Sample records for models combining local
-
A NEW COMBINED LOCAL AND NON-LOCAL PBL MODEL FOR METEOROLOGY AND AIR QUALITY MODELING
A new version of the Asymmetric Convective Model (ACM) has been developed to describe sub-grid vertical turbulent transport in both meteorology models and air quality models. The new version (ACM2) combines the non-local convective mixing of the original ACM with local eddy diff...
-
Estimation and prediction under local volatility jump-diffusion model
NASA Astrophysics Data System (ADS)
Kim, Namhyoung; Lee, Younhee
2018-02-01
Volatility is an important factor in operating a company and managing risk. In the portfolio optimization and risk hedging using the option, the value of the option is evaluated using the volatility model. Various attempts have been made to predict option value. Recent studies have shown that stochastic volatility models and jump-diffusion models reflect stock price movements accurately. However, these models have practical limitations. Combining them with the local volatility model, which is widely used among practitioners, may lead to better performance. In this study, we propose a more effective and efficient method of estimating option prices by combining the local volatility model with the jump-diffusion model and apply it using both artificial and actual market data to evaluate its performance. The calibration process for estimating the jump parameters and local volatility surfaces is divided into three stages. We apply the local volatility model, stochastic volatility model, and local volatility jump-diffusion model estimated by the proposed method to KOSPI 200 index option pricing. The proposed method displays good estimation and prediction performance.
-
NASA Astrophysics Data System (ADS)
Skowronek, Sandra; Van De Kerchove, Ruben; Rombouts, Bjorn; Aerts, Raf; Ewald, Michael; Warrie, Jens; Schiefer, Felix; Garzon-Lopez, Carol; Hattab, Tarek; Honnay, Olivier; Lenoir, Jonathan; Rocchini, Duccio; Schmidtlein, Sebastian; Somers, Ben; Feilhauer, Hannes
2018-06-01
Remote sensing is a promising tool for detecting invasive alien plant species. Mapping and monitoring those species requires accurate detection. So far, most studies relied on models that are locally calibrated and validated against available field data. Consequently, detecting invasive alien species at new study areas requires the acquisition of additional field data which can be expensive and time-consuming. Model transfer might thus provide a viable alternative. Here, we mapped the distribution of the invasive alien bryophyte Campylopus introflexus to i) assess the feasibility of spatially transferring locally calibrated models for species detection between four different heathland areas in Germany and Belgium and ii) test the potential of combining calibration data from different sites in one species distribution model (SDM). In a first step, four different SDMs were locally calibrated and validated by combining field data and airborne imaging spectroscopy data with a spatial resolution ranging from 1.8 m to 4 m and a spectral resolution of about 10 nm (244 bands). A one-class classifier, Maxent, which is based on the comparison of probability densities, was used to generate all SDMs. In a second step, each model was transferred to the three other study areas and the performance of the models for predicting C. introflexus occurrences was assessed. Finally, models combining calibration data from three study areas were built and tested on the remaining fourth site. In this step, different combinations of Maxent modelling parameters were tested. For the local models, the area under the curve for a test dataset (test AUC) was between 0.57-0.78, while the test AUC for the single transfer models ranged between 0.45-0.89. For the combined models the test AUC was between 0.54-0.9. The success of transferring models calibrated in one site to another site highly depended on the respective study site; the combined models provided higher test AUC values than the locally calibrated models for three out of four study sites. Furthermore, we also demonstrated the importance of optimizing the Maxent modelling parameters. Overall, our results indicate the potential of a combined model to map C. introflexus without the need for new calibration data.
-
Hao, Yong; Sun, Xu-Dong; Yang, Qiang
2012-12-01
Variables selection strategy combined with local linear embedding (LLE) was introduced for the analysis of complex samples by using near infrared spectroscopy (NIRS). Three methods include Monte Carlo uninformation variable elimination (MCUVE), successive projections algorithm (SPA) and MCUVE connected with SPA were used for eliminating redundancy spectral variables. Partial least squares regression (PLSR) and LLE-PLSR were used for modeling complex samples. The results shown that MCUVE can both extract effective informative variables and improve the precision of models. Compared with PLSR models, LLE-PLSR models can achieve more accurate analysis results. MCUVE combined with LLE-PLSR is an effective modeling method for NIRS quantitative analysis.
-
Local Inflammation in Fracture Hematoma: Results from a Combined Trauma Model in Pigs
Horst, K.; Eschbach, D.; Pfeifer, R.; Hübenthal, S.; Sassen, M.; Steinfeldt, T.; Wulf, H.; Ruchholtz, S.; Pape, H. C.; Hildebrand, F.
2015-01-01
Background. Previous studies showed significant interaction between the local and systemic inflammatory response after severe trauma in small animal models. The purpose of this study was to establish a new combined trauma model in pigs to investigate fracture-associated local inflammation and gain information about the early inflammatory stages after polytrauma. Material and Methods. Combined trauma consisted of tibial fracture, lung contusion, liver laceration, and controlled hemorrhage. Animals were mechanically ventilated and under ICU-monitoring for 48 h. Blood and fracture hematoma samples were collected during the time course of the study. Local and systemic levels of serum cytokines and diverse alarmins were measured by ELISA kit. Results. A statistical significant difference in the systemic serum values of IL-6 and HMGB1 was observed when compared to the sham. Moreover, there was a statistical significant difference in the serum values of the fracture hematoma of IL-6, IL-8, IL-10, and HMGB1 when compared to the systemic inflammatory response. However a decrease of local proinflammatory concentrations was observed while anti-inflammatory mediators increased. Conclusion. Our data showed a time-dependent activation of the local and systemic inflammatory response. Indeed it is the first study focusing on the local and systemic inflammatory response to multiple-trauma in a large animal model. PMID:25694748
-
Localized Principal Component Analysis based Curve Evolution: A Divide and Conquer Approach
Appia, Vikram; Ganapathy, Balaji; Yezzi, Anthony; Faber, Tracy
2014-01-01
We propose a novel localized principal component analysis (PCA) based curve evolution approach which evolves the segmenting curve semi-locally within various target regions (divisions) in an image and then combines these locally accurate segmentation curves to obtain a global segmentation. The training data for our approach consists of training shapes and associated auxiliary (target) masks. The masks indicate the various regions of the shape exhibiting highly correlated variations locally which may be rather independent of the variations in the distant parts of the global shape. Thus, in a sense, we are clustering the variations exhibited in the training data set. We then use a parametric model to implicitly represent each localized segmentation curve as a combination of the local shape priors obtained by representing the training shapes and the masks as a collection of signed distance functions. We also propose a parametric model to combine the locally evolved segmentation curves into a single hybrid (global) segmentation. Finally, we combine the evolution of these semilocal and global parameters to minimize an objective energy function. The resulting algorithm thus provides a globally accurate solution, which retains the local variations in shape. We present some results to illustrate how our approach performs better than the traditional approach with fully global PCA. PMID:25520901
-
Yalcin, Semra; Leroux, Shawn James
2018-04-14
Land-cover and climate change are two main drivers of changes in species ranges. Yet, the majority of studies investigating the impacts of global change on biodiversity focus on one global change driver and usually use simulations to project biodiversity responses to future conditions. We conduct an empirical test of the relative and combined effects of land-cover and climate change on species occurrence changes. Specifically, we examine whether observed local colonization and extinctions of North American birds between 1981-1985 and 2001-2005 are correlated with land-cover and climate change and whether bird life history and ecological traits explain interspecific variation in observed occurrence changes. We fit logistic regression models to test the impact of physical land-cover change, changes in net primary productivity, winter precipitation, mean summer temperature, and mean winter temperature on the probability of Ontario breeding bird local colonization and extinction. Models with climate change, land-cover change, and the combination of these two drivers were the top ranked models of local colonization for 30%, 27%, and 29% of species, respectively. Conversely, models with climate change, land-cover change, and the combination of these two drivers were the top ranked models of local extinction for 61%, 7%, and 9% of species, respectively. The quantitative impacts of land-cover and climate change variables also vary among bird species. We then fit linear regression models to test whether the variation in regional colonization and extinction rate could be explained by mean body mass, migratory strategy, and habitat preference of birds. Overall, species traits were weakly correlated with heterogeneity in species occurrence changes. We provide empirical evidence showing that land-cover change, climate change, and the combination of multiple global change drivers can differentially explain observed species local colonization and extinction. © 2018 John Wiley & Sons Ltd.
-
Modelling machine ensembles with discrete event dynamical system theory
NASA Technical Reports Server (NTRS)
Hunter, Dan
1990-01-01
Discrete Event Dynamical System (DEDS) theory can be utilized as a control strategy for future complex machine ensembles that will be required for in-space construction. The control strategy involves orchestrating a set of interactive submachines to perform a set of tasks for a given set of constraints such as minimum time, minimum energy, or maximum machine utilization. Machine ensembles can be hierarchically modeled as a global model that combines the operations of the individual submachines. These submachines are represented in the global model as local models. Local models, from the perspective of DEDS theory , are described by the following: a set of system and transition states, an event alphabet that portrays actions that takes a submachine from one state to another, an initial system state, a partial function that maps the current state and event alphabet to the next state, and the time required for the event to occur. Each submachine in the machine ensemble is presented by a unique local model. The global model combines the local models such that the local models can operate in parallel under the additional logistic and physical constraints due to submachine interactions. The global model is constructed from the states, events, event functions, and timing requirements of the local models. Supervisory control can be implemented in the global model by various methods such as task scheduling (open-loop control) or implementing a feedback DEDS controller (closed-loop control).
-
Streamflow Prediction based on Chaos Theory
NASA Astrophysics Data System (ADS)
Li, X.; Wang, X.; Babovic, V. M.
2015-12-01
Chaos theory is a popular method in hydrologic time series prediction. Local model (LM) based on this theory utilizes time-delay embedding to reconstruct the phase-space diagram. For this method, its efficacy is dependent on the embedding parameters, i.e. embedding dimension, time lag, and nearest neighbor number. The optimal estimation of these parameters is thus critical to the application of Local model. However, these embedding parameters are conventionally estimated using Average Mutual Information (AMI) and False Nearest Neighbors (FNN) separately. This may leads to local optimization and thus has limitation to its prediction accuracy. Considering about these limitation, this paper applies a local model combined with simulated annealing (SA) to find the global optimization of embedding parameters. It is also compared with another global optimization approach of Genetic Algorithm (GA). These proposed hybrid methods are applied in daily and monthly streamflow time series for examination. The results show that global optimization can contribute to the local model to provide more accurate prediction results compared with local optimization. The LM combined with SA shows more advantages in terms of its computational efficiency. The proposed scheme here can also be applied to other fields such as prediction of hydro-climatic time series, error correction, etc.
-
NASA Astrophysics Data System (ADS)
Wziontek, Hartmut; Wilmes, Herbert; Güntner, Andreas; Creutzfeldt, Benjamin
2010-05-01
Water mass changes are a major source of variations in residual gravimetric time series obtained from the combination of observations with superconducting and absolute gravimeters. Changes in the local water storage are the main influence, but global variations contribute to the signal significantly. For three European gravity stations, Bad Homburg, Wettzell and Medicina, different global hydrology models are compared. The influence of topographic effects is discussed and due to the long-term stability of the combined gravity time series, inter-annual signals in model data and gravimetric observations are compared. Two sources of influence are discriminated, i.e., the effect of a local zone with an extent of a few kilometers around the gravimetric station and the global contribution beyond 50km. Considering their coarse resolution and uncertainties, local effects calculated from global hydrological models are compared with the in-situ gravity observations and, for the station Wettzell, with local hydrological monitoring data.
