scholarly journals Geostatistically based optimization of a rainfall monitoring network extension: case of the climatically heterogeneous Tunisia

2016 ◽  
Vol 48 (2) ◽  
pp. 514-541 ◽  
Author(s):  
Haifa Feki ◽  
Mohamed Slimani ◽  
Christophe Cudennec
Keyword(s):  
Network Performance ◽  
Variance Reduction ◽  
Monitoring Network ◽  
Decisive Role ◽  
Simulation Models ◽  
Study Data ◽  
Data Set ◽  
Kriging Variance ◽  
Regionalized Variables ◽  
Essential Input

Rainfall data are an essential input for many simulation models. In fact, these latter have a decisive role in the development and application of rational water policies. Since the accuracy of the simulation depends strongly on the available data, the task of optimizing the monitoring network is of great importance. In this paper, an application is presented aiming at the evaluation of a precipitation monitoring network by predicting monthly, seasonal, and interannual average rainfall. The method given here is based on the theory of the regionalized variables using the well-known geostatistical variance reduction method. The procedure, which involves different analysis methods of the available data, such as estimation of the interpolation uncertainty and data cross validation, is applied to a case study data set in Tunisia in order to demonstrate the potential for improvement of the observation network quality. Root mean square error values are the criteria for evaluating rainfall estimation, and network performance is discussed based on kriging variance reduction. Based on this study, it was concluded that some sites should be dropped to eliminate redundancy and some others need to be added to the existing network, essentially in the center and the south, to have a more informative network.

Childhood Intelligence Predicts Adult Trait Openness

2016 ◽  
Vol 37 (2) ◽  
pp. 105-111 ◽  
Author(s):  
Adrian Furnham ◽  
Helen Cheng
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Social Background ◽  
Study Data ◽  
Equation Modeling ◽  
Direct Effects ◽  
Data Set ◽  
National Child Development Study ◽  
Nationally Representative ◽  
The Uk

Abstract. This study used a longitudinal data set of 5,672 adults followed for 50 years to determine the factors that influence adult trait Openness-to-Experience. In a large, nationally representative sample in the UK (the National Child Development Study), data were collected at birth, in childhood (age 11), adolescence (age 16), and adulthood (ages 33, 42, and 50) to examine the effects of family social background, childhood intelligence, school motivation during adolescence, education, and occupation on the personality trait Openness assessed at age 50 years. Structural equation modeling showed that parental social status, childhood intelligence, school motivation, education, and occupation all had modest, but direct, effects on trait Openness, among which childhood intelligence was the strongest predictor. Gender was not significantly associated with trait Openness. Limitations and implications of the study are discussed.

Parent and Grandparent Relationships in Emerging Adulthood

2018 ◽  
Author(s):  
Michael W. Pratt ◽  
M. Kyle Matsuba
Keyword(s):  
Emerging Adulthood ◽  
Attachment Theory ◽  
Emerging Adults ◽  
Family Relationships ◽  
Longitudinal Research ◽  
Study Data ◽  
Family Development ◽  
Data Set ◽  
Theory Framework

Chapter 7 begins with an overview of Erikson’s ideas about intimacy and its place in the life cycle, followed by a summary of Bowlby and Ainsworth’s attachment theory framework and its relation to family development. The authors review existing longitudinal research on the development of family relationships in adolescence and emerging adulthood, focusing on evidence with regard to links to McAdams and Pals’ personality model. They discuss the evidence, both questionnaire and narrative, from the Futures Study data set on family relationships, including emerging adults’ relations with parents and, separately, with grandparents, as well as their anticipations of their own parenthood. As a way of illustrating the key personality concepts from this family chapter, the authors end with a case study of Jane Fonda in youth and her father, Henry Fonda, to illustrate these issues through the lives of a 20th-century Hollywood dynasty of actors.

scholarly journals Characterisation of MS phenotypes across the age span using a novel data set integrating 34 clinical trials (NO.MS cohort): Age is a key contributor to presentation

2021 ◽  
pp. 135245852098863
Author(s):  
Frank Dahlke ◽  
Douglas L Arnold ◽  
Piet Aarden ◽  
Habib Ganjgahi ◽  
Dieter A Häring ◽  
...  
Keyword(s):  
Disease Activity ◽  
Brain Volume ◽  
Young Patients ◽  
Clinical Trial Data ◽  
Study Data ◽  
Phase Iii ◽  
Brain Images ◽  
Data Set ◽  
Brain Volume Loss ◽  
Phase Iii Study

