Making medical decisions in dependence of genetic background: estimation of the utility of DNA testing in clinical, pharmaco-epidemiological or genetic studies.

PubMed

Nguyen, Thuy Trang; Schäfer, Helmut; Timmesfeld, Nina

2013-05-01

An index measuring the utility of testing a DNA marker before deciding between two alternative treatments is proposed which can be estimated from pharmaco-epidemiological case-control or cohort studies. In the case-control design, external estimates of the prevalence of the disease and of the frequency of the genetic risk variant are required for estimating the utility index. Formulas for point and interval estimates are derived. Empirical coverage probabilities of the confidence intervals were estimated under different scenarios of disease prevalence, prevalence of drug use, and population frequency of the genetic variant. To illustrate our method, we re-analyse pharmaco-epidemiological case-control data on oral contraceptive intake and venous thrombosis in carriers and non-carriers of the factor V Leiden mutation. We also re-analyse cross-sectional data from the Framingham study on a gene-diet interaction between an APOA2 polymorphism and high saturated fat intake on obesity. We conclude that the utility index may be helpful to evaluate and appraise the potential clinical and public health relevance of gene-environment interaction effects detected in genomic and candidate gene association studies and may be a valuable decision support for designing prospective studies on the clinical utility. © 2013 Wiley Periodicals, Inc.

Organizational context and taxonomy of health care databases.

PubMed

Shatin, D

2001-01-01

An understanding of the organizational context and taxonomy of health care databases is essential to appropriately use these data sources for research purposes. Characteristics of the organizational structure of the specific health care setting, including the model type, financial arrangement, and provider access, have implications for accessing and using this data effectively. Additionally, the benefit coverage environment may affect the utility of health care databases to address specific research questions. Coverage considerations that affect pharmacoepidemiologic research include eligibility, the nature of the pharmacy benefit, and regulatory aspects of the treatment under consideration.

Integrated Primary Care Information Database (IPCI)

Cancer.gov

The Integrated Primary Care Information Database is a longitudinal observational database that was created specifically for pharmacoepidemiological and pharmacoeconomic studies, inlcuding data from computer-based patient records supplied voluntarily by general practitioners.

Observation and experiment on the cusp of collaboration: a parallel examination of clinical pharmacology and pharmacoepidemiology.

PubMed

Lehmann, D F

2000-09-01

Despite a common interest in the effect of drugs in humans, clinical pharmacologists and pharmacoepidemiologists often operate in isolation since the knowledge base underlying the respective parent disciplines of pharmacology and epidemiology is quite distinct. This lack of communication may lead to a potential for lost opportunities that would otherwise be mutually beneficial. Accordingly, this article juxtaposes the two disciplines to emphasize common areas of interest despite differences in methodology. In addition, weaknesses and strengths are contrasted in an effort to document the mirror image nature of both clinical pharmacology and pharmacoepidemiology in this regard. Specific examples underlying the complementary nature of the two disciplines are also offered that may help to stimulate collaboration. The possibility of greater formal cooperation between societies representing the two disciplines is also suggested to cross-educate both clinical pharmacologists and pharmacoepidemiologists as a means to foster collaboration.

Electronic case report forms and electronic data capture within clinical trials and pharmacoepidemiology.

PubMed

Rorie, David A; Flynn, Robert W V; Grieve, Kerr; Doney, Alexander; Mackenzie, Isla; MacDonald, Thomas M; Rogers, Amy

2017-09-01

Researchers in clinical and pharmacoepidemiology fields have adopted information technology (IT) and electronic data capture, but these remain underused despite the benefits. This review discusses electronic case report forms and electronic data capture, specifically within pharmacoepidemiology and clinical research. The review used PubMed and the Institute of Electrical and Electronic Engineers library. Search terms used were agreed by the authors and documented. PubMed is medical and health based, whereas Institute of Electrical and Electronic Engineers is technology based. The review focuses on electronic case report forms and electronic data capture, but briefly considers other relevant topics; consent, ethics and security. There were 1126 papers found using the search terms. Manual filtering and reviewing of abstracts further condensed this number to 136 relevant manuscripts. The papers were further categorized: 17 contained study data; 40 observational data; 27 anecdotal data; 47 covering methodology or design of systems; one case study; one literature review; two feasibility studies; and one cost analysis. Electronic case report forms, electronic data capture and IT in general are viewed with enthusiasm and are seen as a cost-effective means of improving research efficiency, educating participants and improving trial recruitment, provided concerns about how data will be protected from misuse can be addressed. Clear operational guidelines and best practises are key for healthcare providers, and researchers adopting IT, and further work is needed on improving integration of new technologies with current systems. A robust method of evaluation for technical innovation is required. © 2017 The Authors. British Journal of Clinical Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.

Biomedical Informatics Approaches to Identifying Drug-Drug Interactions: Application to Insulin Secretagogues

PubMed Central

Han, Xu; Chiang, ChienWei; Leonard, Charles E.; Bilker, Warren B.; Brensinger, Colleen M.; Li, Lang; Hennessy, Sean

2017-01-01

Background Drug-drug interactions with insulin secretagogues are associated with increased risk of serious hypoglycemia in patients with type 2 diabetes. We aimed to systematically screen for drugs that interact with the five most commonly used secretagogues―glipizide, glyburide, glimepiride, repaglinide, and nateglinide―to cause serious hypoglycemia. Methods We screened 400 drugs frequently co-prescribed with the secretagogues as candidate interacting precipitants. We first predicted the drug–drug interaction potential based on the pharmacokinetics of each secretagogue–precipitant pair. We then performed pharmacoepidemiologic screening for each secretagogue of interest, and for metformin as a negative control, using an administrative claims database and the self-controlled case series design. The overall rate ratios (RRs) and those for four predefined risk periods were estimated using Poisson regression. The RRs were adjusted for multiple estimation using semi-Bayes method, and then adjusted for metformin results to distinguish native effects of the precipitant from a drug–drug interaction. Results We predicted 34 pharmacokinetic drug–drug interactions with the secretagogues, nine moderate and 25 weak. There were 140 and 61 secretagogue–precipitant pairs associated with increased rates of serious hypoglycemia before and after the metformin adjustment, respectively. The results from pharmacokinetic prediction correlated poorly with those from pharmacoepidemiologic screening. Conclusions The self-controlled case series design has the potential to be widely applicable to screening for drug–drug interactions that lead to adverse outcomes identifiable in healthcare databases. Coupling pharmacokinetic prediction with pharmacoepidemiologic screening did not notably improve the ability to identify drug–drug interactions in this case. PMID:28169935

Electronic case report forms and electronic data capture within clinical trials and pharmacoepidemiology

PubMed Central

Flynn, Robert W. V.; Grieve, Kerr; Doney, Alexander; Mackenzie, Isla; MacDonald, Thomas M.; Rogers, Amy

2017-01-01

Aims Researchers in clinical and pharmacoepidemiology fields have adopted information technology (IT) and electronic data capture, but these remain underused despite the benefits. This review discusses electronic case report forms and electronic data capture, specifically within pharmacoepidemiology and clinical research. Methods The review used PubMed and the Institute of Electrical and Electronic Engineers library. Search terms used were agreed by the authors and documented. PubMed is medical and health based, whereas Institute of Electrical and Electronic Engineers is technology based. The review focuses on electronic case report forms and electronic data capture, but briefly considers other relevant topics; consent, ethics and security. Results There were 1126 papers found using the search terms. Manual filtering and reviewing of abstracts further condensed this number to 136 relevant manuscripts. The papers were further categorized: 17 contained study data; 40 observational data; 27 anecdotal data; 47 covering methodology or design of systems; one case study; one literature review; two feasibility studies; and one cost analysis. Conclusion Electronic case report forms, electronic data capture and IT in general are viewed with enthusiasm and are seen as a cost‐effective means of improving research efficiency, educating participants and improving trial recruitment, provided concerns about how data will be protected from misuse can be addressed. Clear operational guidelines and best practises are key for healthcare providers, and researchers adopting IT, and further work is needed on improving integration of new technologies with current systems. A robust method of evaluation for technical innovation is required. PMID:28276585

Contribution of Latin America to pharmacovigilance.

PubMed

González, Juan Camilo; Arango, Victoria E; Einarson, Thomas R

2006-01-01

Pharmacovigilance activities have been ongoing for 4 decades. However, little is known (especially outside of the area) about the contribution of Latin America to this field. To review and quantify the published literature on pharmacovigilance in Latin American countries. We searched electronic databases including MEDLINE (1966-2004), EMBASE (1980-2004), International Pharmaceutical Abstracts (1970-2004), Toxline (1992-2004), Literatura Latino-Americana e do Caribe em Ciências da Saúde (1982-2004), Sistema de Información Esencial en Terapéutica y Salud (1980-2004), and the Pan American Health Organization Web site (1970-2004) for articles on pharmacovigilance or adverse drug reactions in any of the 19 major Latin American countries. Papers were retrieved and categorized according to content and country of origin by 2 independent reviewers. There were 195 usable articles from 13 countries. Fifty-one of the papers retrieved dealt with pharmacovigilance centers (15 national centers, 10 hospitals, 26 other), 55 covered pharmacovigilance itself (21 theoretical papers, 9 with description of models, 25 educational papers), and 89 were pharmacoepidemiologic studies of adverse drug reactions (69 case reports, 13 observational cohorts, 2 cohort studies, 1 randomized clinical trial, 4 clinical papers on adverse reaction management). Studies have increased exponentially since 1980. Five countries (Argentina, Brazil, Chile, Costa Rica, Venezuela) published reports from national centers. No studies were found from 6 countries: Dominican Republic, El Salvador, Honduras, Nicaragua, Paraguay, or Uruguay. Most studied categories were antiinfectives and drugs affecting the central nervous system, cardiovascular system, and musculoskeletal system. Contributions of Latin American countries to the field of pharmacovigilence have been remarkable, considering the constraints on these countries. A need exists for an increased number of formal pharmacovigilance studies and research using methodologically stronger pharmacoepidemiologic models.

76 FR 19376 - Statement of Organizations, Functions, and Delegations of Authority

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-07

... safety mission. These outside groups include academic organizations, private organizations, and other Federal Agencies. 3. Coordinates the access to large databases for pharmacoepidemiologic and..., procedures, training, and security or databases available to OSE. 3. Acts as focal point for all hardware...

Odense Pharmacoepidemiological Database: A Review of Use and Content.

PubMed

Hallas, Jesper; Hellfritzsch, Maja; Rix, Morten; Olesen, Morten; Reilev, Mette; Pottegård, Anton

2017-05-01

The Odense University Pharmacoepidemiological Database (OPED) is a prescription database established in 1990 by the University of Southern Denmark, covering reimbursed prescriptions from the county of Funen in Denmark and the region of Southern Denmark (1.2 million inhabitants). It is still active and thereby has more than 25 years of continuous coverage. In this MiniReview, we review its history, content, quality, coverage, governance and some of its uses. OPED's data include the Danish Civil Registration Number (CPR), which enables unambiguous linkage with virtually all other health-related registers in Denmark. Among its research uses, we review record linkage studies of drug effects, advanced drug utilization studies, some examples of method development and use of OPED as sampling frame to recruit patients for field studies or clinical trials. With the advent of other, more comprehensive sources of prescription data in Denmark, OPED may still play a role as in certain data-intensive regional studies. © 2017 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society).

Pharmacoepidemiology resources in Ireland-an introduction to pharmacy claims data.

PubMed

Sinnott, Sarah-Jo; Bennett, Kathleen; Cahir, Caitriona

2017-11-01

Administrative health data, such as pharmacy claims data, present a valuable resource for conducting pharmacoepidemiological and health services research. Often, data are available for whole populations allowing population level analyses. Moreover, their routine collection ensures that the data reflect health care utilisation in the real-world setting compared to data collected in clinical trials. The Irish Health Service Executive-Primary Care Reimbursement Service (HSE-PCRS) community pharmacy claims database is described. The availability of demographic variables and drug-related information is discussed. The strengths and limitations associated using this database for conducting research are presented, in particular, internal and external validity. Examples of recently conducted research using the HSE-PCRS pharmacy claims database are used to illustrate the breadth of its use. The HSE-PCRS national pharmacy claims database is a large, high-quality, valid and accurate data source for measuring drug exposure in specific populations in Ireland. The main limitation is the lack of generalisability for those aged <70 years and the lack of information on indication or outcome.

Privacy considerations in the context of an Australian observational database.

PubMed

Duszynski, K M; Beilby, J J; Marley, J E; Walker, D C; Pratt, N L

2001-12-01

Observational databases are increasingly acknowledged for their value in clinical investigation. Australian general practice in particular presents an exciting opportunity to examine treatment in a natural setting. The paper explores issues such as privacy and confidentiality--foremost considerations when conducting this form of pharmacoepidemiological research. Australian legislation is currently addressing these exact issues in order to establish clear directives regarding ethical concerns. The development of a pharmacoepidemiological database arising from the integration of computerized Australian general practice records is described in addition, to the challenges associated with creating a database which considers patient privacy. The database known as 'Medic-GP', presently contains more than 950,000 clinical notes (including consultations, pathology, diagnostic imaging and adverse reactions) over a 5-year time period and relates to 55,000 patients. The paper then details a retrospective study which utilized the database to examine the interaction between antibiotic prescribing and patient outcomes from a community perspective, following a policy intervention. This study illustrates the application of computerized general practice records in research.

Postmarketing Safety Study Tool: A Web Based, Dynamic, and Interoperable System for Postmarketing Drug Surveillance Studies

PubMed Central

Sinaci, A. Anil; Laleci Erturkmen, Gokce B.; Gonul, Suat; Yuksel, Mustafa; Invernizzi, Paolo; Thakrar, Bharat; Pacaci, Anil; Cinar, H. Alper; Cicekli, Nihan Kesim

2015-01-01

Postmarketing drug surveillance is a crucial aspect of the clinical research activities in pharmacovigilance and pharmacoepidemiology. Successful utilization of available Electronic Health Record (EHR) data can complement and strengthen postmarketing safety studies. In terms of the secondary use of EHRs, access and analysis of patient data across different domains are a critical factor; we address this data interoperability problem between EHR systems and clinical research systems in this paper. We demonstrate that this problem can be solved in an upper level with the use of common data elements in a standardized fashion so that clinical researchers can work with different EHR systems independently of the underlying information model. Postmarketing Safety Study Tool lets the clinical researchers extract data from different EHR systems by designing data collection set schemas through common data elements. The tool interacts with a semantic metadata registry through IHE data element exchange profile. Postmarketing Safety Study Tool and its supporting components have been implemented and deployed on the central data warehouse of the Lombardy region, Italy, which contains anonymized records of about 16 million patients with over 10-year longitudinal data on average. Clinical researchers in Roche validate the tool with real life use cases. PMID:26543873

Design and methods of a postmarketing pharmacoepidemiology study assessing long-term safety of Prolia® (denosumab) for the treatment of postmenopausal osteoporosis.

PubMed

Xue, Fei; Ma, Haijun; Stehman-Breen, Catherine; Haller, Christine; Katz, Leonid; Wagman, Rachel B; Critchlow, Cathy W

2013-10-01

To describe the rationale and methods for a prospective, open-cohort study assessing the long-term safety of Prolia(®) for treatment of postmenopausal osteoporosis (PMO) in postmarketing settings. Data will be derived from United States Medicare, United Healthcare, and Nordic (Denmark, Sweden, Norway) national registries. Observation will begin on the date of first Prolia(®) regulatory approval (May 26, 2010) and continue for 10 years. Women with PMO will be identified by postmenopausal age, osteoporosis diagnosis, osteoporotic fracture, or osteoporosis treatment. Exposure to Prolia(®) and bisphosphonates will be updated during follow-up; exposure cohorts will be defined based on patient-years during which patients are on- or post-treatment. Nine adverse events (AEs) will be assessed based on diagnosis codes: osteonecrosis of the jaw (ONJ), atypical femoral fracture (AFF), fracture healing complications, hypocalcemia, infection, dermatologic AEs, acute pancreatitis, hypersensitivity, and new primary malignancy. Medical review will confirm selected potential cases of ONJ and AFF. Incidence rates (IRs) of AEs will be described overall and for exposure cohorts; multivariate Cox proportional hazard regression models will compare IRs of AEs across exposure cohorts. Utilization patterns of Prolia(®) for approved, and unapproved indications will be described. This study is based on comprehensive preliminary research and considers methodological challenges specific to the study population. The integrated data systems used in this regulatory committed program can serve as a powerful data resource to assess diverse and rare AEs over time. © 2013 Amgen Inc. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd.

78 FR 28228 - Guidance for Industry and Food and Drug Administration Staff on Best Practices for Conducting and...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-14

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration [Docket No. FDA-2011-D-0057] Guidance for Industry and Food and Drug Administration Staff on Best Practices for Conducting and Reporting Pharmacoepidemiologic Safety Studies Using Electronic Healthcare Data; Availability AGENCY: Food and Drug Administration...

Development of an adverse events reporting form for Korean folk medicine.

PubMed

Park, Jeong Hwan; Choi, Sun-Mi; Moon, Sujeong; Kim, Sungha; Kim, Boyoung; Kim, Min-Kyeoung; Lee, Sanghun

2017-05-01

We developed an adverse events (AEs) reporting form for Korean folk medicine. The first version of the form was developed and tested in the clinical setting for spontaneous reporting of AEs. Additional revisions to the reporting form were made based on collected data and expert input. We developed an AEs reporting form for Korean folk medicine. The items of this form were based on patient information, folk medicine properties, and AEs. For causality assessment, folk medicine properties such as classification, common and vernacular names, scientific name, part used, harvesting time, storage conditions, purchasing route, product licensing, prescription, persons with similar exposure, any remnant of raw natural products collected from the patient, and cautions or contraindications were added. This is the first reporting form for AEs that incorporates important characteristics of Korean folk medicine. This form would have an important role in reporting adverse events for Korean folk medicine. © 2016 The Authors. Pharmacoepidemiology and Drug Safety Published by John Wiley & Sons Ltd. © 2016 The Authors. Pharmacoepidemiology and Drug Safety Published by John Wiley & Sons Ltd.

The IMI PROTECT project: purpose, organizational structure, and procedures.

PubMed

Reynolds, Robert F; Kurz, Xavier; de Groot, Mark C H; Schlienger, Raymond G; Grimaldi-Bensouda, Lamiae; Tcherny-Lessenot, Stephanie; Klungel, Olaf H

2016-03-01

The Pharmacoepidemiological Research on Outcomes of Therapeutics by a European ConsorTium (PROTECT) initiative was a collaborative European project that sought to address limitations of current methods in the field of pharmacoepidemiology and pharmacovigilance. Initiated in 2009 and ending in 2015, PROTECT was part of the Innovative Medicines Initiative, a joint undertaking by the European Union and pharmaceutical industry. Thirty-five partners including academics, regulators, small and medium enterprises, and European Federation of Pharmaceuticals Industries and Associations companies contributed to PROTECT. Two work packages within PROTECT implemented research examining the extent to which differences in the study design, methodology, and choice of data source can contribute to producing discrepant results from observational studies on drug safety. To evaluate the effect of these differences, the project applied different designs and analytic methodology for six drug-adverse event pairs across several electronic healthcare databases and registries. This papers introduces the organizational structure and procedures of PROTECT, including how drug-adverse event and data sources were selected, study design and analyses documents were developed, and results managed centrally. Copyright © 2016 John Wiley & Sons, Ltd.

[What can we expect from clinical trials in psychiatry?

PubMed

Marsot, A; Boucherie, Q; Kheloufi, F; Riff, C; Braunstein, D; Dupouey, J; Guilhaumou, R; Zendjidjian, X; Bonin-Guillaume, S; Fakra, E; Guye, M; Jirsa, V; Azorin, J-M; Belzeaux, R; Adida, M; Micallef, J; Blin, O

2016-12-01

Clinical trials in psychiatry allow to build the regulatory dossiers for market authorization but also to document the mechanism of action of new drugs, to build pharmacodynamics models, evaluate the treatment effects, propose prognosis, efficacy or tolerability biomarkers and altogether to assess the impact of drugs for patient, caregiver and society. However, clinical trials have shown some limitations. Number of recent dossiers failed to convince the regulators. The clinical and biological heterogeneity of psychiatric disorders, the pharmacokinetic and pharmacodynamics properties of the compounds, the lack of translatable biomarkers possibly explain these difficulties. Several breakthrough options are now available: quantitative system pharmacology analysis of drug effects variability, pharmacometry and pharmacoepidemiology, Big Data analysis, brain modelling. In addition to more classical approaches, these opportunities lead to a paradigm change for clinical trials in psychiatry. © L’Encéphale, Paris, 2016.

Measuring the impact of pharmacoepidemiologic research using altmetrics: A case study of a CNODES drug-safety article.

PubMed

Gamble, J M; Traynor, Robyn L; Gruzd, Anatoliy; Mai, Philip; Dormuth, Colin R; Sketris, Ingrid S

2018-03-24

To provide an overview of altmetrics, including their potential benefits and limitations, how they may be obtained, and their role in assessing pharmacoepidemiologic research impact. Our review was informed by compiling relevant literature identified through searching multiple health research databases (PubMed, Embase, and CIHNAHL) and grey literature sources (websites, blogs, and reports). We demonstrate how pharmacoepidemiologists, in particular, may use altmetrics to understand scholarly impact and knowledge translation by providing a case study of a drug-safety study conducted by the Canadian Network of Observational Drug Effect Studies. A common approach to measuring research impact is the use of citation-based metrics, such as an article's citation count or a journal's impact factor. "Alternative" metrics, or altmetrics, are increasingly supported as a complementary measure of research uptake in the age of social media. Altmetrics are nontraditional indicators that capture a diverse set of traceable, online research-related artifacts including peer-reviewed publications and other research outputs (software, datasets, blogs, videos, posters, policy documents, presentations, social media posts, wiki entries, etc). Compared with traditional citation-based metrics, altmetrics take a more holistic view of research impact, attempting to capture the activity and engagement of both scholarly and nonscholarly communities. Despite the limited theoretical underpinnings, possible commercial influence, potential for gaming and manipulation, and numerous data quality-related issues, altmetrics are promising as a supplement to more traditional citation-based metrics because they can ingest and process a larger set of data points related to the flow and reach of scholarly communication from an expanded pool of stakeholders. Unlike citation-based metrics, altmetrics are not inherently rooted in the research publication process, which includes peer review; it is unclear to what extent they should be used for research evaluation. © 2018 The Authors. Pharmacoepidemiology and Drug Safety. Published by John Wiley & Sons, Ltd.

Instrumental variables analysis using multiple databases: an example of antidepressant use and risk of hip fracture.

PubMed

Uddin, Md Jamal; Groenwold, Rolf H H; de Boer, Anthonius; Gardarsdottir, Helga; Martin, Elisa; Candore, Gianmario; Belitser, Svetlana V; Hoes, Arno W; Roes, Kit C B; Klungel, Olaf H

2016-03-01

Instrumental variable (IV) analysis can control for unmeasured confounding, yet it has not been widely used in pharmacoepidemiology. We aimed to assess the performance of IV analysis using different IVs in multiple databases in a study of antidepressant use and hip fracture. Information on adults with at least one prescription of a selective serotonin reuptake inhibitor (SSRI) or tricyclic antidepressant (TCA) during 2001-2009 was extracted from the THIN (UK), BIFAP (Spain), and Mondriaan (Netherlands) databases. IVs were created using the proportion of SSRI prescriptions per practice or using the one, five, or ten previous prescriptions by a physician. Data were analysed using conventional Cox regression and two-stage IV models. In the conventional analysis, SSRI (vs. TCA) was associated with an increased risk of hip fracture, which was consistently found across databases: the adjusted hazard ratio (HR) was approximately 1.35 for time-fixed and 1.50 to 2.49 for time-varying SSRI use, while the IV analysis based on the IVs that appeared to satisfy the IV assumptions showed conflicting results, e.g. the adjusted HRs ranged from 0.55 to 2.75 for time-fixed exposure. IVs for time-varying exposure violated at least one IV assumption and were therefore invalid. This multiple database study shows that the performance of IV analysis varied across the databases for time-fixed and time-varying exposures and strongly depends on the definition of IVs. It remains challenging to obtain valid IVs in pharmacoepidemiological studies, particularly for time-varying exposure, and IV analysis should therefore be interpreted cautiously. Copyright © 2016 John Wiley & Sons, Ltd.

Assumptions made when preparing drug exposure data for analysis have an impact on results: An unreported step in pharmacoepidemiology studies.

PubMed

Pye, Stephen R; Sheppard, Thérèse; Joseph, Rebecca M; Lunt, Mark; Girard, Nadyne; Haas, Jennifer S; Bates, David W; Buckeridge, David L; van Staa, Tjeerd P; Tamblyn, Robyn; Dixon, William G

2018-04-17

Real-world data for observational research commonly require formatting and cleaning prior to analysis. Data preparation steps are rarely reported adequately and are likely to vary between research groups. Variation in methodology could potentially affect study outcomes. This study aimed to develop a framework to define and document drug data preparation and to examine the impact of different assumptions on results. An algorithm for processing prescription data was developed and tested using data from the Clinical Practice Research Datalink (CPRD). The impact of varying assumptions was examined by estimating the association between 2 exemplar medications (oral hypoglycaemic drugs and glucocorticoids) and cardiovascular events after preparing multiple datasets derived from the same source prescription data. Each dataset was analysed using Cox proportional hazards modelling. The algorithm included 10 decision nodes and 54 possible unique assumptions. Over 11 000 possible pathways through the algorithm were identified. In both exemplar studies, similar hazard ratios and standard errors were found for the majority of pathways; however, certain assumptions had a greater influence on results. For example, in the hypoglycaemic analysis, choosing a different variable to define prescription end date altered the hazard ratios (95% confidence intervals) from 1.77 (1.56-2.00) to 2.83 (1.59-5.04). The framework offers a transparent and efficient way to perform and report drug data preparation steps. Assumptions made during data preparation can impact the results of analyses. Improving transparency regarding drug data preparation would increase the repeatability, reproducibility, and comparability of published results. © 2018 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd.

Pharmacoepidemiology of testosterone: Curbing off-label prescribing.

PubMed

Handelsman, David J

2017-10-01

To estimate the impact of the first year of new Pharmaceutical Benefits Scheme (PBS) prescribing criteria that dictate eligibility for national health scheme subsidy of testosterone prescribing. Analysis of cumulative PBS data. Retrospective analysis of testosterone prescribing from PBS data. Nil MAIN OUTCOME MEASURES: PBS expenditure analysed by total expenditure, by state, and by product type as well as the age, indication, and prescriber type for new testosterone treatment. Total PBS expenditure continued to exceed $20 million in 2014 before declining from 2015 with changes that were uniform by state and product type. Prior to 2015, over 80% were for men aged over 40 years of age for low circulating testosterone in the absence of reproductive system disorders ("Low T") initiated by GPs. From 2015, these features were markedly reduced without changing the numbers of new prescriptions for pathological reproductive disorders or specialist initiations. The short-term impact of 2015 PBS criteria showed highly effective and well-targeted curbing of off-label testosterone prescribing. The findings indicate that the main driver for the recent upsurge in testosterone prescribing was treatment of middle-aged men for "Low T" initiated by GPs. © 2017 Government of New South Wales. Pharmacoepidemiology & Drug Safety © 2017 John Wiley & Sons Ltd.

Are selective serotonin reuptake inhibitors safe for drivers? What is the evidence?

PubMed

Ravera, Silvia; Ramaekers, Johannes G; de Jong-van den Berg, Lolkje T W; de Gier, Johan J

2012-05-01

Selective serotonin reuptake inhibitors (SSRIs) are widely used medications to treat several psychiatric diseases and, above all, depression. They seem to be as effective as older antidepressants but have a different adverse effect profile. Despite their favorable safety profile, little is known about their influence on traffic safety. To conduct a literature review to summarize the current evidence on the role of SSRIs in traffic safety, particularly concerning undesirable effects that could potentially impair fitness to drive, experimental and pharmacoepidemiologic studies on driving impairment, 2 existing categorization systems for driving-impairing medications, and the European legislative procedures for assessing fitness to drive before issuing a driver's license and driving under the influence of medicines. The article search was performed in the following electronic databases: MEDLINE, PsycINFO, ScienceDirect, and SafetyLit. The English-language scientific literature was searched using key words such as SSRIs and psychomotor performance, car crash or traffic accident, and adverse effects. For inclusion in this review, papers had to be full-text articles, refer to possible driving-related adverse effects, and be experimental or pharmacoepidemiologic studies on SSRIs and traffic accident risks. No restrictions concerning publication year were applied. Ten articles were selected as background information on driving-related adverse effects, and 15 articles were selected regarding experimental and pharmacoepidemiologic work. Regarding SSRI adverse effects, the most reported undesirable effects referring to driving impairment were anxiety, agitation, sleep disturbances, headache, increased risk of suicidal behavior, and deliberate self-harm. Regarding the remaining issues addressed in this article, inconsistencies were found between the outcomes of the selected experimental and epidemiologic studies and between the 2 existing categorization systems under evaluation. Some pitfalls of the current legislative scenario were identified as well. Based on the current evidence, it was concluded that more experimental and epidemiologic research is needed to elucidate the relationship between SSRI use and traffic safety. Furthermore, a revision of the existing categorization systems and harmonized European legislation in the field of medication use and driving were highly recommended. Copyright © 2012 Elsevier HS Journals, Inc. All rights reserved.

Record linkage for pharmacoepidemiological studies in cancer patients.

PubMed

Herk-Sukel, Myrthe P P van; Lemmens, Valery E P P; Poll-Franse, Lonneke V van de; Herings, Ron M C; Coebergh, Jan Willem W

2012-01-01

An increasing need has developed for the post-approval surveillance of (new) anti-cancer drugs by means of pharmacoepidemiology and outcomes research in the area of oncology. To create an overview that makes researchers aware of the available database linkages in Northern America and Europe which facilitate pharmacoepidemiology and outcomes research in cancer patients. In addition to our own database, i.e. the Eindhoven Cancer Registry (ECR) linked to the PHARMO Record Linkage System, we considered database linkages between a population-based cancer registry and an administrative healthcare database that at least contains information on drug use and offers a longitudinal perspective on healthcare utilization. Eligible database linkages were limited to those that had been used in multiple published articles in English language included in Pubmed. The HMO Cancer Research Network (CRN) in the US was excluded from this review, as an overview of the linked databases participating in the CRN is already provided elsewhere. Researchers who had worked with the data resources included in our review were contacted for additional information and verification of the data presented in the overview. The following database linkages were included: the Surveillance, Epidemiology, and End-Results-Medicare; cancer registry data linked to Medicaid; Canadian cancer registries linked to population-based drug databases; the Scottish cancer registry linked to the Tayside drug dispensing data; linked databases in the Nordic Countries of Europe: Norway, Sweden, Finland and Denmark; and the ECR-PHARMO linkage in the Netherlands. Descriptives of the included database linkages comprise population size, generalizability of the population, year of first data availability, contents of the cancer registry, contents of the administrative healthcare database, the possibility to select a cancer-free control cohort, and linkage to other healthcare databases. The linked databases offer a longitudinal perspective, allowing for observations of health care utilization before, during, and after cancer diagnosis. They create new powerful data resources for the monitoring of post-approval drug utilization, as well as a framework to explore the (cost-)effectiveness of new, often expensive, anti-cancer drugs as used in everyday practice. Copyright © 2011 John Wiley & Sons, Ltd.

Methodological considerations in observational comparative effectiveness research for implantable medical devices: an epidemiologic perspective.

PubMed

Jalbert, Jessica J; Ritchey, Mary Elizabeth; Mi, Xiaojuan; Chen, Chih-Ying; Hammill, Bradley G; Curtis, Lesley H; Setoguchi, Soko

2014-11-01

Medical devices play a vital role in diagnosing, treating, and preventing diseases and are an integral part of the health-care system. Many devices, including implantable medical devices, enter the market through a regulatory pathway that was not designed to assure safety and effectiveness. Several recent studies and high-profile device recalls have demonstrated the need for well-designed, valid postmarketing studies of medical devices. Medical device epidemiology is a relatively new field compared with pharmacoepidemiology, which for decades has been developed to assess the safety and effectiveness of medications. Many methodological considerations in pharmacoepidemiology apply to medical device epidemiology. Fundamental differences in mechanisms of action and use and in how exposure data are captured mean that comparative effectiveness studies of medical devices often necessitate additional and different considerations. In this paper, we discuss some of the most salient issues encountered in conducting comparative effectiveness research on implantable devices. We discuss special methodological considerations regarding the use of data sources, exposure and outcome definitions, timing of exposure, and sources of bias. © The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Use of a German longitudinal prescription database (LRx) in pharmacoepidemiology.

PubMed

Richter, Hartmut; Dombrowski, Silvia; Hamer, Hajo; Hadji, Peyman; Kostev, Karel

2015-01-01

Large epidemiological databases are often used to examine matters pertaining to drug utilization, health services, and drug safety. The major strength of such databases is that they include large sample sizes, which allow precise estimates to be made. The IMS® LRx database has in recent years been used as a data source for epidemiological research. The aim of this paper is to review a number of recent studies published with the aid of this database and compare these with the results of similar studies using independent data published in the literature. In spite of being somewhat limited to studies for which comparative independent results were available, it was possible to include a wide range of possible uses of the LRx database in a variety of therapeutic fields: prevalence/incidence rate determination (diabetes, epilepsy), persistence analyses (diabetes, osteoporosis), use of comedication (diabetes), drug utilization (G-CSF market) and treatment costs (diabetes, G-CSF market). In general, the results of the LRx studies were found to be clearly in line with previously published reports. In some cases, noticeable discrepancies between the LRx results and the literature data were found (e.g. prevalence in epilepsy, persistence in osteoporosis) and these were discussed and possible reasons presented. Overall, it was concluded that the IMS® LRx database forms a suitable database for pharmacoepidemiological studies.

False-positive results in pharmacoepidemiology and pharmacovigilance.

PubMed

Bezin, Julien; Bosco-Levy, Pauline; Pariente, Antoine

2017-09-01

False-positive constitute an important issue in scientific research. In the domain of drug evaluation, it affects all phases of drug development and assessment, from the very early preclinical studies to the late post-marketing evaluations. The core concern associated with this false-positive is the lack of replicability of the results. Aside from fraud or misconducts, false-positive is often envisioned from the statistical angle, which considers them as a price to pay for type I error in statistical testing, and its inflation in the context of multiple testing. If envisioning this problematic in the context of pharmacoepidemiology and pharmacovigilance however, that both evaluate drugs in an observational settings, information brought by statistical testing and the significance of such should only be considered as additional to the estimates provided and their confidence interval, in a context where differences have to be a clinically meaningful upon everything, and the results appear robust to the biases likely to have affected the studies. In the following article, we consequently illustrate these biases and their consequences in generating false-positive results, through studies and associations between drug use and health outcomes that have been widely disputed. Copyright © 2017 Société française de pharmacologie et de thérapeutique. Published by Elsevier Masson SAS. All rights reserved.

Evaluating the effectiveness of risk minimisation measures: the application of a conceptual framework to Danish real-world dabigatran data.

PubMed

Nyeland, Martin Erik; Laursen, Mona Vestergaard; Callréus, Torbjörn

2017-06-01

For both marketing authorization holders and regulatory authorities, evaluating the effectiveness of risk minimization measures is now an integral part of pharmacovigilance in the European Union. The overall aim of activities in this area is to assess the performance of risk minimization measures implemented in order to ensure a positive benefit-risk balance in patients treated with a medicinal product. Following a review of the relevant literature, we developed a conceptual framework consisting of four domains (data, knowledge, behaviour and outcomes) intended for the evaluation of risk minimization measures put into practice in the Danish health-care system. For the implementation of the framework, four classes of monitoring variables can be named and defined: patient descriptors, performance-related indicators of knowledge, behaviour and outcomes. We reviewed the features of the framework when applied to historical, real-world data following the introduction of dabigatran in Denmark for the prophylactic treatment of patients with non-valvular atrial fibrillation. The application of the framework provided useful graphical displays and an opportunity for a statistical evaluation (interrupted time series analysis) of a regulatory intervention. © 2017 Commonwealth of Australia. Pharmacoepidemiology & Drug Safety © 2017 John Wiley & Sons, Ltd. © 2017 Commonwealth of Australia. Pharmacoepidemiology & Drug Safety © 2017 John Wiley & Sons, Ltd.

Immortal time bias in pharmaco-epidemiology.

PubMed

Suissa, Samy

2008-02-15

Immortal time is a span of cohort follow-up during which, because of exposure definition, the outcome under study could not occur. Bias from immortal time was first identified in the 1970s in epidemiology in the context of cohort studies of the survival benefit of heart transplantation. It recently resurfaced in pharmaco-epidemiology, with several observational studies reporting that various medications can be extremely effective at reducing morbidity and mortality. These studies, while using different cohort designs, all involved some form of immortal time and the corresponding bias. In this paper, the author describes various cohort study designs leading to this bias, quantifies its magnitude under different survival distributions, and illustrates it by using data from a cohort of lung cancer patients. The author shows that for time-based, event-based, and exposure-based cohort definitions, the bias in the rate ratio resulting from misclassified or excluded immortal time increases proportionately to the duration of immortal time. The bias is more pronounced with a decreasing hazard function for the outcome event, as illustrated with the Weibull distribution compared with a constant hazard from the exponential distribution. In conclusion, observational studies of drug benefit in which computerized databases are used must be designed and analyzed properly to avoid immortal time bias.

JIM-13-0560 R1: Propensity scores for confounder adjustment when assessing the effects of medical interventions using non-experimental study designs

PubMed Central

Stürmer, Til; Wyss, Richard; Glynn, Robert J.; Brookhart, M. Alan

2014-01-01

Treatment effects, especially when comparing two or more therapeutic alternatives as in comparative effectiveness research, are likely to be heterogeneous across age, gender, co-morbidities, and co-medications. Propensity scores (PSs), an alternative to multivariable outcome models to control for measured confounding, have specific advantages in the presence of heterogeneous treatment effects. Implementing PSs using matching or weighting allows us to estimate different overall treatment effects in differently defined populations. Heterogeneous treatment effects can also be due to unmeasured confounding concentrated in those treated contrary to prediction. Sensitivity analyses based on PSs can help to assess such unmeasured confounding. PSs should be considered a primary or secondary analytic strategy in non-experimental medical research, including pharmacoepidemiology and non-experimental comparative effectiveness research. PMID:24520806

Safety assessment in pediatric studies.

PubMed

Koren, Gideon; Elzagallaai, Abdelbasset; Etwel, Fatma

2011-01-01

It typically takes many years before an association of a drug with a rare, serious adverse reaction is established. As related to pediatric drug use, evidence is even more erratic, as most drugs are used off labels. To enhance child safety, there is an urgent need to develop robust and rapid methods to identify such associations in as timely a manner as possible. In this chapter, several novel methods, both clinically based pharmacoepidemiological approaches and laboratory-based methods, are described.

A pharmacoepidemiological approach to investigating inappropriate physician prescribing in a managed care setting in Israel.

PubMed

Kahan, Natan R; Blackman, Shimon; Kutz, Chaim; Waitman, Dan-Andrei

2005-02-01

To identify cases of inappropriate physician prescribing in a managed care setting in Israel that may have resulted from misuse of magnetic-stripe membership cards. Retrospective drug utilization analysis of electronic patient prescription data. In a managed care setting involving approximately 1000 physicians who issue approximately 1.4 million prescriptions annually, the rate of prescription of sex-specific drugs to patients of the opposite sex for which the drugs are indicated was evaluated for 2003. The categories of drugs included in the analysis were drugs for the treatment of benign prostatic hyperplasia or erectile dysfunction that were prescribed to women, as well as oral contraceptives, vaginal pessaries, hormone therapy, or raloxifene hydrochloride prescribed to men. Throughout the study year, 193 different physicians wrote 341 prescriptions that matched the drug inclusion criteria for 210 different patients. The most frequently observed scenario involved the prescription for women of selective alpha-blockers, including alfuzosin hydrochloride, tamsulosin hydrochloride, and terazosin hydrochloride, that are indicated exclusively for the treatment of benign prostatic hyperplasia. The electronic patient record system used in the health maintenance organization studied was programmed to block the prescription of sex-specific drugs for patients of the opposite sex for which they are intended unless proper authorization has been obtained. Furthermore, periodic investigation into prescription impropriety may be easily accomplished through the implementation of pharmacoepidemiological methods commonly used in drug utilization studies.

Good practices for real-world data studies of treatment and/or comparative effectiveness: Recommendations from the joint ISPOR-ISPE Special Task Force on real-world evidence in health care decision making.

PubMed

Berger, Marc L; Sox, Harold; Willke, Richard J; Brixner, Diana L; Eichler, Hans-Georg; Goettsch, Wim; Madigan, David; Makady, Amr; Schneeweiss, Sebastian; Tarricone, Rosanna; Wang, Shirley V; Watkins, John; Daniel Mullins, C

2017-09-01

Real-world evidence (RWE) includes data from retrospective or prospective observational studies and observational registries and provides insights beyond those addressed by randomized controlled trials. RWE studies aim to improve health care decision making. The International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and the International Society for Pharmacoepidemiology (ISPE) created a task force to make recommendations regarding good procedural practices that would enhance decision makers' confidence in evidence derived from RWD studies. Peer review by ISPOR/ISPE members and task force participants provided a consensus-building iterative process for the topics and framing of recommendations. The ISPOR/ISPE Task Force recommendations cover seven topics such as study registration, replicability, and stakeholder involvement in RWE studies. These recommendations, in concert with earlier recommendations about study methodology, provide a trustworthy foundation for the expanded use of RWE in health care decision making. The focus of these recommendations is good procedural practices for studies that test a specific hypothesis in a specific population. We recognize that some of the recommendations in this report may not be widely adopted without appropriate incentives from decision makers, journal editors, and other key stakeholders. © 2017 The Authors. Pharmacoepidemiology & Drug Safety published by John Wiley & Sons Ltd.

The social science contribution to pharmacoepidemiology.

PubMed

Higginbotham, N; Streiner, D L

1991-01-01

An understanding of the inappropriate use of pharmaceuticals (the prescribing of unnecessary or ineffective medications, and non-compliance by consumers) can be furthered by considering the psychological, social and cultural contexts in which medicines are used. The consumers are influenced by their beliefs about benefits, safety and cost; opinions of their social group; and emotions associated with taking the medication itself. Similar considerations apply to the prescribers or dispensers of the drugs, who are also influenced by the marketing and regulatory practices of their countries. A model of drug use which takes these factors into account can suggest various strategies to increase optimal pharmaceutical utilization. To date, these efforts have focused almost exclusively on the prescriber or manufacturer, and have had limited success. However, other, more effective techniques exist, which can modify the behavior of both of these groups, and of the consumers. A strategy of research in this area is outlined.

Pharmacoepidemiologic investigation of a clonazepam-valproic acid interaction by mixed effect modeling using routine clinical pharmacokinetic data in Japanese patients.

PubMed

Yukawa, E; Nonaka, T; Yukawa, M; Higuchi, S; Kuroda, T; Goto, Y

2003-12-01

Non-linear Mixed Effects Modeling (NONMEM) was used to estimate the effects of clonazepam-valproic acid interaction on clearance values using 576 serum levels collected from 317 pediatric and adult epileptic patients (age range, 0.3-32.6 years) during their clinical routine care. Patients received the administration of clonazepam and/or valproic acid. The final model describing clonazepam clearance was CL = 144.0 TBW-0.172 1.14VPA, where CL is total body clearance (mL/kg/h); TBW is total body weight (kg); VPA = 1 for concomitant administration of valproic acid and VPA = zero otherwise. The final model describing valproic acid clearance was CL (mL/kg/h) = 17.2 TBW-0.264 DOSE0.159 0.821CZP 0.896GEN, where DOSE is the daily dose of valproic acid (mg/kg/day); CZP = 1 for concomitant administration of clonazepam and CZP = zero otherwise; GEN = 1 for female and GEN = zero otherwise. Concomitant administration of clonazepam and valproic acid resulted in a 14% increase in clonazepam clearance, and a 17.9% decrease in valproic acid clearance.

The National Data Bank for Rheumatic Diseases (NDB).

PubMed

Michaud, Kaleb

2016-01-01

The National Data Bank for Rheumatic Diseases (NDB) is a longitudinal observational patient-driven database, founded as a non-profit research organization in 1998 by Dr. Frederick Wolfe. Patients are sent a primary questionnaire twice a year. More than 50,000 patients with more than 100 various rheumatic diseases under the care of more than 1,500 rheumatologists have completed at least one 6-month questionnaire. Many important publications concerning rheumatoid arthritis, osteoarthritis, systemic lupus erythematosus, fibromyalgia, and pharmaco-epidemiology have resulted from NDB research.

Applications of artificial neural networks in medical science.

PubMed

Patel, Jigneshkumar L; Goyal, Ramesh K

2007-09-01

Computer technology has been advanced tremendously and the interest has been increased for the potential use of 'Artificial Intelligence (AI)' in medicine and biological research. One of the most interesting and extensively studied branches of AI is the 'Artificial Neural Networks (ANNs)'. Basically, ANNs are the mathematical algorithms, generated by computers. ANNs learn from standard data and capture the knowledge contained in the data. Trained ANNs approach the functionality of small biological neural cluster in a very fundamental manner. They are the digitized model of biological brain and can detect complex nonlinear relationships between dependent as well as independent variables in a data where human brain may fail to detect. Nowadays, ANNs are widely used for medical applications in various disciplines of medicine especially in cardiology. ANNs have been extensively applied in diagnosis, electronic signal analysis, medical image analysis and radiology. ANNs have been used by many authors for modeling in medicine and clinical research. Applications of ANNs are increasing in pharmacoepidemiology and medical data mining. In this paper, authors have summarized various applications of ANNs in medical science.

Diverging Conclusions from the Same Meta-Analysis in Drug Safety: Source of Data (Primary Versus Secondary) Takes a Toll.

PubMed

Prada-Ramallal, Guillermo; Takkouche, Bahi; Figueiras, Adolfo

2017-04-01

Meta-analyses of observational studies represent an important tool for assessing efficacy and safety in the pharmacoepidemiologic field. The data from the individual studies are either primary (i.e., collected through interviews or self-administered questionnaires) or secondary (i.e., collected from databases that were established for other purposes). So far, the origin of the data (primary vs. secondary) has not been systematically assessed as a source of heterogeneity in pharmacoepidemiologic meta-analyses. The aim was to assess the impact of considering the source of exposure data as a criterion in sensitivity and subgroup analysis on the conclusions of drug safety meta-analyses. We selected meta-analyses published between 2013 and 2015 in which the intake of frequently used over-the-counter medicines was either the main exposure or a concomitant treatment and the outcome had short latency and induction periods. We stratified the results by origin of data (primary vs. secondary) and compared the new results to those presented originally in the meta-analyses. We used four meta-analyses that fulfilled our criteria of inclusion. The results were selective serotonin reuptake inhibitors and upper gastrointestinal bleeding: original estimate odds ratio (OR) = 1.71 [95% confidence interval (CI) 1.44-2.04], OR primary data = 1.19 (95% CI 0.90-1.58), OR secondary data = 1.81 (95% CI 1.50-2.17); proton pump inhibitors and cardiac events: original estimate hazard ratio (HR) = 1.35 (95% CI 1.18-1.54), HR primary data = 1.05 (95% CI 0.87-1.26), HR secondary data = 1.43 (95% CI 1.23-1.66); non-aspirin non-steroidal anti-inflammatory drugs and myocardial infarction: original estimate risk ratio (RR) = 1.08 (95% CI 0.95-1.22), RR primary data = 0.57 (95% CI 0.34-0.96), RR secondary data = 1.15 (95% CI 1.03-1.28); paracetamol during pregnancy and childhood asthma: original estimate OR = 1.32 (95% CI 1.14-1.52), OR primary data = 1.23 (95% CI 1.06-1.42), OR secondary data = 1.53 (95% CI 1.33-1.75). The results after stratification are considerably modified. It is crucial to explore the origin of the data, either primary or secondary, as a source of heterogeneity in pharmacoepidemiologic meta-analyses to avoid misleading conclusions.

Lessons learned on the design and the conduct of Post-Authorization Safety Studies: review of 3 years of PRAC oversight.

PubMed

Engel, Pierre; Almas, Mariana Ferreira; De Bruin, Marieke Louise; Starzyk, Kathryn; Blackburn, Stella; Dreyer, Nancy Ann

2017-04-01

To describe and characterize the first cohort of Post-Authorization Safety Study (PASS) protocols reviewed under the recent European pharmacovigilance legislation. A systematic approach was used to compile all publicly available information on PASS protocols and assessments submitted from July 2012 to July 2015 from Pharmacovigilance Risk Assessment Committee (PRAC) minutes, European Medicines Agency (EMA) and European Network of Pharmacovigilance and Pharmacoepidemiology (ENCePP) webpages. During the study period, 189 different PASS protocols were submitted to the PRAC, half of which were entered in the ENCePP electronic register of post-authorization studies (EU-PAS) by July 2015. Those protocols were assessed during 353 PRAC reviews. The EMA published only 31% of the PRAC feedback, of which the main concerns were study design (37%) and feasibility (30%). Among the 189 PASS, slightly more involved primary data capture (58%). PASS assessing drug utilization mainly leveraged secondary data sources (58%). The majority of the PASS did not include a comparator (65%) and 35% of PASS also evaluated clinical effectiveness endpoints. To the best of our knowledge this is the first comprehensive review of three years of PASS protocols submitted under the new pharmacovigilance legislation. Our results show that both EMA and PASS sponsors could respectively increase the availability of protocol assessments and documents in the EU-PAS. Protocol content review and the high number of PRAC comments related to methodological issues and feasibility concerns should raise awareness among PASS stakeholders to design more thoughtful studies according to pharmacoepidemiological principles and existing guidelines. © 2016 The British Pharmacological Society.

Usage trends for memory and vitality-enhancing medicines: A pharmacoepidemiological study involving pharmacists of the Gujarat region

PubMed Central

Shah, Jigna Samir; Goyal, R. K.

2010-01-01

Objective: The aim of the study was to explore the trends and rationale of use of memory and vitality-enhancing medicines (MVEM) in the Gujarat region. Materials and Methods: A prospective pharmacoepidemiological study involving pharmacists of Gujarat region was carried out in the year 2005. Pharmacists (n = 351) working in general and Ayurvedic medical stores were selected from 12 districts of Gujarat region. The pharmacists were explained about the objective of the study and were given a pretested, validated questionnaire. Outcome Measures: The questionnaire included the questions regarding herbal MVEM used most commonly, percentage sale of herbal MVEM – sold with or without prescriptions – age group of patients and professional groups who used these drugs most commonly. Results: The number of individuals using MVEM was highest in the age group of 11–20 years (17.54%), followed by the 21–40 years group (17.12%), supporting the results that the professional group of students (17.29%) and the persons of business or service class (15.29%) are the highest users of these medicines. Evaluation of various constituents in the marketed polyherbal MVEM revealed that Brahmi (Bacopa monniera), Shankhpushpi (Evolvulus alsinoides), Ashwangandha (Withania somnifera), Jatamansi (Nardostychos jatamansi), Vacha (Acorus calamus) and Amla (Phyllanthus emblica) were the common ingredients in the polyherbal preparations. Conclusions: This study highlights commonly used Ayurvedic medicines that can be explored for safely enhancing memory and vitality performance. Hence, detailed and scientifically designed research on these drugs would help to identify safe and effective drugs for enhancing the same. PMID:21170204

Drug utilization according to reason for prescribing: a pharmacoepidemiologic method based on an indication hierarchy.

PubMed

Wallach Kildemoes, Helle; Hendriksen, Carsten; Andersen, Morten

2012-10-01

To develop a pharmacoepidemiologic method for drug utilization analysis according to indication, gender, and age by means of register-based information. Statin utilization in 2005 was applied as an example. Following the recommendations for statin therapy, we constructed an indication hierarchy with eight mutually exclusive levels of register markers of cardiovascular disease and diabetes. Danish residents, as of January 1, 1996, were followed at the individual level in nationwide registers with respect to dispensed prescriptions of cardiovascular drugs and antidiabetics (1996-2005) along with discharge diagnoses and surgical procedures (1977-2005). The highest current possible indication level was assigned to all cohort members. Stratified by indication, gender, and age, statin treatment prevalence and incidence were calculated. Statin treatment prevalence was highest among individuals with myocardial infarction and tended to be higher among men with indications in the upper part of the hierarchy, but it was higher among women (especially the elderly) in the lower part of the hierarchy. Treatment incidence rates followed roughly the same pattern. Women with no register marker or primary hypertension accounted for almost 50% of all incident female users; among men, the figure was 35%. The proportion of incident users with ischemic heart disease or myocardial infarction increased with age. The proposed indication hierarchy provided new insight into prescription patterns of statins. The method can be implemented for other drug categories and could be useful for studying trends in drug utilization, differential drug adherence, and cross-national comparisons. Copyright © 2011 John Wiley & Sons, Ltd.

Access to linked administrative healthcare utilization data for pharmacoepidemiology and pharmacoeconomics research in Canada: anti-viral drugs as an example.

PubMed

Rawson, Nigel S B

2009-11-01

Administrative healthcare utilization data from Canadian provinces have been used for pharmacoepidemiology and pharmacoeconomics research, but limited transparency exists about opportunities for data access, who can access them, and processes to obtain data. An attempt was made to obtain data from all 10 provinces to evaluate access and its complexity. An initial enquiry about the process and requirements to obtain data on individual, anonymized patients dispensed any of four anti-viral drugs in the ambulatory setting, linked with data from hospital and physician service claims, was sent to each province. Where a response was encouraging, a technical description of the data of interest was submitted. Data were unavailable from the provinces of New Brunswick, Newfoundland and Labrador, and Prince Edward Island, and inaccessible from British Columbia, Manitoba and Ontario due to policies that prohibit collaborative work with pharmaceutical industry researchers. In Nova Scotia, patient-level data were available but only on site. Data were accessible in Alberta, Quebec and Saskatchewan, although variation exists in the currency of the data, time to obtain data, approval requirements and insurance coverage eligibility. As Canada moves towards a life-cycle management approach to drug regulation, more post-marketing studies will be required, potentially using administrative data. Linked patient-level drug and healthcare data are presently accessible to pharmaceutical industry researchers in four provinces, although only logistically realistic in three and limited to seniors and low-income individuals in two. Collaborative endeavours to improve access to provincial data and to create other data resources should be encouraged. (c) 2009 John Wiley & Sons, Ltd.

Increase in the prescription rate of antidepressants after the Sewol Ferry disaster in Ansan, South Korea.

PubMed

Han, Kyu-Man; Kim, Kyoung-Hoon; Lee, Mikyung; Lee, Sang-Min; Ko, Young-Hoon; Paik, Jong-Woo

2017-09-01

Previous pharmaco-epidemiological studies have reported increases in the prescription of psychotropic medications after a disaster, reflecting post-disaster changes in psychiatric conditions and mental health service utilization. We investigated changes in the prescription of psychotropic medications in the Danwon district of Ansan city (Ansan Danwon) compared to a control community before and after the Sewol Ferry disaster on April 16, 2014. Data was collected from the Korean Health Insurance Review and Assessment Service database. We analyzed the prescription rates of psychotropic medications including antidepressants, anxiolytics, and sedatives/hypnotics, and investigated whether the time-series pattern of monthly prescriptions per 100,000 people was different in Ansan Danwon compared to that in Cheonan city after the Sewol Ferry disaster through difference-in-differences regression analysis. Ansan Danwon showed a significantly greater increase (5.6%) in the prescription rate of antidepressants compared to Cheonan city following the Sewol Ferry disaster. There were no significant differences in changes in the prescription rates of anxiolytics or sedatives/hypnotics. In the secondary analysis, a significantly greater increase in the prescription rate of antipsychotics was observed in Ansan Danwon compared to a control community after the disaster. We could not exclude the possibility that other events influenced changes in the prescription rates of psychotropic medications during the study period. Pharmaco-epidemiological studies on psychotropic medication prescription after a disaster provide important information about population-level mental health. Our results suggest that the Sewol Ferry disaster exerted a harmful effect on the mental health status of the affected community. Copyright © 2017 Elsevier B.V. All rights reserved.

Post-market drug evaluation research training capacity in Canada: an environmental scan of Canadian educational institutions.

PubMed

Wiens, Matthew O; Soon, Judith A; MacLeod, Stuart M; Sharma, Sunaina; Patel, Anik

2014-01-01

Ongoing efforts by Health Canada intended to modernize the legislation and regulation of pharmaceuticals will help improve the safety and effectiveness of drug products. It will be imperative to ensure that comprehensive and specialized training sites are available to train researchers to support the regulation of therapeutic products. The objective of this educational institution inventory was to conduct an environmental scan of educational institutions in Canada able to train students in areas of post-market drug evaluation research. A systematic web-based environmental scan of Canadian institutions was conducted. The website of each university was examined for potential academic programs. Six core programmatic areas were determined a priori as necessary to train competent post-market drug evaluation researchers. These included biostatistics, epidemiology, pharmacoepidemiology, health economics or pharmacoeconomics, pharmacogenetics or pharmacogenomics and patient safety/pharmacovigilance. Twenty-three academic institutions were identified that had the potential to train students in post-market drug evaluation research. Overall, 23 institutions taught courses in epidemiology, 22 in biostatistics, 17 in health economics/pharmacoeconomics, 5 in pharmacoepidemiology, 5 in pharmacogenetics/pharmacogenomics, and 3 in patient safety/pharmacovigilance. Of the 23 institutions, only the University of Ottawa offered six core courses. Two institutions offered five, seven offered four and the remaining 14 offered three or fewer. It is clear that some institutions may offer programs not entirely reflected in the nomenclature used for this review. As Heath Canada moves towards a more progressive licensing framework, augmented training to increase research capacity and expertise in drug safety and effectiveness is timely and necessary.

Agreement between patients' self-report and medical records for vaccination: the PGRx database.

PubMed

Grimaldi-Bensouda, Lamiae; Aubrun, Elodie; Leighton, Pamela; Benichou, Jacques; Rossignol, Michel; Abenhaim, Lucien

2013-03-01

Patients' self-reported vaccine exposure (PS) may be subject to memory errors and other biases. Physicians' prescription records and other medical records (MR) do not capture noncompliance with vaccination. This study compared PS with MR for influenza, 23-valent pneumococcal, and human papillomavirus (HPV) vaccines. The Pharmacoepidemiologic General Research Extension (PGRx) database uses a network of over 300 general practitioners across France, who systematically recruit an age- and sex-stratified sample of patients (≥ 14 years old), without reference to their diagnoses or prescriptions. Patients received a structured telephone interview, combined with an interview guide listing vaccines commonly given. Patients' self-reported vaccination in the 3 years before their recruitment was compared with medical records kept by the physician or the patient. Concordance between PS and MR was assessed for 7613 patients for whom both sources of information were available. Agreement within 3 years before the recruitment date was substantial for influenza vaccines (prevalence and bias-adjusted kappa [PABAK] = 0.74, sensitivity PS relative to MR 81.5%) and high for 23-valent pneumococcal vaccines (PABAK = 0.98, sensitivity PS 49.6) and HPV vaccines (PABAK = 0.92, sensitivity PS 91.6). In adjusted analyses, agreement varied with sociodemographic and health-related factors, particularly for influenza and 23-valent pneumococcal vaccines. The PGRx method for drug exposure assessment is a new tool in pharmacoepidemiology that shows substantial to high agreement between PS and MR for exposure to various vaccines. Our finding of high agreement between PS and MR for HPV vaccination status in young women is a significant addition to the literature. Copyright © 2013 John Wiley & Sons, Ltd.

Association between knowledge about levonorgestrel emergency contraception and the risk of ectopic pregnancy following levonorgestrel emergency contraception failure: a comparative survey.

PubMed

Zhang, Duo; Yan, Ming-Xing; Ma, Jue; Xia, Wei; Xue, Rui-Hong; Sun, Jing; Zhang, Jian

2016-08-01

To study the association between knowledge about levonorgestrel emergency contraception (LNG-EC) and the risk of ectopic pregnancy (EP) following LNG-EC failure. This study included 600 women who had visited the hospital with LNG-EC failure. Of these, 300 with EP and 300 with intrauterine pregnancy (IUP) were recruited to the EP group and IUP group respectively. The participants were interviewed face-to-face using a standardized questionnaire. Pearson's chi-square tests and t-test were used to compare the sociodemographic characteristics, reproductive and gynecological history, surgical history, previous contraceptive experience, and answers to 10 questions concerning the knowledge about LNG-EC. Those who gave incorrect answers to the question regarding the basic mechanism and specific method of levonorgestrel emergency contraceptive pills (LNG-ECPs) were at a higher risk of EP after LNG-EC failure. Women who did not strictly follow instructions or advice from healthcare professionals were more likely to subsequently experience EP (p < 10(-4) ). Women with LNG-EC failure reported friends/peers, TV, and Internet as the main sources of information. No difference was observed with regard to the sources of knowledge on LNG-EC (p = 0.07). The results illustrate the importance of strictly following the doctor's guidance or drug instructions when using LNG-ECPs. The media should be used to disseminate information about responsible EC, and pharmacy staff should receive regular educational training sessions in this regard. © 2016 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd. © 2016 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd.

Controlling for Frailty in Pharmacoepidemiologic Studies of Older Adults: Validation of an Existing Medicare Claims-based Algorithm.

PubMed

Cuthbertson, Carmen C; Kucharska-Newton, Anna; Faurot, Keturah R; Stürmer, Til; Jonsson Funk, Michele; Palta, Priya; Windham, B Gwen; Thai, Sydney; Lund, Jennifer L

2018-07-01

Frailty is a geriatric syndrome characterized by weakness and weight loss and is associated with adverse health outcomes. It is often an unmeasured confounder in pharmacoepidemiologic and comparative effectiveness studies using administrative claims data. Among the Atherosclerosis Risk in Communities (ARIC) Study Visit 5 participants (2011-2013; n = 3,146), we conducted a validation study to compare a Medicare claims-based algorithm of dependency in activities of daily living (or dependency) developed as a proxy for frailty with a reference standard measure of phenotypic frailty. We applied the algorithm to the ARIC participants' claims data to generate a predicted probability of dependency. Using the claims-based algorithm, we estimated the C-statistic for predicting phenotypic frailty. We further categorized participants by their predicted probability of dependency (<5%, 5% to <20%, and ≥20%) and estimated associations with difficulties in physical abilities, falls, and mortality. The claims-based algorithm showed good discrimination of phenotypic frailty (C-statistic = 0.71; 95% confidence interval [CI] = 0.67, 0.74). Participants classified with a high predicted probability of dependency (≥20%) had higher prevalence of falls and difficulty in physical ability, and a greater risk of 1-year all-cause mortality (hazard ratio = 5.7 [95% CI = 2.5, 13]) than participants classified with a low predicted probability (<5%). Sensitivity and specificity varied across predicted probability of dependency thresholds. The Medicare claims-based algorithm showed good discrimination of phenotypic frailty and high predictive ability with adverse health outcomes. This algorithm can be used in future Medicare claims analyses to reduce confounding by frailty and improve study validity.

Evaluation of linear classifiers on articles containing pharmacokinetic evidence of drug-drug interactions.

PubMed

Kolchinsky, A; Lourenço, A; Li, L; Rocha, L M

2013-01-01

Drug-drug interaction (DDI) is a major cause of morbidity and mortality. DDI research includes the study of different aspects of drug interactions, from in vitro pharmacology, which deals with drug interaction mechanisms, to pharmaco-epidemiology, which investigates the effects of DDI on drug efficacy and adverse drug reactions. Biomedical literature mining can aid both kinds of approaches by extracting relevant DDI signals from either the published literature or large clinical databases. However, though drug interaction is an ideal area for translational research, the inclusion of literature mining methodologies in DDI workflows is still very preliminary. One area that can benefit from literature mining is the automatic identification of a large number of potential DDIs, whose pharmacological mechanisms and clinical significance can then be studied via in vitro pharmacology and in populo pharmaco-epidemiology. We implemented a set of classifiers for identifying published articles relevant to experimental pharmacokinetic DDI evidence. These documents are important for identifying causal mechanisms behind putative drug-drug interactions, an important step in the extraction of large numbers of potential DDIs. We evaluate performance of several linear classifiers on PubMed abstracts, under different feature transformation and dimensionality reduction methods. In addition, we investigate the performance benefits of including various publicly-available named entity recognition features, as well as a set of internally-developed pharmacokinetic dictionaries. We found that several classifiers performed well in distinguishing relevant and irrelevant abstracts. We found that the combination of unigram and bigram textual features gave better performance than unigram features alone, and also that normalization transforms that adjusted for feature frequency and document length improved classification. For some classifiers, such as linear discriminant analysis (LDA), proper dimensionality reduction had a large impact on performance. Finally, the inclusion of NER features and dictionaries was found not to help classification.

A sudden and unprecedented increase in low dose naltrexone (LDN) prescribing in Norway. Patient and prescriber characteristics, and dispense patterns. A drug utilization cohort study.

PubMed

Raknes, Guttorm; Småbrekke, Lars

2017-02-01

Following a TV documentary in 2013, there was a tremendous increase in low dose naltrexone (LDN) use in a wide range of unapproved indications in Norway. We aim to describe the extent of this sudden and unprecedented increase in LDN prescribing, to characterize patients and LDN prescribers, and to estimate LDN dose sizes. LDN prescriptions recorded in the Norwegian Prescription Database (NorPD) in 2013 and 2014, and sales data not recorded in NorPD from the only Norwegian LDN manufacturer were included in the study. According to NorPD, 15 297 patients (0.3% of population) collected at least one LDN prescription. The actual number of users was higher as at least 23% of total sales were not recorded in NorPD. After an initial wave, there was a steady stream of new and persistent users throughout the study period. Median patient age was 52 years, and 74% of patients were female. Median daily dose was 3.7 mg. Twenty percent of all doctors and 71% of general medicine practitioners registered in Norway in 2014 prescribed LDN at least once. The TV documentary on LDN in Norway was followed by a large increase in LDN prescribing, and the proportion of LDN users went from an insignificant number to 0.3% of the population. There was a high willingness to use and prescribe off label despite limited evidence. Observed median LDN dose, and age and gender distribution were as expected in typical LDN using patients. © 2016 The Authors. Pharmacoepidemiology and Drug Safety Published by John Wiley & Sons Ltd. © 2016 The Authors. Pharmacoepidemiology and Drug Safety Published by John Wiley & Sons Ltd.

Low-dose naltrexone and opioid consumption: a drug utilization cohort study based on data from the Norwegian prescription database.

PubMed

Raknes, Guttorm; Småbrekke, Lars

2017-06-01

Low-dose naltrexone (LDN) is used in a wide range of conditions, including chronic pain and fibromyalgia. Because of the opioid antagonism of naltrexone, LDN users are probably often warned against concomitant use with opioids. In this study, based on data from the Norwegian prescription database, we examine changes in opioid consumption after starting LDN therapy. We included all Norwegian patients (N = 3775) with at least one recorded LDN prescription in 2013 and at least one dispensed opioid prescription during the 365 days preceding the first LDN prescription. We allocated the patients into three subgroups depending on the number of collected LDN prescriptions and recorded the number of defined daily doses (DDDs) on collected prescriptions on opioids, nonsteroidal anti-inflammatory drugs and other analgesics and antipyretics from the same patients. Among the patients collecting ≥4 LDN prescriptions, annual average opioid consumption was reduced by 41 DDDs per person (46%) compared with that of the previous year. The reduction was 12 DDDs per person (15%) among users collecting two to three prescriptions and no change among those collecting only one LDN prescription. We observed no increase in the number of DDDs in nonsteroidal anti-inflammatory drugs or other analgesics and antipyretics corresponding to the decrease in opioid use. Possibly, LDN users avoided opioids because of warnings on concomitant use or the patients continuing on LDN were less opioid dependent than those terminating LDN. Therapeutic effects of LDN contributing to lower opioid consumption cannot be ruled out. © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd. © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd.

Quantification of missing prescriptions in commercial claims databases: results of a cohort study.

PubMed

Cepeda, Maria Soledad; Fife, Daniel; Denarié, Michel; Bradford, Dan; Roy, Stephanie; Yuan, Yingli

2017-04-01

This study aims to quantify the magnitude of missed dispensings in commercial claims databases. A retrospective cohort study has been used linking PharMetrics, a commercial claims database, to a prescription database (LRx) that captures pharmacy dispensings independently of payment method, including cash transactions. We included adults with dispensings for opioids, diuretics, antiplatelet medications, or anticoagulants. To determine the degree of capture of dispensings, we calculated the number of subjects with the following: (1) same number of dispensings in both databases; (2) at least one dispensing, but not all dispensings, missed in PharMetrics; and (3) all dispensings missing in PharMetrics. Similar analyses were conducted using dispensings as the unit of analysis. To assess whether a dispensing in LRx was in PharMetrics, the dispensing in PharMetrics had to be for the same medication class and within ±7 days in LRx. A total of 1 426 498 subjects were included. Overall, 68% of subjects had the same number of dispensings in both databases. In 13% of subjects, PharMetrics identified ≥1 dispensing but also missed ≥1 dispensing. In 19% of the subjects, PharMetrics missed all the dispensings. Taking dispensings as the unit of analysis, 25% of the dispensings present in LRx were not captured in PharMetrics. These patterns were similar across all four classes of medications. Of the dispensings missing in PharMetrics, 48% involved a subject who had >1 health insurance plan. Commercial claims databases provide an incomplete picture of all prescriptions dispensed to patients. The lack of capture goes beyond cash transactions and potentially introduces substantial misclassification bias. © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd. © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd.

Healthcare databases in Europe for studying medicine use and safety during pregnancy.

PubMed

Charlton, Rachel A; Neville, Amanda J; Jordan, Sue; Pierini, Anna; Damase-Michel, Christine; Klungsøyr, Kari; Andersen, Anne-Marie Nybo; Hansen, Anne Vinkel; Gini, Rosa; Bos, Jens H J; Puccini, Aurora; Hurault-Delarue, Caroline; Brooks, Caroline J; de Jong-van den Berg, Lolkje T W; de Vries, Corinne S

2014-06-01

The aim of this study was to describe a number of electronic healthcare databases in Europe in terms of the population covered, the source of the data captured and the availability of data on key variables required for evaluating medicine use and medicine safety during pregnancy. A sample of electronic healthcare databases that captured pregnancies and prescription data was selected on the basis of contacts within the EUROCAT network. For each participating database, a database inventory was completed. Eight databases were included, and the total population covered was 25 million. All databases recorded live births, seven captured stillbirths and five had full data available on spontaneous pregnancy losses and induced terminations. In six databases, data were usually available to determine the date of the woman's last menstrual period, whereas in the remainder, algorithms were needed to establish a best estimate for at least some pregnancies. In seven databases, it was possible to use data recorded in the databases to identify pregnancies where the offspring had a congenital anomaly. Information on confounding variables was more commonly available in databases capturing data recorded by primary-care practitioners. All databases captured maternal co-prescribing and a measure of socioeconomic status. This study suggests that within Europe, electronic healthcare databases may be valuable sources of data for evaluating medicine use and safety during pregnancy. The suitability of a particular database, however, will depend on the research question, the type of medicine to be evaluated, the prevalence of its use and any adverse outcomes of interest. © 2014 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd. © 2014 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd.