-
Huang, Yingxiang; Lee, Junghye; Wang, Shuang; Sun, Jimeng; Liu, Hongfang; Jiang, Xiaoqian
2018-05-16
Data sharing has been a big challenge in biomedical informatics because of privacy concerns. Contextual embedding models have demonstrated a very strong representative capability to describe medical concepts (and their context), and they have shown promise as an alternative way to support deep-learning applications without the need to disclose original data. However, contextual embedding models acquired from individual hospitals cannot be directly combined because their embedding spaces are different, and naive pooling renders combined embeddings useless. The aim of this study was to present a novel approach to address these issues and to promote sharing representation without sharing data. Without sacrificing privacy, we also aimed to build a global model from representations learned from local private data and synchronize information from multiple sources. We propose a methodology that harmonizes different local contextual embeddings into a global model. We used Word2Vec to generate contextual embeddings from each source and Procrustes to fuse different vector models into one common space by using a list of corresponding pairs as anchor points. We performed prediction analysis with harmonized embeddings. We used sequential medical events extracted from the Medical Information Mart for Intensive Care III database to evaluate the proposed methodology in predicting the next likely diagnosis of a new patient using either structured data or unstructured data. Under different experimental scenarios, we confirmed that the global model built from harmonized local models achieves a more accurate prediction than local models and global models built from naive pooling. Such aggregation of local models using our unique harmonization can serve as the proxy for a global model, combining information from a wide range of institutions and information sources. It allows information unique to a certain hospital to become available to other sites, increasing the fluidity of information flow in health care. ©Yingxiang Huang, Junghye Lee, Shuang Wang, Jimeng Sun, Hongfang Liu, Xiaoqian Jiang. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 16.05.2018.
-
Image segmentation using local shape and gray-level appearance models
NASA Astrophysics Data System (ADS)
Seghers, Dieter; Loeckx, Dirk; Maes, Frederik; Suetens, Paul
2006-03-01
A new generic model-based segmentation scheme is presented, which can be trained from examples akin to the Active Shape Model (ASM) approach in order to acquire knowledge about the shape to be segmented and about the gray-level appearance of the object in the image. Because in the ASM approach the intensity and shape models are typically applied alternately during optimizing as first an optimal target location is selected for each landmark separately based on local gray-level appearance information only to which the shape model is fitted subsequently, the ASM may be misled in case of wrongly selected landmark locations. Instead, the proposed approach optimizes for shape and intensity characteristics simultaneously. Local gray-level appearance information at the landmark points extracted from feature images is used to automatically detect a number of plausible candidate locations for each landmark. The shape information is described by multiple landmark-specific statistical models that capture local dependencies between adjacent landmarks on the shape. The shape and intensity models are combined in a single cost function that is optimized non-iteratively using dynamic programming which allows to find the optimal landmark positions using combined shape and intensity information, without the need for initialization.
-
NASA Astrophysics Data System (ADS)
di Stefano, Marco; Paulsen, Jonas; Lien, Tonje G.; Hovig, Eivind; Micheletti, Cristian
2016-10-01
Combining genome-wide structural models with phenomenological data is at the forefront of efforts to understand the organizational principles regulating the human genome. Here, we use chromosome-chromosome contact data as knowledge-based constraints for large-scale three-dimensional models of the human diploid genome. The resulting models remain minimally entangled and acquire several functional features that are observed in vivo and that were never used as input for the model. We find, for instance, that gene-rich, active regions are drawn towards the nuclear center, while gene poor and lamina associated domains are pushed to the periphery. These and other properties persist upon adding local contact constraints, suggesting their compatibility with non-local constraints for the genome organization. The results show that suitable combinations of data analysis and physical modelling can expose the unexpectedly rich functionally-related properties implicit in chromosome-chromosome contact data. Specific directions are suggested for further developments based on combining experimental data analysis and genomic structural modelling.
-
Di Stefano, Marco; Paulsen, Jonas; Lien, Tonje G; Hovig, Eivind; Micheletti, Cristian
2016-10-27
Combining genome-wide structural models with phenomenological data is at the forefront of efforts to understand the organizational principles regulating the human genome. Here, we use chromosome-chromosome contact data as knowledge-based constraints for large-scale three-dimensional models of the human diploid genome. The resulting models remain minimally entangled and acquire several functional features that are observed in vivo and that were never used as input for the model. We find, for instance, that gene-rich, active regions are drawn towards the nuclear center, while gene poor and lamina associated domains are pushed to the periphery. These and other properties persist upon adding local contact constraints, suggesting their compatibility with non-local constraints for the genome organization. The results show that suitable combinations of data analysis and physical modelling can expose the unexpectedly rich functionally-related properties implicit in chromosome-chromosome contact data. Specific directions are suggested for further developments based on combining experimental data analysis and genomic structural modelling.
-
Error assessment of local tie vectors in space geodesy
NASA Astrophysics Data System (ADS)
Falkenberg, Jana; Heinkelmann, Robert; Schuh, Harald
2014-05-01
For the computation of the ITRF, the data of the geometric space-geodetic techniques on co-location sites are combined. The combination increases the redundancy and offers the possibility to utilize the strengths of each technique while mitigating their weaknesses. To enable the combination of co-located techniques each technique needs to have a well-defined geometric reference point. The linking of the geometric reference points enables the combination of the technique-specific coordinate to a multi-technique site coordinate. The vectors between these reference points are called "local ties". The realization of local ties is usually reached by local surveys of the distances and or angles between the reference points. Identified temporal variations of the reference points are considered in the local tie determination only indirectly by assuming a mean position. Finally, the local ties measured in the local surveying network are to be transformed into the ITRF, the global geocentric equatorial coordinate system of the space-geodetic techniques. The current IERS procedure for the combination of the space-geodetic techniques includes the local tie vectors with an error floor of three millimeters plus a distance dependent component. This error floor, however, significantly underestimates the real accuracy of local tie determination. To fullfill the GGOS goals of 1 mm position and 0.1 mm/yr velocity accuracy, an accuracy of the local tie will be mandatory at the sub-mm level, which is currently not achievable. To assess the local tie effects on ITRF computations, investigations of the error sources will be done to realistically assess and consider them. Hence, a reasonable estimate of all the included errors of the various local ties is needed. An appropriate estimate could also improve the separation of local tie error and technique-specific error contributions to uncertainties and thus access the accuracy of space-geodetic techniques. Our investigations concern the simulation of the error contribution of each component of the local tie definition and determination. A closer look into the models of reference point definition, of accessibility, of measurement, and of transformation is necessary to properly model the error of the local tie. The effect of temporal variations on the local ties will be studied as well. The transformation of the local survey into the ITRF can be assumed to be the largest error contributor, in particular the orientation of the local surveying network to the ITRF.
-
Lowe, Michael R.; Sehlinger, Troy; Soniat, Thomas M.; LaPeyre, Megan K.
2017-01-01
Despite nearly a century of exploitation and scientific study, predicting growth and mortality rates of the eastern oyster (Crassostrea virginica) as a means to inform local harvest and management activities remains difficult. Ensuring that models reflect local population responses to varying salinity and temperature combinations requires locally appropriate models. Using long-term (1988 to 2015) monitoring data from Louisiana's public oyster reefs, we develop regionally specific models of temperature- and salinity-driven mortality (sack oysters only) and growth for spat (<25 mm), seed (25–75 mm), and sack (>75 mm) oyster size classes. The results demonstrate that the optimal combination of temperature and salinity where Louisiana oysters experience reduced mortality and fast growth rates is skewed toward lower salinities and higher water temperatures than previous models have suggested. Outside of that optimal range, oysters are commonly exposed to combinations of temperature and salinity that are correlated with high mortality and reduced growth. How these combinations affect growth, and to a lesser degree mortality, appears to be size class dependent. Given current climate predictions for the region and ongoing large-scale restoration activities in coastal Louisiana, the growth and mortality models are a critical step toward ensuring sustainable oyster reefs for long-term harvest and continued delivery of the ecological services in a changing environment.
-
ERIC Educational Resources Information Center
Cheriani, Cheriani; Mahmud, Alimuddin; Tahmir, Suradi; Manda, Darman; Dirawan, Gufran Darma
2015-01-01
This study aims to determine the differences in learning output by using Problem Based Model combines with the "Buginese" Local Cultural Knowledge (PBL-Culture). It is also explores the students activities in learning mathematics subject by using PBL-Culture Models. This research is using Mixed Methods approach that combined quantitative…
-
A Bayesian network approach for modeling local failure in lung cancer
NASA Astrophysics Data System (ADS)
Oh, Jung Hun; Craft, Jeffrey; Lozi, Rawan Al; Vaidya, Manushka; Meng, Yifan; Deasy, Joseph O.; Bradley, Jeffrey D.; El Naqa, Issam
2011-03-01
Locally advanced non-small cell lung cancer (NSCLC) patients suffer from a high local failure rate following radiotherapy. Despite many efforts to develop new dose-volume models for early detection of tumor local failure, there was no reported significant improvement in their application prospectively. Based on recent studies of biomarker proteins' role in hypoxia and inflammation in predicting tumor response to radiotherapy, we hypothesize that combining physical and biological factors with a suitable framework could improve the overall prediction. To test this hypothesis, we propose a graphical Bayesian network framework for predicting local failure in lung cancer. The proposed approach was tested using two different datasets of locally advanced NSCLC patients treated with radiotherapy. The first dataset was collected retrospectively, which comprises clinical and dosimetric variables only. The second dataset was collected prospectively in which in addition to clinical and dosimetric information, blood was drawn from the patients at various time points to extract candidate biomarkers as well. Our preliminary results show that the proposed method can be used as an efficient method to develop predictive models of local failure in these patients and to interpret relationships among the different variables in the models. We also demonstrate the potential use of heterogeneous physical and biological variables to improve the model prediction. With the first dataset, we achieved better performance compared with competing Bayesian-based classifiers. With the second dataset, the combined model had a slightly higher performance compared to individual physical and biological models, with the biological variables making the largest contribution. Our preliminary results highlight the potential of the proposed integrated approach for predicting post-radiotherapy local failure in NSCLC patients.
-
Yang, Fan; Xu, Ying-Ying; Shen, Hong-Bin
2014-01-01
Human protein subcellular location prediction can provide critical knowledge for understanding a protein's function. Since significant progress has been made on digital microscopy, automated image-based protein subcellular location classification is urgently needed. In this paper, we aim to investigate more representative image features that can be effectively used for dealing with the multilabel subcellular image samples. We prepared a large multilabel immunohistochemistry (IHC) image benchmark from the Human Protein Atlas database and tested the performance of different local texture features, including completed local binary pattern, local tetra pattern, and the standard local binary pattern feature. According to our experimental results from binary relevance multilabel machine learning models, the completed local binary pattern, and local tetra pattern are more discriminative for describing IHC images when compared to the traditional local binary pattern descriptor. The combination of these two novel local pattern features and the conventional global texture features is also studied. The enhanced performance of final binary relevance classification model trained on the combined feature space demonstrates that different features are complementary to each other and thus capable of improving the accuracy of classification.
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Blanchard, Miran; Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota; Shim, Kevin G.
Purpose: The oligometastatic state is an intermediate state between a malignancy that can be completely eradicated with conventional modalities and one in which a palliative approach is undertaken. Clinically, high rates of local tumor control are possible with stereotactic ablative radiation therapy (SABR), using precisely targeted, high-dose, low-fraction radiation therapy. However, in oligometastatic melanoma, virtually all patients develop progression systemically at sites not initially treated with ablative radiation therapy that cannot be managed with conventional chemotherapy and immunotherapy. We have demonstrated in mice that intravenous administration of vesicular stomatitis virus (VSV) expressing defined tumor-associated antigens (TAAs) generates systemic immune responsesmore » capable of clearing established tumors. Therefore, in the present preclinical study, we tested whether the combination of systemic VSV-mediated antigen delivery and SABR would be effective against oligometastatic disease. Methods and Materials: We generated a model of oligometastatic melanoma in C57BL/6 immunocompetent mice and then used a combination of SABR and systemically administered VSV-TAA viral immunotherapy to treat both local and systemic disease. Results: Our data showed that SABR generates excellent control or cure of local, clinically detectable, and accessible tumor through direct cell ablation. Also, the immunotherapeutic activity of systemically administered VSV-TAA generated T-cell responses that cleared subclinical metastatic tumors. We also showed that SABR induced weak T-cell-mediated tumor responses, which, particularly if boosted by VSV-TAA, might contribute to control of local and systemic disease. In addition, VSV-TAA therapy alone had significant effects on control of both local and metastatic tumors. Conclusions: We have shown in the present preliminary murine study using a single tumor model that this approach represents an effective, complementary combination therapy model that addresses the need for both systemic and local control in oligometastatic melanoma.« less
-
Meso-macro simulation of the woven fabric local deformation in draping
NASA Astrophysics Data System (ADS)
Iwata, Akira; Inoue, Takuya; Naouar, Naim; Boisse, Philippe; Lomov, Stepan V.
