Research papers

Chemical Reaction Engineering

Octave Levenspiel

ADVERTISEMENT RETURN TO ISSUEPREVCommentaryNEXTChemical Reaction EngineeringOctave LevenspielView Author Information Chemical Engineering Department Oregon State University Corvallis, Oregon 97331Cite this: Ind. Eng. Chem. Res. 1999, 38, 11, 4140–4143Publication Date (Web):September 11, 1999Publication History Published online11 September 1999Published inissue 1 November 1999https://pubs.acs.org/doi/10.1021/ie990488ghttps://doi.org/10.1021/ie990488gbrief-reportACS PublicationsCopyright © 1999 American Chemical SocietyRequest reuse permissionsArticle Views23019Altmetric-Citations1239LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Kinetic modeling,Kinetics,Order,Reaction engineering,Surface reactions Get e-Alerts

Evaluating the public health impact of health promotion interventions: the RE-AIM framework.

Russell E. Glasgow, Thomas Vogt, Shawn M. Boles

Progress in public health and community-based interventions has been hampered by the lack of a comprehensive evaluation framework appropriate to such programs. Multilevel interventions that incorporate policy, environmental, and individual components should be evaluated with measurements suited to their settings, goals, and purpose. In this commentary, the authors propose a model (termed the RE-AIM model) for evaluating public health interventions that assesses 5 dimensions: reach, efficacy, adoption, implementation, and maintenance. These dimensions occur at multiple levels (e.g., individual, clinic or organization, community) and interact to determine the public health or population-based impact of a program or policy. The authors discuss issues in evaluating each of these dimensions and combining them to determine overall public health impact. Failure to adequately evaluate programs on all 5 dimensions can lead to a waste of resources, discontinuities between stages of research, and failure to improve public health to the limits of our capacity. The authors summarize strengths and limitations of the RE-AIM model and recommend areas for future research and application.

Cation-π interactions in structural biology

Justin P. Gallivan, Dennis A. Dougherty

Cation-pi interactions in protein structures are identified and evaluated by using an energy-based criterion for selecting significant sidechain pairs. Cation-pi interactions are found to be common among structures in the Protein Data Bank, and it is clearly demonstrated that, when a cationic sidechain (Lys or Arg) is near an aromatic sidechain (Phe, Tyr, or Trp), the geometry is biased toward one that would experience a favorable cation-pi interaction. The sidechain of Arg is more likely than that of Lys to be in a cation-pi interaction. Among the aromatics, a strong bias toward Trp is clear, such that over one-fourth of all tryptophans in the data bank experience an energetically significant cation-pi interaction.

The Biology of Hair Follicles

Ralf Paus, George Cotsarelis

Hair has many useful biologic functions, including protection from the elements and dispersion of sweat-gland products (e.g., pheromones). It also has psychosocial importance in our society, and patients with hair loss (alopecia) (Table 1) or excessive hair growth often suffer tremendously. Not surprisingly, the demand for drugs that alter hair growth and appearance has led to a multibillion-dollar industry, yet few drugs that are effective for these purposes are available. However, recent progress in our understanding of the biology and pathology of hair follicles should lead to more effective therapies for disorders of hair growth.Structure and Function of Hair . . .

Lecture Notes in Computer Science 1205

In this study, the application of the single input single output (SISO) neural generalized predictive control (NGPC) and SISO generalized predictive control (GPC) of a three joint robotic manipulator are presented. The sinusoidal and cubic trajectory principles were used for position reference and velocity reference trajectories. NGPC-SISO algorithm performs better than GPC-SISO algorithm for both trajectories. The GPC-SISO robotic manipulator control results have better values in the case of the sinusoidal trajectory, but the NGPC-SISO robotic manipulator control results for both the cubic and sinusoidal trajectory are almost similar.

A Proportional Hazards Model for the Subdistribution of a Competing Risk

Jason P. Fine, Malcolm H. Ray

With explanatory covariates, the standard analysis for competing risks data involves modeling the cause-specific hazard functions via a proportional hazards assumption. Unfortunately, the cause-specific hazard function does not have a direct interpretation in terms of survival probabilities for the particular failure type. In recent years many clinicians have begun using the cumulative incidence function, the marginal failure probabilities for a particular cause, which is intuitively appealing and more easily explained to the nonstatistician. The cumulative incidence is especially relevant in cost-effectiveness analyses in which the survival probabilities are needed to determine treatment utility. Previously, authors have considered methods for combining estimates of the cause-specific hazard functions under the proportional hazards formulation. However, these methods do not allow the analyst to directly assess the effect of a covariate on the marginal probability function. In this article we propose a novel semiparametric proportional hazards model for the subdistribution. Using the partial likelihood principle and weighting techniques, we derive estimation and inference procedures for the finite-dimensional regression parameter under a variety of censoring scenarios. We give a uniformly consistent estimator for the predicted cumulative incidence for an individual with certain covariates; confidence intervals and bands can be obtained analytically or with an easy-to-implement simulation technique. To contrast the two approaches, we analyze a dataset from a breast cancer clinical trial under both models.

