Modeling and applications in microbial food safety

USDA-ARS?s Scientific Manuscript database

Mathematical modeling is a scientific and systematic approach to study and describe the recurrent events or phenomena with successful application track for decades. When models are properly developed and validated, their applications may save costs and time. For the microbial food safety concerns, ...

Predictive Microbiology and Food Safety Applications

USDA-ARS?s Scientific Manuscript database

Mathematical modeling is the science of systematic study of recurrent events or phenomena. When models are properly developed, their applications may save costs and time. For microbial food safety research and applications, predictive microbiology models may be developed based on the fact that most ...

A Computational Framework for Bioimaging Simulation

PubMed Central

Watabe, Masaki; Arjunan, Satya N. V.; Fukushima, Seiya; Iwamoto, Kazunari; Kozuka, Jun; Matsuoka, Satomi; Shindo, Yuki; Ueda, Masahiro; Takahashi, Koichi

2015-01-01

Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units. PMID:26147508

Automated method for the systematic interpretation of resonance peaks in spectrum data

DOEpatents

Damiano, B.; Wood, R.T.

1997-04-22

A method is described for spectral signature interpretation. The method includes the creation of a mathematical model of a system or process. A neural network training set is then developed based upon the mathematical model. The neural network training set is developed by using the mathematical model to generate measurable phenomena of the system or process based upon model input parameter that correspond to the physical condition of the system or process. The neural network training set is then used to adjust internal parameters of a neural network. The physical condition of an actual system or process represented by the mathematical model is then monitored by extracting spectral features from measured spectra of the actual process or system. The spectral features are then input into said neural network to determine the physical condition of the system or process represented by the mathematical model. More specifically, the neural network correlates the spectral features (i.e. measurable phenomena) of the actual process or system with the corresponding model input parameters. The model input parameters relate to specific components of the system or process, and, consequently, correspond to the physical condition of the process or system. 1 fig.

Editorial: Mathematical Methods and Modeling in Machine Fault Diagnosis

DOE PAGES

Yan, Ruqiang; Chen, Xuefeng; Li, Weihua; ...

2014-12-18

Modern mathematics has commonly been utilized as an effective tool to model mechanical equipment so that their dynamic characteristics can be studied analytically. This will help identify potential failures of mechanical equipment by observing change in the equipment’s dynamic parameters. On the other hand, dynamic signals are also important and provide reliable information about the equipment’s working status. Modern mathematics has also provided us with a systematic way to design and implement various signal processing methods, which are used to analyze these dynamic signals, and to enhance intrinsic signal components that are directly related to machine failures. This special issuemore » is aimed at stimulating not only new insights on mathematical methods for modeling but also recently developed signal processing methods, such as sparse decomposition with potential applications in machine fault diagnosis. Finally, the papers included in this special issue provide a glimpse into some of the research and applications in the field of machine fault diagnosis through applications of the modern mathematical methods.« less

From Cognitive Science to School Practice: Building the Bridge

ERIC Educational Resources Information Center

Singer, Mihaela

2003-01-01

The paper is focused on recent researches in neuroscience and developmental psychology regarding mathematical abilities of infants. A model that tries to explain these findings is developed. The model underlies the mental operations that could be systematically trained to generate efficient school learning. The model is built from a cognitive…

Automated method for the systematic interpretation of resonance peaks in spectrum data

DOEpatents

Damiano, Brian; Wood, Richard T.

1997-01-01

A method for spectral signature interpretation. The method includes the creation of a mathematical model of a system or process. A neural network training set is then developed based upon the mathematical model. The neural network training set is developed by using the mathematical model to generate measurable phenomena of the system or process based upon model input parameter that correspond to the physical condition of the system or process. The neural network training set is then used to adjust internal parameters of a neural network. The physical condition of an actual system or process represented by the mathematical model is then monitored by extracting spectral features from measured spectra of the actual process or system. The spectral features are then input into said neural network to determine the physical condition of the system or process represented by the mathematical. More specifically, the neural network correlates the spectral features (i.e. measurable phenomena) of the actual process or system with the corresponding model input parameters. The model input parameters relate to specific components of the system or process, and, consequently, correspond to the physical condition of the process or system.

Performance modeling of automated manufacturing systems

NASA Astrophysics Data System (ADS)

Viswanadham, N.; Narahari, Y.

A unified and systematic treatment is presented of modeling methodologies and analysis techniques for performance evaluation of automated manufacturing systems. The book is the first treatment of the mathematical modeling of manufacturing systems. Automated manufacturing systems are surveyed and three principal analytical modeling paradigms are discussed: Markov chains, queues and queueing networks, and Petri nets.

Complete Systematic Error Model of SSR for Sensor Registration in ATC Surveillance Networks

PubMed Central

Besada, Juan A.

2017-01-01

In this paper, a complete and rigorous mathematical model for secondary surveillance radar systematic errors (biases) is developed. The model takes into account the physical effects systematically affecting the measurement processes. The azimuth biases are calculated from the physical error of the antenna calibration and the errors of the angle determination dispositive. Distance bias is calculated from the delay of the signal produced by the refractivity index of the atmosphere, and from clock errors, while the altitude bias is calculated taking into account the atmosphere conditions (pressure and temperature). It will be shown, using simulated and real data, that adapting a classical bias estimation process to use the complete parametrized model results in improved accuracy in the bias estimation. PMID:28934157

A Primary Care Workload Production Model for Estimating Relative Value Unit Output

DTIC Science & Technology

2011-03-01

for Medicare and Medicaid Services, Office of the Actuary , National Health Statistics Group; and U.S. Department of Commerce, Bureau of Economic...The systematic variation in a relationship can be represented by a mathematical expression, whereas stochastic variation cannot. Further, stochastic...expressed mathematically as an equation, whereby a response variable Y is fitted to a function of “regressor variables and parameters” (SAS©, 2010). A

What should be considered if you decide to build your own mathematical model for predicting the development of bacterial resistance? Recommendations based on a systematic review of the literature

PubMed Central

Arepeva, Maria; Kolbin, Alexey; Kurylev, Alexey; Balykina, Julia; Sidorenko, Sergey

2015-01-01

Acquired bacterial resistance is one of the causes of mortality and morbidity from infectious diseases. Mathematical modeling allows us to predict the spread of resistance and to some extent to control its dynamics. The purpose of this review was to examine existing mathematical models in order to understand the pros and cons of currently used approaches and to build our own model. During the analysis, seven articles on mathematical approaches to studying resistance that satisfied the inclusion/exclusion criteria were selected. All models were classified according to the approach used to study resistance in the presence of an antibiotic and were analyzed in terms of our research. Some models require modifications due to the specifics of the research. The plan for further work on model building is as follows: modify some models, according to our research, check all obtained models against our data, and select the optimal model or models with the best quality of prediction. After that we would be able to build a model for the development of resistance using the obtained results. PMID:25972847

One-dimensional nonlinear elastodynamic models and their local conservation laws with applications to biological membranes.

PubMed

Cheviakov, A F; Ganghoffer, J-F

2016-05-01

The framework of incompressible nonlinear hyperelasticity and viscoelasticity is applied to the derivation of one-dimensional models of nonlinear wave propagation in fiber-reinforced elastic solids. Equivalence transformations are used to simplify the resulting wave equations and to reduce the number of parameters. Local conservation laws and global conserved quantities of the models are systematically computed and discussed, along with other related mathematical properties. Sample numerical solutions are presented. The models considered in the paper are appropriate for the mathematical description of certain aspects of the behavior of biological membranes and similar structures. Copyright © 2015 Elsevier Ltd. All rights reserved.

Dynamic Geometry Software Improves Mathematical Achievement: Systematic Review and Meta-Analysis

ERIC Educational Resources Information Center

Chan, Kan Kan; Leung, Siu Wai

2014-01-01

Dynamic geometry software (DGS) aims to enhance mathematics education. This systematic review and meta-analysis evaluated the quasi-experimental studies on the effectiveness of DGS-based instruction in improving students' mathematical achievement. Research articles published between 1990 and 2013 were identified from major databases according to a…

Ross, macdonald, and a theory for the dynamics and control of mosquito-transmitted pathogens.

PubMed

Smith, David L; Battle, Katherine E; Hay, Simon I; Barker, Christopher M; Scott, Thomas W; McKenzie, F Ellis

2012-01-01

Ronald Ross and George Macdonald are credited with developing a mathematical model of mosquito-borne pathogen transmission. A systematic historical review suggests that several mathematicians and scientists contributed to development of the Ross-Macdonald model over a period of 70 years. Ross developed two different mathematical models, Macdonald a third, and various "Ross-Macdonald" mathematical models exist. Ross-Macdonald models are best defined by a consensus set of assumptions. The mathematical model is just one part of a theory for the dynamics and control of mosquito-transmitted pathogens that also includes epidemiological and entomological concepts and metrics for measuring transmission. All the basic elements of the theory had fallen into place by the end of the Global Malaria Eradication Programme (GMEP, 1955-1969) with the concept of vectorial capacity, methods for measuring key components of transmission by mosquitoes, and a quantitative theory of vector control. The Ross-Macdonald theory has since played a central role in development of research on mosquito-borne pathogen transmission and the development of strategies for mosquito-borne disease prevention.

Ross, Macdonald, and a Theory for the Dynamics and Control of Mosquito-Transmitted Pathogens

PubMed Central

Smith, David L.; Battle, Katherine E.; Hay, Simon I.; Barker, Christopher M.; Scott, Thomas W.; McKenzie, F. Ellis

2012-01-01

Ronald Ross and George Macdonald are credited with developing a mathematical model of mosquito-borne pathogen transmission. A systematic historical review suggests that several mathematicians and scientists contributed to development of the Ross-Macdonald model over a period of 70 years. Ross developed two different mathematical models, Macdonald a third, and various “Ross-Macdonald” mathematical models exist. Ross-Macdonald models are best defined by a consensus set of assumptions. The mathematical model is just one part of a theory for the dynamics and control of mosquito-transmitted pathogens that also includes epidemiological and entomological concepts and metrics for measuring transmission. All the basic elements of the theory had fallen into place by the end of the Global Malaria Eradication Programme (GMEP, 1955–1969) with the concept of vectorial capacity, methods for measuring key components of transmission by mosquitoes, and a quantitative theory of vector control. The Ross-Macdonald theory has since played a central role in development of research on mosquito-borne pathogen transmission and the development of strategies for mosquito-borne disease prevention. PMID:22496640

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.

Herpes Zoster Risk Reduction through Exposure to Chickenpox Patients: A Systematic Multidisciplinary Review.

PubMed

Ogunjimi, Benson; Van Damme, Pierre; Beutels, Philippe

2013-01-01

Varicella-zoster virus (VZV) causes chickenpox and may subsequently reactivate to cause herpes zoster later in life. The exogenous boosting hypothesis states that re-exposure to circulating VZV can inhibit VZV reactivation and consequently also herpes zoster in VZV-immune individuals. Using this hypothesis, mathematical models predicted widespread chickenpox vaccination to increase herpes zoster incidence over more than 30 years. Some countries have postponed universal chickenpox vaccination, at least partially based on this prediction. After a systematic search and selection procedure, we analyzed different types of exogenous boosting studies. We graded 13 observational studies on herpes zoster incidence after widespread chickenpox vaccination, 4 longitudinal studies on VZV immunity after re-exposure, 9 epidemiological risk factor studies, 7 mathematical modeling studies as well as 7 other studies. We conclude that exogenous boosting exists, although not for all persons, nor in all situations. Its magnitude is yet to be determined adequately in any study field.

Current advances in mathematical modeling of anti-cancer drug penetration into tumor tissues.

PubMed

Kim, Munju; Gillies, Robert J; Rejniak, Katarzyna A

2013-11-18

Delivery of anti-cancer drugs to tumor tissues, including their interstitial transport and cellular uptake, is a complex process involving various biochemical, mechanical, and biophysical factors. Mathematical modeling provides a means through which to understand this complexity better, as well as to examine interactions between contributing components in a systematic way via computational simulations and quantitative analyses. In this review, we present the current state of mathematical modeling approaches that address phenomena related to drug delivery. We describe how various types of models were used to predict spatio-temporal distributions of drugs within the tumor tissue, to simulate different ways to overcome barriers to drug transport, or to optimize treatment schedules. Finally, we discuss how integration of mathematical modeling with experimental or clinical data can provide better tools to understand the drug delivery process, in particular to examine the specific tissue- or compound-related factors that limit drug penetration through tumors. Such tools will be important in designing new chemotherapy targets and optimal treatment strategies, as well as in developing non-invasive diagnosis to monitor treatment response and detect tumor recurrence.

Student Modeling in Orthopedic Surgery Training: Exploiting Symbiosis between Temporal Bayesian Networks and Fine-Grained Didactic Analysis

ERIC Educational Resources Information Center

Chieu, Vu Minh; Luengo, Vanda; Vadcard, Lucile; Tonetti, Jerome

2010-01-01

Cognitive approaches have been used for student modeling in intelligent tutoring systems (ITSs). Many of those systems have tackled fundamental subjects such as mathematics, physics, and computer programming. The change of the student's cognitive behavior over time, however, has not been considered and modeled systematically. Furthermore, the…

Eleventh-Grade High School Students' Accounts of Mathematical Metacognitive Knowledge: Explicitness and Systematicity

ERIC Educational Resources Information Center

van Velzen, Joke H.

2016-01-01

Theoretically, it has been argued that a conscious understanding of metacognitive knowledge requires that this knowledge is explicit and systematic. The purpose of this descriptive study was to obtain a better understanding of explicitness and systematicity in knowledge of the mathematical problem-solving process. Eighteen 11th-grade…

A Cognitive Analysis of Students’ Mathematical Communication Ability on Geometry

NASA Astrophysics Data System (ADS)

Sari, D. S.; Kusnandi, K.; Suhendra, S.

2017-09-01

This study aims to analyze the difficulties of mathematical communication ability of students in one of secondary school on “three-dimensional space” topic. This research conducted by using quantitative approach with descriptive method. The population in this research was all students of that school and the sample was thirty students that was chosen by purposive sampling technique. Data of mathematical communication were collected through essay test. Furthermore, the data were analyzed with a descriptive way. The results of this study indicate that the percentage of achievement of student mathematical communication indicators as follows 1) Stating a situation, ideas, and mathematic correlation into images, graphics, or algebraic expressions is 35%; 2) Stating daily experience into a mathematic language / symbol, or a mathematic model is 35%; and 3) Associating images or diagrams into mathematical ideas is 53.3%. Based on the percentage of achievement on each indicator, it can be concluded that the level of achievement of students’ mathematical communication ability is still low. It can be caused the students were not used to convey or write their mathematical ideas systematically. Therefore students’ mathematical communication ability need to be improved.

A Systematic Review of the Literature on Mathematics Manipulatives to Support Students with Disabilities

ERIC Educational Resources Information Center

Bouck, Emily C.; Park, Jiyoon

2018-01-01

Manipulatives are considered a common tool for mathematics teaching and learning, for both students with and without disabilities. Yet, a systematic review of the current state of research regarding manipulatives for students with disabilities did not exist prior to this article. This manuscript presents a systematic review of the literature…

DEPOSITION OF SULFATE ACID AEROSOLS IN THE DEVELOPING HUMAN LUNG

EPA Science Inventory

Computations of aerosol deposition as affected by (i) aerosol hygroscopicity, (ii) human age, and (iii) respiratory intensity are accomplished using a validated mathematical model. he interactive effects are very complicated but systematic. ew general observations can be made; ra...

FACTORS AFFECTING THE DEPOSITION OF INHALED POROUS DRUG PARTICLES

EPA Science Inventory

Abstract
Recent findings indicate that the inhalation of large manufactured porous particles may be particularly effective for drug delivery. In this study, a mathematical model was employed to systematically investigate the effects of particle size, particle density, aerosol ...

Mathematics for understanding disease.

PubMed

Bies, R R; Gastonguay, M R; Schwartz, S L

2008-06-01

The application of mathematical models to reflect the organization and activity of biological systems can be viewed as a continuum of purpose. The far left of the continuum is solely the prediction of biological parameter values, wherein an understanding of the underlying biological processes is irrelevant to the purpose. At the far right of the continuum are mathematical models, the purposes of which are a precise understanding of those biological processes. No models in present use fall at either end of the continuum. Without question, however, the emphasis in regards to purpose has been on prediction, e.g., clinical trial simulation and empirical disease progression modeling. Clearly the model that ultimately incorporates a universal understanding of biological organization will also precisely predict biological events, giving the continuum the logical form of a tautology. Currently that goal lies at an immeasurable distance. Nonetheless, the motive here is to urge movement in the direction of that goal. The distance traveled toward understanding naturally depends upon the nature of the scientific question posed with respect to comprehending and/or predicting a particular disease process. A move toward mathematical models implies a move away from static empirical modeling and toward models that focus on systems biology, wherein modeling entails the systematic study of the complex pattern of organization inherent in biological systems.

Exploring Measurement Error with Cookies: A Real and Virtual Approach via Interactive Excel

ERIC Educational Resources Information Center

Sinex, Scott A; Gage, Barbara A.; Beck, Peggy J.

2007-01-01

A simple, guided-inquiry investigation using stacked sandwich cookies is employed to develop a simple linear mathematical model and to explore measurement error by incorporating errors as part of the investigation. Both random and systematic errors are presented. The model and errors are then investigated further by engaging with an interactive…

Applying an alternative mathematics pedagogy for students with weak mathematics: meta-analysis of alternative pedagogies

NASA Astrophysics Data System (ADS)

Lake, Warren; Wallin, Margie; Woolcott, Geoff; Boyd, Wendy; Foster, Alan; Markopoulos, Christos; Boyd, William

2017-02-01

Student mathematics performance and the need for work-ready graduates to be mathematics-competent is a core issue for many universities. While both student and teacher are responsible for learning outcomes, there is a need to explicitly acknowledge the weak mathematics foundation of many university students. A systematic literature review was undertaken of identified innovations and/or interventions that may lead to improvement in student outcomes for university mathematics-based units of study. The review revealed the importance of understanding the foundations of student performance in higher education mathematics learning, especially in first year. Pre-university mathematics skills were identified as significant in student retention and mathematics success at university, and a specific focus on student pre-university mathematics skill level was found to be more effective in providing help, rather than simply focusing on a particular at-risk group. Diagnostics tools were found to be important in identifying (1) student background and (2) appropriate intervention. The studies highlighted the importance of appropriate and validated interventions in mathematics teaching and learning, and the need to improve the learning model for mathematics-based subjects, communication and technology innovations.

Systematic Assessment Through Mathematical Model For Sustainability Reporting In Malaysia Context

NASA Astrophysics Data System (ADS)

Lanang, Wan Nurul Syahirah Wan; Turan, Faiz Mohd; Johan, Kartina

2017-08-01

Sustainability assessment have been studied and increasingly recognized as a powerful and valuable tool to measure the performance of sustainability in a company or industry. Nowadays, there are many existing tools that the users can use for sustainable development. There are various initiatives exists on tools for sustainable development, though most of the tools focused on environmental, economy and social aspects. Using the Green Project Management (GPM) P5 concept that suggests the firms not only needs to engage in mainly 3Ps principle: planet, profit, people responsible behaviours, but also, product and process need to be included in the practices, this study will introduce a new mathematical model for assessing the level of sustainability practice in the company. Based on multiple case studies, involving in-depth interviews with senior directors, feedback from experts, and previous engineering report, a systematic approach is done with the aims to obtain the respective data from the feedbacks and to be developed into a new mathematical model. By reviewing on the methodology of this research it comprises of several phases where it starts with the analyzation of the parameters and criteria selection according to the Malaysian context of industry. Moving on to the next step is data analysis involving regression and finally the normalisation process will be done to determine the result of this research either succeeded or not. Lastly, this study is expected to provide a clear guideline to any company or organization to assimilate the sustainability assessment in their development stage. In future, the better understanding towards the sustainability assessment is attained to be aligned unitedly in order to integrated the process approach into the systematic approach for the sustainability assessment.

Rescheduling nursing shifts: scoping the challenge and examining the potential of mathematical model based tools.

PubMed

Clark, Alistair; Moule, Pam; Topping, Annie; Serpell, Martin

2015-05-01

To review research in the literature on nursing shift scheduling / rescheduling, and to report key issues identified in a consultation exercise with managers in four English National Health Service trusts to inform the development of mathematical tools for rescheduling decision-making. Shift rescheduling is unrecognised as an everyday time-consuming management task with different imperatives from scheduling. Poor rescheduling decisions can have quality, cost and morale implications. A systematic critical literature review identified rescheduling issues and existing mathematic modelling tools. A consultation exercise with nursing managers examined the complex challenges associated with rescheduling. Minimal research exists on rescheduling compared with scheduling. Poor rescheduling can result in greater disruption to planned nursing shifts and may impact negatively on the quality and cost of patient care, and nurse morale and retention. Very little research examines management challenges or mathematical modelling for rescheduling. Shift rescheduling is a complex and frequent management activity that is more challenging than scheduling. Mathematical modelling may have potential as a tool to support managers to minimise rescheduling disruption. The lack of specific methodological support for rescheduling that takes into account its complexity, increases the likelihood of harm for patients and stress for nursing staff and managers. © 2013 John Wiley & Sons Ltd.

Hybrid semi-parametric mathematical systems: bridging the gap between systems biology and process engineering.

PubMed

Teixeira, Ana P; Carinhas, Nuno; Dias, João M L; Cruz, Pedro; Alves, Paula M; Carrondo, Manuel J T; Oliveira, Rui

2007-12-01

Systems biology is an integrative science that aims at the global characterization of biological systems. Huge amounts of data regarding gene expression, proteins activity and metabolite concentrations are collected by designing systematic genetic or environmental perturbations. Then the challenge is to integrate such data in a global model in order to provide a global picture of the cell. The analysis of these data is largely dominated by nonparametric modelling tools. In contrast, classical bioprocess engineering has been primarily founded on first principles models, but it has systematically overlooked the details of the embedded biological system. The full complexity of biological systems is currently assumed by systems biology and this knowledge can now be taken by engineers to decide how to optimally design and operate their processes. This paper discusses possible methodologies for the integration of systems biology and bioprocess engineering with emphasis on applications involving animal cell cultures. At the mathematical systems level, the discussion is focused on hybrid semi-parametric systems as a way to bridge systems biology and bioprocess engineering.

Herpes Zoster Risk Reduction through Exposure to Chickenpox Patients: A Systematic Multidisciplinary Review

PubMed Central

Ogunjimi, Benson; Van Damme, Pierre; Beutels, Philippe

2013-01-01

Varicella-zoster virus (VZV) causes chickenpox and may subsequently reactivate to cause herpes zoster later in life. The exogenous boosting hypothesis states that re-exposure to circulating VZV can inhibit VZV reactivation and consequently also herpes zoster in VZV-immune individuals. Using this hypothesis, mathematical models predicted widespread chickenpox vaccination to increase herpes zoster incidence over more than 30 years. Some countries have postponed universal chickenpox vaccination, at least partially based on this prediction. After a systematic search and selection procedure, we analyzed different types of exogenous boosting studies. We graded 13 observational studies on herpes zoster incidence after widespread chickenpox vaccination, 4 longitudinal studies on VZV immunity after re-exposure, 9 epidemiological risk factor studies, 7 mathematical modeling studies as well as 7 other studies. We conclude that exogenous boosting exists, although not for all persons, nor in all situations. Its magnitude is yet to be determined adequately in any study field. PMID:23805224

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

Yan, Ruqiang; Chen, Xuefeng; Li, Weihua

Modern mathematics has commonly been utilized as an effective tool to model mechanical equipment so that their dynamic characteristics can be studied analytically. This will help identify potential failures of mechanical equipment by observing change in the equipment’s dynamic parameters. On the other hand, dynamic signals are also important and provide reliable information about the equipment’s working status. Modern mathematics has also provided us with a systematic way to design and implement various signal processing methods, which are used to analyze these dynamic signals, and to enhance intrinsic signal components that are directly related to machine failures. This special issuemore » is aimed at stimulating not only new insights on mathematical methods for modeling but also recently developed signal processing methods, such as sparse decomposition with potential applications in machine fault diagnosis. Finally, the papers included in this special issue provide a glimpse into some of the research and applications in the field of machine fault diagnosis through applications of the modern mathematical methods.« less

Educator Perceptions of Response to Intervention

ERIC Educational Resources Information Center

DeLoach, Darcia

2017-01-01

Response to Intervention (RTI) is a research-based process in which students are provided timely intensive interventions. No longer adopting "wait to fail" models, this paradigm shift has challenged educators to employ systematic mathematics interventions which has been reported as challenging to implement within high schools. Therefore,…

HIV Treatment as Prevention: Systematic Comparison of Mathematical Models of the Potential Impact of Antiretroviral Therapy on HIV Incidence in South Africa

PubMed Central

Eaton, Jeffrey W.; Johnson, Leigh F.; Salomon, Joshua A.; Bärnighausen, Till; Bendavid, Eran; Bershteyn, Anna; Bloom, David E.; Cambiano, Valentina; Fraser, Christophe; Hontelez, Jan A. C.; Humair, Salal; Klein, Daniel J.; Long, Elisa F.; Phillips, Andrew N.; Pretorius, Carel; Stover, John; Wenger, Edward A.; Williams, Brian G.; Hallett, Timothy B.

2012-01-01

Background Many mathematical models have investigated the impact of expanding access to antiretroviral therapy (ART) on new HIV infections. Comparing results and conclusions across models is challenging because models have addressed slightly different questions and have reported different outcome metrics. This study compares the predictions of several mathematical models simulating the same ART intervention programmes to determine the extent to which models agree about the epidemiological impact of expanded ART. Methods and Findings Twelve independent mathematical models evaluated a set of standardised ART intervention scenarios in South Africa and reported a common set of outputs. Intervention scenarios systematically varied the CD4 count threshold for treatment eligibility, access to treatment, and programme retention. For a scenario in which 80% of HIV-infected individuals start treatment on average 1 y after their CD4 count drops below 350 cells/µl and 85% remain on treatment after 3 y, the models projected that HIV incidence would be 35% to 54% lower 8 y after the introduction of ART, compared to a counterfactual scenario in which there is no ART. More variation existed in the estimated long-term (38 y) reductions in incidence. The impact of optimistic interventions including immediate ART initiation varied widely across models, maintaining substantial uncertainty about the theoretical prospect for elimination of HIV from the population using ART alone over the next four decades. The number of person-years of ART per infection averted over 8 y ranged between 5.8 and 18.7. Considering the actual scale-up of ART in South Africa, seven models estimated that current HIV incidence is 17% to 32% lower than it would have been in the absence of ART. Differences between model assumptions about CD4 decline and HIV transmissibility over the course of infection explained only a modest amount of the variation in model results. Conclusions Mathematical models evaluating the impact of ART vary substantially in structure, complexity, and parameter choices, but all suggest that ART, at high levels of access and with high adherence, has the potential to substantially reduce new HIV infections. There was broad agreement regarding the short-term epidemiologic impact of ambitious treatment scale-up, but more variation in longer term projections and in the efficiency with which treatment can reduce new infections. Differences between model predictions could not be explained by differences in model structure or parameterization that were hypothesized to affect intervention impact. Please see later in the article for the Editors' Summary PMID:22802730

Systematic, Cooperative Evaluation.

ERIC Educational Resources Information Center

Nassif, Paula M.

Evaluation procedures based on a systematic evaluation methodology, decision-maker validity, new measurement and design techniques, low cost, and a high level of cooperation on the part of the school staff were used in the assessment of a public school mathematics program for grades 3-8. The mathematics curriculum was organized into Spirals which…

Interaction of mathematical modeling and social and behavioral HIV/AIDS research.

PubMed

Cassels, Susan; Goodreau, Steven M

2011-03-01

HIV is transmitted within complex biobehavioral systems. Mathematical modeling can provide insight to complex population-level outcomes of various behaviors measured at an individual level. HIV models in the social and behavioral sciences can be categorized in a number of ways; here, we consider two classes of applications common in the field generally, and in the past year in particular: those models that explore significant behavioral determinants of HIV disparities within and between populations; and those models that seek to evaluate the potential impact of specific social and behavioral interventions. We discuss two overarching issues we see in the field: the need to further systematize effectiveness models of behavioral interventions, and the need for increasing investigation of the use of behavioral data in epidemic models. We believe that a recent initiative by the National Institutes of Health will qualitatively change the relationships between epidemic modeling and sociobehavioral prevention research in the coming years.

A heuristic mathematical model for the dynamics of sensory conflict and motion sickness

NASA Technical Reports Server (NTRS)

Oman, C. M.

1982-01-01

By consideration of the information processing task faced by the central nervous system in estimating body spatial orientation and in controlling active body movement using an internal model referenced control strategy, a mathematical model for sensory conflict generation is developed. The model postulates a major dynamic functional role for sensory conflict signals in movement control, as well as in sensory-motor adaptation. It accounts for the role of active movement in creating motion sickness symptoms in some experimental circumstance, and in alleviating them in others. The relationship between motion sickness produced by sensory rearrangement and that resulting from external motion disturbances is explicitly defined. A nonlinear conflict averaging model is proposed which describes dynamic aspects of experimentally observed subjective discomfort sensation, and suggests resulting behaviours. The model admits several possibilities for adaptive mechanisms which do not involve internal model updating. Further systematic efforts to experimentally refine and validate the model are indicated.

Forecasting--A Systematic Modeling Methodology. Paper No. 489.

ERIC Educational Resources Information Center

Mabert, Vincent A.; Radcliffe, Robert C.

In an attempt to bridge the gap between academic understanding and practical business use, the Box-Jenkins technique of time series analysis for forecasting future events is presented with a minimum of mathematical notation. The method is presented in three stages: a discussion of traditional forecasting techniques, focusing on traditional…

Bridging the gap between evidence and policy for infectious diseases: How models can aid public health decision-making.

PubMed

Knight, Gwenan M; Dharan, Nila J; Fox, Gregory J; Stennis, Natalie; Zwerling, Alice; Khurana, Renuka; Dowdy, David W

2016-01-01

The dominant approach to decision-making in public health policy for infectious diseases relies heavily on expert opinion, which often applies empirical evidence to policy questions in a manner that is neither systematic nor transparent. Although systematic reviews are frequently commissioned to inform specific components of policy (such as efficacy), the same process is rarely applied to the full decision-making process. Mathematical models provide a mechanism through which empirical evidence can be methodically and transparently integrated to address such questions. However, such models are often considered difficult to interpret. In addition, models provide estimates that need to be iteratively re-evaluated as new data or considerations arise. Using the case study of a novel diagnostic for tuberculosis, a framework for improved collaboration between public health decision-makers and mathematical modellers that could lead to more transparent and evidence-driven policy decisions for infectious diseases in the future is proposed. The framework proposes that policymakers should establish long-term collaborations with modellers to address key questions, and that modellers should strive to provide clear explanations of the uncertainty of model structure and outputs. Doing so will improve the applicability of models and clarify their limitations when used to inform real-world public health policy decisions. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Regulatory T cell effects in antitumor laser immunotherapy: a mathematical model and analysis

NASA Astrophysics Data System (ADS)

Dawkins, Bryan A.; Laverty, Sean M.

2016-03-01

Regulatory T cells (Tregs) have tremendous influence on treatment outcomes in patients receiving immunotherapy for cancerous tumors. We present a mathematical model incorporating the primary cellular and molecular components of antitumor laser immunotherapy. We explicitly model developmental classes of dendritic cells (DCs), cytotoxic T cells (CTLs), primary and metastatic tumor cells, and tumor antigen. Regulatory T cells have been shown to kill antigen presenting cells, to influence dendritic cell maturation and migration, to kill activated killer CTLs in the tumor microenvironment, and to influence CTL proliferation. Since Tregs affect explicitly modeled cells, but we do not explicitly model dynamics of Treg themselves, we use model parameters to analyze effects of Treg immunosuppressive activity. We will outline a systematic method for assigning clinical outcomes to model simulations and use this condition to associate simulated patient treatment outcome with Treg activity.

Mathematical Models of Breast and Ovarian Cancers

PubMed Central

Botesteanu, Dana-Adriana; Lipkowitz, Stanley; Lee, Jung-Min; Levy, Doron

2016-01-01

Women constitute the majority of the aging United States (US) population, and this has substantial implications on cancer population patterns and management practices. Breast cancer is the most common women's malignancy, while ovarian cancer is the most fatal gynecological malignancy in the US. In this review we focus on these subsets of women's cancers, seen more commonly in postmenopausal and elderly women. In order to systematically investigate the complexity of cancer progression and response to treatment in breast and ovarian malignancies, we assert that integrated mathematical modeling frameworks viewed from a systems biology perspective are needed. Such integrated frameworks could offer innovative contributions to the clinical women's cancers community, since answers to clinical questions cannot always be reached with contemporary clinical and experimental tools. Here, we recapitulate clinically known data regarding the progression and treatment of the breast and ovarian cancers. We compare and contrast the two malignancies whenever possible, in order to emphasize areas where substantial contributions could be made by clinically inspired and validated mathematical modeling. We show how current paradigms in the mathematical oncology community focusing on the two malignancies do not make comprehensive use of, nor substantially reflect existing clinical data, and we highlight the modeling areas in most critical need of clinical data integration. We emphasize that the primary goal of any mathematical study of women's cancers should be to address clinically relevant questions. PMID:27259061

Modeling Criminal Activity in Urban Landscapes

NASA Astrophysics Data System (ADS)

Brantingham, Patricia; Glässer, Uwe; Jackson, Piper; Vajihollahi, Mona

Computational and mathematical methods arguably have an enormous potential for serving practical needs in crime analysis and prevention by offering novel tools for crime investigations and experimental platforms for evidence-based policy making. We present a comprehensive formal framework and tool support for mathematical and computational modeling of criminal behavior to facilitate systematic experimental studies of a wide range of criminal activities in urban environments. The focus is on spatial and temporal aspects of different forms of crime, including opportunistic and serial violent crimes. However, the proposed framework provides a basis to push beyond conventional empirical research and engage the use of computational thinking and social simulations in the analysis of terrorism and counter-terrorism.

Crossroads in the History of Mathematics and Mathematics Education. The Montana Mathematics Enthusiast: Monograph Series in Mathematics Education

ERIC Educational Resources Information Center

Sriraman, Bharath, Ed.

2012-01-01

The interaction of the history of mathematics and mathematics education has long been construed as an esoteric area of inquiry. Much of the research done in this realm has been under the auspices of the history and pedagogy of mathematics group. However there is little systematization or consolidation of the existing literature aimed at…

From MIMO-OFDM Algorithms to a Real-Time Wireless Prototype: A Systematic Matlab-to-Hardware Design Flow

NASA Astrophysics Data System (ADS)

Weijers, Jan-Willem; Derudder, Veerle; Janssens, Sven; Petré, Frederik; Bourdoux, André

2006-12-01

To assess the performance of forthcoming 4th generation wireless local area networks, the algorithmic functionality is usually modelled using a high-level mathematical software package, for instance, Matlab. In order to validate the modelling assumptions against the real physical world, the high-level functional model needs to be translated into a prototype. A systematic system design methodology proves very valuable, since it avoids, or, at least reduces, numerous design iterations. In this paper, we propose a novel Matlab-to-hardware design flow, which allows to map the algorithmic functionality onto the target prototyping platform in a systematic and reproducible way. The proposed design flow is partly manual and partly tool assisted. It is shown that the proposed design flow allows to use the same testbench throughout the whole design flow and avoids time-consuming and error-prone intermediate translation steps.

Model-Based Phenotypic Signatures Governing the Dynamics of the Stem and Semi-differentiated Cell Populations in Dysplastic Colonic Crypts.

PubMed

Nikolov, Svetoslav; Santos, Guido; Wolkenhauer, Olaf; Vera, Julio

2018-02-01

Mathematical modeling of cell differentiated in colonic crypts can contribute to a better understanding of basic mechanisms underlying colonic tissue organization, but also its deregulation during carcinogenesis and tumor progression. Here, we combined bifurcation analysis to assess the effect that time delay has in the complex interplay of stem cells and semi-differentiated cells at the niche of colonic crypts, and systematic model perturbation and simulation to find model-based phenotypes linked to cancer progression. The models suggest that stem cell and semi-differentiated cell population dynamics in colonic crypts can display chaotic behavior. In addition, we found that clinical profiling of colorectal cancer correlates with the in silico phenotypes proposed by the mathematical model. Further, potential therapeutic targets for chemotherapy resistant phenotypes are proposed, which in any case will require experimental validation.

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.

Development of Systematic Approaches for Calibration of Subsurface Transport Models Using Hard and Soft Data on System Characteristics and Behavior

DTIC Science & Technology

2011-02-02

who graduated during this period and will receive scholarships or fellowships for further studies in science, mathematics, engineering or technology...nature or are collected at discrete points or localized areas in the system. The qualitative data includes, geology , large-scale stratigraphy and

Applying an Alternative Mathematics Pedagogy for Students with Weak Mathematics: Meta-Analysis of Alternative Pedagogies

ERIC Educational Resources Information Center

Lake, Warren; Wallin, Margie; Woolcott, Geoff; Boyd, Wendy; Foster, Alan; Markopoulos, Christos; Boyd, William

2017-01-01

Student mathematics performance and the need for work-ready graduates to be mathematics-competent is a core issue for many universities. While both student and teacher are responsible for learning outcomes, there is a need to explicitly acknowledge the weak mathematics foundation of many university students. A systematic literature review was…

The Effects of a Tier 3 Intervention on the Mathematics Performance of Second Grade Students with Severe Mathematics Difficulties

ERIC Educational Resources Information Center

Bryant, Brian R.; Bryant, Diane Pedrotty; Porterfield, Jennifer; Dennis, Minyi Shih; Falcomata, Terry; Valentine, Courtney; Brewer, Chelsea; Bell, Kathy

2016-01-01

The purpose of this study was to determine the effectiveness of a systematic, explicit, intensive Tier 3 (tertiary) intervention on the mathematics performance of students in second grade with severe mathematics difficulties. A multiple-baseline design across groups of participants showed improved mathematics performance on number and operations…

Systematic investigation of non-Boussinesq effects in variable-density groundwater flow simulations.

PubMed

Guevara Morel, Carlos R; van Reeuwijk, Maarten; Graf, Thomas

2015-12-01

The validity of three mathematical models describing variable-density groundwater flow is systematically evaluated: (i) a model which invokes the Oberbeck-Boussinesq approximation (OB approximation), (ii) a model of intermediate complexity (NOB1) and (iii) a model which solves the full set of equations (NOB2). The NOB1 and NOB2 descriptions have been added to the HydroGeoSphere (HGS) model, which originally contained an implementation of the OB description. We define the Boussinesq parameter ερ=βω Δω where βω is the solutal expansivity and Δω is the characteristic difference in solute mass fraction. The Boussinesq parameter ερ is used to systematically investigate three flow scenarios covering a range of free and mixed convection problems: 1) the low Rayleigh number Elder problem (Van Reeuwijk et al., 2009), 2) a convective fingering problem (Xie et al., 2011) and 3) a mixed convective problem (Schincariol et al., 1994). Results indicate that small density differences (ερ≤ 0.05) produce no apparent changes in the total solute mass in the system, plume penetration depth, center of mass and mass flux independent of the mathematical model used. Deviations between OB, NOB1 and NOB2 occur for large density differences (ερ>0.12), where lower description levels will underestimate the vertical plume position and overestimate mass flux. Based on the cases considered here, we suggest the following guidelines for saline convection: the OB approximation is valid for cases with ερ<0.05, and the full NOB set of equations needs to be used for cases with ερ>0.10. Whether NOB effects are important in the intermediate region differ from case to case. Copyright © 2015 Elsevier B.V. All rights reserved.

Review: To be or not to be an identifiable model. Is this a relevant question in animal science modelling?

PubMed

Muñoz-Tamayo, R; Puillet, L; Daniel, J B; Sauvant, D; Martin, O; Taghipoor, M; Blavy, P

2018-04-01

What is a good (useful) mathematical model in animal science? For models constructed for prediction purposes, the question of model adequacy (usefulness) has been traditionally tackled by statistical analysis applied to observed experimental data relative to model-predicted variables. However, little attention has been paid to analytic tools that exploit the mathematical properties of the model equations. For example, in the context of model calibration, before attempting a numerical estimation of the model parameters, we might want to know if we have any chance of success in estimating a unique best value of the model parameters from available measurements. This question of uniqueness is referred to as structural identifiability; a mathematical property that is defined on the sole basis of the model structure within a hypothetical ideal experiment determined by a setting of model inputs (stimuli) and observable variables (measurements). Structural identifiability analysis applied to dynamic models described by ordinary differential equations (ODEs) is a common practice in control engineering and system identification. This analysis demands mathematical technicalities that are beyond the academic background of animal science, which might explain the lack of pervasiveness of identifiability analysis in animal science modelling. To fill this gap, in this paper we address the analysis of structural identifiability from a practitioner perspective by capitalizing on the use of dedicated software tools. Our objectives are (i) to provide a comprehensive explanation of the structural identifiability notion for the community of animal science modelling, (ii) to assess the relevance of identifiability analysis in animal science modelling and (iii) to motivate the community to use identifiability analysis in the modelling practice (when the identifiability question is relevant). We focus our study on ODE models. By using illustrative examples that include published mathematical models describing lactation in cattle, we show how structural identifiability analysis can contribute to advancing mathematical modelling in animal science towards the production of useful models and, moreover, highly informative experiments via optimal experiment design. Rather than attempting to impose a systematic identifiability analysis to the modelling community during model developments, we wish to open a window towards the discovery of a powerful tool for model construction and experiment design.

General Mathematics; Part 1. Mathematics Curriculum Guide (Career Oriented).

ERIC Educational Resources Information Center

Nuschler, Alexandra; And Others

The curriculum guide for secondary level, career-oriented General Mathematics Part 1, correlates performance objectives in basic mathematics with career-oriented concepts and activities. The material is designed to lead the student in a systematic development that provides for continuous progress. The guide is in outline format, providing a…

Modeling and Reduction With Applications to Semiconductor Processing

DTIC Science & Technology

1999-01-01

smoothies ,” as they kept my energy level high without resorting to coffee (the beverage of choice, it seems, for graduate students). My advisor gave me all...with POC data, and balancing approach. . . . . . . . . . . . . . . . 312 xii LIST OF FIGURES 1.1 General state-space model reduction methodology ...reduction problem, then, is one of finding a systematic methodology within a given mathematical framework to produce an efficient or optimal trade-off of

Engineering Bacteria to Search for Specific Concentrations of Molecules by a Systematic Synthetic Biology Design Method

PubMed Central

Chen, Bor-Sen

2016-01-01

Bacteria navigate environments full of various chemicals to seek favorable places for survival by controlling the flagella’s rotation using a complicated signal transduction pathway. By influencing the pathway, bacteria can be engineered to search for specific molecules, which has great potential for application to biomedicine and bioremediation. In this study, genetic circuits were constructed to make bacteria search for a specific molecule at particular concentrations in their environment through a synthetic biology method. In addition, by replacing the “brake component” in the synthetic circuit with some specific sensitivities, the bacteria can be engineered to locate areas containing specific concentrations of the molecule. Measured by the swarm assay qualitatively and microfluidic techniques quantitatively, the characteristics of each “brake component” were identified and represented by a mathematical model. Furthermore, we established another mathematical model to anticipate the characteristics of the “brake component”. Based on this model, an abundant component library can be established to provide adequate component selection for different searching conditions without identifying all components individually. Finally, a systematic design procedure was proposed. Following this systematic procedure, one can design a genetic circuit for bacteria to rapidly search for and locate different concentrations of particular molecules by selecting the most adequate “brake component” in the library. Moreover, following simple procedures, one can also establish an exclusive component library suitable for other cultivated environments, promoter systems, or bacterial strains. PMID:27096615

A systematic review of mathematical models of mosquito-borne pathogen transmission: 1970–2010

PubMed Central

Reiner, Robert C.; Perkins, T. Alex; Barker, Christopher M.; Niu, Tianchan; Chaves, Luis Fernando; Ellis, Alicia M.; George, Dylan B.; Le Menach, Arnaud; Pulliam, Juliet R. C.; Bisanzio, Donal; Buckee, Caroline; Chiyaka, Christinah; Cummings, Derek A. T.; Garcia, Andres J.; Gatton, Michelle L.; Gething, Peter W.; Hartley, David M.; Johnston, Geoffrey; Klein, Eili Y.; Michael, Edwin; Lindsay, Steven W.; Lloyd, Alun L.; Pigott, David M.; Reisen, William K.; Ruktanonchai, Nick; Singh, Brajendra K.; Tatem, Andrew J.; Kitron, Uriel; Hay, Simon I.; Scott, Thomas W.; Smith, David L.

2013-01-01

Mathematical models of mosquito-borne pathogen transmission originated in the early twentieth century to provide insights into how to most effectively combat malaria. The foundations of the Ross–Macdonald theory were established by 1970. Since then, there has been a growing interest in reducing the public health burden of mosquito-borne pathogens and an expanding use of models to guide their control. To assess how theory has changed to confront evolving public health challenges, we compiled a bibliography of 325 publications from 1970 through 2010 that included at least one mathematical model of mosquito-borne pathogen transmission and then used a 79-part questionnaire to classify each of 388 associated models according to its biological assumptions. As a composite measure to interpret the multidimensional results of our survey, we assigned a numerical value to each model that measured its similarity to 15 core assumptions of the Ross–Macdonald model. Although the analysis illustrated a growing acknowledgement of geographical, ecological and epidemiological complexities in modelling transmission, most models during the past 40 years closely resemble the Ross–Macdonald model. Modern theory would benefit from an expansion around the concepts of heterogeneous mosquito biting, poorly mixed mosquito-host encounters, spatial heterogeneity and temporal variation in the transmission process. PMID:23407571

Modelling and analysis of gene regulatory network using feedback control theory

NASA Astrophysics Data System (ADS)

El-Samad, H.; Khammash, M.

2010-01-01

Molecular pathways are a part of a remarkable hierarchy of regulatory networks that operate at all levels of organisation. These regulatory networks are responsible for much of the biological complexity within the cell. The dynamic character of these pathways and the prevalence of feedback regulation strategies in their operation make them amenable to systematic mathematical analysis using the same tools that have been used with success in analysing and designing engineering control systems. In this article, we aim at establishing this strong connection through various examples where the behaviour exhibited by gene networks is explained in terms of their underlying control strategies. We complement our analysis by a survey of mathematical techniques commonly used to model gene regulatory networks and analyse their dynamic behaviour.

The written mathematical communication profile of prospective math teacher in mathematical proving

NASA Astrophysics Data System (ADS)

Pantaleon, K. V.; Juniati, D.; Lukito, A.; Mandur, K.

2018-01-01

Written mathematical communication is the process of expressing mathematical ideas and understanding in writing. It is one of the important aspects that must be mastered by the prospective math teacher as tool of knowledge transfer. This research was a qualitative research that aimed to describe the mathematical communication profile of the prospective mathematics teacher in mathematical proving. This research involved 48 students of Mathematics Education Study Program; one of them with moderate math skills was chosen as the main subject. Data were collected through tests, assignments, and task-based interviews. The results of this study point out that in the proof of geometry, the subject explains what is understood, presents the idea in the form of drawing and symbols, and explains the content/meaning of a representation accurately and clearly, but the subject can not convey the argument systematically and logically. Whereas in the proof of algebra, the subject describes what is understood, explains the method used, and describes the content/meaning of a symbolic representation accurately, systematically, logically, but the argument presented is not clear because it is insufficient detailed and complete.

Study on the Influence of Building Materials on Indoor Pollutants and Pollution Sources

NASA Astrophysics Data System (ADS)

Wang, Yao

2018-01-01

The paper summarizes the achievements and problems of indoor air quality research at home and abroad. The pollutants and pollution sources in the room are analyzed systematically. The types of building materials and pollutants are also discussed. The physical and chemical properties and health effects of main pollutants were analyzed and studied. According to the principle of mass balance, the basic mathematical model of indoor air quality is established. Considering the release rate of pollutants and indoor ventilation, a mathematical model for predicting the concentration of indoor air pollutants is derived. The model can be used to analyze and describe the variation of pollutant concentration in indoor air, and to predict and calculate the concentration of pollutants in indoor air at a certain time. The results show that the mathematical model established in this study can be used to analyze and predict the variation law of pollutant concentration in indoor air. The evaluation model can be used to evaluate the impact of indoor air quality and evaluation of current situation. Especially in the process of building and interior decoration, through pre-evaluation, it can provide reliable design parameters for selecting building materials and determining ventilation volume.

Mathematical Modeling and Data Analysis of NMR Experiments using Hyperpolarized 13C Metabolites

PubMed Central

Pagès, Guilhem; Kuchel, Philip W.

2013-01-01

Rapid-dissolution dynamic nuclear polarization (DNP) has made significant impact in the characterization and understanding of metabolism that occurs on the sub-minute timescale in several diseases. While significant efforts have been made in developing applications, and in designing rapid-imaging radiofrequency (RF) and magnetic field gradient pulse sequences, very few groups have worked on implementing realistic mathematical/kinetic/relaxation models to fit the emergent data. The critical aspects to consider when modeling DNP experiments depend on both nuclear magnetic resonance (NMR) and (bio)chemical kinetics. The former constraints are due to the relaxation of the NMR signal and the application of ‘read’ RF pulses, while the kinetic constraints include the total amount of each molecular species present. We describe the model-design strategy we have used to fit and interpret our DNP results. To our knowledge, this is the first report on a systematic analysis of DNP data. PMID:25114541

Methodology of Thermodynamics

ERIC Educational Resources Information Center

Mohan, Gyan

1969-01-01

Presents a systematization of the mathematical formulae in thermodynamics. From the set of thermodynamic variables, four equations are derived which contain the total mathematical jargon of thermodynamics. (LC)

Benchmarking electrophysiological models of human atrial myocytes

PubMed Central

Wilhelms, Mathias; Hettmann, Hanne; Maleckar, Mary M.; Koivumäki, Jussi T.; Dössel, Olaf; Seemann, Gunnar

2013-01-01

Mathematical modeling of cardiac electrophysiology is an insightful method to investigate the underlying mechanisms responsible for arrhythmias such as atrial fibrillation (AF). In past years, five models of human atrial electrophysiology with different formulations of ionic currents, and consequently diverging properties, have been published. The aim of this work is to give an overview of strengths and weaknesses of these models depending on the purpose and the general requirements of simulations. Therefore, these models were systematically benchmarked with respect to general mathematical properties and their ability to reproduce certain electrophysiological phenomena, such as action potential (AP) alternans. To assess the models' ability to replicate modified properties of human myocytes and tissue in cardiac disease, electrical remodeling in chronic atrial fibrillation (cAF) was chosen as test case. The healthy and remodeled model variants were compared with experimental results in single-cell, 1D and 2D tissue simulations to investigate AP and restitution properties, as well as the initiation of reentrant circuits. PMID:23316167

Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology.

PubMed

Koutinas, Michalis; Kiparissides, Alexandros; Pistikopoulos, Efstratios N; Mantalaris, Athanasios

2012-01-01

The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals.

Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology

PubMed Central

Koutinas, Michalis; Kiparissides, Alexandros; Pistikopoulos, Efstratios N.; Mantalaris, Athanasios

2013-01-01

The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals. PMID:24688682

Analyses of Children's Mathematics Proficiency from ECLS-K 1998 and 2010 Cohorts: Why Early Mathematics?

ERIC Educational Resources Information Center

Lee, Joohi; Pant, Mohan D.

2017-01-01

This article presents the correlation analyses of mathematics item response theory scores from the Early Childhood Longitudinal Study, Kindergarten Class of 1998 and 2010 data, and proposes the critical need for systematic efforts to improve the quality of pre- and in-service teachers of young children in teaching mathematics.

Differences in Mathematics Teachers' Perceived Preparedness to Demonstrate Competence in Secondary School Mathematics Content by Teacher Characteristics

ERIC Educational Resources Information Center

Ng'eno, J. K.; Chesimet, M. C.

2016-01-01

A sample of 300 mathematics teachers drawn from a population of 1500 participated in this study. The participants were selected using systematic random sampling and stratified random sampling (stratified by qualification and gender). The data was collected using self-report questionnaires for mathematics teachers. One tool was used to collect…

MAX meets ADAM: a dosimetric comparison between a voxel-based and a mathematical model for external exposure to photons

NASA Astrophysics Data System (ADS)

Kramer, R.; Vieira, J. W.; Khoury, H. J.; Lima, F. de Andrade

2004-03-01

The International Commission on Radiological Protection intends to revise the organ and tissue equivalent dose conversion coefficients published in various reports. For this purpose the mathematical human medical internal radiation dose (MIRD) phantoms, actually in use, have to be replaced by recently developed voxel-based phantoms. This study investigates the dosimetric consequences, especially with respect to the effective male dose, if not only a MIRD phantom is replaced by a voxel phantom, but also if the tissue compositions and the radiation transport codes are changed. This task will be resolved by systematically replacing in the mathematical ADAM/GSF exposure model, first the radiation transport code, then the tissue composition and finally the phantom anatomy, in order to arrive at the voxel-based MAX/EGS4 exposure model. The results show that the combined effect of these replacements can decrease the effective male dose by up to 25% for external exposures to photons for incident energies above 30 keV for different field geometries, mainly because of increased shielding by a heterogeneous skeleton and by the overlying adipose and muscle tissue, and also because of the positions internal organs have in a realistically designed human body compared to their positions in the mathematically constructed phantom.