The quality of Medicaid and Medicare data obtained from CMS and its contractors: implications for pharmacoepidemiology.

PubMed

Leonard, Charles E; Brensinger, Colleen M; Nam, Young Hee; Bilker, Warren B; Barosso, Geralyn M; Mangaali, Margaret J; Hennessy, Sean

2017-04-26

Administrative claims of United States Centers for Medicare and Medicaid Services (CMS) beneficiaries have long been used in non-experimental research. While CMS performs in-house checks of these claims, little is known of their quality for conducting pharmacoepidemiologic research. We performed exploratory analyses of the quality of Medicaid and Medicare data obtained from CMS and its contractors. Our study population consisted of Medicaid beneficiaries (with and without dual coverage by Medicare) from California, Florida, New York, Ohio, and Pennsylvania. We obtained and compiled 1999-2011 data from these state Medicaid programs (constituting about 38% of nationwide Medicaid enrollment), together with corresponding national Medicare data for dually-enrolled beneficiaries. This descriptive study examined longitudinal patterns in: dispensed prescriptions by state, by quarter; and inpatient hospitalizations by federal benefit, state, and age group. We further examined discrepancies between demographic characteristics and disease states, in particular frequencies of pregnancy complications among men and women beyond childbearing age, and prostate cancers among women. Dispensed prescriptions generally increased steadily and consistently over time, suggesting that these claims may be complete. A commercially-available National Drug Code lookup database was able to identify the dispensed drug for 95.2-99.4% of these claims. Because of co-coverage by Medicare, Medicaid data appeared to miss a substantial number of hospitalizations among beneficiaries ≥ 45 years of age. Pregnancy complication diagnoses were rare in males and in females ≥ 60 years of age, and prostate cancer diagnoses were rare in females. CMS claims from five large states obtained directly from CMS and its contractors appeared to be of high quality. Researchers using Medicaid data to study hospital outcomes should obtain supplemental Medicare data on dual enrollees, even for non-elders. Not applicable.

Positive predictive value of a case definition for diabetes mellitus using automated administrative health data in children and youth exposed to antipsychotic drugs or control medications: a Tennessee Medicaid study.

PubMed

Bobo, William V; Cooper, William O; Stein, C Michael; Olfson, Mark; Mounsey, Jackie; Daugherty, James; Ray, Wayne A

2012-08-24

We developed and validated an automated database case definition for diabetes in children and youth to facilitate pharmacoepidemiologic investigations of medications and the risk of diabetes. The present study was part of an in-progress retrospective cohort study of antipsychotics and diabetes in Tennessee Medicaid enrollees aged 6-24 years. Diabetes was identified from diabetes-related medical care encounters: hospitalizations, outpatient visits, and filled prescriptions. The definition required either a primary inpatient diagnosis or at least two other encounters of different types, most commonly an outpatient diagnosis with a prescription. Type 1 diabetes was defined by insulin prescriptions with at most one oral hypoglycemic prescription; other cases were considered type 2 diabetes. The definition was validated for cohort members in the 15 county region geographically proximate to the investigators. Medical records were reviewed and adjudicated for cases that met the automated database definition as well as for a sample of persons with other diabetes-related medical care encounters. The study included 64 cases that met the automated database definition. Records were adjudicated for 46 (71.9%), of which 41 (89.1%) met clinical criteria for newly diagnosed diabetes. The positive predictive value for type 1 diabetes was 80.0%. For type 2 and unspecified diabetes combined, the positive predictive value was 83.9%. The estimated sensitivity of the definition, based on adjudication for a sample of 30 cases not meeting the automated database definition, was 64.8%. These results suggest that the automated database case definition for diabetes may be useful for pharmacoepidemiologic studies of medications and diabetes.

Positive predictive value of a case definition for diabetes mellitus using automated administrative health data in children and youth exposed to antipsychotic drugs or control medications: a Tennessee Medicaid study

PubMed Central

2012-01-01

Background We developed and validated an automated database case definition for diabetes in children and youth to facilitate pharmacoepidemiologic investigations of medications and the risk of diabetes. Methods The present study was part of an in-progress retrospective cohort study of antipsychotics and diabetes in Tennessee Medicaid enrollees aged 6–24 years. Diabetes was identified from diabetes-related medical care encounters: hospitalizations, outpatient visits, and filled prescriptions. The definition required either a primary inpatient diagnosis or at least two other encounters of different types, most commonly an outpatient diagnosis with a prescription. Type 1 diabetes was defined by insulin prescriptions with at most one oral hypoglycemic prescription; other cases were considered type 2 diabetes. The definition was validated for cohort members in the 15 county region geographically proximate to the investigators. Medical records were reviewed and adjudicated for cases that met the automated database definition as well as for a sample of persons with other diabetes-related medical care encounters. Results The study included 64 cases that met the automated database definition. Records were adjudicated for 46 (71.9%), of which 41 (89.1%) met clinical criteria for newly diagnosed diabetes. The positive predictive value for type 1 diabetes was 80.0%. For type 2 and unspecified diabetes combined, the positive predictive value was 83.9%. The estimated sensitivity of the definition, based on adjudication for a sample of 30 cases not meeting the automated database definition, was 64.8%. Conclusion These results suggest that the automated database case definition for diabetes may be useful for pharmacoepidemiologic studies of medications and diabetes. PMID:22920280

Cheminformatics-aided pharmacovigilance: application to Stevens-Johnson Syndrome

PubMed Central

Low, Yen S; Caster, Ola; Bergvall, Tomas; Fourches, Denis; Zang, Xiaoling; Norén, G Niklas; Rusyn, Ivan; Edwards, Ralph

2016-01-01

Objective Quantitative Structure-Activity Relationship (QSAR) models can predict adverse drug reactions (ADRs), and thus provide early warnings of potential hazards. Timely identification of potential safety concerns could protect patients and aid early diagnosis of ADRs among the exposed. Our objective was to determine whether global spontaneous reporting patterns might allow chemical substructures associated with Stevens-Johnson Syndrome (SJS) to be identified and utilized for ADR prediction by QSAR models. Materials and Methods Using a reference set of 364 drugs having positive or negative reporting correlations with SJS in the VigiBase global repository of individual case safety reports (Uppsala Monitoring Center, Uppsala, Sweden), chemical descriptors were computed from drug molecular structures. Random Forest and Support Vector Machines methods were used to develop QSAR models, which were validated by external 5-fold cross validation. Models were employed for virtual screening of DrugBank to predict SJS actives and inactives, which were corroborated using knowledge bases like VigiBase, ChemoText, and MicroMedex (Truven Health Analytics Inc, Ann Arbor, Michigan). Results We developed QSAR models that could accurately predict if drugs were associated with SJS (area under the curve of 75%–81%). Our 10 most active and inactive predictions were substantiated by SJS reports (or lack thereof) in the literature. Discussion Interpretation of QSAR models in terms of significant chemical descriptors suggested novel SJS structural alerts. Conclusions We have demonstrated that QSAR models can accurately identify SJS active and inactive drugs. Requiring chemical structures only, QSAR models provide effective computational means to flag potentially harmful drugs for subsequent targeted surveillance and pharmacoepidemiologic investigations. PMID:26499102

[Lessons from a heart valve prosthesis controversy].

PubMed

Vandenbroucke, J P; Grobbee, D E

1998-07-18

Two lessons are to be learnt from the Björk-Shiley heart valve prosthesis tragedy. In the first place pharmacoepidemiologic studies are seriously hampered by recent privacy legislation. Individual patients carrying such a prosthesis cannot be traced and advised as to their health risks any more, because their legal autonomy has to be respected. This is clearly not to their advantage. In the second place the atmosphere of marketing and litigation and the increasing dependency of researchers on money from sources with conflicting interests is not conducive to a well-informed and balanced judgement of the epidemiological evidence of safety and efficacy of medical treatments.

Understanding and Avoiding Immortal-Time Bias in Gastrointestinal Observational Research.

PubMed

Targownik, Laura E; Suissa, Samy

2015-12-01

Pharmacoepidemiologic analyses, in which observational data is interrogated to evaluate relationships between patterns of drug use and both beneficial and adverse outcomes, are being increasingly used in the study of inflammatory bowel disease. However, the results of many of these analyses may be corrupted by the presence of immortal person-time bias, an analytic error which can result in an overestimation of the benefits of medical therapy. In this report, we will describe immortal person-time bias, explain the mechanism through which it confers a false benefit, and guide the reader in how to identify this source of bias in the medical literature.

Pharmacoepidemiologic investigation of clonazepam relative clearance by mixed-effect modeling using routine clinical pharmacokinetic data in Japanese patients.

PubMed

Yukawa, Eiji; Satou, Masayasu; Nonaka, Toshiharu; Yukawa, Miho; Ohdo, Shigehiro; Higuchi, Shun; Kuroda, Takeshi; Goto, Yoshinobu

2002-01-01

The effects of drug-drug interactions on clonazepam clearance were examined through a retrospective analysis of serum concentration data from pediatric and adult epileptic patients. Patients received clonazepam as monotherapy or in combination with other antiepileptic drugs. A total of 259 serum clonazepam concentrations gathered from 137 patients were used in a population analysis of drug-drug interactions on clonazepam clearance. Data were analyzed using a nonlinear mixed-effects modeling (NONMEM) technique. The final model describing clonazepam clearance was CL = 152 x TBW(-0.181) x DIF, where CL is clearance (ml/kg/h), TBWis total body weight (kg), and DIF (drug interaction factor) is a scaling factor for concomitant medication with a value of 1 for patients on clonazepam monotherapy, 1.18 for those patients receiving concomitant administration of clonazepam and one antiepileptic drug (carbamazepine or valproic acid), and 2.12 x TBW(-0.119) for those patients receiving concomitant administration of clonazepam and more than two antiepileptic drugs. Clonazepam clearance decreased in a weight-related fashion in children, with minimal changes observed in adults. Concomitant administration of clonazepam and carbamazepine resulted in a 22% increase in clonazepam clearance. Concomitant administration of clonazepam and valproic acid resulted in a 12% increase in clonazepam clearance. Concomitant administration of clonazepam with two or more antiepileptic drugs resulted in a 23% to 75% increase in clonazepam clearance.

Real-World Evidence: What It Is and What It Can Tell Us According to the International Society for Pharmacoepidemiology (ISPE) Comparative Effectiveness Research (CER) Special Interest Group (SIG).

PubMed

Yuan, Hongbo; Ali, M Sanni; Brouwer, Emily S; Girman, Cynthia J; Guo, Jeff J; Lund, Jennifer L; Patorno, Elisabetta; Slaughter, Jonathan L; Wen, Xuerong; Bennett, Dimitri

2018-05-07

On December 8, 2016, the New England Journal of Medicine published a sounding board on Real World Evidence (RWE) 1 by the US Food and Drug Administration (FDA) leadership. While the value of RWE based on nonrandomized observational studies was appreciated, such as for hypothesis generating, safety, and measuring quality in healthcare delivery, the authors expressed concerns on the quality of data sources and the ability of methodologies to control for confounding. In response, we offer a few considerations regarding these concerns. © 2018, The American Society for Clinical Pharmacology and Therapeutics.

A prediction model-based algorithm for computer-assisted database screening of adverse drug reactions in the Netherlands.

PubMed

Scholl, Joep H G; van Hunsel, Florence P A M; Hak, Eelko; van Puijenbroek, Eugène P

2018-02-01

The statistical screening of pharmacovigilance databases containing spontaneously reported adverse drug reactions (ADRs) is mainly based on disproportionality analysis. The aim of this study was to improve the efficiency of full database screening using a prediction model-based approach. A logistic regression-based prediction model containing 5 candidate predictors was developed and internally validated using the Summary of Product Characteristics as the gold standard for the outcome. All drug-ADR associations, with the exception of those related to vaccines, with a minimum of 3 reports formed the training data for the model. Performance was based on the area under the receiver operating characteristic curve (AUC). Results were compared with the current method of database screening based on the number of previously analyzed associations. A total of 25 026 unique drug-ADR associations formed the training data for the model. The final model contained all 5 candidate predictors (number of reports, disproportionality, reports from healthcare professionals, reports from marketing authorization holders, Naranjo score). The AUC for the full model was 0.740 (95% CI; 0.734-0.747). The internal validity was good based on the calibration curve and bootstrapping analysis (AUC after bootstrapping = 0.739). Compared with the old method, the AUC increased from 0.649 to 0.740, and the proportion of potential signals increased by approximately 50% (from 12.3% to 19.4%). A prediction model-based approach can be a useful tool to create priority-based listings for signal detection in databases consisting of spontaneous ADRs. © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd.

Prevalence, incidence, indication, and choice of antidepressants in patients with and without chronic kidney disease: a matched cohort study in UK Clinical Practice Research Datalink.

PubMed

Iwagami, Masao; Tomlinson, Laurie A; Mansfield, Kathryn E; McDonald, Helen I; Smeeth, Liam; Nitsch, Dorothea

2017-07-01

People with chronic kidney disease (CKD) have an increased prevalence of depression, anxiety, and neuropathic pain. We examined prevalence, incidence, indication for, and choice of antidepressants among patients with and without CKD. Using the UK Clinical Practice Research Datalink, we identified patients with CKD (two measurements of estimated glomerular filtration rate < 60 mL/min/1.73m 2 for ≥3 months) between April 2004 and March 2014. We compared those with CKD to a general population cohort without CKD (matched on age, sex, general practice, and calendar time [index date]). We identified any antidepressant prescribing in the six months prior to index date (prevalence), the first prescription after index date among non-prevalent users (incidence), and recorded diagnoses (indication). We compared antidepressant choice between patients with and without CKD among patients with a diagnosis of depression. There were 242 349 matched patients (median age 76 [interquartile range 70-82], male 39.3%) with and without CKD. Prevalence of antidepressant prescribing was 16.3 and 11.9%, and incidence was 57.2 and 42.4/1000 person-years, in patients with and without CKD, respectively. After adjusting for confounders, CKD remained associated with higher prevalence and incidence of antidepressant prescription. Regardless of CKD status, selective serotonin reuptake inhibitors were predominantly prescribed for depression or anxiety, while tricyclic antidepressants were prescribed for neuropathic pain or other reasons. Antidepressant choice was similar in depressed patients with and without CKD. The rate of antidepressant prescribing was nearly one and a half times higher among people with CKD than in the general population. © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd. © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd.

Registries in European post-marketing surveillance: a retrospective analysis of centrally approved products, 2005-2013.

PubMed

Bouvy, Jacoline C; Blake, Kevin; Slattery, Jim; De Bruin, Marie L; Arlett, Peter; Kurz, Xavier

2017-12-01

Regulatory agencies and other stakeholders increasingly rely on data collected through registries to support their decision-making. Data from registries are a cornerstone of post-marketing surveillance for monitoring the use of medicines in clinical practice. This study was aimed at gaining further insight into the European Medicines Agency's (EMA) requests for new registries and registry studies using existing registries and to review the experience gained in their conduct. European Public Assessment Reports were consulted to identify products for which a request for a registry was made as a condition of the marketing authorisation. All centrally authorised products that received a positive opinion of the EMA Committee for Medicinal Products for Human Use between 1 January 2005 and 31 December 2013 were included. Data regarding registry design and experiences were collected from EMA electronic record keeping systems. Of 392 products that received a positive Committee for Medicinal Products for Human Use opinion during 2005-2013, 31 registries were requested for 30 products in total. Sixty-five percent were product registries whereas 35% were disease registries and 71% of the registries had a primary safety objective. Most commonly reported issues with registries were delayed time to start and low patient accrual rates. The delays found in getting new registries up and running support the need to improve the timeliness of data collection in the post-marketing setting. Methodological challenges met in conducting this study highlighted the need for a clarification of definitions and epidemiological concepts around patient registries. The results will inform the EMA Patient Registry initiative to support use of existing patient registries for the post-authorisation benefit-risk monitoring of medicinal products. © 2017 Commonwealth of Australia. Pharmacoepidemiology & Drug Safety © 2017 John Wiley & Sons, Ltd. © 2017 Commonwealth of Australia. Pharmacoepidemiology & Drug Safety © 2017 John Wiley & Sons, Ltd.

Prescription duration and treatment episodes in oral glucocorticoid users: application of the parametric waiting time distribution.

PubMed

Laugesen, Kristina; Støvring, Henrik; Hallas, Jesper; Pottegård, Anton; Jørgensen, Jens Otto Lunde; Sørensen, Henrik Toft; Petersen, Irene

2017-01-01

Glucocorticoids are widely used medications. In many pharmacoepidemiological studies, duration of individual prescriptions and definition of treatment episodes are important issues. However, many data sources lack this information. We aimed to estimate duration of individual prescriptions for oral glucocorticoids and to describe continuous treatment episodes using the parametric waiting time distribution. We used Danish nationwide registries to identify all prescriptions for oral glucocorticoids during 1996-2014. We applied the parametric waiting time distribution to estimate duration of individual prescriptions each year by estimating the 80th, 90th, 95th and 99th percentiles for the interarrival distribution. These corresponded to the time since last prescription during which 80%, 90%, 95% and 99% of users presented a new prescription for redemption. We used the Kaplan-Meier survival function to estimate length of first continuous treatment episodes by assigning estimated prescription duration to each prescription and thereby create treatment episodes from overlapping prescriptions. We identified 5,691,985 prescriptions issued to 854,429 individuals of whom 351,202 (41%) only redeemed 1 prescription in the whole study period. The 80th percentile for prescription duration ranged from 87 to 120 days, the 90th percentile from 116 to 150 days, the 95th percentile from 147 to 181 days, and the 99th percentile from 228 to 259 days during 1996-2014. Based on the 80th, 90th, 95th and 99th percentiles of prescription duration, the median length of continuous treatment was 113, 141, 170 and 243 days, respectively. Our method and results may provide an important framework for future pharmacoepidemiological studies. The choice of which percentile of the interarrival distribution to apply as prescription duration has an impact on the level of misclassification. Use of the 80th percentile provides a measure of drug exposure that is specific, while the 99th percentile provides a sensitive measure.

Can social media data lead to earlier detection of drug-related adverse events?

PubMed

Duh, Mei Sheng; Cremieux, Pierre; Audenrode, Marc Van; Vekeman, Francis; Karner, Paul; Zhang, Haimin; Greenberg, Paul

2016-12-01

To compare the patient characteristics and the inter-temporal reporting patterns of adverse events (AEs) for atorvastatin (Lipitor ® ) and sibutramine (Meridia ® ) in social media (AskaPatient.com) versus the FDA Adverse Event Reporting System (FAERS). We identified clinically important AEs associated with atorvastatin (muscle pain) and sibutramine (cardiovascular AEs), compared their patterns in social media postings versus FAERS and used Granger causality tests to assess whether social media postings were useful in forecasting FAERS reports. We analyzed 998 and 270 social media postings between 2001 and 2014, 69 003 and 7383 FAERS reports between 1997 and 2014 for atorvastatin and sibutramine, respectively. Social media reporters were younger (atorvastatin: 53.9 vs. 64.0 years, p < 0.001; sibutramine: 36.8 vs. 43.8 years, p < 0.001). Social media reviews contained fewer serious AEs (atorvastatin, pain: 2.5% vs. 38.2%; sibutramine, cardiovascular issues: 7.9% vs. 63.0%; p < 0.001 for both) and concentrated on fewer types of AEs (proportion comprising the top 20 AEs: atorvastatin, 88.7% vs. 55.4%; sibutramine, 86.3% vs. 65.4%) compared with FAERS. While social media sibutramine reviews mentioning cardiac issues helped predict those in FAERS 11 months later (p < 0.001), social media atorvastatin reviews did not help predict FAERS reports. Social media AE reporters were younger and focused on less-serious and fewer types of AEs than FAERS reporters. The potential for social media to provide earlier indications of AEs compared with FAERS is uncertain. Our findings highlight some of the promises and limitations of online social media versus conventional pharmacovigilance sources and the need for careful interpretation of the results. © 2016 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd. © 2016 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd.

Increased availability of paracetamol in Sweden and incidence of paracetamol poisoning: using laboratory data to increase validity of a population-based registry study.

PubMed

Gedeborg, Rolf; Svennblad, Bodil; Holm, Lennart; Sjögren, Hans; Bardage, Carola; Personne, Mark; Sjöberg, Gunilla; Feltelius, Nils; Zethelius, Björn

2017-05-01

To estimate the incidence trend and outcome of paracetamol poisoning, in relation to increased availability of paracetamol from non-pharmacy outlets in 2009. Patients' serum paracetamol results over 14 years (2000-2013) from 20 (out of 21) regions in Sweden were linked to national registers of hospital care, cause of death, and prescriptions. Paracetamol poisonings were defined by serum paracetamol levels, hospital diagnoses, or cause of death. The change in incidence of poisonings following increased availability of paracetamol was analysed by using segmental regression of time series. Of the 12 068 paracetamol poisonings, 85% were classified as intentional self-harm. Following increased availability from non-pharmacy outlets, there was a 40.5% increase in the incidence of paracetamol poisoning, from 11.5/100 000 in 2009 to 16.2/100 000 in 2013. Regression analyses indicated a change in the trend (p < 0.0001) but not an immediate jump in the incidence (p = 0.5991) following the increased availability. Adjusting for trends in hospital episodes for self-harm, suicides, and the sales volume of paracetamol did not influence the result. All-cause mortality at 30 days (3.2%) did not change over time. The incidence of paracetamol poisoning in Sweden has increased since 2009, contrasting the decreased incidence in the period of 2007-2009. The change in trend was temporally associated with the introduction of availability of paracetamol from non-pharmacy outlets but did not appear to be related to sales volume of paracetamol or general trends in self-harm or suicides. © 2017 Commonwealth of Australia. Pharmacoepidemiology and Drug Safety © 2017 John Wiley & Sons, Ltd. © 2017 Commonwealth of Australia. Pharmacoepidemiology and Drug Safety © 2017 John Wiley & Sons, Ltd.

Monitoring safety in a phase III real-world effectiveness trial: use of novel methodology in the Salford Lung Study.

PubMed

Collier, Sue; Harvey, Catherine; Brewster, Jill; Bakerly, Nawar Diar; Elkhenini, Hanaa F; Stanciu, Roxana; Williams, Claire; Brereton, Jacqui; New, John P; McCrae, John; McCorkindale, Sheila; Leather, David

2017-03-01

The Salford Lung Study (SLS) programme, encompassing two phase III pragmatic randomised controlled trials, was designed to generate evidence on the effectiveness of a once-daily treatment for asthma and chronic obstructive pulmonary disease in routine primary care using electronic health records. The objective of this study was to describe and discuss the safety monitoring methodology and the challenges associated with ensuring patient safety in the SLS. Refinements to safety monitoring processes and infrastructure are also discussed. The study results are outside the remit of this paper. The results of the COPD study were published recently and a more in-depth exploration of the safety results will be the subject of future publications. The SLS used a linked database system to capture relevant data from primary care practices in Salford and South Manchester, two university hospitals and other national databases. Patient data were collated and analysed to create daily summaries that were used to alert a specialist safety team to potential safety events. Clinical research teams at participating general practitioner sites and pharmacies also captured safety events during routine consultations. Confidence in the safety monitoring processes over time allowed the methodology to be refined and streamlined without compromising patient safety or the timely collection of data. The information technology infrastructure also allowed additional details of safety information to be collected. Integration of multiple data sources in the SLS may provide more comprehensive safety information than usually collected in standard randomised controlled trials. Application of the principles of safety monitoring methodology from the SLS could facilitate safety monitoring processes for future pragmatic randomised controlled trials and yield important complementary safety and effectiveness data. © 2016 The Authors Pharmacoepidemiology and Drug Safety Published by John Wiley & Sons Ltd. © 2016 The Authors Pharmacoepidemiology and Drug Safety Published by John Wiley & Sons Ltd.

Clinical Use of Mood Stabilizers With Antidepressants in Asia: Report From the Research on Asian Psychotropic Prescription Patterns for Antidepressants (REAP-AD) Projects in 2004 and 2013.

PubMed

Rajaratnam, Kamini; Xiang, Yu-Tao; Tripathi, Adarsh; Chiu, Helen F K; Si, Tian-Mei; Chee, Kok-Yoon; Avasthi, Ajit; Grover, Sandeep; Chong, Mian-Yoon; Kuga, Hironori; Kanba, Shigenobu; He, Yan-Ling; Lee, Min-Soo; Yang, Shu-Yu; Udomratn, Pichet; Kallivayalil, Roy A; Tanra, Andi J; Maramis, Margarita M; Shen, Winston W; Sartorius, Norman; Kua, Ee-Heok; Tan, Chay-Hoon; Mahendran, Rathi; Shinfuku, Naotaka; Sum, Min Yi; Baldessarini, Ross J; Sim, Kang

2017-04-01

As most reports concerning treatment with combinations of mood stabilizer (MS) with antidepressant (AD) drugs are based in the West, we surveyed characteristics of such cotreatment in 42 sites caring for the mentally ill in 10 Asian countries. This cross-sectional, pharmacoepidemiologic study used 2004 and 2013 data from the REAP-AD (Research Study on Asian Psychotropic Prescription Patterns for Antidepressants) to evaluate the rates and doses of MSs given with ADs and associated factors in 4164 psychiatric patients, using standard bivariate methods followed by multivariable logistic regression modeling. Use of MS + AD increased by 104% (5.5% to 11.2%) between 2004 and 2013 and was much more associated with diagnosis of bipolar disorder than major depression or anxiety disorder, as well as with hospitalization > outpatient care, psychiatric > general-medical programs, and young age (all P < 0.001), but not with country, sex, or AD dose. The findings provide a broad picture of contemporary use of MSs with ADs in Asia, support predictions that such treatment increased in recent years, and was associated with diagnosis of bipolar disorder, treatment in inpatient and psychiatric settings, and younger age.

Factors Associated With Antidepressant Dosing in Asia: Findings From the Research on Asian Psychotropic Prescription Study.

PubMed

Rajaratnam, Kamini; Xiang, Yu-Tao; Tripathi, Adarsh; Chiu, Helen Fung Kum; Si, Tian-Mei; Chee, Kok-Yoon; Avasthi, Ajit; Grover, Sandeep; Chong, Mian-Yoon; Kuga, Hironori; Kanba, Shigenobu; He, Yan-Ling; Lee, Min-Soo; Yang, Shu-Yu; Udomratn, Pichet; Kallivayalil, Roy Abraham; Tanra, Andi J; Maramis, Margarita; Shen, Winston Wu-Dien; Sartorius, Norman; Kua, Ee-Heok; Tan, Chay-Hoon; Mahendran, Rathi; Shinfuku, Naotaka; Sum, Min Yi; Baldessarini, Ross J; Sim, Kang

2016-12-01

In this study, we sought to examine factors associated with dosing of antidepressants (ADs) in Asia. Based on reported data and clinical experience, we hypothesized that doses of ADs would be associated with demographic and clinical factors and would increase over time. This cross-sectional, pharmacoepidemiological study analyzed data collected within the Research Study on Asian Psychotropic Prescription Pattern for Antidepressants from 4164 participants in 10 Asian countries, using univariate and multivariate methods. The AD doses varied by twofold among countries (highest in PR China and RO Korea, lowest in Singapore and Indonesia), and averaged 124 (120-129) mg/d imipramine-equivalents. Average daily doses increased by 12% between 2004 and 2013. Doses were significantly higher among hospitalized patients and ranked by diagnosis: major depression > anxiety disorders > bipolar disorder, but were not associated with private/public or psychiatric/general-medical settings, nor with age, sex, or cotreatment with a mood stabilizer. In multivariate modeling, AD-dose remained significantly associated with major depressive disorder and being hospitalized. Doses of ADs have increased somewhat in Asia and were higher when used for major depression or anxiety disorders than for bipolar depression and for hospitalized psychiatric patients.

Infant and toddler disease score was useful for risk of hospitalization based on data from administrative claims.

PubMed

Mikaeloff, Yann; Moride, Yola; Khoshnood, Babak; Weill, Alain; Bréart, Gérard

2007-07-01

To develop the infant and toddler disease score (IDS), a population-based predictive tool of morbidity status in infants and toddlers, based on data from administrative claims. A prospective cohort study was conducted, including 35,580 children less than 2 years of age in June 2003 from the French "ERASME" database (mean follow-up 13 months). The outcome variable was incident hospitalization during the follow-up year, that is, before the second birthday for infants and before the third for toddlers. Risk factors before inclusion (age, health care use, medications) were assessed in a 50% random sample (construction sample) by a logistic regression model. Beta coefficients were summed up to obtain the IDS. The IDS was then validated for the remaining 50% of the study population (validation sample). The major variables significantly associated with the outcome were long-term disability, younger age, and >or=1 hospitalization before inclusion. The risks of hospitalization estimated by the IDS were concordant in the construction and validation samples. The IDS is a useful index for the risk of hospitalization of infants and toddlers in relation to their morbidity status and may be used for adjustment in pharmacoepidemiologic studies using administrative claims databases.

Evidence generation from healthcare databases: recommendations for managing change.

PubMed

Bourke, Alison; Bate, Andrew; Sauer, Brian C; Brown, Jeffrey S; Hall, Gillian C

2016-07-01

There is an increasing reliance on databases of healthcare records for pharmacoepidemiology and other medical research, and such resources are often accessed over a long period of time so it is vital to consider the impact of changes in data, access methodology and the environment. The authors discuss change in communication and management, and provide a checklist of issues to consider for both database providers and users. The scope of the paper is database research, and changes are considered in relation to the three main components of database research: the data content itself, how it is accessed, and the support and tools needed to use the database. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Performance of a semi-automated approach for risk estimation using a common data model for longitudinal healthcare databases.

PubMed

Van Le, Hoa; Beach, Kathleen J; Powell, Gregory; Pattishall, Ed; Ryan, Patrick; Mera, Robertino M

2013-02-01

Different structures and coding schemes may limit rapid evaluation of a large pool of potential drug safety signals using multiple longitudinal healthcare databases. To overcome this restriction, a semi-automated approach utilising common data model (CDM) and robust pharmacoepidemiologic methods was developed; however, its performance needed to be evaluated. Twenty-three established drug-safety associations from publications were reproduced in a healthcare claims database and four of these were also repeated in electronic health records. Concordance and discrepancy of pairwise estimates were assessed between the results derived from the publication and results from this approach. For all 27 pairs, an observed agreement between the published results and the results from the semi-automated approach was greater than 85% and Kappa coefficient was 0.61, 95% CI: 0.19-1.00. Ln(IRR) differed by less than 50% for 13/27 pairs, and the IRR varied less than 2-fold for 19/27 pairs. Reproducibility based on the intra-class correlation coefficient was 0.54. Most covariates (>90%) in the publications were available for inclusion in the models. Once the study populations and inclusion/exclusion criteria were obtained from the literature, the analysis was able to be completed in 2-8 h. The semi-automated methodology using a CDM produced consistent risk estimates compared to the published findings for most selected drug-outcome associations, regardless of original study designs, databases, medications and outcomes. Further assessment of this approach is useful to understand its roles, strengths and limitations in rapidly evaluating safety signals.

[Design requirements for clinical trials on re-evaluation of safety and efficacy of post-marketed Chinese herbs].

PubMed

Xie, Yanming; Wei, Xu

2011-10-01

Re-evaluation of post-marketed based on pharmacoepidemiology is to study and collect clinical medicine safety in large population under practical applications for a long time. It is necessary to conduct re-evaluation of clinical effectiveness because of particularity of traditional Chinese medicine (TCM). Right before carrying out clinical trials on re-evaluation of post-marketed TCM, we should determine the objective of the study and progress it in the assessment mode of combination of disease and syndrome. Specical population, involving children and seniors who were excluded in pre-marketed clinical trial, were brought into drug monitoring. Sample size needs to comply with statistical requirement. We commonly use cohort study, case-control study, nested case-control, pragmatic randomized controlled trials.

[Benefits of large healthcare databases for drug risk research].

PubMed

Garbe, Edeltraut; Pigeot, Iris

2015-08-01

Large electronic healthcare databases have become an important worldwide data resource for drug safety research after approval. Signal generation methods and drug safety studies based on these data facilitate the prospective monitoring of drug safety after approval, as has been recently required by EU law and the German Medicines Act. Despite its large size, a single healthcare database may include insufficient patients for the study of a very small number of drug-exposed patients or the investigation of very rare drug risks. For that reason, in the United States, efforts have been made to work on models that provide the linkage of data from different electronic healthcare databases for monitoring the safety of medicines after authorization in (i) the Sentinel Initiative and (ii) the Observational Medical Outcomes Partnership (OMOP). In July 2014, the pilot project Mini-Sentinel included a total of 178 million people from 18 different US databases. The merging of the data is based on a distributed data network with a common data model. In the European Network of Centres for Pharmacoepidemiology and Pharmacovigilance (ENCEPP) there has been no comparable merging of data from different databases; however, first experiences have been gained in various EU drug safety projects. In Germany, the data of the statutory health insurance providers constitute the most important resource for establishing a large healthcare database. Their use for this purpose has so far been severely restricted by the Code of Social Law (Section 75, Book 10). Therefore, a reform of this section is absolutely necessary.

Proteomic Biomarkers for Acute Interstitial Lung Disease in Gefitinib-Treated Japanese Lung Cancer Patients

PubMed Central

Kawakami, Takao; Nagasaka, Keiko; Takami, Sachiko; Wada, Kazuya; Tu, Hsiao-Kun; Otsuji, Makiko; Kyono, Yutaka; Dobashi, Tae; Komatsu, Yasuhiko; Kihara, Makoto; Akimoto, Shingo; Peers, Ian S.; South, Marie C.; Higenbottam, Tim; Fukuoka, Masahiro; Nakata, Koichiro; Ohe, Yuichiro; Kudoh, Shoji; Clausen, Ib Groth; Nishimura, Toshihide; Marko-Varga, György; Kato, Harubumi

2011-01-01

Interstitial lung disease (ILD) events have been reported in Japanese non-small-cell lung cancer (NSCLC) patients receiving EGFR tyrosine kinase inhibitors. We investigated proteomic biomarkers for mechanistic insights and improved prediction of ILD. Blood plasma was collected from 43 gefitinib-treated NSCLC patients developing acute ILD (confirmed by blinded diagnostic review) and 123 randomly selected controls in a nested case-control study within a pharmacoepidemiological cohort study in Japan. We generated ∼7 million tandem mass spectrometry (MS/MS) measurements with extensive quality control and validation, producing one of the largest proteomic lung cancer datasets to date, incorporating rigorous study design, phenotype definition, and evaluation of sample processing. After alignment, scaling, and measurement batch adjustment, we identified 41 peptide peaks representing 29 proteins best predicting ILD. Multivariate peptide, protein, and pathway modeling achieved ILD prediction comparable to previously identified clinical variables; combining the two provided some improvement. The acute phase response pathway was strongly represented (17 of 29 proteins, p = 1.0×10−25), suggesting a key role with potential utility as a marker for increased risk of acute ILD events. Validation by Western blotting showed correlation for identified proteins, confirming that robust results can be generated from an MS/MS platform implementing strict quality control. PMID:21799770

Current issues around the pharmacotherapy of ADHD in children and adults.

PubMed

Meijer, Willemijn M; Faber, Adrianne; van den Ban, Els; Tobi, Hilde

2009-10-01

New drugs and new formulations enter the growing market for ADHD medication. The growing awareness of possible persistence of ADHD impairment beyond childhood and adolescence resulting in increased pharmacotherapy of ADHD in adults, is also a good reason for making an inventory of the what is generally known about pharmacotherapy in ADHD. To discuss current issues in the possible pharmacotherapy treatment of ADHD in children, adolescents and adults with respect to the position of pharmacotherapy in ADHD treatment guidelines, the pharmacoepidemiological trends, and current concerns about the drugs used. A search of the literature with an emphasis on the position of pharmacotherapy in ADHD treatment guidelines, the pharmacoepidemiological trends, and current concerns about the drugs used in pharmacotherapy. According to the guidelines, the treatment of ADHD in children consists of psychosocial interventions in combination with pharmacotherapy when needed. Stimulants are the first-choice drugs in the pharmacological treatment of ADHD in children despite a number of well known and frequently reported side effects like sleep disorders and loss of appetite. With regard to the treatment of adults, stimulant treatment was recommended as the first-choice pharmacotherapy in the single guideline available. Both in children and adults, there appears to be an additional though limited role for the nonadrenergic drug atomoxetine. The increase of ADHD medication use, in children, adolescents and in adults, can not only be interpreted as a sign of overdiagnosis of ADHD. Despite the frequent use of stimulants, there is still a lack of clarity on the effects of long-term use on growth and nutritional status of children. Cardiovascular effects of both stimulants and atomoxetine are rare but can be severe. The literature suggests that atomoxetine may be associated with suicidal ideation in children. Although pharmacotherapy is increasing common in the treatment of ADHD in both children and adults, there are still a lot of questions about side effects and how best to counter them. This suggests an important role for close monitoring of children and adults treated with stimulants or atomoxetine.

Gastrointestinal toxicity among patients taking selective COX-2 inhibitors or conventional NSAIDs, alone or combined with proton pump inhibitors: a case-control study.

PubMed

Bakhriansyah, Mohammad; Souverein, Patrick C; de Boer, Anthonius; Klungel, Olaf H

2017-10-01

To assess the risk of gastrointestinal perforation, ulcers, or bleeding (PUB) associated with the use of conventional nonsteroidal anti-inflammatory drugs (NSAIDs) with proton pump inhibitors (PPIs) and selective COX-2 inhibitors, with or without PPIs compared with conventional NSAIDs. A case-control study was performed within conventional NSAIDs and/or selective COX-2 inhibitors users identified from the Dutch PHARMO Record Linkage System in the period 1998-2012. Cases were patients aged ≥18 years with a first hospital admission for PUB. For each case, up to four controls were matched for age and sex at the date a case was hospitalized (index date). Logistic regression analysis was used to calculate odds ratios (ORs). At the index date, 2634 cases and 5074 controls were current users of conventional NSAIDs or selective COX-2 inhibitors. Compared with conventional NSAIDs, selective COX-2 inhibitors with PPIs had the lowest risk of PUB (adjusted OR 0.51, 95% confidence interval [CI]: 0.35-0.73) followed by selective COX-2 inhibitors (adjusted OR 0.66, 95%CI: 0.48-0.89) and conventional NSAIDs with PPIs (adjusted OR 0.79, 95%CI: 0.68-0.92). Compared with conventional NSAIDs, the risk of PUB was lower for those aged ≥75 years taking conventional NSAIDs with PPIs compared with younger patients (adjusted interaction OR 0.79, 95%CI: 0.64-0.99). However, those aged ≥75 years taking selective COX-2 inhibitors, the risk was higher compared with younger patients (adjusted interaction OR 1.22, 95%CI: 1.01-1.47). Selective COX-2 inhibitors with PPIs, selective COX-2 inhibitors, and conventional NSAIDs with PPIs were associated with lower risks of PUB compared with conventional NSAIDs. These effects were modified by age. © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd. © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd.

Chinese herbal prescriptions for osteoarthritis in Taiwan: analysis of national health insurance dataset

PubMed Central

2014-01-01

Background Chinese herbal medicine (CHM) has been commonly used for treating osteoarthritis in Asia for centuries. This study aimed to conduct a large-scale pharmaco-epidemiologic study and evaluate the frequency and patterns of CHM used in treating osteoarthritis in Taiwan. Methods A complete database (total 22,520,776 beneficiaries) of traditional Chinese medicine (TCM) outpatient claims offered by the National Health Insurance program in Taiwan for the year 2002 was employed for this research. Patients with osteoarthritis were identified according to the diagnostic code of the International Classification of Disease among claimed visiting files. Corresponding prescription files were analyzed, and an association rule was applied to evaluate the co-prescription of CHM for treating osteoarthritis. Results There were 20,059 subjects who visited TCM clinics for osteoarthritis and received a total of 32,050 CHM prescriptions. Subjects between 40 and 49 years of age comprised the largest number of those treated (19.2%), followed by 50-59 years (18.8%) and 60-69 years group (18.2%). In addition, female subjects used CHMs for osteoarthritis more frequently than male subjects (female: male = 1.89: l). There was an average of 5.2 items prescribed in the form of either an individual Chinese herb or formula in a single CHM prescription for osteoarthritis. Du-zhong (Eucommia bark) was the most commonly prescribed Chinese single herb, while Du-huo-ji-sheng-tang was the most commonly prescribed Chinese herbal formula for osteoarthritis. According to the association rule, the most commonly prescribed formula was Du-huo-ji-sheng-tang plus Shen-tong-zhu-yu-tang, and the most commonly prescribed triple-drug combination was Du-huo-ji-sheng-tang, Gu-sui-pu (Drynaria fortune (Kunze) J. Sm.), and Xu-Duan (Himalaya teasel). Nevertheless, further clinical trials are needed to evaluate the efficacy and safety of these CHMs for treating osteoarthritis. Conclusions This study conducted a large scale pharmaco-epidemiology survey of Chinese herbal medicine use in OA patients by analyzing the NHIRD in Taiwan in year 2002. PMID:24606767

ANN multiscale model of anti-HIV drugs activity vs AIDS prevalence in the US at county level based on information indices of molecular graphs and social networks.

PubMed

González-Díaz, Humberto; Herrera-Ibatá, Diana María; Duardo-Sánchez, Aliuska; Munteanu, Cristian R; Orbegozo-Medina, Ricardo Alfredo; Pazos, Alejandro

2014-03-24

This work is aimed at describing the workflow for a methodology that combines chemoinformatics and pharmacoepidemiology methods and at reporting the first predictive model developed with this methodology. The new model is able to predict complex networks of AIDS prevalence in the US counties, taking into consideration the social determinants and activity/structure of anti-HIV drugs in preclinical assays. We trained different Artificial Neural Networks (ANNs) using as input information indices of social networks and molecular graphs. We used a Shannon information index based on the Gini coefficient to quantify the effect of income inequality in the social network. We obtained the data on AIDS prevalence and the Gini coefficient from the AIDSVu database of Emory University. We also used the Balaban information indices to quantify changes in the chemical structure of anti-HIV drugs. We obtained the data on anti-HIV drug activity and structure (SMILE codes) from the ChEMBL database. Last, we used Box-Jenkins moving average operators to quantify information about the deviations of drugs with respect to data subsets of reference (targets, organisms, experimental parameters, protocols). The best model found was a Linear Neural Network (LNN) with values of Accuracy, Specificity, and Sensitivity above 0.76 and AUROC > 0.80 in training and external validation series. This model generates a complex network of AIDS prevalence in the US at county level with respect to the preclinical activity of anti-HIV drugs in preclinical assays. To train/validate the model and predict the complex network we needed to analyze 43,249 data points including values of AIDS prevalence in 2,310 counties in the US vs ChEMBL results for 21,582 unique drugs, 9 viral or human protein targets, 4,856 protocols, and 10 possible experimental measures.

Determining prescription durations based on the parametric waiting time distribution.

PubMed

Støvring, Henrik; Pottegård, Anton; Hallas, Jesper

2016-12-01

The purpose of the study is to develop a method to estimate the duration of single prescriptions in pharmacoepidemiological studies when the single prescription duration is not available. We developed an estimation algorithm based on maximum likelihood estimation of a parametric two-component mixture model for the waiting time distribution (WTD). The distribution component for prevalent users estimates the forward recurrence density (FRD), which is related to the distribution of time between subsequent prescription redemptions, the inter-arrival density (IAD), for users in continued treatment. We exploited this to estimate percentiles of the IAD by inversion of the estimated FRD and defined the duration of a prescription as the time within which 80% of current users will have presented themselves again. Statistical properties were examined in simulation studies, and the method was applied to empirical data for four model drugs: non-steroidal anti-inflammatory drugs (NSAIDs), warfarin, bendroflumethiazide, and levothyroxine. Simulation studies found negligible bias when the data-generating model for the IAD coincided with the FRD used in the WTD estimation (Log-Normal). When the IAD consisted of a mixture of two Log-Normal distributions, but was analyzed with a single Log-Normal distribution, relative bias did not exceed 9%. Using a Log-Normal FRD, we estimated prescription durations of 117, 91, 137, and 118 days for NSAIDs, warfarin, bendroflumethiazide, and levothyroxine, respectively. Similar results were found with a Weibull FRD. The algorithm allows valid estimation of single prescription durations, especially when the WTD reliably separates current users from incident users, and may replace ad-hoc decision rules in automated implementations. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Isopropanolic black cohosh extract and recurrence-free survival after breast cancer.

PubMed

Henneicke-von Zepelin, H H; Meden, H; Kostev, K; Schröder-Bernhardi, D; Stammwitz, U; Becher, H

2007-03-01

To investigate the influence of an isopropanolic Cimicifuga racemosa extract (iCR) on recurrence-free survival after breast cancer, including estrogen-dependent tumors. This pharmacoepidemiologic observational retrospective cohort study examined breast cancer patients treated at general, gynecological and internal facilities linked to a medical database in Germany. The main endpoint was disease-free survival following a diagnosis of breast cancer. The impact of treatment with iCR following diagnosis was analyzed by Cox-proportional hazards models, controlling for age and other confounders. Of 18,861 patients, a total of 1,102 had received an iCR therapy. The mean overall observation time was 3.6 years. Results showed that iCR was not associated with an increase in the risk of recurrence but associated with prolonged disease-free survival. After 2 years following initial diagnosis, 14% of the control group had developed a recurrence, while the iCR group reached this proportion after 6.5 years. The primary Cox regression model controlling for age, tamoxifen use and other confounders demonstrated a protractive effect of iCR on the rate of recurrence (hazard ratio 0.83, 95% confidence interval 0.69 0.99). This effect remained consistent throughout all variations of the statistical model, including subgroup analyses. TNM status was unknown but did not bias the iCR treatment decision as investigated separately. Hence, it was assumed to be equally distributed between treatment groups. Correlation analyses showed good internal and external validity of the database. An increase in the risk of breast cancer recurrence for women having had iCR treatment, compared to women not treated with iCR is unlikely.

Risk of preeclampsia after gestational exposure to selective serotonin reuptake inhibitors and other antidepressants: A study from The Norwegian Mother and Child Cohort Study.

PubMed

Lupattelli, Angela; Wood, Mollie; Lapane, Kate; Spigset, Olav; Nordeng, Hedvig

2017-10-01

To describe the risk of early- and late-onset preeclampsia across pregnancies exposed to antidepressants and to evaluate the impact of timing and length of gestational exposure to antidepressants, particularly selective serotonin reuptake inhibitors (SSRIs), on preeclampsia. The Norwegian Mother and Child Cohort, a prospective population-based study, and the Medical Birth Registry of Norway provided information on antidepressant exposure, depression, and anxiety symptoms in pregnancy, preeclampsia diagnoses, and important covariates. Within a pregnancy cohort of depressed women, we compared the risk of late-onset preeclampsia between SSRI-exposed and nonmedicated pregnancies using marginal structural models (weighted) and modified Poisson regression models. Of the 5887 pregnancies included, 11.1% were exposed at any time before week 34 to SSRIs, 1.3% to serotonin-norepinephrine reuptake inhibitors, 0.4% to tricyclic antidepressants, and 0.5% to other antidepressants. The risks of early- and late-onset preeclampsia by exposure status in pregnancy were 0.3% and 3.6% (nonmedicated), 0.4% and 3.7% (SSRIs), 1.5% and 4.1% (serotonin-norepinephrine reuptake inhibitors), and 7.1% and 10.0% (tricyclic antidepressants). Compared with nonmedicated pregnancies, SSRI-exposed in mid and late gestation had adjusted relative risks for late-onset mild preeclampsia of 0.76 (95% confidence interval, 0.38-1.53) and 1.56 (0.71-3.44) (weighted models), respectively. There was no association between SSRI exposure in pregnancy and severe late-onset preeclampsia. We have provided evidence that SSRI use in early and midpregnancy does not substantially increase the risk of late-onset preeclampsia. © 2017 The Authors. Pharmacoepidemiology & Drug Safety published by John Wiley & Sons Ltd.

Drug-Induced Liver Injury: Pattern Recognition and Future Directions

PubMed Central

Haque, Tanvir; Sasatomi, Eizaburo; Hayashi, Paul H.

2016-01-01

Drug-induced liver injury (DILI) remains a significant clinical challenge and is the leading cause of acute liver failure in most countries. An aging population that uses more medications, a constant influx of newly developed drugs and a growing risk from unfamiliar herbal and dietary supplements will make DILI an increasing part of clinical practice. Currently, the most effective strategy for disease management is rapid identification, withholding the inciting agents, supportive care and having a firm understanding of the expected natural history. There are resources available to aid the clinician, including a new online “textbook” as well as causality assessment tools, but a heightened awareness of risk and the disease’s varying phenotypes and good history-taking remain cornerstones to diagnosis. Looking ahead, growing registries of cases, pharmacoepidemiology studies and translational research into the mechanisms of injury may produce better diagnostic tools, markers for risk and disease, and prevention and therapeutics. PMID:26696029

Pharmacoepidemiological Data from Drug Dispensing Charities as a Measure of Health Patterns in a Population not Assisted by the Italian National Health Service.

PubMed

Bini, Silvia; Cerri, Cesare; Rigamonti, Antonello E; Bertazzi, Pietro A; Fiorini, Gianfrancesco; Cella, Silvano G

2016-08-19

We analysed drug dispensation by charitable organisations in a year time. Drugs were grouped according to the Anatomic Therapeutic Chemical classification and the amount dispensed was calculated with the system of the Daily Defined Dose (DDD) and expressed as DDD/1000 subjects/day. A number of 87,550 subjects were studied (13,308 Italians; 74,242 Immigrants). Though we noticed a great sesonal variability, the drugs most frequently dispensed were those for the respiratory, cardiovascular and gastrointestinal system and antibiotics, which is different from the rest of the Italian population and the immigrant population assisted by our National Health Service (NHS). We also found that chronic diseases are increasing in these subjects. We conclude that the subjects not receiving NHS assitance have, at least in part, different health patterns and requirements. This should be considered when planning tailored interventions.

Update on the epidemiology of the rheumatic diseases.

PubMed

Gabriel, S E

1996-03-01

Epidemiologic studies continue to enhance our understanding of the rheumatic diseases. Such studies now indicate that 26 million American women are at risk for osteoporotic fractures. Contrary to previous recommendations, the identification and treatment of patients at risk for osteoporosis may be valuable even among very elderly people. Other epidemiologic studies suggest that the incidence of rheumatoid arthritis is decreasing and that it is a more benign disease than previously recognized. Osteoarthritis remains a leading cause of physical and work disability in North America. The roles of occupational physical activity, obesity, and highly competitive (though not low-impact) exercise as risk factors for osteoarthritis continue to be explored. Pharmacoepidemiologic research has recently demonstrated that a policy of prior authorization for prescription of nonsteroidal anti-inflammatory drugs may be highly cost effective. Finally, controlled epidemiologic studies have not confirmed an association between silicone breast implants and connective tissue diseases, a conclusion recently endorsed by the American College of Rheumatology.

The Australian Pharmaceutical Benefits Scheme data collection: a practical guide for researchers.

PubMed

Mellish, Leigh; Karanges, Emily A; Litchfield, Melisa J; Schaffer, Andrea L; Blanch, Bianca; Daniels, Benjamin J; Segrave, Alicia; Pearson, Sallie-Anne

2015-11-02

The Pharmaceutical Benefits Scheme (PBS) is Australia's national drug subsidy program. This paper provides a practical guide to researchers using PBS data to examine prescribed medicine use. Excerpts of the PBS data collection are available in a variety of formats. We describe the core components of four publicly available extracts (the Australian Statistics on Medicines, PBS statistics online, section 85 extract, under co-payment extract). We also detail common analytical challenges and key issues regarding the interpretation of utilisation using the PBS collection and its various extracts. Research using routinely collected data is increasing internationally. PBS data are a valuable resource for Australian pharmacoepidemiological and pharmaceutical policy research. A detailed knowledge of the PBS, the nuances of data capture, and the extracts available for research purposes are necessary to ensure robust methodology, interpretation, and translation of study findings into policy and practice.

Brief Report: Databases in the Asia-Pacific Region: The Potential for a Distributed Network Approach.

PubMed

Lai, Edward Chia-Cheng; Man, Kenneth K C; Chaiyakunapruk, Nathorn; Cheng, Ching-Lan; Chien, Hsu-Chih; Chui, Celine S L; Dilokthornsakul, Piyameth; Hardy, N Chantelle; Hsieh, Cheng-Yang; Hsu, Chung Y; Kubota, Kiyoshi; Lin, Tzu-Chieh; Liu, Yanfang; Park, Byung Joo; Pratt, Nicole; Roughead, Elizabeth E; Shin, Ju-Young; Watcharathanakij, Sawaeng; Wen, Jin; Wong, Ian C K; Yang, Yea-Huei Kao; Zhang, Yinghong; Setoguchi, Soko

2015-11-01

This study describes the availability and characteristics of databases in Asian-Pacific countries and assesses the feasibility of a distributed network approach in the region. A web-based survey was conducted among investigators using healthcare databases in the Asia-Pacific countries. Potential survey participants were identified through the Asian Pharmacoepidemiology Network. Investigators from a total of 11 databases participated in the survey. Database sources included four nationwide claims databases from Japan, South Korea, and Taiwan; two nationwide electronic health records from Hong Kong and Singapore; a regional electronic health record from western China; two electronic health records from Thailand; and cancer and stroke registries from Taiwan. We identified 11 databases with capabilities for distributed network approaches. Many country-specific coding systems and terminologies have been already converted to international coding systems. The harmonization of health expenditure data is a major obstacle for future investigations attempting to evaluate issues related to medical costs.

A comparison of estimators from self-controlled case series, case-crossover design, and sequence symmetry analysis for pharmacoepidemiological studies.

PubMed

Takeuchi, Yoshinori; Shinozaki, Tomohiro; Matsuyama, Yutaka

2018-01-08

Despite the frequent use of self-controlled methods in pharmacoepidemiological studies, the factors that may bias the estimates from these methods have not been adequately compared in real-world settings. Here, we comparatively examined the impact of a time-varying confounder and its interactions with time-invariant confounders, time trends in exposures and events, restrictions, and misspecification of risk period durations on the estimators from three self-controlled methods. This study analyzed self-controlled case series (SCCS), case-crossover (CCO) design, and sequence symmetry analysis (SSA) using simulated and actual electronic medical records datasets. We evaluated the performance of the three self-controlled methods in simulated cohorts for the following scenarios: 1) time-invariant confounding with interactions between the confounders, 2) time-invariant and time-varying confounding without interactions, 3) time-invariant and time-varying confounding with interactions among the confounders, 4) time trends in exposures and events, 5) restricted follow-up time based on event occurrence, and 6) patient restriction based on event history. The sensitivity of the estimators to misspecified risk period durations was also evaluated. As a case study, we applied these methods to evaluate the risk of macrolides on liver injury using electronic medical records. In the simulation analysis, time-varying confounding produced bias in the SCCS and CCO design estimates, which aggravated in the presence of interactions between the time-invariant and time-varying confounders. The SCCS estimates were biased by time trends in both exposures and events. Erroneously short risk periods introduced bias to the CCO design estimate, whereas erroneously long risk periods introduced bias to the estimates of all three methods. Restricting the follow-up time led to severe bias in the SSA estimates. The SCCS estimates were sensitive to patient restriction. The case study showed that although macrolide use was significantly associated with increased liver injury occurrence in all methods, the value of the estimates varied. The estimations of the three self-controlled methods depended on various underlying assumptions, and the violation of these assumptions may cause non-negligible bias in the resulting estimates. Pharmacoepidemiologists should select the appropriate self-controlled method based on how well the relevant key assumptions are satisfied with respect to the available data.

Pharmacoepidemiology of anemia in kidney transplant recipients.

PubMed

Winkelmayer, Wolfgang C; Kewalramani, Reshma; Rutstein, Mark; Gabardi, Steven; Vonvisger, Tania; Chandraker, Anil

2004-05-01

ABSTRACT. Anemia has long been known to be a complication of end-stage renal disease (ESRD), and it has been linked to cardiovascular morbidity and mortality. Although kidney transplant recipients (KTR) are prone to experiencing cardiovascular outcomes, little is known about the epidemiology of anemia in this population. With few exceptions, studies to date have not fully evaluated the associations between posttransplant anemia (PTA) and medications commonly used in KTR, particularly immunosuppressant drugs, angiotensin-converting enzyme inhibitors (ACEI) and angiotensin II receptor blockers (ARB). The authors aimed to specifically investigate possible associations between these drugs and PTA. Detailed medical information was retrospectively collected on 374 consecutive KTR from our transplant clinic. Univariate/multivariate linear regression models were used to test for associations between hematocrit (HCT) and other covariates, and logistic regression models were used to detect independent predictors of PTA, defined as HCT <33%. The mean time since transplantation was 7.7 yr, and mean creatinine was 2.2 mg/dl. The prevalence of PTA was 28.6%. Ten percent of all patients were on erythropoietin therapy, but only 41.6% of patients whose HCT was <30 received this treatment. From multivariate analyses, the authors found that female gender and lower renal function were associated with lower HCT (both P < 0.001). Patients on ACEI had significantly lower HCT (P = 0.005) compared with patients without such treatment. In addition, a significant curvilinear dose-response relationship was found between ACEI dose and HCT. Among the immunosuppressant drugs, mycophenolate mofetil (P = 0.05) and tacrolimus (P = 0.02) were associated with a lower HCT. The authors conclude that PTA is prevalent and undertreated in KTR. Several medications that are possibly modifiable correlates of PTR deserve further study.

Medical records and privacy: empirical effects of legislation.

PubMed

McCarthy, D B; Shatin, D; Drinkard, C R; Kleinman, J H; Gardner, J S

1999-04-01

To determine the effects of state legislation requiring patient informed consent prior to medical record abstraction by external researchers for a specific study. Informed consent responses obtained from November 1997 through April 1998 from members of a Minnesota-based IPA model health plan. Descriptive case study of consent to gain access to medical records for a pharmaco-epidemiologic study of seizures associated with use of a pain medication that was conducted as part of the FDA's post-marketing safety surveillance program to evaluate adverse events associated with approved drugs. The informed consent process approved by an institutional review board consisted of three phases: (1) a letter from the health plan's medical director requesting participation, (2) a second mailing to nonrespondents, and (3) a follow-up telephone call to nonrespondents. Of 140 Minnesota health plan members asked to participate in the medical records study, 52 percent (73) responded and 19 percent (26) returned a signed consent form authorizing access to their records for the study. For 132 study subjects enrolled in five other health plans in states where study-specific consent was not required, health care providers granted access to patient medical records for 93 percent (123) of the members. Legislation requiring patient informed consent to gain access to medical records for a specific research study was associated with low participation and increased time to complete that observational study. Efforts to protect patient privacy may come into conflict with the ability to produce timely and valid research to safeguard and improve public health.

[Technical improvement of cohort constitution in administrative health databases: Providing a tool for integration and standardization of data applicable in the French National Health Insurance Database (SNIIRAM)].

PubMed

Ferdynus, C; Huiart, L

2016-09-01

Administrative health databases such as the French National Heath Insurance Database - SNIIRAM - are a major tool to answer numerous public health research questions. However the use of such data requires complex and time-consuming data management. Our objective was to develop and make available a tool to optimize cohort constitution within administrative health databases. We developed a process to extract, transform and load (ETL) data from various heterogeneous sources in a standardized data warehouse. This data warehouse is architected as a star schema corresponding to an i2b2 star schema model. We then evaluated the performance of this ETL using data from a pharmacoepidemiology research project conducted in the SNIIRAM database. The ETL we developed comprises a set of functionalities for creating SAS scripts. Data can be integrated into a standardized data warehouse. As part of the performance assessment of this ETL, we achieved integration of a dataset from the SNIIRAM comprising more than 900 million lines in less than three hours using a desktop computer. This enables patient selection from the standardized data warehouse within seconds of the request. The ETL described in this paper provides a tool which is effective and compatible with all administrative health databases, without requiring complex database servers. This tool should simplify cohort constitution in health databases; the standardization of warehouse data facilitates collaborative work between research teams. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Statins Improve Long Term Patency of Arteriovenous Fistula for Hemodialysis

PubMed Central

Chang, Hao-Hsiang; Chang, Yu-Kang; Lu, Chia-Wen; Huang, Chi-Ting; Chien, Chiang-Ting; Hung, Kuan-Yu; Huang, Kuo-Chin; Hsu, Chih-Cheng

2016-01-01

The protective effects of statins against stenosis for permanent hemodialysis access have been repeatedly demonstrated in animal studies, but remain controversial in human studies. This study aims to evaluate the association between statin use and permanent hemodialysis access patency using a nationwide hemodialysis cohort. A total of 9862 pairs of statin users and non-users, matched by age and gender, were selected for investigation from 75404 new hemodialysis patients during 2000–2008. The effect of statins on permanent hemodialysis access patency was evaluated using Cox proportional hazards models. Compared with non-users, statin users had an overall 18% risk reduction in the composite endpoint in which angioplasty and recreation were combined (adjusted hazard ratio = 0.82 [95%CI, 0.78–0.87]) and 21% in recreation of permanent hemodialysis access (adjusted hazard ratio = 0.79 [95%CI, 0.69–0.80]). Specifically, the protective effect was found for arteriovenous fistula (adjusted hazard ratio = 0.78[95% CI, 0.73–0.82] for composite endpoint and 0.74 [95% CI, 0.69–0.80] for vascular recreation), but not for arteriovenous grafts (adjusted hazard ratio = 1.10 [95% CI, 0.98–1.24] and 0.94 [95% CI, 0.83–1.07]). Statins possess a protective effect for arteriovenous fistula against the recreation of permanent hemodialysis access. The results provide a pharmaco-epidemiologic link between basic research and clinical evidence. PMID:26902330

Pharmacosurveillance in hospitalized patients in Italy. Study design of the 'Gruppo Italiano di Farmacovigilanza nell'Anziano' (GIFA).

PubMed

Carosella, L; Pahor, M; Pedone, C; Zuccalà, G; Manto, A; Carbonin, P

1999-09-01

The Italian Group of Pharmacoepidemiology in the Elderly (Gruppo Italiano di Farmacovigilanza nell'Anziano, GIFA) is a collaborative pharmacosurveillance study in hospitalized patients, sponsored by the Italian National Research Council (CNR) and the Italian Society of Gerontology and Geriatrics. It was founded in 1987 with the aim to constitute a multicentre research group to study quality of care and problems related to pharmacological therapy in the elderly. Until now the GIFA study has completed seven periodical surveys and enrolled a total of 28,411 hospitalized patients in 83 clinical centres. The database of the study contains approximately 174,000 in-hospital drug prescriptions, approximately 88,000 discharge diagnoses and a great deal of data on topical geriatric items such as cognitive performance, disability, comorbidity, adverse drug reactions and incontinence. This paper describes the general organization and the methods of the GIFA study and shows in detail the type of data collected. Copyright 1999 Academic Press.

Development of an adverse events reporting form for Korean folk medicine

PubMed Central

Park, Jeong Hwan; Choi, Sun‐Mi; Moon, Sujeong; Kim, Sungha; Kim, Boyoung; Kim, Min‐Kyeoung

2016-01-01

Abstract Purpose We developed an adverse events (AEs) reporting form for Korean folk medicine. Methods The first version of the form was developed and tested in the clinical setting for spontaneous reporting of AEs. Additional revisions to the reporting form were made based on collected data and expert input. Results We developed an AEs reporting form for Korean folk medicine. The items of this form were based on patient information, folk medicine properties, and AEs. For causality assessment, folk medicine properties such as classification, common and vernacular names, scientific name, part used, harvesting time, storage conditions, purchasing route, product licensing, prescription, persons with similar exposure, any remnant of raw natural products collected from the patient, and cautions or contraindications were added. Conclusions This is the first reporting form for AEs that incorporates important characteristics of Korean folk medicine. This form would have an important role in reporting adverse events for Korean folk medicine. © 2016 The Authors. Pharmacoepidemiology and Drug Safety Published by John Wiley & Sons Ltd. PMID:27501410

A Cross-sectional, Descriptive Study of Medication Use Among Persons With a Gastrointestinal Stoma.

PubMed

Pereira de Paula, Bianca Augusta; da Silva Alves, Geisa Cristina; PercÍnio, Álvaro; Pereira, Mariana Linhares; Moraes, Juliano Teixeira; Sanches, Cristina

2017-09-01

Research on the use of medications in people with intestinal stomas is lacking, creating gaps in knowledge of pharmacoepidemiology in these patients. A cross-sectional, descriptive study was conducted over a period of 4 months in Divinópolis, Brazil to describe the profile of medication use among people enrolled in the Health Support Service for People with Stoma - Level II (SSPS II) of a municipality in the state of Minas Gerais, Brazil. All patients from SSPS II with a colostomy or ileostomy were invited by phone to participate; those with incomplete registration data and/or who were <18 years old, hospitalized for any reason, or had their stoma reversed were excluded from participation. During home interviews, researchers obtained sociodemographic profiles (age, gender, education, occupation, and family income) and information on comorbidities, medication use, adherence to medication protocols (per the Morisky Green Levine test), polypharmacy, and adult/pharmaceutical care (medication description and indication, expiration date, self-medication). Drug storage was assessed by visual evaluation. The information was entered onto individual data sheets, numbered to ensure patient anonymity. The data then were entered into and analyzed using SSPS II statistical software using frequency measurements, measures of central tendency, and dispersion of demographic variables, health conditions, and medicine use. The study population included 59 persons (average age 66.9 ± 13.27 years), 36 (61.0%) women, 38 (64.4%) with an incomplete/primary level education, and 44 (74.5%) retired. Forty-nine (49) patients had a colostomy and 10 had an ileostomy; cancer was the main reason for stoma creation (61.1%). Half of the survey participants reported having 1 or 2 comorbidities (average 2.3); the most prevalent (52) was circulatory system disease among which hypertension (38, 64.4%) was most common. Analysis of the pharmacotherapeutic profile (prescribed and used) showed 89.8% of the study population used medication, and 52.8% were prescribed >5 medications (polypharmacy). Low and medium level adherence with prescriptions was noted (37.7%); 39.6% reported receiving no guidance on the use of the medication associated with their condition. Improper storage was observed in 33.9% of participants. In this population, persons with a stoma had complex pharmacotherapy, a high rate of polypharmacy, and deficiency in guidance on the use of medication. Further research into determining whether investments in both inclusion of a pharmacist on the team and more pharmacoepidemiological studies would improve patient care and medication safety in patients with a stoma is warranted.

[The case-case-time-control study design].

PubMed

Wang, Jing; Zhuo, Lin; Zhan, Siyan

2014-12-01

Although the 'self-matched case-only studies' (such as the case-cross-over or self-controlled case-series method) can control the time-invariant confounders (measured or unmeasured) through design of the study, however, they can not control those confounders that vary with time. A bidirectional case-crossover design can be used to adjust the exposure-time trends. In the areas of pharmaco-epidemiology, illness often influence the future use of medications, making a bidirectional study design problematic. Suissa's case-time-control design combines the case-crossover and the case-control design which could adjust for exposure-trend bias, but the control group may reintroduce selection bias, if the matching does not go well. We propose a "case-case-time-control" design which is an extension of the case-time-control design. However, rather than using a sample of external controls, we choose those future cases as controls for current cases to counter the bias that arising from temporal trends caused by exposure to the target of interest. In the end of this article we will discuss the strength and limitations of this design based on an applied example.

From prescriptions to drug use periods - things to notice.

PubMed

Tanskanen, Antti; Taipale, Heidi; Koponen, Marjaana; Tolppanen, Anna-Maija; Hartikainen, Sirpa; Ahonen, Riitta; Tiihonen, Jari

2014-11-14

Electronic prescription registers provide a vast data source for pharmacoepidemiological research. Prescriptions as such are not suitable for all research purposes; e.g., studying concurrent use of different drugs or adverse drug events during current use. For those purposes, data on dispensed prescriptions needs to be transformed to periods of drug use. We used 3,828,292 dispensed prescriptions claimed between 1 January 2002 and 31 December 2009 for 28,093 persons with Alzheimer's disease. Examples of drug use histories are presented to discuss different aspects that should be noticed when using register-based data consisting of drug purchases. There is no simple method for correctly transforming dispensed prescriptions to periods of drug use that is usable for all drugs and drug users. Fixed assumptions of daily dose (in defined daily doses, tablets or other units) and fixed time windows should be used with caution and adjusted for different drug use patterns. We recommend that when transforming prescription drug purchases to drug use periods personal dose, purchasing pattern and other behavioral differences between patients should be taken into account.

Adverse Event extraction from Structured Product Labels using the Event-based Text-mining of Health Electronic Records (ETHER)system.

PubMed

Pandey, Abhishek; Kreimeyer, Kory; Foster, Matthew; Botsis, Taxiarchis; Dang, Oanh; Ly, Thomas; Wang, Wei; Forshee, Richard

2018-01-01

Structured Product Labels follow an XML-based document markup standard approved by the Health Level Seven organization and adopted by the US Food and Drug Administration as a mechanism for exchanging medical products information. Their current organization makes their secondary use rather challenging. We used the Side Effect Resource database and DailyMed to generate a comparison dataset of 1159 Structured Product Labels. We processed the Adverse Reaction section of these Structured Product Labels with the Event-based Text-mining of Health Electronic Records system and evaluated its ability to extract and encode Adverse Event terms to Medical Dictionary for Regulatory Activities Preferred Terms. A small sample of 100 labels was then selected for further analysis. Of the 100 labels, Event-based Text-mining of Health Electronic Records achieved a precision and recall of 81 percent and 92 percent, respectively. This study demonstrated Event-based Text-mining of Health Electronic Record's ability to extract and encode Adverse Event terms from Structured Product Labels which may potentially support multiple pharmacoepidemiological tasks.

Validation of a computer case definition for sudden cardiac death in opioid users.

