Engaging Educators: Common Core State Standards Implementation

ERIC Educational Resources Information Center

Achieve, Inc., 2011

2011-01-01

To date, 44 states and the District of Columbia have adopted the Common Core State Standards (CCSS). Achieve has prepared this planning document to help all states in the American Diploma Project Network (ADP) and the Partnership for Assessment of Readiness for College and Careers (PARCC) consortium engage educators in the essential work of…

Guide to English Language Arts/Literacy Released Items: Understanding Scoring. 2015

ERIC Educational Resources Information Center

Partnership for Assessment of Readiness for College and Careers, 2015

2015-01-01

The Partnership for Assessment of Readiness for College and Careers (PARCC) is a group of states working together to develop a modern assessment that replaces previous state standardized tests. It provides better information for teachers and parents to identify where a student needs help, or is excelling, so they are able to enhance instruction to…

How PARCC's False Rigor Stunts the Academic Growth of All Students. White Paper No. 135

ERIC Educational Resources Information Center

McQuillan, Mark; Phelps, Richard P.; Stotsky, Sandra

2015-01-01

In July 2010, the Massachusetts Board of Elementary and Secondary Education (BESE) voted to adopt Common Core's standards in English language arts (ELA) and mathematics in place of the state's own standards in these two subjects. The vote was based largely on recommendations by Commissioner of Education Mitchell Chester and then Secretary of…

Personal-Level Factors and Google Docs Use in Monmouth County Middle Schools

ERIC Educational Resources Information Center

Tetreault, Steven G.

2014-01-01

Technology has become an essential part of the world, both in people's personal and professional lives. Digital assessments such as those being implemented in New Jersey as part of the Partnership for Assessment of Readiness for College and Careers (PARCC) will soon be instituted on a large scale; these require students to be able to utilize…

Preferred Information Platforms for Parents Choosing to Refuse Mandatory PARCC Testing in a Southern New Jersey School District

ERIC Educational Resources Information Center

Benson, Lauren

2017-01-01

This executive position paper identifies preferred modes of communication for parents and guardians in a small New Jersey Public School District. Research was conducted because there has been an unprecedented test refusal initiative by parents and guardians of New Jersey Public School Students who are mandated to sit for Partnership for Assessment…

Toward a "Common Definition of English Learner": A Brief Defining Policy and Technical Issues and Opportunities for State Assessment Consortia

ERIC Educational Resources Information Center

Linquanti, Robert; Cook, H. Gary

2013-01-01

The U.S. Department of Education (USED) requires states participating in either of the two Race to the Top assessment consortia (Smarter Balanced Assessment Consortium and Partnership for Assessment of Readiness for College and Careers [PARCC]), as well as those participating in either of the two Enhanced Assessment Grant (EAG) English language…

One-to-One Laptop Programs: Do Students in Identified Illinois High Schools Have an Advantage When State Assessments Are Computer-Based?

ERIC Educational Resources Information Center

Bleyer, Charles T.

2017-01-01

The purpose of this study was to determine if students in identified Illinois high schools who were a part of a one-to-one (1:1) laptop program achieved higher results on the computer-based Partnership for the Assessment of Readiness for College and Careers (PARCC) assessment than students in identified Illinois high schools that did not…

Why Massachusetts Should Abandon the PARCC Tests and the 2011 Coleman et al English Language Arts Standards on Which the MCAS Tests Are Based. Testimony

ERIC Educational Resources Information Center

Stotsky, Sandra

2015-01-01

In this testimony, the author first describes her qualifications, as well as the lack of relevant qualifications in Common Core's standards writers and in most of the members of Common Core's Validation Committee, on which she served in 2009-2010. The author then details some of the many problems in the 2011 Massachusetts ELA standards, written by…

Assessment 2.0: "Next-Generation" Comprehensive Assessment Systems. An Analysis of Proposals by the Partnership for the Assessment of Readiness for College and Careers and SMARTER Balanced Assessment Consortium

ERIC Educational Resources Information Center

Tamayo, Joaquin R., Jr.

2010-01-01

On September 2, 2010, the U.S. Department of Education announced the winners of the $350 million Race to the Top Comprehensive Assessment Systems Competition: the Partnership for the Assessment of Readiness for College and Careers (PARCC) and the SMARTER Balanced Assessment Consortium (SMARTER). In his announcement, Secretary of Education Arne…

[Estimation of forest canopy chlorophyll content based on PROSPECT and SAIL models].

PubMed

Yang, Xi-guang; Fan, Wen-yi; Yu, Ying

2010-11-01

The forest canopy chlorophyll content directly reflects the health and stress of forest. The accurate estimation of the forest canopy chlorophyll content is a significant foundation for researching forest ecosystem cycle models. In the present paper, the inversion of the forest canopy chlorophyll content was based on PROSPECT and SAIL models from the physical mechanism angle. First, leaf spectrum and canopy spectrum were simulated by PROSPECT and SAIL models respectively. And leaf chlorophyll content look-up-table was established for leaf chlorophyll content retrieval. Then leaf chlorophyll content was converted into canopy chlorophyll content by Leaf Area Index (LAD). Finally, canopy chlorophyll content was estimated from Hyperion image. The results indicated that the main effect bands of chlorophyll content were 400-900 nm, the simulation of leaf and canopy spectrum by PROSPECT and SAIL models fit better with the measured spectrum with 7.06% and 16.49% relative error respectively, the RMSE of LAI inversion was 0. 542 6 and the forest canopy chlorophyll content was estimated better by PROSPECT and SAIL models with precision = 77.02%.

[Detecting the moisture content of forest surface soil based on the microwave remote sensing technology.

PubMed

Li, Ming Ze; Gao, Yuan Ke; Di, Xue Ying; Fan, Wen Yi

2016-03-01

The moisture content of forest surface soil is an important parameter in forest ecosystems. It is practically significant for forest ecosystem related research to use microwave remote sensing technology for rapid and accurate estimation of the moisture content of forest surface soil. With the aid of TDR-300 soil moisture content measuring instrument, the moisture contents of forest surface soils of 120 sample plots at Tahe Forestry Bureau of Daxing'anling region in Heilongjiang Province were measured. Taking the moisture content of forest surface soil as the dependent variable and the polarization decomposition parameters of C band Quad-pol SAR data as independent variables, two types of quantitative estimation models (multilinear regression model and BP-neural network model) for predicting moisture content of forest surface soils were developed. The spatial distribution of moisture content of forest surface soil on the regional scale was then derived with model inversion. Results showed that the model precision was 86.0% and 89.4% with RMSE of 3.0% and 2.7% for the multilinear regression model and the BP-neural network model, respectively. It indicated that the BP-neural network model had a better performance than the multilinear regression model in quantitative estimation of the moisture content of forest surface soil. The spatial distribution of forest surface soil moisture content in the study area was then obtained by using the BP neural network model simulation with the Quad-pol SAR data.

Prediction of moisture variation during composting process: A comparison of mathematical models.

PubMed

Wang, Yongjiang; Ai, Ping; Cao, Hongliang; Liu, Zhigang

2015-10-01

This study was carried out to develop and compare three models for simulating the moisture content during composting. Model 1 described changes in water content using mass balance, while Model 2 introduced a liquid-gas transferred water term. Model 3 predicted changes in moisture content without complex degradation kinetics. Average deviations for Model 1-3 were 8.909, 7.422 and 5.374 kg m(-3) while standard deviations were 10.299, 8.374 and 6.095, respectively. The results showed that Model 1 is complex and involves more state variables, but can be used to reveal the effect of humidity on moisture content. Model 2 tested the hypothesis of liquid-gas transfer and was shown to be capable of predicting moisture content during composting. Model 3 could predict water content well without considering degradation kinetics. Copyright © 2015 Elsevier Ltd. All rights reserved.

Elementary Content Specialization: Models, Affordances, and Constraints

ERIC Educational Resources Information Center

Markworth, Kimberly A.; Brobst, Joseph; Ohana, Chris; Parker, Ruth

2016-01-01

Background: This study investigates the models of elementary content specialization (ECS) in elementary mathematics and science and the affordances and constraints related to ECS--both generally and in relation to specific models. Elementary content specialists are defined as full-time classroom teachers who are responsible for content instruction…

Middle-School Science Students' Scientific Modelling Performances Across Content Areas and Within a Learning Progression

NASA Astrophysics Data System (ADS)

Bamberger, Yael M.; Davis, Elizabeth A.

2013-01-01

This paper focuses on students' ability to transfer modelling performances across content areas, taking into consideration their improvement of content knowledge as a result of a model-based instruction. Sixty-five sixth grade students of one science teacher in an urban public school in the Midwestern USA engaged in scientific modelling practices that were incorporated into a curriculum focused on the nature of matter. Concept-process models were embedded in the curriculum, as well as emphasis on meta-modelling knowledge and modelling practices. Pre-post test items that required drawing scientific models of smell, evaporation, and friction were analysed. The level of content understanding was coded and scored, as were the following elements of modelling performance: explanation, comparativeness, abstraction, and labelling. Paired t-tests were conducted to analyse differences in students' pre-post tests scores on content knowledge and on each element of the modelling performances. These are described in terms of the amount of transfer. Students significantly improved in their content knowledge for the smell and the evaporation models, but not for the friction model, which was expected as that topic was not taught during the instruction. However, students significantly improved in some of their modelling performances for all the three models. This improvement serves as evidence that the model-based instruction can help students acquire modelling practices that they can apply in a new content area.

A hybrid intelligent method for three-dimensional short-term prediction of dissolved oxygen content in aquaculture.

PubMed

Chen, Yingyi; Yu, Huihui; Cheng, Yanjun; Cheng, Qianqian; Li, Daoliang

2018-01-01

A precise predictive model is important for obtaining a clear understanding of the changes in dissolved oxygen content in crab ponds. Highly accurate interval forecasting of dissolved oxygen content is fundamental to reduce risk, and three-dimensional prediction can provide more accurate results and overall guidance. In this study, a hybrid three-dimensional (3D) dissolved oxygen content prediction model based on a radial basis function (RBF) neural network, K-means and subtractive clustering was developed and named the subtractive clustering (SC)-K-means-RBF model. In this modeling process, K-means and subtractive clustering methods were employed to enhance the hyperparameters required in the RBF neural network model. The comparison of the predicted results of different traditional models validated the effectiveness and accuracy of the proposed hybrid SC-K-means-RBF model for three-dimensional prediction of dissolved oxygen content. Consequently, the proposed model can effectively display the three-dimensional distribution of dissolved oxygen content and serve as a guide for feeding and future studies.

A hybrid intelligent method for three-dimensional short-term prediction of dissolved oxygen content in aquaculture

PubMed Central

Yu, Huihui; Cheng, Yanjun; Cheng, Qianqian; Li, Daoliang

2018-01-01

A precise predictive model is important for obtaining a clear understanding of the changes in dissolved oxygen content in crab ponds. Highly accurate interval forecasting of dissolved oxygen content is fundamental to reduce risk, and three-dimensional prediction can provide more accurate results and overall guidance. In this study, a hybrid three-dimensional (3D) dissolved oxygen content prediction model based on a radial basis function (RBF) neural network, K-means and subtractive clustering was developed and named the subtractive clustering (SC)-K-means-RBF model. In this modeling process, K-means and subtractive clustering methods were employed to enhance the hyperparameters required in the RBF neural network model. The comparison of the predicted results of different traditional models validated the effectiveness and accuracy of the proposed hybrid SC-K-means-RBF model for three-dimensional prediction of dissolved oxygen content. Consequently, the proposed model can effectively display the three-dimensional distribution of dissolved oxygen content and serve as a guide for feeding and future studies. PMID:29466394

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.

How to Build a Course in Mathematical–Biological Modeling: Content and Processes for Knowledge and Skill

PubMed Central

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. PMID:20810966

A model for the distribution of watermarked digital content on mobile networks

NASA Astrophysics Data System (ADS)

Frattolillo, Franco; D'Onofrio, Salvatore

2006-10-01

Although digital watermarking can be considered one of the key technologies to implement the copyright protection of digital contents distributed on the Internet, most of the content distribution models based on watermarking protocols proposed in literature have been purposely designed for fixed networks and cannot be easily adapted to mobile networks. On the contrary, the use of mobile devices currently enables new types of services and business models, and this makes the development of new content distribution models for mobile environments strategic in the current scenario of the Internet. This paper presents and discusses a distribution model of watermarked digital contents for such environments able to achieve a trade-off between the needs of efficiency and security.

Cyberbullying behavior and adolescents' use of media with antisocial content: a cyclic process model.

PubMed

den Hamer, Anouk; Konijn, Elly A; Keijer, Micha G

2014-02-01

The present study examined the role of media use in adolescents' cyberbullying behavior. Following previous research, we propose a Cyclic Process Model of face-to-face victimization and cyberbullying through two mediating processes of anger/frustration and antisocial media content. This model was tested utilizing a cross-sectional design with adolescent participants (N=892). Exposure to antisocial media content was measured with a newly developed content-based scale (i.e., the C-ME), showing good psychometric qualities. Results of structural equation modeling showed that adolescents' exposure to antisocial media content was significantly associated with cyberbullying behavior, especially in adolescents who experienced anger and frustration due to face-to-face victimization. Goodness of fit indices demonstrated a good fit of the theoretical model to the data and indicated that exposure to antisocial media content acts as an amplifier in a cyclic process of victimization-related anger and cyberbullying behavior.

Fish tissue lipid-C:N relationships for correcting δ(13) C values and estimating lipid content in aquatic food-web studies.

PubMed

Hoffman, Joel C; Sierszen, Michael E; Cotter, Anne M

2015-11-15

Normalizing δ(13) C values of animal tissue for lipid content is necessary to accurately interpret food-web relationships from stable isotope analysis. To reduce the effort and expense associated with chemical extraction of lipids, various studies have tested arithmetic mass balance to mathematically normalize δ(13) C values for lipid content; however, the approach assumes that lipid content is related to the tissue C:N ratio. We evaluated two commonly used models for estimating tissue lipid content based on C:N ratio (a mass balance model and a stoichiometric model) by comparing model predictions to measure the lipid content of white muscle tissue. We then determined the effect of lipid model choice on δ(13) C values normalized using arithmetic mass balance. To do so, we used a collection of fish from Lake Superior spanning a wide range in lipid content (5% to 73% lipid). We found that the lipid content was positively related to the bulk muscle tissue C:N ratio. The two different lipid models produced similar estimates of lipid content based on tissue C:N, within 6% for tissue C:N values <7. Normalizing δ(13) C values using an arithmetic mass-balance equation based on either model yielded similar results, with a small bias (<1‰) compared with results based on chemical extraction. Among-species consistency in the relationship between fish muscle tissue C:N ratio and lipid content supports the application of arithmetic mass balance to normalize δ(13) C values for lipid content. The uncertainty associated with both lipid extraction quality and choice of model parameters constrains the achievable precision of normalized δ(13) C values to about ±1.0‰. Published in 2015. This article is a U.S. Government work and is in the public domain in the U.S.A.

Analytical calculation of electrolyte water content of a Proton Exchange Membrane Fuel Cell for on-board modelling applications

NASA Astrophysics Data System (ADS)

Ferrara, Alessandro; Polverino, Pierpaolo; Pianese, Cesare

2018-06-01

This paper proposes an analytical model of the water content of the electrolyte of a Proton Exchange Membrane Fuel Cell. The model is designed by accounting for several simplifying assumptions, which make the model suitable for on-board/online water management applications, while ensuring a good accuracy of the considered phenomena, with respect to advanced numerical solutions. The achieved analytical solution, expressing electrolyte water content, is compared with that obtained by means of a complex numerical approach, used to solve the same mathematical problem. The achieved results show that the mean error is below 5% for electrodes water content values ranging from 2 to 15 (given as boundary conditions), and it does not overcome 0.26% for electrodes water content above 5. These results prove the capability of the solution to correctly model electrolyte water content at any operating condition, aiming at embodiment into more complex frameworks (e.g., cell or stack models), related to fuel cell simulation, monitoring, control, diagnosis and prognosis.

Convergence of Internet and TV: The Commercial Viability of P2P Content Delivery

NASA Astrophysics Data System (ADS)

de Boever, Jorn

The popularity of (illegal) P2P (peer-to-peer) file sharing has a disruptive impact on Internet traffic and business models of content providers. In addition, several studies have found an increasing demand for bandwidth consuming content, such as video, on the Internet. Although P2P systems have been put forward as a scalable and inexpensive model to deliver such content, there has been relatively little economic analysis of the potentials and obstacles of P2P systems as a legal and commercial content distribution model. Many content providers encounter uncertainties regarding the adoption or rejection of P2P networks to spread content over the Internet. The recent launch of several commercial, legal P2P content distribution platforms increases the importance of an integrated analysis of the Strengths, Weaknesses, Opportunities and Threats (SWOT).

A degradation model for high kitchen waste content municipal solid waste.

PubMed

Chen, Yunmin; Guo, Ruyang; Li, Yu-Chao; Liu, Hailong; Zhan, Tony Liangtong

2016-12-01

Municipal solid waste (MSW) in developing countries has a high content of kitchen waste (KW), and therefore contains large quantities of water and non-hollocellulose degradable organics. The degradation of high KW content MSW cannot be well simulated by the existing degradation models, which are mostly established for low KW content MSW in developed countries. This paper presents a two-stage anaerobic degradation model for high KW content MSW with degradations of hollocellulose, sugars, proteins and lipids considered. The ranges of the proportions of chemical compounds in MSW components are summarized with the recommended values given. Waste components are grouped into rapidly or slowly degradable categories in terms of the degradation rates under optimal water conditions for degradation. In the proposed model, the unionized VFA inhibitions of hydrolysis/acidogenesis and methanogenesis are considered as well as the pH inhibition of methanogenesis. Both modest and serious VFA inhibitions can be modeled by the proposed model. Default values for the parameters in the proposed method can be used for predictions of degradations of both low and high KW content MSW. The proposed model was verified by simulating two laboratory experiments, in which low and high KW content MSW were used, respectively. The simulated results are in good agreement with the measured data of the experiments. The results show that under low VFA concentrations, the pH inhibition of methanogenesis is the main inhibition to be considered, while the inhibitions of both hydrolysis/acidogenesis and methanogenesis caused by unionized VFA are significant under high VFA concentrations. The model is also used to compare the degradation behaviors of low and high KW content MSW under a favorable environmental condition, and it shows that the gas potential of high KW content MSW releases more quickly. Copyright © 2016 Elsevier Ltd. All rights reserved.

Development of Prediction Model and Experimental Validation in Predicting the Curcumin Content of Turmeric (Curcuma longa L.).

PubMed

Akbar, Abdul; Kuanar, Ananya; Joshi, Raj K; Sandeep, I S; Mohanty, Sujata; Naik, Pradeep K; Mishra, Antaryami; Nayak, Sanghamitra

2016-01-01

The drug yielding potential of turmeric ( Curcuma longa L.) is largely due to the presence of phyto-constituent 'curcumin.' Curcumin has been found to possess a myriad of therapeutic activities ranging from anti-inflammatory to neuroprotective. Lack of requisite high curcumin containing genotypes and variation in the curcumin content of turmeric at different agro climatic regions are the major stumbling blocks in commercial production of turmeric. Curcumin content of turmeric is greatly influenced by environmental factors. Hence, a prediction model based on artificial neural network (ANN) was developed to map genome environment interaction basing on curcumin content, soli and climatic factors from different agroclimatic regions for prediction of maximum curcumin content at various sites to facilitate the selection of suitable region for commercial cultivation of turmeric. The ANN model was developed and tested using a data set of 119 generated by collecting samples from 8 different agroclimatic regions of Odisha. The curcumin content from these samples was measured that varied from 7.2% to 0.4%. The ANN model was trained with 11 parameters of soil and climatic factors as input and curcumin content as output. The results showed that feed-forward ANN model with 8 nodes (MLFN-8) was the most suitable one with R 2 value of 0.91. Sensitivity analysis revealed that minimum relative humidity, altitude, soil nitrogen content and soil pH had greater effect on curcumin content. This ANN model has shown proven efficiency for predicting and optimizing the curcumin content at a specific site.

Development of Prediction Model and Experimental Validation in Predicting the Curcumin Content of Turmeric (Curcuma longa L.)

PubMed Central

Akbar, Abdul; Kuanar, Ananya; Joshi, Raj K.; Sandeep, I. S.; Mohanty, Sujata; Naik, Pradeep K.; Mishra, Antaryami; Nayak, Sanghamitra

2016-01-01

The drug yielding potential of turmeric (Curcuma longa L.) is largely due to the presence of phyto-constituent ‘curcumin.’ Curcumin has been found to possess a myriad of therapeutic activities ranging from anti-inflammatory to neuroprotective. Lack of requisite high curcumin containing genotypes and variation in the curcumin content of turmeric at different agro climatic regions are the major stumbling blocks in commercial production of turmeric. Curcumin content of turmeric is greatly influenced by environmental factors. Hence, a prediction model based on artificial neural network (ANN) was developed to map genome environment interaction basing on curcumin content, soli and climatic factors from different agroclimatic regions for prediction of maximum curcumin content at various sites to facilitate the selection of suitable region for commercial cultivation of turmeric. The ANN model was developed and tested using a data set of 119 generated by collecting samples from 8 different agroclimatic regions of Odisha. The curcumin content from these samples was measured that varied from 7.2% to 0.4%. The ANN model was trained with 11 parameters of soil and climatic factors as input and curcumin content as output. The results showed that feed-forward ANN model with 8 nodes (MLFN-8) was the most suitable one with R2 value of 0.91. Sensitivity analysis revealed that minimum relative humidity, altitude, soil nitrogen content and soil pH had greater effect on curcumin content. This ANN model has shown proven efficiency for predicting and optimizing the curcumin content at a specific site. PMID:27766103

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements.

PubMed

Bai, Wenming; Yoshimura, Norio; Takayanagi, Masao; Che, Jingai; Horiuchi, Naomi; Ogiwara, Isao

2016-06-28

Nondestructive prediction of ingredient contents of farm products is useful to ship and sell the products with guaranteed qualities. Here, near-infrared spectroscopy is used to predict nondestructively total sugar, total organic acid, and total anthocyanin content in each blueberry. The technique is expected to enable the selection of only delicious blueberries from all harvested ones. The near-infrared absorption spectra of blueberries are measured with the diffuse reflectance mode at the positions not on the calyx. The ingredient contents of a blueberry determined by high-performance liquid chromatography are used to construct models to predict the ingredient contents from observed spectra. Partial least squares regression is used for the construction of the models. It is necessary to properly select the pretreatments for the observed spectra and the wavelength regions of the spectra used for analyses. Validations are necessary for the constructed models to confirm that the ingredient contents are predicted with practical accuracies. Here we present a protocol to construct and validate the models for nondestructive prediction of ingredient contents in blueberries by near-infrared spectroscopy.

Non-linear learning in online tutorial to enhance students’ knowledge on normal distribution application topic

NASA Astrophysics Data System (ADS)

Kartono; Suryadi, D.; Herman, T.

2018-01-01

This study aimed to analyze the enhancement of non-linear learning (NLL) in the online tutorial (OT) content to students’ knowledge of normal distribution application (KONDA). KONDA is a competence expected to be achieved after students studied the topic of normal distribution application in the course named Education Statistics. The analysis was performed by quasi-experiment study design. The subject of the study was divided into an experimental class that was given OT content in NLL model and a control class which was given OT content in conventional learning (CL) model. Data used in this study were the results of online objective tests to measure students’ statistical prior knowledge (SPK) and students’ pre- and post-test of KONDA. The statistical analysis test of a gain score of KONDA of students who had low and moderate SPK’s scores showed students’ KONDA who learn OT content with NLL model was better than students’ KONDA who learn OT content with CL model. Meanwhile, for students who had high SPK’s scores, the gain score of students who learn OT content with NLL model had relatively similar with the gain score of students who learn OT content with CL model. Based on those findings it could be concluded that the NLL model applied to OT content could enhance KONDA of students in low and moderate SPK’s levels. Extra and more challenging didactical situation was needed for students in high SPK’s level to achieve the significant gain score.

Effect of Anisotropy on the Resilient Behaviour of a Granular Material in Low Traffic Pavement

PubMed Central

Jing, Peng; Nowamooz, Hossein; Chazallon, Cyrille

2017-01-01

Granular materials are often used in pavement structures. The influence of anisotropy on the mechanical behaviour of granular materials is very important. The coupled effects of water content and fine content usually lead to more complex anisotropic behaviour. With a repeated load triaxial test (RLTT), it is possible to measure the anisotropic deformation behaviour of granular materials. This article initially presents an experimental study of the resilient repeated load response of a compacted clayey natural sand with three fine contents and different water contents. Based on anisotropic behaviour, the non-linear resilient model (Boyce model) is improved by the radial anisotropy coefficient γ3 instead of the axial anisotropy coefficient γ1. The results from both approaches (γ1 and γ3) are compared with the measured volumetric and deviatoric responses. These results confirm the capacity of the improved model to capture the general trend of the experiments. Finally, finite element calculations are performed with CAST3M in order to validate the improvement of the modified Boyce model (from γ1 to γ3). The modelling results indicate that the modified Boyce model with γ3 is more widely available in different water contents and different fine contents for this granular material. Besides, based on the results, the coupled effects of water content and fine content on the deflection of the structures can also be observed. PMID:29207504

Determination of Leaf Water Content by Visible and Near-Infrared Spectrometry and Multivariate Calibration in Miscanthus

DOE PAGES

Jin, Xiaoli; Shi, Chunhai; Yu, Chang Yeon; ...

2017-05-19

Leaf water content is one of the most common physiological parameters limiting efficiency of photosynthesis and biomass productivity in plants including Miscanthus. Therefore, it is of great significance to determine or predict the water content quickly and non-destructively. In this study, we explored the relationship between leaf water content and diffuse reflectance spectra in Miscanthus. Three multivariate calibrations including partial least squares (PLS), least squares support vector machine regression (LSSVR), and radial basis function (RBF) neural network (NN) were developed for the models of leaf water content determination. The non-linear models including RBF_LSSVR and RBF_NN showed higher accuracy than themore » PLS and Lin_LSSVR models. Moreover, 75 sensitive wavelengths were identified to be closely associated with the leaf water content in Miscanthus. The RBF_LSSVR and RBF_NN models for predicting leaf water content, based on 75 characteristic wavelengths, obtained the high determination coefficients of 0.9838 and 0.9899, respectively. The results indicated the non-linear models were more accurate than the linear models using both wavelength intervals. These results demonstrated that visible and near-infrared (VIS/NIR) spectroscopy combined with RBF_LSSVR or RBF_NN is a useful, non-destructive tool for determinations of the leaf water content in Miscanthus, and thus very helpful for development of drought-resistant varieties in Miscanthus.« less

Determination of Leaf Water Content by Visible and Near-Infrared Spectrometry and Multivariate Calibration in Miscanthus

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

Jin, Xiaoli; Shi, Chunhai; Yu, Chang Yeon

Leaf water content is one of the most common physiological parameters limiting efficiency of photosynthesis and biomass productivity in plants including Miscanthus. Therefore, it is of great significance to determine or predict the water content quickly and non-destructively. In this study, we explored the relationship between leaf water content and diffuse reflectance spectra in Miscanthus. Three multivariate calibrations including partial least squares (PLS), least squares support vector machine regression (LSSVR), and radial basis function (RBF) neural network (NN) were developed for the models of leaf water content determination. The non-linear models including RBF_LSSVR and RBF_NN showed higher accuracy than themore » PLS and Lin_LSSVR models. Moreover, 75 sensitive wavelengths were identified to be closely associated with the leaf water content in Miscanthus. The RBF_LSSVR and RBF_NN models for predicting leaf water content, based on 75 characteristic wavelengths, obtained the high determination coefficients of 0.9838 and 0.9899, respectively. The results indicated the non-linear models were more accurate than the linear models using both wavelength intervals. These results demonstrated that visible and near-infrared (VIS/NIR) spectroscopy combined with RBF_LSSVR or RBF_NN is a useful, non-destructive tool for determinations of the leaf water content in Miscanthus, and thus very helpful for development of drought-resistant varieties in Miscanthus.« less

Effect of Anisotropy on the Resilient Behaviour of a Granular Material in Low Traffic Pavement.

PubMed

Jing, Peng; Nowamooz, Hossein; Chazallon, Cyrille

2017-12-03

Granular materials are often used in pavement structures. The influence of anisotropy on the mechanical behaviour of granular materials is very important. The coupled effects of water content and fine content usually lead to more complex anisotropic behaviour. With a repeated load triaxial test (RLTT), it is possible to measure the anisotropic deformation behaviour of granular materials. This article initially presents an experimental study of the resilient repeated load response of a compacted clayey natural sand with three fine contents and different water contents. Based on anisotropic behaviour, the non-linear resilient model (Boyce model) is improved by the radial anisotropy coefficient γ ₃ instead of the axial anisotropy coefficient γ ₁. The results from both approaches ( γ ₁ and γ ₃) are compared with the measured volumetric and deviatoric responses. These results confirm the capacity of the improved model to capture the general trend of the experiments. Finally, finite element calculations are performed with CAST3M in order to validate the improvement of the modified Boyce model (from γ ₁ to γ ₃). The modelling results indicate that the modified Boyce model with γ ₃ is more widely available in different water contents and different fine contents for this granular material. Besides, based on the results, the coupled effects of water content and fine content on the deflection of the structures can also be observed.

Estimation water vapor content using the mixing ratio method and validated with the ANFIS PWV model

NASA Astrophysics Data System (ADS)

Suparta, W.; Alhasa, K. M.; Singh, M. S. J.

2017-05-01

This study reported the comparison between water vapor content, the surface meteorological data (pressure, temperature, and relative humidity), and precipitable water vapor (PWV) produced by PWV from adaptive neuro fuzzy inference system (ANFIS) for areas in the Universiti Kebangsaan Malaysia Bangi (UKMB) station. The water vapor content value was estimated with mixing ratio method and the surface meteorological data as the parameter inputs. The accuracy of water vapor content was validated with PWV from ANFIS PWV model for the period of 20-23 December 2016. The result showed that the water vapor content has a similar trend with the PWV which produced by ANFIS PWV model (r = 0.975 at the 99% confidence level). This indicates that the water vapor content that obtained with mixing ratio agreed very well with the ANFIS PWV model. In addition, this study also found, the pattern of water vapor content and PWV have more influenced by the relative humidity.

Dissolved oxygen content prediction in crab culture using a hybrid intelligent method

PubMed Central

Yu, Huihui; Chen, Yingyi; Hassan, ShahbazGul; Li, Daoliang

2016-01-01

A precise predictive model is needed to obtain a clear understanding of the changing dissolved oxygen content in outdoor crab ponds, to assess how to reduce risk and to optimize water quality management. The uncertainties in the data from multiple sensors are a significant factor when building a dissolved oxygen content prediction model. To increase prediction accuracy, a new hybrid dissolved oxygen content forecasting model based on the radial basis function neural networks (RBFNN) data fusion method and a least squares support vector machine (LSSVM) with an optimal improved particle swarm optimization(IPSO) is developed. In the modelling process, the RBFNN data fusion method is used to improve information accuracy and provide more trustworthy training samples for the IPSO-LSSVM prediction model. The LSSVM is a powerful tool for achieving nonlinear dissolved oxygen content forecasting. In addition, an improved particle swarm optimization algorithm is developed to determine the optimal parameters for the LSSVM with high accuracy and generalizability. In this study, the comparison of the prediction results of different traditional models validates the effectiveness and accuracy of the proposed hybrid RBFNN-IPSO-LSSVM model for dissolved oxygen content prediction in outdoor crab ponds. PMID:27270206

Dissolved oxygen content prediction in crab culture using a hybrid intelligent method.

PubMed

Yu, Huihui; Chen, Yingyi; Hassan, ShahbazGul; Li, Daoliang

2016-06-08

A precise predictive model is needed to obtain a clear understanding of the changing dissolved oxygen content in outdoor crab ponds, to assess how to reduce risk and to optimize water quality management. The uncertainties in the data from multiple sensors are a significant factor when building a dissolved oxygen content prediction model. To increase prediction accuracy, a new hybrid dissolved oxygen content forecasting model based on the radial basis function neural networks (RBFNN) data fusion method and a least squares support vector machine (LSSVM) with an optimal improved particle swarm optimization(IPSO) is developed. In the modelling process, the RBFNN data fusion method is used to improve information accuracy and provide more trustworthy training samples for the IPSO-LSSVM prediction model. The LSSVM is a powerful tool for achieving nonlinear dissolved oxygen content forecasting. In addition, an improved particle swarm optimization algorithm is developed to determine the optimal parameters for the LSSVM with high accuracy and generalizability. In this study, the comparison of the prediction results of different traditional models validates the effectiveness and accuracy of the proposed hybrid RBFNN-IPSO-LSSVM model for dissolved oxygen content prediction in outdoor crab ponds.

Teaching Concepts of Natural Sciences to Foreigners through Content-Based Instruction: The Adjunct Model

ERIC Educational Resources Information Center

Satilmis, Yilmaz; Yakup, Doganay; Selim, Guvercin; Aybarsha, Islam

2015-01-01

This study investigates three models of content-based instruction in teaching concepts and terms of natural sciences in order to increase the efficiency of teaching these kinds of concepts in realization and to prove that the content-based instruction is a teaching strategy that helps students understand concepts of natural sciences. Content-based…

Three approaches to define desired soil organic matter contents.

PubMed

Sparling, G; Parfitt, R L; Hewitt, A E; Schipper, L A

2003-01-01

Soil organic C is often suggested as an indicator of soil quality, but desirable targets are rarely specified. We tested three approaches to define maximum and lowest desirable soil C contents for four New Zealand soil orders. Approach 1 used the New Zealand National Soils Database (NSD). The maximum C content was defined as the median value of long-term pastures, and the lower quartile defined the lowest desirable soil C content. Approach 2 used the CENTURY model to predict maximum C contents of long-term pasture. Lowest desirable content was defined by the level that still allowed recovery to 80% of the maximum C content over 25 yr. Approach 3 used an expert panel to define desirable C contents based on production and environmental criteria. Median C contents (0-20 cm) for the Recent, Granular, Melanic, and Allophanic orders were 72, 88, 98, 132 Mg ha(-1), and similar to contents predicted by the CENTURY model (78, 93, 102, and 134 Mg ha(-1), respectively). Lower quartile values (54, 78, 73, and 103 Mg ha(-1), respectively) were similar to the lowest desirable C contents calculated by CENTURY (55, 54, 67, and 104 Mg ha(-1), respectively). Expert opinion was that C contents could be depleted below these values with tolerable effects on production but less so for the environment. The CENTURY model is our preferred approach for setting soil organic C targets, but the model needs calibrating for other soils and land uses. The statistical and expert opinion approaches are less defensible in setting lower limits for desirable C contents.

The influence of inquiry learning model on additives theme with ethnoscience content to cultural awareness of students

NASA Astrophysics Data System (ADS)

Sudarmin, S.; Selia, E.; Taufiq, M.

2018-03-01

The purpose of this research is to determine the influence of inquiry learning model on additives theme with ethnoscience content to cultural awareness of students and how the students’ responses to learning. The method applied in this research is a quasi-experimental with non-equivalent control group design. The sampling technique applied in this research is the technique of random sampling. The samples were eight grade students of one of junior high schools in Semarang. The results of this research were (1) thestudents’ cultural awareness of the experiment class is better than the control class (2) inquiry learning model with ethnoscience content strongly influencing the cultural awareness of students by 78% and (3) students gave positive responses to inquiry learning model with ethnoscience content. The conclusions of this research are inquiry-learning model with ethnoscience content has positive influence on students’ cultural awareness.

[Spectral reflectance characteristics and modeling of typical Takyr Solonetzs water content].

PubMed

Zhang, Jun-hua; Jia, Ke-li

2015-03-01

Based on the analysis of the spectral reflectance of the typical Takyr Solonetzs soil in Ningxia, the relationship of soil water content and spectral reflectance was determined, and a quantitative model for the prediction of soil water content was constructed. The results showed that soil spectral reflectance decreased with the increasing soil water content when it was below the water holding capacity but increased with the increasing soil water content when it was higher than the water holding capacity. Soil water content presented significantly negative correlation with original reflectance (r), smooth reflectance (R), logarithm of reflectance (IgR), and positive correlation with the reciprocal of R and logarithm of reciprocal [lg (1/R)]. The correlation coefficient of soil water content and R in the whole wavelength was 0.0013, 0.0397 higher than r and lgR, respectively. Average correlation coefficient of soil water content with 1/R and [lg (1/R)] at the wavelength of 950-1000 nm was 0.2350 higher than that of 400-950 nm. The relationships of soil water content with the first derivate differential (R') , the first derivate differential of logarithm (lgR)' and the first derivate differential of logarithm of reciprocal [lg(1/R)]' were unstable. Base on the coefficients of r, lg(1/R), R' and (lgR)', different regression models were established to predict soil water content, and the coefficients of determination were 0.7610, 0.8184, 0.8524 and 0.8255, respectively. The determination coefficient for power function model of R'. reached 0.9447, while the fitting degree between the predicted value based on this model and on-site measured value was 0.8279. The model of R' had the highest fitted accuracy, while that of r had the lowest one. The results could provide a scientific basis for soil water content prediction and field irrigation in the Takyr Solonetzs region.

Hydrological modelling of the Mara River Basin, Kenya: Application of the Normalised Difference Infrared Index (NDII)

NASA Astrophysics Data System (ADS)

Hulsman, Petra; Savenije, Hubert; Bogaard, Thom

2017-04-01

In hydrology and water resources management, precipitation and discharge are the main time series for hydrological modelling. However, in African river catchments, the quantity and quality of the available precipitation stations and discharge measurements are unfortunately often inadequate for reliable hydrological modelling. To cope with these uncertainties, this study proposes to calibrate on water levels and to constrain the model using the Normalised Difference Infrared Index (NDII) as a proxy for root zone moisture stress. With the NDII, the leaf water content can be monitored. Previous studies related the NDII to the equivalent water thickness (EWT) of leaves, which is used to determine the vegetation water content (VWC). As the water content in the leaves is related to the water content in the root zone, the NDII can also be used as indicator of the soil moisture content in the root zone. In previous studies it was found that the root zone moisture content is exponentially correlated to the NDII during periods of moisture stress. In this study, the semi-distributed rainfall runoff model FLEX-Topo has been applied to the Mara River Basin. In this model seven sub-basins are distinguished and four hydrological response units with each a unique model structure based on the expected dominant flow processes. To calibrate the model, the water levels have been back-calculated from modelled discharges, using cross-section data and the Strickler formula calibrating parameter 'k•s1/2', and compared to measured water levels. In addition, the correlation between the NDII and root zone moisture content has been analysed for this river basin for each sub-catchment and hydrological response unit. Also, the application of the NDII as model constraint or for calibration has been analysed.

40 CFR 80.42 - Simple emissions model.

Code of Federal Regulations, 2010 CFR

2010-07-01

... = Fuel aromatics of the fuel in question, in terms of volume percent (as measured under § 80.46) TOXREDS1... Model per § 80.48. (4) If the fuel aromatics content of the fuel in question is less than 10 volume... Range Benzene content 0.0-4.9 vol %. RVP 6.6-9.0 psi. 1 Oxygenate content 0-4.0 wt %. Aromatics content...

40 CFR 80.42 - Simple emissions model.

Code of Federal Regulations, 2011 CFR

2011-07-01

... = Fuel aromatics of the fuel in question, in terms of volume percent (as measured under § 80.46) TOXREDS1... Model per § 80.48. (4) If the fuel aromatics content of the fuel in question is less than 10 volume... Range Benzene content 0.0-4.9 vol %. RVP 6.6-9.0 psi. 1 Oxygenate content 0-4.0 wt %. Aromatics content...

Supporting Semantic Annotation of Educational Content by Automatic Extraction of Hierarchical Domain Relationships

ERIC Educational Resources Information Center

Vrablecová, Petra; Šimko, Marián

2016-01-01

The domain model is an essential part of an adaptive learning system. For each educational course, it involves educational content and semantics, which is also viewed as a form of conceptual metadata about educational content. Due to the size of a domain model, manual domain model creation is a challenging and demanding task for teachers or…

A Mathematical Model of Neutral Lipid Content in terms of Initial Nitrogen Concentration and Validation in Coelastrum sp. HA-1 and Application in Chlorella sorokiniana

PubMed Central

Zhao, Yue; Liu, Zhiyong; Liu, Chenfeng; Hu, Zhipeng

2017-01-01

Microalgae are considered to be a potential major biomass feedstock for biofuel due to their high lipid content. However, no correlation equations as a function of initial nitrogen concentration for lipid accumulation have been developed for simplicity to predict lipid production and optimize the lipid production process. In this study, a lipid accumulation model was developed with simple parameters based on the assumption protein synthesis shift to lipid synthesis by a linear function of nitrogen quota. The model predictions fitted well for the growth, lipid content, and nitrogen consumption of Coelastrum sp. HA-1 under various initial nitrogen concentrations. Then the model was applied successfully in Chlorella sorokiniana to predict the lipid content with different light intensities. The quantitative relationship between initial nitrogen concentrations and the final lipid content with sensitivity analysis of the model were also discussed. Based on the model results, the conversion efficiency from protein synthesis to lipid synthesis is higher and higher in microalgae metabolism process as nitrogen decreases; however, the carbohydrate composition content remains basically unchanged neither in HA-1 nor in C. sorokiniana. PMID:28194424

Mapping of Biophysical Parameters of Rice Agriculture System from Hyperspectral Imagery

NASA Astrophysics Data System (ADS)

Moharana, Shreedevi; Duta, Subashisa

2017-04-01

Chlorophyll, nitrogen and leaf water content are the most essential parameters for paddy crop growth. Ground hyperspectral observations were collected at canopy level during critical growth period of rice by using hand held Spectroradiometer. Chemical analysis was carried out to quantify the total chlorophyll, nitrogen and leaf water content. By exploiting the in-situ hyperspectral measurements, regression models were established between each of the crop growth parameters and the spectral indices specifically designed for chlorophyll, nitrogen and water stress. Narrow band vegetation index models were developed for mapping these parameters from Hyperion imagery in an agriculture system. It was inferred that the modified simple ratio (SR) and leaf nitrogen concentration (LNC) predictive index models, which followed a linear and nonlinear relationship respectively, produced satisfactory results in predicting rice nitrogen content from hyperspectral imagery. The presently developed model was compared with other models proposed by researchers. It was ascertained that, nitrogen content varied widely from 1-4 percentage and only 2-3 percentage for paddy crop using present modified index models and well-known predicted Tian et al. (2011) model respectively. The modified present LNC index model performed better than the established Tian et al. (2011) model as far as the estimated nitrogen content from Hyperion imagery was concerned. Moreover, within the observed chlorophyll range attained from the rice genotypes cultivated in the studied rice agriculture system, the index models (LNC, OASVI, Gitelson, mSR and MTCI) accomplished satisfactory results in the spatial distribution of rice chlorophyll content from Hyperion imagery. Spatial distribution of total chlorophyll content widely varied from 1.77-5.81 mg/g (LNC), 3.0-13 mg/g (OASVI) and 2.90-5.40 mg/g (MTCI). Following the similar guideline, it was found that normalized difference water index (NDWI) and normalized difference infrared index (NDII) predictive models demonstrated the spatial variability of leaf water content from 40 percentage to 90 percentage in the same rice agriculture system which has a good agreement with observed in-situ leaf water measurements. The spatial information of these parameters will be useful for crop nutrient management and yield forecasting, and will serve as inputs to various crop-forecasting models for developing a precision rice agriculture system. Key words: Rice agriculture system, nitrogen, chlorophyll, leaf water content, vegetation index

A scheme for parameterizing ice cloud water content in general circulation models

NASA Technical Reports Server (NTRS)

Heymsfield, Andrew J.; Donner, Leo J.

1989-01-01

A method for specifying ice water content in GCMs is developed, based on theory and in-cloud measurements. A theoretical development of the conceptual precipitation model is given and the aircraft flights used to characterize the ice mass distribution in deep ice clouds is discussed. Ice water content values derived from the theoretical parameterization are compared with the measured values. The results demonstrate that a simple parameterization for atmospheric ice content can account for ice contents observed in several synoptic contexts.

Peering Strategic Game Models for Interdependent ISPs in Content Centric Internet

PubMed Central

Guan, Jianfeng; Xu, Changqiao; Su, Wei; Zhang, Hongke

2013-01-01

Emergent content-oriented networks prompt Internet service providers (ISPs) to evolve and take major responsibility for content delivery. Numerous content items and varying content popularities motivate interdependence between peering ISPs to elaborate their content caching and sharing strategies. In this paper, we propose the concept of peering for content exchange between interdependent ISPs in content centric Internet to minimize content delivery cost by a proper peering strategy. We model four peering strategic games to formulate four types of peering relationships between ISPs who are characterized by varying degrees of cooperative willingness from egoism to altruism and interconnected as profit-individuals or profit-coalition. Simulation results show the price of anarchy (PoA) and communication cost in the four games to validate that ISPs should decide their peering strategies by balancing intradomain content demand and interdomain peering relations for an optimal cost of content delivery. PMID:24381517

Peering strategic game models for interdependent ISPs in content centric Internet.

PubMed

Zhao, Jia; Guan, Jianfeng; Xu, Changqiao; Su, Wei; Zhang, Hongke

2013-01-01

Emergent content-oriented networks prompt Internet service providers (ISPs) to evolve and take major responsibility for content delivery. Numerous content items and varying content popularities motivate interdependence between peering ISPs to elaborate their content caching and sharing strategies. In this paper, we propose the concept of peering for content exchange between interdependent ISPs in content centric Internet to minimize content delivery cost by a proper peering strategy. We model four peering strategic games to formulate four types of peering relationships between ISPs who are characterized by varying degrees of cooperative willingness from egoism to altruism and interconnected as profit-individuals or profit-coalition. Simulation results show the price of anarchy (PoA) and communication cost in the four games to validate that ISPs should decide their peering strategies by balancing intradomain content demand and interdomain peering relations for an optimal cost of content delivery.

Content Model Use and Development to Redeem Thin Section Records

NASA Astrophysics Data System (ADS)

Hills, D. J.

2014-12-01

The National Geothermal Data System (NGDS) is a catalog of documents and datasets that provide information about geothermal resources located primarily within the United States. The goal of NGDS is to make large quantities of geothermal-relevant geoscience data available to the public by creating a national, sustainable, distributed, and interoperable network of data providers. The Geological Survey of Alabama (GSA) has been a data provider in the initial phase of NGDS. One method by which NGDS facilitates interoperability is through the use of content models. Content models provide a schema (structure) for submitted data. Schemas dictate where and how data should be entered. Content models use templates that simplify data formatting to expedite use by data providers. These methodologies implemented by NGDS can extend beyond geothermal data to all geoscience data. The GSA, using the NGDS physical samples content model, has tested and refined a content model for thin sections and thin section photos. Countless thin sections have been taken from oil and gas well cores housed at the GSA, and many of those thin sections have related photomicrographs. Record keeping for these thin sections has been scattered at best, and it is critical to capture their metadata while the content creators are still available. A next step will be to register the GSA's thin sections with SESAR (System for Earth Sample Registration) and assign an IGSN (International Geo Sample Number) to each thin section. Additionally, the thin section records will be linked to the GSA's online record database. When complete, the GSA's thin sections will be more readily discoverable and have greater interoperability. Moving forward, the GSA is implementing use of NGDS-like content models and registration with SESAR and IGSN to improve collection maintenance and management of additional physical samples.

Nuclear DNA contents of Echinchloa crus-galli and its Gaussian relationships with environments

NASA Astrophysics Data System (ADS)

Li, Dan-Dan; Lu, Yong-Liang; Guo, Shui-Liang; Yin, Li-Ping; Zhou, Ping; Lou, Yu-Xia

2017-02-01

Previous studies on plant nuclear DNA content variation and its relationships with environmental gradients produced conflicting results. We speculated that the relationships between nuclear DNA content of a widely-distributed species and its environmental gradients might be non-linear if it was sampled in a large geographical gradient. Echinochloa crus-galli (L.) P. Beauv. is a worldwide species, but without documents on its intraspecific variation of nuclear DNA content. Our objectives are: 1) to detect intraspecific variation scope of E. crus-galli in its nuclear DNA content, and 2) to testify whether nuclear DNA content of the species changes with environmental gradients following Gaussian models if its populations were sampled in a large geographical gradient. We collected seeds of 36 Chinese populations of E. crus-galli across a wide geographical gradient, and sowed them in a homogeneous field to get their offspring to determine their nuclear DNA content. We analyzed the relationships of nuclear DNA content of these populations with latitude, longitude, and nineteen bioclimatic variables by using Gaussian and linear models. (1) Nuclear DNA content varied from 2.113 to 2.410 pg among 36 Chinese populations of E. crus-galli, with a mean value of 2.256 pg. (2) Gaussian correlations of nuclear DNA content (y) with geographical gradients were detected, with latitude (x) following y = 2.2923*e -(x - 24.9360)2/2*63.79452 (r = 0.546, P < 0.001), and with longitude (x) following y = 2.2933*e -(x - 116.1801)2/2*44.74502 (r = 0.672, P < 0.001). (3) Among the nineteen bioclimatic variables, except temperature isothermality, precipitations of the wettest month, the wettest quarter and the warmest quarter, the others could be better fit with nuclear DNA content by using Gaussian models than by linear models. There exists intra-specific variation among 36 Chinese populations of E. crus-galli, Gaussian models could be applied to fit the correlations of its Nuclear DNA content with geographical and most bioclimatic gradients.

[Estimation of organic matter content of north fluvo-aquic soil based on the coupling model of wavelet transform and partial least squares].

PubMed

Wang, Yan-Cang; Yang, Gui-Jun; Zhu, Jin-Shan; Gu, Xiao-He; Xu, Peng; Liao, Qin-Hong

2014-07-01

For improving the estimation accuracy of soil organic matter content of the north fluvo-aquic soil, wavelet transform technology is introduced. The soil samples were collected from Tongzhou district and Shunyi district in Beijing city. And the data source is from soil hyperspectral data obtained under laboratory condition. First, discrete wavelet transform efficiently decomposes hyperspectral into approximate coefficients and detail coefficients. Then, the correlation between approximate coefficients, detail coefficients and organic matter content was analyzed, and the sensitive bands of the organic matter were screened. Finally, models were established to estimate the soil organic content by using the partial least squares regression (PLSR). Results show that the NIR bands made more contributions than the visible band in estimating organic matter content models; the ability of approximate coefficients to estimate organic matter content is better than that of detail coefficients; The estimation precision of the detail coefficients fir soil organic matter content decreases with the spectral resolution being lower; Compared with the commonly used three types of soil spectral reflectance transforms, the wavelet transform can improve the estimation ability of soil spectral fir organic content; The accuracy of the best model established by the approximate coefficients or detail coefficients is higher, and the coefficient of determination (R2) and the root mean square error (RMSE) of the best model for approximate coefficients are 0.722 and 0.221, respectively. The R2 and RMSE of the best model for detail coefficients are 0.670 and 0.255, respectively.

Diagnosing the Causes and Severity of One-sided Message Contention

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

Tallent, Nathan R.; Vishnu, Abhinav; van Dam, Hubertus

Two trends suggest network contention for one-sided messages is poised to become a performance problem that concerns application developers: an increased interest in one-sided programming models and a rising ratio of hardware threads to network injection bandwidth. Unfortunately, it is difficult to reason about network contention and one-sided messages because one-sided tasks can either decrease or increase contention. We present effective and portable techniques for diagnosing the causes and severity of one-sided message contention. To detect that a message is affected by contention, we maintain statistics representing instantaneous (non-local) network resource demand. Using lightweight measurement and modeling, we identify themore » portion of a message's latency that is due to contention and whether contention occurs at the initiator or target. We attribute these metrics to program statements in their full static and dynamic context. We characterize contention for an important computational chemistry benchmark on InfiniBand, Cray Aries, and IBM Blue Gene/Q interconnects. We pinpoint the sources of contention, estimate their severity, and show that when message delivery time deviates from an ideal model, there are other messages contending for the same network links. With a small change to the benchmark, we reduce contention up to 50% and improve total runtime as much as 20%.« less

Adolescent Health Behavior, Contentment in School, and Academic Achievement

ERIC Educational Resources Information Center

Kristjansson, Alfgeir Logi; Sigfusdottir, Inga Dora; Allegrante, John P.; Helgason, Asgeir R.

2009-01-01

Objectives: To examine the association between health behavior indicators, school contentment, and academic achievement. Methods: Structural equation modeling with 5810 adolescents. Results: Our model explained 36% of the variance in academic achievement and 24% in school contentment. BMI and sedentary lifestyle were negatively related to school…

Effect of PVA fiber content on creep property of fiber reinforced high-strength concrete columns

NASA Astrophysics Data System (ADS)

Xu, Zongnan; Wang, Tao; Wang, Weilun

2018-04-01

The effect of PVA (polyvinyl alcohol) fiber content on the creep property of fiber reinforced high-strength concrete columns was investigated. The correction factor of PVA fiber content was proposed and the creep prediction model of ACI209 was modified. Controlling the concrete strength as C80, changing the content of PVA fiber (volume fraction 0%, 0.25%, 0.5%, 1% respectively), the creep experiment of PVA fiber reinforced concrete columns was carried out, the creep coefficient of each specimen was calculated to characterize the creep property. The influence of PVA fiber content on the creep property was analyzed based on the creep coefficient and the calculation results of several frequently used creep prediction models. The correction factor of PVA fiber content was proposed to modify the ACI209 creep prediction model.

Topsoil organic carbon content of Europe, a new map based on a generalised additive model

NASA Astrophysics Data System (ADS)

de Brogniez, Delphine; Ballabio, Cristiano; Stevens, Antoine; Jones, Robert J. A.; Montanarella, Luca; van Wesemael, Bas

2014-05-01

There is an increasing demand for up-to-date spatially continuous organic carbon (OC) data for global environment and climatic modeling. Whilst the current map of topsoil organic carbon content for Europe (Jones et al., 2005) was produced by applying expert-knowledge based pedo-transfer rules on large soil mapping units, the aim of this study was to replace it by applying digital soil mapping techniques on the first European harmonised geo-referenced topsoil (0-20 cm) database, which arises from the LUCAS (land use/cover area frame statistical survey) survey. A generalized additive model (GAM) was calibrated on 85% of the dataset (ca. 17 000 soil samples) and a backward stepwise approach selected slope, land cover, temperature, net primary productivity, latitude and longitude as environmental covariates (500 m resolution). The validation of the model (applied on 15% of the dataset), gave an R2 of 0.27. We observed that most organic soils were under-predicted by the model and that soils of Scandinavia were also poorly predicted. The model showed an RMSE of 42 g kg-1 for mineral soils and of 287 g kg-1 for organic soils. The map of predicted OC content showed the lowest values in Mediterranean countries and in croplands across Europe, whereas highest OC content were predicted in wetlands, woodlands and in mountainous areas. The map of standard error of the OC model predictions showed high values in northern latitudes, wetlands, moors and heathlands, whereas low uncertainty was mostly found in croplands. A comparison of our results with the map of Jones et al. (2005) showed a general agreement on the prediction of mineral soils' OC content, most probably because the models use some common covariates, namely land cover and temperature. Our model however failed to predict values of OC content greater than 200 g kg-1, which we explain by the imposed unimodal distribution of our model, whose mean is tilted towards the majority of soils, which are mineral. Finally, average OC content predictions for each land cover class compared well between models, with our model always showing smaller standard deviations. We concluded that the chosen model and covariates are appropriate for the prediction of OC content in European mineral soils. We presented in this work the first map of topsoil OC content at European scale based on a harmonised soil dataset. The associated uncertainty map shall support the end-users in a careful use of the predictions.

Influence of Al content on non-equilibrium solidification behavior of Ni-Al-Ta model single crystal alloys

NASA Astrophysics Data System (ADS)

Ai, Cheng; Zhou, Jian; Zhang, Heng; Zhao, Xinbao; Pei, Yanling; Li, Shusuo; Gong, Shengkai

2016-01-01

The non-equilibrium solidification behaviors of five Ni-Al-Ta ternary model single crystal alloys with different Al contents were investigated by experimental analysis and theoretical calculation (by JMatPro) in this study. These model alloys respectively represented the γ' phase with various volume fractions (100%, 75%, 50%, 25% and 0%) at 900 °C. It was found that with decreasing Al content, liquidus temperature of experimental alloys first decreased and then increased. Meanwhile, the solidification range showed a continued downward trend. In addition, with decreasing Al content, the primary phases of non-equilibrium solidified model alloys gradually transformed from γ' phase to γ phase, and the area fraction of which first decreased and then increased. Moreover, the interdendritic/intercellular precipitation of model alloys changed from β phase (for 100% γ') to (γ+γ')Eutectic (for 75% γ'), (γ+γ')Eutectic+γ' (for 50% γ' and 25% γ') and none interdendritic precipitation (for 0% γ'), and the last stage non-equilibrium solidification sequence of model alloys was determined by the nominal Al content and different microsegregation behaviors of Al element.

Suggestions for Implementing a Content Mastery Center

ERIC Educational Resources Information Center

Jenkins, Amelia

2010-01-01

The content mastery center (CMC) model is responsive to the federal requirements of providing access to the general education curriculum for students with disabilities and allowing special education teachers to meet the highly qualified requirement by providing consultation and support services in the content areas. The CMC model has been…

Fundamental factors affecting biomass enzymatic reactivity.

PubMed

Chang, V S; Holtzapple, M T

2000-01-01

Poplar wood was treated with peracetic acid, KOH, and ball milling to produce 147 model lignocelluloses with a broad spectrum of lignin contents, acetyl contents, and crystallinity indices (CrIs), respectively. An empirical model was identified that describes the roles of these three properties in enzymatic hydrolysis. Lignin content and CrI have the greatest impact on biomass digestibility, whereas acetyl content has a minor impact. The digestibility of several lime-treated biomass samples agreed with the empirical model. Lime treatment removes all acetyl groups and a moderate amount of lignin and increases CrI slightly; lignin removal is the dominant benefit from lime treatment.

A Model for Effective Professional Development of Formal Science Educators

NASA Astrophysics Data System (ADS)

Bleacher, L.; Jones, A. P.; Farrell, W. M.

2015-12-01

The Lunar Workshops for Educators (LWE) series was developed by the Lunar Reconnaissance Orbiter (LRO) education team in 2010 to provide professional development on lunar science and exploration concepts for grades 6-9 science teachers. Over 300 educators have been trained to date. The LWE model incorporates best practices from pedagogical research of science education, thoughtful integration of scientists and engineer subject matter experts for both content presentations and informal networking with educators, access to NASA-unique facilities, hands-on and data-rich activities aligned with education standards, exposure to the practice of science, tools for addressing common misconceptions, follow-up with participants, and extensive evaluation. Evaluation of the LWE model via pre- and post-assessments, daily workshop surveys, and follow-up surveys at 6-month and 1-year intervals indicate that the LWE are extremely effective in increasing educators' content knowledge, confidence in incorporating content into the classroom, understanding of the practice of science, and ability to address common student misconceptions. In order to address the efficacy of the LWE model for other science content areas, the Dynamic Response of Environments at Asteroids, the Moon, and moons of Mars (DREAM2) education team, funded by NASA's Solar System Exploration Research Virtual Institute, developed and ran a pilot workshop called Dream2Explore at NASA's Goddard Space Flight Center in June, 2015. Dream2Explore utilized the LWE model, but incorporated content related to the science and exploration of asteroids and the moons of Mars. Evaluation results indicate that the LWE model was effectively used for educator professional development on non-lunar content. We will present more detail on the LWE model, evaluation results from the Dream2Explore pilot workshop, and suggestions for the application of the model with other science content for robust educator professional development.

A Model for Effective Professional Development of Formal Science Educators

NASA Technical Reports Server (NTRS)

Bleacher, L. V.; Jones, A. J. P.; Farrell, W. M.

2015-01-01

The Lunar Workshops for Educators (LWE) series was developed by the Lunar Reconnaissance Orbiter (LRO) education team in 2010 to provide professional development on lunar science and exploration concepts for grades 6-9 science teachers. Over 300 educators have been trained to date. The LWE model incorporates best practices from pedagogical research of science education, thoughtful integration of scientists and engineer subject matter experts for both content presentations and informal networking with educators, access to NASA-unique facilities, hands-on and data-rich activities aligned with education standards, exposure to the practice of science, tools for addressing common misconceptions, follow-up with participants, and extensive evaluation. Evaluation of the LWE model via pre- and post-assessments, daily workshop surveys, and follow-up surveys at 6-month and 1-year intervals indicate that the LWE are extremely effective in increasing educators' content knowledge, confidence in incorporating content into the classroom, understanding of the practice of science, and ability to address common student misconceptions. In order to address the efficacy of the LWE model for other science content areas, the Dynamic Response of Environments at Asteroids, the Moon, and moons of Mars (DREAM2) education team, funded by NASA's Solar System Exploration Research Virtual Institute, developed and ran a pilot workshop called Dream2Explore at NASA's Goddard Space Flight Center in June, 2015. Dream2Explore utilized the LWE model, but incorporated content related to the science and exploration of asteroids and the moons of Mars. Evaluation results indicate that the LWE model was effectively used for educator professional development on non-lunar content. We will present more detail on the LWE model, evaluation results from the Dream2Explore pilot workshop, and suggestions for the application of the model with other science content for robust educator professional development.

Combining a popularity-productivity stochastic block model with a discriminative-content model for general structure detection.

PubMed

Chai, Bian-fang; Yu, Jian; Jia, Cai-Yan; Yang, Tian-bao; Jiang, Ya-wen

2013-07-01

Latent community discovery that combines links and contents of a text-associated network has drawn more attention with the advance of social media. Most of the previous studies aim at detecting densely connected communities and are not able to identify general structures, e.g., bipartite structure. Several variants based on the stochastic block model are more flexible for exploring general structures by introducing link probabilities between communities. However, these variants cannot identify the degree distributions of real networks due to a lack of modeling of the differences among nodes, and they are not suitable for discovering communities in text-associated networks because they ignore the contents of nodes. In this paper, we propose a popularity-productivity stochastic block (PPSB) model by introducing two random variables, popularity and productivity, to model the differences among nodes in receiving links and producing links, respectively. This model has the flexibility of existing stochastic block models in discovering general community structures and inherits the richness of previous models that also exploit popularity and productivity in modeling the real scale-free networks with power law degree distributions. To incorporate the contents in text-associated networks, we propose a combined model which combines the PPSB model with a discriminative model that models the community memberships of nodes by their contents. We then develop expectation-maximization (EM) algorithms to infer the parameters in the two models. Experiments on synthetic and real networks have demonstrated that the proposed models can yield better performances than previous models, especially on networks with general structures.

Combining a popularity-productivity stochastic block model with a discriminative-content model for general structure detection

NASA Astrophysics Data System (ADS)

Chai, Bian-fang; Yu, Jian; Jia, Cai-yan; Yang, Tian-bao; Jiang, Ya-wen

2013-07-01

Latent community discovery that combines links and contents of a text-associated network has drawn more attention with the advance of social media. Most of the previous studies aim at detecting densely connected communities and are not able to identify general structures, e.g., bipartite structure. Several variants based on the stochastic block model are more flexible for exploring general structures by introducing link probabilities between communities. However, these variants cannot identify the degree distributions of real networks due to a lack of modeling of the differences among nodes, and they are not suitable for discovering communities in text-associated networks because they ignore the contents of nodes. In this paper, we propose a popularity-productivity stochastic block (PPSB) model by introducing two random variables, popularity and productivity, to model the differences among nodes in receiving links and producing links, respectively. This model has the flexibility of existing stochastic block models in discovering general community structures and inherits the richness of previous models that also exploit popularity and productivity in modeling the real scale-free networks with power law degree distributions. To incorporate the contents in text-associated networks, we propose a combined model which combines the PPSB model with a discriminative model that models the community memberships of nodes by their contents. We then develop expectation-maximization (EM) algorithms to infer the parameters in the two models. Experiments on synthetic and real networks have demonstrated that the proposed models can yield better performances than previous models, especially on networks with general structures.

Optimal Scaling of Interaction Effects in Generalized Linear Models

ERIC Educational Resources Information Center

van Rosmalen, Joost; Koning, Alex J.; Groenen, Patrick J. F.