Mathematical and physical modeling of thermal stratification phenomena in steel ladles

NASA Astrophysics Data System (ADS)

Putan, V.; Vilceanu, L.; Socalici, A.; Putan, A.

2018-01-01

By means of CFD numerical modeling, a systematic analysis of the similarity between steel ladles and hot-water model regarding natural convection phenomena was studied. The key similarity criteria we found to be dependent on the dimensionless numbers Fr and βΔT. These similarity criteria suggested that hot-water models with scale in the range between 1/5 and 1/3 and using hot water with temperature of 45 °C or higher are appropriate for simulating natural convection in steel ladles. With this physical model, thermal stratification phenomena due to natural convection in steel ladles were investigated. By controlling the cooling intensity of water model to correspond to the heat loss rate of steel ladles, which is governed by Fr and βΔT, the temperature profiles measured in the water bath of the model were to deduce the extent of thermal stratification in liquid steel bath in the ladles. Comparisons between mathematically simulated temperature profiles in the prototype steel ladles and those physically simulated by scaling-up the measured temperatures profiles in the water model showed good agreement. This proved that it is feasible to use a 1/5 scale water model with 45 °C hot water to simulate natural convection in steel ladles. Therefore, besides mathematical CFD models, the physical hot-water model provided an additional means of studying fluid flow and heat transfer in steel ladles.

Examining the Association between Explicit Mathematics Instruction and Student Mathematics Achievement

ERIC Educational Resources Information Center

Doabler, Christian T.; Baker, Scott K.; Kosty, Derek B.; Smolkowski, Keith; Clarke, Ben; Miller, Saralyn J.; Fien, Hank

2015-01-01

Explicit instruction is a systematic instructional approach that facilitates frequent and meaningful instructional interactions between teachers and students around critical academic content. This study examined the relationship between student mathematics outcomes and the rate and quality of explicit instructional interactions that occur during…

Integrating Non-Mathematical Domains into Mathematical Development: Key Factors to Consider in Constructing Effective Interventions

ERIC Educational Resources Information Center

Purpura, David J.; Ganley, Colleen

2013-01-01

The successful acquisition and development of mathematics skills and concepts is a critical aspect of children's early academic growth. The purpose of this study was to systematically evaluate the unique relations of working memory and language to a range of specific early mathematics skills in a sample of preschool and kindergarten age children.…

Modeling human target acquisition in ground-to-air weapon systems

NASA Technical Reports Server (NTRS)

Phatak, A. V.; Mohr, R. L.; Vikmanis, M.; Wei, K. C.

1982-01-01

The problems associated with formulating and validating mathematical models for describing and predicting human target acquisition response are considered. In particular, the extension of the human observer model to include the acquisition phase as well as the tracking segment is presented. Relationship of the Observer model structure to the more complex Standard Optimal Control model formulation and to the simpler Transfer Function/Noise representation is discussed. Problems pertinent to structural identifiability and the form of the parameterization are elucidated. A systematic approach toward the identification of the observer acquisition model parameters from ensemble tracking error data is presented.

A Systematic Review of Longitudinal Studies of Mathematics Difficulty.

PubMed

Nelson, Gena; Powell, Sarah R

2017-06-01

Some students may be diagnosed with a learning disability in mathematics or dyscalculia, whereas other students may demonstrate below-grade-level mathematics performance without a disability diagnosis. In the literature, researchers often identify students in both groups as experiencing math difficulty. To understand the performance of students with math difficulty, we examined 35 studies that reported longitudinal results of mathematics achievement (i.e., mathematics performance measured across at least a 12-month span). Our primary goal was to conduct a systematic review of these studies and to understand whether the growth of students with math difficulty was comparable or stagnant when compared with that of students without math difficulty. We also analyzed whether identification of math difficulty was predictive of mathematics achievement in later grades and whether a diagnosis of math difficulty was stable across grade levels. Results indicate that students with math difficulty demonstrate growth on mathematics measures, but this growth still leads to lower performance than that of students without math difficulty. Identification of math difficulty is strongly related to math performance in subsequent grades, and this diagnosis is often stable. Collectively, this literature indicates that students with math difficulty continue to struggle with mathematics in later grades.

Predicting Statistical Response and Extreme Events in Uncertainty Quantification through Reduced-Order Models

NASA Astrophysics Data System (ADS)

Qi, D.; Majda, A.

2017-12-01

A low-dimensional reduced-order statistical closure model is developed for quantifying the uncertainty in statistical sensitivity and intermittency in principal model directions with largest variability in high-dimensional turbulent system and turbulent transport models. Imperfect model sensitivity is improved through a recent mathematical strategy for calibrating model errors in a training phase, where information theory and linear statistical response theory are combined in a systematic fashion to achieve the optimal model performance. The idea in the reduced-order method is from a self-consistent mathematical framework for general systems with quadratic nonlinearity, where crucial high-order statistics are approximated by a systematic model calibration procedure. Model efficiency is improved through additional damping and noise corrections to replace the expensive energy-conserving nonlinear interactions. Model errors due to the imperfect nonlinear approximation are corrected by tuning the model parameters using linear response theory with an information metric in a training phase before prediction. A statistical energy principle is adopted to introduce a global scaling factor in characterizing the higher-order moments in a consistent way to improve model sensitivity. Stringent models of barotropic and baroclinic turbulence are used to display the feasibility of the reduced-order methods. Principal statistical responses in mean and variance can be captured by the reduced-order models with accuracy and efficiency. Besides, the reduced-order models are also used to capture crucial passive tracer field that is advected by the baroclinic turbulent flow. It is demonstrated that crucial principal statistical quantities like the tracer spectrum and fat-tails in the tracer probability density functions in the most important large scales can be captured efficiently with accuracy using the reduced-order tracer model in various dynamical regimes of the flow field with distinct statistical structures.

Modeling Viral Spread

PubMed Central

Graw, Frederik; Perelson, Alan S.

2016-01-01

The way in which a viral infection spreads within a host is a complex process that is not well understood. Different viruses, such as human immunodeficiency virus type 1 and hepatitis C virus, have evolved different strategies, including direct cell-to-cell transmission and cell-free transmission, to spread within a host. To what extent these two modes of transmission are exploited in vivo is still unknown. Mathematical modeling has been an essential tool to get a better systematic and quantitative understanding of viral processes that are difficult to discern through strictly experimental approaches. In this review, we discuss recent attempts that combine experimental data and mathematical modeling in order to determine and quantify viral transmission modes. We also discuss the current challenges for a systems-level understanding of viral spread, and we highlight the promises and challenges that novel experimental techniques and data will bring to the field. PMID:27618637

Modelling Of Flotation Processes By Classical Mathematical Methods - A Review

NASA Astrophysics Data System (ADS)

Jovanović, Ivana; Miljanović, Igor

2015-12-01

Flotation process modelling is not a simple task, mostly because of the process complexity, i.e. the presence of a large number of variables that (to a lesser or a greater extent) affect the final outcome of the mineral particles separation based on the differences in their surface properties. The attempts toward the development of the quantitative predictive model that would fully describe the operation of an industrial flotation plant started in the middle of past century and it lasts to this day. This paper gives a review of published research activities directed toward the development of flotation models based on the classical mathematical rules. The description and systematization of classical flotation models were performed according to the available references, with emphasize exclusively given to the flotation process modelling, regardless of the model application in a certain control system. In accordance with the contemporary considerations, models were classified as the empirical, probabilistic, kinetic and population balance types. Each model type is presented through the aspects of flotation modelling at the macro and micro process levels.

Analyzing neuronal networks using discrete-time dynamics

NASA Astrophysics Data System (ADS)

Ahn, Sungwoo; Smith, Brian H.; Borisyuk, Alla; Terman, David

2010-05-01

We develop mathematical techniques for analyzing detailed Hodgkin-Huxley like models for excitatory-inhibitory neuronal networks. Our strategy for studying a given network is to first reduce it to a discrete-time dynamical system. The discrete model is considerably easier to analyze, both mathematically and computationally, and parameters in the discrete model correspond directly to parameters in the original system of differential equations. While these networks arise in many important applications, a primary focus of this paper is to better understand mechanisms that underlie temporally dynamic responses in early processing of olfactory sensory information. The models presented here exhibit several properties that have been described for olfactory codes in an insect’s Antennal Lobe. These include transient patterns of synchronization and decorrelation of sensory inputs. By reducing the model to a discrete system, we are able to systematically study how properties of the dynamics, including the complex structure of the transients and attractors, depend on factors related to connectivity and the intrinsic and synaptic properties of cells within the network.

The Role of Cooperative Learning Type Team Assisted Individualization to Improve the Students' Mathematics Communication Ability in the Subject of Probability Theory

ERIC Educational Resources Information Center

Tinungki, Georgina Maria

2015-01-01

The importance of learning mathematics can not be separated from its role in all aspects of life. Communicating ideas by using mathematics language is even more practical, systematic, and efficient. In order to overcome the difficulties of students who have insufficient understanding of mathematics material, good communications should be built in…

Electrical features of new DNC, CNC system viewed

NASA Astrophysics Data System (ADS)

Fritzsch, W.; Kochan, D.; Schaller, J.; Zander, H. J.

1985-03-01

Control structures capable of solving the problems of a flexible minial-labor manufacturing process are analyzed. The present state of development of equipment technology is described, and possible ways of modeling control processes are surveyed. Concepts which are frequently differently interpreted in various specialized disciplines are systematized, with a view toward creating the prerequisites for interdisciplinary cooperation. Problems and information flow during the preparatory and performance phases of manufacturing are examined with respect to coupling CAD/CAM functions. Mathematical modeling for direct numerical control is explored.

Accelerated Math®. Secondary Mathematics. What Works Clearinghouse Intervention Report

ERIC Educational Resources Information Center

What Works Clearinghouse, 2017

2017-01-01

This intervention report presents findings from a systematic review of "Accelerated Math®" conducted using the WWC Procedures and Standards Handbook (version 3.0) and the Secondary Mathematics review protocol (version 3.1). No studies of "Accelerated Math®" that fall within the scope of the Secondary Mathematics review protocol…

Diversifying Our Perspectives on Mathematics about Space and Geometry: An Ecocultural Approach

ERIC Educational Resources Information Center

Owens, Kay

2014-01-01

School mathematics tends to have developed from the major cultures of Asia, the Mediterranean and Europe. However, indigenous cultures in particular may have distinctly different systematic ways of referring to space and thinking mathematically about spatial activity. Their approaches are based on the close link between the environment and…

Persisting mathematics and science high school teachers: A Q-methodology study

NASA Astrophysics Data System (ADS)

Robbins-Lavicka, Michelle M.

There is a lack of qualified mathematics and science teachers at all levels of education in Arkansas. Lasting teaching initiative programs are needed to address retention so qualified teachers remain in the classroom. The dearth of studies regarding why mathematics and science teachers persist in the classroom beyond the traditional 5-year attrition period led this Q-methodological study to evaluate the subjective perceptions of persistent mathematics and science teachers to determine what makes them stay. This study sought to understand what factors persisting mathematics and science teachers used to explain their persistence in the classroom beyond 5 years and what educational factors contributed to persisting mathematics and science teachers. Q-methodology combines qualitative and quantitative techniques and provided a systematic means to investigate personal beliefs by collecting a concourse, developing a Q-sample and a person-sample, conducting a Q-sorting process, and analyzing the data. The results indicated that to encourage longevity within mathematics and science classrooms (a) teachers should remain cognizant of their ability to influence student attitudes toward teaching; (b) administrators should provide support for teachers and emphasize the role and importance of professional development; and (c) policy makers should focus their efforts and resources on developing recruitment plans, including mentorship programs, while providing and improving financial compensation. Significantly, the findings indicate that providing mentorship and role models at every level of mathematics and science education will likely encourage qualified teachers to remain in the mathematics and science classrooms, thus increasing the chance of positive social change.

Path integration mediated systematic search: a Bayesian model.

PubMed

Vickerstaff, Robert J; Merkle, Tobias

2012-08-21

The systematic search behaviour is a backup system that increases the chances of desert ants finding their nest entrance after foraging when the path integrator has failed to guide them home accurately enough. Here we present a mathematical model of the systematic search that is based on extensive behavioural studies in North African desert ants Cataglyphis fortis. First, a simple search heuristic utilising Bayesian inference and a probability density function is developed. This model, which optimises the short-term nest detection probability, is then compared to three simpler search heuristics and to recorded search patterns of Cataglyphis ants. To compare the different searches a method to quantify search efficiency is established as well as an estimate of the error rate in the ants' path integrator. We demonstrate that the Bayesian search heuristic is able to automatically adapt to increasing levels of positional uncertainty to produce broader search patterns, just as desert ants do, and that it outperforms the three other search heuristics tested. The searches produced by it are also arguably the most similar in appearance to the ant's searches. Copyright © 2012 Elsevier Ltd. All rights reserved.

Animal models for studying homeopathy and high dilutions: conceptual critical review.

PubMed

Bonamin, Leoni Villano; Endler, Peter Christian

2010-01-01

This is a systematic review of the animal models used in studies of high dilutions. The objectives are to analyze methodological quality of papers and reported results, and to highlight key conceptual aspects of high dilution to suggest clues concerning putative mechanisms of action. Papers for inclusion were identified systematically, from the Pubmed-Medline database, using 'Homeopathy' and 'Animal' as keywords. Only original full papers in English published between January 1999 and June 2009 were included, reviews, scientific reports, thesis, older papers, papers extracted from Medline using similar keywords, papers about mixed commercial formulas and books were also considered for discussion only. 31 papers describing 33 experiments were identified for the main analysis and a total of 89 items cited. Systematic analysis of the selected papers yielded evidence of some important intrinsic features of high dilution studies performed in animal models: a) methodological quality was generally adequate, some aspects could be improved; b) convergence between results and materia medica is seen in some studies, pointing toward to the possibility of systematic study of the Similia principle c) both isopathic and Similia models seem useful to understand some complex biological phenomena, such as parasite-host interactions; d) the effects of high dilutions seem to stimulate restoration of a 'stable state', as seen in several experimental models from both descriptive and mathematical points of view. Copyright 2009 The Faculty of Homeopathy. Published by Elsevier Ltd. All rights reserved.

Changing Our Perspective on Space: Place Mathematics as a Human Endeavour

ERIC Educational Resources Information Center

Owens, Kay

2010-01-01

This paper collates some of the systematic ways that different cultural groups refer to space. In some cases, space is more strongly identified in terms of place than in school Indo-European mathematics approaches. The affinity to place does not reduce the efficient, abstract, mathematical system behind the reference but it does strengthen its…

A systematic approach for finding the objective function and active constraints for dynamic flux balance analysis.

PubMed

Nikdel, Ali; Braatz, Richard D; Budman, Hector M

2018-05-01

Dynamic flux balance analysis (DFBA) has become an instrumental modeling tool for describing the dynamic behavior of bioprocesses. DFBA involves the maximization of a biologically meaningful objective subject to kinetic constraints on the rate of consumption/production of metabolites. In this paper, we propose a systematic data-based approach for finding both the biological objective function and a minimum set of active constraints necessary for matching the model predictions to the experimental data. The proposed algorithm accounts for the errors in the experiments and eliminates the need for ad hoc choices of objective function and constraints as done in previous studies. The method is illustrated for two cases: (1) for in silico (simulated) data generated by a mathematical model for Escherichia coli and (2) for actual experimental data collected from the batch fermentation of Bordetella Pertussis (whooping cough).

Mathematical structure of unit systems

NASA Astrophysics Data System (ADS)

Kitano, Masao

2013-05-01

We investigate the mathematical structure of unit systems and the relations between them. Looking over the entire set of unit systems, we can find a mathematical structure that is called preorder (or quasi-order). For some pair of unit systems, there exists a relation of preorder such that one unit system is transferable to the other unit system. The transfer (or conversion) is possible only when all of the quantities distinguishable in the latter system are always distinguishable in the former system. By utilizing this structure, we can systematically compare the representations in different unit systems. Especially, the equivalence class of unit systems (EUS) plays an important role because the representations of physical quantities and equations are of the same form in unit systems belonging to an EUS. The dimension of quantities is uniquely defined in each EUS. The EUS's form a partially ordered set. Using these mathematical structures, unit systems and EUS's are systematically classified and organized as a hierarchical tree.

Taking Stock of 40 Years of Research on Mathematical Learning Disability: Methodological Issues and Future Directions

ERIC Educational Resources Information Center

Lewis, Katherine E.; Fisher, Marie B.

2016-01-01

Although approximately 5-8% of students have a mathematical learning disability (MLD), researchers have yet to develop a consensus operational definition. To examine how MLD has been identified and what mathematics topics have been explored, the authors conducted a systematic review of 165 studies on MLD published between 1974 and 2013. To move…

Toward a mathematical formalism of performance, task difficulty, and activation

NASA Technical Reports Server (NTRS)

Samaras, George M.

1988-01-01

The rudiments of a mathematical formalism for handling operational, physiological, and psychological concepts are developed for use by the man-machine system design engineer. The formalism provides a framework for developing a structured, systematic approach to the interface design problem, using existing mathematical tools, and simplifying the problem of telling a machine how to measure and use performance.

Using Mental Imagery Processes for Teaching and Research in Mathematics and Computer Science

ERIC Educational Resources Information Center

Arnoux, Pierre; Finkel, Alain

2010-01-01

The role of mental representations in mathematics and computer science (for teaching or research) is often downplayed or even completely ignored. Using an ongoing work on the subject, we argue for a more systematic study and use of mental representations, to get an intuition of mathematical concepts, and also to understand and build proofs. We…

3D model of filler melting with micro-beam plasma arc based on additive manufacturing technology

NASA Astrophysics Data System (ADS)

Chen, Weilin; Yang, Tao; Yang, Ruixin

2017-07-01

Additive manufacturing technology is a systematic process based on discrete-accumulation principle, which is derived by the dimension of parts. Aiming at the dimension mathematical model and slicing problems in additive manufacturing process, the constitutive relations between micro-beam plasma welding parameters and the dimension of part were investigated. The slicing algorithm and slicing were also studied based on the dimension characteristics. By using the direct slicing algorithm according to the geometric characteristics of model, a hollow thin-wall spherical part was fabricated by 3D additive manufacturing technology using micro-beam plasma.

Incommensurateness in nanotwinning models of modulated martensites

NASA Astrophysics Data System (ADS)

Benešová, Barbora; Frost, Miroslav; Kampschulte, Malte; Melcher, Christof; Sedlák, Petr; Seiner, Hanuš

2015-11-01

We study the formation of modulated martensites in ferromagnetic shape memory alloys by a mathematical model originating from the nanotwinning concept. The results show that the incommensurateness, systematically observed in experiments for the modulated phases, may be understood as a precursor effect of the intermartensitic transitions, and its appearance does not contradict the nanotwinning concept itself. The model sufficiently explains the different levels of incommensurateness reported from different experimental observations for the 14-layered and 10-layered martensites of the Ni-Mn-Ga alloy and outlines the mechanism of formation of faults in the stacking sequences of these materials.

Uncertainty evaluation of nuclear reaction model parameters using integral and microscopic measurements. Covariances evaluation with CONRAD code

NASA Astrophysics Data System (ADS)

de Saint Jean, C.; Habert, B.; Archier, P.; Noguere, G.; Bernard, D.; Tommasi, J.; Blaise, P.

2010-10-01

In the [eV;MeV] energy range, modelling of the neutron induced reactions are based on nuclear reaction models having parameters. Estimation of co-variances on cross sections or on nuclear reaction model parameters is a recurrent puzzle in nuclear data evaluation. Major breakthroughs were asked by nuclear reactor physicists to assess proper uncertainties to be used in applications. In this paper, mathematical methods developped in the CONRAD code[2] will be presented to explain the treatment of all type of uncertainties, including experimental ones (statistical and systematic) and propagate them to nuclear reaction model parameters or cross sections. Marginalization procedure will thus be exposed using analytical or Monte-Carlo solutions. Furthermore, one major drawback found by reactor physicist is the fact that integral or analytical experiments (reactor mock-up or simple integral experiment, e.g. ICSBEP, …) were not taken into account sufficiently soon in the evaluation process to remove discrepancies. In this paper, we will describe a mathematical framework to take into account properly this kind of information.

Reevaluating the two-representation model of numerical magnitude processing.

PubMed

Jiang, Ting; Zhang, Wenfeng; Wen, Wen; Zhu, Haiting; Du, Han; Zhu, Xiangru; Gao, Xuefei; Zhang, Hongchuan; Dong, Qi; Chen, Chuansheng

2016-01-01

One debate in mathematical cognition centers on the single-representation model versus the two-representation model. Using an improved number Stroop paradigm (i.e., systematically manipulating physical size distance), in the present study we tested the predictions of the two models for number magnitude processing. The results supported the single-representation model and, more importantly, explained how a design problem (failure to manipulate physical size distance) and an analytical problem (failure to consider the interaction between congruity and task-irrelevant numerical distance) might have contributed to the evidence used to support the two-representation model. This study, therefore, can help settle the debate between the single-representation and two-representation models.

A Systematic Approach to Determining the Identifiability of Multistage Carcinogenesis Models.

PubMed

Brouwer, Andrew F; Meza, Rafael; Eisenberg, Marisa C

2017-07-01

Multistage clonal expansion (MSCE) models of carcinogenesis are continuous-time Markov process models often used to relate cancer incidence to biological mechanism. Identifiability analysis determines what model parameter combinations can, theoretically, be estimated from given data. We use a systematic approach, based on differential algebra methods traditionally used for deterministic ordinary differential equation (ODE) models, to determine identifiable combinations for a generalized subclass of MSCE models with any number of preinitation stages and one clonal expansion. Additionally, we determine the identifiable combinations of the generalized MSCE model with up to four clonal expansion stages, and conjecture the results for any number of clonal expansion stages. The results improve upon previous work in a number of ways and provide a framework to find the identifiable combinations for further variations on the MSCE models. Finally, our approach, which takes advantage of the Kolmogorov backward equations for the probability generating functions of the Markov process, demonstrates that identifiability methods used in engineering and mathematics for systems of ODEs can be applied to continuous-time Markov processes. © 2016 Society for Risk Analysis.

Autonomy and Non-autonomy of Angiogenic Cell Movements Revealed by Experiment-Driven Mathematical Modeling.

PubMed

Sugihara, Kei; Nishiyama, Koichi; Fukuhara, Shigetomo; Uemura, Akiyoshi; Arima, Satoshi; Kobayashi, Ryo; Köhn-Luque, Alvaro; Mochizuki, Naoki; Suda, Toshio; Ogawa, Hisao; Kurihara, Hiroki

2015-12-01

Angiogenesis is a multicellular phenomenon driven by morphogenetic cell movements. We recently reported morphogenetic vascular endothelial cell (EC) behaviors to be dynamic and complex. However, the principal mechanisms orchestrating individual EC movements in angiogenic morphogenesis remain largely unknown. Here we present an experiment-driven mathematical model that enables us to systematically dissect cellular mechanisms in branch elongation. We found that cell-autonomous and coordinated actions governed these multicellular behaviors, and a cell-autonomous process sufficiently illustrated essential features of the morphogenetic EC dynamics at both the single-cell and cell-population levels. Through refining our model and experimental verification, we further identified a coordinated mode of tip EC behaviors regulated via a spatial relationship between tip and follower ECs, which facilitates the forward motility of tip ECs. These findings provide insights that enhance our mechanistic understanding of not only angiogenic morphogenesis, but also other types of multicellular phenomenon. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

A review of the meteorological parameters which affect aerial application

NASA Technical Reports Server (NTRS)

Christensen, L. S.; Frost, W.

1979-01-01

The ambient wind field and temperature gradient were found to be the most important parameters. Investigation results indicated that the majority of meteorological parameters affecting dispersion were interdependent and the exact mechanism by which these factors influence the particle dispersion was largely unknown. The types and approximately ranges of instrumented capabilities for a systematic study of the significant meteorological parameters influencing aerial applications were defined. Current mathematical dispersion models were also briefly reviewed. Unfortunately, a rigorous dispersion model which could be applied to aerial application was not available.

Identification of metabolic pathways using pathfinding approaches: a systematic review.

PubMed

Abd Algfoor, Zeyad; Shahrizal Sunar, Mohd; Abdullah, Afnizanfaizal; Kolivand, Hoshang

2017-03-01

Metabolic pathways have become increasingly available for various microorganisms. Such pathways have spurred the development of a wide array of computational tools, in particular, mathematical pathfinding approaches. This article can facilitate the understanding of computational analysis of metabolic pathways in genomics. Moreover, stoichiometric and pathfinding approaches in metabolic pathway analysis are discussed. Three major types of studies are elaborated: stoichiometric identification models, pathway-based graph analysis and pathfinding approaches in cellular metabolism. Furthermore, evaluation of the outcomes of the pathways with mathematical benchmarking metrics is provided. This review would lead to better comprehension of metabolism behaviors in living cells, in terms of computed pathfinding approaches. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

System principles, mathematical models and methods to ensure high reliability of safety systems

NASA Astrophysics Data System (ADS)

Zaslavskyi, V.

2017-04-01

Modern safety and security systems are composed of a large number of various components designed for detection, localization, tracking, collecting, and processing of information from the systems of monitoring, telemetry, control, etc. They are required to be highly reliable in a view to correctly perform data aggregation, processing and analysis for subsequent decision making support. On design and construction phases of the manufacturing of such systems a various types of components (elements, devices, and subsystems) are considered and used to ensure high reliability of signals detection, noise isolation, and erroneous commands reduction. When generating design solutions for highly reliable systems a number of restrictions and conditions such as types of components and various constrains on resources should be considered. Various types of components perform identical functions; however, they are implemented using diverse principles, approaches and have distinct technical and economic indicators such as cost or power consumption. The systematic use of different component types increases the probability of tasks performing and eliminates the common cause failure. We consider type-variety principle as an engineering principle of system analysis, mathematical models based on this principle, and algorithms for solving optimization problems of highly reliable safety and security systems design. Mathematical models are formalized in a class of two-level discrete optimization problems of large dimension. The proposed approach, mathematical models, algorithms can be used for problem solving of optimal redundancy on the basis of a variety of methods and control devices for fault and defects detection in technical systems, telecommunication networks, and energy systems.

Mathematics teachers' conceptions and constraints for changing teaching practices in Brazilian higher education: an analysis through activity theory

NASA Astrophysics Data System (ADS)

Campos, Dilhermando Ferreira; Pinto, Márcia Maria Fusaro

2016-11-01

In recent years, changes in the Brazilian economic and social scenario have generated a growing demand for higher education in the country. In response to this new context, the federal government launched in 2007 a programme aiming at expansion of the enrolment to public higher education. In such environment of changes, several proposals have emerged to adapt the Brazilian federal universities to a new reality. Taking this context into account, the focus of our study is on proposals from the Mathematics Department of the Federal University of Minas Gerais. Their aim is to create a new model of teaching practices for the freshman lessons of the Exact Sciences area, which at first were being experimented in special classrooms of students attending their first course on differential and integral calculus. The data were collected from interviews with students and professors from the mathematics department. They were analyzed and systematized using an activity theory approach. We became instigated by a model developed by Engeström in his study on the changes in the Finnish public health system, considering it as a test (testbench) for activity theory in its application to a particular case. Following Engeström's footsteps when developing his research, we arrived at our own model showing the internal tensions in the activity of reformulation of the courses offered by the Department of Mathematics and in the conceptions of teachers that promote - and constraint - the proposals for change.

Helicopter simulation validation using flight data

NASA Technical Reports Server (NTRS)

Key, D. L.; Hansen, R. S.; Cleveland, W. B.; Abbott, W. Y.

1982-01-01

A joint NASA/Army effort to perform a systematic ground-based piloted simulation validation assessment is described. The best available mathematical model for the subject helicopter (UH-60A Black Hawk) was programmed for real-time operation. Flight data were obtained to validate the math model, and to develop models for the pilot control strategy while performing mission-type tasks. The validated math model is to be combined with motion and visual systems to perform ground based simulation. Comparisons of the control strategy obtained in flight with that obtained on the simulator are to be used as the basis for assessing the fidelity of the results obtained in the simulator.

The Limitations of Model-Based Experimental Design and Parameter Estimation in Sloppy Systems.

PubMed

White, Andrew; Tolman, Malachi; Thames, Howard D; Withers, Hubert Rodney; Mason, Kathy A; Transtrum, Mark K

2016-12-01

We explore the relationship among experimental design, parameter estimation, and systematic error in sloppy models. We show that the approximate nature of mathematical models poses challenges for experimental design in sloppy models. In many models of complex biological processes it is unknown what are the relevant physical mechanisms that must be included to explain system behaviors. As a consequence, models are often overly complex, with many practically unidentifiable parameters. Furthermore, which mechanisms are relevant/irrelevant vary among experiments. By selecting complementary experiments, experimental design may inadvertently make details that were ommitted from the model become relevant. When this occurs, the model will have a large systematic error and fail to give a good fit to the data. We use a simple hyper-model of model error to quantify a model's discrepancy and apply it to two models of complex biological processes (EGFR signaling and DNA repair) with optimally selected experiments. We find that although parameters may be accurately estimated, the discrepancy in the model renders it less predictive than it was in the sloppy regime where systematic error is small. We introduce the concept of a sloppy system-a sequence of models of increasing complexity that become sloppy in the limit of microscopic accuracy. We explore the limits of accurate parameter estimation in sloppy systems and argue that identifying underlying mechanisms controlling system behavior is better approached by considering a hierarchy of models of varying detail rather than focusing on parameter estimation in a single model.

Modelling the transmission of healthcare associated infections: a systematic review

PubMed Central

2013-01-01

Background Dynamic transmission models are increasingly being used to improve our understanding of the epidemiology of healthcare-associated infections (HCAI). However, there has been no recent comprehensive review of this emerging field. This paper summarises how mathematical models have informed the field of HCAI and how methods have developed over time. Methods MEDLINE, EMBASE, Scopus, CINAHL plus and Global Health databases were systematically searched for dynamic mathematical models of HCAI transmission and/or the dynamics of antimicrobial resistance in healthcare settings. Results In total, 96 papers met the eligibility criteria. The main research themes considered were evaluation of infection control effectiveness (64%), variability in transmission routes (7%), the impact of movement patterns between healthcare institutes (5%), the development of antimicrobial resistance (3%), and strain competitiveness or co-colonisation with different strains (3%). Methicillin-resistant Staphylococcus aureus was the most commonly modelled HCAI (34%), followed by vancomycin resistant enterococci (16%). Other common HCAIs, e.g. Clostridum difficile, were rarely investigated (3%). Very few models have been published on HCAI from low or middle-income countries. The first HCAI model has looked at antimicrobial resistance in hospital settings using compartmental deterministic approaches. Stochastic models (which include the role of chance in the transmission process) are becoming increasingly common. Model calibration (inference of unknown parameters by fitting models to data) and sensitivity analysis are comparatively uncommon, occurring in 35% and 36% of studies respectively, but their application is increasing. Only 5% of models compared their predictions to external data. Conclusions Transmission models have been used to understand complex systems and to predict the impact of control policies. Methods have generally improved, with an increased use of stochastic models, and more advanced methods for formal model fitting and sensitivity analyses. Insights gained from these models could be broadened to a wider range of pathogens and settings. Improvements in the availability of data and statistical methods could enhance the predictive ability of models. PMID:23809195

Integrating science and business models of sustainability for environmentally-challenging industries such as secondary lead smelters: a systematic review and analysis of findings.

PubMed

Genaidy, A M; Sequeira, R; Tolaymat, T; Kohler, J; Wallace, S; Rinder, M

2010-09-01

Secondary lead smelters (SLS) represent an environmentally-challenging industry as they deal with toxic substances posing potential threats to both human and environmental health, consequently, they operate under strict government regulations. Such challenges have resulted in the significant reduction of SLS plants in the last three decades. In addition, the domestic recycling of lead has been on a steep decline in the past 10 years as the amount of lead recovered has remained virtually unchanged while consumption has increased. Therefore, one may wonder whether sustainable development can be achieved among SLS. The primary objective of this study was to determine whether a roadmap for sustainable development can be established for SLS. The following aims were established in support of the study objective: (1) to conduct a systematic review and an analysis of models of sustainable systems with a particular emphasis on SLS; (2) to document the challenges for the U.S. secondary lead smelting industry; and (3) to explore practices and concepts which act as vehicles for SLS on the road to sustainable development. An evidence-based methodology was adopted to achieve the study objective. A comprehensive electronic search was conducted to implement the aforementioned specific aims. Inclusion criteria were established to filter out irrelevant scientific papers and reports. The relevant articles were closely scrutinized and appraised to extract the required information and data for the possible development of a sustainable roadmap. The search process yielded a number of research articles which were utilized in the systematic review. Two types of models emerged: management/business and science/mathematical models. Although the management/business models explored actions to achieve sustainable growth in the industrial enterprise, science/mathematical models attempted to explain the sustainable behaviors and properties aiming at predominantly ecosystem management. As such, there are major disconnects between the science/mathematical and management/business models in terms of aims and goals. Therefore, there is an urgent need to integrate science and business models of sustainability for the industrial enterprises at large and environmentally-challenging industrial sectors in particular. In this paper, we offered examples of practices and concepts which can be used in charting a path towards sustainable development for secondary lead smelters particularly that the waste generated is much greater outside the industrial enterprise than inside. An environmentally-challenging industry such as secondary lead smelters requires a fresh look to chart a path towards sustainable development (i.e., survivability and purposive needs) for all stakeholders (i.e., industrial enterprise, individual stakeholders, and social/ecological systems). Such a path should deal with issues beyond pollution prevention, product stewardship and clean technologies. 2010 Elsevier Ltd. All rights reserved.

Development of Mathematical Models in Support of AFGL Atmospheric Studies.

DTIC Science & Technology

1980-05-15

can systematically design a sensor and predict its sensitivity, false alarm rate and detection probability. When one considers a mosaic staring sensor...data base to improve the Air Force’s ability to specify and predict geomagnetic activity. This information is very useful in the studying of propagation...storms or proton showers which cause these disturbances cannot be predicted without a knowledge of the solar activity which causes them. During periods

The Limitations of Model-Based Experimental Design and Parameter Estimation in Sloppy Systems

PubMed Central

Tolman, Malachi; Thames, Howard D.; Mason, Kathy A.

2016-01-01

We explore the relationship among experimental design, parameter estimation, and systematic error in sloppy models. We show that the approximate nature of mathematical models poses challenges for experimental design in sloppy models. In many models of complex biological processes it is unknown what are the relevant physical mechanisms that must be included to explain system behaviors. As a consequence, models are often overly complex, with many practically unidentifiable parameters. Furthermore, which mechanisms are relevant/irrelevant vary among experiments. By selecting complementary experiments, experimental design may inadvertently make details that were ommitted from the model become relevant. When this occurs, the model will have a large systematic error and fail to give a good fit to the data. We use a simple hyper-model of model error to quantify a model’s discrepancy and apply it to two models of complex biological processes (EGFR signaling and DNA repair) with optimally selected experiments. We find that although parameters may be accurately estimated, the discrepancy in the model renders it less predictive than it was in the sloppy regime where systematic error is small. We introduce the concept of a sloppy system–a sequence of models of increasing complexity that become sloppy in the limit of microscopic accuracy. We explore the limits of accurate parameter estimation in sloppy systems and argue that identifying underlying mechanisms controlling system behavior is better approached by considering a hierarchy of models of varying detail rather than focusing on parameter estimation in a single model. PMID:27923060

Catalyzing Genetic Thinking in Undergraduate Mathematics Education

ERIC Educational Resources Information Center

King, Samuel Olugbenga

2016-01-01

In undergraduate mathematics education, atypical problem solving approaches are usually discouraged because they are not adaptive to systematic deduction on which undergraduate instructional systems are predicated. I present preliminary qualitative research evidence that indicates that these atypical approaches, such as genetic guessing, which…

The normative structure of mathematization in systematic biology.

PubMed

Sterner, Beckett; Lidgard, Scott

2014-06-01

We argue that the mathematization of science should be understood as a normative activity of advocating for a particular methodology with its own criteria for evaluating good research. As a case study, we examine the mathematization of taxonomic classification in systematic biology. We show how mathematization is a normative activity by contrasting its distinctive features in numerical taxonomy in the 1960s with an earlier reform advocated by Ernst Mayr starting in the 1940s. Both Mayr and the numerical taxonomists sought to formalize the work of classification, but Mayr introduced a qualitative formalism based on human judgment for determining the taxonomic rank of populations, while the numerical taxonomists introduced a quantitative formalism based on automated procedures for computing classifications. The key contrast between Mayr and the numerical taxonomists is how they conceptualized the temporal structure of the workflow of classification, specifically where they allowed meta-level discourse about difficulties in producing the classification. Copyright © 2014. Published by Elsevier Ltd.

Small-Area Estimation of Spatial Access to Care and Its Implications for Policy.

PubMed

Gentili, Monica; Isett, Kim; Serban, Nicoleta; Swann, Julie

2015-10-01

Local or small-area estimates to capture emerging trends across large geographic regions are critical in identifying and addressing community-level health interventions. However, they are often unavailable due to lack of analytic capabilities in compiling and integrating extensive datasets and complementing them with the knowledge about variations in state-level health policies. This study introduces a modeling approach for small-area estimation of spatial access to pediatric primary care that is data "rich" and mathematically rigorous, integrating data and health policy in a systematic way. We illustrate the sensitivity of the model to policy decision making across large geographic regions by performing a systematic comparison of the estimates at the census tract and county levels for Georgia and California. Our results show the proposed approach is able to overcome limitations of other existing models by capturing patient and provider preferences and by incorporating possible changes in health policies. The primary finding is systematic underestimation of spatial access, and inaccurate estimates of disparities across population and across geography at the county level with respect to those at the census tract level with implications on where to focus and which type of interventions to consider.

An Investigation of the Effects on Students' Attitudes, Beliefs, and Abilities in Problem Solving and Mathematics after One Year of a Systematic Approach to the Learning of Problem Solving.

ERIC Educational Resources Information Center

Higgins, Karen M.

This study investigated the effects of Oregon's Lane County "Problem Solving in Mathematics" (PSM) materials on middle-school students' attitudes, beliefs, and abilities in problem solving and mathematics. The instructional approach advocated in PSM includes: the direct teaching of five problem-solving skills, weekly challenge problems,…

Discarded Minds: How Gender, Race and Class Biases Prevent Young Women from Obtaining an Adequate Math and Science Education in New York City Public Schools.

ERIC Educational Resources Information Center

Syron, Lisa

This study is a systematic investigation of female participation in mathematics and science classes in New York City schools. Six major findings reported include: (1) young women's low levels of participation in mathematics and science reflect the overall low levels of participation and reveal lack of attention to excellence in mathematics and…

Design and analysis of a sub-aperture scanning machine for the transmittance measurements of large-aperture optical system

NASA Astrophysics Data System (ADS)

He, Yingwei; Li, Ping; Feng, Guojin; Cheng, Li; Wang, Yu; Wu, Houping; Liu, Zilong; Zheng, Chundi; Sha, Dingguo

2010-11-01

For measuring large-aperture optical system transmittance, a novel sub-aperture scanning machine with double-rotating arms (SSMDA) was designed to obtain sub-aperture beam spot. Optical system full-aperture transmittance measurements can be achieved by applying sub-aperture beam spot scanning technology. The mathematical model of the SSMDA based on a homogeneous coordinate transformation matrix is established to develop a detailed methodology for analyzing the beam spot scanning errors. The error analysis methodology considers two fundamental sources of scanning errors, namely (1) the length systematic errors and (2) the rotational systematic errors. As the systematic errors of the parameters are given beforehand, computational results of scanning errors are between -0.007~0.028mm while scanning radius is not lager than 400.000mm. The results offer theoretical and data basis to the research on transmission characteristics of large optical system.

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

Du, Qiang

The rational design of materials, the development of accurate and efficient material simulation algorithms, and the determination of the response of materials to environments and loads occurring in practice all require an understanding of mechanics at disparate spatial and temporal scales. The project addresses mathematical and numerical analyses for material problems for which relevant scales range from those usually treated by molecular dynamics all the way up to those most often treated by classical elasticity. The prevalent approach towards developing a multiscale material model couples two or more well known models, e.g., molecular dynamics and classical elasticity, each of whichmore » is useful at a different scale, creating a multiscale multi-model. However, the challenges behind such a coupling are formidable and largely arise because the atomistic and continuum models employ nonlocal and local models of force, respectively. The project focuses on a multiscale analysis of the peridynamics materials model. Peridynamics can be used as a transition between molecular dynamics and classical elasticity so that the difficulties encountered when directly coupling those two models are mitigated. In addition, in some situations, peridynamics can be used all by itself as a material model that accurately and efficiently captures the behavior of materials over a wide range of spatial and temporal scales. Peridynamics is well suited to these purposes because it employs a nonlocal model of force, analogous to that of molecular dynamics; furthermore, at sufficiently large length scales and assuming smooth deformation, peridynamics can be approximated by classical elasticity. The project will extend the emerging mathematical and numerical analysis of peridynamics. One goal is to develop a peridynamics-enabled multiscale multi-model that potentially provides a new and more extensive mathematical basis for coupling classical elasticity and molecular dynamics, thus enabling next generation atomistic-to-continuum multiscale simulations. In addition, a rigorous studyof nite element discretizations of peridynamics will be considered. Using the fact that peridynamics is spatially derivative free, we will also characterize the space of admissible peridynamic solutions and carry out systematic analyses of the models, in particular rigorously showing how peridynamics encompasses fracture and other failure phenomena. Additional aspects of the project include the mathematical and numerical analysis of peridynamics applied to stochastic peridynamics models. In summary, the project will make feasible mathematically consistent multiscale models for the analysis and design of advanced materials.« less

Differential roles of two delayed rectifier potassium currents in regulation of ventricular action potential duration and arrhythmia susceptibility.

PubMed

Devenyi, Ryan A; Ortega, Francis A; Groenendaal, Willemijn; Krogh-Madsen, Trine; Christini, David J; Sobie, Eric A

2017-04-01

Arrhythmias result from disruptions to cardiac electrical activity, although the factors that control cellular action potentials are incompletely understood. We combined mathematical modelling with experiments in heart cells from guinea pigs to determine how cellular electrical activity is regulated. A mismatch between modelling predictions and the experimental results allowed us to construct an improved, more predictive mathematical model. The balance between two particular potassium currents dictates how heart cells respond to perturbations and their susceptibility to arrhythmias. Imbalances of ionic currents can destabilize the cardiac action potential and potentially trigger lethal cardiac arrhythmias. In the present study, we combined mathematical modelling with information-rich dynamic clamp experiments to determine the regulation of action potential morphology in guinea pig ventricular myocytes. Parameter sensitivity analysis was used to predict how changes in ionic currents alter action potential duration, and these were tested experimentally using dynamic clamp, a technique that allows for multiple perturbations to be tested in each cell. Surprisingly, we found that a leading mathematical model, developed with traditional approaches, systematically underestimated experimental responses to dynamic clamp perturbations. We then re-parameterized the model using a genetic algorithm, which allowed us to estimate ionic current levels in each of the cells studied. This unbiased model adjustment consistently predicted an increase in the rapid delayed rectifier K + current and a drastic decrease in the slow delayed rectifier K + current, and this prediction was validated experimentally. Subsequent simulations with the adjusted model generated the clinically relevant prediction that the slow delayed rectifier is better able to stabilize the action potential and suppress pro-arrhythmic events than the rapid delayed rectifier. In summary, iterative coupling of simulations and experiments enabled novel insight into how the balance between cardiac K + currents influences ventricular arrhythmia susceptibility. © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.

The Mathematics of Psychotherapy: A Nonlinear Model of Change Dynamics.

PubMed

Schiepek, Gunter; Aas, Benjamin; Viol, Kathrin

2016-07-01

Psychotherapy is a dynamic process produced by a complex system of interacting variables. Even though there are qualitative models of such systems the link between structure and function, between network and network dynamics is still missing. The aim of this study is to realize these links. The proposed model is composed of five state variables (P: problem severity, S: success and therapeutic progress, M: motivation to change, E: emotions, I: insight and new perspectives) interconnected by 16 functions. The shape of each function is modified by four parameters (a: capability to form a trustful working alliance, c: mentalization and emotion regulation, r: behavioral resources and skills, m: self-efficacy and reward expectation). Psychologically, the parameters play the role of competencies or traits, which translate into the concept of control parameters in synergetics. The qualitative model was transferred into five coupled, deterministic, nonlinear difference equations generating the dynamics of each variable as a function of other variables. The mathematical model is able to reproduce important features of psychotherapy processes. Examples of parameter-dependent bifurcation diagrams are given. Beyond the illustrated similarities between simulated and empirical dynamics, the model has to be further developed, systematically tested by simulated experiments, and compared to empirical data.

Novel mathematical model to estimate ball impact force in soccer.

PubMed

Iga, Takahito; Nunome, Hiroyuki; Sano, Shinya; Sato, Nahoko; Ikegami, Yasuo

2017-11-22

To assess ball impact force during soccer kicking is important to quantify from both performance and chronic injury prevention perspectives. We aimed to verify the appropriateness of previous models used to estimate ball impact force and to propose an improved model to better capture the time history of ball impact force. A soccer ball was fired directly onto a force platform (10 kHz) at five realistic kicking ball velocities and ball behaviour was captured by a high-speed camera (5,000 Hz). The time history of ball impact force was estimated using three existing models and two new models. A new mathematical model that took into account a rapid change in ball surface area and heterogeneous ball deformation showed a distinctive advantage to estimate the peak forces and its occurrence times and to reproduce time history of ball impact forces more precisely, thereby reinforcing the possible mechanics of 'footballer's ankle'. Ball impact time was also systematically shortened when ball velocity increases in contrast to practical understanding for producing faster ball velocity, however, the aspect of ball contact time must be considered carefully from practical point of view.

Modelling the social and structural determinants of tuberculosis: opportunities and challenges

PubMed Central

Boccia, D.; Dodd, P. J.; Lönnroth, K.; Dowdy, D. W.; Siroka, A.; Kimerling, M. E.; White, R. G.; Houben, R. M. G. J.

2017-01-01

INTRODUCTION: Despite the close link between tuberculosis (TB) and poverty, most mathematical models of TB have not addressed underlying social and structural determinants. OBJECTIVE: To review studies employing mathematical modelling to evaluate the epidemiological impact of the structural determinants of TB. METHODS: We systematically searched PubMed and personal libraries to identify eligible articles. We extracted data on the modelling techniques employed, research question, types of structural determinants modelled and setting. RESULTS: From 232 records identified, we included eight articles published between 2008 and 2015; six employed population-based dynamic TB transmission models and two non-dynamic analytic models. Seven studies focused on proximal TB determinants (four on nutritional status, one on wealth, one on indoor air pollution, and one examined overcrowding, socioeconomic and nutritional status), and one focused on macro-economic influences. CONCLUSIONS: Few modelling studies have attempted to evaluate structural determinants of TB, resulting in key knowledge gaps. Despite the challenges of modelling such a complex system, models must broaden their scope to remain useful for policy making. Given the intersectoral nature of the interrelations between structural determinants and TB outcomes, this work will require multidisciplinary collaborations. A useful starting point would be to focus on developing relatively simple models that can strengthen our knowledge regarding the potential effect of the structural determinants on TB outcomes. PMID:28826444

Culturally Responsive Teaching in the Context of Mathematics: A Grounded Theory Case Study

ERIC Educational Resources Information Center

Bonner, Emily P.; Adams, Thomasenia L.

2012-01-01

In this grounded theory case study, four interconnected, foundational cornerstones of culturally responsive mathematics teaching (CRMT), communication, knowledge, trust/relationships, and constant reflection/revision, were systematically unearthed to develop an initial working theory of CRMT that directly informs classroom practice. These…

A review of Reynolds stress models for turbulent shear flows

NASA Technical Reports Server (NTRS)

Speziale, Charles G.

1995-01-01

A detailed review of recent developments in Reynolds stress modeling for incompressible turbulent shear flows is provided. The mathematical foundations of both two-equation models and full second-order closures are explored in depth. It is shown how these models can be systematically derived for two-dimensional mean turbulent flows that are close to equilibrium. A variety of examples are provided to demonstrate how well properly calibrated versions of these models perform for such flows. However, substantial problems remain for the description of more complex turbulent flows where there are large departures from equilibrium. Recent efforts to extend Reynolds stress models to nonequilibrium turbulent flows are discussed briefly along with the major modeling issues relevant to practical naval hydrodynamics applications.

Identification of line-specific strategies for improving carotenoid production in synthetic maize through data-driven mathematical modeling.

PubMed

Comas, Jorge; Benfeitas, Rui; Vilaprinyo, Ester; Sorribas, Albert; Solsona, Francesc; Farré, Gemma; Berman, Judit; Zorrilla, Uxue; Capell, Teresa; Sandmann, Gerhard; Zhu, Changfu; Christou, Paul; Alves, Rui

2016-09-01

Plant synthetic biology is still in its infancy. However, synthetic biology approaches have been used to manipulate and improve the nutritional and health value of staple food crops such as rice, potato and maize. With current technologies, production yields of the synthetic nutrients are a result of trial and error, and systematic rational strategies to optimize those yields are still lacking. Here, we present a workflow that combines gene expression and quantitative metabolomics with mathematical modeling to identify strategies for increasing production yields of nutritionally important carotenoids in the seed endosperm synthesized through alternative biosynthetic pathways in synthetic lines of white maize, which is normally devoid of carotenoids. Quantitative metabolomics and gene expression data are used to create and fit parameters of mathematical models that are specific to four independent maize lines. Sensitivity analysis and simulation of each model is used to predict which gene activities should be further engineered in order to increase production yields for carotenoid accumulation in each line. Some of these predictions (e.g. increasing Zmlycb/Gllycb will increase accumulated β-carotenes) are valid across the four maize lines and consistent with experimental observations in other systems. Other predictions are line specific. The workflow is adaptable to any other biological system for which appropriate quantitative information is available. Furthermore, we validate some of the predictions using experimental data from additional synthetic maize lines for which no models were developed. © 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd.

Parameter identification of material constants in a composite shell structure

NASA Technical Reports Server (NTRS)

Martinez, David R.; Carne, Thomas G.

1988-01-01

One of the basic requirements in engineering analysis is the development of a mathematical model describing the system. Frequently comparisons with test data are used as a measurement of the adequacy of the model. An attempt is typically made to update or improve the model to provide a test verified analysis tool. System identification provides a systematic procedure for accomplishing this task. The terms system identification, parameter estimation, and model correlation all refer to techniques that use test information to update or verify mathematical models. The goal of system identification is to improve the correlation of model predictions with measured test data, and produce accurate, predictive models. For nonmetallic structures the modeling task is often difficult due to uncertainties in the elastic constants. A finite element model of the shell was created, which included uncertain orthotropic elastic constants. A modal survey test was then performed on the shell. The resulting modal data, along with the finite element model of the shell, were used in a Bayes estimation algorithm. This permitted the use of covariance matrices to weight the confidence in the initial parameter values as well as confidence in the measured test data. The estimation procedure also employed the concept of successive linearization to obtain an approximate solution to the original nonlinear estimation problem.

Improving Mathematics Performance among Secondary Students with EBD: A Methodological Review

ERIC Educational Resources Information Center

Mulcahy, Candace A.; Krezmien, Michael P.; Travers, Jason

2016-01-01

In this methodological review, the authors apply special education research quality indicators and standards for single case design to analyze mathematics intervention studies for secondary students with emotional and behavioral disorders (EBD). A systematic methodological review of literature from 1975 to December 2012 yielded 19 articles that…

Concreteness Fading in Mathematics and Science Instruction: A Systematic Review

ERIC Educational Resources Information Center

Fyfe, Emily R.; McNeil, Nicole M.; Son, Ji Y.; Goldstone, Robert L.

2014-01-01

A longstanding debate concerns the use of concrete versus abstract instructional materials, particularly in domains such as mathematics and science. Although decades of research have focused on the advantages and disadvantages of concrete and abstract materials considered independently, we argue for an approach that moves beyond this dichotomy and…

Teachers' Perception, Interpretation, and Decision-Making: A Systematic Review of Empirical Mathematics Education Research

ERIC Educational Resources Information Center

Stahnke, Rebekka; Schueler, Sven; Roesken-Winter, Bettina

2016-01-01

Research in mathematics education has investigated teachers' professional knowledge in depth, comprising two different approaches: a cognitive and a situated perspective. Linking these two perspectives leads to addressing situation-specific skills such as perception, interpretation and decision-making, indicative of revealing a teacher's knowledge…

Mapping Children's Understanding of Mathematical Equivalence

ERIC Educational Resources Information Center

Taylor, Roger S.; Rittle-Johnson, Bethany; Matthews, Percival G.; McEldoon, Katherine L.

2009-01-01

The focus of this research is to develop an initial framework for assessing and interpreting students' level of understanding of mathematical equivalence. Although this topic has been studied for many years, there has been no systematic development or evaluation of a valid measure of equivalence knowledge. A powerful method for accomplishing this…

Estimating the production, consumption and export of cannabis: The Dutch case.