PubMed

Kawai, Vivian K; Murray, Katherine T; Stein, C Michael; Cooper, William O; Graham, David J; Hall, Kathi; Ray, Wayne A

2012-08-31

To facilitate the use of automated databases for studies of sudden cardiac death, we previously developed a computerized case definition that had a positive predictive value between 86% and 88%. However, the definition has not been specifically validated for prescription opioid users, for whom out-of-hospital overdose deaths may be difficult to distinguish from sudden cardiac death. We assembled a cohort of persons 30-74 years of age prescribed propoxyphene or hydrocodone who had no life-threatening non-cardiovascular illness, diagnosed drug abuse, residence in a nursing home in the past year, or hospital stay within the past 30 days. Medical records were sought for a sample of 140 cohort deaths within 30 days of a prescription fill meeting the computer case definition. Of the 140 sampled deaths, 81 were adjudicated; 73 (90%) were sudden cardiac deaths. Two deaths had possible opioid overdose; after removing these two the positive predictive value was 88%. These findings are consistent with our previous validation studies and suggest the computer case definition of sudden cardiac death is a useful tool for pharmacoepidemiologic studies of opioid analgesics.

[Approaching the "evidence-practice gap" in pharmaceutical risk management: analysis of healthcare claim data].

PubMed

Nakayama, Takeo

2012-01-01

The concept of evidence-based medicine (EBM) has promulgated among healthcare professionals in recent years, on the other hand, the problem of underuse of useful clinical evidence is coming to be important. This is called as evidence-practice gap. The major concern about evidence-practice gap is insufficient implementation of evidence-based effective treatment, however, the perspective can be extended to measures to improve drug safety and prevention of drug related adverse events. First, this article reviews the characteristics of the database of receipt (healthcare claims) and the usefulness for research purpose of pharmacoepidemiology. Second, as the real example of the study on evidence-practice gap by using the receipt database, the case of ergot-derived anti-Parkinson drugs, of which risk of valvulopathy has been identified, is introduced. The receipt analysis showed that more than 70% of Parkinson's disease patients prescribed with cabergoline or pergolide did not undergo echocardiography despite the revision of the product label recommendation. Afterwards, the issues of pharmaceutical risk management and risk communication will be discussed.

A unique database for gathering data from a mobile app and medical prescription software: a useful data source to collect and analyse patient-reported outcomes of depression and anxiety symptoms.

PubMed

Watanabe, Yoshinori; Hirano, Yoko; Asami, Yuko; Okada, Maki; Fujita, Kazuya

2017-11-01

A unique database named 'AN-SAPO' was developed by Iwato Corp. and Japan Brain Corp. in collaboration with the psychiatric clinics run by Himorogi Group in Japan. The AN-SAPO database includes patients' depression/anxiety score data from a mobile app named AN-SAPO and medical records from medical prescription software named 'ORCA'. On the mobile app, depression/anxiety severity can be evaluated by answering 20 brief questions and the scores are transferred to the AN-SAPO database together with the patients' medical records on ORCA. Currently, this database is used at the Himorogi Group's psychiatric clinics and has over 2000 patients' records accumulated since November 2013. Since the database covers patients' demographic data, prescribed drugs, and the efficacy and safety information, it could be a useful supporting tool for decision-making in clinical practice. We expect it to be utilised in wider areas of medical fields and for future pharmacovigilance and pharmacoepidemiological studies.

Graphic report of the results from propensity score method analyses.

PubMed

Shrier, Ian; Pang, Menglan; Platt, Robert W

2017-08-01

To increase transparency in studies reporting propensity scores by using graphical methods that clearly illustrate (1) the number of participant exclusions that occur as a consequence of the analytic strategy and (2) whether treatment effects are constant or heterogeneous across propensity scores. We applied graphical methods to a real-world pharmacoepidemiologic study that evaluated the effect of initiating statin medication on the 1-year all-cause mortality post-myocardial infarction. We propose graphical methods to show the consequences of trimming and matching on the exclusion of participants from the analysis. We also propose the use of meta-analytical forest plots to show the magnitude of effect heterogeneity. A density plot with vertical lines demonstrated the proportion of subjects excluded because of trimming. A frequency plot with horizontal lines demonstrated the proportion of subjects excluded because of matching. An augmented forest plot illustrates the amount of effect heterogeneity present in the data. Our proposed techniques present additional and useful information that helps readers understand the sample that is analyzed with propensity score methods and whether effect heterogeneity is present. Copyright © 2017 Elsevier Inc. All rights reserved.

Managing security and privacy concerns over data storage in healthcare research.

PubMed

Mackenzie, Isla S; Mantay, Brian J; McDonnell, Patrick G; Wei, Li; MacDonald, Thomas M

2011-08-01

Issues surrounding data security and privacy are of great importance when handling sensitive health-related data for research. The emphasis in the past has been on balancing the risks to individuals with the benefit to society of the use of databases for research. However, a new way of looking at such issues is that by optimising procedures and policies regarding security and privacy of data to the extent that there is no appreciable risk to the privacy of individuals, we can create a 'win-win' situation in which everyone benefits, and pharmacoepidemiological research can flourish with public support. We discuss holistic measures, involving both information technology and people, taken to improve the security and privacy of data storage. After an internal review, we commissioned an external audit by an independent consultant with a view to optimising our data storage and handling procedures. Improvements to our policies and procedures were implemented as a result of the audit. By optimising our storage of data, we hope to inspire public confidence and hence cooperation with the use of health care data in research. Copyright © 2011 John Wiley & Sons, Ltd.

[Quebec Pregnancy Cohort: prevalence of medication use during gestation and pregnancy outcomes].

PubMed

Bérard, Anick; Sheehy, Odile

2014-01-01

Many women are exposed to medications during pregnancy. The Quebec Pregnancy Cohort (QPC) is a prospective population-based cohort which includes all data on pregnancies and children between January 1997 and December 2008. We linked four administrative databases in Quebec, Canada: RAMQ (medical and pharmaceutical), MED-ECHO (hospitalizations), ISQ (births/deaths), and MELS (Ministry of Education). Pregnancies included were covered by the Quebec prescription drug insurance plan (36% of women aged 15-45 years) from 12 months prior until the end of pregnancy. We analyzed 97,680 pregnancies. Prevalence of medication use was 74% pre-pregnancy, 56% during pregnancy, and 80% post-pregnancy. Most frequently used medications during pregnancy were antibiotics (47%), antiemetic drugs (23%), and non-steroïdal anti-inflammatory drugs (NSAIDs) [17%]. Medication users were more likely to have spontaneous abortions, preterm births, children with congenital malformations and postpartum depression than non-users (p<0.01). Medications are commonly used during pregnancy. The QPC is a powerful tool for perinatal pharmacoepidemiological research. © 2014 Société Française de Pharmacologie et de Thérapeutique.

Comparative safety of diabetes medications and risk of incident invasive breast cancer: a population-based cohort study

PubMed Central

Calip, Gregory S.; Yu, Onchee; Elmore, Joann G.; Boudreau, Denise M.

2016-01-01

Purpose Growing evidence suggests that certain commonly used diabetes medications have the potential to differentially alter breast cancer risk. We evaluated the influence of metformin, insulin and sulfonylureas on risk of incident invasive breast cancer. Methods We conducted a retrospective cohort study of women ≥40 years of age enrolled in a health plan between 1996 and 2011. Ever, current (≤12 months), and duration (<1, 1-2.9, ≥3 years) of diabetes medication use were obtained from pharmacy databases and modeled as time-varying. Multivariable Cox proportional hazards models adjusting for potential confounders including screening mammography and body mass index were used to estimate hazard ratios (HR) and 95% confidence intervals (CI). Results Among 10,050 women with diabetes, 57% used metformin, 43% used sulfonylureas, 32% insulin, and 301 were diagnosed with breast cancer over median follow-up of 6.7 years. Results suggested no significant decreased risk of breast cancer among metformin users (HR=0.86;95% CI:0.65-1.12). We found no association between increased breast cancer risk and long-acting insulin (HR=0.95;95% CI:0.51-1.77), but reduced risk with short-/rapid-acting insulin (HR=0.69;95% CI:0.50-0.94), and suggestion of a dose response with increasing duration of short-/rapid-acting insulin use (HR=0.87;95% CI:0.76-1.00). Estimates for sulfonylurea users suggested increased risk with ever use (HR=1.18;95% CI:0.90-1.53) and with longer durations of use (≥3 years: HR=1.23;95% CI:0.88-1.73) but confidence intervals included 1.0. Conclusions Our results provide little support for the previously hypothesized decreased risk of breast cancer with metformin use or for an increased risk with insulin use. Implications for possible residual confounding by screening mammography and comorbidity should be considered in breast cancer pharmacoepidemiology studies. PMID:27053250

Evaluation of abuse and dependence on drugs used for self-medication: a pharmacoepidemiological pilot study based on community pharmacies in France.

PubMed

Orriols, Ludivine; Gaillard, Julia; Lapeyre-Mestre, Maryse; Roussin, Anne

2009-01-01

Drugs that can be obtained without a medical prescription in community pharmacies are used to treat minor pathologies that can easily be diagnosed by the patient. Some of these drugs contain psychoactive substances with a potential for abuse and dependence. However, there is a lack of data concerning their problematic use in a wide population. To explore the feasibility of a pharmacoepidemiological method to investigate misuse, non-medical use, abuse and dependence on drugs used for self-medication. This cross-sectional pilot study, conducted during a 2-month period (from 15 January to 15 March 2007), was based on the participation of community pharmacies in the Midi-Pyrénées region of France to collect patient data. Patients requesting one drug from a list of available drugs used for self-medication and containing psychoactive substances (codeine in analgesics, pseudoephedrine, dextromethorphan and histamine H(1) receptor antagonists [antihistamines]) were included in the study. A control group was set up that consisted of patients requesting antacid drugs. The pharmacy staff proposed to the patients that they filled in an anonymous questionnaire. The questionnaire was designed to investigate patterns of drug use and the harmful consequences of overuse (abuse). In addition, questions on lack of control over drug use were adapted from the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) criteria for evaluation of dependence. Thirty-two percent (n = 74) of the solicited pharmacies participated in the survey. Only 4.8% of the solicited patients (n = 817) refused to complete the questionnaire distributed by the pharmacy staff. The questionnaire was completed inside the pharmacy by 53.3% of the patients. The other patients took the questionnaire away from the pharmacy and 31.7% of them returned it in a prepaid envelope. The patient participation rate was 64.9%, and was higher for the psychoactive substance groups than the control group. Statistically significant differences on misuse (and/or non-medical use), abuse and dependence were obtained between the codeine and antacid groups. In the codeine group, among the patients having used the product in the previous month (n = 53), 15.1% misused the drug and/or used the drug for a non-medical reason, 7.5% were cases of abuse and 7.5% presented criteria of lack of control over drug use related to dependence on the substance for the psychoactive effects or for pain relief. The results obtained in this pilot study indicate that using anonymous self-administered questionnaires offered to patients by pharmacy staff is a reliable method to obtain information on the problematic use of drugs containing psychoactive substances purchased in a pharmacy for self-medication.

Prospective drug safety monitoring using the UK primary-care General Practice Research Database: theoretical framework, feasibility analysis and extrapolation to future scenarios.

PubMed

Johansson, Saga; Wallander, Mari-Ann; de Abajo, Francisco J; García Rodríguez, Luis Alberto

2010-03-01

Post-launch drug safety monitoring is essential for the detection of adverse drug signals that may be missed during preclinical trials. Traditional methods of postmarketing surveillance such as spontaneous reporting have intrinsic limitations, many of which can be overcome by the additional application of structured pharmacoepidemiological approaches. However, further improvement in drug safety monitoring requires a shift towards more proactive pharmacoepidemiological methods that can detect adverse drug signals as they occur in the population. To assess the feasibility of using proactive monitoring of an electronic medical record system, in combination with an independent endpoint adjudication committee, to detect adverse events among users of selected drugs. UK General Practice Research Database (GPRD) information was used to detect acute liver disorder associated with the use of amoxicillin/clavulanic acid (hepatotoxic) or low-dose aspirin (acetylsalicylic acid [non-hepatotoxic]). Individuals newly prescribed these drugs between 1 October 2005 and 31 March 2006 were identified. Acute liver disorder cases were assessed using GPRD computer records in combination with case validation by an independent endpoint adjudication committee. Signal generation thresholds were based on the background rate of acute liver disorder in the general population. Over a 6-month period, 8148 patients newly prescribed amoxicillin/clavulanic acid and 5577 patients newly prescribed low-dose aspirin were identified. Within this cohort, searches identified 11 potential liver disorder cases from computerized records: six for amoxicillin/clavulanic acid and five for low-dose aspirin. The independent endpoint adjudication committee refined this to four potential acute liver disorder cases for whom paper-based information was requested for final case assessment. Final case assessments confirmed no cases of acute liver disorder. The time taken for this study was 18 months (6 months for recruitment and 12 months for data management and case validation). To reach the estimated target exposure necessary to raise or rule out a signal of concern to public health, we determined that a recruitment period 2-3 times longer than that used in this study would be required. Based on the real market uptake of six commonly used medicinal products launched between 2001 and 2006 in the UK (budesonide/eformoterol [fixed-dose combination], duloxetine, ezetimibe, metformin/rosiglitazone [fixed-dose combination], tiotropium bromide and tadalafil) the target exposure would not have been reached until the fifth year of marketing using a single database. It is feasible to set up a system that actively monitors drug safety using a healthcare database and an independent endpoint adjudication committee. However, future successful implementation will require multiple databases to be queried so that larger study populations are included. This requires further development and harmonization of international healthcare databases.

The reliability of diagnostic coding and laboratory data to identify tuberculosis and nontuberculous mycobacterial disease among rheumatoid arthritis patients using anti-tumor necrosis factor therapy.

PubMed

Winthrop, Kevin L; Baxter, Roger; Liu, Liyan; McFarland, Bentson; Austin, Donald; Varley, Cara; Radcliffe, LeAnn; Suhler, Eric; Choi, Dongsoek; Herrinton, Lisa J

2011-03-01

Anti-tumor necrosis factor-alpha (anti-TNF) therapies are associated with severe mycobacterial infections in rheumatoid arthritis patients. We developed and validated electronic record search algorithms for these serious infections. The study used electronic clinical, microbiologic, and pharmacy records from Kaiser Permanente Northern California (KPNC) and the Portland Veterans Affairs Medical Center (PVAMC). We identified suspect tuberculosis and nontuberculous mycobacteria (NTM) cases using inpatient and outpatient diagnostic codes, culture results, and anti-tuberculous medication dispensing. We manually reviewed records to validate our case-finding algorithms. We identified 64 tuberculosis and 367 NTM potential cases, respectively. For tuberculosis, diagnostic code positive predictive value (PPV) was 54% at KPNC and 9% at PVAMC. Adding medication dispensings improved these to 87% and 46%, respectively. Positive tuberculosis cultures had a PPV of 100% with sensitivities of 79% (KPNC) and 55% (PVAMC). For NTM, the PPV of diagnostic codes was 91% (KPNC) and 76% (PVAMC). At KPNC, ≥ 1 positive NTM culture was sensitive (100%) and specific (PPV, 74%) if non-pathogenic species were excluded; at PVAMC, ≥1 positive NTM culture identified 76% of cases with PPV of 41%. Application of the American Thoracic Society NTM microbiology criteria yielded the highest PPV (100% KPNC, 78% PVAMC). The sensitivity and predictive value of electronic microbiologic data for tuberculosis and NTM infections is generally high, but varies with different facilities or models of care. Unlike NTM, tuberculosis diagnostic codes have poor PPV, and in the absence of laboratory data, should be combined with anti-tuberculous therapy dispensings for pharmacoepidemiologic research. Copyright © 2010 John Wiley & Sons, Ltd.

Estimating the incremental net health benefit of requirements for cardiovascular risk evaluation for diabetes therapies

PubMed Central

Chawla, Anita J; Mytelka, Daniel S; McBride, Stephan D; Nellesen, Dave; Elkins, Benjamin R; Ball, Daniel E; Kalsekar, Anupama; Towse, Adrian; Garrison, Louis P

2014-01-01

Purpose To evaluate the advantages and disadvantages of pre-approval requirements for safety data to detect cardiovascular (CV) risk contained in the December 2008 U.S. Food and Drug Administration (FDA) guidance for developing type 2 diabetes drugs compared with the February 2008 FDA draft guidance from the perspective of diabetes population health. Methods We applied the incremental net health benefit (INHB) framework to quantify the benefits and risks of investigational diabetes drugs using a common survival metric (life-years [LYs]). We constructed a decision analytic model for clinical program development consistent with the requirements of each guidance and simulated diabetes drugs, some of which had elevated CV risk. Assuming constant research budgets, we estimate the impact of increased trial size on drugs investigated. We aggregate treatment benefit and CV risks for each approved drug over a 35-year horizon under each guidance. Results The quantitative analysis suggests that the December 2008 guidance adversely impacts diabetes population health. INHB was −1.80 million LYs, attributable to delayed access to diabetes therapies (−0.18 million LYs) and fewer drugs (−1.64 million LYs), but partially offset by reduced CV risk exposure (0.02 million LYs). Results were robust in sensitivity analyses. Conclusion The health outcomes impact of all potential benefits and risks should be evaluated in a common survival measure, including health gain from avoided adverse events, lost health benefits from delayed or forgone efficacious products, and impact of alternative policy approaches. Quantitative analysis of the December 2008 FDA guidance for diabetes therapies indicates that negative impact on patient health will result. © 2014 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd. PMID:24892175

Estimating the incremental net health benefit of requirements for cardiovascular risk evaluation for diabetes therapies.

PubMed

Chawla, Anita J; Mytelka, Daniel S; McBride, Stephan D; Nellesen, Dave; Elkins, Benjamin R; Ball, Daniel E; Kalsekar, Anupama; Towse, Adrian; Garrison, Louis P

2014-03-01

To evaluate the advantages and disadvantages of pre-approval requirements for safety data to detect cardiovascular (CV) risk contained in the December 2008 U.S. Food and Drug Administration (FDA) guidance for developing type 2 diabetes drugs compared with the February 2008 FDA draft guidance from the perspective of diabetes population health. We applied the incremental net health benefit (INHB) framework to quantify the benefits and risks of investigational diabetes drugs using a common survival metric (life-years [LYs]). We constructed a decision analytic model for clinical program development consistent with the requirements of each guidance and simulated diabetes drugs, some of which had elevated CV risk. Assuming constant research budgets, we estimate the impact of increased trial size on drugs investigated. We aggregate treatment benefit and CV risks for each approved drug over a 35-year horizon under each guidance. The quantitative analysis suggests that the December 2008 guidance adversely impacts diabetes population health. INHB was -1.80 million LYs, attributable to delayed access to diabetes therapies (-0 .18 million LYs) and fewer drugs (-1.64 million LYs), but partially offset by reduced CV risk exposure (0.02 million LYs). Results were robust in sensitivity analyses. The health outcomes impact of all potential benefits and risks should be evaluated in a common survival measure, including health gain from avoided adverse events, lost health benefits from delayed or for gone efficacious products, and impact of alternative policy approaches. Quantitative analysis of the December 2008 FDA guidance for diabetes therapies indicates that negative impact on patient health will result. Copyright © 2014 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd.

Patient engagement impacts glycemic management with vildagliptin and vildagliptin/metformin (single pill) regimens in type 2 diabetes mellitus (the GLORIOUS study).

PubMed

Hermans, Michel; Van Gaal, Luc; Rézette, Ingrid; Daci, Evis; MacDonald, Karen; Denhaerynck, Kris; Vancayzeele, Stefaan; De Meester, Lut; Clemens, Andreas; Yee, Brian; Abraham, Ivo

2016-12-01

To evaluate the real-world effectiveness of vildagliptin and vildagliptin/metformin, combined with patient engagement, on glycemic outcomes. Patient engagement included both clinicians' engaging patients through education and counseling; and patients' self-engagement through disease awareness, lifestyle changes, and medication adherence. Prospective, observational, open-label, multi-center, pharmacoepidemiologic study of type 2 diabetes mellitus (T2DM) patients treated de novo with vildagliptin or vildagliptin/metformin. Data were collected at baseline (treatment initiation), 105±15d, and ≥145d. The evaluable sample included 896 mainly male (58%), overweight (mean±SD BMI=30.3±5.4kg/m 2 ), in later middle age (mean±SD age=64±11years) patients. Over the three visits, mean(±SD) HbA1c levels declined from 8.1%(±1.0) to 7.3%(±1.0) to 7.2%(±0.9); HbA1c control rates rose from 7% to 36% to 43%. Mean±SD FPG levels decreased from 170(±49) to 141(±41) to 139(±42)mg/dL; control rates increased from 12% to 39% to 43% (all p<0.0001). Weight decreased nominally by 2kg (p=0.0290) and BMI by 0.8kg/m 2 (p<0.0001). Modeling showed patient engagement activities by clinicians and by patients to be major determinants of glycemic outcomes. No unknown safety signals were detected. Vildagliptin and vildagliptin/metformin are effective and safe oral agents in the management of T2DM, especially if part of a treatment program with active patient engagement by clinicians and empowered patients. Copyright © 2016 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.

Human papillomavirus vaccine and demyelinating diseases-A systematic review and meta-analysis.

PubMed

Mouchet, Julie; Salvo, Francesco; Raschi, Emanuel; Poluzzi, Elisabetta; Antonazzo, Ippazio Cosimo; De Ponti, Fabrizio; Bégaud, Bernard

2018-06-01

Approved in 2006, human papillomavirus (HPV) vaccines were initially targeted for girls aged 9-14 years. Although the safety of these vaccines has been monitored through post-licensure surveillance programmes, cases of neurological events have been reported worldwide. The present study aimed to assess the risk of developing demyelination after HPV immunization by meta-analysing risk estimates from pharmacoepidemiologic studies. A systematic review was conducted in Medline, Embase, ISI Web of Science and the Cochrane Library from inception to 10 May 2017, without language restriction. Only observational studies including a control group were retained. Study selection was performed by two independent reviewers with disagreements solved through discussion. This meta-analysis was performed using a generic inverse variance random-effect model. Outcomes of interest included a broad category of central demyelination, multiple sclerosis (MS), optic neuritis (ON), and Guillain-Barré syndrome (GBS), each being considered independently. Heterogeneity was investigated; sensitivity and subgroup analyses were performed when necessary. In parallel, post-licensure safety studies were considered for a qualitative review. This study followed the PRISMA statement and the MOOSE reporting guideline. Of the 2,863 references identified, 11 articles were selected for meta-analysis. No significant association emerged between HPV vaccination and central demyelination, the pooled odds ratio being 0.96 [95% CI 0.77-1.20], with a moderate but non-significant heterogeneity (I 2  = 29%). Similar results were found for MS and ON. Sensitivity analyses did not alter our conclusions. Findings from qualitative review of 14 safety studies concluded in an absence of a relevant signal. Owing to limited data on GBS, no meta-analysis was performed for this outcome. This study strongly supports the absence of association between HPV vaccines and central demyelination. Copyright © 2018 Elsevier Ltd. All rights reserved.

Association of fasting serum insulin and cancer mortality in a healthy population - 28-year follow-up of the French TELECOM Study.

PubMed

Wargny, M; Balkau, B; Lange, C; Charles, M-A; Giral, P; Simon, D

2018-02-01

Epidemiologic, pharmacoepidemiologic and pathophysiologic evidence points consistently to an association between type 2 diabetes and cancer. This association could be explained by hyperinsulinemia induced by insulin resistance. We studied the association between fasting serum insulin (FSI) and cancer mortality in a population of non-diabetic individuals. We followed 3117 healthy workers (50.2% women), included in the TELECOM cohort study, between 1985 and 1987; their median age was 38 years (Q1-Q3=30-50). Baseline FSI was measured by radioimmunoassay, the INSI-PR method. People with diabetes or cancer at baseline were excluded. Vital status and causes of death were available until December 2013. The association between FSI and cancer deaths was analysed by sex, using a Cox proportional hazards model with age as the time scale, adjusting for body mass index, smoking habits, alcohol consumption, occupational category and ethnic origin. After a 28-year follow-up, 330 (10.6%) deaths were reported, among which, 150 were cancer-related (80 men, 70 women). In men, the association between FSI and death by cancer was J-shaped: compared to the average FSI of 7.1mU/L, men with 5mU/L and 12.9mU/L had respectively adjusted hazard-ratios (HR) of 1.88 (95% confidence interval, 1.00-3.56) and 2.30 (95% CI, 1.34-3.94). Among women, no significant association was found (adjusted HR, 1.03; 95% CI, 0.96-1.11) for an increase of 1mU/L in FSI. These results strengthen the hypothesis of an independent risk of cancer death associated with extreme values of FSI, mainly the highest, among men, but not among women. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Hormonal contraception increases the risk of psychotropic drug use in adolescent girls but not in adults: A pharmacoepidemiological study on 800 000 Swedish women.

PubMed

Zettermark, Sofia; Perez Vicente, Raquel; Merlo, Juan

2018-01-01

The burden of depression and anxiety disorders is greater in women, and female sex hormones have been shown to affect mood. Psychological side effects of hormonal contraception (HC) are also a common complaint in the clinic, but few previous studies have investigated this subject. We therefore wanted to investigate whether use of HC was associated with adverse psychological health outcomes, and whether this association was modified by age. All women aged 12-30 years on 31 December 2010, residing in Sweden for at least four years and with no previous psychiatric morbidity (n = 815 662), were included. We followed the women from their first HC use (or 31 December 2010, if they were non-users) at baseline, until a prescription fill of psychotropic drugs or the end of the one-year follow-up. We performed age-stratified logistic regression models and estimated odds ratios (OR) to measure the association between different HC methods and psychotropic drug use, as well as the area under the receiver operating curve to estimate discriminatory accuracy of HC in relation to psychotropic drugs. Overall, we found an association between HC and psychotropic drugs (adjusted OR 1.34, 95% confidence interval [CI] 1.30-1.37). In the age-stratified analysis, the strongest association was found in adolescent girls (adjusted OR 3.46, 95% CI 3.04-4.94 for age 12 to 14 years), while it was non-existent for adult women. We conclude that hormonal contraception is associated with psychotropic drug use among adolescent girls, suggesting an adverse effect of HC on psychological health in this population.

Progress on Fault Mechanisms for Gear Transmissions in Coal Cutting Machines: From Macro to Nano Models.

PubMed

Jiang, Yu; Zhang, Xiaogang; Zhang, Chao; Li, Zhixiong; Sheng, Chenxing

2017-04-01

Numerical modeling has been recognized as the dispensable tools for mechanical fault mechanism analysis. Techniques, ranging from macro to nano levels, include the finite element modeling boundary element modeling, modular dynamic modeling, nano dynamic modeling and so forth. This work firstly reviewed the progress on the fault mechanism analysis for gear transmissions from the tribological and dynamic aspects. Literature review indicates that the tribological and dynamic properties were separately investigated to explore the fault mechanism in gear transmissions. However, very limited work has been done to address the links between the tribological and dynamic properties and scarce researches have been done for coal cutting machines. For this reason, the tribo-dynamic coupled model was introduced to bridge the gap between the tribological and dynamic models in fault mechanism analysis for gear transmissions in coal cutting machines. The modular dynamic modeling and nano dynamic modeling techniques are expected to establish the links between the tribological and dynamic models. Possible future research directions using the tribo dynamic coupled model were summarized to provide potential references for researchers in the field.

Moving alcohol prevention research forward-Part II: new directions grounded in community-based system dynamics modeling.

PubMed

Apostolopoulos, Yorghos; Lemke, Michael K; Barry, Adam E; Lich, Kristen Hassmiller

2018-02-01

Given the complexity of factors contributing to alcohol misuse, appropriate epistemologies and methodologies are needed to understand and intervene meaningfully. We aimed to (1) provide an overview of computational modeling methodologies, with an emphasis on system dynamics modeling; (2) explain how community-based system dynamics modeling can forge new directions in alcohol prevention research; and (3) present a primer on how to build alcohol misuse simulation models using system dynamics modeling, with an emphasis on stakeholder involvement, data sources and model validation. Throughout, we use alcohol misuse among college students in the United States as a heuristic example for demonstrating these methodologies. System dynamics modeling employs a top-down aggregate approach to understanding dynamically complex problems. Its three foundational properties-stocks, flows and feedbacks-capture non-linearity, time-delayed effects and other system characteristics. As a methodological choice, system dynamics modeling is amenable to participatory approaches; in particular, community-based system dynamics modeling has been used to build impactful models for addressing dynamically complex problems. The process of community-based system dynamics modeling consists of numerous stages: (1) creating model boundary charts, behavior-over-time-graphs and preliminary system dynamics models using group model-building techniques; (2) model formulation; (3) model calibration; (4) model testing and validation; and (5) model simulation using learning-laboratory techniques. Community-based system dynamics modeling can provide powerful tools for policy and intervention decisions that can result ultimately in sustainable changes in research and action in alcohol misuse prevention. © 2017 Society for the Study of Addiction.

Overview of the GRC Stirling Convertor System Dynamic Model

NASA Technical Reports Server (NTRS)

Lewandowski, Edward J.; Regan, Timothy F.

2004-01-01

A Stirling Convertor System Dynamic Model has been developed at the Glenn Research Center for controls, dynamics, and systems development of free-piston convertor power systems. It models the Stirling cycle thermodynamics, heat flow, gas, mechanical, and mounting dynamics, the linear alternator, and the controller. The model's scope extends from the thermal energy input to thermal, mechanical dynamics, and electrical energy out, allowing one to study complex system interactions among subsystems. The model is a non-linear time-domain model containing sub-cycle dynamics, allowing it to simulate transient and dynamic phenomena that other models cannot. The model details and capability are discussed.

[Are newspapers a reliable source of information about doping in sports?].

PubMed

Durrieu, Geneviève; Gorsse, Elisabeth; Montastruc, Jean-Louis

2004-01-01

To study the coverage by French newspapers of doping in sports, we performed a systematic review of articles appearing between January and March 2003 on the following French websites: L'Equipe, Le Monde, Le Figaro, Libération, La Dépêche du Midi and Agence France-Presse (AFP). We recorded a total of 58 articles about doping. Among them, 48 (83%) were collected from the AFP news. L'Equipe, a French sports newspaper, published seven articles (12%). Most of the recorded data reported results of worldwide antidoping control (71%). No information about new drugs was found. The analysis of the selected articles pointed out the following: (i) the seriousness of observations related to doping since, during this 3-month period, we noted two deaths of athletes; (ii) the risks associated with the use of dietary supplements, particularly products including amphetamine derivatives; (iii) the interest in judicial investigation as an information source about doping in sports (investigation of suspicious deaths of Italian football players); and (iv) identification of the sports involved in doping (cycling, but also athletics, football, rugby). Systematic analysis of newspaper reports can be considered as a relevant method for monitoring the pharmacovigilance and pharmacoepidemiology of doping in sports.

Self-reported skin diseases, quality of life and medication use: a nationwide pharmaco-epidemiological survey in Sweden.

PubMed

Lindberg, Magnus; Isacson, Dag; Bingefors, Kerstin

2014-03-01

The aim of this study was to determine self-reported consumption of dermatological pharmaceuticals and quality of life (QoL), measured with Short Form 36, in relation to eczema, acne, psoriasis and other inflammatory skin conditions in the Swedish population. A questionnaire containing questions on the occurrence of skin diseases, health-related QoL and the use of pharmaceuticals was sent to a cross-sectional sample of the Swedish population, age range 18-84 years (n = 8,000). The response rate was 61%. The 1-year prevalence of skin diseases was 30-35%, with females reporting a higher prevalence. The prevalence was 11.5% for eczema other than hand eczema, 10.2% for acne, 7.5% for hand eczema, 3.9% for psoriasis and 3.1% for urticaria. QoL was significantly affected and 25% of females and 19% of males had used a dermatological drug. Compared with hand eczema, persons with psoriasis and other eczema reported significantly more use of topical steroids on prescription and more use of dermatological pharmaceuticals in total. Skin conditions are common; they affect QoL and lead to a high consumption of dermatological drugs; which deserves increased awareness in the society.

Validation of a computer case definition for sudden cardiac death in opioid users

PubMed Central

2012-01-01

Background To facilitate the use of automated databases for studies of sudden cardiac death, we previously developed a computerized case definition that had a positive predictive value between 86% and 88%. However, the definition has not been specifically validated for prescription opioid users, for whom out-of-hospital overdose deaths may be difficult to distinguish from sudden cardiac death. Findings We assembled a cohort of persons 30-74 years of age prescribed propoxyphene or hydrocodone who had no life-threatening non-cardiovascular illness, diagnosed drug abuse, residence in a nursing home in the past year, or hospital stay within the past 30 days. Medical records were sought for a sample of 140 cohort deaths within 30 days of a prescription fill meeting the computer case definition. Of the 140 sampled deaths, 81 were adjudicated; 73 (90%) were sudden cardiac deaths. Two deaths had possible opioid overdose; after removing these two the positive predictive value was 88%. Conclusions These findings are consistent with our previous validation studies and suggest the computer case definition of sudden cardiac death is a useful tool for pharmacoepidemiologic studies of opioid analgesics. PMID:22938531

An investigation of the representativity of neuropsychiatrists and their patients in a drug utilization observation study on fluoxetine.

PubMed

Schaaf, B; Linden, M; Weber, H J

1997-01-01

This study presents a methodological approach to an expost facto investigation of sample bias in drug utilization observation (DUO) studies using the example of a DUO with the nontricyclic antidepressant fluoxetine. A total of 479 psychiatrists and neurologists and 2,401 patients were investigated. The purpose of the study was to judge the representativeness of our DUO sample for two populations: first, for all psychiatrics and neurologists prescribing fluoxetine or all patients being treated with fluoxetine in Germany and, second, for all psychiatrists and neurologists prescribing antidepressants or all patients being treated with antidepressants in Germany. Criteria for the representativeness test were physician variables (gender, size of community where practicing, federal state, age, volume of prescriptions) and patient variables (gender, age, prescription-related diagnosis, concurrent illnesses, concomitant medications). The study shows that the DUO sample can rightfully claim representativeness in the majority of parameters for the psychiatrists and neurologists prescribing fluoxetine and for the patients being treated with fluoxetine. There are more noticeable discrepancies with regard to the psychiatrists and neurologists in general and to the patients being treated with antidepressants in general. The methodological problems of pharmacoepidemiological investigation of representativeness are discussed.

Supplementing electronic health records through sample collection and patient diaries: A study set within a primary care research database.

PubMed

Joseph, Rebecca M; Soames, Jamie; Wright, Mark; Sultana, Kirin; van Staa, Tjeerd P; Dixon, William G

2018-02-01

To describe a novel observational study that supplemented primary care electronic health record (EHR) data with sample collection and patient diaries. The study was set in primary care in England. A list of 3974 potentially eligible patients was compiled using data from the Clinical Practice Research Datalink. Interested general practices opted into the study then confirmed patient suitability and sent out postal invitations. Participants completed a drug-use diary and provided saliva samples to the research team to combine with EHR data. Of 252 practices contacted to participate, 66 (26%) mailed invitations to patients. Of the 3974 potentially eligible patients, 859 (22%) were at participating practices, and 526 (13%) were sent invitations. Of those invited, 117 (22%) consented to participate of whom 86 (74%) completed the study. We have confirmed the feasibility of supplementing EHR with data collected directly from patients. Although the present study successfully collected essential data from patients, it also underlined the requirement for improved engagement with both patients and general practitioners to support similar studies. © 2017 The Authors. Pharmacoepidemiology & Drug Safety published by John Wiley & Sons Ltd.

Testability of evolutionary game dynamics based on experimental economics data

NASA Astrophysics Data System (ADS)

Wang, Yijia; Chen, Xiaojie; Wang, Zhijian

In order to better understand the dynamic processes of a real game system, we need an appropriate dynamics model, so to evaluate the validity of a model is not a trivial task. Here, we demonstrate an approach, considering the dynamical macroscope patterns of angular momentum and speed as the measurement variables, to evaluate the validity of various dynamics models. Using the data in real time Rock-Paper-Scissors (RPS) games experiments, we obtain the experimental dynamic patterns, and then derive the related theoretical dynamic patterns from a series of typical dynamics models respectively. By testing the goodness-of-fit between the experimental and theoretical patterns, the validity of the models can be evaluated. One of the results in our study case is that, among all the nonparametric models tested, the best-known Replicator dynamics model performs almost worst, while the Projection dynamics model performs best. Besides providing new empirical macroscope patterns of social dynamics, we demonstrate that the approach can be an effective and rigorous tool to test game dynamics models. Fundamental Research Funds for the Central Universities (SSEYI2014Z) and the National Natural Science Foundation of China (Grants No. 61503062).

Testability of evolutionary game dynamics based on experimental economics data

NASA Astrophysics Data System (ADS)

Wang, Yijia; Chen, Xiaojie; Wang, Zhijian

2017-11-01

Understanding the dynamic processes of a real game system requires an appropriate dynamics model, and rigorously testing a dynamics model is nontrivial. In our methodological research, we develop an approach to testing the validity of game dynamics models that considers the dynamic patterns of angular momentum and speed as measurement variables. Using Rock-Paper-Scissors (RPS) games as an example, we illustrate the geometric patterns in the experiment data. We then derive the related theoretical patterns from a series of typical dynamics models. By testing the goodness-of-fit between the experimental and theoretical patterns, we show that the validity of these models can be evaluated quantitatively. Our approach establishes a link between dynamics models and experimental systems, which is, to the best of our knowledge, the most effective and rigorous strategy for ascertaining the testability of evolutionary game dynamics models.

RELATING ACCUMULATOR MODEL PARAMETERS AND NEURAL DYNAMICS

PubMed Central

Purcell, Braden A.; Palmeri, Thomas J.

2016-01-01

Accumulator models explain decision-making as an accumulation of evidence to a response threshold. Specific model parameters are associated with specific model mechanisms, such as the time when accumulation begins, the average rate of evidence accumulation, and the threshold. These mechanisms determine both the within-trial dynamics of evidence accumulation and the predicted behavior. Cognitive modelers usually infer what mechanisms vary during decision-making by seeing what parameters vary when a model is fitted to observed behavior. The recent identification of neural activity with evidence accumulation suggests that it may be possible to directly infer what mechanisms vary from an analysis of how neural dynamics vary. However, evidence accumulation is often noisy, and noise complicates the relationship between accumulator dynamics and the underlying mechanisms leading to those dynamics. To understand what kinds of inferences can be made about decision-making mechanisms based on measures of neural dynamics, we measured simulated accumulator model dynamics while systematically varying model parameters. In some cases, decision- making mechanisms can be directly inferred from dynamics, allowing us to distinguish between models that make identical behavioral predictions. In other cases, however, different parameterized mechanisms produce surprisingly similar dynamics, limiting the inferences that can be made based on measuring dynamics alone. Analyzing neural dynamics can provide a powerful tool to resolve model mimicry at the behavioral level, but we caution against drawing inferences based solely on neural analyses. Instead, simultaneous modeling of behavior and neural dynamics provides the most powerful approach to understand decision-making and likely other aspects of cognition and perception. PMID:28392584

Dynamic modeling method for infrared smoke based on enhanced discrete phase model

NASA Astrophysics Data System (ADS)

Zhang, Zhendong; Yang, Chunling; Zhang, Yan; Zhu, Hongbo

2018-03-01

The dynamic modeling of infrared (IR) smoke plays an important role in IR scene simulation systems and its accuracy directly influences the system veracity. However, current IR smoke models cannot provide high veracity, because certain physical characteristics are frequently ignored in fluid simulation; simplifying the discrete phase as a continuous phase and ignoring the IR decoy missile-body spinning. To address this defect, this paper proposes a dynamic modeling method for IR smoke, based on an enhanced discrete phase model (DPM). A mathematical simulation model based on an enhanced DPM is built and a dynamic computing fluid mesh is generated. The dynamic model of IR smoke is then established using an extended equivalent-blackbody-molecule model. Experiments demonstrate that this model realizes a dynamic method for modeling IR smoke with higher veracity.

A simple dynamic engine model for use in a real-time aircraft simulation with thrust vectoring

NASA Technical Reports Server (NTRS)

Johnson, Steven A.

1990-01-01

A simple dynamic engine model was developed at the NASA Ames Research Center, Dryden Flight Research Facility, for use in thrust vectoring control law development and real-time aircraft simulation. The simple dynamic engine model of the F404-GE-400 engine (General Electric, Lynn, Massachusetts) operates within the aircraft simulator. It was developed using tabular data generated from a complete nonlinear dynamic engine model supplied by the manufacturer. Engine dynamics were simulated using a throttle rate limiter and low-pass filter. Included is a description of a method to account for axial thrust loss resulting from thrust vectoring. In addition, the development of the simple dynamic engine model and its incorporation into the F-18 high alpha research vehicle (HARV) thrust vectoring simulation. The simple dynamic engine model was evaluated at Mach 0.2, 35,000 ft altitude and at Mach 0.7, 35,000 ft altitude. The simple dynamic engine model is within 3 percent of the steady state response, and within 25 percent of the transient response of the complete nonlinear dynamic engine model.

Dynamic model updating based on strain mode shape and natural frequency using hybrid pattern search technique

NASA Astrophysics Data System (ADS)

Guo, Ning; Yang, Zhichun; Wang, Le; Ouyang, Yan; Zhang, Xinping

2018-05-01

Aiming at providing a precise dynamic structural finite element (FE) model for dynamic strength evaluation in addition to dynamic analysis. A dynamic FE model updating method is presented to correct the uncertain parameters of the FE model of a structure using strain mode shapes and natural frequencies. The strain mode shape, which is sensitive to local changes in structure, is used instead of the displacement mode for enhancing model updating. The coordinate strain modal assurance criterion is developed to evaluate the correlation level at each coordinate over the experimental and the analytical strain mode shapes. Moreover, the natural frequencies which provide the global information of the structure are used to guarantee the accuracy of modal properties of the global model. Then, the weighted summation of the natural frequency residual and the coordinate strain modal assurance criterion residual is used as the objective function in the proposed dynamic FE model updating procedure. The hybrid genetic/pattern-search optimization algorithm is adopted to perform the dynamic FE model updating procedure. Numerical simulation and model updating experiment for a clamped-clamped beam are performed to validate the feasibility and effectiveness of the present method. The results show that the proposed method can be used to update the uncertain parameters with good robustness. And the updated dynamic FE model of the beam structure, which can correctly predict both the natural frequencies and the local dynamic strains, is reliable for the following dynamic analysis and dynamic strength evaluation.

Differential Equation Models for Sharp Threshold Dynamics

DTIC Science & Technology

2012-08-01

dynamics, and the Lanchester model of armed conflict, where the loss of a key capability drastically changes dynamics. We derive and demonstrate a step...dynamics using differential equations. 15. SUBJECT TERMS Differential Equations, Markov Population Process, S-I-R Epidemic, Lanchester Model 16...infection, where a detection event drastically changes dynamics, and the Lanchester model of armed conflict, where the loss of a key capability

Dynamic Factor Analysis Models with Time-Varying Parameters

ERIC Educational Resources Information Center

Chow, Sy-Miin; Zu, Jiyun; Shifren, Kim; Zhang, Guangjian

2011-01-01

Dynamic factor analysis models with time-varying parameters offer a valuable tool for evaluating multivariate time series data with time-varying dynamics and/or measurement properties. We use the Dynamic Model of Activation proposed by Zautra and colleagues (Zautra, Potter, & Reich, 1997) as a motivating example to construct a dynamic factor…

Primary Nonadherence to Oral Anticoagulants in Patients with Atrial Fibrillation: Real-World Data from a Population-Based Cohort.

PubMed

Rodriguez-Bernal, Clara L; Peiró, Salvador; Hurtado, Isabel; García-Sempere, Aníbal; Sanfélix-Gimeno, Gabriel

2018-05-01

Primary nonadherence (not filling a first prescription) is an important yet unstudied aspect of adherence to oral anticoagulant (OAC) therapy. To estimate the rates of primary nonadherence to OACs and determine associated factors in real-world practice. This population-based retrospective cohort study set in the Valencia region of Spain (about 5 million inhabitants) included all patients with atrial fibrillation who were newly prescribed OACs during 2011-2014 (N = 18,715). Primary nonadherence was obtained by linking electronic prescription and dispensing data and assessed by type of OAC-vitamin K antagonists (VKAs) or non-VKA oral anticoagulants (NOACs). Covariates were obtained from diverse databases, including electronic medical records. Multivariate logistic regression models were used to assess characteristics associated with primary nonadherence, adjusting for a propensity score to minimize confounding by indication. Primary nonadherence to OACs was 5.62% (VKA 4.29% vs. NOAC 10.81%; P < 0.001), with varying rates among specific drugs (acenocoumarol 4.2%, warfarin 10.9%, apixaban 5.0%, dabigatran 7.9%, and rivaroxaban 15.5%). After adjusting for potential confounders, the likelihood of not filling the first prescription was higher for NOAC patients than for VKA patients (OR = 2.76, 95% CI = 2.41-3.15). High coinsurance in the older groups (OR = 2.63, 95% CI = 1.47-4.69 for patients aged 66-75 years and OR = 3.02, 95% CI = 1.58-5.76 for patients aged > 75 years); being a non-Spanish European (OR = 1.49, 95% CI = 1.12-1.99); and having dementia (OR = 1.72, 95% CI = 1.37-2.16) were positively associated with primary nonadherence. Electronic transmission of prescriptions (OR = 0.85, 95% CI = 0.74-0.96); liver disease (OR = 0.73, 95% CI = 0.54-0.99); and polypharmacy (OR = 0.59, 95% CI = 0.50-0.70) were inversely associated with primary nonadherence. Overall, primary nonadherence to OACs was relatively low (5%). However, important differences were found between VKAs and NOACs. After adjustment, patients prescribed NOACs nearly tripled the likelihood of nonadherence compared with patients prescribed VKAs, which could negatively affect their effectiveness in clinical practice. Identified correlates were similar to those shown in the limited evidence for other medications. This work was partially supported by the 2013 Collaboration Agreement between the Fundación para el Fomento de la Investigación Sanitaria y Biomédica (FISABIO) from the Valencia Ministry of Health and Boehringer Ingelheim, a nonconditioned program to conduct independent research in chronic health care, pharmacoepidemiology, and medical practice variation. Rodriguez-Bernal was funded by the Instituto de Salud Carlos III, Spanish Ministry of Health, and cofinanced by the European Regional Development Fund (grant number RD12/0001/0005). The views presented here are those of the authors and not necessarily those of the FISABIO Foundation, the Valencia Ministry of Health, or the study sponsors. The funding sources had no access to study data and did not participate in any way in the design or conduct of the study, data analysis, decisions regarding the dissemination of findings, the development of the manuscript, or its publication. Peiró has received fees for participation in scientific meetings and courses sponsored by Novartis and Ferrer International. In 2014, Sanfélix-Gimeno participated in an advisory meeting of Boehringer Ingelheim. García-Sempere is a former employee of Boehringer Ingelheim. Rodriguez-Bernal and Hurtado have no relationships relevant to the contents of this article to disclose. This work was previously submitted as an abstract (podium presentation) at the 31st International Society of Pharmacoepidemiology (ISPE) Annual Conference; August 22-26, 2015; Boston, Massachusetts.

Equivalent Dynamic Models.

PubMed

Molenaar, Peter C M

2017-01-01

Equivalences of two classes of dynamic models for weakly stationary multivariate time series are discussed: dynamic factor models and autoregressive models. It is shown that exploratory dynamic factor models can be rotated, yielding an infinite set of equivalent solutions for any observed series. It also is shown that dynamic factor models with lagged factor loadings are not equivalent to the currently popular state-space models, and that restriction of attention to the latter type of models may yield invalid results. The known equivalent vector autoregressive model types, standard and structural, are given a new interpretation in which they are conceived of as the extremes of an innovating type of hybrid vector autoregressive models. It is shown that consideration of hybrid models solves many problems, in particular with Granger causality testing.

Metapopulation dynamics and the evolution of dispersal

NASA Astrophysics Data System (ADS)

Parvinen, Kalle

A metapopulation consists of local populations living in habitat patches. In this chapter metapopulation dynamics and the evolution of dispersal is studied in two metapopulation models defined in discrete time. In the first model there are finitely many patches, and in the other one there are infinitely many patches, which allows to incorporate catastrophes into the model. In the first model, cyclic local population dynamics can be either synchronized or not, and increasing dispersal both synchronizes and stabilizes metapopulation dynamics. On the other hand, the type of dynamics has a strong effect on the evolution of dispersal. In case of non-synchronized metapopulation dynamics, dispersal is much more beneficial than in the case of synchronized metapopulation dynamics. Local dynamics has a substantial effect also on the possibility of evolutionary branching in both models. Furthermore, with an Allee effect in the local dynamics of the second model, even evolutionary suicide can occur. It is an evolutionary process in which a viable population adapts in such a way that it can no longer persist.

Dynamics of Change and Change in Dynamics

PubMed Central

Boker, Steven M.; Staples, Angela D.; Hu, Yueqin

2017-01-01

A framework is presented for building and testing models of dynamic regulation by categorizing sources of differences between theories of dynamics. A distinction is made between the dynamics of change, i.e., how a system self–regulates on a short time scale, and change in dynamics, i.e., how those dynamics may themselves change over a longer time scale. In order to clarify the categories, models are first built to estimate individual differences in equilibrium value and equilibrium change. Next, models are presented in which there are individual differences in parameters of dynamics such as frequency of fluctuations, damping of fluctuations, and amplitude of fluctuations. Finally, models for within–person change in dynamics over time are proposed. Simulations demonstrating feasibility of these models are presented and OpenMx scripts for fitting these models have been made available in a downloadable archive along with scripts to simulate data so that a researcher may test a selected models’ feasibility within a chosen experimental design. PMID:29046764

A non-linear mathematical model for dynamic analysis of spur gears including shaft and bearing dynamics

NASA Technical Reports Server (NTRS)

Ozguven, H. Nevzat

1991-01-01

A six-degree-of-freedom nonlinear semi-definite model with time varying mesh stiffness has been developed for the dynamic analysis of spur gears. The model includes a spur gear pair, two shafts, two inertias representing load and prime mover, and bearings. As the shaft and bearing dynamics have also been considered in the model, the effect of lateral-torsional vibration coupling on the dynamics of gears can be studied. In the nonlinear model developed several factors such as time varying mesh stiffness and damping, separation of teeth, backlash, single- and double-sided impacts, various gear errors and profile modifications have been considered. The dynamic response to internal excitation has been calculated by using the 'static transmission error method' developed. The software prepared (DYTEM) employs the digital simulation technique for the solution, and is capable of calculating dynamic tooth and mesh forces, dynamic factors for pinion and gear, dynamic transmission error, dynamic bearing forces and torsions of shafts. Numerical examples are given in order to demonstrate the effect of shaft and bearing dynamics on gear dynamics.

Dynamic output feedback control of a flexible air-breathing hypersonic vehicle via T-S fuzzy approach

NASA Astrophysics Data System (ADS)

Hu, Xiaoxiang; Wu, Ligang; Hu, Changhua; Wang, Zhaoqiang; Gao, Huijun

2014-08-01

By utilising Takagi-Sugeno (T-S) fuzzy set approach, this paper addresses the robust H∞ dynamic output feedback control for the non-linear longitudinal model of flexible air-breathing hypersonic vehicles (FAHVs). The flight control of FAHVs is highly challenging due to the unique dynamic characteristics, and the intricate couplings between the engine and fight dynamics and external disturbance. Because of the dynamics' enormous complexity, currently, only the longitudinal dynamics models of FAHVs have been used for controller design. In this work, T-S fuzzy modelling technique is utilised to approach the non-linear dynamics of FAHVs, then a fuzzy model is developed for the output tracking problem of FAHVs. The fuzzy model contains parameter uncertainties and disturbance, which can approach the non-linear dynamics of FAHVs more exactly. The flexible models of FAHVs are difficult to measure because of the complex dynamics and the strong couplings, thus a full-order dynamic output feedback controller is designed for the fuzzy model. A robust H∞ controller is designed for the obtained closed-loop system. By utilising the Lyapunov functional approach, sufficient solvability conditions for such controllers are established in terms of linear matrix inequalities. Finally, the effectiveness of the proposed T-S fuzzy dynamic output feedback control method is demonstrated by numerical simulations.

Extensions to the Dynamic Aerospace Vehicle Exchange Markup Language

NASA Technical Reports Server (NTRS)

Brian, Geoffrey J.; Jackson, E. Bruce

2011-01-01

The Dynamic Aerospace Vehicle Exchange Markup Language (DAVE-ML) is a syntactical language for exchanging flight vehicle dynamic model data. It provides a framework for encoding entire flight vehicle dynamic model data packages for exchange and/or long-term archiving. Version 2.0.1 of DAVE-ML provides much of the functionality envisioned for exchanging aerospace vehicle data; however, it is limited in only supporting scalar time-independent data. Additional functionality is required to support vector and matrix data, abstracting sub-system models, detailing dynamics system models (both discrete and continuous), and defining a dynamic data format (such as time sequenced data) for validation of dynamics system models and vehicle simulation packages. Extensions to DAVE-ML have been proposed to manage data as vectors and n-dimensional matrices, and record dynamic data in a compatible form. These capabilities will improve the clarity of data being exchanged, simplify the naming of parameters, and permit static and dynamic data to be stored using a common syntax within a single file; thereby enhancing the framework provided by DAVE-ML for exchanging entire flight vehicle dynamic simulation models.

Model-free inference of direct network interactions from nonlinear collective dynamics.

PubMed

Casadiego, Jose; Nitzan, Mor; Hallerberg, Sarah; Timme, Marc

2017-12-19

The topology of interactions in network dynamical systems fundamentally underlies their function. Accelerating technological progress creates massively available data about collective nonlinear dynamics in physical, biological, and technological systems. Detecting direct interaction patterns from those dynamics still constitutes a major open problem. In particular, current nonlinear dynamics approaches mostly require to know a priori a model of the (often high dimensional) system dynamics. Here we develop a model-independent framework for inferring direct interactions solely from recording the nonlinear collective dynamics generated. Introducing an explicit dependency matrix in combination with a block-orthogonal regression algorithm, the approach works reliably across many dynamical regimes, including transient dynamics toward steady states, periodic and non-periodic dynamics, and chaos. Together with its capabilities to reveal network (two point) as well as hypernetwork (e.g., three point) interactions, this framework may thus open up nonlinear dynamics options of inferring direct interaction patterns across systems where no model is known.

Calibration of Reduced Dynamic Models of Power Systems using Phasor Measurement Unit (PMU) Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Ning; Lu, Shuai; Singh, Ruchi

2011-09-23

Accuracy of a power system dynamic model is essential to the secure and efficient operation of the system. Lower confidence on model accuracy usually leads to conservative operation and lowers asset usage. To improve model accuracy, identification algorithms have been developed to calibrate parameters of individual components using measurement data from staged tests. To facilitate online dynamic studies for large power system interconnections, this paper proposes a model reduction and calibration approach using phasor measurement unit (PMU) data. First, a model reduction method is used to reduce the number of dynamic components. Then, a calibration algorithm is developed to estimatemore » parameters of the reduced model. This approach will help to maintain an accurate dynamic model suitable for online dynamic studies. The performance of the proposed method is verified through simulation studies.« less

An individual-based model of zebrafish population dynamics accounting for energy dynamics.

PubMed

Beaudouin, Rémy; Goussen, Benoit; Piccini, Benjamin; Augustine, Starrlight; Devillers, James; Brion, François; Péry, Alexandre R R

2015-01-01

Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model) was coupled to an individual based model of zebrafish population dynamics (IBM model). Next, we fitted the DEB model to new experimental data on zebrafish growth and reproduction thus improving existing models. We further analysed the DEB-model and DEB-IBM using a sensitivity analysis. Finally, the predictions of the DEB-IBM were compared to existing observations on natural zebrafish populations and the predicted population dynamics are realistic. While our zebrafish DEB-IBM model can still be improved by acquiring new experimental data on the most uncertain processes (e.g. survival or feeding), it can already serve to predict the impact of compounds at the population level.

An Individual-Based Model of Zebrafish Population Dynamics Accounting for Energy Dynamics

PubMed Central

Beaudouin, Rémy; Goussen, Benoit; Piccini, Benjamin; Augustine, Starrlight; Devillers, James; Brion, François; Péry, Alexandre R. R.

2015-01-01

Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model) was coupled to an individual based model of zebrafish population dynamics (IBM model). Next, we fitted the DEB model to new experimental data on zebrafish growth and reproduction thus improving existing models. We further analysed the DEB-model and DEB-IBM using a sensitivity analysis. Finally, the predictions of the DEB-IBM were compared to existing observations on natural zebrafish populations and the predicted population dynamics are realistic. While our zebrafish DEB-IBM model can still be improved by acquiring new experimental data on the most uncertain processes (e.g. survival or feeding), it can already serve to predict the impact of compounds at the population level. PMID:25938409

Large eddy simulation of spanwise rotating turbulent channel flow with dynamic variants of eddy viscosity model

NASA Astrophysics Data System (ADS)

Jiang, Zhou; Xia, Zhenhua; Shi, Yipeng; Chen, Shiyi

2018-04-01

A fully developed spanwise rotating turbulent channel flow has been numerically investigated utilizing large-eddy simulation. Our focus is to assess the performances of the dynamic variants of eddy viscosity models, including dynamic Vreman's model (DVM), dynamic wall adapting local eddy viscosity (DWALE) model, dynamic σ (Dσ ) model, and the dynamic volumetric strain-stretching (DVSS) model, in this canonical flow. The results with dynamic Smagorinsky model (DSM) and direct numerical simulations (DNS) are used as references. Our results show that the DVM has a wrong asymptotic behavior in the near wall region, while the other three models can correctly predict it. In the high rotation case, the DWALE can get reliable mean velocity profile, but the turbulence intensities in the wall-normal and spanwise directions show clear deviations from DNS data. DVSS exhibits poor predictions on both the mean velocity profile and turbulence intensities. In all three cases, Dσ performs the best.

Benchmarking novel approaches for modelling species range dynamics

PubMed Central

Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H.; Moore, Kara A.; Zimmermann, Niklaus E.

2016-01-01

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species’ range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species’ response to climate change but also emphasise several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species. PMID:26872305

Benchmarking novel approaches for modelling species range dynamics.

PubMed

Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H; Moore, Kara A; Zimmermann, Niklaus E

2016-08-01

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species. © 2016 John Wiley & Sons Ltd.

Modeling SMAP Spacecraft Attitude Control Estimation Error Using Signal Generation Model

NASA Technical Reports Server (NTRS)

Rizvi, Farheen

2016-01-01

Two ground simulation software are used to model the SMAP spacecraft dynamics. The CAST software uses a higher fidelity model than the ADAMS software. The ADAMS software models the spacecraft plant, controller and actuator models, and assumes a perfect sensor and estimator model. In this simulation study, the spacecraft dynamics results from the ADAMS software are used as CAST software is unavailable. The main source of spacecraft dynamics error in the higher fidelity CAST software is due to the estimation error. A signal generation model is developed to capture the effect of this estimation error in the overall spacecraft dynamics. Then, this signal generation model is included in the ADAMS software spacecraft dynamics estimate such that the results are similar to CAST. This signal generation model has similar characteristics mean, variance and power spectral density as the true CAST estimation error. In this way, ADAMS software can still be used while capturing the higher fidelity spacecraft dynamics modeling from CAST software.

Prevalence and Treatment Management of Oropharyngeal Candidiasis in Cancer Patients: Results of the French Candidoscope Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gligorov, Joseph; Bastit, Laurent; Gervais, Honorine

2011-06-01

Purpose: The aim of this pharmaco-epidemiological study was to evaluate the prevalence of oropharyngeal candidiasis (OPC) in cancer patients treated with chemotherapy and/or radiotherapy. Methods and Materials: Signs and symptoms of OPC were noted for all patients. Antifungal therapeutic management was recorded in OPC patients. Patients receiving local antifungal treatments were monitored until the end of treatment. Results: Enrolled in the study were 2,042 patients with solid tumor and/or lymphoma treated with chemotherapy and/or another systemic cancer treatment and/or radiotherapy. The overall prevalence of OPC was 9.6% (95% confidence interval, 8.4%-11.0%]in this population. It was most frequent in patients treatedmore » with combined chemoradiotherapy (22.0%) or with more than two cytotoxic agents (16.9%). Local antifungal treatments were prescribed in 75.0% of OPC patients as recommended by guidelines. The compliance to treatment was higher in patients receiving once-daily miconazole mucoadhesive buccal tablet (MBT; 88.2%) than in those treated with several daily mouthwashes of amphotericin B (40%) or nystatin (18.8%). Conclusion: OPC prevalence in treated cancer patients was high. Local treatments were usually prescribed as per guidelines. Compliance to local treatments was better with once-daily drugs.« less

[Epidemiology of healthcare-associated infections due to MRSA in Brest University Hospital from 2004 to 2007. Impact of hydroalcoholic gel and antibiotics consumptions].

PubMed

Rouzic, N; Tande, D; Payan, C; Garo, B; Garre, M; Lejeune, B

2011-02-01

The fight against healthcare-associated infections is based on preventive measures of multidrug resistant bacteria diffusion. Hand hygiene is the simplest and the most effective preventive measure to reduce cross-transmission of infectious agents. Hydroalcoholic solutions for hand hygiene was recently introduced in the University Hospital of Brest (France). The aims of the study were: to describe the epidemiology of healthcare-associated infections due to methicillin-resistant Staphylococcus aureus (MRSA); to determine the annual consumptions of antistaphylococcal antibiotics; and to discuss the relation between consumption of antiseptic products or antibiotics and the epidemiology of MRSA. A retrospective epidemiological and pharmaco-epidemiological study was realized from January 2004 to December 2007 in the University Hospital of Brest (France). It allowed to bring to light the cases of healthcare-associated infections due to MRSA and to quantify the consumptions of hang hygiene products and antistaphylococcal antibiotics. this retrospective study showed a decrease of healthcare-associated infections due to MRSA and an increase of the consumption of hydroalcoholic solutions. Antistaphylococcal resistance rates also decreased in a context of fall of the global antibiotics consumption in the hospital. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Testosterone Replacement Therapy and Cardiovascular Risk: A Review

PubMed Central

Corona G, Giovanni; Rastrelli, Giulia; Maseroli, Elisa; Sforza, Alessandra

2015-01-01

Recent reports in the scientific and lay press have suggested that testosterone (T) replacement therapy (TRT) is likely to increase cardiovascular (CV) risk. In a final report released in 2015, the Food and Drug Administration (FDA) cautioned that prescribing T products is approved only for men who have low T levels due to primary or secondary hypogonadism resulting from problems within the testis, pituitary, or hypothalamus (e.g., genetic problems or damage from surgery, chemotherapy, or infection). In this report, the FDA emphasized that the benefits and safety of T medications have not been established for the treatment of low T levels due to aging, even if a man's symptoms seem to be related to low T. In this paper, we reviewed the available evidence on the association between TRT and CV risk. In particular, data from randomized controlled studies and information derived from observational and pharmacoepidemiological investigations were scrutinized. The data meta-analyzed here do not support any causal role between TRT and adverse CV events. This is especially true when hypogonadism is properly diagnosed and replacement therapy is correctly performed. Elevated hematocrit represents the most common adverse event related to TRT. Hence, it is important to monitor hematocrit at regular intervals in T-treated subjects in order to avoid potentially serious adverse events. PMID:26770933

Proton Pump Inhibitors and Kidney Disease - GI Upset for the Nephrologist?

PubMed

Toth-Manikowski, Stephanie; Grams, Morgan E

2017-05-01

Widely regarded as safe and effective, proton pump inhibitors (PPIs) are among the most commonly used medications in the world today. However, a spate of observational studies suggest an association between PPI use and adverse events, including infection, bone fracture, and dementia. This review details evidence linking the use of PPI therapy to the development of kidney disease, including early case reports of acute interstitial nephritis and subsequent large observational studies of acute kidney injury (AKI), chronic kidney disease (CKD), and end-stage renal disease (ESRD). The majority of studies showed higher risk of kidney outcomes among persons prescribed PPI medications, with effect sizes that were slightly higher for AKI (∼2-3-fold) compared to CKD and ESRD (1.2-1.8-fold). Although observational pharmaco-epidemiology studies are limited by the possibility of residual confounding and confounding by indication, many of the described studies conducted rigorous sensitivity analyses aimed at minimizing these biases, including new-user design, comparison to similar agents (e.g., histamine 2 receptor antagonists), and evaluation for a dose-response, with robust results. Given the widespread use of PPIs, even a small effect on kidney outcomes could result in large public health burden. Timely cessation of PPI therapy when there is no clear indication for use might reduce the population burden of kidney disease.

Assessment of cardiovascular disease risk in patients with schizophrenia spectrum disorders in German psychiatric hospitals: results of the pharmacoepidemiologic CATS study.

PubMed

Deuschle, M; Paul, F; Brosz, M; Bergemann, N; Franz, M; Kammerer-Ciernioch, J; Lautenschlager, M; Lederbogen, F; Roesch-Ely, D; Weisbrod, M; Kahl, K G; Reichmann, J; Gross, J; Umbreit, J

2013-08-01

Patients with severe mental illness are at high risk for metabolic and cardiac disorders. Thus, monitoring of cardiovascular risks is imperative and schedules for screening for lipids, glucose, body mass index (BMI), waist-hip ratio and blood pressure have been developed. We intended to analyze screening for metabolic disorders in German patients with schizophrenia spectrum disorders in routine psychiatric care. We included 674 patients with any F2 diagnosis in out- and inpatient settings and analyzed metabolic screening procedures as practiced under conditions of usual care. Except BMI (54 %), all other values were documented only in a minority of patients: waist circumference (23 %), cholesterol (28 %), fasting glucose (19 %), triglycerides (25 %) and blood pressure (37 %). We found evidence for less than perfect quality of blood pressure measures. The group of patients who met the individual metabolic syndrome ATP III criteria was comparable to the US CATIE trial. We conclude that frequency and quality of metabolic monitoring in German in- and outpatients settings are not in accordance with the respective recommendations. Similar to previous reports we found evidence for a high prevalence of metabolic disturbances in German patients with schizophrenia spectrum disorders.

Observational Research Opportunities and Limitations

PubMed Central

Boyko, Edward J.

2013-01-01

Medical research continues to progress in its ability to identify treatments and characteristics associated with benefits and adverse outcomes. The principle engine for the evaluation of treatment efficacy is the randomized controlled trial (RCT). Due to the cost and other considerations, RCTs cannot address all clinically important decisions. Observational research often is used to address issues not addressed or not addressable by RCTs. This article provides an overview of the benefits and limitations of observational research to serve as a guide to the interpretation of this category of research designs in diabetes investigations. The potential for bias is higher in observational research but there are design and analysis features that can address these concerns although not completely eliminate them. Pharmacoepidemiologic research may provide important information regarding relative safety and effectiveness of diabetes pharmaceuticals. Such research must effectively address the important issue of confounding by indication in order to produce clinically meaningful results. Other methods such as instrumental variable analysis are being employed to enable stronger causal inference but these methods also require fulfillment of several key assumptions that may or may not be realistic. Nearly all clinical decisions involve probabilistic reasoning and confronting uncertainly, so a realistic goal for observational research may not be the high standard set by RCTs but instead the level of certainty needed to influence a diagnostic or treatment decision. PMID:24055326

Observational research--opportunities and limitations.

PubMed

Boyko, Edward J

2013-01-01

Medical research continues to progress in its ability to identify treatments and characteristics associated with benefits and adverse outcomes. The principal engine for the evaluation of treatment efficacy is the randomized controlled trial (RCT). Due to the cost and other considerations, RCTs cannot address all clinically important decisions. Observational research often is used to address issues not addressed or not addressable by RCTs. This article provides an overview of the benefits and limitations of observational research to serve as a guide to the interpretation of this category of research designs in diabetes investigations. The potential for bias is higher in observational research but there are design and analysis features that can address these concerns although not completely eliminate them. Pharmacoepidemiologic research may provide important information regarding relative safety and effectiveness of diabetes pharmaceuticals. Such research must effectively address the important issue of confounding by indication in order to produce clinically meaningful results. Other methods such as instrumental variable analysis are being employed to enable stronger causal inference but these methods also require fulfillment of several key assumptions that may or may not be realistic. Nearly all clinical decisions involve probabilistic reasoning and confronting uncertainly, so a realistic goal for observational research may not be the high standard set by RCTs but instead the level of certainty needed to influence a diagnostic or treatment decision. © 2013.

Hypnotics use in children 0-18 months: moderate agreement between mother-reported survey data and prescription registry data.

PubMed

Holdø, Ingvild; Bramness, Jørgen G; Handal, Marte; Torgersen, Leila; Reichborn-Kjennerud, Ted; Ystrøm, Eivind; Nordeng, Hedvig; Skurtveit, Svetlana

2017-01-01

Different methods in pharmacoepidemiology can be used to study hypnotic use in children. But neither questionnaire-based data nor prescription records can be considered a "gold standard". This study aimed to investigate the agreement between mother-reported questionnaire-based data and prescription record data for hypnotic drugs in children aged 0-18 months. The agreement was compared to the agreement for a group of antiepileptic drugs. Prescription record data were collected from the Norwegian prescription database for 47,413 children also surveyed in the Norwegian mother and child cohort between 2005 and 2009. Agreement between in the two data sources was calculated using Cohens Kappa. Multinomial logistic regression was used to calculate the effect of sociodemographic variables on discrepancies in data sources. The agreement between mother-reported and dispensed hypnotics was less than 50% for all hypnotics. Sensitivity of reporting increased with number of filled prescriptions. The agreement of antiepileptic drugs was 92.9% in the same population. Of several sociodemographic factors only paternal educational level and maternal work situation was significantly related to agreement between prescription record and survey data. There was a moderate agreement between reported use and dispensed hypnotic drugs for infants and toddlers. Results indicate that sociodemographic factors play only a minor role in explaining discrepancy.

Frequency and co-prescription pattern of Chinese herbal products for hypertension in Taiwan: a Cohort study.