2009-01-01

Multiplicative interaction models, such as Goodman's (1981) RC(M) association models, can be a useful tool for analyzing the content of interaction effects. However, most models for interaction effects are suitable only for data sets with two or three predictor variables. Here, we discuss an optimal scaling model for analyzing the content of…

Edgar Schein's Process versus Content Consultation Models.

ERIC Educational Resources Information Center

Rockwood, Gary F.

1993-01-01

Describes Schein's three models of consultation based on assumptions inherent in different helping styles: purchase of expertise and doctor-patient models, which focus on content of organization problems; and process consultation model, which focuses on how organizational problems are solved. Notes that Schein has suggested that consultants begin…

``Just Another Distribution Channel?''

NASA Astrophysics Data System (ADS)

Lemstra, Wolter; de Leeuw, Gerd-Jan; van de Kar, Els; Brand, Paul

The telecommunications-centric business model of mobile operators is under attack due to technological convergence in the communication and content industries. This has resulted in a plethora of academic contributions on the design of new business models and service platform architectures. However, a discussion of the challenges that operators are facing in adopting these models is lacking. We assess these challenges by considering the mobile network as part of the value system of the content industry. We will argue that from the perspective of a content provider the mobile network is ‘just another’ distribution channel. Strategic options available for the mobile communication operators are to deliver an excellent distribution channel for content delivery or to move upwards in the value chain by becoming a content aggregator. To become a mobile content aggregator operators will have to develop or acquire complementary resources and capabilities. Whether this strategic option is sustainable remains open.

A Technology Enhanced Learning Model for Quality Education

NASA Astrophysics Data System (ADS)

Sherly, Elizabeth; Uddin, Md. Meraj

Technology Enhanced Learning and Teaching (TELT) Model provides learning through collaborations and interactions with a framework for content development and collaborative knowledge sharing system as a supplementary for learning to improve the quality of education system. TELT deals with a unique pedagogy model for Technology Enhanced Learning System which includes course management system, digital library, multimedia enriched contents and video lectures, open content management system and collaboration and knowledge sharing systems. Open sources like Moodle and Wiki for content development, video on demand solution with a low cost mid range system, an exhaustive digital library are provided in a portal system. The paper depicts a case study of e-learning initiatives with TELT model at IIITM-K and how effectively implemented.

Archetype-based conversion of EHR content models: pilot experience with a regional EHR system.

PubMed

Chen, Rong; Klein, Gunnar O; Sundvall, Erik; Karlsson, Daniel; Ahlfeldt, Hans

2009-07-01

Exchange of Electronic Health Record (EHR) data between systems from different suppliers is a major challenge. EHR communication based on archetype methodology has been developed by openEHR and CEN/ISO. The experience of using archetypes in deployed EHR systems is quite limited today. Currently deployed EHR systems with large user bases have their own proprietary way of representing clinical content using various models. This study was designed to investigate the feasibility of representing EHR content models from a regional EHR system as openEHR archetypes and inversely to convert archetypes to the proprietary format. The openEHR EHR Reference Model (RM) and Archetype Model (AM) specifications were used. The template model of the Cambio COSMIC, a regional EHR product from Sweden, was analyzed and compared to the openEHR RM and AM. This study was focused on the convertibility of the EHR semantic models. A semantic mapping between the openEHR RM/AM and the COSMIC template model was produced and used as the basis for developing prototype software that performs automated bi-directional conversion between openEHR archetypes and COSMIC templates. Automated bi-directional conversion between openEHR archetype format and COSMIC template format has been achieved. Several archetypes from the openEHR Clinical Knowledge Repository have been imported into COSMIC, preserving most of the structural and terminology related constraints. COSMIC templates from a large regional installation were successfully converted into the openEHR archetype format. The conversion from the COSMIC templates into archetype format preserves nearly all structural and semantic definitions of the original content models. A strategy of gradually adding archetype support to legacy EHR systems was formulated in order to allow sharing of clinical content models defined using different formats. The openEHR RM and AM are expressive enough to represent the existing clinical content models from the template based EHR system tested and legacy content models can automatically be converted to archetype format for sharing of knowledge. With some limitations, internationally available archetypes could be converted to the legacy EHR models. Archetype support can be added to legacy EHR systems in an incremental way allowing a migration path to interoperability based on standards.

Influence of three different concentration techniques on evaporation rate, color and phenolics content of blueberry juice.

PubMed

Elik, Aysel; Yanık, Derya Koçak; Maskan, Medeni; Göğüş, Fahrettin

2016-05-01

The present study was undertaken to assess the effects of three different concentration processes open-pan, rotary vacuum evaporator and microwave heating on evaporation rate, the color and phenolics content of blueberry juice. Kinetics model study for changes in soluble solids content (°Brix), color parameters and phenolics content during evaporation was also performed. The final juice concentration of 65° Brix was achieved in 12, 15, 45 and 77 min, for microwave at 250 and 200 W, rotary vacuum and open-pan evaporation processes, respectively. Color changes associated with heat treatment were monitored using Hunter colorimeter (L*, a* and b*). All Hunter color parameters decreased with time and dependently studied concentration techniques caused color degradation. It was observed that the severity of color loss was higher in open-pan technique than the others. Evaporation also affected total phenolics content in blueberry juice. Total phenolics loss during concentration was highest in open-pan technique (36.54 %) and lowest in microwave heating at 200 W (34.20 %). So, the use of microwave technique could be advantageous in food industry because of production of blueberry juice concentrate with a better quality and short time of operation. A first-order kinetics model was applied to modeling changes in soluble solids content. A zero-order kinetics model was used to modeling changes in color parameters and phenolics content.

An Alternative Team Teaching Model for Content-Based Instruction.

ERIC Educational Resources Information Center

Stewart, Timothy; Sagliano, Michael; Sagliano, Julie

2000-01-01

Describes an alternative teaching model of content-based instruction, Collaborative Interdisciplinary Team Teaching (CITT), used in an English-medium Japanese liberal arts university, highlighting the main features of CITT by comparing it to other relevant models. The article describes how the model has been applied, then discusses perceived…

The Use of the Interconnected Model of Teacher Professional Growth for Understanding the Development of Science Teachers' Knowledge on Models and Modelling

ERIC Educational Resources Information Center

Justi, Rosaria; van Driel, Jan

2006-01-01

Models play an important role in science education. However, previous research has revealed that science teachers' content knowledge, curricular knowledge, and pedagogical content knowledge on models and modelling are often incomplete or inadequate. From this perspective, a research project was designed which aimed at the development of beginning…

Within-culture variation in the content of stereotypes: Application and development of the stereotype content model in an Eastern European culture.

PubMed

Stanciu, Adrian; Cohrs, J Christopher; Hanke, Katja; Gavreliuc, Alin

2017-01-01

There is little and unsystematic evidence about whether the content of stereotypes can vary within a culture. Using the Stereotype Content Model (SCM) as a theoretical framework, in two studies we examined the content of stereotypes in an Eastern European culture, namely Romania. Data were collected from four regions prototypical in terms of economic and social development in Romania, and we examined whether the content of stereotypes varies across these regions. As expected, the findings confirm the applicability of the SCM in Romania to reveal culture-specific stereotypes and provide initial support for within-culture variation in the content of stereotypes. We discuss, in particular, possible reasons for two main findings: a strong one-dimensional structure of stereotypes, and regional differences in stereotype content.

[Modeling of sugar content based on NIRS during cider-making fermentation].

PubMed

Peng, Bang-Zhu; Yue, Tian-Li; Yuan, Ya-Hong; Gao, Zhen-Peng

2009-03-01

The sugar content and the matrix always are being changed during cider-making fermentation. In order to measure and monitor sugar content accurately and rapidly, it is necessary for the spectra to be sorted. Calibration models were established at different fermentation stages based on near infrared spectroscopy with artificial neural network. NIR spectral data were collected in the spectral region of 12 000-4 000 cm(-1) for the next analysis. After the different conditions for modeling sugar content were analyzed and discussed, the results indicated that the calibration models developed by the spectral data pretreatment of straight line subtraction(SLS) in the characteristic absorption spectra ranges of 7 502-6 472.1 cm(-1) at stage I and 6 102-5 446.2 cm(-1) at stage II were the best for sugar content. The result of comparison of different data pretreatment methods for establishing calibration model showed that the correlation coefficients of the models (R2) for stage I and II were 98.93% and 99.34% respectively and the root mean square errors of cross validation(RMSECV) for stage I and II were 4.42 and 1.21 g x L(-1) respectively. Then the models were tested and the results showed that the root mean square error of prediction (RMSEP) was 4.07 g x L(-1) and 1.13 g x L(-1) respectively. These demonstrated that the models the authors established are very well and can be applied to quick determination and monitoring of sugar content during cider-making fermentation.

Content Analysis in Computer-Mediated Communication: Analyzing Models for Assessing Critical Thinking through the Lens of Social Constructivism

ERIC Educational Resources Information Center

Buraphadeja, Vasa; Dawson, Kara

2008-01-01

This article reviews content analysis studies aimed to assess critical thinking in computer-mediated communication. It also discusses theories and content analysis models that encourage critical thinking skills in asynchronous learning environments and reviews theories and factors that may foster critical thinking skills and new knowledge…

A Theory of the Measurement of Knowledge Content, Access, and Learning.

ERIC Educational Resources Information Center

Pirolli, Peter; Wilson, Mark

1998-01-01

An approach to the measurement of knowledge content, knowledge access, and knowledge learning is developed. First a theoretical view of cognition is described, and then a class of measurement models, based on Rasch modeling, is presented. Knowledge access and content are viewed as determining the observable actions selected by an agent to achieve…

Using the Integrative Model to Explain How Exposure to Sexual Media Content Influences Adolescent Sexual Behavior

ERIC Educational Resources Information Center

Bleakley, Amy; Hennessy, Michael; Fishbein, Martin; Jordan, Amy

2011-01-01

Published research demonstrates an association between exposure to media sexual content and a variety of sex-related outcomes for adolescents. What is not known is the mechanism through which sexual content produces this "media effect" on adolescent beliefs, attitudes, and behavior. Using the Integrative Model of Behavioral Prediction, this…

Investigating mixing and emptying for aqueous liquid content from the stomach using a coupled biomechanical-SPH model.

PubMed

Harrison, Simon M; Cleary, Paul W; Sinnott, Matthew D

2018-05-18

The stomach is a critical organ for food digestion but it is not well understood how it operates, either when healthy or when dysfunction occurs. Stomach function depends on the timing and amplitude of wall contractions, the fill level and the type of gastric content. Using a coupled biomechanical-Smoothed Particle Hydrodynamics (B-SPH) model, we investigate how gastric discharge is affected by the contraction behaviour of the stomach wall and the viscosity of the content. The results of the model provide new insights into how the content viscosity and the number of compression waves down the length of the stomach affect the mixing within and the discharge rate of the content exiting from the stomach to the duodenum. This investigation shows that the B-SPH model is capable of simulating complicated stomach behaviour. The rate of gastric emptying is found to increase with a smaller period in between contractile waves and to have a nonlinear relationship with content viscosity. Increased resistance to flow into the duodenum is also shown to reduce the rate of emptying. The degree of gastric mixing is found to be insensitive to changes in the period between contractile waves for fluid with a viscosity of water but to be substantially affected by the viscosity of the gastric content.

Applicability of linear regression equation for prediction of chlorophyll content in rice leaves

NASA Astrophysics Data System (ADS)

Li, Yunmei

2005-09-01

A modeling approach is used to assess the applicability of the derived equations which are capable to predict chlorophyll content of rice leaves at a given view direction. Two radiative transfer models, including PROSPECT model operated at leaf level and FCR model operated at canopy level, are used in the study. The study is consisted of three steps: (1) Simulation of bidirectional reflectance from canopy with different leaf chlorophyll contents, leaf-area-index (LAI) and under storey configurations; (2) Establishment of prediction relations of chlorophyll content by stepwise regression; and (3) Assessment of the applicability of these relations. The result shows that the accuracy of prediction is affected by different under storey configurations and, however, the accuracy tends to be greatly improved with increase of LAI.

Sound velocities of olivine at high pressures and temperatures and the composition of Earth's upper mantle

NASA Astrophysics Data System (ADS)

Zhang, Jin S.; Bass, Jay D.

2016-09-01

We present the elastic properties of San Carlos olivine up to P = 12.8(8) GPa and T = 1300(200) K using Brillouin spectroscopy with CO2 laser heating. A comparison of our results with the global seismic model AK135 yields average olivine content near 410 km depth of about 37% and 43% in a dry and wet (1.9 wt % H2O) upper mantle, respectively. These olivine contents are far less than in the pyrolite model. However, comparisons of our results with regional seismic models lead to very different conclusions. High olivine contents of up to 87% are implied by seismic models of the western U.S. and eastern Pacific regions. In contrast, we infer less than 35% olivine under the central Pacific. Strong variations of olivine content and upper mantle lithologies near the 410 km discontinuity are suggested by regional seismic models.

Data assimilation with soil water content sensors and pedotransfer functions in soil water flow modeling

USDA-ARS?s Scientific Manuscript database

Soil water flow models are based on a set of simplified assumptions about the mechanisms, processes, and parameters of water retention and flow. That causes errors in soil water flow model predictions. Soil water content monitoring data can be used to reduce the errors in models. Data assimilation (...

Modeled Instructional Routines: Will Preservice Teachers Embed Them in Their Future Lessons?

ERIC Educational Resources Information Center

Slaughter, Sandra K.

2017-01-01

Modeling in the classroom is the key to successful teaching. This study examines whether preservice teachers would use content area literacy instructional routines, which had been modeled in my university course, in their student teaching and first-year classrooms. Both content area literacy and disciplinary literacy were modeled in my university…

Thoughts About Nursing Conceptual Models and the "Medical Model".

PubMed

Fawcett, Jacqueline

2017-01-01

This essay, written to celebrate the 30th anniversary of Nursing Science Quarterly, focuses on the distinctions between the discipline of nursology and the trade of medicine. The distinctions are drawn from content found in nursing conceptual models and from literature about the elusive content of the so-called "medical model."

Content Analysis of Research Trends in Instructional Design Models: 1999-2014

ERIC Educational Resources Information Center

Göksu, Idris; Özcan, Kursat Volkan; Çakir, Recep; Göktas, Yuksel

2017-01-01

This study examines studies on instructional design models by applying content analysis. It covers 113 papers published in 44 international Social Science Citation Index (SSCI) and Science Citation Index (SCI) journals. Studies on instructional design models are explored in terms of journal of publication, preferred model, country where the study…

Characterization of Cloud Water-Content Distribution

NASA Technical Reports Server (NTRS)

Lee, Seungwon

2010-01-01

The development of realistic cloud parameterizations for climate models requires accurate characterizations of subgrid distributions of thermodynamic variables. To this end, a software tool was developed to characterize cloud water-content distributions in climate-model sub-grid scales. This software characterizes distributions of cloud water content with respect to cloud phase, cloud type, precipitation occurrence, and geo-location using CloudSat radar measurements. It uses a statistical method called maximum likelihood estimation to estimate the probability density function of the cloud water content.

Liver fat contents, abdominal adiposity and insulin resistance in non-diabetic prevalent hemodialysis patients.

PubMed

Chen, Hung-Yuan; Lin, Chien-Chu; Chiu, Yen-Ling; Hsu, Shih-Ping; Pai, Mei-Fen; Yang, Ju-Yeh; Wu, Hon-Yen; Peng, Yu-Sen

2014-01-01

The liver fat contents and abdominal adiposity correlate well with insulin resistance (IR) in the general population. However, the relationship between liver fat content, abdominal adiposity and IR in non-diabetic hemodialysis (HD) patients remains unclear. This study aimed to clarify the associations among these factors. This is a cross-sectional, observational study. All patients received abdominal ultrasound for liver fat content. Abdominal adiposity was quantified with the conicity index (Ci) and waist circumference (WC). We checked the homeostasis model assessment for insulin resistance index (HOMA-IR) for IR. A total of 112 patients (60 women) were analyzed. Subjects with higher liver fat contents and WC had higher IR indices. But Ci did not correlate with IR indices. In both the multi-variable linear regression model and the logistic regression model, only higher liver fat content predicted a severe IR status. Liver fat contents have a remarkable correlation with IR; however, abdominal adiposity, measured either by Ci or WC, dose not independently correlate with IR in non-diabetic prevalent HD patients. © 2014 S. Karger AG, Basel.

Using the Integrative Model to Explain How Exposure to Sexual Media Content Influences Adolescent Sexual Behavior

PubMed Central

Bleakley, Amy; Hennessy, Michael; Fishbein, Martin; Jordan, Amy

2017-01-01

Published research demonstrates an association between exposure to media sexual content and a variety of sex-related outcomes for adolescents. What is not known is the mechanism through which sexual content produces this “media effect” on adolescent beliefs, attitudes, and behavior. Using the Integrative Model of Behavioral Prediction, this paper uses data from a longitudinal study of adolescents ages 16–18 (n=460) to determine how exposure to sexual media content influences sexual behavior. Path analysis and structural equation modeling demonstrated that intention to engage in sexual intercourse is determined by a combination of attitudes, normative pressure, and self efficacy but that exposure to sexual media content only affects normative pressure beliefs. By applying the Integrative Model, we are able to identify which beliefs are influenced by exposure to media sex and improve the ability of health educators, researchers, and others to design effective messages for health communication campaigns and messages pertaining to adolescents’ engaging in sexual intercourse. PMID:21606378

Research on the Optimum Water Content of Detecting Soil Nitrogen Using Near Infrared Sensor

PubMed Central

He, Yong; Nie, Pengcheng; Dong, Tao; Qu, Fangfang; Lin, Lei

2017-01-01

Nitrogen is one of the important indexes to evaluate the physiological and biochemical properties of soil. The level of soil nitrogen content influences the nutrient levels of crops directly. The near infrared sensor can be used to detect the soil nitrogen content rapidly, nondestructively, and conveniently. In order to investigate the effect of the different soil water content on soil nitrogen detection by near infrared sensor, the soil samples were dealt with different drying times and the corresponding water content was measured. The drying time was set from 1 h to 8 h, and every 1 h 90 samples (each nitrogen concentration of 10 samples) were detected. The spectral information of samples was obtained by near infrared sensor, meanwhile, the soil water content was calculated every 1 h. The prediction model of soil nitrogen content was established by two linear modeling methods, including partial least squares (PLS) and uninformative variable elimination (UVE). The experiment shows that the soil has the highest detection accuracy when the drying time is 3 h and the corresponding soil water content is 1.03%. The correlation coefficients of the calibration set are 0.9721 and 0.9656, and the correlation coefficients of the prediction set are 0.9712 and 0.9682, respectively. The prediction accuracy of both models is high, while the prediction effect of PLS model is better and more stable. The results indicate that the soil water content at 1.03% has the minimum influence on the detection of soil nitrogen content using a near infrared sensor while the detection accuracy is the highest and the time cost is the lowest, which is of great significance to develop a portable apparatus detecting nitrogen in the field accurately and rapidly. PMID:28880202

Research on the Optimum Water Content of Detecting Soil Nitrogen Using Near Infrared Sensor.

PubMed

He, Yong; Xiao, Shupei; Nie, Pengcheng; Dong, Tao; Qu, Fangfang; Lin, Lei

2017-09-07

Nitrogen is one of the important indexes to evaluate the physiological and biochemical properties of soil. The level of soil nitrogen content influences the nutrient levels of crops directly. The near infrared sensor can be used to detect the soil nitrogen content rapidly, nondestructively, and conveniently. In order to investigate the effect of the different soil water content on soil nitrogen detection by near infrared sensor, the soil samples were dealt with different drying times and the corresponding water content was measured. The drying time was set from 1 h to 8 h, and every 1 h 90 samples (each nitrogen concentration of 10 samples) were detected. The spectral information of samples was obtained by near infrared sensor, meanwhile, the soil water content was calculated every 1 h. The prediction model of soil nitrogen content was established by two linear modeling methods, including partial least squares (PLS) and uninformative variable elimination (UVE). The experiment shows that the soil has the highest detection accuracy when the drying time is 3 h and the corresponding soil water content is 1.03%. The correlation coefficients of the calibration set are 0.9721 and 0.9656, and the correlation coefficients of the prediction set are 0.9712 and 0.9682, respectively. The prediction accuracy of both models is high, while the prediction effect of PLS model is better and more stable. The results indicate that the soil water content at 1.03% has the minimum influence on the detection of soil nitrogen content using a near infrared sensor while the detection accuracy is the highest and the time cost is the lowest, which is of great significance to develop a portable apparatus detecting nitrogen in the field accurately and rapidly.

Deduction as Stochastic Simulation

DTIC Science & Technology

2013-07-01

different tokens representing entities that it contains. The second parameter constrains the contents of a model, and in particular the different...of premises. In summary, the system manipulates stochastically the size, the contents , and the revisions of models. We now describe in detail each...9 10 0. 0 0. 1 0. 2 0. 3 λ = 4 0 1 2 3 4 5 6 7 8 9 10 0. 0 0. 1 0. 2 0. 3 λ = 5 The contents of a mental model (parameter ε) The second component

A Model of Adolescents’ Seeking of Sexual Content in their Media Choices

PubMed Central

Bleakley, Amy; Hennessy, Michael; Fishbein, Martin

2010-01-01

This paper reports on the extent to which adolescents report actively seeking sexual content in media, identifies from which media they report seeking, estimates the association between seeking sexual information and romantic and sexual behavior, and shows that active seeking of sexual content in media sources is explained by an intention to seek such content using the Integrative Model of Behavioral Prediction, a reasoned action approach. The data are a national sample of 810 adolescents aged 13-18 years. Results show that fifty percent of adolescents reported actively seeking sexual content in their media choices, which included movies, television, music, internet pornography sites, and magazines. Males sought sex content more than females and gender differences were greatest for seeking from internet pornography sites, movies, and television. Path analysis demonstrate that seeking sexual content is well predicted by intentions to seek and intentions are primarily driven by perceived normative pressure to seek sexual content. PMID:20672214

A model of adolescents' seeking of sexual content in their media choices.

PubMed

Bleakley, Amy; Hennessy, Michael; Fishbein, Martin

2011-07-01

This article reports on the extent to which adolescents report actively seeking sexual content in media, identifies from which media they report seeking, estimates the association between seeking sexual information and romantic and sexual behavior, and shows that active seeking of sexual content in media sources is explained by an intention to seek such content using the Integrative Model of Behavioral Prediction, a reasoned action approach. The data are a national sample of 810 adolescents aged 13 to 18 years. Results show that 50% of adolescents reported actively seeking sexual content in their media choices, which included movies, television, music, Internet pornography sites, and magazines. Males sought sex content more than females, and gender differences were greatest for seeking from Internet pornography sites, movies, and television. Path analysis demonstrate that seeking sexual content is well-predicted by intentions to seek, and intentions are primarily driven by perceived normative pressure to seek sexual content.

An empirical analysis of ontology reuse in BioPortal.

PubMed

Ochs, Christopher; Perl, Yehoshua; Geller, James; Arabandi, Sivaram; Tudorache, Tania; Musen, Mark A

2017-07-01

Biomedical ontologies often reuse content (i.e., classes and properties) from other ontologies. Content reuse enables a consistent representation of a domain and reusing content can save an ontology author significant time and effort. Prior studies have investigated the existence of reused terms among the ontologies in the NCBO BioPortal, but as of yet there has not been a study investigating how the ontologies in BioPortal utilize reused content in the modeling of their own content. In this study we investigate how 355 ontologies hosted in the NCBO BioPortal reuse content from other ontologies for the purposes of creating new ontology content. We identified 197 ontologies that reuse content. Among these ontologies, 108 utilize reused classes in the modeling of their own classes and 116 utilize reused properties in class restrictions. Current utilization of reuse and quality issues related to reuse are discussed. Copyright © 2017 Elsevier Inc. All rights reserved.

Inversion of chlorophyll contents by use of hyperspectral CHRIS data based on radiative transfer model

NASA Astrophysics Data System (ADS)

Wang, M. C.; Niu, X. F.; Chen, S. B.; Guo, P. J.; Yang, Q.; Wang, Z. J.

2014-03-01

Chlorophyll content, the most important pigment related to photosynthesis, is the key parameter for vegetation growth. The continuous spectrum characteristics of ground objects can be captured through hyperspectral remotely sensed data. In this study, based on the coniferous forest radiative transfer model, chlorophyll contents were inverted by use of hyperspectral CHRIS data in the coniferous forest coverage of Changbai Mountain Area. In addition, the sensitivity of LIBERTY model was analyzed. The experimental results validated that the reflectance simulation of different chlorophyll contents was coincided with that of the field measurement, and hyperspectral vegetation indices applied to the quantitative inversion of chlorophyll contents was feasible and accurate. This study presents a reasonable method of chlorophyll inversion for the coniferous forest, promotes the inversion precision, is of significance in coniferous forest monitoring.

Controls on Highly Siderophile Element Concentrations in Martian Basalt: Sulfide Saturation and Under-Saturation

NASA Technical Reports Server (NTRS)

Righter, Kevin

2009-01-01

Highly siderophile elements (HSE; Re, Au and the platinum group elements) in shergottites exhibit a wide range from very high, similar to the terrestrial mantle, to very low, similar to sulfide saturated mid ocean ridge basalt (e.g., [1]). This large range has been difficult to explain without good constraints on sulfide saturation or under-saturation [2]. A new model for prediction of sulfide saturation places new constraints on this problem [3]. Shergottite data: For primitive shergottites, pressure and temperature estimates are between 1.2-1.5 GPa, and 1350-1470 C [4]. The range of oxygen fugacities is from FMQ-2 to IW, where the amount of Fe2O3 is low and thus does not have a significant effect on the S saturation values. Finally, the bulk compositions of shergottites have been reported in many recent studies (e.g., [5]). All of this information will be used to test whether shergottites are sulfide saturated [3]. Modeling values and results: The database for HSE partition coefficients has been growing with many new data for silicates and oxides [6-8] to complement a large sulfide database [9- 11]. Combining these data with simple batch melting models allows HSE contents of mantle melts to be estimated for sulfide-bearing vs. sulfide-free mantle. Combining such models with fractional crystallization modeling (e.g., [12]) allows HSE contents of more evolved liquids to be modeled. Most primitive shergottites have high HSE contents (and low S contents) that can be explained by sulfide under-saturated melting of the mantle. An exception is Dhofar 019 which has high S contents and very low HSE contents suggesting sulfide saturation. Most evolved basaltic shergottites have lower S contents than saturation, and intermediate HSE contents that can be explained by olivine, pyroxene, and chromite fractionation. An exception is EET A79001 lithology B, which has very low HSE contents and S contents higher than sulfide saturation values . evidence for sulfide saturation during late fractional crystallization. These results show that shergottite HSE contents are controlled by silicates, oxides, and sulfides. In addition, the mantle producing the most primitive shergottites did not contain near chondritic relative ratios of the HSEs like the terrestrial mantle, and did not experience a late chondritic veneer.

Effect of water content on stability of landslides triggered by earthquakes

NASA Astrophysics Data System (ADS)

Beyabanaki, S.; Bagtzoglou, A. C.; Anagnostou, E. N.

2013-12-01

Earthquake- triggered landslides are one of the most important natural hazards that often result in serious structural damage and loss of life. They are widely studied by several researchers. However, less attention has been focused on soil water content. Although the effect of water content has been widely studied for rainfall- triggered landslides [1], much less attention has been given to it for stability analysis of earthquake- triggered landslides. We developed a combined hydrology and stability model to investigate effect of soil water content on earthquake-triggered landslides. For this purpose, Bishop's method is used to do the slope stability analysis and Richard's equation is employed to model infiltration. Bishop's method is one the most widely methods used for analyzing stability of slopes [2]. Earthquake acceleration coefficient (EAC) is also considered in the model to analyze the effect of earthquake on slope stability. Also, this model is able to automatically determine geometry of the potential landslide. In this study, slopes with different initial water contents are simulated. First, the simulation is performed in the case of earthquake only with different EACs and water contents. As shown in Fig. 1, initial water content has a significant effect on factor of safety (FS). Greater initial water contents lead to less FS. This impact is more significant when EAC is small. Also, when initial water content is high, landslides can happen even with small earthquake accelerations. Moreover, in this study, effect of water content on geometry of landslides is investigated. For this purpose, different cases of landslides triggered by earthquakes only and both rainfall and earthquake for different initial water contents are simulated. The results show that water content has more significant effect on geometry of landslides triggered by rainfall than those triggered by an earthquake. Finally, effect of water content on landslides triggered by earthquakes during rainfall is investigated. In this study, after different durations of rainfall, an earthquake is applied to the model and the elapsed time in which the FS gets less than one obtains by trial and error. The results for different initial water contents and earthquake acceleration coefficients show that landslides can happen after shorter rainfall duration when water content is greater. If water content is high enough, the landslide occurs even without rainfall. References [1] Ray RL, Jacobs JM, de Alba P. Impact of unsaturated zone soil moisture and groundwater table on slope instability. J. Geotech. Geoenviron. Eng., 2010, 136(10):1448-1458. [2] Das B. Principles of Foundation Engineering. Stanford, Cengage Learning, 2011. Fig. 1. Effect of initial water content on FS for different EACs

An Examination of Exposure Control and Content Balancing Restrictions on Item Selection in CATs Using the Partial Credit Model.

ERIC Educational Resources Information Center

Davis, Laurie Laughlin; Pastor, Dena A.; Dodd, Barbara G.; Chiang, Claire; Fitzpatrick, Steven J.

2003-01-01

Examined the effectiveness of the Sympson-Hetter technique and rotated content balancing relative to no exposure control and no content rotation conditions in a computerized adaptive testing system based on the partial credit model. Simulation results show the Sympson-Hetter technique can be used with minimal impact on measurement precision,…

Content Planning and Delivery in a Flipped Classroom: A Qualitative Examination

ERIC Educational Resources Information Center

Oyola, Michelle

2016-01-01

The problem this qualitative case study addressed is the lack of a clear model for flipping all content planning and delivery in elementary classrooms. The purpose of this study was to create a model of how to flip all aspects of content planning and delivery in an elementary classroom. A total of 11 teachers were recruited to participate. All…

Shared Mental Models on the Performance of e-Learning Content Development Teams

ERIC Educational Resources Information Center

Jo, Il-Hyun

2012-01-01

The primary purpose of the study was to investigate team-based e-Learning content development projects from the perspective of the shared mental model (SMM) theory. The researcher conducted a study of 79 e-Learning content development teams in Korea to examine the relationship between taskwork and teamwork SMMs and the performance of the teams.…

Modeling the Soil Water and Energy Balance of a Mixed Grass Rangeland and Evaluating a Soil Water Based Drought Index in Wyoming

NASA Astrophysics Data System (ADS)

Engda, T. A.; Kelleners, T. J.; Paige, G. B.

2013-12-01

Soil water content plays an important role in the complex interaction between terrestrial ecosystems and the atmosphere. Automated soil water content sensing is increasingly being used to assess agricultural drought conditions. A one-dimensional vertical model that calculates incoming solar radiation, canopy energy balance, surface energy balance, snow pack dynamics, soil water flow, snow-soil heat exchange is applied to calculate water flow and heat transport in a Rangeland soil located near Lingel, Wyoming. The model is calibrated and validated using three years of measured soil water content data. Long-term average soil water content dynamics are calculated using a 30 year historical data record. The difference between long-term average soil water content and observed soil water content is compared with plant biomass to evaluate the usefulness of soil water content as a drought indicator. Strong correlation between soil moisture surplus/deficit and plant biomass may prove our hypothesis that soil water content is a good indicator of drought conditions. Soil moisture based drought index is calculated using modeled and measured soil water data input and is compared with measured plant biomass data. A drought index that captures local drought conditions proves the importance of a soil water monitoring network for Wyoming Rangelands to fill the gap between large scale drought indices, which are not detailed enough to assess conditions at local level, and local drought conditions. Results from a combined soil moisture monitoring and computer modeling, and soil water based drought index soil are presented to quantify vertical soil water flow, heat transport, historical soil water variations and drought conditions in the study area.

E-cigarette liquids: Constancy of content across batches and accuracy of labeling.

PubMed

Etter, Jean-François; Bugey, Aurélie

2017-10-01

To assess whether bottles of refill liquids for e-cigarettes were filled true to label, whether their content was constant across two production batches, and whether they contained impurities. In 2013, we purchased on the Internet 18 models from 11 brands of e-liquids. We purchased a second sample of the same models 4months later. We analyzed their content in nicotine, anabasine, propylene glycol, glycerol, ethylene glycol and diethylene glycol, and tested their pH. The median difference between the nicotine value on the labels and the nicotine content in the bottles was 0.3mg/mL (range -5.4 to +3.5mg/mL, i.e. -8% to +30%). For 82% of the samples, the actual nicotine content was within 10% of the value on the labels. All models contained glycerol (median 407mg/mL), and all but three models contained propylene glycol (median 650mg/mL). For all samples, levels of anabasine, ethylene glycol and diethylene glycol were below our limits of detection. The pH of all the e-liquids was alkaline (median pH=9.1; range 8.1 to 9.9). The measured content of two batches of the same model varied by a median of 0% across batches for propylene glycol, 1% for glycerol, 0% for pH, and 0.5% for nicotine (range -15% to +21%; 5th and 95th percentiles: -15% and +10%). The nicotine content of these e-liquids matched the labels on the bottles, and was relatively constant across production batches. The content of propylene glycol and glycerol was also stable across batches, as was the pH. Copyright © 2017. Published by Elsevier Ltd.

Equivalences between refractive index and equilibrium water content of conventional and silicone hydrogel soft contact lenses from automated and manual refractometry.

PubMed

González-Méijome, José M; López-Alemany, Antonio; Lira, Madalena; Almeida, José B; Oliveira, M Elisabete C D Real; Parafita, Manuel A

2007-01-01

The purpose of the present study was to develop mathematical relationships that allow obtaining equilibrium water content and refractive index of conventional and silicone hydrogel soft contact lenses from refractive index measures obtained with automated refractometry or equilibrium water content measures derived from manual refractometry, respectively. Twelve HEMA-based hydrogels of different hydration and four siloxane-based polymers were assayed. A manual refractometer and a digital refractometer were used. Polynomial models obtained from the sucrose curves of equilibrium water content against refractive index and vice-versa were used either considering the whole range of sucrose concentrations (16-100% equilibrium water content) or a range confined to the equilibrium water content of current soft contact lenses (approximately 20-80% equilibrium water content). Values of equilibrium water content measured with the Atago N-2E and those derived from the refractive index measurement with CLR 12-70 by the applications of sucrose-based models displayed a strong linear correlation (r2 = 0.978). The same correlations were obtained when the models are applied to obtain refractive index values from the Atago N-2E and compared with those (values) given by the CLR 12-70 (r2 = 0.978). No significantly different results are obtained between models derived from the whole range of the sucrose solution or the model limited to the normal range of soft contact lens hydration. Present results will have implications for future experimental and clinical research regarding normal hydration and dehydration experiments with hydrogel polymers, and particularly in the field of contact lenses. 2006 Wiley Periodicals, Inc.

Three phase heat and mass transfer model for unsaturated soil freezing process: Part 2 - model validation

NASA Astrophysics Data System (ADS)

Zhang, Yaning; Xu, Fei; Li, Bingxi; Kim, Yong-Song; Zhao, Wenke; Xie, Gongnan; Fu, Zhongbin

2018-04-01

This study aims to validate the three-phase heat and mass transfer model developed in the first part (Three phase heat and mass transfer model for unsaturated soil freezing process: Part 1 - model development). Experimental results from studies and experiments were used for the validation. The results showed that the correlation coefficients for the simulated and experimental water contents at different soil depths were between 0.83 and 0.92. The correlation coefficients for the simulated and experimental liquid water contents at different soil temperatures were between 0.95 and 0.99. With these high accuracies, the developed model can be well used to predict the water contents at different soil depths and temperatures.

Archetype-based conversion of EHR content models: pilot experience with a regional EHR system

PubMed Central

2009-01-01

Background Exchange of Electronic Health Record (EHR) data between systems from different suppliers is a major challenge. EHR communication based on archetype methodology has been developed by openEHR and CEN/ISO. The experience of using archetypes in deployed EHR systems is quite limited today. Currently deployed EHR systems with large user bases have their own proprietary way of representing clinical content using various models. This study was designed to investigate the feasibility of representing EHR content models from a regional EHR system as openEHR archetypes and inversely to convert archetypes to the proprietary format. Methods The openEHR EHR Reference Model (RM) and Archetype Model (AM) specifications were used. The template model of the Cambio COSMIC, a regional EHR product from Sweden, was analyzed and compared to the openEHR RM and AM. This study was focused on the convertibility of the EHR semantic models. A semantic mapping between the openEHR RM/AM and the COSMIC template model was produced and used as the basis for developing prototype software that performs automated bi-directional conversion between openEHR archetypes and COSMIC templates. Results Automated bi-directional conversion between openEHR archetype format and COSMIC template format has been achieved. Several archetypes from the openEHR Clinical Knowledge Repository have been imported into COSMIC, preserving most of the structural and terminology related constraints. COSMIC templates from a large regional installation were successfully converted into the openEHR archetype format. The conversion from the COSMIC templates into archetype format preserves nearly all structural and semantic definitions of the original content models. A strategy of gradually adding archetype support to legacy EHR systems was formulated in order to allow sharing of clinical content models defined using different formats. Conclusion The openEHR RM and AM are expressive enough to represent the existing clinical content models from the template based EHR system tested and legacy content models can automatically be converted to archetype format for sharing of knowledge. With some limitations, internationally available archetypes could be converted to the legacy EHR models. Archetype support can be added to legacy EHR systems in an incremental way allowing a migration path to interoperability based on standards. PMID:19570196

Thoughts About Health Policy Content in Baccalaureate Nursing Programs.

PubMed

Waddell, Ashley; Adams, Jeffrey M; Fawcett, Jacqueline

2016-10-01

We describe a framework used to analyze health policy content in baccalaureate nursing program courses that combines the conceptual model for nursing and health policy and the Adams influence model to account for knowledge and skills needed for health policy work. Our analysis of health policy content in courses in one baccalaureate nursing program focused on what policies were emphasized and how educational content supported the development of personal influence. The analysis revealed course content focused on public sources of health policies and lack of overt course content about policies from organizational and professional sources. Additionally, we identified little course content about the development of personal influence skills except for communication and message articulation components. As the nursing profession continues to build influence in the policy arena, educators must continue to prepare future nurses for such work. © The Author(s) 2016.

Feasibility of Representing a Danish Microbiology Model Using FHIR.

PubMed

Andersen, Mie Vestergaard; Kristensen, Ida Hvass; Larsen, Malene Møller; Pedersen, Claus Hougaard; Gøeg, Kirstine Rosenbeck; Pape-Haugaard, Louise B

2017-01-01

Achieving interoperability in health is a challenge and requires standardization. The newly developed HL7 standard: Fast Healthcare Interoperability Resources (FHIR) promises both flexibility and interoperability. This study investigates the feasibility of expressing a Danish microbiology message model content in FHIR to explore whether complex in-use legacy models can be migrated and what challenges this may pose. The Danish microbiology message model (the DMM) is used as a case to illustrate challenges and opportunities accosted with applying the FHIR standard. Mapping of content from DMM to FHIR was done as close as possible to the DMM to minimize migration costs except when the structure of the content did not fit into FHIR. From the DMM a total of 183 elements were mapped to FHIR. 75 (40.9%) elements were modeled as existing FHIR elements and 96 (52.5%) elements were modeled as extensions and 12 (6.6%) elements were deemed unnecessary because of build-in FHIR characteristics. In this study, it was possible to represent the content of a Danish message model using HL7 FHIR.

Modeling effects of moisture content and advection on odor causing VOCs volatilization from stored swine manure.

PubMed

Liao, C M; Liang, H M

2000-05-01

Two models for evaluating the contents and advection of manure moisture on odor causing volatile organic compounds (VOC-odor) volatilization from stored swine manure were studied for their ability to predict the volatilization rate (indoor air concentration) and cumulative exposure dose: a MJ-I model and a MJ-II model. Both models simulating depletion of source contaminant via volatilization and degradation based on an analytical model adapted from the behavior assessment model of Jury et al. In the MJ-I model, manure moisture movement was negligible, whereas in the MJ-II model, time-dependent indoor air concentrations was a function of constant manure moisture contents and steady-state moisture advection. Predicted indoor air concentrations and inhaled doses for the study VOC-odors of p-cresol, toluene, and p-xylene varied by up to two to three orders of magnitude depending on the manure moisture conditions. The sensitivity analysis of both models suggests that when manure moisture movement exists, simply MJ-I model is inherently not sufficient to represent a more generally volatilization process, which can even become stringent as moisture content increases. The conclusion illustrates how one needs to include a wide variety of manure moisture values in order to fully assess the complex volatilization mechanisms that are present in a real situation.

Integrating auxiliary data and geophysical techniques for the estimation of soil clay content using CHAID algorithm

NASA Astrophysics Data System (ADS)

Abbaszadeh Afshar, Farideh; Ayoubi, Shamsollah; Besalatpour, Ali Asghar; Khademi, Hossein; Castrignano, Annamaria

2016-03-01

This study was conducted to estimate soil clay content in two depths using geophysical techniques (Ground Penetration Radar-GPR and Electromagnetic Induction-EMI) and ancillary variables (remote sensing and topographic data) in an arid region of the southeastern Iran. GPR measurements were performed throughout ten transects of 100 m length with the line spacing of 10 m, and the EMI measurements were done every 10 m on the same transect in six sites. Ten soil cores were sampled randomly in each site and soil samples were taken from the depth of 0-20 and 20-40 cm, and then the clay fraction of each of sixty soil samples was measured in the laboratory. Clay content was predicted using three different sets of properties including geophysical data, ancillary data, and a combination of both as inputs to multiple linear regressions (MLR) and decision tree-based algorithm of Chi-Squared Automatic Interaction Detection (CHAID) models. The results of the CHAID and MLR models with all combined data showed that geophysical data were the most important variables for the prediction of clay content in two depths in the study area. The proposed MLR model, using the combined data, could explain only 0.44 and 0.31% of the total variability of clay content in 0-20 and 20-40 cm depths, respectively. Also, the coefficient of determination (R2) values for the clay content prediction, using the constructed CHAID model with the combined data, was 0.82 and 0.76 in 0-20 and 20-40 cm depths, respectively. CHAID models, therefore, showed a greater potential in predicting soil clay content from geophysical and ancillary data, while traditional regression methods (i.e. the MLR models) did not perform as well. Overall, the results may encourage researchers in using georeferenced GPR and EMI data as ancillary variables and CHAID algorithm to improve the estimation of soil clay content.

A Model for the Redesign of Training Materials for the Nuclear Power Industry.

ERIC Educational Resources Information Center

Gredler, Margaret Bell

1986-01-01

Presents consultant/staff model for training program redesign and discusses activities involved: interpretation of Instructional System Design (ISD) model concepts into plans in trainer's content area and sequenced sets of content-appropriate verbs for objectives; presenting training sessions on design issues; and holding individual conference…

Two-Phase Item Selection Procedure for Flexible Content Balancing in CAT

ERIC Educational Resources Information Center

Cheng, Ying; Chang, Hua-Hua; Yi, Qing

2007-01-01

Content balancing is an important issue in the design and implementation of computerized adaptive testing (CAT). Content-balancing techniques that have been applied in fixed content balancing, where the number of items from each content area is fixed, include constrained CAT (CCAT), the modified multinomial model (MMM), modified constrained CAT…

Content-Related Knowledge of Biology Teachers from Secondary Schools: Structure and Learning Opportunities

ERIC Educational Resources Information Center

Großschedl, Jörg; Mahler, Daniela; Kleickmann, Thilo; Harms, Ute

2014-01-01

Teachers' content-related knowledge is a key factor influencing the learning progress of students. Different models of content-related knowledge have been proposed by educational researchers; most of them take into account three categories: content knowledge, pedagogical content knowledge, and curricular knowledge. As there is no consensus about…

Effect of the science teaching advancement through modeling physical science professional development workshop on teachers' attitudes, beliefs and content knowledge and students' content knowledge

NASA Astrophysics Data System (ADS)

Dietz, Laura

The Science Teaching Advancement through Modeling Physical Science (STAMPS) professional development workshop was evaluated for effectiveness in improving teachers' and students' content knowledge. Previous research has shown modeling to be an effective method of instruction for improving student and teacher content knowledge, evidenced by assessment scores. Data includes teacher scores on the Force Concept Inventory (FCI; Hestenes, Wells, & Swackhamer, 1992) and the Chemistry Concept Inventory (CCI; Jenkins, Birk, Bauer, Krause, & Pavelich, 2004), as well as student scores on a physics and chemistry assessment. Quantitative data is supported by teacher responses to a post workshop survey and classroom observations. Evaluation of the data shows that the STAMPS professional development workshop was successful in improving both student and teacher content knowledge. Conclusions and suggestions for future study are also included.

A genome-wide association study reveals novel elite allelic variations in seed oil content of Brassica napus.

PubMed

Liu, Sheng; Fan, Chuchuan; Li, Jiana; Cai, Guangqin; Yang, Qingyong; Wu, Jian; Yi, Xinqi; Zhang, Chunyu; Zhou, Yongming

2016-06-01

A set of additive loci for seed oil content were identified using association mapping and one of the novel loci on the chromosome A5 was validated by linkage mapping. Increasing seed oil content is one of the most important goals in the breeding of oilseed crops including Brassica napus, yet the genetic basis for variations in this important trait remains unclear. By genome-wide association study of seed oil content using 521 B. napus accessions genotyped with the Brassica 60K SNP array, we identified 50 loci significantly associated with seed oil content using three statistical models, the general linear model, the mixed linear model and the Anderson-Darling test. Together, the identified loci could explain approximately 80 % of the total phenotypic variance, and 29 of these loci have not been reported previously. Furthermore, a novel locus on the chromosome A5 that could increase 1.5-1.7 % of seed oil content was validated in an independent bi-parental linkage population. Haplotype analysis showed that the favorable alleles for seed oil content exhibit cumulative effects. Our results thus provide valuable information for understanding the genetic control of seed oil content in B. napus and may facilitate marker-based breeding for a higher seed oil content in this important oil crop.

Probabilistic modeling of the evolution of gene synteny within reconciled phylogenies

PubMed Central

2015-01-01

Background Most models of genome evolution concern either genetic sequences, gene content or gene order. They sometimes integrate two of the three levels, but rarely the three of them. Probabilistic models of gene order evolution usually have to assume constant gene content or adopt a presence/absence coding of gene neighborhoods which is blind to complex events modifying gene content. Results We propose a probabilistic evolutionary model for gene neighborhoods, allowing genes to be inserted, duplicated or lost. It uses reconciled phylogenies, which integrate sequence and gene content evolution. We are then able to optimize parameters such as phylogeny branch lengths, or probabilistic laws depicting the diversity of susceptibility of syntenic regions to rearrangements. We reconstruct a structure for ancestral genomes by optimizing a likelihood, keeping track of all evolutionary events at the level of gene content and gene synteny. Ancestral syntenies are associated with a probability of presence. We implemented the model with the restriction that at most one gene duplication separates two gene speciations in reconciled gene trees. We reconstruct ancestral syntenies on a set of 12 drosophila genomes, and compare the evolutionary rates along the branches and along the sites. We compare with a parsimony method and find a significant number of results not supported by the posterior probability. The model is implemented in the Bio++ library. It thus benefits from and enriches the classical models and methods for molecular evolution. PMID:26452018

Spatial Irrigation Management Using Remote Sensing Water Balance Modeling and Soil Water Content Monitoring

NASA Astrophysics Data System (ADS)

Barker, J. Burdette

Spatially informed irrigation management may improve the optimal use of water resources. Sub-field scale water balance modeling and measurement were studied in the context of irrigation management. A spatial remote-sensing-based evapotranspiration and soil water balance model was modified and validated for use in real-time irrigation management. The modeled ET compared well with eddy covariance data from eastern Nebraska. Placement and quantity of sub-field scale soil water content measurement locations was also studied. Variance reduction factor and temporal stability were used to analyze soil water content data from an eastern Nebraska field. No consistent predictor of soil water temporal stability patterns was identified. At least three monitoring locations were needed per irrigation management zone to adequately quantify the mean soil water content. The remote-sensing-based water balance model was used to manage irrigation in a field experiment. The research included an eastern Nebraska field in 2015 and 2016 and a western Nebraska field in 2016 for a total of 210 plot-years. The response of maize and soybean to irrigation using variations of the model were compared with responses from treatments using soil water content measurement and a rainfed treatment. The remote-sensing-based treatment prescribed more irrigation than the other treatments in all cases. Excessive modeled soil evaporation and insufficient drainage times were suspected causes of the model drift. Modifying evaporation and drainage reduced modeled soil water depletion error. None of the included response variables were significantly different between treatments in western Nebraska. In eastern Nebraska, treatment differences for maize and soybean included evapotranspiration and a combined variable including evapotranspiration and deep percolation. Both variables were greatest for the remote-sensing model when differences were found to be statistically significant. Differences in maize yield in 2015 were attributed to random error. Soybean yield was lowest for the remote-sensing-based treatment and greatest for rainfed, possibly because of overwatering and lodging. The model performed well considering that it did not include soil water content measurements during the season. Future work should improve the soil evaporation and drainage formulations, because of excessive precipitation and include aerial remote sensing imagery and soil water content measurement as model inputs.

Development of Experienced Science Teachers' Pedagogical Content Knowledge of Models of the Solar System and the Universe

ERIC Educational Resources Information Center

Henze, Ineke; van Driel, Jan H.; Verloop, Nico

2008-01-01

This paper investigates the developing pedagogical content knowledge (PCK) of nine experienced science teachers in their first few years of teaching a new science syllabus in the Dutch secondary education system. We aimed to identify the content and structure of the PCK for a specific topic in the new syllabus, "Models of the Solar System and…

Content and Language Symbiosis in a Maieutic, Translanguaging Pattern (CLSL): An Exploratory Practice in Italy

ERIC Educational Resources Information Center

Agolli, Renata

2015-01-01

This paper aims to introduce pre-CLIL through the CLSL (content & languages [L1/L2] shared learning) model, which operates as a bridge for a full CLIL immersion. It analyses the characteristics of this new learning model that springs up from immanent needs of Italian educational reality by reporting results on the way content and language…

Instructional Developer as Content Specialist: Three Case Studies Utilizing the Instructional Development-Operations Research Model.

ERIC Educational Resources Information Center

Faust, Stephen M.

1980-01-01

Presents a 3-phase model (content research, specification, delivery) for instructional development-operations research and describes its application in developing courses in zoology, geology, and paleontology. (MER)

Initialization of soil-water content in regional-scale atmospheric prediction models

NASA Technical Reports Server (NTRS)

Smith, Christopher B.; Lakhtakia, Mercedes; Capehart, William J.; Carlson, Toby N.

1994-01-01

The purpose of this study is to demonstrate the feasibility of determining the soil-water content fields required as initial conditions for land surface components within atmospheric prediction models. This is done using a model of the hydrologic balance and conventional meteorological observations, land cover, and soils information. A discussion is presented of the subgrid-scale effects, the integration time, and the choice of vegetation type on the soil-water content patterns. Finally, comparisons are made between two The Pennsylvania State University/National Center for Atmospheric Research mesoscale model simulations, one using climatological fields and the other one using the soil-moisture fields produced by this new method.

A Model-Based Method for Content Validation of Automatically Generated Test Items

ERIC Educational Resources Information Center

Zhang, Xinxin; Gierl, Mark

2016-01-01

The purpose of this study is to describe a methodology to recover the item model used to generate multiple-choice test items with a novel graph theory approach. Beginning with the generated test items and working backward to recover the original item model provides a model-based method for validating the content used to automatically generate test…

Modeling moisture content of fine dead wildland fuels: Input to the BEHAVE fire prediction system

Treesearch

Richard C. Rothermel; Ralph A. Wilson; Glen A. Morris; Stephen S. Sackett

1986-01-01

Describes a model for predicting moisture content of fine fuels for use with the BEHAVE fire behavior and fuel modeling system. The model is intended to meet the need for more accurate predictions of fine fuel moisture, particularly in northern conifer stands and on days following rain. The model is based on the Canadian Fine Fuel Moisture Code (FFMC), modified to...

Study on fast measurement of sugar content of yogurt using Vis/NIR spectroscopy techniques

NASA Astrophysics Data System (ADS)

He, Yong; Feng, Shuijuan; Wu, Di; Li, Xiaoli

2006-09-01

In order to measuring the sugar content of yogurt rapidly, a fast measurement of sugar content of yogurt using Vis/NIR-spectroscopy techniques was established. 25 samples selected separately from five different brands of yogurt were measured by Vis/NIR-spectroscopy. The sugar content of yogurt on positions scanned by spectrum were measured by a sugar content meter. The mathematical model between sugar content and Vis/NIR spectral measurements was established and developed based on partial least squares (PLS). The correlation coefficient of sugar content based on PLS model is more than 0.894, and standard error of calibration (SEC) is 0.356, standard error of prediction (SEP) is 0.389. Through predicting the sugar content quantitatively of 35 samples of yogurt from 5 different brands, the correlation coefficient between predictive value and measured value of those samples is more than 0.934. The results show the good to excellent prediction performance. The Vis/NIR spectroscopy technique had significantly greater accuracy for determining the sugar content. It was concluded that the Vis/NIRS measurement technique seems reliable to assess the fast measurement of sugar content of yogurt, and a new method for the measurement of sugar content of yogurt was established.

Water infiltration in prewetted porous media: dynamic capillary pressure and Green-Ampt modeling

NASA Astrophysics Data System (ADS)

Hsu, S.; Hilpert, M.

2013-12-01

Recently, an experimental study has shown that the modified Green-Ampt (GA) model, which accounts for a velocity-dependent capillary pressure, can describe water infiltration in dry sand columns better than the classical GA model. Studies have also shown that the initial water content of prewetted porous media affects the dynamic capillary pressure during infiltration. In this study, we performed a series of downward water infiltration experiments in prewetted sand columns for four different initial water contents: 0%, 3.3%, 6.5%, and 13.8%. We also used three different ponding heights: 10 cm, 20 cm, and 40 cm. As expected, an increase in ponding height resulted in a monotonic increase in cumulative infiltration. However, we found anomalous behavior, in that the cumulative infiltration did not monotonically decrease as the initial water content increased. When modeling the experiments with the modified GA approach, we linked this anomalous behavior to the reduction factor in the model for dynamic capillary pressure that is a function of initial water content.

Complex messages regarding a thin ideal appearing in teenage girls' magazines from 1956 to 2005.

PubMed

Luff, Gina M; Gray, James J

2009-03-01

Seventeen and YM were assessed from 1956 through 2005 (n=312) to examine changes in the messages about thinness sent to teenage women. Trends were analyzed through an investigation of written, internal content focused on dieting, exercise, or both, while cover models were examined to explore fluctuations in body size. Pearson's Product correlations and weighted-least squares linear regression models were used to demonstrate changes over time. The frequency of written content related to exercise and combined plans increased in Seventeen, while a curvilinear relationship between time and content relating to dieting appeared. YM showed a linear increase in content related to dieting, exercise, and combined plans. Average cover model body size increased over time in YM while demonstrating no significant changes in Seventeen. Overall, more written messages about dieting and exercise appeared in teen's magazines in 2005 than before while the average cover model body size increased.

Modularization and Structured Markup for Learning Content in an Academic Environment

ERIC Educational Resources Information Center

Schluep, Samuel; Bettoni, Marco; Schar, Sissel Guttormsen

2006-01-01

This article aims to present a flexible component model for modular, web-based learning content, and a simple structured markup schema for the separation of content and presentation. The article will also contain an overview of the dynamic Learning Content Management System (dLCMS) project, which implements these concepts. Content authors are a…

Mapping the Structure of Knowledge for Teaching Nominal Categorical Data Analysis

ERIC Educational Resources Information Center

Groth, Randall E.; Bergner, Jennifer A.

2013-01-01

This report describes a model for mapping cognitive structures related to content knowledge for teaching. The model consists of knowledge elements pertinent to teaching a content domain, the nature of the connections among them, and a means for representing the elements and connections visually. The model is illustrated through empirical data…

Modeling the release of E. coli D21g with transients in water content

USDA-ARS?s Scientific Manuscript database

Transients in water content are well known to mobilize colloids that are retained in the vadose zone. However, there is no consensus on the proper model formulation to simulate colloid release during drainage and imbibition. We present a model that relates colloid release to changes in the air-water...

Mathematical Modelling Research in Turkey: A Content Analysis Study

ERIC Educational Resources Information Center

Çelik, H. Coskun

2017-01-01

The aim of the present study was to examine the mathematical modelling studies done between 2004 and 2015 in Turkey and to reveal their tendencies. Forty-nine studies were selected using purposeful sampling based on the term, "mathematical modelling" with Higher Education Academic Search Engine. They were analyzed with content analysis.…

Teachers Develop CLIL Materials in Argentina: A Workshop Experience

ERIC Educational Resources Information Center

Banegas, Darío Luis

2016-01-01

Content and language integrated learning (CLIL) is a Europe-born approach. Nevertheless, CLIL as a language learning approach has been implemented in Latin America in different ways and models: content-driven models and language-driven models. As regards the latter, new school curricula demand that CLIL be used in secondary education in Argentina…

The ANISA Model of Education: A Critique. Issues in Native Education.

ERIC Educational Resources Information Center

Four Worlds Development Project, Lethbridge (Alberta).

The ANISA model of education (D. Streets and D. Jordan) classifies curriculum content into four areas--the physical environment, the human environment, the unknown environment, and the self--and encourages horizontal integration between content areas. The ANISA model holds that the process of learning consists of differentiation, integration, and…

Professional Education in Expert Search: A Content Model

ERIC Educational Resources Information Center

Smith, Catherine L.; Roseberry, Martha I.

2013-01-01

This paper presents a descriptive model of the subject matter taught in courses on expert search in ALA-accredited programs, answering the question: What is taught in formal professional education on search expertise? The model emerged from a grounded content analysis of 44 course descriptions and 16 syllabi, and was validated via a review of…

Language Implications for Advertising in International Markets: A Model for Message Content and Message Execution.

ERIC Educational Resources Information Center

Beard, John; Yaprak, Attila

A content analysis model for assessing advertising themes and messages generated primarily for United States markets to overcome barriers in the cultural environment of international markets was developed and tested. The model is based on three primary categories for generating, evaluating, and executing advertisements: rational, emotional, and…

Spatial variability of chlorophyll and nitrogen content of rice from hyperspectral imagery

NASA Astrophysics Data System (ADS)

Moharana, Shreedevi; Dutta, Subashisa

2016-12-01

Chlorophyll and nitrogen are the most essential parameters for paddy crop growth. Spectroradiometric measurements were collected at canopy level during critical growth period of rice. Chemical analysis was performed to quantify the total leaf content. By exploiting the ground based measurements, regression models were established for chlorophyll and nitrogen aimed indices with their corresponding crop growth variables. Vegetation index models were developed for mapping these parameters from Hyperion imagery in an agriculture system. It was inferred that the present Simple Ratio (SR) and Leaf Nitrogen Concentration (LNC) indices, which followed a linear and nonlinear relationship respectively, were completely different from published Tian et al. (2011). The nitrogen content varied widely from 1 to 4% and only 2 to 3% for paddy crop using present modified index models and Tian et al. (2011) respectively. The modified LNC index model performed better than the established Tian et al. (2011) model as far as estimated nitrogen content from Hyperion imagery was concerned. Furthermore, within the observed chlorophyll range obtained from the studied rice varieties grown in the rice agriculture system, the index models (LNC, OASVI, Gitelson, mSR and MTCI) performed well in the spatial distribution of rice chlorophyll content from Hyperion imagery. Spatial distribution of total chlorophyll content varied widely from 1.77 to 5.81 mg/g (LNC), 3.0 to 13 mg/g (OASVI), 0.5 to 10.43 mg/g (Gitelson), 2.18 to 10.61 mg/g (mSR) and 2.90 to 5.40 mg/g (MTCI). The spatial information of these parameters will help in proper nutrient management, yield forecasting, and will serve as inputs for crop growth and forecasting models for a precision rice agriculture system.

A numerical investigation of the influence of radiation and moisture content on pyrolysis and ignition of a leaf-like fuel element

Treesearch

B.L. Yashwanth; B. Shotorban; S. Mahalingam; C.W. Lautenberger; David Weise

2016-01-01

The effects of thermal radiation and moisture content on the pyrolysis and gas phase ignition of a solid fuel element containing high moisture content were investigated using the coupled Gpyro3D/FDS models. The solid fuel has dimensions of a typical Arctostaphylos glandulosa leaf which is modeled as thin cellulose subjected to radiative heating on...

Proposal for a new content model for the Austrian Procedure Catalogue.

PubMed

Neururer, Sabrina B; Pfeiffer, Karl P

2013-01-01

The Austrian Procedure Catalogue is used for procedure coding in Austria. Its architecture and content has some major weaknesses. The aim of this study is the presentation of a new potential content model for this classification system consisting of main characteristics of health interventions. It is visualized using a UML class diagram. Based on this proposition, an implementation of an ontology for procedure coding is planned.

Investigating the Link Between Radiologists Gaze, Diagnostic Decision, and Image Content

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

Tourassi, Georgia; Voisin, Sophie; Paquit, Vincent C

2013-01-01

Objective: To investigate machine learning for linking image content, human perception, cognition, and error in the diagnostic interpretation of mammograms. Methods: Gaze data and diagnostic decisions were collected from six radiologists who reviewed 20 screening mammograms while wearing a head-mounted eye-tracker. Texture analysis was performed in mammographic regions that attracted radiologists attention and in all abnormal regions. Machine learning algorithms were investigated to develop predictive models that link: (i) image content with gaze, (ii) image content and gaze with cognition, and (iii) image content, gaze, and cognition with diagnostic error. Both group-based and individualized models were explored. Results: By poolingmore » the data from all radiologists machine learning produced highly accurate predictive models linking image content, gaze, cognition, and error. Merging radiologists gaze metrics and cognitive opinions with computer-extracted image features identified 59% of the radiologists diagnostic errors while confirming 96.2% of their correct diagnoses. The radiologists individual errors could be adequately predicted by modeling the behavior of their peers. However, personalized tuning appears to be beneficial in many cases to capture more accurately individual behavior. Conclusions: Machine learning algorithms combining image features with radiologists gaze data and diagnostic decisions can be effectively developed to recognize cognitive and perceptual errors associated with the diagnostic interpretation of mammograms.« less

Geographical Topics Learning of Geo-Tagged Social Images.

PubMed

Zhang, Xiaoming; Ji, Shufan; Wang, Senzhang; Li, Zhoujun; Lv, Xueqiang

2016-03-01

With the availability of cheap location sensors, geotagging of images in online social media is very popular. With a large amount of geo-tagged social images, it is interesting to study how these images are shared across geographical regions and how the geographical language characteristics and vision patterns are distributed across different regions. Unlike textual document, geo-tagged social image contains multiple types of content, i.e., textual description, visual content, and geographical information. Existing approaches usually mine geographical characteristics using a subset of multiple types of image contents or combining those contents linearly, which ignore correlations between different types of contents, and their geographical distributions. Therefore, in this paper, we propose a novel method to discover geographical characteristics of geo-tagged social images using a geographical topic model called geographical topic model of social images (GTMSIs). GTMSI integrates multiple types of social image contents as well as the geographical distributions, in which image topics are modeled based on both vocabulary and visual features. In GTMSI, each region of the image would have its own topic distribution, and hence have its own language model and vision pattern. Experimental results show that our GTMSI could identify interesting topics and vision patterns, as well as provide location prediction and image tagging.

Comparison of observed lung retention and urinary excretion of thorium workers and members of the public in India with the values predicted by the ICRP biokinetic model.

