is the first to analyze the economic costs of an Internet-based intervention. Further research into the costs and outcomes of such interventions is certainly warranted before they are widely adopted. Furthermore, more research regarding the safety of Internet-based programs will likely need to be conducted before they are broadly accepted.