PubMed

Yang, Pei-Rung; Shih, Wei-Tai; Chu, Yen-Hua; Chen, Pau-Chung; Wu, Ching-Yuan

2015-06-06

Chinese herbal products (CHPs) have been frequently used among patients with chronic diseases including hypertension; however, the co-prescription pattern of herbal formulae and single herbs remain uncharacterized. Thus, this large-scale pharmacoepidemiological study evaluated the frequency and co-prescription pattern of CHPs for treating hypertension in Taiwan from 2003 to 2009. The database of traditional Chinese medicine (TCM) outpatient claims was obtained from the National Health Insurance in Taiwan. Patients with hypertension during study period were defined according to diagnostic codes in the International Classification of Disease Ninth Revision, Clinical Modification. The frequencies and percentages of herbal formula and single herb prescriptions for hypertension were analyzed. We also applied association rules to evaluate the CHPs co-prescription patterns. The hypertension cohort included 154,083 patients, 123,240 patients of which (approximately 80 %) had used TCM at least once. In total, 81,582 visits involving CHP prescriptions were hypertension related; Tian-Ma-Gou-Teng-Yin and Dan Shen (Radix Salvia Miltiorrhizae) were the most frequently prescribed herbal formula and single herb, respectively, for treating hypertension. This study elucidated the utilization pattern of CHPs for treating hypertension. Future studies on the efficacy and safety of these CHPs and on drug-herb interactions are warranted.

Adverse drug events with hyperkalaemia during inpatient stays: evaluation of an automated method for retrospective detection in hospital databases

PubMed Central

2014-01-01

Background Adverse drug reactions and adverse drug events (ADEs) are major public health issues. Many different prospective tools for the automated detection of ADEs in hospital databases have been developed and evaluated. The objective of the present study was to evaluate an automated method for the retrospective detection of ADEs with hyperkalaemia during inpatient stays. Methods We used a set of complex detection rules to take account of the patient’s clinical and biological context and the chronological relationship between the causes and the expected outcome. The dataset consisted of 3,444 inpatient stays in a French general hospital. An automated review was performed for all data and the results were compared with those of an expert chart review. The complex detection rules’ analytical quality was evaluated for ADEs. Results In terms of recall, 89.5% of ADEs with hyperkalaemia “with or without an abnormal symptom” were automatically identified (including all three serious ADEs). In terms of precision, 63.7% of the automatically identified ADEs with hyperkalaemia were true ADEs. Conclusions The use of context-sensitive rules appears to improve the automated detection of ADEs with hyperkalaemia. This type of tool may have an important role in pharmacoepidemiology via the routine analysis of large inter-hospital databases. PMID:25212108

Adverse drug events with hyperkalaemia during inpatient stays: evaluation of an automated method for retrospective detection in hospital databases.

PubMed

Ficheur, Grégoire; Chazard, Emmanuel; Beuscart, Jean-Baptiste; Merlin, Béatrice; Luyckx, Michel; Beuscart, Régis

2014-09-12

Adverse drug reactions and adverse drug events (ADEs) are major public health issues. Many different prospective tools for the automated detection of ADEs in hospital databases have been developed and evaluated. The objective of the present study was to evaluate an automated method for the retrospective detection of ADEs with hyperkalaemia during inpatient stays. We used a set of complex detection rules to take account of the patient's clinical and biological context and the chronological relationship between the causes and the expected outcome. The dataset consisted of 3,444 inpatient stays in a French general hospital. An automated review was performed for all data and the results were compared with those of an expert chart review. The complex detection rules' analytical quality was evaluated for ADEs. In terms of recall, 89.5% of ADEs with hyperkalaemia "with or without an abnormal symptom" were automatically identified (including all three serious ADEs). In terms of precision, 63.7% of the automatically identified ADEs with hyperkalaemia were true ADEs. The use of context-sensitive rules appears to improve the automated detection of ADEs with hyperkalaemia. This type of tool may have an important role in pharmacoepidemiology via the routine analysis of large inter-hospital databases.

Good Practices for Real-World Data Studies of Treatment and/or Comparative Effectiveness: Recommendations from the Joint ISPOR-ISPE Special Task Force on Real-World Evidence in Health Care Decision Making.

PubMed

Berger, Marc L; Sox, Harold; Willke, Richard J; Brixner, Diana L; Eichler, Hans-Georg; Goettsch, Wim; Madigan, David; Makady, Amr; Schneeweiss, Sebastian; Tarricone, Rosanna; Wang, Shirley V; Watkins, John; Mullins, C Daniel

2017-09-01

Real-world evidence (RWE) includes data from retrospective or prospective observational studies and observational registries and provides insights beyond those addressed by randomized controlled trials. RWE studies aim to improve health care decision making. The International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and the International Society for Pharmacoepidemiology (ISPE) created a task force to make recommendations regarding good procedural practices that would enhance decision makers' confidence in evidence derived from RWD studies. Peer review by ISPOR/ISPE members and task force participants provided a consensus-building iterative process for the topics and framing of recommendations. The ISPOR/ISPE Task Force recommendations cover seven topics such as study registration, replicability, and stakeholder involvement in RWE studies. These recommendations, in concert with earlier recommendations about study methodology, provide a trustworthy foundation for the expanded use of RWE in health care decision making. The focus of these recommendations is good procedural practices for studies that test a specific hypothesis in a specific population. We recognize that some of the recommendations in this report may not be widely adopted without appropriate incentives from decision makers, journal editors, and other key stakeholders. Copyright © 2017. Published by Elsevier Inc.

Use of Pregabalin - A Nationwide Pharmacoepidemiological Drug Utilization Study with Focus on Abuse Potential.

PubMed

Schjerning, O; Pottegård, A; Damkier, P; Rosenzweig, M; Nielsen, J

2016-07-01

Pregabalin is currently approved for the treatment of epilepsy, generalized anxiety disorder and neuropathic pain with a licensed dosage range of 150 mg to 600 mg/day. Growing concern about the abuse potential of pregabalin is partly based on reports of pregabalin being used in dosages that exceed the approved therapeutic range. To identify predictors of pregabalin use above recommended dosage, we conducted a pharmacoepidemological drug utilization study using the Danish nationwide registers. We deployed 4 measures of abuse: high use (≥600 mg/day) or very high use (≥1 200 mg/day) over a 6- or 12-month period, respectively. Multiple logistic regression was used to identify patient and treatment characteristics that were associated with either abuse marker. Out of 42 520 pregabalin users 4 090 (9.6%) were treated with more than 600 mg/day for 6 months and 2 765 (6.5%) for more than 12 months. Male gender and prescription of antipsychotics and benzodiazepines were associated with increased risk of use of above the recommended dosage. Use of pregabalin above recommended dosages was rare but abuse may occur in susceptible patients. © Georg Thieme Verlag KG Stuttgart · New York.

Risk of Gambling Disorder and Impulse Control Disorder With Aripiprazole, Pramipexole, and Ropinirole: A Pharmacoepidemiologic Study.

PubMed

Etminan, Mahyar; Sodhi, Mohit; Samii, Ali; Procyshyn, Ric M; Guo, Michael; Carleton, Bruce C

2017-02-01

Recently, the US Food and Drug Administration issued a warning regarding the potential risk of gambling disorder, but large epidemiologic studies are lacking. We used a large health claims database from the United States and conducted a nested case-control study. Cases were defined as subjects newly diagnosed with gambling disorder or impulse control disorder. For each case, 10 controls were selected and matched to cases by age and follow-up time and calendar time. Adjusted rate ratios were computed with conditional logistic regression. There are 355 cases of gambling disorder and 3550 controls along with 4341 cases of impulse control disorder and 43,410 corresponding controls. After adjusting for confounders, users of aripiprazole demonstrated an increased risk of pathologic gambling (rate ratio [RR], 5.23; 95% confidence interval [CI], 1.78-15.38) and impulse control disorder (RR, 7.71; 95% CI, 5.81-10.34). The risk was also elevated for pramipexole or ropinirole for both gambling disorder and impulse control disorder (RR, 7.61; 95% CI, 2.75-21.07; RR, 3.28; 95% CI, 2.31-4.66, respectively). Our study confirms an association between aripiprazole, pramipexole, or ropinirole and impulse control disorder and gambling disorder.

Building a structured monitoring and evaluating system of postmarketing drug use in Shanghai.

PubMed

Du, Wenmin; Levine, Mitchell; Wang, Longxing; Zhang, Yaohua; Yi, Chengdong; Wang, Hongmin; Wang, Xiaoyu; Xie, Hongjuan; Xu, Jianglong; Jin, Huilin; Wang, Tongchun; Huang, Gan; Wu, Ye

2007-01-01

In order to understand a drug's full profile in the post-marketing environment, information is needed regarding utilization patterns, beneficial effects, ADRs and economic value. China, the most populated country in the world, has the largest number of people who are taking medications. To begin to appreciate the impact of these medications, a multifunctional evaluation and surveillance system was developed, the Shanghai Drug Monitoring and Evaluative System (SDMES). Set up by the Shanghai Center for Adverse Drug Reaction Monitoring in 2001, the SDMES contains three databases: a population health data base of middle aged and elderly persons; hospital patient medical records; and a spontaneous ADR reporting database. Each person has a unique identification and Medicare number, which permits record-linkage within and between these three databases. After more than three years in development, the population health database has comprehensive data for more than 320,000 residents. The hospital database has two years of inpatient medical records from five major hospitals, and will be increasing to 10 hospitals in 2007. The spontaneous reporting ADR database has collected 20,205 cases since 2001 from approximately 295 sources, including hospitals, pharmaceutical companies, drug wholesalers and pharmacies. The SDMES has the potential to become an important national and international pharmacoepidemiology resource for drug evaluation.

Comparability of the age and sex distribution of the UK Clinical Practice Research Datalink and the total Dutch population.

PubMed

de Jong, Roy G P J; Gallagher, Arlene M; Herrett, Emily; Masclee, Ad A M; Janssen-Heijnen, Maryska L G; de Vries, Frank

2016-12-01

The UK Clinical Practice Research Datalink (CPRD) is increasingly being used by Dutch researchers in epidemiology and pharmacoepidemiology. It is however unclear if the UK CPRD is representative of the Dutch population and whether study results would apply to the Dutch population. Therefore, as first step, our objective was to compare the age and sex distribution of the CPRD with the total Dutch population. As a measure of representativeness, the age and sex distribution of the UK CPRD were visually and numerically compared with Dutch census data from the StatLine database of the Dutch National Bureau of Statistics in 2011. The age distribution of men and women in the CPRD population was comparable to the Dutch male and female population. Differences of more than 10% only occurred in older age categories (75+ in men and 80+ in women). Results from observational studies that have used CPRD data are applicable to the Dutch population, and a useful resource for decision making in the Netherlands. Nevertheless, differences in drug exposure likelihood between countries should be kept in mind, as these could still cause variations in the actual population studied, thereby decreasing its generalizability. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Methods of linking mothers and infants using health plan data for studies of pregnancy outcomes.

PubMed

Johnson, Karin E; Beaton, Sarah J; Andrade, Susan E; Cheetham, T Craig; Scott, Pamela E; Hammad, Tarek A; Dashevsky, Inna; Cooper, William O; Davis, Robert L; Pawloski, Pamala A; Raebel, Marsha A; Smith, David H; Toh, Sengwee; Li, De-Kun; Haffenreffer, Katherine; Dublin, Sascha

2013-07-01

Research on medication safety in pregnancy often utilizes health plan and birth certificate records. This study discusses methods used to link mothers with infants, a crucial step in such research. We describe how eight sites participating in the Medication Exposure in Pregnancy Risk Evaluation Program created linkages between deliveries, infants and birth certificates for the 2001-2007 birth cohorts. We describe linkage rates across sites, and for two sites, we compare the characteristics of populations linked using different methods. Of 299,260 deliveries, 256,563 (86%; range by site, 74-99%) could be linked to infants using a deterministic algorithm. At two sites, using birth certificate data to augment mother-infant linkage increased the representation of mothers who were Hispanic or non-White, younger, Medicaid recipients, or had low educational level. A total of 236,460 (92%; range by site, 82-100%) deliveries could be linked to a birth certificate. Tailored approaches enabled linking most deliveries to infants and to birth certificates, even when data systems differed. The methods used may affect the composition of the population identified. Linkages established with such methods can support sound pharmacoepidemiology studies of maternal drug exposure outside the context of a formal registry. Copyright © 2013 John Wiley & Sons, Ltd.

Data Mining of the Public Version of the FDA Adverse Event Reporting System

PubMed Central

Sakaeda, Toshiyuki; Tamon, Akiko; Kadoyama, Kaori; Okuno, Yasushi

2013-01-01

The US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS, formerly AERS) is a database that contains information on adverse event and medication error reports submitted to the FDA. Besides those from manufacturers, reports can be submitted from health care professionals and the public. The original system was started in 1969, but since the last major revision in 1997, reporting has markedly increased. Data mining algorithms have been developed for the quantitative detection of signals from such a large database, where a signal means a statistical association between a drug and an adverse event or a drug-associated adverse event, including the proportional reporting ratio (PRR), the reporting odds ratio (ROR), the information component (IC), and the empirical Bayes geometric mean (EBGM). A survey of our previous reports suggested that the ROR provided the highest number of signals, and the EBGM the lowest. Additionally, an analysis of warfarin-, aspirin- and clopidogrel-associated adverse events suggested that all EBGM-based signals were included in the PRR-based signals, and also in the IC- or ROR-based ones, and that the PRR- and IC-based signals were in the ROR-based ones. In this article, the latest information on this area is summarized for future pharmacoepidemiological studies and/or pharmacovigilance analyses. PMID:23794943

Concepts and tools for predictive modeling of microbial dynamics.

PubMed

Bernaerts, Kristel; Dens, Els; Vereecken, Karen; Geeraerd, Annemie H; Standaert, Arnout R; Devlieghere, Frank; Debevere, Johan; Van Impe, Jan F

2004-09-01

Description of microbial cell (population) behavior as influenced by dynamically changing environmental conditions intrinsically needs dynamic mathematical models. In the past, major effort has been put into the modeling of microbial growth and inactivation within a constant environment (static models). In the early 1990s, differential equation models (dynamic models) were introduced in the field of predictive microbiology. Here, we present a general dynamic model-building concept describing microbial evolution under dynamic conditions. Starting from an elementary model building block, the model structure can be gradually complexified to incorporate increasing numbers of influencing factors. Based on two case studies, the fundamentals of both macroscopic (population) and microscopic (individual) modeling approaches are revisited. These illustrations deal with the modeling of (i) microbial lag under variable temperature conditions and (ii) interspecies microbial interactions mediated by lactic acid production (product inhibition). Current and future research trends should address the need for (i) more specific measurements at the cell and/or population level, (ii) measurements under dynamic conditions, and (iii) more comprehensive (mechanistically inspired) model structures. In the context of quantitative microbial risk assessment, complexity of the mathematical model must be kept under control. An important challenge for the future is determination of a satisfactory trade-off between predictive power and manageability of predictive microbiology models.

Rigid-flexible coupling dynamic modeling and investigation of a redundantly actuated parallel manipulator with multiple actuation modes

NASA Astrophysics Data System (ADS)

Liang, Dong; Song, Yimin; Sun, Tao; Jin, Xueying

2017-09-01

A systematic dynamic modeling methodology is presented to develop the rigid-flexible coupling dynamic model (RFDM) of an emerging flexible parallel manipulator with multiple actuation modes. By virtue of assumed mode method, the general dynamic model of an arbitrary flexible body with any number of lumped parameters is derived in an explicit closed form, which possesses the modular characteristic. Then the completely dynamic model of system is formulated based on the flexible multi-body dynamics (FMD) theory and the augmented Lagrangian multipliers method. An approach of combining the Udwadia-Kalaba formulation with the hybrid TR-BDF2 numerical algorithm is proposed to address the nonlinear RFDM. Two simulation cases are performed to investigate the dynamic performance of the manipulator with different actuation modes. The results indicate that the redundant actuation modes can effectively attenuate vibration and guarantee higher dynamic performance compared to the traditional non-redundant actuation modes. Finally, a virtual prototype model is developed to demonstrate the validity of the presented RFDM. The systematic methodology proposed in this study can be conveniently extended for the dynamic modeling and controller design of other planar flexible parallel manipulators, especially the emerging ones with multiple actuation modes.

Dynamic analysis of Space Shuttle/RMS configuration using continuum approach

NASA Technical Reports Server (NTRS)

Ramakrishnan, Jayant; Taylor, Lawrence W., Jr.

1994-01-01

The initial assembly of Space Station Freedom involves the Space Shuttle, its Remote Manipulation System (RMS) and the evolving Space Station Freedom. The dynamics of this coupled system involves both the structural and the control system dynamics of each of these components. The modeling and analysis of such an assembly is made even more formidable by kinematic and joint nonlinearities. The current practice of modeling such flexible structures is to use finite element modeling in which the mass and interior dynamics is ignored between thousands of nodes, for each major component. The model characteristics of only tens of modes are kept out of thousands which are calculated. The components are then connected by approximating the boundary conditions and inserting the control system dynamics. In this paper continuum models are used instead of finite element models because of the improved accuracy, reduced number of model parameters, the avoidance of model order reduction, and the ability to represent the structural and control system dynamics in the same system of equations. Dynamic analysis of linear versions of the model is performed and compared with finite element model results. Additionally, the transfer matrix to continuum modeling is presented.

Dynamic contraction behaviour of pneumatic artificial muscle

NASA Astrophysics Data System (ADS)

Doumit, Marc D.; Pardoel, Scott

2017-07-01

The development of a dynamic model for the Pneumatic Artificial Muscle (PAM) is an imperative undertaking for understanding and analyzing the behaviour of the PAM as a function of time. This paper proposes a Newtonian based dynamic PAM model that includes the modeling of the muscle geometry, force, inertia, fluid dynamic, static and dynamic friction, heat transfer and valve flow while ignoring the effect of bladder elasticity. This modeling contribution allows the designer to predict, analyze and optimize PAM performance prior to its development. Thus advancing successful implementations of PAM based powered exoskeletons and medical systems. To date, most muscle dynamic properties are determined experimentally, furthermore, no analytical models that can accurately predict the muscle's dynamic behaviour are found in the literature. Most developed analytical models adequately predict the muscle force in static cases but neglect the behaviour of the system in the transient response. This could be attributed to the highly challenging task of deriving such a dynamic model given the number of system elements that need to be identified and the system's highly non-linear properties. The proposed dynamic model in this paper is successfully simulated through MATLAB programing and validated the pressure, contraction distance and muscle temperature with experimental testing that is conducted with in-house built prototype PAM's.

A parameters optimization method for planar joint clearance model and its application for dynamics simulation of reciprocating compressor

NASA Astrophysics Data System (ADS)

Hai-yang, Zhao; Min-qiang, Xu; Jin-dong, Wang; Yong-bo, Li

2015-05-01

In order to improve the accuracy of dynamics response simulation for mechanism with joint clearance, a parameter optimization method for planar joint clearance contact force model was presented in this paper, and the optimized parameters were applied to the dynamics response simulation for mechanism with oversized joint clearance fault. By studying the effect of increased clearance on the parameters of joint clearance contact force model, the relation of model parameters between different clearances was concluded. Then the dynamic equation of a two-stage reciprocating compressor with four joint clearances was developed using Lagrange method, and a multi-body dynamic model built in ADAMS software was used to solve this equation. To obtain a simulated dynamic response much closer to that of experimental tests, the parameters of joint clearance model, instead of using the designed values, were optimized by genetic algorithms approach. Finally, the optimized parameters were applied to simulate the dynamics response of model with oversized joint clearance fault according to the concluded parameter relation. The dynamics response of experimental test verified the effectiveness of this application.

DCMIP2016: a review of non-hydrostatic dynamical core design and intercomparison of participating models

NASA Astrophysics Data System (ADS)

Ullrich, Paul A.; Jablonowski, Christiane; Kent, James; Lauritzen, Peter H.; Nair, Ramachandran; Reed, Kevin A.; Zarzycki, Colin M.; Hall, David M.; Dazlich, Don; Heikes, Ross; Konor, Celal; Randall, David; Dubos, Thomas; Meurdesoif, Yann; Chen, Xi; Harris, Lucas; Kühnlein, Christian; Lee, Vivian; Qaddouri, Abdessamad; Girard, Claude; Giorgetta, Marco; Reinert, Daniel; Klemp, Joseph; Park, Sang-Hun; Skamarock, William; Miura, Hiroaki; Ohno, Tomoki; Yoshida, Ryuji; Walko, Robert; Reinecke, Alex; Viner, Kevin

2017-12-01

Atmospheric dynamical cores are a fundamental component of global atmospheric modeling systems and are responsible for capturing the dynamical behavior of the Earth's atmosphere via numerical integration of the Navier-Stokes equations. These systems have existed in one form or another for over half of a century, with the earliest discretizations having now evolved into a complex ecosystem of algorithms and computational strategies. In essence, no two dynamical cores are alike, and their individual successes suggest that no perfect model exists. To better understand modern dynamical cores, this paper aims to provide a comprehensive review of 11 non-hydrostatic dynamical cores, drawn from modeling centers and groups that participated in the 2016 Dynamical Core Model Intercomparison Project (DCMIP) workshop and summer school. This review includes a choice of model grid, variable placement, vertical coordinate, prognostic equations, temporal discretization, and the diffusion, stabilization, filters, and fixers employed by each system.

CADLIVE toolbox for MATLAB: automatic dynamic modeling of biochemical networks with comprehensive system analysis.

PubMed

Inoue, Kentaro; Maeda, Kazuhiro; Miyabe, Takaaki; Matsuoka, Yu; Kurata, Hiroyuki

2014-09-01

Mathematical modeling has become a standard technique to understand the dynamics of complex biochemical systems. To promote the modeling, we had developed the CADLIVE dynamic simulator that automatically converted a biochemical map into its associated mathematical model, simulated its dynamic behaviors and analyzed its robustness. To enhance the feasibility by CADLIVE and extend its functions, we propose the CADLIVE toolbox available for MATLAB, which implements not only the existing functions of the CADLIVE dynamic simulator, but also the latest tools including global parameter search methods with robustness analysis. The seamless, bottom-up processes consisting of biochemical network construction, automatic construction of its dynamic model, simulation, optimization, and S-system analysis greatly facilitate dynamic modeling, contributing to the research of systems biology and synthetic biology. This application can be freely downloaded from http://www.cadlive.jp/CADLIVE_MATLAB/ together with an instruction.

Dynamics of entanglement and uncertainty relation in coupled harmonic oscillator system: exact results

NASA Astrophysics Data System (ADS)

Park, DaeKil

2018-06-01

The dynamics of entanglement and uncertainty relation is explored by solving the time-dependent Schrödinger equation for coupled harmonic oscillator system analytically when the angular frequencies and coupling constant are arbitrarily time dependent. We derive the spectral and Schmidt decompositions for vacuum solution. Using the decompositions, we derive the analytical expressions for von Neumann and Rényi entropies. Making use of Wigner distribution function defined in phase space, we derive the time dependence of position-momentum uncertainty relations. To show the dynamics of entanglement and uncertainty relation graphically, we introduce two toy models and one realistic quenched model. While the dynamics can be conjectured by simple consideration in the toy models, the dynamics in the realistic quenched model is somewhat different from that in the toy models. In particular, the dynamics of entanglement exhibits similar pattern to dynamics of uncertainty parameter in the realistic quenched model.

Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation.

PubMed

Villaverde, Alejandro F; Banga, Julio R

2017-11-01

The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. However, the original definition of dynamical compensation amounts to lack of structural identifiability. This is relevant if model parameters need to be estimated, as is often the case in biological modelling. Care should we taken when using an unidentifiable model to extract biological insight: the estimated values of structurally unidentifiable parameters are meaningless, and model predictions about unmeasured state variables can be wrong. Taking this into account, we explore alternative definitions of dynamical compensation that do not necessarily imply structural unidentifiability. Accordingly, we show different ways in which a model can be made identifiable while exhibiting dynamical compensation. Our analyses enable the use of the new concept of dynamical compensation in the context of parameter identification, and reconcile it with the desirable property of structural identifiability.

System Dynamic Analysis of a Wind Tunnel Model with Applications to Improve Aerodynamic Data Quality

NASA Technical Reports Server (NTRS)

Buehrle, Ralph David

1997-01-01

The research investigates the effect of wind tunnel model system dynamics on measured aerodynamic data. During wind tunnel tests designed to obtain lift and drag data, the required aerodynamic measurements are the steady-state balance forces and moments, pressures, and model attitude. However, the wind tunnel model system can be subjected to unsteady aerodynamic and inertial loads which result in oscillatory translations and angular rotations. The steady-state force balance and inertial model attitude measurements are obtained by filtering and averaging data taken during conditions of high model vibrations. The main goals of this research are to characterize the effects of model system dynamics on the measured steady-state aerodynamic data and develop a correction technique to compensate for dynamically induced errors. Equations of motion are formulated for the dynamic response of the model system subjected to arbitrary aerodynamic and inertial inputs. The resulting modal model is examined to study the effects of the model system dynamic response on the aerodynamic data. In particular, the equations of motion are used to describe the effect of dynamics on the inertial model attitude, or angle of attack, measurement system that is used routinely at the NASA Langley Research Center and other wind tunnel facilities throughout the world. This activity was prompted by the inertial model attitude sensor response observed during high levels of model vibration while testing in the National Transonic Facility at the NASA Langley Research Center. The inertial attitude sensor cannot distinguish between the gravitational acceleration and centrifugal accelerations associated with wind tunnel model system vibration, which results in a model attitude measurement bias error. Bias errors over an order of magnitude greater than the required device accuracy were found in the inertial model attitude measurements during dynamic testing of two model systems. Based on a theoretical modal approach, a method using measured vibration amplitudes and measured or calculated modal characteristics of the model system is developed to correct for dynamic bias errors in the model attitude measurements. The correction method is verified through dynamic response tests on two model systems and actual wind tunnel test data.

Stage-by-Stage and Parallel Flow Path Compressor Modeling for a Variable Cycle Engine

NASA Technical Reports Server (NTRS)

Kopasakis, George; Connolly, Joseph W.; Cheng, Larry

2015-01-01

This paper covers the development of stage-by-stage and parallel flow path compressor modeling approaches for a Variable Cycle Engine. The stage-by-stage compressor modeling approach is an extension of a technique for lumped volume dynamics and performance characteristic modeling. It was developed to improve the accuracy of axial compressor dynamics over lumped volume dynamics modeling. The stage-by-stage compressor model presented here is formulated into a parallel flow path model that includes both axial and rotational dynamics. This is done to enable the study of compressor and propulsion system dynamic performance under flow distortion conditions. The approaches utilized here are generic and should be applicable for the modeling of any axial flow compressor design.

A comparative study on dynamic stiffness in typical finite element model and multi-body model of C6-C7 cervical spine segment.

PubMed

Wang, Yawei; Wang, Lizhen; Du, Chengfei; Mo, Zhongjun; Fan, Yubo

2016-06-01

In contrast to numerous researches on static or quasi-static stiffness of cervical spine segments, very few investigations on their dynamic stiffness were published. Currently, scale factors and estimated coefficients were usually used in multi-body models for including viscoelastic properties and damping effects, meanwhile viscoelastic properties of some tissues were unavailable for establishing finite element models. Because dynamic stiffness of cervical spine segments in these models were difficult to validate because of lacking in experimental data, we tried to gain some insights on current modeling methods through studying dynamic stiffness differences between these models. A finite element model and a multi-body model of C6-C7 segment were developed through using available material data and typical modeling technologies. These two models were validated with quasi-static response data of the C6-C7 cervical spine segment. Dynamic stiffness differences were investigated through controlling motions of C6 vertebrae at different rates and then comparing their reaction forces or moments. Validation results showed that both the finite element model and the multi-body model could generate reasonable responses under quasi-static loads, but the finite element segment model exhibited more nonlinear characters. Dynamic response investigations indicated that dynamic stiffness of this finite element model might be underestimated because of the absence of dynamic stiffen effect and damping effects of annulus fibrous, while representation of these effects also need to be improved in current multi-body model. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Fractional Relativistic Yamaleev Oscillator Model and Its Dynamical Behaviors

NASA Astrophysics Data System (ADS)

Luo, Shao-Kai; He, Jin-Man; Xu, Yan-Li; Zhang, Xiao-Tian

2016-07-01

In the paper we construct a new kind of fractional dynamical model, i.e. the fractional relativistic Yamaleev oscillator model, and explore its dynamical behaviors. We will find that the fractional relativistic Yamaleev oscillator model possesses Lie algebraic structure and satisfies generalized Poisson conservation law. We will also give the Poisson conserved quantities of the model. Further, the relation between conserved quantities and integral invariants of the model is studied and it is proved that, by using the Poisson conserved quantities, we can construct integral invariants of the model. Finally, the stability of the manifold of equilibrium states of the fractional relativistic Yamaleev oscillator model is studied. The paper provides a general method, i.e. fractional generalized Hamiltonian method, for constructing a family of fractional dynamical models of an actual dynamical system.

Methodology for Uncertainty Analysis of Dynamic Computational Toxicology Models

EPA Science Inventory

The task of quantifying the uncertainty in both parameter estimates and model predictions has become more important with the increased use of dynamic computational toxicology models by the EPA. Dynamic toxicological models include physiologically-based pharmacokinetic (PBPK) mode...

Dynamic response tests of inertial and optical wind-tunnel model attitude measurement devices

NASA Technical Reports Server (NTRS)

Buehrle, R. D.; Young, C. P., Jr.; Burner, A. W.; Tripp, J. S.; Tcheng, P.; Finley, T. D.; Popernack, T. G., Jr.

1995-01-01

Results are presented for an experimental study of the response of inertial and optical wind-tunnel model attitude measurement systems in a wind-off simulated dynamic environment. This study is part of an ongoing activity at the NASA Langley Research Center to develop high accuracy, advanced model attitude measurement systems that can be used in a dynamic wind-tunnel environment. This activity was prompted by the inertial model attitude sensor response observed during high levels of model vibration which results in a model attitude measurement bias error. Significant bias errors in model attitude measurement were found for the measurement using the inertial device during wind-off dynamic testing of a model system. The amount of bias present during wind-tunnel tests will depend on the amplitudes of the model dynamic response and the modal characteristics of the model system. Correction models are presented that predict the vibration-induced bias errors to a high degree of accuracy for the vibration modes characterized in the simulated dynamic environment. The optical system results were uncorrupted by model vibration in the laboratory setup.

Models with Men and Women: Representing Gender in Dynamic Modeling of Social Systems.

PubMed

Palmer, Erika; Wilson, Benedicte

2018-04-01

Dynamic engineering models have yet to be evaluated in the context of feminist engineering ethics. Decision-making concerning gender in dynamic modeling design is a gender and ethical issue that is important to address regardless of the system in which the dynamic modeling is applied. There are many dynamic modeling tools that operationally include the female population, however, there is an important distinction between females and women; it is the difference between biological sex and the social construct of gender, which is fluid and changes over time and geography. The ethical oversight in failing to represent or misrepresenting gender in model design when it is relevant to the model purpose can have implications for model validity and policy model development. This paper highlights this gender issue in the context of feminist engineering ethics using a dynamic population model. Women are often represented in this type of model only in their biological capacity, while lacking their gender identity. This illustrative example also highlights how language, including the naming of variables and communication with decision-makers, plays a role in this gender issue.

A locomotive-track coupled vertical dynamics model with gear transmissions

NASA Astrophysics Data System (ADS)

Chen, Zaigang; Zhai, Wanming; Wang, Kaiyun

2017-02-01

A gear transmission system is a key element in a locomotive for the transmission of traction or braking forces between the motor and the wheel-rail interface. Its dynamic performance has a direct effect on the operational reliability of the locomotive and its components. This paper proposes a comprehensive locomotive-track coupled vertical dynamics model, in which the locomotive is driven by axle-hung motors. In this coupled dynamics model, the dynamic interactions between the gear transmission system and the other components, e.g. motor and wheelset, are considered based on the detailed analysis of its structural properties and working mechanism. Thus, the mechanical transmission system for power delivery from the motor to the wheelset via gear transmission is coupled with a traditional locomotive-track dynamics system via the wheel-rail contact interface and the gear mesh interface. This developed dynamics model enables investigations of the dynamic performance of the entire dynamics system under the excitations from the wheel-rail contact interface and/or the gear mesh interface. Dynamic interactions are demonstrated by numerical simulations using this dynamics model. The results indicate that both of the excitations from the wheel-rail contact interface and the gear mesh interface have a significant effect on the dynamic responses of the components in this coupled dynamics system.

A fully dynamic model of a multi-layer piezoelectric actuator incorporating the power amplifier

NASA Astrophysics Data System (ADS)

Zhu, Wei; Yang, Fufeng; Rui, Xiaoting

2017-12-01

The dynamic input-output characteristics of the multi-layer piezoelectric actuator (PA) are intrinsically rate-dependent and hysteresis. Meanwhile, aiming at the strong capacitive impedance of multi-layer PA, the power amplifier of the actuator can greatly affect the dynamic performances of the actuator. In this paper, a novel dynamic model that includes a model of the electric circuit providing voltage to the actuator, an inverse piezoelectric effect model describing the hysteresis and creep behavior of the actuator, and a mechanical model, in which the vibration characteristics of the multi-layer PA is described, is put forward. Validation experimental tests are conducted. Experimental results show that the proposed dynamic model can accurately predict the fully dynamic behavior of the multi-layer PA with different driving power.

System Dynamics Modeling for Supply Chain Information Sharing

NASA Astrophysics Data System (ADS)

Feng, Yang

In this paper, we try to use the method of system dynamics to model supply chain information sharing. Firstly, we determine the model boundaries, establish system dynamics model of supply chain before information sharing, analyze the model's simulation results under different changed parameters and suggest improvement proposal. Then, we establish system dynamics model of supply chain information sharing and make comparison and analysis on the two model's simulation results, to show the importance of information sharing in supply chain management. We wish that all these simulations would provide scientific supports for enterprise decision-making.

Coupled Vortex-Lattice Flight Dynamic Model with Aeroelastic Finite-Element Model of Flexible Wing Transport Aircraft with Variable Camber Continuous Trailing Edge Flap for Drag Reduction

NASA Technical Reports Server (NTRS)

Nguyen, Nhan; Ting, Eric; Nguyen, Daniel; Dao, Tung; Trinh, Khanh

2013-01-01

This paper presents a coupled vortex-lattice flight dynamic model with an aeroelastic finite-element model to predict dynamic characteristics of a flexible wing transport aircraft. The aircraft model is based on NASA Generic Transport Model (GTM) with representative mass and stiffness properties to achieve a wing tip deflection about twice that of a conventional transport aircraft (10% versus 5%). This flexible wing transport aircraft is referred to as an Elastically Shaped Aircraft Concept (ESAC) which is equipped with a Variable Camber Continuous Trailing Edge Flap (VCCTEF) system for active wing shaping control for drag reduction. A vortex-lattice aerodynamic model of the ESAC is developed and is coupled with an aeroelastic finite-element model via an automated geometry modeler. This coupled model is used to compute static and dynamic aeroelastic solutions. The deflection information from the finite-element model and the vortex-lattice model is used to compute unsteady contributions to the aerodynamic force and moment coefficients. A coupled aeroelastic-longitudinal flight dynamic model is developed by coupling the finite-element model with the rigid-body flight dynamic model of the GTM.

Nonlinear Dynamic Modeling of a Supersonic Commercial Transport Turbo-Machinery Propulsion System for Aero-Propulso-Servo-Elasticity Research

NASA Technical Reports Server (NTRS)

Connolly, Joseph W.; Kopasakis, George; Carlson, Jan-Renee; Woolwine, Kyle

2015-01-01

This paper covers the development of an integrated nonlinear dynamic model for a variable cycle turbofan engine, supersonic inlet, and convergent-divergent nozzle that can be integrated with an aeroelastic vehicle model to create an overall Aero-Propulso-Servo-Elastic (APSE) modeling tool. The primary focus of this study is to provide a means to capture relevant thrust dynamics of a full supersonic propulsion system by using relatively simple quasi-one dimensional computational fluid dynamics (CFD) methods that will allow for accurate control algorithm development and capture the key aspects of the thrust to feed into an APSE model. Previously, propulsion system component models have been developed and are used for this study of the fully integrated propulsion system. An overview of the methodology is presented for the modeling of each propulsion component, with a focus on its associated coupling for the overall model. To conduct APSE studies the de- scribed dynamic propulsion system model is integrated into a high fidelity CFD model of the full vehicle capable of conducting aero-elastic studies. Dynamic thrust analysis for the quasi-one dimensional dynamic propulsion system model is presented along with an initial three dimensional flow field model of the engine integrated into a supersonic commercial transport.

Nonlinear Dynamic Modeling of a Supersonic Commercial Transport Turbo-Machinery Propulsion System for Aero-Propulso-Servo-Elasticity Research

NASA Technical Reports Server (NTRS)

Connolly, Joe; Carlson, Jan-Renee; Kopasakis, George; Woolwine, Kyle

2015-01-01

This paper covers the development of an integrated nonlinear dynamic model for a variable cycle turbofan engine, supersonic inlet, and convergent-divergent nozzle that can be integrated with an aeroelastic vehicle model to create an overall Aero-Propulso-Servo-Elastic (APSE) modeling tool. The primary focus of this study is to provide a means to capture relevant thrust dynamics of a full supersonic propulsion system by using relatively simple quasi-one dimensional computational fluid dynamics (CFD) methods that will allow for accurate control algorithm development and capture the key aspects of the thrust to feed into an APSE model. Previously, propulsion system component models have been developed and are used for this study of the fully integrated propulsion system. An overview of the methodology is presented for the modeling of each propulsion component, with a focus on its associated coupling for the overall model. To conduct APSE studies the described dynamic propulsion system model is integrated into a high fidelity CFD model of the full vehicle capable of conducting aero-elastic studies. Dynamic thrust analysis for the quasi-one dimensional dynamic propulsion system model is presented along with an initial three dimensional flow field model of the engine integrated into a supersonic commercial transport.

Parameterized Linear Longitudinal Airship Model

NASA Technical Reports Server (NTRS)

Kulczycki, Eric; Elfes, Alberto; Bayard, David; Quadrelli, Marco; Johnson, Joseph

2010-01-01

A parameterized linear mathematical model of the longitudinal dynamics of an airship is undergoing development. This model is intended to be used in designing control systems for future airships that would operate in the atmospheres of Earth and remote planets. Heretofore, the development of linearized models of the longitudinal dynamics of airships has been costly in that it has been necessary to perform extensive flight testing and to use system-identification techniques to construct models that fit the flight-test data. The present model is a generic one that can be relatively easily specialized to approximate the dynamics of specific airships at specific operating points, without need for further system identification, and with significantly less flight testing. The approach taken in the present development is to merge the linearized dynamical equations of an airship with techniques for estimation of aircraft stability derivatives, and to thereby make it possible to construct a linearized dynamical model of the longitudinal dynamics of a specific airship from geometric and aerodynamic data pertaining to that airship. (It is also planned to develop a model of the lateral dynamics by use of the same methods.) All of the aerodynamic data needed to construct the model of a specific airship can be obtained from wind-tunnel testing and computational fluid dynamics

The AFDD International Dynamic Stall Workshop on Correlation of Dynamic Stall Models with 3-D Dynamic Stall Data

NASA Technical Reports Server (NTRS)

Tan, C. M.; Carr, L. W.

1996-01-01

A variety of empirical and computational fluid dynamics two-dimensional (2-D) dynamic stall models were compared to recently obtained three-dimensional (3-D) dynamic stall data in a workshop on modeling of 3-D dynamic stall of an unswept, rectangular wing, of aspect ratio 10. Dynamic stall test data both below and above the static stall angle-of-attack were supplied to the participants, along with a 'blind' case where only the test conditions were supplied in advance, with results being compared to experimental data at the workshop itself. Detailed graphical comparisons are presented in the report, which also includes discussion of the methods and the results. The primary conclusion of the workshop was that the 3-D effects of dynamic stall on the oscillating wing studied in the workshop can be reasonably reproduced by existing semi-empirical models once 2-D dynamic stall data have been obtained. The participants also emphasized the need for improved quantification of 2-D dynamic stall.

Exploring tropical forest vegetation dynamics using the FATES model

NASA Astrophysics Data System (ADS)

Koven, C. D.; Fisher, R.; Knox, R. G.; Chambers, J.; Kueppers, L. M.; Christoffersen, B. O.; Davies, S. J.; Dietze, M.; Holm, J.; Massoud, E. C.; Muller-Landau, H. C.; Powell, T.; Serbin, S.; Shuman, J. K.; Walker, A. P.; Wright, S. J.; Xu, C.

2017-12-01

Tropical forest vegetation dynamics represent a critical climate feedback in the Earth system, which is poorly represented in current global modeling approaches. We discuss recent progress on exploring these dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a demographic vegetation model for the CESM and ACME ESMs. We will discuss benchmarks of FATES predictions for forest structure against inventory sites, sensitivity of FATES predictions of size and age structure to model parameter uncertainty, and experiments using the FATES model to explore PFT competitive dynamics and the dynamics of size and age distributions in responses to changing climate and CO2.

Principal process analysis of biological models.

PubMed

Casagranda, Stefano; Touzeau, Suzanne; Ropers, Delphine; Gouzé, Jean-Luc

2018-06-14

Understanding the dynamical behaviour of biological systems is challenged by their large number of components and interactions. While efforts have been made in this direction to reduce model complexity, they often prove insufficient to grasp which and when model processes play a crucial role. Answering these questions is fundamental to unravel the functioning of living organisms. We design a method for dealing with model complexity, based on the analysis of dynamical models by means of Principal Process Analysis. We apply the method to a well-known model of circadian rhythms in mammals. The knowledge of the system trajectories allows us to decompose the system dynamics into processes that are active or inactive with respect to a certain threshold value. Process activities are graphically represented by Boolean and Dynamical Process Maps. We detect model processes that are always inactive, or inactive on some time interval. Eliminating these processes reduces the complex dynamics of the original model to the much simpler dynamics of the core processes, in a succession of sub-models that are easier to analyse. We quantify by means of global relative errors the extent to which the simplified models reproduce the main features of the original system dynamics and apply global sensitivity analysis to test the influence of model parameters on the errors. The results obtained prove the robustness of the method. The analysis of the sub-model dynamics allows us to identify the source of circadian oscillations. We find that the negative feedback loop involving proteins PER, CRY, CLOCK-BMAL1 is the main oscillator, in agreement with previous modelling and experimental studies. In conclusion, Principal Process Analysis is a simple-to-use method, which constitutes an additional and useful tool for analysing the complex dynamical behaviour of biological systems.

Molecular dynamics of conformational substates for a simplified protein model

NASA Astrophysics Data System (ADS)

Grubmüller, Helmut; Tavan, Paul

1994-09-01

Extended molecular dynamics simulations covering a total of 0.232 μs have been carried out on a simplified protein model. Despite its simplified structure, that model exhibits properties similar to those of more realistic protein models. In particular, the model was found to undergo transitions between conformational substates at a time scale of several hundred picoseconds. The computed trajectories turned out to be sufficiently long as to permit a statistical analysis of that conformational dynamics. To check whether effective descriptions neglecting memory effects can reproduce the observed conformational dynamics, two stochastic models were studied. A one-dimensional Langevin effective potential model derived by elimination of subpicosecond dynamical processes could not describe the observed conformational transition rates. In contrast, a simple Markov model describing the transitions between but neglecting dynamical processes within conformational substates reproduced the observed distribution of first passage times. These findings suggest, that protein dynamics generally does not exhibit memory effects at time scales above a few hundred picoseconds, but confirms the existence of memory effects at a picosecond time scale.

Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam's Window.

PubMed

Onorante, Luca; Raftery, Adrian E

2016-01-01

Bayesian model averaging has become a widely used approach to accounting for uncertainty about the structural form of the model generating the data. When data arrive sequentially and the generating model can change over time, Dynamic Model Averaging (DMA) extends model averaging to deal with this situation. Often in macroeconomics, however, many candidate explanatory variables are available and the number of possible models becomes too large for DMA to be applied in its original form. We propose a new method for this situation which allows us to perform DMA without considering the whole model space, but using a subset of models and dynamically optimizing the choice of models at each point in time. This yields a dynamic form of Occam's window. We evaluate the method in the context of the problem of nowcasting GDP in the Euro area. We find that its forecasting performance compares well with that of other methods.

Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam’s Window*

PubMed Central

Onorante, Luca; Raftery, Adrian E.

2015-01-01

Bayesian model averaging has become a widely used approach to accounting for uncertainty about the structural form of the model generating the data. When data arrive sequentially and the generating model can change over time, Dynamic Model Averaging (DMA) extends model averaging to deal with this situation. Often in macroeconomics, however, many candidate explanatory variables are available and the number of possible models becomes too large for DMA to be applied in its original form. We propose a new method for this situation which allows us to perform DMA without considering the whole model space, but using a subset of models and dynamically optimizing the choice of models at each point in time. This yields a dynamic form of Occam’s window. We evaluate the method in the context of the problem of nowcasting GDP in the Euro area. We find that its forecasting performance compares well with that of other methods. PMID:26917859

Multibody dynamic simulation of knee contact mechanics

PubMed Central

Bei, Yanhong; Fregly, Benjamin J.

2006-01-01

Multibody dynamic musculoskeletal models capable of predicting muscle forces and joint contact pressures simultaneously would be valuable for studying clinical issues related to knee joint degeneration and restoration. Current three-dimensional multi-body knee models are either quasi-static with deformable contact or dynamic with rigid contact. This study proposes a computationally efficient methodology for combining multibody dynamic simulation methods with a deformable contact knee model. The methodology requires preparation of the articular surface geometry, development of efficient methods to calculate distances between contact surfaces, implementation of an efficient contact solver that accounts for the unique characteristics of human joints, and specification of an application programming interface for integration with any multibody dynamic simulation environment. The current implementation accommodates natural or artificial tibiofemoral joint models, small or large strain contact models, and linear or nonlinear material models. Applications are presented for static analysis (via dynamic simulation) of a natural knee model created from MRI and CT data and dynamic simulation of an artificial knee model produced from manufacturer’s CAD data. Small and large strain natural knee static analyses required 1 min of CPU time and predicted similar contact conditions except for peak pressure, which was higher for the large strain model. Linear and nonlinear artificial knee dynamic simulations required 10 min of CPU time and predicted similar contact force and torque but different contact pressures, which were lower for the nonlinear model due to increased contact area. This methodology provides an important step toward the realization of dynamic musculoskeletal models that can predict in vivo knee joint motion and loading simultaneously. PMID:15564115

Dynamic Modeling of the SMAP Rotating Flexible Antenna

NASA Technical Reports Server (NTRS)

Nayeri, Reza D.

2012-01-01

Dynamic model development in ADAMS for the SMAP project is explained: The main objective of the dynamic models are for pointing error assessment, and the control/stability margin requirement verifications

A cable-driven parallel robots application: modelling and simulation of a dynamic cable model in Dymola

NASA Astrophysics Data System (ADS)

Othman, M. F.; Kurniawan, R.; Schramm, D.; Ariffin, A. K.

2018-05-01

Modeling a cable model in multibody dynamics simulation tool which dynamically varies in length, mass and stiffness is a challenging task. Simulation of cable-driven parallel robots (CDPR) for instance requires a cable model that can dynamically change in length for every desired pose of the platform. Thus, in this paper, a detailed procedure for modeling and simulation of a dynamic cable model in Dymola is proposed. The approach is also applicable for other types of Modelica simulation environments. The cable is modeled using standard mechanical elements like mass, spring, damper and joint. The parameters of the cable model are based on the factsheet of the manufacturer and experimental results. Its dynamic ability is tested by applying it on a complete planar CDPR model in which the parameters are based on a prototype named CABLAR, which is developed in Chair of Mechatronics, University of Duisburg-Essen. The prototype has been developed to demonstrate an application of CDPR as a goods storage and retrieval machine. The performance of the cable model during the simulation is analyzed and discussed.

Model-data integration to improve the LPJmL dynamic global vegetation model

NASA Astrophysics Data System (ADS)

Forkel, Matthias; Thonicke, Kirsten; Schaphoff, Sibyll; Thurner, Martin; von Bloh, Werner; Dorigo, Wouter; Carvalhais, Nuno

2017-04-01

Dynamic global vegetation models show large uncertainties regarding the development of the land carbon balance under future climate change conditions. This uncertainty is partly caused by differences in how vegetation carbon turnover is represented in global vegetation models. Model-data integration approaches might help to systematically assess and improve model performances and thus to potentially reduce the uncertainty in terrestrial vegetation responses under future climate change. Here we present several applications of model-data integration with the LPJmL (Lund-Potsdam-Jena managed Lands) dynamic global vegetation model to systematically improve the representation of processes or to estimate model parameters. In a first application, we used global satellite-derived datasets of FAPAR (fraction of absorbed photosynthetic activity), albedo and gross primary production to estimate phenology- and productivity-related model parameters using a genetic optimization algorithm. Thereby we identified major limitations of the phenology module and implemented an alternative empirical phenology model. The new phenology module and optimized model parameters resulted in a better performance of LPJmL in representing global spatial patterns of biomass, tree cover, and the temporal dynamic of atmospheric CO2. Therefore, we used in a second application additionally global datasets of biomass and land cover to estimate model parameters that control vegetation establishment and mortality. The results demonstrate the ability to improve simulations of vegetation dynamics but also highlight the need to improve the representation of mortality processes in dynamic global vegetation models. In a third application, we used multiple site-level observations of ecosystem carbon and water exchange, biomass and soil organic carbon to jointly estimate various model parameters that control ecosystem dynamics. This exercise demonstrates the strong role of individual data streams on the simulated ecosystem dynamics which consequently changed the development of ecosystem carbon stocks and fluxes under future climate and CO2 change. In summary, our results demonstrate challenges and the potential of using model-data integration approaches to improve a dynamic global vegetation model.

Drug exposure in register-based research—An expert-opinion based evaluation of methods

PubMed Central

Taipale, Heidi; Koponen, Marjaana; Tolppanen, Anna-Maija; Hartikainen, Sirpa; Ahonen, Riitta; Tiihonen, Jari

2017-01-01

Background In register-based pharmacoepidemiological studies, construction of drug exposure periods from drug purchases is a major methodological challenge. Various methods have been applied but their validity is rarely evaluated. Our objective was to conduct an expert-opinion based evaluation of the correctness of drug use periods produced by different methods. Methods Drug use periods were calculated with three fixed methods: time windows, assumption of one Defined Daily Dose (DDD) per day and one tablet per day, and with PRE2DUP that is based on modelling of individual drug purchasing behavior. Expert-opinion based evaluation was conducted with 200 randomly selected purchase histories of warfarin, bisoprolol, simvastatin, risperidone and mirtazapine in the MEDALZ-2005 cohort (28,093 persons with Alzheimer’s disease). Two experts reviewed purchase histories and judged which methods had joined correct purchases and gave correct duration for each of 1000 drug exposure periods. Results The evaluated correctness of drug use periods was 70–94% for PRE2DUP, and depending on grace periods and time window lengths 0–73% for tablet methods, 0–41% for DDD methods and 0–11% for time window methods. The highest rate of evaluated correct solutions for each method class were observed for 1 tablet per day with 180 days grace period (TAB_1_180, 43–73%), and 1 DDD per day with 180 days grace period (1–41%). Time window methods produced at maximum only 11% correct solutions. The best performing fixed method TAB_1_180 reached highest correctness for simvastatin 73% (95% CI 65–81%) whereas 89% (95% CI 84–94%) of PRE2DUP periods were judged as correct. Conclusions This study shows inaccuracy of fixed methods and the urgent need for new data-driven methods. In the expert-opinion based evaluation, the lowest error rates were observed with data-driven method PRE2DUP. PMID:28886089

User's guide to the western spruce budworm modeling system

Treesearch

Nicholas L. Crookston; J. J. Colbert; Paul W. Thomas; Katharine A. Sheehan; William P. Kemp

1990-01-01

The Budworm Modeling System is a set of four computer programs: The Budworm Dynamics Model, the Prognosis-Budworm Dynamics Model, the Prognosis-Budworm Damage Model, and the Parallel Processing-Budworm Dynamics Model. Input to the first three programs and the output produced are described in this guide. A guide to the fourth program will be published separately....

Dynamic characteristic of electromechanical coupling effects in motor-gear system

NASA Astrophysics Data System (ADS)

Bai, Wenyu; Qin, Datong; Wang, Yawen; Lim, Teik C.

2018-06-01

Dynamic characteristics of an electromechanical model which combines a nonlinear permeance network model (PNM) of a squirrel-cage induction motor and a coupled lateral-torsional dynamic model of a planetary geared rotor system is analyzed in this study. The simulations reveal the effects of internal excitations or parameters like machine slotting, magnetic saturation, time-varying mesh stiffness and shaft stiffness on the system dynamics. The responses of the electromechanical system with PNM motor model are compared with those responses of the system with dynamic motor model. The electromechanical coupling due to the interactions between the motor and gear system are studied. Furthermore, the frequency analysis of the electromechanical system dynamic characteristics predicts an efficient way to detect work condition of unsymmetrical voltage sag.

System Dynamics Modeling for Public Health: Background and Opportunities

PubMed Central

Homer, Jack B.; Hirsch, Gary B.

2006-01-01

The systems modeling methodology of system dynamics is well suited to address the dynamic complexity that characterizes many public health issues. The system dynamics approach involves the development of computer simulation models that portray processes of accumulation and feedback and that may be tested systematically to find effective policies for overcoming policy resistance. System dynamics modeling of chronic disease prevention should seek to incorporate all the basic elements of a modern ecological approach, including disease outcomes, health and risk behaviors, environmental factors, and health-related resources and delivery systems. System dynamics shows promise as a means of modeling multiple interacting diseases and risks, the interaction of delivery systems and diseased populations, and matters of national and state policy. PMID:16449591

Flight-vehicle materials, structures, and dynamics - Assessment and future directions. Vol. 5 - Structural dynamics and aeroelasticity

NASA Technical Reports Server (NTRS)

Noor, Ahmed K. (Editor); Venneri, Samuel L. (Editor)

1993-01-01

Various papers on flight vehicle materials, structures, and dynamics are presented. Individual topics addressed include: general modeling methods, component modeling techniques, time-domain computational techniques, dynamics of articulated structures, structural dynamics in rotating systems, structural dynamics in rotorcraft, damping in structures, structural acoustics, structural design for control, structural modeling for control, control strategies for structures, system identification, overall assessment of needs and benefits in structural dynamics and controlled structures. Also discussed are: experimental aeroelasticity in wind tunnels, aeroservoelasticity, nonlinear aeroelasticity, aeroelasticity problems in turbomachines, rotary-wing aeroelasticity with application to VTOL vehicles, computational aeroelasticity, structural dynamic testing and instrumentation.

Development of a simulation model for dynamic derailment analysis of high-speed trains

NASA Astrophysics Data System (ADS)

Ling, Liang; Xiao, Xin-Biao; Jin, Xue-Song

2014-12-01

The running safety of high-speed trains has become a major concern of the current railway research with the rapid development of high-speed railways around the world. The basic safety requirement is to prevent the derailment. The root causes of the dynamic derailment of high-speed trains operating in severe environments are not easy to identify using the field tests or laboratory experiments. Numerical simulation using an advanced train-track interaction model is a highly efficient and low-cost approach to investigate the dynamic derailment behavior and mechanism of high-speed trains. This paper presents a three-dimensional dynamic model of a high-speed train coupled with a ballast track for dynamic derailment analysis. The model considers a train composed of multiple vehicles and the nonlinear inter-vehicle connections. The ballast track model consists of rails, fastenings, sleepers, ballasts, and roadbed, which are modeled by Euler beams, nonlinear spring-damper elements, equivalent ballast bodies, and continuous viscoelastic elements, in which the modal superposition method was used to reduce the order of the partial differential equations of Euler beams. The commonly used derailment safety assessment criteria around the world are embedded in the simulation model. The train-track model was then used to investigate the dynamic derailment responses of a high-speed train passing over a buckled track, in which the derailment mechanism and train running posture during the dynamic derailment process were analyzed in detail. The effects of train and track modelling on dynamic derailment analysis were also discussed. The numerical results indicate that the train and track modelling options have a significant effect on the dynamic derailment analysis. The inter-vehicle impacts and the track flexibility and nonlinearity should be considered in the dynamic derailment simulations.

Recasting a model atomistic glassformer as a system of icosahedra

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pinney, Rhiannon; Bristol Centre for Complexity Science, University of Bristol, Bristol BS8 1TS; Liverpool, Tanniemola B.

2015-12-28

We consider a binary Lennard-Jones glassformer whose super-Arrhenius dynamics are correlated with the formation of icosahedral structures. Upon cooling, these icosahedra organize into mesoclusters. We recast this glassformer as an effective system of icosahedra which we describe with a population dynamics model. This model we parameterize with data from the temperature regime accessible to molecular dynamics simulations. We then use the model to determine the population of icosahedra in mesoclusters at arbitrary temperature. Using simulation data to incorporate dynamics into the model, we predict relaxation behavior at temperatures inaccessible to conventional approaches. Our model predicts super-Arrhenius dynamics whose relaxation timemore » remains finite for non-zero temperature.« less

Dynamic prediction in functional concurrent regression with an application to child growth.

PubMed

Leroux, Andrew; Xiao, Luo; Crainiceanu, Ciprian; Checkley, William

2018-04-15

In many studies, it is of interest to predict the future trajectory of subjects based on their historical data, referred to as dynamic prediction. Mixed effects models have traditionally been used for dynamic prediction. However, the commonly used random intercept and slope model is often not sufficiently flexible for modeling subject-specific trajectories. In addition, there may be useful exposures/predictors of interest that are measured concurrently with the outcome, complicating dynamic prediction. To address these problems, we propose a dynamic functional concurrent regression model to handle the case where both the functional response and the functional predictors are irregularly measured. Currently, such a model cannot be fit by existing software. We apply the model to dynamically predict children's length conditional on prior length, weight, and baseline covariates. Inference on model parameters and subject-specific trajectories is conducted using the mixed effects representation of the proposed model. An extensive simulation study shows that the dynamic functional regression model provides more accurate estimation and inference than existing methods. Methods are supported by fast, flexible, open source software that uses heavily tested smoothing techniques. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Selecting a dynamic simulation modeling method for health care delivery research-part 2: report of the ISPOR Dynamic Simulation Modeling Emerging Good Practices Task Force.

PubMed

Marshall, Deborah A; Burgos-Liz, Lina; IJzerman, Maarten J; Crown, William; Padula, William V; Wong, Peter K; Pasupathy, Kalyan S; Higashi, Mitchell K; Osgood, Nathaniel D

2015-03-01

In a previous report, the ISPOR Task Force on Dynamic Simulation Modeling Applications in Health Care Delivery Research Emerging Good Practices introduced the fundamentals of dynamic simulation modeling and identified the types of health care delivery problems for which dynamic simulation modeling can be used more effectively than other modeling methods. The hierarchical relationship between the health care delivery system, providers, patients, and other stakeholders exhibits a level of complexity that ought to be captured using dynamic simulation modeling methods. As a tool to help researchers decide whether dynamic simulation modeling is an appropriate method for modeling the effects of an intervention on a health care system, we presented the System, Interactions, Multilevel, Understanding, Loops, Agents, Time, Emergence (SIMULATE) checklist consisting of eight elements. This report builds on the previous work, systematically comparing each of the three most commonly used dynamic simulation modeling methods-system dynamics, discrete-event simulation, and agent-based modeling. We review criteria for selecting the most suitable method depending on 1) the purpose-type of problem and research questions being investigated, 2) the object-scope of the model, and 3) the method to model the object to achieve the purpose. Finally, we provide guidance for emerging good practices for dynamic simulation modeling in the health sector, covering all aspects, from the engagement of decision makers in the model design through model maintenance and upkeep. We conclude by providing some recommendations about the application of these methods to add value to informed decision making, with an emphasis on stakeholder engagement, starting with the problem definition. Finally, we identify areas in which further methodological development will likely occur given the growing "volume, velocity and variety" and availability of "big data" to provide empirical evidence and techniques such as machine learning for parameter estimation in dynamic simulation models. Upon reviewing this report in addition to using the SIMULATE checklist, the readers should be able to identify whether dynamic simulation modeling methods are appropriate to address the problem at hand and to recognize the differences of these methods from those of other, more traditional modeling approaches such as Markov models and decision trees. This report provides an overview of these modeling methods and examples of health care system problems in which such methods have been useful. The primary aim of the report was to aid decisions as to whether these simulation methods are appropriate to address specific health systems problems. The report directs readers to other resources for further education on these individual modeling methods for system interventions in the emerging field of health care delivery science and implementation. Copyright © 2015. Published by Elsevier Inc.

Coupled socioeconomic-crop modelling for the participatory local analysis of climate change impacts on smallholder farmers in Guatemala

NASA Astrophysics Data System (ADS)

Malard, J. J.; Adamowski, J. F.; Wang, L. Y.; Rojas, M.; Carrera, J.; Gálvez, J.; Tuy, H. A.; Melgar-Quiñonez, H.

2015-12-01

The modelling of the impacts of climate change on agriculture requires the inclusion of socio-economic factors. However, while cropping models and economic models of agricultural systems are common, dynamically coupled socio-economic-biophysical models have not received as much success. A promising methodology for modelling the socioeconomic aspects of coupled natural-human systems is participatory system dynamics modelling, in which stakeholders develop mental maps of the socio-economic system that are then turned into quantified simulation models. This methodology has been successful in the water resources management field. However, while the stocks and flows of water resources have also been represented within the system dynamics modelling framework and thus coupled to the socioeconomic portion of the model, cropping models are ill-suited for such reformulation. In addition, most of these system dynamics models were developed without stakeholder input, limiting the scope for the adoption and implementation of their results. We therefore propose a new methodology for the analysis of climate change variability on agroecosystems which uses dynamically coupled system dynamics (socio-economic) and biophysical (cropping) models to represent both physical and socioeconomic aspects of the agricultural system, using two case studies (intensive market-based agricultural development versus subsistence crop-based development) from rural Guatemala. The system dynamics model component is developed with relevant governmental and NGO stakeholders from rural and agricultural development in the case study regions and includes such processes as education, poverty and food security. Common variables with the cropping models (yield and agricultural management choices) are then used to dynamically couple the two models together, allowing for the analysis of the agroeconomic system's response to and resilience against various climatic and socioeconomic shocks.

Predicting the effects of unmodeled dynamics on an aircraft flight control system design using eigenspace assignment

NASA Technical Reports Server (NTRS)

Johnson, Eric N.; Davidson, John B.; Murphy, Patrick C.

1994-01-01

When using eigenspace assignment to design an aircraft flight control system, one must first develop a model of the plant. Certain questions arise when creating this model as to which dynamics of the plant need to be included in the model and which dynamics can be left out or approximated. The answers to these questions are important because a poor choice can lead to closed-loop dynamics that are unpredicted by the design model. To alleviate this problem, a method has been developed for predicting the effect of not including certain dynamics in the design model on the final closed-loop eigenspace. This development provides insight as to which characteristics of unmodeled dynamics will ultimately affect the closed-loop rigid-body dynamics. What results from this insight is a guide for eigenstructure control law designers to aid them in determining which dynamics need or do not need to be included and a new way to include these dynamics in the flight control system design model to achieve a required accuracy in the closed-loop rigid-body dynamics. The method is illustrated for a lateral-directional flight control system design using eigenspace assignment for the NASA High Alpha Research Vehicle (HARV).

Nonlinear dynamic analysis of traveling wave-type ultrasonic motors.

PubMed

Nakagawa, Yosuke; Saito, Akira; Maeno, Takashi

2008-03-01

In this paper, nonlinear dynamic response of a traveling wave-type ultrasonic motor was investigated. In particular, understanding the transient dynamics of a bar-type ultrasonic motor, such as starting up and stopping, is of primary interest. First, the transient response of the bar-type ultrasonic motor at starting up and stopping was measured using a laser Doppler velocimeter, and its driving characteristics are discussed in detail. The motor is shown to possess amplitude-dependent nonlinearity that greatly influences the transient dynamics of the motor. Second, a dynamical model of the motor was constructed as a second-order nonlinear oscillator, which represents the dynamics of the piezoelectric ceramic, stator, and rotor. The model features nonlinearities caused by the frictional interface between the stator and the rotor, and cubic nonlinearity in the dynamics of the stator. Coulomb's friction model was employed for the interface model, and a stick-slip phenomenon is considered. Lastly, it was shown that the model is capable of representing the transient dynamics of the motor accurately. The critical parameters in the model were identified from measured results, and numerical simulations were conducted using the model with the identified parameters. Good agreement between the results of measurements and numerical simulations is observed.

Discrete dynamic modeling of cellular signaling networks.

PubMed

Albert, Réka; Wang, Rui-Sheng

2009-01-01

Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

Diffusion models for innovation: s-curves, networks, power laws, catastrophes, and entropy.

PubMed

Jacobsen, Joseph J; Guastello, Stephen J

2011-04-01

This article considers models for the diffusion of innovation would be most relevant to the dynamics of early 21st century technologies. The article presents an overview of diffusion models and examines the adoption S-curve, network theories, difference models, influence models, geographical models, a cusp catastrophe model, and self-organizing dynamics that emanate from principles of network configuration and principles of heat diffusion. The diffusion dynamics that are relevant to information technologies and energy-efficient technologies are compared. Finally, principles of nonlinear dynamics for innovation diffusion that could be used to rehabilitate the global economic situation are discussed.

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE PAGES

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

2015-10-30

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Optimal Objective-Based Experimental Design for Uncertain Dynamical Gene Networks with Experimental Error.

PubMed

Mohsenizadeh, Daniel N; Dehghannasiri, Roozbeh; Dougherty, Edward R

2018-01-01

In systems biology, network models are often used to study interactions among cellular components, a salient aim being to develop drugs and therapeutic mechanisms to change the dynamical behavior of the network to avoid undesirable phenotypes. Owing to limited knowledge, model uncertainty is commonplace and network dynamics can be updated in different ways, thereby giving multiple dynamic trajectories, that is, dynamics uncertainty. In this manuscript, we propose an experimental design method that can effectively reduce the dynamics uncertainty and improve performance in an interaction-based network. Both dynamics uncertainty and experimental error are quantified with respect to the modeling objective, herein, therapeutic intervention. The aim of experimental design is to select among a set of candidate experiments the experiment whose outcome, when applied to the network model, maximally reduces the dynamics uncertainty pertinent to the intervention objective.

Use of measurement theory for operationalization and quantification of psychological constructs in systems dynamics modelling

NASA Astrophysics Data System (ADS)

Fitkov-Norris, Elena; Yeghiazarian, Ara

2016-11-01

The analytical tools available to social scientists have traditionally been adapted from tools originally designed for analysis of natural science phenomena. This article discusses the applicability of systems dynamics - a qualitative based modelling approach, as a possible analysis and simulation tool that bridges the gap between social and natural sciences. After a brief overview of the systems dynamics modelling methodology, the advantages as well as limiting factors of systems dynamics to the potential applications in the field of social sciences and human interactions are discussed. The issues arise with regards to operationalization and quantification of latent constructs at the simulation building stage of the systems dynamics methodology and measurement theory is proposed as a ready and waiting solution to the problem of dynamic model calibration, with a view of improving simulation model reliability and validity and encouraging the development of standardised, modular system dynamics models that can be used in social science research.

Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation

PubMed Central

2017-01-01

The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. However, the original definition of dynamical compensation amounts to lack of structural identifiability. This is relevant if model parameters need to be estimated, as is often the case in biological modelling. Care should we taken when using an unidentifiable model to extract biological insight: the estimated values of structurally unidentifiable parameters are meaningless, and model predictions about unmeasured state variables can be wrong. Taking this into account, we explore alternative definitions of dynamical compensation that do not necessarily imply structural unidentifiability. Accordingly, we show different ways in which a model can be made identifiable while exhibiting dynamical compensation. Our analyses enable the use of the new concept of dynamical compensation in the context of parameter identification, and reconcile it with the desirable property of structural identifiability. PMID:29186132

Update: Advancement of Contact Dynamics Modeling for Human Spaceflight Simulation Applications

NASA Technical Reports Server (NTRS)

Brain, Thomas A.; Kovel, Erik B.; MacLean, John R.; Quiocho, Leslie J.

2017-01-01

Pong is a new software tool developed at the NASA Johnson Space Center that advances interference-based geometric contact dynamics based on 3D graphics models. The Pong software consists of three parts: a set of scripts to extract geometric data from 3D graphics models, a contact dynamics engine that provides collision detection and force calculations based on the extracted geometric data, and a set of scripts for visualizing the dynamics response with the 3D graphics models. The contact dynamics engine can be linked with an external multibody dynamics engine to provide an integrated multibody contact dynamics simulation. This paper provides a detailed overview of Pong including the overall approach and modeling capabilities, which encompasses force generation from contact primitives and friction to computational performance. Two specific Pong-based examples of International Space Station applications are discussed, and the related verification and validation using this new tool are also addressed.

Tethered satellite system dynamics and control

NASA Technical Reports Server (NTRS)

Musetti, B.; Cibrario, B.; Bussolino, L.; Bodley, C. S.; Flanders, H. A.; Mowery, D. K.; Tomlin, D. D.

1990-01-01

The first tethered satellite system, scheduled for launch in May 1991, is reviewed. The system dynamics, dynamics control, and dynamics simulations are discussed. Particular attention is given to in-plane and out-of-plane librations; tether oscillation modes; orbiter and sub-satellite dynamics; deployer control system; the sub-satellite attitude measurement and control system; the Aeritalia Dynamics Model; the Martin-Marietta and NASA-MSFC Dynamics Model; and simulation results.

Nitrogen feedbacks increase future terrestrial ecosystem carbon uptake in an individual-based dynamic vegetation model

NASA Astrophysics Data System (ADS)

Wårlind, D.; Smith, B.; Hickler, T.; Arneth, A.

2014-11-01

Recently a considerable amount of effort has been put into quantifying how interactions of the carbon and nitrogen cycle affect future terrestrial carbon sinks. Dynamic vegetation models, representing the nitrogen cycle with varying degree of complexity, have shown diverging constraints of nitrogen dynamics on future carbon sequestration. In this study, we use LPJ-GUESS, a dynamic vegetation model employing a detailed individual- and patch-based representation of vegetation dynamics, to evaluate how population dynamics and resource competition between plant functional types, combined with nitrogen dynamics, have influenced the terrestrial carbon storage in the past and to investigate how terrestrial carbon and nitrogen dynamics might change in the future (1850 to 2100; one representative "business-as-usual" climate scenario). Single-factor model experiments of CO2 fertilisation and climate change show generally similar directions of the responses of C-N interactions, compared to the C-only version of the model as documented in previous studies using other global models. Under an RCP 8.5 scenario, nitrogen limitation suppresses potential CO2 fertilisation, reducing the cumulative net ecosystem carbon uptake between 1850 and 2100 by 61%, and soil warming-induced increase in nitrogen mineralisation reduces terrestrial carbon loss by 31%. When environmental changes are considered conjointly, carbon sequestration is limited by nitrogen dynamics up to the present. However, during the 21st century, nitrogen dynamics induce a net increase in carbon sequestration, resulting in an overall larger carbon uptake of 17% over the full period. This contrasts with previous results with other global models that have shown an 8 to 37% decrease in carbon uptake relative to modern baseline conditions. Implications for the plausibility of earlier projections of future terrestrial C dynamics based on C-only models are discussed.