2018-05-01
The paper reports results of such combined meso-macro modelling for a plain weave carbon fabric with spread yarns. The boundary conditions for a local meso-model are taken from the macro draping simulation. The fabric geometry is modelled with WiseTex and transferred to the finite element package. A hyperelastic constitutive model for the yarns (Charmetant - Boisse) is used in the meso-modelling; the model parameters are identified and validated in independent tension, shear, compaction and bending tests of the yarn and the fabric. The simulation reproduces local yarn slippage and buckling, for example, the yarn distortion on the 3D mould corner (see the figure). The simulations are compared with the local fabric distortions observed during draping experiments.
-
Soft sensor modeling based on variable partition ensemble method for nonlinear batch processes
NASA Astrophysics Data System (ADS)
Wang, Li; Chen, Xiangguang; Yang, Kai; Jin, Huaiping
2017-01-01
Batch processes are always characterized by nonlinear and system uncertain properties, therefore, the conventional single model may be ill-suited. A local learning strategy soft sensor based on variable partition ensemble method is developed for the quality prediction of nonlinear and non-Gaussian batch processes. A set of input variable sets are obtained by bootstrapping and PMI criterion. Then, multiple local GPR models are developed based on each local input variable set. When a new test data is coming, the posterior probability of each best performance local model is estimated based on Bayesian inference and used to combine these local GPR models to get the final prediction result. The proposed soft sensor is demonstrated by applying to an industrial fed-batch chlortetracycline fermentation process.
-
NASA Astrophysics Data System (ADS)
Davari, Nazanin; Haghdani, Shokouh; Åstrand, Per-Olof
2015-12-01
A force field model for calculating local field factors, i.e. the linear response of the local electric field for example at a nucleus in a molecule with respect to an applied electric field, is discussed. It is based on a combined charge-transfer and point-dipole interaction model for the polarizability, and thereby it includes two physically distinct terms for describing electronic polarization: changes in atomic charges arising from transfer of charge between the atoms and atomic induced dipole moments. A time dependence is included both for the atomic charges and the atomic dipole moments and if they are assumed to oscillate with the same frequency as the applied electric field, a model for frequency-dependent properties are obtained. Furthermore, if a life-time of excited states are included, a model for the complex frequency-dependent polariability is obtained including also information about excited states and the absorption spectrum. We thus present a model for the frequency-dependent local field factors through the first molecular excitation energy. It is combined with molecular dynamics simulations of liquids where a large set of configurations are sampled and for which local field factors are calculated. We are normally not interested in the average of the local field factor but rather in configurations where it is as high as possible. In electrical insulation, we would like to avoid high local field factors to reduce the risk for electrical breakdown, whereas for example in surface-enhanced Raman spectroscopy, high local field factors are desired to give dramatically increased intensities.
-
Rand, B C C; Penn-Barwell, J G; Wenke, J C
2015-10-01
Systemic antibiotics reduce infection in open fractures. Local delivery of antibiotics can provide higher doses to wounds without toxic systemic effects. This study investigated the effect on infection of combining systemic with local antibiotics via polymethylmethacrylate (PMMA) beads or gel delivery. An established Staphylococcus aureus contaminated fracture model in rats was used. Wounds were debrided and irrigated six hours after contamination and animals assigned to one of three groups, all of which received systemic antibiotics. One group had local delivery via antibiotic gel, another PMMA beads and the control group received no local antibiotics. After two weeks, bacterial levels were quantified. Combined local and systemic antibiotics were superior to systemic antibiotics alone at reducing the quantity of bacteria recoverable from each group (p = 0.002 for gel; p = 0.032 for beads). There was no difference in the bacterial counts between bead and gel delivery (p = 0.62). These results suggest that local antibiotics augment the antimicrobial effect of systemic antibiotics. Although no significant difference was found between vehicles, gel delivery offers technical advantages with its biodegradable nature, ability to conform to wound shape and to deliver increased doses. Further study is required to see if the gel delivery system has a clinical role. ©2015 The British Editorial Society of Bone & Joint Surgery.
-
Downscaler Model for predicting daily air pollution
This model combines daily ozone and particulate matter monitoring and modeling data from across the U.S. to provide improved fine-scale estimates of air quality in communities and other specific locales.
-
2017-08-01
of metallic additive manufacturing processes and show that combining experimental data with modelling and advanced data processing and analytics...manufacturing processes and show that combining experimental data with modelling and advanced data processing and analytics methods will accelerate that...geometries, we develop a methodology that couples experimental data and modelling to convert the scan paths into spatially resolved local thermal histories
-
Sridharan, Vijayalakshmi; Tripathi, Preeti; Sharma, Sunil; Corry, Peter M; Moros, Eduardo G; Singh, Awantika; Compadre, Cesar M; Hauer-Jensen, Martin; Boerma, Marjan
2013-01-01
Radiation-induced heart disease (RIHD) is a long-term side effect of radiotherapy of intrathoracic, chest wall and breast tumors when radiation fields encompass all or part of the heart. Previous studies have shown that pentoxifylline (PTX) in combination with α-tocopherol reduced manifestations of RIHD in rat models of local heart irradiation. The relative contribution of PTX and α-tocopherol to these beneficial effects are not known. This study examined the effects of PTX alone or in combination with tocotrienols, forms of vitamin E with potential potent radiation mitigation properties. Rats received localized X-irradiation of the heart with an image-guided irradiation technique. At 3 months after irradiation rats received oral treatment with vehicle, PTX, or PTX in combination with a tocotrienol-enriched formulation. At 6 months after irradiation, PTX-treated rats showed arrhythmia in 5 out of 14 animals. PTX alone or in combination with tocotrienols did not alter cardiac radiation fibrosis, left ventricular protein expression of the endothelial markers von Willebrand factor and neuregulin-1, or phosphorylation of the signal mediators Akt, Erk1/2, or PKCα. On the other hand, tocotrienols reduced cardiac numbers of mast cells and macrophages, but enhanced the expression of tissue factor. While this new rat model of localized heart irradiation does not support the use of PTX alone, the effects of tocotrienols on chronic manifestations of RIHD deserve further investigation.
-
Sridharan, Vijayalakshmi; Tripathi, Preeti; Sharma, Sunil; Corry, Peter M.; Moros, Eduardo G.; Singh, Awantika; Compadre, Cesar M.; Hauer-Jensen, Martin; Boerma, Marjan
2013-01-01
Radiation-induced heart disease (RIHD) is a long-term side effect of radiotherapy of intrathoracic, chest wall and breast tumors when radiation fields encompass all or part of the heart. Previous studies have shown that pentoxifylline (PTX) in combination with α-tocopherol reduced manifestations of RIHD in rat models of local heart irradiation. The relative contribution of PTX and α-tocopherol to these beneficial effects are not known. This study examined the effects of PTX alone or in combination with tocotrienols, forms of vitamin E with potential potent radiation mitigation properties. Rats received localized X-irradiation of the heart with an image-guided irradiation technique. At 3 months after irradiation rats received oral treatment with vehicle, PTX, or PTX in combination with a tocotrienol-enriched formulation. At 6 months after irradiation, PTX-treated rats showed arrhythmia in 5 out of 14 animals. PTX alone or in combination with tocotrienols did not alter cardiac radiation fibrosis, left ventricular protein expression of the endothelial markers von Willebrand factor and neuregulin-1, or phosphorylation of the signal mediators Akt, Erk1/2, or PKCα. On the other hand, tocotrienols reduced cardiac numbers of mast cells and macrophages, but enhanced the expression of tissue factor. While this new rat model of localized heart irradiation does not support the use of PTX alone, the effects of tocotrienols on chronic manifestations of RIHD deserve further investigation. PMID:23894340
-
NASA Astrophysics Data System (ADS)
Liu, Jian; Ren, Zhongzhou; Xu, Chang
2018-07-01
Combining the modified Skyrme-like model and the local density approximation model, the slope parameter L of symmetry energy is extracted from the properties of finite nuclei with an improved iterative method. The calculations of the iterative method are performed within the framework of the spherical symmetry. By choosing 200 neutron rich nuclei on 25 isotopic chains as candidates, the slope parameter is constrained to be 50 MeV < L < 62 MeV. The validity of this method is examined by the properties of finite nuclei. Results show that reasonable descriptions on the properties of finite nuclei and nuclear matter can be obtained together.
-
Hoos, Anne B.; Patel, Anant R.
1996-01-01
Model-adjustment procedures were applied to the combined data bases of storm-runoff quality for Chattanooga, Knoxville, and Nashville, Tennessee, to improve predictive accuracy for storm-runoff quality for urban watersheds in these three cities and throughout Middle and East Tennessee. Data for 45 storms at 15 different sites (five sites in each city) constitute the data base. Comparison of observed values of storm-runoff load and event-mean concentration to the predicted values from the regional regression models for 10 constituents shows prediction errors, as large as 806,000 percent. Model-adjustment procedures, which combine the regional model predictions with local data, are applied to improve predictive accuracy. Standard error of estimate after model adjustment ranges from 67 to 322 percent. Calibration results may be biased due to sampling error in the Tennessee data base. The relatively large values of standard error of estimate for some of the constituent models, although representing significant reduction (at least 50 percent) in prediction error compared to estimation with unadjusted regional models, may be unacceptable for some applications. The user may wish to collect additional local data for these constituents and repeat the analysis, or calibrate an independent local regression model.
-
A novel cost-effective parallel narrowband ANC system with local secondary-path estimation
NASA Astrophysics Data System (ADS)
Delegà, Riccardo; Bernasconi, Giancarlo; Piroddi, Luigi
2017-08-01
Many noise reduction applications are targeted at multi-tonal disturbances. Active noise control (ANC) solutions for such problems are generally based on the combination of multiple adaptive notch filters. Both the performance and the computational cost are negatively affected by an increase in the number of controlled frequencies. In this work we study a different modeling approach for the secondary path, based on the estimation of various small local models in adjacent frequency subbands, that greatly reduces the impact of reference-filtering operations in the ANC algorithm. Furthermore, in combination with a frequency-specific step size tuning method it provides a balanced attenuation performance over the whole controlled frequency range (and particularly in the high end of the range). Finally, the use of small local models is greatly beneficial for the reactivity of the online secondary path modeling algorithm when the characteristics of the acoustic channels are time-varying. Several simulations are provided to illustrate the positive features of the proposed method compared to other well-known techniques.
-
Supernovae observations in a ``meatball'' universe with a local void
NASA Astrophysics Data System (ADS)
Kainulainen, Kimmo; Marra, Valerio
2009-12-01
We study the impact of cosmic inhomogeneities on the interpretation of observations. We build an inhomogeneous universe model without dark energy that can confront supernova data and yet is reasonably well compatible with the Copernican principle. Our model combines a relatively small local void, that gives apparent acceleration at low redshifts, with a meatball model that gives sizable lensing (dimming) at high redshifts. Together these two elements, which focus on different effects of voids on the data, allow the model to mimic the concordance model.
-
NASA Astrophysics Data System (ADS)
Burin, Alexander L.
2015-09-01
Many-body localization in an XY model with a long-range interaction is investigated. We show that in the regime of a high strength of disordering compared to the interaction an off-resonant flip-flop spin-spin interaction (hopping) generates the effective Ising interactions of spins in the third order of perturbation theory in a hopping. The combination of hopping and induced Ising interactions for the power-law distance dependent hopping V (R ) ∝R-α always leads to the localization breakdown in a thermodynamic limit of an infinite system at α <3 d /2 where d is a system dimension. The delocalization takes place due to the induced Ising interactions U (R ) ∝R-2 α of "extended" resonant pairs. This prediction is consistent with the numerical finite size scaling in one-dimensional systems. Many-body localization in an XY model is more stable with respect to the long-range interaction compared to a many-body problem with similar Ising and Heisenberg interactions requiring α ≥2 d which makes the practical implementations of this model more attractive for quantum information applications. The full summary of dimension constraints and localization threshold size dependencies for many-body localization in the case of combined Ising and hopping interactions is obtained using this and previous work and it is the subject for the future experimental verification using cold atomic systems.