PubMed

van der Giessen, Mark; van Ooyen-Houben, Marianne M J; Moolenaar, Debora E G

2016-05-01

Quantifying an illegal phenomenon like a drug market is inherently complex due to its hidden nature and the limited availability of reliable information. This article presents findings from a recent estimate of the production, consumption and export of Dutch cannabis and discusses the opportunities provided by, and limitations of, mathematical models for estimating the illegal cannabis market. The data collection consisted of a comprehensive literature study, secondary analyses on data from available registrations (2012-2014) and previous studies, and expert opinion. The cannabis market was quantified with several mathematical models. The data analysis included a Monte Carlo simulation to come to a 95% interval estimate (IE) and a sensitivity analysis to identify the most influential indicators. The annual production of Dutch cannabis was estimated to be between 171 and 965tons (95% IE of 271-613tons). The consumption was estimated to be between 28 and 119tons, depending on the inclusion or exclusion of non-residents (95% IE of 51-78tons or 32-49tons respectively). The export was estimated to be between 53 and 937tons (95% IE of 206-549tons or 231-573tons, respectively). Mathematical models are valuable tools for the systematic assessment of the size of illegal markets and determining the uncertainty inherent in the estimates. The estimates required the use of many assumptions and the availability of reliable indicators was limited. This uncertainty is reflected in the wide ranges of the estimates. The estimates are sensitive to 10 of the 45 indicators. These 10 account for 86-93% of the variation found. Further research should focus on improving the variables and the independence of the mathematical models. Copyright © 2016 Elsevier B.V. All rights reserved.

Modeling the North American vertical datum of 1988 errors in the conterminous United States

NASA Astrophysics Data System (ADS)

Li, X.

2018-02-01

A large systematic difference (ranging from -20 cm to +130 cm) was found between NAVD 88 (North AmericanVertical Datum of 1988) and the pure gravimetric geoid models. This difference not only makes it very difficult to augment the local geoid model by directly using the vast NAVD 88 network with state-of-the-art technologies recently developed in geodesy, but also limits the ability of researchers to effectively demonstrate the geoid model improvements on the NAVD 88 network. Here, both conventional regression analyses based on various predefined basis functions such as polynomials, B-splines, and Legendre functions and the Latent Variable Analysis (LVA) such as the Factor Analysis (FA) are used to analyze the systematic difference. Besides giving a mathematical model, the regression results do not reveal a great deal about the physical reasons that caused the large differences in NAVD 88, which may be of interest to various researchers. Furthermore, there is still a significant amount of no-Gaussian signals left in the residuals of the conventional regression models. On the other side, the FA method not only provides a better not of the data, but also offers possible explanations of the error sources. Without requiring extra hypothesis tests on the model coefficients, the results from FA are more efficient in terms of capturing the systematic difference. Furthermore, without using a covariance model, a novel interpolating method based on the relationship between the loading matrix and the factor scores is developed for predictive purposes. The prediction error analysis shows that about 3-7 cm precision is expected in NAVD 88 after removing the systematic difference.

Mathematical modeling and computational prediction of cancer drug resistance.

PubMed

Sun, Xiaoqiang; Hu, Bin

2017-06-23

Diverse forms of resistance to anticancer drugs can lead to the failure of chemotherapy. Drug resistance is one of the most intractable issues for successfully treating cancer in current clinical practice. Effective clinical approaches that could counter drug resistance by restoring the sensitivity of tumors to the targeted agents are urgently needed. As numerous experimental results on resistance mechanisms have been obtained and a mass of high-throughput data has been accumulated, mathematical modeling and computational predictions using systematic and quantitative approaches have become increasingly important, as they can potentially provide deeper insights into resistance mechanisms, generate novel hypotheses or suggest promising treatment strategies for future testing. In this review, we first briefly summarize the current progress of experimentally revealed resistance mechanisms of targeted therapy, including genetic mechanisms, epigenetic mechanisms, posttranslational mechanisms, cellular mechanisms, microenvironmental mechanisms and pharmacokinetic mechanisms. Subsequently, we list several currently available databases and Web-based tools related to drug sensitivity and resistance. Then, we focus primarily on introducing some state-of-the-art computational methods used in drug resistance studies, including mechanism-based mathematical modeling approaches (e.g. molecular dynamics simulation, kinetic model of molecular networks, ordinary differential equation model of cellular dynamics, stochastic model, partial differential equation model, agent-based model, pharmacokinetic-pharmacodynamic model, etc.) and data-driven prediction methods (e.g. omics data-based conventional screening approach for node biomarkers, static network approach for edge biomarkers and module biomarkers, dynamic network approach for dynamic network biomarkers and dynamic module network biomarkers, etc.). Finally, we discuss several further questions and future directions for the use of computational methods for studying drug resistance, including inferring drug-induced signaling networks, multiscale modeling, drug combinations and precision medicine. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Amplitude and frequency modulation control of sound production in a mechanical model of the avian syrinx.

PubMed

Elemans, Coen P H; Muller, Mees; Larsen, Ole Naesbye; van Leeuwen, Johan L

2009-04-01

Birdsong has developed into one of the important models for motor control of learned behaviour and shows many parallels with speech acquisition in humans. However, there are several experimental limitations to studying the vocal organ - the syrinx - in vivo. The multidisciplinary approach of combining experimental data and mathematical modelling has greatly improved the understanding of neural control and peripheral motor dynamics of sound generation in birds. Here, we present a simple mechanical model of the syrinx that facilitates detailed study of vibrations and sound production. Our model resembles the 'starling resistor', a collapsible tube model, and consists of a tube with a single membrane in its casing, suspended in an external pressure chamber and driven by various pressure patterns. With this design, we can separately control 'bronchial' pressure and tension in the oscillating membrane and generate a wide variety of 'syllables' with simple sweeps of the control parameters. We show that the membrane exhibits high frequency, self-sustained oscillations in the audio range (>600 Hz fundamental frequency) using laser Doppler vibrometry, and systematically explore the conditions for sound production of the model in its control space. The fundamental frequency of the sound increases with tension in three membranes with different stiffness and mass. The lower-bound fundamental frequency increases with membrane mass. The membrane vibrations are strongly coupled to the resonance properties of the distal tube, most likely because of its reflective properties to sound waves. Our model is a gross simplification of the complex morphology found in birds, and more closely resembles mathematical models of the syrinx. Our results confirm several assumptions underlying existing mathematical models in a complex geometry.

A hierarchical Bayesian model for understanding the spatiotemporal dynamics of the intestinal epithelium

PubMed Central

Parker, Aimée; Pin, Carmen; Carding, Simon R.; Watson, Alastair J. M.; Byrne, Helen M.

2017-01-01

Our work addresses two key challenges, one biological and one methodological. First, we aim to understand how proliferation and cell migration rates in the intestinal epithelium are related under healthy, damaged (Ara-C treated) and recovering conditions, and how these relations can be used to identify mechanisms of repair and regeneration. We analyse new data, presented in more detail in a companion paper, in which BrdU/IdU cell-labelling experiments were performed under these respective conditions. Second, in considering how to more rigorously process these data and interpret them using mathematical models, we use a probabilistic, hierarchical approach. This provides a best-practice approach for systematically modelling and understanding the uncertainties that can otherwise undermine the generation of reliable conclusions—uncertainties in experimental measurement and treatment, difficult-to-compare mathematical models of underlying mechanisms, and unknown or unobserved parameters. Both spatially discrete and continuous mechanistic models are considered and related via hierarchical conditional probability assumptions. We perform model checks on both in-sample and out-of-sample datasets and use them to show how to test possible model improvements and assess the robustness of our conclusions. We conclude, for the present set of experiments, that a primarily proliferation-driven model suffices to predict labelled cell dynamics over most time-scales. PMID:28753601

A hierarchical Bayesian model for understanding the spatiotemporal dynamics of the intestinal epithelium.

PubMed

Maclaren, Oliver J; Parker, Aimée; Pin, Carmen; Carding, Simon R; Watson, Alastair J M; Fletcher, Alexander G; Byrne, Helen M; Maini, Philip K

2017-07-01

Our work addresses two key challenges, one biological and one methodological. First, we aim to understand how proliferation and cell migration rates in the intestinal epithelium are related under healthy, damaged (Ara-C treated) and recovering conditions, and how these relations can be used to identify mechanisms of repair and regeneration. We analyse new data, presented in more detail in a companion paper, in which BrdU/IdU cell-labelling experiments were performed under these respective conditions. Second, in considering how to more rigorously process these data and interpret them using mathematical models, we use a probabilistic, hierarchical approach. This provides a best-practice approach for systematically modelling and understanding the uncertainties that can otherwise undermine the generation of reliable conclusions-uncertainties in experimental measurement and treatment, difficult-to-compare mathematical models of underlying mechanisms, and unknown or unobserved parameters. Both spatially discrete and continuous mechanistic models are considered and related via hierarchical conditional probability assumptions. We perform model checks on both in-sample and out-of-sample datasets and use them to show how to test possible model improvements and assess the robustness of our conclusions. We conclude, for the present set of experiments, that a primarily proliferation-driven model suffices to predict labelled cell dynamics over most time-scales.

The probability of monophyly of a sample of gene lineages on a species tree

PubMed Central

Mehta, Rohan S.; Bryant, David; Rosenberg, Noah A.

2016-01-01

Monophyletic groups—groups that consist of all of the descendants of a most recent common ancestor—arise naturally as a consequence of descent processes that result in meaningful distinctions between organisms. Aspects of monophyly are therefore central to fields that examine and use genealogical descent. In particular, studies in conservation genetics, phylogeography, population genetics, species delimitation, and systematics can all make use of mathematical predictions under evolutionary models about features of monophyly. One important calculation, the probability that a set of gene lineages is monophyletic under a two-species neutral coalescent model, has been used in many studies. Here, we extend this calculation for a species tree model that contains arbitrarily many species. We study the effects of species tree topology and branch lengths on the monophyly probability. These analyses reveal new behavior, including the maintenance of nontrivial monophyly probabilities for gene lineage samples that span multiple species and even for lineages that do not derive from a monophyletic species group. We illustrate the mathematical results using an example application to data from maize and teosinte. PMID:27432988

Coordinated photomorphogenic UV-B signaling network captured by mathematical modeling.

PubMed

Ouyang, Xinhao; Huang, Xi; Jin, Xiao; Chen, Zheng; Yang, Panyu; Ge, Hao; Li, Shigui; Deng, Xing Wang

2014-08-05

Long-wavelength and low-fluence UV-B light is an informational signal known to induce photomorphogenic development in plants. Using the model plant Arabidopsis thaliana, a variety of factors involved in UV-B-specific signaling have been experimentally characterized over the past decade, including the UV-B light receptor UV resistance locus 8; the positive regulators constitutive photomorphogenesis 1 and elongated hypocotyl 5; and the negative regulators cullin4, repressor of UV-B photomorphogenesis 1 (RUP1), and RUP2. Individual genetic and molecular studies have revealed that these proteins function in either positive or negative regulatory capacities for the sufficient and balanced transduction of photomorphogenic UV-B signal. Less is known, however, regarding how these signaling events are systematically linked. In our study, we use a systems biology approach to investigate the dynamic behaviors and correlations of multiple signaling components involved in Arabidopsis UV-B-induced photomorphogenesis. We define a mathematical representation of photomorphogenic UV-B signaling at a temporal scale. Supplemented with experimental validation, our computational modeling demonstrates the functional interaction that occurs among different protein complexes in early and prolonged response to photomorphogenic UV-B.

The dynamics of hydroponic crops for simulation studies of the CELSS initial reference configurations

NASA Technical Reports Server (NTRS)

Volk, Tyler

1992-01-01

The goal of this research is to develop a progressive series of mathematical models for the CELSS hydroponic crops. These models will systematize the experimental findings from the crop researchers in the CELSS Program into a form useful to investigate system-level considerations, for example, dynamic studies of the CELSS Initial Reference Configurations. The crop models will organize data from different crops into a common modeling framework. This is the fifth semiannual report for this project. The following topics are discussed: (1) use of field crop models to explore phasic control of CELSS crops for optimizing yield; (2) seminar presented at Purdue CELSS NSCORT; and (3) paper submitted on analysis of bioprocessing of inedible plant materials.

Multiscale Modeling of Hematologic Disorders

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

Fedosov, Dmitry A.; Pivkin, Igor; Pan, Wenxiao

Parasitic infectious diseases and other hereditary hematologic disorders are often associated with major changes in the shape and viscoelastic properties of red blood cells (RBCs). Such changes can disrupt blood flow and even brain perfusion, as in the case of cerebral malaria. Modeling of these hematologic disorders requires a seamless multiscale approach, where blood cells and blood flow in the entire arterial tree are represented accurately using physiologically consistent parameters. In this chapter, we present a computational methodology based on dissipative particle dynamics (DPD) which models RBCs as well as whole blood in health and disease. DPD is a Lagrangianmore » method that can be derived from systematic coarse-graining of molecular dynamics but can scale efficiently up to small arteries and can also be used to model RBCs down to spectrin level. To this end, we present two complementary mathematical models for RBCs and describe a systematic procedure on extracting the relevant input parameters from optical tweezers and microfluidic experiments for single RBCs. We then use these validated RBC models to predict the behavior of whole healthy blood and compare with experimental results. The same procedure is applied to modeling malaria, and results for infected single RBCs and whole blood are presented.« less

The Effects of Computerized Instruction and Systematic Presentation and Review of Math Fact Acquisition and Fluency

ERIC Educational Resources Information Center

Reynolds, Jennifer L.

2010-01-01

Cross country investigations have repeatedly demonstrated the disappointing math performance of students in the United States (Beatty, 1997; Ferrini-Mundy & Schmidt, 2005). The National Council of Teachers of Mathematics (2000) listed failure to rapidly recall basic facts as a common problem associated with disabilities in mathematics and…

Illinois Inventory of Educational Progress: 1979 Mathematics Results, 4th Grade.

ERIC Educational Resources Information Center

Brennan, Mervin M.; And Others

Presented is an overview of the 1979 Illinois Inventory of Educational Progress (IIEP) for fourth-grade mathematics. The IIEP is a systematic effort by the Illinois State Board of Education to collect information on the educational achievement of Illinois students in certain areas and to make that information available to education…

Illinois Inventory of Educational Progress: 1979 Mathematics Results, 11th Grade.

ERIC Educational Resources Information Center

Brennan, Mervin M.; And Others

Presented is an overview of the 1979 Illinois Inventory of Educational Progress (IIEP) for eleventh-grade mathematics. The IIEP is a systematic effort by the Illinois State Board of Education to collect information on the educational achievement of Illinois students in certain areas and to make that information available to educational…

Illinois Inventory of Educational Progress: 1979 Mathematics Results, 8th Grade.

ERIC Educational Resources Information Center

Brennan, Mervin M.; And Others

Presented is an overview of the 1979 Illinois Inventory of Educational Progress (IIEP) for eighth-grade mathematics. The IIEP is a systematic effort by the Illinois State Board of Education to collect information on the educational achievement of Illinois students in certain areas and to make that information available to educational…

Teaching Mathematics to Students With Learning Disabilities: A Review Of Literature

ERIC Educational Resources Information Center

Obudo, Francis

2008-01-01

The purpose of this study was to review and synthesize available literature to draw a comprehensive picture of what is necessary to teach mathematics to students with learning disabilities. A systematic search was conducted through 5 computerized databases (Academic Search Complete, ERIC, Education Research Complete, and Primary Search) The…

Developing Prospective Elementary Teachers' Abilities to Identify Evidence of Student Mathematical Achievement

ERIC Educational Resources Information Center

Spitzer, Sandy M.; Phelps, Christine M.; Beyers, James E. R.; Johnson, Delayne Y.; Sieminski, Elizabeth M.

2011-01-01

This study investigated the effects of a classroom intervention on prospective elementary teachers' ability to evaluate evidence of student achievement of mathematical learning goals. The intervention was informed by a framework for teacher education which aims to provide prospective teachers (PTs) with the skills needed to systematically learn…

An Applied Statistics Course for Systematics and Ecology PhD Students

ERIC Educational Resources Information Center

Ojeda, Mario Miguel; Sosa, Victoria

2002-01-01

Statistics education is under review at all educational levels. Statistical concepts, as well as the use of statistical methods and techniques, can be taught in at least two contrasting ways. Specifically, (1) teaching can be theoretically and mathematically oriented, or (2) it can be less mathematically oriented being focused, instead, on…

A mathematical analysis of adaptations to the metabolic fate of fructose in essential fructosuria subjects.

PubMed

Allen, R J; Musante, Cynthia J

2018-04-17

Fructose is a major component of Western diets and is implicated in the pathogenesis of obesity and type 2 diabetes. In response to an oral challenge, the majority of fructose is cleared during "first-pass" liver metabolism, primarily via phosphorylation by ketohexokinase (KHK). A rare benign genetic deficiency in KHK, called essential fructosuria (EF), leads to altered fructose metabolism. The only reported symptom of EF is the appearance of fructose in the urine following either oral or intravenous fructose administration. Here we develop and use a mathematical model to investigate the adaptations to altered fructose metabolism in people with EF. Firstly, the model is calibrated to fit available data in normal healthy subjects. Then, to mathematically represent EF subjects we systematically implement metabolic adaptations such that model simulations match available data for this phenotype. We hypothesize that these modifications represent the major metabolic adaptations present in these subjects. This modeling approach suggests that several other aspects of fructose metabolism, beyond hepatic KHK deficiency, are altered and contribute to the etiology of this benign condition. Specifically, we predict that fructose absorption into the portal vein is altered, peripheral metabolism is slowed, renal re-absorption of fructose is mostly ablated and that alternate pathways for hepatic metabolism of fructose are up-regulated. Moreover, these findings have implications for drug discovery and development, suggesting that the therapeutic targeting of fructose metabolism could lead to unexpected metabolic adaptations, potentially due to a physiological response to high fructose conditions.

Normal forms for reduced stochastic climate models

PubMed Central

Majda, Andrew J.; Franzke, Christian; Crommelin, Daan

2009-01-01

The systematic development of reduced low-dimensional stochastic climate models from observations or comprehensive high-dimensional climate models is an important topic for atmospheric low-frequency variability, climate sensitivity, and improved extended range forecasting. Here techniques from applied mathematics are utilized to systematically derive normal forms for reduced stochastic climate models for low-frequency variables. The use of a few Empirical Orthogonal Functions (EOFs) (also known as Principal Component Analysis, Karhunen–Loéve and Proper Orthogonal Decomposition) depending on observational data to span the low-frequency subspace requires the assessment of dyad interactions besides the more familiar triads in the interaction between the low- and high-frequency subspaces of the dynamics. It is shown below that the dyad and multiplicative triad interactions combine with the climatological linear operator interactions to simultaneously produce both strong nonlinear dissipation and Correlated Additive and Multiplicative (CAM) stochastic noise. For a single low-frequency variable the dyad interactions and climatological linear operator alone produce a normal form with CAM noise from advection of the large scales by the small scales and simultaneously strong cubic damping. These normal forms should prove useful for developing systematic strategies for the estimation of stochastic models from climate data. As an illustrative example the one-dimensional normal form is applied below to low-frequency patterns such as the North Atlantic Oscillation (NAO) in a climate model. The results here also illustrate the short comings of a recent linear scalar CAM noise model proposed elsewhere for low-frequency variability. PMID:19228943

Modelling the impact of correlations between condom use and sexual contact pattern on the dynamics of sexually transmitted infections.

PubMed

Yamamoto, Nao; Ejima, Keisuke; Nishiura, Hiroshi

2018-05-31

It is believed that sexually active people, i.e. people having multiple or concurrent sexual partners, are at a high risk of sexually transmitted infections (STI), but they are likely to be more aware of the risk and may exhibit greater fraction of the use of condom. The purpose of the present study is to examine the correlation between condom use and sexual contact pattern and clarify its impact on the transmission dynamics of STIs using a mathematical model. The definition of sexual contact pattern can be broad, but we focus on two specific aspects: (i) type of partnership (i.e. steady or casual partnership) and (ii) existence of concurrency (i.e. with single or multiple partners). Systematic review and meta-analysis of published studies are performed, analysing literature that epidemiologically examined the relationship between condom use and sexual contact pattern. Subsequently, we employ an epidemiological model and compute the reproduction number that accounts for with and without concurrency so that the corresponding coverage of condom use and its correlation with existence of concurrency can be explicitly investigated using the mathematical model. Combining the model with parameters estimated from the meta-analysis along with other assumed parameters, the impact of varying the proportion of population with multiple partners on the reproduction number is examined. Based on systematic review, we show that a greater number of people used condoms during sexual contact with casual partners than with steady partners. Furthermore, people with multiple partners use condoms more frequently than people with a single partner alone. Our mathematical model revealed a positive relationship between the effective reproduction number and the proportion of people with multiple partners. Nevertheless, the association was reversed to be negative by employing a slightly greater value of the relative risk of condom use for people with multiple partners than that empirically estimated. Depending on the correlation between condom use and the existence of concurrency, association between the proportion of people with multiple partners and the reproduction number can be reversed, suggesting the sexually active population is not necessary a primary target population to encourage condom use (i.e., sexually less active individuals could equivalently be a target in some cases).

An Improved Cochlea Model with a General User Interface

NASA Astrophysics Data System (ADS)

Duifhuis, H.; Kruseman, J. M.; van Hengel, P. W. J.

2003-02-01

We have developed a flexible 1D cochlea model to test hypotheses and data against physical and mathematical constraints. The model is flexible in the sense that several linear and nonlinear model characteristics can be selected, and different boundary conditions can be tested. The software model runs at a reasonable speed at a modern PC. As an example, we will show the results of the model in comparison with the systematic study of the phase behavior (group delay) of distortion product otoacoustic emissions (DPOAEs) in the guinea pig (S. Schneider, V. Prijs and R. Schoonhoven, [9]). We also will demonstrate the effects of some common non-physical boundary conditions. Finally, we briefly indicate that this model of the auditory periphery provides a superior front end for an ASR (automatic speech recognition)-system.

Stochastic Parameterization: Toward a New View of Weather and Climate Models

DOE PAGES

Berner, Judith; Achatz, Ulrich; Batté, Lauriane; ...

2017-03-31

The last decade has seen the success of stochastic parameterizations in short-term, medium-range, and seasonal forecasts: operational weather centers now routinely use stochastic parameterization schemes to represent model inadequacy better and to improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides better estimates of uncertainty, but it is also extremely promising for reducing long-standing climate biases and is relevant for determining the climate response to external forcing. This article highlights recent developments from different research groups that show that the stochastic representation of unresolved processes in the atmosphere, oceans,more » land surface, and cryosphere of comprehensive weather and climate models 1) gives rise to more reliable probabilistic forecasts of weather and climate and 2) reduces systematic model bias. We make a case that the use of mathematically stringent methods for the derivation of stochastic dynamic equations will lead to substantial improvements in our ability to accurately simulate weather and climate at all scales. Recent work in mathematics, statistical mechanics, and turbulence is reviewed; its relevance for the climate problem is demonstrated; and future research directions are outlined« less

Stochastic Parameterization: Toward a New View of Weather and Climate Models

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

Berner, Judith; Achatz, Ulrich; Batté, Lauriane

The last decade has seen the success of stochastic parameterizations in short-term, medium-range, and seasonal forecasts: operational weather centers now routinely use stochastic parameterization schemes to represent model inadequacy better and to improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides better estimates of uncertainty, but it is also extremely promising for reducing long-standing climate biases and is relevant for determining the climate response to external forcing. This article highlights recent developments from different research groups that show that the stochastic representation of unresolved processes in the atmosphere, oceans,more » land surface, and cryosphere of comprehensive weather and climate models 1) gives rise to more reliable probabilistic forecasts of weather and climate and 2) reduces systematic model bias. We make a case that the use of mathematically stringent methods for the derivation of stochastic dynamic equations will lead to substantial improvements in our ability to accurately simulate weather and climate at all scales. Recent work in mathematics, statistical mechanics, and turbulence is reviewed; its relevance for the climate problem is demonstrated; and future research directions are outlined« less

The Smarties-Box Challenge: Supporting Systematic Approaches to Problem Solving

ERIC Educational Resources Information Center

Russo, James

2016-01-01

The Smarties-Box Challenge encourages students to apply several different mathematical capabilities and concepts--such as, estimation, multiplication, and the notion of being systematic--to solve a complex, multistep problem. To effectively engage in the Smarties-Box Challenge, students are required to demonstrate aspects of all four proficiency…

Tracking Instructional Quality across Secondary Mathematics and English Language Arts Classes

ERIC Educational Resources Information Center

Donaldson, Morgaen L.; LeChasseur, Kimberly; Mayer, Anysia

2017-01-01

Teachers have the largest school-based influence on student learning, yet there is little research on how instructional practice is systematically distributed within tracking systems. We examine whether teaching practice varies significantly across track levels and, if so, which aspects of instructional practice differ systematically. Using…

Estimation of Hepatitis C Disease Burden and Budget Impact of Treatment Using Health Economic Modeling.

PubMed

Chhatwal, Jagpreet; Chen, Qiushi; Aggarwal, Rakesh

2018-06-01

Oral direct-acting antiviral agents have revolutionized treatment of hepatitis C virus (HCV) infection. Nonetheless, barriers exist to elimination of HCV as a public health threat including low uptake of treatment, limited budget allocations for HCV treatment, and low awareness rates of HCV status among infected people. Mathematical modeling provides a systematic framework to analyze and compare potential solutions and elimination strategies by simulating the HCV epidemic under different conditions. Such models evaluate impact of interventions in advance of implementation. This article describes key components of developing an HCV burden model and illustrates its use by simulating the HCV epidemic in the United States. Copyright © 2018 Elsevier Inc. All rights reserved.

Financial forecasts accuracy in Brazil's social security system.

PubMed

Silva, Carlos Patrick Alves da; Puty, Claudio Alberto Castelo Branco; Silva, Marcelino Silva da; Carvalho, Solon Venâncio de; Francês, Carlos Renato Lisboa

2017-01-01

Long-term social security statistical forecasts produced and disseminated by the Brazilian government aim to provide accurate results that would serve as background information for optimal policy decisions. These forecasts are being used as support for the government's proposed pension reform that plans to radically change the Brazilian Constitution insofar as Social Security is concerned. However, the reliability of official results is uncertain since no systematic evaluation of these forecasts has ever been published by the Brazilian government or anyone else. This paper aims to present a study of the accuracy and methodology of the instruments used by the Brazilian government to carry out long-term actuarial forecasts. We base our research on an empirical and probabilistic analysis of the official models. Our empirical analysis shows that the long-term Social Security forecasts are systematically biased in the short term and have significant errors that render them meaningless in the long run. Moreover, the low level of transparency in the methods impaired the replication of results published by the Brazilian Government and the use of outdated data compromises forecast results. In the theoretical analysis, based on a mathematical modeling approach, we discuss the complexity and limitations of the macroeconomic forecast through the computation of confidence intervals. We demonstrate the problems related to error measurement inherent to any forecasting process. We then extend this exercise to the computation of confidence intervals for Social Security forecasts. This mathematical exercise raises questions about the degree of reliability of the Social Security forecasts.

Financial forecasts accuracy in Brazil’s social security system

PubMed Central

2017-01-01

Long-term social security statistical forecasts produced and disseminated by the Brazilian government aim to provide accurate results that would serve as background information for optimal policy decisions. These forecasts are being used as support for the government’s proposed pension reform that plans to radically change the Brazilian Constitution insofar as Social Security is concerned. However, the reliability of official results is uncertain since no systematic evaluation of these forecasts has ever been published by the Brazilian government or anyone else. This paper aims to present a study of the accuracy and methodology of the instruments used by the Brazilian government to carry out long-term actuarial forecasts. We base our research on an empirical and probabilistic analysis of the official models. Our empirical analysis shows that the long-term Social Security forecasts are systematically biased in the short term and have significant errors that render them meaningless in the long run. Moreover, the low level of transparency in the methods impaired the replication of results published by the Brazilian Government and the use of outdated data compromises forecast results. In the theoretical analysis, based on a mathematical modeling approach, we discuss the complexity and limitations of the macroeconomic forecast through the computation of confidence intervals. We demonstrate the problems related to error measurement inherent to any forecasting process. We then extend this exercise to the computation of confidence intervals for Social Security forecasts. This mathematical exercise raises questions about the degree of reliability of the Social Security forecasts. PMID:28859172

The Adoption of Variation Theory in the Classroom: Effect on Students' Algebraic Achievement and Motivation to Learn

ERIC Educational Resources Information Center

Ting, Jing Jing; Tarmizi, Rohani Tarmizi; Bakar, Kamariah Abu; Aralas, Dalia

2017-01-01

Introduction: Analysis of lessons held in East Asia regions that perform well in Trends in International Mathematics and Science Studies such as; South Korea, Hong Kong and Japan, demonstrated teachers in mathematics classroom enacted features of the content systematically with consideration of variation within students' capabilities. Recent…

The Role of Dynamic Software in the Identification and Construction of Mathematical Relationships

ERIC Educational Resources Information Center

Santos-Trigo, Manuel

2004-01-01

What features of mathematical thinking do students exhibit when they use dynamic software in their problem solving approaches? To what extent does the systematic use of technology favour students' development of problem solving competences? What type of reasoning do students develop as a result of using a particular tool? This study documents…

Catalysts of Women's Talent Development in STEM: A Systematic Review

ERIC Educational Resources Information Center

Mullet, Dianna R.; Rinn, Anne N.; Kettler, Todd

2017-01-01

Numbers of women in the physical sciences, mathematics, and engineering are growing, yet women are still far outnumbered by men at upper levels of those fields. The purpose of the study is to review the literature on academic women who develop exceptional talent in science, technology, engineering, and mathematics (STEM). Data sources included 18…

Characterizing Mathematics Teaching Research Specialists' Mentoring in the Context of Chinese Lesson Study

ERIC Educational Resources Information Center

Gu, Feishi; Gu, Lingyuan

2016-01-01

This study examines how mathematics teaching research specialists mentor practicing teachers during post-lesson debriefs of a lesson study in China. Based on a systematic, fine-grained analysis of 107 h of videotaped mentoring meetings of 20 groups of teachers and teaching research specialists from different elementary schools, this study reveals…

A Meta-Analysis of the Effects of Computer Technology on School Students' Mathematics Learning

ERIC Educational Resources Information Center

Li, Qing; Ma, Xin

2010-01-01

This study examines the impact of computer technology (CT) on mathematics education in K-12 classrooms through a systematic review of existing literature. A meta-analysis of 85 independent effect sizes extracted from 46 primary studies involving a total of 36,793 learners indicated statistically significant positive effects of CT on mathematics…

Problem-Based Learning in K-8 Mathematics and Science Education: A Literature Review

ERIC Educational Resources Information Center

Merritt, Joi; Lee, Mi Yeon; Rillero, Peter; Kinach, Barbara M.

2017-01-01

This systematic literature review was conducted to explore the effectiveness of problem-based and project-based learning (PBL) implemented with students in early elementary to grade 8 (ages 3-14) in mathematics and science classrooms. Nine studies met the following inclusion criteria: (a) focus on PBL, (b) experimental study, (c) kindergarten to…

Computational modeling in melanoma for novel drug discovery.

PubMed

Pennisi, Marzio; Russo, Giulia; Di Salvatore, Valentina; Candido, Saverio; Libra, Massimo; Pappalardo, Francesco

2016-06-01

There is a growing body of evidence highlighting the applications of computational modeling in the field of biomedicine. It has recently been applied to the in silico analysis of cancer dynamics. In the era of precision medicine, this analysis may allow the discovery of new molecular targets useful for the design of novel therapies and for overcoming resistance to anticancer drugs. According to its molecular behavior, melanoma represents an interesting tumor model in which computational modeling can be applied. Melanoma is an aggressive tumor of the skin with a poor prognosis for patients with advanced disease as it is resistant to current therapeutic approaches. This review discusses the basics of computational modeling in melanoma drug discovery and development. Discussion includes the in silico discovery of novel molecular drug targets, the optimization of immunotherapies and personalized medicine trials. Mathematical and computational models are gradually being used to help understand biomedical data produced by high-throughput analysis. The use of advanced computer models allowing the simulation of complex biological processes provides hypotheses and supports experimental design. The research in fighting aggressive cancers, such as melanoma, is making great strides. Computational models represent the key component to complement these efforts. Due to the combinatorial complexity of new drug discovery, a systematic approach based only on experimentation is not possible. Computational and mathematical models are necessary for bringing cancer drug discovery into the era of omics, big data and personalized medicine.

Analysis and design of a capsule landing system and surface vehicle control system for Mars exploration

NASA Technical Reports Server (NTRS)

Frederick, D. K.; Lashmet, P. K.; Sandor, G. N.; Shen, C. N.; Smith, E. V.; Yerazunis, S. W.

1973-01-01

Problems related to the design and control of a mobile planetary vehicle to implement a systematic plan for the exploration of Mars are reported. Problem areas include: vehicle configuration, control, dynamics, systems and propulsion; systems analysis, terrain modeling and path selection; and chemical analysis of specimens. These tasks are summarized: vehicle model design, mathematical model of vehicle dynamics, experimental vehicle dynamics, obstacle negotiation, electrochemical controls, remote control, collapsibility and deployment, construction of a wheel tester, wheel analysis, payload design, system design optimization, effect of design assumptions, accessory optimal design, on-board computer subsystem, laser range measurement, discrete obstacle detection, obstacle detection systems, terrain modeling, path selection system simulation and evaluation, gas chromatograph/mass spectrometer system concepts, and chromatograph model evaluation and improvement.

A mathematical framework for yield (vs. rate) optimization in constraint-based modeling and applications in metabolic engineering.

PubMed

Klamt, Steffen; Müller, Stefan; Regensburger, Georg; Zanghellini, Jürgen

2018-05-01

The optimization of metabolic rates (as linear objective functions) represents the methodical core of flux-balance analysis techniques which have become a standard tool for the study of genome-scale metabolic models. Besides (growth and synthesis) rates, metabolic yields are key parameters for the characterization of biochemical transformation processes, especially in the context of biotechnological applications. However, yields are ratios of rates, and hence the optimization of yields (as nonlinear objective functions) under arbitrary linear constraints is not possible with current flux-balance analysis techniques. Despite the fundamental importance of yields in constraint-based modeling, a comprehensive mathematical framework for yield optimization is still missing. We present a mathematical theory that allows one to systematically compute and analyze yield-optimal solutions of metabolic models under arbitrary linear constraints. In particular, we formulate yield optimization as a linear-fractional program. For practical computations, we transform the linear-fractional yield optimization problem to a (higher-dimensional) linear problem. Its solutions determine the solutions of the original problem and can be used to predict yield-optimal flux distributions in genome-scale metabolic models. For the theoretical analysis, we consider the linear-fractional problem directly. Most importantly, we show that the yield-optimal solution set (like the rate-optimal solution set) is determined by (yield-optimal) elementary flux vectors of the underlying metabolic model. However, yield- and rate-optimal solutions may differ from each other, and hence optimal (biomass or product) yields are not necessarily obtained at solutions with optimal (growth or synthesis) rates. Moreover, we discuss phase planes/production envelopes and yield spaces, in particular, we prove that yield spaces are convex and provide algorithms for their computation. We illustrate our findings by a small example and demonstrate their relevance for metabolic engineering with realistic models of E. coli. We develop a comprehensive mathematical framework for yield optimization in metabolic models. Our theory is particularly useful for the study and rational modification of cell factories designed under given yield and/or rate requirements. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

A Systematic Review of Interventions for Children Presenting with Dyscalculia in Primary Schools

ERIC Educational Resources Information Center

Monei, Thato; Pedro, Athena

2017-01-01

The acquisition of numerical competency is regarded as imperative for quality of life and economic well-being. Many children have significant mathematical learning difficulties known as dyscalculia. The aim of this research was to systematically review the available literature for interventions with children presenting with dyscalculia in primary…

Research Trends in the Use of Mobile Learning in Mathematics

ERIC Educational Resources Information Center

Crompton, Helen; Burke, Diane

2015-01-01

The use of mobile learning in education is growing at an exponential rate. To best understand how mobile learning is being used, it is crucial to gain a collective understanding of the research that has taken place. This research was a systematic review of 36 studies in mobile learning in mathematics from the year 2000 onward. Eight new findings…

The Quality of Instruction in Urban High Schools: Comparing Mathematics and Science to English and Social Studies Classes in Chicago

ERIC Educational Resources Information Center

Lee, Valerie E.; Robinson, Shanta R.; Sebastian, James

2012-01-01

Is the quality of instruction systematically better in one subject than another? Teachers and students in the same Chicago high schools reported on one core-curriculum class (English, mathematics, science, or social studies) in 2007 surveys. Teachers commented on instructional demands and student participation. Students described engagement,…

Mathematical Modeling of the Transmission Dynamics of Clostridium difficile Infection and Colonization in Healthcare Settings: A Systematic Review

PubMed Central

Gingras, Guillaume; Guertin, Marie-Hélène; Laprise, Jean-François; Drolet, Mélanie; Brisson, Marc

2016-01-01

Background We conducted a systematic review of mathematical models of transmission dynamic of Clostridium difficile infection (CDI) in healthcare settings, to provide an overview of existing models and their assessment of different CDI control strategies. Methods We searched MEDLINE, EMBASE and Web of Science up to February 3, 2016 for transmission-dynamic models of Clostridium difficile in healthcare settings. The models were compared based on their natural history representation of Clostridium difficile, which could include health states (S-E-A-I-R-D: Susceptible-Exposed-Asymptomatic-Infectious-Resistant-Deceased) and the possibility to include healthcare workers and visitors (vectors of transmission). Effectiveness of interventions was compared using the relative reduction (compared to no intervention or current practice) in outcomes such as incidence of colonization, CDI, CDI recurrence, CDI mortality, and length of stay. Results Nine studies describing six different models met the inclusion criteria. Over time, the models have generally increased in complexity in terms of natural history and transmission dynamics and number/complexity of interventions/bundles of interventions examined. The models were categorized into four groups with respect to their natural history representation: S-A-I-R, S-E-A-I, S-A-I, and S-E-A-I-R-D. Seven studies examined the impact of CDI control strategies. Interventions aimed at controlling the transmission, lowering CDI vulnerability and reducing the risk of recurrence/mortality were predicted to reduce CDI incidence by 3–49%, 5–43% and 5–29%, respectively. Bundles of interventions were predicted to reduce CDI incidence by 14–84%. Conclusions Although CDI is a major public health problem, there are very few published transmission-dynamic models of Clostridium difficile. Published models vary substantially in the interventions examined, the outcome measures used and the representation of the natural history of Clostridium difficile, which make it difficult to synthesize results and provide a clear picture of optimal intervention strategies. Future modeling efforts should pay specific attention to calibration, structural uncertainties, and transparent reporting practices. PMID:27690247

Using numeric simulation in an online e-learning environment to teach functional physiological contexts.

PubMed

Christ, Andreas; Thews, Oliver

2016-04-01

Mathematical models are suitable to simulate complex biological processes by a set of non-linear differential equations. These simulation models can be used as an e-learning tool in medical education. However, in many cases these mathematical systems have to be treated numerically which is computationally intensive. The aim of the study was to develop a system for numerical simulation to be used in an online e-learning environment. In the software system the simulation is located on the server as a CGI application. The user (student) selects the boundary conditions for the simulation (e.g., properties of a simulated patient) on the browser. With these parameters the simulation on the server is started and the simulation result is re-transferred to the browser. With this system two examples of e-learning units were realized. The first one uses a multi-compartment model of the glucose-insulin control loop for the simulation of the plasma glucose level after a simulated meal or during diabetes (including treatment by subcutaneous insulin application). The second one simulates the ion transport leading to the resting and action potential in nerves. The student can vary parameters systematically to explore the biological behavior of the system. The described system is able to simulate complex biological processes and offers the possibility to use these models in an online e-learning environment. As far as the underlying principles can be described mathematically, this type of system can be applied to a broad spectrum of biomedical or natural scientific topics. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Are Alternative Strategies Required to Accelerate the Global Elimination of Lymphatic Filariasis? Insights From Mathematical Models

PubMed Central

Stolk, Wilma A; Prada, Joaquin M; Smith, Morgan E; Kontoroupis, Periklis; de Vos, Anneke S; Touloupou, Panayiota; Irvine, Michael A; Brown, Paul; Subramanian, Swaminathan; Kloek, Marielle; Michael, E; Hollingsworth, T Deirdre; de Vlas, Sake J

2018-01-01

Abstract Background With the 2020 target year for elimination of lymphatic filariasis (LF) approaching, there is an urgent need to assess how long mass drug administration (MDA) programs with annual ivermectin + albendazole (IA) or diethylcarbamazine + albendazole (DA) would still have to be continued, and how elimination can be accelerated. We addressed this using mathematical modeling. Methods We used 3 structurally different mathematical models for LF transmission (EPIFIL, LYMFASIM, TRANSFIL) to simulate trends in microfilariae (mf) prevalence for a range of endemic settings, both for the current annual MDA strategy and alternative strategies, assessing the required duration to bring mf prevalence below the critical threshold of 1%. Results Three annual MDA rounds with IA or DA and good coverage (≥65%) are sufficient to reach the threshold in settings that are currently at mf prevalence <4%, but the required duration increases with increasing mf prevalence. Switching to biannual MDA or employing triple-drug therapy (ivermectin, diethylcarbamazine, and albendazole [IDA]) could reduce program duration by about one-third. Optimization of coverage reduces the time to elimination and is particularly important for settings with a history of poorly implemented MDA (low coverage, high systematic noncompliance). Conclusions Modeling suggests that, in several settings, current annual MDA strategies will be insufficient to achieve the 2020 LF elimination targets, and programs could consider policy adjustment to accelerate, guided by recent monitoring and evaluation data. Biannual treatment and IDA hold promise in reducing program duration, provided that coverage is good, but their efficacy remains to be confirmed by more extensive field studies. PMID:29860286

Are Alternative Strategies Required to Accelerate the Global Elimination of Lymphatic Filariasis? Insights From Mathematical Models.

PubMed

Stolk, Wilma A; Prada, Joaquin M; Smith, Morgan E; Kontoroupis, Periklis; de Vos, Anneke S; Touloupou, Panayiota; Irvine, Michael A; Brown, Paul; Subramanian, Swaminathan; Kloek, Marielle; Michael, E; Hollingsworth, T Deirdre; de Vlas, Sake J

2018-06-01

With the 2020 target year for elimination of lymphatic filariasis (LF) approaching, there is an urgent need to assess how long mass drug administration (MDA) programs with annual ivermectin + albendazole (IA) or diethylcarbamazine + albendazole (DA) would still have to be continued, and how elimination can be accelerated. We addressed this using mathematical modeling. We used 3 structurally different mathematical models for LF transmission (EPIFIL, LYMFASIM, TRANSFIL) to simulate trends in microfilariae (mf) prevalence for a range of endemic settings, both for the current annual MDA strategy and alternative strategies, assessing the required duration to bring mf prevalence below the critical threshold of 1%. Three annual MDA rounds with IA or DA and good coverage (≥65%) are sufficient to reach the threshold in settings that are currently at mf prevalence <4%, but the required duration increases with increasing mf prevalence. Switching to biannual MDA or employing triple-drug therapy (ivermectin, diethylcarbamazine, and albendazole [IDA]) could reduce program duration by about one-third. Optimization of coverage reduces the time to elimination and is particularly important for settings with a history of poorly implemented MDA (low coverage, high systematic noncompliance). Modeling suggests that, in several settings, current annual MDA strategies will be insufficient to achieve the 2020 LF elimination targets, and programs could consider policy adjustment to accelerate, guided by recent monitoring and evaluation data. Biannual treatment and IDA hold promise in reducing program duration, provided that coverage is good, but their efficacy remains to be confirmed by more extensive field studies.

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.

Virtual Patients and Sensitivity Analysis of the Guyton Model of Blood Pressure Regulation: Towards Individualized Models of Whole-Body Physiology

PubMed Central

Moss, Robert; Grosse, Thibault; Marchant, Ivanny; Lassau, Nathalie; Gueyffier, François; Thomas, S. Randall

2012-01-01

Mathematical models that integrate multi-scale physiological data can offer insight into physiological and pathophysiological function, and may eventually assist in individualized predictive medicine. We present a methodology for performing systematic analyses of multi-parameter interactions in such complex, multi-scale models. Human physiology models are often based on or inspired by Arthur Guyton's whole-body circulatory regulation model. Despite the significance of this model, it has not been the subject of a systematic and comprehensive sensitivity study. Therefore, we use this model as a case study for our methodology. Our analysis of the Guyton model reveals how the multitude of model parameters combine to affect the model dynamics, and how interesting combinations of parameters may be identified. It also includes a “virtual population” from which “virtual individuals” can be chosen, on the basis of exhibiting conditions similar to those of a real-world patient. This lays the groundwork for using the Guyton model for in silico exploration of pathophysiological states and treatment strategies. The results presented here illustrate several potential uses for the entire dataset of sensitivity results and the “virtual individuals” that we have generated, which are included in the supplementary material. More generally, the presented methodology is applicable to modern, more complex multi-scale physiological models. PMID:22761561

Enhanced orbit determination filter: Inclusion of ground system errors as filter parameters

NASA Technical Reports Server (NTRS)

Masters, W. C.; Scheeres, D. J.; Thurman, S. W.

1994-01-01

The theoretical aspects of an orbit determination filter that incorporates ground-system error sources as model parameters for use in interplanetary navigation are presented in this article. This filter, which is derived from sequential filtering theory, allows a systematic treatment of errors in calibrations of transmission media, station locations, and earth orientation models associated with ground-based radio metric data, in addition to the modeling of the spacecraft dynamics. The discussion includes a mathematical description of the filter and an analytical comparison of its characteristics with more traditional filtering techniques used in this application. The analysis in this article shows that this filter has the potential to generate navigation products of substantially greater accuracy than more traditional filtering procedures.

Consistent Chemical Mechanism from Collaborative Data Processing

DOE PAGES

Slavinskaya, Nadezda; Starcke, Jan-Hendrik; Abbasi, Mehdi; ...

2016-04-01

Numerical tool of Process Informatics Model (PrIMe) is mathematically rigorous and numerically efficient approach for analysis and optimization of chemical systems. It handles heterogeneous data and is scalable to a large number of parameters. The Boundto-Bound Data Collaboration module of the automated data-centric infrastructure of PrIMe was used for the systematic uncertainty and data consistency analyses of the H 2/CO reaction model (73/17) and 94 experimental targets (ignition delay times). The empirical rule for evaluation of the shock tube experimental data is proposed. The initial results demonstrate clear benefits of the PrIMe methods for an evaluation of the kinetic datamore » quality and data consistency and for developing predictive kinetic models.« less

Cancer evolution: mathematical models and computational inference.

PubMed

Beerenwinkel, Niko; Schwarz, Roland F; Gerstung, Moritz; Markowetz, Florian

2015-01-01

Cancer is a somatic evolutionary process characterized by the accumulation of mutations, which contribute to tumor growth, clinical progression, immune escape, and drug resistance development. Evolutionary theory can be used to analyze the dynamics of tumor cell populations and to make inference about the evolutionary history of a tumor from molecular data. We review recent approaches to modeling the evolution of cancer, including population dynamics models of tumor initiation and progression, phylogenetic methods to model the evolutionary relationship between tumor subclones, and probabilistic graphical models to describe dependencies among mutations. Evolutionary modeling helps to understand how tumors arise and will also play an increasingly important prognostic role in predicting disease progression and the outcome of medical interventions, such as targeted therapy. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society of Systematic Biologists.

The development of mathematics courseware for learning line and angle

NASA Astrophysics Data System (ADS)

Halim, Noor Dayana Abd; Han, Ong Boon; Abdullah, Zaleha; Yusup, Junaidah

2015-05-01

Learning software is a teaching aid which is often used in schools to increase students' motivation, attract students' attention and also improve the quality of teaching and learning process. However, the development of learning software should be followed the phases in Instructional Design (ID) Model, therefore the process can be carried out systematic and orderly. Thus, this concept paper describes the application of ADDIE model in the development of mathematics learning courseware for learning Line and Angle named CBL-Math. ADDIE model consists of five consecutive phases which are Analysis, Design, Development, Implementation and Evaluation. Each phase must be properly planned in order to achieve the objectives stated. Other than to describe the processes occurring in each phase, this paper also demonstrating how cognitive theory of multimedia learning principles are integrated in the developed courseware. The principles that applied in the courseware reduce the students' cognitive load while learning the topic of line and angle. With well prepared development process and the integration of appropriate principles, it is expected that the developed software can help students learn effectively and also increase students' achievement in the topic of Line and Angle.

Preserving privacy whilst maintaining robust epidemiological predictions.

PubMed

Werkman, Marleen; Tildesley, Michael J; Brooks-Pollock, Ellen; Keeling, Matt J

2016-12-01

Mathematical models are invaluable tools for quantifying potential epidemics and devising optimal control strategies in case of an outbreak. State-of-the-art models increasingly require detailed individual farm-based and sensitive data, which may not be available due to either lack of capacity for data collection or privacy concerns. However, in many situations, aggregated data are available for use. In this study, we systematically investigate the accuracy of predictions made by mathematical models initialised with varying data aggregations, using the UK 2001 Foot-and-Mouth Disease Epidemic as a case study. We consider the scenario when the only data available are aggregated into spatial grid cells, and develop a metapopulation model where individual farms in a single subpopulation are assumed to behave uniformly and transmit randomly. We also adapt this standard metapopulation model to capture heterogeneity in farm size and composition, using farm census data. Our results show that homogeneous models based on aggregated data overestimate final epidemic size but can perform well for predicting spatial spread. Recognising heterogeneity in farm sizes improves predictions of the final epidemic size, identifying risk areas, determining the likelihood of epidemic take-off and identifying the optimal control strategy. In conclusion, in cases where individual farm-based data are not available, models can still generate meaningful predictions, although care must be taken in their interpretation and use. Copyright © 2016. Published by Elsevier B.V.

Spiral-Wave Dynamics in a Mathematical Model of Human Ventricular Tissue with Myocytes and Fibroblasts

PubMed Central

Nayak, Alok Ranjan; Shajahan, T. K.; Panfilov, A. V.; Pandit, Rahul

2013-01-01

Cardiac fibroblasts, when coupled functionally with myocytes, can modulate the electrophysiological properties of cardiac tissue. We present systematic numerical studies of such modulation of electrophysiological properties in mathematical models for (a) single myocyte-fibroblast (MF) units and (b) two-dimensional (2D) arrays of such units; our models build on earlier ones and allow for zero-, one-, and two-sided MF couplings. Our studies of MF units elucidate the dependence of the action-potential (AP) morphology on parameters such as , the fibroblast resting-membrane potential, the fibroblast conductance , and the MF gap-junctional coupling . Furthermore, we find that our MF composite can show autorhythmic and oscillatory behaviors in addition to an excitable response. Our 2D studies use (a) both homogeneous and inhomogeneous distributions of fibroblasts, (b) various ranges for parameters such as , and , and (c) intercellular couplings that can be zero-sided, one-sided, and two-sided connections of fibroblasts with myocytes. We show, in particular, that the plane-wave conduction velocity decreases as a function of , for zero-sided and one-sided couplings; however, for two-sided coupling, decreases initially and then increases as a function of , and, eventually, we observe that conduction failure occurs for low values of . In our homogeneous studies, we find that the rotation speed and stability of a spiral wave can be controlled either by controlling or . Our studies with fibroblast inhomogeneities show that a spiral wave can get anchored to a local fibroblast inhomogeneity. We also study the efficacy of a low-amplitude control scheme, which has been suggested for the control of spiral-wave turbulence in mathematical models for cardiac tissue, in our MF model both with and without heterogeneities. PMID:24023798

A procedure for the significance testing of unmodeled errors in GNSS observations

NASA Astrophysics Data System (ADS)

Li, Bofeng; Zhang, Zhetao; Shen, Yunzhong; Yang, Ling

2018-01-01

It is a crucial task to establish a precise mathematical model for global navigation satellite system (GNSS) observations in precise positioning. Due to the spatiotemporal complexity of, and limited knowledge on, systematic errors in GNSS observations, some residual systematic errors would inevitably remain even after corrected with empirical model and parameterization. These residual systematic errors are referred to as unmodeled errors. However, most of the existing studies mainly focus on handling the systematic errors that can be properly modeled and then simply ignore the unmodeled errors that may actually exist. To further improve the accuracy and reliability of GNSS applications, such unmodeled errors must be handled especially when they are significant. Therefore, a very first question is how to statistically validate the significance of unmodeled errors. In this research, we will propose a procedure to examine the significance of these unmodeled errors by the combined use of the hypothesis tests. With this testing procedure, three components of unmodeled errors, i.e., the nonstationary signal, stationary signal and white noise, are identified. The procedure is tested by using simulated data and real BeiDou datasets with varying error sources. The results show that the unmodeled errors can be discriminated by our procedure with approximately 90% confidence. The efficiency of the proposed procedure is further reassured by applying the time-domain Allan variance analysis and frequency-domain fast Fourier transform. In summary, the spatiotemporally correlated unmodeled errors are commonly existent in GNSS observations and mainly governed by the residual atmospheric biases and multipath. Their patterns may also be impacted by the receiver.

Two-dimensional dispersion of magnetostatic volume spin waves

NASA Astrophysics Data System (ADS)

Buijnsters, Frank J.; van Tilburg, Lennert J. A.; Fasolino, Annalisa; Katsnelson, Mikhail I.

