Drainage Structure Datasets and Effects on LiDAR-Derived Surface Flow Modeling

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Ruopu Li

2013-12-01

Full Text Available With extraordinary resolution and accuracy, Light Detection and Ranging (LiDAR-derived digital elevation models (DEMs have been increasingly used for watershed analyses and modeling by hydrologists, planners and engineers. Such high-accuracy DEMs have demonstrated their effectiveness in delineating watershed and drainage patterns at fine scales in low-relief terrains. However, these high-resolution datasets are usually only available as topographic DEMs rather than hydrologic DEMs, presenting greater land roughness that can affect natural flow accumulation. Specifically, locations of drainage structures such as road culverts and bridges were simulated as barriers to the passage of drainage. This paper proposed a geospatial method for producing LiDAR-derived hydrologic DEMs, which incorporates data collection of drainage structures (i.e., culverts and bridges, data preprocessing and burning of the drainage structures into DEMs. A case study of GIS-based watershed modeling in South Central Nebraska showed improved simulated surface water derivatives after the drainage structures were burned into the LiDAR-derived topographic DEMs. The paper culminates in a proposal and discussion of establishing a national or statewide drainage structure dataset.

Improving Marine Ecosystem Models with Biochemical Tracers

Science.gov (United States)

Pethybridge, Heidi R.; Choy, C. Anela; Polovina, Jeffrey J.; Fulton, Elizabeth A.

2018-01-01

Empirical data on food web dynamics and predator-prey interactions underpin ecosystem models, which are increasingly used to support strategic management of marine resources. These data have traditionally derived from stomach content analysis, but new and complementary forms of ecological data are increasingly available from biochemical tracer techniques. Extensive opportunities exist to improve the empirical robustness of ecosystem models through the incorporation of biochemical tracer data and derived indices, an area that is rapidly expanding because of advances in analytical developments and sophisticated statistical techniques. Here, we explore the trophic information required by ecosystem model frameworks (species, individual, and size based) and match them to the most commonly used biochemical tracers (bulk tissue and compound-specific stable isotopes, fatty acids, and trace elements). Key quantitative parameters derived from biochemical tracers include estimates of diet composition, niche width, and trophic position. Biochemical tracers also provide powerful insight into the spatial and temporal variability of food web structure and the characterization of dominant basal and microbial food web groups. A major challenge in incorporating biochemical tracer data into ecosystem models is scale and data type mismatches, which can be overcome with greater knowledge exchange and numerical approaches that transform, integrate, and visualize data.

Three-Dimensional Patient-Derived In Vitro Sarcoma Models: Promising Tools for Improving Clinical Tumor Management

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Manuela Gaebler

2017-09-01

Full Text Available Over the past decade, the development of new targeted therapeutics directed against specific molecular pathways involved in tumor cell proliferation and survival has allowed an essential improvement in carcinoma treatment. Unfortunately, the scenario is different for sarcomas, a group of malignant neoplasms originating from mesenchymal cells, for which the main therapeutic approach still consists in the combination of surgery, chemotherapy, and radiation therapy. The lack of innovative approaches in sarcoma treatment stems from the high degree of heterogeneity of this tumor type, with more that 70 different histopathological subtypes, and the limited knowledge of the molecular drivers of tumor development and progression. Currently, molecular therapies are available mainly for the treatment of gastrointestinal stromal tumor, a soft-tissue malignancy characterized by an activating mutation of the tyrosine kinase KIT. Since the first application of this approach, a strong effort has been made to understand sarcoma molecular alterations that can be potential targets for therapy. The low incidence combined with the high level of histopathological heterogeneity makes the development of clinical trials for sarcomas very challenging. For this reason, preclinical studies are needed to better understand tumor biology with the aim to develop new targeted therapeutics. Currently, these studies are mainly based on in vitro testing, since cell lines, and in particular patient-derived models, represent a reliable and easy to handle tool for investigation. In the present review, we summarize the most important models currently available in the field, focusing in particular on the three-dimensional spheroid/organoid model. This innovative approach for studying tumor biology better represents tissue architecture and cell–cell as well as cell–microenvironment crosstalk, which are fundamental steps for tumor cell proliferation and survival.

Inflationary models with non-minimally derivative coupling

International Nuclear Information System (INIS)

Yang, Nan; Fei, Qin; Gong, Yungui; Gao, Qing

2016-01-01

We derive the general formulae for the scalar and tensor spectral tilts to the second order for the inflationary models with non-minimally derivative coupling without taking the high friction limit. The non-minimally kinetic coupling to Einstein tensor brings the energy scale in the inflationary models down to be sub-Planckian. In the high friction limit, the Lyth bound is modified with an extra suppression factor, so that the field excursion of the inflaton is sub-Planckian. The inflationary models with non-minimally derivative coupling are more consistent with observations in the high friction limit. In particular, with the help of the non-minimally derivative coupling, the quartic power law potential is consistent with the observational constraint at 95% CL. (paper)

Influence of satellite-derived photolysis rates and NOx emissions on Texas ozone modeling

Science.gov (United States)

Tang, W.; Cohan, D. S.; Pour-Biazar, A.; Lamsal, L. N.; White, A. T.; Xiao, X.; Zhou, W.; Henderson, B. H.; Lash, B. F.

2015-02-01

Uncertain photolysis rates and emission inventory impair the accuracy of state-level ozone (O3) regulatory modeling. Past studies have separately used satellite-observed clouds to correct the model-predicted photolysis rates, or satellite-constrained top-down NOx emissions to identify and reduce uncertainties in bottom-up NOx emissions. However, the joint application of multiple satellite-derived model inputs to improve O3 state implementation plan (SIP) modeling has rarely been explored. In this study, Geostationary Operational Environmental Satellite (GOES) observations of clouds are applied to derive the photolysis rates, replacing those used in Texas SIP modeling. This changes modeled O3 concentrations by up to 80 ppb and improves O3 simulations by reducing modeled normalized mean bias (NMB) and normalized mean error (NME) by up to 0.1. A sector-based discrete Kalman filter (DKF) inversion approach is incorporated with the Comprehensive Air Quality Model with extensions (CAMx)-decoupled direct method (DDM) model to adjust Texas NOx emissions using a high-resolution Ozone Monitoring Instrument (OMI) NO2 product. The discrepancy between OMI and CAMx NO2 vertical column densities (VCDs) is further reduced by increasing modeled NOx lifetime and adding an artificial amount of NO2 in the upper troposphere. The region-based DKF inversion suggests increasing NOx emissions by 10-50% in most regions, deteriorating the model performance in predicting ground NO2 and O3, while the sector-based DKF inversion tends to scale down area and nonroad NOx emissions by 50%, leading to a 2-5 ppb decrease in ground 8 h O3 predictions. Model performance in simulating ground NO2 and O3 are improved using sector-based inversion-constrained NOx emissions, with 0.25 and 0.04 reductions in NMBs and 0.13 and 0.04 reductions in NMEs, respectively. Using both GOES-derived photolysis rates and OMI-constrained NOx emissions together reduces modeled NMB and NME by 0.05, increases the model

Bone Marrow-Derived Stem Cell (BMDSC transplantation improves fertility in a murine model of Asherman's syndrome.

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Feryal Alawadhi

Full Text Available Asherman's Syndrome is characterized by intrauterine adhesions or fibrosis resulting as a consequence of damage to the basal layer of endometrium and is associated with infertility due to loss of normal endometrium. We have previously shown that bone marrow derived stem cells (BMDSCs engraft the endometrium in mice and humans and Ischemia/reperfusion injury of uterus promoted BMDSCs migration to the endometrium; however, the role of BMDSCs in Asherman's syndrome has not been characterized. Here a murine model of Asherman's syndrome was created by traumatizing the uterus. We evaluate stem cell recruitment and pregnancy after BMDSCs transplantation in a model of Asherman's syndrome. In the Asheman's syndrome model, after BMDSC transplant, the Y chromosome bearing CD45-cells represented less than 0.1% of total endometrial cells. Twice the number of Y+CD45- cells was identified in the damaged uterus compared to the uninjured controls. There was no significant difference between the damaged and undamaged uterine horns in mice that received injury to a single horn. In the BMDSC transplant group, 9 of the 10 mice conceived, while only 3 of 10 in the non-transplanted group conceived (Chi-Square p = 0.0225; all mice in an uninjured control group conceived. The time to conception and mean litter size were not different between groups. Taken together, BMDSCs are recruited to endometrium in response to injury. Fertility improves after BMDSC transplant in Asherman's Syndrome mice, demonstrating a functional role for these cells in uterine repair. BMDSC transplantation is a potential novel treatment for Asherman's Syndrome and may also be useful to prevent Asherman's syndrome after uterine injury.

Improved choked flow model for MARS code

International Nuclear Information System (INIS)

Chung, Moon Sun; Lee, Won Jae; Ha, Kwi Seok; Hwang, Moon Kyu

2002-01-01

Choked flow calculation is improved by using a new sound speed criterion for bubbly flow that is derived by the characteristic analysis of hyperbolic two-fluid model. This model was based on the notion of surface tension for the interfacial pressure jump terms in the momentum equations. Real eigenvalues obtained as the closed-form solution of characteristic polynomial represent the sound speed in the bubbly flow regime that agrees well with the existing experimental data. The present sound speed shows more reasonable result in the extreme case than the Nguyens did. The present choked flow criterion derived by the present sound speed is employed in the MARS code and assessed by using the Marviken choked flow tests. The assessment results without any adjustment made by some discharge coefficients demonstrate more accurate predictions of choked flow rate in the bubbly flow regime than those of the earlier choked flow calculations. By calculating the Typical PWR (SBLOCA) problem, we make sure that the present model can reproduce the reasonable transients of integral reactor system

In silico modeling predicts drug sensitivity of patient-derived cancer cells.

Science.gov (United States)

Pingle, Sandeep C; Sultana, Zeba; Pastorino, Sandra; Jiang, Pengfei; Mukthavaram, Rajesh; Chao, Ying; Bharati, Ila Sri; Nomura, Natsuko; Makale, Milan; Abbasi, Taher; Kapoor, Shweta; Kumar, Ansu; Usmani, Shahabuddin; Agrawal, Ashish; Vali, Shireen; Kesari, Santosh

2014-05-21

Glioblastoma (GBM) is an aggressive disease associated with poor survival. It is essential to account for the complexity of GBM biology to improve diagnostic and therapeutic strategies. This complexity is best represented by the increasing amounts of profiling ("omics") data available due to advances in biotechnology. The challenge of integrating these vast genomic and proteomic data can be addressed by a comprehensive systems modeling approach. Here, we present an in silico model, where we simulate GBM tumor cells using genomic profiling data. We use this in silico tumor model to predict responses of cancer cells to targeted drugs. Initially, we probed the results from a recent hypothesis-independent, empirical study by Garnett and co-workers that analyzed the sensitivity of hundreds of profiled cancer cell lines to 130 different anticancer agents. We then used the tumor model to predict sensitivity of patient-derived GBM cell lines to different targeted therapeutic agents. Among the drug-mutation associations reported in the Garnett study, our in silico model accurately predicted ~85% of the associations. While testing the model in a prospective manner using simulations of patient-derived GBM cell lines, we compared our simulation predictions with experimental data using the same cells in vitro. This analysis yielded a ~75% agreement of in silico drug sensitivity with in vitro experimental findings. These results demonstrate a strong predictability of our simulation approach using the in silico tumor model presented here. Our ultimate goal is to use this model to stratify patients for clinical trials. By accurately predicting responses of cancer cells to targeted agents a priori, this in silico tumor model provides an innovative approach to personalizing therapy and promises to improve clinical management of cancer.

A spatial structural derivative model for ultraslow diffusion

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Xu Wei

2017-01-01

Full Text Available This study investigates the ultraslow diffusion by a spatial structural derivative, in which the exponential function ex is selected as the structural function to construct the local structural derivative diffusion equation model. The analytical solution of the diffusion equation is a form of Biexponential distribution. Its corresponding mean squared displacement is numerically calculated, and increases more slowly than the logarithmic function of time. The local structural derivative diffusion equation with the structural function ex in space is an alternative physical and mathematical modeling model to characterize a kind of ultraslow diffusion.

Improvement of hydrodenitrogenation (HDN) in co-refining of coal-derived liquid and petroleum fraction

Energy Technology Data Exchange (ETDEWEB)

Machida, M.; Ono, S. [Idemitsu Kosan Co. Ltd., Tokyo (Japan); Hattori, H. [Hokkaido University, Sapporo (Japan). Center for Advanced Research of Energy Technology

1997-09-01

The improvement in hydrodenitrogenation (HDN) of coal-derived liquids by co-refining with a petroleum fraction results principally from lowering the nitrogen content of the feedstock (coal-derived liquid) by blending with a nitrogen-free petroleum fraction. Effects of different fractions of coal-derived liquids on HDN and hydrodeoxygenation (HDO) were also examined. The HDN improvement by co-refining could be interpreted in terms of Langmuir-Hinshelwood mechanism. 38 refs., 3 figs., 3 tabs.

Structure activity relationships of quinoxalin-2-one derivatives as platelet-derived growth factor-beta receptor (PDGFbeta R) inhibitors, derived from molecular modeling.

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Mori, Yoshikazu; Hirokawa, Takatsugu; Aoki, Katsuyuki; Satomi, Hisanori; Takeda, Shuichi; Aburada, Masaki; Miyamoto, Ken-ichi

2008-05-01

We previously reported a quinoxalin-2-one compound (Compound 1) that had inhibitory activity equivalent to existing platelet-derived growth factor-beta receptor (PDGFbeta R) inhibitors. Lead optimization of Compound 1 to increase its activity and selectivity, using structural information regarding PDGFbeta R-ligand interactions, is urgently needed. Here we present models of the PDGFbeta R kinase domain complexed with quinoxalin-2-one derivatives. The models were constructed using comparative modeling, molecular dynamics (MD) and ligand docking. In particular, conformations derived from MD, and ligand binding site information presented by alpha-spheres in the pre-docking processing, allowed us to identify optimal protein structures for docking of target ligands. By carrying out molecular modeling and MD of PDGFbeta R in its inactive state, we obtained two structural models having good Compound 1 binding potentials. In order to distinguish the optimal candidate, we evaluated the structural activity relationships (SAR) between the ligand-binding free energies and inhibitory activity values (IC50 values) for available quinoxalin-2-one derivatives. Consequently, a final model with a high SAR was identified. This model included a molecular interaction between the hydrophobic pocket behind the ATP binding site and the substitution region of the quinoxalin-2-one derivatives. These findings should prove useful in lead optimization of quinoxalin-2-one derivatives as PDGFb R inhibitors.

A variable-order fractal derivative model for anomalous diffusion

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Liu Xiaoting

2017-01-01

Full Text Available This paper pays attention to develop a variable-order fractal derivative model for anomalous diffusion. Previous investigations have indicated that the medium structure, fractal dimension or porosity may change with time or space during solute transport processes, results in time or spatial dependent anomalous diffusion phenomena. Hereby, this study makes an attempt to introduce a variable-order fractal derivative diffusion model, in which the index of fractal derivative depends on temporal moment or spatial position, to characterize the above mentioned anomalous diffusion (or transport processes. Compared with other models, the main advantages in description and the physical explanation of new model are explored by numerical simulation. Further discussions on the dissimilitude such as computational efficiency, diffusion behavior and heavy tail phenomena of the new model and variable-order fractional derivative model are also offered.

A 'simple' hybrid model for power derivatives

International Nuclear Information System (INIS)

Lyle, Matthew R.; Elliott, Robert J.

2009-01-01

This paper presents a method for valuing power derivatives using a supply-demand approach. Our method extends work in the field by incorporating randomness into the base load portion of the supply stack function and equating it with a noisy demand process. We obtain closed form solutions for European option prices written on average spot prices considering two different supply models: a mean-reverting model and a Markov chain model. The results are extensions of the classic Black-Scholes equation. The model provides a relatively simple approach to describe the complicated price behaviour observed in electricity spot markets and also allows for computationally efficient derivatives pricing. (author)

Improving PSA quality of KSNP PSA model

International Nuclear Information System (INIS)

Yang, Joon Eon; Ha, Jae Joo

2004-01-01

In the RIR (Risk-informed Regulation), PSA (Probabilistic Safety Assessment) plays a major role because it provides overall risk insights for the regulatory body and utility. Therefore, the scope, the level of details and the technical adequacy of PSA, i.e. the quality of PSA is to be ensured for the successful RIR. To improve the quality of Korean PSA, we evaluate the quality of the KSNP (Korean Standard Nuclear Power Plant) internal full-power PSA model based on the 'ASME PRA Standard' and the 'NEI PRA Peer Review Process Guidance.' As a working group, PSA experts of the regulatory body and industry also participated in the evaluation process. It is finally judged that the overall quality of the KSNP PSA is between the ASME Standard Capability Category I and II. We also derive some items to be improved for upgrading the quality of the PSA up to the ASME Standard Capability Category II. In this paper, we show the result of quality evaluation, and the activities to improve the quality of the KSNP PSA model

Titan I propulsion system modeling and possible performance improvements

Science.gov (United States)

Giusti, Oreste

This thesis features the Titan I propulsion systems and offers data-supported suggestions for improvements to increase performance. The original propulsion systems were modeled both graphically in CAD and via equations. Due to the limited availability of published information, it was necessary to create a more detailed, secondary set of models. Various engineering equations---pertinent to rocket engine design---were implemented in order to generate the desired extra detail. This study describes how these new models were then imported into the ESI CFD Suite. Various parameters are applied to these imported models as inputs that include, for example, bi-propellant combinations, pressure, temperatures, and mass flow rates. The results were then processed with ESI VIEW, which is visualization software. The output files were analyzed for forces in the nozzle, and various results were generated, including sea level thrust and ISP. Experimental data are provided to compare the original engine configuration models to the derivative suggested improvement models.

On the Exploitation of Sensitivity Derivatives for Improving Sampling Methods

Science.gov (United States)

Cao, Yanzhao; Hussaini, M. Yousuff; Zang, Thomas A.

2003-01-01

Many application codes, such as finite-element structural analyses and computational fluid dynamics codes, are capable of producing many sensitivity derivatives at a small fraction of the cost of the underlying analysis. This paper describes a simple variance reduction method that exploits such inexpensive sensitivity derivatives to increase the accuracy of sampling methods. Three examples, including a finite-element structural analysis of an aircraft wing, are provided that illustrate an order of magnitude improvement in accuracy for both Monte Carlo and stratified sampling schemes.

Connecting Biochemical Photosynthesis Models with Crop Models to Support Crop Improvement.

Science.gov (United States)

Wu, Alex; Song, Youhong; van Oosterom, Erik J; Hammer, Graeme L

2016-01-01

The next advance in field crop productivity will likely need to come from improving crop use efficiency of resources (e.g., light, water, and nitrogen), aspects of which are closely linked with overall crop photosynthetic efficiency. Progress in genetic manipulation of photosynthesis is confounded by uncertainties of consequences at crop level because of difficulties connecting across scales. Crop growth and development simulation models that integrate across biological levels of organization and use a gene-to-phenotype modeling approach may present a way forward. There has been a long history of development of crop models capable of simulating dynamics of crop physiological attributes. Many crop models incorporate canopy photosynthesis (source) as a key driver for crop growth, while others derive crop growth from the balance between source- and sink-limitations. Modeling leaf photosynthesis has progressed from empirical modeling via light response curves to a more mechanistic basis, having clearer links to the underlying biochemical processes of photosynthesis. Cross-scale modeling that connects models at the biochemical and crop levels and utilizes developments in upscaling leaf-level models to canopy models has the potential to bridge the gap between photosynthetic manipulation at the biochemical level and its consequences on crop productivity. Here we review approaches to this emerging cross-scale modeling framework and reinforce the need for connections across levels of modeling. Further, we propose strategies for connecting biochemical models of photosynthesis into the cross-scale modeling framework to support crop improvement through photosynthetic manipulation.

Connecting Biochemical Photosynthesis Models with Crop Models to Support Crop Improvement

Science.gov (United States)

Wu, Alex; Song, Youhong; van Oosterom, Erik J.; Hammer, Graeme L.

2016-01-01

The next advance in field crop productivity will likely need to come from improving crop use efficiency of resources (e.g., light, water, and nitrogen), aspects of which are closely linked with overall crop photosynthetic efficiency. Progress in genetic manipulation of photosynthesis is confounded by uncertainties of consequences at crop level because of difficulties connecting across scales. Crop growth and development simulation models that integrate across biological levels of organization and use a gene-to-phenotype modeling approach may present a way forward. There has been a long history of development of crop models capable of simulating dynamics of crop physiological attributes. Many crop models incorporate canopy photosynthesis (source) as a key driver for crop growth, while others derive crop growth from the balance between source- and sink-limitations. Modeling leaf photosynthesis has progressed from empirical modeling via light response curves to a more mechanistic basis, having clearer links to the underlying biochemical processes of photosynthesis. Cross-scale modeling that connects models at the biochemical and crop levels and utilizes developments in upscaling leaf-level models to canopy models has the potential to bridge the gap between photosynthetic manipulation at the biochemical level and its consequences on crop productivity. Here we review approaches to this emerging cross-scale modeling framework and reinforce the need for connections across levels of modeling. Further, we propose strategies for connecting biochemical models of photosynthesis into the cross-scale modeling framework to support crop improvement through photosynthetic manipulation. PMID:27790232

Simultaneous inference for model averaging of derived parameters

DEFF Research Database (Denmark)

Jensen, Signe Marie; Ritz, Christian

2015-01-01

Model averaging is a useful approach for capturing uncertainty due to model selection. Currently, this uncertainty is often quantified by means of approximations that do not easily extend to simultaneous inference. Moreover, in practice there is a need for both model averaging and simultaneous...... inference for derived parameters calculated in an after-fitting step. We propose a method for obtaining asymptotically correct standard errors for one or several model-averaged estimates of derived parameters and for obtaining simultaneous confidence intervals that asymptotically control the family...

Evaluating the potential for site-specific modification of LiDAR DEM derivatives to improve environmental planning-scale wetland identification using Random Forest classification

Science.gov (United States)

O'Neil, Gina L.; Goodall, Jonathan L.; Watson, Layne T.

2018-04-01

Wetlands are important ecosystems that provide many ecological benefits, and their quality and presence are protected by federal regulations. These regulations require wetland delineations, which can be costly and time-consuming to perform. Computer models can assist in this process, but lack the accuracy necessary for environmental planning-scale wetland identification. In this study, the potential for improvement of wetland identification models through modification of digital elevation model (DEM) derivatives, derived from high-resolution and increasingly available light detection and ranging (LiDAR) data, at a scale necessary for small-scale wetland delineations is evaluated. A novel approach of flow convergence modelling is presented where Topographic Wetness Index (TWI), curvature, and Cartographic Depth-to-Water index (DTW), are modified to better distinguish wetland from upland areas, combined with ancillary soil data, and used in a Random Forest classification. This approach is applied to four study sites in Virginia, implemented as an ArcGIS model. The model resulted in significant improvement in average wetland accuracy compared to the commonly used National Wetland Inventory (84.9% vs. 32.1%), at the expense of a moderately lower average non-wetland accuracy (85.6% vs. 98.0%) and average overall accuracy (85.6% vs. 92.0%). From this, we concluded that modifying TWI, curvature, and DTW provides more robust wetland and non-wetland signatures to the models by improving accuracy rates compared to classifications using the original indices. The resulting ArcGIS model is a general tool able to modify these local LiDAR DEM derivatives based on site characteristics to identify wetlands at a high resolution.

Establishing an Improved Kane Dynamic Model for the 7-DOF Reconfigurable Modular Robot

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Xiao Li

2017-01-01

Full Text Available We propose an improved Kane dynamic model theory for the 7-DOF modular robot in this paper, and the model precision is improved by the improved function T′it. We designed three types of progressive modular joints for reconfigurable modular robot that can be used in industrial robot, space robot, and special robot. The Kane dynamic model and the solid dynamic model are established, respectively, for the 7-DOF modular robot. After that, the experimental results are obtained from the simulation experiment of typical task in the established dynamic models. By the analysis model of error, the equation of the improved torque T′it is derived and proposed. And the improved Kane dynamic model is established for the modular robot that used T′it. Based on the experimental data, the undetermined coefficient matrix is five-order linear that was proved in 7-DOF modular robot. And the explicit formulation is solved of the Kane dynamic model and can be used in control system.

Modeling of heat conduction via fractional derivatives

Science.gov (United States)

Fabrizio, Mauro; Giorgi, Claudio; Morro, Angelo

2017-09-01

The modeling of heat conduction is considered by letting the time derivative, in the Cattaneo-Maxwell equation, be replaced by a derivative of fractional order. The purpose of this new approach is to overcome some drawbacks of the Cattaneo-Maxwell equation, for instance possible fluctuations which violate the non-negativity of the absolute temperature. Consistency with thermodynamics is shown to hold for a suitable free energy potential, that is in fact a functional of the summed history of the heat flux, subject to a suitable restriction on the set of admissible histories. Compatibility with wave propagation at a finite speed is investigated in connection with temperature-rate waves. It follows that though, as expected, this is the case for the Cattaneo-Maxwell equation, the model involving the fractional derivative does not allow the propagation at a finite speed. Nevertheless, this new model provides a good description of wave-like profiles in thermal propagation phenomena, whereas Fourier's law does not.

Improvements to the RADIOM non-LTE model

Science.gov (United States)

Busquet, M.; Colombant, D.; Klapisch, M.; Fyfe, D.; Gardner, J.

2009-12-01

In 1993, we proposed the RADIOM model [M. Busquet, Phys. Fluids 85 (1993) 4191] where an ionization temperature T z is used to derive non-LTE properties from LTE data. T z is obtained from an "extended Saha equation" where unbalanced transitions, like radiative decay, give the non-LTE behavior. Since then, major improvements have been made. T z has been shown to be more than a heuristic value, but describes the actual distribution of excited and ionized states and can be understood as an "effective temperature". Therefore we complement the extended Saha equation by introducing explicitly the auto-ionization/dielectronic capture. Also we use the SCROLL model to benchmark the computed values of T z.

Human iPSC-derived cardiomyocytes and tissue engineering strategies for disease modeling and drug screening.

Science.gov (United States)

Smith, Alec S T; Macadangdang, Jesse; Leung, Winnie; Laflamme, Michael A; Kim, Deok-Ho

Improved methodologies for modeling cardiac disease phenotypes and accurately screening the efficacy and toxicity of potential therapeutic compounds are actively being sought to advance drug development and improve disease modeling capabilities. To that end, much recent effort has been devoted to the development of novel engineered biomimetic cardiac tissue platforms that accurately recapitulate the structure and function of the human myocardium. Within the field of cardiac engineering, induced pluripotent stem cells (iPSCs) are an exciting tool that offer the potential to advance the current state of the art, as they are derived from somatic cells, enabling the development of personalized medical strategies and patient specific disease models. Here we review different aspects of iPSC-based cardiac engineering technologies. We highlight methods for producing iPSC-derived cardiomyocytes (iPSC-CMs) and discuss their application to compound efficacy/toxicity screening and in vitro modeling of prevalent cardiac diseases. Special attention is paid to the application of micro- and nano-engineering techniques for the development of novel iPSC-CM based platforms and their potential to advance current preclinical screening modalities. Published by Elsevier Inc.

Price models for oil derivates in Slovenia

International Nuclear Information System (INIS)

Nemac, F.; Saver, A.

1995-01-01

In Slovenia, a law is currently applied according to which any change in the price of oil derivatives is subject to the Governmental approval. Following the target of getting closer to the European Union, the necessity has arisen of finding ways for the introduction of liberalization or automated approach to price modifications depending on oscillations of oil derivative prices on the world market and the rate of exchange of the American dollar. It is for this reason that at the Agency for Energy Restructuring we made a study for the Ministry of Economic Affairs and Development regarding this issue. We analysed the possible models for the formation of oil derivative prices for Slovenia. Based on the assessment of experiences of primarily the west European countries, we proposed three models for the price formation for Slovenia. In future, it is expected that the Government of the Republic of Slovenia will make a selection of one of the proposed models to be followed by enforcement of price liberalization. The paper presents two representative models for price formation as used in Austria and Portugal. In the continuation the authors analyse the application of three models that they find suitable for the use in Slovenia. (author)

Derivation and External Validation of Prediction Models for Advanced Chronic Kidney Disease Following Acute Kidney Injury.

Science.gov (United States)

James, Matthew T; Pannu, Neesh; Hemmelgarn, Brenda R; Austin, Peter C; Tan, Zhi; McArthur, Eric; Manns, Braden J; Tonelli, Marcello; Wald, Ron; Quinn, Robert R; Ravani, Pietro; Garg, Amit X

2017-11-14

Some patients will develop chronic kidney disease after a hospitalization with acute kidney injury; however, no risk-prediction tools have been developed to identify high-risk patients requiring follow-up. To derive and validate predictive models for progression of acute kidney injury to advanced chronic kidney disease. Data from 2 population-based cohorts of patients with a prehospitalization estimated glomerular filtration rate (eGFR) of more than 45 mL/min/1.73 m2 and who had survived hospitalization with acute kidney injury (defined by a serum creatinine increase during hospitalization > 0.3 mg/dL or > 50% of their prehospitalization baseline), were used to derive and validate multivariable prediction models. The risk models were derived from 9973 patients hospitalized in Alberta, Canada (April 2004-March 2014, with follow-up to March 2015). The risk models were externally validated with data from a cohort of 2761 patients hospitalized in Ontario, Canada (June 2004-March 2012, with follow-up to March 2013). Demographic, laboratory, and comorbidity variables measured prior to discharge. Advanced chronic kidney disease was defined by a sustained reduction in eGFR less than 30 mL/min/1.73 m2 for at least 3 months during the year after discharge. All participants were followed up for up to 1 year. The participants (mean [SD] age, 66 [15] years in the derivation and internal validation cohorts and 69 [11] years in the external validation cohort; 40%-43% women per cohort) had a mean (SD) baseline serum creatinine level of 1.0 (0.2) mg/dL and more than 20% had stage 2 or 3 acute kidney injury. Advanced chronic kidney disease developed in 408 (2.7%) of 9973 patients in the derivation cohort and 62 (2.2%) of 2761 patients in the external validation cohort. In the derivation cohort, 6 variables were independently associated with the outcome: older age, female sex, higher baseline serum creatinine value, albuminuria, greater severity of acute kidney injury, and higher

AN IMPROVED SNAKE MODEL FOR REFINEMENT OF LIDAR-DERIVED BUILDING ROOF CONTOURS USING AERIAL IMAGES

Directory of Open Access Journals (Sweden)

Q. Chen

2016-06-01

Full Text Available Building roof contours are considered as very important geometric data, which have been widely applied in many fields, including but not limited to urban planning, land investigation, change detection and military reconnaissance. Currently, the demand on building contours at a finer scale (especially in urban areas has been raised in a growing number of studies such as urban environment quality assessment, urban sprawl monitoring and urban air pollution modelling. LiDAR is known as an effective means of acquiring 3D roof points with high elevation accuracy. However, the precision of the building contour obtained from LiDAR data is restricted by its relatively low scanning resolution. With the use of the texture information from high-resolution imagery, the precision can be improved. In this study, an improved snake model is proposed to refine the initial building contours extracted from LiDAR. First, an improved snake model is constructed with the constraints of the deviation angle, image gradient, and area. Then, the nodes of the contour are moved in a certain range to find the best optimized result using greedy algorithm. Considering both precision and efficiency, the candidate shift positions of the contour nodes are constrained, and the searching strategy for the candidate nodes is explicitly designed. The experiments on three datasets indicate that the proposed method for building contour refinement is effective and feasible. The average quality index is improved from 91.66% to 93.34%. The statistics of the evaluation results for every single building demonstrated that 77.0% of the total number of contours is updated with higher quality index.

Simple model for deriving sdg interacting boson model Hamiltonians: 150Nd example

Science.gov (United States)

Devi, Y. D.; Kota, V. K. B.

1993-07-01

A simple and yet useful model for deriving sdg interacting boson model (IBM) Hamiltonians is to assume that single-boson energies derive from identical particle (pp and nn) interactions and proton, neutron single-particle energies, and that the two-body matrix elements for bosons derive from pn interaction, with an IBM-2 to IBM-1 projection of the resulting p-n sdg IBM Hamiltonian. The applicability of this model in generating sdg IBM Hamiltonians is demonstrated, using a single-j-shell Otsuka-Arima-Iachello mapping of the quadrupole and hexadecupole operators in proton and neutron spaces separately and constructing a quadrupole-quadrupole plus hexadecupole-hexadecupole Hamiltonian in the analysis of the spectra, B(E2)'s, and E4 strength distribution in the example of 150Nd.

Simple model for deriving sdg interacting boson model Hamiltonians: 150Nd example

International Nuclear Information System (INIS)

Devi, Y.D.; Kota, V.K.B.

1993-01-01

A simple and yet useful model for deriving sdg interacting boson model (IBM) Hamiltonians is to assume that single-boson energies derive from identical particle (pp and nn) interactions and proton, neutron single-particle energies, and that the two-body matrix elements for bosons derive from pn interaction, with an IBM-2 to IBM-1 projection of the resulting p-n sdg IBM Hamiltonian. The applicability of this model in generating sdg IBM Hamiltonians is demonstrated, using a single-j-shell Otsuka-Arima-Iachello mapping of the quadrupole and hexadecupole operators in proton and neutron spaces separately and constructing a quadrupole-quadrupole plus hexadecupole-hexadecupole Hamiltonian in the analysis of the spectra, B(E2)'s, and E4 strength distribution in the example of 150 Nd

Modelling Fanconi anemia pathogenesis and therapeutics using integration-free patient-derived iPSCs.

Science.gov (United States)

Liu, Guang-Hui; Suzuki, Keiichiro; Li, Mo; Qu, Jing; Montserrat, Nuria; Tarantino, Carolina; Gu, Ying; Yi, Fei; Xu, Xiuling; Zhang, Weiqi; Ruiz, Sergio; Plongthongkum, Nongluk; Zhang, Kun; Masuda, Shigeo; Nivet, Emmanuel; Tsunekawa, Yuji; Soligalla, Rupa Devi; Goebl, April; Aizawa, Emi; Kim, Na Young; Kim, Jessica; Dubova, Ilir; Li, Ying; Ren, Ruotong; Benner, Chris; Del Sol, Antonio; Bueren, Juan; Trujillo, Juan Pablo; Surralles, Jordi; Cappelli, Enrico; Dufour, Carlo; Esteban, Concepcion Rodriguez; Belmonte, Juan Carlos Izpisua

2014-07-07

Fanconi anaemia (FA) is a recessive disorder characterized by genomic instability, congenital abnormalities, cancer predisposition and bone marrow (BM) failure. However, the pathogenesis of FA is not fully understood partly due to the limitations of current disease models. Here, we derive integration free-induced pluripotent stem cells (iPSCs) from an FA patient without genetic complementation and report in situ gene correction in FA-iPSCs as well as the generation of isogenic FANCA-deficient human embryonic stem cell (ESC) lines. FA cellular phenotypes are recapitulated in iPSCs/ESCs and their adult stem/progenitor cell derivatives. By using isogenic pathogenic mutation-free controls as well as cellular and genomic tools, our model serves to facilitate the discovery of novel disease features. We validate our model as a drug-screening platform by identifying several compounds that improve hematopoietic differentiation of FA-iPSCs. These compounds are also able to rescue the hematopoietic phenotype of FA patient BM cells.

Modeling Fanconi Anemia pathogenesis and therapeutics using integration-free patient-derived iPSCs

Science.gov (United States)

Montserrat, Nuria; Tarantino, Carolina; Gu, Ying; Yi, Fei; Xu, Xiuling; Zhang, Weiqi; Ruiz, Sergio; Plongthongkum, Nongluk; Zhang, Kun; Masuda, Shigeo; Nivet, Emmanuel; Tsunekawa, Yuji; Soligalla, Rupa Devi; Goebl, April; Aizawa, Emi; Kim, Na Young; Kim, Jessica; Dubova, Ilir; Li, Ying; Ren, Ruotong; Benner, Chris; del Sol, Antonio; Bueren, Juan; Trujillo, Juan Pablo; Surralles, Jordi; Cappelli, Enrico; Dufour, Carlo; Esteban, Concepcion Rodriguez; Belmonte, Juan Carlos Izpisua

2014-01-01

Fanconi Anemia (FA) is a recessive disorder characterized by genomic instability, congenital abnormalities, cancer predisposition and bone marrow failure. However, the pathogenesis of FA is not fully understood partly due to the limitations of current disease models. Here, we derive integration-free induced pluripotent stem cells (iPSCs) from an FA patient without genetic complementation and report in situ gene correction in FA-iPSCs as well as the generation of isogenic FANCA deficient human embryonic stem cell (ESC) lines. FA cellular phenotypes are recapitulated in iPSCs/ESCs and their adult stem/progenitor cell derivatives. By using isogenic pathogenic mutation-free controls as well as cellular and genomic tools, our model serves to facilitate the discovery of novel disease features. We validate our model as a drug-screening platform by identifying several compounds that improve hematopoietic differentiation of FA-iPSCs. These compounds are also able to rescue the hematopoietic phenotype of FA-patient bone marrow cells. PMID:24999918

State-Space Modelling of Loudspeakers using Fractional Derivatives

DEFF Research Database (Denmark)

King, Alexander Weider; Agerkvist, Finn T.

2015-01-01

This work investigates the use of fractional order derivatives in modeling moving-coil loudspeakers. A fractional order state-space solution is developed, leading the way towards incorporating nonlinearities into a fractional order system. The method is used to calculate the response of a fractio......This work investigates the use of fractional order derivatives in modeling moving-coil loudspeakers. A fractional order state-space solution is developed, leading the way towards incorporating nonlinearities into a fractional order system. The method is used to calculate the response...... of a fractional harmonic oscillator, representing the mechanical part of a loudspeaker, showing the effect of the fractional derivative and its relationship to viscoelasticity. Finally, a loudspeaker model with a fractional order viscoelastic suspension and fractional order voice coil is fit to measurement data...

Analysis of Drude model using fractional derivatives without singular kernels

Directory of Open Access Journals (Sweden)

Jiménez Leonardo Martínez

2017-11-01

Full Text Available We report study exploring the fractional Drude model in the time domain, using fractional derivatives without singular kernels, Caputo-Fabrizio (CF, and fractional derivatives with a stretched Mittag-Leffler function. It is shown that the velocity and current density of electrons moving through a metal depend on both the time and the fractional order 0 < γ ≤ 1. Due to non-singular fractional kernels, it is possible to consider complete memory effects in the model, which appear neither in the ordinary model, nor in the fractional Drude model with Caputo fractional derivative. A comparison is also made between these two representations of the fractional derivatives, resulting a considered difference when γ < 0.8.

Large deflection of viscoelastic beams using fractional derivative model

International Nuclear Information System (INIS)

Bahranini, Seyed Masoud Sotoodeh; Eghtesad, Mohammad; Ghavanloo, Esmaeal; Farid, Mehrdad

2013-01-01

This paper deals with large deflection of viscoelastic beams using a fractional derivative model. For this purpose, a nonlinear finite element formulation of viscoelastic beams in conjunction with the fractional derivative constitutive equations has been developed. The four-parameter fractional derivative model has been used to describe the constitutive equations. The deflected configuration for a uniform beam with different boundary conditions and loads is presented. The effect of the order of fractional derivative on the large deflection of the cantilever viscoelastic beam, is investigated after 10, 100, and 1000 hours. The main contribution of this paper is finite element implementation for nonlinear analysis of viscoelastic fractional model using the storage of both strain and stress histories. The validity of the present analysis is confirmed by comparing the results with those found in the literature.

Improved point-kinetics model for the BWR control rod drop accident

International Nuclear Information System (INIS)

Neogy, P.; Wakabayashi, T.; Carew, J.F.

1985-01-01

A simple prescription to account for spatial feedback weighting effects in RDA (rod drop accident) point-kinetics analyses has been derived and tested. The point-kinetics feedback model is linear in the core peaking factor, F/sub Q/, and in the core average void fraction and fuel temperature. Comparison with detailed spatial kinetics analyses indicates that the improved point-kinetics model provides an accurate description of the BWR RDA

A stochastic post-processing method for solar irradiance forecasts derived from NWPs models

Science.gov (United States)

Lara-Fanego, V.; Pozo-Vazquez, D.; Ruiz-Arias, J. A.; Santos-Alamillos, F. J.; Tovar-Pescador, J.

2010-09-01

Solar irradiance forecast is an important area of research for the future of the solar-based renewable energy systems. Numerical Weather Prediction models (NWPs) have proved to be a valuable tool for solar irradiance forecasting with lead time up to a few days. Nevertheless, these models show low skill in forecasting the solar irradiance under cloudy conditions. Additionally, climatic (averaged over seasons) aerosol loading are usually considered in these models, leading to considerable errors for the Direct Normal Irradiance (DNI) forecasts during high aerosols load conditions. In this work we propose a post-processing method for the Global Irradiance (GHI) and DNI forecasts derived from NWPs. Particularly, the methods is based on the use of Autoregressive Moving Average with External Explanatory Variables (ARMAX) stochastic models. These models are applied to the residuals of the NWPs forecasts and uses as external variables the measured cloud fraction and aerosol loading of the day previous to the forecast. The method is evaluated for a set one-moth length three-days-ahead forecast of the GHI and DNI, obtained based on the WRF mesoscale atmospheric model, for several locations in Andalusia (Southern Spain). The Cloud fraction is derived from MSG satellite estimates and the aerosol loading from the MODIS platform estimates. Both sources of information are readily available at the time of the forecast. Results showed a considerable improvement of the forecasting skill of the WRF model using the proposed post-processing method. Particularly, relative improvement (in terms of the RMSE) for the DNI during summer is about 20%. A similar value is obtained for the GHI during the winter.

Improvement for Amelioration Inventory Model with Weibull Distribution

Directory of Open Access Journals (Sweden)

Han-Wen Tuan

2017-01-01

Full Text Available Most inventory models dealt with deteriorated items. On the contrary, just a few papers considered inventory systems under amelioration environment. We study an amelioration inventory model with Weibull distribution. However, there are some questionable results in the amelioration paper. We will first point out those questionable results in the previous paper that did not derive the optimal solution and then provide some improvements. We will provide a rigorous analytical work for different cases dependent on the size of the shape parameter. We present a detailed numerical example for different ranges of the sharp parameter to illustrate that our solution method attains the optimal solution. We developed a new amelioration model and then provided a detailed analyzed procedure to find the optimal solution. Our findings will help researchers develop their new inventory models.

Turbulence modeling with fractional derivatives: Derivation from first principles and initial results

Science.gov (United States)

Epps, Brenden; Cushman-Roisin, Benoit

2017-11-01

Fluid turbulence is an outstanding unsolved problem in classical physics, despite 120+ years of sustained effort. Given this history, we assert that a new mathematical framework is needed to make a transformative breakthrough. This talk offers one such framework, based upon kinetic theory tied to the statistics of turbulent transport. Starting from the Boltzmann equation and ``Lévy α-stable distributions'', we derive a turbulence model that expresses the turbulent stresses in the form of a fractional derivative, where the fractional order is tied to the transport behavior of the flow. Initial results are presented herein, for the cases of Couette-Poiseuille flow and 2D boundary layers. Among other results, our model is able to reproduce the logarithmic Law of the Wall in shear turbulence.

Vulnerable Derivatives and Good Deal Bounds: A Structural Model

DEFF Research Database (Denmark)

Murgoci, Agatha

2013-01-01

We price vulnerable derivatives -- i.e. derivatives where the counterparty may default. These are basically the derivatives traded on the over-the-counter (OTC) markets. Default is modeled in a structural framework. The technique employed for pricing is good deal bounds (GDBs). The method imposes...

Hamiltonian derivation of the nonhydrostatic pressure-coordinate model

Science.gov (United States)

Salmon, Rick; Smith, Leslie M.

1994-07-01

In 1989, the Miller-Pearce (MP) model for nonhydrostatic fluid motion governed by equations written in pressure coordinates was extended by removing the prescribed reference temperature, T(sub s)(p), while retaining the conservation laws and other desirable properties. It was speculated that this extension of the MP model had a Hamiltonian structure and that a slick derivation of the Ertel property could be constructed if the relevant Hamiltonian were known. In this note, the extended equations are derived using Hamilton's principle. The potential vorticity law arises from the usual particle-relabeling symmetry of the Lagrangian, and even the absence of sound waves is anticipated from the fact that the pressure inside the free energy G(p, theta) in the derived equation is hydrostatic and thus G is insensitive to local pressure fluctuations. The model extension is analogous to the semigeostrophic equations for nearly geostrophic flow, which do not incorporate a prescribed reference state, while the earlier MP model is analogous to the quasigeostrophic equations, which become highly inaccurate when the flow wanders from a prescribed state with nearly flat isothermal surfaces.

Improved Model for Depth Bias Correction in Airborne LiDAR Bathymetry Systems

Directory of Open Access Journals (Sweden)

Jianhu Zhao

2017-07-01

Full Text Available Airborne LiDAR bathymetry (ALB is efficient and cost effective in obtaining shallow water topography, but often produces a low-accuracy sounding solution due to the effects of ALB measurements and ocean hydrological parameters. In bathymetry estimates, peak shifting of the green bottom return caused by pulse stretching induces depth bias, which is the largest error source in ALB depth measurements. The traditional depth bias model is often applied to reduce the depth bias, but it is insufficient when used with various ALB system parameters and ocean environments. Therefore, an accurate model that considers all of the influencing factors must be established. In this study, an improved depth bias model is developed through stepwise regression in consideration of the water depth, laser beam scanning angle, sensor height, and suspended sediment concentration. The proposed improved model and a traditional one are used in an experiment. The results show that the systematic deviation of depth bias corrected by the traditional and improved models is reduced significantly. Standard deviations of 0.086 and 0.055 m are obtained with the traditional and improved models, respectively. The accuracy of the ALB-derived depth corrected by the improved model is better than that corrected by the traditional model.

Triple Diagonal modeling: A mechanism to focus productivity improvement for business success

Energy Technology Data Exchange (ETDEWEB)

Levine, L.O. [Pacific Northwest Lab., Richland, WA (United States); Villareal, L.D. [Army Depot, Corpus Christi, TX (United States)

1993-09-01

Triple Diagonal (M) modeling is a technique to help quickly diagnose an organization`s existing production system and to identify significant improvement opportunities in executing, controlling, and planning operations. TD modeling is derived from ICAM Definition Language (IDEF 0)-also known as Structured Analysis and Design Technique. It has been used successfully at several Department of Defense remanufacturing facilities trying to accomplish significant production system modernization. TD has several advantages over other modeling techniques. First, it quickly does ``As-ls`` analysis and then moves on to identify improvements. Second, creating one large diagram makes it easier to share the TD model throughout an organization, rather than the many linked 8 1/2 {times} 11`` drawings used in traditional decomposition approaches. Third, it acts as a communication mechanism to share understanding about improvement opportunities that may cross existing functional/organizational boundaries. Finally, TD acts as a vehicle to build a consensus on a prioritized list of improvement efforts that ``hangs togethers as an agenda for systemic changes in the production system and the improved integration of support functions.

Modeling neurodegenerative diseases with patient-derived induced pluripotent cells

DEFF Research Database (Denmark)

Poon, Anna; Zhang, Yu; Chandrasekaran, Abinaya

2017-01-01

patient-specific induced pluripotent stem cells (iPSCs) and isogenic controls generated using CRISPR-Cas9 mediated genome editing. The iPSCs are self-renewable and capable of being differentiated into the cell types affected by the diseases. These in vitro models based on patient-derived iPSCs provide...... the possibilities of generating three-dimensional (3D) models using the iPSCs-derived cells and compare their advantages and disadvantages to conventional two-dimensional (2D) models....

Dynamic PET of human liver inflammation: impact of kinetic modeling with optimization-derived dual-blood input function.

Science.gov (United States)

Wang, Guobao; Corwin, Michael T; Olson, Kristin A; Badawi, Ramsey D; Sarkar, Souvik

2018-05-30

The hallmark of nonalcoholic steatohepatitis is hepatocellular inflammation and injury in the setting of hepatic steatosis. Recent work has indicated that dynamic 18F-FDG PET with kinetic modeling has the potential to assess hepatic inflammation noninvasively, while static FDG-PET did not show a promise. Because the liver has dual blood supplies, kinetic modeling of dynamic liver PET data is challenging in human studies. The objective of this study is to evaluate and identify a dual-input kinetic modeling approach for dynamic FDG-PET of human liver inflammation. Fourteen human patients with nonalcoholic fatty liver disease were included in the study. Each patient underwent one-hour dynamic FDG-PET/CT scan and had liver biopsy within six weeks. Three models were tested for kinetic analysis: traditional two-tissue compartmental model with an image-derived single-blood input function (SBIF), model with population-based dual-blood input function (DBIF), and modified model with optimization-derived DBIF through a joint estimation framework. The three models were compared using Akaike information criterion (AIC), F test and histopathologic inflammation reference. The results showed that the optimization-derived DBIF model improved the fitting of liver time activity curves and achieved lower AIC values and higher F values than the SBIF and population-based DBIF models in all patients. The optimization-derived model significantly increased FDG K1 estimates by 101% and 27% as compared with traditional SBIF and population-based DBIF. K1 by the optimization-derived model was significantly associated with histopathologic grades of liver inflammation while the other two models did not provide a statistical significance. In conclusion, modeling of DBIF is critical for kinetic analysis of dynamic liver FDG-PET data in human studies. The optimization-derived DBIF model is more appropriate than SBIF and population-based DBIF for dynamic FDG-PET of liver inflammation. © 2018

Deriving simulators for hybrid Chi models

NARCIS (Netherlands)

Beek, van D.A.; Man, K.L.; Reniers, M.A.; Rooda, J.E.; Schiffelers, R.R.H.

2006-01-01

The hybrid Chi language is formalism for modeling, simulation and verification of hybrid systems. The formal semantics of hybrid Chi allows the definition of provably correct implementations for simulation, verification and realtime control. This paper discusses the principles of deriving an

Remarks on the microscopic derivation of the collective model

International Nuclear Information System (INIS)

Toyoda, T.; Wildermuth, K.

1984-01-01

The rotational part of the phenomenological collective model of Bohr and Mottelson and others is derived microscopically, starting with the Schrodinger equation written in projection form and introducing a new set of 'relative Euler angles'. In order to derive the local Schrodinger equation of the collective model, it is assumed that the intrinsic wave functions give strong peaking properties to the overlapping kernels

Hamiltonian derivation of a gyrofluid model for collisionless magnetic reconnection

International Nuclear Information System (INIS)

Tassi, E

2014-01-01

We consider a simple electromagnetic gyrokinetic model for collisionless plasmas and show that it possesses a Hamiltonian structure. Subsequently, from this model we derive a two-moment gyrofluid model by means of a procedure which guarantees that the resulting gyrofluid model is also Hamiltonian. The first step in the derivation consists of imposing a generic fluid closure in the Poisson bracket of the gyrokinetic model, after expressing such bracket in terms of the gyrofluid moments. The constraint of the Jacobi identity, which every Poisson bracket has to satisfy, selects then what closures can lead to a Hamiltonian gyrofluid system. For the case at hand, it turns out that the only closures (not involving integro/differential operators or an explicit dependence on the spatial coordinates) that lead to a valid Poisson bracket are those for which the second order parallel moment, independently for each species, is proportional to the zero order moment. In particular, if one chooses an isothermal closure based on the equilibrium temperatures and derives accordingly the Hamiltonian of the system from the Hamiltonian of the parent gyrokinetic model, one recovers a known Hamiltonian gyrofluid model for collisionless reconnection. The proposed procedure, in addition to yield a gyrofluid model which automatically conserves the total energy, provides also, through the resulting Poisson bracket, a way to derive further conservation laws of the gyrofluid model, associated with the so called Casimir invariants. We show that a relation exists between Casimir invariants of the gyrofluid model and those of the gyrokinetic parent model. The application of such Hamiltonian derivation procedure to this two-moment gyrofluid model is a first step toward its application to more realistic, higher-order fluid or gyrofluid models for tokamaks. It also extends to the electromagnetic gyrokinetic case, recent applications of the same procedure to Vlasov and drift- kinetic systems

Evaluation of the National Research Council (2001) dairy model and derivation of new prediction equations. 1. Digestibility of fiber, fat, protein, and nonfiber carbohydrate.

Science.gov (United States)

White, R R; Roman-Garcia, Y; Firkins, J L; VandeHaar, M J; Armentano, L E; Weiss, W P; McGill, T; Garnett, R; Hanigan, M D

2017-05-01

Evaluation of ration balancing systems such as the National Research Council (NRC) Nutrient Requirements series is important for improving predictions of animal nutrient requirements and advancing feeding strategies. This work used a literature data set (n = 550) to evaluate predictions of total-tract digested neutral detergent fiber (NDF), fatty acid (FA), crude protein (CP), and nonfiber carbohydrate (NFC) estimated by the NRC (2001) dairy model. Mean biases suggested that the NRC (2001) lactating cow model overestimated true FA and CP digestibility by 26 and 7%, respectively, and under-predicted NDF digestibility by 16%. All NRC (2001) estimates had notable mean and slope biases and large root mean squared prediction error (RMSPE), and concordance (CCC) ranged from poor to good. Predicting NDF digestibility with independent equations for legumes, corn silage, other forages, and nonforage feeds improved CCC (0.85 vs. 0.76) compared with the re-derived NRC (2001) equation form (NRC equation with parameter estimates re-derived against this data set). Separate FA digestion coefficients were derived for different fat supplements (animal fats, oils, and other fat types) and for the basal diet. This equation returned improved (from 0.76 to 0.94) CCC compared with the re-derived NRC (2001) equation form. Unique CP digestibility equations were derived for forages, animal protein feeds, plant protein feeds, and other feeds, which improved CCC compared with the re-derived NRC (2001) equation form (0.74 to 0.85). New NFC digestibility coefficients were derived for grain-specific starch digestibilities, with residual organic matter assumed to be 98% digestible. A Monte Carlo cross-validation was performed to evaluate repeatability of model fit. In this procedure, data were randomly subsetted 500 times into derivation (60%) and evaluation (40%) data sets, and equations were derived using the derivation data and then evaluated against the independent evaluation data. Models

Local administration of platelet-derived growth factor B (PDGFB) improves follicular development and ovarian angiogenesis in a rat model of Polycystic Ovary Syndrome.