-
NASA Astrophysics Data System (ADS)
Dooley, Gregory A.; Peter, Annika H. G.; Yang, Tianyi; Willman, Beth; Griffen, Brendan F.; Frebel, Anna
2017-11-01
A recent surge in the discovery of new ultrafaint dwarf satellites of the Milky Way has inspired the idea of searching for faint satellites, 103 M⊙
-
A Core Journal Decision Model Based on Weighted Page Rank
ERIC Educational Resources Information Center
Wang, Hei-Chia; Chou, Ya-lin; Guo, Jiunn-Liang
2011-01-01
Purpose: The paper's aim is to propose a core journal decision method, called the local impact factor (LIF), which can evaluate the requirements of the local user community by combining both the access rate and the weighted impact factor, and by tracking citation information on the local users' articles. Design/methodology/approach: Many…
-
Online Adaboost-Based Parameterized Methods for Dynamic Distributed Network Intrusion Detection.
Hu, Weiming; Gao, Jun; Wang, Yanguo; Wu, Ou; Maybank, Stephen
2014-01-01
Current network intrusion detection systems lack adaptability to the frequently changing network environments. Furthermore, intrusion detection in the new distributed architectures is now a major requirement. In this paper, we propose two online Adaboost-based intrusion detection algorithms. In the first algorithm, a traditional online Adaboost process is used where decision stumps are used as weak classifiers. In the second algorithm, an improved online Adaboost process is proposed, and online Gaussian mixture models (GMMs) are used as weak classifiers. We further propose a distributed intrusion detection framework, in which a local parameterized detection model is constructed in each node using the online Adaboost algorithm. A global detection model is constructed in each node by combining the local parametric models using a small number of samples in the node. This combination is achieved using an algorithm based on particle swarm optimization (PSO) and support vector machines. The global model in each node is used to detect intrusions. Experimental results show that the improved online Adaboost process with GMMs obtains a higher detection rate and a lower false alarm rate than the traditional online Adaboost process that uses decision stumps. Both the algorithms outperform existing intrusion detection algorithms. It is also shown that our PSO, and SVM-based algorithm effectively combines the local detection models into the global model in each node; the global model in a node can handle the intrusion types that are found in other nodes, without sharing the samples of these intrusion types.
-
Model-Based Localization and Tracking Using Bluetooth Low-Energy Beacons
Cemgil, Ali Taylan
2017-01-01
We introduce a high precision localization and tracking method that makes use of cheap Bluetooth low-energy (BLE) beacons only. We track the position of a moving sensor by integrating highly unreliable and noisy BLE observations streaming from multiple locations. A novel aspect of our approach is the development of an observation model, specifically tailored for received signal strength indicator (RSSI) fingerprints: a combination based on the optimal transport model of Wasserstein distance. The tracking results of the entire system are compared with alternative baseline estimation methods, such as nearest neighboring fingerprints and an artificial neural network. Our results show that highly accurate estimation from noisy Bluetooth data is practically feasible with an observation model based on Wasserstein distance interpolation combined with the sequential Monte Carlo (SMC) method for tracking. PMID:29109375
-
Model-Based Localization and Tracking Using Bluetooth Low-Energy Beacons.
Daniş, F Serhan; Cemgil, Ali Taylan
2017-10-29
We introduce a high precision localization and tracking method that makes use of cheap Bluetooth low-energy (BLE) beacons only. We track the position of a moving sensor by integrating highly unreliable and noisy BLE observations streaming from multiple locations. A novel aspect of our approach is the development of an observation model, specifically tailored for received signal strength indicator (RSSI) fingerprints: a combination based on the optimal transport model of Wasserstein distance. The tracking results of the entire system are compared with alternative baseline estimation methods, such as nearest neighboring fingerprints and an artificial neural network. Our results show that highly accurate estimation from noisy Bluetooth data is practically feasible with an observation model based on Wasserstein distance interpolation combined with the sequential Monte Carlo (SMC) method for tracking.
-
NASA Astrophysics Data System (ADS)
He, Lin; Li, Jiancheng; Chu, Yonghai; Zhang, Tengxu
2017-04-01
National height reference systems have conventionally been linked to the coastal local mean sea level, observed at one tide gauge, such as the China national height datum 1985. Due to the effect of the local sea surface topography, the reference level surface of local datum is inconsistent with the global datum or other local datum. In order to unify or connect the local datum to the global height datum, it is necessary to obtain the zero-height geopotential value of local datum or the height offset with respect to the global datum. The GRACE and GOCE satellite mission are promising for purposes of unification of local vertical datums because they have brought a significant improvement in modeling of low-frequency or rather medium-frequency part of the Earth's static gravity field in the past ten years. The focus of this work is directed to the evaluation of most available Global Geopotential Models (GGMs) from GOCE and GRACE, both satellite only as well as combined ones. From the evaluation with the 649 GPS/Levelling benchmarks (BMs) in China, the GOCE/GRACE GGMs provide the accuracy at 42-52cm level, up to their max degree and order. The latest release 5 DIR, TIM GGMs improve the accuracies by 6-10cm compared to the release 1 models. The DIR_R1 is based on the fewer GOCE data performs equally well with the DIR_R4 and DIR_R5 model, this is attributed to the fact that during its development which used a priori information from EIGEN-51C. The zero-height geopotential value W0LVD for the China Local Vertical Datum (LVD) is 62636855.1606m2s-2 from the originally GOCE/GRACE GGMs. Taking into account the GPS/Levelling data contains the full spectral information, and the GOCE-only or GRACE-GOCE combined model are limited to the long wavelengths. To improve the accuracy of the GGMs, it is indispensable to account for the remaining signal above this maximum degree, known as the omission error of the GGM. The effect of GRACE/GOCE omission error is investigated by extending the models with the high-resolution gravity field model EGM2008. In China, the effect of the GRACE/GOCE GGMs omission error is at the decimeter level. The combined GGMs (up to 2160 degree and order) could provide an accuracy at 20cm level, which is better than that from EGM2008. Meanwhile, if an appropriate degree and order is chosen for the GOCE-only or GRACE-GOCE combined GGMs to connect with the EGM2008, the extended GGMs provide an accuracy at 16cm level. From the extended GGMs, the geopotential value W0LVD determined for the China local vertical datum is 62636853.4351 m2s-2 indicates a bias of about 2.5649 m2/s-2 compared to the conventional value of 62,636,856.0 m2s-2. This is support by National key research and development program No:2016YFB0501702. Keywords: Global Geopotential Models; GRACE; GOCE; GPS/Levelling; zero-height geopotential
-
The small length scale effect for a non-local cantilever beam: a paradox solved.
Challamel, N; Wang, C M
2008-08-27
Non-local continuum mechanics allows one to account for the small length scale effect that becomes significant when dealing with microstructures or nanostructures. This paper presents some simplified non-local elastic beam models, for the bending analyses of small scale rods. Integral-type or gradient non-local models abandon the classical assumption of locality, and admit that stress depends not only on the strain value at that point but also on the strain values of all points on the body. There is a paradox still unresolved at this stage: some bending solutions of integral-based non-local elastic beams have been found to be identical to the classical (local) solution, i.e. the small scale effect is not present at all. One example is the Euler-Bernoulli cantilever nanobeam model with a point load which has application in microelectromechanical systems and nanoelectromechanical systems as an actuator. In this paper, it will be shown that this paradox may be overcome with a gradient elastic model as well as an integral non-local elastic model that is based on combining the local and the non-local curvatures in the constitutive elastic relation. The latter model comprises the classical gradient model and Eringen's integral model, and its application produces small length scale terms in the non-local elastic cantilever beam solution.
-
NASA Astrophysics Data System (ADS)
Li, Mingming; Li, Lin; Li, Qiang; Zou, Zongshu
2018-05-01
A filter-based Euler-Lagrange multiphase flow model is used to study the mixing behavior in a combined blowing steelmaking converter. The Euler-based volume of fluid approach is employed to simulate the top blowing, while the Lagrange-based discrete phase model that embeds the local volume change of rising bubbles for the bottom blowing. A filter-based turbulence method based on the local meshing resolution is proposed aiming to improve the modeling of turbulent eddy viscosities. The model validity is verified through comparison with physical experiments in terms of mixing curves and mixing times. The effects of the bottom gas flow rate on bath flow and mixing behavior are investigated and the inherent reasons for the mixing result are clarified in terms of the characteristics of bottom-blowing plumes, the interaction between plumes and top-blowing jets, and the change of bath flow structure.
-
Enhanced antitumor effect of curcumin liposomes with local hyperthermia in the LL/2 model.
Tang, Jian-Cai; Shi, Hua-Shan; Wan, Li-Qiang; Wang, Yong-Sheng; Wei, Yu-Quan
2013-01-01
Curcumin previously was proven to inhibit angiogenesis and display potent antitumor activity in vivo and in vitro. In the present study, we investigated whether a combination curcumin with hyperthermia would have a synergistic antitumor effect in the LL/2 model. The results indicated that combination therapy significantly inhibited cell proliferation of MS-1 and LL/2 in vitro. LL/2 experiment model also demonstrated that the combination therapy inhibited tumor growth and prolonged the life span in vivo. Furthermore, combination therapy reduced angiogenesis and increased tumor apoptosis. Our findings suggest that the combination therapy exerted synergistic antitumor effects, providing a new perspective fpr clinical tumor therapy.
-
Nazemi, S Majid; Kalajahi, S Mehrdad Hosseini; Cooper, David M L; Kontulainen, Saija A; Holdsworth, David W; Masri, Bassam A; Wilson, David R; Johnston, James D
2017-07-05
Previously, a finite element (FE) model of the proximal tibia was developed and validated against experimentally measured local subchondral stiffness. This model indicated modest predictions of stiffness (R 2 =0.77, normalized root mean squared error (RMSE%)=16.6%). Trabecular bone though was modeled with isotropic material properties despite its orthotropic anisotropy. The objective of this study was to identify the anisotropic FE modeling approach which best predicted (with largest explained variance and least amount of error) local subchondral bone stiffness at the proximal tibia. Local stiffness was measured at the subchondral surface of 13 medial/lateral tibial compartments using in situ macro indentation testing. An FE model of each specimen was generated assuming uniform anisotropy with 14 different combinations of cortical- and tibial-specific density-modulus relationships taken from the literature. Two FE models of each specimen were also generated which accounted for the spatial variation of trabecular bone anisotropy directly from clinical CT images using grey-level structure tensor and Cowin's fabric-elasticity equations. Stiffness was calculated using FE and compared to measured stiffness in terms of R 2 and RMSE%. The uniform anisotropic FE model explained 53-74% of the measured stiffness variance, with RMSE% ranging from 12.4 to 245.3%. The models which accounted for spatial variation of trabecular bone anisotropy predicted 76-79% of the variance in stiffness with RMSE% being 11.2-11.5%. Of the 16 evaluated finite element models in this study, the combination of Synder and Schneider (for cortical bone) and Cowin's fabric-elasticity equations (for trabecular bone) best predicted local subchondral bone stiffness. Copyright © 2017 Elsevier Ltd. All rights reserved.
-
Cross-scale assessment of potential habitat shifts in a rapidly changing climate
Jarnevich, Catherine S.; Holcombe, Tracy R.; Bella, Elizabeth S.; Carlson, Matthew L.; Graziano, Gino; Lamb, Melinda; Seefeldt, Steven S.; Morisette, Jeffrey T.