Explaining African Economic Performance

Paul Collier, Jan Willem Gunning

Africa has had slow growth and a massive exodus of capital. In many respects it has been the most capital-hostile region. We review and interpret the aggregate-level and microeconomic literatures to identify the key explanations for this performance. There is a reasonable correspondence of the two sets of evidence, pointing to four factors as being important. These are a lack of openness to international trade; a high-risk environment; a low level of social capital; and poor infrastructure. These problems are to a substantial extent attributable to government behavior, and the paper includes a review of the political economy literature addressing that behavior.

Chemistry and Physics in One Dimension:  Synthesis and Properties of Nanowires and Nanotubes

Jiangtao Hu, Teri W. Odom, Charles M. Lieber

Dimensionality plays a critical role in determining the properties of materials due to, for example, the different ways that electrons interact in three-dimensional, two-dimensional (2D), and one-dimensional (1D) structures.1-5

Monte Carlo Methods in Statistical Physics

M. E. J. Newman, G. T. Barkema

Abstract This book provides an introduction to Monte Carlo simulations in classical statistical physics and is aimed both at students beginning work in the field and at more experienced researchers who wish to learn more about Monte Carlo methods. The material covered includes methods for both equilibrium and out of equilibrium systems, and common algorithms like the Metropolis and heat-bath algorithms are discussed in detail, as well as more sophisticated ones such as continuous time Monte Carlo, cluster algorithms, multigrid methods, entropic sampling and simulated tempering. Data analysis techniques are also explained starting with straightforward measurement and error-estimation techniques and progressing to topics such as the single and multiple histogram methods and finite size scaling. The last few chapters of the book are devoted to implementation issues, including discussions of such topics as lattice representations, efficient implementation of data structures, multispin coding, parallelization of Monte Carlo algorithms, and random number generation. At the end of the book the authors give a number of example programs demonstrating the applications of these techniques to a variety of well-known models.

Model Checking

Edmund M. Clarke, Bernd–Holger Schlingloff

Principles of Fluorescence Spectroscopy

Joseph R. Lakowicz

Communities of practice learning, meaning, and identity

Étienne Wenger

This book presents a theory of learning that starts with the assumption that engagement in social practice is the fundamental process by which we get to know what we know and by which we become who we are. The primary unit of analysis of this process is neither the individual nor social institutions, but the informal 'communities of practice' that people form as they pursue shared enterprises over time. To give a social account of learning, the theory explores in a systematic way the intersection of issues of community, social practice, meaning, and identity. The result is a broad framework for thinking about learning as a process of social participation. This ambitious but thoroughly accessible framework has relevance for the practitioner as well as the theoretician, presented with all the breadth, depth, and rigor necessary to address such a complex and yet profoundly human topic.

Self-Efficacy: The Exercise of Control

Albert Bandura, Wendy Freeman, Richard Lightsey

Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives

Li‐tze Hu, Peter M. Bentler

This article examines the adequacy of the “rules of thumb” conventional cutoff criteria and several new alternatives for various fit indexes used to evaluate model fit in practice. Using a 2‐index presentation strategy, which includes using the maximum likelihood (ML)‐based standardized root mean squared residual (SRMR) and supplementing it with either Tucker‐Lewis Index (TLI), Bollen's (1989) Fit Index (BL89), Relative Noncentrality Index (RNI), Comparative Fit Index (CFI), Gamma Hat, McDonald's Centrality Index (Mc), or root mean squared error of approximation (RMSEA), various combinations of cutoff values from selected ranges of cutoff criteria for the ML‐based SRMR and a given supplemental fit index were used to calculate rejection rates for various types of true‐population and misspecified models; that is, models with misspecified factor covariance(s) and models with misspecified factor loading(s). The results suggest that, for the ML method, a cutoff value close to .95 for TLI, BL89, CFI, RNI, and Gamma Hat; a cutoff value close to .90 for Mc; a cutoff value close to .08 for SRMR; and a cutoff value close to .06 for RMSEA are needed before we can conclude that there is a relatively good fit between the hypothesized model and the observed data. Furthermore, the 2‐index presentation strategy is required to reject reasonable proportions of various types of true‐population and misspecified models. Finally, using the proposed cutoff criteria, the ML‐based TLI, Mc, and RMSEA tend to overreject true‐population models at small sample size and thus are less preferable when sample size is small.