Science.gov (United States)

Di Pietro, Mariana; Scotti, Leopoldina; Irusta, Griselda; Tesone, Marta; Parborell, Fernanda; Abramovich, Dalhia

2016-09-15

Alterations in ovarian angiogenesis are common features in Polycystic Ovary Syndrome (PCOS) patients; the most studied of these alterations is the increase in vascular endothelial growth factor (VEGF) production by ovarian cells. Platelet-derived growth factor B (PDGFB) and D (PDGFD) are decreased in follicular fluid of PCOS patients and in the ovaries of a rat model of PCOS. In the present study, we aimed to analyze the effects of local administration of PDGFB on ovarian angiogenesis, follicular development and ovulation in a DHEA-induced PCOS rat model. Ovarian PDGFB administration to PCOS rats partially restored follicular development, decreased the percentage of cysts, increased the percentage of corpora lutea, and decreased the production of anti-Müllerian hormone. In addition, PDGFB administration improved ovarian angiogenesis by reversing the increase in periendothelial cell area and restoring VEGF levels. Our results shed light into the mechanisms that lead to altered ovarian function in PCOS and provide new data for potential therapeutic strategies. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Improved SAR Amplitude Image Offset Measurements for Deriving Three-Dimensional Coseismic Displacements

KAUST Repository

Wang, Teng; Jonsson, Sigurjon

2015-01-01

Offsets of synthetic aperture radar (SAR) images have played an important role in deriving complete three-dimensional (3-D) surface displacement fields in geoscientific applications. However, offset maps often suffer from multiple outliers and patch-like artifacts, because the standard offset-measurement method is a regular moving-window operation that does not consider the scattering characteristics of the ground. Here, we show that by focusing the offset measurements on predetected strong reflectors, the reliability and accuracy of SAR offsets can be significantly improved. Application to the 2011 Van (Turkey) earthquake reveals a clear deformation signal from an otherwise decorrelated interferogram, making derivation of the 3-D coseismic displacement field possible. Our proposed method can improve mapping of coseismic deformation and other ground displacements, such as glacier flow and landslide movement when strong reflectors exist.

Improved SAR Amplitude Image Offset Measurements for Deriving Three-Dimensional Coseismic Displacements

KAUST Repository

Wang, Teng

2015-02-03

Offsets of synthetic aperture radar (SAR) images have played an important role in deriving complete three-dimensional (3-D) surface displacement fields in geoscientific applications. However, offset maps often suffer from multiple outliers and patch-like artifacts, because the standard offset-measurement method is a regular moving-window operation that does not consider the scattering characteristics of the ground. Here, we show that by focusing the offset measurements on predetected strong reflectors, the reliability and accuracy of SAR offsets can be significantly improved. Application to the 2011 Van (Turkey) earthquake reveals a clear deformation signal from an otherwise decorrelated interferogram, making derivation of the 3-D coseismic displacement field possible. Our proposed method can improve mapping of coseismic deformation and other ground displacements, such as glacier flow and landslide movement when strong reflectors exist.

Island-Model Genomic Selection for Long-Term Genetic Improvement of Autogamous Crops.

Science.gov (United States)

Yabe, Shiori; Yamasaki, Masanori; Ebana, Kaworu; Hayashi, Takeshi; Iwata, Hiroyoshi

2016-01-01

Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS), which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an "island model" inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the potential of genomic

Island-Model Genomic Selection for Long-Term Genetic Improvement of Autogamous Crops.

Directory of Open Access Journals (Sweden)

Shiori Yabe

Full Text Available Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS, which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an "island model" inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the

PSA Model Improvement Using Maintenance Rule Function Mapping

Energy Technology Data Exchange (ETDEWEB)

Seo, Mi Ro [KHNP-CRI, Nuclear Safety Laboratory, Daejeon (Korea, Republic of)

2011-10-15

The Maintenance Rule (MR) program, in nature, is a performance-based program. Therefore, the risk information derived from the Probabilistic Safety Assessment model is introduced into the MR program during the Safety Significance determination and Performance Criteria selection processes. However, this process also facilitates the determination of the vulnerabilities in currently utilized PSA models and offers means of improving them. To find vulnerabilities in an existing PSA model, an initial review determines whether the safety-related MR functions are included in the PSA model. Because safety-related MR functions are related to accident prevention and mitigation, it is generally necessary for them to be included in the PSA model. In the process of determining the safety significance of each functions, quantitative risk importance levels are determined through a process known as PSA model basic event mapping to MR functions. During this process, it is common for some inadequate and overlooked models to be uncovered. In this paper, the PSA model and the MR program of Wolsong Unit 1 were used as references

Improved dust representation in the Community Atmosphere Model

Science.gov (United States)

Albani, S.; Mahowald, N. M.; Perry, A. T.; Scanza, R. A.; Zender, C. S.; Heavens, N. G.; Maggi, V.; Kok, J. F.; Otto-Bliesner, B. L.

2014-09-01

Aerosol-climate interactions constitute one of the major sources of uncertainty in assessing changes in aerosol forcing in the anthropocene as well as understanding glacial-interglacial cycles. Here we focus on improving the representation of mineral dust in the Community Atmosphere Model and assessing the impacts of the improvements in terms of direct effects on the radiative balance of the atmosphere. We simulated the dust cycle using different parameterization sets for dust emission, size distribution, and optical properties. Comparing the results of these simulations with observations of concentration, deposition, and aerosol optical depth allows us to refine the representation of the dust cycle and its climate impacts. We propose a tuning method for dust parameterizations to allow the dust module to work across the wide variety of parameter settings which can be used within the Community Atmosphere Model. Our results include a better representation of the dust cycle, most notably for the improved size distribution. The estimated net top of atmosphere direct dust radiative forcing is -0.23 ± 0.14 W/m2 for present day and -0.32 ± 0.20 W/m2 at the Last Glacial Maximum. From our study and sensitivity tests, we also derive some general relevant findings, supporting the concept that the magnitude of the modeled dust cycle is sensitive to the observational data sets and size distribution chosen to constrain the model as well as the meteorological forcing data, even within the same modeling framework, and that the direct radiative forcing of dust is strongly sensitive to the optical properties and size distribution used.

Vasodilative effects of prostaglandin E1 derivate on arteries of nerve roots in a canine model of a chronically compressed cauda equina

Directory of Open Access Journals (Sweden)

Konno Shin-ichi

2008-04-01

Full Text Available Abstract Background Reduction of blood flow is important in the induction of neurogenic intermittent claudication (NIC in lumbar spinal canal stenosis. PGE1 improves the mean walking distance in patients with NIC type cauda equina compression. PGE1 derivate might be effective in dilating blood vessels and improving blood flow in nerve roots with chronically compressed cauda equina. The aim of this study was to assess whether PGE1 derivate has vasodilatory effects on both arteries and veins in a canine model of chronic cauda equina compression. Methods Fourteen dogs were used in this study. A plastic balloon inflated to 10 mmHg was placed under the lamina of the 7th lumbar vertebra for 1 week. OP-1206-cyclodextrin clathrate (OP-1206-CD: prostaglandin E1 derivate was administered orally. The blood vessels of the second or third sacral nerve root were identified using a specially designed surgical microscope equipped with a video camera. The diameter of the blood vessels was measured on video-recordings every 15 minutes until 90 minutes after the administration of the PGE1 derivate. Results We observed seven arteries and seven veins. The diameter and blood flow of the arteries was significantly increased compared with the veins at both 60 and 75 minutes after administration of the PGE1 derivate (p Discussion The PGE1 derivate improved blood flow in the arteries but did not induce blood stasis in the veins. Our results suggest that the PGE1 derivate might be a potential therapeutic agent, as it improved blood flow in the nerve roots in a canine model of chronic cauda equina compression.

Fluorescently labeled chimeric anti-CEA antibody improves detection and resection of human colon cancer in a patient-derived orthotopic xenograft (PDOX) nude mouse model.

Science.gov (United States)

Metildi, Cristina A; Kaushal, Sharmeela; Luiken, George A; Talamini, Mark A; Hoffman, Robert M; Bouvet, Michael

2014-04-01

The aim of this study was to evaluate a new fluorescently labeled chimeric anti-CEA antibody for improved detection and resection of colon cancer. Frozen tumor and normal human tissue samples were stained with chimeric and mouse antibody-fluorophore conjugates for comparison. Mice with patient-derived orthotopic xenografts (PDOX) of colon cancer underwent fluorescence-guided surgery (FGS) or bright-light surgery (BLS) 24 hr after tail vein injection of fluorophore-conjugated chimeric anti-CEA antibody. Resection completeness was assessed using postoperative images. Mice were followed for 6 months for recurrence. The fluorophore conjugation efficiency (dye/mole ratio) improved from 3-4 to >5.5 with the chimeric CEA antibody compared to mouse anti-CEA antibody. CEA-expressing tumors labeled with chimeric CEA antibody provided a brighter fluorescence signal on frozen human tumor tissues (P = 0.046) and demonstrated consistently lower fluorescence signals in normal human tissues compared to mouse antibody. Chimeric CEA antibody accurately labeled PDOX colon cancer in nude mice, enabling improved detection of tumor margins for more effective FGS. The R0 resection rate increased from 86% to 96% with FGS compared to BLS. Improved conjugating efficiency and labeling with chimeric fluorophore-conjugated antibody resulted in better detection and resection of human colon cancer in an orthotopic mouse model. © 2013 Wiley Periodicals, Inc.

Nuclear-derived techniques improve cattle productivity and milk quality in Cameroon

International Nuclear Information System (INIS)

Dixit, Aabha

2016-01-01

Increasing agricultural production and improving the quality of milk and meat are key to combating poverty and increasing food security in Africa. Countries such as Cameroon are increasingly turning to innovative, nuclear and nuclear-derived techniques to control and prevent diseases among livestock, and boost cattle and milk production.

Improvement of distributed snowmelt energy balance modeling with MODIS-based NDSI-derived fractional snow-covered area data

Science.gov (United States)

Joel W. Homan; Charles H. Luce; James P. McNamara; Nancy F. Glenn

2011-01-01

Describing the spatial variability of heterogeneous snowpacks at a watershed or mountain-front scale is important for improvements in large-scale snowmelt modelling. Snowmelt depletion curves, which relate fractional decreases in snowcovered area (SCA) against normalized decreases in snow water equivalent (SWE), are a common approach to scale-up snowmelt models....

The Arbitrage Pricing Model: A Pedagogic Derivation and a Spreadsheet-Based Illustration

Directory of Open Access Journals (Sweden)

Clarence C. Y. Kwan

2016-05-01

Full Text Available This paper derives, from a pedagogic perspective, the Arbitrage Pricing Model, which is an important asset pricing model in modern finance. The derivation is based on the idea that, if a self-financed investment has no risk exposures, the payoff from the investment can only be zero. Microsoft Excel plays an important pedagogic role in this paper. The Excel illustration not only helps students recognize more fully the various nuances in the model derivation, but also serves as a good starting point for students to explore on their own the relevance of the noise issue in the model derivation.

Comparison of human adipose-derived stem cells and bone marrow-derived stem cells in a myocardial infarction model

DEFF Research Database (Denmark)

Rasmussen, Jeppe; Frøbert, Ole; Holst-Hansen, Claus

2014-01-01

Background: Treatment of myocardial infarction with bone marrow-derived mesenchymal stem cells and recently also adipose-derived stem cells has shown promising results. In contrast to clinical trials and their use of autologous bone marrow-derived cells from the ischemic patient, the animal...... myocardial infarction models are often using young donors and young, often immune-compromised, recipient animals. Our objective was to compare bone marrow-derived mesenchymal stem cells with adipose-derived stem cells from an elderly ischemic patient in the treatment of myocardial infarction, using a fully...... grown non-immunecompromised rat model. Methods: Mesenchymal stem cells were isolated from adipose tissue and bone marrow and compared with respect to surface markers and proliferative capability. To compare the regenerative potential of the two stem cell populations, male Sprague-Dawley rats were...

Derivation and analysis of cross relations of photosynthesis and respiration across at FLUXNET sites for model improvement

Science.gov (United States)

Lasslop, G.; Reichstein, M.; Papale, D.; Richardson, A. D.

2009-12-01

The FLUXNET database provides measurements of the net ecosystem exchange (NEE) of carbon across vegetation types and climate regions. To simplify the interpretation in terms of processes the net exchange is frequently split up into the two main components: gross primary production (GPP) and ecosystem respiration (Reco). A strong relation between these two fluxes related derived from eddy covariance data was found across temporal scales and is to be expected as variation in recent photosynthesis is known to be correlated with root respiration; plants use energy from photosynthesis to drive the metabolism. At long time scales, substrate availability (constrained by past productivity) limits the whole-ecosystem respiration. Previous studies exploring this relationship relied on GPP and Reco estimates derived from the same data, this may lead to spurious correlation that must not be interpreted ecologically. In this study we use two estimates derived from disjunct datasets, one based on daytime data, the other on nighttime data and explore the reliability and robustness of this relationship. We find distinct relationship between the two, varying between vegetation types but also across temporal and spatial scales. We also infer that spatial and temporal variability of net ecosystem exchange is driven by GPP in many cases. Exceptions to this rule include for example disturbed sites. We advocate that for model calibration and evaluation not only the fluxes itself but also robust patterns between fluxes that can be extracted from the database, for instance between the flux components, should be considered.

A fractal derivative constitutive model for three stages in granite creep

Directory of Open Access Journals (Sweden)

R. Wang

Full Text Available In this paper, by replacing the Newtonian dashpot with the fractal dashpot and considering damage effect, a new constitutive model is proposed in terms of time fractal derivative to describe the full creep regions of granite. The analytic solutions of the fractal derivative creep constitutive equation are derived via scaling transform. The conventional triaxial compression creep tests are performed on MTS 815 rock mechanics test system to verify the efficiency of the new model. The granite specimen is taken from Beishan site, the most potential area for the China’s high-level radioactive waste repository. It is shown that the proposed fractal model can characterize the creep behavior of granite especially in accelerating stage which the classical models cannot predict. The parametric sensitivity analysis is also conducted to investigate the effects of model parameters on the creep strain of granite. Keywords: Beishan granite, Fractal derivative, Damage evolution, Scaling transformation

The Fibrin-Derived Peptide Bβ15-42 (FX06) Ameliorates Vascular Leakage and Improves Survival and Neurocognitive Recovery: Implications From Two Animal Models of Cardiopulmonary Resuscitation.

Science.gov (United States)

Bergt, Stefan; Gruenewald, Matthias; Beltschany, Claudia; Grub, Andrea; Neumann, Tobias; Albrecht, Martin; Vollmar, Brigitte; Zacharowski, Kai; Roesner, Jan P; Meybohm, Patrick

2016-10-01

The fibrin-derived peptide Bβ15-42 (FX06) has been proven to attenuate ischemia/reperfusion injury. We tested the hypothesis that Bβ15-42 improves survival rate and neurocognitive recovery after cardiopulmonary resuscitation. Pig and mouse model of cardiopulmonary resuscitation. Two university hospitals. Pigs and mice. Pigs (n = 16) were subjected to 8-minute cardiac arrest. Successful resuscitated pigs (n = 12) were randomized either to 3 mg/kg Bβ15-42 followed by a continuous infusion of 1 mg/kg/hr for 5 hours (pFX06; n = 6) or the control group (pCONTROL; n = 6). Cardiac damage, function, and hemodynamics were recorded up to 8 hours. Mice (n = 52) were subjected to 4-minute cardiac arrest followed by cardiopulmonary resuscitation, and randomized either to two boli of 2.4 mg/kg Bβ15-42 (mFX06; n = 26) or the control group (mCONTROL; n = 26). Fourteen-day survival rate, neurocognitive function, and endothelial integrity (additional experiment with n = 26 mice) were evaluated. Bβ15-42 reduced cumulative fluid intake (3,500 [2,600-4,200] vs 6,800 [5,700-7,400] mL; p = 0.004) within 8 hours in pigs. In mice, Bβ15-42 improved 14-day survival rate (mFX06 vs mCONTROL; 11/26 vs 6/26; p Water-Maze test (15/26 vs 9/26 mice with competence to perform test; p < 0.05). Bβ15-42-treated mice showed a significant higher length of intact pulmonary endothelium and reduced pulmonary leukocyte infiltration. This study confirms the new concept of an important role of fibrin derivatives in global ischemia/reperfusion injury, which can be attenuated by the fibrin-derived peptide Bβ15-42.

Deterministically patterned biomimetic human iPSC-derived hepatic model via rapid 3D bioprinting.

Science.gov (United States)

Ma, Xuanyi; Qu, Xin; Zhu, Wei; Li, Yi-Shuan; Yuan, Suli; Zhang, Hong; Liu, Justin; Wang, Pengrui; Lai, Cheuk Sun Edwin; Zanella, Fabian; Feng, Gen-Sheng; Sheikh, Farah; Chien, Shu; Chen, Shaochen

2016-02-23

The functional maturation and preservation of hepatic cells derived from human induced pluripotent stem cells (hiPSCs) are essential to personalized in vitro drug screening and disease study. Major liver functions are tightly linked to the 3D assembly of hepatocytes, with the supporting cell types from both endodermal and mesodermal origins in a hexagonal lobule unit. Although there are many reports on functional 2D cell differentiation, few studies have demonstrated the in vitro maturation of hiPSC-derived hepatic progenitor cells (hiPSC-HPCs) in a 3D environment that depicts the physiologically relevant cell combination and microarchitecture. The application of rapid, digital 3D bioprinting to tissue engineering has allowed 3D patterning of multiple cell types in a predefined biomimetic manner. Here we present a 3D hydrogel-based triculture model that embeds hiPSC-HPCs with human umbilical vein endothelial cells and adipose-derived stem cells in a microscale hexagonal architecture. In comparison with 2D monolayer culture and a 3D HPC-only model, our 3D triculture model shows both phenotypic and functional enhancements in the hiPSC-HPCs over weeks of in vitro culture. Specifically, we find improved morphological organization, higher liver-specific gene expression levels, increased metabolic product secretion, and enhanced cytochrome P450 induction. The application of bioprinting technology in tissue engineering enables the development of a 3D biomimetic liver model that recapitulates the native liver module architecture and could be used for various applications such as early drug screening and disease modeling.

Mint3 in bone marrow-derived cells promotes lung metastasis in breast cancer model mice.

Science.gov (United States)

Hara, Toshiro; Murakami, Yoshinori; Seiki, Motoharu; Sakamoto, Takeharu

2017-08-26

Breast cancer is one of the most common cancers in women in the world. Although breast cancer is well treatable at the early stage, patients with distant metastases show a poor prognosis. Data from recent studies using transplantation models indicate that Mint3/APBA3 might promote breast cancer malignancy. However, whether Mint3 indeed contributes to tumor development, progression, or metastasis in vivo remains unclear. To address this, here we examined whether Mint3 depletion affects tumor malignancy in MMTV-PyMT breast cancer model mice. In MMTV-PyMT mice, Mint3 depletion did not affect tumor onset and tumor growth, but attenuated lung metastases. Experimental lung metastasis of breast cancer Met-1 cells derived from MMTV-PyMT mice also decreased in Mint3-depleted mice, indicating that host Mint3 expression affected lung metastasis of MMTV-PyMT-derived breast cancer cells. Further bone marrow transplant experiments revealed that Mint3 in bone marrow-derived cells promoted lung metastasis in MMTV-PyMT mice. Thus, targeting Mint3 in bone marrow-derived cells might be a good strategy for preventing metastasis and improving the prognosis of breast cancer patients. Copyright © 2017 Elsevier Inc. All rights reserved.

Modeling and Forecasting Average Temperature for Weather Derivative Pricing

Directory of Open Access Journals (Sweden)

Zhiliang Wang

2015-01-01

Full Text Available The main purpose of this paper is to present a feasible model for the daily average temperature on the area of Zhengzhou and apply it to weather derivatives pricing. We start by exploring the background of weather derivatives market and then use the 62 years of daily historical data to apply the mean-reverting Ornstein-Uhlenbeck process to describe the evolution of the temperature. Finally, Monte Carlo simulations are used to price heating degree day (HDD call option for this city, and the slow convergence of the price of the HDD call can be found through taking 100,000 simulations. The methods of the research will provide a frame work for modeling temperature and pricing weather derivatives in other similar places in China.

Delivery of Bone Marrow-Derived Mesenchymal Stem Cells Improves Tear Production in a Mouse Model of Sjögren’s Syndrome

Directory of Open Access Journals (Sweden)

Hema S. Aluri

2017-01-01

Full Text Available The purpose of the present study was to test the potential of mouse bone marrow-derived mesenchymal stem cells (BD-MSCs in improving tear production in a mouse model of Sjögren’s syndrome dry eye and to investigate the underlying mechanisms involved. NOD mice (n=20 were randomized to receive i.p. injection of sterile phosphate buffered saline (PBS, control or murine BD-MSCs (1 × 106 cells. Tears production was measured at baseline and once a week after treatment using phenol red impregnated threads. Cathepsin S activity in the tears was measured at the end of treatment. After 4 weeks, animals were sacrificed and the lacrimal glands were excised and processed for histopathology, immunohistochemistry, and RNA analysis. Following BD-MSC injection, tears production increased over time when compared to both baseline and PBS injected mice. Although the number of lymphocytic foci in the lacrimal glands of treated animals did not change, the size of the foci decreased by 40.5% when compared to control animals. The mRNA level of the water channel aquaporin 5 was significantly increased following delivery of BD-MSCs. We conclude that treatment with BD-MSCs increases tear production in the NOD mouse model of Sjögren’s syndrome. This is likely due to decreased inflammation and increased expression of aquaporin 5.

Some remarks on the small-distance derivative model

International Nuclear Information System (INIS)

Jannussis, A.

1985-01-01

In the present work the new expressions of the derivatives for small distance are investigated according to Gonzales-Diaz model. This model is noncanonical, is a particular case of the Lie-admissible formulation and has applications for distance and time scales comparable with the Planck dimensions

On the equivalence between the thirring model and a derivative coupling model

International Nuclear Information System (INIS)

Gomes, M.; Silva, A.J. da.

1986-07-01

The equivalence between the Thirring model and the fermionic sector of the theory of a Dirac field interacting via derivate coupling with two boson fields is analysed. For a certain choice of the parameters the two models have the same fermionic Green functions. (Author) [pt

Derivative interactions and perturbative UV contributions in N Higgs doublet models

Energy Technology Data Exchange (ETDEWEB)

Kikuta, Yohei [KEK Theory Center, KEK, Tsukuba (Japan); The Graduate University for Advanced Studies, Department of Particle and Nuclear Physics, Tsukuba (Japan); Yamamoto, Yasuhiro [Universidad de Granada, Deportamento de Fisica Teorica y del Cosmos, Facultad de Ciencias and CAFPE, Granada (Spain)

2016-05-15

We study the Higgs derivative interactions on models including arbitrary number of the Higgs doublets. These interactions are generated by two ways. One is higher order corrections of composite Higgs models, and the other is integration of heavy scalars and vectors. In the latter case, three point couplings between the Higgs doublets and these heavy states are the sources of the derivative interactions. Their representations are constrained to couple with the doublets. We explicitly calculate all derivative interactions generated by integrating out. Their degrees of freedom and conditions to impose the custodial symmetry are discussed. We also study the vector boson scattering processes with a couple of two Higgs doublet models to see experimental signals of the derivative interactions. They are differently affected by each heavy field. (orig.)

Synergizing two NWP models to improve hub-height wind speed forecasts

Energy Technology Data Exchange (ETDEWEB)

Liu, H. [Ortech International, Mississauga, ON (Canada); Taylor, P. [York Univ., Toronto, ON (Canada)

2010-07-01

This PowerPoint presentation discussed some of the methods used to optimize hub-height wind speed forecasts. Statistical and physical forecast paradigms were considered. Forecast errors are often dictated by phase error, while refined NWP modelling is limited by data availability. A nested meso-scale NWP model was combined with a physical model to predict wind and power forecasts. Maps of data sources were included as well as equations used to derive predictions. Data from meteorological masts located near the Great Lakes were used to demonstrate the model. The results were compared with other modelling prediction methods. Forecasts obtained using the modelling approach can help operators in scheduling and trading procedures. Further research is being conducted to determine if the model can be used to improve ramp forecasts. tabs., figs.

Currents, HF Radio-derived, Monterey Bay, Normal Model, Zonal, EXPERIMENTAL

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The data is the zonal component of ocean surface currents derived from High Frequency Radio-derived measurements, with missing values filled in by a normal model....

Antidepressant Effects of Pharmacopuncture on Behavior and Brain-Derived Neurotrophic Factor (BDNF Expression in Chronic Stress Model of Mice

Directory of Open Access Journals (Sweden)

Yunna Kim

2017-12-01

Conclusion: HJ11 improves depressive-like behaviors in the stress-induced mouse model of depression, and the results indicate that the neuroprotective effect of HJ11, identified by brain-derived neurotrophic factor expression, may play a critical role in its antidepressant effect.

Managing health care decisions and improvement through simulation modeling.

Science.gov (United States)

Forsberg, Helena Hvitfeldt; Aronsson, Håkan; Keller, Christina; Lindblad, Staffan

2011-01-01

Simulation modeling is a way to test changes in a computerized environment to give ideas for improvements before implementation. This article reviews research literature on simulation modeling as support for health care decision making. The aim is to investigate the experience and potential value of such decision support and quality of articles retrieved. A literature search was conducted, and the selection criteria yielded 59 articles derived from diverse applications and methods. Most met the stated research-quality criteria. This review identified how simulation can facilitate decision making and that it may induce learning. Furthermore, simulation offers immediate feedback about proposed changes, allows analysis of scenarios, and promotes communication on building a shared system view and understanding of how a complex system works. However, only 14 of the 59 articles reported on implementation experiences, including how decision making was supported. On the basis of these articles, we proposed steps essential for the success of simulation projects, not just in the computer, but also in clinical reality. We also presented a novel concept combining simulation modeling with the established plan-do-study-act cycle for improvement. Future scientific inquiries concerning implementation, impact, and the value for health care management are needed to realize the full potential of simulation modeling.

Microscopic Derivation of the Ginzburg-Landau Model

DEFF Research Database (Denmark)

Frank, Rupert; Hainzl, Christian; Seiringer, Robert

2014-01-01

We present a summary of our recent rigorous derivation of the celebrated Ginzburg-Landau (GL) theory, starting from the microscopic Bardeen-Cooper-Schrieffer (BCS) model. Close to the critical temperature, GL arises as an effective theory on the macroscopic scale. The relevant scaling limit...

In vitro generation of three-dimensional substrate-adherent embryonic stem cell-derived neural aggregates for application in animal models of neurological disorders.

Science.gov (United States)

Hargus, Gunnar; Cui, Yi-Fang; Dihné, Marcel; Bernreuther, Christian; Schachner, Melitta

2012-05-01

In vitro-differentiated embryonic stem (ES) cells comprise a useful source for cell replacement therapy, but the efficiency and safety of a translational approach are highly dependent on optimized protocols for directed differentiation of ES cells into the desired cell types in vitro. Furthermore, the transplantation of three-dimensional ES cell-derived structures instead of a single-cell suspension may improve graft survival and function by providing a beneficial microenvironment for implanted cells. To this end, we have developed a new method to efficiently differentiate mouse ES cells into neural aggregates that consist predominantly (>90%) of postmitotic neurons, neural progenitor cells, and radial glia-like cells. When transplanted into the excitotoxically lesioned striatum of adult mice, these substrate-adherent embryonic stem cell-derived neural aggregates (SENAs) showed significant advantages over transplanted single-cell suspensions of ES cell-derived neural cells, including improved survival of GABAergic neurons, increased cell migration, and significantly decreased risk of teratoma formation. Furthermore, SENAs mediated functional improvement after transplantation into animal models of Parkinson's disease and spinal cord injury. This unit describes in detail how SENAs are efficiently derived from mouse ES cells in vitro and how SENAs are isolated for transplantation. Furthermore, methods are presented for successful implantation of SENAs into animal models of Huntington's disease, Parkinson's disease, and spinal cord injury to study the effects of stem cell-derived neural aggregates in a disease context in vivo.

Unsteady Vibration Aerodynamic Modeling and Evaluation of Dynamic Derivatives Using Computational Fluid Dynamics

Directory of Open Access Journals (Sweden)

Xu Liu

2015-01-01

Full Text Available Unsteady aerodynamic system modeling is widely used to solve the dynamic stability problems encountering aircraft design. In this paper, single degree-of-freedom (SDF vibration model and forced simple harmonic motion (SHM model for dynamic derivative prediction are developed on the basis of modified Etkin model. In the light of the characteristics of SDF time domain solution, the free vibration identification methods for dynamic stability parameters are extended and applied to the time domain numerical simulation of blunted cone calibration model examples. The dynamic stability parameters by numerical identification are no more than 0.15% deviated from those by experimental simulation, confirming the correctness of SDF vibration model. The acceleration derivatives, rotary derivatives, and combination derivatives of Army-Navy Spinner Rocket are numerically identified by using unsteady N-S equation and solving different SHV patterns. Comparison with the experimental result of Army Ballistic Research Laboratories confirmed the correctness of the SHV model and dynamic derivative identification. The calculation result of forced SHM is better than that by the slender body theory of engineering approximation. SDF vibration model and SHM model for dynamic stability parameters provide a solution to the dynamic stability problem encountering aircraft design.

Comparison of Ocean Dynamics with a Regional Circulation Model and Improved Altimetry in the North-Western Mediterranean

Directory of Open Access Journals (Sweden)

Jérôme Bouffard

2008-01-01

Full Text Available The spatial and temporal resolution of satellite altimetry is usually sufficient for monitoring the changes of sea surface topography in the open ocean. However, coastal ocean dynamics are much more complex, being characterized by smaller spatial and temporal scales of variability. The quality and availability of satellite-derived products along the coasts have to be improved, with a strategy optimized for coastal targets. Therefore a coastal multi-satellite altimetry dataset (TOPEX/Poseidon, Jason-1; Envisat; GFO at a 10 - 20 Hz sampling rate has been derived from routine geophysical data products using a new processing software dedicated to coastal zone applications. Improved along-track sea level variations with fine space scales are available in the North-western Mediterranean Sea from 2001 to 2003, and are compared with high-resolution numerical model elevations from the eddy-resolving model SYMPHONIE. This preparatory work emphasizes the potential of improved multi-satellite altimetry for validating coastal hydro-dynamical models and could contribute in the future to a better tuning of the boundary conditions of the simulations.

Adipose derived stromal vascular fraction improves early tendon healing: an experimental study in rabbits

Directory of Open Access Journals (Sweden)

Mehdi Behfar

2011-11-01

Full Text Available Tendon never restores the complete biological and mechanical properties after healing. Bone marrow and recently adipose tissue have been used as the sources of mesenchymal stem cells, which have been proven to enhance tendon healing. Stromal vascular fraction (SVF, derived from adipose tissue by an enzymatic digestion, represents an alternative source of multipotent cells, which undergo differentiation into multiple lineages to be used in regenerative medicine. In the present study, we investigated potentials of this source on tendon healing. Twenty rabbits were divided into control and treatment groups. Five rabbits were used as donors of adipose tissue. The injury model was unilateral complete transection through the middle one third of deep digital flexor tendon. Immediately after suture repair, either fresh stromal vascular fraction from enzymatic digestion of adipose tissue or placebo was intratendinously injected into the suture site in treatments and controls, respectively. Cast immobilization was continued for two weeks after surgery. Animals were sacrificed at the third week and tendons underwent histological, immunohistochemical, and mechanical evaluations. By histology, improved fibrillar organization and remodeling of neotendon were observed in treatment group. Immunohistochemistry revealed an insignificant increase in collagen type III and I expression in treatments over controls. Mechanical testing showed significant increase in maximum load and energy absorption in SVF treated tendons. The present study showed that intratendinous injection of uncultured adipose derived stromal vascular fraction improved structural and mechanical properties of repaired tendon and it could be an effective modality for treating tendon laceration.

On a derivation of the Salam-Weinberg model

International Nuclear Information System (INIS)

Squires, E.J.

1979-01-01

It is shown how the graded Lie-algebra structure of a recent derivation of the Salam-Weinberg model might arise from the form of allowed transformations on the lepton lagrangian in a 6-dimensional space. The possibility that the model might allow two identically coupled leptonic sectors, and others in which the chiralites are reversed, are discussed. (Auth.)

One loop beta functions and fixed points in higher derivative sigma models

International Nuclear Information System (INIS)

Percacci, Roberto; Zanusso, Omar

2010-01-01

We calculate the one loop beta functions of nonlinear sigma models in four dimensions containing general two- and four-derivative terms. In the O(N) model there are four such terms and nontrivial fixed points exist for all N≥4. In the chiral SU(N) models there are in general six couplings, but only five for N=3 and four for N=2; we find fixed points only for N=2, 3. In the approximation considered, the four-derivative couplings are asymptotically free but the coupling in the two-derivative term has a nonzero limit. These results support the hypothesis that certain sigma models may be asymptotically safe.

Evaluation of bias associated with capture maps derived from nonlinear groundwater flow models

Science.gov (United States)

Nadler, Cara; Allander, Kip K.; Pohll, Greg; Morway, Eric D.; Naranjo, Ramon C.; Huntington, Justin

2018-01-01

The impact of groundwater withdrawal on surface water is a concern of water users and water managers, particularly in the arid western United States. Capture maps are useful tools to spatially assess the impact of groundwater pumping on water sources (e.g., streamflow depletion) and are being used more frequently for conjunctive management of surface water and groundwater. Capture maps have been derived using linear groundwater flow models and rely on the principle of superposition to demonstrate the effects of pumping in various locations on resources of interest. However, nonlinear models are often necessary to simulate head-dependent boundary conditions and unconfined aquifers. Capture maps developed using nonlinear models with the principle of superposition may over- or underestimate capture magnitude and spatial extent. This paper presents new methods for generating capture difference maps, which assess spatial effects of model nonlinearity on capture fraction sensitivity to pumping rate, and for calculating the bias associated with capture maps. The sensitivity of capture map bias to selected parameters related to model design and conceptualization for the arid western United States is explored. This study finds that the simulation of stream continuity, pumping rates, stream incision, well proximity to capture sources, aquifer hydraulic conductivity, and groundwater evapotranspiration extinction depth substantially affect capture map bias. Capture difference maps demonstrate that regions with large capture fraction differences are indicative of greater potential capture map bias. Understanding both spatial and temporal bias in capture maps derived from nonlinear groundwater flow models improves their utility and defensibility as conjunctive-use management tools.

Precision Orbit Derived Atmospheric Density: Development and Performance

Science.gov (United States)

McLaughlin, C.; Hiatt, A.; Lechtenberg, T.; Fattig, E.; Mehta, P.

2012-09-01

Precision orbit ephemerides (POE) are used to estimate atmospheric density along the orbits of CHAMP (Challenging Minisatellite Payload) and GRACE (Gravity Recovery and Climate Experiment). The densities are calibrated against accelerometer derived densities and considering ballistic coefficient estimation results. The 14-hour density solutions are stitched together using a linear weighted blending technique to obtain continuous solutions over the entire mission life of CHAMP and through 2011 for GRACE. POE derived densities outperform the High Accuracy Satellite Drag Model (HASDM), Jacchia 71 model, and NRLMSISE-2000 model densities when comparing cross correlation and RMS with accelerometer derived densities. Drag is the largest error source for estimating and predicting orbits for low Earth orbit satellites. This is one of the major areas that should be addressed to improve overall space surveillance capabilities; in particular, catalog maintenance. Generally, density is the largest error source in satellite drag calculations and current empirical density models such as Jacchia 71 and NRLMSISE-2000 have significant errors. Dynamic calibration of the atmosphere (DCA) has provided measurable improvements to the empirical density models and accelerometer derived densities of extremely high precision are available for a few satellites. However, DCA generally relies on observations of limited accuracy and accelerometer derived densities are extremely limited in terms of measurement coverage at any given time. The goal of this research is to provide an additional data source using satellites that have precision orbits available using Global Positioning System measurements and/or satellite laser ranging. These measurements strike a balance between the global coverage provided by DCA and the precise measurements of accelerometers. The temporal resolution of the POE derived density estimates is around 20-30 minutes, which is significantly worse than that of accelerometer

Automated Student Model Improvement

Science.gov (United States)

Koedinger, Kenneth R.; McLaughlin, Elizabeth A.; Stamper, John C.

2012-01-01

Student modeling plays a critical role in developing and improving instruction and instructional technologies. We present a technique for automated improvement of student models that leverages the DataShop repository, crowd sourcing, and a version of the Learning Factors Analysis algorithm. We demonstrate this method on eleven educational…

Successful function of autologous iPSC-derived dopamine neurons following transplantation in a non-human primate model of Parkinson's disease

DEFF Research Database (Denmark)

Hallett, Penelope J; Deleidi, Michela; Astradsson, Arnar

2015-01-01

that unilateral engraftment of CM-iPSCs could provide a gradual onset of functional motor improvement contralateral to the side of dopamine neuron transplantation, and increased motor activity, without a need for immunosuppression. Postmortem analyses demonstrated robust survival of midbrain-like dopaminergic......Autologous transplantation of patient-specific induced pluripotent stem cell (iPSC)-derived neurons is a potential clinical approach for treatment of neurological disease. Preclinical demonstration of long-term efficacy, feasibility, and safety of iPSC-derived dopamine neurons in non-human primate...... models will be an important step in clinical development of cell therapy. Here, we analyzed cynomolgus monkey (CM) iPSC-derived midbrain dopamine neurons for up to 2 years following autologous transplantation in a Parkinson's disease (PD) model. In one animal, with the most successful protocol, we found...

An equilibrium pricing model for weather derivatives in a multi-commodity setting

International Nuclear Information System (INIS)

Lee, Yongheon; Oren, Shmuel S.

2009-01-01

Many industries are exposed to weather risk. Weather derivatives can play a key role in hedging and diversifying such risk because the uncertainty in a company's profit function can be correlated to weather condition which affects diverse industry sectors differently. Unfortunately the weather derivatives market is a classical example of an incomplete market that is not amenable to standard methodologies used for derivative pricing in complete markets. In this paper, we develop an equilibrium pricing model for weather derivatives in a multi-commodity setting. The model is constructed in the context of a stylized economy where agents optimize their hedging portfolios which include weather derivatives that are issued in a fixed quantity by a financial underwriter. The supply and demand resulting from hedging activities and the supply by the underwriter are combined in an equilibrium pricing model under the assumption that all agents maximize some risk averse utility function. We analyze the gains due to the inclusion of weather derivatives in hedging portfolios and examine the components of that gain attributable to hedging and to risk sharing. (author)

Improved modeling techniques for turbomachinery flow fields

Energy Technology Data Exchange (ETDEWEB)

Lakshminarayana, B. [Pennsylvania State Univ., University Park, PA (United States); Fagan, J.R. Jr. [Allison Engine Company, Indianapolis, IN (United States)

1995-10-01

This program has the objective of developing an improved methodology for modeling turbomachinery flow fields, including the prediction of losses and efficiency. Specifically, the program addresses the treatment of the mixing stress tensor terms attributed to deterministic flow field mechanisms required in steady-state Computational Fluid Dynamic (CFD) models for turbo-machinery flow fields. These mixing stress tensors arise due to spatial and temporal fluctuations (in an absolute frame of reference) caused by rotor-stator interaction due to various blade rows and by blade-to-blade variation of flow properties. These tasks include the acquisition of previously unavailable experimental data in a high-speed turbomachinery environment, the use of advanced techniques to analyze the data, and the development of a methodology to treat the deterministic component of the mixing stress tensor. Penn State will lead the effort to make direct measurements of the momentum and thermal mixing stress tensors in high-speed multistage compressor flow field in the turbomachinery laboratory at Penn State. They will also process the data by both conventional and conditional spectrum analysis to derive momentum and thermal mixing stress tensors due to blade-to-blade periodic and aperiodic components, revolution periodic and aperiodic components arising from various blade rows and non-deterministic (which includes random components) correlations. The modeling results from this program will be publicly available and generally applicable to steady-state Navier-Stokes solvers used for turbomachinery component (compressor or turbine) flow field predictions. These models will lead to improved methodology, including loss and efficiency prediction, for the design of high-efficiency turbomachinery and drastically reduce the time required for the design and development cycle of turbomachinery.

Derivative Geometric Modeling of Basic Rotational Solids on CATIA

Institute of Scientific and Technical Information of China (English)

MENG Xiang-bao; PAN Zi-jian; ZHU Yu-xiang; LI Jun

2011-01-01

Hybrid models derived from rotational solids like cylinders, cones and spheres were implemented on CATIA software. Firstly, make the isosceles triangular prism, cuboid, cylinder, cone, sphere, and the prism with tangent conic and curved triangle ends, the cuboid with tangent cylindrical and curved rectangle ends, the cylinder with tangent spherical and curved circular ends as the basic Boolean deference units to the primary cylinders, cones and spheres on symmetrical and some critical geometric conditions, forming a series of variant solid models. Secondly, make the deference units above as the basic union units to the main cylinders, cones, and spheres accordingly, forming another set of solid models. Thirdly, make the tangent ends of union units into oblique conic, cylindrical, or with revolved triangular pyramid, quarterly cylinder and annulus ends on sketch based features to the main cylinders, cones, and spheres repeatedly, thus forming still another set of solid models. It is expected that these derivative models be beneficial both in the structure design, hybrid modeling, and finite element analysis of engineering components and in comprehensive training of spatial configuration of engineering graphics.

Comparing multiple model-derived aerosol optical properties to spatially collocated ground-based and satellite measurements

Science.gov (United States)

Ocko, Ilissa B.; Ginoux, Paul A.

2017-04-01

Anthropogenic aerosols are a key factor governing Earth's climate and play a central role in human-caused climate change. However, because of aerosols' complex physical, optical, and dynamical properties, aerosols are one of the most uncertain aspects of climate modeling. Fortunately, aerosol measurement networks over the past few decades have led to the establishment of long-term observations for numerous locations worldwide. Further, the availability of datasets from several different measurement techniques (such as ground-based and satellite instruments) can help scientists increasingly improve modeling efforts. This study explores the value of evaluating several model-simulated aerosol properties with data from spatially collocated instruments. We compare aerosol optical depth (AOD; total, scattering, and absorption), single-scattering albedo (SSA), Ångström exponent (α), and extinction vertical profiles in two prominent global climate models (Geophysical Fluid Dynamics Laboratory, GFDL, CM2.1 and CM3) to seasonal observations from collocated instruments (AErosol RObotic NETwork, AERONET, and Cloud-Aerosol Lidar with Orthogonal Polarization, CALIOP) at seven polluted and biomass burning regions worldwide. We find that a multi-parameter evaluation provides key insights on model biases, data from collocated instruments can reveal underlying aerosol-governing physics, column properties wash out important vertical distinctions, and improved models does not mean all aspects are improved. We conclude that it is important to make use of all available data (parameters and instruments) when evaluating aerosol properties derived by models.

Energetic and exergetic efficiency modeling of a cargo aircraft by a topology improving neuro-evolution algorithm

International Nuclear Information System (INIS)

Baklacioglu, Tolga; Aydin, Hakan; Turan, Onder

2016-01-01

An aircraft is a complex system that requires methodologies for an efficient thermodynamic design process. So, it is important to gain a deeper understanding of energy and exergy use throughout an aircraft. The aim of this study is to propose a topology improving NE (neuro-evolution) algorithm modeling for assessing energy and exergy efficiency of a cargo aircraft for the phases of a flight. In this regard, energy and exergy data of the aircraft achieved from several engine runs at different power settings have been utilized to derive the ANN (artificial neural network) models optimized by a GA (genetic algorithm). NE of feed-forward networks trained by a BP (backpropagation) algorithm with momentum has assured the accomplishment of optimum initial network weights as well as the improvement of the network topology. The linear correlation coefficients very close to unity obtained for the derived ANN models have proved the tight fitting of the real data and the estimated values of the efficiencies provided by the models. Finally, compared to the trial-and-error case, evolving the networks by GAs has enhanced the accuracy of the modeling simply further as the reduction in the MSE (mean squared errors) for the energy and exergy efficiencies indicates. - Highlights: • Optimization using neuro-evolution algorithm. • Improved backpropagation algorithm using momentum factor. • Turboprop parameters as independent variables. • Energy and exergy efficiency modeling of a cargo aircraft.

Human adipose stem cell and ASC-derived cardiac progenitor cellular therapy improves outcomes in a murine model of myocardial infarction

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Davy PMC

2015-10-01

Full Text Available Philip MC Davy,1 Kevin D Lye,2,3 Juanita Mathews,1 Jesse B Owens,1 Alice Y Chow,1 Livingston Wong,2 Stefan Moisyadi,1 Richard C Allsopp1 1Institute for Biogenesis Research, 2John A. Burns School of Medicine, University of Hawaii at Mānoa, 3Tissue Genesis, Inc., Honolulu, HI, USA Background: Adipose tissue is an abundant and potent source of adult stem cells for transplant therapy. In this study, we present our findings on the potential application of adipose-derived stem cells (ASCs as well as induced cardiac-like progenitors (iCPs derived from ASCs for the treatment of myocardial infarction. Methods and results: Human bone marrow (BM-derived stem cells, ASCs, and iCPs generated from ASCs using three defined cardiac lineage transcription factors were assessed in an immune-compromised mouse myocardial infarction model. Analysis of iCP prior to transplant confirmed changes in gene and protein expression consistent with a cardiac phenotype. Endpoint analysis was performed 1 month posttransplant. Significantly increased endpoint fractional shortening, as well as reduction in the infarct area at risk, was observed in recipients of iCPs as compared to the other recipient cohorts. Both recipients of iCPs and ASCs presented higher myocardial capillary densities than either recipients of BM-derived stem cells or the control cohort. Furthermore, mice receiving iCPs had a significantly higher cardiac retention of transplanted cells than all other groups. Conclusion: Overall, iCPs generated from ASCs outperform BM-derived stem cells and ASCs in facilitating recovery from induced myocardial infarction in mice. Keywords: adipose stem cells, myocardial infarction, cellular reprogramming, cellular therapy, piggyBac, induced cardiac-like progenitors

Two-Dimensional Magnetotelluric Modelling of Ore Deposits: Improvements in Model Constraints by Inclusion of Borehole Measurements

Science.gov (United States)

Kalscheuer, Thomas; Juhojuntti, Niklas; Vaittinen, Katri

2017-12-01

A combination of magnetotelluric (MT) measurements on the surface and in boreholes (without metal casing) can be expected to enhance resolution and reduce the ambiguity in models of electrical resistivity derived from MT surface measurements alone. In order to quantify potential improvement in inversion models and to aid design of electromagnetic (EM) borehole sensors, we considered two synthetic 2D models containing ore bodies down to 3000 m depth (the first with two dipping conductors in resistive crystalline host rock and the second with three mineralisation zones in a sedimentary succession exhibiting only moderate resistivity contrasts). We computed 2D inversion models from the forward responses based on combinations of surface impedance measurements and borehole measurements such as (1) skin-effect transfer functions relating horizontal magnetic fields at depth to those on the surface, (2) vertical magnetic transfer functions relating vertical magnetic fields at depth to horizontal magnetic fields on the surface and (3) vertical electric transfer functions relating vertical electric fields at depth to horizontal magnetic fields on the surface. Whereas skin-effect transfer functions are sensitive to the resistivity of the background medium and 2D anomalies, the vertical magnetic and electric field transfer functions have the disadvantage that they are comparatively insensitive to the resistivity of the layered background medium. This insensitivity introduces convergence problems in the inversion of data from structures with strong 2D resistivity contrasts. Hence, we adjusted the inversion approach to a three-step procedure, where (1) an initial inversion model is computed from surface impedance measurements, (2) this inversion model from surface impedances is used as the initial model for a joint inversion of surface impedances and skin-effect transfer functions and (3) the joint inversion model derived from the surface impedances and skin-effect transfer

Model-based software process improvement

Science.gov (United States)

Zettervall, Brenda T.

1994-01-01

The activities of a field test site for the Software Engineering Institute's software process definition project are discussed. Products tested included the improvement model itself, descriptive modeling techniques, the CMM level 2 framework document, and the use of process definition guidelines and templates. The software process improvement model represents a five stage cyclic approach for organizational process improvement. The cycles consist of the initiating, diagnosing, establishing, acting, and leveraging phases.

ESC-Derived Basal Forebrain Cholinergic Neurons Ameliorate the Cognitive Symptoms Associated with Alzheimer’s Disease in Mouse Models

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Wei Yue

2015-11-01

Full Text Available Degeneration of basal forebrain cholinergic neurons (BFCNs is associated with cognitive impairments of Alzheimer’s disease (AD, implying that BFCNs hold potentials in exploring stem cell-based replacement therapy for AD. However, studies on derivation of BFCNs from embryonic stem cells (ESCs are limited, and the application of ESC-derived BFCNs remains to be determined. Here, we report on differentiation approaches for directing both mouse and human ESCs into mature BFCNs. These ESC-derived BFCNs exhibit features similar to those of their in vivo counterparts and acquire appropriate functional properties. After transplantation into the basal forebrain of AD model mice, ESC-derived BFCN progenitors predominantly differentiate into mature cholinergic neurons that functionally integrate into the endogenous basal forebrain cholinergic projection system. The AD mice grafted with mouse or human BFCNs exhibit improvements in learning and memory performances. Our findings suggest a promising perspective of ESC-derived BFCNs in the development of stem cell-based therapies for treatment of AD.

IMPROVED TOPOGRAPHIC MODELS VIA CONCURRENT AIRBORNE LIDAR AND DENSE IMAGE MATCHING

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G. Mandlburger

2017-09-01

Full Text Available Modern airborne sensors integrate laser scanners and digital cameras for capturing topographic data at high spatial resolution. The capability of penetrating vegetation through small openings in the foliage and the high ranging precision in the cm range have made airborne LiDAR the prime terrain acquisition technique. In the recent years dense image matching evolved rapidly and outperforms laser scanning meanwhile in terms of the achievable spatial resolution of the derived surface models. In our contribution we analyze the inherent properties and review the typical processing chains of both acquisition techniques. In addition, we present potential synergies of jointly processing image and laser data with emphasis on sensor orientation and point cloud fusion for digital surface model derivation. Test data were concurrently acquired with the RIEGL LMS-Q1560 sensor over the city of Melk, Austria, in January 2016 and served as basis for testing innovative processing strategies. We demonstrate that (i systematic effects in the resulting scanned and matched 3D point clouds can be minimized based on a hybrid orientation procedure, (ii systematic differences of the individual point clouds are observable at penetrable, vegetated surfaces due to the different measurement principles, and (iii improved digital surface models can be derived combining the higher density of the matching point cloud and the higher reliability of LiDAR point clouds, especially in the narrow alleys and courtyards of the study site, a medieval city.

DFT application for chlorin derivatives photosensitizer drugs modeling

Science.gov (United States)

Machado, Neila; Carvalho, B. G.; Téllez Soto, C. A.; Martin, A. A.; Favero, P. P.

2018-04-01

Photodynamic therapy is an alternative form of cancer treatment that meets the desire for a less aggressive approach to the body. It is based on the interaction between a photosensitizer, activating light, and molecular oxygen. This interaction results in a cascade of reactions that leads to localized cell death. Many studies have been conducted to discover an ideal photosensitizer, which aggregates all the desirable characteristics of a potent cell killer and generates minimal side effects. Using Density Functional Theory (DFT) implemented in the program Vienna Ab-initio Simulation Package, new chlorin derivatives with different functional groups were simulated to evaluate the different absorption wavelengths to permit resonant absorption with the incident laser. Gaussian 09 program was used to determine vibrational wave numbers and Natural Bond Orbitals. The chosen drug with the best characteristics for the photosensitizer was a modified model of the original chlorin, which was called as Thiol chlorin. According to our calculations it is stable and is 19.6% more efficient at optical absorption in 708 nm in comparison to the conventional chlorin e6. Vibrational modes, optical and electronic properties were predicted. In conclusion, this study is an attempt to improve the development of new photosensitizer drugs through computational methods that save time and contribute to decrease the numbers of animals for model application.

CT-derived Biomechanical Metrics Improve Agreement Between Spirometry and Emphysema.

Science.gov (United States)

Bhatt, Surya P; Bodduluri, Sandeep; Newell, John D; Hoffman, Eric A; Sieren, Jessica C; Han, Meilan K; Dransfield, Mark T; Reinhardt, Joseph M

2016-10-01

Many patients with chronic obstructive pulmonary disease (COPD) have marked discordance between forced expiratory volume in 1 second (FEV1) and degree of emphysema on computed tomography (CT). Biomechanical differences between these patients have not been studied. We aimed to identify reasons for the discordance between CT and spirometry in some patients with COPD. Subjects with Global initiative for chronic Obstructive Lung Disease stages I-IV from a large multicenter study (The Genetic Epidemiology of COPD) were arranged by percentiles of %predicted FEV1 and emphysema on CT. Three categories were created using differences in percentiles: Catspir with predominant airflow obstruction/minimal emphysema, CatCT with predominant emphysema/minimal airflow obstruction, and Catmatched with matched FEV1 and emphysema. Image registration was used to derive Jacobian determinants, a measure of lung elasticity, anisotropy, and strain tensors, to assess biomechanical differences between groups. Regression models were created with the previously mentioned categories as outcome variable, adjusting for demographics, scanner type, quantitative CT-derived emphysema, gas trapping, and airway thickness (model 1), and after adding biomechanical CT metrics (model 2). Jacobian determinants, anisotropy, and strain tensors were strongly associated with FEV1. With Catmatched as control, model 2 predicted Catspir and CatCT better than model 1 (Akaike information criterion 255.8 vs. 320.8). In addition to demographics, the strongest independent predictors of FEV1 were Jacobian mean (β = 1.60,95%confidence intervals [CI] = 1.16 to 1.98; P spirometry, offering the potential for new insights into the linkage between regional parenchymal destruction and global decrement in lung function in patients with COPD. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Coastal Improvements for Tide Models: The Impact of ALES Retracker

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Gaia Piccioni

2018-05-01

Full Text Available Since the launch of the first altimetry satellites, ocean tide models have been improved dramatically for deep and shallow waters. However, issues are still found for areas of great interest for climate change investigations: the coastal regions. The purpose of this study is to analyze the influence of the ALES coastal retracker on tide modeling in these regions with respect to a standard open ocean retracker. The approach used to compute the tidal constituents is an updated and along-track version of the Empirical Ocean Tide model developed at DGFI-TUM. The major constituents are derived from a least-square harmonic analysis of sea level residuals based on the FES2014 tide model. The results obtained with ALES are compared with the ones estimated with the standard product. A lower fitting error is found for the ALES solution, especially for distances closer than 20 km from the coast. In comparison with in situ data, the root mean squared error computed with ALES can reach an improvement larger than 2 cm at single locations, with an average impact of over 10% for tidal constituents K 2 , O 1 , and P 1 . For Q 1 , the improvement is over 25%. It was observed that improvements to the root-sum squares are larger for distances closer than 10 km to the coast, independently on the sea state. Finally, the performance of the solutions changes according to the satellite’s flight direction: for tracks approaching land from open ocean root mean square differences larger than 1 cm are found in comparison to tracks going from land to ocean.