Background: The Oxford Big Data Institute, multiple sclerosis (MS) physicians and Novartis aim to address unresolved questions in MS with a novel comprehensive clinical trial data set. Objective: The objective of this study is to describe the Novartis–Oxford MS (NO.MS) data set and to explore the relationships between age, disease activity and disease worsening across MS phenotypes. Methods: We report key characteristics of NO.MS. We modelled MS lesion formation, relapse frequency, brain volume change and disability worsening cross-sectionally, as a function of patients’ baseline age, using phase III study data (≈8000 patients). Results: NO.MS contains data of ≈35,000 patients (>200,000 brain images from ≈10,000 patients), with >10 years follow-up. (1) Focal disease activity is highest in paediatric patients and decreases with age, (2) brain volume loss is similar across age and phenotypes and (3) the youngest patients have the lowest likelihood (<25%) of disability worsening over 2 years while risk is higher (25%–75%) in older, disabled or progressive MS patients. Young patients benefit most from treatment. Conclusion: NO.MS will illuminate questions related to MS characterisation, progression and prognosis. Age modulates relapse frequency and, thus, the phenotypic presentation of MS. Disease worsening across all phenotypes is mediated by age and appears to some extent be independent from new focal inflammatory activity.

Association of Demographic and Disability Characteristics With Total PROMISE Expenditure: Wisconsin PROMISE Findings—Brief Report

2021 ◽  
pp. 003435522098079
Author(s):  
Emre Umucu ◽  
Beatrice Lee ◽  
Veronica Estala-Gutierrez ◽  
Timothy Tansey
Keyword(s):  
Health Care ◽  
Cost Effectiveness ◽  
Treatment Group ◽  
Exploratory Study ◽  
Health Care Expenditure ◽  
Study Data ◽  
Data Set ◽  
Youth With Disabilities ◽  
Total Health Care Expenditure

The purpose of this exploratory study was to examine whether demographic and disability variables predict total health care expenditure of Wisconsin PROMISE. The findings are intended to assist in promoting cost-effectiveness for future similar initiates. This study data were extracted from Wisconsin PROMISE data set. This study had a total of 1,443 youth with disabilities ( Mage = 14.89). The majority of participants were male (69%). Our results indicated that some demographic and disability–related characteristics are associated with total health care expenditure in control with VR case during PROMISE, control without VR case during PROMISE, and treatment group. Overall, findings of the current study suggest demographic and disability variables do assist in predicting total health care expenditure of Wisconsin PROMISE.

scholarly journals A Physical Activity Reference Data-Set Recorded from Older Adults Using Body-Worn Inertial Sensors and Video Technology—The ADAPT Study Data-Set

Sensors ◽  
2017 ◽  
Vol 17 (3) ◽  
pp. 559 ◽  
Author(s):  
Alan Bourke ◽  
Espen Ihlen ◽  
Ronny Bergquist ◽  
Per Wik ◽  
Beatrix Vereijken ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Reference Data ◽  
Inertial Sensors ◽  
Study Data ◽  
Video Technology ◽  
Data Set

scholarly journals The Murrumbidgee soil moisture monitoring network data set

2012 ◽  
Vol 48 (7) ◽  
Author(s):  
A. B. Smith ◽  
J. P. Walker ◽  
A. W. Western ◽  
R. I. Young ◽  
K. M. Ellett ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Monitoring Network ◽  
Network Data ◽  
Data Set ◽  
Soil Moisture Monitoring

scholarly journals Building prediction models for coronary heart disease by synthesizing multiple longitudinal research findings

2005 ◽  
Vol 12 (5) ◽  
pp. 459-464 ◽  
Author(s):  
Guizhou Hu ◽  
Martin M. Root
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Prediction Model ◽  
Empirical Model ◽  
Complex Disease ◽  
Prediction Models ◽  
Longitudinal Research ◽  
Study Data ◽  
Individual Risk ◽  
Data Set