2018-06-01

Owing to the dipolar (magnetostatic) interaction, long-wavelength spin waves in in-plane magnetized films show an unusual dispersion behavior, which can be mathematically described by the model of and and refinements thereof. However, solving the two-dimensional dispersion requires the evaluation of a set of coupled transcendental equations and one has to rely on numerics. In this work, we present a systematic perturbative analysis of the spin wave model. An expansion in the in-plane wavevector allows us to obtain explicit closed-form expressions for the dispersion relation and mode profiles in various asymptotic regimes. Moreover, we derive a very accurate semi-analytical expression for the dispersion relation of the lowest-frequency mode that is straightforward to evaluate.

Modelling and Simulation of Search Engine

NASA Astrophysics Data System (ADS)

Nasution, Mahyuddin K. M.

2017-01-01

The best tool currently used to access information is a search engine. Meanwhile, the information space has its own behaviour. Systematically, an information space needs to be familiarized with mathematics so easily we identify the characteristics associated with it. This paper reveal some characteristics of search engine based on a model of document collection, which are then estimated the impact on the feasibility of information. We reveal some of characteristics of search engine on the lemma and theorem about singleton and doubleton, then computes statistically characteristic as simulating the possibility of using search engine. In this case, Google and Yahoo. There are differences in the behaviour of both search engines, although in theory based on the concept of documents collection.

Strategies for Reduced-Order Models in Uncertainty Quantification of Complex Turbulent Dynamical Systems

NASA Astrophysics Data System (ADS)

Qi, Di

Turbulent dynamical systems are ubiquitous in science and engineering. Uncertainty quantification (UQ) in turbulent dynamical systems is a grand challenge where the goal is to obtain statistical estimates for key physical quantities. In the development of a proper UQ scheme for systems characterized by both a high-dimensional phase space and a large number of instabilities, significant model errors compared with the true natural signal are always unavoidable due to both the imperfect understanding of the underlying physical processes and the limited computational resources available. One central issue in contemporary research is the development of a systematic methodology for reduced order models that can recover the crucial features both with model fidelity in statistical equilibrium and with model sensitivity in response to perturbations. In the first part, we discuss a general mathematical framework to construct statistically accurate reduced-order models that have skill in capturing the statistical variability in the principal directions of a general class of complex systems with quadratic nonlinearity. A systematic hierarchy of simple statistical closure schemes, which are built through new global statistical energy conservation principles combined with statistical equilibrium fidelity, are designed and tested for UQ of these problems. Second, the capacity of imperfect low-order stochastic approximations to model extreme events in a passive scalar field advected by turbulent flows is investigated. The effects in complicated flow systems are considered including strong nonlinear and non-Gaussian interactions, and much simpler and cheaper imperfect models with model error are constructed to capture the crucial statistical features in the stationary tracer field. Several mathematical ideas are introduced to improve the prediction skill of the imperfect reduced-order models. Most importantly, empirical information theory and statistical linear response theory are applied in the training phase for calibrating model errors to achieve optimal imperfect model parameters; and total statistical energy dynamics are introduced to improve the model sensitivity in the prediction phase especially when strong external perturbations are exerted. The validity of reduced-order models for predicting statistical responses and intermittency is demonstrated on a series of instructive models with increasing complexity, including the stochastic triad model, the Lorenz '96 model, and models for barotropic and baroclinic turbulence. The skillful low-order modeling methods developed here should also be useful for other applications such as efficient algorithms for data assimilation.

Analysis and design of a capsule landing system and surface vehicle control system for Mars exporation

NASA Technical Reports Server (NTRS)

Frederick, D. K.; Lashmet, P. K.; Sandor, G. N.; Shen, C. N.; Smith, E. J.; Yerazunis, S. W.

1972-01-01

The problems related to the design and control of a mobile planetary vehicle to implement a systematic plan for the exploration of Mars were investigated. Problem areas receiving attention include: vehicle configuration, control, dynamics, systems and propulsion; systems analysis; navigation, terrain modeling and path selection; and chemical analysis of specimens. The following specific tasks were studied: vehicle model design, mathematical modeling of dynamic vehicle, experimental vehicle dynamics, obstacle negotiation, electromechanical controls, collapsibility and deployment, construction of a wheel tester, wheel analysis, payload design, system design optimization, effect of design assumptions, accessory optimal design, on-board computer subsystem, laser range measurement, discrete obstacle detection, obstacle detection systems, terrain modeling, path selection system simulation and evaluation, gas chromatograph/mass spectrometer system concepts, chromatograph model evaluation and improvement and transport parameter evaluation.

Analysis and design of a capsule landing system and surface vehicle control system for Mars exploration

NASA Technical Reports Server (NTRS)

Frederick, D. K.; Lashmet, P. K.; Sandor, G. N.; Shen, C. N.; Smith, E. J.; Yerazunis, S. W.

1972-01-01

Investigation of problems related to the design and control of a mobile planetary vehicle to implement a systematic plan for the exploration of Mars has been undertaken. Problem areas receiving attention include: vehicle configuration, control, dynamics, systems and propulsion; systems analysis; terrain modeling and path selection; and chemical analysis of specimens. The following specific tasks have been under study: vehicle model design, mathematical modeling of a dynamic vehicle, experimental vehicle dynamics, obstacle negotiation, electromechanical controls, collapsibility and deployment, construction of a wheel tester, wheel analysis, payload design, system design optimization, effect of design assumptions, accessory optimal design, on-board computer sybsystem, laser range measurement, discrete obstacle detection, obstacle detection systems, terrain modeling, path selection system simulation and evaluation, gas chromatograph/mass spectrometer system concepts, chromatograph model evaluation and improvement.

Continuous real-time in vivo measurement of cerebral nitric oxide supports theoretical predictions of an irreversible switching in cerebral ROS after sufficient exposure to external toxins.

PubMed

Finnerty, Niall J; O'Riordan, Saidhbhe L; Lowry, John P; Cloutier, Mathieu; Wellstead, Peter

2013-01-01

Mathematical models of the interactions between alphasynuclein (αS) and reactive oxygen species (ROS) predict a systematic and irreversible switching to damagingly high levels of ROS after sufficient exposure to risk factors associated with Parkinson's disease (PD). We tested this prediction by continuously monitoring real-time changes in neurochemical levels over periods of several days in animals exposed to a toxin known to cause Parkinsonian symptoms. Nitric oxide (NO) sensors were implanted in the brains of freely moving rats and the NO levels continuously recorded while the animals were exposed to paraquat (PQ) injections of various amounts and frequencies. Long-term, real-time measurement of NO in a cohort of animals showed systematic switching in levels when PQ injections of sufficient size and frequency were administered. The experimental observations of changes in NO imply a corresponding switching in endogenous ROS levels and support theoretical predictions of an irreversible change to damagingly high levels of endogenous ROS when PD risks are sufficiently large. Our current results only consider one form of PD risk, however, we are sufficiently confident in them to conclude that: (i) continuous long-term measurement of neurochemical dynamics provide a novel way to measure the temporal change and system dynamics which determine Parkinsonian damage, and (ii) the bistable feedback switching predicted by mathematical modelling seems to exist and that a deeper analysis of its characteristics would provide a way of understanding the pathogenic mechanisms that initiate Parkinsonian cell damage.

A Mathematical Model of Neonatal Rat Atrial Monolayers with Constitutively Active Acetylcholine-Mediated K+ Current

PubMed Central

Majumder, Rupamanjari; Jangsangthong, Wanchana; Feola, Iolanda; Ypey, Dirk L.; Pijnappels, Daniël A.; Panfilov, Alexander V.

2016-01-01

Atrial fibrillation (AF) is the most frequent form of arrhythmia occurring in the industrialized world. Because of its complex nature, each identified form of AF requires specialized treatment. Thus, an in-depth understanding of the bases of these arrhythmias is essential for therapeutic development. A variety of experimental studies aimed at understanding the mechanisms of AF are performed using primary cultures of neonatal rat atrial cardiomyocytes (NRAMs). Previously, we have shown that the distinct advantage of NRAM cultures is that they allow standardized, systematic, robust re-entry induction in the presence of a constitutively-active acetylcholine-mediated K+ current (IKACh-c). Experimental studies dedicated to mechanistic explorations of AF, using these cultures, often use computer models for detailed electrophysiological investigations. However, currently, no mathematical model for NRAMs is available. Therefore, in the present study we propose the first model for the action potential (AP) of a NRAM with constitutively-active acetylcholine-mediated K+ current (IKACh-c). The descriptions of the ionic currents were based on patch-clamp data obtained from neonatal rats. Our monolayer model closely mimics the action potential duration (APD) restitution and conduction velocity (CV) restitution curves presented in our previous in vitro studies. In addition, the model reproduces the experimentally observed dynamics of spiral wave rotation, in the absence and in the presence of drug interventions, and in the presence of localized myofibroblast heterogeneities. PMID:27332890

System-level modeling of acetone-butanol-ethanol fermentation.

PubMed

Liao, Chen; Seo, Seung-Oh; Lu, Ting

2016-05-01

Acetone-butanol-ethanol (ABE) fermentation is a metabolic process of clostridia that produces bio-based solvents including butanol. It is enabled by an underlying metabolic reaction network and modulated by cellular gene regulation and environmental cues. Mathematical modeling has served as a valuable strategy to facilitate the understanding, characterization and optimization of this process. In this review, we highlight recent advances in system-level, quantitative modeling of ABE fermentation. We begin with an overview of integrative processes underlying the fermentation. Next we survey modeling efforts including early simple models, models with a systematic metabolic description, and those incorporating metabolism through simple gene regulation. Particular focus is given to a recent system-level model that integrates the metabolic reactions, gene regulation and environmental cues. We conclude by discussing the remaining challenges and future directions towards predictive understanding of ABE fermentation. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Measuring Near-Infrared Spectroscopy Derived Cerebral Autoregulation in Neonates: From Research Tool Toward Bedside Multimodal Monitoring

PubMed Central

Thewissen, Liesbeth; Caicedo, Alexander; Lemmers, Petra; Van Bel, Frank; Van Huffel, Sabine; Naulaers, Gunnar

2018-01-01

Introduction: Cerebral autoregulation (CAR), the ability of the human body to maintain cerebral blood flow (CBF) in a wide range of perfusion pressures, can be calculated by describing the relation between arterial blood pressure (ABP) and cerebral oxygen saturation measured by near-infrared spectroscopy (NIRS). In literature, disturbed CAR is described in different patient groups, using multiple measurement techniques and mathematical models. Furthermore, it is unclear to what extent cerebral pathology and outcome can be explained by impaired CAR. Aim and methods: In order to summarize CAR studies using NIRS in neonates, a systematic review was performed in the PUBMED and EMBASE database. To provide a general overview of the clinical framework used to study CAR, the different preprocessing methods and mathematical models are described and explained. Furthermore, patient characteristics, definition of impaired CAR and the outcome according to this definition is described organized for the different patient groups. Results: Forty-six articles were included in this review. Four patient groups were established: preterm infants during the transitional period, neonates receiving specific medication/treatment, neonates with congenital heart disease and neonates with hypoxic-ischemic encephalopathy (HIE) treated with therapeutic hypothermia. Correlation, coherence and transfer function (TF) gain are the mathematical models most frequently used to describe CAR. The definition of impaired CAR is depending on the mathematical model used. The incidence of intraventricular hemorrhage in preterm infants is the outcome variable most frequently correlated with impaired CAR. Hypotension, disease severity, dopamine treatment, injury on magnetic resonance imaging (MRI) and long term outcome are associated with impaired CAR. Prospective interventional studies are lacking in all research areas. Discussion and conclusion: NIRS derived CAR measurement is an important research tool to improve knowledge about central hemodynamic fluctuations during the transitional period, cerebral pharmacodynamics of frequently used medication (sedatives-inotropes) and cerebral effects of specific therapies in neonatology. Uniformity regarding measurement techniques and mathematical models is needed. Multimodal monitoring databases of neonatal intensive care patients of multiple centers, together with identical outcome parameters are needed to compare different techniques and make progress in this field. Real-time bedside monitoring of CAR, together with conventional monitoring, seems a promising technique to improve individual patient care. PMID:29868521

Mathematization Competencies of Pre-Service Elementary Mathematics Teachers in the Mathematical Modelling Process

ERIC Educational Resources Information Center

Yilmaz, Suha; Tekin-Dede, Ayse

2016-01-01

Mathematization competency is considered in the field as the focus of modelling process. Considering the various definitions, the components of the mathematization competency are determined as identifying assumptions, identifying variables based on the assumptions and constructing mathematical model/s based on the relations among identified…

A systematic literature review of Burgers' equation with recent advances

NASA Astrophysics Data System (ADS)

Bonkile, Mayur P.; Awasthi, Ashish; Lakshmi, C.; Mukundan, Vijitha; Aswin, V. S.

2018-06-01

Even if numerical simulation of the Burgers' equation is well documented in the literature, a detailed literature survey indicates that gaps still exist for comparative discussion regarding the physical and mathematical significance of the Burgers' equation. Recently, an increasing interest has been developed within the scientific community, for studying non-linear convective-diffusive partial differential equations partly due to the tremendous improvement in computational capacity. Burgers' equation whose exact solution is well known, is one of the famous non-linear partial differential equations which is suitable for the analysis of various important areas. A brief historical review of not only the mathematical, but also the physical significance of the solution of Burgers' equation is presented, emphasising current research strategies, and the challenges that remain regarding the accuracy, stability and convergence of various schemes are discussed. One of the objectives of this paper is to discuss the recent developments in mathematical modelling of Burgers' equation and thus open doors for improvement. No claim is made that the content of the paper is new. However, it is a sincere effort to outline the physical and mathematical importance of Burgers' equation in the most simplified ways. We throw some light on the plethora of challenges which need to be overcome in the research areas and give motivation for the next breakthrough to take place in a numerical simulation of ordinary / partial differential equations.

The futility of utility: how market dynamics marginalize Adam Smith

NASA Astrophysics Data System (ADS)

McCauley, Joseph L.

2000-10-01

Economic theorizing is based on the postulated, nonempiric notion of utility. Economists assume that prices, dynamics, and market equilibria are supposed to be derived from utility. The results are supposed to represent mathematically the stabilizing action of Adam Smith's invisible hand. In deterministic excess demand dynamics I show the following. A utility function generally does not exist mathematically due to nonintegrable dynamics when production/investment are accounted for, resolving Mirowski's thesis. Price as a function of demand does not exist mathematically either. All equilibria are unstable. I then explain how deterministic chaos can be distinguished from random noise at short times. In the generalization to liquid markets and finance theory described by stochastic excess demand dynamics, I also show the following. Market price distributions cannot be rescaled to describe price movements as ‘equilibrium’ fluctuations about a systematic drift in price. Utility maximization does not describe equilibrium. Maximization of the Gibbs entropy of the observed price distribution of an asset would describe equilibrium, if equilibrium could be achieved, but equilibrium does not describe real, liquid markets (stocks, bonds, foreign exchange). There are three inconsistent definitions of equilibrium used in economics and finance, only one of which is correct. Prices in unregulated free markets are unstable against both noise and rising or falling expectations: Adam Smith's stabilizing invisible hand does not exist, either in mathematical models of liquid market data, or in real market data.

The mathematical origins of the kinetic compensation effect: 2. The effect of systematic errors.

PubMed

Barrie, Patrick J

2012-01-07

The kinetic compensation effect states that there is a linear relationship between Arrhenius parameters ln A and E for a family of related processes. It is a widely observed phenomenon in many areas of science, notably heterogeneous catalysis. This paper explores mathematical, rather than physicochemical, explanations for the compensation effect in certain situations. Three different topics are covered theoretically and illustrated by examples. Firstly, the effect of systematic errors in experimental kinetic data is explored, and it is shown that these create apparent compensation effects. Secondly, analysis of kinetic data when the Arrhenius parameters depend on another parameter is examined. In the case of temperature programmed desorption (TPD) experiments when the activation energy depends on surface coverage, it is shown that a common analysis method induces a systematic error, causing an apparent compensation effect. Thirdly, the effect of analysing the temperature dependence of an overall rate of reaction, rather than a rate constant, is investigated. It is shown that this can create an apparent compensation effect, but only under some conditions. This result is illustrated by a case study for a unimolecular reaction on a catalyst surface. Overall, the work highlights the fact that, whenever a kinetic compensation effect is observed experimentally, the possibility of it having a mathematical origin should be carefully considered before any physicochemical conclusions are drawn.

A New Biogeochemical Computational Framework Integrated within the Community Land Model

NASA Astrophysics Data System (ADS)

Fang, Y.; Li, H.; Liu, C.; Huang, M.; Leung, L.

2012-12-01

Terrestrial biogeochemical processes, particularly carbon cycle dynamics, have been shown to significantly influence regional and global climate changes. Modeling terrestrial biogeochemical processes within the land component of Earth System Models such as the Community Land model (CLM), however, faces three major challenges: 1) extensive efforts in modifying modeling structures and rewriting computer programs to incorporate biogeochemical processes with increasing complexity, 2) expensive computational cost to solve the governing equations due to numerical stiffness inherited from large variations in the rates of biogeochemical processes, and 3) lack of an efficient framework to systematically evaluate various mathematical representations of biogeochemical processes. To address these challenges, we introduce a new computational framework to incorporate biogeochemical processes into CLM, which consists of a new biogeochemical module with a generic algorithm and reaction database. New and updated biogeochemical processes can be incorporated into CLM without significant code modification. To address the stiffness issue, algorithms and criteria will be developed to identify fast processes, which will be replaced with algebraic equations and decoupled from slow processes. This framework can serve as a generic and user-friendly platform to test out different mechanistic process representations and datasets and gain new insight on the behavior of the terrestrial ecosystems in response to climate change in a systematic way.

Systematic modelling and design evaluation of unperturbed tumour dynamics in xenografts.

PubMed

Parra Guillen, Zinnia P Patricia; Mangas Sanjuan, Victor; Garcia-Cremades, Maria; Troconiz, Inaki F; Mo, Gary; Pitou, Celine; Iversen, Philip W; Wallin, Johan E

2018-04-24

Xenograft mice are largely used to evaluate the efficacy of oncological drugs during preclinical phases of drug discovery and development. Mathematical models provide a useful tool to quantitatively characterise tumour growth dynamics and also optimise upcoming experiments. To the best of our knowledge, this is the first report where unperturbed growth of a large set of tumour cell lines (n=28) has been systematically analysed using the model proposed by Simeoni in the context of non-linear mixed effect (NLME). Exponential growth was identified as the governing mechanism in the majority of the cell lines, with constant rate values ranging from 0.0204 to 0.203 day -1 No common patterns could be observed across tumour types, highlighting the importance of combining information from different cell lines when evaluating drug activity. Overall, typical model parameters were precisely estimated using designs where tumour size measurements were taken every two days. Moreover, reducing the number of measurement to twice per week, or even once per week for cell lines with low growth rates, showed little impact on parameter precision. However, in order to accurately characterise parameter variability (i.e. relative standard errors below 50%), a sample size of at least 50 mice is needed. This work illustrates the feasibility to systematically apply NLME models to characterise tumour growth in drug discovery and development, and constitutes a valuable source of data to optimise experimental designs by providing an a priori sampling window and minimising the number of samples required. The American Society for Pharmacology and Experimental Therapeutics.

Calcium dynamics and signaling in vascular regulation: computational models

PubMed Central

Tsoukias, Nikolaos Michael

2013-01-01

Calcium is a universal signaling molecule with a central role in a number of vascular functions including in the regulation of tone and blood flow. Experimentation has provided insights into signaling pathways that lead to or affected by Ca2+ mobilization in the vasculature. Mathematical modeling offers a systematic approach to the analysis of these mechanisms and can serve as a tool for data interpretation and for guiding new experimental studies. Comprehensive models of calcium dynamics are well advanced for some systems such as the heart. This review summarizes the progress that has been made in modeling Ca2+ dynamics and signaling in vascular cells. Model simulations show how Ca2+ signaling emerges as a result of complex, nonlinear interactions that cannot be properly analyzed using only a reductionist's approach. A strategy of integrative modeling in the vasculature is outlined that will allow linking macroscale pathophysiological responses to the underlying cellular mechanisms. PMID:21061306

A Quantitative Model of Early Atherosclerotic Plaques Parameterized Using In Vitro Experiments.

PubMed

Thon, Moritz P; Ford, Hugh Z; Gee, Michael W; Myerscough, Mary R

2018-01-01

There are a growing number of studies that model immunological processes in the artery wall that lead to the development of atherosclerotic plaques. However, few of these models use parameters that are obtained from experimental data even though data-driven models are vital if mathematical models are to become clinically relevant. We present the development and analysis of a quantitative mathematical model for the coupled inflammatory, lipid and macrophage dynamics in early atherosclerotic plaques. Our modeling approach is similar to the biologists' experimental approach where the bigger picture of atherosclerosis is put together from many smaller observations and findings from in vitro experiments. We first develop a series of three simpler submodels which are least-squares fitted to various in vitro experimental results from the literature. Subsequently, we use these three submodels to construct a quantitative model of the development of early atherosclerotic plaques. We perform a local sensitivity analysis of the model with respect to its parameters that identifies critical parameters and processes. Further, we present a systematic analysis of the long-term outcome of the model which produces a characterization of the stability of model plaques based on the rates of recruitment of low-density lipoproteins, high-density lipoproteins and macrophages. The analysis of the model suggests that further experimental work quantifying the different fates of macrophages as a function of cholesterol load and the balance between free cholesterol and cholesterol ester inside macrophages may give valuable insight into long-term atherosclerotic plaque outcomes. This model is an important step toward models applicable in a clinical setting.

Mathematical Modeling in Mathematics Education: Basic Concepts and Approaches

ERIC Educational Resources Information Center

Erbas, Ayhan Kürsat; Kertil, Mahmut; Çetinkaya, Bülent; Çakiroglu, Erdinç; Alacaci, Cengiz; Bas, Sinem

2014-01-01

Mathematical modeling and its role in mathematics education have been receiving increasing attention in Turkey, as in many other countries. The growing body of literature on this topic reveals a variety of approaches to mathematical modeling and related concepts, along with differing perspectives on the use of mathematical modeling in teaching and…

Elementary Preservice Teachers' and Elementary Inservice Teachers' Knowledge of Mathematical Modeling

ERIC Educational Resources Information Center

Schwerdtfeger, Sara

2017-01-01

This study examined the differences in knowledge of mathematical modeling between a group of elementary preservice teachers and a group of elementary inservice teachers. Mathematical modeling has recently come to the forefront of elementary mathematics classrooms because of the call to add mathematical modeling tasks in mathematics classes through…

A Case Study of Teachers' Development of Well-Structured Mathematical Modelling Activities

ERIC Educational Resources Information Center

Stohlmann, Micah; Maiorca, Cathrine; Allen, Charlie

2017-01-01

This case study investigated how three teachers developed mathematical modelling activities integrated with content standards through participation in a course on mathematical modelling. The class activities involved experiencing a mathematical modelling activity, reading and rating example mathematical modelling activities, reading articles about…

Surface conservation laws at microscopically diffuse interfaces.

PubMed

Chu, Kevin T; Bazant, Martin Z

2007-11-01

In studies of interfaces with dynamic chemical composition, bulk and interfacial quantities are often coupled via surface conservation laws of excess surface quantities. While this approach is easily justified for microscopically sharp interfaces, its applicability in the context of microscopically diffuse interfaces is less theoretically well-established. Furthermore, surface conservation laws (and interfacial models in general) are often derived phenomenologically rather than systematically. In this article, we first provide a mathematically rigorous justification for surface conservation laws at diffuse interfaces based on an asymptotic analysis of transport processes in the boundary layer and derive general formulae for the surface and normal fluxes that appear in surface conservation laws. Next, we use nonequilibrium thermodynamics to formulate surface conservation laws in terms of chemical potentials and provide a method for systematically deriving the structure of the interfacial layer. Finally, we derive surface conservation laws for a few examples from diffusive and electrochemical transport.

Systematic design for trait introgression projects.

PubMed

Cameron, John N; Han, Ye; Wang, Lizhi; Beavis, William D

2017-10-01

Using an Operations Research approach, we demonstrate design of optimal trait introgression projects with respect to competing objectives. We demonstrate an innovative approach for designing Trait Introgression (TI) projects based on optimization principles from Operations Research. If the designs of TI projects are based on clear and measurable objectives, they can be translated into mathematical models with decision variables and constraints that can be translated into Pareto optimality plots associated with any arbitrary selection strategy. The Pareto plots can be used to make rational decisions concerning the trade-offs between maximizing the probability of success while minimizing costs and time. The systematic rigor associated with a cost, time and probability of success (CTP) framework is well suited to designing TI projects that require dynamic decision making. The CTP framework also revealed that previously identified 'best' strategies can be improved to be at least twice as effective without increasing time or expenses.

Clinical and economic assessment of different general population strategies of pertussis vaccine booster regarding number of doses and age of application for reducing whooping cough disease burden: a systematic review.

PubMed

Rodríguez-Cobo, Iria; Chen, Yen-Fu; Olowokure, Babatunde; Litchfield, Ian

2008-12-09

Pertussis continues to be an important cause of morbidity and mortality in children too young to be fully protected despite high vaccination coverage. This has been attributed to waning immunity in older people, leading to the development of strategies to increase levels of immunity. A systematic review was conducted to assess the clinical and cost effectiveness of four population-based strategies for pertussis booster vaccination: single booster at 12-24 months old, single pre-school booster, single adolescent booster and multiple boosters in adulthood every 10 years. Electronic databases and Internet resources were searched to June 2006. Nine observational studies, four mathematical models and eight economic evaluations were included, evaluating four different strategies. Strong evidence to recommend any of these strategies was not found.

Modeling genome-wide dynamic regulatory network in mouse lungs with influenza infection using high-dimensional ordinary differential equations.

PubMed

Wu, Shuang; Liu, Zhi-Ping; Qiu, Xing; Wu, Hulin

2014-01-01

The immune response to viral infection is regulated by an intricate network of many genes and their products. The reverse engineering of gene regulatory networks (GRNs) using mathematical models from time course gene expression data collected after influenza infection is key to our understanding of the mechanisms involved in controlling influenza infection within a host. A five-step pipeline: detection of temporally differentially expressed genes, clustering genes into co-expressed modules, identification of network structure, parameter estimate refinement, and functional enrichment analysis, is developed for reconstructing high-dimensional dynamic GRNs from genome-wide time course gene expression data. Applying the pipeline to the time course gene expression data from influenza-infected mouse lungs, we have identified 20 distinct temporal expression patterns in the differentially expressed genes and constructed a module-based dynamic network using a linear ODE model. Both intra-module and inter-module annotations and regulatory relationships of our inferred network show some interesting findings and are highly consistent with existing knowledge about the immune response in mice after influenza infection. The proposed method is a computationally efficient, data-driven pipeline bridging experimental data, mathematical modeling, and statistical analysis. The application to the influenza infection data elucidates the potentials of our pipeline in providing valuable insights into systematic modeling of complicated biological processes.

Development Mathematic Assessment to Increase Mathematical Prerequisite Ability on The Student with Learning Disabilities in Inclusive Elementary School

NASA Astrophysics Data System (ADS)

Robiansyah, S. T. U.; Nanang, F.; Hidayat

2018-01-01

The purpose of this study was to introduce about mathematic assessment is a process of obtaining data or information about the mastery of a student's mathematical skills as an ingredient in preparing a learning program. With this mathematics assessment can be known obstacles, difficulties and needs of students especially in the field of mathematic, so that the learning program will be in accordance with the potential students because it is tailored to what is required of students. This research study was conducted at elementary school of inclusive precisely at SDN Sukagalih I Bandung City based learning in setting of inclusive education. This research study is motivated by the existence of a first-grade student who has disabilities learning in mathematics, the ability of the mathematical prerequisite mastery of the classification of objects by color. The results of the research can provide a profile picture of student data information, the data obtained from the results of the development of systematic and formal mathematical assessment. After doing the development of mathematics assessment then the teacher gets important related information: 1. process the analysis of students’ learning needs, especially in the field of mathematics, 2. preparing the learning program planning according to student learning needs, 3. Designing procedural of method remedial program.

Dependence of Dynamic Modeling Accuracy on Sensor Measurements, Mass Properties, and Aircraft Geometry

NASA Technical Reports Server (NTRS)

Grauer, Jared A.; Morelli, Eugene A.

2013-01-01

The NASA Generic Transport Model (GTM) nonlinear simulation was used to investigate the effects of errors in sensor measurements, mass properties, and aircraft geometry on the accuracy of identified parameters in mathematical models describing the flight dynamics and determined from flight data. Measurements from a typical flight condition and system identification maneuver were systematically and progressively deteriorated by introducing noise, resolution errors, and bias errors. The data were then used to estimate nondimensional stability and control derivatives within a Monte Carlo simulation. Based on these results, recommendations are provided for maximum allowable errors in sensor measurements, mass properties, and aircraft geometry to achieve desired levels of dynamic modeling accuracy. Results using additional flight conditions and parameter estimation methods, as well as a nonlinear flight simulation of the General Dynamics F-16 aircraft, were compared with these recommendations

Specific learning disability in mathematics: a comprehensive review.

PubMed

Soares, Neelkamal; Evans, Teresa; Patel, Dilip R

2018-01-01

Math skills are necessary for success in the childhood educational and future adult work environment. This article reviews the changing terminology for specific learning disabilities (SLD) in math and describes the emerging genetics and neuroimaging studies that relate to individuals with math disability (MD). It is important to maintain a developmental perspective on MD, as presentation changes with age, instruction, and the different models (educational and medical) of identification. Intervention requires a systematic approach to screening and remediation that has evolved with more evidence-based literature. Newer directions in behavioral, educational and novel interventions are described.

Specific learning disability in mathematics: a comprehensive review

PubMed Central

Evans, Teresa; Patel, Dilip R.

2018-01-01

Math skills are necessary for success in the childhood educational and future adult work environment. This article reviews the changing terminology for specific learning disabilities (SLD) in math and describes the emerging genetics and neuroimaging studies that relate to individuals with math disability (MD). It is important to maintain a developmental perspective on MD, as presentation changes with age, instruction, and the different models (educational and medical) of identification. Intervention requires a systematic approach to screening and remediation that has evolved with more evidence-based literature. Newer directions in behavioral, educational and novel interventions are described. PMID:29441282

Development of innovative activity of the enterprises of construction branch in the direction of increase in resource-saving and energy efficiency

NASA Astrophysics Data System (ADS)

Papelniuk, Oksana

2017-10-01

The author studies innovative activity of enterprises and carries out the classification of conditions and factors of construction enterprises’ innovative activity, and conducts systematization of specific features of this innovative activity. On the basis of statistical data on structure and dynamics of innovations the author carries out the research with the use of methods of economic-mathematical modelling in order to offer the approach which will allow construction enterprises to define the directions of innovative activity for achievement of a resource-saving and energy efficiency in construction sector.

Mathematical Modelling Approach in Mathematics Education

ERIC Educational Resources Information Center

Arseven, Ayla

2015-01-01

The topic of models and modeling has come to be important for science and mathematics education in recent years. The topic of "Modeling" topic is especially important for examinations such as PISA which is conducted at an international level and measures a student's success in mathematics. Mathematical modeling can be defined as using…

Mathematical Modelling in the Junior Secondary Years: An Approach Incorporating Mathematical Technology

ERIC Educational Resources Information Center

Lowe, James; Carter, Merilyn; Cooper, Tom

2018-01-01

Mathematical models are conceptual processes that use mathematics to describe, explain, and/or predict the behaviour of complex systems. This article is written for teachers of mathematics in the junior secondary years (including out-of-field teachers of mathematics) who may be unfamiliar with mathematical modelling, to explain the steps involved…

Mathematics teachers' conceptions about modelling activities and its reflection on their beliefs about mathematics

NASA Astrophysics Data System (ADS)

Shahbari, Juhaina Awawdeh

2018-07-01

The current study examines whether the engagement of mathematics teachers in modelling activities and subsequent changes in their conceptions about these activities affect their beliefs about mathematics. The sample comprised 52 mathematics teachers working in small groups in four modelling activities. The data were collected from teachers' Reports about features of each activity, interviews and questionnaires on teachers' beliefs about mathematics. The findings indicated changes in teachers' conceptions about the modelling activities. Most teachers referred to the first activity as a mathematical problem but emphasized only the mathematical notions or the mathematical operations in the modelling process; changes in their conceptions were gradual. Most of the teachers referred to the fourth activity as a mathematical problem and emphasized features of the whole modelling process. The results of the interviews indicated that changes in the teachers' conceptions can be attributed to structure of the activities, group discussions, solution paths and elicited models. These changes about modelling activities were reflected in teachers' beliefs about mathematics. The quantitative findings indicated that the teachers developed more constructive beliefs about mathematics after engagement in the modelling activities and that the difference was significant, however there was no significant difference regarding changes in their traditional beliefs.

The 24-Hour Mathematical Modeling Challenge

ERIC Educational Resources Information Center

Galluzzo, Benjamin J.; Wendt, Theodore J.

2015-01-01

Across the mathematics curriculum there is a renewed emphasis on applications of mathematics and on mathematical modeling. Providing students with modeling experiences beyond the ordinary classroom setting remains a challenge, however. In this article, we describe the 24-hour Mathematical Modeling Challenge, an extracurricular event that exposes…

Systematic Co-Operation between Theory and Practice in Mathematics Education. Mini-Conference at ICME 5. Topic Area Research and Teaching (Adelaide, Australia, August 25-29, 1984).

ERIC Educational Resources Information Center

Christiansen, Bent; And Others

A miniconference (consisting of four 60-minute sessions) was organized to contribute to the exploration of frames, forms, and contents of systematic cooperation and interaction between the researcher and teacher in the classroom. These proceedings of the conference include descriptions of the organization, purpose, and background of the…

Estimation of population mean under systematic sampling

NASA Astrophysics Data System (ADS)

Noor-ul-amin, Muhammad; Javaid, Amjad

2017-11-01

In this study we propose a generalized ratio estimator under non-response for systematic random sampling. We also generate a class of estimators through special cases of generalized estimator using different combinations of coefficients of correlation, kurtosis and variation. The mean square errors and mathematical conditions are also derived to prove the efficiency of proposed estimators. Numerical illustration is included using three populations to support the results.

An Integrative Approach to Computational Modelling of the Gene Regulatory Network Controlling Clostridium botulinum Type A1 Toxin Production.

PubMed

Ihekwaba, Adaoha E C; Mura, Ivan; Walshaw, John; Peck, Michael W; Barker, Gary C

2016-11-01

Clostridium botulinum produces botulinum neurotoxins (BoNTs), highly potent substances responsible for botulism. Currently, mathematical models of C. botulinum growth and toxigenesis are largely aimed at risk assessment and do not include explicit genetic information beyond group level but integrate many component processes, such as signalling, membrane permeability and metabolic activity. In this paper we present a scheme for modelling neurotoxin production in C. botulinum Group I type A1, based on the integration of diverse information coming from experimental results available in the literature. Experiments show that production of BoNTs depends on the growth-phase and is under the control of positive and negative regulatory elements at the intracellular level. Toxins are released as large protein complexes and are associated with non-toxic components. Here, we systematically review and integrate those regulatory elements previously described in the literature for C. botulinum Group I type A1 into a population dynamics model, to build the very first computational model of toxin production at the molecular level. We conduct a validation of our model against several items of published experimental data for different wild type and mutant strains of C. botulinum Group I type A1. The result of this process underscores the potential of mathematical modelling at the cellular level, as a means of creating opportunities in developing new strategies that could be used to prevent botulism; and potentially contribute to improved methods for the production of toxin that is used for therapeutics.

Can reliable values of Young's modulus be deduced from Fisher's (1971) spinning lens measurements?

PubMed

Burd, H J; Wilde, G S; Judge, S J

2006-04-01

The current textbook view of the causes of presbyopia rests very largely on a series of experiments reported by R.F. Fisher some three decades ago, and in particular on the values of lens Young's modulus inferred from the deformation caused by spinning excised lenses about their optical axis (Fisher 1971) We studied the extent to which inferred values of Young's modulus are influenced by assumptions inherent in the mathematical procedures used by Fisher to interpret the test and we investigated several alternative interpretation methods. The results suggest that modelling assumptions inherent in Fisher's original method may have led to systematic errors in the determination of the Young's modulus of the cortex and nucleus. Fisher's conclusion that the cortex is stiffer than the nucleus, particularly in middle age, may be an artefact associated with these systematic errors. Moreover, none of the models we explored are able to account for Fisher's claim that the removal of the capsule has only a modest effect on the deformations induced in the spinning lens.

Extending the Human Papillomavirus Vaccination Programme to Include Males in High-Income Countries: A Systematic Review of the Cost-Effectiveness Studies.

PubMed

Ben Hadj Yahia, Mohamed-Béchir; Jouin-Bortolotti, Anaïs; Dervaux, Benoît

2015-08-01

Giving the human papillomavirus (HPV) vaccination to females has been shown to be cost-effective in most countries. The epidemiological evidence and economic burden of HPV-related diseases have gradually been shown to be gender neutral. Randomized clinical trials report high efficacy, immunogenicity and safety of the HPV vaccine in males aged 16-26 years. Some pioneering countries extended their HPV vaccination programme to include males, regardless of the cost-effectiveness analysis results. Nevertheless, decision makers need evidence provided by modelling and economic studies to justify the funding of mass vaccination. This systematic review aims to assess the cost-effectiveness of extending the HPV vaccination programme to include males living in high-income countries. A systematic review of the cost-effectiveness analyses of HPV vaccination in males was performed. Data were extracted and analysed using a checklist adapted from the Consolidated Health Economic Evaluation Reporting Standards Statement. Seventeen studies and 12 underlying mathematical models were identified. Model filiation showed evolution in time from aggregate models (static and dynamic) to individual-based models. When considering the health outcomes HPV vaccines are licensed for, regardless of modelling approaches and assumptions, extending vaccinations to males is rarely found to be cost-effective in heterosexual populations. Cost-effectiveness ratios become more attractive when all HPV-related diseases are considered and when vaccine coverage in females is below 40%. Targeted vaccination of men who have sex with men (MSM) seems to be the best cost-effectiveness option. The feasibility of this strategy is still an open question, since early identification of this specific population remains difficult.

The Relationship between Students' Performance on Conventional Standardized Mathematics Assessments and Complex Mathematical Modeling Problems

ERIC Educational Resources Information Center

Kartal, Ozgul; Dunya, Beyza Aksu; Diefes-Dux, Heidi A.; Zawojewski, Judith S.

2016-01-01

Critical to many science, technology, engineering, and mathematics (STEM) career paths is mathematical modeling--specifically, the creation and adaptation of mathematical models to solve problems in complex settings. Conventional standardized measures of mathematics achievement are not structured to directly assess this type of mathematical…

Annual Perspectives in Mathematics Education 2016: Mathematical Modeling and Modeling Mathematics

ERIC Educational Resources Information Center

Hirsch, Christian R., Ed.; McDuffie, Amy Roth, Ed.

2016-01-01

Mathematical modeling plays an increasingly important role both in real-life applications--in engineering, business, the social sciences, climate study, advanced design, and more--and within mathematics education itself. This 2016 volume of "Annual Perspectives in Mathematics Education" ("APME") focuses on this key topic from a…

Numerical implementation of the S-matrix algorithm for modeling of relief diffraction gratings

NASA Astrophysics Data System (ADS)

Yaremchuk, Iryna; Tamulevičius, Tomas; Fitio, Volodymyr; Gražulevičiūte, Ieva; Bobitski, Yaroslav; Tamulevičius, Sigitas

2013-11-01

A new numerical implementation is developed to calculate the diffraction efficiency of relief diffraction gratings. In the new formulation, vectors containing the expansion coefficients of electric and magnetic fields on boundaries of the grating layer are expressed by additional constants. An S-matrix algorithm has been systematically described in detail and adapted to a simple matrix form. This implementation is suitable for the study of optical characteristics of periodic structures by using modern object-oriented programming languages and different standard mathematical software. The modeling program has been developed on the basis of this numerical implementation and tested by comparison with other commercially available programs and experimental data. Numerical examples are given to show the usefulness of the new implementation.

Lights All Askew: Systematics in Galaxy Images from Megaparsecs to Microns

NASA Astrophysics Data System (ADS)

Bradshaw, Andrew Kenneth

The stars and galaxies are not where they seem. In the process of imaging and measurement, the light from distant objects is distorted, blurred, and skewed by several physical effects on scales from megaparsecs to microns. Charge-coupled devices (CCDs) provide sensitive detection of this light, but introduce their own problems in the form of systematic biases. Images of these stars and galaxies are formed in CCDs when incoming light generates photoelectrons which are then collected in a pixel's potential well and measured as signal. However, these signal electrons can be diverted from purely parallel paths toward the pixel wells by transverse fields sourced by structural elements of the CCD, accidental imperfections in fabrication, or dynamic electric fields induced by other collected charges. These charge transport anomalies lead to measurable systematic errors in the images which bias cosmological inferences based on them. The physics of imaging therefore deserves thorough investigation, which is performed in the laboratory using a unique optical beam simulator and in computer simulations of charge transport. On top of detector systematics, there are often biases in the mathematical analysis of pixelized images; in particular, the location, shape, and orientation of stars and galaxies. Using elliptical Gaussians as a toy model for galaxies, it is demonstrated how small biases in the computed image moments lead to observable orientation patterns in modern survey data. Also presented are examples of the reduction of data and fitting of optical aberrations of images in the lab and on the sky which are modeled by physically or mathematically-motivated methods. Finally, end-to-end analysis of the weak gravitational lensing signal is presented using deep sky data as well as in N-body simulations. It is demonstrated how measured weak lens shear can be transformed by signal matched filters which aid in the detection of mass overdensities and separate signal from noise. A commonly-used decomposition of shear into two components, E- and B-modes, is thoroughly tested and both modes are shown to be useful in the detection of large scale structure. We find several astrophysical sources of B-mode and explain their apparent origin. The methods presented therefore offer an optimal way to filter weak gravitational shear into maps of large scale structure through the process of cosmic mass cartography.

Mathematical Modeling: A Bridge to STEM Education

ERIC Educational Resources Information Center

Kertil, Mahmut; Gurel, Cem

2016-01-01

The purpose of this study is making a theoretical discussion on the relationship between mathematical modeling and integrated STEM education. First of all, STEM education perspective and the construct of mathematical modeling in mathematics education is introduced. A review of literature is provided on how mathematical modeling literature may…

The influence of mathematics learning using SAVI approach on junior high school students’ mathematical modelling ability

NASA Astrophysics Data System (ADS)

Khusna, H.; Heryaningsih, N. Y.

2018-01-01

The aim of this research was to examine mathematical modeling ability who learn mathematics by using SAVI approach. This research was a quasi-experimental research with non-equivalent control group designed by using purposive sampling technique. The population of this research was the state junior high school students in Lembang while the sample consisted of two class at 8th grade. The instrument used in this research was mathematical modeling ability. Data analysis of this research was conducted by using SPSS 20 by Windows. The result showed that students’ ability of mathematical modeling who learn mathematics by using SAVI approach was better than students’ ability of mathematical modeling who learn mathematics using conventional learning.

Event- and Time-Driven Techniques Using Parallel CPU-GPU Co-processing for Spiking Neural Networks

PubMed Central

Naveros, Francisco; Garrido, Jesus A.; Carrillo, Richard R.; Ros, Eduardo; Luque, Niceto R.

2017-01-01

Modeling and simulating the neural structures which make up our central neural system is instrumental for deciphering the computational neural cues beneath. Higher levels of biological plausibility usually impose higher levels of complexity in mathematical modeling, from neural to behavioral levels. This paper focuses on overcoming the simulation problems (accuracy and performance) derived from using higher levels of mathematical complexity at a neural level. This study proposes different techniques for simulating neural models that hold incremental levels of mathematical complexity: leaky integrate-and-fire (LIF), adaptive exponential integrate-and-fire (AdEx), and Hodgkin-Huxley (HH) neural models (ranged from low to high neural complexity). The studied techniques are classified into two main families depending on how the neural-model dynamic evaluation is computed: the event-driven or the time-driven families. Whilst event-driven techniques pre-compile and store the neural dynamics within look-up tables, time-driven techniques compute the neural dynamics iteratively during the simulation time. We propose two modifications for the event-driven family: a look-up table recombination to better cope with the incremental neural complexity together with a better handling of the synchronous input activity. Regarding the time-driven family, we propose a modification in computing the neural dynamics: the bi-fixed-step integration method. This method automatically adjusts the simulation step size to better cope with the stiffness of the neural model dynamics running in CPU platforms. One version of this method is also implemented for hybrid CPU-GPU platforms. Finally, we analyze how the performance and accuracy of these modifications evolve with increasing levels of neural complexity. We also demonstrate how the proposed modifications which constitute the main contribution of this study systematically outperform the traditional event- and time-driven techniques under increasing levels of neural complexity. PMID:28223930

Beyond Motivation: Exploring Mathematical Modeling as a Context for Deepening Students' Understandings of Curricular Mathematics

ERIC Educational Resources Information Center

Zbiek, Rose Mary; Conner, Annamarie

2006-01-01

Views of mathematical modeling in empirical, expository, and curricular references typically capture a relationship between real-world phenomena and mathematical ideas from the perspective that competence in mathematical modeling is a clear goal of the mathematics curriculum. However, we work within a curricular context in which mathematical…

An Investigation of Mathematical Modeling with Pre-Service Secondary Mathematics Teachers

ERIC Educational Resources Information Center

Thrasher, Emily Plunkett

2016-01-01

The goal of this thesis was to investigate and enhance our understanding of what occurs while pre-service mathematics teachers engage in a mathematical modeling unit that is broadly based upon mathematical modeling as defined by the Common Core State Standards for Mathematics (National Governors Association Center for Best Practices & Council…

A systematic composite service design modeling method using graph-based theory.

PubMed

Elhag, Arafat Abdulgader Mohammed; Mohamad, Radziah; Aziz, Muhammad Waqar; Zeshan, Furkh

2015-01-01

The composite service design modeling is an essential process of the service-oriented software development life cycle, where the candidate services, composite services, operations and their dependencies are required to be identified and specified before their design. However, a systematic service-oriented design modeling method for composite services is still in its infancy as most of the existing approaches provide the modeling of atomic services only. For these reasons, a new method (ComSDM) is proposed in this work for modeling the concept of service-oriented design to increase the reusability and decrease the complexity of system while keeping the service composition considerations in mind. Furthermore, the ComSDM method provides the mathematical representation of the components of service-oriented design using the graph-based theoryto facilitate the design quality measurement. To demonstrate that the ComSDM method is also suitable for composite service design modeling of distributed embedded real-time systems along with enterprise software development, it is implemented in the case study of a smart home. The results of the case study not only check the applicability of ComSDM, but can also be used to validate the complexity and reusability of ComSDM. This also guides the future research towards the design quality measurement such as using the ComSDM method to measure the quality of composite service design in service-oriented software system.

A Systematic Composite Service Design Modeling Method Using Graph-Based Theory

PubMed Central

Elhag, Arafat Abdulgader Mohammed; Mohamad, Radziah; Aziz, Muhammad Waqar; Zeshan, Furkh

2015-01-01

The composite service design modeling is an essential process of the service-oriented software development life cycle, where the candidate services, composite services, operations and their dependencies are required to be identified and specified before their design. However, a systematic service-oriented design modeling method for composite services is still in its infancy as most of the existing approaches provide the modeling of atomic services only. For these reasons, a new method (ComSDM) is proposed in this work for modeling the concept of service-oriented design to increase the reusability and decrease the complexity of system while keeping the service composition considerations in mind. Furthermore, the ComSDM method provides the mathematical representation of the components of service-oriented design using the graph-based theoryto facilitate the design quality measurement. To demonstrate that the ComSDM method is also suitable for composite service design modeling of distributed embedded real-time systems along with enterprise software development, it is implemented in the case study of a smart home. The results of the case study not only check the applicability of ComSDM, but can also be used to validate the complexity and reusability of ComSDM. This also guides the future research towards the design quality measurement such as using the ComSDM method to measure the quality of composite service design in service-oriented software system. PMID:25928358

A Survey of Methods for Computing Best Estimates of Endoatmospheric and Exoatmospheric Trajectories

NASA Technical Reports Server (NTRS)

Bernard, William P.

2018-01-01

Beginning with the mathematical prediction of planetary orbits in the early seventeenth century up through the most recent developments in sensor fusion methods, many techniques have emerged that can be employed on the problem of endo and exoatmospheric trajectory estimation. Although early methods were ad hoc, the twentieth century saw the emergence of many systematic approaches to estimation theory that produced a wealth of useful techniques. The broad genesis of estimation theory has resulted in an equally broad array of mathematical principles, methods and vocabulary. Among the fundamental ideas and methods that are briefly touched on are batch and sequential processing, smoothing, estimation, and prediction, sensor fusion, sensor fusion architectures, data association, Bayesian and non Bayesian filtering, the family of Kalman filters, models of the dynamics of the phases of a rocket's flight, and asynchronous, delayed, and asequent data. Along the way, a few trajectory estimation issues are addressed and much of the vocabulary is defined.

Reflective Modeling in Teacher Education.

ERIC Educational Resources Information Center

Shealy, Barry E.

This paper describes mathematical modeling activities from a secondary mathematics teacher education course taken by fourth-year university students. Experiences with mathematical modeling are viewed as important in helping teachers develop a more intuitive understanding of mathematics, generate and evaluate mathematical interpretations, and…

National Advisory Groups and their role in immunization policy-making processes in European countries.

PubMed

Nohynek, H; Wichmann, O; D Ancona, F

2013-12-01

During the twenty-first century, the development of national immunization programmes (NIP) has matured into robust processes where evidence-based methodologies and frameworks have increasingly been adopted. A key role in the decision-making and recommending processes is played by National Immunization Technical Advisory Groups (NITAGs). In a survey performed among European Union member states, Norway and Iceland, in February 2013, 85% of the 27 responding countries reported having established a NITAG, and of these, 45% have formal frameworks in place for the systematic development of vaccination recommendations. Independent of whether a formal framework is in place, common key factors are addressed by all NITAGs and also in countries without NITAGs. The four main factors addressed by all were: disease burden in the country, severity of the disease, vaccine effectiveness or efficacy, and vaccine safety at population level. Mathematical modelling and cost-effectiveness analyses are still not common tools. Differences in the relative weighting of these key factors, differences in data or assumptions on country-specific key factors, and differences in existing vaccination systems and financing, are likely to be reasons for differences in NITAG recommendations, and eventually NIPs, across Europe. Even if harmonization of NIPs is presently not a reasonable aim, systematic reviews and the development of mathematical/economic models could be performed at supranational level, thus sharing resources and easing the present work-load of NITAGs. Nevertheless, it has been argued that harmonization would ease central purchase of vaccines, thus reducing the price and increasing access to new vaccines. © 2013 The Authors Clinical Microbiology and Infection © 2013 European Society of Clinical Microbiology and Infectious Diseases.

Primary School Pre-Service Mathematics Teachers' Views on Mathematical Modeling

ERIC Educational Resources Information Center

Karali, Diren; Durmus, Soner

2015-01-01

The current study aimed to identify the views of pre-service teachers, who attended a primary school mathematics teaching department but did not take mathematical modeling courses. The mathematical modeling activity used by the pre-service teachers was developed with regards to the modeling activities utilized by Lesh and Doerr (2003) in their…

Application of recursive Gibbs-Appell formulation in deriving the equations of motion of N-viscoelastic robotic manipulators in 3D space using Timoshenko Beam Theory

NASA Astrophysics Data System (ADS)

Korayem, M. H.; Shafei, A. M.

2013-02-01

The goal of this paper is to describe the application of Gibbs-Appell (G-A) formulation and the assumed modes method to the mathematical modeling of N-viscoelastic link manipulators. The paper's focus is on obtaining accurate and complete equations of motion which encompass the most related structural properties of lightweight elastic manipulators. In this study, two important damping mechanisms, namely, the structural viscoelasticity (Kelvin-Voigt) effect (as internal damping) and the viscous air effect (as external damping) have been considered. To include the effects of shear and rotational inertia, the assumption of Timoshenko beam (TB) theory (TBT) has been applied. Gravity, torsion, and longitudinal elongation effects have also been included in the formulations. To systematically derive the equations of motion and improve the computational efficiency, a recursive algorithm has been used in the modeling of the system. In this algorithm, all the mathematical operations are carried out by only 3×3 and 3×1 matrices. Finally, a computational simulation for a manipulator with two elastic links is performed in order to verify the proposed method.

On the Nature and Role of Peer Review in Mathematics.

PubMed

Andersen, Line Edslev

2017-01-01

For the past three decades, peer review practices have received much attention in the literature. But although this literature covers many research fields, only one previous systematic study has been devoted to the practice of peer review in mathematics, namely a study by Geist, Löwe, and Van Kerkhove from 2010. This lack of attention may be due to a view that peer review in mathematics is more reliable, and therefore less interesting as an object of study, than peer review in other fields. In fact, Geist, Löwe, and Van Kerkhove argue that peer review in mathematics is relatively reliable. At the same time, peer review in mathematics differs from peer review in most, if not all, other fields in that papers submitted to mathematical journals are usually only reviewed by a single referee. Furthermore, recent empirical studies indicate that the referees do not check the papers line by line. I argue that, in spite of this, mathematical practice in general and refereeing practices in particular are such that the common practice of mathematical journals of using just one referee is justified from the point of view of proof validity assessment. The argument is based on interviews I conducted with seven mathematicians.

Multi-objective optimization for evaluation of simulation fidelity for precipitation, cloudiness and insolation in regional climate models

NASA Astrophysics Data System (ADS)

Lee, H.