A Remote Sensing-Derived Corn Yield Assessment Model

Science.gov (United States)

Shrestha, Ranjay Man

Agricultural studies and food security have become critical research topics due to continuous growth in human population and simultaneous shrinkage in agricultural land. In spite of modern technological advancements to improve agricultural productivity, more studies on crop yield assessments and food productivities are still necessary to fulfill the constantly increasing food demands. Besides human activities, natural disasters such as flood and drought, along with rapid climate changes, also inflect an adverse effect on food productivities. Understanding the impact of these disasters on crop yield and making early impact estimations could help planning for any national or international food crisis. Similarly, the United States Department of Agriculture (USDA) Risk Management Agency (RMA) insurance management utilizes appropriately estimated crop yield and damage assessment information to sustain farmers' practice through timely and proper compensations. Through County Agricultural Production Survey (CAPS), the USDA National Agricultural Statistical Service (NASS) uses traditional methods of field interviews and farmer-reported survey data to perform annual crop condition monitoring and production estimations at the regional and state levels. As these manual approaches of yield estimations are highly inefficient and produce very limited samples to represent the entire area, NASS requires supplemental spatial data that provides continuous and timely information on crop production and annual yield. Compared to traditional methods, remote sensing data and products offer wider spatial extent, more accurate location information, higher temporal resolution and data distribution, and lower data cost--thus providing a complementary option for estimation of crop yield information. Remote sensing derived vegetation indices such as Normalized Difference Vegetation Index (NDVI) provide measurable statistics of potential crop growth based on the spectral reflectance and could

Prediction of HIFU Propagation in a Dispersive Medium via Khokhlov–Zabolotskaya–Kuznetsov Model Combined with a Fractional Order Derivative

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Shilei Liu

2018-04-01

Full Text Available High intensity focused ultrasound (HIFU has been proven to be promising in non-invasive therapies, in which precise prediction of the focused ultrasound field is crucial for its accurate and safe application. Although the Khokhlov–Zabolotskaya–Kuznetsov (KZK equation has been widely used in the calculation of the nonlinear acoustic field of HIFU, some deviations still exist when it comes to dispersive medium. This problem also exists as an obstacle to the Westervelt model and the Spherical Beam Equation. Considering that the KZK equation is the most prevalent model in HIFU applications due to its accurate and simple simulation algorithms, there is an urgent need to improve its performance in dispersive medium. In this work, a modified KZK (mKZK equation derived from a fractional order derivative is proposed to calculate the nonlinear acoustic field in a dispersive medium. By correcting the power index in the attenuation term, this model is capable of providing improved prediction accuracy, especially in the axial position of the focal area. Simulation results using the obtained model were further compared with the experimental results from a gel phantom. Good agreements were found, indicating the applicability of the proposed model. The findings of this work will be helpful in making more accurate treatment plans for HIFU therapies, as well as facilitating the application of ultrasound in acoustic hyperthermia therapy.

On the assimilation of satellite derived soil moisture in numerical weather prediction models

Science.gov (United States)

Drusch, M.

2006-12-01

Satellite derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analysed from the modelled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. Three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF) have been performed for the two months period of June and July 2002: A control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating bias corrected TMI (TRMM Microwave Imager) derived soil moisture over the southern United States through a nudging scheme using 6-hourly departures. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analysed in the nudging experiment is the most accurate estimate when compared against in-situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage. The transferability of the results to other satellite derived soil moisture data sets will be discussed.

On (in)stabilities of perturbations in mimetic models with higher derivatives

Energy Technology Data Exchange (ETDEWEB)

Zheng, Yunlong; Shen, Liuyuan [Department of Physics, Nanjing University, Nanjing 210093 (China); Mou, Yicen; Li, Mingzhe, E-mail: zylakx@163.com, E-mail: sly12271103@163.com, E-mail: moinch@mail.ustc.edu.cn, E-mail: limz@ustc.edu.cn [Interdisciplinary Center for Theoretical Study, University of Science and Technology of China, Hefei, Anhui 230026 (China)

2017-08-01

Usually when applying the mimetic model to the early universe, higher derivative terms are needed to promote the mimetic field to be dynamical. However such models suffer from the ghost and/or the gradient instabilities and simple extensions cannot cure this pathology. We point out in this paper that it is possible to overcome this difficulty by considering the direct couplings of the higher derivatives of the mimetic field to the curvature of the spacetime.

Improving Earth/Prediction Models to Improve Network Processing

Science.gov (United States)

Wagner, G. S.

2017-12-01

The United States Atomic Energy Detection System (USAEDS) primaryseismic network consists of a relatively small number of arrays andthree-component stations. The relatively small number of stationsin the USAEDS primary network make it both necessary and feasibleto optimize both station and network processing.Station processing improvements include detector tuning effortsthat use Receiver Operator Characteristic (ROC) curves to helpjudiciously set acceptable Type 1 (false) vs. Type 2 (miss) errorrates. Other station processing improvements include the use ofempirical/historical observations and continuous background noisemeasurements to compute time-varying, maximum likelihood probabilityof detection thresholds.The USAEDS network processing software makes extensive use of theazimuth and slowness information provided by frequency-wavenumberanalysis at array sites, and polarization analysis at three-componentsites. Most of the improvements in USAEDS network processing aredue to improvements in the models used to predict azimuth, slowness,and probability of detection. Kriged travel-time, azimuth andslowness corrections-and associated uncertainties-are computedusing a ground truth database. Improvements in station processingand the use of improved models for azimuth, slowness, and probabilityof detection have led to significant improvements in USADES networkprocessing.

Algorithm for Financial Derivatives Evaluation in a Generalized Multi-Heston Model

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Dan Negura

2013-02-01

Full Text Available In this paper we show how could a financial derivative be estimated based on an assumed Multi-Heston model support.Keywords: Euler Maruyama discretization method, Monte Carlo simulation, Heston model, Double-Heston model, Multi-Heston model

Adipose-derived Stem Cells Stimulated with n-Butylidenephthalide Exhibit Therapeutic Effects in a Mouse Model of Parkinson's Disease.

Science.gov (United States)

Chi, Kang; Fu, Ru-Huei; Huang, Yu-Chuen; Chen, Shih-Yin; Hsu, Ching-Ju; Lin, Shinn-Zong; Tu, Chi-Tang; Chang, Li-Hsun; Wu, Ping-An; Liu, Shih-Ping

2018-03-01

Parkinson's disease (PD) causes motor dysfunction and dopaminergic cell death. Drug treatments can effectively reduce symptoms but often cause unwanted side effects. Stem cell therapies using cell replacement or indirect beneficial secretomes have recently emerged as potential therapeutic strategies. Although various types of stem cells have been proposed as possible candidates, adipose-derived stem cells (ADSCs) are easily obtainable, more abundant, less ethically disputed, and able to differentiate into multiple cell lineages. However, treatment of PD using adult stem cells is known to be less efficacious than neuron or embryonic stem cell transplantation. Therefore, improved therapies are urgently needed. n-Butylidenephthalide (BP), which is extracted from Angelica sinensis, has been shown to have anti-inflammatory and neuroprotective effects. Indeed, we previously demonstrated that BP treatment of ADSCs enhances the expression of neurogenesis and homing factors such as nuclear receptor related 1 protein, stromal-derived factor 1, and brain-derived neurotrophic factor. In the present study, we examined the ability of BP-pretreated ADSC transplantation to improve PD motor symptoms and protect dopamine neurons in a mouse model of PD. We evaluated the results using neuronal behavior tests such as beam walking, rotarod, and locomotor activity tests. ADSCs with or without BP pretreatment were transplanted into the striatum. Our findings demonstrated that ADSC transplantation improved motor abilities with varied efficacies and that BP stimulation improved the therapeutic effects of transplantation. Dopaminergic cell numbers returned to normal in ADSC-transplanted mice after 22 d. In summary, stimulating ADSCs with BP improved PD recovery efficiency. Thus, our results provide important new strategies to improve stem cell therapies for neurodegenerative diseases in future studies.

Development of a MODIS-Derived Surface Albedo Data Set: An Improved Model Input for Processing the NSRDB

Energy Technology Data Exchange (ETDEWEB)

Maclaurin, Galen [National Renewable Energy Lab. (NREL), Golden, CO (United States); Sengupta, Manajit [National Renewable Energy Lab. (NREL), Golden, CO (United States); Xie, Yu [National Renewable Energy Lab. (NREL), Golden, CO (United States); Gilroy, Nicholas [National Renewable Energy Lab. (NREL), Golden, CO (United States)

2016-12-01

A significant source of bias in the transposition of global horizontal irradiance to plane-of-array (POA) irradiance arises from inaccurate estimations of surface albedo. The current physics-based model used to produce the National Solar Radiation Database (NSRDB) relies on model estimations of surface albedo from a reanalysis climatalogy produced at relatively coarse spatial resolution compared to that of the NSRDB. As an input to spectral decomposition and transposition models, more accurate surface albedo data from remotely sensed imagery at finer spatial resolutions would improve accuracy in the final product. The National Renewable Energy Laboratory (NREL) developed an improved white-sky (bi-hemispherical reflectance) broadband (0.3-5.0 ..mu..m) surface albedo data set for processing the NSRDB from two existing data sets: a gap-filled albedo product and a daily snow cover product. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard the Terra and Aqua satellites have provided high-quality measurements of surface albedo at 30 arc-second spatial resolution and 8-day temporal resolution since 2001. The high spatial and temporal resolutions and the temporal coverage of the MODIS sensor will allow for improved modeling of POA irradiance in the NSRDB. However, cloud and snow cover interfere with MODIS observations of ground surface albedo, and thus they require post-processing. The MODIS production team applied a gap-filling methodology to interpolate observations obscured by clouds or ephemeral snow. This approach filled pixels with ephemeral snow cover because the 8-day temporal resolution is too coarse to accurately capture the variability of snow cover and its impact on albedo estimates. However, for this project, accurate representation of daily snow cover change is important in producing the NSRDB. Therefore, NREL also used the Integrated Multisensor Snow and Ice Mapping System data set, which provides daily snow cover observations of the

Hydroxyurea derivatives of irofulven with improved antitumor efficacy.

Science.gov (United States)

Staake, Michael D; Kashinatham, Alisala; McMorris, Trevor C; Estes, Leita A; Kelner, Michael J

2016-04-01

Irofulven is a semi-synthetic derivative of Illudin S, a toxic sesquiterpene isolated from the mushroom Omphalotus illudens. Irofulven has displayed significant antitumor activity in various clinical trials but displayed a limited therapeutic index. A new derivative of irofulven was prepared by reacting hydroxyurea with irofulven under acidic conditions. Acetylation of this new compound with acetic anhydride produced a second derivative. Both of these new derivatives displayed significant antitumor activity in vitro and in vivo comparable to or exceeding that of irofulven. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modeling Anti-HIV Activity of HEPT Derivatives Revisited. Multiregression Models Are Not Inferior Ones

International Nuclear Information System (INIS)

Basic, Ivan; Nadramija, Damir; Flajslik, Mario; Amic, Dragan; Lucic, Bono

2007-01-01

Several quantitative structure-activity studies for this data set containing 107 HEPT derivatives have been performed since 1997, using the same set of molecules by (more or less) different classes of molecular descriptors. Multivariate Regression (MR) and Artificial Neural Network (ANN) models were developed and in each study the authors concluded that ANN models are superior to MR ones. We re-calculated multivariate regression models for this set of molecules using the same set of descriptors, and compared our results with the previous ones. Two main reasons for overestimation of the quality of the ANN models in previous studies comparing with MR models are: (1) wrong calculation of leave-one-out (LOO) cross-validated (CV) correlation coefficient for MR models in Luco et al., J. Chem. Inf. Comput. Sci. 37 392-401 (1997), and (2) incorrect estimation/interpretation of leave-one-out (LOO) cross-validated and predictive performance and power of ANN models. More precise and fairer comparison of fit and LOO CV statistical parameters shows that MR models are more stable. In addition, MR models are much simpler than ANN ones. For real testing the predictive performance of both classes of models we need more HEPT derivatives, because all ANN models that presented results for external set of molecules used experimental values in optimization of modeling procedure and model parameters

An Improved Information Value Model Based on Gray Clustering for Landslide Susceptibility Mapping

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Qianqian Ba

2017-01-01

Full Text Available Landslides, as geological hazards, cause significant casualties and economic losses. Therefore, it is necessary to identify areas prone to landslides for prevention work. This paper proposes an improved information value model based on gray clustering (IVM-GC for landslide susceptibility mapping. This method uses the information value derived from an information value model to achieve susceptibility classification and weight determination of landslide predisposing factors and, hence, obtain the landslide susceptibility of each study unit based on the clustering analysis. Using a landslide inventory of Chongqing, China, which contains 8435 landslides, three landslide susceptibility maps were generated based on the common information value model (IVM, an information value model improved by an analytic hierarchy process (IVM-AHP and our new improved model. Approximately 70% (5905 of the inventory landslides were used to generate the susceptibility maps, while the remaining 30% (2530 were used to validate the results. The training accuracies of the IVM, IVM-AHP and IVM-GC were 81.8%, 78.7% and 85.2%, respectively, and the prediction accuracies were 82.0%, 78.7% and 85.4%, respectively. The results demonstrate that all three methods perform well in evaluating landslide susceptibility. Among them, IVM-GC has the best performance.

Towards improved parameterization of a macroscale hydrologic model in a discontinuous permafrost boreal forest ecosystem

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A. Endalamaw

2017-09-01

Full Text Available Modeling hydrological processes in the Alaskan sub-arctic is challenging because of the extreme spatial heterogeneity in soil properties and vegetation communities. Nevertheless, modeling and predicting hydrological processes is critical in this region due to its vulnerability to the effects of climate change. Coarse-spatial-resolution datasets used in land surface modeling pose a new challenge in simulating the spatially distributed and basin-integrated processes since these datasets do not adequately represent the small-scale hydrological, thermal, and ecological heterogeneity. The goal of this study is to improve the prediction capacity of mesoscale to large-scale hydrological models by introducing a small-scale parameterization scheme, which better represents the spatial heterogeneity of soil properties and vegetation cover in the Alaskan sub-arctic. The small-scale parameterization schemes are derived from observations and a sub-grid parameterization method in the two contrasting sub-basins of the Caribou Poker Creek Research Watershed (CPCRW in Interior Alaska: one nearly permafrost-free (LowP sub-basin and one permafrost-dominated (HighP sub-basin. The sub-grid parameterization method used in the small-scale parameterization scheme is derived from the watershed topography. We found that observed soil thermal and hydraulic properties – including the distribution of permafrost and vegetation cover heterogeneity – are better represented in the sub-grid parameterization method than the coarse-resolution datasets. Parameters derived from the coarse-resolution datasets and from the sub-grid parameterization method are implemented into the variable infiltration capacity (VIC mesoscale hydrological model to simulate runoff, evapotranspiration (ET, and soil moisture in the two sub-basins of the CPCRW. Simulated hydrographs based on the small-scale parameterization capture most of the peak and low flows, with similar accuracy in both sub

Vinblastine 20' Amides: Synthetic Analogues That Maintain or Improve Potency and Simultaneously Overcome Pgp-Derived Efflux and Resistance.

Science.gov (United States)

Lukesh, John C; Carney, Daniel W; Dong, Huijun; Cross, R Matthew; Shukla, Vyom; Duncan, Katharine K; Yang, Shouliang; Brody, Daniel M; Brütsch, Manuela M; Radakovic, Aleksandar; Boger, Dale L

2017-09-14

A series of 180 vinblastine 20' amides were prepared in three steps from commercially available starting materials, systematically exploring a typically inaccessible site in the molecule enlisting a powerful functionalization strategy. Clear structure-activity relationships and a structural model were developed in the studies which provided many such 20' amides that exhibit substantial and some even remarkable enhancements in potency, many that exhibit further improvements in activity against a Pgp overexpressing resistant cancer cell line, and an important subset of the vinblastine analogues that display little or no differential in activity against a matched pair of vinblastine sensitive and resistant (Pgp overexpressing) cell lines. The improvements in potency directly correlated with target tubulin binding affinity, and the reduction in differential functional activity against the sensitive and Pgp overexpressing resistant cell lines was found to correlate directly with an impact on Pgp-derived efflux.

Modeling the Interest Rate Term Structure: Derivatives Contracts Dynamics and Evaluation

Directory of Open Access Journals (Sweden)

Pedro L. Valls Pereira

2005-06-01

Full Text Available This article deals with a model for the term structure of interest rates and the valuation of derivative contracts directly dependent on it. The work is of a theoretical nature and deals, exclusively, with continuous time models, making ample use of stochastic calculus results and presents original contributions that we consider relevant to the development of the fixed income market modeling. We develop a new multifactorial model of the term structure of interest rates. The model is based on the decomposition of the yield curve into the factors level, slope, curvature, and the treatment of their collective dynamics. We show that this model may be applied to serve various objectives: analysis of bond price dynamics, valuation of derivative contracts and also market risk management and formulation of operational strategies which is presented in another article.

PDX-MI: Minimal Information for Patient-Derived Tumor Xenograft Models

NARCIS (Netherlands)

Meehan, Terrence F.; Conte, Nathalie; Goldstein, Theodore; Inghirami, Giorgio; Murakami, Mark A.; Brabetz, Sebastian; Gu, Zhiping; Wiser, Jeffrey A.; Dunn, Patrick; Begley, Dale A.; Krupke, Debra M.; Bertotti, Andrea; Bruna, Alejandra; Brush, Matthew H.; Byrne, Annette T.; Caldas, Carlos; Christie, Amanda L.; Clark, Dominic A.; Dowst, Heidi; Dry, Jonathan R.; Doroshow, James H.; Duchamp, Olivier; Evrard, Yvonne A.; Ferretti, Stephane; Frese, Kristopher K.; Goodwin, Neal C.; Greenawalt, Danielle; Haendel, Melissa A.; Hermans, Els; Houghton, Peter J.; Jonkers, Jos; Kemper, Kristel; Khor, Tin O.; Lewis, Michael T.; Lloyd, K. C. Kent; Mason, Jeremy; Medico, Enzo; Neuhauser, Steven B.; Olson, James M.; Peeper, Daniel S.; Rueda, Oscar M.; Seong, Je Kyung; Trusolino, Livio; Vinolo, Emilie; Wechsler-Reya, Robert J.; Weinstock, David M.; Welm, Alana; Weroha, S. John; Amant, Frédéric; Pfister, Stefan M.; Kool, Marcel; Parkinson, Helen; Butte, Atul J.; Bult, Carol J.

2017-01-01

Patient-derived tumor xenograft (PDX) mouse models have emerged as an important oncology research platform to study tumor evolution, mechanisms of drug response and resistance, and tailoring chemotherapeutic approaches for individual patients. The lack of robust standards for reporting on PDX models

Application of a Patient Derived Xenograft Model for Predicative Study of Uterine Fibroid Disease.

Directory of Open Access Journals (Sweden)

Martin Fritsch

Full Text Available Human uterine fibroids, benign tumors derived from the smooth muscle layers of the uterus, impose a major health burden to up to 50% of premenopausal women in their daily life. To improve our understanding of this disease, we developed and characterized a patient-derived xenograft model by subcutaneous transplantation of pieces of human uterine fibroid tissue into three different strains of severe combined immunodeficient mice. Engrafted uterine fibroid tissue preserved the classical morphology with interwoven bundles of smooth muscle cells and an abundant deposition of collagenous matrix, similar to uterine fibroids in situ. The grafts expressed both estrogen receptor 1 and progesterone receptor. Additionally, both receptors were up-regulated by estrogen treatment. Growth of the fibroid grafts was dependent on 17β-estradiol and progesterone supplementation at levels similar to women with the disease and was studied for up to 60 days at maximum. Co-treatment with the antiprogestin mifepristone reduced graft growth (four independent donors, p<0.0001 two-sided t-test, as did treatment with the mTOR inhibitor rapamycin (three independent donors, p<0.0001 two-sided t-test. This in vivo animal model preserves the main histological and functional characteristics of human uterine fibroids, is amenable to intervention by pharmacological treatment, and can thus serve as an adequate model for the development of novel therapies.

Umbilical Cord Blood-Derived Stem Cells Improve Heat Tolerance and Hypothalamic Damage in Heat Stressed Mice

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Ling-Shu Tseng

2014-01-01

Full Text Available Heatstroke is characterized by excessive hyperthermia associated with systemic inflammatory responses, which leads to multiple organ failure, in which brain disorders predominate. This definition can be almost fulfilled by a mouse model of heatstroke used in the present study. Unanesthetized mice were exposed to whole body heating (41.2°C for 1 hour and then returned to room temperature (26°C for recovery. Immediately after termination of whole body heating, heated mice displayed excessive hyperthermia (body core temperature ~42.5°C. Four hours after termination of heat stress, heated mice displayed (i systemic inflammation; (ii ischemic, hypoxic, and oxidative damage to the hypothalamus; (iii hypothalamo-pituitary-adrenocortical axis impairment (reflected by plasma levels of both adrenocorticotrophic-hormone and corticosterone; (iv decreased fractional survival; and (v thermoregulatory deficits (e.g., they became hypothermia when they were exposed to room temperature. These heatstroke reactions can be significantly attenuated by human umbilical cord blood-derived CD34+ cells therapy. Our data suggest that human umbilical cord blood-derived stem cells therapy may improve outcomes of heatstroke in mice by reducing systemic inflammation as well as hypothalamo-pituitary-adrenocortical axis impairment.

Algebraic Bethe ansatz for a quantum integrable derivative nonlinear Schroedinger model

International Nuclear Information System (INIS)

Basu-Mallick, B.; Bhattacharyya, Tanaya

2002-01-01

We find that the quantum monodromy matrix associated with a derivative nonlinear Schroedinger (DNLS) model exhibits U(2) or U(1,1) symmetry depending on the sign of the related coupling constant. By using a variant of quantum inverse scattering method which is directly applicable to field theoretical models, we derive all possible commutation relations among the operator valued elements of such monodromy matrix. Thus, we obtain the commutation relation between creation and annihilation operators of quasi-particles associated with DNLS model and find out the S-matrix for two-body scattering. We also observe that, for some special values of the coupling constant, there exists an upper bound on the number of quasi-particles which can form a soliton state for the quantum DNLS model

Stem cell-derived vasculature: A potent and multidimensional technology for basic research, disease modeling, and tissue engineering.

Science.gov (United States)

Lowenthal, Justin; Gerecht, Sharon

2016-05-06

Proper blood vessel networks are necessary for constructing and re-constructing tissues, promoting wound healing, and delivering metabolic necessities throughout the body. Conversely, an understanding of vascular dysfunction has provided insight into the pathogenesis and progression of diseases both common and rare. Recent advances in stem cell-based regenerative medicine - including advances in stem cell technologies and related progress in bioscaffold design and complex tissue engineering - have allowed rapid advances in the field of vascular biology, leading in turn to more advanced modeling of vascular pathophysiology and improved engineering of vascularized tissue constructs. In this review we examine recent advances in the field of stem cell-derived vasculature, providing an overview of stem cell technologies as a source for vascular cell types and then focusing on their use in three primary areas: studies of vascular development and angiogenesis, improved disease modeling, and the engineering of vascularized constructs for tissue-level modeling and cell-based therapies. Copyright © 2015 Elsevier Inc. All rights reserved.

ESC-Derived BDNF-Overexpressing Neural Progenitors Differentially Promote Recovery in Huntington's Disease Models by Enhanced Striatal Differentiation

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Tina Zimmermann

2016-10-01

Full Text Available Huntington's disease (HD is characterized by fatal motoric failures induced by loss of striatal medium spiny neurons. Neuronal cell death has been linked to impaired expression and axonal transport of the neurotrophin BDNF (brain-derived neurotrophic factor. By transplanting embryonic stem cell-derived neural progenitors overexpressing BDNF, we combined cell replacement and BDNF supply as a potential HD therapy approach. Transplantation of purified neural progenitors was analyzed in a quinolinic acid (QA chemical and two genetic HD mouse models (R6/2 and N171-82Q on the basis of distinct behavioral parameters, including CatWalk gait analysis. Explicit rescue of motor function by BDNF neural progenitors was found in QA-lesioned mice, whereas genetic mouse models displayed only minor improvements. Tumor formation was absent, and regeneration was attributed to enhanced neuronal and striatal differentiation. In addition, adult neurogenesis was preserved in a BDNF-dependent manner. Our findings provide significant insight for establishing therapeutic strategies for HD to ameliorate neurodegenerative symptoms.

A critical view on temperature modelling for application in weather derivatives markets

International Nuclear Information System (INIS)

Šaltytė Benth, Jūratė; Benth, Fred Espen

2012-01-01

In this paper we present a stochastic model for daily average temperature. The model contains seasonality, a low-order autoregressive component and a variance describing the heteroskedastic residuals. The model is estimated on daily average temperature records from Stockholm (Sweden). By comparing the proposed model with the popular model of Campbell and Diebold (2005), we point out some important issues to be addressed when modelling the temperature for application in weather derivatives market. - Highlights: ► We present a stochastic model for daily average temperature, containing seasonality, a low-order autoregressive component and a variance describing the heteroskedastic residuals. ► We compare the proposed model with the popular model of Campbell and Diebold (2005). ► Some important issues to be addressed when modelling the temperature for application in weather derivatives market are pointed out.

Neonatal Transplantation Confers Maturation of PSC-Derived Cardiomyocytes Conducive to Modeling Cardiomyopathy

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Gun-Sik Cho

2017-01-01

Full Text Available Summary: Pluripotent stem cells (PSCs offer unprecedented opportunities for disease modeling and personalized medicine. However, PSC-derived cells exhibit fetal-like characteristics and remain immature in a dish. This has emerged as a major obstacle for their application for late-onset diseases. We previously showed that there is a neonatal arrest of long-term cultured PSC-derived cardiomyocytes (PSC-CMs. Here, we demonstrate that PSC-CMs mature into adult CMs when transplanted into neonatal hearts. PSC-CMs became similar to adult CMs in morphology, structure, and function within a month of transplantation into rats. The similarity was further supported by single-cell RNA-sequencing analysis. Moreover, this in vivo maturation allowed patient-derived PSC-CMs to reveal the disease phenotype of arrhythmogenic right ventricular cardiomyopathy, which manifests predominantly in adults. This study lays a foundation for understanding human CM maturation and pathogenesis and can be instrumental in PSC-based modeling of adult heart diseases. : Pluripotent stem cell (PSC-derived cells remain fetal like, and this has become a major impediment to modeling adult diseases. Cho et al. find that PSC-derived cardiomyocytes mature into adult cardiomyocytes when transplanted into neonatal rat hearts. This method can serve as a tool to understand maturation and pathogenesis in human cardiomyocytes. Keywords: cardiomyocyte, maturation, iPS, cardiac progenitor, neonatal, disease modeling, cardiomyopathy, ARVC, T-tubule, calcium transient, sarcomere shortening

A constitutive rheological model for agglomerating blood derived from nonequilibrium thermodynamics

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Tsimouri, Ioanna Ch.; Stephanou, Pavlos S.; Mavrantzas, Vlasis G.

2018-03-01

Red blood cells tend to aggregate in the presence of plasma proteins, forming structures known as rouleaux. Here, we derive a constitutive rheological model for human blood which accounts for the formation and dissociation of rouleaux using the generalized bracket formulation of nonequilibrium thermodynamics. Similar to the model derived by Owens and co-workers ["A non-homogeneous constitutive model for human blood. Part 1. Model derivation and steady flow," J. Fluid Mech. 617, 327-354 (2008)] through polymer network theory, each rouleau in our model is represented as a dumbbell; the corresponding structural variable is the conformation tensor of the dumbbell. The kinetics of rouleau formation and dissociation is treated as in the work of Germann et al. ["Nonequilibrium thermodynamic modeling of the structure and rheology of concentrated wormlike micellar solutions," J. Non-Newton. Fluid Mech. 196, 51-57 (2013)] by assuming a set of reversible reactions, each characterized by a forward and a reverse rate constant. The final set of evolution equations for the microstructure of each rouleau and the expression for the stress tensor turn out to be very similar to those of Owens and co-workers. However, by explicitly considering a mechanism for the formation and breakage of rouleaux, our model further provides expressions for the aggregation and disaggregation rates appearing in the final transport equations, which in the kinetic theory-based network model of Owens were absent and had to be specified separately. Despite this, the two models are found to provide similar descriptions of experimental data on the size distribution of rouleaux.

Hydrologic Derivatives for Modeling and Analysis—A new global high-resolution database

Science.gov (United States)

Verdin, Kristine L.

2017-07-17

The U.S. Geological Survey has developed a new global high-resolution hydrologic derivative database. Loosely modeled on the HYDRO1k database, this new database, entitled Hydrologic Derivatives for Modeling and Analysis, provides comprehensive and consistent global coverage of topographically derived raster layers (digital elevation model data, flow direction, flow accumulation, slope, and compound topographic index) and vector layers (streams and catchment boundaries). The coverage of the data is global, and the underlying digital elevation model is a hybrid of three datasets: HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales), GMTED2010 (Global Multi-resolution Terrain Elevation Data 2010), and the SRTM (Shuttle Radar Topography Mission). For most of the globe south of 60°N., the raster resolution of the data is 3 arc-seconds, corresponding to the resolution of the SRTM. For the areas north of 60°N., the resolution is 7.5 arc-seconds (the highest resolution of the GMTED2010 dataset) except for Greenland, where the resolution is 30 arc-seconds. The streams and catchments are attributed with Pfafstetter codes, based on a hierarchical numbering system, that carry important topological information. This database is appropriate for use in continental-scale modeling efforts. The work described in this report was conducted by the U.S. Geological Survey in cooperation with the National Aeronautics and Space Administration Goddard Space Flight Center.

Modeling neurodegenerative diseases with patient-derived induced pluripotent cells: Possibilities and challenges.

Science.gov (United States)

Poon, Anna; Zhang, Yu; Chandrasekaran, Abinaya; Phanthong, Phetcharat; Schmid, Benjamin; Nielsen, Troels T; Freude, Kristine K

2017-10-25

The rising prevalence of progressive neurodegenerative diseases coupled with increasing longevity poses an economic burden at individual and societal levels. There is currently no effective cure for the majority of neurodegenerative diseases and disease-affected tissues from patients have been difficult to obtain for research and drug discovery in pre-clinical settings. While the use of animal models has contributed invaluable mechanistic insights and potential therapeutic targets, the translational value of animal models could be further enhanced when combined with in vitro models derived from patient-specific induced pluripotent stem cells (iPSCs) and isogenic controls generated using CRISPR-Cas9 mediated genome editing. The iPSCs are self-renewable and capable of being differentiated into the cell types affected by the diseases. These in vitro models based on patient-derived iPSCs provide the opportunity to model disease development, uncover novel mechanisms and test potential therapeutics. Here we review findings from iPSC-based modeling of selected neurodegenerative diseases, including Alzheimer's disease, frontotemporal dementia and spinocerebellar ataxia. Furthermore, we discuss the possibilities of generating three-dimensional (3D) models using the iPSCs-derived cells and compare their advantages and disadvantages to conventional two-dimensional (2D) models. Copyright © 2017 Elsevier B.V. All rights reserved.

Improved steamflood analytical model

Energy Technology Data Exchange (ETDEWEB)

Chandra, S.; Mamora, D.D. [Society of Petroleum Engineers, Richardson, TX (United States)]|[Texas A and M Univ., TX (United States)

2005-11-01

Predicting the performance of steam flooding can help in the proper execution of enhanced oil recovery (EOR) processes. The Jones model is often used for analytical steam flooding performance prediction, but it does not accurately predict oil production peaks. In this study, an improved steam flood model was developed by modifying 2 of the 3 components of the capture factor in the Jones model. The modifications were based on simulation results from a Society of Petroleum Engineers (SPE) comparative project case model. The production performance of a 5-spot steamflood pattern unit was simulated and compared with results obtained from the Jones model. Three reservoir types were simulated through the use of 3-D Cartesian black oil models. In order to correlate the simulation and the Jones analytical model results for the start and height of the production peak, the dimensionless steam zone size was modified to account for a decrease in oil viscosity during steam flooding and its dependence on the steam injection rate. In addition, the dimensionless volume of displaced oil produced was modified from its square-root format to an exponential form. The modified model improved results for production performance by up to 20 years of simulated steam flooding, compared to the Jones model. Results agreed with simulation results for 13 different cases, including 3 different sets of reservoir and fluid properties. Reservoir engineers will benefit from the improved accuracy of the model. Oil displacement calculations were based on methods proposed in earlier research, in which the oil displacement rate is a function of cumulative oil steam ratio. The cumulative oil steam ratio is a function of overall thermal efficiency. Capture factor component formulae were presented, as well as charts of oil production rates and cumulative oil-steam ratios for various reservoirs. 13 refs., 4 tabs., 29 figs.

Precision comparison of the erosion rates derived from 137Cs measurements models with predictions based on empirical relationship

International Nuclear Information System (INIS)

Yang Mingyi; Liu Puling; Li Liqing

2004-01-01

The soil samples were collected in 6 cultivated runoff plots with grid sampling method, and the soil erosion rates derived from 137 Cs measurements were calculated. The models precision of Zhang Xinbao, Zhou Weizhi, Yang Hao and Walling were compared with predictions based on empirical relationship, data showed that the precision of 4 models is high within 50m slope length except for the slope with low slope angle and short length. Relatively, the precision of Walling's model is better than that of Zhang Xinbao, Zhou Weizhi and Yang Hao. In addition, the relationship between parameter Γ in Walling's improved model and slope angle was analyzed, the ralation is: Y=0.0109 X 1.0072 . (authors)

Improving UWB-Based Localization in IoT Scenarios with Statistical Models of Distance Error.

Science.gov (United States)

Monica, Stefania; Ferrari, Gianluigi

2018-05-17

Interest in the Internet of Things (IoT) is rapidly increasing, as the number of connected devices is exponentially growing. One of the application scenarios envisaged for IoT technologies involves indoor localization and context awareness. In this paper, we focus on a localization approach that relies on a particular type of communication technology, namely Ultra Wide Band (UWB). UWB technology is an attractive choice for indoor localization, owing to its high accuracy. Since localization algorithms typically rely on estimated inter-node distances, the goal of this paper is to evaluate the improvement brought by a simple (linear) statistical model of the distance error. On the basis of an extensive experimental measurement campaign, we propose a general analytical framework, based on a Least Square (LS) method, to derive a novel statistical model for the range estimation error between a pair of UWB nodes. The proposed statistical model is then applied to improve the performance of a few illustrative localization algorithms in various realistic scenarios. The obtained experimental results show that the use of the proposed statistical model improves the accuracy of the considered localization algorithms with a reduction of the localization error up to 66%.

Relativistic nuclear matter with alternative derivative coupling models

International Nuclear Information System (INIS)

Delfino, A.; Coelho, C.T.; Malheiro, M.

1994-01-01

Effective Lagrangians involving nucleons coupled to scalar and vector fields are investigated within the framework of relativistic mean-field theory. The study presents the traditional Walecka model and different kinds of scalar derivative coupling suggested by Zimanyi and Moszkowski. The incompressibility (presented in an analytical form), scalar potential, and vector potential at the saturation point of nuclear matter are compared for these models. The real optical potential for the models are calculated and one of the models fits well the experimental curve from-50 to 400 MeV while also gives a soft equation of state. By varying the coupling constants and keeping the saturation point of nuclear matter approximately fixed, only the Walecka model presents a first order phase transition of finite temperature at zero density. (author)

Mesenchymal stem cell and derived exosome as small RNA carrier and Immunomodulator to improve islet transplantation.

Science.gov (United States)

Wen, Di; Peng, Yang; Liu, Di; Weizmann, Yossi; Mahato, Ram I

2016-09-28

Human bone marrow mesenchymal stem cells (hBMSCs) and their exosomes can suppress immune reaction and deliver small RNAs. Thus, they may improve islet transplantation by delivering small RNAs for promoting islet function and inhibiting immune rejection. Here, we proposed an hBMSC and its exosome-based therapy to overcome immune rejection and poor islet function, both of which hinder the success of islet transplantation. We found overexpressed siFas and anti-miR-375 in plasmid encoding shFas and anti-miR-375 transfected hBMSC-derived exosomes, which silenced Fas and miR-375 of human islets and improved their viability and function against inflammatory cytokines. This plasmid transfected hBMSCs downregulated Fas and miR-375 of human islets in a humanized NOD scid gamma (NSG) mouse model, whose immune reaction was inhibited by injecting hBMSC and peripheral blood mononuclear cell (PBMC) co-cultured exosomes. These exosomes suppressed immune reaction by inhibiting PBMC proliferation and enhancing regulatory T cell (Treg) function. Collectively, our studies elucidated the mechanisms of RNA delivery from hBMSCs to human islets and the immunosuppressive effect of hBMSC and peripheral blood mononuclear cell co-cultured exosomes for improving islet transplantation. Copyright © 2016 Elsevier B.V. All rights reserved.

Drosophila melanogaster "a potential model organism" for identification of pharmacological properties of plants/plant-derived components.

Science.gov (United States)

Panchal, Komal; Tiwari, Anand K

2017-05-01

Plants/plant-derived components have been used from ancient times to treat/cure several human diseases. Plants and their parts possess several chemical components that play the vital role in the improvement of human health and their life expectancy. Allopathic medicines have been playing a key role in the treatment of several diseases. Though allopathic medicines provide fast relief, long time consumption cause serious health concerns such as hyperallergic reactions, liver damage, etc. So, the study of medicinal plants which rarely cause any side effect is very important to mankind. Plants contain many health benefit properties like antioxidant, anti-aging, neuroprotective, anti-genotoxic, anti-mutagenic and bioinsecticidal activity. Thus, identification of pharmacological properties of plants/plant-derived components are of utmost importance to be explored. Several model organisms have been used to identify the pharmacological properties of the different plants or active components therein and Drosophila is one of them. Drosophila melanogaster "fruit fly" is a well understood, high-throughput model organism being used more than 110 years to study the different biological aspects related to the development and diseases. Most of the developmental and cell signaling pathways and ∼75% human disease-related genes are conserved between human and Drosophila. Using Drosophila, one can easily analyze the pharmacological properties of plants/plant-derived components by performing several assays available with flies such as survivorship, locomotor, antioxidant, cell death, etc. The current review focuses on the potential of Drosophila melanogaster for the identification of medicinal/pharmacological properties associated with plants/plant-derived components. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Ab initio derivation of model energy density functionals

International Nuclear Information System (INIS)

Dobaczewski, Jacek

2016-01-01

I propose a simple and manageable method that allows for deriving coupling constants of model energy density functionals (EDFs) directly from ab initio calculations performed for finite fermion systems. A proof-of-principle application allows for linking properties of finite nuclei, determined by using the nuclear nonlocal Gogny functional, to the coupling constants of the quasilocal Skyrme functional. The method does not rely on properties of infinite fermion systems but on the ab initio calculations in finite systems. It also allows for quantifying merits of different model EDFs in describing the ab initio results. (letter)

Improved water density feedback model for pressurized water reactors

International Nuclear Information System (INIS)

Casadei, A.L.

1976-01-01

An improved water density feedback model has been developed for neutron diffusion calculations of PWR cores. This work addresses spectral effects on few-group cross sections due to water density changes, and water density predictions considering open channel and subcooled boiling effects. An homogenized spectral model was also derived using the unit assembly diffusion method for employment in a coarse mesh 3D diffusion computer program. The spectral and water density evaluation models described were incorporated in a 3D diffusion code, and neutronic calculations for a typical PWR were completed for both nominal and accident conditions. Comparison of neutronic calculations employing the open versus the closed channel model for accident conditions indicates that significant safety margin increases can be obtained if subcooled boiling and open channel effects are considered in accident calculations. This is attributed to effects on both core reactivity and power distribution, which result in increased margin to fuel degradation limits. For nominal operating conditions, negligible differences in core reactivity and power distribution exist since flow redistribution and subcooled voids are not significant at such conditions. The results serve to confirm the conservatism of currently employed closed channel feedback methods in accident analysis, and indicate that the model developed in this work can contribute to show increased safety margins for certain accidents

Deriving the Dividend Discount Model in the Intermediate Microeconomics Class

Science.gov (United States)

Norman, Stephen; Schlaudraff, Jonathan; White, Karianne; Wills, Douglas

2013-01-01

In this article, the authors show that the dividend discount model can be derived using the basic intertemporal consumption model that is introduced in a typical intermediate microeconomics course. This result will be of use to instructors who teach microeconomics to finance students in that it demonstrates the value of utility maximization in…

Operational derivation of Boltzmann distribution with Maxwell's demon model.

Science.gov (United States)

Hosoya, Akio; Maruyama, Koji; Shikano, Yutaka

2015-11-24

The resolution of the Maxwell's demon paradox linked thermodynamics with information theory through information erasure principle. By considering a demon endowed with a Turing-machine consisting of a memory tape and a processor, we attempt to explore the link towards the foundations of statistical mechanics and to derive results therein in an operational manner. Here, we present a derivation of the Boltzmann distribution in equilibrium as an example, without hypothesizing the principle of maximum entropy. Further, since the model can be applied to non-equilibrium processes, in principle, we demonstrate the dissipation-fluctuation relation to show the possibility in this direction.

Improved isolation protocol for equine cord blood-derived mesenchymal stromal cells

DEFF Research Database (Denmark)

Koch, Thomas Gadegaard; Thomsen, Preben Dybdahl; Betts, Dean H.

2009-01-01

  BACKGROUND AIMS: A robust methodology for the isolation of cord blood-derived multipotent mesenchymal stromal cells (CB-MSCs) from fresh umbilical cord blood has not been reported in any species. The objective of this study was to improve the isolation procedure for equine CB-MSCs. METHODS: Pre......-culture separation of red and white blood cells was done using either PrepaCyte?-EQ medium or Ficoll-Paque? PREMIUM density medium. Regular FBS and MSC-qualified FBS were compared for their ability to support the establishment of putative primary MSC colonies. RESULTS AND CONCLUSIONS: Our results indicate that Prepa...

Three-Dimensional Human Tissue Models That Incorporate Diabetic Foot Ulcer-Derived Fibroblasts Mimic In Vivo Features of Chronic Wounds

Science.gov (United States)

Maione, Anna G.; Brudno, Yevgeny; Stojadinovic, Olivera; Park, Lara K.; Smith, Avi; Tellechea, Ana; Leal, Ermelindo C.; Kearney, Cathal J.; Veves, Aristidis; Tomic-Canic, Marjana; Mooney, David J.

2015-01-01

Diabetic foot ulcers (DFU) are a major, debilitating complication of diabetes mellitus. Unfortunately, many DFUs are refractory to existing treatments and frequently lead to amputation. The development of more effective therapies has been hampered by the lack of predictive in vitro methods to investigate the mechanisms underlying impaired healing. To address this need for realistic wound-healing models, we established patient-derived fibroblasts from DFUs and site-matched controls and used them to construct three-dimensional (3D) models of chronic wound healing. Incorporation of DFU-derived fibroblasts into these models accurately recapitulated the following key aspects of chronic ulcers: reduced stimulation of angiogenesis, increased keratinocyte proliferation, decreased re-epithelialization, and impaired extracellular matrix deposition. In addition to reflecting clinical attributes of DFUs, the wound-healing potential of DFU fibroblasts demonstrated in this suite of models correlated with in vivo wound closure in mice. Thus, the reported panel of 3D DFU models provides a more biologically relevant platform for elucidating the cell–cell and cell–matrix-related mechanisms responsible for chronic wound pathogenesis and may improve translation of in vitro findings into efficacious clinical applications. PMID:25343343

Improvement of mouse cloning using nuclear transfer-derived embryonic stem cells and/or histone deacetylase inhibitor.

Science.gov (United States)

Wakayama, Sayaka; Wakayama, Teruhiko

2010-01-01

Nuclear transfer-derived ES (ntES) cell lines can be established from somatic cell nuclei with a relatively high success rate. Although ntES cells have been shown to be equivalent to ES cells, there are ethical objections concerning human cells, such as the use of fresh oocyte donation from young healthy woman. In contrast, the use of induced pluripotent stem (iPS) cells for cloning poses few ethical problems and is a relatively easy technique compared with nuclear transfer. Therefore, although there are several reports proposing the use of ntES cells as a model of regenerative medicine, the use of these cells in preliminary medical research is waning. However, in theory, 5 to 10 donor cells can establish one ntES cell line and, once established, these cells will propagate indefinitely. These cells can be used to generate cloned animals from ntES cell lines using a second round of NT. Even in infertile and "unclonable" strains of mice, we can generate offspring from somatic cells by combining cloning with ntES technology. Moreover, cloned offspring can be generated potentially even from the nuclei of dead bodies or freeze-dried cells via ntES cells, such as from an extinct frozen animal. Currently, only the ntES technology is available for this purpose, because all other techniques, including iPS cell derivation, require significant numbers of living donor cells. This review describes how to improve the efficiency of cloning, the establishment of clone-derived embryonic stem cells and further applications.

Improving salt marsh digital elevation model accuracy with full-waveform lidar and nonparametric predictive modeling

Science.gov (United States)

Rogers, Jeffrey N.; Parrish, Christopher E.; Ward, Larry G.; Burdick, David M.

2018-03-01

Salt marsh vegetation tends to increase vertical uncertainty in light detection and ranging (lidar) derived elevation data, often causing the data to become ineffective for analysis of topographic features governing tidal inundation or vegetation zonation. Previous attempts at improving lidar data collected in salt marsh environments range from simply computing and subtracting the global elevation bias to more complex methods such as computing vegetation-specific, constant correction factors. The vegetation specific corrections can be used along with an existing habitat map to apply separate corrections to different areas within a study site. It is hypothesized here that correcting salt marsh lidar data by applying location-specific, point-by-point corrections, which are computed from lidar waveform-derived features, tidal-datum based elevation, distance from shoreline and other lidar digital elevation model based variables, using nonparametric regression will produce better results. The methods were developed and tested using full-waveform lidar and ground truth for three marshes in Cape Cod, Massachusetts, U.S.A. Five different model algorithms for nonparametric regression were evaluated, with TreeNet's stochastic gradient boosting algorithm consistently producing better regression and classification results. Additionally, models were constructed to predict the vegetative zone (high marsh and low marsh). The predictive modeling methods used in this study estimated ground elevation with a mean bias of 0.00 m and a standard deviation of 0.07 m (0.07 m root mean square error). These methods appear very promising for correction of salt marsh lidar data and, importantly, do not require an existing habitat map, biomass measurements, or image based remote sensing data such as multi/hyperspectral imagery.

Modeling of scroll compressors - Improvements

Energy Technology Data Exchange (ETDEWEB)

Duprez, Marie-Eve; Dumont, Eric; Frere, Marc [Thermodynamics Department, Universite de Mons - Faculte Polytechnique, 31 bd Dolez, 7000 Mons (Belgium)

2010-06-15

This paper presents an improvement of the scroll compressors model previously published by. This improved model allows the calculation of refrigerant mass flow rate, power consumption and heat flow rate that would be released at the condenser of a heat pump equipped with the compressor, from the knowledge of operating conditions and parameters. Both basic and improved models have been tested on scroll compressors using different refrigerants. This study has been limited to compressors with a maximum electrical power of 14 kW and for evaporation temperatures ranging from -40 to 15 C and condensation temperatures from 10 to 75 C. The average discrepancies on mass flow rate, power consumption and heat flow rate are respectively 0.50%, 0.93% and 3.49%. Using a global parameter determination (based on several refrigerants data), this model can predict the behavior of a compressor with another fluid for which no manufacturer data are available. (author)

Derivation of inner magnetospheric electric field (UNH-IMEF model using Cluster data set

Directory of Open Access Journals (Sweden)

H. Matsui

2008-09-01

Full Text Available We derive an inner magnetospheric electric field (UNH-IMEF model at L=2–10 using primarily Cluster electric field data for more than 5 years between February 2001 and October 2006. This electric field data set is divided into several ranges of the interplanetary electric field (IEF values measured by ACE. As ring current simulations which require electric field as an input parameter are often performed at L=2–6.6, we have included statistical results from ground radars and low altitude satellites inside the perigee of Cluster in our data set (L~4. Electric potential patterns are derived from the average electric fields by solving an inverse problem. The electric potential pattern for small IEF values is probably affected by the ionospheric dynamo. The magnitudes of the electric field increase around the evening local time as IEF increases, presumably due to the sub-auroral polarization stream (SAPS. Another region with enhanced electric fields during large IEF periods is located around 9 MLT at L>8, which is possibly related to solar wind-magnetosphere coupling. Our potential patterns are consistent with those derived from self-consistent simulations. As the potential patterns can be interpolated/extrapolated to any discrete IEF value within measured ranges, we thus derive an empirical electric potential model. The performance of the model is evaluated by comparing the electric field derived from the model with original one measured by Cluster and mapped to the equator. The model is open to the public through our website.

Derivation of inner magnetospheric electric field (UNH-IMEF model using Cluster data set

Directory of Open Access Journals (Sweden)

H. Matsui

2008-09-01

Full Text Available We derive an inner magnetospheric electric field (UNH-IMEF model at L=2–10 using primarily Cluster electric field data for more than 5 years between February 2001 and October 2006. This electric field data set is divided into several ranges of the interplanetary electric field (IEF values measured by ACE. As ring current simulations which require electric field as an input parameter are often performed at L=2–6.6, we have included statistical results from ground radars and low altitude satellites inside the perigee of Cluster in our data set (L~4. Electric potential patterns are derived from the average electric fields by solving an inverse problem. The electric potential pattern for small IEF values is probably affected by the ionospheric dynamo. The magnitudes of the electric field increase around the evening local time as IEF increases, presumably due to the sub-auroral polarization stream (SAPS. Another region with enhanced electric fields during large IEF periods is located around 9 MLT at L>8, which is possibly related to solar wind-magnetosphere coupling. Our potential patterns are consistent with those derived from self-consistent simulations. As the potential patterns can be interpolated/extrapolated to any discrete IEF value within measured ranges, we thus derive an empirical electric potential model. The performance of the model is evaluated by comparing the electric field derived from the model with original one measured by Cluster and mapped to the equator. The model is open to the public through our website.

Patient-Derived Xenograft Models : An Emerging Platform for Translational Cancer Research

NARCIS (Netherlands)

Hidalgo, Manuel; Amant, Frederic; Biankin, Andrew V.; Budinska, Eva; Byrne, Annette T.; Caldas, Carlos; Clarke, Robert B.; de Jong, Steven; Jonkers, Jos; Maelandsmo, Gunhild Mari; Roman-Roman, Sergio; Seoane, Joan; Trusolino, Livio; Villanueva, Alberto

Recently, there has been an increasing interest in the development and characterization of patient-derived tumor xenograft (PDX) models for cancer research. PDX models mostly retain the principal histologic and genetic characteristics of their donor tumor and remain stable across passages. These

An extended car-following model considering the acceleration derivative in some typical traffic environments

Science.gov (United States)

Zhou, Tong; Chen, Dong; Liu, Weining

2018-03-01

Based on the full velocity difference and acceleration car-following model, an extended car-following model is proposed by considering the vehicle’s acceleration derivative. The stability condition is given by applying the control theory. Considering some typical traffic environments, the results of theoretical analysis and numerical simulation show the extended model has a more actual acceleration of string vehicles than that of the previous models in starting process, stopping process and sudden brake. Meanwhile, the traffic jams more easily occur when the coefficient of vehicle’s acceleration derivative increases, which is presented by space-time evolution. The results confirm that the vehicle’s acceleration derivative plays an important role in the traffic jamming transition and the evolution of traffic congestion.

Columnar metaplasia in a surgical mouse model of gastro-esophageal reflux disease is not derived from bone marrow-derived cell.

Science.gov (United States)

Aikou, Susumu; Aida, Junko; Takubo, Kaiyo; Yamagata, Yukinori; Seto, Yasuyuki; Kaminishi, Michio; Nomura, Sachiyo

2013-09-01

The incidence of esophageal adenocarcinoma has increased in the last 25 years. Columnar metaplasia in Barrett's mucosa is assumed to be a precancerous lesion for esophageal adenocarcinoma. However, the induction process of Barrett's mucosa is still unknown. To analyze the induction of esophageal columnar metaplasia, we established a mouse gastro-esophageal reflux disease (GERD) model with associated development of columnar metaplasia in the esophagus. C57BL/6 mice received side-to-side anastomosis of the esophagogastric junction with the jejunum, and mice were killed 10, 20, and 40 weeks after operation. To analyze the contribution of bone marrow-derived cells to columnar metaplasia in this surgical GERD model, some mice were transplanted with GFP-marked bone marrow after the operation. Seventy-three percent of the mice (16/22) showed thickened mucosa in esophagus and 41% of mice (9/22) developed columnar metaplasia 40 weeks after the operation with a mortality rate of 4%. Bone marrow-derived cells were not detected in columnar metaplastic epithelia. However, scattered epithelial cells in the thickened squamous epithelia in regions of esophagitis did show bone marrow derivation. The results demonstrate that reflux induced by esophago-jejunostomy in mice leads to the development of columnar metaplasia in the esophagus. However, bone marrow-derived cells do not contribute directly to columnar metaplasia in this mouse model. © 2013 Japanese Cancer Association.

Improving Estimated Optical Constants With MSTM and DDSCAT Modeling

Science.gov (United States)

Pitman, K. M.; Wolff, M. J.