Addressing Dynamic Issues of Program Model Checking

NASA Technical Reports Server (NTRS)

Lerda, Flavio; Visser, Willem

2001-01-01

Model checking real programs has recently become an active research area. Programs however exhibit two characteristics that make model checking difficult: the complexity of their state and the dynamic nature of many programs. Here we address both these issues within the context of the Java PathFinder (JPF) model checker. Firstly, we will show how the state of a Java program can be encoded efficiently and how this encoding can be exploited to improve model checking. Next we show how to use symmetry reductions to alleviate some of the problems introduced by the dynamic nature of Java programs. Lastly, we show how distributed model checking of a dynamic program can be achieved, and furthermore, how dynamic partitions of the state space can improve model checking. We support all our findings with results from applying these techniques within the JPF model checker.

An AD100 implementation of a real-time STOVL aircraft propulsion system

NASA Technical Reports Server (NTRS)

Ouzts, Peter J.; Drummond, Colin K.

1990-01-01

A real-time dynamic model of the propulsion system for a Short Take-Off and Vertical Landing (STOVL) aircraft was developed for the AD100 simulation environment. The dynamic model was adapted from a FORTRAN based simulation using the dynamic programming capabilities of the AD100 ADSIM simulation language. The dynamic model includes an aerothermal representation of a turbofan jet engine, actuator and sensor models, and a multivariable control system. The AD100 model was tested for agreement with the FORTRAN model and real-time execution performance. The propulsion system model was also linked to an airframe dynamic model to provide an overall STOVL aircraft simulation for the purposes of integrated flight and propulsion control studies. An evaluation of the AD100 system for use as an aircraft simulation environment is included.

Gear fatigue crack prognosis using embedded model, gear dynamic model and fracture mechanics

NASA Astrophysics Data System (ADS)

Li, C. James; Lee, Hyungdae

2005-07-01

This paper presents a model-based method that predicts remaining useful life of a gear with a fatigue crack. The method consists of an embedded model to identify gear meshing stiffness from measured gear torsional vibration, an inverse method to estimate crack size from the estimated meshing stiffness; a gear dynamic model to simulate gear meshing dynamics and determine the dynamic load on the cracked tooth; and a fast crack propagation model to forecast the remaining useful life based on the estimated crack size and dynamic load. The fast crack propagation model was established to avoid repeated calculations of FEM and facilitate field deployment of the proposed method. Experimental studies were conducted to validate and demonstrate the feasibility of the proposed method for prognosis of a cracked gear.

Analysis, simulation and visualization of 1D tapping via reduced dynamical models

NASA Astrophysics Data System (ADS)

Blackmore, Denis; Rosato, Anthony; Tricoche, Xavier; Urban, Kevin; Zou, Luo

2014-04-01

A low-dimensional center-of-mass dynamical model is devised as a simplified means of approximately predicting some important aspects of the motion of a vertical column comprised of a large number of particles subjected to gravity and periodic vertical tapping. This model is investigated first as a continuous dynamical system using analytical, simulation and visualization techniques. Then, by employing an approach analogous to that used to approximate the dynamics of a bouncing ball on an oscillating flat plate, it is modeled as a discrete dynamical system and analyzed to determine bifurcations and transitions to chaotic motion along with other properties. The predictions of the analysis are then compared-primarily qualitatively-with visualization and simulation results of the reduced continuous model, and ultimately with simulations of the complete system dynamics.

A lateral dynamics of a wheelchair: identification and analysis of tire parameters.

PubMed

Silva, L C A; Corrêa, F C; Eckert, J J; Santiciolli, F M; Dedini, F G

2017-02-01

In vehicle dynamics studies, the tire behaviour plays an important role in planar motion of the vehicle. Therefore, a correct representation of tire is a necessity. This paper describes a mathematical model for wheelchair tire based on the Magic Formula model. This model is widely used to represent forces and moments between the tire and the ground; however some experimental parameters must be determined. The purpose of this work is to identify the tire parameters for the wheelchair tire model, implementing them in a dynamic model of the wheelchair. For this, we developed an experimental test rig to measure the tires parameters for the lateral dynamics of a wheelchair. This dynamic model was made using a multi-body software and the wheelchair behaviour was analysed and discussed according to the tire parameters. The result of this work is one step further towards the understanding of wheelchair dynamics.

Automatic network coupling analysis for dynamical systems based on detailed kinetic models.

PubMed

Lebiedz, Dirk; Kammerer, Julia; Brandt-Pollmann, Ulrich

2005-10-01

We introduce a numerical complexity reduction method for the automatic identification and analysis of dynamic network decompositions in (bio)chemical kinetics based on error-controlled computation of a minimal model dimension represented by the number of (locally) active dynamical modes. Our algorithm exploits a generalized sensitivity analysis along state trajectories and subsequent singular value decomposition of sensitivity matrices for the identification of these dominant dynamical modes. It allows for a dynamic coupling analysis of (bio)chemical species in kinetic models that can be exploited for the piecewise computation of a minimal model on small time intervals and offers valuable functional insight into highly nonlinear reaction mechanisms and network dynamics. We present results for the identification of network decompositions in a simple oscillatory chemical reaction, time scale separation based model reduction in a Michaelis-Menten enzyme system and network decomposition of a detailed model for the oscillatory peroxidase-oxidase enzyme system.

Dynamic model of production enterprises based on accounting registers and its identification

NASA Astrophysics Data System (ADS)

Sirazetdinov, R. T.; Samodurov, A. V.; Yenikeev, I. A.; Markov, D. S.

2016-06-01

The report focuses on the mathematical modeling of economic entities based on accounting registers. Developed the dynamic model of financial and economic activity of the enterprise as a system of differential equations. Created algorithms for identification of parameters of the dynamic model. Constructed and identified the model of Russian machine-building enterprises.

The past and future of modeling forest dynamics: from growth and yield curves to forest landscape models

Treesearch

Stephen R. Shifley; Hong S. He; Heike Lischke; Wen J. Wang; Wenchi Jin; Eric J. Gustafson; Jonathan R. Thompson; Frank R. Thompson; William D. Dijak; Jian Yang

2017-01-01

Context. Quantitative models of forest dynamics have followed a progression toward methods with increased detail, complexity, and spatial extent. Objectives. We highlight milestones in the development of forest dynamics models and identify future research and application opportunities. Methods. We reviewed...

The System Dynamics Model User Sustainability Explorer (SD-MUSE): a user-friendly tool for interpreting system dynamic models

EPA Science Inventory

System Dynamics (SD) models are useful for holistic integration of data to evaluate indirect and cumulative effects and inform decisions. Complex SD models can provide key insights into how decisions affect the three interconnected pillars of sustainability. However, the complexi...

Supply based on demand dynamical model

NASA Astrophysics Data System (ADS)

Levi, Asaf; Sabuco, Juan; Sanjuán, Miguel A. F.

2018-04-01

We propose and numerically analyze a simple dynamical model that describes the firm behaviors under uncertainty of demand. Iterating this simple model and varying some parameter values, we observe a wide variety of market dynamics such as equilibria, periodic, and chaotic behaviors. Interestingly, the model is also able to reproduce market collapses.

Dynamics in Higher Education Politics: A Theoretical Model

ERIC Educational Resources Information Center

Kauko, Jaakko

2013-01-01

This article presents a model for analysing dynamics in higher education politics (DHEP). Theoretically the model draws on the conceptual history of political contingency, agenda-setting theories and previous research on higher education dynamics. According to the model, socio-historical complexity can best be analysed along two dimensions: the…

Volterra representation enables modeling of complex synaptic nonlinear dynamics in large-scale simulations.

PubMed

Hu, Eric Y; Bouteiller, Jean-Marie C; Song, Dong; Baudry, Michel; Berger, Theodore W

2015-01-01

Chemical synapses are comprised of a wide collection of intricate signaling pathways involving complex dynamics. These mechanisms are often reduced to simple spikes or exponential representations in order to enable computer simulations at higher spatial levels of complexity. However, these representations cannot capture important nonlinear dynamics found in synaptic transmission. Here, we propose an input-output (IO) synapse model capable of generating complex nonlinear dynamics while maintaining low computational complexity. This IO synapse model is an extension of a detailed mechanistic glutamatergic synapse model capable of capturing the input-output relationships of the mechanistic model using the Volterra functional power series. We demonstrate that the IO synapse model is able to successfully track the nonlinear dynamics of the synapse up to the third order with high accuracy. We also evaluate the accuracy of the IO synapse model at different input frequencies and compared its performance with that of kinetic models in compartmental neuron models. Our results demonstrate that the IO synapse model is capable of efficiently replicating complex nonlinear dynamics that were represented in the original mechanistic model and provide a method to replicate complex and diverse synaptic transmission within neuron network simulations.

Volterra representation enables modeling of complex synaptic nonlinear dynamics in large-scale simulations

PubMed Central

Hu, Eric Y.; Bouteiller, Jean-Marie C.; Song, Dong; Baudry, Michel; Berger, Theodore W.

2015-01-01

Chemical synapses are comprised of a wide collection of intricate signaling pathways involving complex dynamics. These mechanisms are often reduced to simple spikes or exponential representations in order to enable computer simulations at higher spatial levels of complexity. However, these representations cannot capture important nonlinear dynamics found in synaptic transmission. Here, we propose an input-output (IO) synapse model capable of generating complex nonlinear dynamics while maintaining low computational complexity. This IO synapse model is an extension of a detailed mechanistic glutamatergic synapse model capable of capturing the input-output relationships of the mechanistic model using the Volterra functional power series. We demonstrate that the IO synapse model is able to successfully track the nonlinear dynamics of the synapse up to the third order with high accuracy. We also evaluate the accuracy of the IO synapse model at different input frequencies and compared its performance with that of kinetic models in compartmental neuron models. Our results demonstrate that the IO synapse model is capable of efficiently replicating complex nonlinear dynamics that were represented in the original mechanistic model and provide a method to replicate complex and diverse synaptic transmission within neuron network simulations. PMID:26441622

Propagating waves can explain irregular neural dynamics.

PubMed

Keane, Adam; Gong, Pulin

2015-01-28

Cortical neurons in vivo fire quite irregularly. Previous studies about the origin of such irregular neural dynamics have given rise to two major models: a balanced excitation and inhibition model, and a model of highly synchronized synaptic inputs. To elucidate the network mechanisms underlying synchronized synaptic inputs and account for irregular neural dynamics, we investigate a spatially extended, conductance-based spiking neural network model. We show that propagating wave patterns with complex dynamics emerge from the network model. These waves sweep past neurons, to which they provide highly synchronized synaptic inputs. On the other hand, these patterns only emerge from the network with balanced excitation and inhibition; our model therefore reconciles the two major models of irregular neural dynamics. We further demonstrate that the collective dynamics of propagating wave patterns provides a mechanistic explanation for a range of irregular neural dynamics, including the variability of spike timing, slow firing rate fluctuations, and correlated membrane potential fluctuations. In addition, in our model, the distributions of synaptic conductance and membrane potential are non-Gaussian, consistent with recent experimental data obtained using whole-cell recordings. Our work therefore relates the propagating waves that have been widely observed in the brain to irregular neural dynamics. These results demonstrate that neural firing activity, although appearing highly disordered at the single-neuron level, can form dynamical coherent structures, such as propagating waves at the population level. Copyright © 2015 the authors 0270-6474/15/351591-15$15.00/0.

Dynamic inverse models in human-cyber-physical systems

NASA Astrophysics Data System (ADS)

Robinson, Ryan M.; Scobee, Dexter R. R.; Burden, Samuel A.; Sastry, S. Shankar

2016-05-01

Human interaction with the physical world is increasingly mediated by automation. This interaction is characterized by dynamic coupling between robotic (i.e. cyber) and neuromechanical (i.e. human) decision-making agents. Guaranteeing performance of such human-cyber-physical systems will require predictive mathematical models of this dynamic coupling. Toward this end, we propose a rapprochement between robotics and neuromechanics premised on the existence of internal forward and inverse models in the human agent. We hypothesize that, in tele-robotic applications of interest, a human operator learns to invert automation dynamics, directly translating from desired task to required control input. By formulating the model inversion problem in the context of a tracking task for a nonlinear control system in control-a_ne form, we derive criteria for exponential tracking and show that the resulting dynamic inverse model generally renders a portion of the physical system state (i.e., the internal dynamics) unobservable from the human operator's perspective. Under stability conditions, we show that the human can achieve exponential tracking without formulating an estimate of the system's state so long as they possess an accurate model of the system's dynamics. These theoretical results are illustrated using a planar quadrotor example. We then demonstrate that the automation can intervene to improve performance of the tracking task by solving an optimal control problem. Performance is guaranteed to improve under the assumption that the human learns and inverts the dynamic model of the altered system. We conclude with a discussion of practical limitations that may hinder exact dynamic model inversion.

Faster than Real-Time Dynamic Simulation for Large-Size Power System with Detailed Dynamic Models using High-Performance Computing Platform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Renke; Jin, Shuangshuang; Chen, Yousu

This paper presents a faster-than-real-time dynamic simulation software package that is designed for large-size power system dynamic simulation. It was developed on the GridPACKTM high-performance computing (HPC) framework. The key features of the developed software package include (1) faster-than-real-time dynamic simulation for a WECC system (17,000 buses) with different types of detailed generator, controller, and relay dynamic models, (2) a decoupled parallel dynamic simulation algorithm with optimized computation architecture to better leverage HPC resources and technologies, (3) options for HPC-based linear and iterative solvers, (4) hidden HPC details, such as data communication and distribution, to enable development centered on mathematicalmore » models and algorithms rather than on computational details for power system researchers, and (5) easy integration of new dynamic models and related algorithms into the software package.« less

Dynamics of aerospace vehicles

NASA Technical Reports Server (NTRS)

Schmidt, David K.

1991-01-01

The focus of this research was to address the modeling, including model reduction, of flexible aerospace vehicles, with special emphasis on models used in dynamic analysis and/or guidance and control system design. In the modeling, it is critical that the key aspects of the system being modeled be captured in the model. In this work, therefore, aspects of the vehicle dynamics critical to control design were important. In this regard, fundamental contributions were made in the areas of stability robustness analysis techniques, model reduction techniques, and literal approximations for key dynamic characteristics of flexible vehicles. All these areas are related. In the development of a model, approximations are always involved, so control systems designed using these models must be robust against uncertainties in these models.

Dynamic Modelling Of A SCARA Robot

NASA Astrophysics Data System (ADS)

Turiel, J. Perez; Calleja, R. Grossi; Diez, V. Gutierrez

1987-10-01

This paper describes a method for modelling industrial robots that considers dynamic approach to manipulation systems motion generation, obtaining the complete dynamic model for the mechanic part of the robot and taking into account the dynamic effect of actuators acting at the joints. For a four degree of freedom SCARA robot we obtain the dynamic model for the basic (minimal) configuration, that is, the three degrees of freedom that allow us to place the robot end effector in a desired point, using the Lagrange Method to obtain the dynamic equations in matrix form. The manipulator is considered to be a set of rigid bodies inter-connected by joints in the form of simple kinematic pairs. Then, the state space model is obtained for the actuators that move the robot joints, uniting the models of the single actuators, that is, two DC permanent magnet servomotors and an electrohydraulic actuator. Finally, using a computer simulation program written in FORTRAN language, we can compute the matrices of the complete model.

Optimal post-experiment estimation of poorly modeled dynamic systems

NASA Technical Reports Server (NTRS)

Mook, D. Joseph

1988-01-01

Recently, a novel strategy for post-experiment state estimation of discretely-measured dynamic systems has been developed. The method accounts for errors in the system dynamic model equations in a more general and rigorous manner than do filter-smoother algorithms. The dynamic model error terms do not require the usual process noise assumptions of zero-mean, symmetrically distributed random disturbances. Instead, the model error terms require no prior assumptions other than piecewise continuity. The resulting state estimates are more accurate than filters for applications in which the dynamic model error clearly violates the typical process noise assumptions, and the available measurements are sparse and/or noisy. Estimates of the dynamic model error, in addition to the states, are obtained as part of the solution of a two-point boundary value problem, and may be exploited for numerous reasons. In this paper, the basic technique is explained, and several example applications are given. Included among the examples are both state estimation and exploitation of the model error estimates.

A dynamic, climate-driven model of Rift Valley fever.

PubMed

Leedale, Joseph; Jones, Anne E; Caminade, Cyril; Morse, Andrew P

2016-03-31

Outbreaks of Rift Valley fever (RVF) in eastern Africa have previously occurred following specific rainfall dynamics and flooding events that appear to support the emergence of large numbers of mosquito vectors. As such, transmission of the virus is considered to be sensitive to environmental conditions and therefore changes in climate can impact the spatiotemporal dynamics of epizootic vulnerability. Epidemiological information describing the methods and parameters of RVF transmission and its dependence on climatic factors are used to develop a new spatio-temporal mathematical model that simulates these dynamics and can predict the impact of changes in climate. The Liverpool RVF (LRVF) model is a new dynamic, process-based model driven by climate data that provides a predictive output of geographical changes in RVF outbreak susceptibility as a result of the climate and local livestock immunity. This description of the multi-disciplinary process of model development is accessible to mathematicians, epidemiological modellers and climate scientists, uniting dynamic mathematical modelling, empirical parameterisation and state-of-the-art climate information.

Blob-Spring Model for the Dynamics of Ring Polymer in Obstacle Environment

NASA Astrophysics Data System (ADS)

Lele, Ashish K.; Iyer, Balaji V. S.; Juvekar, Vinay A.

2008-07-01

The dynamical behavior of cyclic macromolecules in a fixed obstacle (FO) environment is very different than the behavior of linear chains in the same topological environment; while the latter relax by a snake-like reptational motion from their chain ends the former can relax only by contour length fluctuations since they are endless. Duke, Obukhov and Rubinstein proposed a scaling model (the DOR model) to interpret the dynamical scaling exponents shown by Monte Carlo simulations of rings in a FO environment. We present a model (blob-spring model) to describe the dynamics of flexible and non-concatenated ring polymer in FO environment based on a theoretical formulation developed for the dynamics of an unentangled fractal polymer. We argue that the perpetual evolution of ring perimeter by the motion of contour segments results in an extra frictional load. Our model predicts self-similar dynamics with scaling exponents for the molecular weight dependence of diffusion coefficient and relaxation times that are in agreement with the scaling model proposed by Obukhov et al.

Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model.

PubMed

Bringmann, Laura F; Ferrer, Emilio; Hamaker, Ellen L; Borsboom, Denny; Tuerlinckx, Francis

2018-01-01

Emotion dynamics are likely to arise in an interpersonal context. Standard methods to study emotions in interpersonal interaction are limited because stationarity is assumed. This means that the dynamics, for example, time-lagged relations, are invariant across time periods. However, this is generally an unrealistic assumption. Whether caused by an external (e.g., divorce) or an internal (e.g., rumination) event, emotion dynamics are prone to change. The semi-parametric time-varying vector-autoregressive (TV-VAR) model is based on well-studied generalized additive models, implemented in the software R. The TV-VAR can explicitly model changes in temporal dependency without pre-existing knowledge about the nature of change. A simulation study is presented, showing that the TV-VAR model is superior to the standard time-invariant VAR model when the dynamics change over time. The TV-VAR model is applied to empirical data on daily feelings of positive affect (PA) from a single couple. Our analyses indicate reliable changes in the male's emotion dynamics over time, but not in the female's-which were not predicted by her own affect or that of her partner. This application illustrates the usefulness of using a TV-VAR model to detect changes in the dynamics in a system.

A micromechanical constitutive model for the dynamic response of brittle materials "Dynamic response of marble"

NASA Astrophysics Data System (ADS)

Haberman, Keith

2001-07-01

A micromechanically based constitutive model for the dynamic inelastic behavior of brittle materials, specifically "Dionysus-Pentelicon marble" with distributed microcracking is presented. Dionysus-Pentelicon marble was used in the construction of the Parthenon, in Athens, Greece. The constitutive model is a key component in the ability to simulate this historic explosion and the preceding bombardment form cannon fire that occurred at the Parthenon in 1678. Experiments were performed by Rosakis (1999) that characterized the static and dynamic response of this unique material. A micromechanical constitutive model that was previously successfully used to model the dynamic response of granular brittle materials is presented. The constitutive model was fitted to the experimental data for marble and reproduced the experimentally observed basic uniaxial dynamic behavior quite well. This micromechanical constitutive model was then implemented into the three dimensional nonlinear lagrangain finite element code Dyna3d(1998). Implementing this methodology into the three dimensional nonlinear dynamic finite element code allowed the model to be exercised on several preliminary impact experiments. During future simulations, the model is to be used in conjunction with other numerical techniques to simulate projectile impact and blast loading on the Dionysus-Pentelicon marble and on the structure of the Parthenon.

Aerodynamic analysis of the Darrieus wind turbines including dynamic-stall effects

NASA Astrophysics Data System (ADS)

Paraschivoiu, Ion; Allet, Azeddine

Experimental data for a 17-m wind turbine are compared with aerodynamic performance predictions obtained with two dynamic stall methods which are based on numerical correlations of the dynamic stall delay with the pitch rate parameter. Unlike the Gormont (1973) model, the MIT model predicts that dynamic stall does not occur in the downwind part of the turbine, although it does exist in the upwind zone. The Gormont model is shown to overestimate the aerodynamic coefficients relative to the MIT model. The MIT model is found to accurately predict the dynamic-stall regime, which is characterized by a plateau oscillating near values of the experimental data for the rotor power vs wind speed at the equator.

Closed-form dynamics of a hexarot parallel manipulator by means of the principle of virtual work

NASA Astrophysics Data System (ADS)

Pedrammehr, Siamak; Nahavandi, Saeid; Abdi, Hamid

2018-04-01

In this research, a systematic approach to solving the inverse dynamics of hexarot manipulators is addressed using the methodology of virtual work. For the first time, a closed form of the mathematical formulation of the standard dynamic model is presented for this class of mechanisms. An efficient algorithm for solving this closed-form dynamic model of the mechanism is developed and it is used to simulate the dynamics of the system for different trajectories. Validation of the proposed model is performed using SimMechanics and it is shown that the results of the proposed mathematical model match with the results obtained by the SimMechanics model.

Advanced superposition methods for high speed turbopump vibration analysis

NASA Technical Reports Server (NTRS)

Nielson, C. E.; Campany, A. D.

1981-01-01

The small, high pressure Mark 48 liquid hydrogen turbopump was analyzed and dynamically tested to determine the cause of high speed vibration at an operating speed of 92,400 rpm. This approaches the design point operating speed of 95,000 rpm. The initial dynamic analysis in the design stage and subsequent further analysis of the rotor only dynamics failed to predict the vibration characteristics found during testing. An advanced procedure for dynamics analysis was used in this investigation. The procedure involves developing accurate dynamic models of the rotor assembly and casing assembly by finite element analysis. The dynamically instrumented assemblies are independently rap tested to verify the analytical models. The verified models are then combined by modal superposition techniques to develop a completed turbopump model where dynamic characteristics are determined. The results of the dynamic testing and analysis obtained are presented and methods of moving the high speed vibration characteristics to speeds above the operating range are recommended. Recommendations for use of these advanced dynamic analysis procedures during initial design phases are given.

Tools for assessing mitochondrial dynamics in mouse tissues and neurodegenerative models

NASA Astrophysics Data System (ADS)

Pham, Anh H.

Mitochondria are dynamic organelles that undergo membrane fusion and fission and transport. The dynamic properties of mitochondria are important for regulating mitochondrial function. Defects in mitochondrial dynamics are linked neurodegenerative diseases and affect the development of many tissues. To investigate the role of mitochondrial dynamics in diseases, versatile tools are needed to explore the physiology of these dynamic organelles in multiple tissues. Current tools for monitoring mitochondrial dynamics have been limited to studies in cell culture, which may be inadequate model systems for exploring the network of tissues. Here, we have generated mouse models for monitoring mitochondrial dynamics in a broad spectrum of tissues and cell types. The Photo-Activatable Mitochondrial (PhAM floxed) line enables Cre-inducible expression of a mitochondrial targeted photoconvertible protein, Dendra2 (mito-Dendra2). In the PhAMexcised line, mito-Dendra2 is ubiquitously expressed to facilitate broad analysis of mitochondria at various developmental processes. We have utilized these models to study mitochondrial dynamics in the nigrostriatal circuit of Parkinson's disease (PD) and in the development of skeletal muscles. Increasing evidences implicate aberrant regulation of mitochondrial fusion and fission in models of PD. To assess the function of mitochondrial dynamics in the nigrostriatal circuit, we utilized transgenic techniques to abrogate mitochondrial fusion. We show that deletion of the Mfn2 leads to the degeneration of dopaminergic neurons and Parkinson's-like features in mice. To elucidate the dynamic properties of mitochondria during muscle development, we established a platform for examining mitochondrial compartmentalization in skeletal muscles. This model system may yield clues to the role of mitochondrial dynamics in mitochondrial myopathies.

Dynamics and Collapse in a Power System Model with Voltage Variation: The Damping Effect.

PubMed

Ma, Jinpeng; Sun, Yong; Yuan, Xiaoming; Kurths, Jürgen; Zhan, Meng

2016-01-01

Complex nonlinear phenomena are investigated in a basic power system model of the single-machine-infinite-bus (SMIB) with a synchronous generator modeled by a classical third-order differential equation including both angle dynamics and voltage dynamics, the so-called flux decay equation. In contrast, for the second-order differential equation considering the angle dynamics only, it is the classical swing equation. Similarities and differences of the dynamics generated between the third-order model and the second-order one are studied. We mainly find that, for positive damping, these two models show quite similar behavior, namely, stable fixed point, stable limit cycle, and their coexistence for different parameters. However, for negative damping, the second-order system can only collapse, whereas for the third-order model, more complicated behavior may happen, such as stable fixed point, limit cycle, quasi-periodicity, and chaos. Interesting partial collapse phenomena for angle instability only and not for voltage instability are also found here, including collapse from quasi-periodicity and from chaos etc. These findings not only provide a basic physical picture for power system dynamics in the third-order model incorporating voltage dynamics, but also enable us a deeper understanding of the complex dynamical behavior and even leading to a design of oscillation damping in electric power systems.

Multiscale Modeling of Multiphase Fluid Flow

DTIC Science & Technology

2016-08-01

the disparate time and length scales involved in modeling fluid flow and heat transfer. Molecular dynamics simulations were carried out to provide a...fluid dynamics methods were used to investigate the heat transfer process in open-cell micro-foam with phase change material; enhancement of natural...Computational fluid dynamics, Heat transfer, Phase change material in Micro-foam, Molecular Dynamics, Multiphase flow, Multiscale modeling, Natural

Microworlds of the dynamic balanced scorecard for university (DBSC-UNI)

NASA Astrophysics Data System (ADS)

Hawari, Nurul Nazihah; Tahar, Razman Mat

2015-12-01

This research focuses on the development of a Microworlds of the dynamic balanced scorecard for university in order to enhance the university strategic planning process. To develop the model, we integrated both the balanced scorecard method and the system dynamics modelling method. Contrasting the traditional university planning tools, the developed model addresses university management problems holistically and dynamically. It is found that using system dynamics modelling method, the cause-and-effect relationships among variables related to the four conventional balanced scorecard perspectives are better understand. The dynamic processes that give rise to performance differences between targeted and actual performances also could be better understood. So, it is expected that the quality of the decisions taken are improved because of being better informed. The developed Microworlds can be exploited by university management to design policies that can positively influence the future in the direction of desired goals, and will have minimal side effects. This paper integrates balanced scorecard and system dynamics modelling methods in analyzing university performance. Therefore, this paper demonstrates the effectiveness and strength of system dynamics modelling method in solving problem in strategic planning area particularly in higher education sector.

Population-reaction model and microbial experimental ecosystems for understanding hierarchical dynamics of ecosystems.

PubMed

Hosoda, Kazufumi; Tsuda, Soichiro; Kadowaki, Kohmei; Nakamura, Yutaka; Nakano, Tadashi; Ishii, Kojiro

2016-02-01

Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population-reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population-reaction model. We also show that population-reaction models can be applied to various ecological concepts, such as predator-prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Modelling, simulation and applications of longitudinal train dynamics

NASA Astrophysics Data System (ADS)

Cole, Colin; Spiryagin, Maksym; Wu, Qing; Sun, Yan Quan

2017-10-01

Significant developments in longitudinal train simulation and an overview of the approaches to train models and modelling vehicle force inputs are firstly presented. The most important modelling task, that of the wagon connection, consisting of energy absorption devices such as draft gears and buffers, draw gear stiffness, coupler slack and structural stiffness is then presented. Detailed attention is given to the modelling approaches for friction wedge damped and polymer draft gears. A significant issue in longitudinal train dynamics is the modelling and calculation of the input forces - the co-dimensional problem. The need to push traction performances higher has led to research and improvement in the accuracy of traction modelling which is discussed. A co-simulation method that combines longitudinal train simulation, locomotive traction control and locomotive vehicle dynamics is presented. The modelling of other forces, braking propulsion resistance, curve drag and grade forces are also discussed. As extensions to conventional longitudinal train dynamics, lateral forces and coupler impacts are examined in regards to interaction with wagon lateral and vertical dynamics. Various applications of longitudinal train dynamics are then presented. As an alternative to the tradition single wagon mass approach to longitudinal train dynamics, an example incorporating fully detailed wagon dynamics is presented for a crash analysis problem. Further applications of starting traction, air braking, distributed power, energy analysis and tippler operation are also presented.

Nitrogen dynamics in flooded soil systems: an overview on concepts and performance of models

PubMed Central

Nurulhuda, Khairudin; Gaydon, Donald S; Jing, Qi; Zakaria, Mohamad P; Struik, Paul C

2017-01-01

Abstract Extensive modelling studies on nitrogen (N) dynamics in flooded soil systems have been published. Consequently, many N dynamics models are available for users to select from. With the current research trend, inclined towards multidisciplinary research, and with substantial progress in understanding of N dynamics in flooded soil systems, the objective of this paper is to provide an overview of the modelling concepts and performance of 14 models developed to simulate N dynamics in flooded soil systems. This overview provides breadth of knowledge on the models, and, therefore, is valuable as a first step in the selection of an appropriate model for a specific application. © 2017 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. PMID:28940491

Comparing models of Red Knot population dynamics

USGS Publications Warehouse

McGowan, Conor P.

2015-01-01

Predictive population modeling contributes to our basic scientific understanding of population dynamics, but can also inform management decisions by evaluating alternative actions in virtual environments. Quantitative models mathematically reflect scientific hypotheses about how a system functions. In Delaware Bay, mid-Atlantic Coast, USA, to more effectively manage horseshoe crab (Limulus polyphemus) harvests and protect Red Knot (Calidris canutus rufa) populations, models are used to compare harvest actions and predict the impacts on crab and knot populations. Management has been chiefly driven by the core hypothesis that horseshoe crab egg abundance governs the survival and reproduction of migrating Red Knots that stopover in the Bay during spring migration. However, recently, hypotheses proposing that knot dynamics are governed by cyclical lemming dynamics garnered some support in data analyses. In this paper, I present alternative models of Red Knot population dynamics to reflect alternative hypotheses. Using 2 models with different lemming population cycle lengths and 2 models with different horseshoe crab effects, I project the knot population into the future under environmental stochasticity and parametric uncertainty with each model. I then compare each model's predictions to 10 yr of population monitoring from Delaware Bay. Using Bayes' theorem and model weight updating, models can accrue weight or support for one or another hypothesis of population dynamics. With 4 models of Red Knot population dynamics and only 10 yr of data, no hypothesis clearly predicted population count data better than another. The collapsed lemming cycle model performed best, accruing ~35% of the model weight, followed closely by the horseshoe crab egg abundance model, which accrued ~30% of the weight. The models that predicted no decline or stable populations (i.e. the 4-yr lemming cycle model and the weak horseshoe crab effect model) were the most weakly supported.

MSEE: Stochastic Cognitive Linguistic Behavior Models for Semantic Sensing

DTIC Science & Technology

2013-09-01

recognition, a Gaussian Process Dynamic Model with Social Network Analysis (GPDM-SNA) for a small human group action recognition, an extended GPDM-SNA...44  3.2. Small Human Group Activity Modeling Based on Gaussian Process Dynamic Model and Social Network Analysis (SN-GPDM...51  Approved for public release; distribution unlimited. 3 3.2.3. Gaussian Process Dynamical Model and

Nonlinear dynamic mechanism of vocal tremor from voice analysis and model simulations

NASA Astrophysics Data System (ADS)

Zhang, Yu; Jiang, Jack J.

2008-09-01

Nonlinear dynamic analysis and model simulations are used to study the nonlinear dynamic characteristics of vocal folds with vocal tremor, which can typically be characterized by low-frequency modulation and aperiodicity. Tremor voices from patients with disorders such as paresis, Parkinson's disease, hyperfunction, and adductor spasmodic dysphonia show low-dimensional characteristics, differing from random noise. Correlation dimension analysis statistically distinguishes tremor voices from normal voices. Furthermore, a nonlinear tremor model is proposed to study the vibrations of the vocal folds with vocal tremor. Fractal dimensions and positive Lyapunov exponents demonstrate the evidence of chaos in the tremor model, where amplitude and frequency play important roles in governing vocal fold dynamics. Nonlinear dynamic voice analysis and vocal fold modeling may provide a useful set of tools for understanding the dynamic mechanism of vocal tremor in patients with laryngeal diseases.

The effects of spatial dynamics on a wormhole throat

NASA Astrophysics Data System (ADS)

Alias, Anuar; Wan Abdullah, Wan Ahmad Tajuddin

2018-02-01

Previous studies on dynamic wormholes were focused on the dynamics of the wormhole itself, be it either rotating or evolutionary in character and also in various frameworks from classical to braneworld cosmological models. In this work, we modeled a dynamic factor that represents the spatial dynamics in terms of spacetime expansion and contraction surrounding the wormhole itself. Using an RS2-based braneworld cosmological model, we modified the spacetime metric of Wong and subsequently employed the method of Bronnikov, where it is observed that a traversable wormhole is easier to exist in an expanding brane universe, however it is difficult to exist in a contracting brane universe due to stress-energy tensors requirement. This model of spatial dynamic factor affecting the wormhole throat can also be applied on the cyclic or the bounce universe model.

Structure and dynamics of complex liquid water: Molecular dynamics simulation

NASA Astrophysics Data System (ADS)

S, Indrajith V.; Natesan, Baskaran

2015-06-01

We have carried out detailed structure and dynamical studies of complex liquid water using molecular dynamics simulations. Three different model potentials, namely, TIP3P, TIP4P and SPC-E have been used in the simulations, in order to arrive at the best possible potential function that could reproduce the structure of experimental bulk water. All the simulations were performed in the NVE micro canonical ensemble using LAMMPS. The radial distribution functions, gOO, gOH and gHH and the self diffusion coefficient, Ds, were calculated for all three models. We conclude from our results that the structure and dynamical parameters obtained for SPC-E model matched well with the experimental values, suggesting that among the models studied here, the SPC-E model gives the best structure and dynamics of bulk water.

A Novel Fractional Order Model for the Dynamic Hysteresis of Piezoelectrically Actuated Fast Tool Servo

PubMed Central

Zhu, Zhiwei; Zhou, Xiaoqin

2012-01-01

The main contribution of this paper is the development of a linearized model for describing the dynamic hysteresis behaviors of piezoelectrically actuated fast tool servo (FTS). A linearized hysteresis force model is proposed and mathematically described by a fractional order differential equation. Combining the dynamic modeling of the FTS mechanism, a linearized fractional order dynamic hysteresis (LFDH) model for the piezoelectrically actuated FTS is established. The unique features of the LFDH model could be summarized as follows: (a) It could well describe the rate-dependent hysteresis due to its intrinsic characteristics of frequency-dependent nonlinear phase shifts and amplitude modulations; (b) The linearization scheme of the LFDH model would make it easier to implement the inverse dynamic control on piezoelectrically actuated micro-systems. To verify the effectiveness of the proposed model, a series of experiments are conducted. The toolpaths of the FTS for creating two typical micro-functional surfaces involving various harmonic components with different frequencies and amplitudes are scaled and employed as command signals for the piezoelectric actuator. The modeling errors in the steady state are less than ±2.5% within the full span range which is much smaller than certain state-of-the-art modeling methods, demonstrating the efficiency and superiority of the proposed model for modeling dynamic hysteresis effects. Moreover, it indicates that the piezoelectrically actuated micro systems would be more suitably described as a fractional order dynamic system.

The Dynamics of the Law of Effect: A Comparison of Models

ERIC Educational Resources Information Center

Navakatikyan, Michael A.; Davison, Michael

2010-01-01

Dynamical models based on three steady-state equations for the law of effect were constructed under the assumption that behavior changes in proportion to the difference between current behavior and the equilibrium implied by current reinforcer rates. A comparison of dynamical models showed that a model based on Navakatikyan's (2007) two-component…

Validation of a "Kane's Dynamics" Model for the Active Rack Isolation System

NASA Technical Reports Server (NTRS)

Beech, Geoffrey S.; Hampton, R. David

2000-01-01

Many microgravity space-science experiments require vibratory acceleration levels unachievable without active isolation. The Boeing Corporation's Active Rack Isolation System (ARIS) employs a novel combination of magnetic actuation and mechanical linkages, to address these isolation requirements on the International Space Station (ISS). ARIS provides isolation at the rack (international Standard Payload Rack, or ISPR) level. Effective model-based vibration isolation requires (1) an isolation device, (2) an adequate dynamic (i.e., mathematical) model of that isolator, and (3) a suitable, corresponding controller, ARIS provides the ISS response to the first requirement. In November 1999, the authors presented a response to the second ("A 'Kane's Dynamics' model for the Active Rack Isolation System", Hampton and Beech) intended to facilitate an optimal-controls approach to the third. This paper documents the validation of that high-fidelity dynamic model of ARIS. As before, this model contains the full actuator dynamics, however, the umbilical models are not included in this presentation. The validation of this dynamics model was achieved by utilizing two Commercial Off the Shelf (COTS) software tools: Deneb's ENVISION, and Online Dynamics' AUTOLEV. ENVISION is a robotics software package developed for the automotive industry that employs 3-dimensional (3-D) Computer Aided Design (CAD) models to facilitate both forward and inverse kinematics analyses. AUTOLEV is a DOS based interpreter that is designed in general to solve vector based mathematical problems and specifically to solve Dynamics problems using Kane's method.

Development of a dynamic computational model of social cognitive theory.

PubMed

Riley, William T; Martin, Cesar A; Rivera, Daniel E; Hekler, Eric B; Adams, Marc A; Buman, Matthew P; Pavel, Misha; King, Abby C

2016-12-01

Social cognitive theory (SCT) is among the most influential theories of behavior change and has been used as the conceptual basis of health behavior interventions for smoking cessation, weight management, and other health behaviors. SCT and other behavior theories were developed primarily to explain differences between individuals, but explanatory theories of within-person behavioral variability are increasingly needed as new technologies allow for intensive longitudinal measures and interventions adapted from these inputs. These within-person explanatory theoretical applications can be modeled as dynamical systems. SCT constructs, such as reciprocal determinism, are inherently dynamical in nature, but SCT has not been modeled as a dynamical system. This paper describes the development of a dynamical system model of SCT using fluid analogies and control systems principles drawn from engineering. Simulations of this model were performed to assess if the model performed as predicted based on theory and empirical studies of SCT. This initial model generates precise and testable quantitative predictions for future intensive longitudinal research. Dynamic modeling approaches provide a rigorous method for advancing health behavior theory development and refinement and for guiding the development of more potent and efficient interventions.

Potential formulation of sleep dynamics

NASA Astrophysics Data System (ADS)

Phillips, A. J. K.; Robinson, P. A.

2009-02-01

A physiologically based model of the mechanisms that control the human sleep-wake cycle is formulated in terms of an equivalent nonconservative mechanical potential. The potential is analytically simplified and reduced to a quartic two-well potential, matching the bifurcation structure of the original model. This yields a dynamics-based model that is analytically simpler and has fewer parameters than the original model, allowing easier fitting to experimental data. This model is first demonstrated to semiquantitatively match the dynamics of the physiologically based model from which it is derived, and is then fitted directly to a set of experimentally derived criteria. These criteria place rigorous constraints on the parameter values, and within these constraints the model is shown to reproduce normal sleep-wake dynamics and recovery from sleep deprivation. Furthermore, this approach enables insights into the dynamics by direct analogies to phenomena in well studied mechanical systems. These include the relation between friction in the mechanical system and the timecourse of neurotransmitter action, and the possible relation between stochastic resonance and napping behavior. The model derived here also serves as a platform for future investigations of sleep-wake phenomena from a dynamical perspective.

The dynamics of charge transfer with and without a barrier: A very simplified model of cyclic voltammetry.

PubMed

Ouyang, Wenjun; Subotnik, Joseph E

2017-05-07

Using the Anderson-Holstein model, we investigate charge transfer dynamics between a molecule and a metal surface for two extreme cases. (i) With a large barrier, we show that the dynamics follow a single exponential decay as expected; (ii) without any barrier, we show that the dynamics are more complicated. On the one hand, if the metal-molecule coupling is small, single exponential dynamics persist. On the other hand, when the coupling between the metal and the molecule is large, the dynamics follow a biexponential decay. We analyze the dynamics using the Smoluchowski equation, develop a simple model, and explore the consequences of biexponential dynamics for a hypothetical cyclic voltammetry experiment.

DRAINMOD-FOREST: Integrated modeling of hydrology, soil carbon and nitrogen dynamics, and plant growth for drained forests

Treesearch

Shiying Tian; Mohamed A. Youssef; R. Wayne Skaggs; Devendra M. Amatya; G.M. Chescheir

2012-01-01

We present a hybrid and stand-level forest ecosystem model, DRAINMOD-FOREST, for simulating the hydrology, carbon (C) and nitrogen (N) dynamics, and tree growth for drained forest lands under common silvicultural practices. The model was developed by linking DRAINMOD, the hydrological model, and DRAINMOD-N II, the soil C and N dynamics model, to a forest growth model,...

Generic solar photovoltaic system dynamic simulation model specification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ellis, Abraham; Behnke, Michael Robert; Elliott, Ryan Thomas

This document is intended to serve as a specification for generic solar photovoltaic (PV) system positive-sequence dynamic models to be implemented by software developers and approved by the WECC MVWG for use in bulk system dynamic simulations in accordance with NERC MOD standards. Two specific dynamic models are included in the scope of this document. The first, a Central Station PV System model, is intended to capture the most important dynamic characteristics of large scale (> 10 MW) PV systems with a central Point of Interconnection (POI) at the transmission level. The second, a Distributed PV System model, is intendedmore » to represent an aggregation of smaller, distribution-connected systems that comprise a portion of a composite load that might be modeled at a transmission load bus.« less

[A dynamic model of the extravehicular (correction of extravehicuar) activity space suit].

PubMed

Yang, Feng; Yuan, Xiu-gan

2002-12-01

Objective. To establish a dynamic model of the space suit base on the particular configuration of the space suit. Method. The mass of the space suit components, moment of inertia, mobility of the joints of space suit, as well as the suit-generated torques, were considered in this model. The expressions to calculate the moment of inertia were developed by simplifying the geometry of the space suit. A modified Preisach model was used to mathematically describe the hysteretic torque characteristics of joints in a pressurized space suit, and it was implemented numerically basing on the observed suit parameters. Result. A dynamic model considering mass, moment of inertia and suit-generated torques was established. Conclusion. This dynamic model provides some elements for the dynamic simulation of the astronaut extravehicular activity.

Modelling Holocene peatland and permafrost dynamics with the LPJ-GUESS dynamic vegetation model

NASA Astrophysics Data System (ADS)

Chaudhary, Nitin; Miller, Paul A.; Smith, Benjamin

2016-04-01

Dynamic global vegetation models (DGVMs) are an important platform to study past, present and future vegetation patterns together with associated biogeochemical cycles and climate feedbacks (e.g. Sitch et al. 2008, Smith et al. 2001). However, very few attempts have been made to simulate peatlands using DGVMs (Kleinen et al. 2012, Tang et al. 2015, Wania et al. 2009a). In the present study, we have improved the peatland dynamics in the state-of-the-art dynamic vegetation model (LPJ-GUESS) in order to understand the long-term evolution of northern peatland ecosystems and to assess the effect of changing climate on peatland carbon balance. We combined a dynamic multi-layer approach (Frolking et al. 2010, Hilbert et al. 2000) with soil freezing-thawing functionality (Ekici et al. 2015, Wania et al. 2009a) in LPJ-GUESS. The new model is named LPJ-GUESS Peatland (LPJ-GUESS-P) (Chaudhary et al. in prep). The model was calibrated and tested at the sub-arctic mire in Stordalen, Sweden, and the model was able to capture the reported long-term vegetation dynamics and peat accumulation patterns in the mire (Kokfelt et al. 2010). For evaluation, the model was run at 13 grid points across a north to south transect in Europe. The modelled peat accumulation values were found to be consistent with the published data for each grid point (Loisel et al. 2014). Finally, a series of additional experiments were carried out to investigate the vulnerability of high-latitude peatlands to climate change. We find that the Stordalen mire will sequester more carbon in the future due to milder and wetter climate conditions, longer growing seasons, and the carbon fertilization effect. References: - Chaudhary et al. (in prep.). Modelling Holocene peatland and permafrost dynamics with the LPJ-GUESS dynamic vegetation model - Ekici A, et al. 2015. Site-level model intercomparison of high latitude and high altitude soil thermal dynamics in tundra and barren landscapes. The Cryosphere 9: 1343-1361. - Frolking S, Roulet NT, Tuittila E, Bubier JL, Quillet A, Talbot J, Richard PJH. 2010. A new model of Holocene peatland net primary production, decomposition, water balance, and peat accumulation. Earth Syst. Dynam., 1, 1-21, doi:10.5194/esd-1-1-2010, 2010. - Hilbert DW, Roulet N, Moore T. 2000. Modelling and analysis of peatlands as dynamical systems. Journal of Ecology 88: 230-242. - Kleinen T, Brovkin V, Schuldt RJ. 2012. A dynamic model of wetland extent and peat accumulation: results for the Holocene. Biogeosciences 9: 235-248. - Kokfelt U, Reuss N, Struyf E, Sonesson M, Rundgren M, Skog G, Rosen P, Hammarlund D. 2010. Wetland development, permafrost history and nutrient cycling inferred from late Holocene peat and lake sediment records in subarctic Sweden. Journal of Paleolimnology 44: 327-342. - Loisel J, et al. 2014. A database and synthesis of northern peatland soil properties and Holocene carbon and nitrogen accumulation. Holocene 24: 1028-1042. - Sitch S, et al. 2008. Evaluation of the terrestrial carbon cycle, future plant geography and climate-carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs). Global Change Biology 14: 2015-2039. - Smith B, Prentice IC, Sykes MT. 2001. Representation of vegetation dynamics in the modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space. Global Ecology and Biogeography 10: 621-637. - Tang J, et al. 2015. Carbon budget estimation of a subarctic catchment using a dynamic ecosystem model at high spatial resolution. Biogeosciences 12: 2791-2808. - Wania R, Ross I, Prentice IC. 2009a. Integrating peatlands and permafrost into a dynamic global vegetation model: 1. Evaluation and sensitivity of physical land surface processes. Global Biogeochemical Cycles 23.

Predicting and testing continental vertical motion histories since the Paleozoic

NASA Astrophysics Data System (ADS)

Zhang, Nan; Zhong, Shijie; Flowers, Rebecca M.

2012-02-01

Dynamic topography at the Earth's surface caused by mantle convection can affect a range of geophysical and geological observations including bathymetry, sea-level change, continental flooding, sedimentation and erosion. These observations provide important constraints on and test of mantle dynamic models. Based on global mantle convection models coupled with the surface plate motion history, we compute dynamic topography and its history for the last 400 Ma associated with Pangea assembly and breakup, with particular focus on cratonic regions. We propose that burial-unroofing histories of cratons inferred from thermochronology data can be used as a new diagnostic to test dynamic topography and mantle dynamic models. Our models show that there are currently two broad dynamic topography highs in the Pacific and Africa for the present-day Earth that are associated with the broad, warm structures (i.e., superplumes) in the deep mantle, consistent with previous proposals of dynamical support for the Pacific and African superswells. Our models reveal that Pangea assembly and breakup, by affecting subduction and mantle upwelling processes, have significant effects on continental vertical motions. Our models predict that the Slave craton in North America subsides before Pangea assembly at 330 Ma but uplifts significantly from 330 Ma to 240 Ma in response to pre-Pangea subduction and post-assembly mantle warming. The Kaapvaal craton of Africa is predicted to undergo uplift from ~180 Ma to 90 Ma after Pangea breakup, but its dynamic topography remains stable for the last 90 Ma. The predicted histories of elevation change for the Slave and Kaapvaal cratons compare well with the burial-unroofing histories inferred from thermochronology studies, thus supporting our dynamic models including the development of the African superplume mantle structure. The vertical motion histories for other cratons can provide further tests of and constraints on our mantle dynamic models.

Predicting and testing continental vertical motion histories since the Paleozoic

NASA Astrophysics Data System (ADS)

Zhang, N.; Zhong, S.; Flowers, R. M.

2011-12-01

Dynamic topography at the Earth's surface caused by mantle convection can affect a range of geophysical and geological observations including bathymetry, sea-level change, continental flooding, sedimentation and erosion. These observations provide important constraints on and test of mantle dynamic models. Based on global mantle convection models coupled with the surface plate motion history, we compute dynamic topography and its history for the last 400 Ma associated with Pangea assembly and breakup, with particular focus on continental cratonic regions. We propose that burial-unroofing histories of continental cratons inferred from thermochronology data can be used as a new diagnostic to test dynamic topography and mantle dynamic models. Our models show that there are currently two broad dynamic topography highs in the Pacific and Africa for the present-day Earth that are associated with the broad, warm structures (i.e., superplumes) in the deep mantle, consistent with previous proposals of dynamical support for the Pacific and African superswells. Our models reveal that Pangea assembly and breakup, by affecting subduction and mantle upwelling processes, have significant effects on continental vertical motions. Our models predict that the Slave craton in North America subsides before Pangea assembly at 330 Ma but uplifts significantly from 330 Ma to 240 Ma in response to pre-Pangea subduction and post-assembly mantle warming. The Kaapvaal craton of Africa is predicted to undergo uplift from ~180 Ma to 90 Ma after Pangea breakup, but its dynamic topography remains stable for the last 90 Ma. The predicted histories of elevation change for the Slave and Kaapvaal cratons compare well with the burial-unroofing histories inferred from thermochronology studies, thus supporting our dynamic models including the development of the African superplume mantle structure. The vertical motion histories for other cratons can provide further tests and constraints on our mantle dynamic models.

Research on Generating Method of Embedded Software Test Document Based on Dynamic Model

NASA Astrophysics Data System (ADS)

Qu, MingCheng; Wu, XiangHu; Tao, YongChao; Liu, Ying

2018-03-01

This paper provides a dynamic model-based test document generation method for embedded software that provides automatic generation of two documents: test requirements specification documentation and configuration item test documentation. This method enables dynamic test requirements to be implemented in dynamic models, enabling dynamic test demand tracking to be easily generated; able to automatically generate standardized, standardized test requirements and test documentation, improved document-related content inconsistency and lack of integrity And other issues, improve the efficiency.

Development of dynamic Bayesian models for web application test management

NASA Astrophysics Data System (ADS)

Azarnova, T. V.; Polukhin, P. V.; Bondarenko, Yu V.; Kashirina, I. L.

2018-03-01

The mathematical apparatus of dynamic Bayesian networks is an effective and technically proven tool that can be used to model complex stochastic dynamic processes. According to the results of the research, mathematical models and methods of dynamic Bayesian networks provide a high coverage of stochastic tasks associated with error testing in multiuser software products operated in a dynamically changing environment. Formalized representation of the discrete test process as a dynamic Bayesian model allows us to organize the logical connection between individual test assets for multiple time slices. This approach gives an opportunity to present testing as a discrete process with set structural components responsible for the generation of test assets. Dynamic Bayesian network-based models allow us to combine in one management area individual units and testing components with different functionalities and a direct influence on each other in the process of comprehensive testing of various groups of computer bugs. The application of the proposed models provides an opportunity to use a consistent approach to formalize test principles and procedures, methods used to treat situational error signs, and methods used to produce analytical conclusions based on test results.

A coarse-grained model of microtubule self-assembly

NASA Astrophysics Data System (ADS)

Regmi, Chola; Cheng, Shengfeng

Microtubules play critical roles in cell structures and functions. They also serve as a model system to stimulate the next-generation smart, dynamic materials. A deep understanding of their self-assembly process and biomechanical properties will not only help elucidate how microtubules perform biological functions, but also lead to exciting insight on how microtubule dynamics can be altered or even controlled for specific purposes such as suppressing the division of cancer cells. Combining all-atom molecular dynamics (MD) simulations and the essential dynamics coarse-graining method, we construct a coarse-grained (CG) model of the tubulin protein, which is the building block of microtubules. In the CG model a tubulin dimer is represented as an elastic network of CG sites, the locations of which are determined by examining the protein dynamics of the tubulin and identifying the essential dynamic domains. Atomistic MD modeling is employed to directly compute the tubulin bond energies in the surface lattice of a microtubule, which are used to parameterize the interactions between CG building blocks. The CG model is then used to study the self-assembly pathways, kinetics, dynamics, and nanomechanics of microtubules.

Further steps in the modeling of behavioural crowd dynamics, good news for safe handling. Comment on "Human behaviours in evacuation crowd dynamics: From modelling to "big data" toward crisis management" by Nicola Bellomo et al.

NASA Astrophysics Data System (ADS)

Knopoff, Damián A.

2016-09-01

The recent review paper [4] constitutes a valuable contribution on the understanding, modeling and simulation of crowd dynamics in extreme situations. It provides a very comprehensive revision about the complexity features of the system under consideration, scaling and the consequent justification of the used methods. In particular, macro and microscopic models have so far been used to model crowd dynamics [9] and authors appropriately explain that working at the mesoscale is a good choice to deal with the heterogeneous behaviour of walkers as well as with the difficulty of their deterministic identification. In this way, methods based on the kinetic theory and statistical dynamics are employed, more precisely the so-called kinetic theory for active particles [7]. This approach has successfully been applied in the modeling of several complex dynamics, with recent applications to learning [2,8] that constitutes the key to understand communication and is of great importance in social dynamics and behavioral sciences.

Qualitative dynamics semantics for SBGN process description.

PubMed

Rougny, Adrien; Froidevaux, Christine; Calzone, Laurence; Paulevé, Loïc

2016-06-16

Qualitative dynamics semantics provide a coarse-grain modeling of networks dynamics by abstracting away kinetic parameters. They allow to capture general features of systems dynamics, such as attractors or reachability properties, for which scalable analyses exist. The Systems Biology Graphical Notation Process Description language (SBGN-PD) has become a standard to represent reaction networks. However, no qualitative dynamics semantics taking into account all the main features available in SBGN-PD had been proposed so far. We propose two qualitative dynamics semantics for SBGN-PD reaction networks, namely the general semantics and the stories semantics, that we formalize using asynchronous automata networks. While the general semantics extends standard Boolean semantics of reaction networks by taking into account all the main features of SBGN-PD, the stories semantics allows to model several molecules of a network by a unique variable. The obtained qualitative models can be checked against dynamical properties and therefore validated with respect to biological knowledge. We apply our framework to reason on the qualitative dynamics of a large network (more than 200 nodes) modeling the regulation of the cell cycle by RB/E2F. The proposed semantics provide a direct formalization of SBGN-PD networks in dynamical qualitative models that can be further analyzed using standard tools for discrete models. The dynamics in stories semantics have a lower dimension than the general one and prune multiple behaviors (which can be considered as spurious) by enforcing the mutual exclusiveness between the activity of different nodes of a same story. Overall, the qualitative semantics for SBGN-PD allow to capture efficiently important dynamical features of reaction network models and can be exploited to further refine them.

Neural network adaptive control of wing-rock motion of aircraft model mounted on three-degree-of-freedom dynamic rig in wind tunnel

NASA Astrophysics Data System (ADS)

Ignatyev, D. I.

2018-06-01

High-angles-of-attack dynamics of aircraft are complicated with dangerous phenomena such as wing rock, stall, and spin. Autonomous dynamically scaled aircraft model mounted in three-degree-of-freedom (3DoF) dynamic rig is proposed for studying aircraft dynamics and prototyping of control laws in wind tunnel. Dynamics of the scaled aircraft model in 3DoF manoeuvre rig in wind tunnel is considered. The model limit-cycle oscillations are obtained at high angles of attack. A neural network (NN) adaptive control suppressing wing rock motion is designed. The wing rock suppression with the proposed control law is validated using nonlinear time-domain simulations.

Recent NASA Research on Aerodynamic Modeling of Post-Stall and Spin Dynamics of Large Transport Airplanes

NASA Technical Reports Server (NTRS)

Murch, Austin M.; Foster, John V.

2007-01-01

A simulation study was conducted to investigate aerodynamic modeling methods for prediction of post-stall flight dynamics of large transport airplanes. The research approach involved integrating dynamic wind tunnel data from rotary balance and forced oscillation testing with static wind tunnel data to predict aerodynamic forces and moments during highly dynamic departure and spin motions. Several state-of-the-art aerodynamic modeling methods were evaluated and predicted flight dynamics using these various approaches were compared. Results showed the different modeling methods had varying effects on the predicted flight dynamics and the differences were most significant during uncoordinated maneuvers. Preliminary wind tunnel validation data indicated the potential of the various methods for predicting steady spin motions.

Dynamics of embedded curves by doubly-nonlocal reaction-diffusion systems

NASA Astrophysics Data System (ADS)

von Brecht, James H.; Blair, Ryan

2017-11-01

We study a class of nonlocal, energy-driven dynamical models that govern the motion of closed, embedded curves from both an energetic and dynamical perspective. Our energetic results provide a variety of ways to understand physically motivated energetic models in terms of more classical, combinatorial measures of complexity for embedded curves. This line of investigation culminates in a family of complexity bounds that relate a rather broad class of models to a generalized, or weighted, variant of the crossing number. Our dynamic results include global well-posedness of the associated partial differential equations, regularity of equilibria for these flows as well as a more detailed investigation of dynamics near such equilibria. Finally, we explore a few global dynamical properties of these models numerically.

Nitrogen feedbacks increase future terrestrial ecosystem carbon uptake in an individual-based dynamic vegetation model

NASA Astrophysics Data System (ADS)

Wårlind, D.; Smith, B.; Hickler, T.; Arneth, A.

2014-01-01

Recently a considerable amount of effort has been put into quantifying how interactions of the carbon and nitrogen cycle affect future terrestrial carbon sinks. Dynamic vegetation models, representing the nitrogen cycle with varying degree of complexity, have shown diverging constraints of nitrogen dynamics on future carbon sequestration. In this study, we use the dynamic vegetation model LPJ-GUESS to evaluate how population dynamics and resource competition between plant functional types, combined with nitrogen dynamics, have influenced the terrestrial carbon storage in the past and to investigate how terrestrial carbon and nitrogen dynamics might change in the future (1850 to 2100; one exemplary "business-as-usual" climate scenario). Single factor model experiments of CO2 fertilisation and climate change show generally similar directions of the responses of C-N interactions, compared to the C-only version of the model, as documented in previous studies. Under a RCP 8.5 scenario, nitrogen limitation suppresses potential CO2 fertilisation, reducing the cumulative net ecosystem carbon uptake between 1850 and 2100 by 61%, and soil warming-induced increase in nitrogen mineralisation reduces terrestrial carbon loss by 31%. When environmental changes are considered conjointly, carbon sequestration is limited by nitrogen dynamics until present. However, during the 21st century nitrogen dynamics induce a net increase in carbon sequestration, resulting in an overall larger carbon uptake of 17% over the full period. This contradicts earlier model results that showed an 8 to 37% decrease in carbon uptake, questioning the often stated assumption that projections of future terrestrial C dynamics from C-only models are too optimistic.

Research on hysteresis loop considering the prestress effect and electrical input dynamics for a giant magnetostrictive actuator

NASA Astrophysics Data System (ADS)

Zhu, Yuchuan; Yang, Xulei; Wereley, Norman M.

2016-08-01

In this paper, focusing on the application-oriented giant magnetostrictive material (GMM)-based electro-hydrostatic actuator, which features an applied magnetic field at high frequency and high amplitude, and concentrating on the static and dynamic characteristics of a giant magnetostrictive actuator (GMA) considering the prestress effect on the GMM rod and the electrical input dynamics involving the power amplifier and the inductive coil, a methodology for studying the static and dynamic characteristics of a GMA using the hysteresis loop as a tool is developed. A GMA that can display the preforce on the GMM rod in real-time is designed, and a magnetostrictive model dependent on the prestress on a GMM rod instead of the existing quadratic domain rotation model is proposed. Additionally, an electrical input dynamics model to excite GMA is developed according to the simplified circuit diagram, and the corresponding parameters are identified by the experimental data. A dynamic magnetization model with the eddy current effect is deduced according to the Jiles-Atherton model and the Maxwell equations. Next, all of the parameters, including the electrical input characteristics, the dynamic magnetization and the mechanical structure of GMA, are identified by the experimental data from the current response, magnetization response and displacement response, respectively. Finally, a comprehensive comparison between the model results and experimental data is performed, and the results show that the test data agree well with the presented model results. An analysis on the relation between the GMA displacement response and the parameters from the electrical input dynamics, magnetization dynamics and mechanical structural dynamics is performed.

Solar Dynamics Observatory (SDO) HGAS Induced Jitter

NASA Technical Reports Server (NTRS)

Liu, Alice; Blaurock, Carl; Liu, Kuo-Chia; Mule, Peter

2008-01-01

This paper presents the results of a comprehensive assessment of High Gain Antenna System induced jitter on the Solar Dynamics Observatory. The jitter prediction is created using a coupled model of the structural dynamics, optical response, control systems, and stepper motor actuator electromechanical dynamics. The paper gives an overview of the model components, presents the verification processes used to evaluate the models, describes validation and calibration tests and model-to-measurement comparison results, and presents the jitter analysis methodology and results.

A dynamic organic soil biogeochemical model for simulating the effects of wildfire on soil environmental conditions and carbon dynamics of black spruce forests

Treesearch

Shuhua Yi; A. David McGuire; Eric Kasischke; Jennifer Harden; Kristen Manies; Michelle Mack; Merritt Turetsky

2010-01-01

Ecosystem models have not comprehensively considered how interactions among fire disturbance, soil environmental conditions, and biogeochemical processes affect ecosystem dynamics in boreal forest ecosystems. In this study, we implemented a dynamic organic soil structure in the Terrestrial Ecosystem Model (DOS-TEM) to investigate the effects of fire on soil temperature...

Estimating spatio-temporal dynamics of stream total phosphate concentration by soft computing techniques.

PubMed

Chang, Fi-John; Chen, Pin-An; Chang, Li-Chiu; Tsai, Yu-Hsuan

2016-08-15

This study attempts to model the spatio-temporal dynamics of total phosphate (TP) concentrations along a river for effective hydro-environmental management. We propose a systematical modeling scheme (SMS), which is an ingenious modeling process equipped with a dynamic neural network and three refined statistical methods, for reliably predicting the TP concentrations along a river simultaneously. Two different types of artificial neural network (BPNN-static neural network; NARX network-dynamic neural network) are constructed in modeling the dynamic system. The Dahan River in Taiwan is used as a study case, where ten-year seasonal water quality data collected at seven monitoring stations along the river are used for model training and validation. Results demonstrate that the NARX network can suitably capture the important dynamic features and remarkably outperforms the BPNN model, and the SMS can effectively identify key input factors, suitably overcome data scarcity, significantly increase model reliability, satisfactorily estimate site-specific TP concentration at seven monitoring stations simultaneously, and adequately reconstruct seasonal TP data into a monthly scale. The proposed SMS can reliably model the dynamic spatio-temporal water pollution variation in a river system for missing, hazardous or costly data of interest. Copyright © 2016 Elsevier B.V. All rights reserved.

A framework for studying transient dynamics of population projection matrix models.

PubMed

Stott, Iain; Townley, Stuart; Hodgson, David James

2011-09-01

Empirical models are central to effective conservation and population management, and should be predictive of real-world dynamics. Available modelling methods are diverse, but analysis usually focuses on long-term dynamics that are unable to describe the complicated short-term time series that can arise even from simple models following ecological disturbances or perturbations. Recent interest in such transient dynamics has led to diverse methodologies for their quantification in density-independent, time-invariant population projection matrix (PPM) models, but the fragmented nature of this literature has stifled the widespread analysis of transients. We review the literature on transient analyses of linear PPM models and synthesise a coherent framework. We promote the use of standardised indices, and categorise indices according to their focus on either convergence times or transient population density, and on either transient bounds or case-specific transient dynamics. We use a large database of empirical PPM models to explore relationships between indices of transient dynamics. This analysis promotes the use of population inertia as a simple, versatile and informative predictor of transient population density, but criticises the utility of established indices of convergence times. Our findings should guide further development of analyses of transient population dynamics using PPMs or other empirical modelling techniques. © 2011 Blackwell Publishing Ltd/CNRS.

A meta-model for computer executable dynamic clinical safety checklists.

PubMed

Nan, Shan; Van Gorp, Pieter; Lu, Xudong; Kaymak, Uzay; Korsten, Hendrikus; Vdovjak, Richard; Duan, Huilong

2017-12-12

Safety checklist is a type of cognitive tool enforcing short term memory of medical workers with the purpose of reducing medical errors caused by overlook and ignorance. To facilitate the daily use of safety checklists, computerized systems embedded in the clinical workflow and adapted to patient-context are increasingly developed. However, the current hard-coded approach of implementing checklists in these systems increase the cognitive efforts of clinical experts and coding efforts for informaticists. This is due to the lack of a formal representation format that is both understandable by clinical experts and executable by computer programs. We developed a dynamic checklist meta-model with a three-step approach. Dynamic checklist modeling requirements were extracted by performing a domain analysis. Then, existing modeling approaches and tools were investigated with the purpose of reusing these languages. Finally, the meta-model was developed by eliciting domain concepts and their hierarchies. The feasibility of using the meta-model was validated by two case studies. The meta-model was mapped to specific modeling languages according to the requirements of hospitals. Using the proposed meta-model, a comprehensive coronary artery bypass graft peri-operative checklist set and a percutaneous coronary intervention peri-operative checklist set have been developed in a Dutch hospital and a Chinese hospital, respectively. The result shows that it is feasible to use the meta-model to facilitate the modeling and execution of dynamic checklists. We proposed a novel meta-model for the dynamic checklist with the purpose of facilitating creating dynamic checklists. The meta-model is a framework of reusing existing modeling languages and tools to model dynamic checklists. The feasibility of using the meta-model is validated by implementing a use case in the system.

Lumped Parameter Modeling for Rapid Vibration Response Prototyping and Test Correlation for Electronic Units

NASA Technical Reports Server (NTRS)

Van Dyke, Michael B.

2013-01-01

Present preliminary work using lumped parameter models to approximate dynamic response of electronic units to random vibration; Derive a general N-DOF model for application to electronic units; Illustrate parametric influence of model parameters; Implication of coupled dynamics for unit/board design; Demonstrate use of model to infer printed wiring board (PWB) dynamics from external chassis test measurement.

Combat Simulation Using Breach Computer Language

DTIC Science & Technology

1979-09-01

simulation and weapon system analysis computer language Two types of models were constructed: a stochastic duel and a dynamic engagement model The... duel model validates the BREACH approach by comparing results with mathematical solutions. The dynamic model shows the capability of the BREACH...BREACH 2 Background 2 The Language 3 Static Duel 4 Background and Methodology 4 Validation 5 Results 8 Tank Duel Simulation 8 Dynamic Assault Model

Robust Flutter Analysis for Aeroservoelastic Systems

NASA Astrophysics Data System (ADS)

Kotikalpudi, Aditya

The dynamics of a flexible air vehicle are typically described using an aeroservoelastic model which accounts for interaction between aerodynamics, structural dynamics, rigid body dynamics and control laws. These subsystems can be individually modeled using a theoretical approach and experimental data from various ground tests can be combined into them. For instance, a combination of linear finite element modeling and data from ground vibration tests may be used to obtain a validated structural model. Similarly, an aerodynamic model can be obtained using computational fluid dynamics or simple panel methods and partially updated using limited data from wind tunnel tests. In all cases, the models obtained for these subsystems have a degree of uncertainty owing to inherent assumptions in the theory and errors in experimental data. Suitable uncertain models that account for these uncertainties can be built to study the impact of these modeling errors on the ability to predict dynamic instabilities known as flutter. This thesis addresses the methods used for modeling rigid body dynamics, structural dynamics and unsteady aerodynamics of a blended wing design called the Body Freedom Flutter vehicle. It discusses the procedure used to incorporate data from a wide range of ground based experiments in the form of model uncertainties within these subsystems. Finally, it provides the mathematical tools for carrying out flutter analysis and sensitivity analysis which account for these model uncertainties. These analyses are carried out for both open loop and controller in the loop (closed loop) cases.

Practical limits for reverse engineering of dynamical systems: a statistical analysis of sensitivity and parameter inferability in systems biology models.

PubMed

Erguler, Kamil; Stumpf, Michael P H

2011-05-01

The size and complexity of cellular systems make building predictive models an extremely difficult task. In principle dynamical time-course data can be used to elucidate the structure of the underlying molecular mechanisms, but a central and recurring problem is that many and very different models can be fitted to experimental data, especially when the latter are limited and subject to noise. Even given a model, estimating its parameters remains challenging in real-world systems. Here we present a comprehensive analysis of 180 systems biology models, which allows us to classify the parameters with respect to their contribution to the overall dynamical behaviour of the different systems. Our results reveal candidate elements of control in biochemical pathways that differentially contribute to dynamics. We introduce sensitivity profiles that concisely characterize parameter sensitivity and demonstrate how this can be connected to variability in data. Systematically linking data and model sloppiness allows us to extract features of dynamical systems that determine how well parameters can be estimated from time-course measurements, and associates the extent of data required for parameter inference with the model structure, and also with the global dynamical state of the system. The comprehensive analysis of so many systems biology models reaffirms the inability to estimate precisely most model or kinetic parameters as a generic feature of dynamical systems, and provides safe guidelines for performing better inferences and model predictions in the context of reverse engineering of mathematical models for biological systems.