2014-01-01
We assessed the ability of climatic, environmental, and anthropogenic variables to predict areas of high-risk for plant invasion and consider the relative importance and contribution of these predictor variables by considering two spatial scales in a region of rapidly changing climate. We created predictive distribution models, using Maxent, for three highly invasive plant species (Canada thistle, white sweetclover, and reed canarygrass) in Alaska at both a regional scale and a local scale. Regional scale models encompassed southern coastal Alaska and were developed from topographic and climatic data at a 2 km (1.2 mi) spatial resolution. Models were applied to future climate (2030). Local scale models were spatially nested within the regional area; these models incorporated physiographic and anthropogenic variables at a 30 m (98.4 ft) resolution. Regional and local models performed well (AUC values > 0.7), with the exception of one species at each spatial scale. Regional models predict an increase in area of suitable habitat for all species by 2030 with a general shift to higher elevation areas; however, the distribution of each species was driven by different climate and topographical variables. In contrast local models indicate that distance to right-of-ways and elevation are associated with habitat suitability for all three species at this spatial level. Combining results from regional models, capturing long-term distribution, and local models, capturing near-term establishment and distribution, offers a new and effective tool for highlighting at-risk areas and provides insight on how variables acting at different scales contribute to suitability predictions. The combinations also provides easy comparison, highlighting agreement between the two scales, where long-term distribution factors predict suitability while near-term do not and vice versa.
-
Learning Human Actions by Combining Global Dynamics and Local Appearance.
Luo, Guan; Yang, Shuang; Tian, Guodong; Yuan, Chunfeng; Hu, Weiming; Maybank, Stephen J
2014-12-01
In this paper, we address the problem of human action recognition through combining global temporal dynamics and local visual spatio-temporal appearance features. For this purpose, in the global temporal dimension, we propose to model the motion dynamics with robust linear dynamical systems (LDSs) and use the model parameters as motion descriptors. Since LDSs live in a non-Euclidean space and the descriptors are in non-vector form, we propose a shift invariant subspace angles based distance to measure the similarity between LDSs. In the local visual dimension, we construct curved spatio-temporal cuboids along the trajectories of densely sampled feature points and describe them using histograms of oriented gradients (HOG). The distance between motion sequences is computed with the Chi-Squared histogram distance in the bag-of-words framework. Finally we perform classification using the maximum margin distance learning method by combining the global dynamic distances and the local visual distances. We evaluate our approach for action recognition on five short clips data sets, namely Weizmann, KTH, UCF sports, Hollywood2 and UCF50, as well as three long continuous data sets, namely VIRAT, ADL and CRIM13. We show competitive results as compared with current state-of-the-art methods.
-
NASA Astrophysics Data System (ADS)
Cui, Tao; Moore, Catherine; Raiber, Matthias
2018-05-01
Modelling cumulative impacts of basin-scale coal seam gas (CSG) extraction is challenging due to the long time frames and spatial extent over which impacts occur combined with the need to consider local-scale processes. The computational burden of such models limits the ability to undertake calibration and sensitivity and uncertainty analyses. A framework is presented that integrates recently developed methods and tools to address the computational burdens of an assessment of drawdown impacts associated with rapid CSG development in the Surat Basin, Australia. The null space Monte Carlo method combined with singular value decomposition (SVD)-assisted regularisation was used to analyse the uncertainty of simulated drawdown impacts. The study also describes how the computational burden of assessing local-scale impacts was mitigated by adopting a novel combination of a nested modelling framework which incorporated a model emulator of drawdown in dual-phase flow conditions, and a methodology for representing local faulting. This combination provides a mechanism to support more reliable estimates of regional CSG-related drawdown predictions. The study indicates that uncertainties associated with boundary conditions are reduced significantly when expressing differences between scenarios. The results are analysed and distilled to enable the easy identification of areas where the simulated maximum drawdown impacts could exceed trigger points associated with legislative `make good' requirements; trigger points require that either an adjustment in the development scheme or other measures are implemented to remediate the impact. This report contributes to the currently small body of work that describes modelling and uncertainty analyses of CSG extraction impacts on groundwater.
-
Local variability mediates vulnerability of trout populations to land use and climate change
Brooke E. Penaluna; Jason B. Dunham; Steve F. Railsback; Ivan Arismendi; Sherri L. Johnson; Robert E. Bilby; Mohammad Safeeq; Arne E. Skaugset; James P. Meador
2015-01-01
Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of...
-
A local-circulation model for Darrieus vertical-axis wind turbines
NASA Astrophysics Data System (ADS)
Masse, B.
1986-04-01
A new computational model for the aerodynamics of the vertical-axis wind turbine is presented. Based on the local-circulation method generalized for curved blades, combined with a wake model for the vertical-axis wind turbine, it differs markedly from current models based on variations in the streamtube momentum and vortex models using the lifting-line theory. A computer code has been developed to calculate the loads and performance of the Darrieus vertical-axis wind turbine. The results show good agreement with experimental data and compare well with other methods.
-
Open-ocean boundary conditions from interior data: Local and remote forcing of Massachusetts Bay
Bogden, P.S.; Malanotte-Rizzoli, P.; Signell, R.
1996-01-01
Massachusetts and Cape Cod Bays form a semienclosed coastal basin that opens onto the much larger Gulf of Maine. Subtidal circulation in the bay is driven by local winds and remotely driven flows from the gulf. The local-wind forced flow is estimated with a regional shallow water model driven by wind measurements. The model uses a gravity wave radiation condition along the open-ocean boundary. Results compare reasonably well with observed currents near the coast. In some offshore regions however, modeled flows are an order of magnitude less energetic than the data. Strong flows are observed even during periods of weak local wind forcing. Poor model-data comparisons are attributable, at least in part, to open-ocean boundary conditions that neglect the effects of remote forcing. Velocity measurements from within Massachusetts Bay are used to estimate the remotely forced component of the flow. The data are combined with shallow water dynamics in an inverse-model formulation that follows the theory of Bennett and McIntosh [1982], who considered tides. We extend their analysis to consider the subtidal response to transient forcing. The inverse model adjusts the a priori open-ocean boundary condition, thereby minimizing a combined measure of model-data misfit and boundary condition adjustment. A "consistency criterion" determines the optimal trade-off between the two. The criterion is based on a measure of plausibility for the inverse solution. The "consistent" inverse solution reproduces 56% of the average squared variation in the data. The local-wind-driven flow alone accounts for half of the model skill. The other half is attributable to remotely forced flows from the Gulf of Maine. The unexplained 44% comes from measurement errors and model errors that are not accounted for in the analysis.
-
Gateuille, David; Evrard, Olivier; Lefevre, Irène; Moreau-Guigon, Elodie; Alliot, Fabrice; Chevreuil, Marc; Mouchel, Jean-Marie
2014-06-01
Various sources supply PAHs that accumulate in soils. The methodology we developed provided an evaluation of the contribution of local sources (road traffic, local industries) versus remote sources (long range atmospheric transport, fallout and gaseous exchanges) to PAH stocks in two contrasting subcatchments (46-614 km²) of the Seine River basin (France). Soil samples (n = 336) were analysed to investigate the spatial pattern of soil contamination across the catchments and an original combination with radionuclide measurements provided new insights into the evolution of the contamination with depth. Relationships between PAH concentrations and the distance to the potential sources were modelled. Despite both subcatchments are mainly rural, roadside areas appeared to concentrate 20% of the contamination inside the catchment while a local industry was found to be responsible for up to 30% of the stocks. Those results have important implications for understanding and controlling PAH contamination in rural areas of early-industrialized regions. Copyright © 2014 Elsevier Ltd. All rights reserved.
-
Kroin, Jeffrey S; Li, Jinyuan; Moric, Mario; Birmingham, Brian W; Tuman, Kenneth J; Buvanendran, Asokumar
There is an increasing use of local infiltration analgesia (LIA) to reduce postoperative pain. Despite widespread use of LIA, wide variations in drug combinations and concomitant use of systemic analgesics have made it difficult to determine the optimal drug combinations for LIA. Using a previously validated rat laparotomy model, the optimal LIA combination of medications to reduce postoperative pain was determined. Laparotomy was performed in an adult rat model under isoflurane anesthesia. During surgery, combinations of bupivacaine, ketorolac, and dexamethasone were injected over the sutured muscle wound before skin closing, and compared to saline (placebo). The same medications were injected systemically as controls. Postoperative pain was assessed by measuring spontaneous rearing activity. A high-dose 3-drug LIA combination (50 μL of bupivacaine 0.75%, ketorolac 6.0 mg/mL, and dexamethasone 2.0 mg/mL) increased rearing (decreased pain) at 2 hours (P = 0.0032) postsurgery compared to saline. However, the same 3 drugs injected systemically had a similar analgesic effect (P = 0.0002). Bupivacaine 0.75% alone was not effective for LIA. When low-dose (9-fold reduction) 3-drug LIA combination was used, LIA increased rearing (P = 0.0034) whereas the same 3 drugs injected systemically had no effect. Low-dose LIA ketorolac/dexamethasone (2-drug combination) also increased rearing (P = 0.0393). Our animal study suggests that clinical trials with low-dose LIA combinations of local anesthetic, nonsteroidal anti-inflammatory drug, and corticosteroid may be useful for reducing postoperative pain after laparotomy.
-
Piatkowski, Pawel; Kasprzak, Joanna M; Kumar, Deepak; Magnus, Marcin; Chojnowski, Grzegorz; Bujnicki, Janusz M
2016-01-01
RNA encompasses an essential part of all known forms of life. The functions of many RNA molecules are dependent on their ability to form complex three-dimensional (3D) structures. However, experimental determination of RNA 3D structures is laborious and challenging, and therefore, the majority of known RNAs remain structurally uncharacterized. To address this problem, computational structure prediction methods were developed that either utilize information derived from known structures of other RNA molecules (by way of template-based modeling) or attempt to simulate the physical process of RNA structure formation (by way of template-free modeling). All computational methods suffer from various limitations that make theoretical models less reliable than high-resolution experimentally determined structures. This chapter provides a protocol for computational modeling of RNA 3D structure that overcomes major limitations by combining two complementary approaches: template-based modeling that is capable of predicting global architectures based on similarity to other molecules but often fails to predict local unique features, and template-free modeling that can predict the local folding, but is limited to modeling the structure of relatively small molecules. Here, we combine the use of a template-based method ModeRNA with a template-free method SimRNA. ModeRNA requires a sequence alignment of the target RNA sequence to be modeled with a template of the known structure; it generates a model that predicts the structure of a conserved core and provides a starting point for modeling of variable regions. SimRNA can be used to fold small RNAs (<80 nt) without any additional structural information, and to refold parts of models for larger RNAs that have a correctly modeled core. ModeRNA can be either downloaded, compiled and run locally or run through a web interface at http://genesilico.pl/modernaserver/ . SimRNA is currently available to download for local use as a precompiled software package at http://genesilico.pl/software/stand-alone/simrna and as a web server at http://genesilico.pl/SimRNAweb . For model optimization we use QRNAS, available at http://genesilico.pl/qrnas .
-
Local Drug Infiltration Analgesia During Knee Surgery to Reduce Postoperative Pain in Rats.
Buvanendran, Asokumar; Kroin, Jeffrey S; Della Valle, Craig J; Moric, Mario; Tuman, Kenneth J
2016-01-01
There is increasing interest in local infiltration analgesia (LIA) to reduce postoperative pain with knee surgery. Despite widespread use of LIA, wide variations in drug combinations, infiltration techniques, and the concomitant use of systemic analgesics have made it difficult to determine the optimal drug combination for LIA.Using a previously validated animal knee surgery model, we aimed to determine the optimal combination of medications to reduce postoperative pain, and the best anatomical location and timing for local drug injection during surgery. Knee surgery was performed in an adult rat model under isoflurane anesthesia. During surgery, combinations of bupivacaine, ketorolac, dexamethasone, and morphine were injected around the knee and compared to saline placebo. Similar medications were injected systemically as a comparator group. Postoperative pain was assessed by measuring spontaneous rearing activity. Injections were given after bone drilling and/or just before wound closure. The 3-drug LIA combination of bupivacaine, ketorolac, and dexamethasone increased rearing (decreased pain) at 2 hours (P = 0.0198) and 24 hours (P = 0.0384) postsurgery compared to saline. The same drugs injected systemically had no effect. The ketorolac/dexamethasone combination for LIA was also effective at 2 hours (P = 0.0006) and 24 hours (P = 0.0279), and ketorolac alone reduced pain at 2 hours (P = 0.0045). Bupivacaine alone was less effective, and the addition of morphine had no effect. The 3-drug combination infiltrated just after creating holes in bone was more effective than when given into the wound just before wound closure. Our animal study suggests that clinical trials with LIA combinations of local anesthetic, nonsteroidal anti-inflammatory drug, and corticosteroid might be useful for reducing postoperative pain after knee surgery, with the nonsteroidal anti-inflammatory drug having the greatest effect.Perioperative physicians should consider delivering LIA earlier during the procedure as opposed to solely at the time of wound closure.