2016-12-01

Precipitation is one of the most important climate variables that are taken into account in studying regional climate. Nevertheless, how precipitation will respond to a changing climate and even its mean state in the current climate are not well represented in regional climate models (RCMs). Hence, comprehensive and mathematically rigorous methodologies to evaluate precipitation and related variables in multiple RCMs are required. The main objective of the current study is to evaluate the joint variability of climate variables related to model performance in simulating precipitation and condense multiple evaluation metrics into a single summary score. We use multi-objective optimization, a mathematical process that provides a set of optimal tradeoff solutions based on a range of evaluation metrics, to characterize the joint representation of precipitation, cloudiness and insolation in RCMs participating in the North American Regional Climate Change Assessment Program (NARCCAP) and Coordinated Regional Climate Downscaling Experiment-North America (CORDEX-NA). We also leverage ground observations, NASA satellite data and the Regional Climate Model Evaluation System (RCMES). Overall, the quantitative comparison of joint probability density functions between the three variables indicates that performance of each model differs markedly between sub-regions and also shows strong seasonal dependence. Because of the large variability across the models, it is important to evaluate models systematically and make future projections using only models showing relatively good performance. Our results indicate that the optimized multi-model ensemble always shows better performance than the arithmetic ensemble mean and may guide reliable future projections.

The implementation of multiple intelligences based teaching model to improve mathematical problem solving ability for student of junior high school

NASA Astrophysics Data System (ADS)

Fasni, Nurli; Fatimah, Siti; Yulanda, Syerli

2017-05-01

This research aims to achieve some purposes such as: to know whether mathematical problem solving ability of students who have learned mathematics using Multiple Intelligences based teaching model is higher than the student who have learned mathematics using cooperative learning; to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using Multiple Intelligences based teaching model., to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using cooperative learning; to know the attitude of the students to Multiple Intelligences based teaching model. The method employed here is quasi-experiment which is controlled by pre-test and post-test. The population of this research is all of VII grade in SMP Negeri 14 Bandung even-term 2013/2014, later on two classes of it were taken for the samples of this research. A class was taught using Multiple Intelligences based teaching model and the other one was taught using cooperative learning. The data of this research were gotten from the test in mathematical problem solving, scale questionnaire of the student attitudes, and observation. The results show the mathematical problem solving of the students who have learned mathematics using Multiple Intelligences based teaching model learning is higher than the student who have learned mathematics using cooperative learning, the mathematical problem solving ability of the student who have learned mathematics using cooperative learning and Multiple Intelligences based teaching model are in intermediate level, and the students showed the positive attitude in learning mathematics using Multiple Intelligences based teaching model. As for the recommendation for next author, Multiple Intelligences based teaching model can be tested on other subject and other ability.

Using Mathematics, Mathematical Applications, Mathematical Modelling, and Mathematical Literacy: A Theoretical Study

ERIC Educational Resources Information Center

Mumcu, Hayal Yavuz

2016-01-01

The purpose of this theoretical study is to explore the relationships between the concepts of using mathematics in the daily life, mathematical applications, mathematical modelling, and mathematical literacy. As these concepts are generally taken as independent concepts in the related literature, they are confused with each other and it becomes…

Pre-Service Teachers' Developing Conceptions about the Nature and Pedagogy of Mathematical Modeling in the Context of a Mathematical Modeling Course

ERIC Educational Resources Information Center

Cetinkaya, Bulent; Kertil, Mahmut; Erbas, Ayhan Kursat; Korkmaz, Himmet; Alacaci, Cengiz; Cakiroglu, Erdinc

2016-01-01

Adopting a multitiered design-based research perspective, this study examines pre-service secondary mathematics teachers' developing conceptions about (a) the nature of mathematical modeling in simulations of "real life" problem solving, and (b) pedagogical principles and strategies needed to teach mathematics through modeling. Unlike…

Evolution of Mathematics Teachers' Pedagogical Knowledge When They Are Teaching through Modeling

ERIC Educational Resources Information Center

Aydogan Yenmez, Arzu; Erbas, Ayhan Kursat; Alacaci, Cengiz; Cakiroglu, Erdinc; Cetinkaya, Bulent

2017-01-01

Use of mathematical modeling in mathematics education has been receiving significant attention as a way to develop students' mathematical knowledge and skills. As effective use of modeling in classes depends on the competencies of teachers we need to know more about the nature of teachers' knowledge to use modeling in mathematics education and how…

Mathematical Modeling in Science: Using Spreadsheets to Create Mathematical Models and Address Scientific Inquiry

ERIC Educational Resources Information Center

Horton, Robert M.; Leonard, William H.

2005-01-01

In science, inquiry is used as students explore important and interesting questions concerning the world around them. In mathematics, one contemporary inquiry approach is to create models that describe real phenomena. Creating mathematical models using spreadsheets can help students learn at deep levels in both science and mathematics, and give…

Mathematical models for predicting human mobility in the context of infectious disease spread: introducing the impedance model.

PubMed

Sallah, Kankoé; Giorgi, Roch; Bengtsson, Linus; Lu, Xin; Wetter, Erik; Adrien, Paul; Rebaudet, Stanislas; Piarroux, Renaud; Gaudart, Jean

2017-11-22

Mathematical models of human mobility have demonstrated a great potential for infectious disease epidemiology in contexts of data scarcity. While the commonly used gravity model involves parameter tuning and is thus difficult to implement without reference data, the more recent radiation model based on population densities is parameter-free, but biased. In this study we introduce the new impedance model, by analogy with electricity. Previous research has compared models on the basis of a few specific available spatial patterns. In this study, we use a systematic simulation-based approach to assess the performances. Five hundred spatial patterns were generated using various area sizes and location coordinates. Model performances were evaluated based on these patterns. For simulated data, comparison measures were average root mean square error (aRMSE) and bias criteria. Modeling of the 2010 Haiti cholera epidemic with a basic susceptible-infected-recovered (SIR) framework allowed an empirical evaluation through assessing the goodness-of-fit of the observed epidemic curve. The new, parameter-free impedance model outperformed previous models on simulated data according to average aRMSE and bias criteria. The impedance model achieved better performances with heterogeneous population densities and small destination populations. As a proof of concept, the basic compartmental SIR framework was used to confirm the results obtained with the impedance model in predicting the spread of cholera in Haiti in 2010. The proposed new impedance model provides accurate estimations of human mobility, especially when the population distribution is highly heterogeneous. This model can therefore help to achieve more accurate predictions of disease spread in the context of an epidemic.

Physical consistency of subgrid-scale models for large-eddy simulation of incompressible turbulent flows

NASA Astrophysics Data System (ADS)

Silvis, Maurits H.; Remmerswaal, Ronald A.; Verstappen, Roel

2017-01-01

We study the construction of subgrid-scale models for large-eddy simulation of incompressible turbulent flows. In particular, we aim to consolidate a systematic approach of constructing subgrid-scale models, based on the idea that it is desirable that subgrid-scale models are consistent with the mathematical and physical properties of the Navier-Stokes equations and the turbulent stresses. To that end, we first discuss in detail the symmetries of the Navier-Stokes equations, and the near-wall scaling behavior, realizability and dissipation properties of the turbulent stresses. We furthermore summarize the requirements that subgrid-scale models have to satisfy in order to preserve these important mathematical and physical properties. In this fashion, a framework of model constraints arises that we apply to analyze the behavior of a number of existing subgrid-scale models that are based on the local velocity gradient. We show that these subgrid-scale models do not satisfy all the desired properties, after which we explain that this is partly due to incompatibilities between model constraints and limitations of velocity-gradient-based subgrid-scale models. However, we also reason that the current framework shows that there is room for improvement in the properties and, hence, the behavior of existing subgrid-scale models. We furthermore show how compatible model constraints can be combined to construct new subgrid-scale models that have desirable properties built into them. We provide a few examples of such new models, of which a new model of eddy viscosity type, that is based on the vortex stretching magnitude, is successfully tested in large-eddy simulations of decaying homogeneous isotropic turbulence and turbulent plane-channel flow.

Effectiveness and cost-effectiveness of traditional and new partner notification technologies for curable sexually transmitted infections: observational study, systematic reviews and mathematical modelling.

PubMed

Althaus, Christian L; Turner, Katherine M E; Mercer, Catherine H; Auguste, Peter; Roberts, Tracy E; Bell, Gill; Herzog, Sereina A; Cassell, Jackie A; Edmunds, W John; White, Peter J; Ward, Helen; Low, Nicola

2014-01-01

Partner notification is essential to the comprehensive case management of sexually transmitted infections. Systematic reviews and mathematical modelling can be used to synthesise information about the effects of new interventions to enhance the outcomes of partner notification. To study the effectiveness and cost-effectiveness of traditional and new partner notification technologies for curable sexually transmitted infections (STIs). Secondary data analysis of clinical audit data; systematic reviews of randomised controlled trials (MEDLINE, EMBASE and Cochrane Central Register of Controlled Trials) published from 1 January 1966 to 31 August 2012 and of studies of health-related quality of life (HRQL) [MEDLINE, EMBASE, ISI Web of Knowledge, NHS Economic Evaluation Database (NHS EED), Database of Abstracts of Reviews of Effects (DARE) and Health Technology Assessment (HTA)] published from 1 January 1980 to 31 December 2011; static models of clinical effectiveness and cost-effectiveness; and dynamic modelling studies to improve parameter estimation and examine effectiveness. General population and genitourinary medicine clinic attenders. Heterosexual women and men. Traditional partner notification by patient or provider referral, and new partner notification by expedited partner therapy (EPT) or its UK equivalent, accelerated partner therapy (APT). Population prevalence; index case reinfection; and partners treated per index case. Enhanced partner therapy reduced reinfection in index cases with curable STIs more than simple patient referral [risk ratio (RR) 0.71; 95% confidence interval (CI) 0.56 to 0.89]. There are no randomised trials of APT. The median number of partners treated for chlamydia per index case in UK clinics was 0.60. The number of partners needed to treat to interrupt transmission of chlamydia was lower for casual than for regular partners. In dynamic model simulations, >10% of partners are chlamydia positive with look-back periods of up to 18 months. In the presence of a chlamydia screening programme that reduces population prevalence, treatment of current partners achieves most of the additional reduction in prevalence attributable to partner notification. Dynamic model simulations show that cotesting and treatment for chlamydia and gonorrhoea reduce the prevalence of both STIs. APT has a limited additional effect on prevalence but reduces the rate of index case reinfection. Published quality-adjusted life-year (QALY) weights were of insufficient quality to be used in a cost-effectiveness study of partner notification in this project. Using an intermediate outcome of cost per infection diagnosed, doubling the efficacy of partner notification from 0.4 to 0.8 partners treated per index case was more cost-effective than increasing chlamydia screening coverage. There is evidence to support the improved clinical effectiveness of EPT in reducing index case reinfection. In a general heterosexual population, partner notification identifies new infected cases but the impact on chlamydia prevalence is limited. Partner notification to notify casual partners might have a greater impact than for regular partners in genitourinary clinic populations. Recommendations for future research are (1) to conduct randomised controlled trials using biological outcomes of the effectiveness of APT and of methods to increase testing for human immunodeficiency virus (HIV) and STIs after APT; (2) collection of HRQL data should be a priority to determine QALYs associated with the sequelae of curable STIs; and (3) standardised parameter sets for curable STIs should be developed for mathematical models of STI transmission that are used for policy-making. The National Institute for Health Research Health Technology Assessment programme.

The natural mathematics of behavior analysis.

PubMed

Li, Don; Hautus, Michael J; Elliffe, Douglas

2018-04-19

Models that generate event records have very general scope regarding the dimensions of the target behavior that we measure. From a set of predicted event records, we can generate predictions for any dependent variable that we could compute from the event records of our subjects. In this sense, models that generate event records permit us a freely multivariate analysis. To explore this proposition, we conducted a multivariate examination of Catania's Operant Reserve on single VI schedules in transition using a Markov Chain Monte Carlo scheme for Approximate Bayesian Computation. Although we found systematic deviations between our implementation of Catania's Operant Reserve and our observed data (e.g., mismatches in the shape of the interresponse time distributions), the general approach that we have demonstrated represents an avenue for modelling behavior that transcends the typical constraints of algebraic models. © 2018 Society for the Experimental Analysis of Behavior.

Mathematical Modeling and Pure Mathematics

ERIC Educational Resources Information Center

Usiskin, Zalman

2015-01-01

Common situations, like planning air travel, can become grist for mathematical modeling and can promote the mathematical ideas of variables, formulas, algebraic expressions, functions, and statistics. The purpose of this article is to illustrate how the mathematical modeling that is present in everyday situations can be naturally embedded in…

Understanding Prospective Teachers' Mathematical Modeling Processes in the Context of a Mathematical Modeling Course

ERIC Educational Resources Information Center

Zeytun, Aysel Sen; Cetinkaya, Bulent; Erbas, Ayhan Kursat

2017-01-01

This paper investigates how prospective teachers develop mathematical models while they engage in modeling tasks. The study was conducted in an undergraduate elective course aiming to improve prospective teachers' mathematical modeling abilities, while enhancing their pedagogical knowledge for the integrating of modeling tasks into their future…

Introducing Modeling Transition Diagrams as a Tool to Connect Mathematical Modeling to Mathematical Thinking

ERIC Educational Resources Information Center

Czocher, Jennifer A.

2016-01-01

This study contributes a methodological tool to reconstruct the cognitive processes and mathematical activities carried out by mathematical modelers. Represented as Modeling Transition Diagrams (MTDs), individual modeling routes were constructed for four engineering undergraduate students. Findings stress the importance and limitations of using…

An Experimental Approach to Mathematical Modeling in Biology

ERIC Educational Resources Information Center

Ledder, Glenn

2008-01-01

The simplest age-structured population models update a population vector via multiplication by a matrix. These linear models offer an opportunity to introduce mathematical modeling to students of limited mathematical sophistication and background. We begin with a detailed discussion of mathematical modeling, particularly in a biological context.…

Mathematical Modeling with Middle School Students: The Robot Art Model-Eliciting Activity

ERIC Educational Resources Information Center

Stohlmann, Micah S.

2017-01-01

Internationally mathematical modeling is garnering more attention for the benefits associated with it. Mathematical modeling can develop students' communication skills and the ability to demonstrate understanding through different representations. With the increased attention on mathematical modeling, there is a need for more curricula to be…

Changing Pre-Service Mathematics Teachers' Beliefs about Using Computers for Teaching and Learning Mathematics: The Effect of Three Different Models

ERIC Educational Resources Information Center

Karatas, Ilhan

2014-01-01

This study examines the effect of three different computer integration models on pre-service mathematics teachers' beliefs about using computers in mathematics education. Participants included 104 pre-service mathematics teachers (36 second-year students in the Computer Oriented Model group, 35 fourth-year students in the Integrated Model (IM)…

A critical comparison of systematic calibration protocols for activated sludge models: a SWOT analysis.

PubMed

Sin, Gürkan; Van Hulle, Stijn W H; De Pauw, Dirk J W; van Griensven, Ann; Vanrolleghem, Peter A

2005-07-01

Modelling activated sludge systems has gained an increasing momentum after the introduction of activated sludge models (ASMs) in 1987. Application of dynamic models for full-scale systems requires essentially a calibration of the chosen ASM to the case under study. Numerous full-scale model applications have been performed so far which were mostly based on ad hoc approaches and expert knowledge. Further, each modelling study has followed a different calibration approach: e.g. different influent wastewater characterization methods, different kinetic parameter estimation methods, different selection of parameters to be calibrated, different priorities within the calibration steps, etc. In short, there was no standard approach in performing the calibration study, which makes it difficult, if not impossible, to (1) compare different calibrations of ASMs with each other and (2) perform internal quality checks for each calibration study. To address these concerns, systematic calibration protocols have recently been proposed to bring guidance to the modeling of activated sludge systems and in particular to the calibration of full-scale models. In this contribution four existing calibration approaches (BIOMATH, HSG, STOWA and WERF) will be critically discussed using a SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis. It will also be assessed in what way these approaches can be further developed in view of further improving the quality of ASM calibration. In this respect, the potential of automating some steps of the calibration procedure by use of mathematical algorithms is highlighted.

Mathematical Modeling: A Structured Process

ERIC Educational Resources Information Center

Anhalt, Cynthia Oropesa; Cortez, Ricardo

2015-01-01

Mathematical modeling, in which students use mathematics to explain or interpret physical, social, or scientific phenomena, is an essential component of the high school curriculum. The Common Core State Standards for Mathematics (CCSSM) classify modeling as a K-12 standard for mathematical practice and as a conceptual category for high school…

Mathematical Models of Elementary Mathematics Learning and Performance. Final Report.

ERIC Educational Resources Information Center

Suppes, Patrick

This project was concerned with the development of mathematical models of elementary mathematics learning and performance. Probabilistic finite automata and register machines with a finite number of registers were developed as models and extensively tested with data arising from the elementary-mathematics strand curriculum developed by the…

To Assess Students' Attitudes, Skills and Competencies in Mathematical Modeling

ERIC Educational Resources Information Center

Lingefjard, Thomas; Holmquist, Mikael

2005-01-01

Peer-to-peer assessment, take-home exams and a mathematical modeling survey were used to monitor and assess students' attitudes, skills and competencies in mathematical modeling. The students were all in a secondary mathematics, teacher education program with a comprehensive amount of mathematics studies behind them. Findings indicate that…

Mathematical Modeling in the Undergraduate Curriculum

ERIC Educational Resources Information Center

Toews, Carl

2012-01-01

Mathematical modeling occupies an unusual space in the undergraduate mathematics curriculum: typically an "advanced" course, it nonetheless has little to do with formal proof, the usual hallmark of advanced mathematics. Mathematics departments are thus forced to decide what role they want the modeling course to play, both as a component of the…

Teachers' Conceptions of Mathematical Modeling

ERIC Educational Resources Information Center

Gould, Heather

2013-01-01

The release of the "Common Core State Standards for Mathematics" in 2010 resulted in a new focus on mathematical modeling in United States curricula. Mathematical modeling represents a way of doing and understanding mathematics new to most teachers. The purpose of this study was to determine the conceptions and misconceptions held by…

Experimentation of cooperative learning model Numbered Heads Together (NHT) type by concept maps and Teams Games Tournament (TGT) by concept maps in terms of students logical mathematics intellegences

NASA Astrophysics Data System (ADS)

Irawan, Adi; Mardiyana; Retno Sari Saputro, Dewi

2017-06-01

This research is aimed to find out the effect of learning model towards learning achievement in terms of students’ logical mathematics intelligences. The learning models that were compared were NHT by Concept Maps, TGT by Concept Maps, and Direct Learning model. This research was pseudo experimental by factorial design 3×3. The population of this research was all of the students of class XI Natural Sciences of Senior High School in all regency of Karanganyar in academic year 2016/2017. The conclusions of this research were: 1) the students’ achievements with NHT learning model by Concept Maps were better than students’ achievements with TGT model by Concept Maps and Direct Learning model. The students’ achievements with TGT model by Concept Maps were better than the students’ achievements with Direct Learning model. 2) The students’ achievements that exposed high logical mathematics intelligences were better than students’ medium and low logical mathematics intelligences. The students’ achievements that exposed medium logical mathematics intelligences were better than the students’ low logical mathematics intelligences. 3) Each of student logical mathematics intelligences with NHT learning model by Concept Maps has better achievement than students with TGT learning model by Concept Maps, students with NHT learning model by Concept Maps have better achievement than students with the direct learning model, and the students with TGT by Concept Maps learning model have better achievement than students with Direct Learning model. 4) Each of learning model, students who have logical mathematics intelligences have better achievement then students who have medium logical mathematics intelligences, and students who have medium logical mathematics intelligences have better achievement than students who have low logical mathematics intelligences.

Pre-Service Teachers' Modelling Processes through Engagement with Model Eliciting Activities with a Technological Tool

ERIC Educational Resources Information Center

Daher, Wajeeh M.; Shahbari, Juhaina Awawdeh

2015-01-01

Engaging mathematics students with modelling activities helps them learn mathematics meaningfully. This engagement, in the case of model eliciting activities, helps the students elicit mathematical models by interpreting real-world situation in mathematical ways. This is especially true when the students utilize technology to build the models.…

Spiral-wave dynamics in a mathematical model of human ventricular tissue with myocytes and fibroblasts.

PubMed

Nayak, Alok Ranjan; Shajahan, T K; Panfilov, A V; Pandit, Rahul

2013-01-01

Cardiac fibroblasts, when coupled functionally with myocytes, can modulate the electrophysiological properties of cardiac tissue. We present systematic numerical studies of such modulation of electrophysiological properties in mathematical models for (a) single myocyte-fibroblast (MF) units and (b) two-dimensional (2D) arrays of such units; our models build on earlier ones and allow for zero-, one-, and two-sided MF couplings. Our studies of MF units elucidate the dependence of the action-potential (AP) morphology on parameters such as [Formula: see text], the fibroblast resting-membrane potential, the fibroblast conductance [Formula: see text], and the MF gap-junctional coupling [Formula: see text]. Furthermore, we find that our MF composite can show autorhythmic and oscillatory behaviors in addition to an excitable response. Our 2D studies use (a) both homogeneous and inhomogeneous distributions of fibroblasts, (b) various ranges for parameters such as [Formula: see text], and [Formula: see text], and (c) intercellular couplings that can be zero-sided, one-sided, and two-sided connections of fibroblasts with myocytes. We show, in particular, that the plane-wave conduction velocity [Formula: see text] decreases as a function of [Formula: see text], for zero-sided and one-sided couplings; however, for two-sided coupling, [Formula: see text] decreases initially and then increases as a function of [Formula: see text], and, eventually, we observe that conduction failure occurs for low values of [Formula: see text]. In our homogeneous studies, we find that the rotation speed and stability of a spiral wave can be controlled either by controlling [Formula: see text] or [Formula: see text]. Our studies with fibroblast inhomogeneities show that a spiral wave can get anchored to a local fibroblast inhomogeneity. We also study the efficacy of a low-amplitude control scheme, which has been suggested for the control of spiral-wave turbulence in mathematical models for cardiac tissue, in our MF model both with and without heterogeneities.

Correction of dichroic mirror-induced PSF distortion in STED microscopy

NASA Astrophysics Data System (ADS)

Li, Yanghui; Zhou, Hui; Liu, Xiaoyu; Xia, Chengliang; Wang, Le

2018-07-01

Due to its spectral transmission/reflection properties, dichroic mirror (DM) is widely applied in nearly all microscopes to separate and combine beams with diverse wavelengths. However, its potential distortion effects to the point-spread function (PSF) have been ignored to a large extent. Here, we built a mathematical model to quantify these effects. Specifically, we focus on STED microscopy, whose performance is extremely sensitive to the systematic deficiencies. Both excitation and depletion beams are analysed, and the peak intensity and the shape of the effective PSF are calculated accordingly. More importantly, the strategy to compensate the DM-induced PSF distortion is also given in this paper.

The Application of LT-Table in TRIZ Contradiction Resolving Process

NASA Astrophysics Data System (ADS)

Wei, Zihui; Li, Qinghai; Wang, Donglin; Tian, Yumei

TRIZ is used to resolve invention problems. ARIZ is the most powerful systematic method which integrates all of TRIZ heuristics. Definition of ideal final result (IFR), identification of contradictions and resource utilization are main lines of ARIZ. But resource searching of ARIZ has fault of blindness. Alexandr sets up mathematical model of transformation of the hereditary information in an invention problem using the theory of catastrophes, and provides method of resource searching using LT-table. The application of LT-table on contradiction resolving is introduced. Resource utilization using LT-table is joined into ARIZ step as an addition of TRIZ, apply this method in separator paper punching machine design.

Mathematical modeling in realistic mathematics education

NASA Astrophysics Data System (ADS)

Riyanto, B.; Zulkardi; Putri, R. I. I.; Darmawijoyo

2017-12-01

The purpose of this paper is to produce Mathematical modelling in Realistics Mathematics Education of Junior High School. This study used development research consisting of 3 stages, namely analysis, design and evaluation. The success criteria of this study were obtained in the form of local instruction theory for school mathematical modelling learning which was valid and practical for students. The data were analyzed using descriptive analysis method as follows: (1) walk through, analysis based on the expert comments in the expert review to get Hypothetical Learning Trajectory for valid mathematical modelling learning; (2) analyzing the results of the review in one to one and small group to gain practicality. Based on the expert validation and students’ opinion and answers, the obtained mathematical modeling problem in Realistics Mathematics Education was valid and practical.

Mathematical Problem Solving Ability of Junior High School Students through Ang’s Framework for Mathematical Modelling Instruction

NASA Astrophysics Data System (ADS)

Fasni, N.; Turmudi, T.; Kusnandi, K.

2017-09-01

This research background of this research is the importance of student problem solving abilities. The purpose of this study is to find out whether there are differences in the ability to solve mathematical problems between students who have learned mathematics using Ang’s Framework for Mathematical Modelling Instruction (AFFMMI) and students who have learned using scientific approach (SA). The method used in this research is a quasi-experimental method with pretest-postest control group design. Data analysis of mathematical problem solving ability using Indepent Sample Test. The results showed that there was a difference in the ability to solve mathematical problems between students who received learning with Ang’s Framework for Mathematical Modelling Instruction and students who received learning with a scientific approach. AFFMMI focuses on mathematical modeling. This modeling allows students to solve problems. The use of AFFMMI is able to improve the solving ability.

The Effect of Teacher Beliefs on Student Competence in Mathematical Modeling--An Intervention Study

ERIC Educational Resources Information Center

Mischo, Christoph; Maaß, Katja

2013-01-01

This paper presents an intervention study whose aim was to promote teacher beliefs about mathematics and learning mathematics and student competences in mathematical modeling. In the intervention, teachers received written curriculum materials about mathematical modeling. The concept underlying the materials was based on constructivist ideas and…

Leaning on Mathematical Habits of Mind

ERIC Educational Resources Information Center

Sword, Sarah; Matsuura, Ryota; Cuoco, Al; Kang, Jane; Gates, Miriam

2018-01-01

Mathematical modeling has taken on increasing curricular importance in the past decade due in no small measure to the Common Core State Standards in Mathematics (CCSSM) identifying modeling as one of the Standards for Mathematical Practice (SMP 4, CCSSI 2010, p. 7). Although researchers have worked on mathematical modeling (Lesh and Doerr 2003;…

V/STOL tilt rotor study. Volume 5: A mathematical model for real time flight simulation of the Bell model 301 tilt rotor research aircraft

NASA Technical Reports Server (NTRS)

Harendra, P. B.; Joglekar, M. J.; Gaffey, T. M.; Marr, R. L.

1973-01-01

A mathematical model for real-time flight simulation of a tilt rotor research aircraft was developed. The mathematical model was used to support the aircraft design, pilot training, and proof-of-concept aspects of the development program. The structure of the mathematical model is indicated by a block diagram. The mathematical model differs from that for a conventional fixed wing aircraft principally in the added requirement to represent the dynamics and aerodynamics of the rotors, the interaction of the rotor wake with the airframe, and the rotor control and drive systems. The constraints imposed on the mathematical model are defined.

Equation-free analysis of agent-based models and systematic parameter determination

NASA Astrophysics Data System (ADS)

Thomas, Spencer A.; Lloyd, David J. B.; Skeldon, Anne C.

2016-12-01

Agent based models (ABM)s are increasingly used in social science, economics, mathematics, biology and computer science to describe time dependent systems in circumstances where a description in terms of equations is difficult. Yet few tools are currently available for the systematic analysis of ABM behaviour. Numerical continuation and bifurcation analysis is a well-established tool for the study of deterministic systems. Recently, equation-free (EF) methods have been developed to extend numerical continuation techniques to systems where the dynamics are described at a microscopic scale and continuation of a macroscopic property of the system is considered. To date, the practical use of EF methods has been limited by; (1) the over-head of application-specific implementation; (2) the laborious configuration of problem-specific parameters; and (3) large ensemble sizes (potentially) leading to computationally restrictive run-times. In this paper we address these issues with our tool for the EF continuation of stochastic systems, which includes algorithms to systematically configuration problem specific parameters and enhance robustness to noise. Our tool is generic and can be applied to any 'black-box' simulator and determines the essential EF parameters prior to EF analysis. Robustness is significantly improved using our convergence-constraint with a corrector-repeat (C3R) method. This algorithm automatically detects outliers based on the dynamics of the underlying system enabling both an order of magnitude reduction in ensemble size and continuation of systems at much higher levels of noise than classical approaches. We demonstrate our method with application to several ABM models, revealing parameter dependence, bifurcation and stability analysis of these complex systems giving a deep understanding of the dynamical behaviour of the models in a way that is not otherwise easily obtainable. In each case we demonstrate our systematic parameter determination stage for configuring the system specific EF parameters.

Systematic Analysis of Hollow Fiber Model of Tuberculosis Experiments.

PubMed

Pasipanodya, Jotam G; Nuermberger, Eric; Romero, Klaus; Hanna, Debra; Gumbo, Tawanda

2015-08-15

The in vitro hollow fiber system model of tuberculosis (HFS-TB), in tandem with Monte Carlo experiments, was introduced more than a decade ago. Since then, it has been used to perform a large number of tuberculosis pharmacokinetics/pharmacodynamics (PK/PD) studies that have not been subjected to systematic analysis. We performed a literature search to identify all HFS-TB experiments published between 1 January 2000 and 31 December 2012. There was no exclusion of articles by language. Bias minimization was according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Steps for reporting systematic reviews were followed. There were 22 HFS-TB studies published, of which 12 were combination therapy studies and 10 were monotherapy studies. There were 4 stand-alone Monte Carlo experiments that utilized quantitative output from the HFS-TB. All experiments reported drug pharmacokinetics, which recapitulated those encountered in humans. HFS-TB studies included log-phase growth studies under ambient air, semidormant bacteria at pH 5.8, and nonreplicating persisters at low oxygen tension of ≤ 10 parts per billion. The studies identified antibiotic exposures associated with optimal kill of Mycobacterium tuberculosis and suppression of acquired drug resistance (ADR) and informed predictions about optimal clinical doses, expected performance of standard doses and regimens in patients, and expected rates of ADR, as well as a proposal of new susceptibility breakpoints. The HFS-TB model offers the ability to perform PK/PD studies including humanlike drug exposures, to identify bactericidal and sterilizing effect rates, and to identify exposures associated with suppression of drug resistance. Because of the ability to perform repetitive sampling from the same unit over time, the HFS-TB vastly improves statistical power and facilitates the execution of time-to-event analyses and repeated event analyses, as well as dynamic system pharmacology mathematical models. © The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Developing Students' Reflections on the Function and Status of Mathematical Modeling in Different Scientific Practices: History as a Provider of Cases

ERIC Educational Resources Information Center

Kjeldsen, Tinne Hoff; Blomhøj, Morten

2013-01-01

Mathematical models and mathematical modeling play different roles in the different areas and problems in which they are used. The function and status of mathematical modeling and models in the different areas depend on the scientific practice as well as the underlying philosophical and theoretical position held by the modeler(s) and the…

How Ordinary Meaning Underpins the Meaning of Mathematics.

ERIC Educational Resources Information Center

Ormell, Christopher

1991-01-01

Discusses the meaning of mathematics by looking at its uses in the real world. Offers mathematical modeling as a way to represent mathematical applications in real or potential situations. Presents levels of applicability, modus operandi, relationship to "pure mathematics," and consequences for education for mathematical modeling. (MDH)

An Integrative Approach to Computational Modelling of the Gene Regulatory Network Controlling Clostridium botulinum Type A1 Toxin Production

PubMed Central

Walshaw, John; Peck, Michael W.; Barker, Gary C.

2016-01-01

Clostridium botulinum produces botulinum neurotoxins (BoNTs), highly potent substances responsible for botulism. Currently, mathematical models of C. botulinum growth and toxigenesis are largely aimed at risk assessment and do not include explicit genetic information beyond group level but integrate many component processes, such as signalling, membrane permeability and metabolic activity. In this paper we present a scheme for modelling neurotoxin production in C. botulinum Group I type A1, based on the integration of diverse information coming from experimental results available in the literature. Experiments show that production of BoNTs depends on the growth-phase and is under the control of positive and negative regulatory elements at the intracellular level. Toxins are released as large protein complexes and are associated with non-toxic components. Here, we systematically review and integrate those regulatory elements previously described in the literature for C. botulinum Group I type A1 into a population dynamics model, to build the very first computational model of toxin production at the molecular level. We conduct a validation of our model against several items of published experimental data for different wild type and mutant strains of C. botulinum Group I type A1. The result of this process underscores the potential of mathematical modelling at the cellular level, as a means of creating opportunities in developing new strategies that could be used to prevent botulism; and potentially contribute to improved methods for the production of toxin that is used for therapeutics. PMID:27855161

Strong Inference in Mathematical Modeling: A Method for Robust Science in the Twenty-First Century.

PubMed

Ganusov, Vitaly V

2016-01-01

While there are many opinions on what mathematical modeling in biology is, in essence, modeling is a mathematical tool, like a microscope, which allows consequences to logically follow from a set of assumptions. Only when this tool is applied appropriately, as microscope is used to look at small items, it may allow to understand importance of specific mechanisms/assumptions in biological processes. Mathematical modeling can be less useful or even misleading if used inappropriately, for example, when a microscope is used to study stars. According to some philosophers (Oreskes et al., 1994), the best use of mathematical models is not when a model is used to confirm a hypothesis but rather when a model shows inconsistency of the model (defined by a specific set of assumptions) and data. Following the principle of strong inference for experimental sciences proposed by Platt (1964), I suggest "strong inference in mathematical modeling" as an effective and robust way of using mathematical modeling to understand mechanisms driving dynamics of biological systems. The major steps of strong inference in mathematical modeling are (1) to develop multiple alternative models for the phenomenon in question; (2) to compare the models with available experimental data and to determine which of the models are not consistent with the data; (3) to determine reasons why rejected models failed to explain the data, and (4) to suggest experiments which would allow to discriminate between remaining alternative models. The use of strong inference is likely to provide better robustness of predictions of mathematical models and it should be strongly encouraged in mathematical modeling-based publications in the Twenty-First century.

A generic biogeochemical module for earth system models

NASA Astrophysics Data System (ADS)

Fang, Y.; Huang, M.; Liu, C.; Li, H.-Y.; Leung, L. R.

2013-06-01

Physical and biogeochemical processes regulate soil carbon dynamics and CO2 flux to and from the atmosphere, influencing global climate changes. Integration of these processes into earth system models (e.g. community land models - CLM), however, currently faces three major challenges: (1) extensive efforts are required to modify modeling structures and to rewrite computer programs to incorporate new or updated processes as new knowledge is being generated, (2) computational cost is prohibitively expensive to simulate biogeochemical processes in land models due to large variations in the rates of biogeochemical processes, and (3) various mathematical representations of biogeochemical processes exist to incorporate different aspects of fundamental mechanisms, but systematic evaluation of the different mathematical representations is difficult, if not impossible. To address these challenges, we propose a new computational framework to easily incorporate physical and biogeochemical processes into land models. The new framework consists of a new biogeochemical module with a generic algorithm and reaction database so that new and updated processes can be incorporated into land models without the need to manually set up the ordinary differential equations to be solved numerically. The reaction database consists of processes of nutrient flow through the terrestrial ecosystems in plants, litter and soil. This framework facilitates effective comparison studies of biogeochemical cycles in an ecosystem using different conceptual models under the same land modeling framework. The approach was first implemented in CLM and benchmarked against simulations from the original CLM-CN code. A case study was then provided to demonstrate the advantages of using the new approach to incorporate a phosphorus cycle into the CLM model. To our knowledge, the phosphorus-incorporated CLM is a new model that can be used to simulate phosphorus limitation on the productivity of terrestrial ecosystems.

Summer Camp of Mathematical Modeling in China

ERIC Educational Resources Information Center

Tian, Xiaoxi; Xie, Jinxing

2013-01-01

The Summer Camp of Mathematical Modeling in China is a recently created experience designed to further Chinese students' academic pursuits in mathematical modeling. Students are given more than three months to research on a mathematical modeling project. Researchers and teams with outstanding projects are invited to the Summer Camp to present…

Numerical simulation of mechanical mixing in high solid anaerobic digester.

PubMed

Yu, Liang; Ma, Jingwei; Chen, Shulin

2011-01-01

Computational fluid dynamics (CFD) was employed to study mixing performance in high solid anaerobic digester (HSAD) with A-310 impeller and helical ribbon. A mathematical model was constructed to assess flow fields. Good agreement of the model results with experimental data was obtained for the A-310 impeller. A systematic comparison for the interrelationship of power number, flow number and Reynolds number was simulated in a digester with less than 5% TS and 10% TS (total solids). The simulation results suggested a great potential for using the helical ribbon mixer in the mixing of high solids digester. The results also provided quantitative confirmation for minimum power consumption in HSAD and the effect of share rate on bio-structure. Copyright © 2010 Elsevier Ltd. All rights reserved.

Cost-Based Optimization of a Papermaking Wastewater Regeneration Recycling System

NASA Astrophysics Data System (ADS)

Huang, Long; Feng, Xiao; Chu, Khim H.

2010-11-01

Wastewater can be regenerated for recycling in an industrial process to reduce freshwater consumption and wastewater discharge. Such an environment friendly approach will also lead to cost savings that accrue due to reduced freshwater usage and wastewater discharge. However, the resulting cost savings are offset to varying degrees by the costs incurred for the regeneration of wastewater for recycling. Therefore, systematic procedures should be used to determine the true economic benefits for any water-using system involving wastewater regeneration recycling. In this paper, a total cost accounting procedure is employed to construct a comprehensive cost model for a paper mill. The resulting cost model is optimized by means of mathematical programming to determine the optimal regeneration flowrate and regeneration efficiency that will yield the minimum total cost.

Dynamic Stochastic Control of Freeway Corridor Systems : Summary and Project Overview

DOT National Transportation Integrated Search

1978-12-01

Systematic methodological approaches to overall traffic management from both short-term (real-time) and long-term (planning) perspectives have been developed. The approach embodies formulation and solution of interrelated mathematical problems from o...

Strong Inference in Mathematical Modeling: A Method for Robust Science in the Twenty-First Century

PubMed Central

Ganusov, Vitaly V.

2016-01-01

While there are many opinions on what mathematical modeling in biology is, in essence, modeling is a mathematical tool, like a microscope, which allows consequences to logically follow from a set of assumptions. Only when this tool is applied appropriately, as microscope is used to look at small items, it may allow to understand importance of specific mechanisms/assumptions in biological processes. Mathematical modeling can be less useful or even misleading if used inappropriately, for example, when a microscope is used to study stars. According to some philosophers (Oreskes et al., 1994), the best use of mathematical models is not when a model is used to confirm a hypothesis but rather when a model shows inconsistency of the model (defined by a specific set of assumptions) and data. Following the principle of strong inference for experimental sciences proposed by Platt (1964), I suggest “strong inference in mathematical modeling” as an effective and robust way of using mathematical modeling to understand mechanisms driving dynamics of biological systems. The major steps of strong inference in mathematical modeling are (1) to develop multiple alternative models for the phenomenon in question; (2) to compare the models with available experimental data and to determine which of the models are not consistent with the data; (3) to determine reasons why rejected models failed to explain the data, and (4) to suggest experiments which would allow to discriminate between remaining alternative models. The use of strong inference is likely to provide better robustness of predictions of mathematical models and it should be strongly encouraged in mathematical modeling-based publications in the Twenty-First century. PMID:27499750

[Mathematical exploration of essence of herbal properties based on "Three-Elements" theory].

PubMed

Jin, Rui; Zhao, Qian; Zhang, Bing

2014-10-01

Herbal property theory of traditional Chinese medicines is the theoretical guidance on authentication of medicinal plants, herborization, preparation of herbal medicines for decoction and clinical application, with important theoretical value and prac- tical significance. Our research team proposed the "three-element" theory for herbal properties for the first time, conducted a study by using combined methods of philology, chemistry, pharmacology and mathematics, and then drew the research conclusion that herbal properties are defined as the chemical compositions-based comprehensive expression with complex and multi-level (positive/negative) biological effects in specific organism state. In this paper, researchers made a systematic mathematical analysis in four aspects--the correlation between herbal properties and chemical component factors, the correlation between herbal properties and organism state fac- tor, the correlation between herbal properties and biological effect factor and the integration study of the three elements, proposed future outlook, and provided reference to mathematical studies and mathematical analysis of herbal properties.

Modeling of pathogen survival during simulated gastric digestion.

PubMed

Koseki, Shige; Mizuno, Yasuko; Sotome, Itaru

2011-02-01

The objective of the present study was to develop a mathematical model of pathogenic bacterial inactivation kinetics in a gastric environment in order to further understand a part of the infectious dose-response mechanism. The major bacterial pathogens Listeria monocytogenes, Escherichia coli O157:H7, and Salmonella spp. were examined by using simulated gastric fluid adjusted to various pH values. To correspond to the various pHs in a stomach during digestion, a modified logistic differential equation model and the Weibull differential equation model were examined. The specific inactivation rate for each pathogen was successfully described by a square-root model as a function of pH. The square-root models were combined with the modified logistic differential equation to obtain a complete inactivation curve. Both the modified logistic and Weibull models provided a highly accurate fitting of the static pH conditions for every pathogen. However, while the residuals plots of the modified logistic model indicated no systematic bias and/or regional prediction problems, the residuals plots of the Weibull model showed a systematic bias. The modified logistic model appropriately predicted the pathogen behavior in the simulated gastric digestion process with actual food, including cut lettuce, minced tuna, hamburger, and scrambled egg. Although the developed model enabled us to predict pathogen inactivation during gastric digestion, its results also suggested that the ingested bacteria in the stomach would barely be inactivated in the real digestion process. The results of this study will provide important information on a part of the dose-response mechanism of bacterial pathogens.

Modeling of Pathogen Survival during Simulated Gastric Digestion ▿

PubMed Central

Koseki, Shige; Mizuno, Yasuko; Sotome, Itaru

2011-01-01

The objective of the present study was to develop a mathematical model of pathogenic bacterial inactivation kinetics in a gastric environment in order to further understand a part of the infectious dose-response mechanism. The major bacterial pathogens Listeria monocytogenes, Escherichia coli O157:H7, and Salmonella spp. were examined by using simulated gastric fluid adjusted to various pH values. To correspond to the various pHs in a stomach during digestion, a modified logistic differential equation model and the Weibull differential equation model were examined. The specific inactivation rate for each pathogen was successfully described by a square-root model as a function of pH. The square-root models were combined with the modified logistic differential equation to obtain a complete inactivation curve. Both the modified logistic and Weibull models provided a highly accurate fitting of the static pH conditions for every pathogen. However, while the residuals plots of the modified logistic model indicated no systematic bias and/or regional prediction problems, the residuals plots of the Weibull model showed a systematic bias. The modified logistic model appropriately predicted the pathogen behavior in the simulated gastric digestion process with actual food, including cut lettuce, minced tuna, hamburger, and scrambled egg. Although the developed model enabled us to predict pathogen inactivation during gastric digestion, its results also suggested that the ingested bacteria in the stomach would barely be inactivated in the real digestion process. The results of this study will provide important information on a part of the dose-response mechanism of bacterial pathogens. PMID:21131530

Using Covariation Reasoning to Support Mathematical Modeling

ERIC Educational Resources Information Center

Jacobson, Erik

2014-01-01

For many students, making connections between mathematical ideas and the real world is one of the most intriguing and rewarding aspects of the study of mathematics. In the Common Core State Standards for Mathematics (CCSSI 2010), mathematical modeling is highlighted as a mathematical practice standard for all grades. To engage in mathematical…

An Examination of Pre-Service Mathematics Teachers' Approaches to Construct and Solve Mathematical Modelling Problems

ERIC Educational Resources Information Center

Bukova-Guzel, Esra

2011-01-01

This study examines the approaches displayed by pre-service mathematics teachers in their experiences of constructing mathematical modelling problems and the extent to which they perform the modelling process when solving the problems they construct. This case study was carried out with 35 pre-service teachers taking the Mathematical Modelling…

Estimation of geopotential differences over intercontinental locations using satellite and terrestrial measurements. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Pavlis, Nikolaos K.

1991-01-01

An error analysis study was conducted in order to assess the current accuracies and the future anticipated improvements in the estimation of geopotential differences over intercontinental locations. An observation/estimation scheme was proposed and studied, whereby gravity disturbance measurements on the Earth's surface, in caps surrounding the estimation points, are combined with corresponding data in caps directly over these points at the altitude of a low orbiting satellite, for the estimation of the geopotential difference between the terrestrial stations. The mathematical modeling required to relate the primary observables to the parameters to be estimated, was studied for the terrestrial data and the data at altitude. Emphasis was placed on the examination of systematic effects and on the corresponding reductions that need to be applied to the measurements to avoid systematic errors. The error estimation for the geopotential differences was performed using both truncation theory and least squares collocation with ring averages, in case observations on the Earth's surface only are used. The error analysis indicated that with the currently available global geopotential model OSU89B and with gravity disturbance data in 2 deg caps surrounding the estimation points, the error of the geopotential difference arising from errors in the reference model and the cap data is about 23 kgal cm, for 30 deg station separation.

Learning to teach mathematical modelling in secondary and tertiary education

NASA Astrophysics Data System (ADS)

Ferri, Rita Borromeo

2017-07-01

Since 2003 mathematical modelling in Germany is not only a topic for scientific disciplines in university mathematics courses, but also in school starting with primary school. This paper shows what mathematical modelling means in school and how it can be taught as a basis for complex modeling problems in tertiary education.

Development of a Multidisciplinary Middle School Mathematics Infusion Model

ERIC Educational Resources Information Center

Russo, Maria; Hecht, Deborah; Burghardt, M. David; Hacker, Michael; Saxman, Laura

2011-01-01

The National Science Foundation (NSF) funded project "Mathematics, Science, and Technology Partnership" (MSTP) developed a multidisciplinary instructional model for connecting mathematics to science, technology and engineering content areas at the middle school level. Specifically, the model infused mathematics into middle school curriculum…

Frequencies as Proportions: Using a Teaching Model Based on Pirie and Kieren's Model of Mathematical Understanding

ERIC Educational Resources Information Center

Wright, Vince

2014-01-01

Pirie and Kieren (1989 "For the learning of mathematics", 9(3)7-11, 1992 "Journal of Mathematical Behavior", 11, 243-257, 1994a "Educational Studies in Mathematics", 26, 61-86, 1994b "For the Learning of Mathematics":, 14(1)39-43) created a model (P-K) that describes a dynamic and recursive process by which…

Detecting Strengths and Weaknesses in Learning Mathematics through a Model Classifying Mathematical Skills

ERIC Educational Resources Information Center

Karagiannakis, Giannis N.; Baccaglini-Frank, Anna E.; Roussos, Petros

2016-01-01

Through a review of the literature on mathematical learning disabilities (MLD) and low achievement in mathematics (LA) we have proposed a model classifying mathematical skills involved in learning mathematics into four domains (Core number, Memory, Reasoning, and Visual-spatial). In this paper we present a new experimental computer-based battery…

Teaching Mathematical Modeling in Mathematics Education

ERIC Educational Resources Information Center

Saxena, Ritu; Shrivastava, Keerty; Bhardwaj, Ramakant

2016-01-01

Mathematics is not only a subject but it is also a language consisting of many different symbols and relations. Taught as a compulsory subject up the 10th class, students are then able to choose whether or not to study mathematics as a main subject. The present paper discusses mathematical modeling in mathematics education. The article provides…

No evidence for systematic white matter correlates of dyslexia and dyscalculia.

PubMed

Moreau, David; Wilson, Anna J; McKay, Nicole S; Nihill, Kasey; Waldie, Karen E

2018-01-01

Learning disabilities such as dyslexia, dyscalculia and their comorbid manifestation are prevalent, affecting as much as 15% of the population. Structural neuroimaging studies have indicated that these disorders can be related to differences in white matter integrity, although findings remain disparate. In this study, we used a unique design composed of individuals with dyslexia, dyscalculia, both disorders and controls, to systematically explore differences in fractional anisotropy across groups using diffusion tensor imaging. Specifically, we focused on the corona radiata and the arcuate fasciculus, two tracts associated with reading and mathematics in a number of previous studies. Using Bayesian hypothesis testing, we show that the present data favor the null model of no differences between groups for these particular tracts-a finding that seems to go against the current view but might be representative of the disparities within this field of research. Together, these findings suggest that structural differences associated with dyslexia and dyscalculia might not be as reliable as previously thought, with potential ramifications in terms of remediation.

Systematic Sensitivity Analysis of Metabolic Controllers During Reductions in Skeletal Muscle Blood Flow

NASA Technical Reports Server (NTRS)

Radhakrishnan, Krishnan; Cabrera, Marco

2000-01-01

An acute reduction in oxygen delivery to skeletal muscle is generally associated with profound derangements in substrate metabolism. Given the complexity of the human bioenergetic system and its components, it is difficult to quantify the interaction of cellular metabolic processes to maintain ATP homeostasis during stress (e.g., hypoxia, ischemia, and exercise). Of special interest is the determination of mechanisms relating tissue oxygenation to observed metabolic responses at the tissue, organ, and whole body levels and the quantification of how changes in oxygen availability affect the pathways of ATP synthesis and their regulation. In this study, we apply a previously developed mathematical model of human bioenergetics to study effects of ischemia during periods of increased ATP turnover (e.g., exercise). By using systematic sensitivity analysis the oxidative phosphorylation rate was found to be the most important rate parameter affecting lactate production during ischemia under resting conditions. Here we examine whether mild exercise under ischemic conditions alters the relative importance of pathways and parameters previously obtained.

Topological analysis of polymeric melts: chain-length effects and fast-converging estimators for entanglement length.

PubMed

Hoy, Robert S; Foteinopoulou, Katerina; Kröger, Martin

2009-09-01

Primitive path analyses of entanglements are performed over a wide range of chain lengths for both bead spring and atomistic polyethylene polymer melts. Estimators for the entanglement length N_{e} which operate on results for a single chain length N are shown to produce systematic O(1/N) errors. The mathematical roots of these errors are identified as (a) treating chain ends as entanglements and (b) neglecting non-Gaussian corrections to chain and primitive path dimensions. The prefactors for the O(1/N) errors may be large; in general their magnitude depends both on the polymer model and the method used to obtain primitive paths. We propose, derive, and test new estimators which eliminate these systematic errors using information obtainable from the variation in entanglement characteristics with chain length. The new estimators produce accurate results for N_{e} from marginally entangled systems. Formulas based on direct enumeration of entanglements appear to converge faster and are simpler to apply.

Teaching Mathematical Modelling for Earth Sciences via Case Studies

NASA Astrophysics Data System (ADS)

Yang, Xin-She

2010-05-01

Mathematical modelling is becoming crucially important for earth sciences because the modelling of complex systems such as geological, geophysical and environmental processes requires mathematical analysis, numerical methods and computer programming. However, a substantial fraction of earth science undergraduates and graduates may not have sufficient skills in mathematical modelling, which is due to either limited mathematical training or lack of appropriate mathematical textbooks for self-study. In this paper, we described a detailed case-study-based approach for teaching mathematical modelling. We illustrate how essential mathematical skills can be developed for students with limited training in secondary mathematics so that they are confident in dealing with real-world mathematical modelling at university level. We have chosen various topics such as Airy isostasy, greenhouse effect, sedimentation and Stokes' flow,free-air and Bouguer gravity, Brownian motion, rain-drop dynamics, impact cratering, heat conduction and cooling of the lithosphere as case studies; and we use these step-by-step case studies to teach exponentials, logarithms, spherical geometry, basic calculus, complex numbers, Fourier transforms, ordinary differential equations, vectors and matrix algebra, partial differential equations, geostatistics and basic numeric methods. Implications for teaching university mathematics for earth scientists for tomorrow's classroom will also be discussed. Refereces 1) D. L. Turcotte and G. Schubert, Geodynamics, 2nd Edition, Cambridge University Press, (2002). 2) X. S. Yang, Introductory Mathematics for Earth Scientists, Dunedin Academic Press, (2009).

Mathematics Literacy on Problem Based Learning with Indonesian Realistic Mathematics Education Approach Assisted E-Learning Edmodo

NASA Astrophysics Data System (ADS)

Wardono; Waluya, S. B.; Mariani, Scolastika; Candra D, S.

2016-02-01

This study aims to find out that there are differences in mathematical literacy ability in content Change and Relationship class VII Junior High School 19, Semarang by Problem Based Learning (PBL) model with an Indonesian Realistic Mathematics Education (called Pendidikan Matematika Realistik Indonesia or PMRI in Indonesia) approach assisted Elearning Edmodo, PBL with a PMRI approach, and expository; to know whether the group of students with learning PBL models with PMRI approach and assisted E-learning Edmodo can improve mathematics literacy; to know that the quality of learning PBL models with a PMRI approach assisted E-learning Edmodo has a good category; to describe the difficulties of students in working the problems of mathematical literacy ability oriented PISA. This research is a mixed methods study. The population was seventh grade students of Junior High School 19, Semarang Indonesia. Sample selection is done by random sampling so that the selected experimental class 1, class 2 and the control experiment. Data collected by the methods of documentation, tests and interviews. From the results of this study showed average mathematics literacy ability of students in the group PBL models with a PMRI approach assisted E-learning Edmodo better than average mathematics literacy ability of students in the group PBL models with a PMRI approach and better than average mathematics literacy ability of students in the expository models; Mathematics literacy ability in the class using the PBL model with a PMRI approach assisted E-learning Edmodo have increased and the improvement of mathematics literacy ability is higher than the improvement of mathematics literacy ability of class that uses the model of PBL learning with PMRI approach and is higher than the improvement of mathematics literacy ability of class that uses the expository models; The quality of learning using PBL models with a PMRI approach assisted E-learning Edmodo have very good category.

