Research papers

Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations

Daniel N. Moriasi, J. G. Arnold, M. W. Van Liew, Ronald L. Bingner, R. Daren Harmel, Tamie L. Veith

Watershed models are powerful tools for simulating the effect of watershed processes and management on soil and water resources. However, no comprehensive guidance is available to facilitate model evaluation in terms of the accuracy of simulated data compared to measured flow and constituent values. Thus, the objectives of this research were to: (1) determine recommended model evaluation techniques (statistical and graphical), (2) review reported ranges of values and corresponding performance ratings for the recommended statistics, and (3) establish guidelines for model evaluation based on the review results and project-specific considerations; all of these objectives focus on simulation of streamflow and transport of sediment and nutrients. These objectives were achieved with a thorough review of relevant literature on model application and recommended model evaluation methods. Based on this analysis, we recommend that three quantitative statistics, Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), and ratio of the root mean square error to the standard deviation of measured data (RSR), in addition to the graphical techniques, be used in model evaluation. The following model evaluation performance ratings were established for each recommended statistic. In general, model simulation can be judged as satisfactory if NSE > 0.50 and RSR < 0.70, and if PBIAS + 25% for streamflow, PBIAS + 55% for sediment, and PBIAS + 70% for N and P. For PBIAS, constituent-specific performance ratings were determined based on uncertainty of measured data. Additional considerations related to model evaluation guidelines are also discussed. These considerations include: single-event simulation, quality and quantity of measured data, model calibration procedure, evaluation time step, and project scope and magnitude. A case study illustrating the application of the model evaluation guidelines is also provided.

Particle Accelerator Physics

Helmut Wiedemann

Stochastic Processes in Physics and Chemistry

N. G. van Kampen

Data Analysis Using Regression and Multilevel/Hierarchical Models

Andrew Gelman, Jennifer Hill

Data Analysis Using Regression and Multilevel/Hierarchical Models, first published in 2007, is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout.

The Biology of NKT Cells

Albert Bendelac, Paul B. Savage, Luc Teyton

Recognized more than a decade ago, NKT cells differentiate from mainstream thymic precursors through instructive signals emanating during TCR engagement by CD1d-expressing cortical thymocytes. Their semi-invariant alphabeta TCRs recognize isoglobotrihexosylceramide, a mammalian glycosphingolipid, as well as microbial alpha-glycuronylceramides found in the cell wall of Gram-negative, lipopolysaccharide-negative bacteria. This dual recognition of self and microbial ligands underlies innate-like antimicrobial functions mediated by CD40L induction and massive Th1 and Th2 cytokine and chemokine release. Through reciprocal activation of NKT cells and dendritic cells, synthetic NKT ligands constitute promising new vaccine adjuvants. NKT cells also regulate a range of immunopathological conditions, but the mechanisms and the ligands involved remain unknown. NKT cell biology has emerged as a new field of research at the frontier between innate and adaptive immunity, providing a powerful model to study fundamental aspects of the cell and structural biology of glycolipid trafficking, processing, and recognition.

Development of remedial method for teaching electric circuits in secondary schools

Jophus Anamuah‐Mensah, J. O. E. Otuka, Farouq Sessah Mensah

Many senior secondary students experience learning difficulties in physics. This study was to reveal the kind of thinking and understanding about electric circuits of 123 senior secondary Year Two physics students in Cape Coast municipality in the Central Region of Ghana. Also it attempted to develop a remedial teaching method that would be used to remedy any identified misconceptions. An electric circuit Remedial Teaching Method was therefore developed, and its impact was assessed using a nonrandomized control pretest/post-test design. The percentages of students who had various misconceptions before and after the treatment were calculated. The findings indicated that the remedial teaching method helped to remedy most of the misconceptions they held. However, a few of the misconceptions were found to be of firm rooting and resisted changes by this teaching method. African Journal of Educational Studies in Mathematics and Sciences Vol. 1, 2001: 31-44

Decision Curve Analysis: A Novel Method for Evaluating Prediction Models

Andrew J. Vickers, Elena B. Elkin

BACKGROUND: Diagnostic and prognostic models are typically evaluated with measures of accuracy that do not address clinical consequences. Decision-analytic techniques allow assessment of clinical outcomes but often require collection of additional information and may be cumbersome to apply to models that yield a continuous result. The authors sought a method for evaluating and comparing prediction models that incorporates clinical consequences,requires only the data set on which the models are tested,and can be applied to models that have either continuous or dichotomous results. METHOD: The authors describe decision curve analysis, a simple, novel method of evaluating predictive models. They start by assuming that the threshold probability of a disease or event at which a patient would opt for treatment is informative of how the patient weighs the relative harms of a false-positive and a false-negative prediction. This theoretical relationship is then used to derive the net benefit of the model across different threshold probabilities. Plotting net benefit against threshold probability yields the "decision curve." The authors apply the method to models for the prediction of seminal vesicle invasion in prostate cancer patients. Decision curve analysis identified the range of threshold probabilities in which a model was of value, the magnitude of benefit, and which of several models was optimal. CONCLUSION: Decision curve analysis is a suitable method for evaluating alternative diagnostic and prognostic strategies that has advantages over other commonly used measures and techniques.