-
Pan, Xiaoyong; Shen, Hong-Bin
2018-05-02
RNA-binding proteins (RBPs) take over 5∼10% of the eukaryotic proteome and play key roles in many biological processes, e.g. gene regulation. Experimental detection of RBP binding sites is still time-intensive and high-costly. Instead, computational prediction of the RBP binding sites using pattern learned from existing annotation knowledge is a fast approach. From the biological point of view, the local structure context derived from local sequences will be recognized by specific RBPs. However, in computational modeling using deep learning, to our best knowledge, only global representations of entire RNA sequences are employed. So far, the local sequence information is ignored in the deep model construction process. In this study, we present a computational method iDeepE to predict RNA-protein binding sites from RNA sequences by combining global and local convolutional neural networks (CNNs). For the global CNN, we pad the RNA sequences into the same length. For the local CNN, we split a RNA sequence into multiple overlapping fixed-length subsequences, where each subsequence is a signal channel of the whole sequence. Next, we train deep CNNs for multiple subsequences and the padded sequences to learn high-level features, respectively. Finally, the outputs from local and global CNNs are combined to improve the prediction. iDeepE demonstrates a better performance over state-of-the-art methods on two large-scale datasets derived from CLIP-seq. We also find that the local CNN run 1.8 times faster than the global CNN with comparable performance when using GPUs. Our results show that iDeepE has captured experimentally verified binding motifs. https://github.com/xypan1232/iDeepE. xypan172436@gmail.com or hbshen@sjtu.edu.cn. Supplementary data are available at Bioinformatics online.
-
Ocean Tide Loading Computation
NASA Technical Reports Server (NTRS)
Agnew, Duncan Carr
2005-01-01
September 15,2003 through May 15,2005 This grant funds the maintenance, updating, and distribution of programs for computing ocean tide loading, to enable the corrections for such loading to be more widely applied in space- geodetic and gravity measurements. These programs, developed under funding from the CDP and DOSE programs, incorporate the most recent global tidal models developed from Topex/Poscidon data, and also local tide models for regions around North America; the design of the algorithm and software makes it straightforward to combine local and global models.
-
Genetic Algorithms and Local Search
NASA Technical Reports Server (NTRS)
Whitley, Darrell
1996-01-01
The first part of this presentation is a tutorial level introduction to the principles of genetic search and models of simple genetic algorithms. The second half covers the combination of genetic algorithms with local search methods to produce hybrid genetic algorithms. Hybrid algorithms can be modeled within the existing theoretical framework developed for simple genetic algorithms. An application of a hybrid to geometric model matching is given. The hybrid algorithm yields results that improve on the current state-of-the-art for this problem.
-
3D model retrieval method based on mesh segmentation
NASA Astrophysics Data System (ADS)
Gan, Yuanchao; Tang, Yan; Zhang, Qingchen
2012-04-01
In the process of feature description and extraction, current 3D model retrieval algorithms focus on the global features of 3D models but ignore the combination of global and local features of the model. For this reason, they show less effective performance to the models with similar global shape and different local shape. This paper proposes a novel algorithm for 3D model retrieval based on mesh segmentation. The key idea is to exact the structure feature and the local shape feature of 3D models, and then to compares the similarities of the two characteristics and the total similarity between the models. A system that realizes this approach was built and tested on a database of 200 objects and achieves expected results. The results show that the proposed algorithm improves the precision and the recall rate effectively.
-
Using spatial mark-recapture for conservation monitoring of grizzly bear populations in Alberta.
Boulanger, John; Nielsen, Scott E; Stenhouse, Gordon B
2018-03-26
One of the challenges in conservation is determining patterns and responses in population density and distribution as it relates to habitat and changes in anthropogenic activities. We applied spatially explicit capture recapture (SECR) methods, combined with density surface modelling from five grizzly bear (Ursus arctos) management areas (BMAs) in Alberta, Canada, to assess SECR methods and to explore factors influencing bear distribution. Here we used models of grizzly bear habitat and mortality risk to test local density associations using density surface modelling. Results demonstrated BMA-specific factors influenced density, as well as the effects of habitat and topography on detections and movements of bears. Estimates from SECR were similar to those from closed population models and telemetry data, but with similar or higher levels of precision. Habitat was most associated with areas of higher bear density in the north, whereas mortality risk was most associated (negatively) with density of bears in the south. Comparisons of the distribution of mortality risk and habitat revealed differences by BMA that in turn influenced local abundance of bears. Combining SECR methods with density surface modelling increases the resolution of mark-recapture methods by directly inferring the effect of spatial factors on regulating local densities of animals.
-
Thermophysical modelling for high-resolution digital terrain models
NASA Astrophysics Data System (ADS)
Pelivan, I.
2018-07-01
A method is presented for efficiently calculating surface temperatures for highly resolved celestial body shapes. A thorough investigation of the necessary conditions leading to reach model convergence shows that the speed of surface temperature convergence depends on factors such as the quality of initial boundary conditions, thermal inertia, illumination conditions, and resolution of the numerical depth grid. The optimization process to shorten the simulation time while increasing or maintaining the accuracy of model results includes the introduction of facet-specific boundary conditions such as pre-computed temperature estimates and pre-evaluated simulation times. The individual facet treatment also allows for assigning other facet-specific properties such as local thermal inertia. The approach outlined in this paper is particularly useful for very detailed digital terrain models in combination with unfavourable illumination conditions such as little-to-no sunlight at all for a period of time as experienced locally on comet 67P/Churyumov-Gerasimenko. Possible science applications include thermal analysis of highly resolved local (landing) sites experiencing seasonal, environment, and lander shadowing. In combination with an appropriate roughness model, the method is very suitable for application to disc-integrated and disc-resolved data. Further applications are seen where the complexity of the task has led to severe shape or thermophysical model simplifications such as in studying surface activity or thermal cracking.
-
Thermophysical modeling for high-resolution digital terrain models
NASA Astrophysics Data System (ADS)
Pelivan, I.
2018-04-01
A method is presented for efficiently calculating surface temperatures for highly resolved celestial body shapes. A thorough investigation of the necessary conditions leading to reach model convergence shows that the speed of surface temperature convergence depends on factors such as the quality of initial boundary conditions, thermal inertia, illumination conditions, and resolution of the numerical depth grid. The optimization process to shorten the simulation time while increasing or maintaining the accuracy of model results includes the introduction of facet-specific boundary conditions such as pre-computed temperature estimates and pre-evaluated simulation times. The individual facet treatment also allows for assigning other facet-specific properties such as local thermal inertia. The approach outlined in this paper is particularly useful for very detailed digital terrain models in combination with unfavorable illumination conditions such as little to no sunlight at all for a period of time as experienced locally on comet 67P/Churyumov-Gerasimenko. Possible science applications include thermal analysis of highly resolved local (landing) sites experiencing seasonal, environment and lander shadowing. In combination with an appropriate roughness model, the method is very suitable for application to disk-integrated and disk-resolved data. Further applications are seen where the complexity of the task has led to severe shape or thermophysical model simplifications such as in studying surface activity or thermal cracking.
-
Enhancing Air Pollution Exposure Assessment in the 21st Century by Measurement and Modeling
Exposure assessments may be conducted using measurement data, modeling results, or through a combination of measurements and models. Models are required to estimate exposure when measurement data is insufficient due to spatial or temporal gaps (e.g., for refined local scale asses...
-
A Particle Swarm Optimization-Based Approach with Local Search for Predicting Protein Folding.
Yang, Cheng-Hong; Lin, Yu-Shiun; Chuang, Li-Yeh; Chang, Hsueh-Wei
2017-10-01
The hydrophobic-polar (HP) model is commonly used for predicting protein folding structures and hydrophobic interactions. This study developed a particle swarm optimization (PSO)-based algorithm combined with local search algorithms; specifically, the high exploration PSO (HEPSO) algorithm (which can execute global search processes) was combined with three local search algorithms (hill-climbing algorithm, greedy algorithm, and Tabu table), yielding the proposed HE-L-PSO algorithm. By using 20 known protein structures, we evaluated the performance of the HE-L-PSO algorithm in predicting protein folding in the HP model. The proposed HE-L-PSO algorithm exhibited favorable performance in predicting both short and long amino acid sequences with high reproducibility and stability, compared with seven reported algorithms. The HE-L-PSO algorithm yielded optimal solutions for all predicted protein folding structures. All HE-L-PSO-predicted protein folding structures possessed a hydrophobic core that is similar to normal protein folding.
-
Modular GIS Framework for National Scale Hydrologic and Hydraulic Modeling Support
NASA Astrophysics Data System (ADS)
Djokic, D.; Noman, N.; Kopp, S.
2015-12-01
Geographic information systems (GIS) have been extensively used for pre- and post-processing of hydrologic and hydraulic models at multiple scales. An extensible GIS-based framework was developed for characterization of drainage systems (stream networks, catchments, floodplain characteristics) and model integration. The framework is implemented as a set of free, open source, Python tools and builds on core ArcGIS functionality and uses geoprocessing capabilities to ensure extensibility. Utilization of COTS GIS core capabilities allows immediate use of model results in a variety of existing online applications and integration with other data sources and applications.The poster presents the use of this framework to downscale global hydrologic models to local hydraulic scale and post process the hydraulic modeling results and generate floodplains at any local resolution. Flow forecasts from ECMWF or WRF-Hydro are downscaled and combined with other ancillary data for input into the RAPID flood routing model. RAPID model results (stream flow along each reach) are ingested into a GIS-based scale dependent stream network database for efficient flow utilization and visualization over space and time. Once the flows are known at localized reaches, the tools can be used to derive the floodplain depth and extent for each time step in the forecast at any available local resolution. If existing rating curves are available they can be used to relate the flow to the depth of flooding, or synthetic rating curves can be derived using the tools in the toolkit and some ancillary data/assumptions. The results can be published as time-enabled spatial services to be consumed by web applications that use floodplain information as an input. Some of the existing online presentation templates can be easily combined with available online demographic and infrastructure data to present the impact of the potential floods on the local community through simple, end user products. This framework has been successfully used in both the data rich environments as well as in locales with minimum available spatial and hydrographic data.
-
Freedman, Adam H; Buermann, Wolfgang; Lebreton, Matthew; Chirio, Laurent; Smith, Thomas B
2009-02-01
We used a species-distribution modeling approach, ground-based climate data sets, and newly available remote-sensing data on vegetation from the MODIS and Quick Scatterometer sensors to investigate the combined effects of human-caused habitat alterations and climate on potential invasions of rainforest by 3 savanna snake species in Cameroon, Central Africa: the night adder (Causus maculatus), olympic lined snake (Dromophis lineatus), and African house snake (Lamprophis fuliginosus). Models with contemporary climate variables and localities from native savanna habitats showed that the current climate in undisturbed rainforest was unsuitable for any of the snake species due to high precipitation. Limited availability of thermally suitable nest sites and mismatches between important life-history events and prey availability are a likely explanation for the predicted exclusion from undisturbed rainforest. Models with only MODIS-derived vegetation variables and savanna localities predicted invasion in disturbed areas within the rainforest zone, which suggests that human removal of forest cover creates suitable microhabitats that facilitate invasions into rainforest. Models with a combination of contemporary climate, MODIS- and Quick Scatterometer-derived vegetation variables, and forest and savanna localities predicted extensive invasion into rainforest caused by rainforest loss. In contrast, a projection of the present-day species-climate envelope on future climate suggested a reduction in invasion potential within the rainforest zone as a consequence of predicted increases in precipitation. These results emphasize that the combined responses of deforestation and climate change will likely be complex in tropical rainforest systems.
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Semple, Scott; Harry, Vanessa N. MRCOG.; Parkin, David E.