Influence of beta-cyclodextrin complexation on glipizide release from hydroxypropyl methylcellulose matrix tablets.

PubMed

Shivakumar, H N; Desai, B G; Pandya, Saumyak; Karki, S S

2007-01-01

Glipizide was complexed with beta-cyclodextrin in an attempt to enhance the drug solubility. The phase solubility diagram was classified as A(L) type, which was characterized by an apparent 1:1 stability constant that had a value of 413.82 M(-1). Fourier transform infrared spectrophotometry, differential scanning calorimetry, powder x-ray diffractometry and proton nuclear magnetic resonance spectral analysis indicated considerable interaction between the drug and beta-cyclodextrin. A 2(3) factorial design was employed to prepare hydroxypropyl methylcellulose (HPMC) matrix tablets containing the drug or its complex. The effect of the total polymer loads (X1), levels of HPMC K100LV (X9), and complexation (X3) on release at first hour (Y1), 24 h (Y2), time taken for 50% release (Y3), and diffusion exponent (Y4) was systematically analyzed using the F test. Mathematical models containing only the significant terms (P < 0.05) were generated for each parameter by multiple linear regression analysis and analysis of variance. Complexation was found to exert a significant effect on Y1, Y2, and Y3, whereas total polymer loads significantly influenced all the responses. The models generated were validated by developing two new formulations with a combination of factors within the experimental domain. The experimental values of the response parameters were in close agreement with the predicted values, thereby proving-the validity of the generated mathematical models.

New Methodology for Estimating Fuel Economy by Vehicle Class

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

Chin, Shih-Miao; Dabbs, Kathryn; Hwang, Ho-Ling

2011-01-01

Office of Highway Policy Information to develop a new methodology to generate annual estimates of average fuel efficiency and number of motor vehicles registered by vehicle class for Table VM-1 of the Highway Statistics annual publication. This paper describes the new methodology developed under this effort and compares the results of the existing manual method and the new systematic approach. The methodology developed under this study takes a two-step approach. First, the preliminary fuel efficiency rates are estimated based on vehicle stock models for different classes of vehicles. Then, a reconciliation model is used to adjust the initial fuel consumptionmore » rates from the vehicle stock models and match the VMT information for each vehicle class and the reported total fuel consumption. This reconciliation model utilizes a systematic approach that produces documentable and reproducible results. The basic framework utilizes a mathematical programming formulation to minimize the deviations between the fuel economy estimates published in the previous year s Highway Statistics and the results from the vehicle stock models, subject to the constraint that fuel consumptions for different vehicle classes must sum to the total fuel consumption estimate published in Table MF-21 of the current year Highway Statistics. The results generated from this new approach provide a smoother time series for the fuel economies by vehicle class. It also utilizes the most up-to-date and best available data with sound econometric models to generate MPG estimates by vehicle class.« less

A Review of Mathematical Models for Leukemia and Lymphoma

PubMed Central

Clapp, Geoffrey; Levy, Doron

2014-01-01

Recently, there has been significant activity in the mathematical community, aimed at developing quantitative tools for studying leukemia and lymphoma. Mathematical models have been applied to evaluate existing therapies and to suggest novel therapies. This article reviews the recent contributions of mathematical modeling to leukemia and lymphoma research. These developments suggest that mathematical modeling has great potential in this field. Collaboration between mathematicians, clinicians, and experimentalists can significantly improve leukemia and lymphoma therapy. PMID:26744598

A theory of behaviour on progressive ratio schedules, with applications in behavioural pharmacology.

PubMed

Bradshaw, C M; Killeen, P R

2012-08-01

Mathematical principles of reinforcement (MPR) provide the theoretical basis for a family of models of schedule-controlled behaviour. A model of fixed-ratio schedule performance that was applied to behaviour on progressive ratio (PR) schedules showed systematic departures from the data. This study aims to derive a new model from MPR that will account for overall and running response rates in the component ratios of PR schedules, and their decline toward 0, the breakpoint. The role of pausing is represented in a real-time model containing four parameters: T (0) and k are the intercept and slope of the linear relation between post-reinforcement pause duration and the prior inter-reinforcer interval; a (specific activation) measures the incentive value of the reinforcer; δ (response time) sets biomechanical limits on response rate. Running rate is predicted to decrease with negative acceleration as ratio size increments, overall rate to increase and then decrease. Differences due to type of progression are explained as hysteresis in the control by reinforcement rates. Re-analysis of extant data focuses on the effects of acute treatment with antipsychotic drugs, lesions of the nucleus accumbens core, and destruction of orexinergic neurones of the lateral hypothalamus. The new model resolves some anomalies evident in earlier analyses, and provides new insights to the results of these interventions. Because they can render biologically relevant parameters, mathematical models can provide greater power in interpreting the effects of interventions on the processes underlying schedule-controlled behaviour than is possible for first-order data such as the breakpoint.

An evaluation of models of bare soil evaporation formulated with different land surface boundary conditions and assumptions

NASA Astrophysics Data System (ADS)

Smits, Kathleen M.; Ngo, Viet V.; Cihan, Abdullah; Sakaki, Toshihiro; Illangasekare, Tissa H.

2012-12-01

Bare soil evaporation is a key process for water exchange between the land and the atmosphere and an important component of the water balance. However, there is no agreement on the best modeling methodology to determine evaporation under different atmospheric boundary conditions. Also, there is a lack of directly measured soil evaporation data for model validation to compare these methods to establish the validity of their mathematical formulations. Thus, a need exists to systematically compare evaporation estimates using existing methods to experimental observations. The goal of this work is to test different conceptual and mathematical formulations that are used to estimate evaporation from bare soils to critically investigate various formulations and surface boundary conditions. Such a comparison required the development of a numerical model that has the ability to incorporate these boundary conditions. For this model, we modified a previously developed theory that allows nonequilibrium liquid/gas phase change with gas phase vapor diffusion to better account for dry soil conditions. Precision data under well-controlled transient heat and wind boundary conditions were generated, and results from numerical simulations were compared with experimental data. Results demonstrate that the approaches based on different boundary conditions varied in their ability to capture different stages of evaporation. All approaches have benefits and limitations, and no one approach can be deemed most appropriate for every scenario. Comparisons of different formulations of the surface boundary condition validate the need for further research on heat and vapor transport processes in soil for better modeling accuracy.

A mathematical model of endovascular heat transfer for human brain cooling

NASA Astrophysics Data System (ADS)

Salsac, Anne-Virginie; Lasheras, Juan Carlos; Yon, Steven; Magers, Mike; Dobak, John

2000-11-01

Selective cooling of the brain has been shown to exhibit protective effects in cerebral ischemia, trauma, and spinal injury/ischemia. A multi-compartment, unsteady thermal model of the response of the human brain to endovascular cooling is discussed and its results compared to recent experimental data conducted with sheep and other mammals. The model formulation is based on the extension of the bioheat equation, originally proposed by Pennes(1) and later modified by Wissler(2), Stolwijk(3) and Werner and Webb(4). The temporal response of the brain temperature and that of the various body compartments to the cooling of the blood flowing through the common carotid artery is calculated under various scenarios. The effect of the boundary conditions as well as the closure assumptions used in the model, i.e. perfusion rate, metabolism heat production, etc. on the cooling rate of the brain are systematically investigated. (1) Pennes H. H., “Analysis of tissue and arterial blood temperature in the resting forearm.” J. Appl. Physiol. 1: 93-122, 1948. (2) Wissler E. H., “Steady-state temperature distribution in man”, J. Appl. Physiol., 16: 764-740, 1961. (3) Stolwick J. A. J., “Mathematical model of thermoregulation” in “Physiological and behavioral temperature regulation”, edited by J. D. Hardy, A. P. Gagge and A. J. Stolwijk, Charles C. Thomas Publisher, Springfiels, Ill., 703-721, 1971. (4) Werner J., Webb P., “A six-cylinder model of human thermoregulation for general use on personal computers”, Ann. Physiol. Anthrop., 12(3): 123-134, 1993.

Predicting spiral wave patterns from cell properties in a model of biological self-organization.

PubMed

Geberth, Daniel; Hütt, Marc-Thorsten

2008-09-01

In many biological systems, biological variability (i.e., systematic differences between the system components) can be expected to outrank statistical fluctuations in the shaping of self-organized patterns. In principle, the distribution of single-element properties should thus allow predicting features of such patterns. For a mathematical model of a paradigmatic and well-studied pattern formation process, spiral waves of cAMP signaling in colonies of the slime mold Dictyostelium discoideum, we explore this possibility and observe a pronounced anticorrelation between spiral waves and cell properties (namely, the firing rate) and particularly a clustering of spiral wave tips in regions devoid of spontaneously firing (pacemaker) cells. Furthermore, we observe local inhomogeneities in the distribution of spiral chiralities, again induced by the pacemaker distribution. We show that these findings can be explained by a simple geometrical model of spiral wave generation.

Developing a job-exposure matrix with exposure uncertainty from expert elicitation and data modeling.

PubMed

Fischer, Heidi J; Vergara, Ximena P; Yost, Michael; Silva, Michael; Lombardi, David A; Kheifets, Leeka

2017-01-01

Job exposure matrices (JEMs) are tools used to classify exposures for job titles based on general job tasks in the absence of individual level data. However, exposure uncertainty due to variations in worker practices, job conditions, and the quality of data has never been quantified systematically in a JEM. We describe a methodology for creating a JEM which defines occupational exposures on a continuous scale and utilizes elicitation methods to quantify exposure uncertainty by assigning exposures probability distributions with parameters determined through expert involvement. Experts use their knowledge to develop mathematical models using related exposure surrogate data in the absence of available occupational level data and to adjust model output against other similar occupations. Formal expert elicitation methods provided a consistent, efficient process to incorporate expert judgment into a large, consensus-based JEM. A population-based electric shock JEM was created using these methods, allowing for transparent estimates of exposure.

Predicting spiral wave patterns from cell properties in a model of biological self-organization

NASA Astrophysics Data System (ADS)

Geberth, Daniel; Hütt, Marc-Thorsten

2008-09-01

In many biological systems, biological variability (i.e., systematic differences between the system components) can be expected to outrank statistical fluctuations in the shaping of self-organized patterns. In principle, the distribution of single-element properties should thus allow predicting features of such patterns. For a mathematical model of a paradigmatic and well-studied pattern formation process, spiral waves of cAMP signaling in colonies of the slime mold Dictyostelium discoideum, we explore this possibility and observe a pronounced anticorrelation between spiral waves and cell properties (namely, the firing rate) and particularly a clustering of spiral wave tips in regions devoid of spontaneously firing (pacemaker) cells. Furthermore, we observe local inhomogeneities in the distribution of spiral chiralities, again induced by the pacemaker distribution. We show that these findings can be explained by a simple geometrical model of spiral wave generation.

Temporal controls of the asymmetric cell division cycle in Caulobacter crescentus.

PubMed

Li, Shenghua; Brazhnik, Paul; Sobral, Bruno; Tyson, John J

2009-08-01

The asymmetric cell division cycle of Caulobacter crescentus is orchestrated by an elaborate gene-protein regulatory network, centered on three major control proteins, DnaA, GcrA and CtrA. The regulatory network is cast into a quantitative computational model to investigate in a systematic fashion how these three proteins control the relevant genetic, biochemical and physiological properties of proliferating bacteria. Different controls for both swarmer and stalked cell cycles are represented in the mathematical scheme. The model is validated against observed phenotypes of wild-type cells and relevant mutants, and it predicts the phenotypes of novel mutants and of known mutants under novel experimental conditions. Because the cell cycle control proteins of Caulobacter are conserved across many species of alpha-proteobacteria, the model we are proposing here may be applicable to other genera of importance to agriculture and medicine (e.g., Rhizobium, Brucella).

Statistical Methodologies to Integrate Experimental and Computational Research

NASA Technical Reports Server (NTRS)

Parker, P. A.; Johnson, R. T.; Montgomery, D. C.

2008-01-01

Development of advanced algorithms for simulating engine flow paths requires the integration of fundamental experiments with the validation of enhanced mathematical models. In this paper, we provide an overview of statistical methods to strategically and efficiently conduct experiments and computational model refinement. Moreover, the integration of experimental and computational research efforts is emphasized. With a statistical engineering perspective, scientific and engineering expertise is combined with statistical sciences to gain deeper insights into experimental phenomenon and code development performance; supporting the overall research objectives. The particular statistical methods discussed are design of experiments, response surface methodology, and uncertainty analysis and planning. Their application is illustrated with a coaxial free jet experiment and a turbulence model refinement investigation. Our goal is to provide an overview, focusing on concepts rather than practice, to demonstrate the benefits of using statistical methods in research and development, thereby encouraging their broader and more systematic application.

Visual Form Perception Can Be a Cognitive Correlate of Lower Level Math Categories for Teenagers.

PubMed

Cui, Jiaxin; Zhang, Yiyun; Cheng, Dazhi; Li, Dawei; Zhou, Xinlin

2017-01-01

Numerous studies have assessed the cognitive correlates of performance in mathematics, but little research has been conducted to systematically examine the relations between visual perception as the starting point of visuospatial processing and typical mathematical performance. In the current study, we recruited 223 seventh graders to perform a visual form perception task (figure matching), numerosity comparison, digit comparison, exact computation, approximate computation, and curriculum-based mathematical achievement tests. Results showed that, after controlling for gender, age, and five general cognitive processes (choice reaction time, visual tracing, mental rotation, spatial working memory, and non-verbal matrices reasoning), visual form perception had unique contributions to numerosity comparison, digit comparison, and exact computation, but had no significant relation with approximate computation or curriculum-based mathematical achievement. These results suggest that visual form perception is an important independent cognitive correlate of lower level math categories, including the approximate number system, digit comparison, and exact computation.

Decision-analytic modeling studies: An overview for clinicians using multiple myeloma as an example.

PubMed

Rochau, U; Jahn, B; Qerimi, V; Burger, E A; Kurzthaler, C; Kluibenschaedl, M; Willenbacher, E; Gastl, G; Willenbacher, W; Siebert, U

2015-05-01

The purpose of this study was to provide a clinician-friendly overview of decision-analytic models evaluating different treatment strategies for multiple myeloma (MM). We performed a systematic literature search to identify studies evaluating MM treatment strategies using mathematical decision-analytic models. We included studies that were published as full-text articles in English, and assessed relevant clinical endpoints, and summarized methodological characteristics (e.g., modeling approaches, simulation techniques, health outcomes, perspectives). Eleven decision-analytic modeling studies met our inclusion criteria. Five different modeling approaches were adopted: decision-tree modeling, Markov state-transition modeling, discrete event simulation, partitioned-survival analysis and area-under-the-curve modeling. Health outcomes included survival, number-needed-to-treat, life expectancy, and quality-adjusted life years. Evaluated treatment strategies included novel agent-based combination therapies, stem cell transplantation and supportive measures. Overall, our review provides a comprehensive summary of modeling studies assessing treatment of MM and highlights decision-analytic modeling as an important tool for health policy decision making. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Facing the challenges of multiscale modelling of bacterial and fungal pathogen–host interactions

PubMed Central

Schleicher, Jana; Conrad, Theresia; Gustafsson, Mika; Cedersund, Gunnar; Guthke, Reinhard

2017-01-01

Abstract Recent and rapidly evolving progress on high-throughput measurement techniques and computational performance has led to the emergence of new disciplines, such as systems medicine and translational systems biology. At the core of these disciplines lies the desire to produce multiscale models: mathematical models that integrate multiple scales of biological organization, ranging from molecular, cellular and tissue models to organ, whole-organism and population scale models. Using such models, hypotheses can systematically be tested. In this review, we present state-of-the-art multiscale modelling of bacterial and fungal infections, considering both the pathogen and host as well as their interaction. Multiscale modelling of the interactions of bacteria, especially Mycobacterium tuberculosis, with the human host is quite advanced. In contrast, models for fungal infections are still in their infancy, in particular regarding infections with the most important human pathogenic fungi, Candida albicans and Aspergillus fumigatus. We reflect on the current availability of computational approaches for multiscale modelling of host–pathogen interactions and point out current challenges. Finally, we provide an outlook for future requirements of multiscale modelling. PMID:26857943

Preservice Secondary Teachers' Conceptions from a Mathematical Modeling Activity and Connections to the Common Core State Standards

ERIC Educational Resources Information Center

Stohlmann, Micah; Maiorca, Cathrine; Olson, Travis A.

2015-01-01

Mathematical modeling is an essential integrated piece of the Common Core State Standards. However, researchers have shown that mathematical modeling activities can be difficult for teachers to implement. Teachers are more likely to implement mathematical modeling activities if they have their own successful experiences with such activities. This…

Investigating and Developing Engineering Students' Mathematical Modelling and Problem-Solving Skills

ERIC Educational Resources Information Center

Wedelin, Dag; Adawi, Tom; Jahan, Tabassum; Andersson, Sven

2015-01-01

How do engineering students approach mathematical modelling problems and how can they learn to deal with such problems? In the context of a course in mathematical modelling and problem solving, and using a qualitative case study approach, we found that the students had little prior experience of mathematical modelling. They were also inexperienced…

Mathematical-Artificial Neural Network Hybrid Model to Predict Roll Force during Hot Rolling of Steel

NASA Astrophysics Data System (ADS)

Rath, S.; Sengupta, P. P.; Singh, A. P.; Marik, A. K.; Talukdar, P.

2013-07-01

Accurate prediction of roll force during hot strip rolling is essential for model based operation of hot strip mills. Traditionally, mathematical models based on theory of plastic deformation have been used for prediction of roll force. In the last decade, data driven models like artificial neural network have been tried for prediction of roll force. Pure mathematical models have accuracy limitations whereas data driven models have difficulty in convergence when applied to industrial conditions. Hybrid models by integrating the traditional mathematical formulations and data driven methods are being developed in different parts of world. This paper discusses the methodology of development of an innovative hybrid mathematical-artificial neural network model. In mathematical model, the most important factor influencing accuracy is flow stress of steel. Coefficients of standard flow stress equation, calculated by parameter estimation technique, have been used in the model. The hybrid model has been trained and validated with input and output data collected from finishing stands of Hot Strip Mill, Bokaro Steel Plant, India. It has been found that the model accuracy has been improved with use of hybrid model, over the traditional mathematical model.

Predictive models of control strategies involved in containing indoor airborne infections.

PubMed

Chen, S-C; Chang, C-F; Liao, C-M

2006-12-01

Recently developed control measure modeling approaches for containing airborne infections, including engineering controls with respiratory protection and public health interventions, are readily amenable to an integrated-scale analysis. Here we show that such models can be derived from an integrated-scale analysis generated from three different types of functional relationship: Wells-Riley mathematical model, competing-risks model, and Von Foerster equation, both of the key epidemiological determinants involved and of the functional connections between them. We examine mathematically the impact of engineering control measures such as enhanced air exchange and air filtration rates with personal masking combined with public health interventions such as vaccination, isolation, and contact tracing in containing the spread of indoor airborne infections including influenza, chickenpox, measles, and severe acute respiratory syndrome (SARS). If enhanced engineering controls could reduce the basic reproductive number (R0) below 1.60 for chickenpox and 3 for measles, our simulations show that in such a prepared response with public health interventions would have a high probability of containing the indoor airborne infections. Combinations of engineering control measures and public health interventions could moderately contain influenza strains with an R0 as high as 4. Our analysis indicates that effective isolation of symptomatic patients with low-efficacy contact tracing is sufficient to control a SARS outbreak. We suggest that a valuable added dimension to public health inventions could be provided by systematically quantifying transmissibility and proportion of asymptomatic infection of indoor airborne infection. Practical Implications We have developed a flexible mathematical model that can help determine the best intervention strategies for containing indoor airborne infections. The approach presented here is scalable and can be extended to include additional control efficacies. If a newly emergent airborne infection should appear, the model could be quickly calibrated to data and intervention options at the early stage of the outbreak. Data could be provided from the field to estimate value of R0, the serial interval between cases, the distributions of the latent, incubation, and infectious periods, case fatality rates, and secondary spread within important mixing groups. The combination of enhanced engineering control measures and assigned effective public health interventions would have a high probability for containing airborne infection.

Transmission Dinamics Model Of Dengue Fever

NASA Astrophysics Data System (ADS)

Debora; Rendy; Rahmi

2018-01-01

Dengue fever is an endemic disease that is transmitted through the Aedes aegypti mosquito vector. The disease is present in more than 100 countries in America, Africa, and Asia, especially tropical countries. Differential equations can be used to represent the spread of dengue virus occurring in time intervals and model in the form of mathematical models. The mathematical model in this study tries to represent the spread of dengue fever based on the data obtained and the assumptions used. The mathematical model used is a mathematical model consisting of Susceptible (S), Infected (I), Viruses (V) subpopulations. The SIV mathematical model is then analyzed to see the solution behaviour of the system.

Mathematical Modeling: Convoying Merchant Ships

ERIC Educational Resources Information Center

Mathews, Susann M.

2004-01-01

This article describes a mathematical model that connects mathematics with social studies. Students use mathematics to model independent versus convoyed ship deployments and sinkings to determine if the British should have convoyed their merchant ships during World War I. During the war, the British admiralty opposed sending merchant ships grouped…

Making the Most of Modeling Tasks

ERIC Educational Resources Information Center

Wernet, Jamie L.; Lawrence, Kevin A.; Gilbertson, Nicholas J.

2015-01-01

While there is disagreement among mathematics educators about some aspects of its meaning, mathematical modeling generally involves taking a real-world scenario and translating it into the mathematical world (Niss, Blum, and Galbraith 2007). The complete modeling process involves describing situations posed in problems with mathematical concepts,…

Modeling and Implementation of Multi-Position Non-Continuous Rotation Gyroscope North Finder.

PubMed

Luo, Jun; Wang, Zhiqian; Shen, Chengwu; Kuijper, Arjan; Wen, Zhuoman; Liu, Shaojin

2016-09-20

Even when the Global Positioning System (GPS) signal is blocked, a rate gyroscope (gyro) north finder is capable of providing the required azimuth reference information to a certain extent. In order to measure the azimuth between the observer and the north direction very accurately, we propose a multi-position non-continuous rotation gyro north finding scheme. Our new generalized mathematical model analyzes the elements that affect the azimuth measurement precision and can thus provide high precision azimuth reference information. Based on the gyro's principle of detecting a projection of the earth rotation rate on its sensitive axis and the proposed north finding scheme, we are able to deduct an accurate mathematical model of the gyro outputs against azimuth with the gyro and shaft misalignments. Combining the gyro outputs model and the theory of propagation of uncertainty, some approaches to optimize north finding are provided, including reducing the gyro bias error, constraining the gyro random error, increasing the number of rotation points, improving rotation angle measurement precision, decreasing the gyro and the shaft misalignment angles. According them, a north finder setup is built and the azimuth uncertainty of 18" is obtained. This paper provides systematic theory for analyzing the details of the gyro north finder scheme from simulation to implementation. The proposed theory can guide both applied researchers in academia and advanced practitioners in industry for designing high precision robust north finder based on different types of rate gyroscopes.

Superstructure-based Design and Optimization of Batch Biodiesel Production Using Heterogeneous Catalysts

NASA Astrophysics Data System (ADS)

Nuh, M. Z.; Nasir, N. F.

2017-08-01

Biodiesel as a fuel comprised of mono alkyl esters of long chain fatty acids derived from renewable lipid feedstock, such as vegetable oil and animal fat. Biodiesel production is complex process which need systematic design and optimization. However, no case study using the process system engineering (PSE) elements which are superstructure optimization of batch process, it involves complex problems and uses mixed-integer nonlinear programming (MINLP). The PSE offers a solution to complex engineering system by enabling the use of viable tools and techniques to better manage and comprehend the complexity of the system. This study is aimed to apply the PSE tools for the simulation of biodiesel process and optimization and to develop mathematical models for component of the plant for case A, B, C by using published kinetic data. Secondly, to determine economic analysis for biodiesel production, focusing on heterogeneous catalyst. Finally, the objective of this study is to develop the superstructure for biodiesel production by using heterogeneous catalyst. The mathematical models are developed by the superstructure and solving the resulting mixed integer non-linear model and estimation economic analysis by using MATLAB software. The results of the optimization process with the objective function of minimizing the annual production cost by batch process from case C is 23.2587 million USD. Overall, the implementation a study of process system engineering (PSE) has optimized the process of modelling, design and cost estimation. By optimizing the process, it results in solving the complex production and processing of biodiesel by batch.

Mathematical model of a gene regulatory network reconciles effects of genetic perturbations on hematopoietic stem cell emergence.

PubMed

Narula, Jatin; Williams, C J; Tiwari, Abhinav; Marks-Bluth, Jonathon; Pimanda, John E; Igoshin, Oleg A

2013-07-15

Interlinked gene regulatory networks (GRNs) are vital for the spatial and temporal control of gene expression during development. The hematopoietic transcription factors (TFs) Scl, Gata2 and Fli1 form one such densely connected GRN which acts as a master regulator of embryonic hematopoiesis. This triad has been shown to direct the specification of the hemogenic endothelium and emergence of hematopoietic stem cells (HSCs) in response to Notch1 and Bmp4-Smad signaling. Here we employ previously published data to construct a mathematical model of this GRN network and use this model to systematically investigate the network dynamical properties. Our model uses a statistical-thermodynamic framework to describe the combinatorial regulation of gene expression and reconciles, mechanistically, several previously published but unexplained results from different genetic perturbation experiments. In particular, our results demonstrate how the interactions of Runx1, an essential hematopoietic TF, with components of the Bmp4 signaling pathway allow it to affect triad activation and acts as a key regulator of HSC emergence. We also explain why heterozygous deletion of this essential TF, Runx1, speeds up the network dynamics leading to accelerated HSC emergence. Taken together our results demonstrate that the triad, a master-level controller of definitive hematopoiesis, is an irreversible bistable switch whose dynamical properties are modulated by Runx1 and components of the Bmp4 signaling pathway. Copyright © 2013 Elsevier Inc. All rights reserved.

Optimized oral cholera vaccine distribution strategies to minimize disease incidence: A mixed integer programming model and analysis of a Bangladesh scenario.

PubMed

Smalley, Hannah K; Keskinocak, Pinar; Swann, Julie; Hinman, Alan

2015-11-17

In addition to improved sanitation, hygiene, and better access to safe water, oral cholera vaccines can help to control the spread of cholera in the short term. However, there is currently no systematic method for determining the best allocation of oral cholera vaccines to minimize disease incidence in a population where the disease is endemic and resources are limited. We present a mathematical model for optimally allocating vaccines in a region under varying levels of demographic and incidence data availability. The model addresses the questions of where, when, and how many doses of vaccines to send. Considering vaccine efficacies (which may vary based on age and the number of years since vaccination), we analyze distribution strategies which allocate vaccines over multiple years. Results indicate that, given appropriate surveillance data, targeting age groups and regions with the highest disease incidence should be the first priority, followed by other groups primarily in order of disease incidence, as this approach is the most life-saving and cost-effective. A lack of detailed incidence data results in distribution strategies which are not cost-effective and can lead to thousands more deaths from the disease. The mathematical model allows for what-if analysis for various vaccine distribution strategies by providing the ability to easily vary parameters such as numbers and sizes of regions and age groups, risk levels, vaccine price, vaccine efficacy, production capacity and budget. Copyright © 2015 Elsevier Ltd. All rights reserved.

A general theory of kinetics and thermodynamics of steady-state copolymerization.

PubMed

Shu, Yao-Gen; Song, Yong-Shun; Ou-Yang, Zhong-Can; Li, Ming

2015-06-17

Kinetics of steady-state copolymerization has been investigated since the 1940s. Irreversible terminal and penultimate models were successfully applied to a number of comonomer systems, but failed for systems where depropagation is significant. Although a general mathematical treatment of the terminal model with depropagation was established in the 1980s, a penultimate model and higher-order terminal models with depropagation have not been systematically studied, since depropagation leads to hierarchically-coupled and unclosed kinetic equations which are hard to solve analytically. In this work, we propose a truncation method to solve the steady-state kinetic equations of any-order terminal models with depropagation in a unified way, by reducing them into closed steady-state equations which give the exact solution of the original kinetic equations. Based on the steady-state equations, we also derive a general thermodynamic equality in which the Shannon entropy of the copolymer sequence is explicitly introduced as part of the free energy dissipation of the whole copolymerization system.

Data-driven modelling of social forces and collective behaviour in zebrafish.

PubMed

Zienkiewicz, Adam K; Ladu, Fabrizio; Barton, David A W; Porfiri, Maurizio; Bernardo, Mario Di

2018-04-14

Zebrafish are rapidly emerging as a powerful model organism in hypothesis-driven studies targeting a number of functional and dysfunctional processes. Mathematical models of zebrafish behaviour can inform the design of experiments, through the unprecedented ability to perform pilot trials on a computer. At the same time, in-silico experiments could help refining the analysis of real data, by enabling the systematic investigation of key neurobehavioural factors. Here, we establish a data-driven model of zebrafish social interaction. Specifically, we derive a set of interaction rules to capture the primary response mechanisms which have been observed experimentally. Contrary to previous studies, we include dynamic speed regulation in addition to turning responses, which together provide attractive, repulsive and alignment interactions between individuals. The resulting multi-agent model provides a novel, bottom-up framework to describe both the spontaneous motion and individual-level interaction dynamics of zebrafish, inferred directly from experimental observations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Improving mathematical problem solving ability through problem-based learning and authentic assessment for the students of Bali State Polytechnic

NASA Astrophysics Data System (ADS)

Darma, I. K.

2018-01-01

This research is aimed at determining: 1) the differences of mathematical problem solving ability between the students facilitated with problem-based learning model and conventional learning model, 2) the differences of mathematical problem solving ability between the students facilitated with authentic and conventional assessment model, and 3) interaction effect between learning and assessment model on mathematical problem solving. The research was conducted in Bali State Polytechnic, using the 2x2 experiment factorial design. The samples of this research were 110 students. The data were collected using a theoretically and empirically-validated test. Instruments were validated by using Aiken’s approach of technique content validity and item analysis, and then analyzed using anova stylistic. The result of the analysis shows that the students facilitated with problem-based learning and authentic assessment models get the highest score average compared to the other students, both in the concept understanding and mathematical problem solving. The result of hypothesis test shows that, significantly: 1) there is difference of mathematical problem solving ability between the students facilitated with problem-based learning model and conventional learning model, 2) there is difference of mathematical problem solving ability between the students facilitated with authentic assessment model and conventional assessment model, and 3) there is interaction effect between learning model and assessment model on mathematical problem solving. In order to improve the effectiveness of mathematics learning, collaboration between problem-based learning model and authentic assessment model can be considered as one of learning models in class.

Influence of Problem-Based Learning Model of Learning to the Mathematical Communication Ability of Students of Grade XI IPA SMAN 14 Padang

NASA Astrophysics Data System (ADS)

Nisa, I. M.

2018-04-01

The ability of mathematical communication is one of the goals of learning mathematics expected to be mastered by students. However, reality in the field found that the ability of mathematical communication the students of grade XI IPA SMA Negeri 14 Padang have not developed optimally. This is evident from the low test results of communication skills mathematically done. One of the factors that causes this happens is learning that has not been fully able to facilitate students to develop mathematical communication skills well. By therefore, to improve students' mathematical communication skills required a model in the learning activities. One of the models learning that can be used is Problem Based learning model Learning (PBL). The purpose of this study is to see whether the ability the students' mathematical communication using the PBL model better than the students' mathematical communication skills of the learning using conventional learning in Class XI IPA SMAN 14 Padang. This research type is quasi experiment with design Randomized Group Only Design. Population in this research that is student of class XI IPA SMAN 14 Padang with sample class XI IPA 3 and class XI IPA 4. Data retrieval is done by using communication skill test mathematically shaped essay. To test the hypothesis used U-Mann test Whitney. Based on the results of data analysis, it can be concluded that the ability mathematical communication of students whose learning apply more PBL model better than the students' mathematical communication skills of their learning apply conventional learning in class XI IPA SMA 14 Padang at α = 0.05. This indicates that the PBL learning model effect on students' mathematical communication ability.

The Real and the Mathematical in Quantum Modeling: From Principles to Models and from Models to Principles

NASA Astrophysics Data System (ADS)

Plotnitsky, Arkady

2017-06-01

The history of mathematical modeling outside physics has been dominated by the use of classical mathematical models, C-models, primarily those of a probabilistic or statistical nature. More recently, however, quantum mathematical models, Q-models, based in the mathematical formalism of quantum theory have become more prominent in psychology, economics, and decision science. The use of Q-models in these fields remains controversial, in part because it is not entirely clear whether Q-models are necessary for dealing with the phenomena in question or whether C-models would still suffice. My aim, however, is not to assess the necessity of Q-models in these fields, but instead to reflect on what the possible applicability of Q-models may tell us about the corresponding phenomena there, vis-à-vis quantum phenomena in physics. In order to do so, I shall first discuss the key reasons for the use of Q-models in physics. In particular, I shall examine the fundamental principles that led to the development of quantum mechanics. Then I shall consider a possible role of similar principles in using Q-models outside physics. Psychology, economics, and decision science borrow already available Q-models from quantum theory, rather than derive them from their own internal principles, while quantum mechanics was derived from such principles, because there was no readily available mathematical model to handle quantum phenomena, although the mathematics ultimately used in quantum did in fact exist then. I shall argue, however, that the principle perspective on mathematical modeling outside physics might help us to understand better the role of Q-models in these fields and possibly to envision new models, conceptually analogous to but mathematically different from those of quantum theory, helpful or even necessary there or in physics itself. I shall suggest one possible type of such models, singularized probabilistic, SP, models, some of which are time-dependent, TDSP-models. The necessity of using such models may change the nature of mathematical modeling in science and, thus, the nature of science, as it happened in the case of Q-models, which not only led to a revolutionary transformation of physics but also opened new possibilities for scientific thinking and mathematical modeling beyond physics.

A Primer for Mathematical Modeling

ERIC Educational Resources Information Center

Sole, Marla

2013-01-01

With the implementation of the National Council of Teachers of Mathematics recommendations and the adoption of the Common Core State Standards for Mathematics, modeling has moved to the forefront of K-12 education. Modeling activities not only reinforce purposeful problem-solving skills, they also connect the mathematics students learn in school…

Strategies to Support Students' Mathematical Modeling

ERIC Educational Resources Information Center

Jung, Hyunyi

2015-01-01

An important question for mathematics teachers is this: "How can we help students learn mathematics to solve everyday problems, rather than teaching them only to memorize rules and practice mathematical procedures?" Teaching students using modeling activities can help them learn mathematics in real-world problem-solving situations that…

Mathematical Modeling in the High School Curriculum

ERIC Educational Resources Information Center

Hernández, Maria L.; Levy, Rachel; Felton-Koestler, Mathew D.; Zbiek, Rose Mary

2016-01-01

In 2015, mathematics leaders and instructors from the Society for Industrial and Applied Mathematics (SIAM) and the Consortium for Mathematics and Its Applications (COMAP), with input from NCTM, came together to write the "Guidelines for Assessment and Instruction in Mathematical Modeling Education" (GAIMME) report as a resource for…

The Effect of Instruction through Mathematical Modelling on Modelling Skills of Prospective Elementary Mathematics Teachers

ERIC Educational Resources Information Center

Ciltas, Alper; Isik, Ahmet

2013-01-01

The aim of this study was to examine the modelling skills of prospective elementary mathematics teachers who were studying the mathematical modelling method. The research study group was composed of 35 prospective teachers. The exploratory case analysis method was used in the study. The data were obtained via semi-structured interviews and a…

[SciELO Public Health: the performance of Cadernos de Saúde Pública and Revista de Saúde Pública].

PubMed

Barata, Rita Barradas

2007-12-01

The aim of this paper was to analyze two Brazilian scientific journals included in the SciELO Library of Public Health, using a group of bibliometric indicators and scrutinizing the articles most viewed. Cadernos de Saúde Pública was accessed 3,743.59 times per month, with an average of 30.31 citations per article. The 50 articles most viewed (6.72 to 524.5 views) were mostly published in Portuguese (92%). 42% were theoretical essays, 20% surveys, and 16% descriptive studies. 42% used argumentative techniques, 34% quantitative techniques, 18% qualitative techniques, and 6% mathematical modeling. The most common themes were: health and work (50%), epidemiology (22%), and environmental health (8%). Revista de Saúde Pública was accessed 1,590.97 times per month, with an average of 26.27 citations per article. The 50 articles most viewed (7.33 and 56.50 views) were all published in Portuguese: 46% were surveys, 14% databases analysis, and 12% systematic reviews. Quantitative techniques were adopted in 66% of such articles, while mathematical modeling was the same as observed in Cadernos de Saúde Pública, as were qualitative techniques. The most common themes were health services organization (22%), nutrition (22%), health and work (18%), epidemiology (12%), and environmental health (12%).

Systematic Interventions for Teaching Ratios

ERIC Educational Resources Information Center

Hunter, Amy E.; Bush, Sarah B.; Karp, Karen

2014-01-01

Mathematics interventions for struggling students supplement regular instruction and are frequently implemented through computer programs and activity sheet practice (Swanson et al. 2012). However, students with foundational misunderstandings do not benefit from additional drill and practice alone. Instead, interventions that balance concepts with…

Elementary Applications of Information Theory in Various Fields of Science and Technology.

ERIC Educational Resources Information Center

Sexl, Roman U.

1979-01-01

Discusses how the concept of information is fundamental to many branches of science, technology, and mathematics and how a systematic use of the information concept can help to bridge the gap between different subjects in school. (HM)

Mathematical Modeling: Challenging the Figured Worlds of Elementary Mathematics

ERIC Educational Resources Information Center

Wickstrom, Megan H.

2017-01-01

This article is a report on a teacher study group that focused on three elementary teachers' perceptions of mathematical modeling in contrast to typical mathematics instruction. Through the theoretical lens of figured worlds, I discuss how mathematics instruction was conceptualized across the classrooms in terms of artifacts, discourse, and…

Mathematics Teachers' Ideas about Mathematical Models: A Diverse Landscape

ERIC Educational Resources Information Center

Bautista, Alfredo; Wilkerson-Jerde, Michelle H.; Tobin, Roger G.; Brizuela, Bárbara M.

2014-01-01

This paper describes the ideas that mathematics teachers (grades 5-9) have regarding mathematical models of real-world phenomena, and explores how teachers' ideas differ depending on their educational background. Participants were 56 United States in-service mathematics teachers. We analyzed teachers' written responses to three open-ended…

Mathematical Modelling at Secondary School: The MACSI-Clongowes Wood College Experience

ERIC Educational Resources Information Center

Charpin, J. P. F.; O'Hara, S.; Mackey, D.

2013-01-01

In Ireland, to encourage the study of STEM (science, technology, engineering and mathematics) subjects and particularly mathematics, the Mathematics Applications Consortium for Science and Industry (MACSI) and Clongowes Wood College (County Kildare, Ireland) organized a mathematical modelling workshop for senior cycle secondary school students.…

Mathematical models of thermoregulation and heat transfer in mammals. A compendium of research

NASA Technical Reports Server (NTRS)

Shitzer, A.

1972-01-01

An annotated compendium on mathematical modeling of mammal thermoregulation systems is presented. Author abstracts, tables containing the more used mathematical models, solutions to these models, and each thermoregulation mechanism considered are included.

Ocular hemodynamics and glaucoma: the role of mathematical modeling.

PubMed

Harris, Alon; Guidoboni, Giovanna; Arciero, Julia C; Amireskandari, Annahita; Tobe, Leslie A; Siesky, Brent A

2013-01-01

To discuss the role of mathematical modeling in studying ocular hemodynamics, with a focus on glaucoma. We reviewed recent literature on glaucoma, ocular blood flow, autoregulation, the optic nerve head, and the use of mathematical modeling in ocular circulation. Many studies suggest that alterations in ocular hemodynamics play a significant role in the development, progression, and incidence of glaucoma. Although there is currently a limited number of studies involving mathematical modeling of ocular blood flow, regulation, and diseases (such as glaucoma), preliminary modeling work shows the potential of mathematical models to elucidate the mechanisms that contribute most significantly to glaucoma progression. Mathematical modeling is a useful tool when used synergistically with clinical and laboratory data in the study of ocular blood flow and glaucoma. The development of models to investigate the relationship between ocular hemodynamic alterations and glaucoma progression will provide a unique and useful method for studying the pathophysiology of glaucoma.

Comparison of learning models based on mathematics logical intelligence in affective domain

NASA Astrophysics Data System (ADS)

Widayanto, Arif; Pratiwi, Hasih; Mardiyana

2018-04-01

The purpose of this study was to examine the presence or absence of different effects of multiple treatments (used learning models and logical-mathematical intelligence) on the dependent variable (affective domain of mathematics). This research was quasi experimental using 3x3 of factorial design. The population of this research was VIII grade students of junior high school in Karanganyar under the academic year 2017/2018. Data collected in this research was analyzed by two ways analysis of variance with unequal cells using 5% of significance level. The result of the research were as follows: (1) Teaching and learning with model TS lead to better achievement in affective domain than QSH, teaching and learning with model QSH lead to better achievement in affective domain than using DI; (2) Students with high mathematics logical intelligence have better achievement in affective domain than students with low mathematics logical intelligence have; (3) In teaching and learning mathematics using learning model TS, students with moderate mathematics logical intelligence have better achievement in affective domain than using DI; and (4) In teaching and learning mathematics using learning model TS, students with low mathematics logical intelligence have better achievement in affective domain than using QSH and DI.

Effect of drug law enforcement on drug market violence: a systematic review.

PubMed

Werb, Dan; Rowell, Greg; Guyatt, Gordon; Kerr, Thomas; Montaner, Julio; Wood, Evan

2011-03-01

Violence is amongst the primary concerns of communities around the world and research has demonstrated links between violence and the illicit drug trade, particularly in urban settings. Given the growing emphasis on evidence-based policy-making, and the ongoing severe drug market violence in Mexico and other settings, we conducted a systematic review to examine the impacts of drug law enforcement on drug market violence. We conducted a systematic review using Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) guidelines. Specifically, we undertook a search of English language electronic databases (Academic Search Complete, PubMed, PsycINFO, EMBASE, Web of Science, Sociological Abstracts, Social Service Abstracts, PAIS International and Lexis-Nexis), the Internet (Google, Google Scholar), and article reference lists, from database inception to January 24, 2011. Overall, 15 studies were identified that evaluated the impact of drug law enforcement on drug market violence, including 11 (73%) longitudinal analyses using linear regression, 2 (13%) mathematical drug market models, and 2 (13%) qualitative studies. Fourteen (93%) studies reported an adverse impact of drug law enforcement on levels of violence. Ten of the 11 (91%) studies employing longitudinal qualitative analyses found a significant association between drug law enforcement and drug market violence. Our findings suggest that increasing drug law enforcement is unlikely to reduce drug market violence. Instead, the existing evidence base suggests that gun violence and high homicide rates may be an inevitable consequence of drug prohibition and that disrupting drug markets can paradoxically increase violence. In this context, and since drug prohibition has not meaningfully reduced drug supply, alternative regulatory models will be required if drug supply and drug market violence are to be meaningfully reduced. Copyright © 2011 Elsevier B.V. All rights reserved.

The impact of mathematical models of teaching materials on square and rectangle concepts to improve students' mathematical connection ability and mathematical disposition in middle school

NASA Astrophysics Data System (ADS)

Afrizal, Irfan Mufti; Dachlan, Jarnawi Afghani

2017-05-01

The aim of this study was to determine design of mathematical models of teaching materials to improve students' mathematical connection ability and mathematical disposition in middle school through experimental studies. The design in this study was quasi-experimental with non-equivalent control group type. This study consisted of two phases, the first phase was identify students' learning obstacle on square and rectangle concepts to obtain the appropriate design of teaching materials, beside that there were internalization of the values or characters expected to appear on students through the teaching materials. Second phase was experiments on the effectiveness and efficiency of mathematical models of teaching materials to improve students' mathematical connection ability and mathematical disposition. The result of this study are 1) Students' learning obstacle that have identified was categorized as an epistemological obstacle. 2) The improvement of students' mathematical connection ability and mathematical disposition who used mathematical teaching materials is better than the students who used conventional learning.

Mathematical models for plant-herbivore interactions

USGS Publications Warehouse

Feng, Zhilan; DeAngelis, Donald L.

2017-01-01

Mathematical Models of Plant-Herbivore Interactions addresses mathematical models in the study of practical questions in ecology, particularly factors that affect herbivory, including plant defense, herbivore natural enemies, and adaptive herbivory, as well as the effects of these on plant community dynamics. The result of extensive research on the use of mathematical modeling to investigate the effects of plant defenses on plant-herbivore dynamics, this book describes a toxin-determined functional response model (TDFRM) that helps explains field observations of these interactions. This book is intended for graduate students and researchers interested in mathematical biology and ecology.

Dealing with dissatisfaction in mathematical modelling to integrate QFD and Kano’s model

NASA Astrophysics Data System (ADS)

Retno Sari Dewi, Dian; Debora, Joana; Edy Sianto, Martinus

2017-12-01

The purpose of the study is to implement the integration of Quality Function Deployment (QFD) and Kano’s Model into mathematical model. Voice of customer data in QFD was collected using questionnaire and the questionnaire was developed based on Kano’s model. Then the operational research methodology was applied to build the objective function and constraints in the mathematical model. The relationship between voice of customer and engineering characteristics was modelled using linier regression model. Output of the mathematical model would be detail of engineering characteristics. The objective function of this model is to maximize satisfaction and minimize dissatisfaction as well. Result of this model is 62% .The major contribution of this research is to implement the existing mathematical model to integrate QFD and Kano’s Model in the case study of shoe cabinet.

Minimizing systematic errors from atmospheric multiple scattering and satellite viewing geometry in coastal zone color scanner level IIA imagery

NASA Technical Reports Server (NTRS)

Martin, D. L.; Perry, M. J.

1994-01-01

Water-leaving radiances and phytoplankton pigment concentrations are calculated from coastal zone color scanner (CZCS) radiance measurements by removing atmospheric Rayleigh and aerosol radiances from the total radiance signal measured at the satellite. The single greatest source of error in CZCS atmospheric correction algorithms in the assumption that these Rayleigh and aerosol radiances are separable. Multiple-scattering interactions between Rayleigh and aerosol components cause systematic errors in calculated aerosol radiances, and the magnitude of these errors is dependent on aerosol type and optical depth and on satellite viewing geometry. A technique was developed which extends the results of previous radiative transfer modeling by Gordon and Castano to predict the magnitude of these systematic errors for simulated CZCS orbital passes in which the ocean is viewed through a modeled, physically realistic atmosphere. The simulated image mathematically duplicates the exact satellite, Sun, and pixel locations of an actual CZCS image. Errors in the aerosol radiance at 443 nm are calculated for a range of aerosol optical depths. When pixels in the simulated image exceed an error threshhold, the corresponding pixels in the actual CZCS image are flagged and excluded from further analysis or from use in image compositing or compilation of pigment concentration databases. Studies based on time series analyses or compositing of CZCS imagery which do not address Rayleigh-aerosol multiple scattering should be interpreted cautiously, since the fundamental assumption used in their atmospheric correction algorithm is flawed.

Striking a Balance: Students' Tendencies to Oversimplify or Overcomplicate in Mathematical Modeling

ERIC Educational Resources Information Center

Gould, Heather; Wasserman, Nicholas H.

2014-01-01

With the adoption of the "Common Core State Standards for Mathematics" (CCSSM), the process of mathematical modeling has been given increased attention in mathematics education. This article reports on a study intended to inform the implementation of modeling in classroom contexts by examining students' interactions with the process of…

Attitudes of Pre-Service Mathematics Teachers towards Modelling: A South African Inquiry

ERIC Educational Resources Information Center

Jacobs, Gerrie J.; Durandt, Rina

2017-01-01

This study explores the attitudes of mathematics pre-service teachers, based on their initial exposure to a model-eliciting challenge. The new Curriculum and Assessment Policy Statement determines that mathematics students should be able to identify, investigate and solve problems via modelling. The unpreparedness of mathematics teachers in…

Achilles and the tortoise: Some caveats to mathematical modeling in biology.

PubMed

Gilbert, Scott F

2018-01-31

Mathematical modeling has recently become a much-lauded enterprise, and many funding agencies seek to prioritize this endeavor. However, there are certain dangers associated with mathematical modeling, and knowledge of these pitfalls should also be part of a biologist's training in this set of techniques. (1) Mathematical models are limited by known science; (2) Mathematical models can tell what can happen, but not what did happen; (3) A model does not have to conform to reality, even if it is logically consistent; (4) Models abstract from reality, and sometimes what they eliminate is critically important; (5) Mathematics can present a Platonic ideal to which biologically organized matter strives, rather than a trial-and-error bumbling through evolutionary processes. This "Unity of Science" approach, which sees biology as the lowest physical science and mathematics as the highest science, is part of a Western belief system, often called the Great Chain of Being (or Scala Natura), that sees knowledge emerge as one passes from biology to chemistry to physics to mathematics, in an ascending progression of reason being purification from matter. This is also an informal model for the emergence of new life. There are now other informal models for integrating development and evolution, but each has its limitations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Automatic mathematical modeling for real time simulation program (AI application)

NASA Technical Reports Server (NTRS)

Wang, Caroline; Purinton, Steve

1989-01-01

A methodology is described for automatic mathematical modeling and generating simulation models. The major objective was to create a user friendly environment for engineers to design, maintain, and verify their models; to automatically convert the mathematical models into conventional code for computation; and finally, to document the model automatically.

Microstructural and mechanical characterization of scarred vocal folds.

PubMed

Heris, Hossein K; Miri, Amir K; Ghattamaneni, Nageswara R; Li, Nicole Y K; Thibeault, Susan L; Wiseman, Paul W; Mongeau, Luc

2015-02-26

The goal of this study was to characterize the vocal folds microstructure and elasticity using nonlinear laser scanning microscopy and atomic force microscopy-based indentation, respectively. As a pilot study, the vocal folds of fourteen rats were unilaterally injured by full removal of lamina propria; the uninjured folds of the same animals served as controls. The area fraction of collagen fibrils was found to be greater in scarred tissues two months after injury than the uninjured controls. A novel mathematical model was also proposed to relate collagen concentration and tissue bulk modulus. This work presents a first step towards systematic investigation of microstructural and mechanical characteristics in scarred vocal fold tissue. Copyright © 2015 Elsevier Ltd. All rights reserved.

Use of symbolic computation in robotics education

NASA Technical Reports Server (NTRS)

Vira, Naren; Tunstel, Edward

1992-01-01

An application of symbolic computation in robotics education is described. A software package is presented which combines generality, user interaction, and user-friendliness with the systematic usage of symbolic computation and artificial intelligence techniques. The software utilizes MACSYMA, a LISP-based symbolic algebra language, to automatically generate closed-form expressions representing forward and inverse kinematics solutions, the Jacobian transformation matrices, robot pose error-compensation models equations, and Lagrange dynamics formulation for N degree-of-freedom, open chain robotic manipulators. The goal of such a package is to aid faculty and students in the robotics course by removing burdensome tasks of mathematical manipulations. The software package has been successfully tested for its accuracy using commercially available robots.

The Effects of a Tier 3 Intervention on the Mathematics Performance of Second Grade Students With Severe Mathematics Difficulties.

PubMed

Bryant, Brian R; Bryant, Diane Pedrotty; Porterfield, Jennifer; Dennis, Minyi Shih; Falcomata, Terry; Valentine, Courtney; Brewer, Chelsea; Bell, Kathy

2016-01-01

The purpose of this study was to determine the effectiveness of a systematic, explicit, intensive Tier 3 (tertiary) intervention on the mathematics performance of students in second grade with severe mathematics difficulties. A multiple-baseline design across groups of participants showed improved mathematics performance on number and operations concepts and procedures, which are the foundation for later mathematics success. In the previous year, 12 participants had experienced two doses (first and second semesters) of a Tier 2 intervention. In second grade, the participants continued to demonstrate low performance, falling below the 10th percentile on a researcher-designed universal screener and below the 16th percentile on a distal measure, thus qualifying for the intensive intervention. A project interventionist, who met with the students 5 days a week for 10 weeks (9 weeks for one group), conducted the intensive intervention. The intervention employed more intensive instructional design features than the previous Tier 2 secondary instruction, and also included weekly games to reinforce concepts and skills from the lessons. Spring results showed significantly improved mathematics performance (scoring at or above the 25th percentile) for most of the students, thus making them eligible to exit the Tier 3 intervention. © Hammill Institute on Disabilities 2014.

How to build a course in mathematical-biological modeling: content and processes for knowledge and skill.

PubMed

Hoskinson, Anne-Marie

2010-01-01

Biological problems in the twenty-first century are complex and require mathematical insight, often resulting in mathematical models of biological systems. Building mathematical-biological models requires cooperation among biologists and mathematicians, and mastery of building models. A new course in mathematical modeling presented the opportunity to build both content and process learning of mathematical models, the modeling process, and the cooperative process. There was little guidance from the literature on how to build such a course. Here, I describe the iterative process of developing such a course, beginning with objectives and choosing content and process competencies to fulfill the objectives. I include some inductive heuristics for instructors seeking guidance in planning and developing their own courses, and I illustrate with a description of one instructional model cycle. Students completing this class reported gains in learning of modeling content, the modeling process, and cooperative skills. Student content and process mastery increased, as assessed on several objective-driven metrics in many types of assessments.