PubMed

Jaiswal, D D; Singh, I S; Nair, Suma; Dang, H S; Garg, S P; Pradhan, A S

2004-01-01

The daily intake of natural Th and its contents in lungs, skeleton and liver of an Indian adult population group were estimated using radiochemical neutron activation analysis (RNAA) technique. These data on daily intake (through inhalation and ingestion) were used to compute Th contents in lungs and other systemic organs such as skeleton and liver using the new human respiratory tract model (HRTM) and the new biokinetic model of Th. The theoretically computed Th contents in lungs, skeleton and liver of an average Indian adult are 2.56, 4.00 and 0.17 microg, respectively which are comparable with the corresponding experimentally measured values of 4.31, 3.45 and 0.14 microg in an urban population group living in Mumbai. The measured lung contents of Th in a group of five occupational workers were used to compute their total body Th contents and the corresponding daily urinary excretions. The computed total body contents and daily urinary excretions of Th in the five subjects compared favourably with their measured values. These studies, thus, validate the new biokinetic model of Th in natural as well as in occupational exposures in Indian conditions.

Separating Cognitive and Content Domains in Mathematical Competence

ERIC Educational Resources Information Center

Harks, Birgit; Klieme, Eckhard; Hartig, Johannes; Leiss, Dominik

2014-01-01

The present study investigates the empirical separability of mathematical (a) content domains, (b) cognitive domains, and (c) content-specific cognitive domains. There were 122 items representing two content domains (linear equations vs. theorem of Pythagoras) combined with two cognitive domains (modeling competence vs. technical competence)…

Biodiesel content determination in diesel fuel blends using near infrared (NIR) spectroscopy and support vector machines (SVM).

PubMed

Alves, Julio Cesar L; Poppi, Ronei J

2013-01-30

This work verifies the potential of support vector machine (SVM) algorithm applied to near infrared (NIR) spectroscopy data to develop multivariate calibration models for determination of biodiesel content in diesel fuel blends that are more effective and appropriate for analytical determinations of this type of fuel nowadays, providing the usual extended analytical range with required accuracy. Considering the difficulty to develop suitable models for this type of determination in an extended analytical range and that, in practice, biodiesel/diesel fuel blends are nowadays most often used between 0 and 30% (v/v) of biodiesel content, a calibration model is suggested for the range 0-35% (v/v) of biodiesel in diesel blends. The possibility of using a calibration model for the range 0-100% (v/v) of biodiesel in diesel fuel blends was also investigated and the difficulty in obtaining adequate results for this full analytical range is discussed. The SVM models are compared with those obtained with PLS models. The best result was obtained by the SVM model using the spectral region 4400-4600 cm(-1) providing the RMSEP value of 0.11% in 0-35% biodiesel content calibration model. This model provides the determination of biodiesel content in agreement with the accuracy required by ABNT NBR and ASTM reference methods and without interference due to the presence of vegetable oil in the mixture. The best SVM model fit performance for the relationship studied is also verified by providing similar prediction results with the use of 4400-6200 cm(-1) spectral range while the PLS results are much worse over this spectral region. Copyright © 2012 Elsevier B.V. All rights reserved.

The U.S. Military and Social Media

DTIC Science & Technology

2015-04-01

Instruction 51-303, it is not copyrighted, but is the property of the United States government. iii   TABLE OF CONTENTS Page...DISCLAIMER ................................................................................................................... .ii TABLE OF CONTENTS ...38 FIGURE 1: Content Acceptance Model ..............................................................................5

[Application of time domain reflectometry for determination of wate content in Xiangsha Yangwei pills].

PubMed

Long, Feng-Lai; Sun, Xiao-Mei; Peng, Xiu-Juan; Liu, Peng; He, Fang-Hui

2016-08-01

Xiangsha Yangwei pill was selected as a model drug in this research, and time domain reflectometry (TDR) was used to determine the water content in the pill. The effects of five factors including the number of pill layers, pill packing density, atmospheric moisture, ambient temperature and the ratio of pill formula were investigated on water content. The results showed that the number of pill layers and ambient temperature had significant effects on water content of pills, while the pill packing density, atmospheric moisture and pill formula ratio had little effect on the determination of water content in pills. The reflection value was stable when 6 layers of pills were used. Under the condition of 25 ℃ and 45% relative humidity, the water content of pills ranged from 4.01% to 22.38%, showing good linear relationship between water content and reflection value, and the model equation was as follows: Y=0.279X－21.670 (R²=0.997 0). Verification experiment was used to explain the feasibility of this prediction model. The precision of the method complied with the methodology standard. It is concluded that TDR can be used in determination of water content in Xiangsha Yangwei pills. Additionally, TDR, as a new way to quickly and efficiently determine the water content, has a prospect application in the processing of traditional Chinese medicine pharmacy, especially for concentrated pill. Copyright© by the Chinese Pharmaceutical Association.

Estimating cadmium concentration in the edible part of Capsicum annuum using hyperspectral models.

PubMed

Wang, Ting; Wei, Hong; Zhou, Cui; Gu, Yanwen; Li, Rui; Chen, Hongchun; Ma, Wenchao

2017-10-09

Hyperspectral remote sensing can be applied to the rapid and nondestructive monitoring of heavy-metal pollution in crops. To realize the rapid and real-time detection of cadmium in the edible part (fruit) of Capsicum annuum, the leaf spectral reflectance of plants exposed to different levels of cadmium stress was measured using hyperspectral remote sensing during four growth stages. The spectral indices or bands sensitive to cadmium stress were determined by correlation analysis, and hyperspectral estimation models for predicting the cadmium content in the fruit of C. annuum during the mature growth stage were established. The models were cross validated by taking the sensitive spectral indices in the bud stage and the sensitive spectral bands in the flowering stage as the input variables. The results indicated that cadmium accumulated in the leaves and fruit of C. annuum and leaf cadmium content in the three early growth stages were correlated with the cadmium content of the pepper in the mature stage. Leaf spectral reflectance was sensitive to cadmium stress, and the first derivative of the original spectral reflectance was strongly correlated with leaf cadmium content during all growth stages. Among the established models, the multiple regression model based on the sensitive spectral bands in the flowering stage was optimal for predicting fruit cadmium content of the pepper. This model provides a promising method to ensure food safety during the early growth stage of the plant.

Study on Hyperspectral Characteristics and Estimation Model of Soil Mercury Content

NASA Astrophysics Data System (ADS)

Liu, Jinbao; Dong, Zhenyu; Sun, Zenghui; Ma, Hongchao; Shi, Lei

2017-12-01

In this study, the mercury content of 44 soil samples in Guan Zhong area of Shaanxi Province was used as the data source, and the reflectance spectrum of soil was obtained by ASD Field Spec HR (350-2500 nm) Comparing the reflection characteristics of different contents and the effect of different pre-treatment methods on the establishment of soil heavy metal spectral inversion model. The first order differential, second order differential and reflectance logarithmic transformations were carried out after the pre-treatment of NOR, MSC and SNV, and the sensitive bands of reflectance and mercury content in different mathematical transformations were selected. A hyperspectral estimation model is established by regression method. The results of chemical analysis show that there is a serious Hg pollution in the study area. The results show that: (1) the reflectivity decreases with the increase of mercury content, and the sensitive regions of mercury are located at 392 ~ 455nm, 923nm ~ 1040nm and 1806nm ~ 1969nm. (2) The combination of NOR, MSC and SNV transformations combined with differential transformations can improve the information of heavy metal elements in the soil, and the combination of high correlation band can improve the stability and prediction ability of the model. (3) The partial least squares regression model based on the logarithm of the original reflectance is better and the precision is higher, Rc2 = 0.9912, RMSEC = 0.665; Rv2 = 0.9506, RMSEP = 1.93, which can achieve the mercury content in this region Quick forecast.

Ultrasound hepatic/renal ratio and hepatic attenuation rate for quantifying liver fat content.

PubMed

Zhang, Bo; Ding, Fang; Chen, Tian; Xia, Liang-Hua; Qian, Juan; Lv, Guo-Yi

2014-12-21

To establish and validate a simple quantitative assessment method for nonalcoholic fatty liver disease (NAFLD) based on a combination of the ultrasound hepatic/renal ratio and hepatic attenuation rate. A total of 170 subjects were enrolled in this study. All subjects were examined by ultrasound and (1)H-magnetic resonance spectroscopy ((1)H-MRS) on the same day. The ultrasound hepatic/renal echo-intensity ratio and ultrasound hepatic echo-intensity attenuation rate were obtained from ordinary ultrasound images using the MATLAB program. Correlation analysis revealed that the ultrasound hepatic/renal ratio and hepatic echo-intensity attenuation rate were significantly correlated with (1)H-MRS liver fat content (ultrasound hepatic/renal ratio: r = 0.952, P = 0.000; hepatic echo-intensity attenuation r = 0.850, P = 0.000). The equation for predicting liver fat content by ultrasound (quantitative ultrasound model) is: liver fat content (%) = 61.519 × ultrasound hepatic/renal ratio + 167.701 × hepatic echo-intensity attenuation rate -26.736. Spearman correlation analysis revealed that the liver fat content ratio of the quantitative ultrasound model was positively correlated with serum alanine aminotransferase, aspartate aminotransferase, and triglyceride, but negatively correlated with high density lipoprotein cholesterol. Receiver operating characteristic curve analysis revealed that the optimal point for diagnosing fatty liver was 9.15% in the quantitative ultrasound model. Furthermore, in the quantitative ultrasound model, fatty liver diagnostic sensitivity and specificity were 94.7% and 100.0%, respectively, showing that the quantitative ultrasound model was better than conventional ultrasound methods or the combined ultrasound hepatic/renal ratio and hepatic echo-intensity attenuation rate. If the (1)H-MRS liver fat content had a value < 15%, the sensitivity and specificity of the ultrasound quantitative model would be 81.4% and 100%, which still shows that using the model is better than the other methods. The quantitative ultrasound model is a simple, low-cost, and sensitive tool that can accurately assess hepatic fat content in clinical practice. It provides an easy and effective parameter for the early diagnosis of mild hepatic steatosis and evaluation of the efficacy of NAFLD treatment.

A model for the prediction of latent errors using data obtained during the development process

NASA Technical Reports Server (NTRS)

Gaffney, J. E., Jr.; Martello, S. J.

1984-01-01

A model implemented in a program that runs on the IBM PC for estimating the latent (or post ship) content of a body of software upon its initial release to the user is presented. The model employs the count of errors discovered at one or more of the error discovery processes during development, such as a design inspection, as the input data for a process which provides estimates of the total life-time (injected) error content and of the latent (or post ship) error content--the errors remaining a delivery. The model presented presumes that these activities cover all of the opportunities during the software development process for error discovery (and removal).

Agricultural soil moisture experiment, Colby, Kansas 1978: Measured and predicted hydrological properties of the soil

NASA Technical Reports Server (NTRS)

Arya, L. M. (Principal Investigator)

1980-01-01

Predictive procedures for developing soil hydrologic properties (i.e., relationships of soil water pressure and hydraulic conductivity to soil water content) are presented. Three models of the soil water pressure-water content relationship and one model of the hydraulic conductivity-water content relationship are discussed. Input requirements for the models are indicated, and computational procedures are outlined. Computed hydrologic properties for Keith silt loam, a soil typer near Colby, Kansas, on which the 1978 Agricultural Soil Moisture Experiment was conducted, are presented. A comparison of computed results with experimental data in the dry range shows that analytical models utilizing a few basic hydrophysical parameters can produce satisfactory data for large-scale applications.

Content and Workflow Management for Library Websites: Case Studies

ERIC Educational Resources Information Center

Yu, Holly, Ed.

2005-01-01

Using database-driven web pages or web content management (WCM) systems to manage increasingly diverse web content and to streamline workflows is a commonly practiced solution recognized in libraries today. However, limited library web content management models and funding constraints prevent many libraries from purchasing commercially available…

Automatic Content Recommendation and Aggregation According to SCORM

ERIC Educational Resources Information Center

Neves, Daniel Eugênio; Brandão, Wladmir Cardoso; Ishitani, Lucila

2017-01-01

Although widely used, the SCORM metadata model for content aggregation is difficult to be used by educators, content developers and instructional designers. Particularly, the identification of contents related with each other, in large repositories, and their aggregation using metadata as defined in SCORM, has been demanding efforts of computer…

Based on user interest level of modeling scenarios and browse content

NASA Astrophysics Data System (ADS)

Zhao, Yang

2017-08-01

User interest modeling is the core of personalized service, taking into account the impact of situational information on user preferences, the user behavior days of financial information. This paper proposes a method of user interest modeling based on scenario information, which is obtained by calculating the similarity of the situation. The user's current scene of the approximate scenario set; on the "user - interest items - scenarios" three-dimensional model using the situation pre-filtering method of dimension reduction processing. View the content of the user interested in the theme, the analysis of the page content to get each topic of interest keywords, based on the level of vector space model user interest. The experimental results show that the user interest model based on the scenario information is within 9% of the user's interest prediction, which is effective.

Prediction of Moisture Content for Congou Black Tea Withering Leaves Using Image Features and Nonlinear Method.

PubMed

Liang, Gaozhen; Dong, Chunwang; Hu, Bin; Zhu, Hongkai; Yuan, Haibo; Jiang, Yongwen; Hao, Guoshuang

2018-05-18

Withering is the first step in the processing of congou black tea. With respect to the deficiency of traditional water content detection methods, a machine vision based NDT (Non Destructive Testing) method was established to detect the moisture content of withered leaves. First, according to the time sequences using computer visual system collected visible light images of tea leaf surfaces, and color and texture characteristics are extracted through the spatial changes of colors. Then quantitative prediction models for moisture content detection of withered tea leaves was established through linear PLS (Partial Least Squares) and non-linear SVM (Support Vector Machine). The results showed correlation coefficients higher than 0.8 between the water contents and green component mean value (G), lightness component mean value (L * ) and uniformity (U), which means that the extracted characteristics have great potential to predict the water contents. The performance parameters as correlation coefficient of prediction set (Rp), root-mean-square error of prediction (RMSEP), and relative standard deviation (RPD) of the SVM prediction model are 0.9314, 0.0411 and 1.8004, respectively. The non-linear modeling method can better describe the quantitative analytical relations between the image and water content. With superior generalization and robustness, the method would provide a new train of thought and theoretical basis for the online water content monitoring technology of automated production of black tea.

Using the Communication in Science Inquiry Project Professional Development Model to Facilitate Learning Middle School Genetics Concepts

ERIC Educational Resources Information Center

Baker, Dale R.; Lewis, Elizabeth B.; Uysal, Sibel; Purzer, Senay; Lang, Michael; Baker, Perry

2011-01-01

This study describes the effect of embedding content in the Communication in Inquiry Science Project professional development model for science and language arts teachers. The model uses four components of successful professional development (content focus, active learning, extended duration, participation by teams of teachers from the same school…

Designing Cognitively Diagnostic Assessment for Algebraic Content Knowledge and Thinking Skills

ERIC Educational Resources Information Center

Zhang, Zhidong

2018-01-01

This study explored a diagnostic assessment method that emphasized the cognitive process of algebra learning. The study utilized a design and a theory-driven model to examine the content knowledge. Using the theory driven model, the thinking skills of algebra learning was also examined. A Bayesian network model was applied to represent the theory…

Calculating moisture content for 1000-hour timelag fuels in western Washington and western Oregon.

Treesearch

Roger D. Ottmar; David V. Sandberg

1985-01-01

A predictive model is presented to calculate moisture content of 1000-hour timelag fuels in Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) and western hemlock (Tsuga heterophylla (Raf.) Sarg.) logging slash in western Washington and western Oregon. The model is a modification of the 1000-hour fuel moisture model of the...

Factorial Validity of the Decisional Involvement Scale as a Measure of Content and Context of Nursing Practice.

PubMed

Yurek, Leo A; Havens, Donna S; Hays, Spencer; Hughes, Linda C

2015-10-01

Decisional involvement is widely recognized as an essential component of a professional nursing practice environment. In recent years, researchers have added to the conceptualization of nurses' role in decision-making to differentiate between the content and context of nursing practice. Yet, instruments that clearly distinguish between these two dimensions of practice are lacking. The purpose of this study was to examine the factorial validity of the Decisional Involvement Scale (DIS) as a measure of both the content and context of nursing practice. This secondary analysis was conducted using data from a longitudinal action research project to improve the quality of nursing practice and patient care in six hospitals (N = 1,034) in medically underserved counties of Pennsylvania. A cross-sectional analysis of baseline data from the parent study was used to compare the factor structure of two models (one nested within the other) using confirmatory factor analysis. Although a comparison of the two models indicated that the addition of second-order factors for the content and context of nursing practice improved model fit, neither model provided optimal fit to the data. Additional model-generating research is needed to develop the DIS as a valid measure of decisional involvement for both the content and context of nursing practice. © 2015 Wiley Periodicals, Inc.

What Makes a Message Stick? The Role of Content and Context in Social Media Epidemics

DTIC Science & Technology

2013-09-23

First, we propose visual memes , or frequently re-posted short video segments, for detecting and monitoring latent video interactions at scale. Content...interactions (such as quoting, or remixing, parts of a video). Visual memes are extracted by scalable detection algorithms that we develop, with...high accuracy. We further augment visual memes with text, via a statistical model of latent topics. We model content interactions on YouTube with

Homepage to distribute the anatomy learning contents including Visible Korean products, comics, and books.

PubMed

Chung, Beom Sun; Chung, Min Suk

2018-03-01

The authors have operated the homepage (http://anatomy.co.kr) to provide the learning contents of anatomy. From the homepage, sectioned images, volume models, and surface models-all Visible Korean products-can be downloaded. The realistic images can be interactively manipulated, which will give rise to the interest in anatomy. The various anatomy comics (learning comics, comic strips, plastination comics, etc.) are approachable. Visitors can obtain the regional anatomy book with concise contents, mnemonics, and schematics as well as the simplified dissection manual and the pleasant anatomy essay. Medical students, health allied professional students, and even laypeople are expected to utilize the easy and comforting anatomy contents. It is hoped that other anatomists successively produce and distribute their own informative contents.

[Effect of Small Knife Needle on β-enorpin and Enkehalin Contents of Tansverse Process Syndrome of the Third Vertebra].

PubMed

Liu, Nai-gang; Guo, Chang-qing; Sun, Hong-mei; Li, Xiao-hong; Wu, Hai-xia; Xu, Hong

2016-04-01

To explore the analgesic mechanism of small knife needle for treating transverse process syndrome of the third vertebra (TPSTV) by observing peripheral and central changesof β-endorphin (β-EP) and enkephalin (ENK) contents. Totally 30 Japanese white big-ear rabbits of clean grade were divided into 5 groups according to random digit table, i.e., the normal control group, the model group, the small knife needle group, the electroacupunture (EA) group, and the small knife needle plus EA group, 6 in each group. The TPSTV model was established by inserting a piece of gelatin sponge into the left transverse process of 3rd lumbar vertebrae. Rabbits in the small knife needlegroup were intervened by small knife needle. Those in the EA group were intervened by EA at bilateralWeizhong (BL40). Those in the small knife needle plus EA group were intervened by small knife needleand EA at bilateral Weizhong (BL40). Contents of β-EP and ENK in plasma, muscle, spinal cord, and hypothalamus were determined after sample collection at day 28 after modeling. Compared with the normal control group, contents of β-EP and ENK in plasma and muscle increased significantly, and contents of β-EP and ENK in spinal cord and hypothalamus decreased significantly in the model group (P < 0.05, P < 0.01). Contents of β-EP and ENK approximated normal levels in the three treatment groups after respective treatment. Compared with the model group, the content of β-EP in muscle decreased, and contents of β-EP and ENK in hypothalamus increased in the three treatment groups after respective treatment (P < 0.05). There were no significant difference among the three treatment groups (P > 0.05). Small knife needle treatment and EA had benign regulation on peripheral and central β-EP and ENK in TPSTV rabbits. Small knife needle treatment showed better effect than that of EA.

The Second Prototype of the Development of a Technological Pedagogical Content Knowledge Based Instructional Design Model: An Implementation Study in a Technology Integration Course

ERIC Educational Resources Information Center

Lee, Chia-Jung; Kim, ChanMin

2014-01-01

This study presents a refined technological pedagogical content knowledge (also known as TPACK) based instructional design model, which was revised using findings from the implementation study of a prior model. The refined model was applied in a technology integration course with 38 preservice teachers. A case study approach was used in this…

Web 2.0 Articles: Content Analysis and a Statistical Model to Predict Recognition of the Need for New Instructional Design Strategies

ERIC Educational Resources Information Center

Liu, Leping; Maddux, Cleborne D.

2008-01-01

This article presents a study of Web 2.0 articles intended to (a) analyze the content of what is written and (b) develop a statistical model to predict whether authors' write about the need for new instructional design strategies and models. Eighty-eight technology articles were subjected to lexical analysis and a logistic regression model was…

Uncertainty in modeled upper ocean heat content change

NASA Astrophysics Data System (ADS)

Tokmakian, Robin; Challenor, Peter

2014-02-01

This paper examines the uncertainty in the change in the heat content in the ocean component of a general circulation model. We describe the design and implementation of our statistical methodology. Using an ensemble of model runs and an emulator, we produce an estimate of the full probability distribution function (PDF) for the change in upper ocean heat in an Atmosphere/Ocean General Circulation Model, the Community Climate System Model v. 3, across a multi-dimensional input space. We show how the emulator of the GCM's heat content change and hence, the PDF, can be validated and how implausible outcomes from the emulator can be identified when compared to observational estimates of the metric. In addition, the paper describes how the emulator outcomes and related uncertainty information might inform estimates of the same metric from a multi-model Coupled Model Intercomparison Project phase 3 ensemble. We illustrate how to (1) construct an ensemble based on experiment design methods, (2) construct and evaluate an emulator for a particular metric of a complex model, (3) validate the emulator using observational estimates and explore the input space with respect to implausible outcomes and (4) contribute to the understanding of uncertainties within a multi-model ensemble. Finally, we estimate the most likely value for heat content change and its uncertainty for the model, with respect to both observations and the uncertainty in the value for the input parameters.

FTIR-ATR-based prediction and modelling of lignin and energy contents reveals independent intra-specific variation of these traits in bioenergy poplars

PubMed Central

2011-01-01

Background There is an increasing demand for renewable resources to replace fossil fuels. However, different applications such as the production of secondary biofuels or combustion for energy production require different wood properties. Therefore, high-throughput methods are needed for rapid screening of wood in large scale samples, e.g., to evaluate the outcome of tree breeding or genetic engineering. In this study, we investigated the intra-specific variability of lignin and energy contents in extractive-free wood of hybrid poplar progenies (Populus trichocarpa × deltoides) and tested if the range was sufficient for the development of quantitative prediction models based on Fourier transform infrared spectroscopy (FTIR). Since lignin is a major energy-bearing compound, we expected that the energy content of wood would be positively correlated with the lignin content. Results Lignin contents of extractive-free poplar wood samples determined by the acetyl bromide method ranged from 23.4% to 32.1%, and the calorific values measured with a combustion calorimeter varied from 17260 to 19767 J g-1. For the development of calibration models partial least square regression and cross validation was applied to correlate FTIR spectra determined with an attenuated total reflectance (ATR) unit to measured values of lignin or energy contents. The best models with high coefficients of determination (R2 (calibration) = 0.91 and 0.90; R2 (cross-validation) = 0.81 and 0.79) and low root mean square errors of cross validation (RMSECV = 0.77% and 62 J g-1) for lignin and energy determination, respectively, were obtained after data pre-processing and automatic wavenumber restriction. The calibration models were validated by analyses of independent sets of wood samples yielding R2 = 0.88 and 0.86 for lignin and energy contents, respectively. Conclusions These results show that FTIR-ATR spectroscopy is suitable as a high-throughput method for lignin and energy estimations in large data sets. Our study revealed that the intra-specific variations in lignin and energy contents were unrelated to each other and that the lignin content, therefore, was no predictor of the energy content. Employing principle component analyses we showed that factor loadings for the energy content were mainly associated with carbohydrate ring vibrations, whereas those for lignin were mainly related to aromatic compounds. Therefore, our analysis suggests that it may be possible to optimize the energy content of trees without concomitant increase in lignin. PMID:21477346

Assessing uncertainty in radar measurements on simplified meteorological scenarios

NASA Astrophysics Data System (ADS)

Molini, L.; Parodi, A.; Rebora, N.; Siccardi, F.

2006-02-01

A three-dimensional radar simulator model (RSM) developed by Haase (1998) is coupled with the nonhydrostatic mesoscale weather forecast model Lokal-Modell (LM). The radar simulator is able to model reflectivity measurements by using the following meteorological fields, generated by Lokal Modell, as inputs: temperature, pressure, water vapour content, cloud water content, cloud ice content, rain sedimentation flux and snow sedimentation flux. This work focuses on the assessment of some uncertainty sources associated with radar measurements: absorption by the atmospheric gases, e.g., molecular oxygen, water vapour, and nitrogen; attenuation due to the presence of a highly reflecting structure between the radar and a "target structure". RSM results for a simplified meteorological scenario, consisting of a humid updraft on a flat surface and four cells placed around it, are presented.

Sugar and acid content of Citrus prediction modeling using FT-IR fingerprinting in combination with multivariate statistical analysis.

PubMed

Song, Seung Yeob; Lee, Young Koung; Kim, In-Jung

2016-01-01

A high-throughput screening system for Citrus lines were established with higher sugar and acid contents using Fourier transform infrared (FT-IR) spectroscopy in combination with multivariate analysis. FT-IR spectra confirmed typical spectral differences between the frequency regions of 950-1100 cm(-1), 1300-1500 cm(-1), and 1500-1700 cm(-1). Principal component analysis (PCA) and subsequent partial least square-discriminant analysis (PLS-DA) were able to discriminate five Citrus lines into three separate clusters corresponding to their taxonomic relationships. The quantitative predictive modeling of sugar and acid contents from Citrus fruits was established using partial least square regression algorithms from FT-IR spectra. The regression coefficients (R(2)) between predicted values and estimated sugar and acid content values were 0.99. These results demonstrate that by using FT-IR spectra and applying quantitative prediction modeling to Citrus sugar and acid contents, excellent Citrus lines can be early detected with greater accuracy. Copyright © 2015 Elsevier Ltd. All rights reserved.

Estimating chlorophyll content of spartina alterniflora at leaf level using hyper-spectral data

NASA Astrophysics Data System (ADS)

Wang, Jiapeng; Shi, Runhe; Liu, Pudong; Zhang, Chao; Chen, Maosi

2017-09-01

Spartina alterniflora, one of most successful invasive species in the world, was firstly introduced to China in 1979 to accelerate sedimentation and land formation via so-called "ecological engineering", and it is now widely distributed in coastal saltmarshes in China. A key question is how to retrieve chlorophyll content to reflect growth status, which has important implication of potential invasiveness. In this work, an estimation model of chlorophyll content of S. alterniflora was developed based on hyper-spectral data in the Dongtan Wetland, Yangtze Estuary, China. The spectral reflectance of S. alterniflora leaves and their corresponding chlorophyll contents were measured, and then the correlation analysis and regression (i.e., linear, logarithmic, quadratic, power and exponential regression) method were established. The spectral reflectance was transformed and the feature parameters (i.e., "san bian", "lv feng" and "hong gu") were extracted to retrieve the chlorophyll content of S. alterniflora . The results showed that these parameters had a large correlation coefficient with chlorophyll content. On the basis of the correlation coefficient, mathematical models were established, and the models of power and exponential based on SDb had the least RMSE and larger R2 , which had a good performance regarding the inversion of chlorophyll content of S. alterniflora.

Simple, fast, and low-cost camera-based water content measurement with colorimetric fluorescent indicator

NASA Astrophysics Data System (ADS)

Song, Seok-Jeong; Kim, Tae-Il; Kim, Youngmi; Nam, Hyoungsik

2018-05-01

Recently, a simple, sensitive, and low-cost fluorescent indicator has been proposed to determine water contents in organic solvents, drugs, and foodstuffs. The change of water content leads to the change of the indicator's fluorescence color under the ultra-violet (UV) light. Whereas the water content values could be estimated from the spectrum obtained by a bulky and expensive spectrometer in the previous research, this paper demonstrates a simple and low-cost camera-based water content measurement scheme with the same fluorescent water indicator. Water content is calculated over the range of 0-30% by quadratic polynomial regression models with color information extracted from the captured images of samples. Especially, several color spaces such as RGB, xyY, L∗a∗b∗, u‧v‧, HSV, and YCBCR have been investigated to establish the optimal color information features over both linear and nonlinear RGB data given by a camera before and after gamma correction. In the end, a 2nd order polynomial regression model along with HSV in a linear domain achieves the minimum mean square error of 1.06% for a 3-fold cross validation method. Additionally, the resultant water content estimation model is implemented and evaluated in an off-the-shelf Android-based smartphone.

Systematized water content calculation in cartilage using T1-mapping MR estimations: design and validation of a mathematical model.

PubMed

Shiguetomi-Medina, J M; Ramirez-Gl, J L; Stødkilde-Jørgensen, H; Møller-Madsen, B

2017-09-01

Up to 80 % of cartilage is water; the rest is collagen fibers and proteoglycans. Magnetic resonance (MR) T1-weighted measurements can be employed to calculate the water content of a tissue using T1 mapping. In this study, a method that translates T1 values into water content data was tested statistically. To develop a predictive equation, T1 values were obtained for tissue-mimicking gelatin samples. 1.5 T MRI was performed using inverse angle phase and an inverse sequence at 37 (±0.5) °C. Regions of interest were manually delineated and the mean T1 value was estimated in arbitrary units. Data were collected and modeled using linear regression. To validate the method, articular cartilage from six healthy pigs was used. The experiment was conducted in accordance with the Danish Animal Experiment Committee. Double measurements were performed for each animal. Ex vivo, all water in the tissue was extracted by lyophilization, thus allowing the volume of water to be measured. This was then compared with the predicted water content via Lin's concordance correlation coefficient at the 95 % confidence level. The mathematical model was highly significant when compared to a null model (p < 0.0001). 97.3 % of the variation in water content can be explained by absolute T1 values. Percentage water content could be predicted as 0.476 + (T1 value) × 0.000193 × 100 %. We found that there was 98 % concordance between the actual and predicted water contents. The results of this study demonstrate that MR data can be used to predict percentage water contents of cartilage samples. 3 (case-control study).

Validation of Soil Water Content Estimation Method on Agricultural Regions in South Korea

NASA Astrophysics Data System (ADS)

Shin, Y.; Kim, M.

2016-12-01

The continuous water stress caused by decrease of soil water has a direct influence to the crop growth in a upland crop area. The agricultural drought is occured if water requirement is not supplied timely in crop growh process. It is more important to understand the soil characteristics for high accuracy soil moisture estimation because of the soil water contents largely depends on soil properties. The RDA(Rural Development Administration) has provided real-time soil moisture observations corrected for 71 points in the South Korea. In this study, we developed a soil water content estimation method that considered soil hydraulic parameters for the observation points of soil water content in agricultural regions operated by the RDA. SWAP(Soil-Water-Atmosphere-Plant) model was used in the estimation of soil water contents. The soil hydraulic parameters that is the input data of the SWAP model were estimated using the ROSETTA model developed by the U.S. Department of Agriculture(USDA). Meteorological data observed from AWS(Automatic Weather Station) were used including daily maximum temperature(°), daily minimum temperature(°), relative humidity(%), solar radiation, wind speed and precipitation data. We choosed 56 stations there are no missing of meteorological data and have soil physical properties. For the verification of soil water content estimation method, we used Haenam KoFlux observation data that are observed long-term soil water contents over 2009-2015(2014 missing) years. In the case of 2015, there are good reproducibility between observation of soil water contents and results of SWAP model simulation with R2=0.72, RMSE=0.026 and TCC=0.849. In the case of precipitation event, the simulation results were slightly overestimated more than observation. However there are good reproducibility in the case of soil water reduction due to continuous non-precipitation periods. We have simulated the soil water contents of the 56 stations that being operated in the RDA from 4 January 2015 to 31 October 2015 using the SWAP model. The environmental setting of SWAP modle according to the station applied it equally. The results showed a significant difference to the reproducibility according to the observation station.

Coupled Land Surface-Subsurface Hydrogeophysical Inverse Modeling to Estimate Soil Organic Carbon Content in an Arctic Tundra

NASA Astrophysics Data System (ADS)

Tran, A. P.; Dafflon, B.; Hubbard, S.

2017-12-01

Soil organic carbon (SOC) is crucial for predicting carbon climate feedbacks in the vulnerable organic-rich Arctic region. However, it is challenging to achieve this property due to the general limitations of conventional core sampling and analysis methods. In this study, we develop an inversion scheme that uses single or multiple datasets, including soil liquid water content, temperature and ERT data, to estimate the vertical profile of SOC content. Our approach relies on the fact that SOC content strongly influences soil hydrological-thermal parameters, and therefore, indirectly controls the spatiotemporal dynamics of soil liquid water content, temperature and their correlated electrical resistivity. The scheme includes several advantages. First, this is the first time SOC content is estimated by using a coupled hydrogeophysical inversion. Second, by using the Community Land Model, we can account for the land surface dynamics (evapotranspiration, snow accumulation and melting) and ice/liquid phase transition. Third, we combine a deterministic and an adaptive Markov chain Monte Carlo optimization algorithm to better estimate the posterior distributions of desired model parameters. Finally, the simulated subsurface variables are explicitly linked to soil electrical resistivity via petrophysical and geophysical models. We validate the developed scheme using synthetic experiments. The results show that compared to inversion of single dataset, joint inversion of these datasets significantly reduces parameter uncertainty. The joint inversion approach is able to estimate SOC content within the shallow active layer with high reliability. Next, we apply the scheme to estimate OC content along an intensive ERT transect in Barrow, Alaska using multiple datasets acquired in the 2013-2015 period. The preliminary results show a good agreement between modeled and measured soil temperature, thaw layer thickness and electrical resistivity. The accuracy of estimated SOC content will be evaluated by comparison with measurements from soil samples along the transect. Our study presents a new surface-subsurface, deterministic-stochastic hydrogeophysical inversion approach, as well as the benefit of including multiple types of data to estimate SOC and associated hydrological-thermal dynamics.

Developing a NIR multispectral imaging for prediction and visualization of peanut protein content using variable selection algorithms

NASA Astrophysics Data System (ADS)

Cheng, Jun-Hu; Jin, Huali; Liu, Zhiwei

2018-01-01

The feasibility of developing a multispectral imaging method using important wavelengths from hyperspectral images selected by genetic algorithm (GA), successive projection algorithm (SPA) and regression coefficient (RC) methods for modeling and predicting protein content in peanut kernel was investigated for the first time. Partial least squares regression (PLSR) calibration model was established between the spectral data from the selected optimal wavelengths and the reference measured protein content ranged from 23.46% to 28.43%. The RC-PLSR model established using eight key wavelengths (1153, 1567, 1972, 2143, 2288, 2339, 2389 and 2446 nm) showed the best predictive results with the coefficient of determination of prediction (R2P) of 0.901, and root mean square error of prediction (RMSEP) of 0.108 and residual predictive deviation (RPD) of 2.32. Based on the obtained best model and image processing algorithms, the distribution maps of protein content were generated. The overall results of this study indicated that developing a rapid and online multispectral imaging system using the feature wavelengths and PLSR analysis is potential and feasible for determination of the protein content in peanut kernels.

Effects of moisture content on wind erosion thresholds of biochar

NASA Astrophysics Data System (ADS)

Silva, F. C.; Borrego, C.; Keizer, J. J.; Amorim, J. H.; Verheijen, F. G. A.

2015-12-01

Biochar, i.e. pyrolysed biomass, as a soil conditioner is gaining increasing attention in research and industry, with guidelines and certifications being developed for biochar production, storage and handling, as well as for application to soils. Adding water to biochar aims to reduce its susceptibility to become air-borne during and after the application to soils, thereby preventing, amongst others, human health issues from inhalation. The Bagnold model has previously been modified to explain the threshold friction velocity of coal particles at different moisture contents, by adding an adhesive effect. However, it is unknown if this model also works for biochar particles. We measured the threshold friction velocities of a range of biochar particles (woody feedstock) under a range of moisture contents by using a wind tunnel, and tested the performance of the modified Bagnold model. Results showed that the threshold friction velocity can be significantly increased by keeping the gravimetric moisture content at or above 15% to promote adhesive effects between the small particles. For the specific biochar of this study, the modified Bagnold model accurately estimated threshold friction velocities of biochar particles up to moisture contents of 10%.

Using a System Model for Irrigation Management

NASA Astrophysics Data System (ADS)

de Souza, Leonardo; de Miranda, Eu; Sánchez-Román, Rodrigo; Orellana-González, Alba

2014-05-01

When using Systems Thinking variables involved in any process have a dynamic behavior, according to nonstatic relationships with the environment. In this paper it is presented a system dynamics model developed to be used as an irrigation management tool. The model involves several parameters related to irrigation such as: soil characteristics, climate data and culture's physiological parameters. The water availability for plants in the soil is defined as a stock in the model, and this soil water content will define the right moment to irrigate and the water depth required to be applied. The crop water consumption will reduce soil water content; it is defined by the potential evapotranspiration (ET) that acts as an outflow from the stock (soil water content). ET can be estimated by three methods: a) FAO Penman-Monteith (ETPM), b) Hargreaves-Samani (ETHS) method, based on air temperature data and c) Class A pan (ETTCA) method. To validate the model were used data from the States of Ceará and Minas Gerais, Brazil, and the culture was bean. Keyword: System Dynamics, soil moisture content, agricultural water balance, irrigation scheduling.

[Influence of shenxu gutong capsule on femoral inorganic elements content and ash weight in rats].

PubMed

Chen, X; Wei, J; Chen, Y

1998-02-01

To explore the mechanism of Shenxu Gutong Capsule (SXGTC) in treating postmenopausal osteoporosis. Using ovariectomized rats as the model of postmenopausal osteoporosis, the effect of SXGTC on inorganic element content of femur and femoral ash weight of the model rats were surveyed. Animals were divided into model group, SXGTC high dose group, SXGTC low dose group, positive control group (treated with Gushukang) and normal control group. The medication began at one week after operation and lasting for 120 days. The contents of inorganic elements, including Ca, P, Mg, Zn, Cu and Mn in the three medicated groups were higher than those of the model group (P < 0.01). The effect of SXGTC was dose dependent. The difference between the SXGTC groups and the positive control group was insignificant. The femoral ash weight of the SXGTC high dose group and the positive control group was significantly higher than that of the model group (P < 0.01). SXGTC could antagonize the rat's bony change caused by ovariectomy to increase the inorganic contents in bone, which may, in grneral, lead to a bone-strengthening effect.

Digital Broadband Content: Digital Content Strategies and policies. OECD Digital Economy Papers, No. 119

ERIC Educational Resources Information Center

OECD Publishing (NJ1), 2006

2006-01-01

The development of digital content raises new issues as rapid technological developments challenge existing business models and government policies. This OECD study identifies and discusses six groups of business and public policy issues and illustrates these with existing and potential OECD Digital Content Strategies and Policies: (1) Innovation…

Mineral content prediction for unconventional oil and gas reservoirs based on logging data

NASA Astrophysics Data System (ADS)

Maojin, Tan; Youlong, Zou; Guoyue

2012-09-01

Coal bed methane and shale oil &gas are both important unconventional oil and gas resources, whose reservoirs are typical non-linear with complex and various mineral components, and the logging data interpretation model are difficult to establish for calculate the mineral contents, and the empirical formula cannot be constructed due to various mineral. The radial basis function (RBF) network analysis is a new method developed in recent years; the technique can generate smooth continuous function of several variables to approximate the unknown forward model. Firstly, the basic principles of the RBF is discussed including net construct and base function, and the network training is given in detail the adjacent clustering algorithm specific process. Multi-mineral content for coal bed methane and shale oil &gas, using the RBF interpolation method to achieve a number of well logging data to predict the mineral component contents; then, for coal-bed methane reservoir parameters prediction, the RBF method is used to realized some mineral contents calculation such as ash, volatile matter, carbon content, which achieves a mapping from various logging data to multimineral. To shale gas reservoirs, the RBF method can be used to predict the clay content, quartz content, feldspar content, carbonate content and pyrite content. Various tests in coalbed and gas shale show the method is effective and applicable for mineral component contents prediction

Response Styles in Rating Scales: Simultaneous Modeling of Content-Related Effects and the Tendency to Middle or Extreme Categories

ERIC Educational Resources Information Center

Tutz, Gerhard; Berger, Moritz

2016-01-01

Heterogeneity in response styles can affect the conclusions drawn from rating scale data. In particular, biased estimates can be expected if one ignores a tendency to middle categories or to extreme categories. An adjacent categories model is proposed that simultaneously models the content-related effects and the heterogeneity in response styles.…

Explorable Three-Dimensional Digital Model of the Female Pelvis, Pelvic Contents, and Perineum for Anatomical Education

ERIC Educational Resources Information Center

Sergovich, Aimee; Johnson, Marjorie; Wilson, Timothy D.

2010-01-01

The anatomy of the pelvis is complex, multilayered, and its three-dimensional organization is conceptually difficult for students to grasp. The aim of this project was to create an explorable and projectable stereoscopic, three-dimensional (3D) model of the female pelvis and pelvic contents for anatomical education. The model was created using…

A Dynamic Model for Nitrogen‐stressed Lettuce

PubMed Central

SEGINER, IDO

2003-01-01

A previously developed dynamic lettuce model, designed to predict growth and nitrate content under the normal range of glasshouse environmental conditions, has been extended to cover high nitrogen‐stress situations. Under severe shortage of nitrogen, lettuce has been observed to grow at a very slow rate, as well as to have abnormally low water content, low reduced‐nitrogen content and negligible nitrate content. The new model mimics these observations by adding to the original model a storage compartment for ‘excess’ carbon. The resulting model has three compartments: (1) ‘vacuole’, where the soluble non‐structural material is stored, and the nitrate : carbon ratio may vary as needed to maintain a constant osmotic potential; (2) ‘structure’, a metabolically active compartment with fixed chemical composition; and (3) ‘excess‐carbon’, which serves as a long‐term storage of ‘waterless’ carbohydrates. Simulations with the model illustrate its ability to predict the effect of light, temperature and nitrogen in the nutrient solution on the long‐term growth and composition of lettuce. They also illustrate the effects of plant size, and the associated relative growth rate, on the characteristic times of transient responses resulting from step changes in the environment. PMID:12714361

[Development of an analyzing system for soil parameters based on NIR spectroscopy].

PubMed

Zheng, Li-Hua; Li, Min-Zan; Sun, Hong

2009-10-01

A rapid estimation system for soil parameters based on spectral analysis was developed by using object-oriented (OO) technology. A class of SOIL was designed. The instance of the SOIL class is the object of the soil samples with the particular type, specific physical properties and spectral characteristics. Through extracting the effective information from the modeling spectral data of soil object, a map model was established between the soil parameters and its spectral data, while it was possible to save the mapping model parameters in the database of the model. When forecasting the content of any soil parameter, the corresponding prediction model of this parameter can be selected with the same soil type and the similar soil physical properties of objects. And after the object of target soil samples was carried into the prediction model and processed by the system, the accurate forecasting content of the target soil samples could be obtained. The system includes modules such as file operations, spectra pretreatment, sample analysis, calibrating and validating, and samples content forecasting. The system was designed to run out of equipment. The parameters and spectral data files (*.xls) of the known soil samples can be input into the system. Due to various data pretreatment being selected according to the concrete conditions, the results of predicting content will appear in the terminal and the forecasting model can be stored in the model database. The system reads the predicting models and their parameters are saved in the model database from the module interface, and then the data of the tested samples are transferred into the selected model. Finally the content of soil parameters can be predicted by the developed system. The system was programmed with Visual C++6.0 and Matlab 7.0. And the Access XP was used to create and manage the model database.

[Study on effect of jinshui liujun jian oral liquid on serum superoxide dismutase activity and malonyldialdehyde content in mice with chronic bronchitis].

PubMed

Zhao, C Y; Shen, Y S; Meng, H

2001-11-01

To study the effect of Jinshui Liujun Jian Oral Liquid (JLJOL) on serum superoxide dismutase (SOD) activity and malonyldialdehyde (MDA) content in mice with chronic bronchitis. JLJOL was given to the chronic bronchitis mice model (induced by smoking) through gastrogavage, and then SOD activity and MDA content were tested. SOD activity in model mice after JLJOL treatment was 0.67 +/- 0.15 NU/L, which was significantly higher than that in the untreated model (0.39 +/- 0.13 NU/L, P < 0.01). But the MDA content in treated mice was significantly lower than that in untreated one (9.26 +/- 2.90 nmol/L vs 16.07 +/- 5.62 nmol/L, P < 0.01). JLJOL could scavenge the injury of free radical on organism.

Content, Process, and Product: Modeling Differentiated Instruction

ERIC Educational Resources Information Center

Taylor, Barbara Kline

2015-01-01

Modeling differentiated instruction is one way to demonstrate how educators can incorporate instructional strategies to address students' needs, interests, and learning styles. This article discusses how secondary teacher candidates learn to focus on content--the "what" of instruction; process--the "how" of instruction;…

Quantifying the sensitivity of feedstock properties and process conditions on hydrochar yield, carbon content, and energy content.

PubMed

Li, Liang; Wang, Yiying; Xu, Jiting; Flora, Joseph R V; Hoque, Shamia; Berge, Nicole D

2018-08-01

Hydrothermal carbonization (HTC) is a wet, low temperature thermal conversion process that continues to gain attention for the generation of hydrochar. The importance of specific process conditions and feedstock properties on hydrochar characteristics is not well understood. To evaluate this, linear and non-linear models were developed to describe hydrochar characteristics based on data collected from HTC-related literature. A Sobol analysis was subsequently conducted to identify parameters that most influence hydrochar characteristics. Results from this analysis indicate that for each investigated hydrochar property, the model fit and predictive capability associated with the random forest models is superior to both the linear and regression tree models. Based on results from the Sobol analysis, the feedstock properties and process conditions most influential on hydrochar yield, carbon content, and energy content were identified. In addition, a variational process parameter sensitivity analysis was conducted to determine how feedstock property importance changes with process conditions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Development of a multivariate calibration model for the determination of dry extract content in Brazilian commercial bee propolis extracts through UV-Vis spectroscopy

NASA Astrophysics Data System (ADS)

Barbeira, Paulo J. S.; Paganotti, Rosilene S. N.; Ássimos, Ariane A.

2013-10-01

This study had the objective of determining the content of dry extract of commercial alcoholic extracts of bee propolis through Partial Least Squares (PLS) multivariate calibration and electronic spectroscopy. The PLS model provided a good prediction of dry extract content in commercial alcoholic extracts of bee propolis in the range of 2.7 a 16.8% (m/v), presenting the advantage of being less laborious and faster than the traditional gravimetric methodology. The PLS model was optimized with outlier detection tests according to the ASTM E 1655-05. In this study it was possible to verify that a centrifugation stage is extremely important in order to avoid the presence of waxes, resulting in a more accurate model. Around 50% of the analyzed samples presented content of dry extract lower than the value established by Brazilian legislation, in most cases, the values found were different from the values claimed in the product's label.

Further experimentation on bubble generation during transformer overload

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

Oommen, T.V.

1992-03-01

This report covers additional work done during 1990 and 1991 on gas bubble generation under overload conditions. To improve visual bubble detection, a single disc coil was used. To further improve detection, a corona device was also used which signaled the onset of corona activity in the early stages of bubble formation. A total of fourteen model tests were conducted, half of which used the Inertaire system, and the remaining, a conservator (COPS). Moisture content of paper in the coil varied from 1.0% to 8.0%; gas (nitrogen) content varied from 1.0% to 8.8%. The results confirmed earlier observations that themore » mathematical bubble prediction model was not valid for high gas content model with relatively low moisture levels in the coil. An empirical relationship was formulated to accurately predict bubble evolution temperatures from known moisture and gas content values. For low moisture content models (below 2%), the simple Piper relationship was sufficient to predict bubble evolution temperatures, regardless of gas content. Moisture in the coil appears to be the key factor in bubble generation. Gas blanketed (Inertaire) systems do not appear to be prone to premature bubble generation from overloads as previously thought. The new bubble prediction model reveals that for a coil with 2% moisture, the bubble evolution temperature would be about 140{degrees}C. Since old transformers in service may have as much as 2% moisture in paper, the 140{degrees}C bubble evolution temperature may be taken as the lower limit of bubble evolution temperature under overload conditions for operating transformers. Drier insulation would raise the bubble evolution temperature.« less

Characterization of pH-sensitive hydrogels by conductimetry and calorimetry

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

Sheppard, N.F. Jr.; Chen, Jey-Hsin; Lawson, H.C.

1993-12-31

The total and freezing water contents, and electrical conductivity of pH-sensitive hydrogels formed from poly(hydroxyethyl methacrylate - co - dimethylaminoethyl methacrylate) were measured as a function of copolymer composition and pH. For an 80/20 HEMA/DMAEMA gel (mole ratio), the water content increases from 37% at pH 10 of the bathing solution value at pH 10 to 90% at low pH. The difference between total and freezing water content in the gels is approximately 25%, consistent with values reported in the literature. An examination of the results in the context of the Yasuda free- volume model suggests that freezing water content,more » rather than total water content, may be suitable for modelling of hydrogel conductivity.« less

An empirical model for the complex dielectric permittivity of soils as a function of water content

NASA Technical Reports Server (NTRS)

Wang, J. R.; Chmugge, T. J.

1978-01-01

The recent measurements on the dielectric properties of soils shows that the variation of dielectric constant with moisture content depends on soil types. The observed dielectric constant increases only slowly with moisture content up to a transition point. Beyond the transition it increases rapidly with moisture content. The moisture value of transition region was found to be higher for high clay content soils than for sandy soils. Many mixing formulas were compared with, and were found incompatible with, the measured dielectric variations of soil-water mixtures. A simple empirical model was proposed to describe the dielectric behavior of ths soil-water mixtures. The relationship between transition moisture and wilting point provides a means of estimating soil dielectric properties on the basis of texture information.

Precipitation extreme changes exceeding moisture content increases in MIROC and IPCC climate models

PubMed Central

Sugiyama, Masahiro; Shiogama, Hideo; Emori, Seita

2010-01-01

Precipitation extreme changes are often assumed to scale with, or are constrained by, the change in atmospheric moisture content. Studies have generally confirmed the scaling based on moisture content for the midlatitudes but identified deviations for the tropics. In fact half of the twelve selected Intergovernmental Panel on Climate Change (IPCC) models exhibit increases faster than the climatological-mean precipitable water change for high percentiles of tropical daily precipitation, albeit with significant intermodel scatter. Decomposition of the precipitation extreme changes reveals that the variations among models can be attributed primarily to the differences in the upward velocity. Both the amplitude and vertical profile of vertical motion are found to affect precipitation extremes. A recently proposed scaling that incorporates these dynamical effects can capture the basic features of precipitation changes in both the tropics and midlatitudes. In particular, the increases in tropical precipitation extremes significantly exceed the precipitable water change in Model for Interdisciplinary Research on Climate (MIROC), a coupled general circulation model with the highest resolution among IPCC climate models whose precipitation characteristics have been shown to reasonably match those of observations. The expected intensification of tropical disturbances points to the possibility of precipitation extreme increases beyond the moisture content increase as is found in MIROC and some of IPCC models. PMID:20080720

Lipid and moisture content modeling of amphidromous Dolly Varden using bioelectrical impedance analysis

USGS Publications Warehouse

Stolarski, J.T.; Margraf, F.J.; Carlson, J.G.; Sutton, T.M.

2014-01-01

The physiological well-being or condition of fish is most commonly estimated from aspects of individual morphology. However, these metrics may be only weakly correlated with nutritional reserves stored as lipid, the primary form of accumulated energy in fish. We constructed and evaluated bioelectrical impedance analysis (BIA) models as an alternative method of assessing condition in amphidromous Dolly Varden Salvelinus malma collected from nearshore estuarine and lotic habitats of the Alaskan Arctic. Data on electrical resistance and reactance were collected from the lateral and ventral surfaces of 192 fish, and whole-body percent lipid and moisture content were determined using standard laboratory methods. Significant inverse relationships between temperature and resistance and reactance prompted the standardization of these data to a constant temperature using corrective equations developed herein. No significant differences in resistance or reactance were detected among spawning and nonspawning females after accounting for covariates, suggesting that electrical pathways do not intersect the gonads. Best-fit BIA models incorporating electrical variables calculated from the lateral and ventral surfaces produced the strongest associations between observed and model-predicted estimates of proximate content. These models explained between 6% and 20% more of the variability in laboratory-derived estimates of proximate content than models developed from single-surface BIA data and 32% more than models containing only length and weight data. While additional research is required to address the potential effects of methodological variation, bioelectrical impedance analysis shows promise as a way to provide high-quality, minimally invasive estimates of Dolly Varden lipid or moisture content in the field with only small increases in handling time.

Assessing the Evaluative Content of Personality Questionnaires Using Bifactor Models.

PubMed

Biderman, Michael D; McAbee, Samuel T; Job Chen, Zhuo; Hendy, Nhung T

2018-01-01

Exploratory bifactor models with keying factors were applied to item response data for the NEO-FFI-3 and HEXACO-PI-R questionnaires. Loadings on a general factor and positive and negative keying factors correlated with independent estimates of item valence, suggesting that item valence influences responses to these questionnaires. Correlations between personality domain scores and measures of self-esteem, depression, and positive and negative affect were all reduced significantly when the influence of evaluative content represented by the general and keying factors was removed. Findings support the need to model personality inventories in ways that capture reactions to evaluative item content.

Magnetic Resonance Imaging of Heart Failure Using a Swine Model

DTIC Science & Technology

2011-03-21

Defense or the Uniformed Services University of the Health Sciences. / Ma een N. Hood, MR, RN, RT (R)(MR), FSMRT Gr duate School of Nursing U iformed...2652710212087 License date Apr 19, 2011 Licensed content publisher Wolters Kluwer Health Licensed content publication Journal of Cardiovascular Nursing ...Licensed content title A Review of Cohort Study Design for Cardiovascular Nursing Research Licensed content author Maureen Hood Licensed content date Jan

The Relationship of Explanatory Flexibility to Explanatory Style

ERIC Educational Resources Information Center

Moore, Michael T.; Fresco, David M.

2007-01-01

Traditional cognitive vulnerability-stress models regarding the etiology of depression emphasize the content of the depressed individual's thoughts. One important cognitive content index, explanatory style, represents the habitual way that individuals assign causes to events that occur in their lives. A more contemporary model, however, emphasizes…

Colorado Model Content Standards: Foreign Language.

ERIC Educational Resources Information Center

Colorado State Dept. of Education, Denver.

The model course content standards for foreign language instruction in Colorado's public schools, K-12, provide guidelines, not curriculum, for school districts to design language programs. An introductory section presents some basic considerations in program design. The two general standards for foreign language performance are that: (1) students…

Extended Relation Metadata for SCORM-Based Learning Content Management Systems

ERIC Educational Resources Information Center

Lu, Eric Jui-Lin; Horng, Gwoboa; Yu, Chia-Ssu; Chou, Ling-Ying

2010-01-01

To increase the interoperability and reusability of learning objects, Advanced Distributed Learning Initiative developed a model called Content Aggregation Model (CAM) to describe learning objects and express relationships between learning objects. However, the suggested relations defined in the CAM can only describe structure-oriented…

A Thermal Analysis of a Hot-Wire Probe for Icing Applications

NASA Technical Reports Server (NTRS)

Struk, Peter M.; Rigby, David L.; Venkataraman, Krishna

2014-01-01

This paper presents a steady-state thermal model of a hot-wire instrument applicable to atmospheric measurement of water content in clouds. In this application, the power required to maintain the wire at a given temperature is used to deduce the water content of the cloud. The model considers electrical resistive heating, axial conduction, convection to the flow, radiation to the surroundings, as well as energy loss due to the heating, melting, and evaporation of impinging liquid and or ice. All of these parameters can be varied axially along the wire. The model further introduces a parameter called the evaporation potential which locally gauges the maximum fraction of incoming water that evaporates. The primary outputs of the model are the steady-state power required to maintain a spatially-average constant temperature as well as the variation of that temperature and other parameters along the wire. The model is used to understand the sensitivity of the hot-wire performance to various flow and boundary conditions including a detailed comparison of dry air and wet (i.e. cloud-on) conditions. The steady-state power values are compared to experimental results from a Science Engineering Associates (SEA) Multi-Element probe, a commonly used water-content measurement instrument. The model results show good agreement with experiment for both dry and cloud-on conditions with liquid water content. For ice, the experimental measurements under read the actual water content due to incomplete evaporation and splashing. Model results, which account for incomplete evaporation, are still higher than experimental results where the discrepancy is attributed to splashing mass-loss which is not accounted in the model.

Biological Model Development as an Opportunity to Provide Content Auditing for the Foundational Model of Anatomy Ontology.

PubMed

Wang, Lucy L; Grunblatt, Eli; Jung, Hyunggu; Kalet, Ira J; Whipple, Mark E

2015-01-01

Constructing a biological model using an established ontology provides a unique opportunity to perform content auditing on the ontology. We built a Markov chain model to study tumor metastasis in the regional lymphatics of patients with head and neck squamous cell carcinoma (HNSCC). The model attempts to determine regions with high likelihood for metastasis, which guides surgeons and radiation oncologists in selecting the boundaries of treatment. To achieve consistent anatomical relationships, the nodes in our model are populated using lymphatic objects extracted from the Foundational Model of Anatomy (FMA) ontology. During this process, we discovered several classes of inconsistencies in the lymphatic representations within the FMA. We were able to use this model building opportunity to audit the entities and connections in this region of interest (ROI). We found five subclasses of errors that are computationally detectable and resolvable, one subclass of errors that is computationally detectable but unresolvable, requiring the assistance of a content expert, and also errors of content, which cannot be detected through computational means. Mathematical descriptions of detectable errors along with expert review were used to discover inconsistencies and suggest concepts for addition and removal. Out of 106 organ and organ parts in the ROI, 8 unique entities were affected, leading to the suggestion of 30 concepts for addition and 4 for removal. Out of 27 lymphatic chain instances, 23 were found to have errors, with a total of 32 concepts suggested for addition and 15 concepts for removal. These content corrections are necessary for the accurate functioning of the FMA and provide benefits for future research and educational uses.

Biological Model Development as an Opportunity to Provide Content Auditing for the Foundational Model of Anatomy Ontology

PubMed Central

Wang, Lucy L.; Grunblatt, Eli; Jung, Hyunggu; Kalet, Ira J.; Whipple, Mark E.

2015-01-01

Constructing a biological model using an established ontology provides a unique opportunity to perform content auditing on the ontology. We built a Markov chain model to study tumor metastasis in the regional lymphatics of patients with head and neck squamous cell carcinoma (HNSCC). The model attempts to determine regions with high likelihood for metastasis, which guides surgeons and radiation oncologists in selecting the boundaries of treatment. To achieve consistent anatomical relationships, the nodes in our model are populated using lymphatic objects extracted from the Foundational Model of Anatomy (FMA) ontology. During this process, we discovered several classes of inconsistencies in the lymphatic representations within the FMA. We were able to use this model building opportunity to audit the entities and connections in this region of interest (ROI). We found five subclasses of errors that are computationally detectable and resolvable, one subclass of errors that is computationally detectable but unresolvable, requiring the assistance of a content expert, and also errors of content, which cannot be detected through computational means. Mathematical descriptions of detectable errors along with expert review were used to discover inconsistencies and suggest concepts for addition and removal. Out of 106 organ and organ parts in the ROI, 8 unique entities were affected, leading to the suggestion of 30 concepts for addition and 4 for removal. Out of 27 lymphatic chain instances, 23 were found to have errors, with a total of 32 concepts suggested for addition and 15 concepts for removal. These content corrections are necessary for the accurate functioning of the FMA and provide benefits for future research and educational uses. PMID:26958311

Application of near-infrared spectroscopy for estimation of non-structural carbohydrates in foliar samples of Eucalyptus globulus Labilladière.

PubMed

Quentin, A G; Rodemann, T; Doutreleau, M-F; Moreau, M; Davies, N W; Millard, Peter

2017-01-31

Near-infrared reflectance spectroscopy (NIRS) is frequently used for the assessment of key nutrients of forage or crops but remains underused in ecological and physiological studies, especially to quantify non-structural carbohydrates. The aim of this study was to develop calibration models to assess the content in soluble sugars (fructose, glucose, sucrose) and starch in foliar material of Eucalyptus globulus. A partial least squares (PLS) regression was used on the sample spectral data and was compared to the contents measured using standard wet chemistry methods. The calibration models were validated using a completely independent set of samples. We used key indicators such as the ratio of prediction to deviation (RPD) and the range error ratio to give an assessment of the performance of the calibration models. Accurate calibration models were obtained for fructose and sucrose content (R2 > 0.85, root mean square error of prediction (RMSEP) of 0.95%–1.26% in the validation models), followed by sucrose and total soluble sugar content (R2 ~ 0.70 and RMSEP > 2.3%). In comparison to the others, calibration of the starch model performed very poorly with RPD = 1.70. This study establishes the ability of the NIRS calibration model to infer soluble sugar content in foliar samples of E. globulus in a rapid and cost-effective way. We suggest a complete redevelopment of the starch analysis using more specific quantification such as an HPLC-based technique to reach higher performance in the starch model. Overall, NIRS could serve as a high-throughput phenotyping tool to study plant response to stress factors.

A comparison of operational and LANDSAT-aided snow water content estimation systems. [Feather River Basin, California

NASA Technical Reports Server (NTRS)

Sharp, J. M.; Thomas, R. W.

1975-01-01

How LANDSAT imagery can be cost effectively employed to augment an operational hydrologic model is described. Attention is directed toward the estimation of snow water content, a major predictor variable in the volumetric runoff forecasting model. A stratified double sampling scheme is supplemented with qualitative and quantitative analyses of existing operations to develop a comparison between the existing and satellite-aided approaches to snow water content estimation. Results show a decided advantage for the LANDSAT-aided approach.

Designing an Online Course Content Structure Using a Design Patterns Approach

ERIC Educational Resources Information Center

Hathaway, Dawn; Norton, Priscilla

2013-01-01

Despite the central role that well organized and structured course content plays in engaging online learners with content, the authors point to the absence of guidelines for organizing content in ways that meet course learning goals. Recognizing the need for a design solution and, perhaps, the need for a new design model, "design…

The Diagonal Model of Job Satisfaction and Motivation: Extracted from the Logical Comparison of Content and Process Theories

ERIC Educational Resources Information Center

Sahito, Zafarullah; Vaisanen, Pertti

2017-01-01

The purpose of this study is to explore the strongest areas of all prime theories of job satisfaction and motivation to create a new multidimensional model. This model relies on all explored areas from the logical comparison of content and process theories to understand the phenomenon of job satisfaction and motivation of employees. The model…

Ensemble kalman filtering to perform data assimilation with soil water content probes and pedotransfer functions in modeling water flow in variably saturated soils

USDA-ARS?s Scientific Manuscript database

Data from modern soil water contents probes can be used for data assimilation in soil water flow modeling, i.e. continual correction of the flow model performance based on observations. The ensemble Kalman filter appears to be an appropriate method for that. The method requires estimates of the unce...

Predicting Young’s Modulus of Glass/Ceramic Sealant for Solid Oxide Fuel Cell Considering the Combined Effects of Aging, Micro-Voids and Self-Healing

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

Liu, Wenning N.; Sun, Xin; Khaleel, Mohammad A.

We study the temperature dependent Young’s modulus for the glass/ceramic seal material used in Solid Oxide Fuel Cells (SOFCs). With longer heat treatment or aging time during operation, further devitrification may reduce the residual glass content in the seal material while boosting the ceramic crystalline content. In the meantime, micro-voids induced by the cooling process from the high operating temperature to room temperature can potentially degrade the mechanical properties of the glass/ceramic sealant. Upon reheating to the SOFC operating temperature, possible self-healing phenomenon may occur in the glass/ceramic sealant which can potentially restore some of its mechanical properties. A phenomenologicalmore » model is developed to model the temperature dependent Young’s modulus of glass/ceramic seal considering the combined effects of aging, micro-voids, and possible self-healing. An aging-time-dependent crystalline content model is first developed to describe the increase of the crystalline content due to the continuing devitrification under high operating temperature. A continuum damage mechanics (CDM) model is then adapted to model the effects of both cooling induced micro-voids and reheating induced self-healing. This model is applied to model the glass-ceramic G18, a candidate SOFC seal material previously developed at PNNL. Experimentally determined temperature dependent Young’s modulus is used to validate the model predictions« less

Modeling preferential water flow and solute transport in unsaturated soil using the active region model

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

Sheng, F.; Wang, K.; Zhang, R.