Encyclopedia of Analytical Chemistry

Grochocki, W, Markuszewski, MJ, Quirino, JP

Correlation between light, mostly fluorescence, and electron microscopy (EM) is needed to identify biological molecules within their ultrastructural context and/or to relate the ultrastructure to preceding dynamics of biological molecules. Recent development of labels, sample preparation techniques, and microscopy tools allow researchers to bridge the gap between these two modalities, while dedicated, integrated microscopes merge the two techniques into one. This not only allows broader possibilities for implementation of CLEM (correlative light and electron microscopy) in analytical sciences but also enables novel applications crossing boundaries between the traditional microscopes. We provide an overview of the different CLEM approaches, including common labels and sample preparation techniques, and focus attention specifically on the advanced instrumentation and the novel opportunities and challenges these bring for the chemical and biological sciences.

Comparative Protein Structure Modeling Using Modeller

Narayanan Eswar, Ben Webb, Marc A. Martı́-Renom, M. S. Madhusudhan, David Eramian, Min‐Yi Shen, Ursula Pieper, Andrej Šali

Functional characterization of a protein sequence is one of the most frequent problems in biology. This task is usually facilitated by accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described.

Quality criteria were proposed for measurement properties of health status questionnaires

Caroline B. Terwee, Sandra D.M. Bot, Michiel R. de Boer, Daniëlle van der Windt, Dirk L. Knol, Joost Dekker, L.M. Bouter, He…

Multilevel Statistical Models

Harvey Goldstein

Comprehensive account of multilevel modelling theory and practice

Reporting Structural Equation Modeling and Confirmatory Factor Analysis Results: A Review

James B. Schreiber, Amaury Nora, Frances K. Stage, Elizabeth A. Barlow, Jamie M. King

The authors provide a basic set of guidelines and recommendations for information that should be included in any manuscript that has confirmatory factor analysis or structural equation modeling as the primary statistical analysis technique. The authors provide an introduction to both techniques, along with sample analyses, recommendations for reporting, evaluation of articles in The Journal of Educational Research using these techniques, and concluding remarks.

Fusion or Failure? The Future of Conservation Biology

Andrew Balmford, Richard M. Cowling

Hydrogels in Biology and Medicine: From Molecular Principles to Bionanotechnology

Nikolaos A. Peppas, J. Zach Hilt, Ali Khademhosseini, Róbert Langer

Abstract Hydrophilic polymers are the center of research emphasis in nanotechnology because of their perceived “intelligence”. They can be used as thin films, scaffolds, or nanoparticles in a wide range of biomedical and biological applications. Here we highlight recent developments in engineering uncrosslinked and crosslinked hydrophilic polymers for these applications. Natural, biohybrid, and synthetic hydrophilic polymers and hydrogels are analyzed and their thermodynamic responses are discussed. In addition, examples of the use of hydrogels for various therapeutic applications are given. We show how such systems' intelligent behavior can be used in sensors, microarrays, and imaging. Finally, we outline challenges for the future in integrating hydrogels into biomedical applications.

A Brief Measure for Assessing Generalized Anxiety Disorder

Robert L. Spitzer, Kurt Kroenke, Janet B. W. Williams, Bernd Löwe

BACKGROUND: Generalized anxiety disorder (GAD) is one of the most common mental disorders; however, there is no brief clinical measure for assessing GAD. The objective of this study was to develop a brief self-report scale to identify probable cases of GAD and evaluate its reliability and validity. METHODS: A criterion-standard study was performed in 15 primary care clinics in the United States from November 2004 through June 2005. Of a total of 2740 adult patients completing a study questionnaire, 965 patients had a telephone interview with a mental health professional within 1 week. For criterion and construct validity, GAD self-report scale diagnoses were compared with independent diagnoses made by mental health professionals; functional status measures; disability days; and health care use. RESULTS: A 7-item anxiety scale (GAD-7) had good reliability, as well as criterion, construct, factorial, and procedural validity. A cut point was identified that optimized sensitivity (89%) and specificity (82%). Increasing scores on the scale were strongly associated with multiple domains of functional impairment (all 6 Medical Outcomes Study Short-Form General Health Survey scales and disability days). Although GAD and depression symptoms frequently co-occurred, factor analysis confirmed them as distinct dimensions. Moreover, GAD and depression symptoms had differing but independent effects on functional impairment and disability. There was good agreement between self-report and interviewer-administered versions of the scale. CONCLUSION: The GAD-7 is a valid and efficient tool for screening for GAD and assessing its severity in clinical practice and research.

PYTHIA 6.4 physics and manual

Torbjörn Sjöstrand, S. Mrenna, Peter Skands

The Four-Phase Model of Interest Development

Suzanne Hidi, K. Ann Renninger

Building on and extending existing research, this article proposes a 4-phase model of interest development. The model describes 4 phases in the development and deepening of learner interest: triggered situational interest, maintained situational interest, emerging (less-developed) individual interest, and well-developed individual interest. Affective as well as cognitive factors are considered. Educational implications of the proposed model are identified.