Developing a Dynamic Pharmacophore Model for HIV-1 Integrase

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carlson, Heather A.; Masukawa, Keven M.; Rubins, Kathleen

2000-05-11

We present the first receptor-based pharmacophore model for HIV-1 integrase. The development of ''dynamic'' pharmacophore models is a new method that accounts for the inherent flexibility of the active site and aims to reduce the entropic penalties associated with binding a ligand. Furthermore, this new drug discovery method overcomes the limitation of an incomplete crystal structure of the target protein. A molecular dynamics (MD) simulation describes the flexibility of the uncomplexed protein. Many conformational models of the protein are saved from the MD simulations and used in a series of multi-unit search for interacting conformers (MUSIC) simulations. MUSIC is amore » multiple-copy minimization method, available in the BOSS program; it is used to determine binding regions for probe molecules containing functional groups that complement the active site. All protein conformations from the MD are overlaid, and conserved binding regions for the probe molecules are identified. Those conserved binding regions define the dynamic pharmacophore model. Here, the dynamic model is compared to known inhibitors of the integrase as well as a three-point, ligand-based pharmacophore model from the literature. Also, a ''static'' pharmacophore model was determined in the standard fashion, using a single crystal structure. Inhibitors thought to bind in the active site of HIV-1 integrase fit the dynamic model but not the static model. Finally, we have identified a set of compounds from the Available Chemicals Directory that fit the dynamic pharmacophore model, and experimental testing of the compounds has confirmed several new inhibitors.« less

A family of dynamic models for large-eddy simulation

NASA Technical Reports Server (NTRS)

Carati, D.; Jansen, K.; Lund, T.

1995-01-01

Since its first application, the dynamic procedure has been recognized as an effective means to compute rather than prescribe the unknown coefficients that appear in a subgrid-scale model for Large-Eddy Simulation (LES). The dynamic procedure is usually used to determine the nondimensional coefficient in the Smagorinsky (1963) model. In reality the procedure is quite general and it is not limited to the Smagorinsky model by any theoretical or practical constraints. The purpose of this note is to consider a generalized family of dynamic eddy viscosity models that do not necessarily rely on the local equilibrium assumption built into the Smagorinsky model. By invoking an inertial range assumption, it will be shown that the coefficients in the new models need not be nondimensional. This additional degree of freedom allows the use of models that are scaled on traditionally unknown quantities such as the dissipation rate. In certain cases, the dynamic models with dimensional coefficients are simpler to implement, and allow for a 30% reduction in the number of required filtering operations.

A Lagrangian dynamic subgrid-scale model turbulence

NASA Technical Reports Server (NTRS)

Meneveau, C.; Lund, T. S.; Cabot, W.

1994-01-01

A new formulation of the dynamic subgrid-scale model is tested in which the error associated with the Germano identity is minimized over flow pathlines rather than over directions of statistical homogeneity. This procedure allows the application of the dynamic model with averaging to flows in complex geometries that do not possess homogeneous directions. The characteristic Lagrangian time scale over which the averaging is performed is chosen such that the model is purely dissipative, guaranteeing numerical stability when coupled with the Smagorinsky model. The formulation is tested successfully in forced and decaying isotropic turbulence and in fully developed and transitional channel flow. In homogeneous flows, the results are similar to those of the volume-averaged dynamic model, while in channel flow, the predictions are superior to those of the plane-averaged dynamic model. The relationship between the averaged terms in the model and vortical structures (worms) that appear in the LES is investigated. Computational overhead is kept small (about 10 percent above the CPU requirements of the volume or plane-averaged dynamic model) by using an approximate scheme to advance the Lagrangian tracking through first-order Euler time integration and linear interpolation in space.

Dynamic Model of Aircraft Passenger Seats for Vibration Comfort Evaluation and Control

NASA Astrophysics Data System (ADS)

Šika, Z.; Valášek, Michael; Vampola, T.; Füllekrug, U.; Klimmek, T.

The paper deals with the development of the seat dynamical model for vibration comfort evaluation and control. The aircraft seats have been tested extensively by vibrations on the 6 DOF vibrating platform. The importance of the careful comfort control together with the flight mechanics control is namely stressed for the blended wing body (BWB) aircrafts. They have a very large fuselage, where the mechanical properties (accelerations, angular accelerations) vary considerably for different seat places. The model have been improved by adding of dynamical models of the aircraft passenger seats identified by the measurements on the 6 DOF vibrating platform. The experiments, their results and the identification of the dynamical seat model are described. The model is further modified by adding of the comfort evaluation norms represented by dynamical filters. The structure and identification of the seat model is briefly described and discussed.

Modelling of creep hysteresis in ferroelectrics

NASA Astrophysics Data System (ADS)

He, Xuan; Wang, Dan; Wang, Linxiang; Melnik, Roderick

2018-05-01

In the current paper, a macroscopic model is proposed to simulate the hysteretic dynamics of ferroelectric ceramics with creep phenomenon incorporated. The creep phenomenon in the hysteretic dynamics is attributed to the rate-dependent characteristic of the polarisation switching processes induced in the materials. A non-convex Helmholtz free energy based on Landau theory is proposed to model the switching dynamics. The governing equation of single-crystal model is formulated by applying the Euler-Lagrange equation. The polycrystalline model is obtained by combining the single crystal dynamics with a density function which is constructed to model the weighted contributions of different grains with different principle axis orientations. In addition, numerical simulations of hysteretic dynamics with creep phenomenon are presented. Comparison of the numerical results and their experimental counterparts is also presented. It is shown that the creep phenomenon is captured precisely, validating the capability of the proposed model in a range of its potential applications.

A dynamic fault tree model of a propulsion system

NASA Technical Reports Server (NTRS)

Xu, Hong; Dugan, Joanne Bechta; Meshkat, Leila

2006-01-01

We present a dynamic fault tree model of the benchmark propulsion system, and solve it using Galileo. Dynamic fault trees (DFT) extend traditional static fault trees with special gates to model spares and other sequence dependencies. Galileo solves DFT models using a judicious combination of automatically generated Markov and Binary Decision Diagram models. Galileo easily handles the complexities exhibited by the benchmark problem. In particular, Galileo is designed to model phased mission systems.

Dynamic large eddy simulation: Stability via realizability

NASA Astrophysics Data System (ADS)

Mokhtarpoor, Reza; Heinz, Stefan

2017-10-01

The concept of dynamic large eddy simulation (LES) is highly attractive: such methods can dynamically adjust to changing flow conditions, which is known to be highly beneficial. For example, this avoids the use of empirical, case dependent approximations (like damping functions). Ideally, dynamic LES should be local in physical space (without involving artificial clipping parameters), and it should be stable for a wide range of simulation time steps, Reynolds numbers, and numerical schemes. These properties are not trivial, but dynamic LES suffers from such problems over decades. We address these questions by performing dynamic LES of periodic hill flow including separation at a high Reynolds number Re = 37 000. For the case considered, the main result of our studies is that it is possible to design LES that has the desired properties. It requires physical consistency: a PDF-realizable and stress-realizable LES model, which requires the inclusion of the turbulent kinetic energy in the LES calculation. LES models that do not honor such physical consistency can become unstable. We do not find support for the previous assumption that long-term correlations of negative dynamic model parameters are responsible for instability. Instead, we concluded that instability is caused by the stable spatial organization of significant unphysical states, which are represented by wall-type gradient streaks of the standard deviation of the dynamic model parameter. The applicability of our realizability stabilization to other dynamic models (including the dynamic Smagorinsky model) is discussed.

Assessing the Dynamic Behavior of Online Q&A Knowledge Markets: A System Dynamics Approach

ERIC Educational Resources Information Center

Jafari, Mostafa; Hesamamiri, Roozbeh; Sadjadi, Jafar; Bourouni, Atieh

2012-01-01

Purpose: The objective of this paper is to propose a holistic dynamic model for understanding the behavior of a complex and internet-based kind of knowledge market by considering both social and economic interactions. Design/methodology/approach: A system dynamics (SD) model is formulated in this study to investigate the dynamic characteristics of…

Modelling and Analysis of a New Piezoelectric Dynamic Balance Regulator

PubMed Central

Du, Zhe; Mei, Xue-Song; Xu, Mu-Xun

2012-01-01

In this paper, a new piezoelectric dynamic balance regulator, which can be used in motorised spindle systems, is presented. The dynamic balancing adjustment mechanism is driven by an in-plane bending vibration from an annular piezoelectric stator excited by a high-frequency sinusoidal input voltage. This device has different construction, characteristics and operating principles than a conventional balance regulator. In this work, a dynamic model of the regulator is first developed using a detailed analytical method. Thereafter, MATLAB is employed to numerically simulate the relations between the dominant parameters and the characteristics of the regulator based on thedynamic model. Finally, experimental measurements are used to certify the validity of the dynamic model. Consequently, the mathematical model presented and analysed in this paper can be used as a tool for optimising the design of a piezoelectric dynamic balance regulator during steady state operation. PMID:23202182

The topology of non-linear global carbon dynamics: from tipping points to planetary boundaries

NASA Astrophysics Data System (ADS)

Anderies, J. M.; Carpenter, S. R.; Steffen, Will; Rockström, Johan

2013-12-01

We present a minimal model of land use and carbon cycle dynamics and use it to explore the relationship between non-linear dynamics and planetary boundaries. Only the most basic interactions between land cover and terrestrial, atmospheric, and marine carbon stocks are considered in the model. Our goal is not to predict global carbon dynamics as it occurs in the actual Earth System. Rather, we construct a conceptually reasonable heuristic model of a feedback system between different carbon stocks that captures the qualitative features of the actual Earth System and use it to explore the topology of the boundaries of what can be called a ‘safe operating space’ for humans. The model analysis illustrates the existence of dynamic, non-linear tipping points in carbon cycle dynamics and the potential complexity of planetary boundaries. Finally, we use the model to illustrate some challenges associated with navigating planetary boundaries.

Biophysical synaptic dynamics in an analog VLSI network of Hodgkin-Huxley neurons.

PubMed

Yu, Theodore; Cauwenberghs, Gert

2009-01-01

We study synaptic dynamics in a biophysical network of four coupled spiking neurons implemented in an analog VLSI silicon microchip. The four neurons implement a generalized Hodgkin-Huxley model with individually configurable rate-based kinetics of opening and closing of Na+ and K+ ion channels. The twelve synapses implement a rate-based first-order kinetic model of neurotransmitter and receptor dynamics, accounting for NMDA and non-NMDA type chemical synapses. The implemented models on the chip are fully configurable by 384 parameters accounting for conductances, reversal potentials, and pre/post-synaptic voltage-dependence of the channel kinetics. We describe the models and present experimental results from the chip characterizing single neuron dynamics, single synapse dynamics, and multi-neuron network dynamics showing phase-locking behavior as a function of synaptic coupling strength. The 3mm x 3mm microchip consumes 1.29 mW power making it promising for applications including neuromorphic modeling and neural prostheses.

Standard representation and unified stability analysis for dynamic artificial neural network models.

PubMed

Kim, Kwang-Ki K; Patrón, Ernesto Ríos; Braatz, Richard D

2018-02-01

An overview is provided of dynamic artificial neural network models (DANNs) for nonlinear dynamical system identification and control problems, and convex stability conditions are proposed that are less conservative than past results. The three most popular classes of dynamic artificial neural network models are described, with their mathematical representations and architectures followed by transformations based on their block diagrams that are convenient for stability and performance analyses. Classes of nonlinear dynamical systems that are universally approximated by such models are characterized, which include rigorous upper bounds on the approximation errors. A unified framework and linear matrix inequality-based stability conditions are described for different classes of dynamic artificial neural network models that take additional information into account such as local slope restrictions and whether the nonlinearities within the DANNs are odd. A theoretical example shows reduced conservatism obtained by the conditions. Copyright © 2017. Published by Elsevier Ltd.

Dynamic access control model for privacy preserving personalized healthcare in cloud environment.

PubMed

Son, Jiseong; Kim, Jeong-Dong; Na, Hong-Seok; Baik, Doo-Kwon

2015-01-01

When sharing and storing healthcare data in a cloud environment, access control is a central issue for preserving data privacy as a patient's personal health data may be accessed without permission from many stakeholders. Specifically, dynamic authorization for the access of data is required because personal health data is stored in cloud storage via wearable devices. Therefore, we propose a dynamic access control model for preserving the privacy of personal healthcare data in a cloud environment. The proposed model considers context information for dynamic access. According to the proposed model, access control can be dynamically determined by changing the context information; this means that even for a subject with the same role in the cloud, access permission is defined differently depending on the context information and access condition. Furthermore, we experiment the ability of the proposed model to provide correct responses by representing a dynamic access decision with real-life personalized healthcare system scenarios.

Representing Causation

ERIC Educational Resources Information Center

Wolff, Phillip

2007-01-01

The dynamics model, which is based on L. Talmy's (1988) theory of force dynamics, characterizes causation as a pattern of forces and a position vector. In contrast to counterfactual and probabilistic models, the dynamics model naturally distinguishes between different cause-related concepts and explains the induction of causal relationships from…

77 FR 13607 - Agency Forms Undergoing Paperwork Reduction Act Review

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-07

... Transformation Grants: Use of System Dynamic Modeling and Economic Analysis in Select Communities--New--National... community interventions. Using a system dynamics approach, CDC also plans to conduct simulation modeling... the development of analytic tools for system dynamics modeling under more limited conditions. The...

[Transmission dynamic model for echinococcosis granulosus: establishment and application].

PubMed

Yang, Shi-Jie; Wu, Wei-Ping

2009-06-01

A dynamic model of disease can be used to quantitatively describe the pattern and characteristics of disease transmission, predict the disease status and evaluate the efficacy of control strategy. This review summarizes the basic transmission dynamic models of echinococcosis granulosus and their application.

Improved global simulation of groundwater-ecosystem interactions via tight coupling of a dynamic global ecosystem model and a global hydrological model

NASA Astrophysics Data System (ADS)

Braakhekke, Maarten; Rebel, Karin; Dekker, Stefan; Smith, Benjamin; Sutanudjaja, Edwin; van Beek, Rens; van Kampenhout, Leo; Wassen, Martin

2017-04-01

In up to 30% of the global land surface ecosystems are potentially influenced by the presence of a shallow groundwater table. In these regions upward water flux by capillary rise increases soil moisture availability in the root zone, which has a strong effect on evapotranspiration, vegetation dynamics, and fluxes of carbon and nitrogen. Most global hydrological models and several land surface models simulate groundwater table dynamics and their effects on land surface processes. However, these models typically have relatively simplistic representation of vegetation and do not consider changes in vegetation type and structure. Dynamic global vegetation models (DGVMs), describe land surface from an ecological perspective, combining detailed description of vegetation dynamics and structure, and biogeochemical processes and are thus more appropriate to simulate the ecological and biogeochemical effects of groundwater interactions. However, currently virtually all DGVMs ignore these effects, assuming that water tables are too deep to affect soil moisture in the root zone. We have implemented a tight coupling between the dynamic global ecosystem model LPJ-GUESS and the global hydrological model PCR-GLOBWB, which explicitly simulates groundwater dynamics. This coupled model allows us to explicitly account for groundwater effects on terrestrial ecosystem processes at global scale. Results of global simulations indicate that groundwater strongly influences fluxes of water, carbon and nitrogen, in many regions, adding up to a considerable effect at the global scale.

Dynamical systems, attractors, and neural circuits.

PubMed

Miller, Paul

2016-01-01

Biology is the study of dynamical systems. Yet most of us working in biology have limited pedagogical training in the theory of dynamical systems, an unfortunate historical fact that can be remedied for future generations of life scientists. In my particular field of systems neuroscience, neural circuits are rife with nonlinearities at all levels of description, rendering simple methodologies and our own intuition unreliable. Therefore, our ideas are likely to be wrong unless informed by good models. These models should be based on the mathematical theories of dynamical systems since functioning neurons are dynamic-they change their membrane potential and firing rates with time. Thus, selecting the appropriate type of dynamical system upon which to base a model is an important first step in the modeling process. This step all too easily goes awry, in part because there are many frameworks to choose from, in part because the sparsely sampled data can be consistent with a variety of dynamical processes, and in part because each modeler has a preferred modeling approach that is difficult to move away from. This brief review summarizes some of the main dynamical paradigms that can arise in neural circuits, with comments on what they can achieve computationally and what signatures might reveal their presence within empirical data. I provide examples of different dynamical systems using simple circuits of two or three cells, emphasizing that any one connectivity pattern is compatible with multiple, diverse functions.

Dynamical principles in neuroscience

NASA Astrophysics Data System (ADS)

Rabinovich, Mikhail I.; Varona, Pablo; Selverston, Allen I.; Abarbanel, Henry D. I.

2006-10-01

Dynamical modeling of neural systems and brain functions has a history of success over the last half century. This includes, for example, the explanation and prediction of some features of neural rhythmic behaviors. Many interesting dynamical models of learning and memory based on physiological experiments have been suggested over the last two decades. Dynamical models even of consciousness now exist. Usually these models and results are based on traditional approaches and paradigms of nonlinear dynamics including dynamical chaos. Neural systems are, however, an unusual subject for nonlinear dynamics for several reasons: (i) Even the simplest neural network, with only a few neurons and synaptic connections, has an enormous number of variables and control parameters. These make neural systems adaptive and flexible, and are critical to their biological function. (ii) In contrast to traditional physical systems described by well-known basic principles, first principles governing the dynamics of neural systems are unknown. (iii) Many different neural systems exhibit similar dynamics despite having different architectures and different levels of complexity. (iv) The network architecture and connection strengths are usually not known in detail and therefore the dynamical analysis must, in some sense, be probabilistic. (v) Since nervous systems are able to organize behavior based on sensory inputs, the dynamical modeling of these systems has to explain the transformation of temporal information into combinatorial or combinatorial-temporal codes, and vice versa, for memory and recognition. In this review these problems are discussed in the context of addressing the stimulating questions: What can neuroscience learn from nonlinear dynamics, and what can nonlinear dynamics learn from neuroscience?

Dynamical principles in neuroscience

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rabinovich, Mikhail I.; Varona, Pablo; Selverston, Allen I.

Dynamical modeling of neural systems and brain functions has a history of success over the last half century. This includes, for example, the explanation and prediction of some features of neural rhythmic behaviors. Many interesting dynamical models of learning and memory based on physiological experiments have been suggested over the last two decades. Dynamical models even of consciousness now exist. Usually these models and results are based on traditional approaches and paradigms of nonlinear dynamics including dynamical chaos. Neural systems are, however, an unusual subject for nonlinear dynamics for several reasons: (i) Even the simplest neural network, with only amore » few neurons and synaptic connections, has an enormous number of variables and control parameters. These make neural systems adaptive and flexible, and are critical to their biological function. (ii) In contrast to traditional physical systems described by well-known basic principles, first principles governing the dynamics of neural systems are unknown. (iii) Many different neural systems exhibit similar dynamics despite having different architectures and different levels of complexity. (iv) The network architecture and connection strengths are usually not known in detail and therefore the dynamical analysis must, in some sense, be probabilistic. (v) Since nervous systems are able to organize behavior based on sensory inputs, the dynamical modeling of these systems has to explain the transformation of temporal information into combinatorial or combinatorial-temporal codes, and vice versa, for memory and recognition. In this review these problems are discussed in the context of addressing the stimulating questions: What can neuroscience learn from nonlinear dynamics, and what can nonlinear dynamics learn from neuroscience?.« less

The results of a limited study of approaches to the design, fabrication, and testing of a dynamic model of the NASA IOC space station. Executive summary

NASA Technical Reports Server (NTRS)

Brooks, George W.

1985-01-01

The options for the design, construction, and testing of a dynamic model of the space station were evaluated. Since the definition of the space station structure is still evolving, the Initial Operating Capacity (IOC) reference configuration was used as the general guideline. The results of the studies treat: general considerations of the need for and use of a dynamic model; factors which deal with the model design and construction; and a proposed system for supporting the dynamic model in the planned Large Spacecraft Laboratory.

Development of a Stirling System Dynamic Model With Enhanced Thermodynamics

NASA Technical Reports Server (NTRS)

Regan, Timothy F.; Lewandowski, Edward J.

2005-01-01

The Stirling Convertor System Dynamic Model developed at NASA Glenn Research Center is a software model developed from first principles that includes the mechanical and mounting dynamics, the thermodynamics, the linear alternator, and the controller of a free-piston Stirling power convertor, along with the end user load. As such it represents the first detailed modeling tool for fully integrated Stirling convertor-based power systems. The thermodynamics of the model were originally a form of the isothermal Stirling cycle. In some situations it may be desirable to improve the accuracy of the Stirling cycle portion of the model. An option under consideration is to enhance the SDM thermodynamics by coupling the model with Gedeon Associates Sage simulation code. The result will be a model that gives a more accurate prediction of the performance and dynamics of the free-piston Stirling convertor. A method of integrating the Sage simulation code with the System Dynamic Model is described. Results of SDM and Sage simulation are compared to test data. Model parameter estimation and model validation are discussed.

Linking models and data on vegetation structure

NASA Astrophysics Data System (ADS)

Hurtt, G. C.; Fisk, J.; Thomas, R. Q.; Dubayah, R.; Moorcroft, P. R.; Shugart, H. H.

2010-06-01

For more than a century, scientists have recognized the importance of vegetation structure in understanding forest dynamics. Now future satellite missions such as Deformation, Ecosystem Structure, and Dynamics of Ice (DESDynI) hold the potential to provide unprecedented global data on vegetation structure needed to reduce uncertainties in terrestrial carbon dynamics. Here, we briefly review the uses of data on vegetation structure in ecosystem models, develop and analyze theoretical models to quantify model-data requirements, and describe recent progress using a mechanistic modeling approach utilizing a formal scaling method and data on vegetation structure to improve model predictions. Generally, both limited sampling and coarse resolution averaging lead to model initialization error, which in turn is propagated in subsequent model prediction uncertainty and error. In cases with representative sampling, sufficient resolution, and linear dynamics, errors in initialization tend to compensate at larger spatial scales. However, with inadequate sampling, overly coarse resolution data or models, and nonlinear dynamics, errors in initialization lead to prediction error. A robust model-data framework will require both models and data on vegetation structure sufficient to resolve important environmental gradients and tree-level heterogeneity in forest structure globally.

Development of a Stirling System Dynamic Model with Enhanced Thermodynamics

NASA Astrophysics Data System (ADS)

Regan, Timothy F.; Lewandowski, Edward J.

2005-02-01

The Stirling Convertor System Dynamic Model developed at NASA Glenn Research Center is a software model developed from first principles that includes the mechanical and mounting dynamics, the thermodynamics, the linear alternator, and the controller of a free-piston Stirling power convertor, along with the end user load. As such it represents the first detailed modeling tool for fully integrated Stirling convertor-based power systems. The thermodynamics of the model were originally a form of the isothermal Stirling cycle. In some situations it may be desirable to improve the accuracy of the Stirling cycle portion of the model. An option under consideration is to enhance the SDM thermodynamics by coupling the model with Gedeon Associates' Sage simulation code. The result will be a model that gives a more accurate prediction of the performance and dynamics of the free-piston Stirling convertor. A method of integrating the Sage simulation code with the System Dynamic Model is described. Results of SDM and Sage simulation are compared to test data. Model parameter estimation and model validation are discussed.

Continuous system modeling

NASA Technical Reports Server (NTRS)

Cellier, Francois E.

1991-01-01

A comprehensive and systematic introduction is presented for the concepts associated with 'modeling', involving the transition from a physical system down to an abstract description of that system in the form of a set of differential and/or difference equations, and basing its treatment of modeling on the mathematics of dynamical systems. Attention is given to the principles of passive electrical circuit modeling, planar mechanical systems modeling, hierarchical modular modeling of continuous systems, and bond-graph modeling. Also discussed are modeling in equilibrium thermodynamics, population dynamics, and system dynamics, inductive reasoning, artificial neural networks, and automated model synthesis.

X-56A MUTT: Aeroservoelastic Modeling

NASA Technical Reports Server (NTRS)

Ouellette, Jeffrey A.

2015-01-01

For the NASA X-56a Program, Armstrong Flight Research Center has been developing a set of linear states space models that integrate the flight dynamics and structural dynamics. These high order models are needed for the control design, control evaluation, and test input design. The current focus has been on developing stiff wing models to validate the current modeling approach. The extension of the modeling approach to the flexible wings requires only a change in the structural model. Individual subsystems models (actuators, inertial properties, etc.) have been validated by component level ground tests. Closed loop simulation of maneuvers designed to validate the flight dynamics of these models correlates very well flight test data. The open loop structural dynamics are also shown to correlate well to the flight test data.

Differential equation models for sharp threshold dynamics.

PubMed

Schramm, Harrison C; Dimitrov, Nedialko B

2014-01-01

We develop an extension to differential equation models of dynamical systems to allow us to analyze probabilistic threshold dynamics that fundamentally and globally change system behavior. We apply our novel modeling approach to two cases of interest: a model of infectious disease modified for malware where a detection event drastically changes dynamics by introducing a new class in competition with the original infection; and the Lanchester model of armed conflict, where the loss of a key capability drastically changes the effectiveness of one of the sides. We derive and demonstrate a step-by-step, repeatable method for applying our novel modeling approach to an arbitrary system, and we compare the resulting differential equations to simulations of the system's random progression. Our work leads to a simple and easily implemented method for analyzing probabilistic threshold dynamics using differential equations. Published by Elsevier Inc.

Stirling System Modeling for Space Nuclear Power Systems

NASA Technical Reports Server (NTRS)

Lewandowski, Edward J.; Johnson, Paul K.

2008-01-01

A dynamic model of a high-power Stirling convertor has been developed for space nuclear power systems modeling. The model is based on the Component Test Power Convertor (CTPC), a 12.5-kWe free-piston Stirling convertor. The model includes the fluid heat source, the Stirling convertor, output power, and heat rejection. The Stirling convertor model includes the Stirling cycle thermodynamics, heat flow, mechanical mass-spring damper systems, and the linear alternator. The model was validated against test data. Both nonlinear and linear versions of the model were developed. The linear version algebraically couples two separate linear dynamic models; one model of the Stirling cycle and one model of the thermal system, through the pressure factors. Future possible uses of the Stirling system dynamic model are discussed. A pair of commercially available 1-kWe Stirling convertors is being purchased by NASA Glenn Research Center. The specifications of those convertors may eventually be incorporated into the dynamic model and analysis compared to the convertor test data. Subsequent potential testing could include integrating the convertors into a pumped liquid metal hot-end interface. This test would provide more data for comparison to the dynamic model analysis.

Dynamic analysis of clamp band joint system subjected to axial vibration

NASA Astrophysics Data System (ADS)

Qin, Z. Y.; Yan, S. Z.; Chu, F. L.

2010-10-01

Clamp band joints are commonly used for connecting circular components together in industry. Some of the systems jointed by clamp band are subjected to dynamic load. However, very little research on the dynamic characteristics for this kind of joint can be found in the literature. In this paper, a dynamic model for clamp band joint system is developed. Contact and frictional slip between the components are accommodated in this model. Nonlinear finite element analysis is conducted to identify the model parameters. Then static experiments are carried out on a scaled model of the clamp band joint to validate the joint model. Finally, the model is adopted to study the dynamic characteristics of the clamp band joint system subjected to axial harmonic excitation and the effects of the wedge angle of the clamp band joint and the preload on the response. The model proposed in this paper can represent the nonlinearity of the clamp band joint and be used conveniently to investigate the effects of the structural and loading parameters on the dynamic characteristics of this type of joint system.

A Comparative Study of Three Methodologies for Modeling Dynamic Stall

NASA Technical Reports Server (NTRS)

Sankar, L.; Rhee, M.; Tung, C.; ZibiBailly, J.; LeBalleur, J. C.; Blaise, D.; Rouzaud, O.

2002-01-01

During the past two decades, there has been an increased reliance on the use of computational fluid dynamics methods for modeling rotors in high speed forward flight. Computational methods are being developed for modeling the shock induced loads on the advancing side, first-principles based modeling of the trailing wake evolution, and for retreating blade stall. The retreating blade dynamic stall problem has received particular attention, because the large variations in lift and pitching moments encountered in dynamic stall can lead to blade vibrations and pitch link fatigue. Restricting to aerodynamics, the numerical prediction of dynamic stall is still a complex and challenging CFD problem, that, even in two dimensions at low speed, gathers the major difficulties of aerodynamics, such as the grid resolution requirements for the viscous phenomena at leading-edge bubbles or in mixing-layers, the bias of the numerical viscosity, and the major difficulties of the physical modeling, such as the turbulence models, the transition models, whose both determinant influences, already present in static maximal-lift or stall computations, are emphasized by the dynamic aspect of the phenomena.

Coupled turbulence and aerosol dynamics modeling of vehicle exhaust plumes using the CTAG model

NASA Astrophysics Data System (ADS)

Wang, Yan Jason; Zhang, K. Max

2012-11-01

This paper presents the development and evaluation of an environmental turbulent reacting flow model, the Comprehensive Turbulent Aerosol Dynamics and Gas Chemistry (CTAG) model. CTAG is designed to simulate transport and transformation of multiple air pollutants, e.g., from emission sources to ambient background. For the on-road and near-road applications, CTAG explicitly couples the major turbulent mixing processes, i.e., vehicle-induced turbulence (VIT), road-induced turbulence (RIT) and atmospheric boundary layer turbulence with gas-phase chemistry and aerosol dynamics. CTAG's transport model is referred to as CFD-VIT-RIT. This paper presents the evaluation of the CTAG model in simulating the dynamics of individual plumes in the “tailpipe-to-road” stage, i.e., VIT behind a moving van and aerosol dynamics in the wake of a diesel car by comparing the modeling results against the respective field measurements. Combined with sensitivity studies, we analyze the relative roles of VIT, sulfuric acid induced nucleation, condensation of organic compounds and presence of soot-mode particles in capturing the dynamics of exhaust plumes as well as their implications in vehicle emission controls.

Inferring microbial interaction networks from metagenomic data using SgLV-EKF algorithm.

PubMed

Alshawaqfeh, Mustafa; Serpedin, Erchin; Younes, Ahmad Bani

2017-03-27

Inferring the microbial interaction networks (MINs) and modeling their dynamics are critical in understanding the mechanisms of the bacterial ecosystem and designing antibiotic and/or probiotic therapies. Recently, several approaches were proposed to infer MINs using the generalized Lotka-Volterra (gLV) model. Main drawbacks of these models include the fact that these models only consider the measurement noise without taking into consideration the uncertainties in the underlying dynamics. Furthermore, inferring the MIN is characterized by the limited number of observations and nonlinearity in the regulatory mechanisms. Therefore, novel estimation techniques are needed to address these challenges. This work proposes SgLV-EKF: a stochastic gLV model that adopts the extended Kalman filter (EKF) algorithm to model the MIN dynamics. In particular, SgLV-EKF employs a stochastic modeling of the MIN by adding a noise term to the dynamical model to compensate for modeling uncertainties. This stochastic modeling is more realistic than the conventional gLV model which assumes that the MIN dynamics are perfectly governed by the gLV equations. After specifying the stochastic model structure, we propose the EKF to estimate the MIN. SgLV-EKF was compared with two similarity-based algorithms, one algorithm from the integral-based family and two regression-based algorithms, in terms of the achieved performance on two synthetic data-sets and two real data-sets. The first data-set models the randomness in measurement data, whereas, the second data-set incorporates uncertainties in the underlying dynamics. The real data-sets are provided by a recent study pertaining to an antibiotic-mediated Clostridium difficile infection. The experimental results demonstrate that SgLV-EKF outperforms the alternative methods in terms of robustness to measurement noise, modeling errors, and tracking the dynamics of the MIN. Performance analysis demonstrates that the proposed SgLV-EKF algorithm represents a powerful and reliable tool to infer MINs and track their dynamics.

From point process observations to collective neural dynamics: Nonlinear Hawkes process GLMs, low-dimensional dynamics and coarse graining

PubMed Central

Truccolo, Wilson

2017-01-01

This review presents a perspective on capturing collective dynamics in recorded neuronal ensembles based on multivariate point process models, inference of low-dimensional dynamics and coarse graining of spatiotemporal measurements. A general probabilistic framework for continuous time point processes reviewed, with an emphasis on multivariate nonlinear Hawkes processes with exogenous inputs. A point process generalized linear model (PP-GLM) framework for the estimation of discrete time multivariate nonlinear Hawkes processes is described. The approach is illustrated with the modeling of collective dynamics in neocortical neuronal ensembles recorded in human and non-human primates, and prediction of single-neuron spiking. A complementary approach to capture collective dynamics based on low-dimensional dynamics (“order parameters”) inferred via latent state-space models with point process observations is presented. The approach is illustrated by inferring and decoding low-dimensional dynamics in primate motor cortex during naturalistic reach and grasp movements. Finally, we briefly review hypothesis tests based on conditional inference and spatiotemporal coarse graining for assessing collective dynamics in recorded neuronal ensembles. PMID:28336305

From point process observations to collective neural dynamics: Nonlinear Hawkes process GLMs, low-dimensional dynamics and coarse graining.

PubMed

Truccolo, Wilson

2016-11-01

This review presents a perspective on capturing collective dynamics in recorded neuronal ensembles based on multivariate point process models, inference of low-dimensional dynamics and coarse graining of spatiotemporal measurements. A general probabilistic framework for continuous time point processes reviewed, with an emphasis on multivariate nonlinear Hawkes processes with exogenous inputs. A point process generalized linear model (PP-GLM) framework for the estimation of discrete time multivariate nonlinear Hawkes processes is described. The approach is illustrated with the modeling of collective dynamics in neocortical neuronal ensembles recorded in human and non-human primates, and prediction of single-neuron spiking. A complementary approach to capture collective dynamics based on low-dimensional dynamics ("order parameters") inferred via latent state-space models with point process observations is presented. The approach is illustrated by inferring and decoding low-dimensional dynamics in primate motor cortex during naturalistic reach and grasp movements. Finally, we briefly review hypothesis tests based on conditional inference and spatiotemporal coarse graining for assessing collective dynamics in recorded neuronal ensembles. Published by Elsevier Ltd.

A Few Integrable Dynamical Systems, Recurrence Operators, Expanding Integrable Models and Hamiltonian Structures by the r-Matrix Method

NASA Astrophysics Data System (ADS)

Zhang, Yu-Feng; Muhammad, Iqbal; Yue, Chao

2017-10-01

We extend two known dynamical systems obtained by Blaszak, et al. via choosing Casimir functions and utilizing Novikov-Lax equation so that a series of novel dynamical systems including generalized Burgers dynamical system, heat equation, and so on, are followed to be generated. Then we expand some differential operators presented in the paper to deduce two types of expanding dynamical models. By taking the generalized Burgers dynamical system as an example, we deform its expanding model to get a half-expanding system, whose recurrence operator is derived from Lax representation, and its Hamiltonian structure is also obtained by adopting a new way. Finally, we expand the generalized Burgers dynamical system to the (2+1)-dimensional case whose Hamiltonian structure is derived by Poisson tensor and gradient of the Casimir function. Besides, a kind of (2+1)-dimensional expanding dynamical model of the (2+1)-dimensional dynamical system is generated as well. Supported by the Fundamental Research Funds for the Central University under Grant No. 2017XKZD11

The Dynamic Model and Inherent Variability: The Case of Northern France.

ERIC Educational Resources Information Center

Hornsby, David

1999-01-01

Explores the claims of the "dynamic" model of variation by testing against data recorded in Avion, Northern France. Parallels are drawn between "langue d'oil" areas of France and decreolization situations in which proponents of the dynamic model have generally worked. (Author/VWL)

Dynamic Evaluation of Long-Term Air Quality Model Simulations Over the Northeastern U.S.

EPA Science Inventory

Dynamic model evaluation assesses a modeling system's ability to reproduce changes in air quality induced by changes in meteorology and/or emissions. In this paper, we illustrate various approaches to dynamic mode evaluation utilizing 18 years of air quality simulations perform...

The Challenges to Coupling Dynamic Geospatial Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goldstein, N

2006-06-23

Many applications of modeling spatial dynamic systems focus on a single system and a single process, ignoring the geographic and systemic context of the processes being modeled. A solution to this problem is the coupled modeling of spatial dynamic systems. Coupled modeling is challenging for both technical reasons, as well as conceptual reasons. This paper explores the benefits and challenges to coupling or linking spatial dynamic models, from loose coupling, where information transfer between models is done by hand, to tight coupling, where two (or more) models are merged as one. To illustrate the challenges, a coupled model of Urbanizationmore » and Wildfire Risk is presented. This model, called Vesta, was applied to the Santa Barbara, California region (using real geospatial data), where Urbanization and Wildfires occur and recur, respectively. The preliminary results of the model coupling illustrate that coupled modeling can lead to insight into the consequences of processes acting on their own.« less

Local dynamic subgrid-scale models in channel flow

NASA Technical Reports Server (NTRS)

Cabot, William H.

1994-01-01

The dynamic subgrid-scale (SGS) model has given good results in the large-eddy simulation (LES) of homogeneous isotropic or shear flow, and in the LES of channel flow, using averaging in two or three homogeneous directions (the DA model). In order to simulate flows in general, complex geometries (with few or no homogeneous directions), the dynamic SGS model needs to be applied at a local level in a numerically stable way. Channel flow, which is inhomogeneous and wall-bounded flow in only one direction, provides a good initial test for local SGS models. Tests of the dynamic localization model were performed previously in channel flow using a pseudospectral code and good results were obtained. Numerical instability due to persistently negative eddy viscosity was avoided by either constraining the eddy viscosity to be positive or by limiting the time that eddy viscosities could remain negative by co-evolving the SGS kinetic energy (the DLk model). The DLk model, however, was too expensive to run in the pseudospectral code due to a large near-wall term in the auxiliary SGS kinetic energy (k) equation. One objective was then to implement the DLk model in a second-order central finite difference channel code, in which the auxiliary k equation could be integrated implicitly in time at great reduction in cost, and to assess its performance in comparison with the plane-averaged dynamic model or with no model at all, and with direct numerical simulation (DNS) and/or experimental data. Other local dynamic SGS models have been proposed recently, e.g., constrained dynamic models with random backscatter, and with eddy viscosity terms that are averaged in time over material path lines rather than in space. Another objective was to incorporate and test these models in channel flow.

Is there a `universal' dynamic zero-parameter hydrological model? Evaluation of a dynamic Budyko model in US and India

NASA Astrophysics Data System (ADS)

Patnaik, S.; Biswal, B.; Sharma, V. C.

2017-12-01

River flow varies greatly in space and time, and the single biggest challenge for hydrologists and ecologists around the world is the fact that most rivers are either ungauged or poorly gauged. Although it is relatively easier to predict long-term average flow of a river using the `universal' zero-parameter Budyko model, lack of data hinders short-term flow prediction at ungauged locations using traditional hydrological models as they require observed flow data for model calibration. Flow prediction in ungauged basins thus requires a dynamic 'zero-parameter' hydrological model. One way to achieve this is to regionalize a dynamic hydrological model's parameters. However, a regionalization method based zero-parameter dynamic hydrological model is not `universal'. An alternative attempt was made recently to develop a zero-parameter dynamic model by defining an instantaneous dryness index as a function of antecedent rainfall and solar energy inputs with the help of a decay function and using the original Budyko function. The model was tested first in 63 US catchments and later in 50 Indian catchments. The median Nash-Sutcliffe efficiency (NSE) was found to be close to 0.4 in both the cases. Although improvements need to be incorporated in order to use the model for reliable prediction, the main aim of this study was to rather understand hydrological processes. The overall results here seem to suggest that the dynamic zero-parameter Budyko model is `universal.' In other words natural catchments around the world are strikingly similar to each other in the way they respond to hydrologic inputs; we thus need to focus more on utilizing catchment similarities in hydrological modelling instead of over parameterizing our models.

Calculation of broadband time histories of ground motion, Part II: Kinematic and dynamic modeling using theoretical Green's functions and comparison with the 1994 northridge earthquake

USGS Publications Warehouse

Hartzell, S.; Guatteri, Mariagiovanna; Mai, P.M.; Liu, P.-C.; Fisk, M. R.

2005-01-01

In the evolution of methods for calculating synthetic time histories of ground motion for postulated earthquakes, kinematic source models have dominated to date because of their ease of application. Dynamic models, however, which incorporate a physical relationship between important faulting parameters of stress drop, slip, rupture velocity, and rise time, are becoming more accessible. This article compares a class of kinematic models based on the summation of a fractal distribution of subevent sizes with a dynamic model based on the slip-weakening friction law. Kinematic modeling is done for the frequency band 0.2 to 10.0. Hz, dynamic models are calculated from 0.2 to 2.0. Hz. The strong motion data set for the 1994 Northridge earthquake is used to evaluate and compare the synthetic time histories. Source models are propagated to the far field by convolution with 1D and 3D theoretical Green’s functions. In addition, the kinematic model is used to evaluate the importance of propagation path effects: velocity structure, scattering, and nonlinearity. At present, the kinematic model gives a better broadband fit to the Northridge ground motion than the simple slip-weakening dynamic model. In general, the dynamic model overpredicts rise times and produces insufficient shorter-period energy. Within the context of the slip-weakening model, the Northridge ground motion requires a short slip-weakening distance, on the order of 0.15 m or less. A more complex dynamic model including rate weakening or one that allows shorter rise times near the hypocenter may fit the data better.

Dynamical entropy via entropy of non-random matrices: application to stability and complexity in modelling ecosystems.

PubMed

Chakrabarti, C G; Ghosh, Koyel

2013-10-01

In the present paper we have first introduced a measure of dynamical entropy of an ecosystem on the basis of the dynamical model of the system. The dynamical entropy which depends on the eigenvalues of the community matrix of the system leads to a consistent measure of complexity of the ecosystem to characterize the dynamical behaviours such as the stability, instability and periodicity around the stationary states of the system. We have illustrated the theory with some model ecosystems. Copyright © 2013 Elsevier Inc. All rights reserved.

Integrating dynamic stereo-radiography and surface-based motion data for subject-specific musculoskeletal dynamic modeling.

PubMed

Zheng, Liying; Li, Kang; Shetye, Snehal; Zhang, Xudong

2014-09-22

This manuscript presents a new subject-specific musculoskeletal dynamic modeling approach that integrates high-accuracy dynamic stereo-radiography (DSX) joint kinematics and surface-based full-body motion data. We illustrate this approach by building a model in OpenSim for a patient who participated in a meniscus transplantation efficacy study, incorporating DSX data of the tibiofemoral joint kinematics. We compared this DSX-incorporated (DSXI) model to a default OpenSim model built using surface-measured data alone. The architectures and parameters of the two models were identical, while the differences in (time-averaged) tibiofemoral kinematics were of the order of magnitude of 10° in rotation and 10mm in translation. Model-predicted tibiofemoral compressive forces and knee muscle activations were compared against literature data acquired from instrumented total knee replacement components (Fregly et al., 2012) and the patient's EMG recording. The comparison demonstrated that the incorporation of DSX data improves the veracity of musculoskeletal dynamic modeling. Copyright © 2014 Elsevier Ltd. All rights reserved.

Integrating dynamic stereo-radiography and surface-based motion data for subject-specific musculoskeletal dynamic modeling

PubMed Central

Zheng, Liying; Li, Kang; Shetye, Snehal; Zhang, Xudong

2014-01-01

This paper presents a new subject-specific musculoskeletal dynamic modeling approach that integrates high-accuracy dynamic stereo-radiography (DSX) joint kinematics and surface-based full-body motion data. We illustrate this approach by building a model in OpenSim for a patient who participated in a meniscus transplantation efficacy study, incorporating DSX data of the tibiofemoral joint kinematics. We compared this DSX-incorporated (DSXI) model to a default OpenSim model built using surface-measured data alone. The architectures and parameters of the two models were identical, while the differences in (time-averaged) tibiofemoral kinematics were of the order of magnitude of 10° in rotation and 10 mm in translation. Model-predicted tibiofemoral compressive forces and knee muscle activations were compared against literature data acquired from instrumented total knee replacement components (Fregly et al., 2012) and the patient's EMG recording. The comparison demonstrated that the incorporation of DSX data improves the veracity of musculoskeletal dynamic modeling. PMID:25169658

New insights into the complex regulation of the glycolytic pathway in Lactococcus lactis. I. Construction and diagnosis of a comprehensive dynamic model.

PubMed

Dolatshahi, Sepideh; Fonseca, Luis L; Voit, Eberhard O

2016-01-01

This article and the companion paper use computational systems modeling to decipher the complex coordination of regulatory signals controlling the glycolytic pathway in the dairy bacterium Lactococcus lactis. In this first article, the development of a comprehensive kinetic dynamic model is described. The model is based on in vivo NMR data that consist of concentration trends in key glycolytic metabolites and cofactors. The model structure and parameter values are identified with a customized optimization strategy that uses as its core the method of dynamic flux estimation. For the first time, a dynamic model with a single parameter set fits all available glycolytic time course data under anaerobic operation. The model captures observations that had not been addressed so far and suggests the existence of regulatory effects that had been observed in other species, but not in L. lactis. The companion paper uses this model to analyze details of the dynamic control of glycolysis under aerobic and anaerobic conditions.

A forward model-based validation of cardiovascular system identification

NASA Technical Reports Server (NTRS)

Mukkamala, R.; Cohen, R. J.

2001-01-01

We present a theoretical evaluation of a cardiovascular system identification method that we previously developed for the analysis of beat-to-beat fluctuations in noninvasively measured heart rate, arterial blood pressure, and instantaneous lung volume. The method provides a dynamical characterization of the important autonomic and mechanical mechanisms responsible for coupling the fluctuations (inverse modeling). To carry out the evaluation, we developed a computational model of the cardiovascular system capable of generating realistic beat-to-beat variability (forward modeling). We applied the method to data generated from the forward model and compared the resulting estimated dynamics with the actual dynamics of the forward model, which were either precisely known or easily determined. We found that the estimated dynamics corresponded to the actual dynamics and that this correspondence was robust to forward model uncertainty. We also demonstrated the sensitivity of the method in detecting small changes in parameters characterizing autonomic function in the forward model. These results provide confidence in the performance of the cardiovascular system identification method when applied to experimental data.

Dynamic sensitivity analysis of biological systems

PubMed Central

Wu, Wu Hsiung; Wang, Feng Sheng; Chang, Maw Shang

2008-01-01

Background A mathematical model to understand, predict, control, or even design a real biological system is a central theme in systems biology. A dynamic biological system is always modeled as a nonlinear ordinary differential equation (ODE) system. How to simulate the dynamic behavior and dynamic parameter sensitivities of systems described by ODEs efficiently and accurately is a critical job. In many practical applications, e.g., the fed-batch fermentation systems, the system admissible input (corresponding to independent variables of the system) can be time-dependent. The main difficulty for investigating the dynamic log gains of these systems is the infinite dimension due to the time-dependent input. The classical dynamic sensitivity analysis does not take into account this case for the dynamic log gains. Results We present an algorithm with an adaptive step size control that can be used for computing the solution and dynamic sensitivities of an autonomous ODE system simultaneously. Although our algorithm is one of the decouple direct methods in computing dynamic sensitivities of an ODE system, the step size determined by model equations can be used on the computations of the time profile and dynamic sensitivities with moderate accuracy even when sensitivity equations are more stiff than model equations. To show this algorithm can perform the dynamic sensitivity analysis on very stiff ODE systems with moderate accuracy, it is implemented and applied to two sets of chemical reactions: pyrolysis of ethane and oxidation of formaldehyde. The accuracy of this algorithm is demonstrated by comparing the dynamic parameter sensitivities obtained from this new algorithm and from the direct method with Rosenbrock stiff integrator based on the indirect method. The same dynamic sensitivity analysis was performed on an ethanol fed-batch fermentation system with a time-varying feed rate to evaluate the applicability of the algorithm to realistic models with time-dependent admissible input. Conclusion By combining the accuracy we show with the efficiency of being a decouple direct method, our algorithm is an excellent method for computing dynamic parameter sensitivities in stiff problems. We extend the scope of classical dynamic sensitivity analysis to the investigation of dynamic log gains of models with time-dependent admissible input. PMID:19091016

Haptics-based dynamic implicit solid modeling.

PubMed

Hua, Jing; Qin, Hong

2004-01-01

This paper systematically presents a novel, interactive solid modeling framework, Haptics-based Dynamic Implicit Solid Modeling, which is founded upon volumetric implicit functions and powerful physics-based modeling. In particular, we augment our modeling framework with a haptic mechanism in order to take advantage of additional realism associated with a 3D haptic interface. Our dynamic implicit solids are semi-algebraic sets of volumetric implicit functions and are governed by the principles of dynamics, hence responding to sculpting forces in a natural and predictable manner. In order to directly manipulate existing volumetric data sets as well as point clouds, we develop a hierarchical fitting algorithm to reconstruct and represent discrete data sets using our continuous implicit functions, which permit users to further design and edit those existing 3D models in real-time using a large variety of haptic and geometric toolkits, and visualize their interactive deformation at arbitrary resolution. The additional geometric and physical constraints afford more sophisticated control of the dynamic implicit solids. The versatility of our dynamic implicit modeling enables the user to easily modify both the geometry and the topology of modeled objects, while the inherent physical properties can offer an intuitive haptic interface for direct manipulation with force feedback.

Traffic jam dynamics in stochastic cellular automata

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nagel, K.; Schreckenberg, M.

1995-09-01

Simple models for particles hopping on a grid (cellular automata) are used to simulate (single lane) traffic flow. Despite their simplicity, these models are astonishingly realistic in reproducing start-stop-waves and realistic fundamental diagrams. One can use these models to investigate traffic phenomena near maximum flow. A so-called phase transition at average maximum flow is visible in the life-times of jams. The resulting dynamic picture is consistent with recent fluid-dynamical results by Kuehne/Kerner/Konhaeuser, and with Treiterer`s hysteresis description. This places CA models between car-following models and fluid-dynamical models for traffic flow. CA models are tested in projects in Los Alamos (USA)more » and in NRW (Germany) for large scale microsimulations of network traffic.« less

A coarse wood dynamics model for the Western Cascades.

Treesearch

K. Mellen; A. Ager

2002-01-01

The Coarse Wood Dynamics Model (CWDM) analyzes the dynamics (fall, fragmentation, and decomposition) of Douglas-fir (Pseudotsuga menziesii) and western hemlock (Tsuga heterophylla) snags and down logs in forested ecosystems of the western Cascades of Oregon and Washington. The model predicts snag fall, height loss and decay,...

The System Dynamics Model User Sustainability Explorer (SD-MUSE) user interface: a user-friendly tool for interpreting system dynamic models

EPA Science Inventory

Sustainability-based decision making is a challenging process that requires balancing trade-offs among social, economic, and environmental components. System Dynamic (SD) models can be useful tools to inform sustainability-based decision making because they provide a holistic co...

CHARACTERIZING SPATIAL AND TEMPORAL DYNAMICS: DEVELOPMENT OF A GRID-BASED WATERSHED MERCURY LOADING MODEL

EPA Science Inventory

A distributed grid-based watershed mercury loading model has been developed to characterize spatial and temporal dynamics of mercury from both point and non-point sources. The model simulates flow, sediment transport, and mercury dynamics on a daily time step across a diverse lan...

Computing the non-Markovian coarse-grained interactions derived from the Mori-Zwanzig formalism in molecular systems: Application to polymer melts

NASA Astrophysics Data System (ADS)

Li, Zhen; Lee, Hee Sun; Darve, Eric; Karniadakis, George Em

2017-01-01

Memory effects are often introduced during coarse-graining of a complex dynamical system. In particular, a generalized Langevin equation (GLE) for the coarse-grained (CG) system arises in the context of Mori-Zwanzig formalism. Upon a pairwise decomposition, GLE can be reformulated into its pairwise version, i.e., non-Markovian dissipative particle dynamics (DPD). GLE models the dynamics of a single coarse particle, while DPD considers the dynamics of many interacting CG particles, with both CG systems governed by non-Markovian interactions. We compare two different methods for the practical implementation of the non-Markovian interactions in GLE and DPD systems. More specifically, a direct evaluation of the non-Markovian (NM) terms is performed in LE-NM and DPD-NM models, which requires the storage of historical information that significantly increases computational complexity. Alternatively, we use a few auxiliary variables in LE-AUX and DPD-AUX models to replace the non-Markovian dynamics with a Markovian dynamics in a higher dimensional space, leading to a much reduced memory footprint and computational cost. In our numerical benchmarks, the GLE and non-Markovian DPD models are constructed from molecular dynamics (MD) simulations of star-polymer melts. Results show that a Markovian dynamics with auxiliary variables successfully generates equivalent non-Markovian dynamics consistent with the reference MD system, while maintaining a tractable computational cost. Also, transient subdiffusion of the star-polymers observed in the MD system can be reproduced by the coarse-grained models. The non-interacting particle models, LE-NM/AUX, are computationally much cheaper than the interacting particle models, DPD-NM/AUX. However, the pairwise models with momentum conservation are more appropriate for correctly reproducing the long-time hydrodynamics characterised by an algebraic decay in the velocity autocorrelation function.

Dynamic PET and Optical Imaging and Compartment Modeling using a Dual-labeled Cyclic RGD Peptide Probe

PubMed Central

Zhu, Lei; Guo, Ning; Li, Quanzheng; Ma, Ying; Jacboson, Orit; Lee, Seulki; Choi, Hak Soo; Mansfield, James R.; Niu, Gang; Chen, Xiaoyuan

2012-01-01

Purpose: The aim of this study is to determine if dynamic optical imaging could provide comparable kinetic parameters to that of dynamic PET imaging by a near-infrared dye/64Cu dual-labeled cyclic RGD peptide. Methods: The integrin αvβ3 binding RGD peptide was conjugated with a macrocyclic chelator 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) for copper labeling and PET imaging and a near-infrared dye ZW-1 for optical imaging. The in vitro biological activity of RGD-C(DOTA)-ZW-1 was characterized by cell staining and receptor binding assay. Sixty-min dynamic PET and optical imaging were acquired on a MDA-MB-435 tumor model. Singular value decomposition (SVD) method was applied to compute the dynamic optical signal from the two-dimensional optical projection images. Compartment models were used to quantitatively analyze and compare the dynamic optical and PET data. Results: The dual-labeled probe 64Cu-RGD-C(DOTA)-ZW-1 showed integrin specific binding in vitro and in vivo. The binding potential (Bp) derived from dynamic optical imaging (1.762 ± 0.020) is comparable to that from dynamic PET (1.752 ± 0.026). Conclusion: The signal un-mixing process using SVD improved the accuracy of kinetic modeling of 2D dynamic optical data. Our results demonstrate that 2D dynamic optical imaging with SVD analysis could achieve comparable quantitative results as dynamic PET imaging in preclinical xenograft models. PMID:22916074

Dynamic PET and Optical Imaging and Compartment Modeling using a Dual-labeled Cyclic RGD Peptide Probe.

PubMed

Zhu, Lei; Guo, Ning; Li, Quanzheng; Ma, Ying; Jacboson, Orit; Lee, Seulki; Choi, Hak Soo; Mansfield, James R; Niu, Gang; Chen, Xiaoyuan

2012-01-01

The aim of this study is to determine if dynamic optical imaging could provide comparable kinetic parameters to that of dynamic PET imaging by a near-infrared dye/(64)Cu dual-labeled cyclic RGD peptide. The integrin α(v)β(3) binding RGD peptide was conjugated with a macrocyclic chelator 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) for copper labeling and PET imaging and a near-infrared dye ZW-1 for optical imaging. The in vitro biological activity of RGD-C(DOTA)-ZW-1 was characterized by cell staining and receptor binding assay. Sixty-min dynamic PET and optical imaging were acquired on a MDA-MB-435 tumor model. Singular value decomposition (SVD) method was applied to compute the dynamic optical signal from the two-dimensional optical projection images. Compartment models were used to quantitatively analyze and compare the dynamic optical and PET data. The dual-labeled probe (64)Cu-RGD-C(DOTA)-ZW-1 showed integrin specific binding in vitro and in vivo. The binding potential (Bp) derived from dynamic optical imaging (1.762 ± 0.020) is comparable to that from dynamic PET (1.752 ± 0.026). The signal un-mixing process using SVD improved the accuracy of kinetic modeling of 2D dynamic optical data. Our results demonstrate that 2D dynamic optical imaging with SVD analysis could achieve comparable quantitative results as dynamic PET imaging in preclinical xenograft models.

Understanding system dynamics of an adaptive enzyme network from globally profiled kinetic parameters.

PubMed

Chiang, Austin W T; Liu, Wei-Chung; Charusanti, Pep; Hwang, Ming-Jing

2014-01-15

A major challenge in mathematical modeling of biological systems is to determine how model parameters contribute to systems dynamics. As biological processes are often complex in nature, it is desirable to address this issue using a systematic approach. Here, we propose a simple methodology that first performs an enrichment test to find patterns in the values of globally profiled kinetic parameters with which a model can produce the required system dynamics; this is then followed by a statistical test to elucidate the association between individual parameters and different parts of the system's dynamics. We demonstrate our methodology on a prototype biological system of perfect adaptation dynamics, namely the chemotaxis model for Escherichia coli. Our results agreed well with those derived from experimental data and theoretical studies in the literature. Using this model system, we showed that there are motifs in kinetic parameters and that these motifs are governed by constraints of the specified system dynamics. A systematic approach based on enrichment statistical tests has been developed to elucidate the relationships between model parameters and the roles they play in affecting system dynamics of a prototype biological network. The proposed approach is generally applicable and therefore can find wide use in systems biology modeling research.

Intelligent classifier for dynamic fault patterns based on hidden Markov model

NASA Astrophysics Data System (ADS)

Xu, Bo; Feng, Yuguang; Yu, Jinsong

2006-11-01

It's difficult to build precise mathematical models for complex engineering systems because of the complexity of the structure and dynamics characteristics. Intelligent fault diagnosis introduces artificial intelligence and works in a different way without building the analytical mathematical model of a diagnostic object, so it's a practical approach to solve diagnostic problems of complex systems. This paper presents an intelligent fault diagnosis method, an integrated fault-pattern classifier based on Hidden Markov Model (HMM). This classifier consists of dynamic time warping (DTW) algorithm, self-organizing feature mapping (SOFM) network and Hidden Markov Model. First, after dynamic observation vector in measuring space is processed by DTW, the error vector including the fault feature of being tested system is obtained. Then a SOFM network is used as a feature extractor and vector quantization processor. Finally, fault diagnosis is realized by fault patterns classifying with the Hidden Markov Model classifier. The importing of dynamic time warping solves the problem of feature extracting from dynamic process vectors of complex system such as aeroengine, and makes it come true to diagnose complex system by utilizing dynamic process information. Simulating experiments show that the diagnosis model is easy to extend, and the fault pattern classifier is efficient and is convenient to the detecting and diagnosing of new faults.

Model systems for single molecule polymer dynamics

PubMed Central

Latinwo, Folarin

2012-01-01

Double stranded DNA (dsDNA) has long served as a model system for single molecule polymer dynamics. However, dsDNA is a semiflexible polymer, and the structural rigidity of the DNA double helix gives rise to local molecular properties and chain dynamics that differ from flexible chains, including synthetic organic polymers. Recently, we developed single stranded DNA (ssDNA) as a new model system for single molecule studies of flexible polymer chains. In this work, we discuss model polymer systems in the context of “ideal” and “real” chain behavior considering thermal blobs, tension blobs, hydrodynamic drag and force–extension relations. In addition, we present monomer aspect ratio as a key parameter describing chain conformation and dynamics, and we derive dynamical scaling relations in terms of this molecular-level parameter. We show that asymmetric Kuhn segments can suppress monomer–monomer interactions, thereby altering global chain dynamics. Finally, we discuss ssDNA in the context of a new model system for single molecule polymer dynamics. Overall, we anticipate that future single polymer studies of flexible chains will reveal new insight into the dynamic behavior of “real” polymers, which will highlight the importance of molecular individualism and the prevalence of non-linear phenomena. PMID:22956980

Clinical Applications of Stochastic Dynamic Models of the Brain, Part I: A Primer.

PubMed

Roberts, James A; Friston, Karl J; Breakspear, Michael

2017-04-01

Biological phenomena arise through interactions between an organism's intrinsic dynamics and stochastic forces-random fluctuations due to external inputs, thermal energy, or other exogenous influences. Dynamic processes in the brain derive from neurophysiology and anatomical connectivity; stochastic effects arise through sensory fluctuations, brainstem discharges, and random microscopic states such as thermal noise. The dynamic evolution of systems composed of both dynamic and random effects can be studied with stochastic dynamic models (SDMs). This article, Part I of a two-part series, offers a primer of SDMs and their application to large-scale neural systems in health and disease. The companion article, Part II, reviews the application of SDMs to brain disorders. SDMs generate a distribution of dynamic states, which (we argue) represent ideal candidates for modeling how the brain represents states of the world. When augmented with variational methods for model inversion, SDMs represent a powerful means of inferring neuronal dynamics from functional neuroimaging data in health and disease. Together with deeper theoretical considerations, this work suggests that SDMs will play a unique and influential role in computational psychiatry, unifying empirical observations with models of perception and behavior. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Understanding and Modeling Teams As Dynamical Systems

PubMed Central

Gorman, Jamie C.; Dunbar, Terri A.; Grimm, David; Gipson, Christina L.

2017-01-01

By its very nature, much of teamwork is distributed across, and not stored within, interdependent people working toward a common goal. In this light, we advocate a systems perspective on teamwork that is based on general coordination principles that are not limited to cognitive, motor, and physiological levels of explanation within the individual. In this article, we present a framework for understanding and modeling teams as dynamical systems and review our empirical findings on teams as dynamical systems. We proceed by (a) considering the question of why study teams as dynamical systems, (b) considering the meaning of dynamical systems concepts (attractors; perturbation; synchronization; fractals) in the context of teams, (c) describe empirical studies of team coordination dynamics at the perceptual-motor, cognitive-behavioral, and cognitive-neurophysiological levels of analysis, and (d) consider the theoretical and practical implications of this approach, including new kinds of explanations of human performance and real-time analysis and performance modeling. Throughout our discussion of the topics we consider how to describe teamwork using equations and/or modeling techniques that describe the dynamics. Finally, we consider what dynamical equations and models do and do not tell us about human performance in teams and suggest future research directions in this area. PMID:28744231

Topics in Modeling of Cochlear Dynamics: Computation, Response and Stability Analysis

NASA Astrophysics Data System (ADS)

Filo, Maurice G.

This thesis touches upon several topics in cochlear modeling. Throughout the literature, mathematical models of the cochlea vary according to the degree of biological realism to be incorporated. This thesis casts the cochlear model as a continuous space-time dynamical system using operator language. This framework encompasses a wider class of cochlear models and makes the dynamics more transparent and easier to analyze before applying any numerical method to discretize space. In fact, several numerical methods are investigated to study the computational efficiency of the finite dimensional realizations in space. Furthermore, we study the effects of the active gain perturbations on the stability of the linearized dynamics. The stability analysis is used to explain possible mechanisms underlying spontaneous otoacoustic emissions and tinnitus. Dynamic Mode Decomposition (DMD) is introduced as a useful tool to analyze the response of nonlinear cochlear models. Cochlear response features are illustrated using DMD which has the advantage of explicitly revealing the spatial modes of vibrations occurring in the Basilar Membrane (BM). Finally, we address the dynamic estimation problem of BM vibrations using Extended Kalman Filters (EKF). Due to the limitations of noninvasive sensing schemes, such algorithms are inevitable to estimate the dynamic behavior of a living cochlea.

Extended Kalman Filter for Estimation of Parameters in Nonlinear State-Space Models of Biochemical Networks

PubMed Central

Sun, Xiaodian; Jin, Li; Xiong, Momiao

2008-01-01

It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks. PMID:19018286

Rethinking the logistic approach for population dynamics of mutualistic interactions.

PubMed

García-Algarra, Javier; Galeano, Javier; Pastor, Juan Manuel; Iriondo, José María; Ramasco, José J

2014-12-21

Mutualistic communities have an internal structure that makes them resilient to external perturbations. Late research has focused on their stability and the topology of the relations between the different organisms to explain the reasons of the system robustness. Much less attention has been invested in analyzing the systems dynamics. The main population models in use are modifications of the r-K formulation of logistic equation with additional terms to account for the benefits produced by the interspecific interactions. These models have shortcomings as the so-called r-K formulation diverges under some conditions. In this work, we introduce a model for population dynamics under mutualism that preserves the original logistic formulation. It is mathematically simpler than the widely used type II models, although it shows similar complexity in terms of fixed points and stability of the dynamics. We perform an analytical stability analysis and numerical simulations to study the model behavior in general interaction scenarios including tests of the resilience of its dynamics under external perturbations. Despite its simplicity, our results indicate that the model dynamics shows an important richness that can be used to gain further insights in the dynamics of mutualistic communities. Copyright © 2014 Elsevier Ltd. All rights reserved.

Modeling Earth's surface topography: decomposition of the static and dynamic components

NASA Astrophysics Data System (ADS)

Guerri, M.; Cammarano, F.; Tackley, P. J.

2017-12-01

Isolating the portion of topography supported by mantle convection, the so-called dynamic topography, would give us precious information on vigor and style of the convection itself. Contrasting results on the estimate of dynamic topography motivate us to analyse the sources of uncertainties affecting its modeling. We obtain models of mantle and crust density, leveraging on seismic and mineral physics constraints. We use the models to compute isostatic topography and residual topography maps. Estimates of dynamic topography and associated synthetic geoid are obtained by instantaneous mantle flow modeling. We test various viscosity profiles and 3D viscosity distributions accounting for inferred lateral variations in temperature. We find that the patterns of residual and dynamic topography are robust, with an average correlation coefficient of 0.74 and 0.71, respectively. The amplitudes are however poorly constrained. For the static component, the considered lithospheric mantle density models result in topographies that differ, on average, 720 m, with peaks reaching 1.7 km. The crustal density models produce variations in isostatic topography averaging 350 m, with peaks of 1 km. For the dynamic component, we obtain peak-to-peak topography amplitude exceeding 3 km for all the tested mantle density and viscosity models. Such values of dynamic topography produce geoid undulations that are not in agreement with observations. Assuming chemical heterogeneities in the lower mantle, in correspondence with the LLSVPs (Large Low Shear wave Velocity Provinces), helps to decrease the amplitudes of dynamic topography and geoid, but reduces the correlation between synthetic and observed geoid. The correlation coefficients between the residual and dynamic topography maps is always less than 0.55. In general, our results indicate that, i) current knowledge of crust density, mantle density and mantle viscosity is still limited, ii) it is important to account for all the various sources of uncertainties when computing static and dynamic topography. In conclusion, a multidisciplinary approach, which involves multiple geophysics observations and constraints from mineral physics, is necessary for obtaining robust density models and, consequently, for properly estimating the dynamic topography.

Comparative Effectiveness Research Through a Collaborative Electronic Reporting Consortium.

PubMed

Fiks, Alexander G; Grundmeier, Robert W; Steffes, Jennifer; Adams, William G; Kaelber, David C; Pace, Wilson D; Wasserman, Richard C

2015-07-01

The United States lacks a system to use routinely collected electronic health record (EHR) clinical data to conduct comparative effectiveness research (CER) on pediatric drug therapeutics and other child health topics. This Special Article describes the creation and details of a network of EHR networks devised to use clinical data in EHRs for conducting CER, led by the American Academy of Pediatrics Pediatric Research in Office Settings (PROS). To achieve this goal, PROS has linked data from its own EHR-based "ePROS" network with data from independent practices and health systems across the United States. Beginning with 4 of proof-of-concept retrospective CER studies on psychotropic and asthma medication use and side effects with a planned full-scale prospective CER study on treatment of pediatric hypertension, the Comparative Effectiveness Research Through Collaborative Electronic Reporting (CER(2)) collaborators are developing a platform to advance the methodology of pediatric pharmacoepidemiology. CER(2) will provide a resource for future CER studies in pediatric drug therapeutics and other child health topics. This article outlines the vision for and present composition of this network, governance, and challenges and opportunities for using the network to advance child health and health care. The goal of this network is to engage child health researchers from around the United States in participating in collaborative research using the CER(2) database. Copyright © 2015 by the American Academy of Pediatrics.

Absorption of Levothyroxine When Coadministered with Various Calcium Formulations

PubMed Central

Zamfirescu, Isabelle

2011-01-01

Background Calcium carbonate is a commonly used dietary supplement and has been shown to interfere with levothyroxine absorption. However, calcium citrate, which is also used for supplementation purposes, has not been studied previously and calcium acetate, which is used to treat hyperphosphatemia in renal failure, has been reported to show little or no interference with levothyroxine absorption in a retrospective pharmacoepidemiologic study. We aimed to compare the effect of these three calcium formulations on levothyroxine absorption. Materials and Methods The study was conducted in eight healthy, euthyroid adults. We performed single-dose pharmacokinetic studies in which we measured levothyroxine absorption when given alone or when coadministered with calcium carbonate, calcium citrate, or calcium acetate in doses containing 500 mg elemental calcium. Serum thyroxine was measured at intervals over a 6-hour period after ingestion of the study drugs. Results Coadministration of each of the three calcium preparations significantly reduced levothyroxine absorption by about 20%–25% compared with levothyroxine given alone. Conclusions Contrary to a prior report, our data suggest that calcium acetate interferes with levothyroxine absorption in a manner similar to that seen with calcium carbonate and calcium citrate. Although the effect of calcium is modest compared with some other medications previously studied, hypothyroid patients should be cautioned to take their levothyroxine well-separated from all of these calcium formulations. PMID:21595516

Implementation of a computer-assisted monitoring system for the detection of adverse drug reactions in gastroenterology.

PubMed

Dormann, H; Criegee-Rieck, M; Neubert, A; Egger, T; Levy, M; Hahn, E G; Brune, K

2004-02-01

To investigate the effectiveness of a computer monitoring system that detects adverse drug reactions (ADRs) by laboratory signals in gastroenterology. A prospective, 6-month, pharmaco-epidemiological survey was carried out on a gastroenterological ward at the University Hospital Erlangen-Nuremberg. Two methods were used to identify ADRs. (i) All charts were reviewed daily by physicians and clinical pharmacists. (ii) A computer monitoring system generated a daily list of automatic laboratory signals and alerts of ADRs, including patient data and dates of events. One hundred and nine ADRs were detected in 474 admissions (377 patients). The computer monitoring system generated 4454 automatic laboratory signals from 39 819 laboratory parameters tested, and issued 2328 alerts, 914 (39%) of which were associated with ADRs; 574 (25%) were associated with ADR-positive admissions. Of all the alerts generated, signals of hepatotoxicity (1255), followed by coagulation disorders (407) and haematological toxicity (207), were prevalent. Correspondingly, the prevailing ADRs were concerned with the metabolic and hepato-gastrointestinal system (61). The sensitivity was 91%: 69 of 76 ADR-positive patients were indicated by an alert. The specificity of alerts was increased from 23% to 76% after implementation of an automatic laboratory signal trend monitoring algorithm. This study shows that a computer monitoring system is a useful tool for the systematic and automated detection of ADRs in gastroenterological patients.