2009-03-15

Preferential flow and solute transport are common processes in the unsaturated soil, in which distributions of soil water content and solute concentrations are often characterized as fractal patterns. An active region model (ARM) was recently proposed to describe the preferential flow and transport patterns. In this study, ARM governing equations were derived to model the preferential soil water flow and solute transport processes. To evaluate the ARM equations, dye infiltration experiments were conducted, in which distributions of soil water content and Cl{sup -} concentration were measured. Predicted results using the ARM and the mobile-immobile region model (MIM) were compared withmore » the measured distributions of soil water content and Cl{sup -} concentration. Although both the ARM and the MIM are two-region models, they are fundamental different in terms of treatments of the flow region. The models were evaluated based on the modeling efficiency (ME). The MIM provided relatively poor prediction results of the preferential flow and transport with negative ME values or positive ME values less than 0.4. On the contrary, predicted distributions of soil water content and Cl- concentration using the ARM agreed reasonably well with the experimental data with ME values higher than 0.8. The results indicated that the ARM successfully captured the macroscopic behavior of preferential flow and solute transport in the unsaturated soil.« less

[Research on Oil Sands Spectral Characteristics and Oil Content by Remote Sensing Estimation].

PubMed

You, Jin-feng; Xing, Li-xin; Pan, Jun; Shan, Xuan-long; Liang, Li-heng; Fan, Rui-xue

2015-04-01

Visible and near infrared spectroscopy is a proven technology to be widely used in identification and exploration of hydrocarbon energy sources with high spectral resolution for detail diagnostic absorption characteristics of hydrocarbon groups. The most prominent regions for hydrocarbon absorption bands are 1,740-1,780, 2,300-2,340 and 2,340-2,360 nm by the reflectance of oil sands samples. These spectral ranges are dominated by various C-H overlapping overtones and combination bands. Meanwhile, there is relatively weak even or no absorption characteristics in the region from 1,700 to 1,730 nm in the spectra of oil sands samples with low bitumen content. With the increase in oil content, in the spectral range of 1,700-1,730 nm the obvious hydrocarbon absorption begins to appear. The bitumen content is the critical parameter for oil sands reserves estimation. The absorption depth was used to depict the response intensity of the absorption bands controlled by first-order overtones and combinations of the various C-H stretching and bending fundamentals. According to the Pearson and partial correlation relationships of oil content and absorption depth dominated by hydrocarbon groups in 1,740-1,780, 2,300-2,340 and 2,340-2,360 nm wavelength range, the scheme of association mode was established between the intensity of spectral response and bitumen content, and then unary linear regression(ULR) and partial least squares regression (PLSR) methods were employed to model the equation between absorption depth attributed to various C-H bond and bitumen content. There were two calibration equations in which ULR method was employed to model the relationship between absorption depth near 2,350 nm region and bitumen content and PLSR method was developed to model the relationship between absorption depth of 1,758, 2,310, 2,350 nm regions and oil content. It turned out that the calibration models had good predictive ability and high robustness and they could provide the scientific basis for rapid estimation of oil content in oil sands in future.

Determination of total flavonoids content in fresh Ginkgo biloba leaf with different colors using near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Shi, Ji-yong; Zou, Xiao-bo; Zhao, Jie-wen; Mel, Holmes; Wang, Kai-liang; Wang, Xue; Chen, Hong

Total flavonoids content is often considered an important quality index of Ginkgo biloba leaf. The feasibility of using near infrared (NIR) spectra at the wavelength range of 10,000-4000 cm-1 for rapid and nondestructive determination of total flavonoids content in G. biloba leaf was investigated. 120 fresh G. biloba leaves in different colors (green, green-yellowish and yellow) were used to spectra acquisition and total flavonoids determination. Partial least squares (PLS), interval partial least squares (iPLS) and synergy interval partial least squares (SiPLS) were used to develop calibration models for total flavonoids content in two colors leaves (green-yellowish and yellow) and three colors leaves (green, green-yellowish and yellow), respectively. The level of total flavonoids content for green, green-yellowish and yellow leaves was in an increasing order. Two characteristic wavelength regions (5840-6090 cm-1 and 6620-6880 cm-1), which corresponded to the absorptions of two aromatic rings in basic flavonoid structure, were selected by SiPLS. The optimal SiPLS model for total flavonoids content in the two colors leaves (r2 = 0.82, RMSEP = 2.62 mg g-1) had better performance than PLS and iPLS models. It could be concluded that NIR spectroscopy has significant potential in the nondestructive determination of total flavonoids content in fresh G. biloba leaf.

Spectral Estimation Model Construction of Heavy Metals in Mining Reclamation Areas

PubMed Central

Dong, Jihong; Dai, Wenting; Xu, Jiren; Li, Songnian

2016-01-01

The study reported here examined, as the research subject, surface soils in the Liuxin mining area of Xuzhou, and explored the heavy metal content and spectral data by establishing quantitative models with Multivariable Linear Regression (MLR), Generalized Regression Neural Network (GRNN) and Sequential Minimal Optimization for Support Vector Machine (SMO-SVM) methods. The study results are as follows: (1) the estimations of the spectral inversion models established based on MLR, GRNN and SMO-SVM are satisfactory, and the MLR model provides the worst estimation, with R2 of more than 0.46. This result suggests that the stress sensitive bands of heavy metal pollution contain enough effective spectral information; (2) the GRNN model can simulate the data from small samples more effectively than the MLR model, and the R2 between the contents of the five heavy metals estimated by the GRNN model and the measured values are approximately 0.7; (3) the stability and accuracy of the spectral estimation using the SMO-SVM model are obviously better than that of the GRNN and MLR models. Among all five types of heavy metals, the estimation for cadmium (Cd) is the best when using the SMO-SVM model, and its R2 value reaches 0.8628; (4) using the optimal model to invert the Cd content in wheat that are planted on mine reclamation soil, the R2 and RMSE between the measured and the estimated values are 0.6683 and 0.0489, respectively. This result suggests that the method using the SMO-SVM model to estimate the contents of heavy metals in wheat samples is feasible. PMID:27367708

Spectral Estimation Model Construction of Heavy Metals in Mining Reclamation Areas.

PubMed

Dong, Jihong; Dai, Wenting; Xu, Jiren; Li, Songnian

2016-06-28

The study reported here examined, as the research subject, surface soils in the Liuxin mining area of Xuzhou, and explored the heavy metal content and spectral data by establishing quantitative models with Multivariable Linear Regression (MLR), Generalized Regression Neural Network (GRNN) and Sequential Minimal Optimization for Support Vector Machine (SMO-SVM) methods. The study results are as follows: (1) the estimations of the spectral inversion models established based on MLR, GRNN and SMO-SVM are satisfactory, and the MLR model provides the worst estimation, with R² of more than 0.46. This result suggests that the stress sensitive bands of heavy metal pollution contain enough effective spectral information; (2) the GRNN model can simulate the data from small samples more effectively than the MLR model, and the R² between the contents of the five heavy metals estimated by the GRNN model and the measured values are approximately 0.7; (3) the stability and accuracy of the spectral estimation using the SMO-SVM model are obviously better than that of the GRNN and MLR models. Among all five types of heavy metals, the estimation for cadmium (Cd) is the best when using the SMO-SVM model, and its R² value reaches 0.8628; (4) using the optimal model to invert the Cd content in wheat that are planted on mine reclamation soil, the R² and RMSE between the measured and the estimated values are 0.6683 and 0.0489, respectively. This result suggests that the method using the SMO-SVM model to estimate the contents of heavy metals in wheat samples is feasible.

Towards a Social Networks Model for Online Learning & Performance

ERIC Educational Resources Information Center

Chung, Kon Shing Kenneth; Paredes, Walter Christian

2015-01-01

In this study, we develop a theoretical model to investigate the association between social network properties, "content richness" (CR) in academic learning discourse, and performance. CR is the extent to which one contributes content that is meaningful, insightful and constructive to aid learning and by social network properties we…

Social and Collaborative Interactions for Educational Content Enrichment in ULEs

ERIC Educational Resources Information Center

Araújo, Rafael D.; Brant-Ribeiro, Taffarel; Mendonça, Igor E. S.; Mendes, Miller M.; Dorça, Fabiano A.; Cattelan, Renan G.

2017-01-01

This article presents a social and collaborative model for content enrichment in Ubiquitous Learning Environments. Designed as a loosely coupled software architecture, the proposed model was implemented and integrated into the Classroom eXperience, a multimedia capture platform for educational environments. After automatically recording a lecture…

Modeling Educational Content: The Cognitive Approach of the PALO Language

ERIC Educational Resources Information Center

Rodriguez-Artacho, Miguel; Verdejo Maillo, M. Felisa

2004-01-01

This paper presents a reference framework to describe educational material. It introduces the PALO Language as a cognitive based approach to Educational Modeling Languages (EML). In accordance with recent trends for reusability and interoperability in Learning Technologies, EML constitutes an evolution of the current content-centered…

National Centers for Environmental Prediction

Science.gov Websites

Reference List Table of Contents NCEP OPERATIONAL MODEL FORECAST GRAPHICS PARALLEL/EXPERIMENTAL MODEL Developmental Air Quality Forecasts and Verification Back to Table of Contents 2. PARALLEL/EXPERIMENTAL GRAPHICS VERIFICATION (GRID VS.OBS) WEB PAGE (NCEP EXPERIMENTAL PAGE, INTERNAL USE ONLY) Interactive web page tool for

A complex permittivity model for field estimation of soil water contents using time domain reflectometry

USDA-ARS?s Scientific Manuscript database

Accurate electromagnetic sensing of soil water contents (') under field conditions is complicated by the dependence of permittivity on specific surface area, temperature, and apparent electrical conductivity, all which may vary across space or time. We present a physically-based mixing model to pred...

Teacher Application and Enactment of Models of Teaching

ERIC Educational Resources Information Center

Allphin, Danielle M.

2011-01-01

This study sought to identify factors that influence teacher decisions about pedagogy based on curriculum content and skills and the degree to which teachers transfer pedagogical content knowledge to practice, specifically through the use of various models of teaching. A purposeful sample included 14 elementary teachers from highly diverse, urban…

Variations of total electron content during geomagnetic disturbances: A model/observation comparison

NASA Technical Reports Server (NTRS)

Roble, G. Lu X. Pi A. D. Richmond R. G.

1997-01-01

This paper studies the ionospheric response to major geomagnetic storm of October 18-19, 1995, using the thermosphere-ionosphere electrodynamic general circulation model (TIE-GCM) simulations and the global ionospheric maps (GIM) of total electron content (TEC) observations from the Global Positioning System (GPS) worldwide network.

Learning to Teach: Pedagogical Content Knowledge in Adventure-Based Learning

ERIC Educational Resources Information Center

Sutherland, Sue; Stuhr, Paul T.; Ayvazo, Shiri

2016-01-01

Background: Many alternative curricular models exist in physical education to better meet the needs of students than the multi-activity team sports curriculum that dominates in the USA. These alternative curricular models typically require different content knowledge (CK) and pedagogical CK (PCK) to implement successfully. One of the complexities…

Pedagogical Content Knowledge in Mathematical Modelling Instruction

ERIC Educational Resources Information Center

Tan, Liang Soon; Ang, Keng Cheng

2012-01-01

This paper posits that teachers' pedagogical content knowledge in mathematical modelling instruction can be demonstrated in the crafting of action plans and expected teaching and learning moves via their lesson images (Schoenfeld, 1998). It can also be developed when teachers shape appropriate teaching moves in response to students' learning…

Near Infrared Spectroscopy for On-line Monitoring of Alkali- Free Cloth/Phenolic Resin Prepreg During Manufacture

PubMed Central

Jiang, Bo; Huang, Yu Dong

2007-01-01

A NIR method was developed for the on-line monitoring of alkali-free cloth/phenolic resin prepreg during its manufacturing process. First, the sizing content of the alkali-free cloth was analyzed, and then the resin, soluble resin and volatiles content of the prepreg was analyzed simultaneously using the FT-NIR spectrometer. Partial least square (PLS) regression was used to develop the calibration models, which for the sizing content was preprocessed by 1stDER +MSC, for the volatile content by 1stDER +VN, for the soluble resin content by 1stDER +MSC and for the resin content by the VN spectral data preprocessing method. RMSEP of the prediction model for the sizing content was 0.732 %, for the resin content it was 0.605, for the soluble resin content it was 0.101 and for volatiles content it was 0.127. The results of the paired t-test revealed that there was no significant difference between the NIR method and the standard method. The NIR spectroscopy method could be used to predict the resin, soluble resin and the volatiles content of the prepreg simultaneously, as well as sizing content of alkali-free cloth. The processing parameters of the prepreg during manufacture could be adjusted quickly with the help of the NIR analysis results. The results indicated that the NIR spectroscopy method was sufficiently accurate and effective for the on-line monitoring of alkali-free cloth/phenolic resin prepreg.

Extracting the Evaluations of Stereotypes: Bi-factor Model of the Stereotype Content Structure

PubMed Central

Sayans-Jiménez, Pablo; Cuadrado, Isabel; Rojas, Antonio J.; Barrada, Juan R.

2017-01-01

Stereotype dimensions—competence, morality and sociability—are fundamental to studying the perception of other groups. These dimensions have shown moderate/high positive correlations with each other that do not reflect the theoretical expectations. The explanation for this (e.g., halo effect) undervalues the utility of the shared variance identified. In contrast, in this work we propose that this common variance could represent the global evaluation of the perceived group. Bi-factor models are proposed to improve the internal structure and to take advantage of the information representing the shared variance among dimensions. Bi-factor models were compared with first order models and other alternative models in three large samples (300–309 participants). The relationships among the global and specific bi-factor dimensions with a global evaluation dimension (measured through a semantic differential) were estimated. The results support the use of bi-factor models rather than first order models (and other alternative models). Bi-factor models also show a greater utility to directly and more easily explore the stereotype content including its evaluative content. PMID:29085313

Rule-based interface generation on mobile devices for structured documentation.

PubMed

Kock, Ann-Kristin; Andersen, Björn; Handels, Heinz; Ingenerf, Josef

2014-01-01

In many software systems to date, interactive graphical user interfaces (GUIs) are represented implicitly in the source code, together with the application logic. Hence, the re-use, development, and modification of these interfaces is often very laborious. Flexible adjustments of GUIs for various platforms and devices as well as individual user preferences are furthermore difficult to realize. These problems motivate a software-based separation of content and GUI models on the one hand, and application logic on the other. In this project, a software solution for structured reporting on mobile devices is developed. Clinical content archetypes developed in a previous project serve as the content model while the Android SDK provides the GUI model. The necessary bindings between the models are specified using the Jess Rule Language.

Cognitive search model and a new query paradigm

NASA Astrophysics Data System (ADS)

Xu, Zhonghui

2001-06-01

This paper proposes a cognitive model in which people begin to search pictures by using semantic content and find a right picture by judging whether its visual content is a proper visualization of the semantics desired. It is essential that human search is not just a process of matching computation on visual feature but rather a process of visualization of the semantic content known. For people to search electronic images in the way as they manually do in the model, we suggest that querying be a semantic-driven process like design. A query-by-design paradigm is prosed in the sense that what you design is what you find. Unlike query-by-example, query-by-design allows users to specify the semantic content through an iterative and incremental interaction process so that a retrieval can start with association and identification of the given semantic content and get refined while further visual cues are available. An experimental image retrieval system, Kuafu, has been under development using the query-by-design paradigm and an iconic language is adopted.

Determination of fat and total protein content in milk using conventional digital imaging.

PubMed

Kucheryavskiy, Sergey; Melenteva, Anastasiia; Bogomolov, Andrey

2014-04-01

The applicability of conventional digital imaging to quantitative determination of fat and total protein in cow's milk, based on the phenomenon of light scatter, has been proved. A new algorithm for extracting features from digital images of milk samples has been developed. The algorithm takes into account spatial distribution of light, diffusely transmitted through a sample. The proposed method has been tested on two sample sets prepared from industrial raw milk standards, with variable fat and protein content. Partial Least-Squares (PLS) regression on the features calculated from images of monochromatically illuminated milk samples resulted in models with high prediction performance when analysed the sets separately (best models with cross-validated R(2)=0.974 for protein and R(2)=0.973 for fat content). However when analysed the sets jointly with the obtained results were significantly worse (best models with cross-validated R(2)=0.890 for fat content and R(2)=0.720 for protein content). The results have been compared with previously published Vis/SW-NIR spectroscopic study of similar samples. Copyright © 2013 Elsevier B.V. All rights reserved.

Tools for studying dry-cured ham processing by using computed tomography.

PubMed

Santos-Garcés, Eva; Muñoz, Israel; Gou, Pere; Sala, Xavier; Fulladosa, Elena

2012-01-11

An accurate knowledge and optimization of dry-cured ham elaboration processes could help to reduce operating costs and maximize product quality. The development of nondestructive tools to characterize chemical parameters such as salt and water contents and a(w) during processing is of special interest. In this paper, predictive models for salt content (R(2) = 0.960 and RMSECV = 0.393), water content (R(2) = 0.912 and RMSECV = 1.751), and a(w) (R(2) = 0.906 and RMSECV = 0.008), which comprise the whole elaboration process, were developed. These predictive models were used to develop analytical tools such as distribution diagrams, line profiles, and regions of interest (ROIs) from the acquired computed tomography (CT) scans. These CT analytical tools provided quantitative information on salt, water, and a(w) in terms of content but also distribution throughout the process. The information obtained was applied to two industrial case studies. The main drawback of the predictive models and CT analytical tools is the disturbance that fat produces in water content and a(w) predictions.

High-throughput prediction of tablet weight and trimethoprim content of compound sulfamethoxazole tablets for controlling the uniformity of dosage units by NIR.

PubMed

Dong, Yanhong; Li, Juan; Zhong, Xiaoxiao; Cao, Liya; Luo, Yang; Fan, Qi

2016-04-15

This paper establishes a novel method to simultaneously predict the tablet weight (TW) and trimethoprim (TMP) content of compound sulfamethoxazole tablets (SMZCO) by near infrared (NIR) spectroscopy with partial least squares (PLS) regression for controlling the uniformity of dosage units (UODU). The NIR spectra for 257 samples were measured using the optimized parameter values and pretreated using the optimized chemometric techniques. After the outliers were ignored, two PLS models for predicting TW and TMP content were respectively established by using the selected spectral sub-ranges and the reference values. The TW model reaches the correlation coefficient of calibration (R(c)) 0.9543 and the TMP content model has the R(c) 0.9205. The experimental results indicate that this strategy expands the NIR application in controlling UODU, especially in the high-throughput and rapid analysis of TWs and contents of the compound pharmaceutical tablets, and may be an important complement to the common NIR on-line analytical method for pharmaceutical tablets. Copyright © 2016 Elsevier B.V. All rights reserved.

Semantic Factors Predict the Rate of Lexical Replacement of Content Words

PubMed Central

Vejdemo, Susanne; Hörberg, Thomas

2016-01-01

The rate of lexical replacement estimates the diachronic stability of word forms on the basis of how frequently a proto-language word is replaced or retained in its daughter languages. Lexical replacement rate has been shown to be highly related to word class and word frequency. In this paper, we argue that content words and function words behave differently with respect to lexical replacement rate, and we show that semantic factors predict the lexical replacement rate of content words. For the 167 content items in the Swadesh list, data was gathered on the features of lexical replacement rate, word class, frequency, age of acquisition, synonyms, arousal, imageability and average mutual information, either from published databases or gathered from corpora and lexica. A linear regression model shows that, in addition to frequency, synonyms, senses and imageability are significantly related to the lexical replacement rate of content words–in particular the number of synonyms that a word has. The model shows no differences in lexical replacement rate between word classes, and outperforms a model with word class and word frequency predictors only. PMID:26820737

Accuracy increase of the coordinate measurement based on the model production of geometrical parts specifications

NASA Astrophysics Data System (ADS)

Zlatkina, O. Yu

2018-04-01

There is a relationship between the service properties of component parts and their geometry; therefore, to predict and control the operational characteristics of parts and machines, it is necessary to measure their geometrical specifications. In modern production, a coordinate measuring machine is the advanced measuring instrument of the products geometrical specifications. The analysis of publications has shown that during the coordinate measurements the problems of choosing locating chart of parts and coordination have not been sufficiently studied. A special role in the coordination of the part is played by the coordinate axes informational content. Informational content is the sum of the degrees of freedom limited by the elementary item of a part. The coordinate planes of a rectangular coordinate system have different informational content (three, two, and one). The coordinate axes have informational content of four, two and zero. The higher the informational content of the coordinate plane or axis, the higher its priority for reading angular and linear coordinates is. The geometrical model production of the coordinate measurements object taking into account the information content of coordinate planes and coordinate axes allows us to clearly reveal the interrelationship of the coordinates of the deviations in location, sizes and deviations of their surfaces shape. The geometrical model helps to select the optimal locating chart of parts for bringing the machine coordinate system to the part coordinate system. The article presents an algorithm the model production of geometrical specifications using the example of the piston rod of a compressor.

Dustfall Effect on Hyperspectral Inversion of Chlorophyll Content - a Laboratory Experiment

NASA Astrophysics Data System (ADS)

Chen, Yuteng; Ma, Baodong; Li, Xuexin; Zhang, Song; Wu, Lixin

2018-04-01

Dust pollution is serious in many areas of China. It is of great significance to estimate chlorophyll content of vegetation accurately by hyperspectral remote sensing for assessing the vegetation growth status and monitoring the ecological environment in dusty areas. By using selected vegetation indices including Medium Resolution Imaging Spectrometer Terrestrial Chlorophyll Index (MTCI) Double Difference Index (DD) and Red Edge Position Index (REP), chlorophyll inversion models were built to study the accuracy of hyperspectral inversion of chlorophyll content based on a laboratory experiment. The results show that: (1) REP exponential model has the most stable accuracy for inversion of chlorophyll content in dusty environment. When dustfall amount is less than 80 g/m2, the inversion accuracy based on REP is stable with the variation of dustfall amount. When dustfall amount is greater than 80 g/m2, the inversion accuracy is slightly fluctuation. (2) Inversion accuracy of DD is worst among three models. (3) MTCI logarithm model has high inversion accuracy when dustfall amount is less than 80 g/m2; When dustfall amount is greater than 80 g/m2, inversion accuracy decreases regularly and inversion accuracy of modified MTCI (mMTCI) increases significantly. The results provide experimental basis and theoretical reference for hyperspectral remote sensing inversion of chlorophyll content.

Soil sail content estimation in the yellow river delta with satellite hyperspectral data

USGS Publications Warehouse

Weng, Yongling; Gong, Peng; Zhu, Zhi-Liang

2008-01-01

Soil salinization is one of the most common land degradation processes and is a severe environmental hazard. The primary objective of this study is to investigate the potential of predicting salt content in soils with hyperspectral data acquired with EO-1 Hyperion. Both partial least-squares regression (PLSR) and conventional multiple linear regression (MLR), such as stepwise regression (SWR), were tested as the prediction model. PLSR is commonly used to overcome the problem caused by high-dimensional and correlated predictors. Chemical analysis of 95 samples collected from the top layer of soils in the Yellow River delta area shows that salt content was high on average, and the dominant chemicals in the saline soil were NaCl and MgCl2. Multivariate models were established between soil contents and hyperspectral data. Our results indicate that the PLSR technique with laboratory spectral data has a strong prediction capacity. Spectral bands at 1487-1527, 1971-1991, 2032-2092, and 2163-2355 nm possessed large absolute values of regression coefficients, with the largest coefficient at 2203 nm. We obtained a root mean squared error (RMSE) for calibration (with 61 samples) of RMSEC = 0.753 (R2 = 0.893) and a root mean squared error for validation (with 30 samples) of RMSEV = 0.574. The prediction model was applied on a pixel-by-pixel basis to a Hyperion reflectance image to yield a quantitative surface distribution map of soil salt content. The result was validated successfully from 38 sampling points. We obtained an RMSE estimate of 1.037 (R2 = 0.784) for the soil salt content map derived by the PLSR model. The salinity map derived from the SWR model shows that the predicted value is higher than the true value. These results demonstrate that the PLSR method is a more suitable technique than stepwise regression for quantitative estimation of soil salt content in a large area. ?? 2008 CASI.

Application of a new model for groundwater age distributions: Modeling and isotopic analysis of artificial recharge in the Rialto-Colton basin, California

USGS Publications Warehouse

Ginn, T.R.; Woolfenden, L.

2002-01-01

A project for modeling and isotopic analysis of artificial recharge in the Rialto-Colton basin aquifer in California, is discussed. The Rialto-Colton aquifer has been divided into four primary and significant flowpaths following the general direction of groundwater flow from NW to SE. The introductory investigation include sophisticated chemical reaction modeling, with highly simplified flow path simulation. A comprehensive reactive transport model with the established set of geochemical reactions over the whole aquifer will also be developed for treating both reactions and transport realistically. This will be completed by making use of HBGC123D implemented with isotopic calculation step to compute Carbon-14 (C14) and stable Carbon-13 (C13) contents of the water. Computed carbon contents will also be calibrated with the measured carbon contents for assessment of the amount of imported recharge into the Linden pond.

Effect of fuel nitrogen and hydrogen content on emissions in hydrocarbon combustion

NASA Technical Reports Server (NTRS)

Bittker, D. A.; Wolfbrandt, G.

1981-01-01

How the emissions of nitrogen oxides and carbon monoxide are affected by: (1) the decreased hydrogen content and (2) the increased organic nitrogen content of coal derived fuels is investigated. Previous CRT experimental work in a two stage flame tube has shown the effectiveness of rich lean two stage combustion in reducing fuel nitrogen conversion to nitrogen oxides. Previous theoretical work gave preliminary indications that emissions trends from the flame tube experiment could be predicted by a two stage, well stirred reactor combustor model using a detailed chemical mechanism for propane oxidation and nitrogen oxide formation. Additional computations are reported and comparisons with experimental results for two additional fuels and a wide range of operating conditions are given. Fuels used in the modeling are pure propane, a propane toluene mixture and pure toluene. These give hydrogen contents 18, 11 and 9 percent by weight, respectively. Fuel bound nitrogen contents of 0.5 and 1.0 percent were used. Results are presented for oxides of nitrogen and also carbon monoxide concentrations as a function of primary equivalence ratio, hydrogen content and fuel bound nitrogen content.

Evaluation of the influence of white grape seed extracts as copigment sources on the anthocyanin extraction from grape skins previously classified by near infrared hyperspectral tools.

PubMed

Nogales-Bueno, Julio; Baca-Bocanegra, Berta; Jara-Palacios, María José; Hernández-Hierro, José Miguel; Heredia, Francisco José

2017-04-15

Hyperspectral imaging has been used to classify red grapes (Vitis vinifera L.) according to their predicted extractable total anthocyanin content (i.e. extractable total anthocyanin content determined by a hyperspectral method). Low, medium and high levels of predicted extractable total anthocyanin content were established. Then, grape skins were split into three parts and each part was macerated into a different model wine solution for a three-day period. Wine model solutions were made up with different concentration of copigments coming from white grape seeds. Aqueous supernatants were analyzed by HPLC-DAD and extractable anthocyanin contents were obtained. Principal component analyses and analyses of variance were carried out with the aim of studying trends related to the extractable anthocyanin contents. Significant differences were found among grapes with different levels of predicted extractable anthocyanin contents. Moreover, no significant differences were found on the extractable anthocyanin contents using different copigment concentrations in grape skin macerations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Genetic Analysis of Reduced γ-Tocopherol Content in Ethiopian Mustard Seeds.

PubMed

García-Navarro, Elena; Fernández-Martínez, José M; Pérez-Vich, Begoña; Velasco, Leonardo

2016-01-01

Ethiopian mustard (Brassica carinata A. Braun) line BCT-6, with reduced γ-tocopherol content in the seeds, has been previously developed. The objective of this research was to conduct a genetic analysis of seed tocopherols in this line. BCT-6 was crossed with the conventional line C-101 and the F1, F2, and BC plant generations were analyzed. Generation mean analysis using individual scaling tests indicated that reduced γ-tocopherol content fitted an additive-dominant genetic model with predominance of additive effects and absence of epistatic interactions. This was confirmed through a joint scaling test and additional testing of the goodness of fit of the model. Conversely, epistatic interactions were identified for total tocopherol content. Estimation of the minimum number of genes suggested that both γ- and total tocopherol content may be controlled by two genes. A positive correlation between total tocopherol content and the proportion of γ-tocopherol was identified in the F2 generation. Additional research on the feasibility of developing germplasm with high tocopherol content and reduced concentration of γ-tocopherol is required.

Bubble generation during transformer overload

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

Oommen, T.V.

1990-03-01

Bubble generation in transformers has been demonstrated under certain overload conditions. The release of large quantities of bubbles would pose a dielectric breakdown hazard. A bubble prediction model developed under EPRI Project 1289-4 attempts to predict the bubble evolution temperature under different overload conditions. This report details a verification study undertaken to confirm the validity of the above model using coil structures subjected to overload conditions. The test variables included moisture in paper insulation, gas content in oil, and the type of oil preservation system. Two aged coils were also tested. The results indicated that the observed bubble temperatures weremore » close to the predicted temperatures for models with low initial gas content in the oil. The predicted temperatures were significantly lower than the observed temperatures for models with high gas content. Some explanations are provided for the anomalous behavior at high gas levels in oil. It is suggested that the dissolved gas content is not a significant factor in bubble evolution. The dominant factor in bubble evolution appears to be the water vapor pressure which must reach critical levels before bubbles can be released. Further study is needed to make a meaningful revision of the bubble prediction model. 8 refs., 13 figs., 11 tabs.« less

Antioxidant responses of damiana (Turnera diffusa Willd) to exposure to artificial ultraviolet (UV) radiation in an in vitro model; part ii; UV-B radiation.

PubMed

Soriano-Melgar, Lluvia de Abril Alexandra; Alcaraz-Meléndez, Lilia; Méndez-Rodríguez, Lía C; Puente, María Esther; Rivera-Cabrera, Fernando; Zenteno-Savín, Tania

2014-05-01

Ultraviolet type B (UV-B) radiation effects on medicinal plants have been recently investigated in the context of climate change, but the modifications generated by UV-B radiation might be used to increase the content of antioxidants, including phenolic compounds. To generate information on the effect of exposure to artificial UV-B radiation at different highdoses in the antioxidant content of damiana plants in an in vitro model. Damiana plantlets (tissue cultures in Murashige- Skoog medium) were irradiated with artificial UV-B at 3 different doses (1) 0.5 ± 0.1 mW cm-2 (high) for 2 h daily, (2) 1 ± 0,1 mW cm-2 (severe) for 2 h daily, or (3) 1 ± 0.1 mW cm-2 for 4 h daily during 3 weeks. The concentration of photosynthetic pigments (chlorophylls a and b, carotenoids), vitamins (C and E) and total phenolic compounds, the enzymatic activity of superoxide dismutase (SOD, EC 1.15.1.1) and total peroxidases (POX, EC 1.11.1), as well as total antioxidant capacity and lipid peroxidation levels were quantified to assess the effect of high artificial UV-B radiation in the antioxidant content of in vitro damiana plants. Severe and high doses of artificial UV-B radiation modified the antioxidant content by increasing the content of vitamin C and decreased the phenolic compound content, as well as modified the oxidative damage of damiana plants in an in vitro model. UV-B radiation modified the antioxidant content in damiana plants in an in vitro model, depending on the intensity and duration of the exposure. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

Factors affecting fat content in mottled ducks on the Upper Texas Gulf Coast

USGS Publications Warehouse

Kearns, Brian; Haukos, David A.; Walther, Patrick; Conway, Warren C.

2014-01-01

Body condition, or an individual's ability to address metabolic needs, is an important measure of organism health. For waterfowl, body condition, usually some measure of fat, provides a useful proxy for assessing energy budgets during different life history periods and potentially is a measure of response to ecosystem changes. The mottled duck (Anas fulvigula) is relatively poorly studied in respect to these dynamics and presents a unique case because its non-migratory life-history strategy releases it from metabolic costs experienced by many related migratory waterfowl species. Additionally, as a species in decline and of conservation concern in many parts of its range, traditional methods of fat content estimation that involve destructive sampling are less viable. The goal of this study was to produce an equation for estimating fat content in mottled ducks using birds (n = 24) donated at hunter-check stations or collected by law enforcement efforts on the Texas Chenier Plain National Wildlife Refuge Complex from 2005 - 2007. Morphometric measurements were taken, and ether extraction and fat removal was used to estimate percent body fat content and abdominal fat mass, respectively. A hierarchical simple linear regression modeling approach was used to determine external morphometrics that best predicted abdominal fat content. A ratio model based on body mass and a length metric (keel and wing chord length possessed equal model support) provided the best relationship with abdominal fat in sampled individuals. We then applied the regression equation to historical check station data to examine fluctuations in fat content over time; fat content or condition varied relatively little with the exception of years characterized by major disturbances. The mottled duck condition model created here can be used to better monitor population status and health without destructively sampling individuals.

Remote Sensing of Vegetation Nitrogen Content for Spatially Explicit Carbon and Water Cycle Estimation

NASA Astrophysics Data System (ADS)

Zhang, Y. L.; Miller, J. R.; Chen, J. M.

2009-05-01

Foliage nitrogen concentration is a determinant of photosynthetic capacity of leaves, thereby an important input to ecological models for estimating terrestrial carbon and water budgets. Recently, spectrally continuous airborne hyperspectral remote sensing imagery has proven to be useful for retrieving an important related parameter, total chlorophyll content at both leaf and canopy scales. Thus remote sensing of vegetation biochemical parameters has promising potential for improving the prediction of global carbon and water balance patterns. In this research, we explored the feasibility of estimating leaf nitrogen content using hyperspectral remote sensing data for spatially explicit estimation of carbon and water budgets. Multi-year measurements of leaf biochemical contents of seven major boreal forest species were carried out in northeastern Ontario, Canada. The variation of leaf chlorophyll and nitrogen content in response to various growth conditions, and the relationship between them,were investigated. Despite differences in plant type (deciduous and evergreen), leaf age, stand growth conditions and developmental stages, leaf nitrogen content was strongly correlated with leaf chlorophyll content on a mass basis during the active growing season (r2=0.78). With this general correlation, leaf nitrogen content was estimated from leaf chlorophyll content at an accuracy of RMSE=2.2 mg/g, equivalent to 20.5% of the average measured leaf nitrogen content. Based on this correlation and a hyperspectral remote sensing algorithm for leaf chlorophyll content retrieval, the spatial variation of leaf nitrogen content was inferred from the airborne hyperspectral remote sensing imagery acquired by Compact Airborne Spectrographic Imager (CASI). A process-based ecological model Boreal Ecosystem Productivity Simulator (BEPS) was used for estimating terrestrial carbon and water budgets. In contrast to the scenario with leaf nitrogen content assigned as a constant value without differentiation between and within vegetation types for calculating the photosynthesis rate, we incorporated the spatial distribution of leaf nitrogen content in the model to estimate net primary productivity and evaportranspiration of boreal ecosystem. These regional estimates of carbon and water budgets with and without N mapping are compared, and the importance of this leaf biochemistry information derived from hyperspectral remote sensing in regional mapping of carbon and water fluxes is quantitatively assessed. Keywords: Remote Sensing, Leaf Nitrogen Content, Spatial Distribution, Carbon and Water Budgets, Estimation

Testing a Technology Integration Education Model for Millennial Preservice Teachers: Exploring the Moderating Relationships of Goals, Feedback, Task Value, and Self-Regulation among Motivation and Technological, Pedagogical, and Content Knowledge Competencies

ERIC Educational Resources Information Center

Holland, Denise D.; Piper, Randy T.

2016-01-01

The technology integration education model is a 12 construct model that includes 8 primary constructs and 4 moderator constructs. By testing the relationships among two primary constructs (motivation and technological, pedagogical, and content knowledge competencies) and four moderator constructs (goals, feedback, task value, and self-regulation),…

Analysis of Flavonoid in Medicinal Plant Extract Using Infrared Spectroscopy and Chemometrics

PubMed Central

Retnaningtyas, Yuni; Nuri; Lukman, Hilmia

2016-01-01

Infrared (IR) spectroscopy combined with chemometrics has been developed for simple analysis of flavonoid in the medicinal plant extract. Flavonoid was extracted from medicinal plant leaves by ultrasonication and maceration. IR spectra of selected medicinal plant extract were correlated with flavonoid content using chemometrics. The chemometric method used for calibration analysis was Partial Last Square (PLS) and the methods used for classification analysis were Linear Discriminant Analysis (LDA), Soft Independent Modelling of Class Analogies (SIMCA), and Support Vector Machines (SVM). In this study, the calibration of NIR model that showed best calibration with R 2 and RMSEC value was 0.9916499 and 2.1521897, respectively, while the accuracy of all classification models (LDA, SIMCA, and SVM) was 100%. R 2 and RMSEC of calibration of FTIR model were 0.8653689 and 8.8958149, respectively, while the accuracy of LDA, SIMCA, and SVM was 86.0%, 91.2%, and 77.3%, respectively. PLS and LDA of NIR models were further used to predict unknown flavonoid content in commercial samples. Using these models, the significance of flavonoid content that has been measured by NIR and UV-Vis spectrophotometry was evaluated with paired samples t-test. The flavonoid content that has been measured with both methods gave no significant difference. PMID:27529051

Numerical and experimental studies on effects of moisture content on combustion characteristics of simulated municipal solid wastes in a fixed bed

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

Sun, Rui, E-mail: Sunsr@hit.edu.cn; Ismail, Tamer M., E-mail: temoil@aucegypt.edu; Ren, Xiaohan

Highlights: • The effects of moisture content on the burning process of MSW are investigated. • A two-dimensional mathematical model was built to simulate the combustion process. • Temperature distributions, process rates, gas species were measured and simulated. • The The conversion ratio of C/CO and N/NO in MSW are inverse to moisture content. - Abstract: In order to reveal the features of the combustion process in the porous bed of a waste incinerator, a two-dimensional unsteady state model and experimental study were employed to investigate the combustion process in a fixed bed of municipal solid waste (MSW) on themore » combustion process in a fixed bed reactor. Conservation equations of the waste bed were implemented to describe the incineration process. The gas phase turbulence was modeled using the k–ε turbulent model and the particle phase was modeled using the kinetic theory of granular flow. The rate of moisture evaporation, devolatilization rate, and char burnout was calculated according to the waste property characters. The simulation results were then compared with experimental data for different moisture content of MSW, which shows that the incineration process of waste in the fixed bed is reasonably simulated. The simulation results of solid temperature, gas species and process rate in the bed are accordant with experimental data. Due to the high moisture content of fuel, moisture evaporation consumes a vast amount of heat, and the evaporation takes up most of the combustion time (about 2/3 of the whole combustion process). The whole bed combustion process reduces greatly as MSW moisture content increases. The experimental and simulation results provide direction for design and optimization of the fixed bed of MSW.« less

Further experimentation on bubble generation during transformer overload. Final report

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

Oommen, T.V.

1992-03-01

This report covers additional work done during 1990 and 1991 on gas bubble generation under overload conditions. To improve visual bubble detection, a single disc coil was used. To further improve detection, a corona device was also used which signaled the onset of corona activity in the early stages of bubble formation. A total of fourteen model tests were conducted, half of which used the Inertaire system, and the remaining, a conservator (COPS). Moisture content of paper in the coil varied from 1.0% to 8.0%; gas (nitrogen) content varied from 1.0% to 8.8%. The results confirmed earlier observations that themore » mathematical bubble prediction model was not valid for high gas content model with relatively low moisture levels in the coil. An empirical relationship was formulated to accurately predict bubble evolution temperatures from known moisture and gas content values. For low moisture content models (below 2%), the simple Piper relationship was sufficient to predict bubble evolution temperatures, regardless of gas content. Moisture in the coil appears to be the key factor in bubble generation. Gas blanketed (Inertaire) systems do not appear to be prone to premature bubble generation from overloads as previously thought. The new bubble prediction model reveals that for a coil with 2% moisture, the bubble evolution temperature would be about 140{degrees}C. Since old transformers in service may have as much as 2% moisture in paper, the 140{degrees}C bubble evolution temperature may be taken as the lower limit of bubble evolution temperature under overload conditions for operating transformers. Drier insulation would raise the bubble evolution temperature.« less

Testing the cognitive catalyst model of rumination with explicit and implicit cognitive content.

PubMed

Sova, Christopher C; Roberts, John E

2018-06-01

The cognitive catalyst model posits that rumination and negative cognitive content, such as negative schema, interact to predict depressive affect. Past research has found support for this model using explicit measures of negative cognitive content such as self-report measures of trait self-esteem and dysfunctional attitudes. The present study tested whether these findings would extend to implicit measures of negative cognitive content such as implicit self-esteem, and whether effects would depend on initial mood state and history of depression. Sixty-one undergraduate students selected on the basis of depression history (27 previously depressed; 34 never depressed) completed explicit and implicit measures of negative cognitive content prior to random assignment to a rumination induction followed by a distraction induction or vice versa. Dysphoric affect was measured both before and after these inductions. Analyses revealed that explicit measures, but not implicit measures, interacted with rumination to predict change in dysphoric affect, and these interactions were further moderated by baseline levels of dysphoria. Limitations include the small nonclinical sample and use of a self-report measure of depression history. These findings suggest that rumination amplifies the association between explicit negative cognitive content and depressive affect primarily among people who are already experiencing sad mood. Copyright © 2018 Elsevier Ltd. All rights reserved.

Contention Modeling for Multithreaded Distributed Shared Memory Machines: The Cray XMT

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

Secchi, Simone; Tumeo, Antonino; Villa, Oreste

Distributed Shared Memory (DSM) machines are a wide class of multi-processor computing systems where a large virtually-shared address space is mapped on a network of physically distributed memories. High memory latency and network contention are two of the main factors that limit performance scaling of such architectures. Modern high-performance computing DSM systems have evolved toward exploitation of massive hardware multi-threading and fine-grained memory hashing to tolerate irregular latencies, avoid network hot-spots and enable high scaling. In order to model the performance of such large-scale machines, parallel simulation has been proved to be a promising approach to achieve good accuracy inmore » reasonable times. One of the most critical factors in solving the simulation speed-accuracy trade-off is network modeling. The Cray XMT is a massively multi-threaded supercomputing architecture that belongs to the DSM class, since it implements a globally-shared address space abstraction on top of a physically distributed memory substrate. In this paper, we discuss the development of a contention-aware network model intended to be integrated in a full-system XMT simulator. We start by measuring the effects of network contention in a 128-processor XMT machine and then investigate the trade-off that exists between simulation accuracy and speed, by comparing three network models which operate at different levels of accuracy. The comparison and model validation is performed by executing a string-matching algorithm on the full-system simulator and on the XMT, using three datasets that generate noticeably different contention patterns.« less

NIR spectroscopy for the quality control of Moringa oleifera (Lam.) leaf powders: Prediction of minerals, protein and moisture contents.

PubMed

Rébufa, Catherine; Pany, Inès; Bombarda, Isabelle

2018-09-30

A rapid methodology was developed to simultaneously predict water content and activity values (a w ) of Moringa oleifera leaf powders (MOLP) using near infrared (NIR) signatures and experimental sorption isotherms. NIR spectra of MOLP samples (n = 181) were recorded. A Partial Least Square Regression model (PLS2) was obtained with low standard errors of prediction (SEP of 1.8% and 0.07 for water content and a w respectively). Experimental sorption isotherms obtained at 20, 30 and 40 °C showed similar profiles. This result is particularly important to use MOLP in food industry. In fact, a temperature variation of the drying process will not affect their available water content (self-life). Nutrient contents based on protein and selected minerals (Ca, Fe, K) were also predicted from PLS1 models. Protein contents were well predicted (SEP of 2.3%). This methodology allowed for an improvement in MOLP safety, quality control and traceability. Published by Elsevier Ltd.

Gastrointestinal transit in nonobese diabetic mouse: an animal model of human diabetes type 1.

PubMed

El-Salhy, M

2001-01-01

Gastrointestinal transit (GI) in the nonobese diabetic (NOD) mouse, an animal model of human diabetes type 1, was examined in animals with short- (duration 1-5 days) and long-term (duration 28-35 days) diabetes. Blood glucose level, serum insulin concentration, and gut neuroendocrine peptide content were also measured. GI was significantly rapid in NOD mice with long-term diabetes (LTD), but was not correlated with blood glucose level, serum insulin concentration, or pancreatic insulin content. GI was correlated with duodenal secretin content, but not with the content of other neuroendocrine peptides in the different segments investigated. Whereas antral vasoactive intestinal peptide (VIP) content in NOD mice with LTD was significantly higher, colonic VIP was lower in NOD mice with short-term diabetes (STD). In the duodenum, whereas the concentration of secretin in NOD mice with both STD and LTD was lower, the gastrin content was higher. Duodenal somatostatin content in NOD mice with LTD was lower. In colon, the content of galanin in NOD mice with LTD was higher than in controls. The decreased content of secretin may be among the factors that cause rapid GI in NOD mice with LTD. Changes in the antral content of VIP, duodenal somatostatin, and colonic galanin in NOD mice with LTD may cause low intestinal secretion and, together with rapid GI, give rise to diarrhoea, which is a common symptom in diabetes.

Chlorophyll content retrieval from hyperspectral remote sensing imagery.

PubMed

Yang, Xiguang; Yu, Ying; Fan, Wenyi

2015-07-01

Chlorophyll content is the essential parameter in the photosynthetic process determining leaf spectral variation in visible bands. Therefore, the accurate estimation of the forest canopy chlorophyll content is a significant foundation in assessing forest growth and stress affected by diseases. Hyperspectral remote sensing with high spatial resolution can be used for estimating chlorophyll content. In this study, the chlorophyll content was retrieved step by step using Hyperion imagery. Firstly, the spectral curve of the leaf was analyzed, 25 spectral characteristic parameters were identified through the correlation coefficient matrix, and a leaf chlorophyll content inversion model was established using a stepwise regression method. Secondly, the pixel reflectance was converted into leaf reflectance by a geometrical-optical model (4-scale). The three most important parameters of reflectance conversion, including the multiple scattering factor (M 0 ), and the probability of viewing the sunlit tree crown (P T ) and the background (P G ), were estimated by leaf area index (LAI), respectively. The results indicated that M 0 , P T , and P G could be described as a logarithmic function of LAI, with all R (2) values above 0.9. Finally, leaf chlorophyll content was retrieved with RMSE = 7.3574 μg/cm(2), and canopy chlorophyll content per unit ground surface area was estimated based on leaf chlorophyll content and LAI. Chlorophyll content mapping can be useful for the assessment of forest growth stage and diseases.

Predicting subsurface uranium transport: Mechanistic modeling constrained by experimental data

NASA Astrophysics Data System (ADS)

Ottman, Michael; Schenkeveld, Walter D. C.; Kraemer, Stephan

2017-04-01

Depleted uranium (DU) munitions and their widespread use throughout conflict zones around the world pose a persistent health threat to the inhabitants of those areas long after the conclusion of active combat. However, little emphasis has been put on developing a comprehensive, quantitative tool for use in remediation and hazard avoidance planning in a wide range of environments. In this context, we report experimental data on U interaction with soils and sediments. Here, we strive to improve existing risk assessment modeling paradigms by incorporating a variety of experimental data into a mechanistic U transport model for subsurface environments. 20 different soils and sediments from a variety of environments were chosen to represent a range of geochemical parameters that are relevant to U transport. The parameters included pH, organic matter content, CaCO3, Fe content and speciation, and clay content. pH ranged from 3 to 10, organic matter content from 6 to 120 g kg-1, CaCO3 from 0 to 700 g kg-1, amorphous Fe content from 0.3 to 6 g kg-1 and clay content from 4 to 580 g kg-1. Sorption experiments were then performed, and linear isotherms were constructed. Sorption experiment results show that among separate sets of sediments and soils, there is an inverse correlation between both soil pH and CaCO¬3 concentration relative to U sorptive affinity. The geological materials with the highest and lowest sorptive affinities for U differed in CaCO3 and organic matter concentrations, as well as clay content and pH. In a further step, we are testing if transport behavior in saturated porous media can be predicted based on adsorption isotherms and generic geochemical parameters, and comparing these modeling predictions with the results from column experiments. The comparison of these two data sets will examine if U transport can be effectively predicted from reactive transport modeling that incorporates the generic geochemical parameters. This work will serve to show whether a more mechanistic approach offers an improvement over statistical regression-based risk assessment models.

Ontological interpretation of biomedical database content.

PubMed

Santana da Silva, Filipe; Jansen, Ludger; Freitas, Fred; Schulz, Stefan

2017-06-26

Biological databases store data about laboratory experiments, together with semantic annotations, in order to support data aggregation and retrieval. The exact meaning of such annotations in the context of a database record is often ambiguous. We address this problem by grounding implicit and explicit database content in a formal-ontological framework. By using a typical extract from the databases UniProt and Ensembl, annotated with content from GO, PR, ChEBI and NCBI Taxonomy, we created four ontological models (in OWL), which generate explicit, distinct interpretations under the BioTopLite2 (BTL2) upper-level ontology. The first three models interpret database entries as individuals (IND), defined classes (SUBC), and classes with dispositions (DISP), respectively; the fourth model (HYBR) is a combination of SUBC and DISP. For the evaluation of these four models, we consider (i) database content retrieval, using ontologies as query vocabulary; (ii) information completeness; and, (iii) DL complexity and decidability. The models were tested under these criteria against four competency questions (CQs). IND does not raise any ontological claim, besides asserting the existence of sample individuals and relations among them. Modelling patterns have to be created for each type of annotation referent. SUBC is interpreted regarding maximally fine-grained defined subclasses under the classes referred to by the data. DISP attempts to extract truly ontological statements from the database records, claiming the existence of dispositions. HYBR is a hybrid of SUBC and DISP and is more parsimonious regarding expressiveness and query answering complexity. For each of the four models, the four CQs were submitted as DL queries. This shows the ability to retrieve individuals with IND, and classes in SUBC and HYBR. DISP does not retrieve anything because the axioms with disposition are embedded in General Class Inclusion (GCI) statements. Ambiguity of biological database content is addressed by a method that identifies implicit knowledge behind semantic annotations in biological databases and grounds it in an expressive upper-level ontology. The result is a seamless representation of database structure, content and annotations as OWL models.

[Near infrared spectroscopy study on water content in turbine oil].

PubMed

Chen, Bin; Liu, Ge; Zhang, Xian-Ming

2013-11-01

Near infrared (NIR) spectroscopy combined with successive projections algorithm (SPA) was investigated for determination of water content in turbine oil. Through the 57 samples of different water content in turbine oil scanned applying near infrared (NIR) spectroscopy, with the water content in the turbine oil of 0-0.156%, different pretreatment methods such as the original spectra, first derivative spectra and differential polynomial least squares fitting algorithm Savitzky-Golay (SG), and successive projections algorithm (SPA) were applied for the extraction of effective wavelengths, the correlation coefficient (R) and root mean square error (RMSE) were used as the model evaluation indices, accordingly water content in turbine oil was investigated. The results indicated that the original spectra with different water content in turbine oil were pretreated by the performance of first derivative + SG pretreatments, then the selected effective wavelengths were used as the inputs of least square support vector machine (LS-SVM). A total of 16 variables selected by SPA were employed to construct the model of SPA and least square support vector machine (SPA-LS-SVM). There is 9 as The correlation coefficient was 0.975 9 and the root of mean square error of validation set was 2.655 8 x 10(-3) using the model, and it is feasible to determine the water content in oil using near infrared spectroscopy and SPA-LS-SVM, and an excellent prediction precision was obtained. This study supplied a new and alternative approach to the further application of near infrared spectroscopy in on-line monitoring of contamination such as water content in oil.

Biodiversity effects on the water balance of an experimental grassland

NASA Astrophysics Data System (ADS)

Leimer, Sophia; Kreutziger, Yvonne; Rosenkranz, Stephan; Beßler, Holger; Engels, Christof; Oelmann, Yvonne; Weisser, Wolfgang W.; Wirth, Christian; Wilcke, Wolfgang

2013-04-01

Plant species richness increases aboveground biomass production in biodiversity experiments. Biomass production depends on and feeds back to the water balance, but it remains unclear how plant species richness influences soil water contents and water fluxes (actual evapotranspiration (ETa), downward flux (DF), and upward flux (UF)). Our objective was to determine the effects of plant species and functional richness and functional identity on soil water contents and water fluxes for two soil depths (0-0.3 and 0.3.-0.7 m). To achieve this, we used a water balance model in connection with Bayesian hierarchical modeling. We monitored soil water contents on 86 plots of a grassland plant diversity experiment in Jena, Germany between July 2002 and January 2006. In the field experiment, plant species richness (0, 1, 2, 4, 8, 16, 60) and functional group composition (0-4 functional groups: legumes, grasses, non-leguminous tall herbs, non-leguminous small herbs) were manipulated in a factorial design. Climate data (air temperature, precipitation, wind velocity, relative humidity, global radiation, soil moisture) was measured at a central climate station between July 2002 and December 2007. Root biomass data from July 2006 was available per plot. Missing water contents per plot and depth were estimated in weekly resolution for the years 2003-2007 with a Bayesian hierarchical model using measured water contents per plot and centrally measured soil moisture. To obtain ETa, DF, and UF of the two different soil depths, we modified a soil water balance model which had been developed for our study site. The model is based on changes in soil water content between subsequent observation dates and modeled potential evapotranspiration which was partitioned between soil layers according to percentage of root biomass. The presence of specific functional groups significantly changed water contents and fluxes with partly opposing effects in the two soil depths. Presence of grasses decreased water contents in both depths, DF in topsoil, and ETa in subsoil, but increased ETa in topsoil. As grasses produce less shade than other plant functional groups because of their leaf morphology, higher ETa in topsoil could be explained by higher soil evaporation. Moreover, grasses have an extensive, shallow rooting system which facilitates exhaustive water use from the upper soil layer and therefore probably decreases water contents and DF. Species richness did not significantly affect water contents and fluxes in both soil layers except that the relation between species richness and water contents in subsoil changed over time. This can be explained by two equivalent but opposite effects. Transpiration increases with biomass which is positively correlated with species richness. By contrast, soil evaporation decreases with species richness because the greater vegetation cover in species-rich communities produces more shade. We conclude that the contrasting effects of plant species richness on transpiration and evaporation counterbalance each other and that functional traits of specific plant functional groups mediate the biologically-induced changes in the water balance.

An Interactive Multimedia Learning Environment for VLSI Built with COSMOS

ERIC Educational Resources Information Center

Angelides, Marios C.; Agius, Harry W.

2002-01-01

This paper presents Bigger Bits, an interactive multimedia learning environment that teaches students about VLSI within the context of computer electronics. The system was built with COSMOS (Content Oriented semantic Modelling Overlay Scheme), which is a modelling scheme that we developed for enabling the semantic content of multimedia to be used…

Comparing Traditional versus Alternative Sequencing of Instruction When Using Simulation Modeling

ERIC Educational Resources Information Center

Bowen, Bradley; DeLuca, William

2015-01-01

Many engineering and technology education classrooms incorporate simulation modeling as part of curricula to teach engineering and STEM-based concepts. The traditional method of the learning process has students first learn the content from the classroom teacher and then may have the opportunity to apply the learned content through simulation…

Pro and Antisocial Television Content and Modeling by High and Low Self-esteem Children.

ERIC Educational Resources Information Center

Baran, Stanley J.

Children will individually react to television program content according to different psychological characteristics, one of which is self-esteem. Results of one study revealed a definite relationship between a child's self-esteem and his "modeling," or imitative behavior, after observing a televised film. A self-esteem inventory was administered…

Encoding Personal Adjectives: The Effects of Depression on Self-Reference.

ERIC Educational Resources Information Center

Kuiper, Nicholas A.; Derry, Paul A.

A central tenet of a self-schema model for depression is the idea that severity of depression is a crucial determinant of the content and cohesiveness of the depressive's self-schema. Consistent with predictions generated form this model, sample nondepressives displayed superior recall for self-referenced, nondepressed-content adjectives. Recall…

Models of the Bilingual Lexicon and Their Theoretical Implications for CLIL

ERIC Educational Resources Information Center

Heine, Lena

2014-01-01

Although many advances have been made in recent years concerning the theoretical dimensions of content and language integrated learning (CLIL), research still has to meet the necessity to come up with integrative models that adequately map the interrelation between content and language learning in CLIL contexts. This article will suggest that…

Modeling the energy content of combustible ship-scrapping waste at Alang-Sosiya, India, using multiple regression analysis.

PubMed

Reddy, M Srinivasa; Basha, Shaik; Joshi, H V; Sravan Kumar, V G; Jha, B; Ghosh, P K

2005-01-01

Alang-Sosiya is the largest ship-scrapping yard in the world, established in 1982. Every year an average of 171 ships having a mean weight of 2.10 x 10(6)(+/-7.82 x 10(5)) of light dead weight tonnage (LDT) being scrapped. Apart from scrapped metals, this yard generates a massive amount of combustible solid waste in the form of waste wood, plastic, insulation material, paper, glass wool, thermocol pieces (polyurethane foam material), sponge, oiled rope, cotton waste, rubber, etc. In this study multiple regression analysis was used to develop predictive models for energy content of combustible ship-scrapping solid wastes. The scope of work comprised qualitative and quantitative estimation of solid waste samples and performing a sequential selection procedure for isolating variables. Three regression models were developed to correlate the energy content (net calorific values (LHV)) with variables derived from material composition, proximate and ultimate analyses. The performance of these models for this particular waste complies well with the equations developed by other researchers (Dulong, Steuer, Scheurer-Kestner and Bento's) for estimating energy content of municipal solid waste.

A cost-effectiveness comparison of existing and Landsat-aided snow water content estimation systems

NASA Technical Reports Server (NTRS)

Sharp, J. M.; Thomas, R. W.

1975-01-01

This study describes how Landsat imagery can be cost-effectively employed to augment an operational hydrologic model. Attention is directed toward the estimation of snow water content, a major predictor variable in the volumetric runoff forecasting model presently used by the California Department of Water Resources. A stratified double sampling scheme is supplemented with qualitative and quantitative analyses of existing operations to develop a comparison between the existing and satellite-aided approaches to snow water content estimation. Results show a decided advantage for the Landsat-aided approach.

What's the Technology For? Teacher Attention and Pedagogical Goals in a Modeling-Focused Professional Development Workshop

NASA Astrophysics Data System (ADS)

Wilkerson, Michelle Hoda; Andrews, Chelsea; Shaban, Yara; Laina, Vasiliki; Gravel, Brian E.

2016-02-01

This paper explores the role that technology can play in engaging pre-service teachers with the iterative, "messy" nature of model-based inquiry. Over the course of 5 weeks, 11 pre-service teachers worked in groups to construct models of diffusion using a computational animation and simulation toolkit, and designed lesson plans for the toolkit. Content analyses of group discussions and lesson plans document attention to content, representation, revision, and evaluation as interwoven aspects of modeling over the course of the workshop. When animating, only content and representation were heavily represented in group discussions. When simulating, all four aspects were represented to different extents across groups. Those differences corresponded with different planned uses for the technology during lessons: to teach modeling, to engage learners with one another's ideas, or to reveal student ideas. We identify specific ways in which technology served an important role in eliciting teachers' knowledge and goals related to scientific modeling in the classroom.

Computational Psychotherapy Research: Scaling up the evaluation of patient-provider interactions

PubMed Central

Imel, Zac E.; Steyvers, Mark; Atkins, David C.

2014-01-01

In psychotherapy, the patient-provider interaction contains the treatment’s active ingredients. However, the technology for analyzing the content of this interaction has not fundamentally changed in decades, limiting both the scale and specificity of psychotherapy research. New methods are required in order to “scale up” to larger evaluation tasks and “drill down” into the raw linguistic data of patient-therapist interactions. In the current paper we demonstrate the utility of statistical text analysis models called topic models for discovering the underlying linguistic structure in psychotherapy. Topic models identify semantic themes (or topics) in a collection of documents (here, transcripts). We used topic models to summarize and visualize 1,553 psychotherapy and drug therapy (i.e., medication management) transcripts. Results showed that topic models identified clinically relevant content, including affective, content, and intervention related topics. In addition, topic models learned to identify specific types of therapist statements associated with treatment related codes (e.g., different treatment approaches, patient-therapist discussions about the therapeutic relationship). Visualizations of semantic similarity across sessions indicate that topic models identify content that discriminates between broad classes of therapy (e.g., cognitive behavioral therapy vs. psychodynamic therapy). Finally, predictive modeling demonstrated that topic model derived features can classify therapy type with a high degree of accuracy. Computational psychotherapy research has the potential to scale up the study of psychotherapy to thousands of sessions at a time, and we conclude by discussing the implications of computational methods such as topic models for the future of psychotherapy research and practice. PMID:24866972

Comparison of Ionospheric Vertical Total Electron Content modelling approaches using spline based representations

NASA Astrophysics Data System (ADS)

Krypiak-Gregorczyk, Anna; Wielgosz, Pawel; Borkowski, Andrzej; Schmidt, Michael; Erdogan, Eren; Goss, Andreas

2017-04-01

Since electromagnetic measurements show dispersive characteristics, accurate modelling of the ionospheric electron content plays an important role for positioning and navigation applications to mitigate the effect of the ionospheric disturbances. Knowledge about the ionosphere contributes to a better understanding of space weather events as well as to forecast these events to enable protective measures in advance for electronic systems and satellite missions. In the last decades, advances in satellite technologies, data analysis techniques and models together with a rapidly growing number of analysis centres allow modelling the ionospheric electron content with an unprecedented accuracy in (near) real-time. In this sense, the representation of electron content variations in time and space with spline basis functions has gained practical importance in global and regional ionosphere modelling. This is due to their compact support and their flexibility to handle unevenly distributed observations and data gaps. In this contribution, the performances of two ionosphere models from UWM and DGFI-TUM, which are developed using spline functions are evaluated. The VTEC model of DGFI-TUM is based on tensor products of trigonometric B-spline functions in longitude and polynomial B-spline functions in latitude for a global representation. The UWM model uses two dimensional planar thin plate spline (TPS) with the Universal Transverse Mercator representation of ellipsoidal coordinates. In order to provide a smooth VTEC model, the TPS minimizes both, the squared norm of the Hessian matrix and deviations between data points and the model. In the evaluations, the differenced STEC analysis method and Jason-2 altimetry comparisons are applied.

A Conceptual Foundation for Measures of Physical Function and Behavioral Health Function for Social Security Work Disability Evaluation

PubMed Central

Marfeo, Elizabeth E.; Haley, Stephen M.; Jette, Alan M.; Eisen, Susan V.; Ni, Pengsheng; Bogusz, Kara; Meterko, Mark; McDonough, Christine M.; Chan, Leighton; Brandt, Diane E.; Rasch, Elizabeth K.

2014-01-01

Physical and mental impairments represent the two largest health condition categories for which workers receive Social Security disability benefits. Comprehensive assessment of physical and mental impairments should include aspects beyond medical conditions such as a person’s underlying capabilities as well as activity demands relevant to the context of work. The objective of this paper is to describe the initial conceptual stages of developing new measurement instruments of behavioral health and physical functioning relevant for Social Security work disability evaluation purposes. To outline a clear conceptualization of the constructs to be measured, two content models were developed using structured and informal qualitative approaches. We performed a structured literature review focusing on work disability and incorporating aspects of the International Classification of Functioning, Disability, and Health (ICF) as a unifying taxonomy for framework development. Expert interviews provided advice and consultation to enhance face validity of the resulting content models. The content model for work-related behavioral health function identifies five major domains (1) Behavior Control, (2) Basic Interactions, (3) Temperament and Personality, (4) Adaptability, and (5) Workplace Behaviors. The content model describing physical functioning includes three domains (1) Changing and Maintaining Body Position, (2) Whole Body Mobility, and (3) Carrying, Moving and Handling Objects. These content models informed subsequent measurement properties including item development, measurement scale construction, and provided conceptual coherence guiding future empirical inquiry. The proposed measurement approaches show promise to comprehensively and systematically assess physical and behavioral health functioning relevant to work. PMID:23548543

A Threshold Model of Content Knowledge Transfer for Socioscientific Argumentation

ERIC Educational Resources Information Center

Sadler, Troy D.; Fowler, Samantha R.