Physics of Semiconductor Devices

Simon M. Sze, Kwok K. Ng

Health benefits of physical activity: the evidence

Darren E. R. Warburton

The primary purpose of this narrative review was to evaluate the current literature and to provide further insight into the role physical inactivity plays in the development of chronic disease and premature death. We confirm that there is irrefutable evidence of the effectiveness of regular physical activity in the primary and secondary prevention of several chronic diseases (e.g., cardiovascular disease, diabetes, cancer, hypertension, obesity, depression and osteoporosis) and premature death. We also reveal that the current Health Canada physical activity guidelines are sufficient to elicit health benefits, especially in previously sedentary people. There appears to be a linear relation between physical activity and health status, such that a further increase in physical activity and fitness will lead to additional improvements in health status.

Doping a Mott insulator: Physics of high-temperature superconductivity

Patrick A. Lee, Naoto Nagaosa, Xiao-Gang Wen

This article reviews the physics of high-temperature superconductors from the point of view of the doping of a Mott insulator. The basic electronic structure of cuprates is reviewed, emphasizing the physics of strong correlation and establishing the model of a doped Mott insulator as a starting point. A variety of experiments are discussed, focusing on the region of the phase diagram close to the Mott insulator (the underdoped region) where the behavior is most anomalous. The normal state in this region exhibits pseudogap phenomenon. In contrast, the quasiparticles in the superconducting state are well defined and behave according to theory. This review introduces Anderson's idea of the resonating valence bond and argues that it gives a qualitative account of the data. The importance of phase fluctuations is discussed, leading to a theory of the transition temperature, which is driven by phase fluctuations and the thermal excitation of quasiparticles. However, an argument is made that phase fluctuations can only explain pseudogap phenomenology over a limited temperature range, and some additional physics is needed to explain the onset of singlet formation at very high temperatures. A description of the numerical method of the projected wave function is presented, which turns out to be a very useful technique for implementing the strong correlation constraint and leads to a number of predictions which are in agreement with experiments. The remainder of the paper deals with an analytic treatment of the $t\text{\ensuremath{-}}J$ model, with the goal of putting the resonating valence bond idea on a more formal footing. The slave boson is introduced to enforce the constraint againt double occupation and it is shown that the implementation of this local constraint leads naturally to gauge theories. This review follows the historical order by first examining the U(1) formulation of the gauge theory. Some inadequacies of this formulation for underdoping are discussed, leading to the SU(2) formulation. Here follows a rather thorough discussion of the role of gauge theory in describing the spin-liquid phase of the undoped Mott insulator. The difference between the high-energy gauge group in the formulation of the problem versus the low-energy gauge group, which is an emergent phenomenon, is emphasized. Several possible routes to deconfinement based on different emergent gauge groups are discussed, which leads to the physics of fractionalization and spin-charge separation. Next the extension of the SU(2) formulation to nonzero doping is described with a focus on a part of the mean-field phase diagram called the staggered flux liquid phase. It will be shown that inclusion of the gauge fluctuation provides a reasonable description of the pseudogap phase. It is emphasized that $d$-wave superconductivity can be considered as evolving from a stable U(1) spin liquid. These ideas are applied to the high-${T}_{c}$ cuprates, and their implications for the vortex structure and the phase diagram are discussed. A possible test of the topological structure of the pseudogap phase is described.

Anyons in an exactly solved model and beyond

Alexei Kitaev

The Molecular Biology of Coronaviruses

Paul S. Masters

EFFECT OF COMPUTER-ASSISTED INSTRUCTION AND SIMULATION/GAMES ON THE ACADEMIC ACHIEVEMENT OF SECONDARY SCHOOL STUDENTS IN BIOLOGY

J.B. Bilesanmi-Awoderu

This study investigated the effect of Computer Assisted Instruction (CAI), Simulation/Games and Conventional Methods on the academic achievement of students in Biology. The treatment at the three levels of CAI, Simulation/Games and Conventional Method was crossed with gender at the two levels of male and female, and locus of control, at the two levels of internals and externals. Data analysis involved Analysis of Covariance as well as Multiple Classification Analysis as a post-hoc measure. The findings revealed no significant two-way and three-way interactions of treatment and gender and locus of control. However, there were significant main effects of treatment and locus of control on students’ achievement in Biology. The MCA further revealed that students taught with the Computer-Assisted Instruction achieved highest while students taught with Simulation/Games achieved better and those students taught with the Conventional Method had the lowest adjusted post-test mean score. Based on these findings, the use of Computer Instruction and Simulation/Games are recommended for teachers in Biology classrooms irrespective of the students’ gender and locus of control. The government is further enjoined to provide computers, programs, instructional packages, costumes and enabling environment for the use of these instructional strategies in schools.

Effects of two teaching methods on the achievement in and attitude to biology of students of different levels of scientific literacy

Chinwe Nwagbo