2015-12-01

We present numerical experiments to determine quantitatively the effects of mineral particle clustering on Mars spacecraft spectral signatures and to improve upon the values of refractive indices (optical constants n, k) derived from Mars dust laboratory analog spectra such as those from RELAB and MRO CRISM libraries. Whereas spectral properties for Mars analog minerals and actual Mars soil are dominated by aggregates of particles smaller than the size of martian atmospheric dust, the analytic radiative transfer (RT) solutions used to interpret planetary surfaces assume that individual, well-separated particles dominate the spectral signature. Both in RT models and in the refractive index derivation methods that include analytic RT approximations, spheres are also over-used to represent nonspherical particles. Part of the motivation is that the integrated effect over randomly oriented particles on quantities such as single scattering albedo and phase function are relatively less than for single particles. However, we have seen in previous numerical experiments that when varying the shape and size of individual grains within a cluster, the phase function changes in both magnitude and slope, thus the "relatively less" effect is more significant than one might think. Here we examine the wavelength dependence of the forward scattering parameter with multisphere T-matrix (MSTM) and discrete dipole approximation (DDSCAT) codes that compute light scattering by layers of particles on planetary surfaces to see how albedo is affected and integrate our model results into refractive index calculations to remove uncertainties in approximations and parameters that can lower the accuracy of optical constants. By correcting the single scattering albedo and phase function terms in the refractive index determinations, our data will help to improve the understanding of Mars in identifying, mapping the distributions, and quantifying abundances for these minerals and will address long

Can assimilation of crowdsourced data in hydrological modelling improve flood prediction?

Science.gov (United States)

Mazzoleni, Maurizio; Verlaan, Martin; Alfonso, Leonardo; Monego, Martina; Norbiato, Daniele; Ferri, Miche; Solomatine, Dimitri P.

2017-02-01

Monitoring stations have been used for decades to properly measure hydrological variables and better predict floods. To this end, methods to incorporate these observations into mathematical water models have also been developed. Besides, in recent years, the continued technological advances, in combination with the growing inclusion of citizens in participatory processes related to water resources management, have encouraged the increase of citizen science projects around the globe. In turn, this has stimulated the spread of low-cost sensors to allow citizens to participate in the collection of hydrological data in a more distributed way than the classic static physical sensors do. However, two main disadvantages of such crowdsourced data are the irregular availability and variable accuracy from sensor to sensor, which makes them challenging to use in hydrological modelling. This study aims to demonstrate that streamflow data, derived from crowdsourced water level observations, can improve flood prediction if integrated in hydrological models. Two different hydrological models, applied to four case studies, are considered. Realistic (albeit synthetic) time series are used to represent crowdsourced data in all case studies. In this study, it is found that the data accuracies have much more influence on the model results than the irregular frequencies of data availability at which the streamflow data are assimilated. This study demonstrates that data collected by citizens, characterized by being asynchronous and inaccurate, can still complement traditional networks formed by few accurate, static sensors and improve the accuracy of flood forecasts.

VCE-003.2, a novel cannabigerol derivative, enhances neuronal progenitor cell survival and alleviates symptomatology in murine models of Huntington's disease.

Science.gov (United States)

Díaz-Alonso, Javier; Paraíso-Luna, Juan; Navarrete, Carmen; Del Río, Carmen; Cantarero, Irene; Palomares, Belén; Aguareles, José; Fernández-Ruiz, Javier; Bellido, María Luz; Pollastro, Federica; Appendino, Giovanni; Calzado, Marco A; Galve-Roperh, Ismael; Muñoz, Eduardo

2016-07-19

Cannabinoids have shown to exert neuroprotective actions in animal models by acting at different targets including canonical cannabinoid receptors and PPARγ. We previously showed that VCE-003, a cannabigerol (CBG) quinone derivative, is a novel neuroprotective and anti-inflammatory cannabinoid acting through PPARγ. We have now generated a non-thiophilic VCE-003 derivative named VCE-003.2 that preserves the ability to activate PPARγ and analyzed its neuroprotective activity. This compound exerted a prosurvival action in progenitor cells during neuronal differentiation, which was prevented by a PPARγ antagonist, without affecting neural progenitor cell proliferation. In addition, VCE-003.2 attenuated quinolinic acid (QA)-induced cell death and caspase-3 activation and also reduced mutant huntingtin aggregates in striatal cells. The neuroprotective profile of VCE-003.2 was analyzed using in vivo models of striatal neurodegeneration induced by QA and 3-nitropropionic acid (3NP) administration. VCE-003.2 prevented medium spiny DARPP32(+) neuronal loss in these Huntington's-like disease mice models improving motor deficits, reactive astrogliosis and microglial activation. In the 3NP model VCE-003.2 inhibited the upregulation of proinflammatory markers and improved antioxidant defenses in the brain. These data lead us to consider VCE-003.2 to have high potential for the treatment of Huntington's disease (HD) and other neurodegenerative diseases with neuroinflammatory traits.

An Improved Computing Method for 3D Mechanical Connectivity Rates Based on a Polyhedral Simulation Model of Discrete Fracture Network in Rock Masses

Science.gov (United States)

Li, Mingchao; Han, Shuai; Zhou, Sibao; Zhang, Ye

2018-06-01

Based on a 3D model of a discrete fracture network (DFN) in a rock mass, an improved projective method for computing the 3D mechanical connectivity rate was proposed. The Monte Carlo simulation method, 2D Poisson process and 3D geological modeling technique were integrated into a polyhedral DFN modeling approach, and the simulation results were verified by numerical tests and graphical inspection. Next, the traditional projective approach for calculating the rock mass connectivity rate was improved using the 3D DFN models by (1) using the polyhedral model to replace the Baecher disk model; (2) taking the real cross section of the rock mass, rather than a part of the cross section, as the test plane; and (3) dynamically searching the joint connectivity rates using different dip directions and dip angles at different elevations to calculate the maximum, minimum and average values of the joint connectivity at each elevation. In a case study, the improved method and traditional method were used to compute the mechanical connectivity rate of the slope of a dam abutment. The results of the two methods were further used to compute the cohesive force of the rock masses. Finally, a comparison showed that the cohesive force derived from the traditional method had a higher error, whereas the cohesive force derived from the improved method was consistent with the suggested values. According to the comparison, the effectivity and validity of the improved method were verified indirectly.

Brain-derived neurotrophic factor mediates cognitive improvements following acute exercise.

Science.gov (United States)

Borror, Andrew

2017-09-01

The mechanisms causing improved cognition following acute exercise are poorly understood. This article proposes that brain-derived neurotrophic factor (BDNF) is the main factor contributing to improved cognition following exercise. Additionally, it argues that cerebral blood flow (CBF) and oxidative stress explain the release of BDNF from cerebral endothelial cells. One way to test these hypotheses is to block endothelial function and measure the effect on BDNF levels and cognitive performance. The CBF and oxidative stress can also be examined in relationship to BDNF using a multiple linear regression. If these hypotheses are true, there would be a linear relationship between CBF+oxidative stress and BDNF levels as well as between BDNF levels and cognitive performance. The novelty of these hypotheses comes from the emphasis on the cerebral endothelium and the interplay between BDNF, CBF, and oxidative stress. If found to be valid, these hypotheses would draw attention to the cerebral endothelium and provide direction for future research regarding methods to optimize BDNF release and enhance cognition. Elucidating these mechanisms would provide direction for expediting recovery in clinical populations, such as stroke, and maintaining quality of life in the elderly. Copyright © 2017 Elsevier Ltd. All rights reserved.

An Improved Car-Following Model Accounting for Impact of Strong Wind

Directory of Open Access Journals (Sweden)

Dawei Liu

2017-01-01

Full Text Available In order to investigate the effect of strong wind on dynamic characteristic of traffic flow, an improved car-following model based on the full velocity difference model is developed in this paper. Wind force is introduced as the influence factor of car-following behavior. Among three components of wind force, lift force and side force are taken into account. The linear stability analysis is carried out and the stability condition of the newly developed model is derived. Numerical analysis is made to explore the effect of strong wind on spatial-time evolution of a small perturbation. The results show that the strong wind can significantly affect the stability of traffic flow. Driving safety in strong wind is also studied by comparing the lateral force under different wind speeds with the side friction of vehicles. Finally, the fuel consumption of vehicle in strong wind condition is explored and the results show that the fuel consumption decreased with the increase of wind speed.

A fractal derivative model for the characterization of anomalous diffusion in magnetic resonance imaging

Science.gov (United States)

Liang, Yingjie; Ye, Allen Q.; Chen, Wen; Gatto, Rodolfo G.; Colon-Perez, Luis; Mareci, Thomas H.; Magin, Richard L.

2016-10-01

Non-Gaussian (anomalous) diffusion is wide spread in biological tissues where its effects modulate chemical reactions and membrane transport. When viewed using magnetic resonance imaging (MRI), anomalous diffusion is characterized by a persistent or 'long tail' behavior in the decay of the diffusion signal. Recent MRI studies have used the fractional derivative to describe diffusion dynamics in normal and post-mortem tissue by connecting the order of the derivative with changes in tissue composition, structure and complexity. In this study we consider an alternative approach by introducing fractal time and space derivatives into Fick's second law of diffusion. This provides a more natural way to link sub-voxel tissue composition with the observed MRI diffusion signal decay following the application of a diffusion-sensitive pulse sequence. Unlike previous studies using fractional order derivatives, here the fractal derivative order is directly connected to the Hausdorff fractal dimension of the diffusion trajectory. The result is a simpler, computationally faster, and more direct way to incorporate tissue complexity and microstructure into the diffusional dynamics. Furthermore, the results are readily expressed in terms of spectral entropy, which provides a quantitative measure of the overall complexity of the heterogeneous and multi-scale structure of biological tissues. As an example, we apply this new model for the characterization of diffusion in fixed samples of the mouse brain. These results are compared with those obtained using the mono-exponential, the stretched exponential, the fractional derivative, and the diffusion kurtosis models. Overall, we find that the order of the fractal time derivative, the diffusion coefficient, and the spectral entropy are potential biomarkers to differentiate between the microstructure of white and gray matter. In addition, we note that the fractal derivative model has practical advantages over the existing models from the

Interaction of hematoporphyrin derivative, light, and ionizing radiation in a rat glioma model

International Nuclear Information System (INIS)

Kostron, H.; Swartz, M.R.; Miller, D.C.; Martuza, R.L.

1986-01-01

The effects of hematoporphyrin derivative, light, and cobalt 60 ( 60 Co) irradiation were studied in a rat glioma model using an in vivo and an in vitro clonogenic assay. There was no effect on tumor growth by visible light or by a single dose of 60 Co irradiation at 4 Gy or 8 Gy, whereas 16 Gy inhibited tumor growth to 40% versus the control. Hematoporphyrin derivative alone slightly stimulated growth (P less than 0.1). Light in the presence of 10 mg hematoporphyrin derivative/kg inhibited tumor growth to 32%. 60 Co irradiation in the presence of hematoporphyrin derivative produced a significant tumor growth inhibition (P less than 0.02). This growth inhibition was directly related to the concentration of hematoporphyrin derivative. The addition of 60 Co to light in the presence of hematoporphyrin derivative produced a greater growth inhibition than light or 60 Co irradiation alone. This effect was most pronounced when light was applied 30 minutes before 60 Co irradiation. Our experiments in a subcutaneous rat glioma model suggest a radiosensitizing effect of hematoporphyrin derivative. Furthermore, the photodynamic inactivation is enhanced by the addition of 60 Co irradiation. These findings may be of importance in planning new treatment modalities in malignant brain tumors

Application of bioethanol derived lignin for improving physico-mechanical properties of thermoset biocomposites.

Science.gov (United States)

Bajwa, Dilpreet S; Wang, Xinnan; Sitz, Evan; Loll, Tyler; Bhattacharjee, Sujal

2016-08-01

Lignin is the most abundant of renewable polymers next to cellulose with a global annual production of 70million tons, largely produced from pulping and second generation biofuel industries. Low value of industrial lignin makes it an attractive biomaterial for wide range of applications. The study investigated the application of wheat straw and corn stover based lignin derived from ethanol production for use in thermoset biocomposites. The biocomposite matrix constituted a two component low viscosity Araldite(®)LY 8601/Aradur(®) 8602 epoxy resin system and the lignin content varied from 0 to 25% by weight fraction. The analysis of the physical and mechanical properties of the biocomposites show bioethanol derived lignin can improve selective properties such as impact strength, and thermal stability without compromising the modulus and strength attributes. Copyright © 2016 Elsevier B.V. All rights reserved.

Gauge coupling unification in superstring derived standard-like models

International Nuclear Information System (INIS)

Faraggi, A.E.

1992-11-01

I discuss gauge coupling unification in a class of superstring standard-like models, which are derived in the free fermionic formulation. Recent calculations indicate that the superstring unification scale is at O(10 18 GeV) while the minimal supersymmetric standard model is consistent with LEP data if the unification scale is at O(10 16 )GeV. A generic feature of the superstring standard-like models is the appearance of extra color triplets (D,D), and electroweak doublets (l,l), in vector-like representations, beyond the supersymmetric standard model. I show that the gauge coupling unification at O(10 18 GeV) in the superstring standard-like models can be consistent with LEP data. I present an explicit standard-like model that can realize superstring gauge coupling unification. (author)

Improvement of density models of geological structures by fusion of gravity data and cosmic muon radiographies

Science.gov (United States)

Jourde, K.; Gibert, D.; Marteau, J.

2015-08-01

This paper examines how the resolution of small-scale geological density models is improved through the fusion of information provided by gravity measurements and density muon radiographies. Muon radiography aims at determining the density of geological bodies by measuring their screening effect on the natural flux of cosmic muons. Muon radiography essentially works like a medical X-ray scan and integrates density information along elongated narrow conical volumes. Gravity measurements are linked to density by a 3-D integration encompassing the whole studied domain. We establish the mathematical expressions of these integration formulas - called acquisition kernels - and derive the resolving kernels that are spatial filters relating the true unknown density structure to the density distribution actually recovered from the available data. The resolving kernel approach allows one to quantitatively describe the improvement of the resolution of the density models achieved by merging gravity data and muon radiographies. The method developed in this paper may be used to optimally design the geometry of the field measurements to be performed in order to obtain a given spatial resolution pattern of the density model to be constructed. The resolving kernels derived in the joined muon-gravimetry case indicate that gravity data are almost useless for constraining the density structure in regions sampled by more than two muon tomography acquisitions. Interestingly, the resolution in deeper regions not sampled by muon tomography is significantly improved by joining the two techniques. The method is illustrated with examples for the La Soufrière volcano of Guadeloupe.

Solutions of Cattaneo-Hristov model of elastic heat diffusion with Caputo-Fabrizio and Atangana-Baleanu fractional derivatives

Directory of Open Access Journals (Sweden)

Koca Ilknur

2017-01-01

Full Text Available Recently Hristov using the concept of a relaxation kernel with no singularity developed a new model of elastic heat diffusion equation based on the Caputo-Fabrizio fractional derivative as an extended version of Cattaneo model of heat diffusion equation. In the present article, we solve exactly the Cattaneo-Hristov model and extend it by the concept of a derivative with non-local and non-singular kernel by using the new Atangana-Baleanu derivative. The Cattaneo-Hristov model with the extended derivative is solved analytically with the Laplace transform, and numerically using the Crank-Nicholson scheme.

Improved Model for Predicting the Free Energy Contribution of Dinucleotide Bulges to RNA Duplex Stability.

Science.gov (United States)

Tomcho, Jeremy C; Tillman, Magdalena R; Znosko, Brent M

2015-09-01

Predicting the secondary structure of RNA is an intermediate in predicting RNA three-dimensional structure. Commonly, determining RNA secondary structure from sequence uses free energy minimization and nearest neighbor parameters. Current algorithms utilize a sequence-independent model to predict free energy contributions of dinucleotide bulges. To determine if a sequence-dependent model would be more accurate, short RNA duplexes containing dinucleotide bulges with different sequences and nearest neighbor combinations were optically melted to derive thermodynamic parameters. These data suggested energy contributions of dinucleotide bulges were sequence-dependent, and a sequence-dependent model was derived. This model assigns free energy penalties based on the identity of nucleotides in the bulge (3.06 kcal/mol for two purines, 2.93 kcal/mol for two pyrimidines, 2.71 kcal/mol for 5'-purine-pyrimidine-3', and 2.41 kcal/mol for 5'-pyrimidine-purine-3'). The predictive model also includes a 0.45 kcal/mol penalty for an A-U pair adjacent to the bulge and a -0.28 kcal/mol bonus for a G-U pair adjacent to the bulge. The new sequence-dependent model results in predicted values within, on average, 0.17 kcal/mol of experimental values, a significant improvement over the sequence-independent model. This model and new experimental values can be incorporated into algorithms that predict RNA stability and secondary structure from sequence.

Novel flurbiprofen derivatives with improved brain delivery: synthesis, in vitro and in vivo evaluations.

Science.gov (United States)

Zheng, Dan; Shuai, Xiao; Li, Yanping; Zhou, Peng; Gong, Tao; Sun, Xun; Zhang, Zhirong

2016-09-01

Tarenflurbil (R-flurbiprofen) was acknowledged as a promising candidate in Alzheimer's disease (AD) therapy. However, the Phase III study of tarenflurbil was extremely restricted by its poor delivery efficiency to the brain. To tackle this problem, the novel carriers for tarenflurbil, racemic flurbiprofen (FLU) derivatives (FLU-D1 and FLU-D2) modified by N,N-dimethylethanolamine-related structures were synthesized and characterized. These derivatives showed good safety level in vitro and they possessed much higher cellular uptake efficiency in brain endothelial cells than FLU did. More importantly, the uptake experiments suggested that they were internalized via active transport mechanisms. Biodistribution studies in rats also illustrated a remarkably enhanced accumulation of these derivatives in the brain. FLU-D2, the ester linkage form of these derivatives, achieved a higher brain-targeting efficiency. Its C max and AUC 0- t were enhanced by 12.09-fold and 4.61-fold, respectively compared with those of FLU. Additionally, it could be hydrolyzed by esterase in the brain to release the parent FLU, which might facilitate its therapeutic effect. These in vitro and in vivo results highlighted the improvement of the brain-targeted delivery of FLU by making use of N,N-dimethylethanolamine ligand, with which an active transport mechanism was involved.

CHAOS-2-a geomagnetic field model derived from one decade of continuous satellite data

DEFF Research Database (Denmark)

Olsen, Nils; Mandea, M.; Sabaka, T.J.

2009-01-01

We have derived a model of the near-Earth's magnetic field using more than 10 yr of high-precision geomagnetic measurements from the three satellites Orsted, CHAMP and SAC-C. This model is an update of the two previous models, CHAOS (Olsen et al. 2006) and xCHAOS (Olsen & Mandea 2008). Data...... by minimizing the second time derivative of the squared magnetic field intensity at the core-mantle boundary. The CHAOS-2 model describes rapid time changes, as monitored by the ground magnetic observatories, much better than its predecessors....

Modeling extracellular electrical stimulation: I. Derivation and interpretation of neurite equations.

Science.gov (United States)

Meffin, Hamish; Tahayori, Bahman; Grayden, David B; Burkitt, Anthony N

2012-12-01

Neuroprosthetic devices, such as cochlear and retinal implants, work by directly stimulating neurons with extracellular electrodes. This is commonly modeled using the cable equation with an applied extracellular voltage. In this paper a framework for modeling extracellular electrical stimulation is presented. To this end, a cylindrical neurite with confined extracellular space in the subthreshold regime is modeled in three-dimensional space. Through cylindrical harmonic expansion of Laplace's equation, we derive the spatio-temporal equations governing different modes of stimulation, referred to as longitudinal and transverse modes, under types of boundary conditions. The longitudinal mode is described by the well-known cable equation, however, the transverse modes are described by a novel ordinary differential equation. For the longitudinal mode, we find that different electrotonic length constants apply under the two different boundary conditions. Equations connecting current density to voltage boundary conditions are derived that are used to calculate the trans-impedance of the neurite-plus-thin-extracellular-sheath. A detailed explanation on depolarization mechanisms and the dominant current pathway under different modes of stimulation is provided. The analytic results derived here enable the estimation of a neurite's membrane potential under extracellular stimulation, hence bypassing the heavy computational cost of using numerical methods.

Yukawa couplings in Superstring derived Standard-like models

International Nuclear Information System (INIS)

Faraggi, A.E.

1991-01-01

I discuss Yukawa couplings in Standard-like models which are derived from Superstring in the free fermionic formulation. I introduce new notation for the construction of these models. I show how choice of boundary conditions selects a trilevel Yukawa coupling either for +2/3 charged quark or for -1/3 charged quark. I prove this selection rule. I make the conjecture that in this class of standard-like models a possible connection may exist between the requirements of F and D flatness at the string level and the heaviness of the top quark relative to lighter quarks and leptons. I discuss how the choice of boundary conditions determines the non vanishing mass terms for quartic order terms. I discuss the implication on the mass of the top quark. (author)

Derivation of a well-posed and multidimensional drift-flux model for boiling flows

International Nuclear Information System (INIS)

Gregoire, O.; Martin, M.

2005-01-01

In this note, we derive a multidimensional drift-flux model for boiling flows. Within this framework, the distribution parameter is no longer a scalar but a tensor that might account for the medium anisotropy and the flow regime. A new model for the drift-velocity vector is also derived. It intrinsically takes into account the effect of the friction pressure loss on the buoyancy force. On the other hand, we show that most drift-flux models might exhibit a singularity for large void fraction. In order to avoid this singularity, a remedy based on a simplified three field approach is proposed. (authors)

Impact of Scattering Model on Disdrometer Derived Attenuation Scaling

Science.gov (United States)

Zemba, Michael; Luini, Lorenzo; Nessel, James; Riva, Carlo (Compiler)

2016-01-01

NASA Glenn Research Center (GRC), the Air Force Research Laboratory (AFRL), and the Politecnico di Milano (POLIMI) are currently entering the third year of a joint propagation study in Milan, Italy utilizing the 20 and 40 GHz beacons of the Alphasat TDP5 Aldo Paraboni scientific payload. The Ka- and Q-band beacon receivers were installed at the POLIMI campus in June of 2014 and provide direct measurements of signal attenuation at each frequency. Collocated weather instrumentation provides concurrent measurement of atmospheric conditions at the receiver; included among these weather instruments is a Thies Clima Laser Precipitation Monitor (optical disdrometer) which records droplet size distributions (DSD) and droplet velocity distributions (DVD) during precipitation events. This information can be used to derive the specific attenuation at frequencies of interest and thereby scale measured attenuation data from one frequency to another. Given the ability to both predict the 40 GHz attenuation from the disdrometer and the 20 GHz timeseries as well as to directly measure the 40 GHz attenuation with the beacon receiver, the Milan terminal is uniquely able to assess these scaling techniques and refine the methods used to infer attenuation from disdrometer data.In order to derive specific attenuation from the DSD, the forward scattering coefficient must be computed. In previous work, this has been done using the Mie scattering model, however, this assumes a spherical droplet shape. The primary goal of this analysis is to assess the impact of the scattering model and droplet shape on disdrometer derived attenuation predictions by comparing the use of the Mie scattering model to the use of the T-matrix method, which does not assume a spherical droplet. In particular, this paper will investigate the impact of these two scattering approaches on the error of the resulting predictions as well as on the relationship between prediction error and rain rate.

Computational optogenetics: empirically-derived voltage- and light-sensitive channelrhodopsin-2 model.

Directory of Open Access Journals (Sweden)

John C Williams

Full Text Available Channelrhodospin-2 (ChR2, a light-sensitive ion channel, and its variants have emerged as new excitatory optogenetic tools not only in neuroscience, but also in other areas, including cardiac electrophysiology. An accurate quantitative model of ChR2 is necessary for in silico prediction of the response to optical stimulation in realistic tissue/organ settings. Such a model can guide the rational design of new ion channel functionality tailored to different cell types/tissues. Focusing on one of the most widely used ChR2 mutants (H134R with enhanced current, we collected a comprehensive experimental data set of the response of this ion channel to different irradiances and voltages, and used these data to develop a model of ChR2 with empirically-derived voltage- and irradiance- dependence, where parameters were fine-tuned via simulated annealing optimization. This ChR2 model offers: 1 accurate inward rectification in the current-voltage response across irradiances; 2 empirically-derived voltage- and light-dependent kinetics (activation, deactivation and recovery from inactivation; and 3 accurate amplitude and morphology of the response across voltage and irradiance settings. Temperature-scaling factors (Q10 were derived and model kinetics was adjusted to physiological temperatures. Using optical action potential clamp, we experimentally validated model-predicted ChR2 behavior in guinea pig ventricular myocytes. The model was then incorporated in a variety of cardiac myocytes, including human ventricular, atrial and Purkinje cell models. We demonstrate the ability of ChR2 to trigger action potentials in human cardiomyocytes at relatively low light levels, as well as the differential response of these cells to light, with the Purkinje cells being most easily excitable and ventricular cells requiring the highest irradiance at all pulse durations. This new experimentally-validated ChR2 model will facilitate virtual experimentation in neural and

The eHealth Enhanced Chronic Care Model: a theory derivation approach.

Science.gov (United States)

Gee, Perry M; Greenwood, Deborah A; Paterniti, Debora A; Ward, Deborah; Miller, Lisa M Soederberg

2015-04-01

Chronic illnesses are significant to individuals and costly to society. When systematically implemented, the well-established and tested Chronic Care Model (CCM) is shown to improve health outcomes for people with chronic conditions. Since the development of the original CCM, tremendous information management, communication, and technology advancements have been established. An opportunity exists to improve the time-honored CCM with clinically efficacious eHealth tools. The first goal of this paper was to review research on eHealth tools that support self-management of chronic disease using the CCM. The second goal was to present a revised model, the eHealth Enhanced Chronic Care Model (eCCM), to show how eHealth tools can be used to increase efficiency of how patients manage their own chronic illnesses. Using Theory Derivation processes, we identified a "parent theory", the Chronic Care Model, and conducted a thorough review of the literature using CINAHL, Medline, OVID, EMBASE PsychINFO, Science Direct, as well as government reports, industry reports, legislation using search terms "CCM or Chronic Care Model" AND "eHealth" or the specific identified components of eHealth. Additionally, "Chronic Illness Self-management support" AND "Technology" AND several identified eHealth tools were also used as search terms. We then used a review of the literature and specific components of the CCM to create the eCCM. We identified 260 papers at the intersection of technology, chronic disease self-management support, the CCM, and eHealth and organized a high-quality subset (n=95) using the components of CCM, self-management support, delivery system design, clinical decision support, and clinical information systems. In general, results showed that eHealth tools make important contributions to chronic care and the CCM but that the model requires modification in several key areas. Specifically, (1) eHealth education is critical for self-care, (2) eHealth support needs to be

Remyelination Is Correlated with Regulatory T Cell Induction Following Human Embryoid Body-Derived Neural Precursor Cell Transplantation in a Viral Model of Multiple Sclerosis.

Directory of Open Access Journals (Sweden)

Warren C Plaisted

Full Text Available We have recently described sustained clinical recovery associated with dampened neuroinflammation and remyelination following transplantation of neural precursor cells (NPCs derived from human embryonic stem cells (hESCs in a viral model of the human demyelinating disease multiple sclerosis. The hNPCs used in that study were derived by a novel direct differentiation method (direct differentiation, DD-NPCs that resulted in a unique gene expression pattern when compared to hNPCs derived by conventional methods. Since the therapeutic potential of human NPCs may differ greatly depending on the method of derivation and culture, we wanted to determine whether NPCs differentiated using conventional methods would be similarly effective in improving clinical outcome under neuroinflammatory demyelinating conditions. For the current study, we utilized hNPCs differentiated from a human induced pluripotent cell line via an embryoid body intermediate stage (EB-NPCs. Intraspinal transplantation of EB-NPCs into mice infected with the neurotropic JHM strain of mouse hepatitis virus (JHMV resulted in decreased accumulation of CD4+ T cells in the central nervous system that was concomitant with reduced demyelination at the site of injection. Dampened neuroinflammation and remyelination was correlated with a transient increase in CD4+FOXP3+ regulatory T cells (Tregs concentrated within the peripheral lymphatics. However, compared to our earlier study, pathological improvements were modest and did not result in significant clinical recovery. We conclude that the genetic signature of NPCs is critical to their effectiveness in this model of viral-induced neurologic disease. These comparisons will be useful for understanding what factors are critical for the sustained clinical improvement.

Modeling Ignition of a Heptane Isomer: Improved Thermodynamics, Reaction Pathways, Kinetic, and Rate Rule Optimizations for 2-Methylhexane

KAUST Repository

Mohamed, Samah; Cai, Liming; Khaled, Fathi; Banyon, Colin; Wang, Zhandong; Rachidi, Mariam El; Pitsch, Heinz; Curran, Henry J.; Farooq, Aamir; Sarathy, Mani

2016-01-01

Accurate chemical kinetic combustion models of lightly branched alkanes (e.g., 2-methylalkanes) are important to investigate the combustion behavior of real fuels. Improving the fidelity of existing kinetic models is a necessity, as new experiments and advanced theories show inaccuracies in certain portions of the models. This study focuses on updating thermodynamic data and the kinetic reaction mechanism for a gasoline surrogate component, 2-methylhexane, based on recently published thermodynamic group values and rate rules derived from quantum calculations and experiments. Alternative pathways for the isomerization of peroxy-alkylhydroperoxide (OOQOOH) radicals are also investigated. The effects of these updates are compared against new high-pressure shock tube and rapid compression machine ignition delay measurements. It is shown that rate constant modifications are required to improve agreement between kinetic modeling simulations and experimental data. We further demonstrate the ability to optimize the kinetic model using both manual and automated techniques for rate parameter tunings to improve agreement with the measured ignition delay time data. Finally, additional low temperature chain branching reaction pathways are shown to improve the model’s performance. The present approach to model development provides better performance across extended operating conditions while also strengthening the fundamental basis of the model.

Modeling Ignition of a Heptane Isomer: Improved Thermodynamics, Reaction Pathways, Kinetic, and Rate Rule Optimizations for 2-Methylhexane

KAUST Repository

Mohamed, Samah

2016-03-21

Accurate chemical kinetic combustion models of lightly branched alkanes (e.g., 2-methylalkanes) are important to investigate the combustion behavior of real fuels. Improving the fidelity of existing kinetic models is a necessity, as new experiments and advanced theories show inaccuracies in certain portions of the models. This study focuses on updating thermodynamic data and the kinetic reaction mechanism for a gasoline surrogate component, 2-methylhexane, based on recently published thermodynamic group values and rate rules derived from quantum calculations and experiments. Alternative pathways for the isomerization of peroxy-alkylhydroperoxide (OOQOOH) radicals are also investigated. The effects of these updates are compared against new high-pressure shock tube and rapid compression machine ignition delay measurements. It is shown that rate constant modifications are required to improve agreement between kinetic modeling simulations and experimental data. We further demonstrate the ability to optimize the kinetic model using both manual and automated techniques for rate parameter tunings to improve agreement with the measured ignition delay time data. Finally, additional low temperature chain branching reaction pathways are shown to improve the model’s performance. The present approach to model development provides better performance across extended operating conditions while also strengthening the fundamental basis of the model.

Improved TOPSIS decision model for NPP emergencies

International Nuclear Information System (INIS)

Zhang Jin; Liu Feng; Huang Lian

2011-01-01

In this paper,an improved decision model is developed for its use as a tool to respond to emergencies at nuclear power plants. Given the complexity of multi-attribute emergency decision-making on nuclear accident, the improved TOPSIS method is used to build a decision-making model that integrates subjective weight and objective weight of each evaluation index. A comparison between the results of this new model and two traditional methods of fuzzy hierarchy analysis method and weighted analysis method demonstrates that the improved TOPSIS model has a better evaluation effect. (authors)

The discussion of descriptors for the QSAR model and molecular dynamics simulation of benzimidazole derivatives as corrosion inhibitors

International Nuclear Information System (INIS)

Li, Lu; Zhang, Xiuhui; Gong, Shida; Zhao, Hongxia; Bai, Yang; Li, Qianshu; Ji, Lin

2015-01-01

Graphical abstract: - Highlights: • Aromaticity is used as a descriptor in QSAR model to describe corrosion inhibition. • Improved calculation of I and A is correlated well with inhibition efficiencies. • Binding energies were calculated using a realistic corrosion environment. • Nonlinear QSAR model was built by support vector machine with radial basis function. • Six designed benzimidazole molecules are predicted with high inhibition efficiencies. - Abstract: The corrosion inhibition performances of 20 protonated benzimidazole derivatives were studied using theoretical methods. Nuclear Independent Chemical Shift (NICS), the measurement of aromaticity, demonstrated good correlation with inhibition efficiencies and was used as a descriptor. Binding energies were calculated on the basis of molecular dynamics simulations using a realistic corrosive environment. Some improved descriptors correlate well with experimental inhibition efficiencies. A reliable nonlinear quantitative structure–activity relationship model was constructed by a support vector machine approach. The correlation coefficient and root-mean-square error were 0.96 and 6.79%, respectively. Additionally, six new benzimidazole molecules were designed, and their inhibition efficiencies were predicted.

An improved interfacial bonding model for material interface modeling

Science.gov (United States)

Lin, Liqiang; Wang, Xiaodu; Zeng, Xiaowei

2016-01-01

An improved interfacial bonding model was proposed from potential function point of view to investigate interfacial interactions in polycrystalline materials. It characterizes both attractive and repulsive interfacial interactions and can be applied to model different material interfaces. The path dependence of work-of-separation study indicates that the transformation of separation work is smooth in normal and tangential direction and the proposed model guarantees the consistency of the cohesive constitutive model. The improved interfacial bonding model was verified through a simple compression test in a standard hexagonal structure. The error between analytical solutions and numerical results from the proposed model is reasonable in linear elastic region. Ultimately, we investigated the mechanical behavior of extrafibrillar matrix in bone and the simulation results agreed well with experimental observations of bone fracture. PMID:28584343

Gravity model improvement investigation. [improved gravity model for determination of ocean geoid

Science.gov (United States)

Siry, J. W.; Kahn, W. D.; Bryan, J. W.; Vonbun, F. F.

1973-01-01

This investigation was undertaken to improve the gravity model and hence the ocean geoid. A specific objective is the determination of the gravity field and geoid with a space resolution of approximately 5 deg and a height resolution of the order of five meters. The concept of the investigation is to utilize both GEOS-C altimeter and satellite-to-satellite tracking data to achieve the gravity model improvement. It is also planned to determine the geoid in selected regions with a space resolution of about a degree and a height resolution of the order of a meter or two. The short term objectives include the study of the gravity field in the GEOS-C calibration area outlined by Goddard, Bermuda, Antigua, and Cape Kennedy, and also in the eastern Pacific area which is viewed by ATS-F.

Impacts of supersymmetric higher derivative terms on inflation models in supergravity

International Nuclear Information System (INIS)

Aoki, Shuntaro; Yamada, Yusuke

2015-01-01

We show the effects of supersymmetric higher derivative terms on inflation models in supergravity. The results show that such terms generically modify the effective kinetic coefficient of the inflaton during inflation if the cut off scale of the higher derivative operators is sufficiently small. In such a case, the η-problem in supergravity does not occur, and we find that the effective potential of the inflaton generically becomes a power type potential with a power smaller than two

Bone marrow-derived mesenchymal stem cells influence early tendon-healing in a rabbit achilles tendon model.

Science.gov (United States)

Chong, Alphonsus K S; Ang, Abel D; Goh, James C H; Hui, James H P; Lim, Aymeric Y T; Lee, Eng Hin; Lim, Beng Hai

2007-01-01

A repaired tendon needs to be protected for weeks until it has accrued enough strength to handle physiological loads. Tissue-engineering techniques have shown promise in the treatment of tendon and ligament defects. The present study tested the hypothesis that bone marrow-derived mesenchymal stem cells can accelerate tendon-healing after primary repair of a tendon injury in a rabbit model. Fifty-seven New Zealand White rabbits were used as the experimental animals, and seven others were used as the source of bone marrow-derived mesenchymal stem cells. The injury model was a sharp complete transection through the midsubstance of the Achilles tendon. The transected tendon was immediately repaired with use of a modified Kessler suture and a running epitendinous suture. Both limbs were used, and each side was randomized to receive either bone marrow-derived mesenchymal stem cells in a fibrin carrier or fibrin carrier alone (control). Postoperatively, the rabbits were not immobilized. Specimens were harvested at one, three, six, and twelve weeks for analysis, which included evaluation of gross morphology (sixty-two specimens), cell tracing (twelve specimens), histological assessment (forty specimens), immunohistochemistry studies (thirty specimens), morphometric analysis (forty specimens), and mechanical testing (sixty-two specimens). There were no differences between the two groups with regard to the gross morphology of the tendons. The fibrin had degraded by three weeks. Cell tracing showed that labeled bone marrow-derived mesenchymal stem cells remained viable and present in the intratendinous region for at least six weeks, becoming more diffuse at later time-periods. At three weeks, collagen fibers appeared more organized and there were better morphometric nuclear parameters in the treatment group (p tendon repair can improve histological and biomechanical parameters in the early stages of tendon-healing.

A Theory-Based Model for Understanding Faculty Intention to Use Students Ratings to Improve Teaching in a Health Sciences Institution in Puerto Rico

Science.gov (United States)

Collazo, Andrés A.

2018-01-01

A model derived from the theory of planned behavior was empirically assessed for understanding faculty intention to use student ratings for teaching improvement. A sample of 175 professors participated in the study. The model was statistically significant and had a very large explanatory power. Instrumental attitude, affective attitude, perceived…

Spatially Explicit Estimation of Optimal Light Use Efficiency for Improved Satellite Data Driven Ecosystem Productivity Modeling

Science.gov (United States)

Madani, N.; Kimball, J. S.; Running, S. W.

2014-12-01

Remote sensing based light use efficiency (LUE) models, including the MODIS (MODerate resolution Imaging Spectroradiometer) MOD17 algorithm are commonly used for regional estimation and monitoring of vegetation gross primary production (GPP) and photosynthetic carbon (CO2) uptake. A common model assumption is that plants in a biome matrix operate at their photosynthetic capacity under optimal climatic conditions. A prescribed biome maximum light use efficiency parameter defines the maximum photosynthetic carbon conversion rate under prevailing climate conditions and is a large source of model uncertainty. Here, we used tower (FLUXNET) eddy covariance measurement based carbon flux data for estimating optimal LUE (LUEopt) over a North American domain. LUEopt was first estimated using tower observed daily carbon fluxes, meteorology and satellite (MODIS) observed fraction of photosynthetically active radiation (FPAR). LUEopt was then spatially interpolated over the domain using empirical models derived from independent geospatial data including global plant traits, surface soil moisture, terrain aspect, land cover type and percent tree cover. The derived LUEopt maps were then used as primary inputs to the MOD17 LUE algorithm for regional GPP estimation; these results were evaluated against tower observations and alternate MOD17 GPP estimates determined using Biome-specific LUEopt constants. Estimated LUEopt shows large spatial variability within and among different land cover classes indicated from a sparse North American tower network. Leaf nitrogen content and soil moisture are two important factors explaining LUEopt spatial variability. GPP estimated from spatially explicit LUEopt inputs shows significantly improved model accuracy against independent tower observations (R2 = 0.76; Mean RMSE plant trait information can explain spatial heterogeneity in LUEopt, leading to improved GPP estimates from satellite based LUE models.

Improvements of Spiers model for compaction creep of crushed rock salt

International Nuclear Information System (INIS)

Poley, A.D.

1996-10-01

This report describes a number of improvements to the existing model for the process of compaction creep of rock salt developed by Spiers and co-workers. The process of compaction creep determines the behaviour of the seals of crushed rock salt, the last engineered barriers of a repository in rock salt for (radioactive) wastes. In Chapter 2 the derivation of the original model of Spiers and co-workers is followed except for some simplifying approximations. A comparison of the model results is made with experimental data and a number of model adjustments are suggested. In Chapter 3 one of these suggested model adjustments is explored, and an alternative model is developed. The results obtained with this model compare favourably with the experimental data without the use of adjustable shape functions as for the original model. Preliminary investigations of the impact of the new model on estimated releases to the geosphere of radionuclides form a repository in rock salt revealed striking differences: with the new model the compaction of the rock salt seals was so rapid that no releases could occur. The striking differences between the results - in terms of releases form a rock salt repository to the geosphere after groundwater intrusion - obtained using the two models clearly indicate the need for further experimental research into the end-compaction behaviour of rock salt backfill. (orig.)

European-wide simulations of croplands using an improved terrestrial biosphere model: Phenology and productivity

Science.gov (United States)

Smith, P. C.; de Noblet-Ducoudré, N.; Ciais, P.; Peylin, P.; Viovy, N.; Meurdesoif, Y.; Bondeau, A.

2010-03-01

Aiming at producing improved estimates of carbon source/sink spatial and interannual patterns across Europe (35% croplands), this work combines the terrestrial biosphere model Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE), for vegetation productivity, water balance, and soil carbon dynamics, and the generic crop model Simulateur Multidisciplinaire pour les Cultures Standard (STICS), for phenology, irrigation, nitrogen balance, and harvest. The ORCHIDEE-STICS model, relying on three plant functional types for the representation of temperate agriculture, is evaluated over the last few decades at various spatial and temporal resolutions. The simulated leaf area index seasonal cycle is largely improved relative to the original ORCHIDEE simulating grasslands, and compares favorably with remote-sensing observations (correlation doubles over Europe). Crop yield is derived from annual net primary productivity and compared with wheat and grain maize harvest data for five European countries. Discrepancies between 30 year mean simulated and reported yields are large in Mediterranean countries. Interannual variability amplitude expressed relative to the mean is reduced toward the observed variability (≈10%) when using ORCHIDEE-STICS. Overall, this study highlights the importance of accounting for the specific phenologies of crops sown both in winter and in spring and for irrigation applied to spring crops in regional/global models of the terrestrial carbon cycle. Limitations suggest to account for temporal and spatial variability in agricultural practices for further simulation improvement.

Covariance matrices for nuclear cross sections derived from nuclear model calculations

International Nuclear Information System (INIS)

Smith, D. L.

2005-01-01

The growing need for covariance information to accompany the evaluated cross section data libraries utilized in contemporary nuclear applications is spurring the development of new methods to provide this information. Many of the current general purpose libraries of evaluated nuclear data used in applications are derived either almost entirely from nuclear model calculations or from nuclear model calculations benchmarked by available experimental data. Consequently, a consistent method for generating covariance information under these circumstances is required. This report discusses a new approach to producing covariance matrices for cross sections calculated using nuclear models. The present method involves establishing uncertainty information for the underlying parameters of nuclear models used in the calculations and then propagating these uncertainties through to the derived cross sections and related nuclear quantities by means of a Monte Carlo technique rather than the more conventional matrix error propagation approach used in some alternative methods. The formalism to be used in such analyses is discussed in this report along with various issues and caveats that need to be considered in order to proceed with a practical implementation of the methodology

Testing an empirically derived mental health training model featuring small groups, distributed practice and patient discussion.

Science.gov (United States)

Murrihy, Rachael C; Byrne, Mitchell K; Gonsalvez, Craig J

2009-02-01

Internationally, family doctors seeking to enhance their skills in evidence-based mental health treatment are attending brief training workshops, despite clear evidence in the literature that short-term, massed formats are not likely to improve skills in this complex area. Reviews of the educational literature suggest that an optimal model of training would incorporate distributed practice techniques; repeated practice over a lengthy time period, small-group interactive learning, mentoring relationships, skills-based training and an ongoing discussion of actual patients. This study investigates the potential role of group-based training incorporating multiple aspects of good pedagogy for training doctors in basic competencies in brief cognitive behaviour therapy (BCBT). Six groups of family doctors (n = 32) completed eight 2-hour sessions of BCBT group training over a 6-month period. A baseline control design was utilised with pre- and post-training measures of doctors' BCBT skills, knowledge and engagement in BCBT treatment. Family doctors' knowledge, skills in and actual use of BCBT with patients improved significantly over the course of training compared with the control period. This research demonstrates preliminary support for the efficacy of an empirically derived group training model for family doctors. Brief CBT group-based training could prove to be an effective and viable model for future doctor training.

Formal derivation of a 6 equation macro scale model for two-phase flows - link with the 4 equation macro scale model implemented in Flica 4; Etablissement formel d'un modele diphasique macroscopique a 6 equations - lien avec le modele macroscopique a 4 equations flica 4

Energy Technology Data Exchange (ETDEWEB)

Gregoire, O

2008-07-01

In order to simulate nuclear reactor cores, we presently use the 4 equation model implemented within FLICA4 code. This model is complemented with 2 algebraic closures for thermal disequilibrium and relative velocity between phases. Using such closures, means an 'a priori' knowledge of flows calculated in order to ensure that modelling assumptions apply. In order to improve the degree of universality to our macroscopic modelling, we propose in the report to derive a more general 6 equation model (balance equations for mass, momentum and enthalpy for each phase) for 2-phase flows. We apply the up-scaling procedure (Whitaker, 1999) classically used in porous media analysis to the statistically averaged equations (Aniel-Buchheit et al., 2003). By doing this, we apply the double-averaging procedure (Pedras and De Lemos, 2001 and Pinson et al. 2006): statistical and spatial averages. Then, using weighted averages (analogous to Favre's average) we extend the spatial averaging concept to variable density and 2-phase flows. This approach allows the global recovering of the structure of the systems of equations implemented in industrial codes. Supplementary contributions, such as dispersion, are also highlighted. Mechanical and thermal exchanges between solids and fluid are formally derived. Then, thanks to realistic simplifying assumptions, we show how it is possible to derive the original 4 equation model from the full 6 equation model. (author)

A statistical model for deriving probability distributions of contamination for accidental releases

International Nuclear Information System (INIS)

ApSimon, H.M.; Davison, A.C.

1986-01-01

Results generated from a detailed long-range transport model, MESOS, simulating dispersal of a large number of hypothetical releases of radionuclides in a variety of meteorological situations over Western Europe have been used to derive a simpler statistical model, MESOSTAT. This model may be used to generate probability distributions of different levels of contamination at a receptor point 100-1000 km or so from the source (for example, across a frontier in another country) without considering individual release and dispersal scenarios. The model is embodied in a series of equations involving parameters which are determined from such factors as distance between source and receptor, nuclide decay and deposition characteristics, release duration, and geostrophic windrose at the source. Suitable geostrophic windrose data have been derived for source locations covering Western Europe. Special attention has been paid to the relatively improbable extreme values of contamination at the top end of the distribution. The MESOSTAT model and its development are described, with illustrations of its use and comparison with the original more detailed modelling techniques. (author)

Modeling of a three-phase reactor for bitumen-derived gas oil hydrotreating

International Nuclear Information System (INIS)

Chacon, R.; Canale, A.; Bouza, A.; Sanchez, Y.

2012-01-01

A three-phase reactor model for describing the hydrotreating reactions of bitumen-derived gas oil was developed. The model incorporates the mass-transfer resistance at the gas-liquid and liquid-solid interfaces and a kinetic rate expression based on a Langmuir-Hinshelwood-type model. We derived three correlations for determining the solubility of hydrogen (H 2 ), hydrogen sulfide (H 2 S) and ammonia (NH 3 ) in hydrocarbon mixtures and the calculation of the catalyst effectiveness factor was included. Experimental data taken from the literature were used to determine the kinetic parameters (stoichiometric coefficients, reaction orders, reaction rate and adsorption constants for hydrodesulfuration (HDS) and hydrodenitrogenation (HDN)) and to validate the model under various operating conditions. Finally, we studied the effect of operating conditions such as pressure, temperature, LHSV, H 2 /feed ratio and the inhibiting effect of H 2 S on HDS and NH 3 on HDN. (author)

Finite element analysis of an atomistically derived cohesive model for brittle fracture

International Nuclear Information System (INIS)

Lloyd, J T; McDowell, D L; Zimmerman, J A; Jones, R E; Zhou, X W

2011-01-01

In order to apply information from molecular dynamics (MD) simulations in problems governed by engineering length and time scales, a coarse graining methodology must be used. In previous work by Zhou et al (2009 Acta Mater. 57 4671–86), a traction-separation cohesive model was developed using results from MD simulations with atomistic-to-continuum measures of stress and displacement. Here, we implement this cohesive model within a combined finite element/cohesive surface element framework (referred to as a finite element approach or FEA), and examine the ability for the atomistically informed FEA to directly reproduce results from MD. We find that FEA shows close agreement of both stress and crack opening displacement profiles at the cohesive interface, although some differences do exist that can be attributed to the stochastic nature of finite temperature MD. The FEA methodology is then used to study slower loading rates that are computationally expensive for MD. We find that the crack growth process initially exhibits a rate-independent relationship between crack length and boundary displacement, followed by a rate-dependent regime where, at a given amount of boundary displacement, a lower applied strain rate produces a longer crack length. Our method is also extended to larger length scales by simulating a compact tension fracture-mechanics specimen with sub-micrometer dimensions. Such a simulation shows a computational speedup of approximately four orders of magnitude over conventional atomistic simulation, while exhibiting the expected fracture-mechanics response. Finally, differences between FEA and MD are explored with respect to ensemble and temperature effects in MD, and their impact on the cohesive model and crack growth behavior. These results enable us to make several recommendations to improve the methodology used to derive cohesive laws from MD simulations. In light of this work, which has critical implications for efforts to derive continuum laws

Aspects of the derivative coupling model in four dimensions

International Nuclear Information System (INIS)

Aste, Andreas

2014-01-01

A concise discussion of a 3 + 1-dimensional derivative coupling model, in which a massive Dirac field couples to the four-gradient of a massless scalar field, is given in order to elucidate the role of different concepts in quantum field theory like the regularization of quantum fields as operator-valued distributions, correlation distributions, locality, causality, and field operator gauge transformations. (orig.)

Aspects of the derivative coupling model in four dimensions

Energy Technology Data Exchange (ETDEWEB)

Aste, Andreas [University of Basel, Department of Physics, Basel (Switzerland); Paul Scherrer Institute, Villigen (Switzerland)

2014-01-15

A concise discussion of a 3 + 1-dimensional derivative coupling model, in which a massive Dirac field couples to the four-gradient of a massless scalar field, is given in order to elucidate the role of different concepts in quantum field theory like the regularization of quantum fields as operator-valued distributions, correlation distributions, locality, causality, and field operator gauge transformations. (orig.)

Re-examining data-intensive surface water models with high-resolution topography derived from unmanned aerial system photogrammetry

Science.gov (United States)

Pai, H.; Tyler, S.

2017-12-01

Small, unmanned aerial systems (sUAS) are quickly becoming a cost-effective and easily deployable tool for high spatial resolution environmental sensing. Land surface studies from sUAS imagery have largely focused on accurate topographic mapping, quantifying geomorphologic changes, and classification/identification of vegetation, sediment, and water quality tracers. In this work, we explore a further application of sUAS-derived topographic mapping to a two-dimensional (2-d), depth-averaged river hydraulic model (Flow and Sediment Transport with Morphological Evolution of Channels, FaSTMECH) along a short, meandering reach of East River, Colorado. On August 8, 2016, we flew a sUAS as part of the Center for Transformative Environmental Monitoring Programs with a consumer-grade visible camera and created a digital elevation map ( 1.5 cm resolution; 5 cm accuracy; 500 m long river corridor) with Agisoft Photoscan software. With the elevation map, we created a longitudinal water surface elevation (WSE) profile by manually delineating the bank-water interface and river bathymetry by applying refraction corrections for more accurate water depth estimates, an area of ongoing research for shallow and clear river systems. We tested both uncorrected and refraction-corrected bathymetries with the steady-state, 2-d model, applying sensitivities for dissipation parameters (bed roughness and eddy characteristics). Model performance was judged from the WSE data and measured stream velocities. While the models converged, performance and insights from model output could be improved with better bed roughness characterization and additional water depth cross-validation for refraction corrections. Overall, this work shows the applicability of sUAS-derived products to a multidimensional river model, where bathymetric data of high resolution and accuracy are key model input requirements.

Pathway computation in models derived from bio-science text sources

DEFF Research Database (Denmark)

Andreasen, Troels; Bulskov, Henrik; Jensen, Per Anker

2017-01-01

This paper outlines a system, OntoScape, serving to accomplish complex inference tasks on knowledge bases and bio-models derived from life-science text corpora. The system applies so-called natural logic, a form of logic which is readable for humans. This logic affords ontological representations...

Application of Improved Radiation Modeling to General Circulation Models

Energy Technology Data Exchange (ETDEWEB)

Michael J Iacono

2011-04-07

This research has accomplished its primary objectives of developing accurate and efficient radiation codes, validating them with measurements and higher resolution models, and providing these advancements to the global modeling community to enhance the treatment of cloud and radiative processes in weather and climate prediction models. A critical component of this research has been the development of the longwave and shortwave broadband radiative transfer code for general circulation model (GCM) applications, RRTMG, which is based on the single-column reference code, RRTM, also developed at AER. RRTMG is a rigorously tested radiation model that retains a considerable level of accuracy relative to higher resolution models and measurements despite the performance enhancements that have made it possible to apply this radiation code successfully to global dynamical models. This model includes the radiative effects of all significant atmospheric gases, and it treats the absorption and scattering from liquid and ice clouds and aerosols. RRTMG also includes a statistical technique for representing small-scale cloud variability, such as cloud fraction and the vertical overlap of clouds, which has been shown to improve cloud radiative forcing in global models. This development approach has provided a direct link from observations to the enhanced radiative transfer provided by RRTMG for application to GCMs. Recent comparison of existing climate model radiation codes with high resolution models has documented the improved radiative forcing capability provided by RRTMG, especially at the surface, relative to other GCM radiation models. Due to its high accuracy, its connection to observations, and its computational efficiency, RRTMG has been implemented operationally in many national and international dynamical models to provide validated radiative transfer for improving weather forecasts and enhancing the prediction of global climate change.

Improving the Accuracy of a Heliocentric Potential (HCP Prediction Model for the Aviation Radiation Dose

Directory of Open Access Journals (Sweden)

Junga Hwang

2016-12-01

Full Text Available The space radiation dose over air routes including polar routes should be carefully considered, especially when space weather shows sudden disturbances such as coronal mass ejections (CMEs, flares, and accompanying solar energetic particle events. We recently established a heliocentric potential (HCP prediction model for real-time operation of the CARI-6 and CARI-6M programs. Specifically, the HCP value is used as a critical input value in the CARI-6/6M programs, which estimate the aviation route dose based on the effective dose rate. The CARI-6/6M approach is the most widely used technique, and the programs can be obtained from the U.S. Federal Aviation Administration (FAA. However, HCP values are given at a one month delay on the FAA official webpage, which makes it difficult to obtain real-time information on the aviation route dose. In order to overcome this critical limitation regarding the time delay for space weather customers, we developed a HCP prediction model based on sunspot number variations (Hwang et al. 2015. In this paper, we focus on improvements to our HCP prediction model and update it with neutron monitoring data. We found that the most accurate method to derive the HCP value involves (1 real-time daily sunspot assessments, (2 predictions of the daily HCP by our prediction algorithm, and (3 calculations of the resultant daily effective dose rate. Additionally, we also derived the HCP prediction algorithm in this paper by using ground neutron counts. With the compensation stemming from the use of ground neutron count data, the newly developed HCP prediction model was improved.