Governing Laws of Complex System Predictability under Co-evolving Uncertainty Sources: Theory and Nonlinear Geophysical Applications

NASA Astrophysics Data System (ADS)

Perdigão, R. A. P.

2017-12-01

Predictability assessments are traditionally made on a case-by-case basis, often by running the particular model of interest with randomly perturbed initial/boundary conditions and parameters, producing computationally expensive ensembles. These approaches provide a lumped statistical view of uncertainty evolution, without eliciting the fundamental processes and interactions at play in the uncertainty dynamics. In order to address these limitations, we introduce a systematic dynamical framework for predictability assessment and forecast, by analytically deriving governing equations of predictability in terms of the fundamental architecture of dynamical systems, independent of any particular problem under consideration. The framework further relates multiple uncertainty sources along with their coevolutionary interplay, enabling a comprehensive and explicit treatment of uncertainty dynamics along time, without requiring the actual model to be run. In doing so, computational resources are freed and a quick and effective a-priori systematic dynamic evaluation is made of predictability evolution and its challenges, including aspects in the model architecture and intervening variables that may require optimization ahead of initiating any model runs. It further brings out universal dynamic features in the error dynamics elusive to any case specific treatment, ultimately shedding fundamental light on the challenging issue of predictability. The formulated approach, framed with broad mathematical physics generality in mind, is then implemented in dynamic models of nonlinear geophysical systems with various degrees of complexity, in order to evaluate their limitations and provide informed assistance on how to optimize their design and improve their predictability in fundamental dynamical terms.

Effect of cephalometer misalignment on calculations of facial asymmetry.

PubMed

Lee, Ki-Heon; Hwang, Hyeon-Shik; Curry, Sean; Boyd, Robert L; Norris, Kevin; Baumrind, Sheldon

2007-07-01

In this study, we evaluated errors introduced into the interpretation of facial asymmetry on posteroanterior (PA) cephalograms due to malpositioning of the x-ray emitter focal spot. We tested the hypothesis that horizontal displacements of the emitter from its ideal position would produce systematic displacements of skull landmarks that could be fully accounted for by the rules of projective geometry alone. A representative dry skull with 22 metal markers was used to generate a series of PA images from different emitter positions by using a fully calibrated stereo cephalometer. Empirical measurements of the resulting cephalograms were compared with mathematical predictions based solely on geometric rules. The empirical measurements matched the mathematical predictions within the limits of measurement error (x= 0.23 mm), thus supporting the hypothesis. Based upon this finding, we generated a completely symmetrical mathematical skull and calculated the expected errors for focal spots of several different magnitudes. Quantitative data were computed for focal spot displacements of different magnitudes. Misalignment of the x-ray emitter focal spot introduces systematic errors into the interpretation of facial asymmetry on PA cephalograms. For misalignments of less than 20 mm, the effect is small in individual cases. However, misalignments as small as 10 mm can introduce spurious statistical findings of significant asymmetry when mean values for large groups of PA images are evaluated.

Systematic misestimation of cell subpopulations by flow cytometry: a mathematical analysis.

PubMed

Petrunkina, A M; Harrison, R A P

2010-04-15

Various sources of variability in flow cytometric determination of cell concentration have previously been investigated with respect to andrologic applications. Although common aspects related to the variation between samples, variation between operators, and accuracy have been extensively studied, specific sources of false-count estimation have found less attention. In particular, a major and well-recognized source of misestimation of cell counts (i.e., contamination of the sample by non-sperm particles) has not to date been characterized in detail. We show here by means of original mathematical research that not only the cell counts but also the percentages of cells expressing different fluorescence patterns are affected by the presence of alien particles often neglected in studies involving flow cytometric characterization. We demonstrate that there is a systematic overestimation in the proportion of unstained (viable) cells detected by flow cytometry in cases where the non-sperm particles are not excluded from analysis by additional identification other than light-scatter characteristics. Moreover, we provide an exact mathematical estimate for the magnitude of this overestimation, and we discuss the consequences for diagnostic applications and studies on sperm physiology, specifically for studies on sperm capacitation and evaluation of cryopreserved semen. Finally, equations are derived for the correction of the flow cytometric values for use in practical applications. Copyright 2010 Elsevier Inc. All rights reserved.

Think Pair Share Using Realistic Mathematics Education Approach in Geometry Learning

NASA Astrophysics Data System (ADS)

Afthina, H.; Mardiyana; Pramudya, I.

2017-09-01

This research aims to determine the impact of mathematics learning applying Think Pair Share (TPS) using Realistic Mathematics Education (RME) viewed from mathematical-logical intelligence in geometry learning. Method that used in this research is quasi experimental research The result of this research shows that (1) mathematics achievement applying TPS using RME approach gives a better result than those applying direct learning model; (2) students with high mathematical-logical intelligence can reach a better mathematics achievement than those with average and low one, whereas students with average mathematical-logical intelligence can reach a better achievement than those with low one; (3) there is no interaction between learning model and the level of students’ mathematical-logical intelligence in giving a mathematics achievement. The impact of this research is that TPS model using RME approach can be applied in mathematics learning so that students can learn more actively and understand the material more, and mathematics learning become more meaningful. On the other hand, internal factors of students must become a consideration toward the success of students’ mathematical achievement particularly in geometry material.

Mathematical foundations of hybrid data assimilation from a synchronization perspective

NASA Astrophysics Data System (ADS)

Penny, Stephen G.

2017-12-01

The state-of-the-art data assimilation methods used today in operational weather prediction centers around the world can be classified as generalized one-way coupled impulsive synchronization. This classification permits the investigation of hybrid data assimilation methods, which combine dynamic error estimates of the system state with long time-averaged (climatological) error estimates, from a synchronization perspective. Illustrative results show how dynamically informed formulations of the coupling matrix (via an Ensemble Kalman Filter, EnKF) can lead to synchronization when observing networks are sparse and how hybrid methods can lead to synchronization when those dynamic formulations are inadequate (due to small ensemble sizes). A large-scale application with a global ocean general circulation model is also presented. Results indicate that the hybrid methods also have useful applications in generalized synchronization, in particular, for correcting systematic model errors.

Low cost digital photogrammetry: From the extraction of point clouds by SFM technique to 3D mathematical modeling

NASA Astrophysics Data System (ADS)

Michele, Mangiameli; Giuseppe, Mussumeci; Salvatore, Zito

2017-07-01

The Structure From Motion (SFM) is a technique applied to a series of photographs of an object that returns a 3D reconstruction made up by points in the space (point clouds). This research aims at comparing the results of the SFM approach with the results of a 3D laser scanning in terms of density and accuracy of the model. The experience was conducted by detecting several architectural elements (walls and portals of historical buildings) both with a 3D laser scanner of the latest generation and an amateur photographic camera. The point clouds acquired by laser scanner and those acquired by the photo camera have been systematically compared. In particular we present the experience carried out on the "Don Diego Pappalardo Palace" site in Pedara (Catania, Sicily).

Mathematical foundations of hybrid data assimilation from a synchronization perspective.

PubMed

Penny, Stephen G

2017-12-01

The state-of-the-art data assimilation methods used today in operational weather prediction centers around the world can be classified as generalized one-way coupled impulsive synchronization. This classification permits the investigation of hybrid data assimilation methods, which combine dynamic error estimates of the system state with long time-averaged (climatological) error estimates, from a synchronization perspective. Illustrative results show how dynamically informed formulations of the coupling matrix (via an Ensemble Kalman Filter, EnKF) can lead to synchronization when observing networks are sparse and how hybrid methods can lead to synchronization when those dynamic formulations are inadequate (due to small ensemble sizes). A large-scale application with a global ocean general circulation model is also presented. Results indicate that the hybrid methods also have useful applications in generalized synchronization, in particular, for correcting systematic model errors.

Preserving Pelicans with Models That Make Sense

ERIC Educational Resources Information Center

Moore, Tamara J.; Doerr, Helen M.; Glancy, Aran W.; Ntow, Forster D.

2015-01-01

Getting students to think deeply about mathematical concepts is not an easy job, which is why we often use problem-solving tasks to engage students in higher-level mathematical thinking. Mathematical modeling, one of the mathematical practices found in the Common Core State Standards for Mathematics (CCSSM), is a type of problem solving that can…

Two Project-Based Strategies in an Interdisciplinary Mathematical Modeling in Biology Course

ERIC Educational Resources Information Center

Ludwig, Patrice; Tongen, Anthony; Walton, Brian

2018-01-01

James Madison University faculty team-teach an interdisciplinary mathematical modeling course for mathematics and biology students. We have used two different project-based approaches to emphasize the mathematical concepts taught in class, while also exposing students to new areas of mathematics not formally covered in class. The first method…

Users manual for an expert system (HSPEXP) for calibration of the hydrological simulation program; Fortran

USGS Publications Warehouse

Lumb, A.M.; McCammon, R.B.; Kittle, J.L.

1994-01-01

Expert system software was developed to assist less experienced modelers with calibration of a watershed model and to facilitate the interaction between the modeler and the modeling process not provided by mathematical optimization. A prototype was developed with artificial intelligence software tools, a knowledge engineer, and two domain experts. The manual procedures used by the domain experts were identified and the prototype was then coded by the knowledge engineer. The expert system consists of a set of hierarchical rules designed to guide the calibration of the model through a systematic evaluation of model parameters. When the prototype was completed and tested, it was rewritten for portability and operational use and was named HSPEXP. The watershed model Hydrological Simulation Program--Fortran (HSPF) is used in the expert system. This report is the users manual for HSPEXP and contains a discussion of the concepts and detailed steps and examples for using the software. The system has been tested on watersheds in the States of Washington and Maryland, and the system correctly identified the model parameters to be adjusted and the adjustments led to improved calibration.

A cluster expansion model for predicting activation barrier of atomic processes

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

Rehman, Tafizur; Jaipal, M.; Chatterjee, Abhijit, E-mail: achatter@iitk.ac.in

2013-06-15

We introduce a procedure based on cluster expansion models for predicting the activation barrier of atomic processes encountered while studying the dynamics of a material system using the kinetic Monte Carlo (KMC) method. Starting with an interatomic potential description, a mathematical derivation is presented to show that the local environment dependence of the activation barrier can be captured using cluster interaction models. Next, we develop a systematic procedure for training the cluster interaction model on-the-fly, which involves: (i) obtaining activation barriers for handful local environments using nudged elastic band (NEB) calculations, (ii) identifying the local environment by analyzing the NEBmore » results, and (iii) estimating the cluster interaction model parameters from the activation barrier data. Once a cluster expansion model has been trained, it is used to predict activation barriers without requiring any additional NEB calculations. Numerical studies are performed to validate the cluster expansion model by studying hop processes in Ag/Ag(100). We show that the use of cluster expansion model with KMC enables efficient generation of an accurate process rate catalog.« less

Mathematical models of behavior of individual animals.

PubMed

Tsibulsky, Vladimir L; Norman, Andrew B

2007-01-01

This review is focused on mathematical modeling of behaviors of a whole organism with special emphasis on models with a clearly scientific approach to the problem that helps to understand the mechanisms underlying behavior. The aim is to provide an overview of old and contemporary mathematical models without complex mathematical details. Only deterministic and stochastic, but not statistical models are reviewed. All mathematical models of behavior can be divided into two main classes. First, models that are based on the principle of teleological determinism assume that subjects choose the behavior that will lead them to a better payoff in the future. Examples are game theories and operant behavior models both of which are based on the matching law. The second class of models are based on the principle of causal determinism, which assume that subjects do not choose from a set of possibilities but rather are compelled to perform a predetermined behavior in response to specific stimuli. Examples are perception and discrimination models, drug effects models and individual-based population models. A brief overview of the utility of each mathematical model is provided for each section.

Problem Posing and Solving with Mathematical Modeling

ERIC Educational Resources Information Center

English, Lyn D.; Fox, Jillian L.; Watters, James J.

2005-01-01

Mathematical modeling is explored as both problem posing and problem solving from two perspectives, that of the child and the teacher. Mathematical modeling provides rich learning experiences for elementary school children and their teachers.

Building Mathematical Models of Simple Harmonic and Damped Motion.

ERIC Educational Resources Information Center

Edwards, Thomas

1995-01-01

By developing a sequence of mathematical models of harmonic motion, shows that mathematical models are not right or wrong, but instead are better or poorer representations of the problem situation. (MKR)

iSTEM: Tinkering with Buoyancy

ERIC Educational Resources Information Center

Lee, Mi Yeon

2014-01-01

In the technology-rich twenty-first century, students are required to actively construct their knowledge and collaboratively engage in problem solving by using such skills as adaptability, communication, self-management, and systematic thinking. In accordance with this necessity, science, technology, engineering, and mathematics (STEM) education…

Taking the mystery out of mathematical model applications to karst aquifers—A primer

USGS Publications Warehouse

Kuniansky, Eve L.

2014-01-01

Advances in mathematical model applications toward the understanding of the complex flow, characterization, and water-supply management issues for karst aquifers have occurred in recent years. Different types of mathematical models can be applied successfully if appropriate information is available and the problems are adequately identified. The mathematical approaches discussed in this paper are divided into three major categories: 1) distributed parameter models, 2) lumped parameter models, and 3) fitting models. The modeling approaches are described conceptually with examples (but without equations) to help non-mathematicians understand the applications.

Secondary Teachers' Conceptions and Practices of Assessment Models: The Case for Mathematics Teachers in Jordan

ERIC Educational Resources Information Center

Al Duwairi, Ahmed

2013-01-01

This study aimed at investigating the extent to which secondary schools mathematics teachers practice to assessment models in their mathematics teaching and learning. Definitely, the study aimed at answering the following questions: (1) To what extent do secondary schools mathematics teachers practice each of the assessment models in their…

Reality-Theoretical Models-Mathematics: A Ternary Perspective on Physics Lessons in Upper-Secondary School

ERIC Educational Resources Information Center

Hansson, Lena; Hansson, Örjan; Juter, Kristina; Redfors, Andreas

2015-01-01

This article discusses the role of mathematics during physics lessons in upper-secondary school. Mathematics is an inherent part of theoretical models in physics and makes powerful predictions of natural phenomena possible. Ability to use both theoretical models and mathematics is central in physics. This paper takes as a starting point that the…

Mathematics Student Teachers' Modelling Approaches While Solving the Designed Esme Rug Problem

ERIC Educational Resources Information Center

Hidiroglu, Çaglar Naci; Dede, Ayse Tekin; Ünver, Semiha Kula; Güzel, Esra Bukova

2017-01-01

The purpose of the study is to analyze the mathematics student teachers' solutions on the Esme Rug Problem through 7-stage mathematical modelling process. This problem was designed by the researchers by considering the modelling problems' main properties. The study was conducted with twenty one secondary mathematics student teachers. The data were…

The use of mathematical models in teaching wastewater treatment engineering.

PubMed

Morgenroth, E; Arvin, E; Vanrolleghem, P

2002-01-01

Mathematical modeling of wastewater treatment processes has become increasingly popular in recent years. To prepare students for their future careers, environmental engineering education should provide students with sufficient background and experiences to understand and apply mathematical models efficiently and responsibly. Approaches for introducing mathematical modeling into courses on wastewater treatment engineering are discussed depending on the learning objectives, level of the course and the time available.

A queueing theory description of fat-tailed price returns in imperfect financial markets

NASA Astrophysics Data System (ADS)

Lamba, H.

2010-09-01

In a financial market, for agents with long investment horizons or at times of severe market stress, it is often changes in the asset price that act as the trigger for transactions or shifts in investment position. This suggests the use of price thresholds to simulate agent behavior over much longer timescales than are currently used in models of order-books. We show that many phenomena, routinely ignored in efficient market theory, can be systematically introduced into an otherwise efficient market, resulting in models that robustly replicate the most important stylized facts. We then demonstrate a close link between such threshold models and queueing theory, with large price changes corresponding to the busy periods of a single-server queue. The distribution of the busy periods is known to have excess kurtosis and non-exponential decay under various assumptions on the queue parameters. Such an approach may prove useful in the development of mathematical models for rapid deleveraging and panics in financial markets, and the stress-testing of financial institutions.

Optimization and analysis of large chemical kinetic mechanisms using the solution mapping method - Combustion of methane

NASA Technical Reports Server (NTRS)

Frenklach, Michael; Wang, Hai; Rabinowitz, Martin J.

1992-01-01

A method of systematic optimization, solution mapping, as applied to a large-scale dynamic model is presented. The basis of the technique is parameterization of model responses in terms of model parameters by simple algebraic expressions. These expressions are obtained by computer experiments arranged in a factorial design. The developed parameterized responses are then used in a joint multiparameter multidata-set optimization. A brief review of the mathematical background of the technique is given. The concept of active parameters is discussed. The technique is applied to determine an optimum set of parameters for a methane combustion mechanism. Five independent responses - comprising ignition delay times, pre-ignition methyl radical concentration profiles, and laminar premixed flame velocities - were optimized with respect to thirteen reaction rate parameters. The numerical predictions of the optimized model are compared to those computed with several recent literature mechanisms. The utility of the solution mapping technique in situations where the optimum is not unique is also demonstrated.

A Mathematical Model Development for the Lateral Collapse of Octagonal Tubes

NASA Astrophysics Data System (ADS)

Ghazali Kamardan, M.; Sufahani, Suliadi; Othman, M. Z. M.; Che-Him, Norziha; Khalid, Kamil; Roslan, Rozaini; Ali, Maselan; Zaidi, A. M. A.

2018-04-01

Many researches has been done on the lateral collapse of tube. However, the previous researches only focus on cylindrical and square tubes. Then a research has been done discovering the collapse behaviour of hexagonal tube and the mathematic model of the deformation behaviour had been developed [8]. The purpose of this research is to study the lateral collapse behaviour of symmetric octagonal tubes and hence to develop a mathematical model of the collapse behaviour of these tubes. For that, a predictive mathematical model was developed and a finite element analysis procedure was conducted for the lateral collapse behaviour of symmetric octagonal tubes. Lastly, the mathematical model was verified by using the finite element analysis simulation results. It was discovered that these tubes performed different deformation behaviour than the cylindrical tube. Symmetric octagonal tubes perform 2 phases of elastic - plastic deformation behaviour patterns. The mathematical model had managed to show the fundamental of the deformation behaviour of octagonal tubes. However, further studies need to be conducted in order to further improve on the proposed mathematical model.

"When Mathematical Activity Moves You": An Exploration of the Design and Use of Purposefully Embodied Mathematical Activities, Models, Contexts, and Environments

ERIC Educational Resources Information Center

Campbell, William James

2017-01-01

This dissertation describes a mathematics curriculum and instruction design experiment involving a series of embodied mathematical activities conducted in two Colorado elementary schools Activities designed for this experiment include multi-scalar number line models focused on supporting students' understanding of elementary mathematics. Realistic…

Mathematical Modeling Is Also Physics--Interdisciplinary Teaching between Mathematics and Physics in Danish Upper Secondary Education

ERIC Educational Resources Information Center

Michelsen, Claus

2015-01-01

Mathematics plays a crucial role in physics. This role is brought about predominantly through the building, employment, and assessment of mathematical models, and teachers and educators should capture this relationship in the classroom in an effort to improve students' achievement and attitude in both physics and mathematics. But although there…

Exploring Yellowstone National Park with Mathematical Modeling

ERIC Educational Resources Information Center

Wickstrom, Megan H.; Carr, Ruth; Lackey, Dacia

2017-01-01

Mathematical modeling, a practice standard in the Common Core State Standards for Mathematics (CCSSM) (CCSSI 2010), is a process by which students develop and use mathematics as a tool to make sense of the world around them. Students investigate a real-world situation by asking mathematical questions; along the way, they need to decide how to use…

"Model Your Genes the Mathematical Way"--A Mathematical Biology Workshop for Secondary School Teachers

ERIC Educational Resources Information Center

Martins, Ana Margarida; Vera-Licona, Paola; Laubenbacher, Reinhard

2008-01-01

This article describes a mathematical biology workshop given to secondary school teachers of the Danville area in Virginia, USA. The goal of the workshop was to enable teams of teachers with biology and mathematics expertise to incorporate lesson plans in mathematical modelling into the curriculum. The biological focus of the activities is the…

An Analysis of Pre-Service Mathematics Teachers' Performance in Modelling Tasks in Terms of Spatial Visualisation Ability

ERIC Educational Resources Information Center

Tasova, Halil Ibrahim; Delice, Ali

2012-01-01

Mathematical modelling involves mathematical constructions chosen to represent some real world situations and the relationships among them; it is the process of expressing a real world situation mathematically. Visualisation can play a significant role in the development of thinking or understanding mathematical concepts, and also makes abstract…

Components of Mathematics Anxiety: Factor Modeling of the MARS30-Brief

PubMed Central

Pletzer, Belinda; Wood, Guilherme; Scherndl, Thomas; Kerschbaum, Hubert H.; Nuerk, Hans-Christoph

2016-01-01

Mathematics anxiety involves feelings of tension, discomfort, high arousal, and physiological reactivity interfering with number manipulation and mathematical problem solving. Several factor analytic models indicate that mathematics anxiety is rather a multidimensional than unique construct. However, the factor structure of mathematics anxiety has not been fully clarified by now. This issue shall be addressed in the current study. The Mathematics Anxiety Rating Scale (MARS) is a reliable measure of mathematics anxiety (Richardson and Suinn, 1972), for which several reduced forms have been developed. Most recently, a shortened version of the MARS (MARS30-brief) with comparable reliability was published. Different studies suggest that mathematics anxiety involves up to seven different factors. Here we examined the factor structure of the MARS30-brief by means of confirmatory factor analysis. The best model fit was obtained by a six-factor model, dismembering the known two general factors “Mathematical Test Anxiety” (MTA) and “Numerical Anxiety” (NA) in three factors each. However, a more parsimonious 5-factor model with two sub-factors for MTA and three for NA fitted the data comparably well. Factors were differentially susceptible to sex differences and differences between majors. Measurement invariance for sex was established. PMID:26924996

Components of Mathematics Anxiety: Factor Modeling of the MARS30-Brief.

PubMed

Pletzer, Belinda; Wood, Guilherme; Scherndl, Thomas; Kerschbaum, Hubert H; Nuerk, Hans-Christoph

2016-01-01

Mathematics anxiety involves feelings of tension, discomfort, high arousal, and physiological reactivity interfering with number manipulation and mathematical problem solving. Several factor analytic models indicate that mathematics anxiety is rather a multidimensional than unique construct. However, the factor structure of mathematics anxiety has not been fully clarified by now. This issue shall be addressed in the current study. The Mathematics Anxiety Rating Scale (MARS) is a reliable measure of mathematics anxiety (Richardson and Suinn, 1972), for which several reduced forms have been developed. Most recently, a shortened version of the MARS (MARS30-brief) with comparable reliability was published. Different studies suggest that mathematics anxiety involves up to seven different factors. Here we examined the factor structure of the MARS30-brief by means of confirmatory factor analysis. The best model fit was obtained by a six-factor model, dismembering the known two general factors "Mathematical Test Anxiety" (MTA) and "Numerical Anxiety" (NA) in three factors each. However, a more parsimonious 5-factor model with two sub-factors for MTA and three for NA fitted the data comparably well. Factors were differentially susceptible to sex differences and differences between majors. Measurement invariance for sex was established.

Control of Crazyflie nano quadcopter using Simulink

NASA Astrophysics Data System (ADS)

Gopabhat Madhusudhan, Meghana

This thesis focuses on developing a mathematical model in Simulink to Crazyflie, an open source platform. Attitude, altitude and position controllers of a Crazyflie are designed in the mathematical model. The mathematical model is developed based on the quadcopter system dynamics using a non-linear approach. The parameters of translational and rotational dynamics of the quadcopter system are linearized and tuned individually. The tuned attitude and altitude controllers from the mathematical model are implemented on real time Crazyflie Simulink model to achieve autonomous and controlled flight.

Computational modeling of the cell-autonomous mammalian circadian oscillator.

PubMed

Podkolodnaya, Olga A; Tverdokhleb, Natalya N; Podkolodnyy, Nikolay L

2017-02-24

This review summarizes various mathematical models of cell-autonomous mammalian circadian clock. We present the basics necessary for understanding of the cell-autonomous mammalian circadian oscillator, modern experimental data essential for its reconstruction and some special problems related to the validation of mathematical circadian oscillator models. This work compares existing mathematical models of circadian oscillator and the results of the computational studies of the oscillating systems. Finally, we discuss applications of the mathematical models of mammalian circadian oscillator for solving specific problems in circadian rhythm biology.

Students’ errors in solving combinatorics problems observed from the characteristics of RME modeling

NASA Astrophysics Data System (ADS)

Meika, I.; Suryadi, D.; Darhim

2018-01-01

This article was written based on the learning evaluation results of students’ errors in solving combinatorics problems observed from the characteristics of Realistic Mathematics Education (RME); that is modeling. Descriptive method was employed by involving 55 students from two international-based pilot state senior high schools in Banten. The findings of the study suggested that the students still committed errors in simplifying the problem as much 46%; errors in making mathematical model (horizontal mathematization) as much 60%; errors in finishing mathematical model (vertical mathematization) as much 65%; and errors in interpretation as well as validation as much 66%.

Structure, function, and behaviour of computational models in systems biology

PubMed Central

2013-01-01

Background Systems Biology develops computational models in order to understand biological phenomena. The increasing number and complexity of such “bio-models” necessitate computer support for the overall modelling task. Computer-aided modelling has to be based on a formal semantic description of bio-models. But, even if computational bio-models themselves are represented precisely in terms of mathematical expressions their full meaning is not yet formally specified and only described in natural language. Results We present a conceptual framework – the meaning facets – which can be used to rigorously specify the semantics of bio-models. A bio-model has a dual interpretation: On the one hand it is a mathematical expression which can be used in computational simulations (intrinsic meaning). On the other hand the model is related to the biological reality (extrinsic meaning). We show that in both cases this interpretation should be performed from three perspectives: the meaning of the model’s components (structure), the meaning of the model’s intended use (function), and the meaning of the model’s dynamics (behaviour). In order to demonstrate the strengths of the meaning facets framework we apply it to two semantically related models of the cell cycle. Thereby, we make use of existing approaches for computer representation of bio-models as much as possible and sketch the missing pieces. Conclusions The meaning facets framework provides a systematic in-depth approach to the semantics of bio-models. It can serve two important purposes: First, it specifies and structures the information which biologists have to take into account if they build, use and exchange models. Secondly, because it can be formalised, the framework is a solid foundation for any sort of computer support in bio-modelling. The proposed conceptual framework establishes a new methodology for modelling in Systems Biology and constitutes a basis for computer-aided collaborative research. PMID:23721297

The Relationship between Big Data and Mathematical Modeling: A Discussion in a Mathematical Education Scenario

ERIC Educational Resources Information Center

Dalla Vecchia, Rodrigo

2015-01-01

This study discusses aspects of the association between Mathematical Modeling (MM) and Big Data in the scope of mathematical education. We present an example of an activity to discuss two ontological factors that involve MM. The first is linked to the modeling stages. The second involves the idea of pedagogical objectives. The main findings…

On a Mathematical Model with Noncompact Boundary Conditions Describing Bacterial Population

NASA Astrophysics Data System (ADS)

Boulanouar, Mohamed

2013-04-01

In this work, we are concerned with the well-posedness of a mathematical model describing a maturation-velocity structured bacterial population. Each bacterium is distinguished by its degree of maturity and its maturation velocity. The bacterial mitosis is mathematically described by noncompact boundary conditions. We show that the mathematical model is governed by a positive strongly continuous semigroup.

What’s about Peer Tutoring Learning Model?

NASA Astrophysics Data System (ADS)

Muthma'innah, M.

2017-09-01

Mathematics learning outcomes in Indonesia in general is still far from satisfactory. One effort that could be expected to solve the problem is to apply the model of peer tutoring learning in mathematics. This study aims to determine whether the results of students’ mathematics learning can be enhanced through peer tutoring learning models. This type of research is the study of literature, so that the method used is to summarize and analyze the results of relevant research that has been done. Peer tutoring learning model is a model of learning in which students learn in small groups that are grouped with different ability levels, all group members to work together and help each other to understand the material. By paying attention to the syntax of the learning, then learning will be invaluable peer tutoring for students who served as teachers and students are taught. In mathematics, the implementation of this learning model can make students understand each other mathematical concepts and help students in solving mathematical problems that are poorly understood, due to the interaction between students in learning. Then it will be able to improve learning outcomes in mathematics. The impact, it can be applied in mathematics learning.

Classroom Interaction in Kenyan Primary Schools.

ERIC Educational Resources Information Center

Ackers, Jim; Hardman, Frank

2001-01-01

Reports on a study of classroom interaction in Kenyan primary schools. Analyzes video recordings of 102 lessons in English, mathematics, and science using systematic observation, discourse analysis, and a time-line analysis. Reveals the preponderance of teacher dominated lessons with little opportunity for student interaction. Considers…

Tutorial Computer-Assisted Language Learning

ERIC Educational Resources Information Center

Heift, Trude; Schulze, Mathias

2015-01-01

"Sometimes maligned for its allegedly behaviorist connotations but critical for success in many fields from music to sport to mathematics and language learning, 'practice' is undergoing something of a revival in the applied linguistics literature" (Long & Richards 2007, p. xi). This research timeline provides a systematic overview of…

Current problems in applied mathematics and mathematical modeling

NASA Astrophysics Data System (ADS)

Alekseev, A. S.

Papers are presented on mathematical modeling noting applications to such fields as geophysics, chemistry, atmospheric optics, and immunology. Attention is also given to models of ocean current fluxes, atmospheric and marine interactions, and atmospheric pollution. The articles include studies of catalytic reactors, models of global climate phenomena, and computer-assisted atmospheric models.

Dynamics of the sensory response to urethral flow over multiple time scales in rat

PubMed Central

Danziger, Zachary C; Grill, Warren M

2015-01-01

The pudendal nerve carries sensory information from the urethra that controls spinal reflexes necessary to maintain continence and achieve efficient micturition. Despite the key role urethral sensory feedback plays in regulation of the lower urinary tract, there is little information about the characteristics of urethral sensory responses to physiological stimuli, and the quantitative relationship between physiological stimuli and the evoked sensory activation is unknown. Such a relation is critical to understanding the neural control of the lower urinary tract and how dysfunction arises in disease states. We systematically quantified pudendal afferent responses to fluid flow in the urethra in vivo in the rat. We characterized the sensory response across a range of stimuli, and describe a previously unreported long-term neural accommodation phenomenon. We developed and validated a compact mechanistic mathematical model capable of reproducing the pudendal sensory activity in response to arbitrary profiles of urethral flows. These results describe the properties and function of urethral afferents that are necessary to understand how sensory disruption manifests in lower urinary tract pathophysiology. Key points Sensory information from the urethra is essential to maintain continence and to achieve efficient micturition and when compromised by disease or injury can lead to substantial loss of function. Despite the key role urethral sensory information plays in the lower urinary tract, the relationship between physiological urethral stimuli, such as fluid flow, and the neural sensory response is poorly understood. This work systematically quantifies pudendal afferent responses to a range of fluid flows in the urethra in vivo and describes a previously unknown long-term neural accommodation phenomenon in these afferents. We present a compact mechanistic mathematical model that reproduces the pudendal sensory activity in response to urethral flow. These results have implications for understanding urinary tract dysfunction caused by neuropathy or nerve damage, such as urinary retention or incontinence, as well as for the development of strategies to mitigate the symptoms of these conditions. PMID:26041695

Mathematical modeling of urea transport in the kidney.

PubMed

Layton, Anita T

2014-01-01

Mathematical modeling techniques have been useful in providing insights into biological systems, including the kidney. This article considers some of the mathematical models that concern urea transport in the kidney. Modeling simulations have been conducted to investigate, in the context of urea cycling and urine concentration, the effects of hypothetical active urea secretion into pars recta. Simulation results suggest that active urea secretion induces a "urea-selective" improvement in urine concentrating ability. Mathematical models have also been built to study the implications of the highly structured organization of tubules and vessels in the renal medulla on urea sequestration and cycling. The goal of this article is to show how physiological problems can be formulated and studied mathematically, and how such models may provide insights into renal functions.

The Effects of Mathematical Modeling on Creative Production Ability and Self-Directed Learning Attitude

ERIC Educational Resources Information Center

Kim, Sun Hee; Kim, Soojin

2010-01-01

What should we do to educate the mathematically gifted and how should we do it? In this research, to satisfy diverse mathematical and cognitive demands of the gifted who have excellent learning ability and task tenacity in mathematics, we sought to apply mathematical modeling. One of the objectives of the gifted education in Korea is cultivating…

A Mathematical Diet Model

ERIC Educational Resources Information Center

Toumasis, Charalampos

2004-01-01

Emphasis on problem solving and mathematical modeling has gained considerable attention in the last few years. Connecting mathematics to other subjects and to the real world outside the classroom has received increased attention in mathematics programs. This article describes an application of simple differential equations in the field of…

Cellular Interrogation: Exploiting Cell-to-Cell Variability to Discriminate Regulatory Mechanisms in Oscillatory Signalling.

PubMed

Estrada, Javier; Andrew, Natalie; Gibson, Daniel; Chang, Frederick; Gnad, Florian; Gunawardena, Jeremy

2016-07-01

The molecular complexity within a cell may be seen as an evolutionary response to the external complexity of the cell's environment. This suggests that the external environment may be harnessed to interrogate the cell's internal molecular architecture. Cells, however, are not only nonlinear and non-stationary, but also exhibit heterogeneous responses within a clonal, isogenic population. In effect, each cell undertakes its own experiment. Here, we develop a method of cellular interrogation using programmable microfluidic devices which exploits the additional information present in cell-to-cell variation, without requiring model parameters to be fitted to data. We focussed on Ca2+ signalling in response to hormone stimulation, which exhibits oscillatory spiking in many cell types and chose eight models of Ca2+ signalling networks which exhibit similar behaviour in simulation. We developed a nonlinear frequency analysis for non-stationary responses, which could classify models into groups under parameter variation, but found that this question alone was unable to distinguish critical feedback loops. We further developed a nonlinear amplitude analysis and found that the combination of both questions ruled out six of the models as inconsistent with the experimentally-observed dynamics and heterogeneity. The two models that survived the double interrogation were mathematically different but schematically identical and yielded the same unexpected predictions that we confirmed experimentally. Further analysis showed that subtle mathematical details can markedly influence non-stationary responses under parameter variation, emphasising the difficulty of finding a "correct" model. By developing questions for the pathway being studied, and designing more versatile microfluidics, cellular interrogation holds promise as a systematic strategy that can complement direct intervention by genetics or pharmacology.

A New Look into the Effect of Large Drops on Radiative Transfer Process

NASA Technical Reports Server (NTRS)

Marshak, Alexander

2003-01-01

Recent studies indicate that a cloudy atmosphere absorbs more solar radiation than any current 1D or 3D radiation model can predict. The excess absorption is not large, perhaps 10-15 W/sq m or less, but any such systematic bias is of concern since radiative transfer models are assumed to be sufficiently accurate for remote sensing applications and climate modeling. The most natural explanation would be that models do not capture real 3D cloud structure and, as a consequence, their photon path lengths are too short. However, extensive calculations, using increasingly realistic 3D cloud structures, failed to produce photon paths long enough to explain the excess absorption. Other possible explanations have also been unsuccessful so, at this point, conventional models seem to offer no solution to this puzzle. The weakest link in conventional models is the way a size distribution of cloud particles is mathematically handled. Basically, real particles are replaced with a single average particle. This "ensemble assumption" assumes that all particle sizes are well represented in any given elementary volume. But the concentration of larger particles can be so low that this assumption is significantly violated. We show how a different mathematical route, using the concept of a cumulative distribution, avoids the ensemble assumption. The cumulative distribution has jumps, or steps, corresponding to the rarer sizes. These jumps result in an additional term, a kind of Green's function, in the solution of the radiative transfer equation. Solving the cloud radiative transfer equation with the measured particle distributions, described in a cumulative rather than an ensemble fashion, may lead to increased cloud absorption of the magnitude observed.

Bacterial Adherence and Dwelling Probability: Two Drivers of Early Alveolar Infection by Streptococcus pneumoniae Identified in Multi-Level Mathematical Modeling

PubMed Central

Santos, Guido; Lai, Xin; Eberhardt, Martin; Vera, Julio

2018-01-01

Pneumococcal infection is the most frequent cause of pneumonia, and one of the most prevalent diseases worldwide. The population groups at high risk of death from bacterial pneumonia are infants, elderly and immunosuppressed people. These groups are more vulnerable because they have immature or impaired immune systems, the efficacy of their response to vaccines is lower, and antibiotic treatment often does not take place until the inflammatory response triggered is already overwhelming. The immune response to bacterial lung infections involves dynamic interactions between several types of cells whose activation is driven by intracellular molecular networks. A feasible approach to the integration of knowledge and data linking tissue, cellular and intracellular events and the construction of hypotheses in this area is the use of mathematical modeling. For this paper, we used a multi-level computational model to analyse the role of cellular and molecular interactions during the first 10 h after alveolar invasion of Streptococcus pneumoniae bacteria. By “multi-level” we mean that we simulated the interplay between different temporal and spatial scales in a single computational model. In this instance, we included the intracellular scale of processes driving lung epithelial cell activation together with the scale of cell-to-cell interactions at the alveolar tissue. In our analysis, we combined systematic model simulations with logistic regression analysis and decision trees to find genotypic-phenotypic signatures that explain differences in bacteria strain infectivity. According to our simulations, pneumococci benefit from a high dwelling probability and a high proliferation rate during the first stages of infection. In addition to this, the model predicts that during the very early phases of infection the bacterial capsule could be an impediment to the establishment of the alveolar infection because it impairs bacterial colonization. PMID:29868515

Bacterial Adherence and Dwelling Probability: Two Drivers of Early Alveolar Infection by Streptococcus pneumoniae Identified in Multi-Level Mathematical Modeling.

PubMed

Santos, Guido; Lai, Xin; Eberhardt, Martin; Vera, Julio

2018-01-01

Pneumococcal infection is the most frequent cause of pneumonia, and one of the most prevalent diseases worldwide. The population groups at high risk of death from bacterial pneumonia are infants, elderly and immunosuppressed people. These groups are more vulnerable because they have immature or impaired immune systems, the efficacy of their response to vaccines is lower, and antibiotic treatment often does not take place until the inflammatory response triggered is already overwhelming. The immune response to bacterial lung infections involves dynamic interactions between several types of cells whose activation is driven by intracellular molecular networks. A feasible approach to the integration of knowledge and data linking tissue, cellular and intracellular events and the construction of hypotheses in this area is the use of mathematical modeling. For this paper, we used a multi-level computational model to analyse the role of cellular and molecular interactions during the first 10 h after alveolar invasion of Streptococcus pneumoniae bacteria. By "multi-level" we mean that we simulated the interplay between different temporal and spatial scales in a single computational model. In this instance, we included the intracellular scale of processes driving lung epithelial cell activation together with the scale of cell-to-cell interactions at the alveolar tissue. In our analysis, we combined systematic model simulations with logistic regression analysis and decision trees to find genotypic-phenotypic signatures that explain differences in bacteria strain infectivity. According to our simulations, pneumococci benefit from a high dwelling probability and a high proliferation rate during the first stages of infection. In addition to this, the model predicts that during the very early phases of infection the bacterial capsule could be an impediment to the establishment of the alveolar infection because it impairs bacterial colonization.

The role of pattern recognition in creative problem solving: a case study in search of new mathematics for biology.

PubMed

Hong, Felix T

2013-09-01

Rosen classified sciences into two categories: formalizable and unformalizable. Whereas formalizable sciences expressed in terms of mathematical theories were highly valued by Rutherford, Hutchins pointed out that unformalizable parts of soft sciences are of genuine interest and importance. Attempts to build mathematical theories for biology in the past century was met with modest and sporadic successes, and only in simple systems. In this article, a qualitative model of humans' high creativity is presented as a starting point to consider whether the gap between soft and hard sciences is bridgeable. Simonton's chance-configuration theory, which mimics the process of evolution, was modified and improved. By treating problem solving as a process of pattern recognition, the known dichotomy of visual thinking vs. verbal thinking can be recast in terms of analog pattern recognition (non-algorithmic process) and digital pattern recognition (algorithmic process), respectively. Additional concepts commonly encountered in computer science, operations research and artificial intelligence were also invoked: heuristic searching, parallel and sequential processing. The refurbished chance-configuration model is now capable of explaining several long-standing puzzles in human cognition: a) why novel discoveries often came without prior warning, b) why some creators had no ideas about the source of inspiration even after the fact, c) why some creators were consistently luckier than others, and, last but not least, d) why it was so difficult to explain what intuition, inspiration, insight, hunch, serendipity, etc. are all about. The predictive power of the present model was tested by means of resolving Zeno's paradox of Achilles and the Tortoise after one deliberately invoked visual thinking. Additional evidence of its predictive power must await future large-scale field studies. The analysis was further generalized to constructions of scientific theories in general. This approach is in line with Campbell's evolutionary epistemology. Instead of treating science as immutable Natural Laws, which already existed and which were just waiting to be discovered, scientific theories are regarded as humans' mental constructs, which must be invented to reconcile with observed natural phenomena. In this way, the pursuit of science is shifted from diligent and systematic (or random) searching for existing Natural Laws to firing up humans' imagination to comprehend Nature's behavioral pattern. The insights gained in understanding human creativity indicated that new mathematics that is capable of handling effectively parallel processing and human subjectivity is sorely needed. The past classification of formalizability vs. non-formalizability was made in reference to contemporary mathematics. Rosen's conclusion did not preclude future inventions of new biology-friendly mathematics. Copyright © 2013 Elsevier Ltd. All rights reserved.

Near Identifiability of Dynamical Systems

NASA Technical Reports Server (NTRS)

Hadaegh, F. Y.; Bekey, G. A.

1987-01-01

Concepts regarding approximate mathematical models treated rigorously. Paper presents new results in analysis of structural identifiability, equivalence, and near equivalence between mathematical models and physical processes they represent. Helps establish rigorous mathematical basis for concepts related to structural identifiability and equivalence revealing fundamental requirements, tacit assumptions, and sources of error. "Structural identifiability," as used by workers in this field, loosely translates as meaning ability to specify unique mathematical model and set of model parameters that accurately predict behavior of corresponding physical system.

How to Develop Teachers' Mathematical Molding Teaching Skills

ERIC Educational Resources Information Center

Mrayyan, Salwa

2016-01-01

This study aimed at developing some of the mathematical modelling skills necessary for the student teachers in mathematics education College. Modeling involves making genuine choices, modeling problems have many possible justifiable answers, modeling problems matter to the end-user who needs to understand something or make a decision. Modeling…

Developing Understanding of Mathematical Modeling in Secondary Teacher Preparation

ERIC Educational Resources Information Center

Anhalt, Cynthia Oropesa; Cortez, Ricardo

2016-01-01

This study examines the evolution of 11 prospective teachers' understanding of mathematical modeling through the implementation of a modeling module within a curriculum course in a secondary teacher preparation program. While the prospective teachers had not previously taken a course on mathematical modeling, they will be expected to include…

Model Eliciting Activities: Fostering 21st Century Learners

ERIC Educational Resources Information Center

Stohlmann, Micah

2013-01-01

Real world mathematical modeling activities can develop needed and valuable 21st century skills. The knowledge and skills to become adept at mathematical modeling need to develop over time and students in the elementary grades should have experiences with mathematical modeling. For this to occur elementary teachers need to have positive…

Some Reflections on the Teaching of Mathematical Modeling

ERIC Educational Resources Information Center

Warwick, Jon

2007-01-01

This paper offers some reflections on the difficulties of teaching mathematical modeling to students taking higher education courses in which modeling plays a significant role. In the author's experience, other aspects of the model development process often cause problems rather than the use of mathematics. Since these other aspects involve…

A general model-based design of experiments approach to achieve practical identifiability of pharmacokinetic and pharmacodynamic models.

PubMed

Galvanin, Federico; Ballan, Carlo C; Barolo, Massimiliano; Bezzo, Fabrizio

2013-08-01

The use of pharmacokinetic (PK) and pharmacodynamic (PD) models is a common and widespread practice in the preliminary stages of drug development. However, PK-PD models may be affected by structural identifiability issues intrinsically related to their mathematical formulation. A preliminary structural identifiability analysis is usually carried out to check if the set of model parameters can be uniquely determined from experimental observations under the ideal assumptions of noise-free data and no model uncertainty. However, even for structurally identifiable models, real-life experimental conditions and model uncertainty may strongly affect the practical possibility to estimate the model parameters in a statistically sound way. A systematic procedure coupling the numerical assessment of structural identifiability with advanced model-based design of experiments formulations is presented in this paper. The objective is to propose a general approach to design experiments in an optimal way, detecting a proper set of experimental settings that ensure the practical identifiability of PK-PD models. Two simulated case studies based on in vitro bacterial growth and killing models are presented to demonstrate the applicability and generality of the methodology to tackle model identifiability issues effectively, through the design of feasible and highly informative experiments.

Group investigation with scientific approach in mathematics learning

NASA Astrophysics Data System (ADS)

Indarti, D.; Mardiyana; Pramudya, I.

2018-03-01

The aim of this research is to find out the effect of learning model toward mathematics achievement. This research is quasi-experimental research. The population of research is all VII grade students of Karanganyar regency in the academic year of 2016/2017. The sample of this research was taken using stratified cluster random sampling technique. Data collection was done based on mathematics achievement test. The data analysis technique used one-way ANOVA following the normality test with liliefors method and homogeneity test with Bartlett method. The results of this research is the mathematics learning using Group Investigation learning model with scientific approach produces the better mathematics learning achievement than learning with conventional model on material of quadrilateral. Group Investigation learning model with scientific approach can be used by the teachers in mathematics learning, especially in the material of quadrilateral, which is can improve the mathematics achievement.

Formally verifying Ada programs which use real number types

NASA Technical Reports Server (NTRS)

Sutherland, David

1986-01-01

Formal verification is applied to programs which use real number arithmetic operations (mathematical programs). Formal verification of a program P consists of creating a mathematical model of F, stating the desired properties of P in a formal logical language, and proving that the mathematical model has the desired properties using a formal proof calculus. The development and verification of the mathematical model are discussed.

Mathematical Modeling in the Secondary School Curriculum.

ERIC Educational Resources Information Center

Swetz, Frank, Ed.; Hartzler, J. S., Ed.

Over the past 10 years, national conferences and committees investigating the state of American mathematics education have advocated an increased emphasis on problem solving and mathematical modeling situations in the secondary school curriculum. However, little effort has been made to prepare secondary school teachers to use mathematical modeling…

The Effect of microRNAs in the Regulation of Human CYP3A4: a Systematic Study using a Mathematical Model

NASA Astrophysics Data System (ADS)

Wei, Zhiyun; Jiang, Songshan; Zhang, Yiting; Wang, Xiaofei; Peng, Xueling; Meng, Chunjie; Liu, Yichen; Wang, Honglian; Guo, Luo; Qin, Shengying; He, Lin; Shao, Fengmin; Zhang, Lirong; Xing, Qinghe

2014-03-01

CYP3A4 metabolizes more than 50% of the drugs on the market. The large inter-individual differences of CYP3A4 expression may contribute to the variability of human drug responses. Post-transcriptional regulation of CYP3A4 is poorly understood, whereas transcriptional regulation has been studied much more thoroughly. In this study, we used multiple software programs to predict miRNAs that might bind to CYP3A4 and identified 112 potentially functional miRNAs. Then a luciferase reporter system was used to assess the effect of the overexpression of each potentially functional miRNA in HEK 293T cells. Fourteen miRNAs that significantly decreased reporter activity were measured in human liver samples (N = 27) as candidate miRNAs. To establish a more effective way to analyze in vivo data for miRNA candidates, the relationship between functional miRNA and target mRNA was modeled mathematically. Taking advantage of this model, we found that hsa-miR-577, hsa-miR-1, hsa-miR-532-3p and hsa-miR-627 could significantly downregulate the translation efficiency of CYP3A4 mRNA in liver. This study used in silico, in vitro and in vivo methods to progressively screen functional miRNAs for CYP3A4 and to enhance our understanding of molecular events underlying the large inter-individual differences of CYP3A4 expression in human populations.

Visual Form Perception Can Be a Cognitive Correlate of Lower Level Math Categories for Teenagers

PubMed Central

Cui, Jiaxin; Zhang, Yiyun; Cheng, Dazhi; Li, Dawei; Zhou, Xinlin

2017-01-01

Numerous studies have assessed the cognitive correlates of performance in mathematics, but little research has been conducted to systematically examine the relations between visual perception as the starting point of visuospatial processing and typical mathematical performance. In the current study, we recruited 223 seventh graders to perform a visual form perception task (figure matching), numerosity comparison, digit comparison, exact computation, approximate computation, and curriculum-based mathematical achievement tests. Results showed that, after controlling for gender, age, and five general cognitive processes (choice reaction time, visual tracing, mental rotation, spatial working memory, and non-verbal matrices reasoning), visual form perception had unique contributions to numerosity comparison, digit comparison, and exact computation, but had no significant relation with approximate computation or curriculum-based mathematical achievement. These results suggest that visual form perception is an important independent cognitive correlate of lower level math categories, including the approximate number system, digit comparison, and exact computation. PMID:28824513

Topics in geophysical fluid dynamics: Atmospheric dynamics, dynamo theory, and climate dynamics

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

Ghil, M.; Childress, S.

1987-01-01

This text is the first study to apply systematically the successive bifurcations approach to complex time-dependent processes in large scale atmospheric dynamics, geomagnetism, and theoretical climate dynamics. The presentation of recent results on planetary-scale phenomena in the earth's atmosphere, ocean, cryosphere, mantle and core provides an integral account of mathematical theory and methods together with physical phenomena and processes. The authors address a number of problems in rapidly developing areas of geophysics, bringing into closer contact the modern tools of nonlinear mathematics and the novel problems of global change in the environment.

What can formal methods offer to digital flight control systems design

NASA Technical Reports Server (NTRS)

Good, Donald I.

1990-01-01

Formal methods research begins to produce methods which will enable mathematic modeling of the physical behavior of digital hardware and software systems. The development of these methods directly supports the NASA mission of increasing the scope and effectiveness of flight system modeling capabilities. The conventional, continuous mathematics that is used extensively in modeling flight systems is not adequate for accurate modeling of digital systems. Therefore, the current practice of digital flight control system design has not had the benefits of extensive mathematical modeling which are common in other parts of flight system engineering. Formal methods research shows that by using discrete mathematics, very accurate modeling of digital systems is possible. These discrete modeling methods will bring the traditional benefits of modeling to digital hardware and hardware design. Sound reasoning about accurate mathematical models of flight control systems can be an important part of reducing risk of unsafe flight control.

Modeling temperature entrainment of circadian clocks using the Arrhenius equation and a reconstructed model from Chlamydomonas reinhardtii.

PubMed

Heiland, Ines; Bodenstein, Christian; Hinze, Thomas; Weisheit, Olga; Ebenhoeh, Oliver; Mittag, Maria; Schuster, Stefan

2012-06-01

Endogenous circadian rhythms allow living organisms to anticipate daily variations in their natural environment. Temperature regulation and entrainment mechanisms of circadian clocks are still poorly understood. To better understand the molecular basis of these processes, we built a mathematical model based on experimental data examining temperature regulation of the circadian RNA-binding protein CHLAMY1 from the unicellular green alga Chlamydomonas reinhardtii, simulating the effect of temperature on the rates by applying the Arrhenius equation. Using numerical simulations, we demonstrate that our model is temperature-compensated and can be entrained to temperature cycles of various length and amplitude. The range of periods that allow entrainment of the model depends on the shape of the temperature cycles and is larger for sinusoidal compared to rectangular temperature curves. We show that the response to temperature of protein (de)phosphorylation rates play a key role in facilitating temperature entrainment of the oscillator in Chlamydomonas reinhardtii. We systematically investigated the response of our model to single temperature pulses to explain experimentally observed phase response curves.

Developing Teachers' Models for Assessing Students' Competence in Mathematical Modelling through Lesson Study

ERIC Educational Resources Information Center

Aydogan Yenmez, Arzu; Erbas, Ayhan Kursat; Cakiroglu, Erdinc; Alacaci, Cengiz; Cetinkaya, Bulent

2017-01-01

Applications and modelling have gained a prominent role in mathematics education reform documents and curricula. Thus, there is a growing need for studies focusing on the effective use of mathematical modelling in classrooms. Assessment is an integral part of using modelling activities in classrooms, since it allows teachers to identify and manage…

Mathematical Modeling in the People's Republic of China--Indicators of Participation and Performance on COMAP's Modeling Contest

ERIC Educational Resources Information Center

Tian, Xiaoxi

2014-01-01

In recent years, Mainland Chinese teams have been the dominant participants in the two COMAP-sponsored mathematical modeling competitions: the Mathematical Contest in Modeling (MCM) and the Interdisciplinary Contest in Modeling (ICM). This study examines five factors that lead to the Chinese teams' dramatic increase in participation rate and…

Using a Functional Model to Develop a Mathematical Formula

ERIC Educational Resources Information Center

Otto, Charlotte A.; Everett, Susan A.; Luera, Gail R.