2006-01-01

This study explores how individuals make use of scientific content knowledge for socioscientific argumentation. More specifically, this mixed-methods study investigates how learners apply genetics content knowledge as they justify claims relative to genetic engineering. Interviews are conducted with 45 participants, representing three distinct…

Ventilation tube insertion simulation: a literature review and validity assessment of five training models.

PubMed

Mahalingam, S; Awad, Z; Tolley, N S; Khemani, S

2016-08-01

The objective of this study was to identify and investigate the face and content validity of ventilation tube insertion (VTI) training models described in the literature. A review of literature was carried out to identify articles describing VTI simulators. Feasible models were replicated and assessed by a group of experts. Postgraduate simulation centre. Experts were defined as surgeons who had performed at least 100 VTI on patients. Seventeen experts were participated ensuring sufficient statistical power for analysis. A standardised 18-item Likert-scale questionnaire was used. This addressed face validity (realism), global and task-specific content (suitability of the model for teaching) and curriculum recommendation. The search revealed eleven models, of which only five had associated validity data. Five models were found to be feasible to replicate. None of the tested models achieved face or global content validity. Only one model achieved task-specific validity, and hence, there was no agreement on curriculum recommendation. The quality of simulation models is moderate and there is room for improvement. There is a need for new models to be developed or existing ones to be refined in order to construct a more realistic training platform for VTI simulation. © 2015 John Wiley & Sons Ltd.

[Total flavones derived from Lagotis brevituba maxim reduce the levels of inflammatory cytokines in cerebral cortex and hippocampus of Alzheimer's disease mice].

PubMed

Yang, Bailing; Hou, Qian; Hu, Feng; Zhang, Fan

2016-07-01

Objective To investigate the mechanism behind the treatment of Alzheimer's disease (AD) with total flavones derived from Lagotis brevituba maxim (TF-LBM). Methods Fifty SAMP8 mice (aged 8 months) were randomly divided into 5 groups, (150, 300, 600) mg/kg TF-LBM groups, 0.65 g/kg donepezil HCl group and AD model group; 10 SAMR1 mice (aged 8 months) were used as a control group of normal aging. The AD model group and the normal aging control group were given the same volume of distilled water as TF-LBM groups. Eight weeks after intragastric administration, Morris water maze experiment was conducted to calculate the latency of place navigation. After the behavioral experiment, the brain cortical tissue and hippocampus (CA1 region) of the mice from various groups were taken to observe the morphological changes of the cortical tissue and hippocampus and test IL-1β, IL-6, TNF-α content. Results Compared with the model group, the escape latency of the normal aging group, the high-dose TF-LBM group and the donepezil HCl group were evidently shortened; compared with the normal aging group, IL-1β, IL-6, TNF-αof the model group increased significantly; compared with the model group, IL-1β content of the low-dose TF-LBM group had no obvious difference, while IL-1β content of the median-dose and high-dose TF-LBM groups and the donepezil HCl group decreased significantly; IL-6 content decreased in all TF-LBM groups and the donepezil HCl group; TNF-α level in the low-dose and median-dose TF-LBM groups had no evident difference, while it was reduced significantly in the high-dose TF-LBM group and the donepezil HCl group. Compared with the normal aging group, IL-1β, IL-6 and TNF-α content of the model group increased significantly; compared with the model group, IL-1β, IL-6 and TNF-α content of all TF-LBM groups and the donepezil HCl group decreased. Conclusion TF-LBM can improve the behavior change of SAMP8 mice with AD. TF-LBM can reduce the content of IL-6, IL-1β and TNF-α in cerebral cortex and hippocampus CA1.

Study on Hyperspectral Estimation Model of Total Nitrogen Content in Soil of Shaanxi Province

NASA Astrophysics Data System (ADS)

Liu, Jinbao; Dong, Zhenyu; Chen, Xi

2018-01-01

The development of hyperspectral remote sensing technology has been widely used in soil nutrient prediction. The soil is the representative soil type in Shaanxi Province. In this study, the soil total nitrogen content in Shaanxi soil was used as the research target, and the soil samples were measured by reflectance spectroscopy using ASD method. Pre-treatment, the first order differential, second order differential and reflectance logarithmic transformation of the reflected spectrum after pre-treatment, and the hyperspectral estimation model is established by using the least squares regression method and the principal component regression method. The results show that the correlation between the reflectance spectrum and the total nitrogen content of the soil is significantly improved. The correlation coefficient between the original reflectance and soil total nitrogen content is in the range of 350 ~ 2500nm. The correlation coefficient of soil total nitrogen content and first deviation of reflectance is more than 0.5 at 142nm, 1963nm, 2204nm and 2307nm, the second deviation has a significant positive correlation at 1114nm, 1470nm, 1967nm, 2372nm and 2402nm, respectively. After the reciprocal logarithmic transformation of the reflectance with the total nitrogen content of the correlation analysis found that the effect is not obvious. Rc2 = 0.7102, RMSEC = 0.0788; Rv2 = 0.8480, RMSEP = 0.0663, which can achieve the rapid prediction of the total nitrogen content in the region. The results show that the principal component regression model is the best.

Genetic parameters for growth performance, fillet traits, and fat percentage of male Nile tilapia (Oreochromis niloticus).

PubMed

Garcia, André Luiz Seccatto; de Oliveira, Carlos Antonio Lopes; Karim, Hanner Mahmud; Sary, César; Todesco, Humberto; Ribeiro, Ricardo Pereira

2017-11-01

Improvement of fillet traits and flesh quality attributes are of great interest in farmed tilapia and other aquaculture species. The main objective of this study was to estimate genetic parameters for fillet traits (fillet weight and fillet yield) and the fat content of fillets from 1136 males combined with 2585 data records on growth traits (body weight at 290 days, weight at slaughter, and daily weight gain) of 1485 males and 1100 females from a third generation of the Aquaamerica tilapia strain. Different models were tested for each trait, and the best models were used to estimate genetic parameters for the fat content, fillet, and growth traits. Genetic and phenotypic correlations were estimated using two-trait animal models. The heritability estimates were moderate for the fat content of fillets and fillet yield (0.2-0.32) and slightly higher for body weight at slaughter (0.41). The genetic correlation between fillet yield and fat was significant (0.6), but the genetic correlations were not significant between body weight and fillet yield, body weight and fat content, daily weight gain and fillet yield, and daily weight gain and fat content (- 0.032, - 0.1, - 0.09, and - 0.4, respectively). Based on the genetic correlation estimates, it is unlikely that changes in fillet yield and fat content will occur when using growth performance as a selection criterion, but indirect changes may be expected in fat content if selecting for higher fillet yield.

Impedance spectroscopy measurements as a tool for distinguishing different luminal content during bolus transit studies.

PubMed

Ruiz-Vargas, A; Mohd Rosli, R; Ivorra, A; Arkwright, J W

2018-01-08

Intraluminal electrical impedance is a well-known diagnostic tool used to study bolus movement in the human esophagus. However, it is use in the human colon it is hindered by the fact that the content cannot be controlled and may include liquid, gas, solid, or a mixture of these at any one time. This article investigates the use of complex impedance spectroscopy to study different luminal content (liquid and gas). An excised section of guinea pig proximal colon was placed in an organ bath with Krebs solution at 37°C and a custom built bioimpedance catheter was placed in the lumen. Liquid (Krebs) and gas (air) content was pumped through the lumen and the intraluminal impedance was measured at five different frequencies (1, 5.6, 31.6, 177.18 kHz and 1 MHz) at 10 samples per second. A numerical model was created to model the passage of bolus with different content and compared to the experimental data. Differences in mean impedance magnitude and phase angle were found (from 1 to 177.18 kHz) for different contents. The numerical results qualitatively agreed with those in the experimental study. Conductivities of bolus had an effect on detecting its passage. Complex impedance spectroscopy can distinguish between different luminal content within a range of measuring frequencies. The numerical model showed the importance of bolus conductivities for bolus transit studies in those where the bolus is controlled. © 2018 John Wiley & Sons Ltd.

A better start for health equity? Qualitative content analysis of implementation of extended postnatal home visiting in a disadvantaged area in Sweden.

PubMed

Barboza, Madelene; Kulane, Asli; Burström, Bo; Marttila, Anneli

2018-04-10

Health inequities among children in Sweden persist despite the country's well-developed welfare system and near universal access to the national child health care programme. A multisectoral extended home visiting intervention, based on the principles of proportionate universalism, has been carried out in a disadvantaged area since 2013. The present study investigates the content of the meetings between families and professionals during the home visits to gain a deeper understanding of how it relates to a health equity perspective on early childhood development. Three child health care nurses documented 501 visits to the families of 98 children between 2013 and 2016. A qualitative data-driven conventional content analysis was performed on all data from the cycle of six visits per child, and a general content model was developed. Additional content analysis was carried out on the data from visits to families who experienced adverse situations or greater needs. The analysis revealed that the home visits covered three main categories of content related to the health, care and development of the child; the strengthening of roles and relations within the new family unit; and the influence and support located in the broader external context around the family. The model of categories and sub-categories proved stable over all six visits. Families with extra needs received continuous attention to their additional issues during the visits, as well as the standard content described in the content model. This study on home visiting implementation indicates that the participating families received programme content which covered all the domains of nurturing care as recommended by the WHO Commission on Social Determinants of Health and recent research. The content of the home visits can be understood to create enabling conditions for health equity effects. The intervention can be seen to represent a practical example of proportionate universalism.

Modeling of soil water retention from saturation to oven dryness

USGS Publications Warehouse

Rossi, Cinzia; Nimmo, John R.

1994-01-01

Most analytical formulas used to model moisture retention in unsaturated porous media have been developed for the wet range and are unsuitable for applications in which low water contents are important. We have developed two models that fit the entire range from saturation to oven dryness in a practical and physically realistic way with smooth, continuous functions that have few parameters. Both models incorporate a power law and a logarithmic dependence of water content on suction, differing in how these two components are combined. In one model, functions are added together (model “sum”); in the other they are joined smoothly together at a discrete point (model “junction”). Both models also incorporate recent developments that assure a continuous derivative and force the function to reach zero water content at a finite value of suction that corresponds to oven dryness. The models have been tested with seven sets of water retention data that each cover nearly the entire range. The three-parameter sum model fits all data well and is useful for extrapolation into the dry range when data for it are unavailable. The two-parameter junction model fits most data sets almost as well as the sum model and has the advantage of being analytically integrable for convenient use with capillary-bundle models to obtain the unsaturated hydraulic conductivity.

Using the Stereotype Content Model to examine group depictions in Fascism: An Archival Approach.

PubMed

Durante, Federica; Volpato, Chiara; Fiske, Susan T

2010-04-01

The Stereotype Content Model (SCM) suggests potentially universal intergroup depictions. If universal, they should apply across history in archival data. Bridging this gap, we examined social groups descriptions during Italy's Fascist era. In Study 1, articles published in a Fascist magazine- La Difesa della Razza -were content analyzed, and results submitted to correspondence analysis. Admiration prejudice depicted ingroups; envious and contemptuous prejudices depicted specific outgroups, generally in line with SCM predictions. No paternalistic prejudice appeared; historical reasons might explain this finding. Results also fit the recently developed BIAS Map of behavioral consequences. In Study 2, ninety-six undergraduates rated the content-analysis traits on warmth and competence, without knowing their origin. They corroborated SCM's interpretations of the archival data.

Is organic matter alone sufficient to predict isoproturon sorption in calcareous soils?

PubMed

El Arfaoui, Achouak; Sayen, Stéphanie; Paris, Michaël; Keziou, Amor; Couderchet, Michel; Guillon, Emmanuel

2012-08-15

Eleven soils collected from Champagne-Ardenne area (France) were used to investigate isoproturon sorption in laboratory conditions. Our results identified the organic matter (OM) and the ratio of calcite content to OM content (Rt) as the main two parameters governing isoproturon retention in soils. While organic matter favored pesticide sorption, calcite had an antagonistic effect since it limited isoproturon retention. The Rt ratio of calcite content to organic matter content in soils appeared to be a parameter that should be considered in predictive models in addition to OM in regions presenting calcareous soils. Adsorption of isoproturon as a function of Rt and OM was successfully described through a simple empirical model. Copyright © 2012 Elsevier B.V. All rights reserved.

Measurement of soy contents in ground beef using near-infrared spectroscopy

USDA-ARS?s Scientific Manuscript database

Models for determining contents of soy products in ground beef were developed using near-infrared (NIR) spectroscopy. Samples were prepared by mixing four kinds of soybean protein products (Arconet, toasted soy grits, Profam and textured vegetable protein (TVP)) with ground beef (content from 0%–100...

Content and Knowledge Management in a Digital Library and Museum.

ERIC Educational Resources Information Center

Yeh, Jian-Hua; Chang, Jia-Yang; Oyang, Yen-Jen

2000-01-01

Discusses the design of the National Taiwan University Digital Library and Museum that addresses both content and knowledge management. Describes a two-tier repository architecture that facilitates content management, includes an object-oriented model to facilitate the management of temporal information, and eliminates the need to manually…

Technological Pedagogical Content Knowledge of Secondary Mathematics Teachers

ERIC Educational Resources Information Center

Handal, Boris; Campbell, Chris; Cavanagh, Michael; Petocz, Peter; Kelly, Nick

2013-01-01

The integration of technology, pedagogy, and content in the teaching of secondary mathematics was explored among 280 secondary mathematics teachers in the State of New South Wales, Australia. The study adopted the technological pedagogical content knowledge (TPCK) model through the administration of a 30-item instrument called TPCK-M. The…

Project CAPABLE: Model Unit.

ERIC Educational Resources Information Center

Madawaska School District, ME.

Project CAPABLE (Classroom Action Program: Aim: Basic Learning Effectiveness) is a classroom approach which integrates the basic learning skills with content. The goal of the project is to use basic learning skills to enhance the learning of content and at the same time use the content to teach basic learning skills. This manual illustrates how…

An Integrated Developmental Model for Studying Identity Content in Context

ERIC Educational Resources Information Center

Galliher, Renee V.; McLean, Kate C.; Syed, Moin

2017-01-01

Historically, identity researchers have placed greater emphasis on processes of identity development ("how" people develop their identities) and less on the content of identity ("what" the identity is). The relative neglect of identity content may reflect the lack of a comprehensive framework to guide research. In this article,…

E-Content: Opportunity and Risk

ERIC Educational Resources Information Center

Waggener, Shel

2012-01-01

For years people have seen scholarly journals shift from paper to electronic versions. Today the e-reader platforms are improving at a rapid rate, prices for devices are plummeting, the e-content is becoming richer and more interactive, and the content publishers are developing capitalistic business models to respond to this disruptive technology.…

Influence of Constructivist Professional Development on Chemistry Content Knowledge and Scientific Model Development

ERIC Educational Resources Information Center

Khourey-Bowers, Claudia; Fenk, Christopher

2009-01-01

The purpose of this study was to explore the relationship between teachers' (N = 69) participation in constructivist chemistry professional development (PD) and enhancement of content (CK) and pedagogical content knowledge (PCK) (representational thinking and conceptual change strategies) and self-efficacy (PSTE). Quantitative measures assessed…

An Experimental Study on the Iso-Content-Based Angle Similarity Measure.

ERIC Educational Resources Information Center

Zhang, Jin; Rasmussen, Edie M.

2002-01-01

Retrieval performance of the iso-content-based angle similarity measure within the angle, distance, conjunction, disjunction, and ellipse retrieval models is compared with retrieval performance of the distance similarity measure and the angle similarity measure. Results show the iso-content-based angle similarity measure achieves satisfactory…

A Portal of Educational Resources: Providing Evidence for Matching Pedagogy with Technology

ERIC Educational Resources Information Center

Di Blas, Nicoletta; Fiore, Alessandro; Mainetti, Luca; Vergallo, Roberto; Paolini, Paolo

2014-01-01

The TPACK (Technology, Pedagogy and Content Knowledge) model presents the three types of knowledge that are necessary to implement a successful technology-based educational activity. It highlights how the intersections between TPK (Technological Pedagogical Knowledge), PCK (Pedagogical Content Knowledge) and TCK (Technological Content Knowledge)…

Examination of Mathematics Teachers' Pedagogical Content Knowledge of Probability

ERIC Educational Resources Information Center

Danisman, Sahin; Tanisli, Dilek

2017-01-01

The aim of this study is to explore the probability-related pedagogical content knowledge (PCK) of secondary school mathematics teachers in terms of content knowledge, curriculum knowledge, student knowledge, and knowledge of teaching methods and strategies. Case study design, a qualitative research model, was used in the study, and the…

Combination of multiple model population analysis and mid-infrared technology for the estimation of copper content in Tegillarca granosa

NASA Astrophysics Data System (ADS)

Hu, Meng-Han; Chen, Xiao-Jing; Ye, Peng-Chao; Chen, Xi; Shi, Yi-Jian; Zhai, Guang-Tao; Yang, Xiao-Kang

2016-11-01

The aim of this study was to use mid-infrared spectroscopy coupled with multiple model population analysis based on Monte Carlo-uninformative variable elimination for rapidly estimating the copper content of Tegillarca granosa. Copper-specific wavelengths were first extracted from the whole spectra, and subsequently, a least square-support vector machine was used to develop the prediction models. Compared with the prediction model based on full wavelengths, models that used 100 multiple MC-UVE selected wavelengths without and with bin operation showed comparable performances with Rp (root mean square error of Prediction) of 0.97 (14.60 mg/kg) and 0.94 (20.85 mg/kg) versus 0.96 (17.27 mg/kg), as well as ratio of percent deviation (number of wavelength) of 2.77 (407) and 1.84 (45) versus 2.32 (1762). The obtained results demonstrated that the mid-infrared technique could be used for estimating copper content in T. granosa. In addition, the proposed multiple model population analysis can eliminate uninformative, weakly informative and interfering wavelengths effectively, that substantially reduced the model complexity and computation time.

Integrating remote sensing and GIS for prediction of winter wheat (Triticum aestivum) protein contents in Linfen (Shanxi), China.

PubMed

Feng, Mei-chen; Xiao, Lu-jie; Zhang, Mei-jun; Yang, Wu-de; Ding, Guang-wei

2014-01-01

In this study, relationships between normalized difference vegetation index (NDVI) and plant (winter wheat) nitrogen content (PNC) and between PNC and grain protein content (GPC) were investigated using multi-temporal moderate-resolution imaging spectroradiometer (MODIS) data at the different stages of winter wheat in Linfen (Shanxi, P. R. China). The anticipating model for GPC of winter wheat was also established by the approach of NDVI at the different stages of winter wheat. The results showed that the spectrum models of PNC passed F test. The NDVI4.14 regression effect of PNC model of irrigated winter wheat was the best, and that in dry land was NDVI4.30. The PNC of irrigated and dry land winter wheat were significantly (P<0.01) and positively correlated to GPC. Both of protein spectral anticipating model of irrigated and dry land winter wheat passed a significance test (P<0.01). Multiple anticipating models (MAM) were established by NDVI from two periods of irrigated and dry land winter wheat and PNC to link GPC anticipating model. The coefficient of determination R(2) (R) of MAM was greater than that of the other two single-factor models. The relative root mean square error (RRMSE) and relative error (RE) of MAM were lower than those of the other two single-factor models. Therefore, test effects of multiple proteins anticipating model were better than those of single-factor models. The application of multiple anticipating models for predication of protein content (PC) of irrigated and dry land winter wheat was more accurate and reliable. The regionalization analysis of GPC was performed using inverse distance weighted function of GIS, which is likely to provide the scientific basis for the reasonable winter wheat planting in Linfen city, China.

Integrating Remote Sensing and GIS for Prediction of Winter Wheat (Triticum aestivum) Protein Contents in Linfen (Shanxi), China

PubMed Central

Feng, Mei-chen; Xiao, Lu-jie; Zhang, Mei-jun; Yang, Wu-de; Ding, Guang-wei

2014-01-01

In this study, relationships between normalized difference vegetation index (NDVI) and plant (winter wheat) nitrogen content (PNC) and between PNC and grain protein content (GPC) were investigated using multi-temporal moderate-resolution imaging spectroradiometer (MODIS) data at the different stages of winter wheat in Linfen (Shanxi, P. R. China). The anticipating model for GPC of winter wheat was also established by the approach of NDVI at the different stages of winter wheat. The results showed that the spectrum models of PNC passed F test. The NDVI4.14 regression effect of PNC model of irrigated winter wheat was the best, and that in dry land was NDVI4.30. The PNC of irrigated and dry land winter wheat were significantly (P<0.01) and positively correlated to GPC. Both of protein spectral anticipating model of irrigated and dry land winter wheat passed a significance test (P<0.01). Multiple anticipating models (MAM) were established by NDVI from two periods of irrigated and dry land winter wheat and PNC to link GPC anticipating model. The coefficient of determination R2 (R) of MAM was greater than that of the other two single-factor models. The relative root mean square error (RRMSE) and relative error (RE) of MAM were lower than those of the other two single-factor models. Therefore, test effects of multiple proteins anticipating model were better than those of single-factor models. The application of multiple anticipating models for predication of protein content (PC) of irrigated and dry land winter wheat was more accurate and reliable. The regionalization analysis of GPC was performed using inverse distance weighted function of GIS, which is likely to provide the scientific basis for the reasonable winter wheat planting in Linfen city, China. PMID:24404124

Validity of Multiprocess IRT Models for Separating Content and Response Styles

ERIC Educational Resources Information Center

Plieninger, Hansjörg; Meiser, Thorsten

2014-01-01

Response styles, the tendency to respond to Likert-type items irrespective of content, are a widely known threat to the reliability and validity of self-report measures. However, it is still debated how to measure and control for response styles such as extreme responding. Recently, multiprocess item response theory models have been proposed that…

Auto Body. Instructional System Development Model for Vermont Area Vocational Centers.

ERIC Educational Resources Information Center

1975

The model curriculum guide was developed to teach auto body repair in secondary schools in Vermont. From a needs assessment of the occupational opportunities in automotive services in the state, a group of selected occupations were analyzed for skill content and translated into the curriculum content. The guide consists of 14 units, each with a…

A Technological Pedagogical Content Knowledge Based Instructional Design Model: A Third Version Implementation Study in a Technology Integration Course

ERIC Educational Resources Information Center

Lee, Chia-Jung; Kim, ChanMin

2017-01-01

This paper presents the third version of a technological pedagogical content knowledge (TPACK) based instructional design model that incorporates the distinctive, transformative, and integrative views of TPACK into a comprehensive actionable framework. Strategies of relating TPACK domains to real-life learning experiences, role-playing, and…

Examining the Relationship between Technological Pedagogical Content Knowledge (TPACK) and Student Achievement Utilizing the Florida Value-Added Model

ERIC Educational Resources Information Center

Farrell, Ivan K.; Hamed, Kastro M.

2017-01-01

Utilizing a correlational research design, we sought to examine the relationship between the technological pedagogical content knowledge (TPACK) of in-service teachers and student achievement measured with each individual teacher's Value-Added Model (VAM) score. The TPACK survey results and a teacher's VAM score were also examined, separately,…

Focusing on Interactions between Content and Cognition: A New Perspective on Gender Differences in Mathematical Sub-Competencies

ERIC Educational Resources Information Center

George, Ann Cathrice; Robitzsch, Alexander

2018-01-01

This article presents a new perspective on measuring gender differences in the large-scale assessment study Trends in International Science Study (TIMSS). The suggested empirical model is directly based on the theoretical competence model of the domain mathematics and thus includes the interaction between content and cognitive sub-competencies.…

Designing a Knowledge Representation Approach for the Generation of Pedagogical Interventions by MTTs

ERIC Educational Resources Information Center

Paquette, Luc; Lebeau, Jean-François; Beaulieu, Gabriel; Mayers, André

2015-01-01

Model-tracing tutors (MTTs) have proven effective for the tutoring of well-defined tasks, but the pedagogical interventions they produce are limited and usually require the inclusion of pedagogical content, such as text message templates, in the model of the task. The capability to generate pedagogical content would be beneficial to MTT…

An Interdisciplinary Inservice Model for Teaching Reading in the Content Areas: Grades 7-9.

ERIC Educational Resources Information Center

Granite School District, Salt Lake City, UT.

The model outlined in this document describes the development of an integrated approach to teaching content reading skills to teachers. Methods and materials applicable to texts and media currently used in classrooms were produced by inservice teachers of science, math, and social studies at a Salt Lake City junior high school. This document…

Colorado Model Content Standards: Science

ERIC Educational Resources Information Center

Colorado Department of Education, 2007

2007-01-01

The Colorado Model Content Standards for Science specify what all students should know and be able to do in science as a result of their school studies. Specific expectations are given for students completing grades K-2, 3-5, 6-8, and 9-12. Five standards outline the essential level of science knowledge and skills needed by Colorado citizens to…

Variations on a Theme: As Needs Change, New Models of Critical Friends Groups Emerge

ERIC Educational Resources Information Center

Fahey, Kevin; Ippolito, Jacy

2015-01-01

The Critical Friends Group, a highly articulated model of professional learning, posits that, in order for teachers to learn together in ways that change their practice, the content and nature of their conversations must change (National School Reform Faculty, 2012). The content needs to change from externally driven agendas that address (in a…

Integrating Computer Content into Social Work Curricula: A Model for Planning

ERIC Educational Resources Information Center

Beaulaurier, Richard L.

2005-01-01

While recent CSWE standards focus on the need for including more relevant technological content in social work curricula, they do not offer guidance regarding how it is to be assessed and selected. Social work educators are in need of an analytic model of computerization to help them understand which technologies are most appropriate and relevant…

Storage stability and improvement of intermediate moisture foods

NASA Technical Reports Server (NTRS)

Labuza, T. P.

1973-01-01

The rates of chemical reactions which deteriorate foods prepared to an intermediate moisture content and water activity (A sub w 0.6 to 0.9) were studied. The phenomenon of sorption hysteresis was used to prepare model systems and foods to similar A sub w's but different moisture levels so that the separate effects of water binding and water content could be elucidated. It was found that water content is the controlling factor for lipid oxidation in model systems comprised of a solid support and an oxidizable liquid. It was proposed that metal chelating agents like EDTA should give good protection to oxidation. EDTA exhibited the highest efficacy, about 10-15 times better than BHA which is a radical scavenger when studied in the model systems.

Should students design or interact with models? Using the Bifocal Modelling Framework to investigate model construction in high school science

NASA Astrophysics Data System (ADS)

Fuhrmann, Tamar; Schneider, Bertrand; Blikstein, Paulo

2018-05-01

The Bifocal Modelling Framework (BMF) is an approach for science learning which links students' physical experimentation with computer modelling in real time, focusing on the comparison of the two media. In this paper, we explore how a Bifocal Modelling implementation supported learning outcomes related to both content and metamodeling knowledge, focusing on the role of designing models. Our study consisted of three conditions implemented with a total of 69 9th grade high-school students. The first and second classes were assigned two implementation modes of BMF: with and without a model design module. The third condition, employed as a control, consisted of a class that received instruction in the school's traditional approach. Our results indicate that students participating in both BMF implementations demonstrated improved content knowledge and a better understanding of metamodeling. However, only the 'BMF-with-design' group improved significantly in both content and metamodeling knowledge. Our qualitative analyses indicate that both BMF groups designed detailed models that included scientific explanations. However only students who engaged in the model design component: (1) completed a detailed model displaying molecular interaction; and (2) developed a critical perspective about models. We discuss the implications of those results for teaching scientific science concepts and metamodeling knowledge.

Moisture sorption isotherms and thermodynamic properties of mexican mennonite-style cheese.

PubMed

Martinez-Monteagudo, Sergio I; Salais-Fierro, Fabiola

2014-10-01

Moisture adsorption isotherms of fresh and ripened Mexican Mennonite-style cheese were investigated using the static gravimetric method at 4, 8, and 12 °C in a water activity range (aw) of 0.08-0.96. These isotherms were modeled using GAB, BET, Oswin and Halsey equations through weighed non-linear regression. All isotherms were sigmoid in shape, showing a type II BET isotherm, and the data were best described by GAB model. GAB model coefficients revealed that water adsorption by cheese matrix is a multilayer process characterized by molecules that are strongly bound in the monolayer and molecules that are slightly structured in a multilayer. Using the GAB model, it was possible to estimate thermodynamic functions (net isosteric heat, differential entropy, integral enthalpy and entropy, and enthalpy-entropy compensation) as function of moisture content. For both samples, the isosteric heat and differential entropy decreased with moisture content in exponential fashion. The integral enthalpy gradually decreased with increasing moisture content after reached a maximum value, while the integral entropy decreased with increasing moisture content after reached a minimum value. A linear compensation was found between integral enthalpy and entropy suggesting enthalpy controlled adsorption. Determination of moisture content and aw relationship yields to important information of controlling the ripening, drying and storage operations as well as understanding of the water state within a cheese matrix.

Optimization and modeling of reduction of wastewater sludge water content and turbidity removal using magnetic iron oxide nanoparticles (MION).

PubMed

Hwang, Jeong-Ha; Han, Dong-Woo

2015-01-01

Economic and rapid reduction of sludge water content in sewage wastewater is difficult and requires special advanced treatment technologies. This study focused on optimizing and modeling decreased sludge water content (Y1) and removing turbidity (Y2) with magnetic iron oxide nanoparticles (Fe3O4, MION) using a central composite design (CCD) and response surface methodology (RSM). CCD and RSM were applied to evaluate and optimize the interactive effects of mixing time (X1) and MION concentration (X2) on chemical flocculent performance. The results show that the optimum conditions were 14.1 min and 22.1 mg L(-1) for response Y1 and 16.8 min and 8.85 mg L(-1) for response Y2, respectively. The two responses were obtained experimentally under this optimal scheme and fit the model predictions well (R(2) = 97.2% for Y1 and R(2) = 96.9% for Y2). A 90.8% decrease in sludge water content and turbidity removal of 29.4% were demonstrated. These results confirm that the statistical models were reliable, and that the magnetic flocculation conditions for decreasing sludge water content and removing turbidity from sewage wastewater were appropriate. The results reveal that MION are efficient for rapid separation and are a suitable alterative to sediment sludge during the wastewater treatment process.

Adaptive observer-based control for an IPMC actuator under varying humidity conditions

NASA Astrophysics Data System (ADS)

Bernat, Jakub; Kolota, Jakub

2018-05-01

As ionic polymer metal composites (IPMC) are increasingly applied to mechatronic systems, many new IPMC modeling efforts have been reported in the literature. The demands of rapidly growing technology has generated interest in advancing the intrinsic actuation and sensing capabilities of IPMC. Classical IPMC applications need constant hydration to operate. On the other hand, for IPMCs operating in air, the water content of the polymer varies with the humidity level of the ambient environment, which leads to its strong humidity-dependent behavior. Furthermore, decreasing water content over time plays a crucial role in the effectiveness of IPMC. Therefore, the primary challenge of this work is to accurately model this phenomenon. The principal contribution of the paper is a new IPMC model, which considers the change of moisture content. A novel nonlinear adaptive observer is designed to determine the unknown electric potential and humidity level in the polymer membrane. This approach effectively determines the moisture content of the IPMC during long-term continuous operation in air. This subsequently allows us to develop an effective back-stepping control algorithm that considers varying moisture content. Data from experiments are presented to support the effectiveness of the observation process, which is shown in illustrative examples.

Modeling and optimization of phospholipase A₁-catalyzed hydrolysis of phosphatidylcholine using response surface methodology for lysophosphatidylcholine production.

PubMed

Lim, Chang Wan; Kim, Byung Hee; Kim, In-Hwan; Lee, Moon-Won

2015-01-01

Modeling the phospholipase A1 (PLA1 )-catalyzed partial hydrolysis of soy phosphatidylcholine (PC) in hexane for the production of lysophosphatidylcholine (LPC) and optimizing the reaction conditions using response surface methodology were described. The reaction was performed with 4 g of PC in a stirred batch reactor using a commercial PLA1 (Lecitase Ultra) as the biocatalyst. The effects of temperature, reaction time, water content, and enzyme loading on LPC and glycerylphosphorylcholine (GPC) content in the reaction products were elucidated using the models established. Optimal reaction conditions for maximizing the LPC content while suppressing acyl migration, which causes GPC formation, were as follows: temperature, 60°C; reaction time, 3 h; water content, 10% of PC; and enzyme loading, 1% of PC. When the reaction was conducted with 40 g of PC under these conditions, the reaction products contained 83.7 mol % LPC and were free of GPC. LPC had a higher total unsaturated fatty acid content than original PC had and was mainly composed of linoleic acid (78.0 mol % of the total fatty acids). © 2014 American Institute of Chemical Engineers.

Linear Regression between CIE-Lab Color Parameters and Organic Matter in Soils of Tea Plantations

NASA Astrophysics Data System (ADS)

Chen, Yonggen; Zhang, Min; Fan, Dongmei; Fan, Kai; Wang, Xiaochang

2018-02-01

To quantify the relationship between the soil organic matter and color parameters using the CIE-Lab system, 62 soil samples (0-10 cm, Ferralic Acrisols) from tea plantations were collected from southern China. After air-drying and sieving, numerical color information and reflectance spectra of soil samples were measured under laboratory conditions using an UltraScan VIS (HunterLab) spectrophotometer equipped with CIE-Lab color models. We found that soil total organic carbon (TOC) and nitrogen (TN) contents were negatively correlated with the L* value (lightness) ( r = -0.84 and -0.80, respectively), a* value (correlation coefficient r = -0.51 and -0.46, respectively) and b* value ( r = -0.76 and -0.70, respectively). There were also linear regressions between TOC and TN contents with the L* value and b* value. Results showed that color parameters from a spectrophotometer equipped with CIE-Lab color models can predict TOC contents well for soils in tea plantations. The linear regression model between color values and soil organic carbon contents showed it can be used as a rapid, cost-effective method to evaluate content of soil organic matter in Chinese tea plantations.

[Effects of extracts from ziziphi spinosae semen and schisandrae chinensis fructus on amino acid neurotransmitter in rats with insomnia induced by PCPA].

PubMed

Gao, Jia-Rong; Ji, Wen-Bo; Jiang, Hui; Chen, Jin-Feng

2013-10-01

To observe the effects of extract from Ziziphus Spinosa Semen and Schisandrae Chinensis Fructus on the content of amino acid neurotransmitter in the hypothalamus of insomnia rats induced by P-Chlorophenylalanine (PCPA) and its mechanism. The model of insomnia rats were established by PCPA intraperitoneal injection, after the modeling, all the therapeutic group were treated with corresponding drug for one week. The hypothalamus pathological changes of the rats were observed. The contents of GABA, Glu in the hypothalamus were detected by Elisa. The GABA, Glu protein expression were detected by immunohistochemical. GABA(A), R(alpha1) and GABA(A)R(gamma2) mRNA expressions were detected by RT-PCR. Compared with model group, the content of GABA in the hypothalamus of rats increased obviously in the alcohol-water group (P < 0.05 or P < 0.01), while the content of Glu decreased obviously (P < 0.05 or P < 0.01). The extract from Ziziphus Spinosae Semen and Schisandrae Chinensis Fructus has obviously Sedative-hypnotic effect. Its mechanism may be related to regulating the content of amino acid neurotransmitter in the hypothalamus of rats.

Viscosity and Structure of CaO-SiO2-P2O5-FetO System with Varying P2O5 and FeO Content

NASA Astrophysics Data System (ADS)

Diao, Jiang; Gu, Pan; Liu, De-Man; Jiang, Lu; Wang, Cong; Xie, Bing

2017-10-01

A rotary viscosimeter and Raman spectrum were employed to measure the viscosity and structural information of the CaO-SiO2-P2O5-FetO system at 1673 K. The experimental data have been compared with the calculated results using different viscosity models. It shows that the National Physical Laboratory (NPL) and Pal models fit the CaO-SiO2-P2O5-FeOt system better. With the P2O5 content increasing from 5% to 14%, the viscosity increases from 0.12 Pa s to 0.27 Pa s. With the FeO content increasing from 30% to 40%, the viscosity decreases from 0.21 Pa s to 0.12 Pa s. Increasing FeO content makes the complicated molten melts become simple, and increasing P2O5 content will complicate the molten melts. The linear relation between viscosity and structure parameter Q(Si + P) was obtained by regression analysis. The calculated viscosity by using the optimized NPL and Pal model are almost identical with the fitted values.

Use of the Rasch Measurement Model to Explore the Relationship between Content Knowledge and Topic-Specific Pedagogical Content Knowledge for Organic Chemistry

ERIC Educational Resources Information Center

Davidowitz, Bette; Potgieter, Marietjie

2016-01-01

Research has shown that a high level of content knowledge (CK) is necessary but not sufficient to develop the special knowledge base of expert teachers known as pedagogical content knowledge (PCK). This study contributes towards research to quantify the relationship between CK and PCK in science. In order to determine the proportion of the…

Predictive relationship between polyphenol and nonfat cocoa solids content of chocolate.

PubMed

Cooper, Karen A; Campos-Giménez, Esther; Jiménez Alvarez, Diego; Rytz, Andreas; Nagy, Kornél; Williamson, Gary

2008-01-09

Chocolate is often labeled with percent cocoa solids content. It is assumed that higher cocoa solids contents are indicative of higher polyphenol concentrations, which have potential health benefits. However, cocoa solids include polyphenol-free cocoa butter and polyphenol-rich nonfat cocoa solids (NFCS). In this study the strength of the relationship between NFCS content (estimated by theobromine as a proxy) and polyphenol content was tested in chocolate samples with labeled cocoa solids contents in the range of 20-100%, grouped as dark (n = 46), milk (n = 8), and those chocolates containing inclusions such as wafers or nuts (n = 15). The relationship was calculated with regard to both total polyphenol content and individual polyphenols. In dark chocolates, NFCS is linearly related to total polyphenols (r2 = 0.73). Total polyphenol content appears to be systematically slightly higher for milk chocolates than estimated by the dark chocolate model, whereas for chocolates containing other ingredients, the estimates fall close to or slightly below the model results. This shows that extra components such as milk, wafers, or nuts might influence the measurements of both theobromine and polyphenol contents. For each of the six main polyphenols (as well as their sum), the relationship with the estimated NFCS was much lower than for total polyphenols (r2 < 0.40), but these relationships were independent of the nature of the chocolate type, indicating that they might still have some predictive capabilities.

Epidemic models for phase transitions: application to a physical gel

NASA Astrophysics Data System (ADS)

Bilge, A. H.; Pekcan, O.; Kara, S.; Ogrenci, A. S.

2017-09-01

Carrageenan gels are characterized by reversible sol-gel and gel-sol transitions under cooling and heating processes and these transitions are approximated by generalized logistic growth curves. We express the transitions of carrageenan-water system, as a representative of reversible physical gels, in terms of a modified Susceptible-Infected-Susceptible epidemic model, as opposed to the Susceptible-Infected-Removed model used to represent the (irreversible) chemical gel formation in the previous work. We locate the gel point Tc of sol-gel and gel-sol transitions and we find that, for the sol-gel transition (cooling), Tc > Tsg (transition temperature), i.e. Tc is earlier in time for all carrageenan contents and moves forward in time and gets closer to Tsg as the carrageenan content increases. For the gel-sol transition (heating), Tc is relatively closer to Tgs; it is greater than Tgs, i.e. later in time for low carrageenan contents and moves backward as carrageenan content increases.

Prediction of sweetness and amino acid content in soybean crops from hyperspectral imagery

NASA Astrophysics Data System (ADS)

Monteiro, Sildomar Takahashi; Minekawa, Yohei; Kosugi, Yukio; Akazawa, Tsuneya; Oda, Kunio

Hyperspectral image data provides a powerful tool for non-destructive crop analysis. This paper investigates a hyperspectral image data-processing method to predict the sweetness and amino acid content of soybean crops. Regression models based on artificial neural networks were developed in order to calculate the level of sucrose, glucose, fructose, and nitrogen concentrations, which can be related to the sweetness and amino acid content of vegetables. A performance analysis was conducted comparing regression models obtained using different preprocessing methods, namely, raw reflectance, second derivative, and principal components analysis. This method is demonstrated using high-resolution hyperspectral data of wavelengths ranging from the visible to the near infrared acquired from an experimental field of green vegetable soybeans. The best predictions were achieved using a nonlinear regression model of the second derivative transformed dataset. Glucose could be predicted with greater accuracy, followed by sucrose, fructose and nitrogen. The proposed method provides the possibility to provide relatively accurate maps predicting the chemical content of soybean crop fields.

Plant–herbivore–decomposer stoichiometric mismatches and nutrient cycling in ecosystems

PubMed Central

Cherif, Mehdi; Loreau, Michel

2013-01-01

Plant stoichiometry is thought to have a major influence on how herbivores affect nutrient availability in ecosystems. Most conceptual models predict that plants with high nutrient contents increase nutrient excretion by herbivores, in turn raising nutrient availability. To test this hypothesis, we built a stoichiometrically explicit model that includes a simple but thorough description of the processes of herbivory and decomposition. Our results challenge traditional views of herbivore impacts on nutrient availability in many ways. They show that the relationship between plant nutrient content and the impact of herbivores predicted by conceptual models holds only at high plant nutrient contents. At low plant nutrient contents, the impact of herbivores is mediated by the mineralization/immobilization of nutrients by decomposers and by the type of resource limiting the growth of decomposers. Both parameters are functions of the mismatch between plant and decomposer stoichiometries. Our work provides new predictions about the impacts of herbivores on ecosystem fertility that depend on critical interactions between plant, herbivore and decomposer stoichiometries in ecosystems. PMID:23303537

Comparison of animal discs used in disc research to human lumbar disc: torsion mechanics and collagen content.

PubMed

Showalter, Brent L; Beckstein, Jesse C; Martin, John T; Beattie, Elizabeth E; Espinoza Orías, Alejandro A; Schaer, Thomas P; Vresilovic, Edward J; Elliott, Dawn M

2012-07-01

Experimental measurement and normalization of in vitro disc torsion mechanics and collagen content for several animal species used in intervertebral disc research and comparing these with the human disc. To aid in the selection of appropriate animal models for disc research by measuring torsional mechanical properties and collagen content. There is lack of data and variability in testing protocols for comparing animal and human disc torsion mechanics and collagen content. Intervertebral disc torsion mechanics were measured and normalized by disc height and polar moment of inertia for 11 disc types in 8 mammalian species: the calf, pig, baboon, goat, sheep, rabbit, rat, and mouse lumbar discs, and cow, rat, and mouse caudal discs. Collagen content was measured and normalized by dry weight for the same discs except the rat and the mouse. Collagen fiber stretch in torsion was calculated using an analytical model. Measured torsion parameters varied by several orders of magnitude across the different species. After geometric normalization, only the sheep and pig discs were statistically different from human discs. Fiber stretch was found to be highly dependent on the assumed initial fiber angle. The collagen content of the discs was similar, especially in the outer annulus where only the calf and goat discs were statistically different from human. Disc collagen content did not correlate with torsion mechanics. Disc torsion mechanics are comparable with human lumbar discs in 9 of 11 disc types after normalization by geometry. The normalized torsion mechanics and collagen content of the multiple animal discs presented are useful for selecting and interpreting results for animal disc models. Structural organization of the fiber angle may explain the differences that were noted between species after geometric normalization.

Error Analysis of Clay-Rock Water Content Estimation with Broadband High-Frequency Electromagnetic Sensors—Air Gap Effect

PubMed Central

Bore, Thierry; Wagner, Norman; Delepine Lesoille, Sylvie; Taillade, Frederic; Six, Gonzague; Daout, Franck; Placko, Dominique

2016-01-01

Broadband electromagnetic frequency or time domain sensor techniques present high potential for quantitative water content monitoring in porous media. Prior to in situ application, the impact of the relationship between the broadband electromagnetic properties of the porous material (clay-rock) and the water content on the frequency or time domain sensor response is required. For this purpose, dielectric properties of intact clay rock samples experimental determined in the frequency range from 1 MHz to 10 GHz were used as input data in 3-D numerical frequency domain finite element field calculations to model the one port broadband frequency or time domain transfer function for a three rods based sensor embedded in the clay-rock. The sensor response in terms of the reflection factor was analyzed in time domain with classical travel time analysis in combination with an empirical model according to Topp equation, as well as the theoretical Lichtenecker and Rother model (LRM) to estimate the volumetric water content. The mixture equation considering the appropriate porosity of the investigated material provide a practical and efficient approach for water content estimation based on classical travel time analysis with the onset-method. The inflection method is not recommended for water content estimation in electrical dispersive and absorptive material. Moreover, the results clearly indicate that effects due to coupling of the sensor to the material cannot be neglected. Coupling problems caused by an air gap lead to dramatic effects on water content estimation, even for submillimeter gaps. Thus, the quantitative determination of the in situ water content requires careful sensor installation in order to reach a perfect probe clay rock coupling. PMID:27096865

Comparison of Animal Discs Used in Disc Research to Human Lumbar Disc: Torsion Mechanics and Collagen Content

PubMed Central

Showalter, Brent L.; Beckstein, Jesse C.; Martin, John T.; Beattie, Elizabeth E.; Orías, Alejandro A. Espinoza; Schaer, Thomas P.; Vresilovic, Edward J.; Elliott, Dawn M.

2012-01-01

Study Design Experimental measurement and normalization of in vitro disc torsion mechanics and collagen content for several animal species used in intervertebral disc research and comparing these to the human disc. Objective To aid in the selection of appropriate animal models for disc research by measuring torsional mechanical properties and collagen content. Summary of Background Data There is lack of data and variability in testing protocols for comparing animal and human disc torsion mechanics and collagen content. Methods Intervertebral disc torsion mechanics were measured and normalized by disc height and polar moment of inertia for 11 disc types in 8 mammalian species: the calf, pig, baboon, goat, sheep, rabbit, rat, and mouse lumbar, and cow, rat, and mouse caudal. Collagen content was measured and normalized by dry weight for the same discs except the rat and mouse. Collagen fiber stretch in torsion was calculated using an analytical model. Results Measured torsion parameters varied by several orders of magnitude across the different species. After geometric normalization, only the sheep and pig discs were statistically different from human. Fiber stretch was found to be highly dependent on the assumed initial fiber angle. The collagen content of the discs was similar, especially in the outer annulus where only the calf and goat discs were statistically different from human. Disc collagen content did not correlate with torsion mechanics. Conclusion Disc torsion mechanics are comparable to human lumbar discs in 9 of 11 disc types after normalization by geometry. The normalized torsion mechanics and collagen content of the multiple animal discs presented is useful for selecting and interpreting results for animal models of the disc. Structural composition of the disc, such as initial fiber angle, may explain the differences that were noted between species after geometric normalization. PMID:22333953

Error Analysis of Clay-Rock Water Content Estimation with Broadband High-Frequency Electromagnetic Sensors--Air Gap Effect.

PubMed

Bore, Thierry; Wagner, Norman; Lesoille, Sylvie Delepine; Taillade, Frederic; Six, Gonzague; Daout, Franck; Placko, Dominique

2016-04-18

Broadband electromagnetic frequency or time domain sensor techniques present high potential for quantitative water content monitoring in porous media. Prior to in situ application, the impact of the relationship between the broadband electromagnetic properties of the porous material (clay-rock) and the water content on the frequency or time domain sensor response is required. For this purpose, dielectric properties of intact clay rock samples experimental determined in the frequency range from 1 MHz to 10 GHz were used as input data in 3-D numerical frequency domain finite element field calculations to model the one port broadband frequency or time domain transfer function for a three rods based sensor embedded in the clay-rock. The sensor response in terms of the reflection factor was analyzed in time domain with classical travel time analysis in combination with an empirical model according to Topp equation, as well as the theoretical Lichtenecker and Rother model (LRM) to estimate the volumetric water content. The mixture equation considering the appropriate porosity of the investigated material provide a practical and efficient approach for water content estimation based on classical travel time analysis with the onset-method. The inflection method is not recommended for water content estimation in electrical dispersive and absorptive material. Moreover, the results clearly indicate that effects due to coupling of the sensor to the material cannot be neglected. Coupling problems caused by an air gap lead to dramatic effects on water content estimation, even for submillimeter gaps. Thus, the quantitative determination of the in situ water content requires careful sensor installation in order to reach a perfect probe clay rock coupling.

A multivariate mixed model system for wood specific gravity and moisture content of planted loblolly pine stands in the southern United States

Treesearch

Finto Antony; Laurence R. Schimleck; Alex Clark; Richard F. Daniels

2012-01-01

Specific gravity (SG) and moisture content (MC) both have a strong influence on the quantity and quality of wood fiber. We proposed a multivariate mixed model system to model the two properties simultaneously. Disk SG and MC at different height levels were measured from 3 trees in 135 stands across the natural range of loblolly pine and the stand level values were used...

Innovative learning model for improving students’ argumentation skill and concept understanding on science

NASA Astrophysics Data System (ADS)

Nafsiati Astuti, Rini

2018-04-01

Argumentation skill is the ability to compose and maintain arguments consisting of claims, supports for evidence, and strengthened-reasons. Argumentation is an important skill student needs to face the challenges of globalization in the 21st century. It is not an ability that can be developed by itself along with the physical development of human, but it must be developed under nerve like process, giving stimulus so as to require a person to be able to argue. Therefore, teachers should develop students’ skill of arguing in science learning in the classroom. The purpose of this study is to obtain an innovative learning model that are valid in terms of content and construct in improving the skills of argumentation and concept understanding of junior high school students. The assessment of content validity and construct validity was done through Focus Group Discussion (FGD), using the content and construct validation sheet, book model, learning video, and a set of learning aids for one meeting. Assessment results from 3 (three) experts showed that the learning model developed in the category was valid. The validity itself shows that the developed learning model has met the content requirement, the student needs, state of the art, strong theoretical and empirical foundation and construct validity, which has a connection of syntax stages and components of learning model so that it can be applied in the classroom activities

[Influence of Kudou Shencha decotion on INF-gamma, ICAM-1, MCP-1 levels of prostate tissue homogenate in immunity prostatitis model rats].

PubMed

Xia, Li-Ying; Liu, Wei-Jia; Li, Ming-Xi; Ge, Wen-Jin; Gao, Xue-Min; Zhang, Jian-Jun

2014-05-01

To investigate the influence of Kudou Shencha decotion on INF-y, ICAM-1, MCP-1 levels of prostate tissue homogenate in immunity prostatitis model rats. Forty Wistar male rats were divided into 5 groups randomly: Kudou Shencha decotion group with high dosage and low dosage, Qianleitai group, the model control group and normal group. The rat model of chronic nonbacterial prostatitis was established by multiple hypodermical injection of the suspension of prostatic protein purification with Freund's completed adjuvant. The level of intercellular adhesion molecule (ICAM-1), interferon gamma (INF-gamma) and monocyte chemotactic protein-1 (MCP-1) were measured by enzyme linked immunosorbent assay (ELISA). The content of ICAM-1 and MCP-1 in the model group was higher than that of the normal group (P < 0.05), the content of ICAM-1 was obviously decreased in Kudou Shencha decotion group with high dosage (P <0.05), the contents of MCP-1 were all obviously decreased in Kudou Shencha decotion groups and Qianlietai group. Compared with the model group, the contents of INF-gamma in all treatment groups were decreased insignificantly. Kudou Shencha decotion has the action of lowering the level of ICAM-1 and MCP-1, which may be one of the mechanisms of Kudou Shencha decotion in the therapy of chronic prostatitis.

Imaging Global Electron Content backwards in time more than 160 years ago

NASA Astrophysics Data System (ADS)

Gulyaeva, T. L.; Veselovsky, I. S.

2014-02-01

The Global Electron Content, GEC, represents the total number of electrons in the spherical layer over the Earth restricted by orbit of Global Positioning Satellite system (20,200 km). GEC is produced from Global Ionospheric Map of Total Electron Content, GIM-TEC, transformed to the electron density varying with height using the International Reference Ionosphere and Plasmasphere model, IRI-Plas. The climatologic GEC model is developed from GIM-TEC maps for a period 1999-2012 including the solar activity, annual and semiannual cycles as the most important factors affecting daily GEC variation. The proxy Rzp of the international sunspot numbers, Ri, is used as a measure of solar activity composed of 3 day smoothed Ri, 7 day and 81 day backwards mean of Ri scaled to the range of 1-40 proxy units, p.u. The root mean square error of the GEC climatologic model is found to vary from 8% to 13% of GEC. Taking advantage of a long history of sunspot numbers, the climatologic GEC model is applied for GEC reconstruction backwards in time for more than 160 years ago since 1850. The extended set of GEC values provides the numerical representation of the ionosphere and plasmasphere electron content coherent with variations of solar activity as a potential proxy index driving the ionosphere models.

Modeling the influence of snow cover temperature and water content on wet-snow avalanche runout

NASA Astrophysics Data System (ADS)

Valero, Cesar Vera; Wever, Nander; Christen, Marc; Bartelt, Perry

2018-03-01

Snow avalanche motion is strongly dependent on the temperature and water content of the snow cover. In this paper we use a snow cover model, driven by measured meteorological data, to set the initial and boundary conditions for wet-snow avalanche calculations. The snow cover model provides estimates of snow height, density, temperature and liquid water content. This information is used to prescribe fracture heights and erosion heights for an avalanche dynamics model. We compare simulated runout distances with observed avalanche deposition fields using a contingency table analysis. Our analysis of the simulations reveals a large variability in predicted runout for tracks with flat terraces and gradual slope transitions to the runout zone. Reliable estimates of avalanche mass (height and density) in the release and erosion zones are identified to be more important than an exact specification of temperature and water content. For wet-snow avalanches, this implies that the layers where meltwater accumulates in the release zone must be identified accurately as this defines the height of the fracture slab and therefore the release mass. Advanced thermomechanical models appear to be better suited to simulate wet-snow avalanche inundation areas than existing guideline procedures if and only if accurate snow cover information is available.

The Role of Content and Context in PISA Interest Scales: A study of the embedded interest items in the PISA 2006 science assessment

NASA Astrophysics Data System (ADS)

Drechsel, Barbara; Carstensen, Claus; Prenzel, Manfred

2011-01-01

This paper focuses interest in science as one of the attitudinal aspects of scientific literacy. Large-scale data from the Programme for International Student Assessment (PISA) 2006 are analysed in order to describe student interest more precisely. So far the analyses have provided a general indicator of interest, aggregated over all contexts and contents in the science test. With its innovative approach PISA embeds interest items within the cognitive test unit and its contents and contexts. The main difference from conventional interest measures is that in most questionnaires, a relatively small number of interest items cover broad fields of contents and contexts. The science units represent a number of systematically differentiated scientific contexts and contents. The units' stimulus texts allow for concrete descriptions of relevant content aspects, applications, and contexts. In the analyses, multidimensional item response models are applied in order to disentangle student interest. The results indicate that multidimensional models fit the data. A two-dimensional model separating interest into two different knowledge of science dimensions described in the PISA science framework is further analysed with respect to gender, performance differences, and country. The findings give a comprehensive description of students' interest in science. The paper deals with methodological problems and describes requirements of the test construction for further assessments. The results are discussed with regard to their significance for science education.

Event-related potentials in response to violations of content and temporal event knowledge.

PubMed

Drummer, Janna; van der Meer, Elke; Schaadt, Gesa

2016-01-08

Scripts that store knowledge of everyday events are fundamentally important for managing daily routines. Content event knowledge (i.e., knowledge about which events belong to a script) and temporal event knowledge (i.e., knowledge about the chronological order of events in a script) constitute qualitatively different forms of knowledge. However, there is limited information about each distinct process and the time course involved in accessing content and temporal event knowledge. Therefore, we analyzed event-related potentials (ERPs) in response to either correctly presented event sequences or event sequences that contained a content or temporal error. We found an N400, which was followed by a posteriorly distributed P600 in response to content errors in event sequences. By contrast, we did not find an N400 but an anteriorly distributed P600 in response to temporal errors in event sequences. Thus, the N400 seems to be elicited as a response to a general mismatch between an event and the established event model. We assume that the expectancy violation of content event knowledge, as indicated by the N400, induces the collapse of the established event model, a process indicated by the posterior P600. The expectancy violation of temporal event knowledge is assumed to induce an attempt to reorganize the event model in working memory, a process indicated by the frontal P600. Copyright © 2015 Elsevier Ltd. All rights reserved.

[Bayesian geostatistical prediction of soil organic carbon contents of solonchak soils in nor-thern Tarim Basin, Xinjiang, China.

PubMed

Wu, Wei Mo; Wang, Jia Qiang; Cao, Qi; Wu, Jia Ping

2017-02-01

Accurate prediction of soil organic carbon (SOC) distribution is crucial for soil resources utilization and conservation, climate change adaptation, and ecosystem health. In this study, we selected a 1300 m×1700 m solonchak sampling area in northern Tarim Basin, Xinjiang, China, and collected a total of 144 soil samples (5-10 cm). The objectives of this study were to build a Baye-sian geostatistical model to predict SOC content, and to assess the performance of the Bayesian model for the prediction of SOC content by comparing with other three geostatistical approaches [ordinary kriging (OK), sequential Gaussian simulation (SGS), and inverse distance weighting (IDW)]. In the study area, soil organic carbon contents ranged from 1.59 to 9.30 g·kg -1 with a mean of 4.36 g·kg -1 and a standard deviation of 1.62 g·kg -1 . Sample semivariogram was best fitted by an exponential model with the ratio of nugget to sill being 0.57. By using the Bayesian geostatistical approach, we generated the SOC content map, and obtained the prediction variance, upper 95% and lower 95% of SOC contents, which were then used to evaluate the prediction uncertainty. Bayesian geostatistical approach performed better than that of the OK, SGS and IDW, demonstrating the advantages of Bayesian approach in SOC prediction.

Evaluation of theoretical and empirical water vapor sorption isotherm models for soils

NASA Astrophysics Data System (ADS)

Arthur, Emmanuel; Tuller, Markus; Moldrup, Per; de Jonge, Lis W.

2016-01-01

The mathematical characterization of water vapor sorption isotherms of soils is crucial for modeling processes such as volatilization of pesticides and diffusive and convective water vapor transport. Although numerous physically based and empirical models were previously proposed to describe sorption isotherms of building materials, food, and other industrial products, knowledge about the applicability of these functions for soils is noticeably lacking. We present an evaluation of nine models for characterizing adsorption/desorption isotherms for a water activity range from 0.03 to 0.93 based on measured data of 207 soils with widely varying textures, organic carbon contents, and clay mineralogy. In addition, the potential applicability of the models for prediction of sorption isotherms from known clay content was investigated. While in general, all investigated models described measured adsorption and desorption isotherms reasonably well, distinct differences were observed between physical and empirical models and due to the different degrees of freedom of the model equations. There were also considerable differences in model performance for adsorption and desorption data. While regression analysis relating model parameters and clay content and subsequent model application for prediction of measured isotherms showed promise for the majority of investigated soils, for soils with distinct kaolinitic and smectitic clay mineralogy predicted isotherms did not closely match the measurements.

Molecular Modeling for Calculation of Mechanical Properties of Epoxies with Moisture Ingress

NASA Technical Reports Server (NTRS)

Clancy, Thomas C.; Frankland, Sarah J.; Hinkley, J. A.; Gates, T. S.

2009-01-01

Atomistic models of epoxy structures were built in order to assess the effect of crosslink degree, moisture content and temperature on the calculated properties of a typical representative generic epoxy. Each atomistic model had approximately 7000 atoms and was contained within a periodic boundary condition cell with edge lengths of about 4 nm. Four atomistic models were built with a range of crosslink degree and moisture content. Each of these structures was simulated at three temperatures: 300 K, 350 K, and 400 K. Elastic constants were calculated for these structures by monitoring the stress tensor as a function of applied strain deformations to the periodic boundary conditions. The mechanical properties showed reasonably consistent behavior with respect to these parameters. The moduli decreased with decreasing crosslink degree with increasing temperature. The moduli generally decreased with increasing moisture content, although this effect was not as consistent as that seen for temperature and crosslink degree.

[Rapid determination of the components in ternary blended edible oil using near infrared transmission spectroscopy].

PubMed

Liu, Fu-Li; Chen, Hua-Cai

2009-08-01

The FT-NIR transmission spectra of ternary blended edible oil samples were collected over 10 000-4 200 cm(-1). After being pretreated with different methods, the calibration models of quantitative analysis of soybean oil, peanut oil and corn oil contents in ternary blended edible oil were established using partial least square (PLS) regression. The accuracy and precision of the models for the predicted sample set were examined to make sure of the practicability of the models. After being pretreated with first derivative and multiplicative signal correction (FD+MSC), the optimal soybean oil NIR model was built over 5 450.1-4 597.7 cm(-1). The best prediction model for peanut oil was established between 7 521.3 and 6 098.1 cm(-1) after using first derivative with straight line subtraction (FD+SLS) preprocess method. The best pretreated method and the best spectrum range for corn oil content model were first derivative (FD) and 9 993.7-7 498.2 cm(-1), respectively. The best correlation coefficients (R2) of the three prediction models were 99.89%, 99.88% and 99.76%, respectively. The RMSEP of the soybean oil content model was 1.09%, while the peanut oil prediction model's RMSEP was 1.17%, and 1.48% for the corn oil prediction model. The values of the t-test were between 0.007 9 and 0.371 9, and all values of the relative standard deviation (RSD) were less than 1.50%. The results showed that NIR could be an ideal tool for fast determination of the soybean oil, peanut oil and corn oil contents in ternary blended edible oil.

Compatible Models of Carbon Content of Individual Trees on a Cunninghamia lanceolata Plantation in Fujian Province, China

PubMed Central

Zhuo, Lin; Tao, Hong; Wei, Hong; Chengzhen, Wu

2016-01-01

We tried to establish compatible carbon content models of individual trees for a Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) plantation from Fujian province in southeast China. In general, compatibility requires that the sum of components equal the whole tree, meaning that the sum of percentages calculated from component equations should equal 100%. Thus, we used multiple approaches to simulate carbon content in boles, branches, foliage leaves, roots and the whole individual trees. The approaches included (i) single optimal fitting (SOF), (ii) nonlinear adjustment in proportion (NAP) and (iii) nonlinear seemingly unrelated regression (NSUR). These approaches were used in combination with variables relating diameter at breast height (D) and tree height (H), such as D, D2H, DH and D&H (where D&H means two separate variables in bivariate model). Power, exponential and polynomial functions were tested as well as a new general function model was proposed by this study. Weighted least squares regression models were employed to eliminate heteroscedasticity. Model performances were evaluated by using mean residuals, residual variance, mean square error and the determination coefficient. The results indicated that models with two dimensional variables (DH, D2H and D&H) were always superior to those with a single variable (D). The D&H variable combination was found to be the most useful predictor. Of all the approaches, SOF could establish a single optimal model separately, but there were deviations in estimating results due to existing incompatibilities, while NAP and NSUR could ensure predictions compatibility. Simultaneously, we found that the new general model had better accuracy than others. In conclusion, we recommend that the new general model be used to estimate carbon content for Chinese fir and considered for other vegetation types as well. PMID:26982054

Desorption isotherms and isosteric heat of desorption of previously frozen raw pork meat.

PubMed

Clemente, G; Bon, J; Benedito, J; Mulet, A

2009-08-01

Some meat products involve drying previously frozen pork meat, which makes the knowledge of sorption characteristics very important for the design and management of meat dehydration processes. The sorption isotherms of raw pork meat from the Biceps femoris and Semimembranosus muscles were determined at four temperatures: 25, 30, 35 and 40°C. The experimental results were modelled using the GAB (Guggenheim, Anderson and De Boer) model. The effect of temperature was also taken into account to model the experimental sorption isotherms using four models (GAB, Oswin, Halsey and Henderson). The best results were provided by the GAB model. From the experimental sorption isotherms the isosteric heats of sorption were determined. For a moisture content higher than 0.15kgwater/kgdm, the isosteric heat of meat was similar to the latent heat of vaporization for pure water. For a lower moisture content, an increase in the isosteric heat was observed when the moisture content decreased.