Using satellite data to improve the leaf phenology of a global terrestrial biosphere model

Science.gov (United States)

MacBean, N.; Maignan, F.; Peylin, P.; Bacour, C.; Bréon, F.-M.; Ciais, P.

2015-12-01

Correct representation of seasonal leaf dynamics is crucial for terrestrial biosphere models (TBMs), but many such models cannot accurately reproduce observations of leaf onset and senescence. Here we optimised the phenology-related parameters of the ORCHIDEE TBM using satellite-derived Normalized Difference Vegetation Index data (MODIS NDVI v5) that are linearly related to the model fAPAR. We found the misfit between the observations and the model decreased after optimisation for all boreal and temperate deciduous plant functional types, primarily due to an earlier onset of leaf senescence. The model bias was only partially reduced for tropical deciduous trees and no improvement was seen for natural C4 grasses. Spatial validation demonstrated the generality of the posterior parameters for use in global simulations, with an increase in global median correlation of 0.56 to 0.67. The simulated global mean annual gross primary productivity (GPP) decreased by ~ 10 PgC yr-1 over the 1990-2010 period due to the substantially shortened growing season length (GSL - by up to 30 days in the Northern Hemisphere), thus reducing the positive bias and improving the seasonal dynamics of ORCHIDEE compared to independent data-based estimates. Finally, the optimisations led to changes in the strength and location of the trends in the simulated vegetation productivity as represented by the GSL and mean annual fraction of absorbed photosynthetically active radiation (fAPAR), suggesting care should be taken when using un-calibrated models in attribution studies. We suggest that the framework presented here can be applied for improving the phenology of all global TBMs.

Recombinant methioninase effectively targets a Ewing's sarcoma in a patient-derived orthotopic xenograft (PDOX) nude-mouse model.

Science.gov (United States)

Murakami, Takashi; Li, Shukuan; Han, Qinghong; Tan, Yuying; Kiyuna, Tasuku; Igarashi, Kentaro; Kawaguchi, Kei; Hwang, Ho Kyoung; Miyake, Kentaro; Singh, Arun S; Nelson, Scott D; Dry, Sarah M; Li, Yunfeng; Hiroshima, Yukihiko; Lwin, Thinzar M; DeLong, Jonathan C; Chishima, Takashi; Tanaka, Kuniya; Bouvet, Michael; Endo, Itaru; Eilber, Fritz C; Hoffman, Robert M

2017-05-30

Methionine dependence is due to the overuse of methionine for aberrant transmethylation reactions in cancer. Methionine dependence may be the only general metabolic defect in cancer. In order to exploit methionine dependence for therapy, our laboratory previously cloned L-methionine α-deamino-γ-mercaptomethane lyase [EC 4.4.1.11]). The cloned methioninase, termed recombinant methioninase, or rMETase, has been tested in mouse models of human cancer cell lines. Ewing's sarcoma is recalcitrant disease even though development of multimodal therapy has improved patients'outcome. Here we report efficacy of rMETase against Ewing's sarcoma in a patient-derived orthotopic xenograft (PDOX) model. The Ewing's sarcoma was implanted in the right chest wall of nude mice to establish a PDOX model. Eight Ewing's sarcoma PDOX mice were randomized into untreated control group (n = 4) and rMETase treatment group (n = 4). rMETase (100 units) was injected intraperitoneally (i.p.) every 24 hours for 14 consecutive days. All mice were sacrificed on day-15, 24 hours after the last rMETase administration. rMETase effectively reduced tumor growth compared to untreated control. The methionine level both of plasma and supernatants derived from sonicated tumors was lower in the rMETase group. Body weight did not significantly differ at any time points between the 2 groups. The present study is the first demonstrating rMETase efficacy in a PDOX model, suggesting potential clinical development, especially in recalcitrant cancers such as Ewing's sarcoma.

A space-jump derivation for non-local models of cell-cell adhesion and non-local chemotaxis.

Science.gov (United States)

Buttenschön, Andreas; Hillen, Thomas; Gerisch, Alf; Painter, Kevin J

2018-01-01

Cellular adhesion provides one of the fundamental forms of biological interaction between cells and their surroundings, yet the continuum modelling of cellular adhesion has remained mathematically challenging. In 2006, Armstrong et al. proposed a mathematical model in the form of an integro-partial differential equation. Although successful in applications, a derivation from an underlying stochastic random walk has remained elusive. In this work we develop a framework by which non-local models can be derived from a space-jump process. We show how the notions of motility and a cell polarization vector can be naturally included. With this derivation we are able to include microscopic biological properties into the model. We show that particular choices yield the original Armstrong model, while others lead to more general models, including a doubly non-local adhesion model and non-local chemotaxis models. Finally, we use random walk simulations to confirm that the corresponding continuum model represents the mean field behaviour of the stochastic random walk.

Sustained IGF-1 Secretion by Adipose-Derived Stem Cells Improves Infarcted Heart Function.

Science.gov (United States)

Bagno, Luiza L; Carvalho, Deivid; Mesquita, Fernanda; Louzada, Ruy A; Andrade, Bruno; Kasai-Brunswick, Taís H; Lago, Vivian M; Suhet, Grazielle; Cipitelli, Debora; Werneck-de-Castro, João Pedro; Campos-de-Carvalho, Antonio C

2016-01-01

The mechanism by which stem cell-based therapy improves heart function is still unknown, but paracrine mechanisms seem to be involved. Adipose-derived stem cells (ADSCs) secrete several factors, including insulin-like growth factor-1 (IGF-1), which may contribute to myocardial regeneration. Our aim was to investigate whether the overexpression of IGF-1 in ADSCs (IGF-1-ADSCs) improves treatment of chronically infarcted rat hearts. ADSCs were transduced with a lentiviral vector to induce IGF-1 overexpression. IGF-1-ADSCs transcribe100- to 200-fold more IGF-1 mRNA levels compared to nontransduced ADSCs. IGF-1 transduction did not alter ADSC immunophenotypic characteristics even under hypoxic conditions. However, IGF-1-ADSCs proliferate at higher rates and release greater amounts of growth factors such as IGF-1, vascular endothelial growth factor (VEGF), and hepatocyte growth factor (HGF) under normoxic and hypoxic conditions. Importantly, IGF-1 secreted by IGF-1-ADSCs is functional given that Akt-1 phosphorylation was remarkably induced in neonatal cardiomyocytes cocultured with IGF-1-ADSCs, and this increase was prevented with phosphatidylinositol 3-kinase (PI3K) inhibitor treatment. Next, we tested IGF-1-ADSCs in a rat myocardial infarction (MI) model. MI was performed by coronary ligation, and 4 weeks after MI, animals received intramyocardial injections of either ADSCs (n = 7), IGF-1-ADSCs (n = 7), or vehicle (n = 7) into the infarcted border zone. Left ventricular function was evaluated by echocardiography before and after 6 weeks of treatment, and left ventricular hemodynamics were assessed 7 weeks after cell injection. Notably, IGF-1-ADSCs improved left ventricular ejection fraction and cardiac contractility index, but did not reduce scar size when compared to the ADSC-treated group. In summary, transplantation of ADSCs transduced with IGF-1 is a superior therapeutic approach to treat MI compared to nontransduced ADSCs, suggesting that gene and cell

Improved healing of transected rabbit Achilles tendon after a single injection of cartilage-derived morphogenetic protein-2.

Science.gov (United States)

Forslund, Carina; Aspenberg, Per

2003-01-01

Achilles tendon ruptures in humans might be treated more efficiently with the help of a growth factor. Cartilage-derived morphogenetic protein-2 has been shown to induce formation of tendon-like tissue. Cartilage-derived morphogenetic protein-2 has a positive effect on mechanical parameters for tendon healing in a rabbit model with Achilles tendon transection. Controlled laboratory study. The right Achilles tendon of 40 rabbits was transected without tendon suture. Cartilage-derived morphogenetic protein-2 (10 micro g) or vehicle control (acetate buffer) was injected locally 2 hours postoperatively. All tendons were tested biomechanically at 8 and 14 days, and treated tendons were histologically and radiographically evaluated at 56 days. At 14 days, both failure load and stiffness of treated tendons were increased by 35%. The treated tendons had significantly larger callus size at 8 and 14 days. Histologic and radiographic examination showed no signs of ossification in the treated tendons after 56 days. A single injection of cartilage-derived morphogenetic protein-2 led to a stronger and stiffer tendon callus than that in the controls without inducing bone formation. Similar results from a larger animal model would suggest a possible future use of cartilage-derived morphogenetic protein-2 in the treatment of human Achilles tendon ruptures.

Derivation of a northern-hemispheric biomass map for use in global carbon cycle models

Science.gov (United States)

Thurner, Martin; Beer, Christian; Santoro, Maurizio; Carvalhais, Nuno; Wutzler, Thomas; Schepaschenko, Dmitry; Shvidenko, Anatoly; Kompter, Elisabeth; Levick, Shaun; Schmullius, Christiane

2013-04-01

(C)/ha(Forest)) and broadleaf/mixed forests (58.0 ± 22.1 Mg(C)/ha(Forest)), whereas boreal forests have a carbon density of only 40.0 ± 15.4 Mg(C)/ha(Forest). While European forest carbon stocks are relatively small, the carbon density is higher compared to the other continents. The derived biomass map substantially improves the knowledge on the current carbon stocks of the northern-hemispheric boreal and temperate forests, serving as a new benchmark for spatially explicit and consistent biomass mapping with moderate spatial resolution. This product can be of great value for global carbon cycle models as well as national carbon monitoring systems. Further investigations concentrate on improving biomass parameterizations and representations in such kind of models. The presented map will help to improve the simulation of biomass spatial patterns and variability and enables identifying the dominant influential factors like climatic conditions and disturbances.

Collaborative Project: Building improved optimized parameter estimation algorithms to improve methane and nitrogen fluxes in a climate model

Energy Technology Data Exchange (ETDEWEB)

Mahowald, Natalie [Cornell Univ., Ithaca, NY (United States)

2016-11-29

earth science with limited numbers of simulations; and, c) will be (as part of the proposed research) significantly improved both by adding asynchronous parallelism, early truncation of unsuccessful simulations, and the improvement of both serial and parallel performance by the use of derivative and sensitivity information from global and local surrogate approximations ^S(x). The algorithm development and testing will be focused on the CLM-ME/N model application, but the methods are general and are expected to also perform well on optimization for parameter estimation of other climate models and other classes of continuous multimodal optimization problems arising from complex simulation models. In addition, this proposal will compile available datasets of emissions of methane, nitrous oxides and reactive nitrogen species and develop protocols for site level comparisons with the CLM-ME/N. Once the model parameters are optimized against site level data, the model will be simulated at the global level and compared to atmospheric concentration measurements for the current climate, and future emissions will be estimated using climate change as simulated by the CESM. This proposal combines experts in earth system modeling, optimization, computer science, and process level understanding of soil gas emissions in an interdisciplinary team in order to improve the modeling of methane and nitrogen gas emissions. This proposal thus meets the requirements of the SciDAC RFP, by integrating state-of-the-art computer science and earth system to build an improved earth system model.

Modeling of a three-phase reactor for bitumen-derived gas oil hydrotreating

Energy Technology Data Exchange (ETDEWEB)

Chacon, R.; Canale, A.; Bouza, A. [Departamento de Termodinamica y Fenomenos de Transporte. Universidad Simon Bolivar, Caracas (Venezuela, Bolivarian Republic of); Sanchez, Y. [Departamento de Procesos y Sistemas. Universidad Simon Bolivar (Venezuela, Bolivarian Republic of)

2012-01-15

A three-phase reactor model for describing the hydrotreating reactions of bitumen-derived gas oil was developed. The model incorporates the mass-transfer resistance at the gas-liquid and liquid-solid interfaces and a kinetic rate expression based on a Langmuir-Hinshelwood-type model. We derived three correlations for determining the solubility of hydrogen (H{sub 2}), hydrogen sulfide (H{sub 2}S) and ammonia (NH{sub 3}) in hydrocarbon mixtures and the calculation of the catalyst effectiveness factor was included. Experimental data taken from the literature were used to determine the kinetic parameters (stoichiometric coefficients, reaction orders, reaction rate and adsorption constants for hydrodesulfuration (HDS) and hydrodenitrogenation (HDN)) and to validate the model under various operating conditions. Finally, we studied the effect of operating conditions such as pressure, temperature, LHSV, H{sub 2}/feed ratio and the inhibiting effect of H{sub 2}S on HDS and NH{sub 3} on HDN. (author)

Dynamics Under Location Uncertainty: Model Derivation, Modified Transport and Uncertainty Quantification

Science.gov (United States)

Resseguier, V.; Memin, E.; Chapron, B.; Fox-Kemper, B.

2017-12-01

In order to better observe and predict geophysical flows, ensemble-based data assimilation methods are of high importance. In such methods, an ensemble of random realizations represents the variety of the simulated flow's likely behaviors. For this purpose, randomness needs to be introduced in a suitable way and physically-based stochastic subgrid parametrizations are promising paths. This talk will propose a new kind of such a parametrization referred to as modeling under location uncertainty. The fluid velocity is decomposed into a resolved large-scale component and an aliased small-scale one. The first component is possibly random but time-correlated whereas the second is white-in-time but spatially-correlated and possibly inhomogeneous and anisotropic. With such a velocity, the material derivative of any - possibly active - tracer is modified. Three new terms appear: a correction of the large-scale advection, a multiplicative noise and a possibly heterogeneous and anisotropic diffusion. This parameterization naturally ensures attractive properties such as energy conservation for each realization. Additionally, this stochastic material derivative and the associated Reynolds' transport theorem offer a systematic method to derive stochastic models. In particular, we will discuss the consequences of the Quasi-Geostrophic assumptions in our framework. Depending on the turbulence amount, different models with different physical behaviors are obtained. Under strong turbulence assumptions, a simplified diagnosis of frontolysis and frontogenesis at the surface of the ocean is possible in this framework. A Surface Quasi-Geostrophic (SQG) model with a weaker noise influence has also been simulated. A single realization better represents small scales than a deterministic SQG model at the same resolution. Moreover, an ensemble accurately predicts extreme events, bifurcations as well as the amplitudes and the positions of the simulation errors. Figure 1 highlights this last

An improved gravity model for Mars: Goddard Mars Model 1

Science.gov (United States)

Smith, D. E.; Lerch, F. J.; Nerem, R. S.; Zuber, M. T.; Patel, G. B.; Fricke, S. K.; Lemoine, F. G.

1993-01-01

Doppler tracking data of three orbiting spacecraft have been reanalyzed to develop a new gravitational field model for the planet Mars, Goddard Mars Model 1 (GMM-1). This model employs nearly all available data, consisting of approximately 1100 days of S band tracking data collected by NASA's Deep Space Network from the Mariner 9 and Viking 1 and Viking 2 spacecraft, in seven different orbits, between 1971 and 1979. GMM-1 is complete to spherical harmonic degree and order 50, which corresponds to a half-wavelength spatial resolution of 200-300 km where the data permit. GMM-1 represents satellite orbits with considerably better accuracy than previous Mars gravity models and shows greater resolution of identifiable geological structures. The notable improvement in GMM-1 over previous models is a consequence of several factors: improved computational capabilities, the use of otpimum weighting and least squares collocation solution techniques which stabilized the behavior of the solution at high degree and order, and the use of longer satellite arcs than employed in previous solutions that were made possible by improved force and measurement models. The inclusion of X band tracking data from the 379-km altitude, nnear-polar orbiting Mars Observer spacecraft should provide a significant improvement over GMM-1, particularly at high latitudes where current data poorly resolve the gravitational signature of the planet.

Improved diagnostic model for estimating wind energy

Energy Technology Data Exchange (ETDEWEB)

Endlich, R.M.; Lee, J.D.

1983-03-01

Because wind data are available only at scattered locations, a quantitative method is needed to estimate the wind resource at specific sites where wind energy generation may be economically feasible. This report describes a computer model that makes such estimates. The model uses standard weather reports and terrain heights in deriving wind estimates; the method of computation has been changed from what has been used previously. The performance of the current model is compared with that of the earlier version at three sites; estimates of wind energy at four new sites are also presented.

An Improved Mathematical Model for Computing Power Output of Solar Photovoltaic Modules

Directory of Open Access Journals (Sweden)

Abdul Qayoom Jakhrani

2014-01-01

Full Text Available It is difficult to determine the input parameters values for equivalent circuit models of photovoltaic modules through analytical methods. Thus, the previous researchers preferred to use numerical methods. Since, the numerical methods are time consuming and need long term time series data which is not available in most developing countries, an improved mathematical model was formulated by combination of analytical and numerical methods to overcome the limitations of existing methods. The values of required model input parameters were computed analytically. The expression for output current of photovoltaic module was determined explicitly by Lambert W function and voltage was determined numerically by Newton-Raphson method. Moreover, the algebraic equations were derived for the shape factor which involves the ideality factor and the series resistance of a single diode photovoltaic module power output model. The formulated model results were validated with rated power output of a photovoltaic module provided by manufacturers using local meteorological data, which gave ±2% error. It was found that the proposed model is more practical in terms of precise estimations of photovoltaic module power output for any required location and number of variables used.

Deformation analysis of polymers composites: rheological model involving time-based fractional derivative

DEFF Research Database (Denmark)

Zhou, H. W.; Yi, H. Y.; Mishnaevsky, Leon

2017-01-01

A modeling approach to time-dependent property of Glass Fiber Reinforced Polymers (GFRP) composites is of special interest for quantitative description of long-term behavior. An electronic creep machine is employed to investigate the time-dependent deformation of four specimens of dog-bond-shaped......A modeling approach to time-dependent property of Glass Fiber Reinforced Polymers (GFRP) composites is of special interest for quantitative description of long-term behavior. An electronic creep machine is employed to investigate the time-dependent deformation of four specimens of dog......-bond-shaped GFRP composites at various stress level. A negative exponent function based on structural changes is introduced to describe the damage evolution of material properties in the process of creep test. Accordingly, a new creep constitutive equation, referred to fractional derivative Maxwell model...... by the fractional derivative Maxwell model proposed in the paper are in a good agreement with the experimental data. It is shown that the new creep constitutive model proposed in the paper needs few parameters to represent various time-dependent behaviors....

Improvement of MARS code reflood model

International Nuclear Information System (INIS)

Hwang, Moonkyu; Chung, Bub-Dong

2011-01-01

A specifically designed heat transfer model for the reflood process which normally occurs at low flow and low pressure was originally incorporated in the MARS code. The model is essentially identical to that of the RELAP5/MOD3.3 code. The model, however, is known to have under-estimated the peak cladding temperature (PCT) with earlier turn-over. In this study, the original MARS code reflood model is improved. Based on the extensive sensitivity studies for both hydraulic and wall heat transfer models, it is found that the dispersed flow film boiling (DFFB) wall heat transfer is the most influential process determining the PCT, whereas the interfacial drag model most affects the quenching time through the liquid carryover phenomenon. The model proposed by Bajorek and Young is incorporated for the DFFB wall heat transfer. Both space grid and droplet enhancement models are incorporated. Inverted annular film boiling (IAFB) is modeled by using the original PSI model of the code. The flow transition between the DFFB and IABF, is modeled using the TRACE code interpolation. A gas velocity threshold is also added to limit the top-down quenching effect. Assessment calculations are performed for the original and modified MARS codes for the Flecht-Seaset test and RBHT test. Improvements are observed in terms of the PCT and quenching time predictions in the Flecht-Seaset assessment. In case of the RBHT assessment, the improvement over the original MARS code is found marginal. A space grid effect, however, is clearly seen from the modified version of the MARS code. (author)

LBH589, A Hydroxamic Acid-Derived HDAC Inhibitor, is Neuroprotective in Mouse Models of Huntington's Disease.

Science.gov (United States)

Chopra, Vanita; Quinti, Luisa; Khanna, Prarthana; Paganetti, Paolo; Kuhn, Rainer; Young, Anne B; Kazantsev, Aleksey G; Hersch, Steven

2016-12-15

Modulation of gene transcription by HDAC inhibitors has been shown repeatedly to be neuroprotective in cellular, invertebrate, and rodent models of Huntington's disease (HD). It has been difficult to translate these treatments to the clinic, however, because existing compounds have limited potency or brain bioavailability. In the present study, we assessed the therapeutic potential of LBH589, an orally bioavailable hydroxamic acid-derived nonselective HDAC inhibitor in mouse models of HD. The efficacy of LBH589 is tested in two HD mouse models using various biochemical, behavioral and neuropathological outcome measures. We show that LBH589 crosses the blood brain barrier; induces histone hyperacetylation and prevents striatal neuronal shrinkage in R6/2 HD mice. In full-length knock-in HD mice LBH589-treatment improves motor performance and reduces neuronal atrophy. Our efficacious results of LBH589 in fragment and full-length mouse models of HD suggest that LBH589 is a promising candidate for clinical assessment in HD patients and provides confirmation that non-selective HDAC inhibitors can be viable clinical candidates.

A model for the derivation of new transport limits for non-fixed contamination

International Nuclear Information System (INIS)

Thierfeldt, S.; Lorenz, B.; Hesse, J.

2004-01-01

The IAEA Regulations for the Safe Transport of Radioactive Material contain requirements for contamination limits on packages and conveyances used for the transport of radioactive material. Current contamination limits for packages and conveyances under routine transport conditions have been derived from a model proposed by Fairbairn more than 40 years ago. This model has proven effective if used with pragmatism, but is based on very conservative as well as extremely simple assumptions which is in no way appropriate any more and which is not compatible with ICRP recommendations regarding radiation protection standards. Therefore, a new model has now been developed which reflects all steps of the transport process. The derivation of this model has been fostered by the IAEA by initiating a Co-ordinated Research Project. The results of the calculations using this model could be directly applied as new nuclide specific transport limits for the non-fixed contamination

A model for the derivation of new transport limits for non-fixed contamination

Energy Technology Data Exchange (ETDEWEB)

Thierfeldt, S. [Brenk Systemplanung GmbH, Aachen (Germany); Lorenz, B. [GNS Gesellschaft fuer Nuklearservice, Essen (Germany); Hesse, J. [RWE Power AG, Essen (Germany)

2004-07-01

The IAEA Regulations for the Safe Transport of Radioactive Material contain requirements for contamination limits on packages and conveyances used for the transport of radioactive material. Current contamination limits for packages and conveyances under routine transport conditions have been derived from a model proposed by Fairbairn more than 40 years ago. This model has proven effective if used with pragmatism, but is based on very conservative as well as extremely simple assumptions which is in no way appropriate any more and which is not compatible with ICRP recommendations regarding radiation protection standards. Therefore, a new model has now been developed which reflects all steps of the transport process. The derivation of this model has been fostered by the IAEA by initiating a Co-ordinated Research Project. The results of the calculations using this model could be directly applied as new nuclide specific transport limits for the non-fixed contamination.

Modeling chemotherapeutic neurotoxicity with human induced pluripotent stem cell-derived neuronal cells.

Directory of Open Access Journals (Sweden)

Heather E Wheeler

Full Text Available There are no effective agents to prevent or treat chemotherapy-induced peripheral neuropathy (CIPN, the most common non-hematologic toxicity of chemotherapy. Therefore, we sought to evaluate the utility of human neuron-like cells derived from induced pluripotent stem cells (iPSCs as a means to study CIPN. We used high content imaging measurements of neurite outgrowth phenotypes to compare the changes that occur to iPSC-derived neuronal cells among drugs and among individuals in response to several classes of chemotherapeutics. Upon treatment of these neuronal cells with the neurotoxic drug paclitaxel, vincristine or cisplatin, we identified significant differences in five morphological phenotypes among drugs, including total outgrowth, mean/median/maximum process length, and mean outgrowth intensity (P < 0.05. The differences in damage among drugs reflect differences in their mechanisms of action and clinical CIPN manifestations. We show the potential of the model for gene perturbation studies by demonstrating decreased expression of TUBB2A results in significantly increased sensitivity of neurons to paclitaxel (0.23 ± 0.06 decrease in total neurite outgrowth, P = 0.011. The variance in several neurite outgrowth and apoptotic phenotypes upon treatment with one of the neurotoxic drugs is significantly greater between than within neurons derived from four different individuals (P < 0.05, demonstrating the potential of iPSC-derived neurons as a genetically diverse model for CIPN. The human neuron model will allow both for mechanistic studies of specific genes and genetic variants discovered in clinical studies and for screening of new drugs to prevent or treat CIPN.

Conference Innovations in Derivatives Market : Fixed Income Modeling, Valuation Adjustments, Risk Management, and Regulation

CERN Document Server

Grbac, Zorana; Scherer, Matthias; Zagst, Rudi

2016-01-01

This book presents 20 peer-reviewed chapters on current aspects of derivatives markets and derivative pricing. The contributions, written by leading researchers in the field as well as experienced authors from the financial industry, present the state of the art in: • Modeling counterparty credit risk: credit valuation adjustment, debit valuation adjustment, funding valuation adjustment, and wrong way risk. • Pricing and hedging in fixed-income markets and multi-curve interest-rate modeling. • Recent developments concerning contingent convertible bonds, the measuring of basis spreads, and the modeling of implied correlations. The recent financial crisis has cast tremendous doubts on the classical view on derivative pricing. Now, counterparty credit risk and liquidity issues are integral aspects of a prudent valuation procedure and the reference interest rates are represented by a multitude of curves according to their different periods and maturities. A panel discussion included in the book (featuring D...

Recruitment of Intracavernously Injected Adipose-Derived Stem Cells to the Major Pelvic Ganglion Improves Erectile Function in a Rat Model of Cavernous Nerve Injury

Science.gov (United States)

Fandel, Thomas M.; Albersen, Maarten; Lin, Guiting; Qiu, Xuefeng; Ning, Hongxiu; Banie, Lia; Lue, Tom F.; Lin, Ching-Shwun

2011-01-01

Background Intracavernous (IC) injection of stem cells has been shown to ameliorate cavernous-nerve (CN) injury-induced erectile dysfunction (ED). However, the mechanisms of action of adipose-derived stem cells (ADSC) remain unclear. Objectives To investigate the mechanism of action and fate of IC injected ADSC in a rat model of CN crush injury. Design, setting, and participants Sprague-Dawley rats (n = 110) were randomly divided into five groups. Thirty-five rats underwent sham surgery and IC injection of ADSC (n = 25) or vehicle (n = 10). Another 75 rats underwent bilateral CN crush injury and were treated with vehicle or ADSC injected either IC or in the dorsal penile perineural space. At 1, 3, 7 (n = 5), and 28 d (n = 10) postsurgery, penile tissues and major pelvic ganglia (MPG) were harvested for histology. ADSC were labeled with 5-ethynyl-2-deoxyuridine (EdU) before treatment. Rats in the 28-d groups were examined for erectile function prior to tissue harvest. Measurements IC pressure recording on CN electrostimulation, immunohistochemistry of the penis and the MPG, and number of EdU-positive (EdU+) cells in the injection site and the MPG. Results and limitations IC, but not perineural, injection of ADSC resulted in significantly improved erectile function. Significantly more EdU+ ADSC appeared in the MPG of animals with CN injury and IC injection of ADSC compared with those injected perineurally and those in the sham group. One day after crush injury, stromal cell-derived factor-1 (SDF-1) was upregulated in the MPG, providing an incentive for ADSC recruitment toward the MPG. Neuroregeneration was observed in the group that underwent IC injection of ADSC, and IC ADSC treatment had beneficial effects on the smooth muscle/collagen ratio in the corpus cavernosum. Conclusions CN injury upregulates SDF-1 expression in the MPG and thereby attracts intracavernously injected ADSC. At the MPG, ADSC exert neuroregenerative effects on the cell bodies of injured nerves

Intermediate modeling between kinetic equations and hydrodynamic limits: derivation, analysis and simulations

International Nuclear Information System (INIS)

Parisot, M.

2011-01-01

This work is dedicated study of a problem resulting from plasma physics: the thermal transfer of electrons in a plasma close to equilibrium Maxwellian. Firstly, a dimensional study of the Vlasov-Fokker-Planck-Maxwell system is performed, allowing one hand to identify a physically relevant parameter of scale and also to define mathematically the contours of validity domain. The asymptotic regime called Spitzer-Harm is studied for a relatively general class of collision operator. The following part of this work is devoted to the derivation and study of the hydrodynamic limit of the system of Vlasov-Maxwell-Landau outside the strictly asymptotic. A model proposed by Schurtz and Nicolais located in this context and analyzed. The particularity of this model lies in the application of a delocalization operation in the heat flux. The link with non-local models of Luciani and Mora is established as well as mathematics properties as the principle of maximum and entropy dissipation. Then a formal derivation from the Vlasov equations with a simplified collision operator, is proposed. The derivation, inspired by the recent work of D. Levermore, involves decomposition methods according to the spherical harmonics and methods of closing called diffusion methods. A hierarchy of intermediate models between the kinetic equations and the hydrodynamic limit is described. In particular a new hydrodynamic system integro-differential by nature, is proposed. The Schurtz and Nicolai model appears as a simplification of the system resulting from the derivation, assuming a steady flow of heat. The above results are then generalized to account for the internal energy dependence which appears naturally in the equation establishment. The existence and uniqueness of the solution of the nonstationary system are established in a simplified framework. The last part is devoted was the implementation of a specific numerical scheme to solve these models. We propose a finite volume approach can be

Modeling soil water content for vegetation modeling improvement

Science.gov (United States)

Cianfrani, Carmen; Buri, Aline; Zingg, Barbara; Vittoz, Pascal; Verrecchia, Eric; Guisan, Antoine

2016-04-01

Soil water content (SWC) is known to be important for plants as it affects the physiological processes regulating plant growth. Therefore, SWC controls plant distribution over the Earth surface, ranging from deserts and grassland to rain forests. Unfortunately, only a few data on SWC are available as its measurement is very time consuming and costly and needs specific laboratory tools. The scarcity of SWC measurements in geographic space makes it difficult to model and spatially project SWC over larger areas. In particular, it prevents its inclusion in plant species distribution model (SDMs) as predictor. The aims of this study were, first, to test a new methodology allowing problems of the scarcity of SWC measurements to be overpassed and second, to model and spatially project SWC in order to improve plant SDMs with the inclusion of SWC parameter. The study was developed in four steps. First, SWC was modeled by measuring it at 10 different pressures (expressed in pF and ranging from pF=0 to pF=4.2). The different pF represent different degrees of soil water availability for plants. An ensemble of bivariate models was built to overpass the problem of having only a few SWC measurements (n = 24) but several predictors to include in the model. Soil texture (clay, silt, sand), organic matter (OM), topographic variables (elevation, aspect, convexity), climatic variables (precipitation) and hydrological variables (river distance, NDWI) were used as predictors. Weighted ensemble models were built using only bivariate models with adjusted-R2 > 0.5 for each SWC at different pF. The second step consisted in running plant SDMs including modeled SWC jointly with the conventional topo-climatic variable used for plant SDMs. Third, SDMs were only run using the conventional topo-climatic variables. Finally, comparing the models obtained in the second and third steps allowed assessing the additional predictive power of SWC in plant SDMs. SWC ensemble models remained very good, with

Human umbilical cord blood-derived stem cells and brain-derived neurotrophic factor protect injured optic nerve: viscoelasticity characterization

Directory of Open Access Journals (Sweden)

Xue-man Lv

2016-01-01

Full Text Available The optic nerve is a viscoelastic solid-like biomaterial. Its normal stress relaxation and creep properties enable the nerve to resist constant strain and protect it from injury. We hypothesized that stress relaxation and creep properties of the optic nerve change after injury. More-over, human brain-derived neurotrophic factor or umbilical cord blood-derived stem cells may restore these changes to normal. To validate this hypothesis, a rabbit model of optic nerve injury was established using a clamp approach. At 7 days after injury, the vitreous body re-ceived a one-time injection of 50 µg human brain-derived neurotrophic factor or 1 × 106 human umbilical cord blood-derived stem cells. At 30 days after injury, stress relaxation and creep properties of the optic nerve that received treatment had recovered greatly, with patho-logical changes in the injured optic nerve also noticeably improved. These results suggest that human brain-derived neurotrophic factor or umbilical cord blood-derived stem cell intervention promotes viscoelasticity recovery of injured optic nerves, and thereby contributes to nerve recovery.

Derivation of the mean annual water-energy balance model based on an Ohms-type law

Science.gov (United States)

Li, X.; Shan, X.; Yang, H.

2017-12-01

The Budyko Hypothesis is used to describe the water partition and energy partition. Many empirical and analytical solutions have been proposed to evaluate the general solution which can be described as E/P = F(E0/P, c), where c is a parameter. And previous studies have given a derivation of Mezentsev-Choudhruy-Yang (MCY) model, based on dimensional analysis and mathematic reasoning, however, little hydrological process. Thus further hydrological meaning is limited to the boundary conditions which are difficult to explore. Note that hydrologic cycle is always forced by the energy conversions and atmospheric transportation, and the parallel in the electric circuits and the atmospheric motions, therefore we try to give a new derivation of MCY model from a conceptual model, considering hydrologic fluxes and atmospheric motions. Here an analogy of Ohms Law and the atmospheric cycle is used to aim at describing the partition of water in a long-term timescale. Then MCY model is derived in a new form, which is based on more physical explanation than mathematic reasoning proposed in previous studies. The implications of this derivation are also explored.

A new visco-elasto-plastic model via time-space fractional derivative

Science.gov (United States)

Hei, X.; Chen, W.; Pang, G.; Xiao, R.; Zhang, C.

2018-02-01

To characterize the visco-elasto-plastic behavior of metals and alloys we propose a new constitutive equation based on a time-space fractional derivative. The rheological representative of the model can be analogous to that of the Bingham-Maxwell model, while the dashpot element and sliding friction element are replaced by the corresponding fractional elements. The model is applied to describe the constant strain rate, stress relaxation and creep tests of different metals and alloys. The results suggest that the proposed simple model can describe the main characteristics of the experimental observations. More importantly, the model can also provide more accurate predictions than the classic Bingham-Maxwell model and the Bingham-Norton model.

Vitamin K2 improves developmental competency and cryo-tolerance of in vitro derived ovine blastocyst.

Science.gov (United States)

Sefid, Fatemeh; Ostadhosseini, S; Hosseini, S M; Ghazvini Zadegan, F; Pezhman, M; Nasr Esfahani, Mohammad Hossein

2017-08-01

Vitamin K2 (VK2), acts as an electron carrier in mitochondria and thereby effects reactive oxygen species (ROS) and ATP production. This study evaluates role of VK2 on in vitro developmental competency and cryo-survival of pre-implantation ovine embryos. Initially the optimal and beneficial concentration of VK2 on compaction and blastocyst formation rates was defined (0.1 μM). Subsequently, it was shown that 0.1 μM VK2, at blastocyst stage, reduces H2O2 production, increase the expression of mitochondrial related gene and improved embryos quality. We further assessed presence VK2 supplementation before and/or after vitrification of in vitro derived blastocysts. Our results reveal that presence of VK2 before and after vitrification improves rates of blastocysts re-expansion (88.19± 3.37% vs 73.68± 1.86%, P < 0.05) and hatching (49.55± 4.37% vs 32.7± 3.32%) compared to control group. These observation were consistent with reduction in H2O2 production and improved in expression of mitochondrial related genes. However, VK2 before or after vitrification, not only had no positive effect on these two parameters, but also significantly reduced these parameters. Therefore, in concordance with pervious report in bovine, we show that VK2 supplementation post genomic activation (Day 3-7) improved developmental competency of ovine in vitro derived embryos. We also showed that presence of VK2 after vitrification improves the cryo-survival of ovine embryos. Copyright © 2017 Elsevier Inc. All rights reserved.

EchoSeed Model 6733 Iodine-125 brachytherapy source: Improved dosimetric characterization using the MCNP5 Monte Carlo code

Energy Technology Data Exchange (ETDEWEB)

Mosleh-Shirazi, M. A.; Hadad, K.; Faghihi, R.; Baradaran-Ghahfarokhi, M.; Naghshnezhad, Z.; Meigooni, A. S. [Center for Research in Medical Physics and Biomedical Engineering and Physics Unit, Radiotherapy Department, Shiraz University of Medical Sciences, Shiraz 71936-13311 (Iran, Islamic Republic of); Radiation Research Center and Medical Radiation Department, School of Engineering, Shiraz University, Shiraz 71936-13311 (Iran, Islamic Republic of); Comprehensive Cancer Center of Nevada, Las Vegas, Nevada 89169 (United States)

2012-08-15

This study primarily aimed to obtain the dosimetric characteristics of the Model 6733 {sup 125}I seed (EchoSeed) with improved precision and accuracy using a more up-to-date Monte-Carlo code and data (MCNP5) compared to previously published results, including an uncertainty analysis. Its secondary aim was to compare the results obtained using the MCNP5, MCNP4c2, and PTRAN codes for simulation of this low-energy photon-emitting source. The EchoSeed geometry and chemical compositions together with a published {sup 125}I spectrum were used to perform dosimetric characterization of this source as per the updated AAPM TG-43 protocol. These simulations were performed in liquid water material in order to obtain the clinically applicable dosimetric parameters for this source model. Dose rate constants in liquid water, derived from MCNP4c2 and MCNP5 simulations, were found to be 0.993 cGyh{sup -1} U{sup -1} ({+-}1.73%) and 0.965 cGyh{sup -1} U{sup -1} ({+-}1.68%), respectively. Overall, the MCNP5 derived radial dose and 2D anisotropy functions results were generally closer to the measured data (within {+-}4%) than MCNP4c and the published data for PTRAN code (Version 7.43), while the opposite was seen for dose rate constant. The generally improved MCNP5 Monte Carlo simulation may be attributed to a more recent and accurate cross-section library. However, some of the data points in the results obtained from the above-mentioned Monte Carlo codes showed no statistically significant differences. Derived dosimetric characteristics in liquid water are provided for clinical applications of this source model.

Neonatal Transplantation Confers Maturation of PSC-Derived Cardiomyocytes Conducive to Modeling Cardiomyopathy.

Science.gov (United States)

Cho, Gun-Sik; Lee, Dong I; Tampakakis, Emmanouil; Murphy, Sean; Andersen, Peter; Uosaki, Hideki; Chelko, Stephen; Chakir, Khalid; Hong, Ingie; Seo, Kinya; Chen, Huei-Sheng Vincent; Chen, Xiongwen; Basso, Cristina; Houser, Steven R; Tomaselli, Gordon F; O'Rourke, Brian; Judge, Daniel P; Kass, David A; Kwon, Chulan

2017-01-10

Pluripotent stem cells (PSCs) offer unprecedented opportunities for disease modeling and personalized medicine. However, PSC-derived cells exhibit fetal-like characteristics and remain immature in a dish. This has emerged as a major obstacle for their application for late-onset diseases. We previously showed that there is a neonatal arrest of long-term cultured PSC-derived cardiomyocytes (PSC-CMs). Here, we demonstrate that PSC-CMs mature into adult CMs when transplanted into neonatal hearts. PSC-CMs became similar to adult CMs in morphology, structure, and function within a month of transplantation into rats. The similarity was further supported by single-cell RNA-sequencing analysis. Moreover, this in vivo maturation allowed patient-derived PSC-CMs to reveal the disease phenotype of arrhythmogenic right ventricular cardiomyopathy, which manifests predominantly in adults. This study lays a foundation for understanding human CM maturation and pathogenesis and can be instrumental in PSC-based modeling of adult heart diseases. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Improvement of PEP-II Linear Optics with a MIA-Derived Virtual Accelerator

International Nuclear Information System (INIS)

Cerio, B.; Colgate U.

2006-01-01

In several past studies, model independent analysis, in conjunction with a virtual accelerator model, has been successful in improving PEP-II linear geometric optics. In many cases, optics improvement yielded an increase in machine luminosity. In this study, an updated characterization of linear optics is presented. With the PEP-II beam position monitor (BPM) system, four independent beam centroid orbits were extracted and used to determine phase advances and linear Green's functions among BPM locations. A magnetic lattice model was then constructed with a singular value decomposition-enhanced least-square fitting of phase advances and Green's functions, which are functions of quadrupole strengths, sextupole feed-downs, as well as BPM errors, to the corresponding measured quantities. The fitting process yielded a machine model that matched the measured linear optics of the real machine and was therefore deemed the virtual accelerator. High beta beat, as well as linear coupling, was observed in both LER and HER of the virtual accelerator. Since there was higher beta beating in LER, focus was shifted to the improvement of this ring. By adjusting select quadrupoles of the virtual LER and fitting the resulting beta functions and phase advances to those of the desired lattice, the average beta beat of the virtual machine was effectively reduced. The new magnet configuration was dialed into LER on August 10, 2006, and beta beat was reduced by a factor of three. After fine tuning HER to match the improved LER for optimal collision, a record peak luminosity of 12.069 x 10 33 cm -2 s -1 was attained on August 16, 2006

Leveraging North Carolina's QL2 Lidar to Quantify Sensitivity of National Water Model Derived Flood Inundation Extent to DEM Resolution

Science.gov (United States)

Lovette, J. P.; Lenhardt, W. C.; Blanton, B.; Duncan, J. M.; Stillwell, L.

2017-12-01

The National Water Model (NWM) has provided a novel framework for near real time flood inundation mapping across CONUS at a 10m resolution. In many regions, this spatial scale is quickly being surpassed through the collection of high resolution lidar (1 - 3m). As one of the leading states in data collection for flood inundation mapping, North Carolina is currently improving their previously available 20 ft statewide elevation product to a Quality Level 2 (QL2) product with a nominal point spacing of 0.7 meters. This QL2 elevation product increases the ground points by roughly ten times over the previous statewide lidar product, and by over 250 times when compared to the 10m NED elevation grid. When combining these new lidar data with the discharge estimates from the NWM, we can further improve statewide flood inundation maps and predictions of at-risk areas. In the context of flood risk management, these improved predictions with higher resolution elevation models consistently represent an improvement on coarser products. Additionally, the QL2 lidar also includes coarse land cover classification data for each point return, opening the possibility for expanding analysis beyond the use of only digital elevation models (e.g. improving estimates of surface roughness, identifying anthropogenic features in floodplains, characterizing riparian zones, etc.). Using the NWM Height Above Nearest Drainage approach, we compare flood inundation extents derived from multiple lidar-derived grid resolutions to assess the tradeoff between precision and computational load in North Carolina's coastal river basins. The elevation data distributed through the state's new lidar collection program provide spatial resolutions ranging from 5-50 feet, with most inland areas also including a 3 ft product. Data storage increases by almost two orders of magnitude across this range, as does processing load. In order to further assess the validity of the higher resolution elevation products on

Neonatal Transplantation Confers Maturation of PSC-Derived Cardiomyocytes Conducive to Modeling Cardiomyopathy

OpenAIRE

Cho, Gun-Sik; Lee, Dong I.; Tampakakis, Emmanouil; Murphy, Sean; Andersen, Peter; Uosaki, Hideki; Chelko, Stephen; Chakir, Khalid; Hong, Ingie; Seo, Kinya; Vincent Chen, Huei-Sheng; Chen, Xiongwen; Basso, Cristina; Houser, Steven R.; Tomaselli, Gordon F.

2017-01-01

Summary: Pluripotent stem cells (PSCs) offer unprecedented opportunities for disease modeling and personalized medicine. However, PSC-derived cells exhibit fetal-like characteristics and remain immature in a dish. This has emerged as a major obstacle for their application for late-onset diseases. We previously showed that there is a neonatal arrest of long-term cultured PSC-derived cardiomyocytes (PSC-CMs). Here, we demonstrate that PSC-CMs mature into adult CMs when transplanted into neonata...

Precise troposphere delay model for Egypt, as derived from radiosonde data

Directory of Open Access Journals (Sweden)

M.A. Abdelfatah

2015-06-01

Real GPS data of six stations in 8-day period were used for the assessment of zenith part of PTD model against the available international models. These international models include Saastamoinen, Hopfield, and the local Egyptian dry model proposed by Mousa & El-Fiky. The data were processed using Bernese software version 5.0. The closure error results indicate that the PTD model is the best model in all session, but when the available radiosonde stations are less, the accuracy of PTD model is near to classic models. As radiosonde data for all ten stations are not available every session, it is recommended to use one of the regularization techniques for database to overcome missing data and derive consistent tropospheric delay information.

Patient Derived Xenograft Models: An Emerging Platform for Translational Cancer Research

Science.gov (United States)

Hidalgo, Manuel; Amant, Frederic; Biankin, Andrew V.; Budinská, Eva; Byrne, Annette T.; Caldas, Carlos; Clarke, Robert B.; de Jong, Steven; Jonkers, Jos; Mælandsmo, Gunhild Mari; Roman-Roman, Sergio; Seoane, Joan; Trusolino, Livio; Villanueva, Alberto

2014-01-01

Recently, there has been increasing interest in the development and characterization of patient derived tumor xenograft (PDX) models for cancer research. PDX models mostly retain the principal histological and genetic characteristics of their donor tumor and remain stable across passages. These models have been shown to be predictive of clinical outcomes and are being used for preclinical drug evaluation, biomarker identification, biological studies, and personalized medicine strategies. This paper summarizes the current state of the art in this field including methodological issues, available collections, practical applications, challenges and shortcoming, and future directions, and introduces a European consortium of PDX models. PMID:25185190

Improvements of evaporation drag model

International Nuclear Information System (INIS)

Li Xiaoyan; Yang Yanhua; Xu Jijun

2004-01-01

A special observable experiment facility has been established, and a series of experiments have been carried out on this facility by pouring one or several high-temperature particles into a water pool. The experiment has verified the evaporation drag model, which believe the non-symmetric profile of the local evaporation rate and the local density of the vapor would bring about a resultant force on the hot particle so as to resist its motion. However, in Yang's evaporation drag model, radiation heat transfer is taken as the only way to transfer heat from hot particle to the vapor-liquid interface and all of the radiation energy is deposited on the vapor-liquid interface, thus contributing to the vaporization rate and mass balance of the vapor film. So, the heat conduction and the heat convection are taken into account in improved model. At the same time, the improved model given by this paper presented calculations of the effect of hot particles temperature on the radiation absorption behavior of water

Market segment derivation and profiling via a finite mixture model framework

NARCIS (Netherlands)

Wedel, M; Desarbo, WS

The Marketing literature has shown how difficult it is to profile market segments derived with finite mixture models. especially using traditional descriptor variables (e.g., demographics). Such profiling is critical for the proper implementation of segmentation strategy. we propose a new finite

Integrating hydrodynamic models and COSMO-SkyMed derived products for flood damage assessment

Science.gov (United States)

Giuffra, Flavio; Boni, Giorgio; Pulvirenti, Luca; Pierdicca, Nazzareno; Rudari, Roberto; Fiorini, Mattia

2015-04-01

Floods are the most frequent weather disasters in the world and probably the most costly in terms of social and economic losses. They may have a strong impact on infrastructures and health because the range of possible damages includes casualties, loss of housing and destruction of crops. Presently, the most common approach for remotely sensing floods is the use of synthetic aperture radar (SAR) images. Key features of SAR data for inundation mapping are the synoptic view, the capability to operate even in cloudy conditions and during both day and night time and the sensitivity of the microwave radiation to water. The launch of a new generation of instruments, such as TerraSAR-X and COSMO-SkyMed (CSK) allows producing near real time flood maps having a spatial resolution in the order of 1-5 m. Moreover, the present (CSK) and upcoming (Sentinel-1) constellations permit the acquisition of radar data characterized by a short revisit time (in the order of some hours for CSK), so that the production of frequent inundation maps can be envisaged. Nonetheless, gaps might be present in the SAR-derived flood maps because of the limited area imaged by SAR; moreover, the detection of floodwater may be complicated by the presence of very dense vegetation or urban settlements. Hence the need to complement SAR-derived flood maps with the outputs of physical models. Physical models allow delivering to end users very useful information for a complete flood damage assessment, such as data on water depths and flow directions, which cannot be directly derived from satellite remote sensing images. In addition, the flood extent predictions of hydraulic models can be compared to SAR-derived inundation maps to calibrate the models, or to fill the aforementioned gaps that can be present in the SAR-derived maps. Finally, physical models enable the construction of risk scenarios useful for emergency managers to take their decisions and for programming additional SAR acquisitions in order to

QUALITY IMPROVEMENT MODEL AT THE MANUFACTURING PROCESS PREPARATION LEVEL

Directory of Open Access Journals (Sweden)

Dusko Pavletic

2009-12-01

Full Text Available The paper expresses base for an operational quality improvement model at the manufacturing process preparation level. A numerous appropriate related quality assurance and improvement methods and tools are identified. Main manufacturing process principles are investigated in order to scrutinize one general model of manufacturing process and to define a manufacturing process preparation level. Development and introduction of the operational quality improvement model is based on a research conducted and results of methods and tools application possibilities in real manufacturing processes shipbuilding and automotive industry. Basic model structure is described and presented by appropriate general algorithm. Operational quality improvement model developed lays down main guidelines for practical and systematic application of quality improvements methods and tools.

Soil-landscape modelling using fuzzy c-means clustering of attribute data derived from a Digital Elevation Model (DEM).

NARCIS (Netherlands)

Bruin, de S.; Stein, A.

1998-01-01

This study explores the use of fuzzy c-means clustering of attribute data derived from a digital elevation model to represent transition zones in the soil-landscape. The conventional geographic model used for soil-landscape description is not able to properly deal with these. Fuzzy c-means

A Consistent Pricing Model for Index Options and Volatility Derivatives

DEFF Research Database (Denmark)

Kokholm, Thomas

to be priced consistently, while allowing for jumps in volatility and returns. An affine specification using Lévy processes as building blocks leads to analytically tractable pricing formulas for volatility derivatives, such as VIX options, as well as efficient numerical methods for pricing of European options...... on the underlying asset. The model has the convenient feature of decoupling the vanilla skews from spot/volatility correlations and allowing for different conditional correlations in large and small spot/volatility moves. We show that our model can simultaneously fit prices of European options on S&P 500 across...

A Consistent Pricing Model for Index Options and Volatility Derivatives

DEFF Research Database (Denmark)

Cont, Rama; Kokholm, Thomas

2013-01-01

to be priced consistently, while allowing for jumps in volatility and returns. An affine specification using Lévy processes as building blocks leads to analytically tractable pricing formulas for volatility derivatives, such as VIX options, as well as efficient numerical methods for pricing of European options...... on the underlying asset. The model has the convenient feature of decoupling the vanilla skews from spot/volatility correlations and allowing for different conditional correlations in large and small spot/volatility moves. We show that our model can simultaneously fit prices of European options on S&P 500 across...

Statistical modeling of phenological phases in Poland based on coupling satellite derived products and gridded meteorological data

Science.gov (United States)

Czernecki, Bartosz; Jabłońska, Katarzyna; Nowosad, Jakub

2016-04-01

), average monthly temperatures for each month over the previous year for each site, etc. A few commonly applied statistical methods, including multiple regression, random forest, and neural network techniques were tested and evaluated against the onset dates of phenophases. To avoid overfitting of the models, the dataset was divided into a calibration and a validation period using leave-one-out cross-validation method. The obtained results show good potential of using statistical models in filling the temporal and spatial gaps in data, as well as, for forecasting selected phenological phases. However, there are some clear limitations of applying modern satellite observation in plant phenology modelling. Therefore, most of the created phenology models are primarily based on agrometeorological indices with only slightly improvements while using satellite derived products.

Model improvements to simulate charging in SEM

Science.gov (United States)

Arat, K. T.; Klimpel, T.; Hagen, C. W.

2018-03-01

Charging of insulators is a complex phenomenon to simulate since the accuracy of the simulations is very sensitive to the interaction of electrons with matter and electric fields. In this study, we report model improvements for a previously developed Monte-Carlo simulator to more accurately simulate samples that charge. The improvements include both modelling of low energy electron scattering and charging of insulators. The new first-principle scattering models provide a more realistic charge distribution cloud in the material, and a better match between non-charging simulations and experimental results. Improvements on charging models mainly focus on redistribution of the charge carriers in the material with an induced conductivity (EBIC) and a breakdown model, leading to a smoother distribution of the charges. Combined with a more accurate tracing of low energy electrons in the electric field, we managed to reproduce the dynamically changing charging contrast due to an induced positive surface potential.

Vascular input function correction of inflow enhancement for improved pharmacokinetic modeling of liver DCE-MRI.

Science.gov (United States)

Ning, Jia; Schubert, Tilman; Johnson, Kevin M; Roldán-Alzate, Alejandro; Chen, Huijun; Yuan, Chun; Reeder, Scott B

2018-06-01

To propose a simple method to correct vascular input function (VIF) due to inflow effects and to test whether the proposed method can provide more accurate VIFs for improved pharmacokinetic modeling. A spoiled gradient echo sequence-based inflow quantification and contrast agent concentration correction method was proposed. Simulations were conducted to illustrate improvement in the accuracy of VIF estimation and pharmacokinetic fitting. Animal studies with dynamic contrast-enhanced MR scans were conducted before, 1 week after, and 2 weeks after portal vein embolization (PVE) was performed in the left portal circulation of pigs. The proposed method was applied to correct the VIFs for model fitting. Pharmacokinetic parameters fitted using corrected and uncorrected VIFs were compared between different lobes and visits. Simulation results demonstrated that the proposed method can improve accuracy of VIF estimation and pharmacokinetic fitting. In animal study results, pharmacokinetic fitting using corrected VIFs demonstrated changes in perfusion consistent with changes expected after PVE, whereas the perfusion estimates derived by uncorrected VIFs showed no significant changes. The proposed correction method improves accuracy of VIFs and therefore provides more precise pharmacokinetic fitting. This method may be promising in improving the reliability of perfusion quantification. Magn Reson Med 79:3093-3102, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Process correlation analysis model for process improvement identification.

Science.gov (United States)

Choi, Su-jin; Kim, Dae-Kyoo; Park, Sooyong

2014-01-01

Software process improvement aims at improving the development process of software systems. It is initiated by process assessment identifying strengths and weaknesses and based on the findings, improvement plans are developed. In general, a process reference model (e.g., CMMI) is used throughout the process of software process improvement as the base. CMMI defines a set of process areas involved in software development and what to be carried out in process areas in terms of goals and practices. Process areas and their elements (goals and practices) are often correlated due to the iterative nature of software development process. However, in the current practice, correlations of process elements are often overlooked in the development of an improvement plan, which diminishes the efficiency of the plan. This is mainly attributed to significant efforts and the lack of required expertise. In this paper, we present a process correlation analysis model that helps identify correlations of process elements from the results of process assessment. This model is defined based on CMMI and empirical data of improvement practices. We evaluate the model using industrial data.