Background No methodology is currently available to allow the combining of individual risk factor information derived from different longitudinal studies for a chronic disease in a multivariate fashion. This paper introduces such a methodology, named Synthesis Analysis, which is essentially a multivariate meta-analytic technique. Design The construction and validation of statistical models using available data sets. Methods and results Two analyses are presented. (1) With the same data, Synthesis Analysis produced a similar prediction model to the conventional regression approach when using the same risk variables. Synthesis Analysis produced better prediction models when additional risk variables were added. (2) A four-variable empirical logistic model for death from coronary heart disease was developed with data from the Framingham Heart Study. A synthesized prediction model with five new variables added to this empirical model was developed using Synthesis Analysis and literature information. This model was then compared with the four-variable empirical model using the first National Health and Nutrition Examination Survey (NHANES I) Epidemiologic Follow-up Study data set. The synthesized model had significantly improved predictive power ( x2 = 43.8, P < 0.00001). Conclusions Synthesis Analysis provides a new means of developing complex disease predictive models from the medical literature.

Do intraday week effect in currencies hourly trading reflect leverage and asymmetric anomalies? Policy implications for traders

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wajid Shakeel Ahmed ◽  
Muhammad Sohaib ◽  
Jamal Maqsood ◽  
Ateeb Siddiqui
Keyword(s):  
Emerging Economies ◽  
Garch Model ◽  
Study Data ◽  
Policy Implications ◽  
Asymmetric Effect ◽  
Data Set ◽  
Content Type ◽  
Study Results ◽  
Rational Choices ◽  
Trading Pattern

Purpose The purpose of this study is to determine if intraday week (IDW) effect of the currencies reflect leverage and asymmetric impact in currencies market. The study data set comprises of intraday patterns of 15 currencies from developed and emerging economies. Design methodology approach The study applies the exponential generalized autoregressive conditional heteroscedasticity (E-GARCH) model technique to observe the IDW leverage and asymmetric effect after introducing hourly dummies variables, namely, IDWmon, IDWwed, IDWfrid and IDWfrid-mon. Findings The study results favor the propositions and confirm that IDW effect do exist in the international forex markets in relation to hourly trading pattern for respective currencies. Mostly, currencies do depreciate on Monday and Wednesday compared to the rest of the days. However, on the last trading day, i.e. Friday currencies observe an appreciation pattern which is for both economies. The results have an evidence of leverage and asymmetric effect confirmed by the E-GARCH model as a result of press releases and influence by micro-factors in the currency markets. Practical implications The study believes to have theoretical connection related to the better understanding of currencies trend for developed and emerging economies, as the IDW effect exists. Moreover, confirmation of both the leverage and asymmetric effect in observed currencies would be able to assist the investors in making rational choices during the trading hours and would confirm considerable profits through profit incentivized strategies. Originality value The study not only add knowledge to the previous study work in relation to the hourly trading pattern of currencies with reference to the IDW effects but also highlights the leverage and asymmetric effect in currencies that will help in formulating future trading strategies particular to emerging economies.

Understanding the Importance of Capturing Climate and Occupancy Trends During Concept-Stage Sustainable Building Design

2018 ◽  
Author(s):  
Sean Lin ◽  
Bahaa Albarhami ◽  
Salvador Mayoral ◽  
Joseph Piacenza
Keyword(s):  
Energy Consumption ◽  
Simulation Models ◽  
Building Design ◽  
Building Energy ◽  
Simulation Software ◽  
Phase Iii ◽  
Data Set ◽  
Climate Zones ◽  
Leed Certification ◽  
Actual Energy Consumption

This paper presents a comparison of concept stage computational model predictions to capture how building energy consumption is affected by different climate zones. The California State University, Fullerton (CSUF) Student Housing Phase III, which received a Platinum Leadership in Energy and Environmental Design (LEED) certification for the Building Design and Construction category, and its performance in a LEED California Nonresidential Title 24 (NRT24) and ASHRAE 90.1 climate zones is used as a case study to illustrate the method. Through LEED approved simulation software, the standard compliant energy simulation models are compared to the occupancy scheduled models along with the actual energy consumption in different climate zones. The results provide insight to how variables within student dormitory life affect total building energy usage. Total amount of energy consumed per area is one new factor providing understanding into occupancy trends. This new data set reveals more understanding regarding how and where the energy is consumed to maintain a comfortable learning environment.

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