Cultural selection drives the evolution of human communication systems

PubMed Central

Tamariz, Monica; Ellison, T. Mark; Barr, Dale J.; Fay, Nicolas

2014-01-01

Human communication systems evolve culturally, but the evolutionary mechanisms that drive this evolution are not well understood. Against a baseline that communication variants spread in a population following neutral evolutionary dynamics (also known as drift models), we tested the role of two cultural selection models: coordination- and content-biased. We constructed a parametrized mixed probabilistic model of the spread of communicative variants in four 8-person laboratory micro-societies engaged in a simple communication game. We found that selectionist models, working in combination, explain the majority of the empirical data. The best-fitting parameter setting includes an egocentric bias and a content bias, suggesting that participants retained their own previously used communicative variants unless they encountered a superior (content-biased) variant, in which case it was adopted. This novel pattern of results suggests that (i) a theory of the cultural evolution of human communication systems must integrate selectionist models and (ii) human communication systems are functionally adaptive complex systems. PMID:24966310

Cultural selection drives the evolution of human communication systems.

PubMed

Tamariz, Monica; Ellison, T Mark; Barr, Dale J; Fay, Nicolas

2014-08-07

Human communication systems evolve culturally, but the evolutionary mechanisms that drive this evolution are not well understood. Against a baseline that communication variants spread in a population following neutral evolutionary dynamics (also known as drift models), we tested the role of two cultural selection models: coordination- and content-biased. We constructed a parametrized mixed probabilistic model of the spread of communicative variants in four 8-person laboratory micro-societies engaged in a simple communication game. We found that selectionist models, working in combination, explain the majority of the empirical data. The best-fitting parameter setting includes an egocentric bias and a content bias, suggesting that participants retained their own previously used communicative variants unless they encountered a superior (content-biased) variant, in which case it was adopted. This novel pattern of results suggests that (i) a theory of the cultural evolution of human communication systems must integrate selectionist models and (ii) human communication systems are functionally adaptive complex systems.

Modeling and Simulation of Voids in Composite Tape Winding Process Based on Domain Superposition Technique

NASA Astrophysics Data System (ADS)

Deng, Bo; Shi, Yaoyao

2017-11-01

The tape winding technology is an effective way to fabricate rotationally composite materials. Nevertheless, some inevitable defects will seriously influence the performance of winding products. One of the crucial ways to identify the quality of fiber-reinforced composite material products is examining its void content. Significant improvement in products' mechanical properties can be achieved by minimizing the void defect. Two methods were applied in this study, finite element analysis and experimental testing, respectively, to investigate the mechanism of how void forming in composite tape winding processing. Based on the theories of interlayer intimate contact and Domain Superposition Technique (DST), a three-dimensional model of prepreg tape void with SolidWorks has been modeled in this paper. Whereafter, ABAQUS simulation software was used to simulate the void content change with pressure and temperature. Finally, a series of experiments were performed to determine the accuracy of the model-based predictions. The results showed that the model is effective for predicting the void content in the composite tape winding process.

Modeling Information Content Via Dirichlet-Multinomial Regression Analysis.

PubMed

Ferrari, Alberto

2017-01-01

Shannon entropy is being increasingly used in biomedical research as an index of complexity and information content in sequences of symbols, e.g. languages, amino acid sequences, DNA methylation patterns and animal vocalizations. Yet, distributional properties of information entropy as a random variable have seldom been the object of study, leading to researchers mainly using linear models or simulation-based analytical approach to assess differences in information content, when entropy is measured repeatedly in different experimental conditions. Here a method to perform inference on entropy in such conditions is proposed. Building on results coming from studies in the field of Bayesian entropy estimation, a symmetric Dirichlet-multinomial regression model, able to deal efficiently with the issue of mean entropy estimation, is formulated. Through a simulation study the model is shown to outperform linear modeling in a vast range of scenarios and to have promising statistical properties. As a practical example, the method is applied to a data set coming from a real experiment on animal communication.

Fourier transform infrared spectroscopy to quantify collagen and elastin in an in vitro model of extracellular matrix degradation in aorta.

PubMed

Cheheltani, Rabee; McGoverin, Cushla M; Rao, Jayashree; Vorp, David A; Kiani, Mohammad F; Pleshko, Nancy

2014-06-21

Extracellular matrix (ECM) is a key component and regulator of many biological tissues including aorta. Several aortic pathologies are associated with significant changes in the composition of the matrix, especially in the content, quality and type of aortic structural proteins, collagen and elastin. The purpose of this study was to develop an infrared spectroscopic methodology that is comparable to biochemical assays to quantify collagen and elastin in aorta. Enzymatically degraded porcine aorta samples were used as a model of ECM degradation in abdominal aortic aneurysm (AAA). After enzymatic treatment, Fourier transform infrared (FTIR) spectra of the aortic tissue were acquired by an infrared fiber optic probe (IFOP) and FTIR imaging spectroscopy (FT-IRIS). Collagen and elastin content were quantified biochemically and partial least squares (PLS) models were developed to predict collagen and elastin content in aorta based on FTIR spectra. PLS models developed from FT-IRIS spectra were able to predict elastin and collagen content of the samples with strong correlations (RMSE of validation = 8.4% and 11.1% of the range respectively), and IFOP spectra were successfully used to predict elastin content (RMSE = 11.3% of the range). The PLS regression coefficients from the FT-IRIS models were used to map collagen and elastin in tissue sections of degraded porcine aortic tissue as well as a human AAA biopsy tissue, creating a similar map of each component compared to histology. These results support further application of FTIR spectroscopic techniques for evaluation of AAA tissues.

Fourier Transform Infrared Spectroscopy to Quantify Collagen and Elastin in an In Vitro Model of Extracellular Matrix Degradation in Aorta

PubMed Central

Cheheltani, Rabee; McGoverin, Cushla M.; Rao, Jayashree; Vorp, David A.; Kiani, Mohammad F.; Pleshko, N.

2014-01-01

Extracellular matrix (ECM) is a key component and regulator of many biological tissues including aorta. Several aortic pathologies are associated with significant changes in the composition of the matrix, especially in the content, quality and type of aortic structural proteins, collagen and elastin. The purpose of this study was to develop an infrared spectroscopic methodology that is comparable to biochemical assays to quantify collagen and elastin in aorta. Enzymatically degraded porcine aorta samples were used as a model of ECM degradation in abdominal aortic aneurysm (AAA). After enzymatic treatment, Fourier transform infrared (FTIR) spectra of the aortic tissue were acquired by an infrared fiber optic probe (IFOP) and FTIR imaging spectroscopy (FT-IRIS). Collagen and elastin content were quantified biochemically and partial least squares (PLS) models were developed to predict collagen and elastin content in aorta based on FTIR spectra. PLS models developed from FT-IRIS spectra were able to predict elastin and collagen content of the samples with strong correlations (RMSE of validation = 8.4% and 11.1% of the range respectively), and IFOP spectra were successfully used to predict elastin content (RMSE = 11.3% of the range). The PLS regression coefficients from the FT-IRIS models were used to map collagen and elastin in tissue sections of degraded porcine aortic tissue as well as a human AAA biopsy tissue, creating a similar map of each component compared to histology. These results support further application of FTIR spectroscopic techniques for evaluation of AAA tissues. PMID:24761431

NIR techniques create added values for the pellet and biofuel industry.

PubMed

Lestander, Torbjörn A; Johnsson, Bo; Grothage, Morgan

2009-02-01

A 2(3)-factorial experiment was carried out in an industrial plant producing biofuel pellets with sawdust as feedstock. The aim was to use on-line near infrared (NIR) spectra from sawdust for real time predictions of moisture content, blends of sawdust and energy consumption of the pellet press. The factors varied were: drying temperature and wood powder dryness in binary blends of sawdust from Norway spruce and Scots pine. The main results were excellent NIR calibration models for on-line prediction of moisture content and binary blends of sawdust from the two species, but also for the novel finding that the consumption of electrical energy per unit pelletized biomass can be predicted by NIR reflectance spectra from sawdust entering the pellet press. This power consumption model, explaining 91.0% of the variation, indicated that NIR data contained information of the compression and friction properties of the biomass feedstock. The moisture content model was validated using a running NIR calibration model in the pellet plant. It is shown that the adjusted prediction error was 0.41% moisture content for grinded sawdust dried to ca. 6-12% moisture content. Further, although used drying temperatures influenced NIR spectra the models for drying temperature resulted in low prediction accuracy. The results show that on-line NIR can be used as an important tool in the monitoring and control of the pelletizing process and that the use of NIR technique in fuel pellet production has possibilities to better meet customer specifications, and therefore create added production values.

Conceptual foundation for measures of physical function and behavioral health function for Social Security work disability evaluation.

PubMed

Marfeo, Elizabeth E; Haley, Stephen M; Jette, Alan M; Eisen, Susan V; Ni, Pengsheng; Bogusz, Kara; Meterko, Mark; McDonough, Christine M; Chan, Leighton; Brandt, Diane E; Rasch, Elizabeth K

2013-09-01

Physical and mental impairments represent the 2 largest health condition categories for which workers receive Social Security disability benefits. Comprehensive assessment of physical and mental impairments should include aspects beyond medical conditions such as a person's underlying capabilities as well as activity demands relevant to the context of work. The objective of this article is to describe the initial conceptual stages of developing new measurement instruments of behavioral health and physical functioning relevant for Social Security work disability evaluation purposes. To outline a clear conceptualization of the constructs to be measured, 2 content models were developed using structured and informal qualitative approaches. We performed a structured literature review focusing on work disability and incorporating aspects of the International Classification of Functioning, Disability and Health as a unifying taxonomy for framework development. Expert interviews provided advice and consultation to enhance face validity of the resulting content models. The content model for work-related behavioral health function identifies 5 major domains: (1) behavior control, (2) basic interactions, (3) temperament and personality, (4) adaptability, and (5) workplace behaviors. The content model describing physical functioning includes 3 domains: (1) changing and maintaining body position, (2) whole-body mobility, and (3) carrying, moving, and handling objects. These content models informed subsequent measurement properties including item development and measurement scale construction, and provided conceptual coherence guiding future empirical inquiry. The proposed measurement approaches show promise to comprehensively and systematically assess physical and behavioral health functioning relevant to work. Copyright © 2013 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Theorizing Content: Tools from Cultural History

ERIC Educational Resources Information Center

Hawkey, Kate

2007-01-01

What lies behind the lack of theorizing about content in history in contrast to much greater attention given to theorizing about children's developing understanding of historical skills and processes? Egan's model of the characteristic ways in which children of different ages engage with the world is used to raise the question of what content to…

A SCORM Compliant Courseware Authoring Tool for Supporting Pervasive Learning

ERIC Educational Resources Information Center

Wang, Te-Hua; Chang, Flora Chia-I

2007-01-01

The sharable content object reference model (SCORM) includes a representation of distance learning contents and a behavior definition of how users should interact with the contents. Generally, SCORMcompliant systems were based on multimedia and Web technologies on PCs. We further build a pervasive learning environment, which allows users to read…

Moving Toward SCORM Compliant Content Production at Educational Software Company: Technical and Administrative Challenges

ERIC Educational Resources Information Center

Kultur, Can; Oytun, Erden; Cagiltay, Kursat; Ozden, M. Yasar; Kucuk, Mehmet Emin

2004-01-01

The Shareable Content Object Reference Model (SCORM) aims to standardize electronic course content, its packaging and delivery. Instructional designers and e-learning material producer organizations accept SCORM?s significant impact on instructional design/delivery process, however not much known about how such standards will be implemented to…

The Construct Validity of Higher Order Structure-of-Intellect Factors Reflecting Semantic and Symbolic Content Abilities.

ERIC Educational Resources Information Center

Khattab, Ali-Maher; Michael, William B.

1986-01-01

Based on reanalyses of correlational data obtained from the University of Southern California Aptitudes Research Project, this investigation examined the extent to which two higher order factors of semantic content and symbolic content form Guilford's structure-of-intellect model reflected distinct constructs. (Author/LMO)

Keeping the Language Focus in Content-Based ESL Instruction through Proactive Curriculum-Planning

ERIC Educational Resources Information Center

Bigelow, Martha; Ranney, Susan; Dahlman, Anne

2006-01-01

For content-based instruction (CBI) to work to its maximum potential, a concerted planning effort must be made to address language objectives, combined with effective instructional strategies that target and assess student performance in relation to those objectives. In this article, after considering various models of content-language…

Past and Future Directions in Content Area Literacies

ERIC Educational Resources Information Center

Bean, Tom; O'Brien, David

2013-01-01

In this column, content area literacy scholars Tom Bean and David O'Brien challenge the older "infusion" model of content area literacy with its emphasis on generic strategies. Rather, they argue for and provide examples of projects that draw on the unique dimensions of various disciplines like history, science, and English, particularly in light…

Upper Washita River experimental watersheds: Multiyear stability of soil water content profiles

USDA-ARS?s Scientific Manuscript database

Scaling in situ soil water content time series data to a large spatial domain is a key element of watershed environmental monitoring and modeling. The primary method of estimating and monitoring large-scale soil water content distributions is via in situ networks. It is critical to establish the s...

Beyond clay: Towards an improved set of variables for predicting soil organic matter content

USGS Publications Warehouse

Rasmussen, Craig; Heckman, Katherine; Wieder, William R.; Keiluweit, Marco; Lawrence, Corey R.; Berhe, Asmeret Asefaw; Blankinship, Joseph C.; Crow, Susan E.; Druhan, Jennifer; Hicks Pries, Caitlin E.; Marin-Spiotta, Erika; Plante, Alain F.; Schadel, Christina; Schmiel, Joshua P.; Sierra, Carlos A.; Thompson, Aaron; Wagai, Rota

2018-01-01

Improved quantification of the factors controlling soil organic matter (SOM) stabilization at continental to global scales is needed to inform projections of the largest actively cycling terrestrial carbon pool on Earth, and its response to environmental change. Biogeochemical models rely almost exclusively on clay content to modify rates of SOM turnover and fluxes of climate-active CO2 to the atmosphere. Emerging conceptual understanding, however, suggests other soil physicochemical properties may predict SOM stabilization better than clay content. We addressed this discrepancy by synthesizing data from over 5,500 soil profiles spanning continental scale environmental gradients. Here, we demonstrate that other physicochemical parameters are much stronger predictors of SOM content, with clay content having relatively little explanatory power. We show that exchangeable calcium strongly predicted SOM content in water-limited, alkaline soils, whereas with increasing moisture availability and acidity, iron- and aluminum-oxyhydroxides emerged as better predictors, demonstrating that the relative importance of SOM stabilization mechanisms scales with climate and acidity. These results highlight the urgent need to modify biogeochemical models to better reflect the role of soil physicochemical properties in SOM cycling.

Spectral reflectance of surface soils: Relationships with some soil properties

NASA Technical Reports Server (NTRS)

Kiesewetter, C. H.

1983-01-01

Using a published atlas of reflectance curves and physicochemical properties of soils, a statistical analysis was carried out. Reflectance bands which correspond to five of the wavebands used by NASA's Thematic Mapper were examined for relationships to specific soil properties. The properties considered in this study include: Sand Content, Silt Content, Clay Content, Organic Matter Content, Cation Exchange Capacity, Iron Oxide Content and Moisture Content. Regression of these seven properties on the mean values of five TM bands produced results that indicate that the predictability of the properties can be increased by stratifying the data. The data was stratified by parent material, taxonomic order, temperature zone, moisture zone and climate (combined temperature and moisture). The best results were obtained when the sample was examined by climatic classes. The middle Infra-red bands, 5 and 7, as well as the visible bands, 2 and 3, are significant in the model. The near Infra-red band, band 4, is almost as useful and should be included in any studies. General linear modeling procedures examined relationships of the seven properties with certain wavebands in the stratified samples.

Distance-Based Opportunistic Mobile Data Offloading

PubMed Central

Lu, Xiaofeng; Lio, Pietro; Hui, Pan

2016-01-01

Cellular network data traffic can be offload onto opportunistic networks. This paper proposes a Distance-based Opportunistic Publish/Subscribe (DOPS) content dissemination model, which is composed of three layers: application layer, decision-making layer and network layer. When a user wants new content, he/she subscribes on a subscribing server. Users having the contents decide whether to deliver the contents to the subscriber based on the distance information. If in the meantime a content owner has traveled further in the immediate past time than the distance between the owner and the subscriber, the content owner will send the content to the subscriber through opportunistic routing. Simulations provide an evaluation of the data traffic offloading efficiency of DOPS. PMID:27314361

Distance-Based Opportunistic Mobile Data Offloading.

PubMed

Lu, Xiaofeng; Lio, Pietro; Hui, Pan

2016-06-15

Cellular network data traffic can be offload onto opportunistic networks. This paper proposes a Distance-based Opportunistic Publish/Subscribe (DOPS) content dissemination model, which is composed of three layers: application layer, decision-making layer and network layer. When a user wants new content, he/she subscribes on a subscribing server. Users having the contents decide whether to deliver the contents to the subscriber based on the distance information. If in the meantime a content owner has traveled further in the immediate past time than the distance between the owner and the subscriber, the content owner will send the content to the subscriber through opportunistic routing. Simulations provide an evaluation of the data traffic offloading efficiency of DOPS.

The Relationship between Bulk and Mobile Forms of Heavy Metals in Soils of Kursk

NASA Astrophysics Data System (ADS)

Nevedrov, N. P.; Protsenko, E. P.; Glebova, I. V.

2018-01-01

The contamination of Kursk urboecotopes by heavy metals (Pb, Cd, Zn, Cu, Ni) is considered. The relationships between the contents of bulk and mobile forms of heavy metal ions have been examined. The results of monitoring studies attest to a tendency for the accumulation of both bulk and mobile forms of heavy metals in the humus-accumulative horizon, except for bulk cadmium and mobile nickel. Linear and nonlinear regression models of the bulk contents of Pb, Cd, Zn, and Ni as dependent on the contents of their mobile forms have been developed. These models allow us to calculate the bulk content of heavy metal ions in the soils of urboecotopes using simpler methods of the extraction and laboratory determination of their mobile forms.

Using the Stereotype Content Model to examine group depictions in Fascism: An Archival Approach

PubMed Central

Durante, Federica; Volpato, Chiara; Fiske, Susan T.

2013-01-01

The Stereotype Content Model (SCM) suggests potentially universal intergroup depictions. If universal, they should apply across history in archival data. Bridging this gap, we examined social groups descriptions during Italy’s Fascist era. In Study 1, articles published in a Fascist magazine— La Difesa della Razza —were content analyzed, and results submitted to correspondence analysis. Admiration prejudice depicted ingroups; envious and contemptuous prejudices depicted specific outgroups, generally in line with SCM predictions. No paternalistic prejudice appeared; historical reasons might explain this finding. Results also fit the recently developed BIAS Map of behavioral consequences. In Study 2, ninety-six undergraduates rated the content-analysis traits on warmth and competence, without knowing their origin. They corroborated SCM’s interpretations of the archival data. PMID:24403646

Discrimination of soil hydraulic properties by combined thermal infrared and microwave remote sensing

NASA Technical Reports Server (NTRS)

Vandegriend, A. A.; Oneill, P. E.

1986-01-01

Using the De Vries models for thermal conductivity and heat capacity, thermal inertia was determined as a function of soil moisture for 12 classes of soil types ranging from sand to clay. A coupled heat and moisture balance model was used to describe the thermal behavior of the top soil, while microwave remote sensing was used to estimate the soil moisture content of the same top soil. Soil hydraulic parameters are found to be very highly correlated with the combination of soil moisture content and thermal inertia at the same moisture content. Therefore, a remotely sensed estimate of the thermal behavior of the soil from diurnal soil temperature observations and an independent remotely sensed estimate of soil moisture content gives the possibility of estimating soil hydraulic properties by remote sensing.

Analysis of the Relations among the Components of Technological Pedagogical and Content Knowledge (TPACK): A Structural Equation Model

ERIC Educational Resources Information Center

Celik, Ismail; Sahin, Ismail; Akturk, Ahmet Oguz

2014-01-01

In the current study, the model of technological pedagogical and content knowledge (TPACK) is used as the theoretical framework in the process of data collection and interpretation of the results. This study analyzes the perceptions of 744 undergraduate students regarding their TPACK levels measured by responses to a survey developed by Sahin…

Using CONTENT 1.5 to analyze an SIR model for childhood infectious diseases

NASA Astrophysics Data System (ADS)

Su, Rui; He, Daihai

2008-11-01

In this work, we introduce a standard software CONTENT 1.5 for analysis of dynamical systems. A simple model for childhood infectious diseases is used as an example. The detailed steps to obtain the bifurcation structures of the system are given. These bifurcation structures can be used to explain the observed dynamical transition in measles incidences.

Online Community and User-Generated Content: Understanding the Role of Social Networks

ERIC Educational Resources Information Center

Oh, Jeong Ha

2010-01-01

Models of user generated content (UGC) creation such as Facebook, MySpace, and YouTube are facing robust growth accelerated by the adoption of Web 2.0 technologies and standards. These business models offer a fascinating avenue for exploring the role of social influence online. This dissertation is motivated by the success of YouTube, which is…

The Trilayer Approach of Teaching Physiology, Pathophysiology, and Pharmacology Concepts in a First-Year Pharmacy Course: The TLAT Model

ERIC Educational Resources Information Center

Islam, Mohammed A.; Sabnis, Gauri; Farris, Fred

2017-01-01

This paper describes the development, implementation, and students' perceptions of a new trilayer approach of teaching (TLAT). The TLAT model involved blending lecture, in-class group activities, and out-of-class assignments on selected content areas and was implemented initially in a first-year integrated pharmacy course. Course contents were…

From Nominal to Quantitative Codification of Content-Neutral Variables in Graphics Research: The Beginnings of a Manifest Content Model.

ERIC Educational Resources Information Center

Crow, Wendell C.

This paper suggests ways in which manifest, physical attributes of graphic elements can be described and measured. It also proposes a preliminary conceptual model that accounts for the readily apparent, measurable variables in a visual message. The graphic elements that are described include format, typeface, and photographs/artwork. The…

Promoting Conceptual Change of Learning Sorting Algorithm through the Diagnosis of Mental Models: The Effects of Gender and Learning Styles

ERIC Educational Resources Information Center

Lau, Wilfred W. F.; Yuen, Allan H. K.

2010-01-01

It has been advocated that pedagogical content knowledge as well as subject matter knowledge are important for improving classroom instructions. To develop pedagogical content knowledge, it is argued that understanding of students' mental representations of concepts is deemed necessary. Yet assessing and comparing mental model of each individual…

The Influence of Content Knowledge on Teaching and Learning in Traditional and Sport Education Contexts: An Exploratory Study

ERIC Educational Resources Information Center

Iserbyt, Peter; Ward, Phillip; Martens, Jonas

2016-01-01

Background: Our understanding of the role in which content knowledge (CK) can strengthen instructional models and how that knowledge matters for professional development is limited. It is contended that mere use of an instructional model is insufficient to impact psychomotor learning in meaningful ways. Purpose: This study was conducted to…

Mathematical Practice in Textbooks Analysis: Praxeological Reference Models, the Case of Proportion

ERIC Educational Resources Information Center

Wijayanti, Dyana; Winsløw, Carl

2017-01-01

We present a new method in textbook analysis, based on so-called praxeological reference models focused on specific content at task level. This method implies that the mathematical contents of a textbook (or textbook part) is analyzed in terms of the tasks and techniques which are exposed to or demanded from readers; this can then be interpreted…

Characterization of articular cartilage by combining microscopic analysis with a fibril-reinforced finite-element model.

PubMed

Julkunen, Petro; Kiviranta, Panu; Wilson, Wouter; Jurvelin, Jukka S; Korhonen, Rami K

2007-01-01

Load-bearing characteristics of articular cartilage are impaired during tissue degeneration. Quantitative microscopy enables in vitro investigation of cartilage structure but determination of tissue functional properties necessitates experimental mechanical testing. The fibril-reinforced poroviscoelastic (FRPVE) model has been used successfully for estimation of cartilage mechanical properties. The model includes realistic collagen network architecture, as shown by microscopic imaging techniques. The aim of the present study was to investigate the relationships between the cartilage proteoglycan (PG) and collagen content as assessed by quantitative microscopic findings, and model-based mechanical parameters of the tissue. Site-specific variation of the collagen network moduli, PG matrix modulus and permeability was analyzed. Cylindrical cartilage samples (n=22) were harvested from various sites of the bovine knee and shoulder joints. Collagen orientation, as quantitated by polarized light microscopy, was incorporated into the finite-element model. Stepwise stress-relaxation experiments in unconfined compression were conducted for the samples, and sample-specific models were fitted to the experimental data in order to determine values of the model parameters. For comparison, Fourier transform infrared imaging and digital densitometry were used for the determination of collagen and PG content in the same samples, respectively. The initial and strain-dependent fibril network moduli as well as the initial permeability correlated significantly with the tissue collagen content. The equilibrium Young's modulus of the nonfibrillar matrix and the strain dependency of permeability were significantly associated with the tissue PG content. The present study demonstrates that modern quantitative microscopic methods in combination with the FRPVE model are feasible methods to characterize the structure-function relationships of articular cartilage.

Laboratory-based electrical conductivity at Martian mantle conditions

NASA Astrophysics Data System (ADS)

Verhoeven, Olivier; Vacher, Pierre

2016-12-01

Information on temperature and composition of planetary mantles can be obtained from electrical conductivity profiles derived from induced magnetic field analysis. This requires a modeling of the conductivity for each mineral phase at conditions relevant to planetary interiors. Interpretation of iron-rich Martian mantle conductivity profile therefore requires a careful modeling of the conductivity of iron-bearing minerals. In this paper, we show that conduction mechanism called small polaron is the dominant conduction mechanism at temperature, water and iron content conditions relevant to Mars mantle. We then review the different measurements performed on mineral phases with various iron content. We show that, for all measurements of mineral conductivity reported so far, the effect of iron content on the activation energy governing the exponential decrease in the Arrhenius law can be modeled as the cubic square root of the iron content. We recast all laboratory results on a common generalized Arrhenius law for iron-bearing minerals, anchored on Earth's mantle values. We then use this modeling to compute a new synthetic profile of Martian mantle electrical conductivity. This new profile matches perfectly, in the depth range [100,1000] km, the electrical conductivity profile recently derived from the study of Mars Global Surveyor magnetic field measurements.

To Each According to its Degree: The Meritocracy and Topocracy of Embedded Markets

NASA Astrophysics Data System (ADS)

Borondo, J.; Borondo, F.; Rodriguez-Sickert, C.; Hidalgo, C. A.

2014-01-01

A system is said to be meritocratic if the compensation and power available to individuals is determined by their abilities and merits. A system is topocratic if the compensation and power available to an individual is determined primarily by her position in a network. Here we introduce a model that is perfectly meritocratic for fully connected networks but that becomes topocratic for sparse networks-like the ones in society. In the model, individuals produce and sell content, but also distribute the content produced by others when they belong to the shortest path connecting a buyer and a seller. The production and distribution of content defines two channels of compensation: a meritocratic channel, where individuals are compensated for the content they produce, and a topocratic channel, where individual compensation is based on the number of shortest paths that go through them in the network. We solve the model analytically and show that the distribution of payoffs is meritocratic only if the average degree of the nodes is larger than a root of the total number of nodes. We conclude that, in the light of this model, the sparsity and structure of networks represents a fundamental constraint to the meritocracy of societies.

To each according to its degree: the meritocracy and topocracy of embedded markets.

PubMed

Borondo, J; Borondo, F; Rodriguez-Sickert, C; Hidalgo, C A

2014-01-21

A system is said to be meritocratic if the compensation and power available to individuals is determined by their abilities and merits. A system is topocratic if the compensation and power available to an individual is determined primarily by her position in a network. Here we introduce a model that is perfectly meritocratic for fully connected networks but that becomes topocratic for sparse networks-like the ones in society. In the model, individuals produce and sell content, but also distribute the content produced by others when they belong to the shortest path connecting a buyer and a seller. The production and distribution of content defines two channels of compensation: a meritocratic channel, where individuals are compensated for the content they produce, and a topocratic channel, where individual compensation is based on the number of shortest paths that go through them in the network. We solve the model analytically and show that the distribution of payoffs is meritocratic only if the average degree of the nodes is larger than a root of the total number of nodes. We conclude that, in the light of this model, the sparsity and structure of networks represents a fundamental constraint to the meritocracy of societies.

[Application of near infrared spectroscopy in rapid and simultaneous determination of essential components in five varieties of anti-tuberculosis tablets].

PubMed

Teng, Le-sheng; Wang, Di; Song, Jia; Zhang, Yi-bo; Guo, Wei-liang; Teng, Li-rong

2008-08-01

Since 1980s, tuberculosis has become increasingly serious. Rifampicin tablets, isoniazide tablets, pyrazinamide tablets, rifampicin and isoniazide tablets and rifampicin isoniazide and pyrazinamide tablets are currently relatively efficacious antituberculosis drugs. In the present paper, near infrared spectroscopy (NIRS) with partial least squares (PLS) was applied to the simultaneous determination of rifampicin (RMP), isoniazide (INH) and pyrazinamide (PZA) contents in 5 varieties of anti-tuberculosis tablets. As the results showed, all of the models for the determination of RMP, INH and PZA contents applied the original NIR spectra. The most efficacious wavelength range for the determination of RMP contents was 1981-2195 nm, it was 1540-1717 nm and 2086-2197 nm for the determination of INH contents, and it was 1460-1537 nm, 1956-2022 nm and 2268-2393 nm for determination of PZA contents. The root mean square error of the calibration set obtained by cross-validation (RMSECV) of the optimum models for the quantitative analysis of RMP, INH and PZA contents was 0.0494, 0.0257 and 0.0307, respectively. Using these optimum models for the determination of RMP, INH and PZA contents in prediction set, the root mean square error of prediction set (RMSEP) was 0.0182, 0.0166 and 0.0134, respectively. The correlation coefficient (r(p)) between the predicted values and actual values was 0.9864, 0.9989 and 0.9993, respectively. These results demonstrated that this method was precise and reliable, and is significative for in situ measurement and the on-line quality control for anti-tuberculosis tablets production.

Spatial prediction of Soil Organic Carbon contents in croplands, grasslands and forests using environmental covariates and Generalized Additive Models (Southern Belgium)

NASA Astrophysics Data System (ADS)

Chartin, Caroline; Stevens, Antoine; van Wesemael, Bas

2015-04-01

Providing spatially continuous Soil Organic Carbon data (SOC) is needed to support decisions regarding soil management, and inform the political debate with quantified estimates of the status and change of the soil resource. Digital Soil Mapping techniques are based on relations existing between a soil parameter (measured at different locations in space at a defined period) and relevant covariates (spatially continuous data) that are factors controlling soil formation and explaining the spatial variability of the target variable. This study aimed at apply DSM techniques to recent SOC content measurements (2005-2013) in three different landuses, i.e. cropland, grassland, and forest, in the Walloon region (Southern Belgium). For this purpose, SOC databases of two regional Soil Monitoring Networks (CARBOSOL for croplands and grasslands, and IPRFW for forests) were first harmonized, totalising about 1,220 observations. Median values of SOC content for croplands, grasslands, and forests, are respectively of 12.8, 29.0, and 43.1 g C kg-1. Then, a set of spatial layers were prepared with a resolution of 40 meters and with the same grid topology, containing environmental covariates such as, landuses, Digital Elevation Model and its derivatives, soil texture, C factor, carbon inputs by manure, and climate. Here, in addition to the three classical texture classes (clays, silt, and sand), we tested the use of clays + fine silt content (particles < 20 µm and related to stable carbon fraction) as soil covariate explaining SOC variations. For each of the three land uses (cropland, grassland and forest), a Generalized Additive Model (GAM) was calibrated on two thirds of respective dataset. The remaining samples were assigned to a test set to assess model performance. A backward stepwise procedure was followed to select the relevant environmental covariates using their approximate p-values (the level of significance was set at p < 0.05). Standard errors were estimated for each of the three models. The backward stepwise procedure selected coordinates, elevation and clays + fine silt content as environment covariates to model SOC variation in cropland soils; latitude, precipitation, and clays + fine silt content (< 20 µm) for grassland soils; and latitude, elevation, topographic position index and clays + fine silt content (< 20 µm) for forest soils. The validation of the models gave a R² of 0.62 for croplands, 0.38 for grasslands, and 0.35 for forests. These results will be developed and discussed based on implications of natural against anthropogenic drivers on SOC distribution for these three landuses. To finish, a map combining detailed information of SOC content for agricultural soils and forests was for the first time computed for the Walloon region.

Prediction of soil organic carbon in a coal mining area by Vis-NIR spectroscopy.

PubMed

Sun, Wenjuan; Li, Xinju; Niu, Beibei

2018-01-01

Coal mining has led to increasingly serious land subsidence, and the reclamation of the subsided land has become a hot topic of concern for governments and scholars. Soil quality of reclaimed land is the key indicator to the evaluation of the reclamation effect; hence, rapid monitoring and evaluation of reclaimed land is of great significance. Visible-near infrared (Vis-NIR) spectroscopy has been shown to be a rapid, timely and efficient tool for the prediction of soil organic carbon (SOC). In this study, 104 soil samples were collected from the Baodian mining area of Shandong province. Vis-NIR reflectance spectra and soil organic carbon content were then measured under laboratory conditions. The spectral data were first denoised using the Savitzky-Golay (SG) convolution smoothing method or the multiple scattering correction (MSC) method, after which the spectral reflectance (R) was subjected to reciprocal, reciprocal logarithm and differential transformations to improve spectral sensitivity. Finally, regression models for estimating the SOC content by the spectral data were constructed using partial least squares regression (PLSR). The results showed that: (1) The SOC content in the mining area was generally low (at the below-average level) and exhibited great variability. (2) The spectral reflectance increased with the decrease of soil organic carbon content. In addition, the sensitivity of the spectrum to the change in SOC content, especially that in the near-infrared band of the original reflectance, decreased when the SOC content was low. (3) The modeling results performed best when the spectral reflectance was preprocessed by Savitzky-Golay (SG) smoothing coupled with multiple scattering correction (MSC) and first-order differential transformation (modeling R2 = 0.86, RMSE = 2.00 g/kg, verification R2 = 0.78, RMSE = 1.81 g/kg, and RPD = 2.69). In addition, the first-order differential of R combined with SG, MSC with R, SG together with MSC and R also produced better modeling results than other pretreatment combinations. Vis-NIR modeling with specific spectral preprocessing methods could predict SOC content effectively.

Effect of Jiangzhi tablet on serum indexes of mice with fatty liver induced by CCL4

NASA Astrophysics Data System (ADS)

Geng, Xiuli; Kong, Xuejun; Li, Chongxian; Hao, Shaojun; Wang, Hongyu; Chen, Weiliang; Zhang, Zhengchen

2018-04-01

To investigate the effect of Jiangzhi tablet on serum indexes of mice with fatty liver induced by CCL4, 60 mice were randomly divided into blank control group, model group, positive group, high, middle and low dose group. High fat diet fed mice for 2 weeks, in second the beginning of the weekend, each group of experimental animal except the blank group in the afternoon 1:00 subcutaneous injection of 40% CCl4 of edible oil (0.05 mL/10g, 2 times / week) for modeling; at the same time, 9:00 in the morning to lipid-lowering tablets LARGEMEDTUM and small dose group (0.1125g/ml, 0.05625g/ml, 0.02815g/ml) and Gantai tablet group (0.045g/ml) mice fed with corresponding drugs, the model group received the same volume of physiological saline. At the end of the fifth week, the eyeballs were collected and the serum was separated. The levels of serum triglyceride, high density lipoprotein, low density lipoprotein, serum AST, ALT and ALP were detected. Compared with the model group, Dongbao Gantai group, Jiangzhi tablets, high dose group had significantly decreased TG and LDL content in serum of mice (p<0.01), significantly increased the content of HDL (p<0.01); Jiangzhi tablets low dose group can significantly reduce TG and LDL content in serum (p<0.05), high HDL content increased significantly in the serum of mice (p<0.01). Dongbao Gantai group, Jiangzhi tablet high dose group and middle dose group could significantly reduce the content of ALT, ALP, AST in serum of mice (p<0.01), lipid-lowering tablets in small dose group can significantly reduce ALP and AST content in serum (p<0.01), decreased the content of ALT in serum of mice (p<0.05). The high, middle and low dose groups of Jiangzhi tablets have a better intervention effect on the mice model of fatty liver induced by small dose of carbon tetrachloride.

Modeling spatial patterns of soil respiration in maize fields from vegetation and soil property factors with the use of remote sensing and geographical information system.

PubMed

Huang, Ni; Wang, Li; Guo, Yiqiang; Hao, Pengyu; Niu, Zheng

2014-01-01

To examine the method for estimating the spatial patterns of soil respiration (Rs) in agricultural ecosystems using remote sensing and geographical information system (GIS), Rs rates were measured at 53 sites during the peak growing season of maize in three counties in North China. Through Pearson's correlation analysis, leaf area index (LAI), canopy chlorophyll content, aboveground biomass, soil organic carbon (SOC) content, and soil total nitrogen content were selected as the factors that affected spatial variability in Rs during the peak growing season of maize. The use of a structural equation modeling approach revealed that only LAI and SOC content directly affected Rs. Meanwhile, other factors indirectly affected Rs through LAI and SOC content. When three greenness vegetation indices were extracted from an optical image of an environmental and disaster mitigation satellite in China, enhanced vegetation index (EVI) showed the best correlation with LAI and was thus used as a proxy for LAI to estimate Rs at the regional scale. The spatial distribution of SOC content was obtained by extrapolating the SOC content at the plot scale based on the kriging interpolation method in GIS. When data were pooled for 38 plots, a first-order exponential analysis indicated that approximately 73% of the spatial variability in Rs during the peak growing season of maize can be explained by EVI and SOC content. Further test analysis based on independent data from 15 plots showed that the simple exponential model had acceptable accuracy in estimating the spatial patterns of Rs in maize fields on the basis of remotely sensed EVI and GIS-interpolated SOC content, with R2 of 0.69 and root-mean-square error of 0.51 µmol CO2 m(-2) s(-1). The conclusions from this study provide valuable information for estimates of Rs during the peak growing season of maize in three counties in North China.

Modeling Spatial Patterns of Soil Respiration in Maize Fields from Vegetation and Soil Property Factors with the Use of Remote Sensing and Geographical Information System

PubMed Central

Huang, Ni; Wang, Li; Guo, Yiqiang; Hao, Pengyu; Niu, Zheng

2014-01-01

To examine the method for estimating the spatial patterns of soil respiration (Rs) in agricultural ecosystems using remote sensing and geographical information system (GIS), Rs rates were measured at 53 sites during the peak growing season of maize in three counties in North China. Through Pearson's correlation analysis, leaf area index (LAI), canopy chlorophyll content, aboveground biomass, soil organic carbon (SOC) content, and soil total nitrogen content were selected as the factors that affected spatial variability in Rs during the peak growing season of maize. The use of a structural equation modeling approach revealed that only LAI and SOC content directly affected Rs. Meanwhile, other factors indirectly affected Rs through LAI and SOC content. When three greenness vegetation indices were extracted from an optical image of an environmental and disaster mitigation satellite in China, enhanced vegetation index (EVI) showed the best correlation with LAI and was thus used as a proxy for LAI to estimate Rs at the regional scale. The spatial distribution of SOC content was obtained by extrapolating the SOC content at the plot scale based on the kriging interpolation method in GIS. When data were pooled for 38 plots, a first-order exponential analysis indicated that approximately 73% of the spatial variability in Rs during the peak growing season of maize can be explained by EVI and SOC content. Further test analysis based on independent data from 15 plots showed that the simple exponential model had acceptable accuracy in estimating the spatial patterns of Rs in maize fields on the basis of remotely sensed EVI and GIS-interpolated SOC content, with R2 of 0.69 and root-mean-square error of 0.51 µmol CO2 m−2 s−1. The conclusions from this study provide valuable information for estimates of Rs during the peak growing season of maize in three counties in North China. PMID:25157827

A neuromathematical model of human information processing and its application to science content acquisition

NASA Astrophysics Data System (ADS)

Anderson, O. Roger

The rate of information processing during science learning and the efficiency of the learner in mobilizing relevant information in long-term memory as an aid in transmitting newly acquired information to stable storage in long-term memory are fundamental aspects of science content acquisition. These cognitive processes, moreover, may be substantially related in tempo and quality of organization to the efficiency of higher thought processes such as divergent thinking and problem-solving ability that characterize scientific thought. As a contribution to our quantitative understanding of these fundamental information processes, a mathematical model of information acquisition is presented and empirically evaluated in comparison to evidence obtained from experimental studies of science content acquisition. Computer-based models are used to simulate variations in learning parameters and to generate the theoretical predictions to be empirically tested. The initial tests of the predictive accuracy of the model show close agreement between predicted and actual mean recall scores in short-term learning tasks. Implications of the model for human information acquisition and possible future research are discussed in the context of the unique theoretical framework of the model.

Leaf Surface Effects on Retrieving Chlorophyll Content from Hyperspectral Remote Sensing

NASA Astrophysics Data System (ADS)

Qiu, Feng; Chen, JingMing; Ju, Weimin; Wang, Jun; Zhang, Qian

2017-04-01

Light reflected directly from the leaf surface without entering the surface layer is not influenced by leaf internal biochemical content. Leaf surface reflectance varies from leaf to leaf due to differences in the surface roughness features and is relatively more important in strong absorption spectral regions. Therefore it introduces dispersion of data points in the relationship between biochemical concentration and reflectance (especially in the visible region). Separation of surface from total leaf reflection is important to improve the link between leaf pigments content and remote sensing data. This study aims to estimate leaf surface reflectance from hyperspectral remote sensing data and retrieve chlorophyll content by inverting a modified PROSPECT model. Considering leaf surface reflectance is almost the same in the visible and near infrared spectral regions, a surface layer with a reflectance independent of wavelength but varying from leaf to leaf was added to the PROSPECT model. The specific absorption coefficients of pigments were recalibrated. Then the modified model was inverted on independent datasets to check the performance of the model in predicting the chlorophyll content. Results show that differences in estimated surface layer reflectance of various species are noticeable. Surface reflectance of leaves with epicuticular waxes and trichomes is usually higher than other samples. Reconstruction of leaf reflectance and transmittance in the 400-1000 nm wavelength region using the modified PROSPECT model is excellent with low root mean square error (RMSE) and bias. Improvements for samples with high surface reflectance (e.g. maize) are significant, especially for high pigment leaves. Moreover, chlorophyll retrieved from inversion of the modified model is consequently improved (RMSE from 5.9-13.3 ug/cm2 with mean value 8.1 ug/cm2, while mean correlation coefficient is 0.90) compared to results of PROSPECT-5 (RMSE from 9.6-20.2 ug/cm2 with mean value 13.1 ug/cm2, while mean correlation coefficient is 0.81). Underestimation of high chlorophyll content, which is due to underestimation of reflectance in the visible region of PROSPECT, is partially corrected or alleviated. Improvements are particularly noticeable for leaves with high surface reflectance or high chlorophyll content, which both lead to large proportions of surface reflectance to the total leaf reflectance.

Velocities and Attenuations of Gas Hydrate-Bearing Sediments

USGS Publications Warehouse

Lee, Myung W.

2007-01-01

Monopole and dipole logging data at the Mallik 5L-38, Mackenzie Delta, Canada, provide a challenge for sonic velocity and attenuation models used to remotely estimate pore-space gas hydrate content. Velocity and attenuation are linked, with velocity dispersion causing increased attenuation. Sonic waveforms for Mallik 5L-38, however, show no velocity dispersion in gas hydrate-bearing layers, yet are highly attenuated. Attenuation models applied to Mallik 5L-38 data are shown to be inconsistent with the observed velocity measurements, and therefore are suspect in their ability to predict gas hydrate content. A model explicitly linking velocity and attenuation data is presented, accurately predicting gas hydrate content from velocity data alone while demonstrating that the attenuation mechanisms at the Mallik 5L-38 site have not yet been identified.

Ionospheric Slant Total Electron Content Analysis Using Global Positioning System Based Estimation

NASA Technical Reports Server (NTRS)

Komjathy, Attila (Inventor); Mannucci, Anthony J. (Inventor); Sparks, Lawrence C. (Inventor)

2017-01-01

A method, system, apparatus, and computer program product provide the ability to analyze ionospheric slant total electron content (TEC) using global navigation satellite systems (GNSS)-based estimation. Slant TEC is estimated for a given set of raypath geometries by fitting historical GNSS data to a specified delay model. The accuracy of the specified delay model is estimated by computing delay estimate residuals and plotting a behavior of the delay estimate residuals. An ionospheric threat model is computed based on the specified delay model. Ionospheric grid delays (IGDs) and grid ionospheric vertical errors (GIVEs) are computed based on the ionospheric threat model.

Prediction of the true digestible amino acid contents from the chemical composition of sorghum grain for poultry.

PubMed

Ebadi, M R; Sedghi, M; Golian, A; Ahmadi, H

2011-10-01

Accurate knowledge of true digestible amino acid (TDAA) contents of feedstuffs is necessary to accurately formulate poultry diets for profitable production. Several experimental approaches that are highly expensive and time consuming have been used to determine available amino acids. Prediction of the nutritive value of a feed ingredient from its chemical composition via regression methodology has been attempted for many years. The artificial neural network (ANN) model is a powerful method that may describe the relationship between digestible amino acid contents and chemical composition. Therefore, multiple linear regressions (MLR) and ANN models were developed for predicting the TDAA contents of sorghum grain based on chemical composition. A precision-fed assay trial using cecectomized roosters was performed to determine the TDAA contents in 48 sorghum samples from 12 sorghum varieties differing in chemical composition. The input variables for both MLR and ANN models were CP, ash, crude fiber, ether extract, and total phenols whereas the output variable was each individual TDAA for every sample. The results of this study revealed that it is possible to satisfactorily estimate the TDAA of sorghum grain through its chemical composition. The chemical composition of sorghum grain seems to highly influence the TDAA contents when considering components such as CP, crude fiber, ether extract, ash and total phenols. It is also possible to estimate the TDAA contents through multiple regression equations with reasonable accuracy depending on composition. However, a more satisfactory prediction may be achieved via ANN for all amino acids. The R(2) values for the ANN model corresponding to testing and training parameters showed a higher accuracy of prediction than equations established by the MLR method. In addition, the current data confirmed that chemical composition, often considered in total amino acid prediction, could be also a useful predictor of true digestible values of selected amino acids for poultry.

User-Adapted Recommendation of Content on Mobile Devices Using Bayesian Networks

NASA Astrophysics Data System (ADS)

Iwasaki, Hirotoshi; Mizuno, Nobuhiro; Hara, Kousuke; Motomura, Yoichi

Mobile devices, such as cellular phones and car navigation systems, are essential to daily life. People acquire necessary information and preferred content over communication networks anywhere, anytime. However, usability issues arise from the simplicity of user interfaces themselves. Thus, a recommendation of content that is adapted to a user's preference and situation will help the user select content. In this paper, we describe a method to realize such a system using Bayesian networks. This user-adapted mobile system is based on a user model that provides recommendation of content (i.e., restaurants, shops, and music that are suitable to the user and situation) and that learns incrementally based on accumulated usage history data. However, sufficient samples are not always guaranteed, since a user model would require combined dependency among users, situations, and contents. Therefore, we propose the LK method for modeling, which complements incomplete and insufficient samples using knowledge data, and CPT incremental learning for adaptation based on a small number of samples. In order to evaluate the methods proposed, we applied them to restaurant recommendations made on car navigation systems. The evaluation results confirmed that our model based on the LK method can be expected to provide better generalization performance than that of the conventional method. Furthermore, our system would require much less operation than current car navigation systems from the beginning of use. Our evaluation results also indicate that learning a user's individual preference through CPT incremental learning would be beneficial to many users, even with only a few samples. As a result, we have developed the technology of a system that becomes more adapted to a user the more it is used.

Modeling the soil water retention curves of soil-gravel mixtures with regression method on the Loess Plateau of China.

PubMed

Wang, Huifang; Xiao, Bo; Wang, Mingyu; Shao, Ming'an

2013-01-01

Soil water retention parameters are critical to quantify flow and solute transport in vadose zone, while the presence of rock fragments remarkably increases their variability. Therefore a novel method for determining water retention parameters of soil-gravel mixtures is required. The procedure to generate such a model is based firstly on the determination of the quantitative relationship between the content of rock fragments and the effective saturation of soil-gravel mixtures, and then on the integration of this relationship with former analytical equations of water retention curves (WRCs). In order to find such relationships, laboratory experiments were conducted to determine WRCs of soil-gravel mixtures obtained with a clay loam soil mixed with shale clasts or pebbles in three size groups with various gravel contents. Data showed that the effective saturation of the soil-gravel mixtures with the same kind of gravels within one size group had a linear relation with gravel contents, and had a power relation with the bulk density of samples at any pressure head. Revised formulas for water retention properties of the soil-gravel mixtures are proposed to establish the water retention curved surface models of the power-linear functions and power functions. The analysis of the parameters obtained by regression and validation of the empirical models showed that they were acceptable by using either the measured data of separate gravel size group or those of all the three gravel size groups having a large size range. Furthermore, the regression parameters of the curved surfaces for the soil-gravel mixtures with a large range of gravel content could be determined from the water retention data of the soil-gravel mixtures with two representative gravel contents or bulk densities. Such revised water retention models are potentially applicable in regional or large scale field investigations of significantly heterogeneous media, where various gravel sizes and different gravel contents are present.

Modeling the Soil Water Retention Curves of Soil-Gravel Mixtures with Regression Method on the Loess Plateau of China

PubMed Central

Wang, Huifang; Xiao, Bo; Wang, Mingyu; Shao, Ming'an

2013-01-01

Soil water retention parameters are critical to quantify flow and solute transport in vadose zone, while the presence of rock fragments remarkably increases their variability. Therefore a novel method for determining water retention parameters of soil-gravel mixtures is required. The procedure to generate such a model is based firstly on the determination of the quantitative relationship between the content of rock fragments and the effective saturation of soil-gravel mixtures, and then on the integration of this relationship with former analytical equations of water retention curves (WRCs). In order to find such relationships, laboratory experiments were conducted to determine WRCs of soil-gravel mixtures obtained with a clay loam soil mixed with shale clasts or pebbles in three size groups with various gravel contents. Data showed that the effective saturation of the soil-gravel mixtures with the same kind of gravels within one size group had a linear relation with gravel contents, and had a power relation with the bulk density of samples at any pressure head. Revised formulas for water retention properties of the soil-gravel mixtures are proposed to establish the water retention curved surface models of the power-linear functions and power functions. The analysis of the parameters obtained by regression and validation of the empirical models showed that they were acceptable by using either the measured data of separate gravel size group or those of all the three gravel size groups having a large size range. Furthermore, the regression parameters of the curved surfaces for the soil-gravel mixtures with a large range of gravel content could be determined from the water retention data of the soil-gravel mixtures with two representative gravel contents or bulk densities. Such revised water retention models are potentially applicable in regional or large scale field investigations of significantly heterogeneous media, where various gravel sizes and different gravel contents are present. PMID:23555040

Optimizing spatial and temporal constraints for cropland canopy water content retrieval through coupled radiative transfer model inversion

NASA Astrophysics Data System (ADS)

Boren, E. J.; Boschetti, L.; Johnson, D.

2017-12-01

Water plays a critical role in all plant physiological processes, including transpiration, photosynthesis, nutrient transportation, and maintenance of proper plant cell functions. Deficits in water content cause drought-induced stress conditions, such as constrained plant growth and cellular metabolism, while overabundance of water cause anoxic conditions which limit plant physiological processes and promote disease. Vegetation water content maps can provide agricultural producers key knowledge for improving production capacity and resiliency in agricultural systems while facilitating the ability to pinpoint, monitor, and resolve water scarcity issues. Radiative transfer model (RTM) inversion has been successfully applied to remotely sensed data to retrieve biophysical and canopy parameter estimates, including water content. The successful launch of the Landsat 8 Operational Land Imager (OLI) in 2012, Sentinel 2A Multispectral Instrument (MSI) in 2015, followed by Sentinel 2B in 2017, the systematic acquisition schedule and free data distribution policy provide the opportunity for water content estimation at a spatial and temporal scale that can meet the demands of potential operational users: combined, these polar-orbiting systems provide 10 m to 30 m multi-spectral global coverage up to every 3 days. The goal of the present research is to prototype the generation of a cropland canopy water content product, obtained from the newly developed Landsat 8 and Sentinel 2 atmospherically corrected HLS product, through the inversion of the leaf and canopy model PROSAIL5B. We assess the impact of a novel spatial and temporal stratification, where some parameters of the model are constrained by crop type and phenological phase, based on ancillary biophysical data, collected from various crop species grown in a controlled setting and under different water stress conditions. Canopy-level data, collected coincidently with satellite overpasses during four summer field campaigns in northern Idaho (2014 to 2017), are used to validate the results of the model inversion.

An intelligent content discovery technique for health portal content management.

PubMed

De Silva, Daswin; Burstein, Frada

2014-04-23

Continuous content management of health information portals is a feature vital for its sustainability and widespread acceptance. Knowledge and experience of a domain expert is essential for content management in the health domain. The rate of generation of online health resources is exponential and thereby manual examination for relevance to a specific topic and audience is a formidable challenge for domain experts. Intelligent content discovery for effective content management is a less researched topic. An existing expert-endorsed content repository can provide the necessary leverage to automatically identify relevant resources and evaluate qualitative metrics. This paper reports on the design research towards an intelligent technique for automated content discovery and ranking for health information portals. The proposed technique aims to improve efficiency of the current mostly manual process of portal content management by utilising an existing expert-endorsed content repository as a supporting base and a benchmark to evaluate the suitability of new content A model for content management was established based on a field study of potential users. The proposed technique is integral to this content management model and executes in several phases (ie, query construction, content search, text analytics and fuzzy multi-criteria ranking). The construction of multi-dimensional search queries with input from Wordnet, the use of multi-word and single-word terms as representative semantics for text analytics and the use of fuzzy multi-criteria ranking for subjective evaluation of quality metrics are original contributions reported in this paper. The feasibility of the proposed technique was examined with experiments conducted on an actual health information portal, the BCKOnline portal. Both intermediary and final results generated by the technique are presented in the paper and these help to establish benefits of the technique and its contribution towards effective content management. The prevalence of large numbers of online health resources is a key obstacle for domain experts involved in content management of health information portals and websites. The proposed technique has proven successful at search and identification of resources and the measurement of their relevance. It can be used to support the domain expert in content management and thereby ensure the health portal is up-to-date and current.

Radiation Belt and Plasma Model Requirements

NASA Technical Reports Server (NTRS)

Barth, Janet L.

2005-01-01

Contents include the following: Radiation belt and plasma model environment. Environment hazards for systems and humans. Need for new models. How models are used. Model requirements. How can space weather community help?

In defense of compilation: A response to Davis' form and content in model-based reasoning

NASA Technical Reports Server (NTRS)

Keller, Richard

1990-01-01

In a recent paper entitled 'Form and Content in Model Based Reasoning', Randy Davis argues that model based reasoning research aimed at compiling task specific rules from underlying device models is mislabeled, misguided, and diversionary. Some of Davis' claims are examined and his basic conclusions are challenged about the value of compilation research to the model based reasoning community. In particular, Davis' claim is refuted that model based reasoning is exempt from the efficiency benefits provided by knowledge compilation techniques. In addition, several misconceptions are clarified about the role of representational form in compilation. It is concluded that techniques have the potential to make a substantial contribution to solving tractability problems in model based reasoning.

Kinetic improvement of olive leaves' bioactive compounds extraction by using power ultrasound in a wide temperature range.

PubMed

Khemakhem, Ibtihel; Ahmad-Qasem, Margarita Hussam; Catalán, Enrique Barrajón; Micol, Vicente; García-Pérez, Jose Vicente; Ayadi, Mohamed Ali; Bouaziz, Mohamed

2017-01-01

In this study, the effect of temperature and ultrasonic application on extraction kinetics of polyphenols from dried olive leaf was investigated. Conventional (CVE) and ultrasonic-assisted extraction (UAE) were performed at 10, 20, 30, 50 and 70°C using water as solvent. Extracts were characterized by measuring the total phenolic content, the antioxidant capacity and the oleuropein content (HPLC-DAD/MS-MS). Moreover, Naik's model was used to mathematically describe the extraction kinetics. The experimental results showed that phenolic extraction was faster in UAE (ultrasonic-assisted extraction) than in CVE (conventional extraction), being extraction kinetics satisfactorily described using Naik model (include VAR>98%). Besides, the total phenolic content, the antioxidant capacity and the oleuropein content were significantly (p<0.05) improved by increasing the temperature in both CVE and UAE. Oleuropein content reached 6.57±0.18 being extracted approximately 88% in the first minute for UAE experiments. Copyright © 2016 Elsevier B.V. All rights reserved.

Preservice Teachers' Level of Web Pedagogical Content Knowledge: Assessment by Individual Innovativeness

ERIC Educational Resources Information Center

Gökçearslan, Sahin; Karademir, Tugra; Korucu, Agah Tugrul

2017-01-01

Technological Pedagogical Content Knowledge, one of the frameworks proposed in order to popularize the use of technology in a classroom environment, has been customized and has taken the form of Web Pedagogical Content Knowledge. The Relational Screening Model was used in this study. It aims to determine whether a profile of preservice teachers…

The Effect of Content Representation Design Principles on Users' Intuitive Beliefs and Use of E-Learning Systems

ERIC Educational Resources Information Center

Al-Samarraie, Hosam; Selim, Hassan; Zaqout, Fahed

2016-01-01

A model is proposed to assess the effect of different content representation design principles on learners' intuitive beliefs about using e-learning. We hypothesized that the impact of the representation of course contents is mediated by the design principles of alignment, quantity, clarity, simplicity, and affordance, which influence the…

Participatory Social Media and the Evaluation of Online Behavior

ERIC Educational Resources Information Center

DeAndrea, David C.

2012-01-01

In many online settings, the content that appears on a webpage is created by both website owners and viewers. This study employed the folk model of intentionality to examine how people evaluate collectively created web content. The results indicate that how website owners respond to content posted by others can (1) affect the extent to which they…

Bounded and Unbounded Knowledge: Teaching and Learning in a Web 2 World

ERIC Educational Resources Information Center

Nagy, Judy; Bigum, Chris

2007-01-01

In the recent past, the proliferation of digitally available content heralded the beginning of serious problems for the business models of publishers. The ease with which content can be accessed, copied and distributed disrupts the control of those whose role has been to manage and profit from the intellectual property rights of content producers.…

Content Analysis of Suicide Notes as a Test of the Motivational Component of the Existential-Constructivist Model of Suicide

ERIC Educational Resources Information Center

Rogers, James R.; Bromley, Jamie L.; McNally, Christopher J.; Lester, David

2007-01-01

A sample of 40 suicide notes were analyzed for motivational content in relation to an existential-constructivist theory of suicide. Results generally supported the 4 theoretical categories of somatic, relational, spiritual, and psychological motivations, with 39 notes having content that could be classified according to the aforementioned…

Increasing Equity and Achievement in Fifth Grade Mathematics: The Contribution of Content Exposure

ERIC Educational Resources Information Center

Ottmar, Erin R.; Konold, Timothy R.; Berry, Robert Q.; Grissmer, David W.; Cameron, Claire E.

2013-01-01

This study uses a large nationally representative data set (ECLS-K) of 5,181 students to examine the extent to which exposure to content and instructional practice contributes to mathematics achievement in fifth grade. Using hierarchical linear modeling, results suggest that more exposure to content beyond numbers and operations (i.e., geometry,…

[The catecholamine content of the hypothalamus during the modelling of the ulcer process in the gastroduodenal area].

PubMed

Iemel'ianenko, I V; Sultanova, I D; Voronych, N M

1995-01-01

The content of catecholamines in rat hypothalamus in experimental ulcer process in gastroduodenal region has been studied in experiments on rats. It was determined that under these conditions the content of hypothalamus adrenalin increases and the content of noradrenalin decreases. The level of dofamin and DOFA in this brain structure changes in phases. The mentioned shifts depended on the duration and character of the pathological process in the gastroduodenal region.

Content analysis in information flows

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

Grusho, Alexander A.; Faculty of Computational Mathematics and Cybernetics, Moscow State University, Moscow; Grusho, Nick A.

The paper deals with architecture of content recognition system. To analyze the problem the stochastic model of content recognition in information flows was built. We proved that under certain conditions it is possible to solve correctly a part of the problem with probability 1, viewing a finite section of the information flow. That means that good architecture consists of two steps. The first step determines correctly certain subsets of contents, while the second step may demand much more time for true decision.

Centipod WEC, Advanced Controls, Resultant LCOE

DOE Data Explorer

McCall, Alan

2016-02-15

Project resultant LCOE model after implementation of MPC controller. Contains AEP, CBS, model documentation, and LCOE content model. This is meant for comparison with this project's baseline LCOE model.

A nondestructive method to estimate the chlorophyll content of Arabidopsis seedlings

DOE PAGES

Liang, Ying; Urano, Daisuke; Liao, Kang-Ling; ...

2017-04-14

Chlorophyll content decreases in plants under stress conditions, therefore it is used commonly as an indicator of plant health. Arabidopsis thaliana offers a convenient and fast way to test physiological phenotypes of mutations and treatments. But, chlorophyll measurements with conventional solvent extraction are not applicable to Arabidopsis leaves due to their small size, especially when grown on culture dishes. We provide a nondestructive method for chlorophyll measurement whereby the red, green and blue (RGB) values of a color leaf image is used to estimate the chlorophyll content from Arabidopsis leaves. The method accommodates different profiles of digital cameras by incorporatingmore » the ColorChecker chart to make the digital negative profiles, to adjust the white balance, and to calibrate the exposure rate differences caused by the environment so that this method is applicable in any environment. We chose an exponential function model to estimate chlorophyll content from the RGB values, and fitted the model parameters with physical measurements of chlorophyll contents. As further proof of utility, this method was used to estimate chlorophyll content of G protein mutants grown on different sugar to nitrogen ratios. Our method is a simple, fast, inexpensive, and nondestructive estimation of chlorophyll content of Arabidopsis seedlings. This method lead to the discovery that G proteins are important in sensing the C/N balance to control chlorophyll content in Arabidopsis.« less

Processing and memory of information presented in narrative or expository texts.

PubMed

Wolfe, Michael B W; Woodwyk, Joshua M

2010-09-01

Previous research suggests that narrative and expository texts differ in the extent to which they prompt students to integrate to-be-learned content with relevant prior knowledge during comprehension. We expand on previous research by examining on-line processing and representation in memory of to-be-learned content that is embedded in narrative or expository texts. We are particularly interested in how differences in the use of relevant prior knowledge leads to differences in terms of levels of discourse representation (textbase vs. situation model). A total of 61 university undergraduates in Expt 1, and 160 in Expt 2. In Expt 1, subjects thought out loud while comprehending circulatory system content embedded in a narrative or expository text, followed by free recall of text content. In Expt 2, subjects read silently and completed a sentence recognition task to assess memory. In Expt 1, subjects made more associations to prior knowledge while reading the expository text, and recalled more content. Content recall was also correlated with amount of relevant prior knowledge for subjects who read the expository text but not the narrative text. In Expt 2, subjects reading the expository text (compared to the narrative text) had a weaker textbase representation of the to-be-learned content, but a marginally stronger situation model. Results suggest that in terms of to-be-learned content, expository texts trigger students to utilize relevant prior knowledge more than narrative texts.

[Fire behavior of Mongolian oak leaves fuel bed under no-wind and zero-slope conditions. II. Analysis of the factors affecting flame length and residence time and related prediction models].

PubMed

Zhang, Ji-Li; Liu, Bo-Fei; Di, Xue-Ying; Chu, Teng-Fei; Jin, Sen

2012-11-01

Taking fuel moisture content, fuel loading, and fuel bed depth as controlling factors, the fuel beds of Mongolian oak leaves in Maoershan region of Northeast China in field were simulated, and a total of one hundred experimental burnings under no-wind and zero-slope conditions were conducted in laboratory, with the effects of the fuel moisture content, fuel loading, and fuel bed depth on the flame length and its residence time analyzed and the multivariate linear prediction models constructed. The results indicated that fuel moisture content had a significant negative liner correlation with flame length, but less correlation with flame residence time. Both the fuel loading and the fuel bed depth were significantly positively correlated with flame length and its residence time. The interactions of fuel bed depth with fuel moisture content and fuel loading had significant effects on the flame length, while the interactions of fuel moisture content with fuel loading and fuel bed depth affected the flame residence time significantly. The prediction model of flame length had better prediction effect, which could explain 83.3% of variance, with a mean absolute error of 7.8 cm and a mean relative error of 16.2%, while the prediction model of flame residence time was not good enough, which could only explain 54% of variance, with a mean absolute error of 9.2 s and a mean relative error of 18.6%.