Theoretical algorithms for satellite-derived sea surface temperatures

Science.gov (United States)

Barton, I. J.; Zavody, A. M.; O'Brien, D. M.; Cutten, D. R.; Saunders, R. W.; Llewellyn-Jones, D. T.

1989-03-01

Reliable climate forecasting using numerical models of the ocean-atmosphere system requires accurate data sets of sea surface temperature (SST) and surface wind stress. Global sets of these data will be supplied by the instruments to fly on the ERS 1 satellite in 1990. One of these instruments, the Along-Track Scanning Radiometer (ATSR), has been specifically designed to provide SST in cloud-free areas with an accuracy of 0.3 K. The expected capabilities of the ATSR can be assessed using transmission models of infrared radiative transfer through the atmosphere. The performances of several different models are compared by estimating the infrared brightness temperatures measured by the NOAA 9 AVHRR for three standard atmospheres. Of these, a computationally quick spectral band model is used to derive typical AVHRR and ATSR SST algorithms in the form of linear equations. These algorithms show that a low-noise 3.7-μm channel is required to give the best satellite-derived SST and that the design accuracy of the ATSR is likely to be achievable. The inclusion of extra water vapor information in the analysis did not improve the accuracy of multiwavelength SST algorithms, but some improvement was noted with the multiangle technique. Further modeling is required with atmospheric data that include both aerosol variations and abnormal vertical profiles of water vapor and temperature.

Soil hydraulic properties near saturation, an improved conductivity model

DEFF Research Database (Denmark)

Børgesen, Christen Duus; Jacobsen, Ole Hørbye; Hansen, Søren

2006-01-01

of commonly used hydraulic conductivity models and give suggestions for improved models. Water retention and near saturated and saturated hydraulic conductivity were measured for a variety of 81 top and subsoils. The hydraulic conductivity models by van Genuchten [van Genuchten, 1980. A closed-form equation...... for predicting the hydraulic conductivity of unsaturated soils. Soil Sci. Soc. Am. J. 44, 892–898.] (vGM) and Brooks and Corey, modified by Jarvis [Jarvis, 1991. MACRO—A Model of Water Movement and Solute Transport in Macroporous Soils. Swedish University of Agricultural Sciences. Department of Soil Sciences....... Optimising a matching factor (k0) improved the fit considerably whereas optimising the l-parameter in the vGM model improved the fit only slightly. The vGM was improved with an empirical scaling function to account for the rapid increase in conductivity near saturation. Using the improved models...

Phenotype analysis of early risk factors from electronic medical records improves image-derived diagnostic classifiers for optic nerve pathology

Science.gov (United States)

Chaganti, Shikha; Nabar, Kunal P.; Nelson, Katrina M.; Mawn, Louise A.; Landman, Bennett A.

2017-03-01

We examine imaging and electronic medical records (EMR) of 588 subjects over five major disease groups that affect optic nerve function. An objective evaluation of the role of imaging and EMR data in diagnosis of these conditions would improve understanding of these diseases and help in early intervention. We developed an automated image processing pipeline that identifies the orbital structures within the human eyes from computed tomography (CT) scans, calculates structural size, and performs volume measurements. We customized the EMR-based phenome-wide association study (PheWAS) to derive diagnostic EMR phenotypes that occur at least two years prior to the onset of the conditions of interest from a separate cohort of 28,411 ophthalmology patients. We used random forest classifiers to evaluate the predictive power of image-derived markers, EMR phenotypes, and clinical visual assessments in identifying disease cohorts from a control group of 763 patients without optic nerve disease. Image-derived markers showed more predictive power than clinical visual assessments or EMR phenotypes. However, the addition of EMR phenotypes to the imaging markers improves the classification accuracy against controls: the AUC improved from 0.67 to 0.88 for glaucoma, 0.73 to 0.78 for intrinsic optic nerve disease, 0.72 to 0.76 for optic nerve edema, 0.72 to 0.77 for orbital inflammation, and 0.81 to 0.85 for thyroid eye disease. This study illustrates the importance of diagnostic context for interpretation of image-derived markers and the proposed PheWAS technique provides a flexible approach for learning salient features of patient history and incorporating these data into traditional machine learning analyses.

A Semianalytical Solution of the Fractional Derivative Model and Its Application in Financial Market

Directory of Open Access Journals (Sweden)

Lina Song

2018-01-01

Full Text Available Fractional differential equation has been introduced to the financial theory, which presents new ideas and tools for the theoretical researches and the practical applications. In the work, an approximate semianalytical solution of the time-fractional European option pricing model is derived using the method of combining the enhanced technique of Adomian decomposition method with the finite difference method. And then the result is introduced in China’s financial market. The work makes every effort to test the feasibility of the fractional derivative model in the actual financial market.

An improved empirical dynamic control system model of global mean sea level rise and surface temperature change

Science.gov (United States)

Wu, Qing; Luu, Quang-Hung; Tkalich, Pavel; Chen, Ge

2018-04-01

Having great impacts on human lives, global warming and associated sea level rise are believed to be strongly linked to anthropogenic causes. Statistical approach offers a simple and yet conceptually verifiable combination of remotely connected climate variables and indices, including sea level and surface temperature. We propose an improved statistical reconstruction model based on the empirical dynamic control system by taking into account the climate variability and deriving parameters from Monte Carlo cross-validation random experiments. For the historic data from 1880 to 2001, we yielded higher correlation results compared to those from other dynamic empirical models. The averaged root mean square errors are reduced in both reconstructed fields, namely, the global mean surface temperature (by 24-37%) and the global mean sea level (by 5-25%). Our model is also more robust as it notably diminished the unstable problem associated with varying initial values. Such results suggest that the model not only enhances significantly the global mean reconstructions of temperature and sea level but also may have a potential to improve future projections.

Novel Thiazole Derivatives of Medicinal Potential: Synthesis and Modeling

Directory of Open Access Journals (Sweden)

Nour E. A. Abdel-Sattar

2017-01-01

Full Text Available This paper reports on the synthesis of new thiazole derivatives that could be profitably exploited in medical treatment of tumors. Molecular electronic structures have been modeled within density function theory (DFT framework. Reactivity indices obtained from the frontier orbital energies as well as electrostatic potential energy maps are discussed and correlated with the molecular structure. X-ray crystallographic data of one of the new compounds is measured and used to support and verify the theoretical results.

Badhwar-O'Neill 2011 Galactic Cosmic Ray Model Update and Future Improvements

Science.gov (United States)

O'Neill, Pat M.; Kim, Myung-Hee Y.

2014-01-01

The Badhwar-O'Neill Galactic Cosmic Ray (GCR) Model based on actual GR measurements is used by deep space mission planners for the certification of micro-electronic systems and the analysis of radiation health risks to astronauts in space missions. The BO GCR Model provides GCR flux in deep space (outside the earth's magnetosphere) for any given time from 1645 to present. The energy spectrum from 50 MeV/n-20 GeV/n is provided for ions from hydrogen to uranium. This work describes the most recent version of the BO GCR model (BO'11). BO'11 determines the GCR flux at a given time applying an empirical time delay function to past sunspot activity. We describe the GCR measurement data used in the BO'11 update - modern data from BESS, PAMELA, CAPRICE, and ACE emphasized for than the older balloon data used for the previous BO model (BO'10). We look at the GCR flux for the last 24 solar minima and show how much greater the flux was for the cycle 24 minimum in 2010. The BO'11 Model uses the traditional, steady-state Fokker-Planck differential equation to account for particle transport in the heliosphere due to diffusion, convection, and adiabatic deceleration. It assumes a radially symmetrical diffusion coefficient derived from magnetic disturbances caused by sunspots carried onward by a constant solar wind. A more complex differential equation is now being tested to account for particle transport in the heliosphere in the next generation BO model. This new model is time-dependent (no longer a steady state model). In the new model, the dynamics and anti-symmetrical features of the actual heliosphere are accounted for so empirical time delay functions will no longer be required. The new model will be capable of simulating the more subtle features of modulation - such as the Sun's polarity and modulation dependence on the gradient and curvature drift. This improvement is expected to significantly improve the fidelity of the BO GCR model. Preliminary results of its

Evaluating measurement of dynamic constructs: defining a measurement model of derivatives.

Science.gov (United States)

Estabrook, Ryne

2015-03-01

While measurement evaluation has been embraced as an important step in psychological research, evaluating measurement structures with longitudinal data is fraught with limitations. This article defines and tests a measurement model of derivatives (MMOD), which is designed to assess the measurement structure of latent constructs both for analyses of between-person differences and for the analysis of change. Simulation results indicate that MMOD outperforms existing models for multivariate analysis and provides equivalent fit to data generation models. Additional simulations show MMOD capable of detecting differences in between-person and within-person factor structures. Model features, applications, and future directions are discussed. (c) 2015 APA, all rights reserved).

Mathematical modeling of tetrahydroimidazole benzodiazepine-1-one derivatives as an anti HIV agent

Science.gov (United States)

Ojha, Lokendra Kumar

2017-07-01

The goal of the present work is the study of drug receptor interaction via QSAR (Quantitative Structure-Activity Relationship) analysis for 89 set of TIBO (Tetrahydroimidazole Benzodiazepine-1-one) derivatives. MLR (Multiple Linear Regression) method is utilized to generate predictive models of quantitative structure-activity relationships between a set of molecular descriptors and biological activity (IC50). The best QSAR model was selected having a correlation coefficient (r) of 0.9299 and Standard Error of Estimation (SEE) of 0.5022, Fisher Ratio (F) of 159.822 and Quality factor (Q) of 1.852. This model is statistically significant and strongly favours the substitution of sulphur atom, IS i.e. indicator parameter for -Z position of the TIBO derivatives. Two other parameter logP (octanol-water partition coefficient) and SAG (Surface Area Grid) also played a vital role in the generation of best QSAR model. All three descriptor shows very good stability towards data variation in leave-one-out (LOO).

Study on Software Quality Improvement based on Rayleigh Model and PDCA Model

OpenAIRE

Ning Jingfeng; Hu Ming

2013-01-01

As the software industry gradually becomes mature, software quality is regarded as the life of a software enterprise. This article discusses how to improve the quality of software, applies Rayleigh model and PDCA model to the software quality management, combines with the defect removal effectiveness index, exerts PDCA model to solve the problem of quality management objectives when using the Rayleigh model in bidirectional quality improvement strategies of software quality management, a...

Derivation of the Verlinde formula from Chern-Simons theory and the G/G model

International Nuclear Information System (INIS)

Blau, M.; Thompson, G.

1993-01-01

We give a derivation of the Verlinde formula for the G k WZW model from Chern-Simons theory, without taking recourse to CFT, by calculating explicitly the partition function Z ΣxS 1 of Σ x S 1 with an arbitrary number of labelled punctures. By what is essentially a suitable gauge choice, Z ΣxS 1 is reduced to the partition function of an abelian topological field theory on Σ (a deformation of non-abelian BF and Yang-Mills theory) whose evaluation is straightforward. This relates the Verlinde formula to the Ray-Singer torsion of Σ x S 1 . We derive the G k /G k model from Chern-Simons theory, proving their equivalence, and give an alternative derivation of the Verlinde formula by calculating the G k /G k path integral via a functional version of the Weyl integral formula. From this point of view the Verlinde formula arises from the corresponding jacobian, the Weyl determinant. Also, a novel derivation of the shift k → k + h is given, based on the index of the twisted Dolbeault complex. (orig.)

A Modified Groundwater Flow Model Using the Space Time Riemann-Liouville Fractional Derivatives Approximation

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Abdon Atangana

2014-01-01

Full Text Available The notion of uncertainty in groundwater hydrology is of great importance as it is known to result in misleading output when neglected or not properly accounted for. In this paper we examine this effect in groundwater flow models. To achieve this, we first introduce the uncertainties functions u as function of time and space. The function u accounts for the lack of knowledge or variability of the geological formations in which flow occur (aquifer in time and space. We next make use of Riemann-Liouville fractional derivatives that were introduced by Kobelev and Romano in 2000 and its approximation to modify the standard version of groundwater flow equation. Some properties of the modified Riemann-Liouville fractional derivative approximation are presented. The classical model for groundwater flow, in the case of density-independent flow in a uniform homogeneous aquifer is reformulated by replacing the classical derivative by the Riemann-Liouville fractional derivatives approximations. The modified equation is solved via the technique of green function and the variational iteration method.

Modeling marbled murrelet (Brachyramphus marmoratus) habitat using LiDAR-derived canopy data

Science.gov (United States)

Hagar, Joan C.; Eskelson, Bianca N.I.; Haggerty, Patricia K.; Nelson, S. Kim; Vesely, David G.

2014-01-01

LiDAR (Light Detection And Ranging) is an emerging remote-sensing tool that can provide fine-scale data describing vertical complexity of vegetation relevant to species that are responsive to forest structure. We used LiDAR data to estimate occupancy probability for the federally threatened marbled murrelet (Brachyramphus marmoratus) in the Oregon Coast Range of the United States. Our goal was to address the need identified in the Recovery Plan for a more accurate estimate of the availability of nesting habitat by developing occupancy maps based on refined measures of nest-strand structure. We used murrelet occupancy data collected by the Bureau of Land Management Coos Bay District, and canopy metrics calculated from discrete return airborne LiDAR data, to fit a logistic regression model predicting the probability of occupancy. Our final model for stand-level occupancy included distance to coast, and 5 LiDAR-derived variables describing canopy structure. With an area under the curve value (AUC) of 0.74, this model had acceptable discrimination and fair agreement (Cohen's κ = 0.24), especially considering that all sites in our sample were regarded by managers as potential habitat. The LiDAR model provided better discrimination between occupied and unoccupied sites than did a model using variables derived from Gradient Nearest Neighbor maps that were previously reported as important predictors of murrelet occupancy (AUC = 0.64, κ = 0.12). We also evaluated LiDAR metrics at 11 known murrelet nest sites. Two LiDAR-derived variables accurately discriminated nest sites from random sites (average AUC = 0.91). LiDAR provided a means of quantifying 3-dimensional canopy structure with variables that are ecologically relevant to murrelet nesting habitat, and have not been as accurately quantified by other mensuration methods.

Modeling the diurnal tide with dissipation derived from UARS/HRDI measurements

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M. A. Geller

1997-09-01

Full Text Available This paper uses dissipation values derived from UARS/HRDI observations in a recently published diurnal-tide model. These model structures compare quite well with the UARS/HRDI observations with respect to the annual variation of the diurnal tidal amplitudes and the size of the amplitudes themselves. It is suggested that the annual variation of atmospheric dissipation in the mesosphere-lower thermosphere is a major controlling factor in determining the annual variation of the diurnal tide.

On the derivation of approximations to cellular automata models and the assumption of independence.

Science.gov (United States)

Davies, K J; Green, J E F; Bean, N G; Binder, B J; Ross, J V

2014-07-01

Cellular automata are discrete agent-based models, generally used in cell-based applications. There is much interest in obtaining continuum models that describe the mean behaviour of the agents in these models. Previously, continuum models have been derived for agents undergoing motility and proliferation processes, however, these models only hold under restricted conditions. In order to narrow down the reason for these restrictions, we explore three possible sources of error in deriving the model. These sources are the choice of limiting arguments, the use of a discrete-time model as opposed to a continuous-time model and the assumption of independence between the state of sites. We present a rigorous analysis in order to gain a greater understanding of the significance of these three issues. By finding a limiting regime that accurately approximates the conservation equation for the cellular automata, we are able to conclude that the inaccuracy between our approximation and the cellular automata is completely based on the assumption of independence. Copyright © 2014 Elsevier Inc. All rights reserved.

Gravity model improvement using GEOS-3 (GEM 9 and 10)

Science.gov (United States)

Lerch, F. J.; Klosko, S. M.; Laubscher, R. E.; Wagner, C. A.

1977-01-01

The use of collocation permitted GEM 9 to be a larger field than previous derived satellite models, GEM 9 having harmonics complete to 20 x 20 with selected higher degree terms. The satellite data set has approximately 840,000 observations, of which 200,000 are laser ranges taken on 9 satellites equipped with retroreflectors. GEM 10 is complete to 22 x 22 with selected higher degree terms out to degree and order 30 amounting to a total of 592 coefficients. Comparisons with surface gravity and altimeter data indicate a substantial improvement in GEM 9 over previous satellite solutions; GEM 9 is in even closer agreement with surface data than the previously published GEM 6 solution which contained surface gravity. In particular the free air gravity anomalies calculated from GEM 9 and a surface gravity solution are in excellent agreement for the high degree terms.

Estimation efficiency of usage satellite derived and modelled biophysical products for yield forecasting

Science.gov (United States)

Kolotii, Andrii; Kussul, Nataliia; Skakun, Sergii; Shelestov, Andrii; Ostapenko, Vadim; Oliinyk, Tamara

2015-04-01

Efficient and timely crop monitoring and yield forecasting are important tasks for ensuring of stability and sustainable economic development [1]. As winter crops pay prominent role in agriculture of Ukraine - the main focus of this study is concentrated on winter wheat. In our previous research [2, 3] it was shown that usage of biophysical parameters of crops such as FAPAR (derived from Geoland-2 portal as for SPOT Vegetation data) is far more efficient for crop yield forecasting to NDVI derived from MODIS data - for available data. In our current work efficiency of usage such biophysical parameters as LAI, FAPAR, FCOVER (derived from SPOT Vegetation and PROBA-V data at resolution of 1 km and simulated within WOFOST model) and NDVI product (derived from MODIS) for winter wheat monitoring and yield forecasting is estimated. As the part of crop monitoring workflow (vegetation anomaly detection, vegetation indexes and products analysis) and yield forecasting SPIRITS tool developed by JRC is used. Statistics extraction is done for landcover maps created in SRI within FP-7 SIGMA project. Efficiency of usage satellite based and modelled with WOFOST model biophysical products is estimated. [1] N. Kussul, S. Skakun, A. Shelestov, O. Kussul, "Sensor Web approach to Flood Monitoring and Risk Assessment", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 815-818. [2] F. Kogan, N. Kussul, T. Adamenko, S. Skakun, O. Kravchenko, O. Kryvobok, A. Shelestov, A. Kolotii, O. Kussul, and A. Lavrenyuk, "Winter wheat yield forecasting in Ukraine based on Earth observation, meteorological data and biophysical models," International Journal of Applied Earth Observation and Geoinformation, vol. 23, pp. 192-203, 2013. [3] Kussul O., Kussul N., Skakun S., Kravchenko O., Shelestov A., Kolotii A, "Assessment of relative efficiency of using MODIS data to winter wheat yield forecasting in Ukraine", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 3235 - 3238.

Discovery of Antibiotics-derived Polymers for Gene Delivery using Combinatorial Synthesis and Cheminformatics Modeling

Science.gov (United States)

Potta, Thrimoorthy; Zhen, Zhuo; Grandhi, Taraka Sai Pavan; Christensen, Matthew D.; Ramos, James; Breneman, Curt M.; Rege, Kaushal

2014-01-01

We describe the combinatorial synthesis and cheminformatics modeling of aminoglycoside antibiotics-derived polymers for transgene delivery and expression. Fifty-six polymers were synthesized by polymerizing aminoglycosides with diglycidyl ether cross-linkers. Parallel screening resulted in identification of several lead polymers that resulted in high transgene expression levels in cells. The role of polymer physicochemical properties in determining efficacy of transgene expression was investigated using Quantitative Structure-Activity Relationship (QSAR) cheminformatics models based on Support Vector Regression (SVR) and ‘building block’ polymer structures. The QSAR model exhibited high predictive ability, and investigation of descriptors in the model, using molecular visualization and correlation plots, indicated that physicochemical attributes related to both, aminoglycosides and diglycidyl ethers facilitated transgene expression. This work synergistically combines combinatorial synthesis and parallel screening with cheminformatics-based QSAR models for discovery and physicochemical elucidation of effective antibiotics-derived polymers for transgene delivery in medicine and biotechnology. PMID:24331709

Adipose-derived mesenchymal stem cells accelerate nerve regeneration and functional recovery in a rat model of recurrent laryngeal nerve injury

Directory of Open Access Journals (Sweden)

Yun Li

2017-01-01

Full Text Available Medialization thyroplasty or injection laryngoplasty for unilateral vocal fold paralysis cannot restore mobility of the vocal fold. Recent studies have shown that transplantation of mesenchymal stem cells is effective in the repair of nerve injuries. This study investigated whether adipose-derived stem cell transplantation could repair recurrent laryngeal nerve injury. Rat models of recurrent laryngeal nerve injury were established by crushing with micro forceps. Adipose-derived mesenchymal stem cells (ADSCs; 8 × 105 or differentiated Schwann-like adipose-derived mesenchymal stem cells (dADSCs; 8 × 105 or extracellular matrix were injected at the site of injury. At 2, 4 and 6 weeks post-surgery, a higher density of myelinated nerve fiber, thicker myelin sheath, improved vocal fold movement, better recovery of nerve conduction capacity and reduced thyroarytenoid muscle atrophy were found in ADSCs and dADSCs groups compared with the extracellular matrix group. The effects were more pronounced in the ADSCs group than in the dADSCs group. These experimental results indicated that ADSCs transplantation could be an early interventional strategy to promote regeneration after recurrent laryngeal nerve injury.

An Improved Scale-Adaptive Simulation Model for Massively Separated Flows

Directory of Open Access Journals (Sweden)

Yue Liu

2018-01-01

Full Text Available A new hybrid modelling method termed improved scale-adaptive simulation (ISAS is proposed by introducing the von Karman operator into the dissipation term of the turbulence scale equation, proper derivation as well as constant calibration of which is presented, and the typical circular cylinder flow at Re = 3900 is selected for validation. As expected, the proposed ISAS approach with the concept of scale-adaptive appears more efficient than the original SAS method in obtaining a convergent resolution, meanwhile, comparable with DES in visually capturing the fine-scale unsteadiness. Furthermore, the grid sensitivity issue of DES is encouragingly remedied benefiting from the local-adjusted limiter. The ISAS simulation turns out to attractively represent the development of the shear layers and the flow profiles of the recirculation region, and thus, the focused statistical quantities such as the recirculation length and drag coefficient are closer to the available measurements than DES and SAS outputs. In general, the new modelling method, combining the features of DES and SAS concepts, is capable to simulate turbulent structures down to the grid limit in a simple and effective way, which is practically valuable for engineering flows.

Intramuscular injection of human umbilical cord-derived mesenchymal stem cells improves cardiac function in dilated cardiomyopathy rats.

Science.gov (United States)

Mao, Chenggang; Hou, Xu; Wang, Benzhen; Chi, Jingwei; Jiang, Yanjie; Zhang, Caining; Li, Zipu

2017-01-28

Stem cells provide a promising candidate for the treatment of the fatal pediatric dilated cardiomyopathy (DCM). This study aimed to investigate the effects of intramuscular injection of human umbilical cord-derived mesenchymal stem cells (hUCMSCs) on the cardiac function of a DCM rat model. A DCM model was established by intraperitoneal injections of doxorubicin in Sprague-Dawley rats. hUCMSCs at different concentrations or cultured medium were injected via limb skeletal muscles, with blank medium injected as the control. The rats were monitored for 4 weeks, meanwhile BNP, cTNI, VEGF, HGF, GM-CSF, and LIF in the peripheral blood were examined by ELISA, and cardiac function was monitored by echocardiography (Echo-CG). Finally, the expression of IGF-1, HGF, and VEGF in the myocardium was examined by histoimmunochemistry and real-time PCR, and the ultrastructure of the myocardium was examined by electron microscopy. Injection of hUCMSCs markedly improved cardiac function in the DCM rats by significantly elevating left ventricular ejection fraction (LVEF) and left ventricular fraction shortening (LVFS). The BNP and cTNI levels in the peripheral blood were reduced by hUCMSCs, while HGF, LIF, GM-CSF, and VEGF were increased by hUCMSCs. Expression of IGF-1, HGF, and VEGF in the myocardium from the DCM rats was significantly increased by hUCMSC injection. Furthermore, hUCMSCs protected the ultrastructure of cardiomyocytes by attenuating mitochondrial swelling and maintaining sarcolemma integrity. Intramuscular injection of UCMSCs can improve DCM-induced cardiac function impairment and protect the myocardium. These effects may be mediated by regulation of relevant cytokines in serum and the myocardium.

Identification of the Structural Features of Guanine Derivatives as MGMT Inhibitors Using 3D-QSAR Modeling Combined with Molecular Docking

Directory of Open Access Journals (Sweden)

Guohui Sun

2016-06-01

Full Text Available DNA repair enzyme O6-methylguanine-DNA methyltransferase (MGMT, which plays an important role in inducing drug resistance against alkylating agents that modify the O6 position of guanine in DNA, is an attractive target for anti-tumor chemotherapy. A series of MGMT inhibitors have been synthesized over the past decades to improve the chemotherapeutic effects of O6-alkylating agents. In the present study, we performed a three-dimensional quantitative structure activity relationship (3D-QSAR study on 97 guanine derivatives as MGMT inhibitors using comparative molecular field analysis (CoMFA and comparative molecular similarity indices analysis (CoMSIA methods. Three different alignment methods (ligand-based, DFT optimization-based and docking-based alignment were employed to develop reliable 3D-QSAR models. Statistical parameters derived from the models using the above three alignment methods showed that the ligand-based CoMFA (Qcv2 = 0.672 and Rncv2 = 0.997 and CoMSIA (Qcv2 = 0.703 and Rncv2 = 0.946 models were better than the other two alignment methods-based CoMFA and CoMSIA models. The two ligand-based models were further confirmed by an external test-set validation and a Y-randomization examination. The ligand-based CoMFA model (Qext2 = 0.691, Rpred2 = 0.738 and slope k = 0.91 was observed with acceptable external test-set validation values rather than the CoMSIA model (Qext2 = 0.307, Rpred2 = 0.4 and slope k = 0.719. Docking studies were carried out to predict the binding modes of the inhibitors with MGMT. The results indicated that the obtained binding interactions were consistent with the 3D contour maps. Overall, the combined results of the 3D-QSAR and the docking obtained in this study provide an insight into the understanding of the interactions between guanine derivatives and MGMT protein, which will assist in designing novel MGMT inhibitors with desired activity.

Neural assembly models derived through nano-scale measurements.

Energy Technology Data Exchange (ETDEWEB)

Fan, Hongyou; Branda, Catherine; Schiek, Richard Louis; Warrender, Christina E.; Forsythe, James Chris

2009-09-01

This report summarizes accomplishments of a three-year project focused on developing technical capabilities for measuring and modeling neuronal processes at the nanoscale. It was successfully demonstrated that nanoprobes could be engineered that were biocompatible, and could be biofunctionalized, that responded within the range of voltages typically associated with a neuronal action potential. Furthermore, the Xyce parallel circuit simulator was employed and models incorporated for simulating the ion channel and cable properties of neuronal membranes. The ultimate objective of the project had been to employ nanoprobes in vivo, with the nematode C elegans, and derive a simulation based on the resulting data. Techniques were developed allowing the nanoprobes to be injected into the nematode and the neuronal response recorded. To the authors's knowledge, this is the first occasion in which nanoparticles have been successfully employed as probes for recording neuronal response in an in vivo animal experimental protocol.

Network-based modeling and intelligent data mining of social media for improving care.

Science.gov (United States)

Akay, Altug; Dragomir, Andrei; Erlandsson, Bjorn-Erik

2015-01-01

Intelligently extracting knowledge from social media has recently attracted great interest from the Biomedical and Health Informatics community to simultaneously improve healthcare outcomes and reduce costs using consumer-generated opinion. We propose a two-step analysis framework that focuses on positive and negative sentiment, as well as the side effects of treatment, in users' forum posts, and identifies user communities (modules) and influential users for the purpose of ascertaining user opinion of cancer treatment. We used a self-organizing map to analyze word frequency data derived from users' forum posts. We then introduced a novel network-based approach for modeling users' forum interactions and employed a network partitioning method based on optimizing a stability quality measure. This allowed us to determine consumer opinion and identify influential users within the retrieved modules using information derived from both word-frequency data and network-based properties. Our approach can expand research into intelligently mining social media data for consumer opinion of various treatments to provide rapid, up-to-date information for the pharmaceutical industry, hospitals, and medical staff, on the effectiveness (or ineffectiveness) of future treatments.

Dynamic assessment of nonlinear typical section aeroviscoelastic systems using fractional derivative-based viscoelastic model

Science.gov (United States)

Sales, T. P.; Marques, Flávio D.; Pereira, Daniel A.; Rade, Domingos A.

2018-06-01

Nonlinear aeroelastic systems are prone to the appearance of limit cycle oscillations, bifurcations, and chaos. Such problems are of increasing concern in aircraft design since there is the need to control nonlinear instabilities and improve safety margins, at the same time as aircraft are subjected to increasingly critical operational conditions. On the other hand, in spite of the fact that viscoelastic materials have already been successfully used for the attenuation of undesired vibrations in several types of mechanical systems, a small number of research works have addressed the feasibility of exploring the viscoelastic effect to improve the behavior of nonlinear aeroelastic systems. In this context, the objective of this work is to assess the influence of viscoelastic materials on the aeroelastic features of a three-degrees-of-freedom typical section with hardening structural nonlinearities. The equations of motion are derived accounting for the presence of viscoelastic materials introduced in the resilient elements associated to each degree-of-freedom. A constitutive law based on fractional derivatives is adopted, which allows the modeling of temperature-dependent viscoelastic behavior in time and frequency domains. The unsteady aerodynamic loading is calculated based on the classical linear potential theory for arbitrary airfoil motion. The aeroelastic behavior is investigated through time domain simulations, and subsequent frequency transformations, from which bifurcations are identified from diagrams of limit cycle oscillations amplitudes versus airspeed. The influence of the viscoelastic effect on the aeroelastic behavior, for different values of temperature, is also investigated. The numerical simulations show that viscoelastic damping can increase the flutter speed and reduce the amplitudes of limit cycle oscillations. These results prove the potential that viscoelastic materials have to increase aircraft components safety margins regarding aeroelastic

Multi-factor energy price models and exotic derivatives pricing

Science.gov (United States)

Hikspoors, Samuel

The high pace at which many of the world's energy markets have gradually been opened to competition have generated a significant amount of new financial activity. Both academicians and practitioners alike recently started to develop the tools of energy derivatives pricing/hedging as a quantitative topic of its own. The energy contract structures as well as their underlying asset properties set the energy risk management industry apart from its more standard equity and fixed income counterparts. This thesis naturally contributes to these broad market developments in participating to the advances of the mathematical tools aiming at a better theory of energy contingent claim pricing/hedging. We propose many realistic two-factor and three-factor models for spot and forward price processes that generalize some well known and standard modeling assumptions. We develop the associated pricing methodologies and propose stable calibration algorithms that motivate the application of the relevant modeling schemes.

Improving Satellite-Driven PM2.5 Models with VIIRS Nighttime Light Data in the Beijing–Tianjin–Hebei Region, China

Directory of Open Access Journals (Sweden)

Xiya Zhang

2017-08-01

Full Text Available Previous studies have estimated ground-level concentrations of particulate matter 2.5 (PM2.5 using satellite-derived aerosol optical depth (AOD in conjunction with meteorological and land use variables. However, the impacts of urbanization on air pollution for predicting PM2.5 are seldom considered. Nighttime light (NTL data, acquired with the Visible Infrared Imaging Radiometer Suite (VIIRS aboard the Suomi National Polar-orbiting Partnership (S-NPP satellite, could be useful for predictions because they have been shown to be good indicators of the urbanization and human activity that can affect PM2.5 concentrations. This study investigated the potential of incorporating VIIRS NTL data in statistical models for PM2.5 concentration predictions. We developed a mixed-effects model to derive daily estimations of surface PM2.5 levels in the Beijing–Tianjin–Hebei region using 3 km resolution satellite AOD and VIIRS NTL data. The results showed the addition of NTL information could improve the performance of the PM2.5 prediction model. The NTL data revealed additional details for predication results in areas with low PM2.5 concentrations and greater apparent seasonal variation due to the seasonal variability of human activity. Comparison showed prediction accuracy was improved more substantially for the model using NTL directly than for the model using the vegetation-adjusted NTL urban index that included NTL. Our findings indicate that VIIRS NTL data have potential for predicting PM2.5 and that they could constitute a useful supplemental data source for estimating ground-level PM2.5 distributions.

Trans-synaptic zinc mobilization improves social interaction in two mouse models of autism through NMDAR activation

Science.gov (United States)

Lee, Eun-Jae; Lee, Hyejin; Huang, Tzyy-Nan; Chung, Changuk; Shin, Wangyong; Kim, Kyungdeok; Koh, Jae-Young; Hsueh, Yi-Ping; Kim, Eunjoon

2015-01-01

Genetic aspects of autism spectrum disorders (ASDs) have recently been extensively explored, but environmental influences that affect ASDs have received considerably less attention. Zinc (Zn) is a nutritional factor implicated in ASDs, but evidence for a strong association and linking mechanism is largely lacking. Here we report that trans-synaptic Zn mobilization rapidly rescues social interaction in two independent mouse models of ASD. In mice lacking Shank2, an excitatory postsynaptic scaffolding protein, postsynaptic Zn elevation induced by clioquinol (a Zn chelator and ionophore) improves social interaction. Postsynaptic Zn is mainly derived from presynaptic pools and activates NMDA receptors (NMDARs) through postsynaptic activation of the tyrosine kinase Src. Clioquinol also improves social interaction in mice haploinsufficient for the transcription factor Tbr1, which accompanies NMDAR activation in the amygdala. These results suggest that trans-synaptic Zn mobilization induced by clioquinol rescues social deficits in mouse models of ASD through postsynaptic Src and NMDAR activation. PMID:25981743

Selection of productivity improvement techniques via mathematical modeling

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Mahassan M. Khater

2011-07-01

Full Text Available This paper presents a new mathematical model to select an optimal combination of productivity improvement techniques. The proposed model of this paper considers four-stage cycle productivity and the productivity is assumed to be a linear function of fifty four improvement techniques. The proposed model of this paper is implemented for a real-world case study of manufacturing plant. The resulted problem is formulated as a mixed integer programming which can be solved for optimality using traditional methods. The preliminary results of the implementation of the proposed model of this paper indicate that the productivity can be improved through a change on equipments and it can be easily applied for both manufacturing and service industries.

Modeling the ascent of sounding balloons: derivation of the vertical air motion

Directory of Open Access Journals (Sweden)

A. Gallice

2011-10-01

Full Text Available A new model to describe the ascent of sounding balloons in the troposphere and lower stratosphere (up to ∼30–35 km altitude is presented. Contrary to previous models, detailed account is taken of both the variation of the drag coefficient with altitude and the heat imbalance between the balloon and the atmosphere. To compensate for the lack of data on the drag coefficient of sounding balloons, a reference curve for the relationship between drag coefficient and Reynolds number is derived from a dataset of flights launched during the Lindenberg Upper Air Methods Intercomparisons (LUAMI campaign. The transfer of heat from the surrounding air into the balloon is accounted for by solving the radial heat diffusion equation inside the balloon. In its present state, the model does not account for solar radiation, i.e. it is only able to describe the ascent of balloons during the night. It could however be adapted to also represent daytime soundings, with solar radiation modeled as a diffusive process. The potential applications of the model include the forecast of the trajectory of sounding balloons, which can be used to increase the accuracy of the match technique, and the derivation of the air vertical velocity. The latter is obtained by subtracting the ascent rate of the balloon in still air calculated by the model from the actual ascent rate. This technique is shown to provide an approximation for the vertical air motion with an uncertainty error of 0.5 m s⁻¹ in the troposphere and 0.2 m s⁻¹ in the stratosphere. An example of extraction of the air vertical velocity is provided in this paper. We show that the air vertical velocities derived from the balloon soundings in this paper are in general agreement with small-scale atmospheric velocity fluctuations related to gravity waves, mechanical turbulence, or other small-scale air motions measured during the SUCCESS campaign (Subsonic Aircraft: Contrail and Cloud Effects

Improved sphincter contractility after allogenic muscle-derived progenitor cell injection into the denervated rat urethra.

Science.gov (United States)

Cannon, Tracy W; Lee, Ji Youl; Somogyi, George; Pruchnic, Ryan; Smith, Christopher P; Huard, Johnny; Chancellor, Michael B

2003-11-01

To study the physiologic outcome of allogenic transplant of muscle-derived progenitor cells (MDPCs) in the denervated female rat urethra. MDPCs were isolated from muscle biopsies of normal 6-week-old Sprague-Dawley rats and purified using the preplate technique. Sciatic nerve-transected rats were used as a model of stress urinary incontinence. The experimental group was divided into three subgroups: control, denervated plus 20 microL saline injection, and denervated plus allogenic MDPCs (1 to 1.5 x 10(6) cells) injection. Two weeks after injection, urethral muscle strips were prepared and underwent electrical field stimulation. The pharmacologic effects of d-tubocurare, phentolamine, and tetrodotoxin on the urethral strips were assessed by contractions induced by electrical field stimulation. The urethral tissues also underwent immunohistochemical staining for fast myosin heavy chain and CD4-activated lymphocytes. Urethral denervation resulted in a significant decrease of the maximal fast-twitch muscle contraction amplitude to only 8.77% of the normal urethra and partial impairment of smooth muscle contractility. Injection of MDPCs into the denervated sphincter significantly improved the fast-twitch muscle contraction amplitude to 87.02% of normal animals. Immunohistochemistry revealed a large amount of new skeletal muscle fiber formation at the injection site of the urethra with minimal inflammation. CD4 staining showed minimal lymphocyte infiltration around the MDPC injection sites. Urethral denervation resulted in near-total abolishment of the skeletal muscle and partial impairment of smooth muscle contractility. Allogenic MDPCs survived 2 weeks in sciatic nerve-transected urethra with minimal inflammation. This is the first report of the restoration of deficient urethral sphincter function through muscle-derived progenitor cell tissue engineering. MDPC-mediated cellular urethral myoplasty warrants additional investigation as a new method to treat stress urinary

Statistical Analyses of High-Resolution Aircraft and Satellite Observations of Sea Ice: Applications for Improving Model Simulations

Science.gov (United States)

Farrell, S. L.; Kurtz, N. T.; Richter-Menge, J.; Harbeck, J. P.; Onana, V.

2012-12-01

Satellite-derived estimates of ice thickness and observations of ice extent over the last decade point to a downward trend in the basin-scale ice volume of the Arctic Ocean. This loss has broad-ranging impacts on the regional climate and ecosystems, as well as implications for regional infrastructure, marine navigation, national security, and resource exploration. New observational datasets at small spatial and temporal scales are now required to improve our understanding of physical processes occurring within the ice pack and advance parameterizations in the next generation of numerical sea-ice models. High-resolution airborne and satellite observations of the sea ice are now available at meter-scale resolution or better that provide new details on the properties and morphology of the ice pack across basin scales. For example the NASA IceBridge airborne campaign routinely surveys the sea ice of the Arctic and Southern Oceans with an advanced sensor suite including laser and radar altimeters and digital cameras that together provide high-resolution measurements of sea ice freeboard, thickness, snow depth and lead distribution. Here we present statistical analyses of the ice pack primarily derived from the following IceBridge instruments: the Digital Mapping System (DMS), a nadir-looking, high-resolution digital camera; the Airborne Topographic Mapper, a scanning lidar; and the University of Kansas snow radar, a novel instrument designed to estimate snow depth on sea ice. Together these instruments provide data from which a wide range of sea ice properties may be derived. We provide statistics on lead distribution and spacing, lead width and area, floe size and distance between floes, as well as ridge height, frequency and distribution. The goals of this study are to (i) identify unique statistics that can be used to describe the characteristics of specific ice regions, for example first-year/multi-year ice, diffuse ice edge/consolidated ice pack, and convergent

Finite-time adaptive sliding mode force control for electro-hydraulic load simulator based on improved GMS friction model

Science.gov (United States)

Kang, Shuo; Yan, Hao; Dong, Lijing; Li, Changchun

2018-03-01

This paper addresses the force tracking problem of electro-hydraulic load simulator under the influence of nonlinear friction and uncertain disturbance. A nonlinear system model combined with the improved generalized Maxwell-slip (GMS) friction model is firstly derived to describe the characteristics of load simulator system more accurately. Then, by using particle swarm optimization (PSO) algorithm ​combined with the system hysteresis characteristic analysis, the GMS friction parameters are identified. To compensate for nonlinear friction and uncertain disturbance, a finite-time adaptive sliding mode control method is proposed based on the accurate system model. This controller has the ability to ensure that the system state moves along the nonlinear sliding surface to steady state in a short time as well as good dynamic properties under the influence of parametric uncertainties and disturbance, which further improves the force loading accuracy and rapidity. At the end of this work, simulation and experimental results are employed to demonstrate the effectiveness of the proposed sliding mode control strategy.

Atomic scale simulations for improved CRUD and fuel performance modeling

Energy Technology Data Exchange (ETDEWEB)

Andersson, Anders David Ragnar [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Cooper, Michael William Donald [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-01-06

A more mechanistic description of fuel performance codes can be achieved by deriving models and parameters from atomistic scale simulations rather than fitting models empirically to experimental data. The same argument applies to modeling deposition of corrosion products on fuel rods (CRUD). Here are some results from publications in 2016 carried out using the CASL allocation at LANL.

Bio-lubricants derived from waste cooking oil with improved oxidation stability and low-temperature properties.

Science.gov (United States)

Li, Weimin; Wang, Xiaobo

2015-01-01

Waste cooking oil (WCO) was chemically modified via epoxidation using H2O2 followed by transesterification with methanol and branched alcohols (isooctanol, isotridecanol and isooctadecanol) to produce bio-lubricants with improved oxidative stability and low temperature properties. Physicochemical properties of synthesized bio-lubricants such as pour point (PP), cloud point (CP), viscosity, viscosity index (VI), oxidative stability, and corrosion resistant property were determined according to standard methods. The synthesized bio-lubricants showed improved low temperature flow performances compared with WCO, which can be attributing to the introduction of branched chains in their molecular structures. What's more, the oxidation stability of the WCO showed more than 10 folds improvement due to the elimination of -C=C-bonds in the WCO molecule. Tribological performances of these bio-lubricants were also investigated using four-ball friction and wear tester. Experimental results showed that derivatives of WCO exhibited favorable physicochemical properties and tribological performances which making them good candidates in formulating eco-friendly lubricants.

Pro-region engineering for improved yeast display and secretion of brain derived neurotrophic factor.

Science.gov (United States)

Burns, Michael L; Malott, Thomas M; Metcalf, Kevin J; Puguh, Arthya; Chan, Jonah R; Shusta, Eric V

2016-03-01

Brain derived neurotrophic factor (BDNF) is a promising therapeutic candidate for a variety of neurological diseases. However, it is difficult to produce as a recombinant protein. In its native mammalian context, BDNF is first produced as a pro-protein with subsequent proteolytic removal of the pro-region to yield mature BDNF protein. Therefore, in an attempt to improve yeast as a host for heterologous BDNF production, the BDNF pro-region was first evaluated for its effects on BDNF surface display and secretion. Addition of the wild-type pro-region to yeast BDNF production constructs improved BDNF folding both as a surface-displayed and secreted protein in terms of binding its natural receptors TrkB and p75, but titers remained low. Looking to further enhance the chaperone-like functions provided by the pro-region, two rounds of directed evolution were performed, yielding mutated pro-regions that further improved the display and secretion properties of BDNF. Subsequent optimization of the protease recognition site was used to control whether the produced protein was in pro- or mature BDNF forms. Taken together, we have demonstrated an effective strategy for improving BDNF compatibility with yeast protein engineering and secretion platforms. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Continuous Improvement Capital Funding Model.

Science.gov (United States)

Adams, Matt

2001-01-01

Describes a capital funding model that helps assess facility renewal needs in a way that minimizes resources while maximizing results. The article explains the sub-components of a continuous improvement capital funding model, including budgeting processes for finish renewal, building performance renewal, and critical outcome. (GR)

Therapeutic Effect of Ligustilide-Stimulated Adipose-Derived Stem Cells in a Mouse Thromboembolic Stroke Model.

Science.gov (United States)

Chi, Kang; Fu, Ru-Huei; Huang, Yu-Chuen; Chen, Shih-Yin; Lin, Shinn-Zong; Huang, Pi-Chun; Lin, Po-Cheng; Chang, Fu-Kuei; Liu, Shih-Ping

2016-01-01

Stroke is a result of cerebral ischemia that triggers a cascade of both physiological and biochemical events. No effective treatment is available for stroke; however, stem cells have the potential to rescue tissue from the effects of stroke. Adipose-derived stem cells (ADSCs) are an abundant source of adult stem cells; therefore, ADSC therapy can be considered as a future strategy for regenerative medicine. However, more research is required to improve the effectiveness of transplanted ADSCs as a treatment for stroke in the mouse stroke model. Ligustilide, isolated from the herb Angelica sinensis, exhibits a protective effect on neurons and inhibits inflammation. We also demonstrated that ligustilide treatment increases the expression levels of homing factors such as SDF-1 and CXCR4. In the present study, we evaluated the therapeutic effects of ADSC transplantation and ligustilide treatment in a mouse thromboembolic stroke model by behavioral tests, including beam walking, locomotor activity, and rotarod analysis. ADSCs pretreated with ligustilide were transplanted into the brains of stroke mice. The results showed that the therapeutic effect of ADSCs pretreated with ligustilide was better than that of ADSCs without ligustilide pretreatment. There was no difference between the recovery of mice treated by ADSC transplantation combined with subcutaneous ligustilide injection and that of mice treated only with ADSCs. The TUNEL assay showed fewer apoptotic cells in the brains of mice transplanted with ADSCs pretreated with ligustilide as well as in those without pretreatment. In summary, pretreatment of ADSCs with ligustilide improves the therapeutic efficacy of ADSC transplantation. The results of this study will help improve stem cell therapies being developed for future clinical applications.

Calibration by Hydrological Response Unit of a National Hydrologic Model to Improve Spatial Representation and Distribution of Parameters

Science.gov (United States)

Norton, P. A., II

2015-12-01

The U. S. Geological Survey is developing a National Hydrologic Model (NHM) to support consistent hydrologic modeling across the conterminous United States (CONUS). The Precipitation-Runoff Modeling System (PRMS) simulates daily hydrologic and energy processes in watersheds, and is used for the NHM application. For PRMS each watershed is divided into hydrologic response units (HRUs); by default each HRU is assumed to have a uniform hydrologic response. The Geospatial Fabric (GF) is a database containing initial parameter values for input to PRMS and was created for the NHM. The parameter values in the GF were derived from datasets that characterize the physical features of the entire CONUS. The NHM application is composed of more than 100,000 HRUs from the GF. Selected parameter values commonly are adjusted by basin in PRMS using an automated calibration process based on calibration targets, such as streamflow. Providing each HRU with distinct values that captures variability within the CONUS may improve simulation performance of the NHM. During calibration of the NHM by HRU, selected parameter values are adjusted for PRMS based on calibration targets, such as streamflow, snow water equivalent (SWE) and actual evapotranspiration (AET). Simulated SWE, AET, and runoff were compared to value ranges derived from multiple sources (e.g. the Snow Data Assimilation System, the Moderate Resolution Imaging Spectroradiometer (i.e. MODIS) Global Evapotranspiration Project, the Simplified Surface Energy Balance model, and the Monthly Water Balance Model). This provides each HRU with a distinct set of parameter values that captures the variability within the CONUS, leading to improved model performance. We present simulation results from the NHM after preliminary calibration, including the results of basin-level calibration for the NHM using: 1) default initial GF parameter values, and 2) parameter values calibrated by HRU.

Modelling and simulation of a dynamical system with the Atangana-Baleanu fractional derivative

Science.gov (United States)

Owolabi, Kolade M.

2018-01-01

In this paper, we model an ecological system consisting of a predator and two preys with the newly derived two-step fractional Adams-Bashforth method via the Atangana-Baleanu derivative in the Caputo sense. We analyze the dynamical system for correct choice of parameter values that are biologically meaningful. The local analysis of the main model is based on the application of qualitative theory for ordinary differential equations. By using the fixed point theorem idea, we establish the existence and uniqueness of the solutions. Convergence results of the new scheme are verified in both space and time. Dynamical wave phenomena of solutions are verified via some numerical results obtained for different values of the fractional index, which have some interesting ecological implications.

Improvements and Limitations of Humanized Mouse Models for HIV Research: NIH/NIAID “Meet the Experts” 2015 Workshop Summary

OpenAIRE

Akkina, Ramesh; Allam, Atef; Balazs, Alejandro B.; Blankson, Joel N.; Burnett, John C.; Casares, Sofia; Garcia, J. Victor; Hasenkrug, Kim J.; Kashanchi, Fatah; Kitchen, Scott G.; Klein, Florian; Kumar, Priti; Luster, Andrew D.; Poluektova, Larisa Y.; Rao, Mangala

2016-01-01

The number of humanized mouse models for the human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) and other infectious diseases has expanded rapidly over the past 8 years. Highly immunodeficient mouse strains, such as NOD/SCID/gamma chainnull (NSG, NOG), support better human hematopoietic cell engraftment. Another improvement is the derivation of highly immunodeficient mice, transgenic with human leukocyte antigens (HLAs) and cytokines that supported development of HLA...

Derivation of Green's function of a spin Calogero-Sutherland model by Uglov's method

International Nuclear Information System (INIS)

Nakai, Ryota; Kato, Yusuke

2009-01-01

The hole propagator of a spin 1/2 Calogero-Sutherland model is derived using Uglov's method, which maps the exact eigenfunctions of the model, called the Yangian Gelfand-Zetlin basis, to a limit of Macdonald polynomials (gl 2 -Jack polynomials). To apply this mapping method to the calculation of 1-particle Green's function, we confirm that the sum of the field annihilation operator ψ u + ψ ↓ on a Yangian Gelfand-Zetlin basis is transformed to the field annihilation operator ψ on gl 2 -Jack polynomials by the mapping. The resultant expression for the hole propagator for a finite-size system is written in terms of renormalized momenta and spin of quasi-holes, and the expression in the thermodynamic limit coincides with the earlier result derived by another method. We also discuss the singularity of the spectral function for a specific coupling parameter where the hole propagator of the spin Calogero-Sutherland model becomes equivalent to the dynamical colour correlation function of an SU(3) Haldane-Shastry model

Intercomparison of Satellite Derived Gravity Time Series with Inferred Gravity Time Series from TOPEX/POSEIDON Sea Surface Heights and Climatological Model Output

Science.gov (United States)

Cox, C.; Au, A.; Klosko, S.; Chao, B.; Smith, David E. (Technical Monitor)

2001-01-01

The upcoming GRACE mission promises to open a window on details of the global mass budget that will have remarkable clarity, but it will not directly answer the question of what the state of the Earth's mass budget is over the critical last quarter of the 20th century. To address that problem we must draw upon existing technologies such as SLR, DORIS, and GPS, and climate modeling runs in order to improve our understanding. Analysis of long-period geopotential changes based on SLR and DORIS tracking has shown that addition of post 1996 satellite tracking data has a significant impact on the recovered zonal rates and long-period tides. Interannual effects such as those causing the post 1996 anomalies must be better characterized before refined estimates of the decadal period changes in the geopotential can be derived from the historical database of satellite tracking. A possible cause of this anomaly is variations in ocean mass distribution, perhaps associated with the recent large El Nino/La Nina. In this study, a low-degree spherical harmonic gravity time series derived from satellite tracking is compared with a TOPEX/POSEIDON-derived sea surface height time series. Corrections for atmospheric mass effects, continental hydrology, snowfall accumulation, and ocean steric model predictions will be considered.

Global Derivatives

DEFF Research Database (Denmark)

Andersen, Torben Juul

approaches to dealing in the global business environment." - Sharon Brown-Hruska, Commissioner, Commodity Futures Trading Commission, USA. "This comprehensive survey of modern risk management using derivative securities is a fine demonstration of the practical relevance of modern derivatives theory to risk......" provides comprehensive coverage of different types of derivatives, including exchange traded contracts and over-the-counter instruments as well as real options. There is an equal emphasis on the practical application of derivatives and their actual uses in business transactions and corporate risk...... management situations. Its key features include: derivatives are introduced in a global market perspective; describes major derivative pricing models for practical use, extending these principles to valuation of real options; practical applications of derivative instruments are richly illustrated...

Characterizing and improving generalized belief propagation algorithms on the 2D Edwards–Anderson model

International Nuclear Information System (INIS)

Domínguez, Eduardo; Lage-Castellanos, Alejandro; Mulet, Roberto; Ricci-Tersenghi, Federico; Rizzo, Tommaso

2011-01-01

We study the performance of different message passing algorithms in the two-dimensional Edwards–Anderson model. We show that the standard belief propagation (BP) algorithm converges only at high temperature to a paramagnetic solution. Then, we test a generalized belief propagation (GBP) algorithm, derived from a cluster variational method (CVM) at the plaquette level. We compare its performance with BP and with other algorithms derived under the same approximation: double loop (DL) and a two-way message passing algorithm (HAK). The plaquette-CVM approximation improves BP in at least three ways: the quality of the paramagnetic solution at high temperatures, a better estimate (lower) for the critical temperature, and the fact that the GBP message passing algorithm converges also to nonparamagnetic solutions. The lack of convergence of the standard GBP message passing algorithm at low temperatures seems to be related to the implementation details and not to the appearance of long range order. In fact, we prove that a gauge invariance of the constrained CVM free energy can be exploited to derive a new message passing algorithm which converges at even lower temperatures. In all its region of convergence this new algorithm is faster than HAK and DL by some orders of magnitude

Improving weather predictability by including land-surface model parameter uncertainty

Science.gov (United States)

Orth, Rene; Dutra, Emanuel; Pappenberger, Florian

2016-04-01

The land surface forms an important component of Earth system models and interacts nonlinearly with other parts such as ocean and atmosphere. To capture the complex and heterogenous hydrology of the land surface, land surface models include a large number of parameters impacting the coupling to other components of the Earth system model. Focusing on ECMWF's land-surface model HTESSEL we present in this study a comprehensive parameter sensitivity evaluation using multiple observational datasets in Europe. We select 6 poorly constrained effective parameters (surface runoff effective depth, skin conductivity, minimum stomatal resistance, maximum interception, soil moisture stress function shape, total soil depth) and explore their sensitivity to model outputs such as soil moisture, evapotranspiration and runoff using uncoupled simulations and coupled seasonal forecasts. Additionally we investigate the possibility to construct ensembles from the multiple land surface parameters. In the uncoupled runs we find that minimum stomatal resistance and total soil depth have the most influence on model performance. Forecast skill scores are moreover sensitive to the same parameters as HTESSEL performance in the uncoupled analysis. We demonstrate the robustness of our findings by comparing multiple best performing parameter sets and multiple randomly chosen parameter sets. We find better temperature and precipitation forecast skill with the best-performing parameter perturbations demonstrating representativeness of model performance across uncoupled (and hence less computationally demanding) and coupled settings. Finally, we construct ensemble forecasts from ensemble members derived with different best-performing parameterizations of HTESSEL. This incorporation of parameter uncertainty in the ensemble generation yields an increase in forecast skill, even beyond the skill of the default system. Orth, R., E. Dutra, and F. Pappenberger, 2016: Improving weather predictability by

Improved flow cytometric assessment reveals distinct microvesicle (cell-derived microparticle signatures in joint diseases.