Reporting to Improve Reproducibility and Facilitate Validity Assessment for Healthcare Database Studies V1.0.

PubMed

Wang, Shirley V; Schneeweiss, Sebastian; Berger, Marc L; Brown, Jeffrey; de Vries, Frank; Douglas, Ian; Gagne, Joshua J; Gini, Rosa; Klungel, Olaf; Mullins, C Daniel; Nguyen, Michael D; Rassen, Jeremy A; Smeeth, Liam; Sturkenboom, Miriam

2017-09-01

Defining a study population and creating an analytic dataset from longitudinal healthcare databases involves many decisions. Our objective was to catalogue scientific decisions underpinning study execution that should be reported to facilitate replication and enable assessment of validity of studies conducted in large healthcare databases. We reviewed key investigator decisions required to operate a sample of macros and software tools designed to create and analyze analytic cohorts from longitudinal streams of healthcare data. A panel of academic, regulatory, and industry experts in healthcare database analytics discussed and added to this list. Evidence generated from large healthcare encounter and reimbursement databases is increasingly being sought by decision-makers. Varied terminology is used around the world for the same concepts. Agreeing on terminology and which parameters from a large catalogue are the most essential to report for replicable research would improve transparency and facilitate assessment of validity. At a minimum, reporting for a database study should provide clarity regarding operational definitions for key temporal anchors and their relation to each other when creating the analytic dataset, accompanied by an attrition table and a design diagram. A substantial improvement in reproducibility, rigor and confidence in real world evidence generated from healthcare databases could be achieved with greater transparency about operational study parameters used to create analytic datasets from longitudinal healthcare databases. © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd.

A day in the life of a pharmacovigilance case processor.

PubMed

Bhangale, Ritesh; Vaity, Sayali; Kulkarni, Niranjan

2017-01-01

Pharmacovigilance (PV) has grown significantly in India in the last couple of decades. The etymological roots for the word "pharmacovigilance" are "Pharmakon" (Greek for drug) and "Vigilare" (Latin for to keep watch). It relies on information gathered from the collection of individual case safety reports and other pharmacoepidemiological data. The PV data processing cycle starts with data collection in computerized systems followed by complete data entry which includes adverse event coding, drug coding, causality and expectedness assessment, narrative writing, quality control, and report submissions followed by data storage and maintenance. A case processor plays an important role in conducting these various tasks. The case processor should also manage drug safety information, possess updated knowledge about global drug safety regulations, summarize clinical safety data, participate in meetings, write narratives with medical input from a physician, report serious adverse events to the regulatory authorities, participate in the training of operational staff on drug safety issues, quality control work of other staff in the department, and take on any other task as assigned by the manager or medical director within the capabilities of the drug safety associate. There can be challenges while handling all these tasks at a time, hence the associate will have to maintain a balance to overcome them and keep on updating their knowledge on drug safety regulations, which in turn, would help in increasing their learning curve.

International trends in antipsychotic use: A study in 16 countries, 2005-2014.

PubMed

Hálfdánarson, Óskar; Zoëga, Helga; Aagaard, Lise; Bernardo, Miquel; Brandt, Lena; Fusté, Anna Coma; Furu, Kari; Garuoliené, Kristina; Hoffmann, Falk; Huybrechts, Krista F; Kalverdijk, Luuk J; Kawakami, Koji; Kieler, Helle; Kinoshita, Takuya; Litchfield, Melisa; López, Soffy C; Machado-Alba, Jorge E; Machado-Duque, Manuel E; Mahesri, Mufaddal; Nishtala, Prasad S; Pearson, Sallie-Anne; Reutfors, Johan; Saastamoinen, Leena K; Sato, Izumi; Schuiling-Veninga, Catharina C M; Shyu, Yu-Chiau; Skurtveit, Svetlana; Verdoux, Hélène; Wang, Liang-Jen; Yahni, Corinne Zara; Bachmann, Christian J

2017-10-01

The objective of this study was to assess international trends in antipsychotic use, using a standardised methodology. A repeated cross-sectional design was applied to data extracts from the years 2005 to 2014 from 16 countries worldwide. During the study period, the overall prevalence of antipsychotic use increased in 10 of the 16 studied countries. In 2014, the overall prevalence of antipsychotic use was highest in Taiwan (78.2/1000 persons), and lowest in Colombia (3.2/1000). In children and adolescents (0-19 years), antipsychotic use ranged from 0.5/1000 (Lithuania) to 30.8/1000 (Taiwan). In adults (20-64 years), the range was 2.8/1000 (Colombia) to 78.9/1000 (publicly insured US population), and in older adults (65+ years), antipsychotic use ranged from 19.0/1000 (Colombia) to 149.0/1000 (Taiwan). Atypical antipsychotic use increased in all populations (range of atypical/typical ratio: 0.7 (Taiwan) to 6.1 (New Zealand, Australia)). Quetiapine, risperidone, and olanzapine were most frequently prescribed. Prevalence and patterns of antipsychotic use varied markedly between countries. In the majority of populations, antipsychotic utilisation and especially the use of atypical antipsychotics increased over time. The high rates of antipsychotic prescriptions in older adults and in youths in some countries merit further investigation and systematic pharmacoepidemiologic monitoring. Copyright © 2017 Elsevier B.V. and ECNP. All rights reserved.

Risk of Extrapyramidal Adverse Events With Aripiprazole.

PubMed

Etminan, Mahyar; Procyshyn, Ric M; Samii, Ali; Carleton, Bruce C

2016-10-01

Aripiprazole is a unique atypical antipsychotic with partial agonist activity on the dopamine-2 (D2) receptor. This unique pharmacological profile of aripiprazole was thought to lead to a lower incidence of extrapyramidal symptoms (EPSs). However, recent case reports have alluded to an increase in the risk of EPS in aripiprazole users compared with nonusers of the drug. No epidemiologic studies to date have quantified this risk. We conducted a pharmacoepidemiologic study composed of a nested case-control study using a large health claims database (IMS Health) in the United States. In the nested case-control analysis, there were 5242 cases of EPS with 50,532 corresponding controls in the entire cohort. The odds ratio (OR) for EPS among those with any prescription of aripiprazole was 5.38 (95% confidence interval [CI], 3.03-9.57). The OR was lower among those taking 2 to 3 prescriptions (OR, 2.9; 95% CI, 1.07-7.85) but increased in those receiving greater than 4 prescriptions (OR, 8.64; 95% CI, 2.63-28.38). All risk periods were compared with those of subjects who had not used aripiprazole or other antipsychotics. For the secondary outcome of dyskinesia, the risk for aripiprazole was 8.50 (95% CI, 8.53-2.27-31.97) compared with that of nonusers. In conclusion, we found an increase in the risk of EPS and dyskinesias among users of aripiprazole.

Phynx: an open source software solution supporting data management and web-based patient-level data review for drug safety studies in the general practice research database and other health care databases.

PubMed

Egbring, Marco; Kullak-Ublick, Gerd A; Russmann, Stefan

2010-01-01

To develop a software solution that supports management and clinical review of patient data from electronic medical records databases or claims databases for pharmacoepidemiological drug safety studies. We used open source software to build a data management system and an internet application with a Flex client on a Java application server with a MySQL database backend. The application is hosted on Amazon Elastic Compute Cloud. This solution named Phynx supports data management, Web-based display of electronic patient information, and interactive review of patient-level information in the individual clinical context. This system was applied to a dataset from the UK General Practice Research Database (GPRD). Our solution can be setup and customized with limited programming resources, and there is almost no extra cost for software. Access times are short, the displayed information is structured in chronological order and visually attractive, and selected information such as drug exposure can be blinded. External experts can review patient profiles and save evaluations and comments via a common Web browser. Phynx provides a flexible and economical solution for patient-level review of electronic medical information from databases considering the individual clinical context. It can therefore make an important contribution to an efficient validation of outcome assessment in drug safety database studies.

Drug- and herb-induced liver injury: Progress, current challenges and emerging signals of post-marketing risk

PubMed Central

Raschi, Emanuel; De Ponti, Fabrizio

2015-01-01

Drug-induced liver injury (DILI) and herb-induced liver injury is a hot topic for clinicians, academia, drug companies and regulators, as shown by the steadily increasing number of publications in the past 15 years. This review will first provide clues for clinicians to suspect idiosyncratic (unpredictable) DILI and succeed in diagnosis. Causality assessment remains challenging and requires careful medical history as well as awareness of multifaceted aspects, especially for herbs. Drug discontinuation and therapy reconciliation remain the mainstay in patent’s management to minimize occurrence of acute liver failure. The second section will address novel agents associated with liver injury in 2014 (referred to as “signals”), especially in terms of clinical, research and drug development implications. Insights will be provided into recent trends by highlighting the contribution of different post-marketing data, especially registries and spontaneous reporting systems. This literature scrutiny suggests: (1) the importance of post-marketing databases as tools of clinical evidence to detect signals of DILI risk; and (2) the need for joining efforts in improving predictivity of pre-clinical assays, continuing post-marketing surveillance and design ad hoc post-authorization safety studies. In this context, ongoing European/United States research consortia and novel pharmaco-epidemiological tools (e.g., specialist prescription event monitoring) will support innovation in this field. Direct oral anticoagulants and herbal/dietary supplements appear as key research priorities. PMID:26167249

Package leaflets of the most consumed medicines in Portugal: safety and regulatory compliance issues. A descriptive study.

PubMed

Pires, Carla; Vigário, Marina; Cavaco, Afonso

2015-01-01

Package leaflets are necessary for safe use of medicines. The aims of the present study were: 1) to assess the compliance between the content of the package leaflets and the specifications of the pharmaceutical regulations; and 2) to identify potential safety issues for patients. Qualitative descriptive study, involving all the package leaflets of branded medicines from the three most consumed therapeutic groups in Portugal, analyzed in the Department of Pharmacoepidemiology, School of Pharmacy, University of Lisbon. A checklist validated through an expert consensus process was used to gather the data. The content of each package leaflet in the sample was classified as compliant or non-compliant with compulsory regulatory issues (i.e. stated dosage and descriptions of adverse reactions) and optional regulatory issues (i.e. adverse reaction frequency, symptoms and procedures in cases of overdose). A total of 651 package leaflets were identified. Overall, the package leaflets were found to be compliant with the compulsory regulatory issues. However, the optional regulatory issues were only addressed in around half of the sample of package leaflets, which made it possible to identify some situations of potentially compromised drug safety. Ideally, the methodologies for package leaflet approval should be reviewed and optimized as a way of ensuring the inclusion of the minimum essential information for safe use of medicines.

Frequency and pattern of Chinese herbal medicine prescriptions for chronic hepatitis in Taiwan.

PubMed

Chen, Fang-Pey; Kung, Yen-Ying; Chen, Yu-Chun; Jong, Maw-Shiou; Chen, Tzeng-Ji; Chen, Fun-Jou; Hwang, Shinn-Jang

2008-04-17

Chinese herbal medicine (CHM) has been commonly used in treating liver diseases in Asian countries. To conduct a large-scale pharmacoepidemiological study and evaluate the frequency and pattern of CHM prescriptions in treating chronic hepatitis. We obtained the database of traditional Chinese medicine outpatient claims from the national health insurance in Taiwan for the whole 2002. Patients with chronic hepatitis were identified by the corresponding diagnosis of International Classification of Disease among claimed visiting files. Corresponding prescription files were analyzed, and association rule were applied to evaluate the co-prescription of CHM in treating chronic hepatitis. Among the 91,080 subjects treated by CHM for chronic hepatitis, the peak age was in the 40 s, followed by 30 s and 50 s. Male/female ratio was 2.07:1. Long-dan-xie-gan-tang and Saliva miltiorrhiza (Dan-shen) were the most commonly prescribed Chinese herbal formula and single herbal drug, respectively. The most common two-drug prescription was Jia-wei-xia-yao-san plus Saliva miltiorrhiza, and the most common three-drug prescription was Jia-wei-xia-yao-san plus Saliva miltiorrhiza and Artemisia capillaries (Yin-chen-hao). This study showed the utilization pattern of Chinese herbal drugs or formulae in treating chronic hepatitis. Further researches and clinical trials are needed to evaluate the efficacy of these Chinese herbs or its ingredients in treating chronic hepatitis.

Gingival bleeding, a possible "serious" adverse drug reaction: An observational study in the French PharmacoVigilance Database.

PubMed

Bondon-Guitton, Emmanuelle; Mourgues, Thibaut; Rousseau, Vanessa; Cousty, Sarah; Cottin, Judith; Drablier, Guillaume; Micallef, Joëlle; Montastruc, Jean-Louis

2017-09-01

Antithrombotic drugs are known to increase the risk of gingival bleeding because they affect coagulation. However, other drugs could also be involved in gingival bleeding. We performed a pharmacoepidemiological study to identify the drugs most frequently "suspected" in the occurrence of gingival bleeding. We selected reports of "gingival bleeding" from 1 January 1985 to 30 September 2014 in the French PharmacoVigilance Database. Among 523,808 reports of adverse drug reactions, we identified 454 reports of gingival bleeding (0.09%). Most of them were "serious" (58.4%) and occurred in females (54.6%). The frequency of gingival bleeding increased with age. The most frequently "suspected" drugs were antithrombotics (67.8%), particularly fluindione. Other drugs frequently involved were furosemide followed by paracetamol, amiodarone, amoxicillin, paroxetine, ketoprofen, zolpidem, enalapril and ramipril. Thirty-nine reports involved a drug-drug interaction with antithrombotics, mainly with anti-infectives. Gingival bleeding can be an adverse drug reaction, often "serious" and rarely fatal. Patients older than 50 years and women are particularly at risk. Among drugs known to increase the risk of gingival bleeding, the most frequently involved were fluindione, furosemide, paracetamol, amiodarone, amoxicillin, paroxetine or ketoprofen. We also identified signal for drugs not usually known to be involved in bleeding, like zolpidem, enalapril or ramipril. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Drug- and herb-induced liver injury: Progress, current challenges and emerging signals of post-marketing risk.

PubMed

Raschi, Emanuel; De Ponti, Fabrizio

2015-07-08

Drug-induced liver injury (DILI) and herb-induced liver injury is a hot topic for clinicians, academia, drug companies and regulators, as shown by the steadily increasing number of publications in the past 15 years. This review will first provide clues for clinicians to suspect idiosyncratic (unpredictable) DILI and succeed in diagnosis. Causality assessment remains challenging and requires careful medical history as well as awareness of multifaceted aspects, especially for herbs. Drug discontinuation and therapy reconciliation remain the mainstay in patent's management to minimize occurrence of acute liver failure. The second section will address novel agents associated with liver injury in 2014 (referred to as "signals"), especially in terms of clinical, research and drug development implications. Insights will be provided into recent trends by highlighting the contribution of different post-marketing data, especially registries and spontaneous reporting systems. This literature scrutiny suggests: (1) the importance of post-marketing databases as tools of clinical evidence to detect signals of DILI risk; and (2) the need for joining efforts in improving predictivity of pre-clinical assays, continuing post-marketing surveillance and design ad hoc post-authorization safety studies. In this context, ongoing European/United States research consortia and novel pharmaco-epidemiological tools (e.g., specialist prescription event monitoring) will support innovation in this field. Direct oral anticoagulants and herbal/dietary supplements appear as key research priorities.

A novel approach for medical research on lymphomas

PubMed Central

Conte, Cécile; Palmaro, Aurore; Grosclaude, Pascale; Daubisse-Marliac, Laetitia; Despas, Fabien; Lapeyre-Mestre, Maryse

2018-01-01

Abstract The use of claims database to study lymphomas in real-life conditions is a crucial issue in the future. In this way, it is essential to develop validated algorithms for the identification of lymphomas in these databases. The aim of this study was to assess the validity of diagnosis codes in the French health insurance database to identify incident cases of lymphomas according to results of a regional cancer registry, as the gold standard. Between 2010 and 2013, incident lymphomas were identified in hospital data through 2 algorithms of selection. The results of the identification process and characteristics of incident lymphomas cases were compared with data from the Tarn Cancer Registry. Each algorithm's performance was assessed by estimating sensitivity, predictive positive value, specificity (SPE), and negative predictive value. During the period, the registry recorded 476 incident cases of lymphomas, of which 52 were Hodgkin lymphomas and 424 non-Hodgkin lymphomas. For corresponding area and period, algorithm 1 provides a number of incident cases close to the Registry, whereas algorithm 2 overestimated the number of incident cases by approximately 30%. Both algorithms were highly specific (SPE = 99.9%) but moderately sensitive. The comparative analysis illustrates that similar distribution and characteristics are observed in both sources. Given these findings, the use of claims database can be consider as a pertinent and powerful tool to conduct medico-economic or pharmacoepidemiological studies in lymphomas. PMID:29480830

Good pharmacovigilance practices: technology enabled.

PubMed

Nelson, Robert C; Palsulich, Bruce; Gogolak, Victor

2002-01-01

The assessment of spontaneous reports is most effective it is conducted within a defined and rigorous process. The framework for good pharmacovigilance process (GPVP) is proposed as a subset of good postmarketing surveillance process (GPMSP), a functional structure for both a public health and corporate risk management strategy. GPVP has good practices that implement each step within a defined process. These practices are designed to efficiently and effectively detect and alert the drug safety professional to new and potentially important information on drug-associated adverse reactions. These practices are enabled by applied technology designed specifically for the review and assessment of spontaneous reports. Specific practices include rules-based triage, active query prompts for severe organ insults, contextual single case evaluation, statistical proportionality and correlational checks, case-series analyses, and templates for signal work-up and interpretation. These practices and the overall GPVP are supported by state-of-the-art web-based systems with powerful analytical engines, workflow and audit trials to allow validated systems support for valid drug safety signalling efforts. It is also important to understand that a process has a defined set of steps and any one cannot stand independently. Specifically, advanced use of technical alerting methods in isolation can mislead and allow one to misunderstand priorities and relative value. In the end, pharmacovigilance is a clinical art and a component process to the science of pharmacoepidemiology and risk management.

Quality of life, use of topical medications and socio-economic data in hand eczema: a Swedish nationwide survey.

PubMed

Bingefors, Kerstin; Lindberg, Magnus; Isacson, Dag

2011-06-01

Hand eczema is common and has an adverse impact on the lives of patients. There is a need for population-based surveys on the pharmacoepidemiological aspects, quality of life and impact of socioeconomic factors in hand eczema. The aim of this cross-sectional study was to investigate these factors. A questionnaire-based nationwide survey of health was performed, including questions on hand eczema, use of pharmaceuticals and socioeconomic factors. Quality of life was estimated with the generic instrument Short Form 36 (SF-36). The questionnaire was sent to 7,985 persons (age range 18-84 years), response rate 61.1% (n = 4,875). The 1-year prevalence of hand eczema in the study population was 7.5%. In this group, quality of life was lower. All dimensions of SF-36 were affected, most markedly general health and those dimensions reporting on mental health. In the group with self-reported hand eczema, 51% reported using topical pharmaceuticals. Hand eczema was more common among women (9.1%, n = 2,630) than among men (5.6%, n = 2,245) and in the age group below 65 years (8.5%, n = 3,274) compared with those aged 65 years and over (4.3%, n = 1,151). This survey clearly demonstrates the impact of hand eczema on several dimensions of life and also highlights age, gender and socioeconomic differences.

Medication Exposure in Pregnancy Risk Evaluation Program (MEPREP).

PubMed

Davis, Robert L

2010-01-01

Knowledge about safe medication use during pregnancy is limited, yet about two of every three women take at least one prescription medication during pregnancy, furthermore, there is a lack of rigorous studies evaluating birth outcomes associated with in utero exposure to medications. The Medication Exposure in Pregnancy Risk Evaluation Program (MEPREP) is intended to provide a mechanism for collaborative pharmacoepidemiological research to address the safety of pharmaceutical product exposure during pregnancy, through the development of standardized data requirements and of the necessary data linkages of mother-infant pairs to conduct multi-site investigations. This presentation will describe the program, the types of data collected, and progress to date. The current MEPREP population includes female health plan members of 11 distinct health management entities within three research centres who have delivered an infant between January 1, 2001 and December 31, 2007, along with the administrative and birth certificate data on over one million children linked to mothers. There is information on all the medications those mothers took, as well as most of the outcomes of the babies. One of the benefits of this dataset is the information that could be investigated, such as birth weight, fetal growth, congenital anomalies, perinatal conditions, etc., against various demographics of the women in the dataset. The population size within the dataset suggests that various parameters could be studied with at least a modest degree of power.

A pharmaco-epidemiological study of antibacterial treatments and bacterial diseases in Norwegian aquaculture from 2011 to 2016.

PubMed

Lillehaug, Atle; Børnes, Christine; Grave, Kari

2018-05-07

The sales and prescription of antibacterials for use in Norwegian fish-farming according to diagnosis, fish species and production stage from 2011 to 2016 are analysed. The study is based on antibacterial sales data from wholesalers, pharmacies and feed mills and on prescription data obtained from a register of all prescriptions of antibacterials used in farmed fish. The results show that the fish-farming industry uses very small volumes of antibacterials. In 2016, a total of 212 kg were sold; the only antibacterial substances sold were florfenicol and oxolinic acid. The total amount corresponded to 0.16 mg kg-1 fish slaughtered, or to approximately 0.14% of the fish produced that year. The majority of prescriptions were for non-specific bacterial infections; as most common diseases are under control by vaccination. Most prescriptions for salmonid fish were during early production stages. However, due to higher biomasses of fish, the highest quantities of antibacterials were prescribed during the seawater production phase of Atlantic salmon Salmo salar. An increasing proportion of the prescriptions was for other species, including cleaner fish used for salmon lice control; in 2016 most prescriptions were for this fish category. Due to the negligible use of antibacterials in Norwegian aquaculture, in particular for on-growers, the risk of development of antimicrobial resistance and its transmission to humans through consumption of fish is considered negligible.

Modelling and simulation of biased agonism dynamics at a G protein-coupled receptor.

PubMed

Bridge, L J; Mead, J; Frattini, E; Winfield, I; Ladds, G

2018-04-07

Theoretical models of G protein-coupled receptor (GPCR) concentration-response relationships often assume an agonist producing a single functional response via a single active state of the receptor. These models have largely been analysed assuming steady-state conditions. There is now much experimental evidence to suggest that many GPCRs can exist in multiple receptor conformations and elicit numerous functional responses, with ligands having the potential to activate different signalling pathways to varying extents-a concept referred to as biased agonism, functional selectivity or pluri-dimensional efficacy. Moreover, recent experimental results indicate a clear possibility for time-dependent bias, whereby an agonist's bias with respect to different pathways may vary dynamically. Efforts towards understanding the implications of temporal bias by characterising and quantifying ligand effects on multiple pathways will clearly be aided by extending current equilibrium binding and biased activation models to include G protein activation dynamics. Here, we present a new model of time-dependent biased agonism, based on ordinary differential equations for multiple cubic ternary complex activation models with G protein cycle dynamics. This model allows simulation and analysis of multi-pathway activation bias dynamics at a single receptor for the first time, at the level of active G protein (α GTP ), towards the analysis of dynamic functional responses. The model is generally applicable to systems with N G G proteins and N* active receptor states. Numerical simulations for N G =N * =2 reveal new insights into the effects of system parameters (including cooperativities, and ligand and receptor concentrations) on bias dynamics, highlighting new phenomena including the dynamic inter-conversion of bias direction. Further, we fit this model to 'wet' experimental data for two competing G proteins (G i and G s ) that become activated upon stimulation of the adenosine A 1 receptor with adenosine derivative compounds. Finally, we show that our model can qualitatively describe the temporal dynamics of this competing G protein activation. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Using an Active-Optical Sensor to Develop an Optimal NDVI Dynamic Model for High-Yield Rice Production (Yangtze, China)

PubMed Central

Liu, Xiaojun; Ferguson, Richard B.; Zheng, Hengbiao; Cao, Qiang; Tian, Yongchao; Cao, Weixing; Zhu, Yan

2017-01-01

The successful development of an optimal canopy vegetation index dynamic model for obtaining higher yield can offer a technical approach for real-time and nondestructive diagnosis of rice (Oryza sativa L) growth and nitrogen (N) nutrition status. In this study, multiple rice cultivars and N treatments of experimental plots were carried out to obtain: normalized difference vegetation index (NDVI), leaf area index (LAI), above-ground dry matter (DM), and grain yield (GY) data. The quantitative relationships between NDVI and these growth indices (e.g., LAI, DM and GY) were analyzed, showing positive correlations. Using the normalized modeling method, an appropriate NDVI simulation model of rice was established based on the normalized NDVI (RNDVI) and relative accumulative growing degree days (RAGDD). The NDVI dynamic model for high-yield production in rice can be expressed by a double logistic model: RNDVI=(1+e−15.2829×(RAGDDi−0.1944))−1−(1+e−11.6517×(RAGDDi−1.0267))−1 (R2 = 0.8577**), which can be used to accurately predict canopy NDVI dynamic changes during the entire growth period. Considering variation among rice cultivars, we constructed two relative NDVI (RNDVI) dynamic models for Japonica and Indica rice types, with R2 reaching 0.8764** and 0.8874**, respectively. Furthermore, independent experimental data were used to validate the RNDVI dynamic models. The results showed that during the entire growth period, the accuracy (k), precision (R2), and standard deviation of RNDVI dynamic models for the Japonica and Indica cultivars were 0.9991, 1.0170; 0.9084**, 0.8030**; and 0.0232, 0.0170, respectively. These results indicated that RNDVI dynamic models could accurately reflect crop growth and predict dynamic changes in high-yield crop populations, providing a rapid approach for monitoring rice growth status. PMID:28338637

Using an Active-Optical Sensor to Develop an Optimal NDVI Dynamic Model for High-Yield Rice Production (Yangtze, China).

PubMed

Liu, Xiaojun; Ferguson, Richard B; Zheng, Hengbiao; Cao, Qiang; Tian, Yongchao; Cao, Weixing; Zhu, Yan

2017-03-24

The successful development of an optimal canopy vegetation index dynamic model for obtaining higher yield can offer a technical approach for real-time and nondestructive diagnosis of rice (Oryza sativa L) growth and nitrogen (N) nutrition status. In this study, multiple rice cultivars and N treatments of experimental plots were carried out to obtain: normalized difference vegetation index (NDVI), leaf area index (LAI), above-ground dry matter (DM), and grain yield (GY) data. The quantitative relationships between NDVI and these growth indices (e.g., LAI, DM and GY) were analyzed, showing positive correlations. Using the normalized modeling method, an appropriate NDVI simulation model of rice was established based on the normalized NDVI (RNDVI) and relative accumulative growing degree days (RAGDD). The NDVI dynamic model for high-yield production in rice can be expressed by a double logistic model: RNDVI = ( 1 + e - 15.2829 × ( R A G D D i - 0.1944 ) ) - 1 - ( 1 + e - 11.6517 × ( R A G D D i - 1.0267 ) ) - 1 (R2 = 0.8577**), which can be used to accurately predict canopy NDVI dynamic changes during the entire growth period. Considering variation among rice cultivars, we constructed two relative NDVI (RNDVI) dynamic models for Japonica and Indica rice types, with R2 reaching 0.8764** and 0.8874**, respectively. Furthermore, independent experimental data were used to validate the RNDVI dynamic models. The results showed that during the entire growth period, the accuracy (k), precision (R2), and standard deviation of RNDVI dynamic models for the Japonica and Indica cultivars were 0.9991, 1.0170; 0.9084**, 0.8030**; and 0.0232, 0.0170, respectively. These results indicated that RNDVI dynamic models could accurately reflect crop growth and predict dynamic changes in high-yield crop populations, providing a rapid approach for monitoring rice growth status.

LOGISTIC NETWORK REGRESSION FOR SCALABLE ANALYSIS OF NETWORKS WITH JOINT EDGE/VERTEX DYNAMICS

PubMed Central

Almquist, Zack W.; Butts, Carter T.

2015-01-01

Change in group size and composition has long been an important area of research in the social sciences. Similarly, interest in interaction dynamics has a long history in sociology and social psychology. However, the effects of endogenous group change on interaction dynamics are a surprisingly understudied area. One way to explore these relationships is through social network models. Network dynamics may be viewed as a process of change in the edge structure of a network, in the vertex set on which edges are defined, or in both simultaneously. Although early studies of such processes were primarily descriptive, recent work on this topic has increasingly turned to formal statistical models. Although showing great promise, many of these modern dynamic models are computationally intensive and scale very poorly in the size of the network under study and/or the number of time points considered. Likewise, currently used models focus on edge dynamics, with little support for endogenously changing vertex sets. Here, the authors show how an existing approach based on logistic network regression can be extended to serve as a highly scalable framework for modeling large networks with dynamic vertex sets. The authors place this approach within a general dynamic exponential family (exponential-family random graph modeling) context, clarifying the assumptions underlying the framework (and providing a clear path for extensions), and they show how model assessment methods for cross-sectional networks can be extended to the dynamic case. Finally, the authors illustrate this approach on a classic data set involving interactions among windsurfers on a California beach. PMID:26120218

Dynamical localization of coupled relativistic kicked rotors

NASA Astrophysics Data System (ADS)

Rozenbaum, Efim B.; Galitski, Victor

2017-02-01

A periodically driven rotor is a prototypical model that exhibits a transition to chaos in the classical regime and dynamical localization (related to Anderson localization) in the quantum regime. In a recent work [Phys. Rev. B 94, 085120 (2016), 10.1103/PhysRevB.94.085120], A. C. Keser et al. considered a many-body generalization of coupled quantum kicked rotors, and showed that in the special integrable linear case, dynamical localization survives interactions. By analogy with many-body localization, the phenomenon was dubbed dynamical many-body localization. In the present work, we study nonintegrable models of single and coupled quantum relativistic kicked rotors (QRKRs) that bridge the gap between the conventional quadratic rotors and the integrable linear models. For a single QRKR, we supplement the recent analysis of the angular-momentum-space dynamics with a study of the spin dynamics. Our analysis of two and three coupled QRKRs along with the proved localization in the many-body linear model indicate that dynamical localization exists in few-body systems. Moreover, the relation between QRKR and linear rotor models implies that dynamical many-body localization can exist in generic, nonintegrable many-body systems. And localization can generally result from a complicated interplay between Anderson mechanism and limiting integrability, since the many-body linear model is a high-angular-momentum limit of many-body QRKRs. We also analyze the dynamics of two coupled QRKRs in the highly unusual superballistic regime and find that the resonance conditions are relaxed due to interactions. Finally, we propose experimental realizations of the QRKR model in cold atoms in optical lattices.

LOGISTIC NETWORK REGRESSION FOR SCALABLE ANALYSIS OF NETWORKS WITH JOINT EDGE/VERTEX DYNAMICS.

PubMed

Almquist, Zack W; Butts, Carter T

2014-08-01

Change in group size and composition has long been an important area of research in the social sciences. Similarly, interest in interaction dynamics has a long history in sociology and social psychology. However, the effects of endogenous group change on interaction dynamics are a surprisingly understudied area. One way to explore these relationships is through social network models. Network dynamics may be viewed as a process of change in the edge structure of a network, in the vertex set on which edges are defined, or in both simultaneously. Although early studies of such processes were primarily descriptive, recent work on this topic has increasingly turned to formal statistical models. Although showing great promise, many of these modern dynamic models are computationally intensive and scale very poorly in the size of the network under study and/or the number of time points considered. Likewise, currently used models focus on edge dynamics, with little support for endogenously changing vertex sets. Here, the authors show how an existing approach based on logistic network regression can be extended to serve as a highly scalable framework for modeling large networks with dynamic vertex sets. The authors place this approach within a general dynamic exponential family (exponential-family random graph modeling) context, clarifying the assumptions underlying the framework (and providing a clear path for extensions), and they show how model assessment methods for cross-sectional networks can be extended to the dynamic case. Finally, the authors illustrate this approach on a classic data set involving interactions among windsurfers on a California beach.

A study of helicopter stability and control including blade dynamics

NASA Technical Reports Server (NTRS)

Zhao, Xin; Curtiss, H. C., Jr.

1988-01-01

A linearized model of rotorcraft dynamics has been developed through the use of symbolic automatic equation generating techniques. The dynamic model has been formulated in a unique way such that it can be used to analyze a variety of rotor/body coupling problems including a rotor mounted on a flexible shaft with a number of modes as well as free-flight stability and control characteristics. Direct comparison of the time response to longitudinal, lateral and directional control inputs at various trim conditions shows that the linear model yields good to very good correlation with flight test. In particular it is shown that a dynamic inflow model is essential to obtain good time response correlation, especially for the hover trim condition. It also is shown that the main rotor wake interaction with the tail rotor and fixed tail surfaces is a significant contributor to the response at translational flight trim conditions. A relatively simple model for the downwash and sidewash at the tail surfaces based on flat vortex wake theory is shown to produce good agreement. Then, the influence of rotor flap and lag dynamics on automatic control systems feedback gain limitations is investigated with the model. It is shown that the blade dynamics, especially lagging dynamics, can severly limit the useable values of the feedback gain for simple feedback control and that multivariable optimal control theory is a powerful tool to design high gain augmentation control system. The frequency-shaped optimal control design can offer much better flight dynamic characteristics and a stable margin for the feedback system without need to model the lagging dynamics.

Neural Population Dynamics during Reaching Are Better Explained by a Dynamical System than Representational Tuning

PubMed Central

Dann, Benjamin

2016-01-01

Recent models of movement generation in motor cortex have sought to explain neural activity not as a function of movement parameters, known as representational models, but as a dynamical system acting at the level of the population. Despite evidence supporting this framework, the evaluation of representational models and their integration with dynamical systems is incomplete in the literature. Using a representational velocity-tuning based simulation of center-out reaching, we show that incorporating variable latency offsets between neural activity and kinematics is sufficient to generate rotational dynamics at the level of neural populations, a phenomenon observed in motor cortex. However, we developed a covariance-matched permutation test (CMPT) that reassigns neural data between task conditions independently for each neuron while maintaining overall neuron-to-neuron relationships, revealing that rotations based on the representational model did not uniquely depend on the underlying condition structure. In contrast, rotations based on either a dynamical model or motor cortex data depend on this relationship, providing evidence that the dynamical model more readily explains motor cortex activity. Importantly, implementing a recurrent neural network we demonstrate that both representational tuning properties and rotational dynamics emerge, providing evidence that a dynamical system can reproduce previous findings of representational tuning. Finally, using motor cortex data in combination with the CMPT, we show that results based on small numbers of neurons or conditions should be interpreted cautiously, potentially informing future experimental design. Together, our findings reinforce the view that representational models lack the explanatory power to describe complex aspects of single neuron and population level activity. PMID:27814352

Neural Population Dynamics during Reaching Are Better Explained by a Dynamical System than Representational Tuning.

PubMed

Michaels, Jonathan A; Dann, Benjamin; Scherberger, Hansjörg

2016-11-01

Recent models of movement generation in motor cortex have sought to explain neural activity not as a function of movement parameters, known as representational models, but as a dynamical system acting at the level of the population. Despite evidence supporting this framework, the evaluation of representational models and their integration with dynamical systems is incomplete in the literature. Using a representational velocity-tuning based simulation of center-out reaching, we show that incorporating variable latency offsets between neural activity and kinematics is sufficient to generate rotational dynamics at the level of neural populations, a phenomenon observed in motor cortex. However, we developed a covariance-matched permutation test (CMPT) that reassigns neural data between task conditions independently for each neuron while maintaining overall neuron-to-neuron relationships, revealing that rotations based on the representational model did not uniquely depend on the underlying condition structure. In contrast, rotations based on either a dynamical model or motor cortex data depend on this relationship, providing evidence that the dynamical model more readily explains motor cortex activity. Importantly, implementing a recurrent neural network we demonstrate that both representational tuning properties and rotational dynamics emerge, providing evidence that a dynamical system can reproduce previous findings of representational tuning. Finally, using motor cortex data in combination with the CMPT, we show that results based on small numbers of neurons or conditions should be interpreted cautiously, potentially informing future experimental design. Together, our findings reinforce the view that representational models lack the explanatory power to describe complex aspects of single neuron and population level activity.

Bayesian dynamic regression models for interval censored survival data with application to children dental health.

PubMed

Wang, Xiaojing; Chen, Ming-Hui; Yan, Jun

2013-07-01

Cox models with time-varying coefficients offer great flexibility in capturing the temporal dynamics of covariate effects on event times, which could be hidden from a Cox proportional hazards model. Methodology development for varying coefficient Cox models, however, has been largely limited to right censored data; only limited work on interval censored data has been done. In most existing methods for varying coefficient models, analysts need to specify which covariate coefficients are time-varying and which are not at the time of fitting. We propose a dynamic Cox regression model for interval censored data in a Bayesian framework, where the coefficient curves are piecewise constant but the number of pieces and the jump points are covariate specific and estimated from the data. The model automatically determines the extent to which the temporal dynamics is needed for each covariate, resulting in smoother and more stable curve estimates. The posterior computation is carried out via an efficient reversible jump Markov chain Monte Carlo algorithm. Inference of each coefficient is based on an average of models with different number of pieces and jump points. A simulation study with three covariates, each with a coefficient of different degree in temporal dynamics, confirmed that the dynamic model is preferred to the existing time-varying model in terms of model comparison criteria through conditional predictive ordinate. When applied to a dental health data of children with age between 7 and 12 years, the dynamic model reveals that the relative risk of emergence of permanent tooth 24 between children with and without an infected primary predecessor is the highest at around age 7.5, and that it gradually reduces to one after age 11. These findings were not seen from the existing studies with Cox proportional hazards models.

Mastodon

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coleman, Justin Leigh; Veeraraghavan, Swetha; Bolisetti, Chandrakanth

MASTODON has the capability to model stochastic nonlinear soil-structure interaction (NLSSI) in a dynamic probabilistic risk assessment framework. The NLSSI simulations include structural dynamics, time integration, dynamic porous media flow, nonlinear hysteretic soil constitutive models, geometric nonlinearities (gapping, sliding, and uplift). MASTODON is also the MOOSE based master application for dynamic PRA of external hazards.

The life of a meander bend: Connecting shape and dynamics via analysis of a numerical model

NASA Astrophysics Data System (ADS)

Schwenk, Jon; Lanzoni, Stefano; Foufoula-Georgiou, Efi

2015-04-01

Analysis of bend-scale meandering river dynamics is a problem of theoretical and practical interest. This work introduces a method for extracting and analyzing the history of individual meander bends from inception until cutoff (called "atoms") by tracking backward through time the set of two cutoff nodes in numerical meander migration models. Application of this method to a simplified yet physically based model provides access to previously unavailable bend-scale meander dynamics over long times and at high temporal resolutions. We find that before cutoffs, the intrinsic model dynamics invariably simulate a prototypical cutoff atom shape we dub simple. Once perturbations from cutoffs occur, two other archetypal cutoff planform shapes emerge called long and round that are distinguished by a stretching along their long and perpendicular axes, respectively. Three measures of meander migration—growth rate, average migration rate, and centroid migration rate—are introduced to capture the dynamic lives of individual bends and reveal that similar cutoff atom geometries share similar dynamic histories. Specifically, through the lens of the three shape types, simples are seen to have the highest growth and average migration rates, followed by rounds, and finally longs. Using the maximum average migration rate as a metric describing an atom's dynamic past, we show a strong connection between it and two metrics of cutoff geometry. This result suggests both that early formative dynamics may be inferred from static cutoff planforms and that there exists a critical period early in a meander bend's life when its dynamic trajectory is most sensitive to cutoff perturbations. An example of how these results could be applied to Mississippi River oxbow lakes with unknown historic dynamics is shown. The results characterize the underlying model and provide a framework for comparisons against more complex models and observed dynamics.

Fractional-order in a macroeconomic dynamic model

NASA Astrophysics Data System (ADS)

David, S. A.; Quintino, D. D.; Soliani, J.

2013-10-01

In this paper, we applied the Riemann-Liouville approach in order to realize the numerical simulations to a set of equations that represent a fractional-order macroeconomic dynamic model. It is a generalization of a dynamic model recently reported in the literature. The aforementioned equations have been simulated for several cases involving integer and non-integer order analysis, with some different values to fractional order. The time histories and the phase diagrams have been plotted to visualize the effect of fractional order approach. The new contribution of this work arises from the fact that the macroeconomic dynamic model proposed here involves the public sector deficit equation, which renders the model more realistic and complete when compared with the ones encountered in the literature. The results reveal that the fractional-order macroeconomic model can exhibit a real reasonable behavior to macroeconomics systems and might offer greater insights towards the understanding of these complex dynamic systems.

[Study on the dynamic model with supercritical CO2 fluid extracting the lipophilic components in Panax notoginseng].

PubMed

Duan, Xian-Chun; Wang, Yong-Zhong; Zhang, Jun-Ru; Luo, Huan; Zhang, Heng; Xia, Lun-Zhu

2011-08-01

To establish a dynamics model for extracting the lipophilic components in Panax notoginseng with supercritical carbon dioxide (CO2). Based on the theory of counter-flow mass transfer and the molecular mass transfer between the material and the supercritical CO2 fluid under differential mass-conservation equation, a dynamics model was established and computed to compare forecasting result with the experiment process. A dynamics model has been established for supercritical CO2 to extract the lipophilic components in Panax notoginseng, the computed result of this model was consistent with the experiment process basically. The supercritical fluid extract dynamics model established in this research can expound the mechanism in the extract process of which lipophilic components of Panax notoginseng dissolve the mass transfer and is tallied with the actual extract process. This provides certain instruction for the supercritical CO2 fluid extract' s industrialization enlargement.

NASTRAN analysis of the 1/8-scale space shuttle dynamic model

NASA Technical Reports Server (NTRS)

Bernstein, M.; Mason, P. W.; Zalesak, J.; Gregory, D. J.; Levy, A.

1973-01-01

The space shuttle configuration has more complex structural dynamic characteristics than previous launch vehicles primarily because of the high model density at low frequencies and the high degree of coupling between the lateral and longitudinal motions. An accurate analytical representation of these characteristics is a primary means for treating structural dynamics problems during the design phase of the shuttle program. The 1/8-scale model program was developed to explore the adequacy of available analytical modeling technology and to provide the means for investigating problems which are more readily treated experimentally. The basic objectives of the 1/8-scale model program are: (1) to provide early verification of analytical modeling procedures on a shuttle-like structure, (2) to demonstrate important vehicle dynamic characteristics of a typical shuttle design, (3) to disclose any previously unanticipated structural dynamic characteristics, and (4) to provide for development and demonstration of cost effective prototype testing procedures.

The Living Cell as a Multi-agent Organisation: A Compositional Organisation Model of Intracellular Dynamics

NASA Astrophysics Data System (ADS)

Jonker, C. M.; Snoep, J. L.; Treur, J.; Westerhoff, H. V.; Wijngaards, W. C. A.

Within the areas of Computational Organisation Theory and Artificial Intelligence, techniques have been developed to simulate and analyse dynamics within organisations in society. Usually these modelling techniques are applied to factories and to the internal organisation of their process flows, thus obtaining models of complex organisations at various levels of aggregation. The dynamics in living cells are often interpreted in terms of well-organised processes, a bacterium being considered a (micro)factory. This suggests that organisation modelling techniques may also benefit their analysis. Using the example of Escherichia coli it is shown how indeed agent-based organisational modelling techniques can be used to simulate and analyse E.coli's intracellular dynamics. Exploiting the abstraction levels entailed by this perspective, a concise model is obtained that is readily simulated and analysed at the various levels of aggregation, yet shows the cell's essential dynamic patterns.

Molecular Dynamics implementation of BN2D or 'Mercedes Benz' water model

NASA Astrophysics Data System (ADS)

Scukins, Arturs; Bardik, Vitaliy; Pavlov, Evgen; Nerukh, Dmitry

2015-05-01

Two-dimensional 'Mercedes Benz' (MB) or BN2D water model (Naim, 1971) is implemented in Molecular Dynamics. It is known that the MB model can capture abnormal properties of real water (high heat capacity, minima of pressure and isothermal compressibility, negative thermal expansion coefficient) (Silverstein et al., 1998). In this work formulas for calculating the thermodynamic, structural and dynamic properties in microcanonical (NVE) and isothermal-isobaric (NPT) ensembles for the model from Molecular Dynamics simulation are derived and verified against known Monte Carlo results. The convergence of the thermodynamic properties and the system's numerical stability are investigated. The results qualitatively reproduce the peculiarities of real water making the model a visually convenient tool that also requires less computational resources, thus allowing simulations of large (hydrodynamic scale) molecular systems. We provide the open source code written in C/C++ for the BN2D water model implementation using Molecular Dynamics.

Equivalent dynamic model of DEMES rotary joint

NASA Astrophysics Data System (ADS)

Zhao, Jianwen; Wang, Shu; Xing, Zhiguang; McCoul, David; Niu, Junyang; Huang, Bo; Liu, Liwu; Leng, Jinsong

2016-07-01

The dielectric elastomer minimum energy structure (DEMES) can realize large angular deformations by a small voltage-induced strain of the dielectric elastomer (DE), so it is a suitable candidate to make a rotary joint for a soft robot. Dynamic analysis is necessary for some applications, but the dynamic response of DEMESs is difficult to model because of the complicated morphology and viscoelasticity of the DE film. In this paper, a method composed of theoretical analysis and experimental measurement is presented to model the dynamic response of a DEMES rotary joint under an alternating voltage. Based on measurements of equivalent driving force and damping of the DEMES, the model can be derived. Some experiments were carried out to validate the equivalent dynamic model. The maximum angle error between model and experiment is greater than ten degrees, but it is acceptable to predict angular velocity of the DEMES, therefore, it can be applied in feedforward-feedback compound control.

Methods for modeling cytoskeletal and DNA filaments

NASA Astrophysics Data System (ADS)

Andrews, Steven S.

2014-02-01

This review summarizes the models that researchers use to represent the conformations and dynamics of cytoskeletal and DNA filaments. It focuses on models that address individual filaments in continuous space. Conformation models include the freely jointed, Gaussian, angle-biased chain (ABC), and wormlike chain (WLC) models, of which the first three bend at discrete joints and the last bends continuously. Predictions from the WLC model generally agree well with experiment. Dynamics models include the Rouse, Zimm, stiff rod, dynamic WLC, and reptation models, of which the first four apply to isolated filaments and the last to entangled filaments. Experiments show that the dynamic WLC and reptation models are most accurate. They also show that biological filaments typically experience strong hydrodynamic coupling and/or constrained motion. Computer simulation methods that address filament dynamics typically compute filament segment velocities from local forces using the Langevin equation and then integrate these velocities with explicit or implicit methods; the former are more versatile and the latter are more efficient. Much remains to be discovered in biological filament modeling. In particular, filament dynamics in living cells are not well understood, and current computational methods are too slow and not sufficiently versatile. Although primarily a review, this paper also presents new statistical calculations for the ABC and WLC models. Additionally, it corrects several discrepancies in the literature about bending and torsional persistence length definitions, and their relations to flexural and torsional rigidities.

Studies on the population dynamics of a rumor-spreading model in online social networks

NASA Astrophysics Data System (ADS)

Dong, Suyalatu; Fan, Feng-Hua; Huang, Yong-Chang

2018-02-01

This paper sets up a rumor spreading model in online social networks based on the European fox rabies SIR model. The model considers the impact of changing number of online social network users, combines the transmission dynamics to set up a population dynamics of rumor spreading model in online social networks. Simulation is carried out on online social network, and results show that the new rumor spreading model is in accordance with the real propagation characteristics in online social networks.

Plate falling in a fluid: Regular and chaotic dynamics of finite-dimensional models

NASA Astrophysics Data System (ADS)

Kuznetsov, Sergey P.

2015-05-01

Results are reviewed concerning the planar problem of a plate falling in a resisting medium studied with models based on ordinary differential equations for a small number of dynamical variables. A unified model is introduced to conduct a comparative analysis of the dynamical behaviors of models of Kozlov, Tanabe-Kaneko, Belmonte-Eisenberg-Moses and Andersen-Pesavento-Wang using common dimensionless variables and parameters. It is shown that the overall structure of the parameter spaces for the different models manifests certain similarities caused by the same inherent symmetry and by the universal nature of the phenomena involved in nonlinear dynamics (fixed points, limit cycles, attractors, and bifurcations).

Dual-Schemata Model

NASA Astrophysics Data System (ADS)

Taniguchi, Tadahiro; Sawaragi, Tetsuo

In this paper, a new machine-learning method, called Dual-Schemata model, is presented. Dual-Schemata model is a kind of self-organizational machine learning methods for an autonomous robot interacting with an unknown dynamical environment. This is based on Piaget's Schema model, that is a classical psychological model to explain memory and cognitive development of human beings. Our Dual-Schemata model is developed as a computational model of Piaget's Schema model, especially focusing on sensori-motor developing period. This developmental process is characterized by a couple of two mutually-interacting dynamics; one is a dynamics formed by assimilation and accommodation, and the other dynamics is formed by equilibration and differentiation. By these dynamics schema system enables an agent to act well in a real world. This schema's differentiation process corresponds to a symbol formation process occurring within an autonomous agent when it interacts with an unknown, dynamically changing environment. Experiment results obtained from an autonomous facial robot in which our model is embedded are presented; an autonomous facial robot becomes able to chase a ball moving in various ways without any rewards nor teaching signals from outside. Moreover, emergence of concepts on the target movements within a robot is shown and discussed in terms of fuzzy logics on set-subset inclusive relationships.

Dynamic phase transitions of the Blume-Emery-Griffiths model under an oscillating external magnetic field by the path probability method

NASA Astrophysics Data System (ADS)

Ertaş, Mehmet; Keskin, Mustafa

2015-03-01

By using the path probability method (PPM) with point distribution, we study the dynamic phase transitions (DPTs) in the Blume-Emery-Griffiths (BEG) model under an oscillating external magnetic field. The phases in the model are obtained by solving the dynamic equations for the average order parameters and a disordered phase, ordered phase and four mixed phases are found. We also investigate the thermal behavior of the dynamic order parameters to analyze the nature dynamic transitions as well as to obtain the DPT temperatures. The dynamic phase diagrams are presented in three different planes in which exhibit the dynamic tricritical point, double critical end point, critical end point, quadrupole point, triple point as well as the reentrant behavior, strongly depending on the values of the system parameters. We compare and discuss the dynamic phase diagrams with dynamic phase diagrams that were obtained within the Glauber-type stochastic dynamics based on the mean-field theory.

Single-trial dynamics of motor cortex and their applications to brain-machine interfaces

PubMed Central

Kao, Jonathan C.; Nuyujukian, Paul; Ryu, Stephen I.; Churchland, Mark M.; Cunningham, John P.; Shenoy, Krishna V.

2015-01-01

Increasing evidence suggests that neural population responses have their own internal drive, or dynamics, that describe how the neural population evolves through time. An important prediction of neural dynamical models is that previously observed neural activity is informative of noisy yet-to-be-observed activity on single-trials, and may thus have a denoising effect. To investigate this prediction, we built and characterized dynamical models of single-trial motor cortical activity. We find these models capture salient dynamical features of the neural population and are informative of future neural activity on single trials. To assess how neural dynamics may beneficially denoise single-trial neural activity, we incorporate neural dynamics into a brain–machine interface (BMI). In online experiments, we find that a neural dynamical BMI achieves substantially higher performance than its non-dynamical counterpart. These results provide evidence that neural dynamics beneficially inform the temporal evolution of neural activity on single trials and may directly impact the performance of BMIs. PMID:26220660

Modelling hydrologic responses in a small forested catchment (Panola Mountain, Georgia, USA): A comparison of the original and a new dynamic TOPMODEL

USGS Publications Warehouse

Peters, N.E.; Freer, J.; Beven, K.

2003-01-01

Preliminary modelling results for a new version of the rainfall-runoff model TOPMODEL, dynamic TOPMODEL, are compared with those of the original TOPMODEL formulation for predicting streamflow at the Panola Mountain Research Watershed, Georgia. Dynamic TOPMODEL uses a kinematic wave routing of subsurface flow, which allows for dynamically variable upslope contributing areas, while retaining the concept of hydrological similarity to increase computational efficiency. Model performance in predicting discharge was assessed for the original TOPMODEL and for one landscape unit (LU) and three LU versions of the dynamic TOPMODEL (a bare rock area, hillslope with regolith <1 m, and a riparian zone with regolith ???5 m). All simulations used a 30 min time step for each of three water years. Each 1-LU model underpredicted the peak streamflow, and generally overpredicted recession streamflow during wet periods and underpredicted during dry periods. The difference between predicted recession streamflow generally was less for the dynamic TOPMODEL and smallest for the 3-LU model. Bayesian combination of results for different water years within the GLUE methodology left no behavioural original or 1-LU dynamic models and only 168 (of 96 000 sample parameter sets) for the 3-LU model. The efficiency for the streamflow prediction of the best 3-LU model was 0.83 for an individual year, but the results suggest that further improvements could be made. ?? 2003 John Wiley & Sons, Ltd.

From terrestrial to aquatic fluxes: Integrating stream dynamics within a dynamic global vegetation modeling framework

NASA Astrophysics Data System (ADS)

Hoy, Jerad; Poulter, Benjamin; Emmett, Kristen; Cross, Molly; Al-Chokhachy, Robert; Maneta, Marco

2016-04-01

Integrated terrestrial ecosystem models simulate the dynamics and feedbacks between climate, vegetation, disturbance, and hydrology and are used to better understand biogeography and biogeochemical cycles. Extending dynamic vegetation models to the aquatic interface requires coupling surface and sub-surface runoff to catchment routing schemes and has the potential to enhance how researchers and managers investigate how changes in the environment might impact the availability of water resources for human and natural systems. In an effort towards creating such a coupled model, we developed catchment-based hydrologic routing and stream temperature model to pair with LPJ-GUESS, a dynamic global vegetation model. LPJ-GUESS simulates detailed stand-level vegetation dynamics such as growth, carbon allocation, and mortality, as well as various physical and hydrologic processes such as canopy interception and through-fall, and can be applied at small spatial scales, i.e., 1 km. We demonstrate how the coupled model can be used to investigate the effects of transient vegetation dynamics and CO2 on seasonal and annual stream discharge and temperature regimes. As a direct management application, we extend the modeling framework to predict habitat suitability for fish habitat within the Greater Yellowstone Ecosystem, a 200,000 km2 region that provides critical habitat for a range of aquatic species. The model is used to evaluate, quantitatively, the effects of management practices aimed to enhance hydrologic resilience to climate change, and benefits for water storage and fish habitat in the coming century.

Nonlinear electromechanical modelling and dynamical behavior analysis of a satellite reaction wheel

NASA Astrophysics Data System (ADS)

Aghalari, Alireza; Shahravi, Morteza

2017-12-01

The present research addresses the satellite reaction wheel (RW) nonlinear electromechanical coupling dynamics including dynamic eccentricity of brushless dc (BLDC) motor and gyroscopic effects, as well as dry friction of shaft-bearing joints (relative small slip) and bearing friction. In contrast to other studies, the rotational velocity of the flywheel is considered to be controllable, so it is possible to study the reaction wheel dynamical behavior in acceleration stages. The RW is modeled as a three-phases BLDC motor as well as flywheel with unbalances on a rigid shaft and flexible bearings. Improved Lagrangian dynamics for electromechanical systems is used to obtain the mathematical model of the system. The developed model can properly describe electromechanical nonlinear coupled dynamical behavior of the satellite RW. Numerical simulations show the effectiveness of the presented approach.

Dynamic Evolution Model Based on Social Network Services

NASA Astrophysics Data System (ADS)

Xiong, Xi; Gou, Zhi-Jian; Zhang, Shi-Bin; Zhao, Wen

2013-11-01

Based on the analysis of evolutionary characteristics of public opinion in social networking services (SNS), in the paper we propose a dynamic evolution model, in which opinions are coupled with topology. This model shows the clustering phenomenon of opinions in dynamic network evolution. The simulation results show that the model can fit the data from a social network site. The dynamic evolution of networks accelerates the opinion, separation and aggregation. The scale and the number of clusters are influenced by confidence limit and rewiring probability. Dynamic changes of the topology reduce the number of isolated nodes, while the increased confidence limit allows nodes to communicate more sufficiently. The two effects make the distribution of opinion more neutral. The dynamic evolution of networks generates central clusters with high connectivity and high betweenness, which make it difficult to control public opinions in SNS.

Dynamics of the diffusive DM-DE interaction – Dynamical system approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haba, Zbigniew; Stachowski, Aleksander; Szydłowski, Marek, E-mail: zhab@ift.uni.wroc.pl, E-mail: aleksander.stachowski@uj.edu.pl, E-mail: marek.szydlowski@uj.edu.pl

We discuss dynamics of a model of an energy transfer between dark energy (DE) and dark matter (DM) . The energy transfer is determined by a non-conservation law resulting from a diffusion of dark matter in an environment of dark energy. The relativistic invariance defines the diffusion in a unique way. The system can contain baryonic matter and radiation which do not interact with the dark sector. We treat the Friedman equation and the conservation laws as a closed dynamical system. The dynamics of the model is examined using the dynamical systems methods for demonstration how solutions depend on initialmore » conditions. We also fit the model parameters using astronomical observation: SNIa, H ( z ), BAO and Alcock-Paczynski test. We show that the model with diffuse DM-DE is consistent with the data.« less

Influence of polygonal wear of railway wheels on the wheel set axle stress

NASA Astrophysics Data System (ADS)

Wu, Xingwen; Chi, Maoru; Wu, Pingbo

2015-11-01

The coupled vehicle/track dynamic model with the flexible wheel set was developed to investigate the effects of polygonal wear on the dynamic stresses of the wheel set axle. In the model, the railway vehicle was modelled by the rigid multibody dynamics. The wheel set was established by the finite element method to analyse the high-frequency oscillation and dynamic stress of wheel set axle induced by the polygonal wear based on the modal stress recovery method. The slab track model was taken into account in which the rail was described by the Timoshenko beam and the three-dimensional solid finite element was employed to establish the concrete slab. Furthermore, the modal superposition method was adopted to calculate the dynamic response of the track. The wheel/rail normal forces and the tangent forces were, respectively, determined by the Hertz nonlinear contact theory and the Shen-Hedrick-Elkins model. Using the coupled vehicle/track dynamic model, the dynamic stresses of wheel set axle with consideration of the ideal polygonal wear and measured polygonal wear were investigated. The results show that the amplitude of wheel/rail normal forces and the dynamic stress of wheel set axle increase as the vehicle speeds rise. Moreover, the impact loads induced by the polygonal wear could excite the resonance of wheel set axle. In the resonance region, the amplitude of the dynamic stress for the wheel set axle would increase considerably comparing with the normal conditions.

Reduction of Tunnel Dynamics at the National Transonic Facility (Invited)

NASA Technical Reports Server (NTRS)

Kilgore, W. A.; Balakrishna, S.; Butler, D. H.

2001-01-01

This paper describes the results of recent efforts to reduce the tunnel dynamics at the National Transonic Facility. The results presented describe the findings of an extensive data analysis, the proposed solutions to reduce dynamics and the results of implementing these solutions. These results show a 90% reduction in the dynamics around the model support structure and a small impact on reducing model dynamics. Also presented are several continuing efforts to further reduce dynamics.

Propulsive Reaction Control System Model

NASA Technical Reports Server (NTRS)

Brugarolas, Paul; Phan, Linh H.; Serricchio, Frederick; San Martin, Alejandro M.

2011-01-01

This software models a propulsive reaction control system (RCS) for guidance, navigation, and control simulation purposes. The model includes the drive electronics, the electromechanical valve dynamics, the combustion dynamics, and thrust. This innovation follows the Mars Science Laboratory entry reaction control system design, and has been created to meet the Mars Science Laboratory (MSL) entry, descent, and landing simulation needs. It has been built to be plug-and-play on multiple MSL testbeds [analysis, Monte Carlo, flight software development, hardware-in-the-loop, and ATLO (assembly, test and launch operations) testbeds]. This RCS model is a C language program. It contains two main functions: the RCS electronics model function that models the RCS FPGA (field-programmable-gate-array) processing and commanding of the RCS valve, and the RCS dynamic model function that models the valve and combustion dynamics. In addition, this software provides support functions to initialize the model states, set parameters, access model telemetry, and access calculated thruster forces.

Physical properties of the benchmark models program supercritical wing

NASA Technical Reports Server (NTRS)

Dansberry, Bryan E.; Durham, Michael H.; Bennett, Robert M.; Turnock, David L.; Silva, Walter A.; Rivera, Jose A., Jr.

1993-01-01

The goal of the Benchmark Models Program is to provide data useful in the development and evaluation of aeroelastic computational fluid dynamics (CFD) codes. To that end, a series of three similar wing models are being flutter tested in the Langley Transonic Dynamics Tunnel. These models are designed to simultaneously acquire model response data and unsteady surface pressure data during wing flutter conditions. The supercritical wing is the second model of this series. It is a rigid semispan model with a rectangular planform and a NASA SC(2)-0414 supercritical airfoil shape. The supercritical wing model was flutter tested on a flexible mount, called the Pitch and Plunge Apparatus, that provides a well-defined, two-degree-of-freedom dynamic system. The supercritical wing model and associated flutter test apparatus is described and experimentally determined wind-off structural dynamic characteristics of the combined rigid model and flexible mount system are included.

Agent-based model for rural-urban migration: A dynamic consideration

NASA Astrophysics Data System (ADS)

Cai, Ning; Ma, Hai-Ying; Khan, M. Junaid

2015-10-01

This paper develops a dynamic agent-based model for rural-urban migration, based on the previous relevant works. The model conforms to the typical dynamic linear multi-agent systems model concerned extensively in systems science, in which the communication network is formulated as a digraph. Simulations reveal that consensus of certain variable could be harmful to the overall stability and should be avoided.

Modeling Gas Dynamics in California Sea Lions

DTIC Science & Technology

2015-09-30

W. and Fahlman, A. (2009). Could beaked whales get the bends?. Effect of diving behaviour and physiology on modelled gas exchange for three species...1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Modeling Gas Dynamics in California Sea Lions Andreas...to update a current gas dynamics model with recently acquired data for respiratory compliance (P-V), and body compartment size estimates in

Time scale of dynamic heterogeneity in model ionic liquids and its relation to static length scale and charge distribution.

PubMed

Park, Sang-Won; Kim, Soree; Jung, YounJoon

2015-11-21

We study how dynamic heterogeneity in ionic liquids is affected by the length scale of structural relaxation and the ionic charge distribution by the molecular dynamics simulations performed on two differently charged models of ionic liquid and their uncharged counterpart. In one model of ionic liquid, the charge distribution in the cation is asymmetric, and in the other it is symmetric, while their neutral counterpart has no charge with the ions. It is found that all the models display heterogeneous dynamics, exhibiting subdiffusive dynamics and a nonexponential decay of structural relaxation. We investigate the lifetime of dynamic heterogeneity, τ(dh), in these systems by calculating the three-time correlation functions to find that τ(dh) has in general a power-law behavior with respect to the structural relaxation time, τ(α), i.e., τ(dh) ∝ τ(α)(ζ(dh)). Although the dynamics of the asymmetric-charge model is seemingly more heterogeneous than that of the symmetric-charge model, the exponent is found to be similar, ζ(dh) ≈ 1.2, for all the models studied in this work. The same scaling relation is found regardless of interactions, i.e., with or without Coulomb interaction, and it holds even when the length scale of structural relaxation is long enough to become the Fickian diffusion. This fact indicates that τ(dh) is a distinctive time scale from τ(α), and the dynamic heterogeneity is mainly affected by the short-range interaction and the molecular structure.

System Dynamics Modeling of Transboundary Systems: The Bear River Basin Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gerald Sehlke; Jake Jacobson

2005-09-01

System dynamics is a computer-aided approach to evaluating the interrelationships of different components and activities within complex systems. Recently, system dynamics models have been developed in areas such as policy design, biological and medical modeling, energy and the environmental analysis, and in various other areas in the natural and social sciences. The Idaho National Engineering and Environmental Laboratory, a multi-purpose national laboratory managed by the Department of Energy, has developed a systems dynamics model in order to evaluate its utility for modeling large complex hydrological systems. We modeled the Bear River Basin, a transboundary basin that includes portions of Idaho,more » Utah and Wyoming. We found that system dynamics modeling is very useful for integrating surface water and groundwater data and for simulating the interactions between these sources within a given basin. In addition, we also found system dynamics modeling is useful for integrating complex hydrologic data with other information (e.g., policy, regulatory and management criteria) to produce a decision support system. Such decision support systems can allow managers and stakeholders to better visualize the key hydrologic elements and management constraints in the basin, which enables them to better understand the system via the simulation of multiple “what-if” scenarios. Although system dynamics models can be developed to conduct traditional hydraulic/hydrologic surface water or groundwater modeling, we believe that their strength lies in their ability to quickly evaluate trends and cause–effect relationships in large-scale hydrological systems; for integrating disparate data; for incorporating output from traditional hydraulic/hydrologic models; and for integration of interdisciplinary data, information and criteria to support better management decisions.« less

System Dynamics Modeling of Transboundary Systems: the Bear River Basin Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gerald Sehlke; Jacob J. Jacobson

2005-09-01

System dynamics is a computer-aided approach to evaluating the interrelationships of different components and activities within complex systems. Recently, system dynamics models have been developed in areas such as policy design, biological and medical modeling, energy and the environmental analysis, and in various other areas in the natural and social sciences. The Idaho National Engineering and Environmental Laboratory, a multi-purpose national laboratory managed by the Department of Energy, has developed a systems dynamics model in order to evaluate its utility for modeling large complex hydrological systems. We modeled the Bear River Basin, a transboundary basin that includes portions of Idaho,more » Utah and Wyoming. We found that system dynamics modeling is very useful for integrating surface water and ground water data and for simulating the interactions between these sources within a given basin. In addition, we also found system dynamics modeling is useful for integrating complex hydrologic data with other information (e.g., policy, regulatory and management criteria) to produce a decision support system. Such decision support systems can allow managers and stakeholders to better visualize the key hydrologic elements and management constraints in the basin, which enables them to better understand the system via the simulation of multiple “what-if” scenarios. Although system dynamics models can be developed to conduct traditional hydraulic/hydrologic surface water or ground water modeling, we believe that their strength lies in their ability to quickly evaluate trends and cause–effect relationships in large-scale hydrological systems; for integrating disparate data; for incorporating output from traditional hydraulic/hydrologic models; and for integration of interdisciplinary data, information and criteria to support better management decisions.« less

BEEHAVE: a systems model of honeybee colony dynamics and foraging to explore multifactorial causes of colony failure

PubMed Central

Becher, Matthias A; Grimm, Volker; Thorbek, Pernille; Horn, Juliane; Kennedy, Peter J; Osborne, Juliet L

2014-01-01

A notable increase in failure of managed European honeybee Apis mellifera L. colonies has been reported in various regions in recent years. Although the underlying causes remain unclear, it is likely that a combination of stressors act together, particularly varroa mites and other pathogens, forage availability and potentially pesticides. It is experimentally challenging to address causality at the colony scale when multiple factors interact. In silico experiments offer a fast and cost-effective way to begin to address these challenges and inform experiments. However, none of the published bee models combine colony dynamics with foraging patterns and varroa dynamics. We have developed a honeybee model, BEEHAVE, which integrates colony dynamics, population dynamics of the varroa mite, epidemiology of varroa-transmitted viruses and allows foragers in an agent-based foraging model to collect food from a representation of a spatially explicit landscape. We describe the model, which is freely available online (www.beehave-model.net). Extensive sensitivity analyses and tests illustrate the model's robustness and realism. Simulation experiments with various combinations of stressors demonstrate, in simplified landscape settings, the model's potential: predicting colony dynamics and potential losses with and without varroa mites under different foraging conditions and under pesticide application. We also show how mitigation measures can be tested. Synthesis and applications. BEEHAVE offers a valuable tool for researchers to design and focus field experiments, for regulators to explore the relative importance of stressors to devise management and policy advice and for beekeepers to understand and predict varroa dynamics and effects of management interventions. We expect that scientists and stakeholders will find a variety of applications for BEEHAVE, stimulating further model development and the possible inclusion of other stressors of potential importance to honeybee colony dynamics. PMID:25598549

BEEHAVE: a systems model of honeybee colony dynamics and foraging to explore multifactorial causes of colony failure.

PubMed

Becher, Matthias A; Grimm, Volker; Thorbek, Pernille; Horn, Juliane; Kennedy, Peter J; Osborne, Juliet L

2014-04-01

A notable increase in failure of managed European honeybee Apis mellifera L. colonies has been reported in various regions in recent years. Although the underlying causes remain unclear, it is likely that a combination of stressors act together, particularly varroa mites and other pathogens, forage availability and potentially pesticides. It is experimentally challenging to address causality at the colony scale when multiple factors interact. In silico experiments offer a fast and cost-effective way to begin to address these challenges and inform experiments. However, none of the published bee models combine colony dynamics with foraging patterns and varroa dynamics.We have developed a honeybee model, BEEHAVE, which integrates colony dynamics, population dynamics of the varroa mite, epidemiology of varroa-transmitted viruses and allows foragers in an agent-based foraging model to collect food from a representation of a spatially explicit landscape.We describe the model, which is freely available online (www.beehave-model.net). Extensive sensitivity analyses and tests illustrate the model's robustness and realism. Simulation experiments with various combinations of stressors demonstrate, in simplified landscape settings, the model's potential: predicting colony dynamics and potential losses with and without varroa mites under different foraging conditions and under pesticide application. We also show how mitigation measures can be tested. Synthesis and applications . BEEHAVE offers a valuable tool for researchers to design and focus field experiments, for regulators to explore the relative importance of stressors to devise management and policy advice and for beekeepers to understand and predict varroa dynamics and effects of management interventions. We expect that scientists and stakeholders will find a variety of applications for BEEHAVE, stimulating further model development and the possible inclusion of other stressors of potential importance to honeybee colony dynamics.

Rényi information flow in the Ising model with single-spin dynamics.