Evaluation of Sexual Communication Message Strategies

PubMed Central

2011-01-01

Parent-child communication about sex is an important proximal reproductive health outcome. But while campaigns to promote it such as the Parents Speak Up National Campaign (PSUNC) have been effective, little is known about how messages influence parental cognitions and behavior. This study examines which message features explain responses to sexual communication messages. We content analyzed 4 PSUNC ads to identify specific, measurable message and advertising execution features. We then develop quantitative measures of those features, including message strategies, marketing strategies, and voice and other stylistic features, and merged the resulting data into a dataset drawn from a national media tracking survey of the campaign. Finally, we conducted multivariable logistic regression models to identify relationships between message content and ad reactions/receptivity, and between ad reactions/receptivity and parents' cognitions related to sexual communication included in the campaign's conceptual model. We found that overall parents were highly receptive to the PSUNC ads. We did not find significant associations between message content and ad reactions/receptivity. However, we found that reactions/receptivity to specific PSUNC ads were associated with increased norms, self-efficacy, short- and long-term expectations about parent-child sexual communication, as theorized in the conceptual model. This study extends previous research and methods to analyze message content and reactions/receptivity. The results confirm and extend previous PSUNC campaign evaluation and provide further evidence for the conceptual model. Future research should examine additional message content features and the effects of reactions/receptivity. PMID:21599875

HI-Selected Galaxies in Hierarchical Models of Galaxy Formation and Evolution

NASA Astrophysics Data System (ADS)

Zoldan, Anna

2017-07-01

This poster presents the main results of a statistical study of HI-selected galaxies based on six different semi-analytic models, all run on the same cosmological N-body simulation. One of these models includes an explicit treatment for the partition of cold gas into atomic and molecular hydrogen. All models considered agree nicely with the measured HI mass function in the local Universe and with the measured scaling relations between HI and galaxy stellar mass. Most models also reproduce the observed 2-point correlation function for HI rich galaxies, with the exception of one model that predicts very little HI associated with galaxies in haloes above 10^12 Msun. We investigated the influence of satellite treatment on the final HI content and found that it introduces large uncertainties at low HI masses. We found that the assumption of instantaneous stripping of hot gas in satellites does not translate necessarily in lower HI masses. We demonstrate that the assumed stellar feedback, combined with star formation, also affect significantly the gas content of satellite galaxies. Finally, we also analyse the origin of the correlation between HI content of model galaxies and the spin of the parent haloes. Zoldan et al., 2016, MNRAS, 465, 2236

Exploring the Content of Shared Mental Models in Project Teams

DTIC Science & Technology

2005-09-30

FINAL REPORT Grant Title: EXPLORING THE CONTENT OF SHARED MENTAL MODELS IN PROJECT TEAMS Office of Naval Research Award Number: N000140210535... Research Laboratory, Attn: code 5227, 4555 Overlook Ave., SW, Washington, DC •t• The University of Massachusetts Amherst is an Affirmative Action/Equal...satisfaction. 2.0 PROJECT SUMMARY No consensus among researchers studying shared cognition exists regarding the identification of what should be

Comparison of the Features of EPUB E-Book and SCORM E-Learning Content Model

ERIC Educational Resources Information Center

Chang, Hsuan-Pu; Hung, Jason C.

2018-01-01

E-books nowadays have greatly evolved in its presentation and functions, however its features for education need to be investigated and inspired because people who are accustomed to using printed books may consider and approach it in the same way as they do printed ones. Therefore, the authors compared the EPUB e-book content model with the SCORM…

Non-destructive and rapid prediction of moisture content in red pepper (Capsicum annuum L.) powder using near-infrared spectroscopy and a partial least squares regression model

USDA-ARS?s Scientific Manuscript database

Purpose: The aim of this study was to develop a technique for the non-destructive and rapid prediction of the moisture content in red pepper powder using near-infrared (NIR) spectroscopy and a partial least squares regression (PLSR) model. Methods: Three red pepper powder products were separated in...

Modeling and Explaining Content: Definition, Research Support, and Measurement of the "ETS"® National Observational Teaching Examination (NOTE) Assessment Series. Research Memorandum No. RM-16-07

ERIC Educational Resources Information Center

Stickler, Leslie; Sykes, Gary

2016-01-01

This report reviews the scholarly and research evidence supporting the construct labeled modeling and explaining content (MEC), which is measured via a performance assessment in the "ETS"® National Observational Teaching Examination (NOTE) assessment series. This construct involves practices at the heart of teaching that deal with how…

Assessing Complexity in Learning Outcomes--A Comparison between the SOLO Taxonomy and the Model of Hierarchical Complexity

ERIC Educational Resources Information Center

Stålne, Kristian; Kjellström, Sofia; Utriainen, Jukka

2016-01-01

An important aspect of higher education is to educate students who can manage complex relationships and solve complex problems. Teachers need to be able to evaluate course content with regard to complexity, as well as evaluate students' ability to assimilate complex content and express it in the form of a learning outcome. One model for evaluating…

Design of experiments-based monitoring of critical quality attributes for the spray-drying process of insulin by NIR spectroscopy.

PubMed

Maltesen, Morten Jonas; van de Weert, Marco; Grohganz, Holger

2012-09-01

Moisture content and aerodynamic particle size are critical quality attributes for spray-dried protein formulations. In this study, spray-dried insulin powders intended for pulmonary delivery were produced applying design of experiments methodology. Near infrared spectroscopy (NIR) in combination with preprocessing and multivariate analysis in the form of partial least squares projections to latent structures (PLS) were used to correlate the spectral data with moisture content and aerodynamic particle size measured by a time of flight principle. PLS models predicting the moisture content were based on the chemical information of the water molecules in the NIR spectrum. Models yielded prediction errors (RMSEP) between 0.39% and 0.48% with thermal gravimetric analysis used as reference method. The PLS models predicting the aerodynamic particle size were based on baseline offset in the NIR spectra and yielded prediction errors between 0.27 and 0.48 μm. The morphology of the spray-dried particles had a significant impact on the predictive ability of the models. Good predictive models could be obtained for spherical particles with a calibration error (RMSECV) of 0.22 μm, whereas wrinkled particles resulted in much less robust models with a Q (2) of 0.69. Based on the results in this study, NIR is a suitable tool for process analysis of the spray-drying process and for control of moisture content and particle size, in particular for smooth and spherical particles.

The Efficiency of UVC Radiation in the Inactivation of
Listeria monocytogenes on Beef-Agar Food Models.

PubMed

Hamidi-Oskouei, Amir M; James, Christian; James, Stephen

2015-06-01

The aim of this study is to evaluate the effect of meat content and surface smoothness on the deactivation of Listeria monocytogenes in beef-agar food models achieved by shortwave ultraviolet (UVC) light. Food models with various meat contents were made using chopped beef slices and agar solution. Prepared models together with a Listeria selective agar (LSA) plate and a slice of cooked beef were inoculated with L. monocytogenes and then exposed to UVC light. Population of Listeria reduced to below the level of detection on the LSA plates. As the content of beef in the beef-agar models increased, more L. monocytogenes cells survived. Survival was greatest on the treated cooked slice of beef. To better understand the effect of surface irregularities, a white light interferometer was used to analyse the surface smoothness of beef-agar media and LSA plates. No correlation was observed between the surface roughness of seven out of nine types of produced beef-agar media and the degree of inactivation resulting from UVC radiation at the given dose, whereas, less bacterial cells were killed as beef content of the food models increased. The findings of the current study show that the chemical composition of the treated sample also plays an important role in pathogen resistance and survival, meaning that two samples with similar surface irregularities but different chemical composition might produce very different inactivation results when exposed to UVC light.

The Efficiency of UVC Radiation in the Inactivation of
Listeria monocytogenes on Beef-Agar Food Models

PubMed Central

James, Christian; James, Stephen

2015-01-01

Summary The aim of this study is to evaluate the effect of meat content and surface smoothness on the deactivation of Listeria monocytogenes in beef-agar food models achieved by shortwave ultraviolet (UVC) light. Food models with various meat contents were made using chopped beef slices and agar solution. Prepared models together with a Listeria selective agar (LSA) plate and a slice of cooked beef were inoculated with L. monocytogenes and then exposed to UVC light. Population of Listeria reduced to below the level of detection on the LSA plates. As the content of beef in the beef-agar models increased, more L. monocytogenes cells survived. Survival was greatest on the treated cooked slice of beef. To better understand the effect of surface irregularities, a white light interferometer was used to analyse the surface smoothness of beef-agar media and LSA plates. No correlation was observed between the surface roughness of seven out of nine types of produced beef-agar media and the degree of inactivation resulting from UVC radiation at the given dose, whereas, less bacterial cells were killed as beef content of the food models increased. The findings of the current study show that the chemical composition of the treated sample also plays an important role in pathogen resistance and survival, meaning that two samples with similar surface irregularities but different chemical composition might produce very different inactivation results when exposed to UVC light. PMID:27904353

Thermal degradation kinetics of anthocyanins from blood orange, blackberry, and roselle using the arrhenius, eyring, and ball models.

PubMed

Cisse, Mady; Vaillant, Fabrice; Acosta, Oscar; Dhuique-Mayer, Claudie; Dornier, Manuel

2009-07-22

Anthocyanin stability was assessed over temperatures ranging from 30 to 90 degrees C for seven products: blood orange juice [Citrus sinensis (L.) Osbeck]; two tropical highland blackberry juices (Rubus adenotrichus Schlech.), one with high content and the other with low content of suspended insoluble solids (SIS); and four roselle extracts (Hibiscus sabdariffa L.). The blackberry juice showed the highest content of anthocyanins with 1.2 g/L (two times less in the roselle extracts and 12 times less in the blood orange juice). The rate constant for anthocyanin degradation and isothermal kinetic parameters were calculated according to three models: Arrhenius, Eyring, and Ball. Anthocyanins in blood orange juice presented the highest rate constant for degradation, followed by the blackberry juices and roselle extracts. Values of activation energies were 66 and 37 kJ/mol, respectively, for blood orange and blackberry and 47-61 kJ/mol for roselle extracts. For the blackberry juices, a high SIS content provided only slight protection for the anthocyanins. The increasing content of dissolved oxygen, from 0.5 to 8.5 g/L, did not significantly increase the rate constant. For both isothermal and nonisothermal treatments, all three models accurately predicted anthocyanin losses from different food matrices.

Detection of triterpene acids distribution in loquat (Eriobotrya japonica) leaf using hyperspectral imaging

NASA Astrophysics Data System (ADS)

Shi, Jiyong; Chen, Wu; Zou, Xiaobo; Xu, Yiwei; Huang, Xiaowei; Zhu, Yaodi; Shen, Tingting

2018-01-01

Hyperspectral images (431-962 nm) and partial least squares (PLS) were used to detect the distribution of triterpene acids within loquat (Eriobotrya japonica) leaves. 72 fresh loquat leaves in the young group, mature group and old group were collected for hyperspectral imaging; and triterpene acids content of the loquat leaves was analyzed using high performance liquid chromatography (HPLC). Then the spectral data of loquat leaf hyperspectral images and the triterpene acids content were employed to build calibration models. After spectra pre-processing and wavelength selection, an optimum calibration model (Rp = 0.8473, RMSEP = 2.61 mg/g) for predicting triterpene acids was obtained by synergy interval partial least squares (siPLS). Finally, spectral data of each pixel in the loquat leaf hyperspectral image were extracted and substituted into the optimum calibration model to predict triterpene acids content of each pixel. Therefore, the distribution map of triterpene acids content was obtained. As shown in the distribution map, triterpene acids are accumulated mainly in the leaf mesophyll regions near the main veins, and triterpene acids concentration of young group is less than that of mature and old groups. This study showed that hyperspectral imaging is suitable to determine the distribution of active constituent content in medical herbs in a rapid and non-invasive manner.

Resolving model parameter values from carbon and nitrogen stock measurements in a wide range of tropical mature forests using nonlinear inversion and regression trees

USGS Publications Warehouse

Liu, S.; Anderson, P.; Zhou, G.; Kauffman, B.; Hughes, F.; Schimel, D.; Watson, Vicente; Tosi, Joseph

2008-01-01

Objectively assessing the performance of a model and deriving model parameter values from observations are critical and challenging in landscape to regional modeling. In this paper, we applied a nonlinear inversion technique to calibrate the ecosystem model CENTURY against carbon (C) and nitrogen (N) stock measurements collected from 39 mature tropical forest sites in seven life zones in Costa Rica. Net primary productivity from the Moderate-Resolution Imaging Spectroradiometer (MODIS), C and N stocks in aboveground live biomass, litter, coarse woody debris (CWD), and in soils were used to calibrate the model. To investigate the resolution of available observations on the number of adjustable parameters, inversion was performed using nine setups of adjustable parameters. Statistics including observation sensitivity, parameter correlation coefficient, parameter sensitivity, and parameter confidence limits were used to evaluate the information content of observations, resolution of model parameters, and overall model performance. Results indicated that soil organic carbon content, soil nitrogen content, and total aboveground biomass carbon had the highest information contents, while measurements of carbon in litter and nitrogen in CWD contributed little to the parameter estimation processes. The available information could resolve the values of 2-4 parameters. Adjusting just one parameter resulted in under-fitting and unacceptable model performance, while adjusting five parameters simultaneously led to over-fitting. Results further indicated that the MODIS NPP values were compressed as compared with the spatial variability of net primary production (NPP) values inferred from inverse modeling. Using inverse modeling to infer NPP and other sensitive model parameters from C and N stock observations provides an opportunity to utilize data collected by national to regional forest inventory systems to reduce the uncertainties in the carbon cycle and generate valuable databases to validate and improve MODIS NPP algorithms.

A game-theoretical approach to multimedia social networks security.

PubMed

Liu, Enqiang; Liu, Zengliang; Shao, Fei; Zhang, Zhiyong

2014-01-01

The contents access and sharing in multimedia social networks (MSNs) mainly rely on access control models and mechanisms. Simple adoptions of security policies in the traditional access control model cannot effectively establish a trust relationship among parties. This paper proposed a novel two-party trust architecture (TPTA) to apply in a generic MSN scenario. According to the architecture, security policies are adopted through game-theoretic analyses and decisions. Based on formalized utilities of security policies and security rules, the choice of security policies in content access is described as a game between the content provider and the content requester. By the game method for the combination of security policies utility and its influences on each party's benefits, the Nash equilibrium is achieved, that is, an optimal and stable combination of security policies, to establish and enhance trust among stakeholders.

Predictive modeling of low solubility semiconductor alloys

NASA Astrophysics Data System (ADS)

Rodriguez, Garrett V.; Millunchick, Joanna M.

2016-09-01

GaAsBi is of great interest for applications in high efficiency optoelectronic devices due to its highly tunable bandgap. However, the experimental growth of high Bi content films has proven difficult. Here, we model GaAsBi film growth using a kinetic Monte Carlo simulation that explicitly takes cation and anion reactions into account. The unique behavior of Bi droplets is explored, and a sharp decrease in Bi content upon Bi droplet formation is demonstrated. The high mobility of simulated Bi droplets on GaAsBi surfaces is shown to produce phase separated Ga-Bi droplets as well as depressions on the film surface. A phase diagram for a range of growth rates that predicts both Bi content and droplet formation is presented to guide the experimental growth of high Bi content GaAsBi films.

A Game-Theoretical Approach to Multimedia Social Networks Security

PubMed Central

Liu, Enqiang; Liu, Zengliang; Shao, Fei; Zhang, Zhiyong

2014-01-01

The contents access and sharing in multimedia social networks (MSNs) mainly rely on access control models and mechanisms. Simple adoptions of security policies in the traditional access control model cannot effectively establish a trust relationship among parties. This paper proposed a novel two-party trust architecture (TPTA) to apply in a generic MSN scenario. According to the architecture, security policies are adopted through game-theoretic analyses and decisions. Based on formalized utilities of security policies and security rules, the choice of security policies in content access is described as a game between the content provider and the content requester. By the game method for the combination of security policies utility and its influences on each party's benefits, the Nash equilibrium is achieved, that is, an optimal and stable combination of security policies, to establish and enhance trust among stakeholders. PMID:24977226

Colorimetric Analysis of Hibiscus Beverages and their Potential Antioxidant Properties.

PubMed

Camelo-Méndez, G A; Vanegas-Espinoza, P E; Escudero-Gilete, M L; Heredia, F J; Paredes-López, O; Del Villar-Martínez, A A

2018-05-25

In food industry, roselle beverages and their subproducts could be functional ingredients since they are an excellent source of bioactive compounds with improved performance due to their important anthocyanins content. The aim of this study was to analyze anthocyanin content and antioxidant properties of aqueous infusions elaborated with color contrasting Hibiscus materials and design a mathematical model in order to predict color-composition relationship. Color measurements of beverages from roselle (Negra, Sudan and Rosa) were made by transmission spectrophotometry, anthocyanins quantification was determined by HPLC, and antioxidant potential was evaluated by in vitro methods (ABTS and FRAP assays). Beverages prepared with particle size minor of 250 μm presented until 4- and 2- times more anthocyanins content and antioxidant capacity respectively, in comparison to beverages prepared with powders with particle size major of 750 μm. Positive correlations among pigments composition and color parameters were found (p < 0.05), showing that anthocyanins content, antioxidant capacity, C* ab and h ab values increased in relation with the smallest particle size of flours. Also, mathematical models were stablished to predict anthocyanin content (r ≥ 0.97) and antioxidant capacity (r ≥ 0.89) from color data; we propose equations for quick estimation of the antioxidant capacity in the Hibiscus beverages with high anthocyanin content. The obtained models could be an important tool to be used in food industry for pigment characterization or functional compounds with potential health benefits.

Estimation of soil sorption coefficients of veterinary pharmaceuticals from soil properties.

PubMed

ter Laak, Thomas L; Gebbink, Wouter A; Tolls, Johannes

2006-04-01

Environmental exposure assessment of veterinary pharmaceuticals requires estimating the sorption to soil. Soil sorption coefficients of three common, ionizable, antimicrobial agents (oxytetracycline [OTC], tylosin [TYL], and sulfachloropyridazine [SCP]) were studied in relation to the soil properties of 11 different soils. The soil sorption coefficient at natural pH varied from 950 to 7,200, 10 to 370, and 0.4 to 35 L/kg for OTC, TYL, and SCP, respectively. The variation increased by almost two orders of magnitude for OTC and TYL when pH was artificially adjusted. Separate soil properties (pH, organic carbon content, clay content, cation-exchange capacity, aluminum oxyhydroxide content, and iron oxyhydroxide content) were not able to explain more than half the variation observed in soil sorption coefficients. This reflects the complexity of the sorbent-sorbate interactions. Partial-least-squares (PLS) models, integrating all the soil properties listed above, were able to explain as much as 78% of the variation in sorption coefficients. The PLS model was able to predict the sorption coefficient with an accuracy of a factor of six. Considering the pH-dependent speciation, species-specific PLS models were developed. These models were able to predict species-specific sorption coefficients with an accuracy of a factor of three to four. However, the species-specific sorption models did not improve the estimation of sorption coefficients of species mixtures, because these models were developed with a reduced data set at standardized aqueous concentrations. In conclusion, pragmatic approaches like PLS modeling might be suitable to estimate soil sorption for risk assessment purposes.

Physical retrieval of precipitation water contents from Special Sensor Microwave/Imager (SSM/I) data. Part 1: A cloud ensemble/radiative parameterization for sensor response (report version)

NASA Technical Reports Server (NTRS)

Olson, William S.; Raymond, William H.

1990-01-01

The physical retrieval of geophysical parameters based upon remotely sensed data requires a sensor response model which relates the upwelling radiances that the sensor observes to the parameters to be retrieved. In the retrieval of precipitation water contents from satellite passive microwave observations, the sensor response model has two basic components. First, a description of the radiative transfer of microwaves through a precipitating atmosphere must be considered, because it is necessary to establish the physical relationship between precipitation water content and upwelling microwave brightness temperature. Also the spatial response of the satellite microwave sensor (or antenna pattern) must be included in the description of sensor response, since precipitation and the associated brightness temperature field can vary over a typical microwave sensor resolution footprint. A 'population' of convective cells, as well as stratiform clouds, are simulated using a computationally-efficient multi-cylinder cloud model. Ensembles of clouds selected at random from the population, distributed over a 25 km x 25 km model domain, serve as the basis for radiative transfer calculations of upwelling brightness temperatures at the SSM/I frequencies. Sensor spatial response is treated explicitly by convolving the upwelling brightness temperature by the domain-integrated SSM/I antenna patterns. The sensor response model is utilized in precipitation water content retrievals.

Quantitative determination of wool in textile by near-infrared spectroscopy and multivariate models.

PubMed

Chen, Hui; Tan, Chao; Lin, Zan

2018-08-05

The wool content in textiles is a key quality index and the corresponding quantitative analysis takes an important position due to common adulterations in both raw and finished textiles. Conventional methods are maybe complicated, destructive, time-consuming, environment-unfriendly. Developing a quick, easy-to-use and green alternative method is interesting. The work focuses on exploring the feasibility of combining near-infrared (NIR) spectroscopy and several partial least squares (PLS)-based algorithms and elastic component regression (ECR) algorithms for measuring wool content in textile. A total of 108 cloth samples with wool content ranging from 0% to 100% (w/w) were collected and all the compositions are really existent in the market. The dataset was divided equally into the training and test sets for developing and validating calibration models. When using local PLS, the original spectrum axis was split into 20 sub-intervals. No obvious difference of performance can be seen for the local PLS models. The ECR model is comparable or superior to the other models due its flexibility, i.e., being transition state from PCR to PLS. It seems that ECR combined with NIR technique may be a potential method for determining wool content in textile products. In addition, it might have regulatory advantages to avoid time-consuming and environmental-unfriendly chemical analysis. Copyright © 2018 Elsevier B.V. All rights reserved.

[Effects of electroacupuncture of "Sanyinjiao" (SP 6) on contents of MDA and beta-EP, and expression of HSP 70 in the uterus in rats with dysmenorrhea].

PubMed

Song, Xiao-Lin; Zhang, Lu-Fen; Li, Xiao-Hong; Xu, Li-Li; Li, Chun-Hua; Ding, Xi-Yan; Ren, Xiao-Xuan; Zhao, Ya-Fang; Guo, Meng-Wei; Sun, Zhi-Fang; Zhu, Jiang

2010-10-01

To investigate the effect of electroacupuncture (EA) of "Sanyinjiao" (SP 6) on the uterus in dysmenorrhea rats so as to study its underlying analgesic mechanism. A total of 48 SD rats during diestrus were randomized into normal saline (control) group, model group and acupuncture group according to a random number table, with 16 rats in each group. Dysmenorrhea model was established by subcutaneous injection of Estradiol benzoate (0.5 mg/d on the 1st and 10th day, and 0.2 mg/d from day 2 to day 9, once daily for 10 days) and oxytocin (2 U/rat, once on day 10). Malondialdehyde (MDA) and beta-endorphin (beta-EP) contents in the uterus were detected by radioimmunoassay, and the heat shock protein 70 (HSP 70) immunoactivity of the uterus was detected by immunohistochemistry. In comparison with the control group, MDA content in the uterus was increased significantly in the model group (P < 0.01), while the beta-EP level and the immunoactivity of HSP 70 immune-reaction (IR) positive products in the uterus decrease significantly (P < 0.01) and moderately, respectively in the model group. In comparison with the model group, uterine MDA content in the EA group was decreased significantly (P < 0.01), while uterine beta-EP level increased considerably (P < 0.01) and HSP 70 expression was upregulated to a certain degree. EA of "Sanyinjiao" (SP 6) can reduce MDA content and upregulate beta-EP level of the uterus in rats with dysmenorrhea, which may contribute to its analgesic effect in relieving dysmenorrhea by clearing away oxygen free radicals and raising analgesic substance in the uterus.

Desert soil clay content estimation using reflectance spectroscopy preprocessed by fractional derivative

PubMed Central

Tiyip, Tashpolat; Ding, Jianli; Zhang, Dong; Liu, Wei; Wang, Fei; Tashpolat, Nigara

2017-01-01

Effective pretreatment of spectral reflectance is vital to model accuracy in soil parameter estimation. However, the classic integer derivative has some disadvantages, including spectral information loss and the introduction of high-frequency noise. In this paper, the fractional order derivative algorithm was applied to the pretreatment and partial least squares regression (PLSR) was used to assess the clay content of desert soils. Overall, 103 soil samples were collected from the Ebinur Lake basin in the Xinjiang Uighur Autonomous Region of China, and used as data sets for calibration and validation. Following laboratory measurements of spectral reflectance and clay content, the raw spectral reflectance and absorbance data were treated using the fractional derivative order from the 0.0 to the 2.0 order (order interval: 0.2). The ratio of performance to deviation (RPD), determinant coefficients of calibration (Rc2), root mean square errors of calibration (RMSEC), determinant coefficients of prediction (Rp2), and root mean square errors of prediction (RMSEP) were applied to assess the performance of predicting models. The results showed that models built on the fractional derivative order performed better than when using the classic integer derivative. Comparison of the predictive effects of 22 models for estimating clay content, calibrated by PLSR, showed that those models based on the fractional derivative 1.8 order of spectral reflectance (Rc2 = 0.907, RMSEC = 0.425%, Rp2 = 0.916, RMSEP = 0.364%, and RPD = 2.484 ≥ 2.000) and absorbance (Rc2 = 0.888, RMSEC = 0.446%, Rp2 = 0.918, RMSEP = 0.383% and RPD = 2.511 ≥ 2.000) were most effective. Furthermore, they performed well in quantitative estimations of the clay content of soils in the study area. PMID:28934274

Psychotomimetic effects of different doses of MK-801 and the underlying mechanisms in a selective memory impairment model.

PubMed

Liu, Weiqing; Wang, Dong; Hong, Wenjuan; Yu, Yi; Tang, Jinsong; Wang, Jicai; Liu, Fang; Xu, Xiufeng; Tan, Liwen; Chen, Xiaogang

2017-03-01

Although N-methyl-d-aspartate receptor antagonists-induced hypoglutamate rodent models are the most well-established models for preclinical studies of schizophrenia-related deficits, they also evoke a wide spectrum of psychotomimetic side effects. It is significant to increase the specificity of hypoglutamate rodent models. In this study, the recognition memory was evaluated in rats by object recognition test (ORT), sensorimotor gating was evaluated by prepulse inhibition of the startle reflex (PPI), and locomotor activity was measured using open field test. High-performance liquid chromatography was used to measure neurotransmitters content in the medial prefrontal cortex (mPFC) and thalamus (THA). Total Akt and phospho-Akt protein was measured by Western blots. Results showed that 0.3mg/kg of MK-801 was most effective in inducing locomotion. 0.3mg/kg of MK-801 was most effective in decreasing PPI. 0.03mg/kg of MK-801 was most effective in decreasing object memory while not affecting exploration manners in the training session. 0.03mg/kg of MK-801 significantly increased HVA and Glu content in the mPFC. 0.1mg/kg of MK-801 significantly decreased GABA content in the THA. 0.03mg/kg of MK-801 significantly decreased Akt phosphorylation in the mPFC, which was related to the ORT index. In conclusion, a dose of 0.03mg/kg MK-801 can establish a "pure" memory impairment model without contaminations of sensorimotor gating and locomotor activity. MK-801-induced cognitive deficits is associated with increased DA metabolites and glutamate content in the mPFC and decreased GABA content in the THA as well as decrease in Akt phosphorylation in the mPFC. Copyright © 2016. Published by Elsevier B.V.

Soil-water content characterisation in a modified Jarvis-Stewart model: A case study of a conifer forest on a shallow unconfined aquifer

NASA Astrophysics Data System (ADS)

Guyot, Adrien; Fan, Junliang; Oestergaard, Kasper T.; Whitley, Rhys; Gibbes, Badin; Arsac, Margaux; Lockington, David A.

2017-01-01

Groundwater-vegetation-atmosphere fluxes were monitored for a subtropical coastal conifer forest in South-East Queensland, Australia. Observations were used to quantify seasonal changes in transpiration rates with respect to temporal fluctuations of the local water table depth. The applicability of a Modified Jarvis-Stewart transpiration model (MJS), which requires soil-water content data, was assessed for this system. The influence of single depth values compared to use of vertically averaged soil-water content data on MJS-modelled transpiration was assessed over both a wet and a dry season, where the water table depth varied from the surface to a depth of 1.4 m below the surface. Data for tree transpiration rates relative to water table depth showed that trees transpire when the water table was above a threshold depth of 0.8 m below the ground surface (water availability is non-limiting). When the water table reached the ground surface (i.e., surface flooding) transpiration was found to be limited. When the water table is below this threshold depth, a linear relationship between water table depth and the transpiration rate was observed. MJS modelling results show that the influence of different choices for soil-water content on transpiration predictions was insignificant in the wet season. However, during the dry season, inclusion of deeper soil-water content data improved the model performance (except for days after isolated rainfall events, here a shallower soil-water representation was better). This study demonstrated that, to improve MJS simulation results, appropriate selection of soil water measurement depths based on the dynamic behaviour of soil water profiles through the root zone was required in a shallow unconfined aquifer system.

Effects of visual and verbal sexual television content and perceived realism on attitudes and beliefs.

PubMed

Tayler, Laramie D

2005-05-01

Previous studies of the effects of sexual television content have resulted in mixed findings. Based on the information processing model of media effects, I proposed that the messages embodied n such content, the degree to which viewers perceive television content as realistic, and whether sexual content is conveyed using visual or verbal symbols may influence the nature or degree of such effects. I explored this possibility through an experiment in which 182 college undergraduates were exposed to visual or verbal sexual television content, neutral television content, or no television at all prior to completing measures of sexual attitudes and beliefs. Although exposure to sexual content generally did not produce significant main effects, it did influence the attitudes of those who perceive television to be relatively realistic. Verbal sexual content was found to influence beliefs about women's sexual activity among the same group.

Land surface evapotranspiration modelling at the regional scale

NASA Astrophysics Data System (ADS)

Raffelli, Giulia; Ferraris, Stefano; Canone, Davide; Previati, Maurizio; Gisolo, Davide; Provenzale, Antonello

2017-04-01

Climate change has relevant implications for the environment, water resources and human life in general. The observed increment of mean air temperature, in addition to a more frequent occurrence of extreme events such as droughts, may have a severe effect on the hydrological cycle. Besides climate change, land use changes are assumed to be another relevant component of global change in terms of impacts on terrestrial ecosystems: socio-economic changes have led to conversions between meadows and pastures and in most cases to a complete abandonment of grasslands. Water is subject to different physical processes among which evapotranspiration (ET) is one of the most significant. In fact, ET plays a key role in estimating crop growth, water demand and irrigation water management, so estimating values of ET can be crucial for water resource planning, irrigation requirement and agricultural production. Potential evapotranspiration (PET) is the amount of evaporation that occurs when a sufficient water source is available. It can be estimated just knowing temperatures (mean, maximum and minimum) and solar radiation. Actual evapotranspiration (AET) is instead the real quantity of water which is consumed by soil and vegetation; it is obtained as a fraction of PET. The aim of this work was to apply a simplified hydrological model to calculate AET for the province of Turin (Italy) in order to assess the water content and estimate the groundwater recharge at a regional scale. The soil is seen as a bucket (FAO56 model, Allen et al., 1998) made of different layers, which interact with water and vegetation. The water balance is given by precipitations (both rain and snow) and dew as positive inputs, while AET, runoff and drainage represent the rate of water escaping from soil. The difference between inputs and outputs is the water stock. Model data inputs are: soil characteristics (percentage of clay, silt, sand, rocks and organic matter); soil depth; the wilting point (i.e. the minimal point of soil moisture that plant requires not to wilt); the field capacity (i.e. the maximum amount of water content that a soil can held); the available water content (AWC), obtained as the difference between field capacity and wilting point. Furthermore, the model considers 15 different ID of land use, with a resolution of 250 m. The model was then tested by a direct comparison with experimental data. First, the modelled water content from the surface down to 65 cm of soil depth was compared to the measured one with a Time Domain Reflectometry (TDR) in Grugliasco (TO), a non-irrigated flat permanent meadow, for years 2006-2008. Here, the soil is sandy with a slope of about 1%. Then, considering three corn farms located in the Cuneo district, the goodness of modelled irrigations was verified. The soil texture of the three farms, analysed according to the USDA criteria, is loam or silty-loam. In particular, we compared the number of irrigations done by the farmers with the ones given by the model, which irrigates as soon as the plant reaches an imposed level of water stress. We also compared the irrigation turn given by the model with the farmers' one. Then we compared the modelled water content with the one measured before and after the irrigation. We observed that the modelled irrigation occurred when the measured water content was close to the modelled wilting point. In both test cases, the model seems to reflect quite well the real behaviour of water content.

Webizing mobile augmented reality content

NASA Astrophysics Data System (ADS)

Ahn, Sangchul; Ko, Heedong; Yoo, Byounghyun

2014-01-01

This paper presents a content structure for building mobile augmented reality (AR) applications in HTML5 to achieve a clean separation of the mobile AR content and the application logic for scaling as on the Web. We propose that the content structure contains the physical world as well as virtual assets for mobile AR applications as document object model (DOM) elements and that their behaviour and user interactions are controlled through DOM events by representing objects and places with a uniform resource identifier. Our content structure enables mobile AR applications to be seamlessly developed as normal HTML documents under the current Web eco-system.

Near-infrared diffuse reflection systems for chlorophyll content of tomato leaves measurement

NASA Astrophysics Data System (ADS)

Jiang, Huanyu; Ying, Yibin; Lu, Huishan

2006-10-01

In this study, two measuring systems for chlorophyll content of tomato leaves were developed based on near-infrared spectral techniques. The systems mainly consists of a FT-IR spectrum analyzer, optic fiber diffuses reflection accessories and data card. Diffuse reflectance of intact tomato leaves was measured by an optics fiber optic fiber diffuses reflection accessory and a smart diffuses reflection accessory. Calibration models were developed from spectral and constituent measurements. 90 samples served as the calibration sets and 30 samples served as the validation sets. Partial least squares (PLS) and principal component regression (PCR) technique were used to develop the prediction models by different data preprocessing. The best model for chlorophyll content had a high correlation efficient of 0.9348 and a low standard error of prediction RMSEP of 4.79 when we select full range (12500-4000 cm -1), MSC path length correction method by the log(1/R). The results of this study suggest that FT-NIR method can be feasible to detect chlorophyll content of tomato leaves rapidly and nondestructively.

A network flow model for load balancing in circuit-switched multicomputers

NASA Technical Reports Server (NTRS)

Bokhari, Shahid H.

1990-01-01

In multicomputers that utilize circuit switching or wormhole routing, communication overhead depends largely on link contention - the variation due to distance between nodes is negligible. This has a major impact on the load balancing problem. In this case, there are some nodes with excess load (sources) and others with deficit load (sinks) and it is required to find a matching of sources to sinks that avoids contention. The problem is made complex by the hardwired routing on currently available machines: the user can control only which nodes communicate but not how the messages are routed. Network flow models of message flow in the mesh and the hypercube were developed to solve this problem. The crucial property of these models is the correspondence between minimum cost flows and correctly routed messages. To solve a given load balancing problem, a minimum cost flow algorithm is applied to the network. This permits one to determine efficiently a maximum contention free matching of sources to sinks which, in turn, tells one how much of the given imbalance can be eliminated without contention.

Impacts of amount of impregnated iron in granular activated carbon on arsenate adsorption capacities and kinetics.

PubMed

Chang, Qigang; Lin, Wei; Ying, Wei-Chi

2012-06-01

Iron-impregnated granular activated carbons (Fe-GAC) can remove arsenic effectively from water. In this study, Fe-GACs with iron content of 1.64 to 28.90% were synthesized using a new multi-step procedure for the investigation of effects of iron amount on arsenic adsorption capacities and kinetics. Langmuir model satisfactorily fit arsenic adsorption on Fe-GACs. The maximum arsenic adsorption capacity (q(m)) increased significantly with iron impregnation and reached 1,867 to 1,912 microg/g with iron content of 9.96 to 13.59%. Further increase of iron content (> 13.59%) caused gradual decrease of q(m). It was found that the amount of impregnated iron showed little impact on the affinity for arsenate. Kinetic study showed that the amount of impregnated iron affected the arsenic intraparticle diffusion rate greatly. The pseudo-second-order kinetic model fit arsenic adsorption kinetics on Fe-GACs better than the pseudo-first-order model. The arsenic adsorption rate increased with increasing of iron content from 1.64% to 13.59%, and then decreased with more impregnated iron (13.59 to 28.90%).

Improving Global Models of Remotely Sensed Ocean Chlorophyll Content Using Partial Least Squares and Geographically Weighted Regression

NASA Astrophysics Data System (ADS)

Gholizadeh, H.; Robeson, S. M.

2015-12-01

Empirical models have been widely used to estimate global chlorophyll content from remotely sensed data. Here, we focus on the standard NASA empirical models that use blue-green band ratios. These band ratio ocean color (OC) algorithms are in the form of fourth-order polynomials and the parameters of these polynomials (i.e. coefficients) are estimated from the NASA bio-Optical Marine Algorithm Data set (NOMAD). Most of the points in this data set have been sampled from tropical and temperate regions. However, polynomial coefficients obtained from this data set are used to estimate chlorophyll content in all ocean regions with different properties such as sea-surface temperature, salinity, and downwelling/upwelling patterns. Further, the polynomial terms in these models are highly correlated. In sum, the limitations of these empirical models are as follows: 1) the independent variables within the empirical models, in their current form, are correlated (multicollinear), and 2) current algorithms are global approaches and are based on the spatial stationarity assumption, so they are independent of location. Multicollinearity problem is resolved by using partial least squares (PLS). PLS, which transforms the data into a set of independent components, can be considered as a combined form of principal component regression (PCR) and multiple regression. Geographically weighted regression (GWR) is also used to investigate the validity of spatial stationarity assumption. GWR solves a regression model over each sample point by using the observations within its neighbourhood. PLS results show that the empirical method underestimates chlorophyll content in high latitudes, including the Southern Ocean region, when compared to PLS (see Figure 1). Cluster analysis of GWR coefficients also shows that the spatial stationarity assumption in empirical models is not likely a valid assumption.

Study of Temporal Effects on Subjective Video Quality of Experience.

PubMed

Bampis, Christos George; Zhi Li; Moorthy, Anush Krishna; Katsavounidis, Ioannis; Aaron, Anne; Bovik, Alan Conrad

2017-11-01

HTTP adaptive streaming is being increasingly deployed by network content providers, such as Netflix and YouTube. By dividing video content into data chunks encoded at different bitrates, a client is able to request the appropriate bitrate for the segment to be played next based on the estimated network conditions. However, this can introduce a number of impairments, including compression artifacts and rebuffering events, which can severely impact an end-user's quality of experience (QoE). We have recently created a new video quality database, which simulates a typical video streaming application, using long video sequences and interesting Netflix content. Going beyond previous efforts, the new database contains highly diverse and contemporary content, and it includes the subjective opinions of a sizable number of human subjects regarding the effects on QoE of both rebuffering and compression distortions. We observed that rebuffering is always obvious and unpleasant to subjects, while bitrate changes may be less obvious due to content-related dependencies. Transient bitrate drops were preferable over rebuffering only on low complexity video content, while consistently low bitrates were poorly tolerated. We evaluated different objective video quality assessment algorithms on our database and found that objective video quality models are unreliable for QoE prediction on videos suffering from both rebuffering events and bitrate changes. This implies the need for more general QoE models that take into account objective quality models, rebuffering-aware information, and memory. The publicly available video content as well as metadata for all of the videos in the new database can be found at http://live.ece.utexas.edu/research/LIVE_NFLXStudy/nflx_index.html.

Ocean carbon and heat variability in an Earth System Model

NASA Astrophysics Data System (ADS)

Thomas, J. L.; Waugh, D.; Gnanadesikan, A.

2016-12-01

Ocean carbon and heat content are very important for regulating global climate. Furthermore, due to lack of observations and dependence on parameterizations, there has been little consensus in the modeling community on the magnitude of realistic ocean carbon and heat content variability, particularly in the Southern Ocean. We assess the differences between global oceanic heat and carbon content variability in GFDL ESM2Mc using a 500-year, pre-industrial control simulation. The global carbon and heat content are directly out of phase with each other; however, in the Southern Ocean the heat and carbon content are in phase. The global heat mutli-decadal variability is primarily explained by variability in the tropics and mid-latitudes, while the variability in global carbon content is primarily explained by Southern Ocean variability. In order to test the robustness of this relationship, we use three additional pre-industrial control simulations using different mesoscale mixing parameterizations. Three pre-industrial control simulations are conducted with the along-isopycnal diffusion coefficient (Aredi) set to constant values of 400, 800 (control) and 2400 m2 s-1. These values for Aredi are within the range of parameter settings commonly used in modeling groups. Finally, one pre-industrial control simulation is conducted where the minimum in the Gent-McWilliams parameterization closure scheme (AGM) increased to 600 m2 s-1. We find that the different simulations have very different multi-decadal variability, especially in the Weddell Sea where the characteristics of deep convection are drastically changed. While the temporal frequency and amplitude global heat and carbon content changes significantly, the overall spatial pattern of variability remains unchanged between the simulations.

Beyond clay - using selective extractions to improve predictions of soil carbon content

NASA Astrophysics Data System (ADS)

Rasmussen, C.; Berhe, A. A.; Blankinship, J. C.; Crow, S. E.; Druhan, J. L.; Heckman, K. A.; Keiluweit, M.; Lawrence, C. R.; Marin-Spiotta, E.; Plante, A. F.; Schaedel, C.; Schimel, J.; Sierra, C. A.; Thompson, A.; Wagai, R.; Wieder, W. R.

2016-12-01

A central component of modern soil carbon (C) models is the use of clay content to scale the relative partitioning of decomposing plant material to respiration and mineral stabilized soil C. However, numerous pedon to plot scale studies indicate that other soil mineral parameters, such as Fe- or Al-oxyhydroxide content and specific surface area, may be more effective than clay alone for predicting soil C content and stabilization. Here we directly address the following question: Are there soil physicochemical parameters that represent mineral C association and soil C content that can replace or be used in conjunction with clay content as scalars in soil C models. We explored the relationship of soil C content to a number of soil physicochemical and physiographic parameters using the National Cooperative Soil Survey database that contains horizon level data for > 62,000 pedons spanning global ecoregions and geographic areas. The data indicated significant variation in the degree of correlation among soil C, clay and Fe-/Al-oxyhydroxides with increasing moisture variability. Specifically, dry, water-limited systems (PET/MAP > 1) presented strong positive correlations between clay and soil C, that decreased significantly to little or no correlation in wet, energy-limited systems (PET/MAP < 1). In contrast, the correlation of soil C to oxalate extractable Al+Fe increased significantly with increasing moisture availability. This pattern was particularly well expressed for subsurface B horizons. Multivariate analyses indicated similar patterns, with clear climate and ecosystem level variation in the degree of correlation among soil C and soil physicochemical properties. The results indicate a need to modify current soil C models to incorporate additional C partitioning parameters that better account for climate and ecoregion variability in C stabilization mechanisms.

Energy content of stormtime ring current from phase space mapping simulations

NASA Technical Reports Server (NTRS)

Chen, Margaret W.; Schulz, Michael; Lyons, Larry R.

1993-01-01

We perform a phase space mapping study to estimate the enhancement in energy content that results from stormtime particle transport in the equatorial magnetosphere. Our pre-storm phase space distribution is based on a steady-state transport model. Using results from guiding-center simulations of ion transport during model storms having main phases of 3 hr, 6 hr, and 12 hr, we map phase space distributions of ring current protons from the pre-storm distribution in accordance with Liouville's theorem. We find that transport can account for the entire ten to twenty-fold increase in magnetospheric particle energy content typical of a major storm if a realistic stormtime enhancement of the phase space density f is imposed at the nightside tail plasma sheet (represented by an enhancement of f at the neutral line in our model).

Respondeo: method and content in casuistry.

PubMed

Wildes, Kevin Wm

1994-02-01

James Tallmon has argued that my criticisms of Jonsen and Toulmin are ill founded. Tallmon argues that Jonsen and Toulmin argue for a method of rhetorical reasoning and not for a particular content. He argues that if one distinguishes the content and method of casuistry the Jonsen-Toulmin model can work. But Tallmon, like Jonsen and Toulmin, cannot escape the need for casuistry to have a content. Tallmon's response evidences that need since he assumes that there is a 'Medical Community' which has a moral vision.

Thermal properties of soils: effect of biochar application

NASA Astrophysics Data System (ADS)

Usowicz, Boguslaw; Lukowski, Mateusz; Lipiec, Jerzy

2014-05-01

Thermal properties (thermal conductivity, heat capacity and thermal diffusivity) have a significant effect on the soil surface energy partitioning and resulting in the temperature distribution. Thermal properties of soil depend on water content, bulk density and organic matter content. An important source of organic matter is biochar. Biochar as a material is defined as: "charcoal for application as a soil conditioner". Biochar is generally associated with co-produced end products of pyrolysis. Many different materials are used as biomass feedstock for biochar, including wood, crop residues and manures. Additional predictions were done for terra preta soil (also known as "Amazonian dark earth"), high in charcoal content, due to adding a mixture of charcoal, bone, and manure for thousands of years i.e. approximately 10-1,000 times longer than residence times of most soil organic matter. The effect of biochar obtained from the wood biomass and other organic amendments (peat, compost) on soil thermal properties is presented in this paper. The results were compared with wetland soils of different organic matter content. The measurements of the thermal properties at various water contents were performed after incubation, under laboratory conditions using KD2Pro, Decagon Devices. The measured data were compared with predictions made using Usowicz statistical-physical model (Usowicz et al., 2006) for biochar, mineral soil and soil with addition of biochar at various water contents and bulk densities. The model operates statistically by probability of occurrence of contacts between particular fractional compounds. It combines physical properties, specific to particular compounds, into one apparent conductance specific to the mixture. The results revealed that addition of the biochar and other organic amendments into the soil caused considerable reduction of the thermal conductivity and diffusivity. The mineral soil showed the highest thermal conductivity and diffusivity that decreased in soil with addition of biochar and pure biochar. The reduction of both properties was mostly due to decrease in both particle density and bulk density. Both biochar and the organic amendments addition resulted in a decrease of the heat capacity of the mixtures in dry state and considerable increase in wet state. The lowest and highest reduction in the thermal conductivity with decreasing water content was obtained for pure biochar and mineral soil, respectively. The thermal diffusivity had a characteristic maximum at higher bulk densities and lower water contents. The wetland soil higher in organic matter content exhibit smaller temporal variation of the thermal properties compared to soils lower in organic matter content in response to changes of water content. The statistical-physical model was found to be useful for satisfactory predicting thermal properties of the soil with addition of biochar and organic amendments. Usowicz B. et al., 2006. Thermal conductivity modelling of terrestrial soil media - A comparative study. Planetary and Space Science 54, 1086-1095.

Experimental determination of CO2 content at graphite saturation along a natural basalt-peridotite melt join: Implications for the fate of carbon in terrestrial magma oceans

NASA Astrophysics Data System (ADS)

Duncan, Megan S.; Dasgupta, Rajdeep; Tsuno, Kyusei

2017-05-01

Knowledge of the carbon carrying capacity of peridotite melt at reducing conditions is critical to constrain the mantle budget and planet-scale distribution of carbon set at early stage of differentiation. Yet, neither measurements of CO2 content in reduced peridotite melt nor a reliable model to extrapolate the known solubility of CO2 in basaltic (mafic) melt to solubility in peridotitic (ultramafic) melt exist. There are several reasons for this gap; one reason is due to the unknown relative contributions of individual network modifying cations, such as Ca2+ versus Mg2+, on carbonate dissolution particularly at reducing conditions. Here we conducted high pressure, temperature experiments to estimate the CO2 contents in silicate melts at graphite saturation over a compositional range from natural basalts toward peridotite at a fixed pressure (P) of 1.0 GPa, temperature (T) of 1600 °C, and oxygen fugacity (log ⁡ fO2 ∼ IW + 1.6). We also conducted experiments to determine the relative effects of variable Ca and Mg contents in mafic compositions on the dissolution of carbonate. Carbon in quenched glasses was measured and characterized using Fourier transform infrared spectroscopy (FTIR) and Raman Spectroscopy and was found to be dissolved as carbonate (CO32-). The FTIR spectra showed CO32- doublets that shifted systematically with the MgO and CaO content of silicate melts. Using our data and previous work we constructed a new composition-based model to determine the CO2 content of ultramafic (peridotitic) melt representative of an early Earth, magma ocean composition at graphite saturation. Our data and model suggest that the dissolved CO2 content of reduced, peridotite melt is significantly higher than that of basaltic melt at shallow magma ocean conditions; however, the difference in C content between the basaltic and peridotitic melts may diminish with depth as the more depolymerized peridotite melt is more compressible. Using our model of CO2 content at graphite saturation as a function of P-T-fO2-melt composition, we predict that a superliquidus shallow magma ocean should degas CO2. Whereas if the increase of fO2 with depth is weak, a magma ocean may ingas a modest amount of carbon during crystallization. Further, using the carbon content of peridotite melt at log ⁡ fO2 of IW and the knowledge of C content of Fe-rich alloy melt, we also consider the core-mantle partitioning of carbon, showing that DCmetal/peridotite of a shallow magma ocean is generally higher than previously estimated.

Coupled land surface-subsurface hydrogeophysical inverse modeling to estimate soil organic carbon content and explore associated hydrological and thermal dynamics in the Arctic tundra

NASA Astrophysics Data System (ADS)

Phuong Tran, Anh; Dafflon, Baptiste; Hubbard, Susan S.

2017-09-01

Quantitative characterization of soil organic carbon (OC) content is essential due to its significant impacts on surface-subsurface hydrological-thermal processes and microbial decomposition of OC, which both in turn are important for predicting carbon-climate feedbacks. While such quantification is particularly important in the vulnerable organic-rich Arctic region, it is challenging to achieve due to the general limitations of conventional core sampling and analysis methods, and to the extremely dynamic nature of hydrological-thermal processes associated with annual freeze-thaw events. In this study, we develop and test an inversion scheme that can flexibly use single or multiple datasets - including soil liquid water content, temperature and electrical resistivity tomography (ERT) data - to estimate the vertical distribution of OC content. Our approach relies on the fact that OC content strongly influences soil hydrological-thermal parameters and, therefore, indirectly controls the spatiotemporal dynamics of soil liquid water content, temperature and their correlated electrical resistivity. We employ the Community Land Model to simulate nonisothermal surface-subsurface hydrological dynamics from the bedrock to the top of canopy, with consideration of land surface processes (e.g., solar radiation balance, evapotranspiration, snow accumulation and melting) and ice-liquid water phase transitions. For inversion, we combine a deterministic and an adaptive Markov chain Monte Carlo (MCMC) optimization algorithm to estimate a posteriori distributions of desired model parameters. For hydrological-thermal-to-geophysical variable transformation, the simulated subsurface temperature, liquid water content and ice content are explicitly linked to soil electrical resistivity via petrophysical and geophysical models. We validate the developed scheme using different numerical experiments and evaluate the influence of measurement errors and benefit of joint inversion on the estimation of OC and other parameters. We also quantify the propagation of uncertainty from the estimated parameters to prediction of hydrological-thermal responses. We find that, compared to inversion of single dataset (temperature, liquid water content or apparent resistivity), joint inversion of these datasets significantly reduces parameter uncertainty. We find that the joint inversion approach is able to estimate OC and sand content within the shallow active layer (top 0.3 m of soil) with high reliability. Due to the small variations of temperature and moisture within the shallow permafrost (here at about 0.6 m depth), the approach is unable to estimate OC with confidence. However, if the soil porosity is functionally related to the OC and mineral content, which is often observed in organic-rich Arctic soil, the uncertainty of OC estimate at this depth remarkably decreases. Our study documents the value of the new surface-subsurface, deterministic-stochastic inversion approach, as well as the benefit of including multiple types of data to estimate OC and associated hydrological-thermal dynamics.

Computer programs for adjusting the mechanical properties of 2-inch dimension lumber for changes in moisture content

Treesearch

James W. Evans; Jane K. Evans; David W. Green

1990-01-01

This paper presents computer programs for adjusting the mechanical properties of 2-in. dimension lumber for changes in moisture content. Mechanical properties adjusted are modulus of rupture, ultimate tensile stress parallel to the grain, ultimate compressive stress parallel to the gain, and flexural modulus of elasticity. The models are valid for moisture contents...

"I'm Not the Science Type": Effect of an Inquiry Biology Content Course on Preservice Elementary Teachers' Intentions about Teaching Science

ERIC Educational Resources Information Center

Weld, Jeffrey; Funk, Lucas

2005-01-01

Inquiry Into Life Science is a content biology course expressly for the fulfillment of the General Education life science laboratory course requirement of elementary education majors at this university. The course is modeled on the Teaching Standards and Content Standards of the National Science Education Standards [National Research Council.…

Formation Mechanism of Oxide-Sulfide Complex Inclusions in High-Sulfur-Containing Steel Melts

NASA Astrophysics Data System (ADS)

Shin, Jae Hong; Park, Joo Hyun

2018-02-01

The [S] content in resulfurized steel is controlled in the range of 200 to 800 ppm to ensure good machinability and workability. It is well known that "MgAl2O4(spinel)+CaS" complex inclusions are formed in molten steel during the ladle refining process, and these cause nozzle clogging during continuous casting. Thus, in the present study, the "Refractory-Slag-Metal-Inclusions (ReSMI)" multiphase reaction model was employed in conjunction with experiments to investigate the influence of slag composition and [S] content in the steel on the formation of oxide-sulfide complex inclusions. The critical [S] and [Al] contents necessary for the precipitation of CaS in the CaO-Al2O3-MgO-SiO2 (CAMS) oxide inclusions were predicted from the composition of the liquid inclusions, as observed by scanning electron microscopy-electron dispersive spectrometry (SEM-EDS) and calculated using the ReSMI multiphase reaction model. The critical [S] content increases with increasing content of SiO2 in the slag at a given [Al] content. Formation mechanisms for spinel+CaS and spinel+MnS complex inclusions were also proposed.

[Inversion of organic matter content of the north fluvo-aquic soil based on hyperspectral and multi-spectra].

PubMed

Wang, Yan-Cang; Gu, Xiao-He; Zhu, Jin-Shan; Long, Hui-Ling; Xu, Peng; Liao, Qin-Hong

2014-01-01

The present study aims to assess the feasibility of multi-spectral data in monitoring soil organic matter content. The data source comes from hyperspectral measured under laboratory condition, and simulated multi-spectral data from the hyperspectral. According to the reflectance response functions of Landsat TM and HJ-CCD (the Environment and Disaster Reduction Small Satellites, HJ), the hyperspectra were resampled for the corresponding bands of multi-spectral sensors. The correlation between hyperspectral, simulated reflectance spectra and organic matter content was calculated, and used to extract the sensitive bands of the organic matter in the north fluvo-aquic soil. The partial least square regression (PLSR) method was used to establish experiential models to estimate soil organic matter content. Both root mean squared error (RMSE) and coefficient of the determination (R2) were introduced to test the precision and stability of the modes. Results demonstrate that compared with the hyperspectral data, the best model established by simulated multi-spectral data gives a good result for organic matter content, with R2=0.586, and RMSE=0.280. Therefore, using multi-spectral data to predict tide soil organic matter content is feasible.

Modelling the combustion of charcoal in a model blast furnace

NASA Astrophysics Data System (ADS)

Shen, Yansong; Shiozawa, Tomo; Yu, Aibing; Austin, Peter

2013-07-01

The pulverized charcoal (PCH) combustion in ironmaking blast furnaces is abstracting remarkable attention due to various benefits such as lowering CO2 emission. In this study, a three-dimensional CFD model is used to simulate the flow and thermo-chemical behaviours in this process. The model is validated against the experimental results from a pilot-scale combustion test rig for a range of conditions. The typical flow and thermo-chemical phenomena is simulated. The effect of charcoal type, i.e. VM content is examined, showing that the burnout increases with VM content in a linear relationship. This model provides an effective way for designing and optimizing PCH operation in blast furnace practice.

Estimating net rainfall, evaporation and water storage of a bare soil from sequential L-band emissivities

NASA Technical Reports Server (NTRS)

Stroosnijder, L.; Lascano, R. J.; Newton, R. W.; Vanbavel, C. H. M.

1984-01-01

A general method to use a time series of L-band emissivities as an input to a hydrological model for continuously monitoring the net rainfall and evaporation as well as the water content over the entire soil profile is proposed. The model requires a sufficiently accurate and general relation between soil emissivity and surface moisture content. A model which requires the soil hydraulic properties as an additional input, but does not need any weather data was developed. The method is shown to be numerically consistent.

A Science for Citizenship Model: Assessing the Effects of Benefits, Risks, and Trust for Predicting Students' Interest in and Understanding of Science-Related Content

ERIC Educational Resources Information Center

Jack, Brady Michael; Lee, Ling; Yang, Kuay-Keng; Lin, Huann-shyang

2017-01-01

This study showcases the Science for Citizenship Model (SCM) as a new instructional methodology for presenting, to secondary students, science-related technology content related to the use of science in society not taught in the science curriculum, and a new approach for assessing the intercorrelations among three independent variables (benefits,…

The Effects of a Socioscientific Issues Instructional Model in Secondary Agricultural Education on Students' Content Knowledge, Scientific Reasoning Ability, Argumentation Skills, and Views of the Nature of Science

ERIC Educational Resources Information Center

Shoulders, Catherine Woglom

2012-01-01

The purpose of this study was to determine the effects of a socioscientific issues-based instructional model on secondary agricultural education students' content knowledge, scientific reasoning ability, argumentation skills, and views of the nature of science. This study utilized a pre-experimental, single group pretest-posttest design to assess…

Building global models for fat and total protein content in raw milk based on historical spectroscopic data in the visible and short-wave near infrared range.

PubMed

Melenteva, Anastasiia; Galyanin, Vladislav; Savenkova, Elena; Bogomolov, Andrey

2016-07-15

A large set of fresh cow milk samples collected from many suppliers over a large geographical area in Russia during a year has been analyzed by optical spectroscopy in the range 400-1100 nm in accordance with previously developed scatter-based technique. The global (i.e. resistant to seasonal, genetic, regional and other variations of the milk composition) models for fat and total protein content, which were built using partial least-squares (PLS) regression, exhibit satisfactory prediction performances enabling their practical application in the dairy. The root mean-square errors of prediction (RMSEP) were 0.09 and 0.10 for fat and total protein content, respectively. The issues of raw milk analysis and multivariate modelling based on the historical spectroscopic data have been considered and approaches to the creation of global models and their transfer between the instruments have been proposed. Availability of global models should significantly facilitate the dissemination of optical spectroscopic methods for the laboratory and in-line quantitative milk analysis. Copyright © 2016. Published by Elsevier Ltd.

Development of NIRS models to predict protein and amylose content of brown rice and proximate compositions of rice bran.

PubMed

Bagchi, Torit Baran; Sharma, Srigopal; Chattopadhyay, Krishnendu

2016-01-15

With the escalating persuasion of economic and nutritional importance of rice grain protein and nutritional components of rice bran (RB), NIRS can be an effective tool for high throughput screening in rice breeding programme. Optimization of NIRS is prerequisite for accurate prediction of grain quality parameters. In the present study, 173 brown rice (BR) and 86 RB samples with a wide range of values were used to compare the calibration models generated by different chemometrics for grain protein (GPC) and amylose content (AC) of BR and proximate compositions (protein, crude oil, moisture, ash and fiber content) of RB. Various modified partial least square (mPLSs) models corresponding with the best mathematical treatments were identified for all components. Another set of 29 genotypes derived from the breeding programme were employed for the external validation of these calibration models. High accuracy of all these calibration and prediction models was ensured through pair t-test and correlation regression analysis between reference and predicted values. Copyright © 2015 Elsevier Ltd. All rights reserved.

How do we know what makes for "best practice" in clinical supervision for psychological therapists? A content analysis of supervisory models and approaches.

PubMed

Simpson-Southward, Chloe; Waller, Glenn; Hardy, Gillian E

2017-11-01

Clinical supervision for psychotherapies is widely used in clinical and research contexts. Supervision is often assumed to ensure therapy adherence and positive client outcomes, but there is little empirical research to support this contention. Regardless, there are numerous supervision models, but it is not known how consistent their recommendations are. This review aimed to identify which aspects of supervision are consistent across models, and which are not. A content analysis of 52 models revealed 71 supervisory elements. Models focus more on supervisee learning and/or development (88.46%), but less on emotional aspects of work (61.54%) or managerial or ethical responsibilities (57.69%). Most models focused on the supervisee (94.23%) and supervisor (80.77%), rather than the client (48.08%) or monitoring client outcomes (13.46%). Finally, none of the models were clearly or adequately empirically based. Although we might expect clinical supervision to contribute to positive client outcomes, the existing models have limited client focus and are inconsistent. Therefore, it is not currently recommended that one should assume that the use of such models will ensure consistent clinician practice or positive therapeutic outcomes. There is little evidence for the effectiveness of supervision. There is a lack of consistency in supervision models. Services need to assess whether supervision is effective for practitioners and patients. Copyright © 2017 John Wiley & Sons, Ltd.

A comparative modeling study of a dual tracer experiment in a large lysimeter under atmospheric conditions

NASA Astrophysics Data System (ADS)

Stumpp, C.; Nützmann, G.; Maciejewski, S.; Maloszewski, P.

2009-09-01

SummaryIn this paper, five model approaches with different physical and mathematical concepts varying in their model complexity and requirements were applied to identify the transport processes in the unsaturated zone. The applicability of these model approaches were compared and evaluated investigating two tracer breakthrough curves (bromide, deuterium) in a cropped, free-draining lysimeter experiment under natural atmospheric boundary conditions. The data set consisted of time series of water balance, depth resolved water contents, pressure heads and resident concentrations measured during 800 days. The tracer transport parameters were determined using a simple stochastic (stream tube model), three lumped parameter (constant water content model, multi-flow dispersion model, variable flow dispersion model) and a transient model approach. All of them were able to fit the tracer breakthrough curves. The identified transport parameters of each model approach were compared. Despite the differing physical and mathematical concepts the resulting parameters (mean water contents, mean water flux, dispersivities) of the five model approaches were all in the same range. The results indicate that the flow processes are also describable assuming steady state conditions. Homogeneous matrix flow is dominant and a small pore volume with enhanced flow velocities near saturation was identified with variable saturation flow and transport approach. The multi-flow dispersion model also identified preferential flow and additionally suggested a third less mobile flow component. Due to high fitting accuracy and parameter similarity all model approaches indicated reliable results.

Water Sorption Isotherm of Pea Starch Edible Films and Prediction Models.

PubMed

Saberi, Bahareh; Vuong, Quan V; Chockchaisawasdee, Suwimol; Golding, John B; Scarlett, Christopher J; Stathopoulos, Costas E

2015-12-24

The moisture sorption isotherm of pea starch films prepared with various glycerol contents as plasticizer was investigated at different storage relative humidities (11%-96% RH) and at 5 ± 1, 15 ± 1, 25 ± 1 and 40 ± 1 °C by using gravimetric method. The results showed that the equilibrium moisture content of all films increased substantially above a w = 0.6. Films plasticized with glycerol, under all temperatures and RH conditions (11%-96%), adsorbed more moisture resulting in higher equilibrium moisture contents. Reduction of the temperature enhanced the equilibrium moisture content and monolayer water of the films. The obtained experimental data were fitted to different models including two-parameter equations (Oswin, Henderson, Brunauer-Emmitt-Teller (BET), Flory-Huggins, and Iglesias-Chirife), three-parameter equations Guggenhiem-Anderson-deBoer (GAB), Ferro-Fontan, and Lewicki) and a four-parameter equation (Peleg). The three-parameter Lewicki model was found to be the best-fitted model for representing the experimental data within the studied temperatures and whole range of relative humidities (11%-98%). Addition of glycerol increased the net isosteric heat of moisture sorption of pea starch film. The results provide important information with estimating of stability and functional characteristics of the films in various environments.