Lecture Notes in Artificial Intelligence

Patrick Brézillon, Paolo Bouquet

Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification.

Li‐tze Hu, Peter M. Bentler

This study evaluated the sensitivity of maximum likelihood (ML)-, generalized least squares (GLS)-, and asymptotic distribution-free (ADF)-based fit indices to model misspecification, under conditions that varied sample size and distribution. The effect of violating assumptions of asymptotic robustness theory also was ex-amined. Standardized root-mean-square residual (SRMR) was the most sensitive index to models with misspecified factor covariance(s), and Tucker-Lewis Index (1973; TLI), Bollen's fit index (1989; BL89), relative noncentrality index (RNI), comparative fit index (CFI), and the ML- and GLS-based gamma hat, McDonald's centrality index (1989; Me), and root-mean-square error of approximation (RMSEA) were the most sensitive indices to models with misspecified factor loadings. With ML and GLS methods, we recommend the use of SRMR, supple-mented by TLI, BL89, RNI, CFI, gamma hat, Me, or RMSEA (TLI, Me, and RMSEA are less preferable at small sample sizes). With the ADF method, we recommend the use of SRMR, supplemented by TLI, BL89, RNI, or CFI. Finally, most of the ML-based fit indices outperformed those obtained from GLS and ADF

On economic causes of civil war

Paul Collier

We investigate whether civil wars have economic causes. The model is based on utility theory, rebels will conduct a civil war if the perceived benefits outweigh the costs of rebellion. Using probit and tobit models the propositions are tested empirically. Four variables, initial income, ethno-linguistic fractionalisation, the amount of natural resources, and initial population size are significant and strong determinants of the duration and the probability of civil wars. One important finding is that the relationship between civil wars and ethnic diversity is non-monotoniq highly fractionalised societies have no greater risk of experiencing a civil war than homogenous ones.

Cyclooxygenase in biology and disease

Raymond N. DuBois, Steven B. Abramson, Leslie J. Crofford, Rajnish A. Gupta, Lee S. Simon, L. B. A. van de Putte, Peter E. L…

Cyclooxygenase (COX), the key enzyme required for the conversion of arachidonic acid to prostaglandins was first identified over 20 years ago. Drugs, like aspirin, that inhibit cyclooxygenase activity have been available to the public for about 100 years. In the past decade, however, more progress has been made in understanding the role of cyclooxygenase enzymes in biology and disease than at any other time in history. Two cyclooxygenase isoforms have been identified and are referred to as COX-1 and COX-2. Under many circumstances the COX-1 enzyme is produced constitutively (i.e., gastric mucosa) whereas COX-2 is inducible (i.e., sites of inflammation). Here, we summarize the current understanding of the role of cyclooxygenase-1 and -2 in different physiological situations and disease processes ranging from inflammation to cancer. We have attempted to include all of the most relevant material in the field, but due to the rapid progress in this area of research we apologize that certain recent findings may have been left out.

The Mathematical Theory Of Plasticity

R. Hill

Abstract First published in 1950, this important book details the mathematical theory underlying the behaviour of plastic materials, especially metals. ‘the author has done his work so well that it is difficult to see how it could be bettered. The book should rank for many years as an authoritative source of reference.‘ Engineering ‘In the reviewer’s opinion this book should be in the possession of all those who wish to undertake study and research in the theory of plasticity’ Mathematical Gazette ‘the many examples in the book relating to the shaping of metals should be of considerable value ... The book is well-written ... and a pleasure to read.’ J.F. Nye in Research