Directory of Open Access Journals (Sweden)

Bence György

Full Text Available INTRODUCTION: Microvesicles (MVs, earlier referred to as microparticles, represent a major type of extracellular vesicles currently considered as novel biomarkers in various clinical settings such as autoimmune disorders. However, the analysis of MVs in body fluids has not been fully standardized yet, and there are numerous pitfalls that hinder the correct assessment of these structures. METHODS: In this study, we analyzed synovial fluid (SF samples of patients with osteoarthritis (OA, rheumatoid arthritis (RA and juvenile idiopathic arthritis (JIA. To assess factors that may confound MV detection in joint diseases, we used electron microscopy (EM, Nanoparticle Tracking Analysis (NTA and mass spectrometry (MS. For flow cytometry, a method commonly used for phenotyping and enumeration of MVs, we combined recent advances in the field, and used a novel approach of differential detergent lysis for the exclusion of MV-mimicking non-vesicular signals. RESULTS: EM and NTA showed that substantial amounts of particles other than MVs were present in SF samples. Beyond known MV-associated proteins, MS analysis also revealed abundant plasma- and immune complex-related proteins in MV preparations. Applying improved flow cytometric analysis, we demonstrate for the first time that CD3(+ and CD8(+ T-cell derived SF MVs are highly elevated in patients with RA compared to OA patients (p=0.027 and p=0.009, respectively, after Bonferroni corrections. In JIA, we identified reduced numbers of B cell-derived MVs (p=0.009, after Bonferroni correction. CONCLUSIONS: Our results suggest that improved flow cytometric assessment of MVs facilitates the detection of previously unrecognized disease-associated vesicular signatures.

An optimization model for improving highway safety

Directory of Open Access Journals (Sweden)

Promothes Saha

2016-12-01

Full Text Available This paper developed a traffic safety management system (TSMS for improving safety on county paved roads in Wyoming. TSMS is a strategic and systematic process to improve safety of roadway network. When funding is limited, it is important to identify the best combination of safety improvement projects to provide the most benefits to society in terms of crash reduction. The factors included in the proposed optimization model are annual safety budget, roadway inventory, roadway functional classification, historical crashes, safety improvement countermeasures, cost and crash reduction factors (CRFs associated with safety improvement countermeasures, and average daily traffics (ADTs. This paper demonstrated how the proposed model can identify the best combination of safety improvement projects to maximize the safety benefits in terms of reducing overall crash frequency. Although the proposed methodology was implemented on the county paved road network of Wyoming, it could be easily modified for potential implementation on the Wyoming state highway system. Other states can also benefit by implementing a similar program within their jurisdictions.

Lagrangian derivation of the two coupled field equations in the Janus cosmological model

Science.gov (United States)

Petit, Jean-Pierre; D'Agostini, G.

2015-05-01

After a review citing the results obtained in previous articles introducing the Janus Cosmological Model, consisting of a set of two coupled field equations, where one metrics refers to the positive masses and the other to the negative masses, which explains the observed cosmic acceleration and the nature of dark energy, we present the Lagrangian derivation of the model.

The Urgent Need for Improved Climate Models and Predictions

Science.gov (United States)

Goddard, Lisa; Baethgen, Walter; Kirtman, Ben; Meehl, Gerald

2009-09-01

An investment over the next 10 years of the order of US$2 billion for developing improved climate models was recommended in a report (http://wcrp.wmo.int/documents/WCRP_WorldModellingSummit_Jan2009.pdf) from the May 2008 World Modelling Summit for Climate Prediction, held in Reading, United Kingdom, and presented by the World Climate Research Programme. The report indicated that “climate models will, as in the past, play an important, and perhaps central, role in guiding the trillion dollar decisions that the peoples, governments and industries of the world will be making to cope with the consequences of changing climate.” If trillions of dollars are going to be invested in making decisions related to climate impacts, an investment of $2 billion, which is less than 0.1% of that amount, to provide better climate information seems prudent. One example of investment in adaptation is the World Bank's Climate Investment Fund, which has drawn contributions of more than $6 billion for work on clean technologies and adaptation efforts in nine pilot countries and two pilot regions. This is just the beginning of expenditures on adaptation efforts by the World Bank and other mechanisms, focusing on only a small fraction of the nations of the world and primarily aimed at anticipated anthropogenic climate change. Moreover, decisions are being made now, all around the world—by individuals, companies, and governments—that affect people and their livelihoods today, not just 50 or more years in the future. Climate risk management, whether related to projects of the scope of the World Bank's or to the planning and decisions of municipalities, will be best guided by meaningful climate information derived from observations of the past and model predictions of the future.

Can better modelling improve tokamak control?

International Nuclear Information System (INIS)

Lister, J.B.; Vyas, P.; Ward, D.J.; Albanese, R.; Ambrosino, G.; Ariola, M.; Villone, F.; Coutlis, A.; Limebeer, D.J.N.; Wainwright, J.P.

1997-01-01

The control of present day tokamaks usually relies upon primitive modelling and TCV is used to illustrate this. A counter example is provided by the successful implementation of high order SISO controllers on COMPASS-D. Suitable models of tokamaks are required to exploit the potential of modern control techniques. A physics based MIMO model of TCV is presented and validated with experimental closed loop responses. A system identified open loop model is also presented. An enhanced controller based on these models is designed and the performance improvements discussed. (author) 5 figs., 9 refs

Dynamical symmetry restoration for a higher-derivative four-fermion model in an external electromagnetic field

International Nuclear Information System (INIS)

Elizalde, E.; Gavrilov, S.P.; Shil'nov, Yu.I.

2000-01-01

A four-fermion model with additional higher-derivative terms is investigated in an external electromagnetic field. The effective potential in the leading order of large-N expansion is calculated in external constant magnetic and electric fields. It is shown that, in contrast to the former results concerning the universal character of 'magnetic catalysis' in dynamical symmetry breaking, in the present higher-derivative model the magnetic field restores chiral symmetry broken initially on the tree level. Numerical results describing a second-order phase transition that accompanies the symmetry restoration at the quantum level are presented. (author)

Improved bounds on the epidemic threshold of exact SIS models on complex networks

KAUST Repository

Ruhi, Navid Azizan; Thrampoulidis, Christos; Hassibi, Babak

2017-01-01

The SIS (susceptible-infected-susceptible) epidemic model on an arbitrary network, without making approximations, is a 2n-state Markov chain with a unique absorbing state (the all-healthy state). This makes analysis of the SIS model and, in particular, determining the threshold of epidemic spread quite challenging. It has been shown that the exact marginal probabilities of infection can be upper bounded by an n-dimensional linear time-invariant system, a consequence of which is that the Markov chain is “fast-mixing” when the LTI system is stable, i.e. when equation (where β is the infection rate per link, δ is the recovery rate, and λmax(A) is the largest eigenvalue of the network's adjacency matrix). This well-known threshold has been recently shown not to be tight in several cases, such as in a star network. In this paper, we provide tighter upper bounds on the exact marginal probabilities of infection, by also taking pairwise infection probabilities into account. Based on this improved bound, we derive tighter eigenvalue conditions that guarantee fast mixing (i.e., logarithmic mixing time) of the chain. We demonstrate the improvement of the threshold condition by comparing the new bound with the known one on various networks with various epidemic parameters.

Improved bounds on the epidemic threshold of exact SIS models on complex networks

KAUST Repository

Ruhi, Navid Azizan

2017-01-05

The SIS (susceptible-infected-susceptible) epidemic model on an arbitrary network, without making approximations, is a 2n-state Markov chain with a unique absorbing state (the all-healthy state). This makes analysis of the SIS model and, in particular, determining the threshold of epidemic spread quite challenging. It has been shown that the exact marginal probabilities of infection can be upper bounded by an n-dimensional linear time-invariant system, a consequence of which is that the Markov chain is “fast-mixing” when the LTI system is stable, i.e. when equation (where β is the infection rate per link, δ is the recovery rate, and λmax(A) is the largest eigenvalue of the network\\'s adjacency matrix). This well-known threshold has been recently shown not to be tight in several cases, such as in a star network. In this paper, we provide tighter upper bounds on the exact marginal probabilities of infection, by also taking pairwise infection probabilities into account. Based on this improved bound, we derive tighter eigenvalue conditions that guarantee fast mixing (i.e., logarithmic mixing time) of the chain. We demonstrate the improvement of the threshold condition by comparing the new bound with the known one on various networks with various epidemic parameters.

Kojyl cinnamate ester derivatives promote adiponectin production during adipogenesis in human adipose tissue-derived mesenchymal stem cells.

Science.gov (United States)

Rho, Ho Sik; Hong, Soo Hyun; Park, Jongho; Jung, Hyo-Il; Park, Young-Ho; Lee, John Hwan; Shin, Song Seok; Noh, Minsoo

2014-05-01

The subcutaneous fat tissue mass gradually decreases with age, and its regulation is a strategy to develop anti-aging compounds to ameliorate the photo-aging of human skin. The adipogenesis of human adipose tissue-mesenchymal stem cells (hAT-MSCs) can be used as a model to discover novel anti-aging compounds. Cinnamomum cassia methanol extracts were identified as adipogenesis-promoting agents by natural product library screening. Cinnamates, the major chemical components of Cinnamomum cassia extracts, promoted adipogenesis in hAT-MSCs. We synthesized kojyl cinnamate ester derivatives to improve the pharmacological activity of cinnamates. Structure-activity studies of kojyl cinnamate derivatives showed that both the α,β-unsaturated carbonyl ester group and the kojic acid moiety play core roles in promoting adiponectin production during adipogenesis in hAT-MSCs. We conclude that kojyl cinnamate ester derivatives provide novel pharmacophores that can regulate adipogenesis in hAT-MSCs. Copyright © 2014 Elsevier Ltd. All rights reserved.

An improved gravity model for Mars: Goddard Mars Model-1 (GMM-1)

Science.gov (United States)

Smith, D. E.; Lerch, F. J.; Nerem, R. S.; Zuber, M. T.; Patel, G. B.; Fricke, S. K.; Lemoine, F. G.

1993-01-01

Doppler tracking data of three orbiting spacecraft have been reanalyzed to develop a new gravitational field model for the planet Mars, GMM-1 (Goddard Mars Model-1). This model employs nearly all available data, consisting of approximately 1100 days of S-bank tracking data collected by NASA's Deep Space Network from the Mariner 9, and Viking 1 and Viking 2 spacecraft, in seven different orbits, between 1971 and 1979. GMM-1 is complete to spherical harmonic degree and order 50, which corresponds to a half-wavelength spatial resolution of 200-300 km where the data permit. GMM-1 represents satellite orbits with considerably better accuracy than previous Mars gravity models and shows greater resolution of identifiable geological structures. The notable improvement in GMM-1 over previous models is a consequence of several factors: improved computational capabilities, the use of optimum weighting and least-squares collocation solution techniques which stabilized the behavior of the solution at high degree and order, and the use of longer satellite arcs than employed in previous solutions that were made possible by improved force and measurement models. The inclusion of X-band tracking data from the 379-km altitude, near-polar orbiting Mars Observer spacecraft should provide a significant improvement over GMM-1, particularly at high latitudes where current data poorly resolves the gravitational signature of the planet.

Time Domain Modeling and Simulation of Nonlinear Slender Viscoelastic Beams Associating Cosserat Theory and a Fractional Derivative Model

Directory of Open Access Journals (Sweden)

Adailton S. Borges

Full Text Available Abstract A broad class of engineering systems can be satisfactory modeled under the assumptions of small deformations and linear material properties. However, many mechanical systems used in modern applications, like structural elements typical of aerospace and petroleum industries, have been characterized by increased slenderness and high static and dynamic loads. In such situations, it becomes indispensable to consider the nonlinear geometric effects and/or material nonlinear behavior. At the same time, in many cases involving dynamic loads, there comes the need for attenuation of vibration levels. In this context, this paper describes the development and validation of numerical models of viscoelastic slender beam-like structures undergoing large displacements. The numerical approach is based on the combination of the nonlinear Cosserat beam theory and a viscoelastic model based on Fractional Derivatives. Such combination enables to derive nonlinear equations of motion that, upon finite element discretization, can be used for predicting the dynamic behavior of the structure in the time domain, accounting for geometric nonlinearity and viscoelastic damping. The modeling methodology is illustrated and validated by numerical simulations, the results of which are compared to others available in the literature.

Low-dose radiation pretreatment improves survival of human ceiling culture-derived proliferative adipocytes (ccdPAs) under hypoxia via HIF-1 alpha and MMP-2 induction

International Nuclear Information System (INIS)

Adachi, Naoki; Kubota, Yoshitaka; Kosaka, Kentarou; Akita, Shinsuke; Sasahara, Yoshitarou; Kira, Tomoe; Kuroda, Masayuki; Mitsukawa, Nobuyuki; Bujo, Hideaki; Satoh, Kaneshige

2015-01-01

Poor survival is a major problem of adipocyte transplantation. We previously reported that VEGF and MMPs secreted from transplanted adipocytes are essential for angiogenesis and adipogenesis. Pretreatment with low-dose (5 Gy) radiation (LDR) increased VEGF, MMP-2, and HIF-1 alpha mRNA expression in human ceiling culture-derived proliferative adipocytes (hccdPAs). Gene expression after LDR differed between adipose-derived stem cells (hASCs) and hccdPAs. Pretreatment with LDR improved the survival of hccdPAs under hypoxia, which is inevitable in the early stages after transplantation. Upregulation of VEGF and MMP-2 after LDR in hccdPAs is mediated by HIF-1 alpha expression. Our results suggest that pretreatment with LDR may improve adipocyte graft survival in a clinical setting through upregulation of VEGF and MMP-2 via HIF-1 alpha. - Highlights: • Ceiling culture-derived proliferative adipocytes (ccdPAs) react to radiation. • Low-dose radiation (LDR) pretreatment improves survival of ccdPAs under hypoxia. • Gene expression after LDR differs between ccdPAs and adipose-derived stem cells. • LDR-induced increase in MMP-2 and VEGF is dependent on HIF-1 alpha induction. • LDR pretreatment may improve the adipocyte graft survival rate in clinical settings

Low-dose radiation pretreatment improves survival of human ceiling culture-derived proliferative adipocytes (ccdPAs) under hypoxia via HIF-1 alpha and MMP-2 induction

Energy Technology Data Exchange (ETDEWEB)

Adachi, Naoki [Department of Plastic Surgery, Chiba University, 1-8-1, Inohana, Chuo-ku, Chiba-city, Chiba, #260-8677 (Japan); Kubota, Yoshitaka, E-mail: kubota-cbu@umin.ac.jp [Department of Plastic Surgery, Chiba University, 1-8-1, Inohana, Chuo-ku, Chiba-city, Chiba, #260-8677 (Japan); Kosaka, Kentarou; Akita, Shinsuke; Sasahara, Yoshitarou; Kira, Tomoe [Department of Plastic Surgery, Chiba University, 1-8-1, Inohana, Chuo-ku, Chiba-city, Chiba, #260-8677 (Japan); Kuroda, Masayuki [Center for Advanced Medicine, Chiba University, 1-8-1, Inohana, Chuo-ku, Chiba-city, Chiba, #260-8677 (Japan); Mitsukawa, Nobuyuki [Department of Plastic Surgery, Chiba University, 1-8-1, Inohana, Chuo-ku, Chiba-city, Chiba, #260-8677 (Japan); Bujo, Hideaki [Department of Clinical-Laboratory and Experimental-Research Medicine, Toho University, Sakura Medical Center, 564-1 Shimoshizu, Sakura-shi, Chiba, #285-8741 (Japan); Satoh, Kaneshige [Department of Plastic Surgery, Chiba University, 1-8-1, Inohana, Chuo-ku, Chiba-city, Chiba, #260-8677 (Japan)

2015-08-07

Poor survival is a major problem of adipocyte transplantation. We previously reported that VEGF and MMPs secreted from transplanted adipocytes are essential for angiogenesis and adipogenesis. Pretreatment with low-dose (5 Gy) radiation (LDR) increased VEGF, MMP-2, and HIF-1 alpha mRNA expression in human ceiling culture-derived proliferative adipocytes (hccdPAs). Gene expression after LDR differed between adipose-derived stem cells (hASCs) and hccdPAs. Pretreatment with LDR improved the survival of hccdPAs under hypoxia, which is inevitable in the early stages after transplantation. Upregulation of VEGF and MMP-2 after LDR in hccdPAs is mediated by HIF-1 alpha expression. Our results suggest that pretreatment with LDR may improve adipocyte graft survival in a clinical setting through upregulation of VEGF and MMP-2 via HIF-1 alpha. - Highlights: • Ceiling culture-derived proliferative adipocytes (ccdPAs) react to radiation. • Low-dose radiation (LDR) pretreatment improves survival of ccdPAs under hypoxia. • Gene expression after LDR differs between ccdPAs and adipose-derived stem cells. • LDR-induced increase in MMP-2 and VEGF is dependent on HIF-1 alpha induction. • LDR pretreatment may improve the adipocyte graft survival rate in clinical settings.

Derivation of Event-B Models from OWL Ontologies

Directory of Open Access Journals (Sweden)

Alkhammash Eman H.

2016-01-01

Full Text Available The derivation of formal specifications from large and complex requirements is a key challenge in systems engineering. In this paper we present an approach that aims to address this challenge by building formal models from OWL ontologies. An ontology is used in the field of knowledge representation to capture a clear view of the domain and to produce a concise and unambiguous set of domain requirements. We harness the power of ontologies to handle inconsistency of domain requirements and produce clear, concise and unambiguous set of domain requirements for Event-B modelling. The proposed approach works by generating Attempto Controlled English (ACE from the OWL ontology and then maps the ACE requirements to develop Event-B models. ACE is a subset of English that can be unambiguously translated into first-order logic. There is an injective mapping between OWL ontology and a subset of ACE. ACE is a suitable interlingua for producing the mapping between OWL and Event-B models for many reasons. Firstly, ACE is easy to learn and understand, it hides the math of OWL and would be natural to use by everybody. Secondly ACE has a parser that converts ACE texts into Discourse Representation Structures (DRS. Finally, ACE can be extended to target a richer syntactic subset of Event-B which ultimately would facilitate the translation of ACE requirements to Event-B.

Improving Agent Based Modeling of Critical Incidents

Directory of Open Access Journals (Sweden)

Robert Till

2010-04-01

Full Text Available Agent Based Modeling (ABM is a powerful method that has been used to simulate potential critical incidents in the infrastructure and built environments. This paper will discuss the modeling of some critical incidents currently simulated using ABM and how they may be expanded and improved by using better physiological modeling, psychological modeling, modeling the actions of interveners, introducing Geographic Information Systems (GIS and open source models.

INTEGRATED COST MODEL FOR IMPROVING THE PRODUCTION IN COMPANIES

Directory of Open Access Journals (Sweden)

Zuzana Hajduova

2014-12-01

Full Text Available Purpose: All processes in the company play important role in ensuring functional integrated management system. We point out the importance of need for a systematic approach to the use of quantitative, but especially statistical methods for modelling the cost of the improvement activities that are part of an integrated management system. Development of integrated management systems worldwide leads towards building of systematic procedures of implementation maintenance and improvement of all systems according to the requirements of all the sides involved.Methodology: Statistical evaluation of the economic indicators of improvement costs and the need for a systematic approach to their management in terms of integrated management systems have become a key role also in the management of processes in the company Cu Drôt, a.s. The aim of this publication is to highlight the importance of proper implementation of statistical methods in the process of improvement costs management in the integrated management system of current market conditions and document the legitimacy of a systematic approach in the area of monitoring and analysing indicators of improvement with the aim of the efficient process management of company. We provide specific example of the implementation of appropriate statistical methods in the production of copper wire in a company Cu Drôt, a.s. This publication also aims to create a model for the estimation of integrated improvement costs, which through the use of statistical methods in the company Cu Drôt, a.s. is used to support decision-making on improving efficiency.Findings: In the present publication, a method for modelling the improvement process, by an integrated manner, is proposed. It is a method in which the basic attributes of the improvement in quality, safety and environment are considered and synergistically combined in the same improvement project. The work examines the use of sophisticated quantitative, especially

Derivation and application of mathematical model for well test analysis with variable skin factor in hydrocarbon reservoirs

Directory of Open Access Journals (Sweden)

Pengcheng Liu

2016-06-01

Full Text Available Skin factor is often regarded as a constant in most of the mathematical model for well test analysis in oilfields, but this is only a kind of simplified treatment with the actual skin factor changeable. This paper defined the average permeability of a damaged area as a function of time by using the definition of skin factor. Therefore a relationship between a variable skin factor and time was established. The variable skin factor derived was introduced into existing traditional models rather than using a constant skin factor, then, this newly derived mathematical model for well test analysis considering variable skin factor was solved by Laplace transform. The dimensionless wellbore pressure and its derivative changed with dimensionless time were plotted with double logarithm and these plots can be used for type curve fitting. The effects of all the parameters in the expression of variable skin factor were analyzed based on the dimensionless wellbore pressure and its derivative. Finally, actual well testing data were used to fit the type curves developed which validates the applicability of the mathematical model from Sheng-2 Block, Shengli Oilfield, China.

iPot: Improved potato monitoring in Belgium using remote sensing and crop growth modelling

Science.gov (United States)

Piccard, Isabelle; Gobin, Anne; Curnel, Yannick; Goffart, Jean-Pierre; Planchon, Viviane; Wellens, Joost; Tychon, Bernard; Cattoor, Nele; Cools, Romain

2016-04-01

Potato processors, traders and packers largely work with potato contracts. The close follow up of contracted parcels is important to improve the quantity and quality of the crop and reduce risks related to storage, packaging or processing. The use of geo-information by the sector is limited, notwithstanding the great benefits that this type of information may offer. At the same time, new sensor-based technologies continue to gain importance and farmers increasingly invest in these. The combination of geo-information and crop modelling might strengthen the competitiveness of the Belgian potato chain in a global market. The iPot project, financed by the Belgian Science Policy Office (Belspo), aims at providing the Belgian potato processing sector, represented by Belgapom, with near real time information on field condition (weather-soil), crop development and yield estimates, derived from a combination of satellite images and crop growth models. During the cropping season regular UAV flights (RGB, 3x3 cm) and high resolution satellite images (DMC/Deimos, 22m pixel size) were combined to elucidate crop phenology and performance at variety trials. UAV images were processed using a K-means clustering algorithm to classify the crop according to its greenness at 5m resolution. Vegetation indices such as %Cover and LAI were calculated with the Cyclopes algorithm (INRA-EMMAH) on the DMC images. Both DMC and UAV-based cover maps showed similar patterns, and helped detect different crop stages during the season. A wide spread field monitoring campaign with crop observations and measurements allowed for further calibration of the satellite image derived vegetation indices. Curve fitting techniques and phenological models were developed and compared with the vegetation indices during the season, both at trials and farmers' fields. Understanding and predicting crop phenology and canopy development is important for timely crop management and ultimately for yield estimates. An

Mapping SOC (Soil Organic Carbon) using LiDAR-derived vegetation indices in a random forest regression model

Science.gov (United States)

Will, R. M.; Glenn, N. F.; Benner, S. G.; Pierce, J. L.; Spaete, L.; Li, A.

2015-12-01

Quantifying SOC (Soil Organic Carbon) storage in complex terrain is challenging due to high spatial variability. Generally, the challenge is met by transforming point data to the entire landscape using surrogate, spatially-distributed, variables like elevation or precipitation. In many ecosystems, remotely sensed information on above-ground vegetation (e.g. NDVI) is a good predictor of below-ground carbon stocks. In this project, we are attempting to improve this predictive method by incorporating LiDAR-derived vegetation indices. LiDAR provides a mechanism for improved characterization of aboveground vegetation by providing structural parameters such as vegetation height and biomass. In this study, a random forest model is used to predict SOC using a suite of LiDAR-derived vegetation indices as predictor variables. The Reynolds Creek Experimental Watershed (RCEW) is an ideal location for a study of this type since it encompasses a strong elevation/precipitation gradient that supports lower biomass sagebrush ecosystems at low elevations and forests with more biomass at higher elevations. Sagebrush ecosystems composed of Wyoming, Low and Mountain Sagebrush have SOC values ranging from .4 to 1% (top 30 cm), while higher biomass ecosystems composed of aspen, juniper and fir have SOC values approaching 4% (top 30 cm). Large differences in SOC have been observed between canopy and interspace locations and high resolution vegetation information is likely to explain plot scale variability in SOC. Mapping of the SOC reservoir will help identify underlying controls on SOC distribution and provide insight into which processes are most important in determining SOC in semi-arid mountainous regions. In addition, airborne LiDAR has the potential to characterize vegetation communities at a high resolution and could be a tool for improving estimates of SOC at larger scales.

Modeling ramp-hold indentation measurements based on Kelvin-Voigt fractional derivative model

Science.gov (United States)

Zhang, Hongmei; zhe Zhang, Qing; Ruan, Litao; Duan, Junbo; Wan, Mingxi; Insana, Michael F.

2018-03-01

Interpretation of experimental data from micro- and nano-scale indentation testing is highly dependent on the constitutive model selected to relate measurements to mechanical properties. The Kelvin-Voigt fractional derivative model (KVFD) offers a compact set of viscoelastic features appropriate for characterizing soft biological materials. This paper provides a set of KVFD solutions for converting indentation testing data acquired for different geometries and scales into viscoelastic properties of soft materials. These solutions, which are mostly in closed-form, apply to ramp-hold relaxation, load-unload and ramp-load creep-testing protocols. We report on applications of these model solutions to macro- and nano-indentation testing of hydrogels, gastric cancer cells and ex vivo breast tissue samples using an atomic force microscope (AFM). We also applied KVFD models to clinical ultrasonic breast data using a compression plate as required for elasticity imaging. Together the results show that KVFD models fit a broad range of experimental data with a correlation coefficient typically R 2  >  0.99. For hydrogel samples, estimation of KVFD model parameters from test data using spherical indentation versus plate compression as well as ramp relaxation versus load-unload compression all agree within one standard deviation. Results from measurements made using macro- and nano-scale indentation agree in trend. For gastric cell and ex vivo breast tissue measurements, KVFD moduli are, respectively, 1/3-1/2 and 1/6 of the elasticity modulus found from the Sneddon model. In vivo breast tissue measurements yield model parameters consistent with literature results. The consistency of results found for a broad range of experimental parameters suggest the KVFD model is a reliable tool for exploring intrinsic features of the cell/tissue microenvironments.

Reversible dual inhibitor against G9a and DNMT1 improves human iPSC derivation enhancing MET and facilitating transcription factor engagement to the genome.

Directory of Open Access Journals (Sweden)

Juan Roberto Rodriguez-Madoz

Full Text Available The combination of defined factors with small molecules targeting epigenetic factors is a strategy that has been shown to enhance optimal derivation of iPSCs and could be used for disease modelling, high throughput screenings and/or regenerative medicine applications. In this study, we showed that a new first-in-class reversible dual G9a/DNMT1 inhibitor compound (CM272 improves the efficiency of human cell reprogramming and iPSC generation from primary cells of healthy donors and patient samples, using both integrative and non-integrative methods. Moreover, CM272 facilitates the generation of human iPSC with only two factors allowing the removal of the most potent oncogenic factor cMYC. Furthermore, we demonstrated that mechanistically, treatment with CM272 induces heterochromatin relaxation, facilitates the engagement of OCT4 and SOX2 transcription factors to OSKM refractory binding regions that are required for iPSC establishment, and enhances mesenchymal to epithelial transition during the early phase of cell reprogramming. Thus, the use of this new G9a/DNMT reversible dual inhibitor compound may represent an interesting alternative for improving cell reprogramming and human iPSC derivation for many different applications while providing interesting insights into reprogramming mechanisms.

Reversible dual inhibitor against G9a and DNMT1 improves human iPSC derivation enhancing MET and facilitating transcription factor engagement to the genome.

Science.gov (United States)

Rodriguez-Madoz, Juan Roberto; San Jose-Eneriz, Edurne; Rabal, Obdulia; Zapata-Linares, Natalia; Miranda, Estibaliz; Rodriguez, Saray; Porciuncula, Angelo; Vilas-Zornoza, Amaia; Garate, Leire; Segura, Victor; Guruceaga, Elizabeth; Agirre, Xabier; Oyarzabal, Julen; Prosper, Felipe

2017-01-01

The combination of defined factors with small molecules targeting epigenetic factors is a strategy that has been shown to enhance optimal derivation of iPSCs and could be used for disease modelling, high throughput screenings and/or regenerative medicine applications. In this study, we showed that a new first-in-class reversible dual G9a/DNMT1 inhibitor compound (CM272) improves the efficiency of human cell reprogramming and iPSC generation from primary cells of healthy donors and patient samples, using both integrative and non-integrative methods. Moreover, CM272 facilitates the generation of human iPSC with only two factors allowing the removal of the most potent oncogenic factor cMYC. Furthermore, we demonstrated that mechanistically, treatment with CM272 induces heterochromatin relaxation, facilitates the engagement of OCT4 and SOX2 transcription factors to OSKM refractory binding regions that are required for iPSC establishment, and enhances mesenchymal to epithelial transition during the early phase of cell reprogramming. Thus, the use of this new G9a/DNMT reversible dual inhibitor compound may represent an interesting alternative for improving cell reprogramming and human iPSC derivation for many different applications while providing interesting insights into reprogramming mechanisms.

Relating Derived Relations as a Model of Analogical Reasoning: Reaction Times and Event-Related Potentials

Science.gov (United States)

Barnes-Holmes, Dermot; Regan, Donal; Barnes-Holmes, Yvonne; Commins, Sean; Walsh, Derek; Stewart, Ian; Smeets, Paul M.; Whelan, Robert; Dymond, Simon

2005-01-01

The current study aimed to test a Relational Frame Theory (RFT) model of analogical reasoning based on the relating of derived same and derived difference relations. Experiment 1 recorded reaction time measures of similar-similar (e.g., "apple is to orange as dog is to cat") versus different-different (e.g., "he is to his brother as…

Dynamic Longitudinal and Directional Stability Derivatives for a 45 deg. Sweptback-Wing Airplane Model at Transonic Speeds

Science.gov (United States)

Bielat, Ralph P.; Wiley, Harleth G.

1959-01-01

An investigation was made at transonic speeds to determine some of the dynamic stability derivatives of a 45 deg. sweptback-wing airplane model. The model was sting mounted and was rigidly forced to perform a single-degree-of-freedom angular oscillation in pitch or yaw of +/- 2 deg. The investigation was made for angles of attack alpha, from -4 deg. to 14 deg. throughout most of the transonic speed range for values of reduced-frequency parameter from 0.015 to 0.040 based on wing mean aerodynamic chord and from 0.04 to 0.14 based on wing span. The results show that reduced frequency had only a small effect on the damping-in-pitch derivative and the oscillatory longitudinal stability derivative for all Mach numbers M and angles of attack with the exception of the values of damping coefficient near M = 1.03 and alpha = 8 deg. to 14 deg. In this region, the damping coefficient changed rapidly with reduced frequency and negative values of damping coefficient were measured at low values of reduced frequency. This abrupt variation of pitch damping with reduced frequency was a characteristic of the complete model or wing-body-vertical-tail combination. The damping-in-pitch derivative varied considerably with alpha and M for the horizontal-tail-on and horizontal-tail-off configurations, and the damping was relatively high at angles of attack corresponding to the onset of pitch-up for both configurations. The damping-in-yaw derivative was generally independent of reduced frequency and M at alpha = -4 deg. to 4 deg. At alpha = 8 deg. to 14 deg., the damping derivative increased with an increase in reduced frequency and alpha for the configurations having the wing, whereas the damping derivative was either independent of or decreased with increase in reduced frequency for the configuration without the wing. The oscillatory directional stability derivative for all configurations generally decreased with an increase in the reduced-frequency parameter, and, in some instances

Deriving the expected utility of a predictive model when the utilities are uncertain.

Science.gov (United States)

Cooper, Gregory F; Visweswaran, Shyam

2005-01-01

Predictive models are often constructed from clinical databases with the goal of eventually helping make better clinical decisions. Evaluating models using decision theory is therefore natural. When constructing a model using statistical and machine learning methods, however, we are often uncertain about precisely how the model will be used. Thus, decision-independent measures of classification performance, such as the area under an ROC curve, are popular. As a complementary method of evaluation, we investigate techniques for deriving the expected utility of a model under uncertainty about the model's utilities. We demonstrate an example of the application of this approach to the evaluation of two models that diagnose coronary artery disease.

Mapping populations at risk: improving spatial demographic data for infectious disease modeling and metric derivation

Directory of Open Access Journals (Sweden)

Tatem Andrew J

2012-05-01

Full Text Available Abstract The use of Global Positioning Systems (GPS and Geographical Information Systems (GIS in disease surveys and reporting is becoming increasingly routine, enabling a better understanding of spatial epidemiology and the improvement of surveillance and control strategies. In turn, the greater availability of spatially referenced epidemiological data is driving the rapid expansion of disease mapping and spatial modeling methods, which are becoming increasingly detailed and sophisticated, with rigorous handling of uncertainties. This expansion has, however, not been matched by advancements in the development of spatial datasets of human population distribution that accompany disease maps or spatial models. Where risks are heterogeneous across population groups or space or dependent on transmission between individuals, spatial data on human population distributions and demographic structures are required to estimate infectious disease risks, burdens, and dynamics. The disease impact in terms of morbidity, mortality, and speed of spread varies substantially with demographic profiles, so that identifying the most exposed or affected populations becomes a key aspect of planning and targeting interventions. Subnational breakdowns of population counts by age and sex are routinely collected during national censuses and maintained in finer detail within microcensus data. Moreover, demographic and health surveys continue to collect representative and contemporary samples from clusters of communities in low-income countries where census data may be less detailed and not collected regularly. Together, these freely available datasets form a rich resource for quantifying and understanding the spatial variations in the sizes and distributions of those most at risk of disease in low income regions, yet at present, they remain unconnected data scattered across national statistical offices and websites. In this paper we discuss the deficiencies of existing

Crop Model Improvement Reduces the Uncertainty of the Response to Temperature of Multi-Model Ensembles

Science.gov (United States)

Maiorano, Andrea; Martre, Pierre; Asseng, Senthold; Ewert, Frank; Mueller, Christoph; Roetter, Reimund P.; Ruane, Alex C.; Semenov, Mikhail A.; Wallach, Daniel; Wang, Enli

2016-01-01

To improve climate change impact estimates and to quantify their uncertainty, multi-model ensembles (MMEs) have been suggested. Model improvements can improve the accuracy of simulations and reduce the uncertainty of climate change impact assessments. Furthermore, they can reduce the number of models needed in a MME. Herein, 15 wheat growth models of a larger MME were improved through re-parameterization and/or incorporating or modifying heat stress effects on phenology, leaf growth and senescence, biomass growth, and grain number and size using detailed field experimental data from the USDA Hot Serial Cereal experiment (calibration data set). Simulation results from before and after model improvement were then evaluated with independent field experiments from a CIMMYT worldwide field trial network (evaluation data set). Model improvements decreased the variation (10th to 90th model ensemble percentile range) of grain yields simulated by the MME on average by 39% in the calibration data set and by 26% in the independent evaluation data set for crops grown in mean seasonal temperatures greater than 24 C. MME mean squared error in simulating grain yield decreased by 37%. A reduction in MME uncertainty range by 27% increased MME prediction skills by 47%. Results suggest that the mean level of variation observed in field experiments and used as a benchmark can be reached with half the number of models in the MME. Improving crop models is therefore important to increase the certainty of model-based impact assessments and allow more practical, i.e. smaller MMEs to be used effectively.

A non-local structural derivative model for characterization of ultraslow diffusion in dense colloids

Science.gov (United States)

Liang, Yingjie; Chen, Wen

2018-03-01

Ultraslow diffusion has been observed in numerous complicated systems. Its mean squared displacement (MSD) is not a power law function of time, but instead a logarithmic function, and in some cases grows even more slowly than the logarithmic rate. The distributed-order fractional diffusion equation model simply does not work for the general ultraslow diffusion. Recent study has used the local structural derivative to describe ultraslow diffusion dynamics by using the inverse Mittag-Leffler function as the structural function, in which the MSD is a function of inverse Mittag-Leffler function. In this study, a new stretched logarithmic diffusion law and its underlying non-local structural derivative diffusion model are proposed to characterize the ultraslow diffusion in aging dense colloidal glass at both the short and long waiting times. It is observed that the aging dynamics of dense colloids is a class of the stretched logarithmic ultraslow diffusion processes. Compared with the power, the logarithmic, and the inverse Mittag-Leffler diffusion laws, the stretched logarithmic diffusion law has better precision in fitting the MSD of the colloidal particles at high densities. The corresponding non-local structural derivative diffusion equation manifests clear physical mechanism, and its structural function is equivalent to the first-order derivative of the MSD.

A relative permeability model to derive fractional-flow functions of water-alternating-gas and surfactant-alternating-gas foam core-floods

International Nuclear Information System (INIS)

Al-Mossawy, Mohammed Idrees; Demiral, Birol; Raja, D M Anwar

2013-01-01

Foam is used in enhanced oil recovery to improve the sweep efficiency by controlling the gas mobility. The surfactant-alternating-gas (SAG) foam process is used as an alternative to the water-alternating-gas (WAG) injection. In the WAG technique, the high mobility and the low density of the gas lead the gas to flow in channels through the high permeability zones of the reservoir and to rise to the top of the reservoir by gravity segregation. As a result, the sweep efficiency decreases and there will be more residual oil in the reservoir. The foam can trap the gas in liquid films and reduces the gas mobility. The fractional-flow method describes the physics of immiscible displacements in porous media. Finding the water fractional flow theoretically or experimentally as a function of the water saturation represents the heart of this method. The relative permeability function is the conventional way to derive the fractional-flow function. This study presents an improved relative permeability model to derive the fractional-flow functions for WAG and SAG foam core-floods. The SAG flow regimes are characterized into weak foam, strong foam without a shock front and strong foam with a shock front. (paper)

Data-Driven Derivation of an "Informer Compound Set" for Improved Selection of Active Compounds in High-Throughput Screening.

Science.gov (United States)

Paricharak, Shardul; IJzerman, Adriaan P; Jenkins, Jeremy L; Bender, Andreas; Nigsch, Florian

2016-09-26

Despite the usefulness of high-throughput screening (HTS) in drug discovery, for some systems, low assay throughput or high screening cost can prohibit the screening of large numbers of compounds. In such cases, iterative cycles of screening involving active learning (AL) are employed, creating the need for smaller "informer sets" that can be routinely screened to build predictive models for selecting compounds from the screening collection for follow-up screens. Here, we present a data-driven derivation of an informer compound set with improved predictivity of active compounds in HTS, and we validate its benefit over randomly selected training sets on 46 PubChem assays comprising at least 300,000 compounds and covering a wide range of assay biology. The informer compound set showed improvement in BEDROC(α = 100), PRAUC, and ROCAUC values averaged over all assays of 0.024, 0.014, and 0.016, respectively, compared to randomly selected training sets, all with paired t-test p-values agnostic fashion. This approach led to a consistent improvement in hit rates in follow-up screens without compromising scaffold retrieval. The informer set is adjustable in size depending on the number of compounds one intends to screen, as performance gains are realized for sets with more than 3,000 compounds, and this set is therefore applicable to a variety of situations. Finally, our results indicate that random sampling may not adequately cover descriptor space, drawing attention to the importance of the composition of the training set for predicting actives.

An improved numerical approximation for the first derivative

Indian Academy of Sciences (India)

Administrator

The traditional numerical computation of the first derivative f ′(x) of a given function f (x) of a single argument ... includes the option of user-provided analytic deriva- tives, but its ...... will be in the near future, and back to the present. The macro ...

Improving the Fit of a Land-Surface Model to Data Using its Adjoint

Science.gov (United States)

Raoult, N.; Jupp, T. E.; Cox, P. M.; Luke, C.

2015-12-01

Land-surface models (LSMs) are of growing importance in the world of climate prediction. They are crucial components of larger Earth system models that are aimed at understanding the effects of land surface processes on the global carbon cycle. The Joint UK Land Environment Simulator (JULES) is the land-surface model used by the UK Met Office. It has been automatically differentiated using commercial software from FastOpt, resulting in an analytical gradient, or 'adjoint', of the model. Using this adjoint, the adJULES parameter estimation system has been developed, to search for locally optimum parameter sets by calibrating against observations. adJULES presents an opportunity to confront JULES with many different observations, and make improvements to the model parameterisation. In the newest version of adJULES, multiple sites can be used in the calibration, to giving a generic set of parameters that can be generalised over plant functional types. We present an introduction to the adJULES system and its applications to data from a variety of flux tower sites. We show that calculation of the 2nd derivative of JULES allows us to produce posterior probability density functions of the parameters and how knowledge of parameter values is constrained by observations.

The role of HUCB derived stem cells therapy in repair of renal ...

African Journals Online (AJOL)

Dr Olaleye Samuel

and improvement of renal function in cisplatin-induced ARF model. Forty four rats ... 88.9% of animals in MSCs treated rats versus 87.5% in CD34+ cells treated rats. HUCB derived .... containing 5 ml of citrate phosphate dextrose adenine-1.

A discrete-time two-factor model for pricing bonds and interest rate derivatives under random volatility

OpenAIRE

Heston, Steven L.; Nandi, Saikat

1999-01-01

This paper develops a discrete-time two-factor model of interest rates with analytical solutions for bonds and many interest rate derivatives when the volatility of the short rate follows a GARCH process that can be correlated with the level of the short rate itself. Besides bond and bond futures, the model yields analytical solutions for prices of European options on discount bonds (and futures) as well as other interest rate derivatives such as caps, floors, average rate options, yield curv...

Derivation and Numerical Approximation of the Quantum Drift Diffusion Model for Semiconductors

International Nuclear Information System (INIS)

Ohnmar Nwe

2004-06-01

This paper is concerned with the study of the quantum drift diffusion equation for semiconductors. Derivation of the mathematical model, which describes the electeon flow through a semiconductor device due to the application of a voltage, is considered and studied in numerical point of view by using some methods

Dataset of curcumin derivatives for QSAR modeling of anti cancer against P388 cell line

Directory of Open Access Journals (Sweden)

Yum Eryanti

2016-12-01

Full Text Available The dataset of curcumin derivatives consists of 45 compounds (Table 1 with their anti cancer biological activity (IC50 against P388 cell line. 45 curcumin derivatives were used in the model development where 30 of these compounds were in the training set and the remaining 15 compounds were in the test set. The development of the QSAR model involved the use of the multiple linear regression analysis (MLRA method. Based on the method, r2 value, r2 (CV value of 0.81, 0.67 were obtained. The QSAR model was also employed to predict the biological activity of compounds in the test set. Predictive correlation coefficient r2 values of 0.88 were obtained for the test set.

An Optimization Principle for Deriving Nonequilibrium Statistical Models of Hamiltonian Dynamics

Science.gov (United States)

Turkington, Bruce

2013-08-01

A general method for deriving closed reduced models of Hamiltonian dynamical systems is developed using techniques from optimization and statistical estimation. Given a vector of resolved variables, selected to describe the macroscopic state of the system, a family of quasi-equilibrium probability densities on phase space corresponding to the resolved variables is employed as a statistical model, and the evolution of the mean resolved vector is estimated by optimizing over paths of these densities. Specifically, a cost function is constructed to quantify the lack-of-fit to the microscopic dynamics of any feasible path of densities from the statistical model; it is an ensemble-averaged, weighted, squared-norm of the residual that results from submitting the path of densities to the Liouville equation. The path that minimizes the time integral of the cost function determines the best-fit evolution of the mean resolved vector. The closed reduced equations satisfied by the optimal path are derived by Hamilton-Jacobi theory. When expressed in terms of the macroscopic variables, these equations have the generic structure of governing equations for nonequilibrium thermodynamics. In particular, the value function for the optimization principle coincides with the dissipation potential that defines the relation between thermodynamic forces and fluxes. The adjustable closure parameters in the best-fit reduced equations depend explicitly on the arbitrary weights that enter into the lack-of-fit cost function. Two particular model reductions are outlined to illustrate the general method. In each example the set of weights in the optimization principle contracts into a single effective closure parameter.

High-resolution mutational profiling suggests the genetic validity of glioblastoma patient-derived pre-clinical models.

Directory of Open Access Journals (Sweden)

Shawn E Yost

Full Text Available Recent advances in the ability to efficiently characterize tumor genomes is enabling targeted drug development, which requires rigorous biomarker-based patient selection to increase effectiveness. Consequently, representative DNA biomarkers become equally important in pre-clinical studies. However, it is still unclear how well these markers are maintained between the primary tumor and the patient-derived tumor models. Here, we report the comprehensive identification of somatic coding mutations and copy number aberrations in four glioblastoma (GBM primary tumors and their matched pre-clinical models: serum-free neurospheres, adherent cell cultures, and mouse xenografts. We developed innovative methods to improve the data quality and allow a strict comparison of matched tumor samples. Our analysis identifies known GBM mutations altering PTEN and TP53 genes, and new actionable mutations such as the loss of PIK3R1, and reveals clear patient-to-patient differences. In contrast, for each patient, we do not observe any significant remodeling of the mutational profile between primary to model tumors and the few discrepancies can be attributed to stochastic errors or differences in sample purity. Similarly, we observe ∼96% primary-to-model concordance in copy number calls in the high-cellularity samples. In contrast to previous reports based on gene expression profiles, we do not observe significant differences at the DNA level between in vitro compared to in vivo models. This study suggests, at a remarkable resolution, the genome-wide conservation of a patient's tumor genetics in various pre-clinical models, and therefore supports their use for the development and testing of personalized targeted therapies.

Improvements and Limitations of Humanized Mouse Models for HIV Research: NIH/NIAID “Meet the Experts” 2015 Workshop Summary

Science.gov (United States)

Akkina, Ramesh; Allam, Atef; Balazs, Alejandro B.; Blankson, Joel N.; Burnett, John C.; Casares, Sofia; Garcia, J. Victor; Hasenkrug, Kim J.; Kitchen, Scott G.; Klein, Florian; Kumar, Priti; Luster, Andrew D.; Poluektova, Larisa Y.; Rao, Mangala; Shultz, Leonard D.; Zack, Jerome A.

2016-01-01

Abstract The number of humanized mouse models for the human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) and other infectious diseases has expanded rapidly over the past 8 years. Highly immunodeficient mouse strains, such as NOD/SCID/gamma chainnull (NSG, NOG), support better human hematopoietic cell engraftment. Another improvement is the derivation of highly immunodeficient mice, transgenic with human leukocyte antigens (HLAs) and cytokines that supported development of HLA-restricted human T cells and heightened human myeloid cell engraftment. Humanized mice are also used to study the HIV reservoir using new imaging techniques. Despite these advances, there are still limitations in HIV immune responses and deficits in lymphoid structures in these models in addition to xenogeneic graft-versus-host responses. To understand and disseminate the improvements and limitations of humanized mouse models to the scientific community, the NIH sponsored and convened a meeting on April 15, 2015 to discuss the state of knowledge concerning these questions and best practices for selecting a humanized mouse model for a particular scientific investigation. This report summarizes the findings of the NIH meeting. PMID:26670361

Improved prediction of residue flexibility by embedding optimized amino acid grouping into RSA-based linear models.

Science.gov (United States)

Zhang, Hua; Kurgan, Lukasz

2014-12-01

Knowledge of protein flexibility is vital for deciphering the corresponding functional mechanisms. This knowledge would help, for instance, in improving computational drug design and refinement in homology-based modeling. We propose a new predictor of the residue flexibility, which is expressed by B-factors, from protein chains that use local (in the chain) predicted (or native) relative solvent accessibility (RSA) and custom-derived amino acid (AA) alphabets. Our predictor is implemented as a two-stage linear regression model that uses RSA-based space in a local sequence window in the first stage and a reduced AA pair-based space in the second stage as the inputs. This method is easy to comprehend explicit linear form in both stages. Particle swarm optimization was used to find an optimal reduced AA alphabet to simplify the input space and improve the prediction performance. The average correlation coefficients between the native and predicted B-factors measured on a large benchmark dataset are improved from 0.65 to 0.67 when using the native RSA values and from 0.55 to 0.57 when using the predicted RSA values. Blind tests that were performed on two independent datasets show consistent improvements in the average correlation coefficients by a modest value of 0.02 for both native and predicted RSA-based predictions.

Improved SPICE electrical model of silicon photomultipliers

Energy Technology Data Exchange (ETDEWEB)

Marano, D., E-mail: davide.marano@oact.inaf.it [INAF, Osservatorio Astrofisico di Catania, Via S. Sofia 78, I-95123 Catania (Italy); Bonanno, G.; Belluso, M.; Billotta, S.; Grillo, A.; Garozzo, S.; Romeo, G. [INAF, Osservatorio Astrofisico di Catania, Via S. Sofia 78, I-95123 Catania (Italy); Catalano, O.; La Rosa, G.; Sottile, G.; Impiombato, D.; Giarrusso, S. [INAF, Istituto di Astrofisica Spaziale e Fisica Cosmica di Palermo, Via U. La Malfa 153, I-90146 Palermo (Italy)

2013-10-21

The present work introduces an improved SPICE equivalent electrical model of silicon photomultiplier (SiPM) detectors, in order to simulate and predict their transient response to avalanche triggering events. In particular, the developed circuit model provides a careful investigation of the magnitude and timing of the read-out signals and can therefore be exploited to perform reliable circuit-level simulations. The adopted modeling approach is strictly related to the physics of each basic microcell constituting the SiPM device, and allows the avalanche timing as well as the photodiode current and voltage to be accurately simulated. Predictive capabilities of the proposed model are demonstrated by means of experimental measurements on a real SiPM detector. Simulated and measured pulses are found to be in good agreement with the expected results. -- Highlights: • An improved SPICE electrical model of silicon photomultipliers is proposed. • The developed model provides a truthful representation of the physics of the device. • An accurate charge collection as a function of the overvoltage is achieved. • The adopted electrical model allows reliable circuit-level simulations to be performed. • Predictive capabilities of the adopted model are experimentally demonstrated.

Modelling vertical error in LiDAR-derived digital elevation models

Science.gov (United States)

Aguilar, Fernando J.; Mills, Jon P.; Delgado, Jorge; Aguilar, Manuel A.; Negreiros, J. G.; Pérez, José L.

2010-01-01

A hybrid theoretical-empirical model has been developed for modelling the error in LiDAR-derived digital elevation models (DEMs) of non-open terrain. The theoretical component seeks to model the propagation of the sample data error (SDE), i.e. the error from light detection and ranging (LiDAR) data capture of ground sampled points in open terrain, towards interpolated points. The interpolation methods used for infilling gaps may produce a non-negligible error that is referred to as gridding error. In this case, interpolation is performed using an inverse distance weighting (IDW) method with the local support of the five closest neighbours, although it would be possible to utilize other interpolation methods. The empirical component refers to what is known as "information loss". This is the error purely due to modelling the continuous terrain surface from only a discrete number of points plus the error arising from the interpolation process. The SDE must be previously calculated from a suitable number of check points located in open terrain and assumes that the LiDAR point density was sufficiently high to neglect the gridding error. For model calibration, data for 29 study sites, 200×200 m in size, belonging to different areas around Almeria province, south-east Spain, were acquired by means of stereo photogrammetric methods. The developed methodology was validated against two different LiDAR datasets. The first dataset used was an Ordnance Survey (OS) LiDAR survey carried out over a region of Bristol in the UK. The second dataset was an area located at Gador mountain range, south of Almería province, Spain. Both terrain slope and sampling density were incorporated in the empirical component through the calibration phase, resulting in a very good agreement between predicted and observed data (R2 = 0.9856 ; p reasonably good fit to the predicted errors. Even better results were achieved in the more rugged morphology of the Gador mountain range dataset. The findings

Using scale heights derived from bottomside ionograms for modelling the IRI topside profile

Directory of Open Access Journals (Sweden)

B. W. Reinisch

2004-01-01

Full Text Available Groundbased ionograms measure the Chapman scale height HT at the F2-layer peak that is used to construct the topside profile. After a brief review of the topside model extrapolation technique, comparisons are presented between the modeled profiles with incoherent scatter radar and satellite measurements for the mid latitude and equatorial ionosphere. The total electron content TEC, derived from measurements on satellite beacon signals, is compared with the height-integrated profiles ITEC from the ionograms. Good agreement is found with the ISR profiles and with results using the low altitude TOPEX satellite. The TEC values derived from GPS signal analysis are systematically larger than ITEC. It is suggested to use HT , routinely measured by a large number of Digisondes around the globe, for the construction of the IRI topside electron density profile.

Improvements in ECN Wake Model

Energy Technology Data Exchange (ETDEWEB)

Versteeg, M.C. [University of Twente, Enschede (Netherlands); Ozdemir, H.; Brand, A.J. [ECN Wind Energy, Petten (Netherlands)

2013-08-15

Wind turbines extract energy from the flow field so that the flow in the wake of a wind turbine contains less energy and more turbulence than the undisturbed flow, leading to less energy extraction for the downstream turbines. In large wind farms, most turbines are located in the wake of one or more turbines causing the flow characteristics felt by these turbines differ considerably from the free stream flow conditions. The most important wake effect is generally considered to be the lower wind speed behind the turbine(s) since this decreases the energy production and as such the economical performance of a wind farm. The overall loss of a wind farm is very much dependent on the conditions and the lay-out of the farm but it can be in the order of 5-10%. Apart from the loss in energy production an additional wake effect is formed by the increase in turbulence intensity, which leads to higher fatigue loads. In this sense it becomes important to understand the details of wake behavior to improve and/or optimize a wind farm layout. Within this study improvements are presented for the existing ECN wake model which constructs the fundamental basis of ECN's FarmFlow wind farm wake simulation tool. The outline of this paper is as follows: first, the governing equations of the ECN wake farm model are presented. Then the near wake modeling is discussed and the results compared with the original near wake modeling and EWTW (ECN Wind Turbine Test Site Wieringermeer) data as well as the results obtained for various near wake implementation cases are shown. The details of the atmospheric stability model are given and the comparison with the solution obtained for the original surface layer model and with the available data obtained by EWTW measurements are presented. Finally the conclusions are summarized.