2009-10-01
Purpose: To investigate the combination of pharmacokinetic and radiologic assessment of dynamic contrast-enhanced magnetic resonance imaging (MRI) as an early response indicator in women receiving chemoradiation for advanced cervical cancer. Methods and Materials: Twenty women with locally advanced cervical cancer were included in a prospective cohort study. Dynamic contrast-enhanced MRI was carried out before chemoradiation, after 2 weeks of therapy, and at the conclusion of therapy using a 1.5-T MRI scanner. Radiologic assessment of uptake parameters was obtained from resultant intensity curves. Pharmacokinetic analysis using a multicompartment model was also performed. General linear modeling was used to combine radiologic andmore » pharmacokinetic parameters and correlated with eventual response as determined by change in MRI tumor size and conventional clinical response. A subgroup of 11 women underwent repeat pretherapy MRI to test pharmacokinetic reproducibility. Results: Pretherapy radiologic parameters and pharmacokinetic K{sup trans} correlated with response (p < 0.01). General linear modeling demonstrated that a combination of radiologic and pharmacokinetic assessments before therapy was able to predict more than 88% of variance of response. Reproducibility of pharmacokinetic modeling was confirmed. Conclusions: A combination of radiologic assessment with pharmacokinetic modeling applied to dynamic MRI before the start of chemoradiation improves the predictive power of either by more than 20%. The potential improvements in therapy response prediction using this type of combined analysis of dynamic contrast-enhanced MRI may aid in the development of more individualized, effective therapy regimens for this patient group.« less
-
NASA Astrophysics Data System (ADS)
Valtierra, Robert Daniel
Passive acoustic localization has benefited from many major developments and has become an increasingly important focus point in marine mammal research. Several challenges still remain. This work seeks to address several of these challenges such as tracking the calling depths of baleen whales. In this work, data from an array of widely spaced Marine Acoustic Recording Units (MARUs) was used to achieve three dimensional localization by combining the methods Time Difference of Arrival (TDOA) and Direct-Reflected Time Difference of Arrival (DRTD) along with a newly developed autocorrelation technique. TDOA was applied to data for two dimensional (latitude and longitude) localization and depth was resolved using DRTD. Previously, DRTD had been limited to pulsed broadband signals, such as sperm whale or dolphin echolocation, where individual direct and reflected signals are separated in time. Due to the length of typical baleen whale vocalizations, individual multipath signal arrivals can overlap making time differences of arrival difficult to resolve. This problem can be solved using an autocorrelation, which can extract reflection information from overlapping signals. To establish this technique, a derivation was made to model the autocorrelation of a direct signal and its overlapping reflection. The model was exploited to derive performance limits allowing for prediction of the minimum resolvable direct-reflected time difference for a known signal type. The dependence on signal parameters (sweep rate, call duration) was also investigated. The model was then verified using both recorded and simulated data from two analysis cases for North Atlantic right whales (NARWs, Eubalaena glacialis) and humpback whales (Megaptera noveaengliae). The newly developed autocorrelation technique was then combined with DRTD and tested using data from playback transmissions to localize an acoustic transducer at a known depth and location. The combined DRTD-autocorrelation methods enabled calling depth and range estimations of a vocalizing NARW and humpback whale in two separate cases. The DRTD-autocorrelation method was then combined with TDOA to create a three dimensional track of a NARW in the Stellwagen Bank National Marine Sanctuary. Results from these experiments illustrated the potential of the combined methods to successfully resolve baleen calling depths in three dimensions.
-
Nam, Vu Thanh; van Kuijk, Marijke; Anten, Niels P R
2016-01-01
Allometric regression models are widely used to estimate tropical forest biomass, but balancing model accuracy with efficiency of implementation remains a major challenge. In addition, while numerous models exist for aboveground mass, very few exist for roots. We developed allometric equations for aboveground biomass (AGB) and root biomass (RB) based on 300 (of 45 species) and 40 (of 25 species) sample trees respectively, in an evergreen forest in Vietnam. The biomass estimations from these local models were compared to regional and pan-tropical models. For AGB we also compared local models that distinguish functional types to an aggregated model, to assess the degree of specificity needed in local models. Besides diameter at breast height (DBH) and tree height (H), wood density (WD) was found to be an important parameter in AGB models. Existing pan-tropical models resulted in up to 27% higher estimates of AGB, and overestimated RB by nearly 150%, indicating the greater accuracy of local models at the plot level. Our functional group aggregated local model which combined data for all species, was as accurate in estimating AGB as functional type specific models, indicating that a local aggregated model is the best choice for predicting plot level AGB in tropical forests. Finally our study presents the first allometric biomass models for aboveground and root biomass in forests in Vietnam.
-
Nam, Vu Thanh; van Kuijk, Marijke; Anten, Niels P. R.
2016-01-01
Allometric regression models are widely used to estimate tropical forest biomass, but balancing model accuracy with efficiency of implementation remains a major challenge. In addition, while numerous models exist for aboveground mass, very few exist for roots. We developed allometric equations for aboveground biomass (AGB) and root biomass (RB) based on 300 (of 45 species) and 40 (of 25 species) sample trees respectively, in an evergreen forest in Vietnam. The biomass estimations from these local models were compared to regional and pan-tropical models. For AGB we also compared local models that distinguish functional types to an aggregated model, to assess the degree of specificity needed in local models. Besides diameter at breast height (DBH) and tree height (H), wood density (WD) was found to be an important parameter in AGB models. Existing pan-tropical models resulted in up to 27% higher estimates of AGB, and overestimated RB by nearly 150%, indicating the greater accuracy of local models at the plot level. Our functional group aggregated local model which combined data for all species, was as accurate in estimating AGB as functional type specific models, indicating that a local aggregated model is the best choice for predicting plot level AGB in tropical forests. Finally our study presents the first allometric biomass models for aboveground and root biomass in forests in Vietnam. PMID:27309718
-
Causal learning with local computations.
Fernbach, Philip M; Sloman, Steven A
2009-05-01
The authors proposed and tested a psychological theory of causal structure learning based on local computations. Local computations simplify complex learning problems via cues available on individual trials to update a single causal structure hypothesis. Structural inferences from local computations make minimal demands on memory, require relatively small amounts of data, and need not respect normative prescriptions as inferences that are principled locally may violate those principles when combined. Over a series of 3 experiments, the authors found (a) systematic inferences from small amounts of data; (b) systematic inference of extraneous causal links; (c) influence of data presentation order on inferences; and (d) error reduction through pretraining. Without pretraining, a model based on local computations fitted data better than a Bayesian structural inference model. The data suggest that local computations serve as a heuristic for learning causal structure. Copyright 2009 APA, all rights reserved.
-
Concerted action of IFN-α and IFN-λ induces local NK cell immunity and halts cancer growth.
Lasfar, Ahmed; de laTorre, Andrew; Abushahba, Walid; Cohen-Solal, Karine A; Castaneda, Ismael; Yuan, Yao; Reuhl, Kenneth; Zloza, Andrew; Raveche, Elizabeth; Laskin, Debra L; Kotenko, Sergei V
2016-08-02
Hepatocellular carcinoma (HCC) is the most prevalent type of liver cancer. No significant improvement has been reported with currently available systemic therapies. IFN-α has been tested in both clinic and animal models and only moderate benefits have been observed. In animal models, similar modest antitumor efficacy has also been reported for IFN-λ, a new type of IFN that acts through its own receptor complex. In the present study, the antitumor efficacy of the combination of IFN-α and IFN-λ was tested in the BNL mouse hepatoma model. This study was accomplished by using either engineered tumor cells (IFN-α/IFN-λ gene therapy) or by directly injecting tumor-bearing mice with IFN-α/IFN-λ. Both approaches demonstrated that IFN-α/IFN-λ combination therapy was more efficacious than IFN monotherapy based on either IFN-α or IFN-λ. In complement to tumor surgery, IFN-α/IFN-λ combination induced complete tumor remission. Highest antitumor efficacy has been obtained following local administration of IFN-α/IFN-λ combination at the tumor site that was associated with strong NK cells tumor infiltration. This supports the use of IFN-α/IFN-λ combination as a new cancer immunotherapy for stimulating antitumor response after cancer surgery.
-
Concerted action of IFN-α and IFN-λ induces local NK cell immunity and halts cancer growth
Lasfar, Ahmed; de la Torre, Andrew; Abushahba, Walid; Cohen-Solal, Karine A; Castaneda, Ismael; Yuan, Yao; Reuhl, Kenneth; Zloza, Andrew; Raveche, Elizabeth; Laskin, Debra L; Kotenko, Sergei V
2016-01-01
Hepatocellular carcinoma (HCC) is the most prevalent type of liver cancer. No significant improvement has been reported with currently available systemic therapies. IFN-α has been tested in both clinic and animal models and only moderate benefits have been observed. In animal models, similar modest antitumor efficacy has also been reported for IFN-λ, a new type of IFN that acts through its own receptor complex. In the present study, the antitumor efficacy of the combination of IFN-α and IFN-λ was tested in the BNL mouse hepatoma model. This study was accomplished by using either engineered tumor cells (IFN-α/IFN-λ gene therapy) or by directly injecting tumor-bearing mice with IFN-α/IFN-λ. Both approaches demonstrated that IFN-α/IFN-λ combination therapy was more efficacious than IFN monotherapy based on either IFN-α or IFN-λ. In complement to tumor surgery, IFN-α/IFN-λ combination induced complete tumor remission. Highest antitumor efficacy has been obtained following local administration of IFN-α/IFN-λ combination at the tumor site that was associated with strong NK cells tumor infiltration. This supports the use of IFN-α/IFN-λ combination as a new cancer immunotherapy for stimulating antitumor response after cancer surgery. PMID:27363032
-
Unsupervised Indoor Localization Based on Smartphone Sensors, iBeacon and Wi-Fi.
Chen, Jing; Zhang, Yi; Xue, Wei
2018-04-28
In this paper, we propose UILoc, an unsupervised indoor localization scheme that uses a combination of smartphone sensors, iBeacons and Wi-Fi fingerprints for reliable and accurate indoor localization with zero labor cost. Firstly, compared with the fingerprint-based method, the UILoc system can build a fingerprint database automatically without any site survey and the database will be applied in the fingerprint localization algorithm. Secondly, since the initial position is vital to the system, UILoc will provide the basic location estimation through the pedestrian dead reckoning (PDR) method. To provide accurate initial localization, this paper proposes an initial localization module, a weighted fusion algorithm combined with a k-nearest neighbors (KNN) algorithm and a least squares algorithm. In UILoc, we have also designed a reliable model to reduce the landmark correction error. Experimental results show that the UILoc can provide accurate positioning, the average localization error is about 1.1 m in the steady state, and the maximum error is 2.77 m.
-
2017-01-01
This paper summarises key advances and priorities since the 2011 presentation of the Malaria Eradication Research Agenda (malERA), with a focus on the combinations of intervention tools and strategies for elimination and their evaluation using modelling approaches. With an increasing number of countries embarking on malaria elimination programmes, national and local decisions to select combinations of tools and deployment strategies directed at malaria elimination must address rapidly changing transmission patterns across diverse geographic areas. However, not all of these approaches can be systematically evaluated in the field. Thus, there is potential for modelling to investigate appropriate ‘packages’ of combined interventions that include various forms of vector control, case management, surveillance, and population-based approaches for different settings, particularly at lower transmission levels. Modelling can help prioritise which intervention packages should be tested in field studies, suggest which intervention package should be used at a particular level or stratum of transmission intensity, estimate the risk of resurgence when scaling down specific interventions after local transmission is interrupted, and evaluate the risk and impact of parasite drug resistance and vector insecticide resistance. However, modelling intervention package deployment against a heterogeneous transmission background is a challenge. Further validation of malaria models should be pursued through an iterative process, whereby field data collected with the deployment of intervention packages is used to refine models and make them progressively more relevant for assessing and predicting elimination outcomes. PMID:29190295
-
Combining global and local approximations
NASA Technical Reports Server (NTRS)
Haftka, Raphael T.
1991-01-01
A method based on a linear approximation to a scaling factor, designated the 'global-local approximation' (GLA) method, is presented and shown capable of extending the range of usefulness of derivative-based approximations to a more refined model. The GLA approach refines the conventional scaling factor by means of a linearly varying, rather than constant, scaling factor. The capabilities of the method are demonstrated for a simple beam example with a crude and more refined FEM model.