Persistent Pain and Well-being

Oye Gureje, Michael Von Korff, Gregory E. Simon, Richard Gater

CONTEXT: There is little information on the extent of persistent pain across cultures. Even though pain is a common reason for seeking health care, information on the frequency and impacts of persistent pain among primary care patients is inadequate. OBJECTIVE: To assess the prevalence and impact of persistent pain among primary care patients. DESIGN AND SETTING: Survey data were collected from representative samples of primary care patients as part of the World Health Organization Collaborative Study of Psychological Problems in General Health Care, conducted in 15 centers in Asia, Africa, Europe, and the Americas. PARTICIPANTS: Consecutive primary care attendees between the age of majority (typically 18 years) and 65 years were screened (n = 25 916) and stratified random samples interviewed (n = 5438). MAIN OUTCOME MEASURES: Persistent pain, defined as pain present most of the time for a period of 6 months or more during the prior year, and psychological illness were assessed by the Composite International Diagnostic Interview. Disability was assessed by the Groningen Social Disability Schedule and by activity-limitation days in the prior month. RESULTS: Across all 15 centers, 22% of primary care patients reported persistent pain, but there was wide variation in prevalence rates across centers (range, 5.5%-33.0%). Relative to patients without persistent pain, pain sufferers were more likely to have an anxiety or depressive disorder (adjusted odds ratio [OR], 4.14; 95% confidence interval [CI], 3.52-4.86), to experience significant activity limitations (adjusted OR, 1.63; 95% CI, 1.41 -1.89), and to have unfavorable health perceptions (adjusted OR, 1.26; 95% CI, 1.07-1.49). The relationship between psychological disorder and persistent pain was observed in every center, while the relationship between disability and persistent pain was inconsistent across centers. CONCLUSIONS: Persistent pain was a commonly reported health problem among primary care patients and was consistently associated with psychological illness across centers. Large variation in frequency and the inconsistent relationship between persistent pain and disability across centers suggests caution in drawing conclusions about the role of culture in shaping responses to persistent pain when comparisons are based on patient samples drawn from a limited number of health care settings in each culture.

Collective dynamics of ‘small-world’ networks

Duncan J. Watts, Steven H. Strogatz

Deciphering the biology of Mycobacterium tuberculosis from the complete genome sequence

Stewart T. Cole, Roland Brosch, Julian Parkhill, T. Garnier, Carol Churcher, David Harris, Stephen V. Gordon, Karin Eiglmeie…

Calibration of the Computer Science and Applications, Inc. accelerometer

Patty S. Freedson, Edward L. Melanson, John R. Sirard

PURPOSE: We established accelerometer count ranges for the Computer Science and Applications, Inc. (CSA) activity monitor corresponding to commonly employed MET categories. METHODS: Data were obtained from 50 adults (25 males, 25 females) during treadmill exercise at three different speeds (4.8, 6.4, and 9.7 km x h(-1)). RESULTS: Activity counts and steady-state oxygen consumption were highly correlated (r = 0.88), and count ranges corresponding to light, moderate, hard, and very hard intensity levels were < or = 1951, 1952-5724, 5725-9498, > or = 9499 cnts x min(-1), respectively. A model to predict energy expenditure from activity counts and body mass was developed using data from a random sample of 35 subjects (r2 = 0.82, SEE = 1.40 kcal x min(-1)). Cross validation with data from the remaining 15 subjects revealed no significant differences between actual and predicted energy expenditure at any treadmill speed (SEE = 0.50-1.40 kcal x min(-1)). CONCLUSIONS: These data provide a template on which patterns of activity can be classified into intensity levels using the CSA accelerometer.

All-Atom Empirical Potential for Molecular Modeling and Dynamics Studies of Proteins

Alexander D. MacKerell, Donald Bashford, M. Bellott, Roland L. Dunbrack, Jeffrey D. Evanseck, Martin J. Field, Stefan Fische…

New protein parameters are reported for the all-atom empirical energy function in the CHARMM program. The parameter evaluation was based on a self-consistent approach designed to achieve a balance between the internal (bonding) and interaction (nonbonding) terms of the force field and among the solvent-solvent, solvent-solute, and solute-solute interactions. Optimization of the internal parameters used experimental gas-phase geometries, vibrational spectra, and torsional energy surfaces supplemented with ab initio results. The peptide backbone bonding parameters were optimized with respect to data for N-methylacetamide and the alanine dipeptide. The interaction parameters, particularly the atomic charges, were determined by fitting ab initio interaction energies and geometries of complexes between water and model compounds that represented the backbone and the various side chains. In addition, dipole moments, experimental heats and free energies of vaporization, solvation and sublimation, molecular volumes, and crystal pressures and structures were used in the optimization. The resulting protein parameters were tested by applying them to noncyclic tripeptide crystals, cyclic peptide crystals, and the proteins crambin, bovine pancreatic trypsin inhibitor, and carbonmonoxy myoglobin in vacuo and in crystals. A detailed analysis of the relationship between the alanine dipeptide potential energy surface and calculated protein φ, χ angles was made and used in optimizing the peptide group torsional parameters. The results demonstrate that use of ab initio structural and energetic data by themselves are not sufficient to obtain an adequate backbone representation for peptides and proteins in solution and in crystals. Extensive comparisons between molecular dynamics simulations and experimental data for polypeptides and proteins were performed for both structural and dynamic properties. Energy minimization and dynamics simulations for crystals demonstrate that the latter are needed to obtain meaningful comparisons with experimental crystal structures. The presented parameters, in combination with the previously published CHARMM all-atom parameters for nucleic acids and lipids, provide a consistent set for condensed-phase simulations of a wide variety of molecules of biological interest.