PubMed

Deng, Zehui; Wu, Jinshan; Guo, Wenan

2014-12-01

The n-index Rényi mutual information and transfer entropies for the two-dimensional kinetic Ising model with arbitrary single-spin dynamics in the thermodynamic limit are derived as functions of ensemble averages of observables and spin-flip probabilities. Cluster Monte Carlo algorithms with different dynamics from the single-spin dynamics are thus applicable to estimate the transfer entropies. By means of Monte Carlo simulations with the Wolff algorithm, we calculate the information flows in the Ising model with the Metropolis dynamics and the Glauber dynamics, respectively. We find that not only the global Rényi transfer entropy, but also the pairwise Rényi transfer entropy, peaks in the disorder phase.

Review of Dynamic Modeling and Simulation of Large Scale Belt Conveyor System

NASA Astrophysics Data System (ADS)

He, Qing; Li, Hong

Belt conveyor is one of the most important devices to transport bulk-solid material for long distance. Dynamic analysis is the key to decide whether the design is rational in technique, safe and reliable in running, feasible in economy. It is very important to study dynamic properties, improve efficiency and productivity, guarantee conveyor safe, reliable and stable running. The dynamic researches and applications of large scale belt conveyor are discussed. The main research topics, the state-of-the-art of dynamic researches on belt conveyor are analyzed. The main future works focus on dynamic analysis, modeling and simulation of main components and whole system, nonlinear modeling, simulation and vibration analysis of large scale conveyor system.

Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes

PubMed Central

Bai, Cong; Peng, Zhong-Ren; Lu, Qing-Chang; Sun, Jian

2015-01-01

Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes. PMID:26294903

Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes.

PubMed

Bai, Cong; Peng, Zhong-Ren; Lu, Qing-Chang; Sun, Jian

2015-01-01

Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes.

On the dynamics of a generalized predator-prey system with Z-type control.

PubMed

Lacitignola, Deborah; Diele, Fasma; Marangi, Carmela; Provenzale, Antonello

2016-10-01

We apply the Z-control approach to a generalized predator-prey system and consider the specific case of indirect control of the prey population. We derive the associated Z-controlled model and investigate its properties from the point of view of the dynamical systems theory. The key role of the design parameter λ for the successful application of the method is stressed and related to specific dynamical properties of the Z-controlled model. Critical values of the design parameter are also found, delimiting the λ-range for the effectiveness of the Z-method. Analytical results are then numerically validated by the means of two ecological models: the classical Lotka-Volterra model and a model related to a case study of the wolf-wild boar dynamics in the Alta Murgia National Park. Investigations on these models also highlight how the Z-control method acts in respect to different dynamical regimes of the uncontrolled model. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Nitrogen dynamics in flooded soil systems: an overview on concepts and performance of models.

PubMed

Nurulhuda, Khairudin; Gaydon, Donald S; Jing, Qi; Zakaria, Mohamad P; Struik, Paul C; Keesman, Karel J

2018-02-01

Extensive modelling studies on nitrogen (N) dynamics in flooded soil systems have been published. Consequently, many N dynamics models are available for users to select from. With the current research trend, inclined towards multidisciplinary research, and with substantial progress in understanding of N dynamics in flooded soil systems, the objective of this paper is to provide an overview of the modelling concepts and performance of 14 models developed to simulate N dynamics in flooded soil systems. This overview provides breadth of knowledge on the models, and, therefore, is valuable as a first step in the selection of an appropriate model for a specific application. © 2017 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. © 2017 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Malczynski, Leonard A.

This guide addresses software quality in the construction of Powersim{reg_sign} Studio 8 system dynamics simulation models. It is the result of almost ten years of experience with the Powersim suite of system dynamics modeling tools (Constructor and earlier Studio versions). It is a guide that proposes a common look and feel for the construction of Powersim Studio system dynamics models.

Estimation of Spatial Dynamic Nonparametric Durbin Models with Fixed Effects

ERIC Educational Resources Information Center

Qian, Minghui; Hu, Ridong; Chen, Jianwei

2016-01-01

Spatial panel data models have been widely studied and applied in both scientific and social science disciplines, especially in the analysis of spatial influence. In this paper, we consider the spatial dynamic nonparametric Durbin model (SDNDM) with fixed effects, which takes the nonlinear factors into account base on the spatial dynamic panel…

Dynamics Modelling of Transmission Gear Rattle and Analysis on Influence Factors

NASA Astrophysics Data System (ADS)

He, Xiaona; Zhang, Honghui

2018-02-01

Based on the vibration dynamics modeling for the single stage gear of transmission system, this paper is to understand the mechanism of transmission rattle. The dynamic model response using MATLAB and Runge-Kutta algorithm is analyzed, and the ways for reducing the rattle noise of the automotive transmission is summarized.

Comparative dynamics in a health investment model.

PubMed

Eisenring, C

1999-10-01

The method of comparative dynamics fully exploits the inter-temporal structure of optimal control models. I derive comparative dynamic results in a simplified demand for health model. The effect of a change in the depreciation rate on the optimal paths for health capital and investment in health is studied by use of a phase diagram.

Qualitative models and experimental investigation of chaotic NOR gates and set/reset flip-flops

NASA Astrophysics Data System (ADS)

Rahman, Aminur; Jordan, Ian; Blackmore, Denis

2018-01-01

It has been observed through experiments and SPICE simulations that logical circuits based upon Chua's circuit exhibit complex dynamical behaviour. This behaviour can be used to design analogues of more complex logic families and some properties can be exploited for electronics applications. Some of these circuits have been modelled as systems of ordinary differential equations. However, as the number of components in newer circuits increases so does the complexity. This renders continuous dynamical systems models impractical and necessitates new modelling techniques. In recent years, some discrete dynamical models have been developed using various simplifying assumptions. To create a robust modelling framework for chaotic logical circuits, we developed both deterministic and stochastic discrete dynamical models, which exploit the natural recurrence behaviour, for two chaotic NOR gates and a chaotic set/reset flip-flop. This work presents a complete applied mathematical investigation of logical circuits. Experiments on our own designs of the above circuits are modelled and the models are rigorously analysed and simulated showing surprisingly close qualitative agreement with the experiments. Furthermore, the models are designed to accommodate dynamics of similarly designed circuits. This will allow researchers to develop ever more complex chaotic logical circuits with a simple modelling framework.

High Speed Civil Transport Aircraft Simulation: Reference-H Cycle 1, MATLAB Implementation

NASA Technical Reports Server (NTRS)

Sotack, Robert A.; Chowdhry, Rajiv S.; Buttrill, Carey S.

1999-01-01

The mathematical model and associated code to simulate a high speed civil transport aircraft - the Boeing Reference H configuration - are described. The simulation was constructed in support of advanced control law research. In addition to providing time histories of the dynamic response, the code includes the capabilities for calculating trim solutions and for generating linear models. The simulation relies on the nonlinear, six-degree-of-freedom equations which govern the motion of a rigid aircraft in atmospheric flight. The 1962 Standard Atmosphere Tables are used along with a turbulence model to simulate the Earth atmosphere. The aircraft model has three parts - an aerodynamic model, an engine model, and a mass model. These models use the data from the Boeing Reference H cycle 1 simulation data base. Models for the actuator dynamics, landing gear, and flight control system are not included in this aircraft model. Dynamic responses generated by the nonlinear simulation are presented and compared with results generated from alternate simulations at Boeing Commercial Aircraft Company and NASA Langley Research Center. Also, dynamic responses generated using linear models are presented and compared with dynamic responses generated using the nonlinear simulation.

Qualitative models and experimental investigation of chaotic NOR gates and set/reset flip-flops.

PubMed

Rahman, Aminur; Jordan, Ian; Blackmore, Denis

2018-01-01

It has been observed through experiments and SPICE simulations that logical circuits based upon Chua's circuit exhibit complex dynamical behaviour. This behaviour can be used to design analogues of more complex logic families and some properties can be exploited for electronics applications. Some of these circuits have been modelled as systems of ordinary differential equations. However, as the number of components in newer circuits increases so does the complexity. This renders continuous dynamical systems models impractical and necessitates new modelling techniques. In recent years, some discrete dynamical models have been developed using various simplifying assumptions. To create a robust modelling framework for chaotic logical circuits, we developed both deterministic and stochastic discrete dynamical models, which exploit the natural recurrence behaviour, for two chaotic NOR gates and a chaotic set/reset flip-flop. This work presents a complete applied mathematical investigation of logical circuits. Experiments on our own designs of the above circuits are modelled and the models are rigorously analysed and simulated showing surprisingly close qualitative agreement with the experiments. Furthermore, the models are designed to accommodate dynamics of similarly designed circuits. This will allow researchers to develop ever more complex chaotic logical circuits with a simple modelling framework.

Nonlinear dynamic modeling of rotor system supported by angular contact ball bearings

NASA Astrophysics Data System (ADS)

Wang, Hong; Han, Qinkai; Zhou, Daning

2017-02-01

In current bearing dynamic models, the displacement coordinate relations are usually utilized to approximately obtain the contact deformations between the rolling element and raceways, and then the nonlinear restoring forces of the rolling bearing could be calculated accordingly. Although the calculation efficiency is relatively higher, the accuracy is lower as the contact deformations should be solved through iterative analysis. Thus, an improved nonlinear dynamic model is presented in this paper. Considering the preload condition, surface waviness, Hertz contact and elastohydrodynamic lubrication, load distribution analysis is solved iteratively to more accurately obtain the contact deformations and angles between the rolling balls and raceways. The bearing restoring forces are then obtained through iteratively solving the load distribution equations at every time step. Dynamic tests upon a typical rotor system supported by two angular contact ball bearings are conducted to verify the model. Through comparisons, the differences between the nonlinear dynamic model and current models are also pointed out. The effects of axial preload, rotor eccentricity and inner/outer waviness amplitudes on the dynamic response are discussed in detail.

Preliminary shuttle structural dynamics modeling design study

NASA Technical Reports Server (NTRS)

1972-01-01

The design and development of a structural dynamics model of the space shuttle are discussed. The model provides for early study of structural dynamics problems, permits evaluation of the accuracy of the structural and hydroelastic analysis methods used on test vehicles, and provides for efficiently evaluating potential cost savings in structural dynamic testing techniques. The discussion is developed around the modes in which major input forces and responses occur and the significant structural details in these modes.

Dynamical features of an anisotropic cosmological model

NASA Astrophysics Data System (ADS)

Mishra, B.; Tarai, Sankarsan; Tripathy, S. K.

2018-04-01

The dynamical features of Bianchi type VI_h (BVI_h) universe are investigated in f(R, T) theory of gravity. The field equations and the physical properties of the model are derived considering a power law expansion of the universe. The effect of anisotropy on the dynamics of the universe as well as on the energy conditions are studied. The assumed anisotropy of the model is found to have substantial effects on the energy conditions and dynamical parameters.

Flight Dynamics of Flexible Aircraft with Aeroelastic and Inertial Force Interactions

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Tuzcu, Ilhan

2009-01-01

This paper presents an integrated flight dynamic modeling method for flexible aircraft that captures coupled physics effects due to inertial forces, aeroelasticity, and propulsive forces that are normally present in flight. The present approach formulates the coupled flight dynamics using a structural dynamic modeling method that describes the elasticity of a flexible, twisted, swept wing using an equivalent beam-rod model. The structural dynamic model allows for three types of wing elastic motion: flapwise bending, chordwise bending, and torsion. Inertial force coupling with the wing elasticity is formulated to account for aircraft acceleration. The structural deflections create an effective aeroelastic angle of attack that affects the rigid-body motion of flexible aircraft. The aeroelastic effect contributes to aerodynamic damping forces that can influence aerodynamic stability. For wing-mounted engines, wing flexibility can cause the propulsive forces and moments to couple with the wing elastic motion. The integrated flight dynamics for a flexible aircraft are formulated by including generalized coordinate variables associated with the aeroelastic-propulsive forces and moments in the standard state-space form for six degree-of-freedom flight dynamics. A computational structural model for a generic transport aircraft has been created. The eigenvalue analysis is performed to compute aeroelastic frequencies and aerodynamic damping. The results will be used to construct an integrated flight dynamic model of a flexible generic transport aircraft.

Stability analysis of an implicitly defined labor market model

NASA Astrophysics Data System (ADS)

Mendes, Diana A.; Mendes, Vivaldo M.

2008-06-01

Until very recently, the pervasive existence of models exhibiting well-defined backward dynamics but ill-defined forward dynamics in economics and finance has apparently posed no serious obstacles to the analysis of their dynamics and stability, despite the problems that may arise from possible erroneous conclusions regarding theoretical considerations and policy prescriptions from such models. A large number of papers have dealt with this problem in the past by assuming the existence of symmetry between forward and backward dynamics, even in the case when the map cannot be invertible either forward or backwards. However, this procedure has been seriously questioned over the last few years in a series of papers dealing with implicit difference equations and inverse limit spaces. This paper explores the search and matching labor market model developed by Bhattacharya and Bunzel [J. Bhattacharya, H. Bunzel, Chaotic Planning Solution in the Textbook Model of Equilibrium Labor Market Search and Matching, Mimeo, Iowa State University, 2002; J. Bhattacharya, H. Bunzel, Economics Bulletin 5 (19) (2003) 1-10], with the following objectives in mind: (i) to show that chaotic dynamics may still be present in the model for acceptable parameter values, (ii) to clarify some open questions related with the admissible dynamics in the forward looking setting, by providing a rigorous proof of the existence of cyclic and chaotic dynamics through the application of tools from symbolic dynamics and inverse limit theory.

The importance of correct specification of tribological parameters in dynamical systems modelling

NASA Astrophysics Data System (ADS)

Alaci, S.; Ciornei, F. C.; Romanu, I. C.; Ciornei, M. C.

2018-01-01

When modelling the behaviour of dynamical systems, the friction phenomenon cannot be neglected. Dry and fluid friction may occur, but dry friction has more severe effects upon the behaviour of the systems, based on the fact that the introduced discontinuities are more important. In the modelling of dynamical systems, dry friction is the main cause of occurrence of the bifurcation phenomenon. These aspects become more complex if, in the case of dry friction, static and dynamic frictions are put forward. The behaviour of a simple dynamical system is studied, consisting in a prismatic body linked to the ground by a spring, placed on a conveyor belt. The theoretical model is described by a nonlinear differential equation which after numerical integration leads to the conclusion that the steady motion of the prism is an un-damped oscillatory motion. The system was qualitatively modelled using specialised software for dynamical analysis. It was impractical to obtain a steady uniform translational motion of a rigid, therefore the conveyor belt was replaced by a metallic disc in uniform rotation motion. The attempts to compare the CAD model to the theoretical model were unsuccessful because the efforts of selecting the tribological parameters directed to the conclusion that the motion of the prism is a damped oscillation. To decide which of the methods depicts reality, a test-rig was assembled and it indicated a sustained oscillation. The conclusion is that the model employed by the dynamical analysis software cannot describe the actual model and a more complex model is required in the description of the friction phenomenon.

A Lagrangian subgrid-scale model with dynamic estimation of Lagrangian time scale for large eddy simulation of complex flows

NASA Astrophysics Data System (ADS)

Verma, Aman; Mahesh, Krishnan

2012-08-01

The dynamic Lagrangian averaging approach for the dynamic Smagorinsky model for large eddy simulation is extended to an unstructured grid framework and applied to complex flows. The Lagrangian time scale is dynamically computed from the solution and does not need any adjustable parameter. The time scale used in the standard Lagrangian model contains an adjustable parameter θ. The dynamic time scale is computed based on a "surrogate-correlation" of the Germano-identity error (GIE). Also, a simple material derivative relation is used to approximate GIE at different events along a pathline instead of Lagrangian tracking or multi-linear interpolation. Previously, the time scale for homogeneous flows was computed by averaging along directions of homogeneity. The present work proposes modifications for inhomogeneous flows. This development allows the Lagrangian averaged dynamic model to be applied to inhomogeneous flows without any adjustable parameter. The proposed model is applied to LES of turbulent channel flow on unstructured zonal grids at various Reynolds numbers. Improvement is observed when compared to other averaging procedures for the dynamic Smagorinsky model, especially at coarse resolutions. The model is also applied to flow over a cylinder at two Reynolds numbers and good agreement with previous computations and experiments is obtained. Noticeable improvement is obtained using the proposed model over the standard Lagrangian model. The improvement is attributed to a physically consistent Lagrangian time scale. The model also shows good performance when applied to flow past a marine propeller in an off-design condition; it regularizes the eddy viscosity and adjusts locally to the dominant flow features.

Fine-scale population dynamics in a marine fish species inferred from dynamic state-space models.

PubMed

Rogers, Lauren A; Storvik, Geir O; Knutsen, Halvor; Olsen, Esben M; Stenseth, Nils C

2017-07-01

Identifying the spatial scale of population structuring is critical for the conservation of natural populations and for drawing accurate ecological inferences. However, population studies often use spatially aggregated data to draw inferences about population trends and drivers, potentially masking ecologically relevant population sub-structure and dynamics. The goals of this study were to investigate how population dynamics models with and without spatial structure affect inferences on population trends and the identification of intrinsic drivers of population dynamics (e.g. density dependence). Specifically, we developed dynamic, age-structured, state-space models to test different hypotheses regarding the spatial structure of a population complex of coastal Atlantic cod (Gadus morhua). Data were from a 93-year survey of juvenile (age 0 and 1) cod sampled along >200 km of the Norwegian Skagerrak coast. We compared two models: one which assumes all sampled cod belong to one larger population, and a second which assumes that each fjord contains a unique population with locally determined dynamics. Using the best supported model, we then reconstructed the historical spatial and temporal dynamics of Skagerrak coastal cod. Cross-validation showed that the spatially structured model with local dynamics had better predictive ability. Furthermore, posterior predictive checks showed that a model which assumes one homogeneous population failed to capture the spatial correlation pattern present in the survey data. The spatially structured model indicated that population trends differed markedly among fjords, as did estimates of population parameters including density-dependent survival. Recent biomass was estimated to be at a near-record low all along the coast, but the finer scale model indicated that the decline occurred at different times in different regions. Warm temperatures were associated with poor recruitment, but local changes in habitat and fishing pressure may have played a role in driving local dynamics. More generally, we demonstrated how state-space models can be used to test evidence for population spatial structure based on survey time-series data. Our study shows the importance of considering spatially structured dynamics, as the inferences from such an approach can lead to a different ecological understanding of the drivers of population declines, and fundamentally different management actions to restore populations. © 2017 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.

Site-level model intercomparison of high latitude and high altitude soil thermal dynamics in tundra and barren landscapes

NASA Astrophysics Data System (ADS)

Ekici, A.; Chadburn, S.; Chaudhary, N.; Hajdu, L. H.; Marmy, A.; Peng, S.; Boike, J.; Burke, E.; Friend, A. D.; Hauck, C.; Krinner, G.; Langer, M.; Miller, P. A.; Beer, C.

2015-07-01

Modeling soil thermal dynamics at high latitudes and altitudes requires representations of physical processes such as snow insulation, soil freezing and thawing and subsurface conditions like soil water/ice content and soil texture. We have compared six different land models: JSBACH, ORCHIDEE, JULES, COUP, HYBRID8 and LPJ-GUESS, at four different sites with distinct cold region landscape types, to identify the importance of physical processes in capturing observed temperature dynamics in soils. The sites include alpine, high Arctic, wet polygonal tundra and non-permafrost Arctic, thus showing how a range of models can represent distinct soil temperature regimes. For all sites, snow insulation is of major importance for estimating topsoil conditions. However, soil physics is essential for the subsoil temperature dynamics and thus the active layer thicknesses. This analysis shows that land models need more realistic surface processes, such as detailed snow dynamics and moss cover with changing thickness and wetness, along with better representations of subsoil thermal dynamics.

Modal simulation of gearbox vibration with experimental correlation

NASA Technical Reports Server (NTRS)

Choy, Fred K.; Ruan, Yeefeng F.; Zakrajsek, James J.; Oswald, Fred B.

1992-01-01

A newly developed global dynamic model was used to simulate the dynamics of a gear noise rig at NASA Lewis Research Center. Experimental results from the test rig were used to verify the analytical model. In this global dynamic model, the number of degrees of freedom of the system are reduced by transforming the system equations of motion into modal coordinates. The vibration of the individual gear-shaft system are coupled through the gear mesh forces. A three-dimensional, axial-lateral coupled, bearing model was used to couple the casing structural vibration to the gear-rotor dynamics. The coupled system of modal equations is solved to predict the resulting vibration at several locations on the test rig. Experimental vibration data was compared to the predictions of the global dynamic model. There is excellent agreement between the vibration results from analysis and experiment.

Measles metapopulation dynamics: a gravity model for epidemiological coupling and dynamics.

PubMed

Xia, Yingcun; Bjørnstad, Ottar N; Grenfell, Bryan T

2004-08-01

Infectious diseases provide a particularly clear illustration of the spatiotemporal underpinnings of consumer-resource dynamics. The paradigm is provided by extremely contagious, acute, immunizing childhood infections. Partially synchronized, unstable oscillations are punctuated by local extinctions. This, in turn, can result in spatial differentiation in the timing of epidemics and, depending on the nature of spatial contagion, may result in traveling waves. Measles epidemics are one of a few systems documented well enough to reveal all of these properties and how they are affected by spatiotemporal variations in population structure and demography. On the basis of a gravity coupling model and a time series susceptible-infected-recovered (TSIR) model for local dynamics, we propose a metapopulation model for regional measles dynamics. The model can capture all the major spatiotemporal properties in prevaccination epidemics of measles in England and Wales.

Global dynamics in a stoichiometric food chain model with two limiting nutrients.

PubMed

Chen, Ming; Fan, Meng; Kuang, Yang

2017-07-01

Ecological stoichiometry studies the balance of energy and multiple chemical elements in ecological interactions to establish how the nutrient content affect food-web dynamics and nutrient cycling in ecosystems. In this study, we formulate a food chain with two limiting nutrients in the form of a stoichiometric population model. A comprehensive global analysis of the rich dynamics of the targeted model is explored both analytically and numerically. Chaotic dynamic is observed in this simple stoichiometric food chain model and is compared with traditional model without stoichiometry. The detailed comparison reveals that stoichiometry can reduce the parameter space for chaotic dynamics. Our findings also show that decreasing producer production efficiency may have only a small effect on the consumer growth but a more profound impact on the top predator growth. Copyright © 2017 Elsevier Inc. All rights reserved.

Activated aging dynamics and effective trap model description in the random energy model

NASA Astrophysics Data System (ADS)

Baity-Jesi, M.; Biroli, G.; Cammarota, C.

2018-01-01

We study the out-of-equilibrium aging dynamics of the random energy model (REM) ruled by a single spin-flip Metropolis dynamics. We focus on the dynamical evolution taking place on time-scales diverging with the system size. Our aim is to show to what extent the activated dynamics displayed by the REM can be described in terms of an effective trap model. We identify two time regimes: the first one corresponds to the process of escaping from a basin in the energy landscape and to the subsequent exploration of high energy configurations, whereas the second one corresponds to the evolution from a deep basin to the other. By combining numerical simulations with analytical arguments we show why the trap model description does not hold in the former but becomes exact in the second.

Coarse-grained molecular dynamics simulations for giant protein-DNA complexes

NASA Astrophysics Data System (ADS)

Takada, Shoji

Biomolecules are highly hierarchic and intrinsically flexible. Thus, computational modeling calls for multi-scale methodologies. We have been developing a coarse-grained biomolecular model where on-average 10-20 atoms are grouped into one coarse-grained (CG) particle. Interactions among CG particles are tuned based on atomistic interactions and the fluctuation matching algorithm. CG molecular dynamics methods enable us to simulate much longer time scale motions of much larger molecular systems than fully atomistic models. After broad sampling of structures with CG models, we can easily reconstruct atomistic models, from which one can continue conventional molecular dynamics simulations if desired. Here, we describe our CG modeling methodology for protein-DNA complexes, together with various biological applications, such as the DNA duplication initiation complex, model chromatins, and transcription factor dynamics on chromatin-like environment.

Sparse Additive Ordinary Differential Equations for Dynamic Gene Regulatory Network Modeling.

PubMed

Wu, Hulin; Lu, Tao; Xue, Hongqi; Liang, Hua

2014-04-02

The gene regulation network (GRN) is a high-dimensional complex system, which can be represented by various mathematical or statistical models. The ordinary differential equation (ODE) model is one of the popular dynamic GRN models. High-dimensional linear ODE models have been proposed to identify GRNs, but with a limitation of the linear regulation effect assumption. In this article, we propose a sparse additive ODE (SA-ODE) model, coupled with ODE estimation methods and adaptive group LASSO techniques, to model dynamic GRNs that could flexibly deal with nonlinear regulation effects. The asymptotic properties of the proposed method are established and simulation studies are performed to validate the proposed approach. An application example for identifying the nonlinear dynamic GRN of T-cell activation is used to illustrate the usefulness of the proposed method.

Populational Growth Models Proportional to Beta Densities with Allee Effect

NASA Astrophysics Data System (ADS)

Aleixo, Sandra M.; Rocha, J. Leonel; Pestana, Dinis D.

2009-05-01

We consider populations growth models with Allee effect, proportional to beta densities with shape parameters p and 2, where the dynamical complexity is related with the Malthusian parameter r. For p>2, these models exhibit a population dynamics with natural Allee effect. However, in the case of 1

Modeling Dynamic Regulatory Processes in Stroke.

DOE Office of Scientific and Technical Information (OSTI.GOV)

McDermott, Jason E.; Jarman, Kenneth D.; Taylor, Ronald C.

2012-10-11

The ability to examine in silico the behavior of biological systems can greatly accelerate the pace of discovery in disease pathologies, such as stroke, where in vivo experimentation is lengthy and costly. In this paper we describe an approach to in silico examination of blood genomic responses to neuroprotective agents and subsequent stroke through the development of dynamic models of the regulatory processes observed in the experimental gene expression data. First, we identified functional gene clusters from these data. Next, we derived ordinary differential equations (ODEs) relating regulators and functional clusters from the data. These ODEs were used to developmore » dynamic models that simulate the expression of regulated functional clusters using system dynamics as the modeling paradigm. The dynamic model has the considerable advantage of only requiring an initial starting state, and does not require measurement of regulatory influences at each time point in order to make accurate predictions. The manipulation of input model parameters, such as changing the magnitude of gene expression, made it possible to assess the behavior of the networks through time under varying conditions. We report that an optimized dynamic model can provide accurate predictions of overall system behavior under several different preconditioning paradigms.« less

Counteracting structural errors in ensemble forecast of influenza outbreaks.

PubMed

Pei, Sen; Shaman, Jeffrey

2017-10-13

For influenza forecasts generated using dynamical models, forecast inaccuracy is partly attributable to the nonlinear growth of error. As a consequence, quantification of the nonlinear error structure in current forecast models is needed so that this growth can be corrected and forecast skill improved. Here, we inspect the error growth of a compartmental influenza model and find that a robust error structure arises naturally from the nonlinear model dynamics. By counteracting these structural errors, diagnosed using error breeding, we develop a new forecast approach that combines dynamical error correction and statistical filtering techniques. In retrospective forecasts of historical influenza outbreaks for 95 US cities from 2003 to 2014, overall forecast accuracy for outbreak peak timing, peak intensity and attack rate, are substantially improved for predicted lead times up to 10 weeks. This error growth correction method can be generalized to improve the forecast accuracy of other infectious disease dynamical models.Inaccuracy of influenza forecasts based on dynamical models is partly due to nonlinear error growth. Here the authors address the error structure of a compartmental influenza model, and develop a new improved forecast approach combining dynamical error correction and statistical filtering techniques.

Dynamic Heterogeneous Multiscale Filtration Model: Probing Micro- and Macroscopic Filtration Characteristics of Gasoline Particulate Filters.

PubMed

Gong, Jian; Viswanathan, Sandeep; Rothamer, David A; Foster, David E; Rutland, Christopher J

2017-10-03

Motivated by high filtration efficiency (mass- and number-based) and low pressure drop requirements for gasoline particulate filters (GPFs), a previously developed heterogeneous multiscale filtration (HMF) model is extended to simulate dynamic filtration characteristics of GPFs. This dynamic HMF model is based on a probability density function (PDF) description of the pore size distribution and classical filtration theory. The microstructure of the porous substrate in a GPF is resolved and included in the model. Fundamental particulate filtration experiments were conducted using an exhaust filtration analysis (EFA) system for model validation. The particulate in the filtration experiments was sampled from a spark-ignition direct-injection (SIDI) gasoline engine. With the dynamic HMF model, evolution of the microscopic characteristics of the substrate (pore size distribution, porosity, permeability, and deposited particulate inside the porous substrate) during filtration can be probed. Also, predicted macroscopic filtration characteristics including particle number concentration and normalized pressure drop show good agreement with the experimental data. The resulting dynamic HMF model can be used to study the dynamic particulate filtration process in GPFs with distinct microstructures, serving as a powerful tool for GPF design and optimization.

Dynamic system simulation of small satellite projects

NASA Astrophysics Data System (ADS)

Raif, Matthias; Walter, Ulrich; Bouwmeester, Jasper

2010-11-01

A prerequisite to accomplish a system simulation is to have a system model holding all necessary project information in a centralized repository that can be accessed and edited by all parties involved. At the Institute of Astronautics of the Technische Universitaet Muenchen a modular approach for modeling and dynamic simulation of satellite systems has been developed called dynamic system simulation (DySyS). DySyS is based on the platform independent description language SysML to model a small satellite project with respect to the system composition and dynamic behavior. A library of specific building blocks and possible relations between these blocks have been developed. From this library a system model of the satellite of interest can be created. A mapping into a C++ simulation allows the creation of an executable system model with which simulations are performed to observe the dynamic behavior of the satellite. In this paper DySyS is used to model and simulate the dynamic behavior of small satellites, because small satellite projects can act as a precursor to demonstrate the feasibility of a system model since they are less complex compared to a large scale satellite project.

Dynamic PET of human liver inflammation: impact of kinetic modeling with optimization-derived dual-blood input function.

PubMed

Wang, Guobao; Corwin, Michael T; Olson, Kristin A; Badawi, Ramsey D; Sarkar, Souvik

2018-05-30

The hallmark of nonalcoholic steatohepatitis is hepatocellular inflammation and injury in the setting of hepatic steatosis. Recent work has indicated that dynamic 18F-FDG PET with kinetic modeling has the potential to assess hepatic inflammation noninvasively, while static FDG-PET did not show a promise. Because the liver has dual blood supplies, kinetic modeling of dynamic liver PET data is challenging in human studies. The objective of this study is to evaluate and identify a dual-input kinetic modeling approach for dynamic FDG-PET of human liver inflammation. Fourteen human patients with nonalcoholic fatty liver disease were included in the study. Each patient underwent one-hour dynamic FDG-PET/CT scan and had liver biopsy within six weeks. Three models were tested for kinetic analysis: traditional two-tissue compartmental model with an image-derived single-blood input function (SBIF), model with population-based dual-blood input function (DBIF), and modified model with optimization-derived DBIF through a joint estimation framework. The three models were compared using Akaike information criterion (AIC), F test and histopathologic inflammation reference. The results showed that the optimization-derived DBIF model improved the fitting of liver time activity curves and achieved lower AIC values and higher F values than the SBIF and population-based DBIF models in all patients. The optimization-derived model significantly increased FDG K1 estimates by 101% and 27% as compared with traditional SBIF and population-based DBIF. K1 by the optimization-derived model was significantly associated with histopathologic grades of liver inflammation while the other two models did not provide a statistical significance. In conclusion, modeling of DBIF is critical for kinetic analysis of dynamic liver FDG-PET data in human studies. The optimization-derived DBIF model is more appropriate than SBIF and population-based DBIF for dynamic FDG-PET of liver inflammation. © 2018 Institute of Physics and Engineering in Medicine.

Bayesian Estimation of Random Coefficient Dynamic Factor Models

ERIC Educational Resources Information Center

Song, Hairong; Ferrer, Emilio

2012-01-01

Dynamic factor models (DFMs) have typically been applied to multivariate time series data collected from a single unit of study, such as a single individual or dyad. The goal of DFMs application is to capture dynamics of multivariate systems. When multiple units are available, however, DFMs are not suited to capture variations in dynamics across…

High frequency dynamic engine simulation. [TF-30 engine

NASA Technical Reports Server (NTRS)

Schuerman, J. A.; Fischer, K. E.; Mclaughlin, P. W.

1977-01-01

A digital computer simulation of a mixed flow, twin spool turbofan engine was assembled to evaluate and improve the dynamic characteristics of the engine simulation to disturbance frequencies of at least 100 Hz. One dimensional forms of the dynamic mass, momentum and energy equations were used to model the engine. A TF30 engine was simulated so that dynamic characteristics could be evaluated against results obtained from testing of the TF30 engine at the NASA Lewis Research Center. Dynamic characteristics of the engine simulation were improved by modifying the compression system model. Modifications to the compression system model were established by investigating the influence of size and number of finite dynamic elements. Based on the results of this program, high frequency engine simulations using finite dynamic elements can be assembled so that the engine dynamic configuration is optimum with respect to dynamic characteristics and computer execution time. Resizing of the compression systems finite elements improved the dynamic characteristics of the engine simulation but showed that additional refinements are required to obtain close agreement simulation and actual engine dynamic characteristics.

DSGRN: Examining the Dynamics of Families of Logical Models.

PubMed

Cummins, Bree; Gedeon, Tomas; Harker, Shaun; Mischaikow, Konstantin

2018-01-01

We present a computational tool DSGRN for exploring the dynamics of a network by computing summaries of the dynamics of switching models compatible with the network across all parameters. The network can arise directly from a biological problem, or indirectly as the interaction graph of a Boolean model. This tool computes a finite decomposition of parameter space such that for each region, the state transition graph that describes the coarse dynamical behavior of a network is the same. Each of these parameter regions corresponds to a different logical description of the network dynamics. The comparison of dynamics across parameters with experimental data allows the rejection of parameter regimes or entire networks as viable models for representing the underlying regulatory mechanisms. This in turn allows a search through the space of perturbations of a given network for networks that robustly fit the data. These are the first steps toward discovering a network that optimally matches the observed dynamics by searching through the space of networks.

Asymmetric dynamics of the inner core and impact on the outer core

NASA Astrophysics Data System (ADS)

Alboussière, Thierry; Deguen, Renaud

2012-10-01

The history and present state of knowledge of the dynamics of the inner core are outlined in this paper. The observations that motivated ideas on the dynamical processes are introduced, but the main objective is really to concentrate on the diverse dynamical models that have been and are currently proposed for the formation and evolution of the inner core. A deliberate choice has been made of reproducing key figures from the literature in a didactic attempt to provide clear and quick identification for these models. This review looses impartiality concerning recent models, notably those aiming at explaining the hemispherical asymmetry. A preference for an intrinsic dynamic mode of the inner core is expressed, as opposed to the distant influence of the dynamics of the mantle through heat-flux heterogeneities. Meanwhile, the opinion is conveyed that the dynamics of the inner core is largely not understood yet and that every model must be considered with a critical eye.

Energy Balance Models and Planetary Dynamics

NASA Technical Reports Server (NTRS)

Domagal-Goldman, Shawn

2012-01-01

We know that planetary dynamics can have a significant affect on the climate of planets. Planetary dynamics dominate the glacial-interglacial periods on Earth, leaving a significant imprint on the geological record. They have also been demonstrated to have a driving influence on the climates of other planets in our solar system. We should therefore expect th.ere to be similar relationships on extrasolar planets. Here we describe a simple energy balance model that can predict the growth and thickness of glaciers, and their feedbacks on climate. We will also describe model changes that we have made to include planetary dynamics effects. This is the model we will use at the start of our collaboration to handle the influence of dynamics on climate.

Application of numerical optimization techniques to control system design for nonlinear dynamic models of aircraft

NASA Technical Reports Server (NTRS)

Lan, C. Edward; Ge, Fuying

1989-01-01

Control system design for general nonlinear flight dynamic models is considered through numerical simulation. The design is accomplished through a numerical optimizer coupled with analysis of flight dynamic equations. The general flight dynamic equations are numerically integrated and dynamic characteristics are then identified from the dynamic response. The design variables are determined iteratively by the optimizer to optimize a prescribed objective function which is related to desired dynamic characteristics. Generality of the method allows nonlinear effects to aerodynamics and dynamic coupling to be considered in the design process. To demonstrate the method, nonlinear simulation models for an F-5A and an F-16 configurations are used to design dampers to satisfy specifications on flying qualities and control systems to prevent departure. The results indicate that the present method is simple in formulation and effective in satisfying the design objectives.

The Influence of Information Acquisition on the Complex Dynamics of Market Competition

NASA Astrophysics Data System (ADS)

Guo, Zhanbing; Ma, Junhai

In this paper, we build a dynamical game model with three bounded rational players (firms) to study the influence of information on the complex dynamics of market competition, where useful information is about rival’s real decision. In this dynamical game model, one information-sharing team is composed of two firms, they acquire and share the information about their common competitor, however, they make their own decisions separately, where the amount of information acquired by this information-sharing team will determine the estimation accuracy about the rival’s real decision. Based on this dynamical game model and some creative 3D diagrams, the influence of the amount of information on the complex dynamics of market competition such as local dynamics, global dynamics and profits is studied. These results have significant theoretical and practical values to realize the influence of information.

Dynamic modelling of a double-pendulum gantry crane system incorporating payload

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ismail, R. M. T. Raja; Ahmad, M. A.; Ramli, M. S.

The natural sway of crane payloads is detrimental to safe and efficient operation. Under certain conditions, the problem is complicated when the payloads create a double pendulum effect. This paper presents dynamic modelling of a double-pendulum gantry crane system based on closed-form equations of motion. The Lagrangian method is used to derive the dynamic model of the system. A dynamic model of the system incorporating payload is developed and the effects of payload on the response of the system are discussed. Extensive results that validate the theoretical derivation are presented in the time and frequency domains.

Software-Engineering Process Simulation (SEPS) model

NASA Technical Reports Server (NTRS)

Lin, C. Y.; Abdel-Hamid, T.; Sherif, J. S.

1992-01-01

The Software Engineering Process Simulation (SEPS) model is described which was developed at JPL. SEPS is a dynamic simulation model of the software project development process. It uses the feedback principles of system dynamics to simulate the dynamic interactions among various software life cycle development activities and management decision making processes. The model is designed to be a planning tool to examine tradeoffs of cost, schedule, and functionality, and to test the implications of different managerial policies on a project's outcome. Furthermore, SEPS will enable software managers to gain a better understanding of the dynamics of software project development and perform postmodern assessments.

Coupling population dynamics with earth system models: the POPEM model.

PubMed

Navarro, Andrés; Moreno, Raúl; Jiménez-Alcázar, Alfonso; Tapiador, Francisco J

2017-09-16

Precise modeling of CO 2 emissions is important for environmental research. This paper presents a new model of human population dynamics that can be embedded into ESMs (Earth System Models) to improve climate modeling. Through a system dynamics approach, we develop a cohort-component model that successfully simulates historical population dynamics with fine spatial resolution (about 1°×1°). The population projections are used to improve the estimates of CO 2 emissions, thus transcending the bulk approach of existing models and allowing more realistic non-linear effects to feature in the simulations. The module, dubbed POPEM (from Population Parameterization for Earth Models), is compared with current emission inventories and validated against UN aggregated data. Finally, it is shown that the module can be used to advance toward fully coupling the social and natural components of the Earth system, an emerging research path for environmental science and pollution research.

The stock-flow model of spatial data infrastructure development refined by fuzzy logic.

PubMed

Abdolmajidi, Ehsan; Harrie, Lars; Mansourian, Ali

2016-01-01

The system dynamics technique has been demonstrated to be a proper method by which to model and simulate the development of spatial data infrastructures (SDI). An SDI is a collaborative effort to manage and share spatial data at different political and administrative levels. It is comprised of various dynamically interacting quantitative and qualitative (linguistic) variables. To incorporate linguistic variables and their joint effects in an SDI-development model more effectively, we suggest employing fuzzy logic. Not all fuzzy models are able to model the dynamic behavior of SDIs properly. Therefore, this paper aims to investigate different fuzzy models and their suitability for modeling SDIs. To that end, two inference and two defuzzification methods were used for the fuzzification of the joint effect of two variables in an existing SDI model. The results show that the Average-Average inference and Center of Area defuzzification can better model the dynamics of SDI development.

Switching moving boundary models for two-phase flow evaporators and condensers

NASA Astrophysics Data System (ADS)

Bonilla, Javier; Dormido, Sebastián; Cellier, François E.

2015-03-01

The moving boundary method is an appealing approach for the design, testing and validation of advanced control schemes for evaporators and condensers. When it comes to advanced control strategies, not only accurate but fast dynamic models are required. Moving boundary models are fast low-order dynamic models, and they can describe the dynamic behavior with high accuracy. This paper presents a mathematical formulation based on physical principles for two-phase flow moving boundary evaporator and condenser models which support dynamic switching between all possible flow configurations. The models were implemented in a library using the equation-based object-oriented Modelica language. Several integrity tests in steady-state and transient predictions together with stability tests verified the models. Experimental data from a direct steam generation parabolic-trough solar thermal power plant is used to validate and compare the developed moving boundary models against finite volume models.

Antibiotics for skin and soft tissues infections in type 2 diabetes mellitus.

PubMed

Butranova, O I; Razdrogina, T N

2015-01-01

Type 2 diabetes mellitus is a chronic pathology characterized by high prevalence, high morbidity and mortality. According to the data of the Ministry of Health of Volgograd region the number of patients with type 2 diabetes was 68,227 people on 01.01.2014. Medical and social significance of type 2 diabetes mellitus is determined by its complications. Skin and soft tissue infections (SSTIs) in patients with type 2 diabetes are among the main factors of hospitalization and mortality [1]. Diabetic foot syndrome is found in 30-80% of patients [2]. Pharmacoepidemiological analysis of the structure of skin and soft tissues infections in patients with type 2 diabetes, taking into account data on pathogens, parameters of their sensitivity, analysis of prescribed medicines and evaluation of their compliance with current clinical guidelines and standards. A retrospective descriptive cross-sectional pharmacoepidemiological study using randomization by random numbers. The sample consisted of 253 medical records of patients with SSTIs and type 2 diabetes. These were patients admitted to the surgical departments of hospitals of the city of Volgograd for the period from January 2011 to December 2014. Gender structure was the following: 51.4% - women, 48.6% - men. The average age of patients was 64.5 years. The average number of hospital days was 19,5 ± 14,9. Diabetic foot syndrome was found in 81.3% of cases (n-204). The most common forms of diabetic foot syndrome were the following: gangrene of the lower extremities - 28% (n-58), ulcers of the skin - 26% (n-53), mixed forms of SSTIs - 18% (n-37 ). Surgical manipulations were performed in 39.1% of cases (n-99), including amputations in 65.7% (n-65) of cases. The blood glucose level on admission was studied in 97.6% (n-247), at discharge - in 89% (n-225). Urine analysis on admission was performed in 66.4% of patients (n-168), at discharge - in 51% of patients (n-129). The glycemic profile was studied in 81.4% of patients (n-206). Bacteriological sowing was carried out in 19% (n-48) of cases: blood - 4,2% (n-2), urine - 6,2% (n-3) (the growth of microorganisms was not detected in 100%); bacteriological sowing from the wound - in 89.6% (n-43), the growth of microorganisms were identified in 95.7% (n-44). Most common pathogens were: St. aureus - 28%, E. coli - 19%, St. epidermidis - 14%. Antibacterial medications were prescribed in 86% (n-216). These were: cephalosporin of the III generation - ceftriaxone (49.4%), other synthetic antibacterials - metronidazole (21%), fluoroquinolone - ciprofloxacin (7.5%). The highest levels of bacterial resistance of SSTIs pathogens were found to beta-lactam antibiotics (amoxicillin/clavulanic acid, ceftriaxone, and ampicillin), rifampin, and gentamicin. The highest levels of sensitivity of SSTIs pathogens were observed to levofloxacin, to vancomycin and meropenem. There is a vicious circle in patients with type 2 diabetes: the infectious process leads to decompensation of carbohydrate metabolism parameters; in turn, hyperglycemia leads to increase of severity of SSTIs. Normalization of glucose levels promotes prompt relief of symptoms of infection and bacterial eradication, rational treatment of infection contributes to rapid correction of glucose level. Therefore, an essential element of comprehensive treatment of this group of patients should be rational antibiotic therapy; the choice of medication should be based on the severity of the disease and potential etiologic agents [3]. The analysis of the degree of conformity of the pharmacotherapy to existing standards is a way to optimize the treatment of the given group of patients [4].

Dynamic Fracture of Concrete. Part 1

DTIC Science & Technology

1990-02-14

unnotched) by Mindess and the Charpy type impact tests by Shah. In both cases, dynamic finite element modeling with the adjusted constitutive equavm for the...Mindess and the Charpy type impact tests by Shah. In both cases, dynamic finite element modeling with the adjusted constitutive equations for the...Modeling Shah’s Charpy Impact Tests ................ 190 Figure 7.20 Specimen Configuration and Finite Element Model for Concrete and Mortar Beam Impact

An analytic modeling and system identification study of rotor/fuselage dynamics at hover

NASA Technical Reports Server (NTRS)

Hong, Steven W.; Curtiss, H. C., Jr.

1993-01-01

A combination of analytic modeling and system identification methods have been used to develop an improved dynamic model describing the response of articulated rotor helicopters to control inputs. A high-order linearized model of coupled rotor/body dynamics including flap and lag degrees of freedom and inflow dynamics with literal coefficients is compared to flight test data from single rotor helicopters in the near hover trim condition. The identification problem was formulated using the maximum likelihood function in the time domain. The dynamic model with literal coefficients was used to generate the model states, and the model was parametrized in terms of physical constants of the aircraft rather than the stability derivatives resulting in a significant reduction in the number of quantities to be identified. The likelihood function was optimized using the genetic algorithm approach. This method proved highly effective in producing an estimated model from flight test data which included coupled fuselage/rotor dynamics. Using this approach it has been shown that blade flexibility is a significant contributing factor to the discrepancies between theory and experiment shown in previous studies. Addition of flexible modes, properly incorporating the constraint due to the lag dampers, results in excellent agreement between flight test and theory, especially in the high frequency range.

An analytic modeling and system identification study of rotor/fuselage dynamics at hover

NASA Technical Reports Server (NTRS)

Hong, Steven W.; Curtiss, H. C., Jr.

1993-01-01

A combination of analytic modeling and system identification methods have been used to develop an improved dynamic model describing the response of articulated rotor helicopters to control inputs. A high-order linearized model of coupled rotor/body dynamics including flap and lag degrees of freedom and inflow dynamics with literal coefficients is compared to flight test data from single rotor helicopters in the near hover trim condition. The identification problem was formulated using the maximum likelihood function in the time domain. The dynamic model with literal coefficients was used to generate the model states, and the model was parametrized in terms of physical constants of the aircraft rather than the stability derivatives, resulting in a significant reduction in the number of quantities to be identified. The likelihood function was optimized using the genetic algorithm approach. This method proved highly effective in producing an estimated model from flight test data which included coupled fuselage/rotor dynamics. Using this approach it has been shown that blade flexibility is a significant contributing factor to the discrepancies between theory and experiment shown in previous studies. Addition of flexible modes, properly incorporating the constraint due to the lag dampers, results in excellent agreement between flight test and theory, especially in the high frequency range.

A "Kane's Dynamics" Model for the Active Rack Isolation System Part Two: Nonlinear Model Development, Verification, and Simplification

NASA Technical Reports Server (NTRS)

Beech, G. S.; Hampton, R. D.; Rupert, J. K.

2004-01-01

Many microgravity space-science experiments require vibratory acceleration levels that are unachievable without active isolation. The Boeing Corporation's active rack isolation system (ARIS) employs a novel combination of magnetic actuation and mechanical linkages to address these isolation requirements on the International Space Station. Effective model-based vibration isolation requires: (1) An isolation device, (2) an adequate dynamic; i.e., mathematical, model of that isolator, and (3) a suitable, corresponding controller. This Technical Memorandum documents the validation of that high-fidelity dynamic model of ARIS. The verification of this dynamics model was achieved by utilizing two commercial off-the-shelf (COTS) software tools: Deneb's ENVISION(registered trademark), and Online Dynamics Autolev(trademark). ENVISION is a robotics software package developed for the automotive industry that employs three-dimensional computer-aided design models to facilitate both forward and inverse kinematics analyses. Autolev is a DOS-based interpreter designed, in general, to solve vector-based mathematical problems and specifically to solve dynamics problems using Kane's method. The simplification of this model was achieved using the small-angle theorem for the joint angle of the ARIS actuators. This simplification has a profound effect on the overall complexity of the closed-form solution while yielding a closed-form solution easily employed using COTS control hardware.

Unraveling cellular pathways contributing to drug-induced liver injury by dynamical modeling.

PubMed

Kuijper, Isoude A; Yang, Huan; Van De Water, Bob; Beltman, Joost B

2017-01-01

Drug-induced liver injury (DILI) is a significant threat to human health and a major problem in drug development. It is hard to predict due to its idiosyncratic nature and which does not show up in animal trials. Hepatic adaptive stress response pathway activation is generally observed in drug-induced liver injury. Dynamical pathway modeling has the potential to foresee adverse effects of drugs before they go in trial. Ordinary differential equation modeling can offer mechanistic insight, and allows us to study the dynamical behavior of stress pathways involved in DILI. Areas covered: This review provides an overview on the progress of the dynamical modeling of stress and death pathways pertinent to DILI, i.e. pathways relevant for oxidative stress, inflammatory stress, DNA damage, unfolded proteins, heat shock and apoptosis. We also discuss the required steps for applying such modeling to the liver. Expert opinion: Despite the strong progress made since the turn of the century, models of stress pathways have only rarely been specifically applied to describe pathway dynamics for DILI. We argue that with minor changes, in some cases only to parameter values, many of these models can be repurposed for application in DILI research. Combining both dynamical models with in vitro testing might offer novel screening methods for the harmful side-effects of drugs.

The dynamical core of the Aeolus 1.0 statistical-dynamical atmosphere model: validation and parameter optimization

NASA Astrophysics Data System (ADS)

Totz, Sonja; Eliseev, Alexey V.; Petri, Stefan; Flechsig, Michael; Caesar, Levke; Petoukhov, Vladimir; Coumou, Dim

2018-02-01

We present and validate a set of equations for representing the atmosphere's large-scale general circulation in an Earth system model of intermediate complexity (EMIC). These dynamical equations have been implemented in Aeolus 1.0, which is a statistical-dynamical atmosphere model (SDAM) and includes radiative transfer and cloud modules (Coumou et al., 2011; Eliseev et al., 2013). The statistical dynamical approach is computationally efficient and thus enables us to perform climate simulations at multimillennia timescales, which is a prime aim of our model development. Further, this computational efficiency enables us to scan large and high-dimensional parameter space to tune the model parameters, e.g., for sensitivity studies.Here, we present novel equations for the large-scale zonal-mean wind as well as those for planetary waves. Together with synoptic parameterization (as presented by Coumou et al., 2011), these form the mathematical description of the dynamical core of Aeolus 1.0.We optimize the dynamical core parameter values by tuning all relevant dynamical fields to ERA-Interim reanalysis data (1983-2009) forcing the dynamical core with prescribed surface temperature, surface humidity and cumulus cloud fraction. We test the model's performance in reproducing the seasonal cycle and the influence of the El Niño-Southern Oscillation (ENSO). We use a simulated annealing optimization algorithm, which approximates the global minimum of a high-dimensional function.With non-tuned parameter values, the model performs reasonably in terms of its representation of zonal-mean circulation, planetary waves and storm tracks. The simulated annealing optimization improves in particular the model's representation of the Northern Hemisphere jet stream and storm tracks as well as the Hadley circulation.The regions of high azonal wind velocities (planetary waves) are accurately captured for all validation experiments. The zonal-mean zonal wind and the integrated lower troposphere mass flux show good results in particular in the Northern Hemisphere. In the Southern Hemisphere, the model tends to produce too-weak zonal-mean zonal winds and a too-narrow Hadley circulation. We discuss possible reasons for these model biases as well as planned future model improvements and applications.

Dynamic coupling of three hydrodynamic models

NASA Astrophysics Data System (ADS)

Hartnack, J. N.; Philip, G. T.; Rungoe, M.; Smith, G.; Johann, G.; Larsen, O.; Gregersen, J.; Butts, M. B.

2008-12-01

The need for integrated modelling is evidently present within the field of flood management and flood forecasting. Engineers, modellers and managers are faced with flood problems which transcend the classical hydrodynamic fields of urban, river and coastal flooding. Historically the modeller has been faced with having to select one hydrodynamic model to cover all the aspects of the potentially complex dynamics occurring in a flooding situation. Such a single hydrodynamic model does not cover all dynamics of flood modelling equally well. Thus the ideal choice may in fact be a combination of models. Models combining two numerical/hydrodynamic models are becoming more standard, typically these models combine a 1D river model with a 2D overland flow model or alternatively a 1D sewer/collection system model with a 2D overland solver. In complex coastal/urban areas the flood dynamics may include rivers/streams, collection/storm water systems along with the overland flow. The dynamics within all three areas is of the same time scale and there is feedback in the system across the couplings. These two aspects dictate a fully dynamic three way coupling as opposed to running the models sequentially. It will be shown that the main challenges of the three way coupling are time step issues related to the difference in numerical schemes used in the three model components and numerical instabilities caused by the linking of the model components. MIKE FLOOD combines the models MIKE 11, MIKE 21 and MOUSE into one modelling framework which makes it possible to couple any combination of river, urban and overland flow fully dynamically. The MIKE FLOOD framework will be presented with an overview of the coupling possibilities. The flood modelling concept will be illustrated through real life cases in Australia and in Germany. The real life cases reflect dynamics and interactions across all three model components which are not possible to reproduce using a two-way coupling alone. The models comprise 2D inundation modelling, river networks with multiple structures (pumps, weirs, culverts), urban drainage networks as well as dam break modelling. The models were used to quantify the results of storm events or failures (dam break, pumping failures etc) coinciding with high discharge in river system and heavy rainfall. The detailed representation of the flow path through the city allowed a direct assessment of flood risk Thus it is found that the three-way coupled model is a practical and useful tool for integrated flood management.

Dynamic Modeling of Process Technologies for Closed-Loop Water Recovery Systems

NASA Technical Reports Server (NTRS)

Allada, Rama Kumar; Lange, Kevin E.; Anderson, Molly S.

2012-01-01

Detailed chemical process simulations are a useful tool in designing and optimizing complex systems and architectures for human life support. Dynamic and steady-state models of these systems help contrast the interactions of various operating parameters and hardware designs, which become extremely useful in trade-study analyses. NASA s Exploration Life Support technology development project recently made use of such models to compliment a series of tests on different waste water distillation systems. This paper presents dynamic simulations of chemical process for primary processor technologies including: the Cascade Distillation System (CDS), the Vapor Compression Distillation (VCD) system, the Wiped-Film Rotating Disk (WFRD), and post-distillation water polishing processes such as the Volatiles Removal Assembly (VRA). These dynamic models were developed using the Aspen Custom Modeler (Registered TradeMark) and Aspen Plus(Registered TradeMark) process simulation tools. The results expand upon previous work for water recovery technology models and emphasize dynamic process modeling and results. The paper discusses system design, modeling details, and model results for each technology and presents some comparisons between the model results and available test data. Following these initial comparisons, some general conclusions and forward work are discussed.

Dynamic characteristics of motor-gear system under load saltations and voltage transients

NASA Astrophysics Data System (ADS)

Bai, Wenyu; Qin, Datong; Wang, Yawen; Lim, Teik C.

2018-02-01

In this paper, a dynamic model of a motor-gear system is proposed. The model combines a nonlinear permeance network model (PNM) of a squirrel-cage induction motor and a coupled lateral-torsional dynamic model of a planetary geared rotor system. The external excitations including voltage transients and load saltations, as well as the internal excitations such as spatial effects, magnetic circuits topology and material nonlinearity in the motor, and time-varying mesh stiffness and damping in the planetary gear system are considered in the proposed model. Then, the simulation results are compared with those predicted by the electromechanical model containing a dynamic motor model with constant inductances. The comparison showed that the electromechanical system model with the PNM motor model yields more reasonable results than the electromechanical system model with the lumped-parameter electric machine. It is observed that electromechanical coupling effect can induce additional and severe gear vibrations. In addition, the external conditions, especially the voltage transients, will dramatically affect the dynamic characteristics of the electromechanical system. Finally, some suggestions are offered based on this analysis for improving the performance and reliability of the electromechanical system.

The Dynamical Core Model Intercomparison Project (DCMIP-2016): Results of the Supercell Test Case

NASA Astrophysics Data System (ADS)

Zarzycki, C. M.; Reed, K. A.; Jablonowski, C.; Ullrich, P. A.; Kent, J.; Lauritzen, P. H.; Nair, R. D.

2016-12-01

The 2016 Dynamical Core Model Intercomparison Project (DCMIP-2016) assesses the modeling techniques for global climate and weather models and was recently held at the National Center for Atmospheric Research (NCAR) in conjunction with a two-week summer school. Over 12 different international modeling groups participated in DCMIP-2016 and focused on the evaluation of the newest non-hydrostatic dynamical core designs for future high-resolution weather and climate models. The paper highlights the results of the third DCMIP-2016 test case, which is an idealized supercell storm on a reduced-radius Earth. The supercell storm test permits the study of a non-hydrostatic moist flow field with strong vertical velocities and associated precipitation. This test assesses the behavior of global modeling systems at extremely high spatial resolution and is used in the development of next-generation numerical weather prediction capabilities. In this regime the effective grid spacing is very similar to the horizontal scale of convective plumes, emphasizing resolved non-hydrostatic dynamics. The supercell test case sheds light on the physics-dynamics interplay and highlights the impact of diffusion on model solutions.

Dynamic Responses and Vibration Control of the Transmission Tower-Line System: A State-of-the-Art Review

PubMed Central

Chen, Bo; Guo, Wei-hua; Li, Peng-yun; Xie, Wen-ping

2014-01-01

This paper presented an overview on the dynamic analysis and control of the transmission tower-line system in the past forty years. The challenges and future developing trends in the dynamic analysis and mitigation of the transmission tower-line system under dynamic excitations are also put forward. It also reviews the analytical models and approaches of the transmission tower, transmission lines, and transmission tower-line systems, respectively, which contain the theoretical model, finite element (FE) model and the equivalent model; shows the advances in wind responses of the transmission tower-line system, which contains the dynamic effects under common wind loading, tornado, downburst, and typhoon; and discusses the dynamic responses under earthquake and ice loads, respectively. The vibration control of the transmission tower-line system is also reviewed, which includes the magnetorheological dampers, friction dampers, tuned mass dampers, and pounding tuned mass dampers. PMID:25105161

Ndarts

NASA Technical Reports Server (NTRS)

Jain, Abhinandan

2011-01-01

Ndarts software provides algorithms for computing quantities associated with the dynamics of articulated, rigid-link, multibody systems. It is designed as a general-purpose dynamics library that can be used for the modeling of robotic platforms, space vehicles, molecular dynamics, and other such applications. The architecture and algorithms in Ndarts are based on the Spatial Operator Algebra (SOA) theory for computational multibody and robot dynamics developed at JPL. It uses minimal, internal coordinate models. The algorithms are low-order, recursive scatter/ gather algorithms. In comparison with the earlier Darts++ software, this version has a more general and cleaner design needed to support a larger class of computational dynamics needs. It includes a frames infrastructure, allows algorithms to operate on subgraphs of the system, and implements lazy and deferred computation for better efficiency. Dynamics modeling modules such as Ndarts are core building blocks of control and simulation software for space, robotic, mechanism, bio-molecular, and material systems modeling.

The mathematical cell model reconstructed from interference microscopy data

NASA Astrophysics Data System (ADS)

Rogotnev, A. A.; Nikitiuk, A. S.; Naimark, O. B.; Nebogatikov, V. O.; Grishko, V. V.

2017-09-01

The mathematical model of cell dynamics is developed to link the dynamics of the phase cell thickness with the signs of the oncological pathology. The measurements of irregular oscillations of cancer cells phase thickness were made with laser interference microscope MIM-340 in order to substantiate this model. These data related to the dynamics of phase thickness for different cross-sections of cells (nuclei, nucleolus, and cytoplasm) allow the reconstruction of the attractor of dynamic system. The attractor can be associated with specific types of collective modes of phase thickness responsible for the normal and cancerous cell dynamics. Specific type of evolution operator was determined using an algorithm of designing of the mathematical cell model and temporal phase thickness data for cancerous and normal cells. Qualitative correspondence of attractor types to the cell states was analyzed in terms of morphological signs associated with maximum value of mean square irregular oscillations of phase thickness dynamics.

Dynamic Deformation Measurements of an Aeroelastic Semispan Model. [conducted in the Transonic Dynamics Tunnel at the NASA Langley Research Center

NASA Technical Reports Server (NTRS)

Graves, Sharon S.; Burner, Alpheus W.; Edwards, John W.; Schuster, David M.

2001-01-01

The techniques used to acquire, reduce, and analyze dynamic deformation measurements of an aeroelastic semispan wind tunnel model are presented. Single-camera, single-view video photogrammetry (also referred to as videogrammetric model deformation, or VMD) was used to determine dynamic aeroelastic deformation of the semispan 'Models for Aeroelastic Validation Research Involving Computation' (MAVRIC) model in the Transonic Dynamics Tunnel at the NASA Langley Research Center. Dynamic deformation was determined from optical retroreflective tape targets at five semispan locations located on the wing from the root to the tip. Digitized video images from a charge coupled device (CCD) camera were recorded and processed to automatically determine target image plane locations that were then corrected for sensor, lens, and frame grabber spatial errors. Videogrammetric dynamic data were acquired at a 60-Hz rate for time records of up to 6 seconds during portions of this flutter/Limit Cycle Oscillation (LCO) test at Mach numbers from 0.3 to 0.96. Spectral analysis of the deformation data is used to identify dominant frequencies in the wing motion. The dynamic data will be used to separate aerodynamic and structural effects and to provide time history deflection data for Computational Aeroelasticity code evaluation and validation.

Consistent View of Protein Fluctuations from All-Atom Molecular Dynamics and Coarse-Grained Dynamics with Knowledge-Based Force-Field.

PubMed

Jamroz, Michal; Orozco, Modesto; Kolinski, Andrzej; Kmiecik, Sebastian

2013-01-08

It is widely recognized that atomistic Molecular Dynamics (MD), a classical simulation method, captures the essential physics of protein dynamics. That idea is supported by a theoretical study showing that various MD force-fields provide a consensus picture of protein fluctuations in aqueous solution [Rueda, M. et al. Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 796-801]. However, atomistic MD cannot be applied to most biologically relevant processes due to its limitation to relatively short time scales. Much longer time scales can be accessed by properly designed coarse-grained models. We demonstrate that the aforementioned consensus view of protein dynamics from short (nanosecond) time scale MD simulations is fairly consistent with the dynamics of the coarse-grained protein model - the CABS model. The CABS model employs stochastic dynamics (a Monte Carlo method) and a knowledge-based force-field, which is not biased toward the native structure of a simulated protein. Since CABS-based dynamics allows for the simulation of entire folding (or multiple folding events) in a single run, integration of the CABS approach with all-atom MD promises a convenient (and computationally feasible) means for the long-time multiscale molecular modeling of protein systems with atomistic resolution.

Effects of the infectious period distribution on predicted transitions in childhood disease dynamics

PubMed Central

Krylova, Olga; Earn, David J. D.

2013-01-01

The population dynamics of infectious diseases occasionally undergo rapid qualitative changes, such as transitions from annual to biennial cycles or to irregular dynamics. Previous work, based on the standard seasonally forced ‘susceptible–exposed–infectious–removed’ (SEIR) model has found that transitions in the dynamics of many childhood diseases result from bifurcations induced by slow changes in birth and vaccination rates. However, the standard SEIR formulation assumes that the stage durations (latent and infectious periods) are exponentially distributed, whereas real distributions are narrower and centred around the mean. Much recent work has indicated that realistically distributed stage durations strongly affect the dynamical structure of seasonally forced epidemic models. We investigate whether inferences drawn from previous analyses of transitions in patterns of measles dynamics are robust to the shapes of the stage duration distributions. As an illustrative example, we analyse measles dynamics in New York City from 1928 to 1972. We find that with a fixed mean infectious period in the susceptible–infectious–removed (SIR) model, the dynamical structure and predicted transitions vary substantially as a function of the shape of the infectious period distribution. By contrast, with fixed mean latent and infectious periods in the SEIR model, the shapes of the stage duration distributions have a less dramatic effect on model dynamical structure and predicted transitions. All these results can be understood more easily by considering the distribution of the disease generation time as opposed to the distributions of individual disease stages. Numerical bifurcation analysis reveals that for a given mean generation time the dynamics of the SIR and SEIR models for measles are nearly equivalent and are insensitive to the shapes of the disease stage distributions. PMID:23676892

Effects of the infectious period distribution on predicted transitions in childhood disease dynamics.

PubMed

Krylova, Olga; Earn, David J D

2013-07-06

The population dynamics of infectious diseases occasionally undergo rapid qualitative changes, such as transitions from annual to biennial cycles or to irregular dynamics. Previous work, based on the standard seasonally forced 'susceptible-exposed-infectious-removed' (SEIR) model has found that transitions in the dynamics of many childhood diseases result from bifurcations induced by slow changes in birth and vaccination rates. However, the standard SEIR formulation assumes that the stage durations (latent and infectious periods) are exponentially distributed, whereas real distributions are narrower and centred around the mean. Much recent work has indicated that realistically distributed stage durations strongly affect the dynamical structure of seasonally forced epidemic models. We investigate whether inferences drawn from previous analyses of transitions in patterns of measles dynamics are robust to the shapes of the stage duration distributions. As an illustrative example, we analyse measles dynamics in New York City from 1928 to 1972. We find that with a fixed mean infectious period in the susceptible-infectious-removed (SIR) model, the dynamical structure and predicted transitions vary substantially as a function of the shape of the infectious period distribution. By contrast, with fixed mean latent and infectious periods in the SEIR model, the shapes of the stage duration distributions have a less dramatic effect on model dynamical structure and predicted transitions. All these results can be understood more easily by considering the distribution of the disease generation time as opposed to the distributions of individual disease stages. Numerical bifurcation analysis reveals that for a given mean generation time the dynamics of the SIR and SEIR models for measles are nearly equivalent and are insensitive to the shapes of the disease stage distributions.

Nonlinear dynamics of planetary gears using analytical and finite element models

NASA Astrophysics Data System (ADS)

Ambarisha, Vijaya Kumar; Parker, Robert G.

2007-05-01

Vibration-induced gear noise and dynamic loads remain key concerns in many transmission applications that use planetary gears. Tooth separations at large vibrations introduce nonlinearity in geared systems. The present work examines the complex, nonlinear dynamic behavior of spur planetary gears using two models: (i) a lumped-parameter model, and (ii) a finite element model. The two-dimensional (2D) lumped-parameter model represents the gears as lumped inertias, the gear meshes as nonlinear springs with tooth contact loss and periodically varying stiffness due to changing tooth contact conditions, and the supports as linear springs. The 2D finite element model is developed from a unique finite element-contact analysis solver specialized for gear dynamics. Mesh stiffness variation excitation, corner contact, and gear tooth contact loss are all intrinsically considered in the finite element analysis. The dynamics of planetary gears show a rich spectrum of nonlinear phenomena. Nonlinear jumps, chaotic motions, and period-doubling bifurcations occur when the mesh frequency or any of its higher harmonics are near a natural frequency of the system. Responses from the dynamic analysis using analytical and finite element models are successfully compared qualitatively and quantitatively. These comparisons validate the effectiveness of the lumped-parameter model to simulate the dynamics of planetary gears. Mesh phasing rules to suppress rotational and translational vibrations in planetary gears are valid even when nonlinearity from tooth contact loss occurs. These mesh phasing rules, however, are not valid in the chaotic and period-doubling regions.

Optimization Scheduling Model for Wind-thermal Power System Considering the Dynamic penalty factor

NASA Astrophysics Data System (ADS)

PENG, Siyu; LUO, Jianchun; WANG, Yunyu; YANG, Jun; RAN, Hong; PENG, Xiaodong; HUANG, Ming; LIU, Wanyu

2018-03-01

In this paper, a new dynamic economic dispatch model for power system is presented.Objective function of the proposed model presents a major novelty in the dynamic economic dispatch including wind farm: introduced the “Dynamic penalty factor”, This factor could be computed by using fuzzy logic considering both the variable nature of active wind power and power demand, and it could change the wind curtailment cost according to the different state of the power system. Case studies were carried out on the IEEE30 system. Results show that the proposed optimization model could mitigate the wind curtailment and the total cost effectively, demonstrate the validity and effectiveness of the proposed model.

Swarm Intelligence for Urban Dynamics Modelling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gerard H. E.

2009-04-16

In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

A study of the adequacy of quasi-geostrophic dynamics for modeling the effect of frontal cyclones on the larger scale flow

NASA Technical Reports Server (NTRS)

Mudrick, S.

1985-01-01

The validity of quasi-geostrophic (QG) dynamics were tested on compared to primitive equation (PE) dynamics, for modeling the effect of cyclone waves on the larger scale flow. The formation of frontal cyclones and the dynamics of occluded frontogenesis were studied. Surface friction runs with the PE model and the wavelength of maximum instability is described. Also fine resolution PE simulation of a polar low is described.

User's guide for a computer program to analyze the LRC 16 ft transonic dynamics tunnel cable mount system

NASA Technical Reports Server (NTRS)

Barbero, P.; Chin, J.

1973-01-01

The theoretical derivation of the set of equations is discussed which is applicable to modeling the dynamic characteristics of aeroelastically-scaled models flown on the two-cable mount system in a 16 ft transonic dynamics tunnel. The computer program provided for the analysis is also described. The program calculates model trim conditions as well as 3 DOF longitudinal and lateral/directional dynamic conditions for various flying cable and snubber cable configurations. Sample input and output are included.

Swarm Intelligence for Urban Dynamics Modelling

NASA Astrophysics Data System (ADS)

Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gérard H. E.

2009-04-01

In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

Dynamic N -occupancy models: estimating demographic rates and local abundance from detection-nondetection data

Treesearch

Sam Rossman; Charles B. Yackulic; Sarah P. Saunders; Janice Reid; Ray Davis; Elise F. Zipkin

2016-01-01

Occupancy modeling is a widely used analytical technique for assessing species distributions and range dynamics. However, occupancy analyses frequently ignore variation in abundance of occupied sites, even though site abundances affect many of the parameters being estimated (e.g., extinction, colonization, detection probability). We introduce a new model (“dynamic