2008-01-01

The unifying theme of models was incorporated into a required Science Capstone course for pre-service elementary teachers based on national standards in science and mathematics. A model of a teeter-totter was selected for use as an example of a functional model for gathering data as well as a visual model of a mathematical equation for developing…

[Representation and mathematical analysis of human crystalline lens].

PubMed

Tălu, Stefan; Giovanzana, Stefano; Tălu, Mihai

2011-01-01

The surface of human crystalline lens can be described and analyzed using mathematical models based on parametric representations, used in biomechanical studies and 3D solid modeling of the lens. The mathematical models used in lens biomechanics allow the study and the behavior of crystalline lens on variables and complex dynamic loads. Also, the lens biomechanics has the potential to improve the results in the development of intraocular lenses and cataract surgery. The paper presents the most representative mathematical models currently used for the modeling of human crystalline lens, both optically and biomechanically.

Science modelling in pre-calculus: how to make mathematics problems contextually meaningful

NASA Astrophysics Data System (ADS)

Sokolowski, Andrzej; Yalvac, Bugrahan; Loving, Cathleen

2011-04-01

'Use of mathematical representations to model and interpret physical phenomena and solve problems is one of the major teaching objectives in high school math curriculum' (National Council of Teachers of Mathematics (NCTM), Principles and Standards for School Mathematics, NCTM, Reston, VA, 2000). Commonly used pre-calculus textbooks provide a wide range of application problems. However, these problems focus students' attention on evaluating or solving pre-arranged formulas for given values. The role of scientific content is reduced to provide a background for these problems instead of being sources of data gathering for inducing mathematical tools. Students are neither required to construct mathematical models based on the contexts nor are they asked to validate or discuss the limitations of applied formulas. Using these contexts, the instructor may think that he/she is teaching problem solving, where in reality he/she is teaching algorithms of the mathematical operations (G. Kulm (ed.), New directions for mathematics assessment, in Assessing Higher Order Thinking in Mathematics, Erlbaum, Hillsdale, NJ, 1994, pp. 221-240). Without a thorough representation of the physical phenomena and the mathematical modelling processes undertaken, problem solving unintentionally appears as simple algorithmic operations. In this article, we deconstruct the representations of mathematics problems from selected pre-calculus textbooks and explicate their limitations. We argue that the structure and content of those problems limits students' coherent understanding of mathematical modelling, and this could result in weak student problem-solving skills. Simultaneously, we explore the ways to enhance representations of those mathematical problems, which we have characterized as lacking a meaningful physical context and limiting coherent student understanding. In light of our discussion, we recommend an alternative to strengthen the process of teaching mathematical modelling - utilization of computer-based science simulations. Although there are several exceptional computer-based science simulations designed for mathematics classes (see, e.g. Kinetic Book (http://www.kineticbooks.com/) or Gizmos (http://www.explorelearning.com/)), we concentrate mainly on the PhET Interactive Simulations developed at the University of Colorado at Boulder (http://phet.colorado.edu/) in generating our argument that computer simulations more accurately represent the contextual characteristics of scientific phenomena than their textual descriptions.

Science Careers in the Classroom.

ERIC Educational Resources Information Center

Smith, Walter S.

1983-01-01

Suggests systematically exposing early adolescents/middle school students to community people who use science in their work to demonstrate the value of science/mathematics study. Discusses activities related to classroom visits of resource personnel, sources of resource people, and Career Oriented Modules to Explore Topics in Science for grades…

Effects of Variation and Prior Knowledge on Abstract Concept Learning

ERIC Educational Resources Information Center

Braithwaite, David W.; Goldstone, Robert L.

2015-01-01

Learning abstract concepts through concrete examples may promote learning at the cost of inhibiting transfer. The present study investigated one approach to solving this problem: systematically varying superficial features of the examples. Participants learned to solve problems involving a mathematical concept by studying either superficially…

ACT Aspire™. What Works Clearinghouse Intervention Report

ERIC Educational Resources Information Center

What Works Clearinghouse, 2017

2017-01-01

The "ACT Aspire"™ system provides a longitudinal, systematic approach for assessing and monitoring students' preparation for high school studies and readiness for college and career. "ACT Aspire"™ includes assessments for students from grade 3 through early high school in five subject areas: English, mathematics, reading,…

Evidence-Based Practices for Students with Visual Disabilities

ERIC Educational Resources Information Center

Ferrell, Kay Alicyn

2006-01-01

Forty years of peer-reviewed research in literacy and 50 years of research in mathematics were systematically analyzed to determine the evidence supporting instructional pedagogy for students with visual disabilities. Review teams identified 30 intervention studies that utilized an appropriate comparison group. Although some studies had large…

Mathematical Manipulative Models: In Defense of “Beanbag Biology”

PubMed Central

Gaff, Holly; Weisstein, Anton E.

2010-01-01

Mathematical manipulative models have had a long history of influence in biological research and in secondary school education, but they are frequently neglected in undergraduate biology education. By linking mathematical manipulative models in a four-step process—1) use of physical manipulatives, 2) interactive exploration of computer simulations, 3) derivation of mathematical relationships from core principles, and 4) analysis of real data sets—we demonstrate a process that we have shared in biological faculty development workshops led by staff from the BioQUEST Curriculum Consortium over the past 24 yr. We built this approach based upon a broad survey of literature in mathematical educational research that has convincingly demonstrated the utility of multiple models that involve physical, kinesthetic learning to actual data and interactive simulations. Two projects that use this approach are introduced: The Biological Excel Simulations and Tools in Exploratory, Experiential Mathematics (ESTEEM) Project (http://bioquest.org/esteem) and Numerical Undergraduate Mathematical Biology Education (NUMB3R5 COUNT; http://bioquest.org/numberscount). Examples here emphasize genetics, ecology, population biology, photosynthesis, cancer, and epidemiology. Mathematical manipulative models help learners break through prior fears to develop an appreciation for how mathematical reasoning informs problem solving, inference, and precise communication in biology and enhance the diversity of quantitative biology education. PMID:20810952

Mathematical manipulative models: in defense of "beanbag biology".

PubMed

Jungck, John R; Gaff, Holly; Weisstein, Anton E

2010-01-01

Mathematical manipulative models have had a long history of influence in biological research and in secondary school education, but they are frequently neglected in undergraduate biology education. By linking mathematical manipulative models in a four-step process-1) use of physical manipulatives, 2) interactive exploration of computer simulations, 3) derivation of mathematical relationships from core principles, and 4) analysis of real data sets-we demonstrate a process that we have shared in biological faculty development workshops led by staff from the BioQUEST Curriculum Consortium over the past 24 yr. We built this approach based upon a broad survey of literature in mathematical educational research that has convincingly demonstrated the utility of multiple models that involve physical, kinesthetic learning to actual data and interactive simulations. Two projects that use this approach are introduced: The Biological Excel Simulations and Tools in Exploratory, Experiential Mathematics (ESTEEM) Project (http://bioquest.org/esteem) and Numerical Undergraduate Mathematical Biology Education (NUMB3R5 COUNT; http://bioquest.org/numberscount). Examples here emphasize genetics, ecology, population biology, photosynthesis, cancer, and epidemiology. Mathematical manipulative models help learners break through prior fears to develop an appreciation for how mathematical reasoning informs problem solving, inference, and precise communication in biology and enhance the diversity of quantitative biology education.

On Fences, Forms and Mathematical Modeling

ERIC Educational Resources Information Center

Lege, Jerry

2009-01-01

The white picket fence is an integral component of the iconic American townscape. But, for mathematics students, it can be a mathematical challenge. Picket fences in a variety of styles serve as excellent sources to model constant, step, absolute value, and sinusoidal functions. "Principles and Standards for School Mathematics" (NCTM 2000)…

Mathematical Modelling as a Professional Task

ERIC Educational Resources Information Center

Frejd, Peter; Bergsten, Christer

2016-01-01

Educational research literature on mathematical modelling is extensive. However, not much attention has been paid to empirical investigations of its scholarly knowledge from the perspective of didactic transposition processes. This paper reports from an interview study of mathematical modelling activities involving nine professional model…

Mathematical Models for Immunology: Current State of the Art and Future Research Directions.

PubMed

Eftimie, Raluca; Gillard, Joseph J; Cantrell, Doreen A

2016-10-01

The advances in genetics and biochemistry that have taken place over the last 10 years led to significant advances in experimental and clinical immunology. In turn, this has led to the development of new mathematical models to investigate qualitatively and quantitatively various open questions in immunology. In this study we present a review of some research areas in mathematical immunology that evolved over the last 10 years. To this end, we take a step-by-step approach in discussing a range of models derived to study the dynamics of both the innate and immune responses at the molecular, cellular and tissue scales. To emphasise the use of mathematics in modelling in this area, we also review some of the mathematical tools used to investigate these models. Finally, we discuss some future trends in both experimental immunology and mathematical immunology for the upcoming years.

Differential equations with applications in cancer diseases.

PubMed

Ilea, M; Turnea, M; Rotariu, M

2013-01-01

Mathematical modeling is a process by which a real world problem is described by a mathematical formulation. The cancer modeling is a highly challenging problem at the frontier of applied mathematics. A variety of modeling strategies have been developed, each focusing on one or more aspects of cancer. The vast majority of mathematical models in cancer diseases biology are formulated in terms of differential equations. We propose an original mathematical model with small parameter for the interactions between these two cancer cell sub-populations and the mathematical model of a vascular tumor. We work on the assumption that, the quiescent cells' nutrient consumption is long. One the equations system includes small parameter epsilon. The smallness of epsilon is relative to the size of the solution domain. MATLAB simulations obtained for transition rate from the quiescent cells' nutrient consumption is long, we show a similar asymptotic behavior for two solutions of the perturbed problem. In this system, the small parameter is an asymptotic variable, different from the independent variable. The graphical output for a mathematical model of a vascular tumor shows the differences in the evolution of the tumor populations of proliferating, quiescent and necrotic cells. The nutrient concentration decreases sharply through the viable rim and tends to a constant level in the core due to the nearly complete necrosis in this region. Many mathematical models can be quantitatively characterized by ordinary differential equations or partial differential equations. The use of MATLAB in this article illustrates the important role of informatics in research in mathematical modeling. The study of avascular tumor growth cells is an exciting and important topic in cancer research and will profit considerably from theoretical input. Interpret these results to be a permanent collaboration between math's and medical oncologists.

Perturbing the Hypothalamic Pituitary Adrenal Axis:A Mathematical Model for Interpreting PTSDAssessment Tests

DTIC Science & Technology

2017-08-15

RESEARCH Perturbing the Hypothalamic–Pituitary–Adrenal Axis: A Mathematical Model for Interpreting PTSD Assessment Tests Lae Un Kim1, Maria R...D’Orsogna2, and Tom Chou1 1Department of Biomathematics, University of California, Los Angeles, USA 2Department of Mathematics , California State University...observed features and experimental responses can arise from a bistable mathematical model containing two steady-states, rather than relying on specific

Mathematical form models of tree trunks

Treesearch

Rudolfs Ozolins

2000-01-01

Assortment structure analysis of tree trunks is a characteristic and proper problem that can be solved by using mathematical modeling and standard computer programs. Mathematical form model of tree trunks consists of tapering curve equations and their parameters. Parameters for nine species were obtained by processing measurements of 2,794 model trees and studying the...

Modeling Achievement in Mathematics: The Role of Learner and Learning Environment Characteristics

ERIC Educational Resources Information Center

Nasser-Abu Alhija, Fadia; Amasha, Marcel

2012-01-01

This study examined a structural model of mathematics achievement among Druze 8th graders in Israel. The model integrates 2 psychosocial theories: goal theory and social learning theory. Variables in the model included gender, father's and mother's education, classroom mastery and performance goal orientation, mathematics self-efficacy and…

Teachers as Managers of the Modelling Process

ERIC Educational Resources Information Center

Lingefjard, Thomas; Meier, Stephanie

2010-01-01

The work in the Comenius Network project Developing Quality in Mathematics Education II (DQME II) has a main focus on development and evaluation of modelling tasks. One reason is the gap between what mathematical modelling is and what is taught in mathematical classrooms. This article deals with one modelling task and focuses on how two teachers…

Rival approaches to mathematical modelling in immunology

NASA Astrophysics Data System (ADS)

Andrew, Sarah M.; Baker, Christopher T. H.; Bocharov, Gennady A.

2007-08-01

In order to formulate quantitatively correct mathematical models of the immune system, one requires an understanding of immune processes and familiarity with a range of mathematical techniques. Selection of an appropriate model requires a number of decisions to be made, including a choice of the modelling objectives, strategies and techniques and the types of model considered as candidate models. The authors adopt a multidisciplinary perspective.

Analysis of creative mathematical thinking ability by using model eliciting activities (MEAs)

NASA Astrophysics Data System (ADS)

Winda, A.; Sufyani, P.; Elah, N.

2018-05-01

Lack of creative mathematical thinking ability can lead to not accustomed with open ended problem. Students’ creative mathematical thinking ability in the first grade at one of junior high school in Tangerang City is not fully developed. The reason of students’ creative mathematical thinking ability is not optimally developed is so related with learning process which has done by the mathematics teacher, maybe the learning design that teacher use is unsuitable for increasing students’ activity in the learning process. This research objective is to see the differences in students’ ways of answering the problems in terms of students’ creative mathematical thinking ability during the implementation of Model Eliciting Activities (MEAs). This research use post-test experimental class design. The indicators for creative mathematical thinking ability in this research arranged in three parts, as follow: (1) Fluency to answer the problems; (2) Flexibility to solve the problems; (3) Originality of answers. The result of this research found that by using the same learning model and same instrument from Model Eliciting Activities (MEAs) there are some differences in the way students answer the problems and Model Eliciting Activities (MEAs) can be one of approach used to increase students’ creative mathematical thinking ability.

Cooperative learning model with high order thinking skills questions: an understanding on geometry

NASA Astrophysics Data System (ADS)

Sari, P. P.; Budiyono; Slamet, I.

2018-05-01

Geometry, a branch of mathematics, has an important role in mathematics learning. This research aims to find out the effect of learning model, emotional intelligence, and the interaction between learning model and emotional intelligence toward students’ mathematics achievement. This research is quasi-experimental research with 2 × 3 factorial design. The sample in this research included 179 Senior High School students on 11th grade in Sukoharjo Regency, Central Java, Indonesia in academic year of 2016/2017. The sample was taken by using stratified cluster random sampling. The results showed that: the student are taught by Thinking Aloud Pairs Problem-Solving using HOTs questions provides better mathematics learning achievement than Make A Match using HOTs questions. High emotional intelligence students have better mathematics learning achievement than moderate and low emotional intelligence students, and moderate emotional intelligence students have better mathematics learning achievement than low emotional intelligence students. There is an interaction between learning model and emotional intelligence, and these affect mathematics learning achievement. We conclude that appropriate learning model can support learning activities become more meaningful and facilitate students to understand material. For further research, we suggest to explore the contribution of other aspects in cooperative learning modification to mathematics achievement.

Mathematical modeling of a process the rolling delivery

NASA Astrophysics Data System (ADS)

Stepanov, Mikhail A.; Korolev, Andrey A.

2018-03-01

An adduced analysis of the scientific researches in a domain of the rolling equipments, also research of properties the working material. A one of perspective direction of scientific research this is mathematical modeling. That is broadly used in many scientific disciplines and especially at the technical, applied sciences. With the aid of mathematical modeling it can be study of physical properties of the researching objects and systems. A research of the rolling delivery and transporting devices realized with the aid of a construction of mathematical model of appropriate process. To be described the basic principles and conditions of a construction of mathematical models of the real objects. For example to be consider a construction of mathematical model the rolling delivery device. For a construction that is model used system of the equations, which consist of: Lagrange’s equation of a motion, describing of the law conservation of energy of a mechanical system, and the Navier - Stokes equations, which characterize of the flow of a continuous non-compressed fluid. A construction of mathematical model the rolling deliver to let determined of a total energy of device, and therefore to got the dependence upon the power of drive to a gap between of rolls. A corroborate the hypothesis about laminar the flow of a material into the rolling gap of deliver.

Promoting students’ mathematical problem-solving skills through 7e learning cycle and hypnoteaching model

NASA Astrophysics Data System (ADS)

Saleh, H.; Suryadi, D.; Dahlan, J. A.

2018-01-01

The aim of this research was to find out whether 7E learning cycle under hypnoteaching model can enhance students’ mathematical problem-solving skill. This research was quasi-experimental study. The design of this study was pretest-posttest control group design. There were two groups of sample used in the study. The experimental group was given 7E learning cycle under hypnoteaching model, while the control group was given conventional model. The population of this study was the student of mathematics education program at one university in Tangerang. The statistical analysis used to test the hypothesis of this study were t-test and Mann-Whitney U. The result of this study show that: (1) The students’ achievement of mathematical problem solving skill who obtained 7E learning cycle under hypnoteaching model are higher than the students who obtained conventional model; (2) There are differences in the students’ enhancement of mathematical problem-solving skill based on students’ prior mathematical knowledge (PMK) category (high, middle, and low).

Segregation effects during solidification in weightless melts. [effects of evaporation and solidification on crystalization

NASA Technical Reports Server (NTRS)

Li, C.

1975-01-01

Computer programs are developed and used in the study of the combined effects of evaporation and solidification in space processing. The temperature and solute concentration profiles during directional solidification of binary alloys with surface evaporation were mathematically formulated. Computer results are included along with an econotechnical model of crystal growth. This model allows: prediction of crystal size, quality, and cost; systematic selection of the best growth equipment or alloy system; optimization of growth or material parameters; and a maximization of zero-gravity effects. Segregation in GaAs crystals was examined along with vibration effects on GaAs crystal growth. It was found that a unique segregation pattern and strong convention currents exist in GaAs crystal growth. Some beneficial effects from vibration during GaAs growth were discovered. The implications of the results in space processing are indicated.

A systematic analysis of the Braitenberg vehicle 2b for point-like stimulus sources.

PubMed

Rañó, Iñaki

2012-09-01

Braitenberg vehicles have been used experimentally for decades in robotics with limited empirical understanding. This paper presents the first mathematical model of the vehicle 2b, displaying so-called aggression behaviour, and analyses the possible trajectories for point-like smooth stimulus sources. This sensory-motor steering control mechanism is used to implement biologically grounded target approach, target-seeking or obstacle-avoidance behaviour. However, the analysis of the resulting model reveals that complex and unexpected trajectories can result even for point-like stimuli. We also prove how the implementation of the controller and the vehicle morphology interact to affect the behaviour of the vehicle. This work provides a better understanding of Braitenberg vehicle 2b, explains experimental results and paves the way for a formally grounded application on robotics as well as for a new way of understanding target seeking in biology.

Physical principle of airway design in human lungs

NASA Astrophysics Data System (ADS)

Park, Keunhwan; Son, Taeho; Kim, Wonjung; Kim, Ho-Young

2014-11-01

From an engineering perspective, lungs are natural microfluidic devices that extract oxygen from air. In the bronchial tree, airways branch by dichotomy with a systematic reduction of their diameters. It is generally accepted that in conducting airways, which air passes on the way to the acinar airways from the atmosphere, the reduction ratio of diameter is closely related to the minimization of viscous dissipation. Such a principle is formulated as the Hess-Murray law. However, in acinar airways, where oxygen transfer to alveolae occurs, the diameter reduction with progressive generations is more moderate than in conducting airways. Noting that the dominant transfer mechanism in acinar airways is diffusion rather than advection, unlike conducting airways, we construct a mathematical model for oxygen transfer through a series of acinar airways. Our model allows us to predict the optimal airway reduction ratio that maximizes the oxygen transfer in a finite airway volume, thereby rationalizing the observed airway reduction ratio in acinar airways.

Unsteady viscous effects in the flow over an oscillating surface. [mathematical model

NASA Technical Reports Server (NTRS)

Lerner, J. I.

1972-01-01

A theoretical model for the interaction of a turbulent boundary layer with an oscillating wavy surface over which a fluid is flowing is developed, with an application to wind-driven water waves and to panel flutter in low supersonic flow. A systematic methodology is developed to obtain the surface pressure distribution by considering separately the effects on the perturbed flow of a mean shear velocity profile, viscous stresses, the turbulent Reynolds stresses, compressibility, and three-dimensionality. The inviscid theory is applied to the wind-water wave problem by specializing to traveling-wave disturbances, and the pressure magnitude and phase shift as a function of the wave phase speed are computed for a logarithmic mean velocity profile and compared with inviscid theory and experiment. The results agree with experimental evidence for the stabilization of the panel motion due to the influence of the unsteady boundary layer.

On the nature of explanation: A PDP approach

NASA Astrophysics Data System (ADS)

Churchland, Paul M.

1990-06-01

Neural network models of sensory processing and associative memory provide the resources for a new theory of what explanatory understanding consists in. That theory finds the theoretically important factors to reside not at the level of propositions and the relations between them, but at the level of the activation patterns across large populations of neurons. The theory portrays explanatory understanding, perceptual recognition, and abductive inference as being different instances of the same more general sort of cognitive achievement, viz. prototype activation. It thus effects a unification of the theories of explanation, perception, and ampliative inference. It also finds systematic unity in the wide diversity of types of explanation (causal, functional, mathematical, intentional, reductive, etc.), a chronic problem for theories of explanation in the logico-linguistic tradition. Finally, it is free of the many defects, both logical and psychological, that plague models in that older tradition.

Market-Based Coordination of Thermostatically Controlled Loads—Part I: A Mechanism Design Formulation

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

Li, Sen; Zhang, Wei; Lian, Jianming

This paper focuses on the coordination of a population of Thermostatically Controlled Loads (TCLs) with unknown parameters to achieve group objectives. The problem involves designing the bidding and market clearing strategy to motivate self-interested users to realize efficient energy allocation subject to a peak power constraint. Using the mechanism design approach, we propose a market-based coordination framework, which can effectively incorporate heterogeneous load dynamics, systematically deal with user preferences, account for the unknown load model parameters, and enable the real-world implementation with limited communication resources. This paper is divided into two parts. Part I presents a mathematical formulation of themore » problem and develops a coordination framework using the mechanism design approach. Part II presents a learning scheme to account for the unknown load model parameters, and evaluates the proposed framework through realistic simulations.« less

The paranasal sinuses: the last frontier in craniofacial biology.

PubMed

Márquez, Samuel

2008-11-01

This special issue of the Anatomical Record explores the presence and diversity of paranasal sinuses in distinct vertebrate groups. The following topics are addressed in particular: dinosaur physiology; development; physiology; adaptation; imaging; and primate systematics. A variety of approaches and techniques are used to examine and characterize the diversity of paranasal sinus pneumatization in a wide spectrum of vertebrates. These range from dissection to histology, from plain X-rays to computer tomography, from comparative anatomy to natural experimental settings, from mathematical computation to computer model simulation, and 2D to 3D reconstructions. The articles in this issue are a combination of literature review and new, hypothesis-driven anatomical research that highlights the complexities of paranasal sinus growth and development; ontogenetic and disease processes; physiology; paleontology; primate systematics; and human evolution. The issue incorporates a wide variety of vertebrates, encompassing a period of over 65 million years, in an effort to offer insight into the diversity of the paranasal sinus complexes through time and space, and thereby providing a greater understanding and appreciation of these special spaces within the cranium. Copyright 2008 Wiley-Liss, Inc.

Synthetic in vitro transcriptional oscillators

PubMed Central

Kim, Jongmin; Winfree, Erik

2011-01-01

The construction of synthetic biochemical circuits from simple components illuminates how complex behaviors can arise in chemistry and builds a foundation for future biological technologies. A simplified analog of genetic regulatory networks, in vitro transcriptional circuits, provides a modular platform for the systematic construction of arbitrary circuits and requires only two essential enzymes, bacteriophage T7 RNA polymerase and Escherichia coli ribonuclease H, to produce and degrade RNA signals. In this study, we design and experimentally demonstrate three transcriptional oscillators in vitro. First, a negative feedback oscillator comprising two switches, regulated by excitatory and inhibitory RNA signals, showed up to five complete cycles. To demonstrate modularity and to explore the design space further, a positive-feedback loop was added that modulates and extends the oscillatory regime. Finally, a three-switch ring oscillator was constructed and analyzed. Mathematical modeling guided the design process, identified experimental conditions likely to yield oscillations, and explained the system's robust response to interference by short degradation products. Synthetic transcriptional oscillators could prove valuable for systematic exploration of biochemical circuit design principles and for controlling nanoscale devices and orchestrating processes within artificial cells. PMID:21283141

Systematic Validation of Protein Force Fields against Experimental Data

PubMed Central

Eastwood, Michael P.; Dror, Ron O.; Shaw, David E.

2012-01-01

Molecular dynamics simulations provide a vehicle for capturing the structures, motions, and interactions of biological macromolecules in full atomic detail. The accuracy of such simulations, however, is critically dependent on the force field—the mathematical model used to approximate the atomic-level forces acting on the simulated molecular system. Here we present a systematic and extensive evaluation of eight different protein force fields based on comparisons of experimental data with molecular dynamics simulations that reach a previously inaccessible timescale. First, through extensive comparisons with experimental NMR data, we examined the force fields' abilities to describe the structure and fluctuations of folded proteins. Second, we quantified potential biases towards different secondary structure types by comparing experimental and simulation data for small peptides that preferentially populate either helical or sheet-like structures. Third, we tested the force fields' abilities to fold two small proteins—one α-helical, the other with β-sheet structure. The results suggest that force fields have improved over time, and that the most recent versions, while not perfect, provide an accurate description of many structural and dynamical properties of proteins. PMID:22384157

Predicting Relationships between Mathematics Anxiety, Mathematics Teaching Anxiety, Self-Efficacy Beliefs towards Mathematics and Mathematics Teaching

ERIC Educational Resources Information Center

Unlu, Melihan; Ertekin, Erhan; Dilmac, Bulent

2017-01-01

The purpose of the research is to investigate the relationships between self-efficacy beliefs toward mathematics, mathematics anxiety and self-efficacy beliefs toward mathematics teaching, mathematics teaching anxiety variables and testing the relationships between these variables with structural equation model. The sample of the research, which…

A generic biogeochemical module for Earth system models: Next Generation BioGeoChemical Module (NGBGC), version 1.0

NASA Astrophysics Data System (ADS)

Fang, Y.; Huang, M.; Liu, C.; Li, H.; Leung, L. R.

2013-11-01

Physical and biogeochemical processes regulate soil carbon dynamics and CO2 flux to and from the atmosphere, influencing global climate changes. Integration of these processes into Earth system models (e.g., community land models (CLMs)), however, currently faces three major challenges: (1) extensive efforts are required to modify modeling structures and to rewrite computer programs to incorporate new or updated processes as new knowledge is being generated, (2) computational cost is prohibitively expensive to simulate biogeochemical processes in land models due to large variations in the rates of biogeochemical processes, and (3) various mathematical representations of biogeochemical processes exist to incorporate different aspects of fundamental mechanisms, but systematic evaluation of the different mathematical representations is difficult, if not impossible. To address these challenges, we propose a new computational framework to easily incorporate physical and biogeochemical processes into land models. The new framework consists of a new biogeochemical module, Next Generation BioGeoChemical Module (NGBGC), version 1.0, with a generic algorithm and reaction database so that new and updated processes can be incorporated into land models without the need to manually set up the ordinary differential equations to be solved numerically. The reaction database consists of processes of nutrient flow through the terrestrial ecosystems in plants, litter, and soil. This framework facilitates effective comparison studies of biogeochemical cycles in an ecosystem using different conceptual models under the same land modeling framework. The approach was first implemented in CLM and benchmarked against simulations from the original CLM-CN code. A case study was then provided to demonstrate the advantages of using the new approach to incorporate a phosphorus cycle into CLM. To our knowledge, the phosphorus-incorporated CLM is a new model that can be used to simulate phosphorus limitation on the productivity of terrestrial ecosystems. The method presented here could in theory be applied to simulate biogeochemical cycles in other Earth system models.

The mathematical and computer modeling of the worm tool shaping

NASA Astrophysics Data System (ADS)

Panchuk, K. L.; Lyashkov, A. A.; Ayusheev, T. V.

2017-06-01

Traditionally mathematical profiling of the worm tool is carried out on the first T. Olivier method, known in the theory of gear gearings, with receiving an intermediate surface of the making lath. It complicates process of profiling and its realization by means of computer 3D-modeling. The purpose of the work is the improvement of mathematical model of profiling and its realization based on the methods of 3D-modeling. Research problems are: receiving of the mathematical model of profiling which excludes the presence of the making lath in it; realization of the received model by means of frame and superficial modeling; development and approbation of technology of solid-state modeling for the solution of the problem of profiling. As the basic, the kinematic method of research of the mutually envelope surfaces is accepted. Computer research is executed by means of CAD based on the methods of 3D-modeling. We have developed mathematical model of profiling of the worm tool; frame, superficial and solid-state models of shaping of the mutually enveloping surfaces of the detail and the tool are received. The offered mathematical models and the technologies of 3D-modeling of shaping represent tools for theoretical and experimental profiling of the worm tool. The results of researches can be used at design of metal-cutting tools.

Valid and Reliable Science Content Assessments for Science Teachers

NASA Astrophysics Data System (ADS)

Tretter, Thomas R.; Brown, Sherri L.; Bush, William S.; Saderholm, Jon C.; Holmes, Vicki-Lynn

2013-03-01

Science teachers' content knowledge is an important influence on student learning, highlighting an ongoing need for programs, and assessments of those programs, designed to support teacher learning of science. Valid and reliable assessments of teacher science knowledge are needed for direct measurement of this crucial variable. This paper describes multiple sources of validity and reliability (Cronbach's alpha greater than 0.8) evidence for physical, life, and earth/space science assessments—part of the Diagnostic Teacher Assessments of Mathematics and Science (DTAMS) project. Validity was strengthened by systematic synthesis of relevant documents, extensive use of external reviewers, and field tests with 900 teachers during assessment development process. Subsequent results from 4,400 teachers, analyzed with Rasch IRT modeling techniques, offer construct and concurrent validity evidence.

Dynamical decoupling of unbounded Hamiltonians

NASA Astrophysics Data System (ADS)

Arenz, Christian; Burgarth, Daniel; Facchi, Paolo; Hillier, Robin

2018-03-01

We investigate the possibility to suppress interactions between a finite dimensional system and an infinite dimensional environment through a fast sequence of unitary kicks on the finite dimensional system. This method, called dynamical decoupling, is known to work for bounded interactions, but physical environments such as bosonic heat baths are usually modeled with unbounded interactions; hence, here, we initiate a systematic study of dynamical decoupling for unbounded operators. We develop a sufficient decoupling criterion for arbitrary Hamiltonians and a necessary decoupling criterion for semibounded Hamiltonians. We give examples for unbounded Hamiltonians where decoupling works and the limiting evolution as well as the convergence speed can be explicitly computed. We show that decoupling does not always work for unbounded interactions and we provide both physically and mathematically motivated examples.

Retardation of organo-bromides in a fractured chalk aquitard.

PubMed

Ezra, Shai; Feinstein, Shimon; Yakirevich, Alex; Adar, Eilon; Bilkis, Itzhak

2006-08-10

This study investigates the mechanisms controlling the distribution of 3-bromo-2,2-bis(bromomethyl)propanol (TBNPA) and 2,2-bis(bromomethyl)propan-1,3-diol (DBNPG) in a fractured chalk aquitard. An extensive monitoring program showed a systematic decrease in the TBNPA/DBNPG ratio with distance from the contamination source. Sorption of TBNPA on the white and/or gray chalks comprising the aquitard is approximately one order of magnitude greater than that of DBNPG. This results in more efficient removal of TBNPA from the fracture into the porous matrix and thus decreases the TBNPA/DBNPG ratio in the fracture water. Mathematical modeling of solute transport in the fracture domain illustrates the probable importance of sorption in controlling the spatial variation in TBNPA and DBNPG ratio.

A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-off on Phenotype Robustness in Biological Networks Part I: Gene Regulatory Networks in Systems and Evolutionary Biology

PubMed Central

Chen, Bor-Sen; Lin, Ying-Po

2013-01-01

Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties observed in biological systems at different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be enough to confer intrinsic robustness in order to tolerate intrinsic parameter fluctuations, genetic robustness for buffering genetic variations, and environmental robustness for resisting environmental disturbances. With this, the phenotypic stability of biological network can be maintained, thus guaranteeing phenotype robustness. This paper presents a survey on biological systems and then develops a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation in systems and evolutionary biology. Further, from the unifying mathematical framework, it was discovered that the phenotype robustness criterion for biological networks at different levels relies upon intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness. When this is true, the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in systems and evolutionary biology can also be investigated through their corresponding phenotype robustness criterion from the systematic point of view. PMID:23515240

A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-off on Phenotype Robustness in Biological Networks Part I: Gene Regulatory Networks in Systems and Evolutionary Biology.

PubMed

Chen, Bor-Sen; Lin, Ying-Po

2013-01-01

Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties observed in biological systems at different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be enough to confer intrinsic robustness in order to tolerate intrinsic parameter fluctuations, genetic robustness for buffering genetic variations, and environmental robustness for resisting environmental disturbances. With this, the phenotypic stability of biological network can be maintained, thus guaranteeing phenotype robustness. This paper presents a survey on biological systems and then develops a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation in systems and evolutionary biology. Further, from the unifying mathematical framework, it was discovered that the phenotype robustness criterion for biological networks at different levels relies upon intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness. When this is true, the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in systems and evolutionary biology can also be investigated through their corresponding phenotype robustness criterion from the systematic point of view.

A Structural Equation Model Explaining 8th Grade Students' Mathematics Achievements

ERIC Educational Resources Information Center

Yurt, Eyüp; Sünbül, Ali Murat

2014-01-01

The purpose of this study is to investigate, via a model, the explanatory and predictive relationships among the following variables: Mathematical Problem Solving and Reasoning Skills, Sources of Mathematics Self-Efficacy, Spatial Ability, and Mathematics Achievements of Secondary School 8th Grade Students. The sample group of the study, itself…

Understanding the Difficulties Faced by Engineering Undergraduates in Learning Mathematical Modelling

ERIC Educational Resources Information Center

Soon, Wanmei; Lioe, Luis Tirtasanjaya; McInnes, Brett

2011-01-01

The teaching of mathematics in Singapore continues, in most cases, to follow a traditional model. While this traditional approach has many advantages, it does not always adequately prepare students for University-level mathematics, especially applied mathematics. In particular, it does not cultivate the ability to deal with "non-routine…

Improving Primary School Prospective Teachers' Understanding of the Mathematics Modeling Process

ERIC Educational Resources Information Center

Bal, Aytgen Pinar; Doganay, Ahmet

2014-01-01

The development of mathematical thinking plays an important role on the solution of problems faced in daily life. Determining the relevant variables and necessary procedural steps in order to solve problems constitutes the essence of mathematical thinking. Mathematical modeling provides an opportunity for explaining thoughts in real life by making…

Science Modelling in Pre-Calculus: How to Make Mathematics Problems Contextually Meaningful

ERIC Educational Resources Information Center

Sokolowski, Andrzej; Yalvac, Bugrahan; Loving, Cathleen

2011-01-01

"Use of mathematical representations to model and interpret physical phenomena and solve problems is one of the major teaching objectives in high school math curriculum" [National Council of Teachers of Mathematics (NCTM), "Principles and Standards for School Mathematics", NCTM, Reston, VA, 2000]. Commonly used pre-calculus textbooks provide a…

Opinions of Secondary School Mathematics Teachers on Mathematical Modelling

ERIC Educational Resources Information Center

Tutak, Tayfun; Güder, Yunus

2013-01-01

The aim of this study is to identify the opinions of secondary school mathematics teachers about mathematical modelling. Qualitative research was used. The participants of the study were 40 secondary school teachers working in the Bingöl Province in Turkey during 2012-2013 education year. Semi-structured interview form prepared by the researcher…

External Representations for Data Distributions: In Search of Cognitive Fit

ERIC Educational Resources Information Center

Lem, Stephanie; Onghana, Patrick; Verschaffel, Lieven; Van Dooren, Wim

2013-01-01

Data distributions can be represented using different external representations, such as histograms and boxplots. Although the role of external representations has been extensively studied in mathematics, this is less the case in statistics. This study helps to fill this gap by systematically varying the representation that accompanies a task…

Improving Performance through the Use of Humor.

ERIC Educational Resources Information Center

Adair, Frank A.; Siegel, Laurence

Although the role of humor in relaxation and interpersonal relationships is well documented, its role in increasing performance in the classroom has not been systematically studied. To investigate the effect of appropriately timed humor on performance of a stressful task, 40 college students performed a mathematics test under one of four…

STEM Motivation Interventions for Adolescents: A Promising Start, but Further to Go

ERIC Educational Resources Information Center

Rosenzweig, Emily Q.; Wigfield, Allan

2016-01-01

One way to increase students' participation in science, technology, engineering, and mathematics (STEM) fields is to target their motivation. Researchers have conducted a growing number of interventions addressing students' motivation in STEM; however, this body of work has not been adequately reviewed. We systematically reviewed experimental and…

Teacher Performance Trajectories in High- and Lower-Poverty Schools

ERIC Educational Resources Information Center

Xu, Zeyu; Özek, Umut; Hansen, Michael

2015-01-01

This study explores whether teacher performance trajectory over time differs by school-poverty settings. Focusing on elementary school mathematics teachers in North Carolina and Florida, we find no systematic relationship between school student poverty rates and teacher performance trajectories. In both high- (=60% free/reduced-price lunch [FRPL])…

Dissociating Averageness and Attractiveness: Attractive Faces Are Not Always Average

ERIC Educational Resources Information Center

DeBruine, Lisa M.; Jones, Benedict C.; Unger, Layla; Little, Anthony C.; Feinberg, David R.

2007-01-01

Although the averageness hypothesis of facial attractiveness proposes that the attractiveness of faces is mostly a consequence of their averageness, 1 study has shown that caricaturing highly attractive faces makes them mathematically less average but more attractive. Here the authors systematically test the averageness hypothesis in 5 experiments…

What Is Scientifically-Based Research on Progress Monitoring?

ERIC Educational Resources Information Center

Fuchs, Lynn S.; Fuchs, Douglas

2001-01-01

When teachers use systematic progress monitoring to track their students progress in reading, mathematics, or spelling, they are better able to identify students in need of additional or different forms of instruction, they design stronger instructional programs, and their students achieve better. This document first describes progress monitoring…

Microbial interaction networks in soil and in silico

NASA Astrophysics Data System (ADS)

Vetsigian, Kalin

2012-02-01

Soil harbors a huge number of microbial species interacting through secretion of antibiotics and other chemicals. What patterns of species interactions allow for this astonishing biodiversity to be sustained, and how do these interactions evolve? I used a combined experimental-theoretical approach to tackle these questions. Focusing on bacteria from the genus Steptomyces, known for their diverse secondary metabolism, I isolated 64 natural strains from several individual grains of soil and systematically measured all pairwise interactions among them. Quantitative measurements on such scale were enabled by a novel experimental platform based on robotic handling, a custom scanner array and automatic image analysis. This unique platform allowed the simultaneous capturing of ˜15,000 time-lapse movies of growing colonies of each isolate on media conditioned by each of the other isolates. The data revealed a rich network of strong negative (inhibitory) and positive (stimulating) interactions. Analysis of this network and the phylogeny of the isolates, together with mathematical modeling of microbial communities, revealed that: 1) The network of interactions has three special properties: ``balance'', ``bi- modality'' and ``reciprocity''; 2) The interaction network is fast evolving; 3) Mathematical modeling explains how rapid evolution can give rise to the three special properties through an interplay between ecology and evolution. These properties are not a result of stable co-existence, but rather of continuous evolutionary turnover of strains with different production and resistance capabilities.

Mathematical modeling of a Ti:sapphire solid-state laser

NASA Technical Reports Server (NTRS)

Swetits, John J.

1987-01-01

The project initiated a study of a mathematical model of a tunable Ti:sapphire solid-state laser. A general mathematical model was developed for the purpose of identifying design parameters which will optimize the system, and serve as a useful predictor of the system's behavior.

Modelling and Optimizing Mathematics Learning in Children

ERIC Educational Resources Information Center

Käser, Tanja; Busetto, Alberto Giovanni; Solenthaler, Barbara; Baschera, Gian-Marco; Kohn, Juliane; Kucian, Karin; von Aster, Michael; Gross, Markus

2013-01-01

This study introduces a student model and control algorithm, optimizing mathematics learning in children. The adaptive system is integrated into a computer-based training system for enhancing numerical cognition aimed at children with developmental dyscalculia or difficulties in learning mathematics. The student model consists of a dynamic…

Mathematical Modelling in Engineering: A Proposal to Introduce Linear Algebra Concepts

ERIC Educational Resources Information Center

Cárcamo Bahamonde, Andrea; Gómez Urgelles, Joan; Fortuny Aymemí, Josep

2016-01-01

The modern dynamic world requires that basic science courses for engineering, including linear algebra, emphasise the development of mathematical abilities primarily associated with modelling and interpreting, which are not exclusively calculus abilities. Considering this, an instructional design was created based on mathematical modelling and…

Mathematical Manipulative Models: In Defense of "Beanbag Biology"

ERIC Educational Resources Information Center

Jungck, John R.; Gaff, Holly; Weisstein, Anton E.

2010-01-01

Mathematical manipulative models have had a long history of influence in biological research and in secondary school education, but they are frequently neglected in undergraduate biology education. By linking mathematical manipulative models in a four-step process--1) use of physical manipulatives, 2) interactive exploration of computer…

Turbine Engine Mathematical Model Validation

DTIC Science & Technology

1976-12-01

AEDC-TR-76-90 ~Ec i ? Z985 TURBINE ENGINE MATHEMATICAL MODEL VALIDATION ENGINE TEST FACILITY ARNOLD ENGINEERING DEVELOPMENT CENTER AIR FORCE...i f n e c e s e a ~ ~ d i den t i f y by b l ock number) YJI01-GE-100 engine turbine engines mathematical models computations mathematical...report presents and discusses the results of an investigation to develop a rationale and technique for the validation of turbine engine steady-state

An Evaluative Review of Simulated Dynamic Smart 3d Objects

NASA Astrophysics Data System (ADS)

Romeijn, H.; Sheth, F.; Pettit, C. J.

2012-07-01

Three-dimensional (3D) modelling of plants can be an asset for creating agricultural based visualisation products. The continuum of 3D plants models ranges from static to dynamic objects, also known as smart 3D objects. There is an increasing requirement for smarter simulated 3D objects that are attributed mathematically and/or from biological inputs. A systematic approach to plant simulation offers significant advantages to applications in agricultural research, particularly in simulating plant behaviour and the influences of external environmental factors. This approach of 3D plant object visualisation is primarily evident from the visualisation of plants using photographed billboarded images, to more advanced procedural models that come closer to simulating realistic virtual plants. However, few programs model physical reactions of plants to external factors and even fewer are able to grow plants based on mathematical and/or biological parameters. In this paper, we undertake an evaluation of plant-based object simulation programs currently available, with a focus upon the components and techniques involved in producing these objects. Through an analytical review process we consider the strengths and weaknesses of several program packages, the features and use of these programs and the possible opportunities in deploying these for creating smart 3D plant-based objects to support agricultural research and natural resource management. In creating smart 3D objects the model needs to be informed by both plant physiology and phenology. Expert knowledge will frame the parameters and procedures that will attribute the object and allow the simulation of dynamic virtual plants. Ultimately, biologically smart 3D virtual plants that react to changes within an environment could be an effective medium to visually represent landscapes and communicate land management scenarios and practices to planners and decision-makers.

Predicting tyrosinaemia: a mathematical model of 4-hydroxyphenylpyruvate dioxygenase inhibition by nitisinone in rats.

PubMed

Ward, John P; Dunster, Joanne L; Derks, Gianne; Mistry, Pratibha; Salazar, José D

2017-09-01

Nitisinone or 2-(2-nitro-4-trifluoromethylbenzoyl)cyclohexane-1,3-dione is a reversible inhibitor of 4-hydroxyphenylpyruvate dioxygenase (HPPD), an enzyme important in tyrosine catabolism. Today, nitisinone is successfully used to treat Hereditary Tyrosinaemia type 1, although its original expected role was as a herbicide. In laboratory animals, treatment with nitisinone leads to the elevation of plasma tyrosine (tyrosinaemia). In rats and Beagle dogs, repeat low-dose exposure to nitisinone leads to corneal opacities whilst similar studies in the mouse and Rhesus monkey showed no comparable toxicities or other treatment related findings. The differences in toxicological sensitivities have been related to the upper limit of the concentration of tyrosine that accumulates in plasma, which is driven by the amount/activity of tyrosine aminotransferase. A physiologically based, pharmacodynamics ordinary differential equation model of HPPD inhibition to bolus exposure of nitisinone in vivo is presented. Going beyond traditional approaches, asymptotic analysis is used to separate the different timescales of events involved in HPPD inhibition and tyrosinaemia. This analysis elucidates, in terms of the model parameters, a critical inhibitor concentration (at which tyrosine concentration starts to rise) and highlights the contribution of in vitro measured parameters to events in an in vivo system. Furthermore, using parameter-fitting methods, a systematically derived reduced model is shown to fit well to rat data, making explicit how the parameters are informed by such data. This model in combination with in vitro descriptors has potential as a surrogate for animal experimentation to predict tyrosinaemia, and further development can extend its application to other related medical scenarios. © The authors 2016. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

A Comparison of Deterministic and Stochastic Modeling Approaches for Biochemical Reaction Systems: On Fixed Points, Means, and Modes.

PubMed

Hahl, Sayuri K; Kremling, Andreas

2016-01-01

In the mathematical modeling of biochemical reactions, a convenient standard approach is to use ordinary differential equations (ODEs) that follow the law of mass action. However, this deterministic ansatz is based on simplifications; in particular, it neglects noise, which is inherent to biological processes. In contrast, the stochasticity of reactions is captured in detail by the discrete chemical master equation (CME). Therefore, the CME is frequently applied to mesoscopic systems, where copy numbers of involved components are small and random fluctuations are thus significant. Here, we compare those two common modeling approaches, aiming at identifying parallels and discrepancies between deterministic variables and possible stochastic counterparts like the mean or modes of the state space probability distribution. To that end, a mathematically flexible reaction scheme of autoregulatory gene expression is translated into the corresponding ODE and CME formulations. We show that in the thermodynamic limit, deterministic stable fixed points usually correspond well to the modes in the stationary probability distribution. However, this connection might be disrupted in small systems. The discrepancies are characterized and systematically traced back to the magnitude of the stoichiometric coefficients and to the presence of nonlinear reactions. These factors are found to synergistically promote large and highly asymmetric fluctuations. As a consequence, bistable but unimodal, and monostable but bimodal systems can emerge. This clearly challenges the role of ODE modeling in the description of cellular signaling and regulation, where some of the involved components usually occur in low copy numbers. Nevertheless, systems whose bimodality originates from deterministic bistability are found to sustain a more robust separation of the two states compared to bimodal, but monostable systems. In regulatory circuits that require precise coordination, ODE modeling is thus still expected to provide relevant indications on the underlying dynamics.

Conceptualization of Approaches and Thought Processes Emerging in Validating of Model in Mathematical Modeling in Technology Aided Environment

ERIC Educational Resources Information Center

Hidiroglu, Çaglar Naci; Bukova Güzel, Esra

2013-01-01

The aim of the present study is to conceptualize the approaches displayed for validation of model and thought processes provided in mathematical modeling process performed in technology-aided learning environment. The participants of this grounded theory study were nineteen secondary school mathematics student teachers. The data gathered from the…

An International Comparison Using a Diagnostic Testing Model: Turkish Students' Profile of Mathematical Skills on TIMSS-R

ERIC Educational Resources Information Center

Dogan, Enis; Tatsuoka, Kikumi

2008-01-01

This study illustrates how a diagnostic testing model can be used to make detailed comparisons between student populations participating in international assessments. The performance of Turkish students on the TIMSS-R mathematics test was reanalyzed with a diagnostic testing model called the Rule Space Model. First, mathematical and cognitive…

Review and verification of CARE 3 mathematical model and code

NASA Technical Reports Server (NTRS)

Rose, D. M.; Altschul, R. E.; Manke, J. W.; Nelson, D. L.

1983-01-01

The CARE-III mathematical model and code verification performed by Boeing Computer Services were documented. The mathematical model was verified for permanent and intermittent faults. The transient fault model was not addressed. The code verification was performed on CARE-III, Version 3. A CARE III Version 4, which corrects deficiencies identified in Version 3, is being developed.

The mathematics of cancer: integrating quantitative models.

PubMed

Altrock, Philipp M; Liu, Lin L; Michor, Franziska

2015-12-01

Mathematical modelling approaches have become increasingly abundant in cancer research. The complexity of cancer is well suited to quantitative approaches as it provides challenges and opportunities for new developments. In turn, mathematical modelling contributes to cancer research by helping to elucidate mechanisms and by providing quantitative predictions that can be validated. The recent expansion of quantitative models addresses many questions regarding tumour initiation, progression and metastases as well as intra-tumour heterogeneity, treatment responses and resistance. Mathematical models can complement experimental and clinical studies, but also challenge current paradigms, redefine our understanding of mechanisms driving tumorigenesis and shape future research in cancer biology.

Comments on "Drill-string horizontal dynamics with uncertainty on the frictional force" by T.G. Ritto, M.R. Escalante, Rubens Sampaio, M.B. Rosales [J. Sound Vib. 332 (2013) 145-153

NASA Astrophysics Data System (ADS)

Li, Zifeng

2016-12-01

This paper analyzes the mechanical and mathematical models in "Ritto et al. (2013) [1]". The results are that: (1) the mechanical model is obviously incorrect; (2) the mathematical model is not complete; (3) the differential equation is obviously incorrect; (4) the finite element equation is obviously not discretized from the corresponding mathematical model above, and is obviously incorrect. A mathematical model of dynamics should include the differential equations, the boundary conditions and the initial conditions.

Illustrations of mathematical modeling in biology: epigenetics, meiosis, and an outlook.

PubMed

Richards, D; Berry, S; Howard, M

2012-01-01

In the past few years, mathematical modeling approaches in biology have begun to fulfill their promise by assisting in the dissection of complex biological systems. Here, we review two recent examples of predictive mathematical modeling in plant biology. The first involves the quantitative epigenetic silencing of the floral repressor gene FLC in Arabidopsis, mediated by a Polycomb-based system. The second involves the spatiotemporal dynamics of telomere bouquet formation in wheat-rye meiosis. Although both the biology and the modeling framework of the two systems are different, both exemplify how mathematical modeling can help to accelerate discovery of the underlying mechanisms in complex biological systems. In both cases, the models that developed were relatively minimal, including only essential features, but both nevertheless yielded fundamental insights. We also briefly review the current state of mathematical modeling in biology, difficulties inherent in its application, and its potential future development.

Exploring Differential Effects of Mathematics Courses on Mathematics Achievement

ERIC Educational Resources Information Center

Ma, Xin; McIntyre, Laureen J.

2005-01-01

Using data from the Longitudinal Study of Mathematics Participation (N = 1,518 students from 34 schools), we investigated the effects of pure and applied mathematics courses on mathematics achievement, controlling for prior mathematics achievement. Results of multilevel modelling showed that the effects of pure mathematics were significant after…

Research Methods in Healthcare Epidemiology and Antimicrobial Stewardship-Mathematical Modeling.

PubMed

Barnes, Sean L; Kasaie, Parastu; Anderson, Deverick J; Rubin, Michael

2016-11-01

Mathematical modeling is a valuable methodology used to study healthcare epidemiology and antimicrobial stewardship, particularly when more traditional study approaches are infeasible, unethical, costly, or time consuming. We focus on 2 of the most common types of mathematical modeling, namely compartmental modeling and agent-based modeling, which provide important advantages-such as shorter developmental timelines and opportunities for extensive experimentation-over observational and experimental approaches. We summarize these advantages and disadvantages via specific examples and highlight recent advances in the methodology. A checklist is provided to serve as a guideline in the development of mathematical models in healthcare epidemiology and antimicrobial stewardship. Infect Control Hosp Epidemiol 2016;1-7.

Modelling for reactor-style aerobic composting based on coupling theory of mass-heat-momentum transport and Contois equation.

PubMed

He, Xueqin; Han, Lujia; Ge, Jinyi; Huang, Guangqun

2018-04-01

This study establishes an optimal mathematical modelling to rationally describe the dynamic changes and spatial distribution of temperature and oxygen concentration in the aerobic composting process using coupling mass-heat-momentum transfer based on the microbial mechanism. Two different conditional composting experiments, namely continuous aeration and intermittent aeration, were performed to verify the proposed model. The results show that the model accurately predicted the dynamic changes in temperature (case I: R 2  = 0.93, RMSE = 1.95 K; case II: R 2  = 0.86, RMSE = 4.69 K) and oxygen concentration (case I: R 2  = 0.90, RMSE = 1.26%; case II: R 2  = 0.75, RMSE = 2.93%) in the central point of compost substrates. It also systematically simulated fluctuations in oxygen concentration caused by boundary conditions and the spatial distribution of the actual temperature and oxygen concentration. The proposed model exhibits good applicability in simulating the actual working conditions of aerobic composting process. Copyright © 2018 Elsevier Ltd. All rights reserved.