Textual and visual content-based anti-phishing: a Bayesian approach.

PubMed

Zhang, Haijun; Liu, Gang; Chow, Tommy W S; Liu, Wenyin

2011-10-01

A novel framework using a Bayesian approach for content-based phishing web page detection is presented. Our model takes into account textual and visual contents to measure the similarity between the protected web page and suspicious web pages. A text classifier, an image classifier, and an algorithm fusing the results from classifiers are introduced. An outstanding feature of this paper is the exploration of a Bayesian model to estimate the matching threshold. This is required in the classifier for determining the class of the web page and identifying whether the web page is phishing or not. In the text classifier, the naive Bayes rule is used to calculate the probability that a web page is phishing. In the image classifier, the earth mover's distance is employed to measure the visual similarity, and our Bayesian model is designed to determine the threshold. In the data fusion algorithm, the Bayes theory is used to synthesize the classification results from textual and visual content. The effectiveness of our proposed approach was examined in a large-scale dataset collected from real phishing cases. Experimental results demonstrated that the text classifier and the image classifier we designed deliver promising results, the fusion algorithm outperforms either of the individual classifiers, and our model can be adapted to different phishing cases. © 2011 IEEE

Climate controls photosynthetic capacity more than leaf nitrogen contents

NASA Astrophysics Data System (ADS)

Ali, A. A.; Xu, C.; McDowell, N. G.

2013-12-01

Global vegetation models continue to lack the ability to make reliable predictions because the photosynthetic capacity varies a lot with growth conditions, season and among species. It is likely that vegetation models link photosynthetic capacity to concurrent changes in leaf nitrogen content only. To improve the predictions of the vegetation models, there is an urgent need to review species growth conditions and their seasonal response to changing climate. We sampled the global distribution of the Vcmax (maximum carboxylation rates) data of various species across different environmental gradients from the literature and standardized its value to 25 degree Celcius. We found that species explained the largest variation in (1) the photosynthetic capacity and (2) the proportion of nitrogen allocated for rubisco (PNcb). Surprisingly, climate variables explained more variations in photosynthetic capacity as well as PNcb than leaf nitrogen content and/or specific leaf area. The chief climate variables that explain variation in photosynthesis and PNcb were radiation, temperature and daylength. Our analysis suggests that species have the greatest control over photosynthesis and PNcb. Further, compared to leaf nitrogen content and/or specific leaf area, climate variables have more control over photosynthesis and PNcb. Therefore, climate variables should be incorporated in the global vegetation models when making predictions about the photosynthetic capacity.

Comparison of APSIM and DNDC simulations of nitrogen transformations and N2O emissions.

PubMed

Vogeler, I; Giltrap, D; Cichota, R

2013-11-01

Various models have been developed to better understand nitrogen (N) cycling in soils, which is governed by a complex interaction of physical, chemical and biological factors. Two process-based models, the Agricultural Production Systems sIMulator (APSIM) and DeNitrification DeComposition (DNDC), were used to simulate nitrification, denitrification and nitrous oxide (N2O) emissions from soils following N input from either fertiliser or excreta deposition. The effect of environmental conditions on N transformations as simulated by the two different models was compared. Temperature had a larger effect in APSIM on nitrification, whereas in DNDC, water content produced a larger response. In contrast, simulated denitrification showed a larger response to temperature and also organic carbon content in DNDC. And while denitrification in DNDC is triggered by rainfall ≥5mm/h, in APSIM, the driving factor is soil water content, with a trigger point at water content at field capacity. The two models also showed different responses to N load, with nearly linearly increasing N2O emission rates with N load simulated by DNDC, and a lower rate by APSIM. Increasing rainfall intensity decreased APSIM-simulated N2O emissions but increased those simulated by DNDC. Copyright © 2012 Elsevier B.V. All rights reserved.

Personalized summarization using user preference for m-learning

NASA Astrophysics Data System (ADS)

Lee, Sihyoung; Yang, Seungji; Ro, Yong Man; Kim, Hyoung Joong

2008-02-01

As the Internet and multimedia technology is becoming advanced, the number of digital multimedia contents is also becoming abundant in learning area. In order to facilitate the access of digital knowledge and to meet the need of a lifelong learning, e-learning could be the helpful alternative way to the conventional learning paradigms. E-learning is known as a unifying term to express online, web-based and technology-delivered learning. Mobile-learning (m-learning) is defined as e-learning through mobile devices using wireless transmission. In a survey, more than half of the people remarked that the re-consumption was one of the convenient features in e-learning. However, it is not easy to find user's preferred segmentation from a full version of lengthy e-learning content. Especially in m-learning, a content-summarization method is strongly required because mobile devices are limited to low processing power and battery capacity. In this paper, we propose a new user preference model for re-consumption to construct personalized summarization for re-consumption. The user preference for re-consumption is modeled based on user actions with statistical model. Based on the user preference model for re-consumption with personalized user actions, our method discriminates preferred parts over the entire content. Experimental results demonstrated successful personalized summarization.

Development and Validation of a Near-Infrared Spectroscopy Method for the Prediction of Acrylamide Content in French-Fried Potato.

PubMed

Adedipe, Oluwatosin E; Johanningsmeier, Suzanne D; Truong, Van-Den; Yencho, G Craig

2016-03-02

This study investigated the ability of near-infrared spectroscopy (NIRS) to predict acrylamide content in French-fried potato. Potato flour spiked with acrylamide (50-8000 μg/kg) was used to determine if acrylamide could be accurately predicted in a potato matrix. French fries produced with various pretreatments and cook times (n = 84) and obtained from quick-service restaurants (n = 64) were used for model development and validation. Acrylamide was quantified using gas chromatography-mass spectrometry, and reflectance spectra (400-2500 nm) of each freeze-dried sample were captured on a Foss XDS Rapid Content Analyzer-NIR spectrometer. Partial least-squares (PLS) discriminant analysis and PLS regression modeling demonstrated that NIRS could accurately detect acrylamide content as low as 50 μg/kg in the model potato matrix. Prediction errors of 135 μg/kg (R(2) = 0.98) and 255 μg/kg (R(2) = 0.93) were achieved with the best PLS models for acrylamide prediction in Russet Norkotah French-fried potato and multiple samples of unknown varieties, respectively. The findings indicate that NIRS can be used as a screening tool in potato breeding and potato processing research to reduce acrylamide in the food supply.

Modeling the Effects of Cu Content and Deformation Variables on the High-Temperature Flow Behavior of Dilute Al-Fe-Si Alloys Using an Artificial Neural Network.

PubMed

Shakiba, Mohammad; Parson, Nick; Chen, X-Grant

2016-06-30

The hot deformation behavior of Al-0.12Fe-0.1Si alloys with varied amounts of Cu (0.002-0.31 wt %) was investigated by uniaxial compression tests conducted at different temperatures (400 °C-550 °C) and strain rates (0.01-10 s -1 ). The results demonstrated that flow stress decreased with increasing deformation temperature and decreasing strain rate, while flow stress increased with increasing Cu content for all deformation conditions studied due to the solute drag effect. Based on the experimental data, an artificial neural network (ANN) model was developed to study the relationship between chemical composition, deformation variables and high-temperature flow behavior. A three-layer feed-forward back-propagation artificial neural network with 20 neurons in a hidden layer was established in this study. The input parameters were Cu content, temperature, strain rate and strain, while the flow stress was the output. The performance of the proposed model was evaluated using the K-fold cross-validation method. The results showed excellent generalization capability of the developed model. Sensitivity analysis indicated that the strain rate is the most important parameter, while the Cu content exhibited a modest but significant influence on the flow stress.

Water Sorption Isotherm of Pea Starch Edible Films and Prediction Models

PubMed Central

Saberi, Bahareh; Vuong, Quan V.; Chockchaisawasdee, Suwimol; Golding, John B.; Scarlett, Christopher J.; Stathopoulos, Costas E.

2015-01-01

The moisture sorption isotherm of pea starch films prepared with various glycerol contents as plasticizer was investigated at different storage relative humidities (11%–96% RH) and at 5 ± 1, 15 ± 1, 25 ± 1 and 40 ± 1 °C by using gravimetric method. The results showed that the equilibrium moisture content of all films increased substantially above aw = 0.6. Films plasticized with glycerol, under all temperatures and RH conditions (11%–96%), adsorbed more moisture resulting in higher equilibrium moisture contents. Reduction of the temperature enhanced the equilibrium moisture content and monolayer water of the films. The obtained experimental data were fitted to different models including two-parameter equations (Oswin, Henderson, Brunauer–Emmitt–Teller (BET), Flory–Huggins, and Iglesias–Chirife), three-parameter equations Guggenhiem–Anderson–deBoer (GAB), Ferro–Fontan, and Lewicki) and a four-parameter equation (Peleg). The three-parameter Lewicki model was found to be the best-fitted model for representing the experimental data within the studied temperatures and whole range of relative humidities (11%–98%). Addition of glycerol increased the net isosteric heat of moisture sorption of pea starch film. The results provide important information with estimating of stability and functional characteristics of the films in various environments. PMID:28231096

Modeling the Effects of Cu Content and Deformation Variables on the High-Temperature Flow Behavior of Dilute Al-Fe-Si Alloys Using an Artificial Neural Network

PubMed Central

Shakiba, Mohammad; Parson, Nick; Chen, X.-Grant

2016-01-01

The hot deformation behavior of Al-0.12Fe-0.1Si alloys with varied amounts of Cu (0.002–0.31 wt %) was investigated by uniaxial compression tests conducted at different temperatures (400 °C–550 °C) and strain rates (0.01–10 s−1). The results demonstrated that flow stress decreased with increasing deformation temperature and decreasing strain rate, while flow stress increased with increasing Cu content for all deformation conditions studied due to the solute drag effect. Based on the experimental data, an artificial neural network (ANN) model was developed to study the relationship between chemical composition, deformation variables and high-temperature flow behavior. A three-layer feed-forward back-propagation artificial neural network with 20 neurons in a hidden layer was established in this study. The input parameters were Cu content, temperature, strain rate and strain, while the flow stress was the output. The performance of the proposed model was evaluated using the K-fold cross-validation method. The results showed excellent generalization capability of the developed model. Sensitivity analysis indicated that the strain rate is the most important parameter, while the Cu content exhibited a modest but significant influence on the flow stress. PMID:28773658

Stellar models for a wide range of initial chemical compositions until helium burning IV. From X = 0.65 to X = 0.80, for Z = 0.004

NASA Astrophysics Data System (ADS)

Claret, A.; Gimenez, A.

1998-11-01

As a continuation of previous papers in a series devoted to the computation of stellar structure and evolution models we present a grid specifically obtained for detailed studies of the stellar content of the Small Magellanic Cloud. The initial metal content has thus been adopted to be Z = 0.004 while the hydrogen content varies from 0.65 to 0.80 leaving as an intermediate value that given by standard laws of enrichment, X = 0.744. Interpolation for different environment is therefore possible with these new models. Other input physics parameters, e.g. convective overshooting, mixing-length, opacities or nuclear reaction rates, have been adopted to be homogeneous with the previously published models in order to facilitate comparative studies. Tables 1-72 are only available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsweb.u-strasbg.fr/Abstract.html}

Experimental study and thermodynamic modeling for determining the effect of non-polar solvent (hexane)/polar solvent (methanol) ratio and moisture content on the lipid extraction efficiency from Chlorella vulgaris.

PubMed

Malekzadeh, Mohammad; Abedini Najafabadi, Hamed; Hakim, Maziar; Feilizadeh, Mehrzad; Vossoughi, Manouchehr; Rashtchian, Davood

2016-02-01

In this research, organic solvent composed of hexane and methanol was used for lipid extraction from dry and wet biomass of Chlorella vulgaris. The results indicated that lipid and fatty acid extraction yield was decreased by increasing the moisture content of biomass. However, the maximum extraction efficiency was attained by applying equivolume mixture of hexane and methanol for both dry and wet biomass. Thermodynamic modeling was employed to estimate the effect of hexane/methanol ratio and moisture content on fatty acid extraction yield. Hansen solubility parameter was used in adjusting the interaction parameters of the model, which led to decrease the number of tuning parameters from 6 to 2. The results indicated that the model can accurately estimate the fatty acid recovery with average absolute deviation percentage (AAD%) of 13.90% and 15.00% for the two cases of using 6 and 2 adjustable parameters, respectively. Copyright © 2015 Elsevier Ltd. All rights reserved.

Quality models for audiovisual streaming

NASA Astrophysics Data System (ADS)

Thang, Truong Cong; Kim, Young Suk; Kim, Cheon Seog; Ro, Yong Man

2006-01-01

Quality is an essential factor in multimedia communication, especially in compression and adaptation. Quality metrics can be divided into three categories: within-modality quality, cross-modality quality, and multi-modality quality. Most research has so far focused on within-modality quality. Moreover, quality is normally just considered from the perceptual perspective. In practice, content may be drastically adapted, even converted to another modality. In this case, we should consider the quality from semantic perspective as well. In this work, we investigate the multi-modality quality from the semantic perspective. To model the semantic quality, we apply the concept of "conceptual graph", which consists of semantic nodes and relations between the nodes. As an typical of multi-modality example, we focus on audiovisual streaming service. Specifically, we evaluate the amount of information conveyed by a audiovisual content where both video and audio channels may be strongly degraded, even audio are converted to text. In the experiments, we also consider the perceptual quality model of audiovisual content, so as to see the difference with semantic quality model.

Construction of technological artifacts and teaching strategies to promote flexible scientific understanding

NASA Astrophysics Data System (ADS)

Spitulnik, Michele Wisnudel

Science education reforms advocate inquiry as a way to build explanations and make informed decisions. Based on this call this dissertation (1) defines flexible scientific understanding by elaborating on content, inquiry and epistemic understandings; (2) describes an inquiry based unit that integrates dynamic modeling software; (3) examines students' understandings as they construct models; and (4) identifies instructional strategies that support inquiry and model building. A curriculum unit was designed to engage students in inquiry by identifying problems and constructing models to represent, explain and predict phenomena. Ninth grade students in a public mid-western high school worked in teams of 2-3 to ask questions, find information and reflect on the purposes of models. Data sources including classroom video, observations, interviews, student models and handouts were used to formulate cases that examine how two groups construct understanding. A teacher case study identifies the teaching strategies that support understanding. Categories within content, inquiry and epistemic understandings were used to analyze student understandings and teaching supports. The findings demonstrate that students can build flexible understanding by constructing models. Students built: (1) content understanding by identifying key ideas and building relationships and explanations of phenomena; (2) inquiry understanding by defining problems, constructing models and developing positions; and (3) epistemic understanding by describing the purposes of models as generalizing phenomena, testing hypotheses and making predictions. However, students demonstrated difficulty in using evidence to defend scientific arguments. Strategies that support flexible understanding were also identified. Content supports include: setting expectations for explanations; using examples to illustrate explanations; modeling questions; and providing feedback that prompts detailed explanations. Supports for inquiry are setting expectations for data gathering; using examples that illustrate model building; modeling the development of an argument; and providing feedback to promote coherent models. Epistemic supports include: using examples to illustrate purposes and assumptions within models, and providing feedback as students evaluate their models. The dissertation demonstrates that teaching strategies impact student understanding but are challenging to implement. When strategies are not used, students do not necessarily construct desired outcomes such as, using evidence to support arguments.

A comparison of different radiative transfer model inversion methods for canopy water content retrieval

NASA Astrophysics Data System (ADS)

Boren, E. J.; Boschetti, L.; Johnson, D.

2016-12-01

With near-future droughts predicted to become both more frequent and more intense (Allen et al. 2015, Diffenbaugh et al. 2015), the estimation of satellite-derived vegetation water content would benefit a wide range of environmental applications including agricultural, vegetation, and fire risk monitoring. No vegetation water content thematic product is currently available (Yebra et al. 2013), but the successful launch of the Landsat 8 OLI and Sentinel 2A satellites, and the forthcoming Sentinel 2B, provide the opportunity for monitoring biophysical variables at a scale (10-30m) and temporal resolution (5 days) needed by most applications. Radiative transfer models (RTM) use a set of biophysical parameters to produce an estimated spectral response and - when used in inverse mode - provide a way to use satellite spectral data to estimate vegetation biophysical parameters, including water content (Zarco-Tejada et al. 2003). Using the coupled leaf and canopy level model PROSAIL5, and Landsat 8 OLI and Sentinel 2A MSI optical satellite data, the present research compares the results of three model inversion techniques: iterative optimization (OPT), look-up table (LUT), and artificial neural network (ANN) training. Ancillary biophysical data, needed for constraining the inversion process, were collected from various crop species grown in a controlled setting and under different water stress conditions. The measurements included fresh weight, dry weight, leaf area, and spectral leaf transmittance and reflectance in the 350-2500 nm range. Plot-level data, collected coincidently with satellite overpasses during three summer field campaigns in northern Idaho (2014 to 2016), are used to evaluate the results of the model inversion. Field measurements included fresh weight, dry weight, leaf area index, plant height, and top of canopy reflectance in the 350-2500 nm range. The results of the model inversion intercomparison exercised are used to characterize the uncertainties of vegetation water content estimation from Landsat 8 OLI and Sentinel 2A data.

Response surface model for predicting chronic toxicity of cadmium to Paronychiurus kimi (Collembola), with a special emphasis on the importance of soil characteristics in the reproduction test.

PubMed

Son, Jino; Shin, Key-il; Cho, Kijong

2009-11-01

A central composite design (CCD) was employed to investigate the effects of organic matter (OM) content and soil pH on the reproduction, and chronic toxicity (28-d EC(50-reproduction)) of cadmium for Paronychiurus kimi after 28days exposure in a standard artificial soil. Two statistical models were developed, one describing reproduction in control artificial soils as a function of OM content and pH, and the other describing cadmium toxicity to the same soil parameters. In the reproduction model, pH was the most important factor, followed by two quadratic factors of OM(2) and pH(2). The parameter pH alone could explain 75.5% of the response variation. The reproduction model will allow us to predict a mean reproduction in the non-treated control soils that contain various combinations of OM content and different pH values. In the chronic toxicity model, only the linear factor of the OM content and pH significantly (p<0.05) affect cadmium toxicity, which explains the 78.9% and 14.9% of total response variance, respectively. Therefore, the final polynomial regression describing the chronic toxicity of cadmium to P. kimi is as follows: predicted 28-d EC(50) of cadmium (mgkg(-1))=-21.231+2.794 x OM+4.874 x pH. The present study show that soil characteristics, which can alter the toxicity of cadmium, can also act as stressors themselves in regards to the reproduction of P. kimi. Based on the physico-chemical characteristics of the test media, the response surface model developed in this study can be used to provide initial toxicity information for cadmium within a region of interest in terms of OM content and pH, and may lead to more scientific based risk assessment for metals.

Study on the prediction of soil heavy metal elements content based on visible near-infrared spectroscopy.

PubMed

Liu, Jinbao; Zhang, Yang; Wang, Huanyuan; Du, Yichun

2018-06-15

The estimation of soils heavy metal content can reflect the impending surroundings of surface, which lays theoretical foundation for using covered vegetation to monitor environment and investigate resource. In this study, the contents of Cr, Mn, Ni, Cu, Zn, As, Cd, Hg and Pb in 44 soil samples were collected from Fufeng County, Yangling County and Wugong County, Shaanxi Province and were used as data sources. ASD FieldSpec HR (350-2500nm), and then the NOR, MSC and SNV of the reflectance were pretreated, the first deviation, second deviation and reflectance reciprocal logarithmic transformation were carried out. The optimal spectroscopy estimation model of nine heavy metal elements of Cr, Mn, Ni, Cu, Zn, As, Cd, Hg and Pb was established by regression method. Comparing the diffuse reflectance characteristics of different heavy metal contents and the effect of different pretreatment methods on the establishment of soil heavy metal spectral inversion model. The results of chemical analysis show that there was a serious Hg pollution in the study area, and the Cd content was close to the critical value. The results show that: (1) NOR, MSC and SNV were adopted for the acquisition of visible near-infrared. Combining differential transformation can improve the information of heavy metal elements in the soil, and use the correlation band energy Significantly improve the stability and predictability of the model. (2) The modeling accuracy of the optimal model of nine heavy metal spectra of Cr, Mn, Ni, Cu, Zn, As, Cd, Hg and Pb by PLSR method were 0.70, 0.79, 0.69, 0.81, 0.86, 0.58, 0.55, 0.99, 0.62. (3) The optimal estimation model of different elements using different treatment methods has better stability and higher precision, and can realize the rapid prediction of nine kinds of heavy metal elements in this region. Copyright © 2018 Elsevier B.V. All rights reserved.

Study on the prediction of soil heavy metal elements content based on visible near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Liu, Jinbao; Zhang, Yang; Wang, Huanyuan; Du, Yichun

2018-06-01

The estimation of soils heavy metal content can reflect the impending surroundings of surface, which lays theoretical foundation for using covered vegetation to monitor environment and investigate resource. In this study, the contents of Cr, Mn, Ni, Cu, Zn, As, Cd, Hg and Pb in 44 soil samples were collected from Fufeng County, Yangling County and Wugong County, Shaanxi Province and were used as data sources. ASD FieldSpec HR (350-2500 nm), and then the NOR, MSC and SNV of the reflectance were pretreated, the first deviation, second deviation and reflectance reciprocal logarithmic transformation were carried out. The optimal spectroscopy estimation model of nine heavy metal elements of Cr, Mn, Ni, Cu, Zn, As, Cd, Hg and Pb was established by regression method. Comparing the diffuse reflectance characteristics of different heavy metal contents and the effect of different pretreatment methods on the establishment of soil heavy metal spectral inversion model. The results of chemical analysis show that there was a serious Hg pollution in the study area, and the Cd content was close to the critical value. The results show that: (1) NOR, MSC and SNV were adopted for the acquisition of visible near-infrared. Combining differential transformation can improve the information of heavy metal elements in the soil, and use the correlation band energy Significantly improve the stability and predictability of the model. (2) The modeling accuracy of the optimal model of nine heavy metal spectra of Cr, Mn, Ni, Cu, Zn, As, Cd, Hg and Pb by PLSR method were 0.70, 0.79, 0.69, 0.81, 0.86, 0.58, 0.55, 0.99, 0.62. (3) The optimal estimation model of different elements using different treatment methods has better stability and higher precision, and can realize the rapid prediction of nine kinds of heavy metal elements in this region.

[Prediction of total nitrogen and alkali hydrolysable nitrogen content in loess using hyperspectral data based on correlation analysis and partial least squares regression].

PubMed

Liu, Xiu-ying; Wang, Li; Chang, Qing-rui; Wang, Xiao-xing; Shang, Yan

2015-07-01

Wuqi County of Shaanxi Province, where the vegetation recovering measures have been carried out for years, was taken as the study area. A total of 100 loess samples from 24 different profiles were collected. Total nitrogen (TN) and alkali hydrolysable nitrogen (AHN) contents of the soil samples were analyzed, and the soil samples were scanned in the visible/near-infrared (VNIR) region of 350-2500 nm in the laboratory. The calibration models were developed between TN and AHN contents and VNIR values based on correlation analysis (CA) and partial least squares regression (PLS). Independent samples validated the calibration models. The results indicated that the optimum model for predicting TN of loess was established by using first derivative of reflectance. The best model for predicting AHN of loess was established by using normal derivative spectra. The optimum TN model could effectively predict TN in loess from 0 to 40 cm, but the optimum AHN model could only roughly predict AHN at the same depth. This study provided a good method for rapidly predicting TN of loess where vegetation recovering measures have been adopted, but prediction of AHN needs to be further studied.

High School Students' Meta-Modeling Knowledge

NASA Astrophysics Data System (ADS)

Fortus, David; Shwartz, Yael; Rosenfeld, Sherman

2016-12-01

Modeling is a core scientific practice. This study probed the meta-modeling knowledge (MMK) of high school students who study science but had not had any explicit prior exposure to modeling as part of their formal schooling. Our goals were to (A) evaluate the degree to which MMK is dependent on content knowledge and (B) assess whether the upper levels of the modeling learning progression defined by Schwarz et al. (2009) are attainable by Israeli K-12 students. Nine Israeli high school students studying physics, chemistry, biology, or general science were interviewed individually, once using a context related to the science subject that they were learning and once using an unfamiliar context. All the interviewees displayed MMK superior to that of elementary and middle school students, despite the lack of formal instruction on the practice. Their MMK was independent of content area, but their ability to engage in the practice of modeling was content dependent. This study indicates that, given proper support, the upper levels of the learning progression described by Schwarz et al. (2009) may be attainable by K-12 science students. The value of explicitly focusing on MMK as a learning goal in science education is considered.

The Relationship between Muscle Fiber Type-Specific PGC-1α Content and Mitochondrial Content Varies between Rodent Models and Humans

PubMed Central

Gouspillou, Gilles; Sgarioto, Nicolas; Norris, Brandon; Barbat-Artigas, Sébastien; Aubertin-Leheudre, Mylène; Morais, Jose A.; Burelle, Yan; Taivassalo, Tanja; Hepple, Russell T.

2014-01-01

PGC-1α regulates critical processes in muscle physiology, including mitochondrial biogenesis, lipid metabolism and angiogenesis. Furthermore, PGC-1α was suggested as an important regulator of fiber type determination. However, whether a muscle fiber type-specific PGC-1α content exists, whether PGC-1α content relates to basal levels of mitochondrial content, and whether such relationships are preserved between humans and classically used rodent models are all questions that have been either poorly addressed or never investigated. To address these issues, we investigated the fiber type-specific content of PGC-1α and its relationship to basal mitochondrial content in mouse, rat and human muscles using in situ immunolabeling and histochemical methods on muscle serial cross-sections. Whereas type IIa fibers exhibited the highest PGC-1α in all three species, other fiber types displayed a hierarchy of type IIx>I>IIb in mouse, type I = IIx> IIb in rat, and type IIx>I in human. In terms of mitochondrial content, we observed a hierarchy of IIa>IIx>I>IIb in mouse, IIa >I>IIx> IIb in rat, and I>IIa> IIx in human skeletal muscle. We also found in rat skeletal muscle that type I fibers displayed the highest capillarization followed by type IIa >IIx>IIb. Finally, we found in human skeletal muscle that type I fibers display the highest lipid content, followed by type IIa>IIx. Altogether, our results reveal that (i) the fiber type-specific PGC-1α and mitochondrial contents were only matched in mouse, (ii) the patterns of PGC-1α and mitochondrial contents observed in mice and rats do not correspond to that seen in humans in several respects, and (iii) the classical phenotypes thought to be regulated by PGC-1α do not vary exclusively as a function of PGC-1α content in rat and human muscles. PMID:25121500

Comparison of inversion accuracy of soil copper content from vegetation indices under different spectral resolution

NASA Astrophysics Data System (ADS)

Sun, Zhongqing; Shang, Kun; Jia, Lingjun

2018-03-01

Remote sensing inversion of heavy metal in vegetation leaves is generally based on the physiological characteristics of vegetation spectrum under heavy metal stress, and empirical models with vegetation indices are established to inverse the heavy metal content of vegetation leaves. However, the research of inversion of heavy metal content in vegetation-covered soil is still rare. In this study, Pulang is chosen as study area. The regression model of a typical heavy metal element, copper (Cu), is established with vegetation indices. We mainly investigate the inversion accuracies of Cu element in vegetation-covered soil by different vegetation indices according to specific spectral resolutions of ASD (Analytical Spectral Device) and Hyperion data. The inversion results of soil copper content in the vegetation-covered area shows a good accuracy, and the vegetation indices under ASD spectral resolution correspond to better results.

Relation between L-band soil emittance and soil water content

NASA Technical Reports Server (NTRS)

Stroosnijder, L.; Lascano, R. J.; Van Bavel, C. H. M.; Newton, R. W.

1986-01-01

An experimental relation between soil emittance (E) at L-band and soil surface moisture content (M) is compared with a theoretical one. The latter depends on the soil dielectric constant, which is a function of both soil moisture content and of soil texture. It appears that a difference of 10 percent in the surface clay content causes a change in the estimate of M on the order of 0.02 cu m/cu m. This is based on calculations with a model that simulates the flow of water and energy, in combination with a radiative transfer model. It is concluded that an experimental determination of the E-M relation for each soil type is not required, and that a rough estimate of the soil texture will lead to a sufficiently accurate estimate of soil moisture from a general, theoretical relationship obtained by numerical simulation.

Mathematical model of organic substrate degradation in solid waste windrow composting.

PubMed

Seng, Bunrith; Kristanti, Risky Ayu; Hadibarata, Tony; Hirayama, Kimiaki; Katayama-Hirayama, Keiko; Kaneko, Hidehiro

2016-01-01

Organic solid waste composting is a complex process that involves many coupled physical, chemical and biological mechanisms. To understand this complexity and to ease in planning, design and management of the composting plant, mathematical model for simulation is usually applied. The aim of this paper is to develop a mathematical model of organic substrate degradation and its performance evaluation in solid waste windrow composting system. The present model is a biomass-dependent model, considering biological growth processes under the limitation of moisture, oxygen and substrate contents, and temperature. The main output of this model is substrate content which was divided into two categories: slowly and rapidly degradable substrates. To validate the model, it was applied to a laboratory scale windrow composting of a mixture of wood chips and dog food. The wastes were filled into a cylindrical reactor of 6 cm diameter and 1 m height. The simulation program was run for 3 weeks with 1 s stepwise. The simulated results were in reasonably good agreement with the experimental results. The MC and temperature of model simulation were found to be matched with those of experiment, but limited for rapidly degradable substrates. Under anaerobic zone, the degradation of rapidly degradable substrate needs to be incorporated into the model to achieve full simulation of a long period static pile composting. This model is a useful tool to estimate the changes of substrate content during composting period, and acts as a basic model for further development of a sophisticated model.

Comparison of three acute stress models for simulating the pathophysiology of stress-related mucosal disease.

PubMed

Saxena, Bhagawati; Singh, Sanjay

2017-05-30

Stress-related mucosal disease (SRMD) is highly prevalent in intensive care patients leading to increasing treatment cost and mortality. SRMD is a disease elusive of ideal treatment. Evaluation of drugs is very pertinent for the efficient and safe treatment of SRMD. It relies mainly on in vivo screening models. There are various stress models, and till date, none of them is validated for simulating the SRMD pathophysiology. The present study aims to choose the best model, which reproduce pathophysiology of SRMD, among previously established stress models. This study evaluates ulcer index, hexosamine content, microvascular permeability, and gastric content in three acute stress models (cold-restraint, restraint, and water immersion restraint). Macroscopic pictures of the ulcerogenic stomach explain that in contrast to other models, cold-restraint stress (CRS) exposure produced marked ulcers on the fundic area of the stomach. Results of the present study depicted that each stress model significantly increased ulcer index, microvascular permeability and decreased hexosamine level, however, the maximum in the case of CRS-exposed rats. Total acidity and pH of the gastric content remains unchanged in all the stress models. On the contrary, the gastric volume significantly decreased only in case of CRS, while unchanged in other stress models. The overall results revealed that the CRS resembles the pathophysiology of SRMD closely. It is the best and feasible model among all the models to evaluate drugs for the treatment of SRMD.

Impact of Sampling and Cellular Separation on Amino Acid Determinations in Drosophila Hemolymph.

PubMed

Cabay, Marissa R; Harris, Jasmine C; Shippy, Scott A

2018-04-03

The fruit fly is a frequently used model system with a high degree of human disease-related genetic homology. The quantitative chemical analysis of fruit fly tissues and hemolymph uniquely brings chemical signaling and compositional information to fly experimentation. The work here explores the impact of measured chemical content of hemolymph with three aspects of sample collection and preparation. Cellular content of hemolymph was quantitated and removed to determine hemolymph composition changes for seven primary amine analytes. Hemolymph sampling methods were adapted to determine differences in primary amine composition of hemolymph collected from the head, antenna, and abdomen. Also, three types of anesthesia were employed with hemolymph collection to quantitate effects on measured amino acid content. Cell content was found to be 45.4 ± 22.1 cells/nL of hemolymph collected from both adult and larvae flies. Cell-concentrated fractions of adult, but not larvae, hemolymph were found to have higher and more variable amine content. There were amino acid content differences found between all three areas indicating a robust method to characterize chemical markers from specific regions of a fly, and these appear related to physiological activity. Methods of anesthesia have an impact on hemolymph amino acid composition related to overall physiological impact to fly including higher amino acid content variability and oxygen deprivation effects. Together, these analyses identify potential complications with Drosophila hemolymph analysis and opportunities for future studies to relate hemolymph content with model physiological activity.

Quantitative assessment on soil enzyme activities of heavy metal contaminated soils with various soil properties.

PubMed

Xian, Yu; Wang, Meie; Chen, Weiping

2015-11-01

Soil enzyme activities are greatly influenced by soil properties and could be significant indicators of heavy metal toxicity in soil for bioavailability assessment. Two groups of experiments were conducted to determine the joint effects of heavy metals and soil properties on soil enzyme activities. Results showed that arylsulfatase was the most sensitive soil enzyme and could be used as an indicator to study the enzymatic toxicity of heavy metals under various soil properties. Soil organic matter (SOM) was the dominant factor affecting the activity of arylsulfatase in soil. A quantitative model was derived to predict the changes of arylsulfatase activity with SOM content. When the soil organic matter content was less than the critical point A (1.05% in our study), the arylsulfatase activity dropped rapidly. When the soil organic matter content was greater than the critical point A, the arylsulfatase activity gradually rose to higher levels showing that instead of harm the soil microbial activities were enhanced. The SOM content needs to be over the critical point B (2.42% in our study) to protect its microbial community from harm due to the severe Pb pollution (500mgkg(-1) in our study). The quantitative model revealed the pattern of variation of enzymatic toxicity due to heavy metals under various SOM contents. The applicability of the model under wider soil properties need to be tested. The model however may provide a methodological basis for ecological risk assessment of heavy metals in soil. Copyright © 2014 Elsevier Ltd. All rights reserved.

Use of differential scanning calorimetry to detect canola oil (Brassica napus L.) adulterated with lard stearin.

PubMed

Marikkar, Jalaldeen Mohammed Nazrim; Rana, Sohel

2014-01-01

A study was conducted to detect and quantify lard stearin (LS) content in canola oil (CaO) using differential scanning calorimetry (DSC). Authentic samples of CaO were obtained from a reliable supplier and the adulterant LS were obtained through a fractional crystallization procedure as reported previously. Pure CaO samples spiked with LS in levels ranging from 5 to 15% (w/w) were analyzed using DSC to obtain their cooling and heating profiles. The results showed that samples contaminated with LS at 5% (w/w) level can be detected using characteristic contaminant peaks appearing in the higher temperature regions (0 to 70°C) of the cooling and heating curves. Pearson correlation analysis of LS content against individual DSC parameters of the adulterant peak namely peak temperature, peak area, peak onset temperature indicated that there were strong correlations between these with the LS content of the CaO admixtures. When these three parameters were engaged as variables in the execution of the stepwise regression procedure, predictive models for determination of LS content in CaO were obtained. The predictive models obtained with single DSC parameter had relatively lower coefficient of determination (R(2) value) and higher standard error than the models obtained using two DSC parameters in combination. This study concluded that the predictive models obtained with peak area and peak onset temperature of the adulteration peak would be more accurate for prediction of LS content in CaO based on the highest coefficient of determination (R(2) value) and smallest standard error.

An Intelligent Content Discovery Technique for Health Portal Content Management

PubMed Central

2014-01-01

Background Continuous content management of health information portals is a feature vital for its sustainability and widespread acceptance. Knowledge and experience of a domain expert is essential for content management in the health domain. The rate of generation of online health resources is exponential and thereby manual examination for relevance to a specific topic and audience is a formidable challenge for domain experts. Intelligent content discovery for effective content management is a less researched topic. An existing expert-endorsed content repository can provide the necessary leverage to automatically identify relevant resources and evaluate qualitative metrics. Objective This paper reports on the design research towards an intelligent technique for automated content discovery and ranking for health information portals. The proposed technique aims to improve efficiency of the current mostly manual process of portal content management by utilising an existing expert-endorsed content repository as a supporting base and a benchmark to evaluate the suitability of new content Methods A model for content management was established based on a field study of potential users. The proposed technique is integral to this content management model and executes in several phases (ie, query construction, content search, text analytics and fuzzy multi-criteria ranking). The construction of multi-dimensional search queries with input from Wordnet, the use of multi-word and single-word terms as representative semantics for text analytics and the use of fuzzy multi-criteria ranking for subjective evaluation of quality metrics are original contributions reported in this paper. Results The feasibility of the proposed technique was examined with experiments conducted on an actual health information portal, the BCKOnline portal. Both intermediary and final results generated by the technique are presented in the paper and these help to establish benefits of the technique and its contribution towards effective content management. Conclusions The prevalence of large numbers of online health resources is a key obstacle for domain experts involved in content management of health information portals and websites. The proposed technique has proven successful at search and identification of resources and the measurement of their relevance. It can be used to support the domain expert in content management and thereby ensure the health portal is up-to-date and current. PMID:25654440

Geochemical study of stream waters affected by mining activities in the SE Spain

NASA Astrophysics Data System (ADS)

Garcia-Lorenzo, Maria Luz; Perez-Sirvent, Carmen; Martinez-Sanchez, Maria Jose; Bech, Jaime

2015-04-01

Water pollution by dissolved metals in mining areas has mainly been associated with the oxidation of sulphide-bearing minerals exposed to weathering conditions, resulting in low quality effluents of acidic pH and containing a high level of dissolved metals. According to transport process, three types of pollution could be established: a) Primary contamination, formed by residues placed close to the contamination sources; b) Secondary contamination, produced as a result of transport out of its production areas; c) Tertiary contamination. The aim of this work was to study trace element in water samples affected by mining activities and to apply the MINTEQ model for calculating aqueous geochemical equilibria. The studied area constituted an important mining centre for more than 2500 years, ceasing activity in 1991. The ore deposits of this zone have iron, lead and zinc as the main metal components. As a result, a lot of contaminations sources, formed by mining steriles, waste piles and foundry residues are present. For this study, 36 surficial water samples were collected after a rain episode in 4 different areas. In these samples, the trace element content was determined by by flame atomic absorption spectrometry (Fe and Zn), electrothermal atomization atomic absorption spectrometry (Pb and Cd), atomic fluorescence spectrometry (As) and ICP-MS for Al. MINTEQA2 is a geochemical equilibrium speciation model capable of computing equilibria among the dissolved, adsorbed, solid, and gas phases in an environmental setting and was applied to collected waters. Zone A: A5 is strongly influenced by tailing dumps and showed high trace element content. In addition, is influenced by the sea water and then showed high bromide, chloride, sodium and magnesium content, together with a basic pH. The MINTEQ model application suggested that Zn and Cd could precipitate as carbonate (hidrocincite, smithsonite and otavite). A9 also showed acid pH and high trace element content; is influenced by tailing dumps and also by waters from gully watercourses, transporting materials from Sierra Minera. The MINTEQ simulation showed that Pb and Ca could precipitate as sulphates (anglesite and gypsum). Waters affected by secondary contamination have been mixed with carbonate materials, present in the zone increasing the pH. Some elements have precipitated, such as Cu and Pb, while Cd, Zn and As are soluble. The MINTEQ model results showed that in A10 and A14, Al could precipitate as diaspore but also carbonates could be formed, particularly dolomite. These model in A12 sample showed that soluble Zn could precipitate as carbonate and Al as oxyhydroxide, similarly than in A13. A2 and A6 waters are affected by tertiary contamination and showed basic pH, soluble carbonates and lower trace element content. Only Zn, Cd and Al are present. The speciation model showed that in A2, Cd and Zn could precipitate as carbonates while Al as oxihydroxide. In A6, the model suggested that soluble Pb could precipitate as carbonate (hidrocerusite and cerusite) or as hydroxide; Al as diaspore, Ca as calcite and Fe as hematite. Zone B: All waters are strongly affected by mining activities and showed acid pH, high trace element content and high content of soluble sulphates. The MINTEQ results showed that in B8, Fe could precipitate as hydroxychloride and in B12 could form alunite. In B9, B10, B13 y B14, the model estimates the precipitation of anglesite, gypsum and Fe hydroxichloride (B9 and B10), diaspore in B13 and B14, and gypsum and Fe hydroxychloride in B13. All the sampling points collected in Zone C are affected by primary contamination, because there are a lot of tailing dumps. C1 showed high trace element content because is a reception point of a lot of tailing dumps. Water samples from C3 to C8 also had acid pH and high trace element content, particularly As, Zn and Cd. In addition, they showed high soluble sulphates. C2 water showed neutral pH, soluble carbonate and low trace element content because is influenced by a stabilised tailing dump. In all samples, except C2, the MINTEQ model showed that a lot of efflorescences could be formed, mainly sulphates. Zone D: All waters collected in this zone showed acid pH and high trace element content, mainly Zn, Cd and As. MINTEQ model results showed that elements could precipitate as jarosite but also anglesite in D8 and gypsum in D9, D11 and D12. D1 is affected by secondary contamination, which showed higher pH (still acid) and lower content in soluble salts and trace elements. The MINTEQ model suggested that Al could precipitate as diaspore, gibbsite and alunite. The applied model is an appropriate tool for the analysis of waters affected by mining activities. The obtained simulations confirm natural attenuation processes.

A Simple Model for the Viscosity of Rhyolites as a Function of Temperature, Pressure and Water Content: Implications for Obsidian Flow Emplacement

NASA Astrophysics Data System (ADS)

Whittington, A. G.; Romine, W. L.

2014-12-01

Understanding the dynamics of rhyolitic conduits and lava flows, requires precise knowledge of how viscosity (η) varies with temperature (T), pressure (P) and volatile content (X). In order to address the paucity of viscosity data for high-silica rhyolite at low water contents, which represent water saturation at near-surface conditions, we made 245 viscosity measurements on Mono Craters (California) rhyolites containing between 0.01 and 1.1 wt.% H2O, at temperatures between 796 and 1774 K using parallel plate and concentric cylinder methods at atmospheric pressure. We then developed and calibrated a new empirical model for the log of the viscosity of rhyolitic melts, where non-linear variations due to temperature and water content are nested within a linear dependence of log η on P. The model was fitted to a total of 563 data points: our 245 new data, 255 published data from rhyolites across a wide P-T-X space, and 63 data on haplogranitic and granitic melts under high P-T conditions. Statistically insignificant parameters were eliminated from the model in an effort to increase parsimony and the final model is simple enough for use in numerical models of conduit or lava flow dynamics: log η = -5.142+(13080-2982log⁡(w+0.229))/(T-(98.9-175.9 log⁡(w+0.229)))- P(0.0007-0.76/T ) where η is in Pa s, w is water content in wt.%, P is in MPa and T is in K. The root mean square deviation (rmsd) between the model predictions and the 563 data points used in calibration is 0.39 log units. Experimental constraints have led previously to spurious correlations between P, T, X and η in viscosity data sets, so that predictive models may struggle to correctly resolve the individual effects of P, T and X, and especially their cross-correlations. The increasing water solubility with depth inside a simple isothermal sheet of obsidian suggests that viscosity should decrease by ~1 order of magnitude at ~20m depth and by ~2 orders of magnitude at ~100m depth. If equilibrium water contents are maintained, then deformation in spreading obsidian flows should be strongly partitioned into the deeper parts of the flow. Kinetically inhibited degassing, or recycling of degassed crust into a flow interior (e.g. by caterpillar-tread motion) could lead to strong lateral variations in viscosity within a flow, affecting flow evolution and morphology.

Current Trends in the Detection of Sociocultural Signatures: Data-Driven Models

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

Sanfilippo, Antonio P.; Bell, Eric B.; Corley, Courtney D.

The harvesting of behavioral data and their analysis through evidence-based reasoning enable the detection of sociocultural signatures in their context to support situation awareness and decision making. Harvested data are used as training materials from which to infer computational models of sociocultural behaviors or calibrate parameters for such models. Harvested data also serve as evidence input that the models use to provide insights about observed and future behaviors for targets of interest. The harvested data is often the result of assembling diverse data types and aggregating them into a form suitable for analysis. Data need to be analyzed to bringmore » out the categories of content that are relevant to the domain being addressed in order to train or run a model. If, for example, we are modeling the intent of a group to engage in violent behavior using messages that the group has broadcasted, then these messages need to be processed to extract and measure indicators of violent intent. The extracted indicators and the associated measurements (e.g. rates or counts of occurrence) can then be used to train/calibrate and run computational models that assess the propensity for violence expressed in the source message. Ubiquitous access to the Internet, mobile telephony and technologies such as digital photography and digital video have enabled social media application platforms such as Facebook, YouTube, and Twitter that are altering the nature of human social interaction. The fast increasing pace of online social interaction introduces new challenges and opportunities for gathering sociocultural data. Challenges include the development of harvesting and processing techniques tailored to new data environments and formats (e.g. Twitter, Facebook), the integration of social media content with traditional media content, and the protection of personal privacy. As these and other challenges are addressed, a new wealth of behavioral data and data analysis methods becomes available that are shaping social computing as a strongly data-driven experimental discipline with an increasingly stronger impact on the decision-making process of groups and individuals alike. In this chapter, we review current advances and trends in the detection of sociocultural signatures. Specific embodiments of the issues discussed are provided with respect to the assessment of violent intent and sociopolitical contention. We begin by reviewing current approaches to the detection of sociocultural signatures in these domains. Next, we turn to the review of novel data harvesting methods for social media content. Finally, we discuss the application of sociocultural models to social media content, and conclude by commenting on current challenges and future developments.« less

Mould spoilage of cereals during transportation by sea from Latin America to Europe mechanisms, impact and management.

PubMed

Mossel, D A

1988-12-01

Safe water contents of consignments of cereals to be shipped overseas can be calculated from the relation between mould-free storage time and storage conditions (temperature of the environment, aw of the cereal), corrected for heterogeneity of water distribution, content of damaged kernels and degree of infestation by insects. The validity of this model was substantiated by the inspection of shipments and theoretical data from the literature. This predictive model can usefully be substituted for previously used, ill-defined criteria like average or any portion's water content and should prompt the trade to sell consignments of cereals on the basis of dry substance.

Towards a model for the measurement of data quality in websites

NASA Astrophysics Data System (ADS)

Leite, Patrícia; Gonçalves, Joaquim; Teixeira, Paulo; Rocha, Álvaro

2014-10-01

Websites are, nowadays, the face of institutions, but they are often neglected, especially when it comes to contents. In the present paper, we put forth an investigation work whose final goal is the development of a model for the measurement of data quality in institutional websites for health units. To that end, we have carried out a bibliographic review of the available approaches for the evaluation of website content quality, in order to identify the most recurrent dimensions and the attributes, and we are currently carrying out a Delphi Method process, presently in its second stage, with the purpose of reaching an adequate set of attributes for the measurement of content quality.

Prospect redux

NASA Technical Reports Server (NTRS)

Jacquemoud, S.; Ustin, S. L.; Verdebout, J.; Schmuck, G.; Andreoli, G.; Hosgood, B.

1995-01-01

The remote estimation of leaf biochemical content from spaceborne platforms has been the subject of many studies aimed at better understanding of terrestrial ecosystem functioning. The major ecological processes involved in exchange of matter and energy, like photosynthesis, primary production, evaportranspiration, respiration, and decomposition can be related to plant properties e.g., chlorophyll, water, protein, cellulose and lignin contents. As leaves represent the most important plant surfaces interacting with solar energy, a top priority has been to relate optical properties to biochemical constituents. Two different approaches have been considered: first, statistical correlations between the leaf reflectance (or transmittance) and biochemical content, and second, physically based models of leaf scattering and absorption developed using the laws of optics. Recently reviewed by Verdebout et al., the development of models of leaf optical properties has resulted in better understanding of the interaction of light with plant leaves. Present radiative transfer models mainly use chlorophyll and/or water contents as input parameters to calculate leaf reflectance. Inversion of these models allows to retrieve these constituents from spectrophotometric measurements. Conel et al. recently proposed a two-stream Kubelka-Munk model to analyze the influence of protein, cellulose, lignin, and starch on leaf reflectance, but in fact, the estimation of leaf biochemistry from remote sensing is still an open question. In order to clarify it, a laboratory experiment associating visible/infrared spectra of plan leaves both with physical measurements and biochemical analyses was conducted at the Joint Research Center during the summer of 1993. This unique data set has been used to upgrade the PROSPECT model, by including leaf biochemistry.

Integrating digital educational content created and stored within disparate software environments: an extensible markup language (XML) solution in real-world use.

PubMed

Frank, M S; Schultz, T; Dreyer, K

2001-06-01

To provide a standardized and scaleable mechanism for exchanging digital radiologic educational content between software systems that use disparate authoring, storage, and presentation technologies. Our institution uses two distinct software systems for creating educational content for radiology. Each system is used to create in-house educational content as well as commercial educational products. One system is an authoring and viewing application that facilitates the input and storage of hierarchical knowledge and associated imagery, and is capable of supporting a variety of entity relationships. This system is primarily used for the production and subsequent viewing of educational CD-ROMS. Another software system is primarily used for radiologic education on the world wide web. This system facilitates input and storage of interactive knowledge and associated imagery, delivering this content over the internet in a Socratic manner simulating in-person interaction with an expert. A subset of knowledge entities common to both systems was derived. An additional subset of knowledge entities that could be bidirectionally mapped via algorithmic transforms was also derived. An extensible markup language (XML) object model and associated lexicon were then created to represent these knowledge entities and their interactive behaviors. Forward-looking attention was exercised in the creation of the object model in order to facilitate straightforward future integration of other sources of educational content. XML generators and interpreters were written for both systems. Deriving the XML object model and lexicon was the most critical and time-consuming aspect of the project. The coding of the XML generators and interpreters required only a few hours for each environment. Subsequently, the transfer of hundreds of educational cases and thematic presentations between the systems can now be accomplished in a matter of minutes. The use of algorithmic transforms results in nearly 100% transfer of context as well as content, thus providing "presentation-ready" outcomes. The automation of knowledge exchange between dissimilar digital teaching environments magnifies the efforts of educators and enriches the learning experience for participants. XML is a powerful and useful mechanism for transfering educational content, as well as the context and interactive behaviors of such content, between disparate systems.

Estimating precise metallicity and stellar mass evolution of galaxies

NASA Astrophysics Data System (ADS)

Mosby, Gregory

2018-01-01

The evolution of galaxies can be conveniently broken down into the evolution of their contents. The changing dust, gas, and stellar content in addition to the changing dark matter potential and periodic feedback from a super-massive blackhole are some of the key ingredients. We focus on the stellar content that can be observed, as the stars reflect information about the galaxy when they were formed. We approximate the stellar content and star formation histories of unresolved galaxies using stellar population modeling. Though simplistic, this approach allows us to reconstruct the star formation histories of galaxies that can be used to test models of galaxy formation and evolution. These models, however, suffer from degeneracies at large lookback times (t > 1 Gyr) as red, low luminosity stars begin to dominate a galaxy’s spectrum. Additionally, degeneracies between stellar populations at different ages and metallicities often make stellar population modeling less precise. The machine learning technique diffusion k-means has been shown to increase the precision in stellar population modeling using a mono-metallicity basis set. However, as galaxies evolve, we expect the metallicity of stellar populations to vary. We use diffusion k-means to generate a multi-metallicity basis set to estimate the stellar mass and chemical evolution of unresolved galaxies. Two basis sets are formed from the Bruzual & Charlot 2003 and MILES stellar population models. We then compare the accuracy and precision of these models in recovering complete (stellar mass and metallicity) histories of mock data. Similarities in the groupings of stellar population spectra in the diffusion maps for each metallicity hint at fundamental age transitions common to both basis sets that can be used to identify stellar populations in a given age range.

Mathematical modelling for the drying method and smoothing drying rate using cubic spline for seaweed Kappaphycus Striatum variety Durian in a solar dryer

NASA Astrophysics Data System (ADS)

M Ali, M. K.; Ruslan, M. H.; Muthuvalu, M. S.; Wong, J.; Sulaiman, J.; Yasir, S. Md.

2014-06-01

The solar drying experiment of seaweed using Green V-Roof Hybrid Solar Drier (GVRHSD) was conducted in Semporna, Sabah under the metrological condition in Malaysia. Drying of sample seaweed in GVRHSD reduced the moisture content from about 93.4% to 8.2% in 4 days at average solar radiation of about 600W/m2 and mass flow rate about 0.5 kg/s. Generally the plots of drying rate need more smoothing compared moisture content data. Special cares is needed at low drying rates and moisture contents. It is shown the cubic spline (CS) have been found to be effective for moisture-time curves. The idea of this method consists of an approximation of data by a CS regression having first and second derivatives. The analytical differentiation of the spline regression permits the determination of instantaneous rate. The method of minimization of the functional of average risk was used successfully to solve the problem. This method permits to obtain the instantaneous rate to be obtained directly from the experimental data. The drying kinetics was fitted with six published exponential thin layer drying models. The models were fitted using the coefficient of determination (R2), and root mean square error (RMSE). The modeling of models using raw data tested with the possible of exponential drying method. The result showed that the model from Two Term was found to be the best models describe the drying behavior. Besides that, the drying rate smoothed using CS shows to be effective method for moisture-time curves good estimators as well as for the missing moisture content data of seaweed Kappaphycus Striatum Variety Durian in Solar Dryer under the condition tested.

Mathematical modelling for the drying method and smoothing drying rate using cubic spline for seaweed Kappaphycus Striatum variety Durian in a solar dryer

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

M Ali, M. K., E-mail: majidkhankhan@ymail.com, E-mail: eutoco@gmail.com; Ruslan, M. H., E-mail: majidkhankhan@ymail.com, E-mail: eutoco@gmail.com; Muthuvalu, M. S., E-mail: sudaram-@yahoo.com, E-mail: jumat@ums.edu.my

2014-06-19

The solar drying experiment of seaweed using Green V-Roof Hybrid Solar Drier (GVRHSD) was conducted in Semporna, Sabah under the metrological condition in Malaysia. Drying of sample seaweed in GVRHSD reduced the moisture content from about 93.4% to 8.2% in 4 days at average solar radiation of about 600W/m{sup 2} and mass flow rate about 0.5 kg/s. Generally the plots of drying rate need more smoothing compared moisture content data. Special cares is needed at low drying rates and moisture contents. It is shown the cubic spline (CS) have been found to be effective for moisture-time curves. The idea ofmore » this method consists of an approximation of data by a CS regression having first and second derivatives. The analytical differentiation of the spline regression permits the determination of instantaneous rate. The method of minimization of the functional of average risk was used successfully to solve the problem. This method permits to obtain the instantaneous rate to be obtained directly from the experimental data. The drying kinetics was fitted with six published exponential thin layer drying models. The models were fitted using the coefficient of determination (R{sup 2}), and root mean square error (RMSE). The modeling of models using raw data tested with the possible of exponential drying method. The result showed that the model from Two Term was found to be the best models describe the drying behavior. Besides that, the drying rate smoothed using CS shows to be effective method for moisture-time curves good estimators as well as for the missing moisture content data of seaweed Kappaphycus Striatum Variety Durian in Solar Dryer under the condition tested.« less

Columnar Metaplasia in Three Types of Surgical Mouse Models of Esophageal Reflux.

PubMed

Terabe, Fabio; Aikou, Susumu; Aida, Junko; Yamamichi, Nobutake; Kaminishi, Michio; Takubo, Kaiyo; Seto, Yasuyuki; Nomura, Sachiyo

2017-07-01

Esophageal adenocarcinoma develops in the setting of gastroesophageal reflux and columnar metaplasia in distal esophagus. Columnar metaplasia arising in gastroesophageal reflux models has developed in rat; however, gastroesophageal reflux models in mice have not been well-characterized. One hundred thirty-five C57Bl/6J mice aged 8 weeks old were divided into the following operations: esophagogastrojejunostomy (side-to-side) (EGJ), esophageal separation and esophagojejunostomy (end-to-side) (EJ), and EJ and gastrectomy (end-to-side) (EJ/TG). The animals were euthanized after 40 weeks and the histology of the junction was examined. Immunohistochemistry for p53, PDX-1, and CDX-2 was performed. Metaplasia developed in 15/33 (45.5%) of EGJ, 0/38 (0%) of EJ, and 6/39 (15.4%) of EJ/TG ( P < .05) and dysplasia developed 7/33 (21.2%) of EGJ, 0% of EJ, and 1/39 (2.6%) of EJ/TG. p53 was positive in all of the dysplastic regions, 12/15 (80%) metaplasias in the EGJ model, and 1/6 (16.7%) metaplasia in the EJ/TG model. CDX-2 was positive in all cases of metaplasias, but decreased in some cases of dysplasia. PDX-1 was positive in 7/8 (88%) cases of dysplasia and in 15/21 (71%) cases of metaplasia ( P < .05). The EGJ model, which causes reflux of gastric acid and duodenal content, developed metaplasia and dysplasia most frequently. No metaplasia developed in the EJ model in which gastric juice and duodenal content mixed before reflux. Thus, duodenal contents alone can induce columnar metaplasia and dysplasia; however, the combination of gastric acid with duodenal content reflux can cause metaplasia and dysplasia more efficiently.

Using agricultural practices information for multiscale environmental assessment of phosphorus risk

NASA Astrophysics Data System (ADS)

Matos Moreira, Mariana; Lemercier, Blandine; Michot, Didier; Dupas, Rémi; Gascuel-Odoux, Chantal

2015-04-01

Phosphorus (P) is an essential nutrient for plant growth. In intensively farmed areas, excessive applications of animal manure and mineral P fertilizers to soils have raised both economic and ecological concerns. P accumulation in agricultural soils leads to increased P losses to surface waterbodies contributing to eutrophication. Increasing soil P content over time in agricultural soils is often correlated with agricultural practices; in Brittany (NW France), an intensive livestock farming region, soil P content is well correlated with animal density (Lemercier et al.,2008). Thus, a better understanding of the factors controlling P distribution is required to enable environmental assessment of P risk. The aim of this study was to understand spatial distribution of extractable (Olsen method) and total P contents and its controlling factors at the catchment scale in order to predict P contents at regional scale (Brittany). Data on soil morphology, soil tests (including P status, particles size, organic carbon…) for 198 punctual positions, crops succession since 20 years, agricultural systems, field and animal manure management were obtained on a well-characterized catchment (ORE Agrhys, 10 km²). A multivariate analysis with mixed quantitative variables and factors and a digital soil mapping approach were performed to identify variables playing a significant role in soil total and extractable P contents and distribution. Spatial analysis was performed by means of the Cubist model, a decision tree-based algorithm. Different scenarios were assessed, considering various panels of predictive variables: soil data, terrain attributes derived from digital elevation model, gamma-ray spectrometry (from airborne geophysical survey) and agricultural practices information. In the research catchment, mean extractable and total P content were 140.0 ± 63.4 mg/kg and 2862.7 ± 773.0 mg/kg, respectively. Organic and mineral P inputs, P balance, soil pH, and Al contents were positively correlated with soil P contents. Also land use, crop rotation and livestock production system influenced P contents. The highest mean values of P were found in croplands and close to pig farms. The lowest mean values of P were found in pastures and nearby dairy farms. The spatial analysis showed that sand content, geophysical parameters and P input by organic fertilization were the most significant variables for the linear predictive model of extractable P contents. For total P, geophysical parameters and P balance had the highest importance for the respective linear predictive model. This study revealed that agricultural practices information plays a significant role in soil P distribution. Once controlling factors of P spatial distribution were identified, relationships could be extrapolated at regional scale using the National Soil Test Database providing information on extractable P content and available information on agricultural practices in order to improve predictions of total P content at regional scale. Lemercier B., Gaudin, L., Walter C., Aurousseau P., Arrouays D., Schvartz C., Saby N., Follain S., Abrassart J., 2008. Soil phosphorus monitoring at the regional level by means of a soil test database. Soil Use and Management, 24, 131-138.

Near-infrared reflectance models for the rapid prediction of quality of brewing raw materials.

PubMed

Marte, Luisa; Belloni, Paolo; Genorini, Emiliano; Sileoni, Valeria; Perretti, Giuseppe; Montanari, Luigi; Marconi, Ombretta

2009-01-28

Calibration models for quickly and reliably predicting moisture content and total nitrogen, both "as is" and "dry matter" on malt, as well as moisture content and total lipids, both "as is" and "dry matter", on maize by means of near-infrared (NIR) spectroscopy were developed. The FT-NIR spectra recorded on the finely ground cereals were correlated to the analytical data by means of the multivariate PLS algorithm. In particular, these models were developed on the raw materials, which are used by the main Italian brewing industries. Validation was carried out both by means of cross-validation and test set validation. Regression coefficients (R(2)) were higher than 97 for both malt and maize moisture content and higher than 85 and 88 for malt total nitrogen and maize total lipids, respectively. The RMSE values (both RMSECV and RMSEP) were lower than 0.1% m/m for both malt and maize moisture contents, whereas they ranged from 0.024 to 0.042% m/m for malt total nitrogen and from 0.042 to 0.055% m/m for maize total lipids. Repeatability was tested by taking into account more than one sample for each calibration and compared, when possible, to those of the standard methods. Repeatability (r(95)) ranged from 0.060 to 0.158% m/m and from 0.020 to 0.055% m/m for malt moisture and total nitrogen contents, respectively, and from 0.094 to 0.160% m/m and from 0.076 to 0.208% m/m for maize moisture and total lipids contents, respectively.

Possible relationships between literacy-based instructional coaching and effects on high school teachers' self-efficacy and attitudes toward teaching reading in the content areas

NASA Astrophysics Data System (ADS)

Jacobs, Jessica Lynn

Grounded in the Theory of Self-Efficacy and the Theory of Reasoned Action, this quantitative, correlational study examined if participation in literacy-based instructional coaching (one-on-one, small group) predicted both high school teachers' self-efficacy as measured by the Teachers' Sense of Efficacy Scale and teachers' attitudes toward teaching reading in the content areas measured by the Scale to Measure Attitudes Toward Teaching Reading in Content Classrooms. This study utilized a convenience sample of content teachers from three high schools in Northeastern Pennsylvania participating in a literacy coaching initiative. The volunteer sample of teachers completed the Likert-type questionnaires. The study used hierarchical regression analysis to determine values for each block of the regression models. The study correlated instances of literacy-based instructional coaching (one-on-one, small group) with the scores on the SMATTRCC and the TSES to examine predictive validity. Gender, years of experience, and content area were control variables in this study. The results of the first model indicated that there was a significant relationship between the number of coaching instances and attitudes toward teaching reading in the content area with participation in instructional coaching accounting for 9.6% of the variance in scores on the SMATTRCC. The results of the second model indicated that there was a significant relationship between the number of coaching instances and teachers' self-efficacy with participation in instructional coaching accounting for 6.1% of the variance in scores on the TSES.

A Multi-Year Study of the Impact of the Rice Model Teacher Professional Development on Elementary Science Teachers

NASA Astrophysics Data System (ADS)

Viorica Diaconu, Dana; Radigan, Judy; Suskavcevic, Milijana; Nichol, Carolyn

2012-04-01

A teacher professional development program for in-service elementary school science teachers, the Rice Elementary Model Science Lab (REMSL), was developed for urban school districts serving predominately high-poverty, high-minority students. Teachers with diverse skills and science capacities came together in Professional Learning Communities, one full day each week throughout an academic year, to create a classroom culture for science instruction. Approximately 80 teachers each year received professional development in science content and pedagogy using the same inquiry-based constructivist methods that the teachers were expected to use in their classrooms. During this four-year study, scientists and educators worked with elementary teachers in a year-long model science lab environment to provide science content and science pedagogy. The effectiveness of the program was measured using a mix of quantitative and qualitative methods that allowed the researchers to triangulate the findings from quantitative measures, such as content test and surveys, with the emerging themes from the qualitative instruments, such as class observations and participant interviews. Results showed that, in all four years, teachers from the REMSL Treatment group have significantly increased their science content knowledge (p < 0.05). During the last two years, their gains in science content knowledge, use of inquiry-based instruction and leadership skills were significantly higher than those of the Control group teachers' (p < 0.01, p < 0.001 and p < 0.05, respectively). Three themes resonated in the interviews with participants: science content knowledge growth, constructivist pedagogy and leadership skills.