A tracer diffusion model derived from microstructure

International Nuclear Information System (INIS)

Lehikoinen, Jarmo; Muurinen, Arto; Olin, Markus

2012-01-01

of reference, is shown to be given by the ratio of the effective diffusivity to the apparent diffusivity for an assumed non-interacting solute, such as tritiated water. Finally, the utility of the model and derivation of the model parameters are demonstrated with tracer diffusion data from the open literature for compacted bentonite. (authors)

Improving Catastrophe Modeling for Business Interruption Insurance Needs.

Science.gov (United States)

Rose, Adam; Huyck, Charles K

2016-10-01

While catastrophe (CAT) modeling of property damage is well developed, modeling of business interruption (BI) lags far behind. One reason is the crude nature of functional relationships in CAT models that translate property damage into BI. Another is that estimating BI losses is more complicated because it depends greatly on public and private decisions during recovery with respect to resilience tactics that dampen losses by using remaining resources more efficiently to maintain business function and to recover more quickly. This article proposes a framework for improving hazard loss estimation for BI insurance needs. Improved data collection that allows for analysis at the level of individual facilities within a company can improve matching the facilities with the effectiveness of individual forms of resilience, such as accessing inventories, relocating operations, and accelerating repair, and can therefore improve estimation accuracy. We then illustrate the difference this can make in a case study example of losses from a hurricane. © 2016 Society for Risk Analysis.

The Accuracy and Reproducibility of Linear Measurements Made on CBCT-derived Digital Models.

Science.gov (United States)

Maroua, Ahmad L; Ajaj, Mowaffak; Hajeer, Mohammad Y

2016-04-01

To evaluate the accuracy and reproducibility of linear measurements made on cone-beam computed tomography (CBCT)-derived digital models. A total of 25 patients (44% female, 18.7 ± 4 years) who had CBCT images for diagnostic purposes were included. Plaster models were obtained and digital models were extracted from CBCT scans. Seven linear measurements from predetermined landmarks were measured and analyzed on plaster models and the corresponding digital models. The measurements included arch length and width at different sites. Paired t test and Bland-Altman analysis were used to evaluate the accuracy of measurements on digital models compared to the plaster models. Also, intraclass correlation coefficients (ICCs) were used to evaluate the reproducibility of the measurements in order to assess the intraobserver reliability. The statistical analysis showed significant differences on 5 out of 14 variables, and the mean differences ranged from -0.48 to 0.51 mm. The Bland-Altman analysis revealed that the mean difference between variables was (0.14 ± 0.56) and (0.05 ± 0.96) mm and limits of agreement between the two methods ranged from -1.2 to 0.96 and from -1.8 to 1.9 mm in the maxilla and the mandible, respectively. The intraobserver reliability values were determined for all 14 variables of two types of models separately. The mean ICC value for the plaster models was 0.984 (0.924-0.999), while it was 0.946 for the CBCT models (range from 0.850 to 0.985). Linear measurements obtained from the CBCT-derived models appeared to have a high level of accuracy and reproducibility.

Human bone marrow-derived and umbilical cord-derived mesenchymal stem cells for alleviating neuropathic pain in a spinal cord injury model

OpenAIRE

Yousefifard, Mahmoud; Nasirinezhad, Farinaz; Shardi Manaheji, Homa; Janzadeh, Atousa; Hosseini, Mostafa; Keshavarz, Mansoor

2016-01-01

Background Stem cell therapy can be used for alleviating the neuropathic pain induced by spinal cord injuries (SCIs). However, survival and differentiation of stem cells following their transplantation vary depending on the host and intrinsic factors of the cell. Therefore, the present study aimed to determine the effect of stem cells derived from bone marrow (BM-MSC) and umbilical cord (UC-MSC) on neuropathic pain relief. Methods A compression model was used to induce SCI in a rat model. A w...

A well-refined in vitro model derived from human embryonic stem cell for screening phytochemicals with midbrain dopaminergic differentiation-boosting potential for improving Parkinson's disease.

Science.gov (United States)

Hsieh, Wen-Ting; Chiang, Been-Huang

2014-07-09

Stimulation of endogenous neurogenesis is a potential approach to compensate for loss of dopaminergic neurons of substantia nigra compacta nigra (SNpc) in patients with Parkinson's disease (PD). This objective was to establish an in vitro model by differentiating pluripotent human embryonic stem cells (hESCs) into midbrain dopaminergic (mDA) neurons for screening phytochemicals with mDA neurogenesis-boosting potentials. Consequently, a five-stage differentiation process was developed. The derived cells expressed many mDA markers including tyrosine hydroxylase (TH), β-III tubulin, and dopamine transporter (DAT). The voltage-gated ion channels and dopamine release were also examined for verifying neuron function, and the dopamine receptor agonists bromocriptine and 7-hydroxy-2-(dipropylamino)tetralin (7-OH-DPAT) were used to validate our model. Then, several potential phytochemicals including green tea catechins and ginsenosides were tested using the model. Finally, ginsenoside Rb1 was identified as the most potent phytochemical which is capable of upregulating neurotrophin expression and inducing mDA differentiation.

Improved hydrogen combustion model for multi-compartment analysis

International Nuclear Information System (INIS)

Ogino, Masao; Hashimoto, Takashi

2000-01-01

NUPEC has been improving a hydrogen combustion model in MELCOR code for severe accident analysis. In the proposed combustion model, the flame velocity in a node was predicted using six different flame front shapes of fireball, prism, bubble, spherical jet, plane jet, and parallelepiped. A verification study of the proposed model was carried out using the NUPEC large-scale combustion test results following the previous work in which the GRS/Battelle multi-compartment combustion test results had been used. The selected test cases for the study were the premixed test and the scenario-oriented test which simulated the severe accident sequences of an actual plant. The improved MELCOR code replaced by the proposed model could predict sufficiently both results of the premixed test and the scenario-oriented test of NUPEC large-scale test. The improved MELCOR code was confirmed to simulate the combustion behavior in the multi-compartment containment vessel during a severe accident with acceptable degree of accuracy. Application of the new model to the LWR severe accident analysis will be continued. (author)

The impact of derivatives on Malaysian stock market

Science.gov (United States)

Malim, M. R.; Halim, F. A.; Murad, A.; Maad, H. A.; Annuar, N. F. M.

2017-09-01

The essential of derivatives has been discovered by researchers over recent decade. However, the conclusions made regarding the impact of derivatives on stock market volatility remains debatable. The main objective of this study is to examine the impact of derivatives on Malaysian stock market volatility by exploring FTSE Bursa Malaysia Kuala Lumpur Composite Index Futures (BMD FKLI) using FBM KLCI as the underlying asset. Generalized Autoregressive Conditional Heteroskedasticity (GARCH) (1, 1) model was employed to realize the objective. The results have shown that the introduction of futures trading has decreased the volatility of Malaysian stock market. The volatility increased vigorously during the Asian financial crisis compared to the Global financial crisis. However, the role of futures as a risk transfer is agreed as it could improve the market by decreasing the volatility in the spot market.

Essays on Derivatives Pricing

DEFF Research Database (Denmark)

Kokholm, Thomas

. With the existence of a liquid market for derivatives with variance as underlying, such as VIX options, VIX futures and a well-developed over-the-counter market for options on variance swaps, it is important to consider models that are able to fit these markets while consistently pricing vanilla options...... financial models, and most importantly, to be aware of their limitations. Following that belief, this thesis consists of three independent and self-contained papers, all dealing with topics in derivatives pricing. The first paper considers the pricing of traffic light options, which are appropriate...... the market for multivariate credit instruments, we take a step back and focus on single-name default modeling and introduce two new model classes for modeling of the default time of a company. Finally, in the third paper we propose a consistent pricing model for index and volatility derivatives...

A Conceptually Simple Modeling Approach for Jason-1 Sea State Bias Correction Based on 3 Parameters Exclusively Derived from Altimetric Information

Directory of Open Access Journals (Sweden)

Nelson Pires

2016-07-01

Full Text Available A conceptually simple formulation is proposed for a new empirical sea state bias (SSB model using information retrieved entirely from altimetric data. Nonparametric regression techniques are used, based on penalized smoothing splines adjusted to each predictor and then combined by a Generalized Additive Model. In addition to the significant wave height (SWH and wind speed (U10, a mediator parameter designed by the mean wave period derived from radar altimetry, has proven to improve the model performance in explaining some of the SSB variability, especially in swell ocean regions with medium-high SWH and low U10. A collinear analysis of scaled sea level anomalies (SLA variance differences shows conformity between the proposed model and the established SSB models. The new formulation aims to be a fast, reliable and flexible SSB model, in line with the well-settled SSB corrections, depending exclusively on altimetric information. The suggested method is computationally efficient and capable of generating a stable model with a small training dataset, a useful feature for forthcoming missions.

Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation

Science.gov (United States)

Qin, Changbo; Jia, Yangwen; Su, Z.(Bob); Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen

2008-01-01

This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems. PMID:27879946

Improvements on Semi-Classical Distorted-Wave model

Energy Technology Data Exchange (ETDEWEB)

Sun Weili; Watanabe, Y.; Kuwata, R. [Kyushu Univ., Fukuoka (Japan); Kohno, M.; Ogata, K.; Kawai, M.

1998-03-01

A method of improving the Semi-Classical Distorted Wave (SCDW) model in terms of the Wigner transform of the one-body density matrix is presented. Finite size effect of atomic nuclei can be taken into account by using the single particle wave functions for harmonic oscillator or Wood-Saxon potential, instead of those based on the local Fermi-gas model which were incorporated into previous SCDW model. We carried out a preliminary SCDW calculation of 160 MeV (p,p`x) reaction on {sup 90}Zr with the Wigner transform of harmonic oscillator wave functions. It is shown that the present calculation of angular distributions increase remarkably at backward angles than the previous ones and the agreement with the experimental data is improved. (author)

Electricity derivatives

CERN Document Server

Aïd, René

2015-01-01

Offering a concise but complete survey of the common features of the microstructure of electricity markets, this book describes the state of the art in the different proposed electricity price models for pricing derivatives and in the numerical methods used to price and hedge the most prominent derivatives in electricity markets, namely power plants and swings. The mathematical content of the book has intentionally been made light in order to concentrate on the main subject matter, avoiding fastidious computations. Wherever possible, the models are illustrated by diagrams. The book should allow prospective researchers in the field of electricity derivatives to focus on the actual difficulties associated with the subject. It should also offer a brief but exhaustive overview of the latest techniques used by financial engineers in energy utilities and energy trading desks.

An improved corrective smoothed particle method approximation for second‐order derivatives

NARCIS (Netherlands)

Korzilius, S.P.; Schilders, W.H.A.; Anthonissen, M.J.H.

2013-01-01

To solve (partial) differential equations it is necessary to have good numerical approximations. In SPH, most approximations suffer from the presence of boundaries. In this work a new approximation for the second-order derivative is derived and numerically compared with two other approximation

Deriving albedo maps for HAPEX-Sahel from ASAS data using kernel-driven BRDF models

Directory of Open Access Journals (Sweden)

P. Lewis

1999-01-01

Full Text Available This paper describes the application and testing of a method for deriving spatial estimates of albedo from multi-angle remote sensing data. Linear kernel-driven models of surface bi-directional reflectance have been inverted against high spatial resolution multi-angular, multi- spectral airborne data of the principal cover types within the HAPEX-Sahel study site in Niger, West Africa. The airborne data are obtained from the NASA Airborne Solid-state Imaging Spectrometer (ASAS instrument, flown in Niger in September and October 1992. The maps of model parameters produced are used to estimate integrated reflectance properties related to spectral albedo. Broadband albedo has been estimated from this by weighting the spectral albedo for each pixel within the map as a function of the appropriate spectral solar irradiance and proportion of direct and diffuse illumination. Partial validation of the results was performed by comparing ASAS reflectance and derived directional-hemispherical reflectance with simulations of a millet canopy made with a complex geometric canopy reflectance model, the Botanical Plant Modelling System (BPMS. Both were found to agree well in magnitude. Broadband albedo values derived from the ASAS data were compared with ground-based (point sample albedo measurements and found to agree extremely well. These results indicate that the linear kernel-driven modelling approach, which is to be used operationally to produce global 16 day, 1 km albedo maps from forthcoming NASA Earth Observing System spaceborne data, is both sound and practical for the estimation of angle-integrated spectral reflectance quantities related to albedo. Results for broadband albedo are dependent on spectral sampling and on obtaining the correct spectral weigthings.

Improved double Q2 rescaling model

International Nuclear Information System (INIS)

Gao Yonghua

2001-01-01

The authors present an improved double Q 2 rescaling model. Based on this condition of the nuclear momentum conservation, the authors have found a Q 2 rescaling parameters' formula of the model, where authors have established the connection between the Q 2 rescaling parameter ζ i (i = v, s, g) and the mean binding energy in nucleus. By using this model, the authors coned explain the experimental data of the EMC effect in the whole x region, the nuclear Drell-Yan process and J/Ψ photoproduction process

Construction of integrable model Kohn-Sham potentials by analysis of the structure of functional derivatives

International Nuclear Information System (INIS)

Gaiduk, Alex P.; Staroverov, Viktor N.

2011-01-01

A directly approximated exchange-correlation potential should, by construction, be a functional derivative of some density functional in order to avoid unphysical results. Using generalized gradient approximations (GGAs) as an example, we show that functional derivatives of explicit density functionals have a very rigid inner structure, the knowledge of which allows one to build the entire functional derivative from a small part. Based on this analysis, we develop a method for direct construction of integrable Kohn-Sham potentials. As an illustration, we transform the model potential of van Leeuwen and Baerends (which is not a functional derivative) into a semilocal exchange potential that has a parent GGA, yields accurate energies, and is free from the artifacts inherent in existing semilocal potential approximations.

Biomimetic synthesis of proline-derivative templated mesoporous silica for increasing the brain distribution of diazepam and improving the pharmacodynamics of nimesulide

DEFF Research Database (Denmark)

Li, Heran; Wang, Jianxin; Cong, Jialiang

2017-01-01

Herein a new kind of proline-derivative templated mesoporous silica with curved channels (CMS) was biomimetically synthesized and applied as carrier to improve the drug dissolution and bioavailability of hydrophobic diazepam (DZP) and nimesulide (NMS). Drugs can be incorporated into CMS with high...... improved, and the inhibition rates of 1:3 NMS/CMS in all pharmacodynamics tests varied from 102.2% to 904.3%....

Development of West-European PM2.5 and NO2 land use regression models incorporating satellite-derived and chemical transport modelling data

NARCIS (Netherlands)

de Hoogh, Kees; Gulliver, John; Donkelaar, Aaron van; Martin, Randall V; Marshall, Julian D; Bechle, Matthew J; Cesaroni, Giulia; Pradas, Marta Cirach; Dedele, Audrius; Eeftens, Marloes|info:eu-repo/dai/nl/315028300; Forsberg, Bertil; Galassi, Claudia; Heinrich, Joachim; Hoffmann, Barbara; Jacquemin, Bénédicte; Katsouyanni, Klea; Korek, Michal; Künzli, Nino; Lindley, Sarah J; Lepeule, Johanna; Meleux, Frederik; de Nazelle, Audrey; Nieuwenhuijsen, Mark; Nystad, Wenche; Raaschou-Nielsen, Ole; Peters, Annette; Peuch, Vincent-Henri; Rouil, Laurence; Udvardy, Orsolya; Slama, Rémy; Stempfelet, Morgane; Stephanou, Euripides G; Tsai, Ming Y; Yli-Tuomi, Tarja; Weinmayr, Gudrun; Brunekreef, Bert|info:eu-repo/dai/nl/067548180; Vienneau, Danielle; Hoek, Gerard|info:eu-repo/dai/nl/069553475

2016-01-01

Satellite-derived (SAT) and chemical transport model (CTM) estimates of PM2.5 and NO2 are increasingly used in combination with Land Use Regression (LUR) models. We aimed to compare the contribution of SAT and CTM data to the performance of LUR PM2.5 and NO2 models for Europe. Four sets of models,

Improvement and Validation of Weld Residual Stress Modelling Procedure

International Nuclear Information System (INIS)

Zang, Weilin; Gunnars, Jens; Dong, Pingsha; Hong, Jeong K.

2009-06-01

The objective of this work is to identify and evaluate improvements for the residual stress modelling procedure currently used in Sweden. There is a growing demand to eliminate any unnecessary conservatism involved in residual stress assumptions. The study was focused on the development and validation of an improved weld residual stress modelling procedure, by taking advantage of the recent advances in residual stress modelling and stress measurement techniques. The major changes applied in the new weld residual stress modelling procedure are: - Improved procedure for heat source calibration based on use of analytical solutions. - Use of an isotropic hardening model where mixed hardening data is not available. - Use of an annealing model for improved simulation of strain relaxation in re-heated material. The new modelling procedure is demonstrated to capture the main characteristics of the through thickness stress distributions by validation to experimental measurements. Three austenitic stainless steel butt-welds cases are analysed, covering a large range of pipe geometries. From the cases it is evident that there can be large differences between the residual stresses predicted using the new procedure, and the earlier procedure or handbook recommendations. Previously recommended profiles could give misleading fracture assessment results. The stress profiles according to the new procedure agree well with the measured data. If data is available then a mixed hardening model should be used

Improvement and Validation of Weld Residual Stress Modelling Procedure

Energy Technology Data Exchange (ETDEWEB)

Zang, Weilin; Gunnars, Jens (Inspecta Technology AB, Stockholm (Sweden)); Dong, Pingsha; Hong, Jeong K. (Center for Welded Structures Research, Battelle, Columbus, OH (United States))

2009-06-15

The objective of this work is to identify and evaluate improvements for the residual stress modelling procedure currently used in Sweden. There is a growing demand to eliminate any unnecessary conservatism involved in residual stress assumptions. The study was focused on the development and validation of an improved weld residual stress modelling procedure, by taking advantage of the recent advances in residual stress modelling and stress measurement techniques. The major changes applied in the new weld residual stress modelling procedure are: - Improved procedure for heat source calibration based on use of analytical solutions. - Use of an isotropic hardening model where mixed hardening data is not available. - Use of an annealing model for improved simulation of strain relaxation in re-heated material. The new modelling procedure is demonstrated to capture the main characteristics of the through thickness stress distributions by validation to experimental measurements. Three austenitic stainless steel butt-welds cases are analysed, covering a large range of pipe geometries. From the cases it is evident that there can be large differences between the residual stresses predicted using the new procedure, and the earlier procedure or handbook recommendations. Previously recommended profiles could give misleading fracture assessment results. The stress profiles according to the new procedure agree well with the measured data. If data is available then a mixed hardening model should be used

Improving practical atmospheric dispersion models

International Nuclear Information System (INIS)

Hunt, J.C.R.; Hudson, B.; Thomson, D.J.

1992-01-01

The new generation of practical atmospheric dispersion model (for short range ≤ 30 km) are based on dispersion science and boundary layer meteorology which have widespread international acceptance. In addition, recent improvements in computer skills and the widespread availability of small powerful computers make it possible to have new regulatory models which are more complex than the previous generation which were based on charts and simple formulae. This paper describes the basis of these models and how they have developed. Such models are needed to satisfy the urgent public demand for sound, justifiable and consistent environmental decisions. For example, it is preferable that the same models are used to simulate dispersion in different industries; in many countries at present different models are used for emissions from nuclear and fossil fuel power stations. The models should not be so simple as to be suspect but neither should they be too complex for widespread use; for example, at public inquiries in Germany, where simple models are mandatory, it is becoming usual to cite the results from highly complex computational models because the simple models are not credible. This paper is written in a schematic style with an emphasis on tables and diagrams. (au) (22 refs.)

A space-time hybrid hourly rainfall model for derived flood frequency analysis

Directory of Open Access Journals (Sweden)

U. Haberlandt

2008-12-01

Full Text Available For derived flood frequency analysis based on hydrological modelling long continuous precipitation time series with high temporal resolution are needed. Often, the observation network with recording rainfall gauges is poor, especially regarding the limited length of the available rainfall time series. Stochastic precipitation synthesis is a good alternative either to extend or to regionalise rainfall series to provide adequate input for long-term rainfall-runoff modelling with subsequent estimation of design floods. Here, a new two step procedure for stochastic synthesis of continuous hourly space-time rainfall is proposed and tested for the extension of short observed precipitation time series.

First, a single-site alternating renewal model is presented to simulate independent hourly precipitation time series for several locations. The alternating renewal model describes wet spell durations, dry spell durations and wet spell intensities using univariate frequency distributions separately for two seasons. The dependence between wet spell intensity and duration is accounted for by 2-copulas. For disaggregation of the wet spells into hourly intensities a predefined profile is used. In the second step a multi-site resampling procedure is applied on the synthetic point rainfall event series to reproduce the spatial dependence structure of rainfall. Resampling is carried out successively on all synthetic event series using simulated annealing with an objective function considering three bivariate spatial rainfall characteristics. In a case study synthetic precipitation is generated for some locations with short observation records in two mesoscale catchments of the Bode river basin located in northern Germany. The synthetic rainfall data are then applied for derived flood frequency analysis using the hydrological model HEC-HMS. The results show good performance in reproducing average and extreme rainfall characteristics as well as in

Modeling heterogeneous (co)variances from adjacent-SNP groups improves genomic prediction for milk protein composition traits

DEFF Research Database (Denmark)

Gebreyesus, Grum; Lund, Mogens Sandø; Buitenhuis, Albert Johannes

2017-01-01

Accurate genomic prediction requires a large reference population, which is problematic for traits that are expensive to measure. Traits related to milk protein composition are not routinely recorded due to costly procedures and are considered to be controlled by a few quantitative trait loci...... of large effect. The amount of variation explained may vary between regions leading to heterogeneous (co)variance patterns across the genome. Genomic prediction models that can efficiently take such heterogeneity of (co)variances into account can result in improved prediction reliability. In this study, we...... developed and implemented novel univariate and bivariate Bayesian prediction models, based on estimates of heterogeneous (co)variances for genome segments (BayesAS). Available data consisted of milk protein composition traits measured on cows and de-regressed proofs of total protein yield derived for bulls...

Understanding catchment behaviour through model concept improvement

NARCIS (Netherlands)

Fenicia, F.

2008-01-01

This thesis describes an approach to model development based on the concept of iterative model improvement, which is a process where by trial and error different hypotheses of catchment behaviour are progressively tested, and the understanding of the system proceeds through a combined process of

Human umbilical cord blood stem cells and brain-derived neurotrophic factor for optic nerve injury: a biomechanical evaluation

Directory of Open Access Journals (Sweden)

Zhong-jun Zhang

2015-01-01

Full Text Available Treatment for optic nerve injury by brain-derived neurotrophic factor or the transplantation of human umbilical cord blood stem cells has gained progress, but analysis by biomechanical indicators is rare. Rabbit models of optic nerve injury were established by a clamp. At 7 days after injury, the vitreous body received a one-time injection of 50 μg brain-derived neurotrophic factor or 1 × 10 6 human umbilical cord blood stem cells. After 30 days, the maximum load, maximum stress, maximum strain, elastic limit load, elastic limit stress, and elastic limit strain had clearly improved in rabbit models of optical nerve injury after treatment with brain-derived neurotrophic factor or human umbilical cord blood stem cells. The damage to the ultrastructure of the optic nerve had also been reduced. These findings suggest that human umbilical cord blood stem cells and brain-derived neurotrophic factor effectively repair the injured optical nerve, improve biomechanical properties, and contribute to the recovery after injury.

Direct phase derivative estimation using difference equation modeling in holographic interferometry

International Nuclear Information System (INIS)

Kulkarni, Rishikesh; Rastogi, Pramod

2014-01-01

A new method is proposed for the direct phase derivative estimation from a single spatial frequency modulated carrier fringe pattern in holographic interferometry. The fringe intensity in a given row/column is modeled as a difference equation of intensity with spatially varying coefficients. These coefficients carry the information on the phase derivative. Consequently, the accurate estimation of the coefficients is obtained by approximating the coefficients as a linear combination of the predefined linearly independent basis functions. Unlike Fourier transform based fringe analysis, the method does not call for performing the filtering of the Fourier spectrum of fringe intensity. Moreover, the estimation of the carrier frequency is performed by applying the proposed method to a reference interferogram. The performance of the proposed method is insensitive to the fringe amplitude modulation and is validated with the simulation results. (paper)

Improved Mathematical Models for Particle-Size Distribution Data

African Journals Online (AJOL)

BirukEdimon

School of Civil & Environmental Engineering, Addis Ababa Institute of Technology,. 3. Murray Rix ... two improved mathematical models to describe ... demand further improvement to handle the PSD ... statistics and the range of the optimized.

A rapid approach for automated comparison of independently derived stream networks

Science.gov (United States)

Stanislawski, Larry V.; Buttenfield, Barbara P.; Doumbouya, Ariel T.

2015-01-01

This paper presents an improved coefficient of line correspondence (CLC) metric for automatically assessing the similarity of two different sets of linear features. Elevation-derived channels at 1:24,000 scale (24K) are generated from a weighted flow-accumulation model and compared to 24K National Hydrography Dataset (NHD) flowlines. The CLC process conflates two vector datasets through a raster line-density differencing approach that is faster and more reliable than earlier methods. Methods are tested on 30 subbasins distributed across different terrain and climate conditions of the conterminous United States. CLC values for the 30 subbasins indicate 44–83% of the features match between the two datasets, with the majority of the mismatching features comprised of first-order features. Relatively lower CLC values result from subbasins with less than about 1.5 degrees of slope. The primary difference between the two datasets may be explained by different data capture criteria. First-order, headwater tributaries derived from the flow-accumulation model are captured more comprehensively through drainage area and terrain conditions, whereas capture of headwater features in the NHD is cartographically constrained by tributary length. The addition of missing headwaters to the NHD, as guided by the elevation-derived channels, can substantially improve the scientific value of the NHD.

Improving the Ni I atomic model for solar and stellar atmospheric models

International Nuclear Information System (INIS)

Vieytes, M. C.; Fontenla, J. M.

2013-01-01

Neutral nickel (Ni I) is abundant in the solar atmosphere and is one of the important elements that contribute to the emission and absorption of radiation in the spectral range between 1900 and 3900 Å. Previously, the Solar Radiation Physical Modeling (SRPM) models of the solar atmosphere only considered a few levels of this species. Here, we improve the Ni I atomic model by taking into account 61 levels and 490 spectral lines. We compute the populations of these levels in full NLTE using the SRPM code and compare the resulting emerging spectrum with observations. The present atomic model significantly improves the calculation of the solar spectral irradiance at near-UV wavelengths, which is important for Earth atmospheric studies, and particularly for ozone chemistry.

Improving the Ni I atomic model for solar and stellar atmospheric models

Energy Technology Data Exchange (ETDEWEB)

Vieytes, M. C. [Instituto de de Astronomía y Física del Espacio, CONICET and UNTREF, Buenos Aires (Argentina); Fontenla, J. M., E-mail: mariela@iafe.uba.ar, E-mail: johnf@digidyna.com [North West Research Associates, 3380 Mitchell Lane, Boulder, CO 80301 (United States)

2013-06-01

Neutral nickel (Ni I) is abundant in the solar atmosphere and is one of the important elements that contribute to the emission and absorption of radiation in the spectral range between 1900 and 3900 Å. Previously, the Solar Radiation Physical Modeling (SRPM) models of the solar atmosphere only considered a few levels of this species. Here, we improve the Ni I atomic model by taking into account 61 levels and 490 spectral lines. We compute the populations of these levels in full NLTE using the SRPM code and compare the resulting emerging spectrum with observations. The present atomic model significantly improves the calculation of the solar spectral irradiance at near-UV wavelengths, which is important for Earth atmospheric studies, and particularly for ozone chemistry.

Assessing the Use of Remote Sensing and a Crop Growth Model to Improve Modeled Streamflow in Central Asia

Science.gov (United States)

Richey, A. S.; Richey, J. E.; Tan, A.; Liu, M.; Adam, J. C.; Sokolov, V.

2015-12-01

Central Asia presents a perfect case study to understand the dynamic, and often conflicting, linkages between food, energy, and water in natural systems. The destruction of the Aral Sea is a well-known environmental disaster, largely driven by increased irrigation demand on the rivers that feed the endorheic sea. Continued reliance on these rivers, the Amu Darya and Syr Darya, often place available water resources at odds between hydropower demands upstream and irrigation requirements downstream. A combination of tools is required to understand these linkages and how they may change in the future as a function of climate change and population growth. In addition, the region is geopolitically complex as the former Soviet basin states develop management strategies to sustainably manage shared resources. This complexity increases the importance of relying upon publically available information sources and tools. Preliminary work has shown potential for the Variable Infiltration Capacity (VIC) model to recreate the natural water balance in the Amu Darya and Syr Darya basins by comparing results to total terrestrial water storage changes observed from NASA's Gravity Recovery and Climate Experiment (GRACE) satellite mission. Modeled streamflow is well correlated to observed streamflow at upstream gauges prior to the large-scale expansion of irrigation and hydropower. However, current modeled results are unable to capture the human influence of water use on downstream flow. This study examines the utility of a crop simulation model, CropSyst, to represent irrigation demand and GRACE to improve modeled streamflow estimates in the Amu Darya and Syr Darya basins. Specifically we determine crop water demand with CropSyst utilizing available data on irrigation schemes and cropping patterns. We determine how this demand can be met either by surface water, modeled by VIC with a reservoir operation scheme, and/or by groundwater derived from GRACE. Finally, we assess how the

Derivative chameleons

International Nuclear Information System (INIS)

Noller, Johannes

2012-01-01

We consider generalized chameleon models where the conformal coupling between matter and gravitational geometries is not only a function of the chameleon field φ, but also of its derivatives via higher order co-ordinate invariants (such as ∂ μ φ∂ μ φ,□φ,...). Specifically we consider the first such non-trivial conformal factor A(φ,∂ μ φ∂ μ φ). The associated phenomenology is investigated and we show that such theories have a new generic mass-altering mechanism, potentially assisting the generation of a sufficiently large chameleon mass in dense environments. The most general effective potential is derived for such derivative chameleon setups and explicit examples are given. Interestingly this points us to the existence of a purely derivative chameleon protected by a shift symmetry for φ → φ+c. We also discuss potential ghost-like instabilities associated with mass-lifting mechanisms and find another, mass-lowering and instability-free, branch of solutions. This suggests that, barring fine-tuning, stable derivative models are in fact typically anti-chameleons that suppress the field's mass in dense environments. Furthermore we investigate modifications to the thin-shell regime and prove a no-go theorem for chameleon effects in non-conformal geometries of the disformal type

Derivative chameleons

Energy Technology Data Exchange (ETDEWEB)

Noller, Johannes, E-mail: johannes.noller08@imperial.ac.uk [Theoretical Physics, Blackett Laboratory, Imperial College London, Prince Consort Road, London, SW7 2BZ (United Kingdom)

2012-07-01

We consider generalized chameleon models where the conformal coupling between matter and gravitational geometries is not only a function of the chameleon field φ, but also of its derivatives via higher order co-ordinate invariants (such as ∂{sub μ}φ∂{sup μ}φ,□φ,...). Specifically we consider the first such non-trivial conformal factor A(φ,∂{sub μ}φ∂{sup μ}φ). The associated phenomenology is investigated and we show that such theories have a new generic mass-altering mechanism, potentially assisting the generation of a sufficiently large chameleon mass in dense environments. The most general effective potential is derived for such derivative chameleon setups and explicit examples are given. Interestingly this points us to the existence of a purely derivative chameleon protected by a shift symmetry for φ → φ+c. We also discuss potential ghost-like instabilities associated with mass-lifting mechanisms and find another, mass-lowering and instability-free, branch of solutions. This suggests that, barring fine-tuning, stable derivative models are in fact typically anti-chameleons that suppress the field's mass in dense environments. Furthermore we investigate modifications to the thin-shell regime and prove a no-go theorem for chameleon effects in non-conformal geometries of the disformal type.

Improved ionic model of liquid uranium dioxide

NARCIS (Netherlands)

Gryaznov, [No Value; Iosilevski, [No Value; Yakub, E; Fortov, [No Value; Hyland, GJ; Ronchi, C

The paper presents a model for liquid uranium dioxide, obtained by improving a simplified ionic model, previously adopted to describe the equation of state of this substance [1]. A "chemical picture" is used for liquid UO2 of stoichiometric and non-stoichiometric composition. Several ionic species

Human embryonic stem cell-derived pancreatic endoderm alleviates diabetic pathology and improves reproductive outcome in C57BL/KsJ-Lep(db/+) gestational diabetes mellitus mice.

Science.gov (United States)

Xing, Baoheng; Wang, Lili; Li, Qin; Cao, Yalei; Dong, Xiujuan; Liang, Jun; Wu, Xiaohua

2015-07-01

Gestational diabetes mellitus is a condition commonly encountered during mid to late pregnancy with pathologic manifestations including hyperglycemia, hyperinsulinemia, insulin resistance, and fetal maldevelopment. The cause of gestational diabetes mellitus can be attributed to both genetic and environmental factors, hence complicating its diagnosis and treatment. Pancreatic progenitors derived from human embryonic stem cells were shown to be able to effectively treat diabetes in mice. In this study, we have developed a system of treating diabetes using human embryonic stem cell-derived pancreatic endoderm in a mouse model of gestational diabetes mellitus. Human embryonic stem cells were differentiated in vitro into pancreatic endoderm, which were then transplanted into db/+ mice suffering from gestational diabetes mellitus. The transplant greatly improved glucose metabolism and reproductive outcome of the females compared with the control groups. Our findings support the feasibility of using differentiated human embryonic stem cells for treating gestational diabetes mellitus patients. Copyright © 2015 Elsevier Inc. All rights reserved.

Modeling Major Adverse Outcomes of Pediatric and Adult Patients With Congenital Heart Disease Undergoing Cardiac Catheterization: Observations From the NCDR IMPACT Registry (National Cardiovascular Data Registry Improving Pediatric and Adult Congenital Treatment).

Science.gov (United States)

Jayaram, Natalie; Spertus, John A; Kennedy, Kevin F; Vincent, Robert; Martin, Gerard R; Curtis, Jeptha P; Nykanen, David; Moore, Phillip M; Bergersen, Lisa

2017-11-21

Risk standardization for adverse events after congenital cardiac catheterization is needed to equitably compare patient outcomes among different hospitals as a foundation for quality improvement. The goal of this project was to develop a risk-standardization methodology to adjust for patient characteristics when comparing major adverse outcomes in the NCDR's (National Cardiovascular Data Registry) IMPACT Registry (Improving Pediatric and Adult Congenital Treatment). Between January 2011 and March 2014, 39 725 consecutive patients within IMPACT undergoing cardiac catheterization were identified. Given the heterogeneity of interventional procedures for congenital heart disease, new procedure-type risk categories were derived with empirical data and expert opinion, as were markers of hemodynamic vulnerability. A multivariable hierarchical logistic regression model to identify patient and procedural characteristics predictive of a major adverse event or death after cardiac catheterization was derived in 70% of the cohort and validated in the remaining 30%. The rate of major adverse event or death was 7.1% and 7.2% in the derivation and validation cohorts, respectively. Six procedure-type risk categories and 6 independent indicators of hemodynamic vulnerability were identified. The final risk adjustment model included procedure-type risk category, number of hemodynamic vulnerability indicators, renal insufficiency, single-ventricle physiology, and coagulation disorder. The model had good discrimination, with a C-statistic of 0.76 and 0.75 in the derivation and validation cohorts, respectively. Model calibration in the validation cohort was excellent, with a slope of 0.97 (standard error, 0.04; P value [for difference from 1] =0.53) and an intercept of 0.007 (standard error, 0.12; P value [for difference from 0] =0.95). The creation of a validated risk-standardization model for adverse outcomes after congenital cardiac catheterization can support reporting of risk

Improved gap conductance model for the TRAC code

International Nuclear Information System (INIS)

Hatch, S.W.; Mandell, D.A.

1980-01-01

The purpose of the present work, as indicated earlier, is to improve the present constant fuel clad spacing in TRAC-P1A without significantly increasing the computer costs. It is realized that the simple model proposed may not be accurate enough for some cases, but for the initial calculations made the DELTAR model improves the predictions over the constant Δr results of TRAC-P1A and the additional computing costs are negligible

Modeling of the influence of transparency of the derivatives market on financial depth

Directory of Open Access Journals (Sweden)

Irina Burdenko

2016-07-01

Full Text Available The market of derivative tools becomes an integral part of the financial market, the functions which are carrying out in it peculiar only to it: hedging, distribution of risks, ensuring liquidity of basic assets, information support of future movement of the prices, decrease in asymmetry of information in the financial markets. However, the insufficiency or lack of transparent information can lead to emergence of the crisis phenomena, shocks in the financial market and growth of system risk. Emergence of need for strengthening of information function of the market of derivatives changes of requirements to transparency of information had been caused by financial crisis of 2008-2009. In this article the attempt of an assessment of influence was made by means of autoregressive models the change of requirements to standard transparency, such as qualitative characteristic of the derivatives market, on quantitative indices of the financial market, in particular financial depth. The results of research demonstrate that reforming of the legislation concerning strengthening of transparency in the derivatives market positively influences the growth of financial depth. The research of this question will promote the best understanding of importance of reforming of regulation of the derivatives market, in particular strengthening of requirements to transparency. Recommendations of the further researches concern the needs of input of reforms of financial regulation in the derivatives market in Ukraine, and, thus, to provide the corresponding conditions for his development

Relevance of near-Earth magnetic field modeling in deriving SEP properties using ground-based data

Science.gov (United States)

Kanellakopoulos, Anastasios; Plainaki, Christina; Mavromichalaki, Helen; Laurenza, Monica; Gerontidou, Maria; Storini, Marisa; Andriopoulou, Maria

2014-05-01

Ground Level Enhancements (GLEs) are short-term increases observed in cosmic ray intensity records of ground-based particle detectors such as neutron monitors (NMs) or muon detectors; they are related to the arrival of solar relativistic particles in the terrestrial environment. Hence, GLE events are related to the most energetic class of solar energetic particle (SEP) events. In this work we investigate how the use of different magnetospheric field models can influence the derivation of the relativistic SEP properties when modeling GLE events. As a case study, we examine the event of 2012 May 17 (also known as GLE71), registered by ground-based NMs. We apply the Tsyganenko 89 and the Tsyganenko 96 models in order to calculate the trajectories of the arriving SEPs in the near-Earth environment. We show that the intersection of the SEP trajectories with the atmospheric layer at ~20 km from the Earth's surface (i.e., where the flux of the generated secondary particles is maximum), forms for each ground-based neutron monitor a specified viewing region that is dependent on the magnetospheric field configuration. Then, we apply the Neutron Monitor Based Anisotropic GLE Pure Power Law (NMBANGLE PPOLA) model (Plainaki et al. 2010, Solar Phys, 264, 239), in order to derive the spectral properties of the related SEP event and the spatial distributions of the SEP fluxes impacting the Earth's atmosphere. We examine the dependence of the results on the used magnetic field models and evaluate their range of validity. Finally we discuss information derived by modeling the SEP spectrum in the frame of particle acceleration scenarios.

A model for ageing-home-care service process improvement

OpenAIRE

Yu, Shu-Yan; Shie, An-Jin

2017-01-01

The purpose of this study was to develop an integrated model to improve service processes in ageing-home-care. According to the literature, existing service processes have potential service failures that affect service quality and efficacy. However, most previous studies have only focused on conceptual model development using New Service Development (NSD) and fail to provide a systematic model to analyse potential service failures and facilitate managers developing solutions to improve the se...

Improving Frozen Precipitation Density Estimation in Land Surface Modeling

Science.gov (United States)

Sparrow, K.; Fall, G. M.

2017-12-01

The Office of Water Prediction (OWP) produces high-value water supply and flood risk planning information through the use of operational land surface modeling. Improvements in diagnosing frozen precipitation density will benefit the NWS's meteorological and hydrological services by refining estimates of a significant and vital input into land surface models. A current common practice for handling the density of snow accumulation in a land surface model is to use a standard 10:1 snow-to-liquid-equivalent ratio (SLR). Our research findings suggest the possibility of a more skillful approach for assessing the spatial variability of precipitation density. We developed a 30-year SLR climatology for the coterminous US from version 3.22 of the Daily Global Historical Climatology Network - Daily (GHCN-D) dataset. Our methods followed the approach described by Baxter (2005) to estimate mean climatological SLR values at GHCN-D sites in the US, Canada, and Mexico for the years 1986-2015. In addition to the Baxter criteria, the following refinements were made: tests were performed to eliminate SLR outliers and frequent reports of SLR = 10, a linear SLR vs. elevation trend was fitted to station SLR mean values to remove the elevation trend from the data, and detrended SLR residuals were interpolated using ordinary kriging with a spherical semivariogram model. The elevation values of each station were based on the GMTED 2010 digital elevation model and the elevation trend in the data was established via linear least squares approximation. The ordinary kriging procedure was used to interpolate the data into gridded climatological SLR estimates for each calendar month at a 0.125 degree resolution. To assess the skill of this climatology, we compared estimates from our SLR climatology with observations from the GHCN-D dataset to consider the potential use of this climatology as a first guess of frozen precipitation density in an operational land surface model. The difference in

Relating derived relations as a model of analogical reasoning: reaction times and event-related potentials.

Science.gov (United States)

Barnes-Holmes, Dermot; Regan, Donal; Barnes-Holmes, Yvonne; Commins, Sean; Walsh, Derek; Stewart, Ian; Smeets, Paul M; Whelan, Robert; Dymond, Simon

2005-11-01

The current study aimed to test a Relational Frame Theory (RFT) model of analogical reasoning based on the relating of derived same and derived difference relations. Experiment 1 recorded reaction time measures of similar-similar (e.g., "apple is to orange as dog is to cat") versus different-different (e.g., "he is to his brother as chalk is to cheese") derived relational responding, in both speed-contingent and speed-noncontingent conditions. Experiment 2 examined the event-related potentials (ERPs) associated with these two response patterns. Both experiments showed similar-similar responding to be significantly faster than different-different responding. Experiment 2 revealed significant differences between the waveforms of the two response patterns in the left-hemispheric prefrontal regions; different-different waveforms were significantly more negative than similar-similar waveforms. The behavioral and neurophysiological data support the RFT prediction that, all things being equal, similar-similar responding is relationally "simpler" than, and functionally distinct from, different-different analogical responding. The ERP data were fully consistent with findings in the neurocognitive literature on analogy. These findings strengthen the validity of the RFT model of analogical reasoning and supplement the behavior-analytic approach to analogy based on the relating of derived relations.

HABSEED: a Simple Spatially Explicit Meta-Populations Model Using Remote Sensing Derived Habitat Quality Data

Science.gov (United States)

Heumann, B. W.; Guichard, F.; Seaquist, J. W.

2005-05-01

The HABSEED model uses remote sensing derived NPP as a surrogate for habitat quality as the driving mechanism for population growth and local seed dispersal. The model has been applied to the Sahel region of Africa. Results show that the functional response of plants to habitat quality alters population distribution. Plants more tolerant of medium quality habitat have greater distributions to the North while plants requiring only the best habitat are limited to the South. For all functional response types, increased seed production results in diminishing returns. Functional response types have been related to life history tradeoffs and r-K strategies based on the results. Results are compared to remote sensing derived vegetation land cover.

Disease Modeling Using 3D Organoids Derived from Human Induced Pluripotent Stem Cells.

Science.gov (United States)

Ho, Beatrice Xuan; Pek, Nicole Min Qian; Soh, Boon-Seng

2018-03-21

The rising interest in human induced pluripotent stem cell (hiPSC)-derived organoid culture has stemmed from the manipulation of various combinations of directed multi-lineage differentiation and morphogenetic processes that mimic organogenesis. Organoids are three-dimensional (3D) structures that are comprised of multiple cell types, self-organized to recapitulate embryonic and tissue development in vitro. This model has been shown to be superior to conventional two-dimensional (2D) cell culture methods in mirroring functionality, architecture, and geometric features of tissues seen in vivo. This review serves to highlight recent advances in the 3D organoid technology for use in modeling complex hereditary diseases, cancer, host-microbe interactions, and possible use in translational and personalized medicine where organoid cultures were used to uncover diagnostic biomarkers for early disease detection via high throughput pharmaceutical screening. In addition, this review also aims to discuss the advantages and shortcomings of utilizing organoids in disease modeling. In summary, studying human diseases using hiPSC-derived organoids may better illustrate the processes involved due to similarities in the architecture and microenvironment present in an organoid, which also allows drug responses to be properly recapitulated in vitro.

Chance-constrained overland flow modeling for improving conceptual distributed hydrologic simulations based on scaling representation of sub-daily rainfall variability

International Nuclear Information System (INIS)

Han, Jing-Cheng; Huang, Guohe; Huang, Yuefei; Zhang, Hua; Li, Zhong; Chen, Qiuwen

2015-01-01

Lack of hydrologic process representation at the short time-scale would lead to inadequate simulations in distributed hydrological modeling. Especially for complex mountainous watersheds, surface runoff simulations are significantly affected by the overland flow generation, which is closely related to the rainfall characteristics at a sub-time step. In this paper, the sub-daily variability of rainfall intensity was considered using a probability distribution, and a chance-constrained overland flow modeling approach was proposed to capture the generation of overland flow within conceptual distributed hydrologic simulations. The integrated modeling procedures were further demonstrated through a watershed of China Three Gorges Reservoir area, leading to an improved SLURP-TGR hydrologic model based on SLURP. Combined with rainfall thresholds determined to distinguish various magnitudes of daily rainfall totals, three levels of significance were simultaneously employed to examine the hydrologic-response simulation. Results showed that SLURP-TGR could enhance the model performance, and the deviation of runoff simulations was effectively controlled. However, rainfall thresholds were so crucial for reflecting the scaling effect of rainfall intensity that optimal levels of significance and rainfall threshold were 0.05 and 10 mm, respectively. As for the Xiangxi River watershed, the main runoff contribution came from interflow of the fast store. Although slight differences of overland flow simulations between SLURP and SLURP-TGR were derived, SLURP-TGR was found to help improve the simulation of peak flows, and would improve the overall modeling efficiency through adjusting runoff component simulations. Consequently, the developed modeling approach favors efficient representation of hydrological processes and would be expected to have a potential for wide applications. - Highlights: • We develop an improved hydrologic model considering the scaling effect of rainfall. • A

Chance-constrained overland flow modeling for improving conceptual distributed hydrologic simulations based on scaling representation of sub-daily rainfall variability

Energy Technology Data Exchange (ETDEWEB)

Han, Jing-Cheng [State Key Laboratory of Hydroscience & Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084 (China); Huang, Guohe, E-mail: huang@iseis.org [Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada); Huang, Yuefei [State Key Laboratory of Hydroscience & Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084 (China); Zhang, Hua [College of Science and Engineering, Texas A& M University — Corpus Christi, Corpus Christi, TX 78412-5797 (United States); Li, Zhong [Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada); Chen, Qiuwen [Center for Eco-Environmental Research, Nanjing Hydraulics Research Institute, Nanjing 210029 (China)

2015-08-15

Lack of hydrologic process representation at the short time-scale would lead to inadequate simulations in distributed hydrological modeling. Especially for complex mountainous watersheds, surface runoff simulations are significantly affected by the overland flow generation, which is closely related to the rainfall characteristics at a sub-time step. In this paper, the sub-daily variability of rainfall intensity was considered using a probability distribution, and a chance-constrained overland flow modeling approach was proposed to capture the generation of overland flow within conceptual distributed hydrologic simulations. The integrated modeling procedures were further demonstrated through a watershed of China Three Gorges Reservoir area, leading to an improved SLURP-TGR hydrologic model based on SLURP. Combined with rainfall thresholds determined to distinguish various magnitudes of daily rainfall totals, three levels of significance were simultaneously employed to examine the hydrologic-response simulation. Results showed that SLURP-TGR could enhance the model performance, and the deviation of runoff simulations was effectively controlled. However, rainfall thresholds were so crucial for reflecting the scaling effect of rainfall intensity that optimal levels of significance and rainfall threshold were 0.05 and 10 mm, respectively. As for the Xiangxi River watershed, the main runoff contribution came from interflow of the fast store. Although slight differences of overland flow simulations between SLURP and SLURP-TGR were derived, SLURP-TGR was found to help improve the simulation of peak flows, and would improve the overall modeling efficiency through adjusting runoff component simulations. Consequently, the developed modeling approach favors efficient representation of hydrological processes and would be expected to have a potential for wide applications. - Highlights: • We develop an improved hydrologic model considering the scaling effect of rainfall. • A

Improved Modeling and Prediction of Surface Wave Amplitudes

Science.gov (United States)

2017-05-31

AFRL-RV-PS- AFRL-RV-PS- TR-2017-0162 TR-2017-0162 IMPROVED MODELING AND PREDICTION OF SURFACE WAVE AMPLITUDES Jeffry L. Stevens, et al. Leidos...data does not license the holder or any other person or corporation; or convey any rights or permission to manufacture, use, or sell any patented...SUBTITLE Improved Modeling and Prediction of Surface Wave Amplitudes 5a. CONTRACT NUMBER FA9453-14-C-0225 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER

Integrating Global Satellite-Derived Data Products as a Pre-Analysis for Hydrological Modelling Studies: A Case Study for the Red River Basin

Directory of Open Access Journals (Sweden)

Gijs Simons

2016-03-01

Full Text Available With changes in weather patterns and intensifying anthropogenic water use, there is an increasing need for spatio-temporal information on water fluxes and stocks in river basins. The assortment of satellite-derived open-access information sources on rainfall (P and land use/land cover (LULC is currently being expanded with the application of actual evapotranspiration (ETact algorithms on the global scale. We demonstrate how global remotely sensed P and ETact datasets can be merged to examine hydrological processes such as storage changes and streamflow prior to applying a numerical simulation model. The study area is the Red River Basin in China in Vietnam, a generally challenging basin for remotely sensed information due to frequent cloud cover. Over this region, several satellite-based P and ETact products are compared, and performance is evaluated using rain gauge records and longer-term averaged streamflow. A method is presented for fusing multiple satellite-derived ETact estimates to generate an ensemble product that may be less susceptible, on a global basis, to errors in individual modeling approaches. Subsequently, monthly satellite-derived rainfall and ETact are combined to assess the water balance for individual subcatchments and types of land use, defined using a global land use classification improved based on auxiliary satellite data. It was found that a combination of TRMM rainfall and the ensemble ETact product is consistent with streamflow records in both space and time. It is concluded that monthly storage changes, multi-annual streamflow and water yield per LULC type in the Red River Basin can be successfully assessed based on currently available global satellite-derived products.

A Model Predictive Control Approach for Fuel Economy Improvement of a Series Hydraulic Hybrid Vehicle

Directory of Open Access Journals (Sweden)

Tri-Vien Vu

2014-10-01

Full Text Available This study applied a model predictive control (MPC framework to solve the cruising control problem of a series hydraulic hybrid vehicle (SHHV. The controller not only regulates vehicle velocity, but also engine torque, engine speed, and accumulator pressure to their corresponding reference values. At each time step, a quadratic programming problem is solved within a predictive horizon to obtain the optimal control inputs. The objective is to minimize the output error. This approach ensures that the components operate at high efficiency thereby improving the total efficiency of the system. The proposed SHHV control system was evaluated under urban and highway driving conditions. By handling constraints and input-output interactions, the MPC-based control system ensures that the system operates safely and efficiently. The fuel economy of the proposed control scheme shows a noticeable improvement in comparison with the PID-based system, in which three Proportional-Integral-Derivative (PID controllers are used for cruising control.

Combretastatin A-4 based thiophene derivatives as antitumor agent: Development of structure activity correlation model using 3D-QSAR, pharmacophore and docking studies

Directory of Open Access Journals (Sweden)

Vijay K. Patel

2017-12-01

Full Text Available The structure and ligand based synergistic approach is being applied to design ligands more correctly. The present report discloses the combination of structure and ligand based tactics i.e., molecular docking, energetic based pharmacophore, pharmacophore and atom based 3D-QSAR modeling for the analysis of thiophene derivatives as anticancer agent. The main purpose of using structure and ligand based synergistic approach is to ascertain a correlation between structure and its biological activity. Thiophene derivatives have been found to possess cytotoxic activity in several cancer cell lines and its mechanism of action basically involves the binding to the colchicine site on β-tubulin. The structure based approach (molecular docking was performed on a series of thiophene derivatives. All the structures were docked to colchicine binding site of β tubulin for examining the binding affinity of compounds for antitumor activity. The pharmacophore and atom based 3D-QSAR modeling was accomplished on a series of thiophene (32 compounds analogues. Five-point common pharmacophore hypotheses (AAAAR.38 were selected for alignment of all compounds. The atom based 3D-QSAR models were developed by selection of 23 compounds as training set and 9 compounds as test set, demonstrated good partial least squares statistical results. The generated common pharmacophore hypothesis and 3D-QSAR models were validated further externally by measuring the activity of database compounds and assessing it with actual activity. The common pharmacophore hypothesis AAAAR.38 resulted in a 3D-QSAR model with excellent PLSs data for factor two characterized by the best predication coefficient Q2 (cross validated r2 (0.7213, regression R2 (0.8311, SD (0.3672, F (49.2, P (1.89E-08, RMSE (0.3864, Stability (0.8702, Pearson-r (0.8722. The results of these molecular modeling studies i.e., molecular docking, energetic based pharmacophore, pharmacophore and atom based 3D-QSAR modeling

A Unified Framework for Systematic Model Improvement

DEFF Research Database (Denmark)

Kristensen, Niels Rode; Madsen, Henrik; Jørgensen, Sten Bay

2003-01-01

A unified framework for improving the quality of continuous time models of dynamic systems based on experimental data is presented. The framework is based on an interplay between stochastic differential equation (SDE) modelling, statistical tests and multivariate nonparametric regression. This co......-batch bioreactor, where it is illustrated how an incorrectly modelled biomass growth rate can be pinpointed and an estimate provided of the functional relation needed to properly describe it....