-
Surface Gravity Data Contribution to the Puerto Rico and U.S. Virgin Islands Geoid Model
NASA Astrophysics Data System (ADS)
Li, X.; Gerhards, C.; Holmes, S. A.; Saleh, J.; Shaw, B.
2015-12-01
The Gravity for the Redefinition of the American Vertical Datum (GRAV-D) project provides updated local gravity field information for the XGEOID15 models. In particular, its airborne gravity data in the area of Puerto Rico and U.S. Virgin Islands (PRVI) made substantial improvements (~60%) on the precision of the geoid models at the local GNSS/Leveling bench marks in the target area. Fortunately, PRVI is free of the huge systematic error in the North American Vertical Datum of 1988 (NAVD88). Thus, the airborne contribution was evaluated more realistically. In addition, the airborne data picked up more detailed gravity field information in the medium wavelength band (spherical harmonic degree 200 to 600) that are largely beyond the resolution of the current satellite missions, especially along the nearby ocean trench areas. Under this circumstance (significant airborne contributions in the medium band), local surface gravity data need to be examined more carefully than before during merging with the satellite and airborne information for local geoid improvement, especially considering the well-known systematic problems in the NGS historical gravity holdings (Saleh et al 2013 JoG). Initial tests showed that it is very important to maintain high consistency between the surface data sets and the airborne enhanced reference model. In addition, a new aggregation method (Gerhards 2014, Inverse Problems) will also be tested to optimally combine the local surface data with the reference model. The data cleaning and combining procedures in the target area will be summarized here as reference for future applications.
-
NASA Astrophysics Data System (ADS)
Klees, R.; Slobbe, D. C.; Farahani, H. H.
2018-04-01
The paper is about a methodology to combine a noisy satellite-only global gravity field model (GGM) with other noisy datasets to estimate a local quasi-geoid model using weighted least-squares techniques. In this way, we attempt to improve the quality of the estimated quasi-geoid model and to complement it with a full noise covariance matrix for quality control and further data processing. The methodology goes beyond the classical remove-compute-restore approach, which does not account for the noise in the satellite-only GGM. We suggest and analyse three different approaches of data combination. Two of them are based on a local single-scale spherical radial basis function (SRBF) model of the disturbing potential, and one is based on a two-scale SRBF model. Using numerical experiments, we show that a single-scale SRBF model does not fully exploit the information in the satellite-only GGM. We explain this by a lack of flexibility of a single-scale SRBF model to deal with datasets of significantly different bandwidths. The two-scale SRBF model performs well in this respect, provided that the model coefficients representing the two scales are estimated separately. The corresponding methodology is developed in this paper. Using the statistics of the least-squares residuals and the statistics of the errors in the estimated two-scale quasi-geoid model, we demonstrate that the developed methodology provides a two-scale quasi-geoid model, which exploits the information in all datasets.
-
Applications of hybrid genetic algorithms in seismic tomography
NASA Astrophysics Data System (ADS)
Soupios, Pantelis; Akca, Irfan; Mpogiatzis, Petros; Basokur, Ahmet T.; Papazachos, Constantinos
2011-11-01
Almost all earth sciences inverse problems are nonlinear and involve a large number of unknown parameters, making the application of analytical inversion methods quite restrictive. In practice, most analytical methods are local in nature and rely on a linearized form of the problem equations, adopting an iterative procedure which typically employs partial derivatives in order to optimize the starting (initial) model by minimizing a misfit (penalty) function. Unfortunately, especially for highly non-linear cases, the final model strongly depends on the initial model, hence it is prone to solution-entrapment in local minima of the misfit function, while the derivative calculation is often computationally inefficient and creates instabilities when numerical approximations are used. An alternative is to employ global techniques which do not rely on partial derivatives, are independent of the misfit form and are computationally robust. Such methods employ pseudo-randomly generated models (sampling an appropriately selected section of the model space) which are assessed in terms of their data-fit. A typical example is the class of methods known as genetic algorithms (GA), which achieves the aforementioned approximation through model representation and manipulations, and has attracted the attention of the earth sciences community during the last decade, with several applications already presented for several geophysical problems. In this paper, we examine the efficiency of the combination of the typical regularized least-squares and genetic methods for a typical seismic tomography problem. The proposed approach combines a local (LOM) and a global (GOM) optimization method, in an attempt to overcome the limitations of each individual approach, such as local minima and slow convergence, respectively. The potential of both optimization methods is tested and compared, both independently and jointly, using the several test models and synthetic refraction travel-time date sets that employ the same experimental geometry, wavelength and geometrical characteristics of the model anomalies. Moreover, real data from a crosswell tomographic project for the subsurface mapping of an ancient wall foundation are used for testing the efficiency of the proposed algorithm. The results show that the combined use of both methods can exploit the benefits of each approach, leading to improved final models and producing realistic velocity models, without significantly increasing the required computation time.
-
One Shot Detection with Laplacian Object and Fast Matrix Cosine Similarity.
Biswas, Sujoy Kumar; Milanfar, Peyman
2016-03-01
One shot, generic object detection involves searching for a single query object in a larger target image. Relevant approaches have benefited from features that typically model the local similarity patterns. In this paper, we combine local similarity (encoded by local descriptors) with a global context (i.e., a graph structure) of pairwise affinities among the local descriptors, embedding the query descriptors into a low dimensional but discriminatory subspace. Unlike principal components that preserve global structure of feature space, we actually seek a linear approximation to the Laplacian eigenmap that permits us a locality preserving embedding of high dimensional region descriptors. Our second contribution is an accelerated but exact computation of matrix cosine similarity as the decision rule for detection, obviating the computationally expensive sliding window search. We leverage the power of Fourier transform combined with integral image to achieve superior runtime efficiency that allows us to test multiple hypotheses (for pose estimation) within a reasonably short time. Our approach to one shot detection is training-free, and experiments on the standard data sets confirm the efficacy of our model. Besides, low computation cost of the proposed (codebook-free) object detector facilitates rather straightforward query detection in large data sets including movie videos.
-
Control of a simulated arm using a novel combination of Cerebellar learning mechanisms
NASA Technical Reports Server (NTRS)
Assad, C.; Hartmann, M.; Paulin, M. G.
2001-01-01
We present a model of cerebellar cortex that combines two types of learning: feedforward predicitve association based on local Hebbian-type learning between granule cell ascending branch and parallel fiber inputs, and reinforcement learning with feedback error correction based on climbing fiber activity.
-
Unofficial Road Building in the Brazilian Amazon: Dilemmas and Models for Road Governance
NASA Technical Reports Server (NTRS)
Perz, Stephen G.; Overdevest, Christine; Caldas, Marcellus M.; Walker, Robert T.; Arima, Eugenio Y.
2007-01-01
Unofficial roads form dense networks in landscapes, generating a litany of negative ecological outcomes, but unofficial roads in frontier areas are also instrumental in local livelihoods and community development. This trade-off poses dilemmas for the governance of unofficial roads. Unofficial road building in frontier areas of the Brazilian Amazon illustrates the challenges of 'road governance.' Both state-based and community based governance models exhibit important liabilities for governing unofficial roads. Whereas state-based governance has experienced difficulties in adapting to specific local contexts and interacting effectively with local interest groups, community-based governance has a mixed record owing to social inequalities and conflicts among local interest groups. A state-community hybrid model may offer more effective governance of unofficial road building by combining the oversight capacity of the state with locally grounded community management via participatory decision-making.
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ohkubo, Yu; Department of Radiation Oncology, Gunma University Graduate School of Medicine, Maebashi; Iwakawa, Mayumi, E-mail: mayumii@nirs.go.j
2010-12-01
Purpose: Our previous report indicated that carbon ion beam irradiation upregulated membrane-associated immunogenic molecules, underlining the potential clinical application of radioimmunotherapy. The antimetastatic efficacy of local combination therapy of carbon ion radiotherapy and immunotherapy was examined by use of an in vivo murine model. Methods and Materials: Tumors of mouse squamous cell carcinoma (NR-S1) cells inoculated in the legs of C3H/HeSlc mice were locally irradiated with a single 6-Gy dose of carbon ions (290 MeV/nucleon, 6-cm spread-out Bragg peak). Thirty-six hours after irradiation, {alpha}-galactosylceramide-pulsed dendritic cells (DCs) were injected into the leg tumor. We investigated the effects on distant lungmore » metastases by counting the numbers of lung tumor colonies, making pathologic observations, and assessing immunohistochemistry. Results: The mice with no treatment (control) presented with 168 {+-} 53.8 metastatic nodules in the lungs, whereas the mice that received the combination therapy of carbon ion irradiation and DCs presented with 2.6 {+-} 1.9 (P = 0.009) at 2 weeks after irradiation. Immunohistochemistry showed that intracellular adhesion molecule 1, which activates DCs, increased from 6 h to 36 h after irradiation in the local tumors of the carbon ion-irradiated group. The expression of S100A8 in lung tissue, a marker of the lung pre-metastatic phase, was decreased only in the group with a combination of carbon ions and DCs. Conclusions: The combination of carbon ion radiotherapy with the injection of {alpha}-galactosylceramide-pulsed DCs into the primary tumor effectively inhibited distant lung metastases.« less
-
Population-based human exposure models predict the distribution of personal exposures to pollutants of outdoor origin using a variety of inputs, including: air pollution concentrations; human activity patterns, such as the amount of time spent outdoors vs. indoors, commuting, wal...
-
Combination of surface and borehole seismic data for robust target-oriented imaging
NASA Astrophysics Data System (ADS)
Liu, Yi; van der Neut, Joost; Arntsen, Børge; Wapenaar, Kees
2016-05-01
A novel application of seismic interferometry (SI) and Marchenko imaging using both surface and borehole data is presented. A series of redatuming schemes is proposed to combine both data sets for robust deep local imaging in the presence of velocity uncertainties. The redatuming schemes create a virtual acquisition geometry where both sources and receivers lie at the horizontal borehole level, thus only a local velocity model near the borehole is needed for imaging, and erroneous velocities in the shallow area have no effect on imaging around the borehole level. By joining the advantages of SI and Marchenko imaging, a macrovelocity model is no longer required and the proposed schemes use only single-component data. Furthermore, the schemes result in a set of virtual data that have fewer spurious events and internal multiples than previous virtual source redatuming methods. Two numerical examples are shown to illustrate the workflow and to demonstrate the benefits of the method. One is a synthetic model and the other is a realistic model of a field in the North Sea. In both tests, improved local images near the boreholes are obtained using the redatumed data without accurate velocities, because the redatumed data are close to the target.
-
Mihailovic, Dragutin T; Alapaty, Kiran; Podrascanin, Zorica
2009-03-01
Improving the parameterization of processes in the atmospheric boundary layer (ABL) and surface layer, in air quality and chemical transport models. To do so, an asymmetrical, convective, non-local scheme, with varying upward mixing rates is combined with the non-local, turbulent, kinetic energy scheme for vertical diffusion (COM). For designing it, a function depending on the dimensionless height to the power four in the ABL is suggested, which is empirically derived. Also, we suggested a new method for calculating the in-canopy resistance for dry deposition over a vegetated surface. The upward mixing rate forming the surface layer is parameterized using the sensible heat flux and the friction and convective velocities. Upward mixing rates varying with height are scaled with an amount of turbulent kinetic energy in layer, while the downward mixing rates are derived from mass conservation. The vertical eddy diffusivity is parameterized using the mean turbulent velocity scale that is obtained by the vertical integration within the ABL. In-canopy resistance is calculated by integration of inverse turbulent transfer coefficient inside the canopy from the effective ground roughness length to the canopy source height and, further, from its the canopy height. This combination of schemes provides a less rapid mass transport out of surface layer into other layers, during convective and non-convective periods, than other local and non-local schemes parameterizing mixing processes in the ABL. The suggested method for calculating the in-canopy resistance for calculating the dry deposition over a vegetated surface differs remarkably from the commonly used one, particularly over forest vegetation. In this paper, we studied the performance of a non-local, turbulent, kinetic energy scheme for vertical diffusion combined with a non-local, convective mixing scheme with varying upward mixing in the atmospheric boundary layer (COM) and its impact on the concentration of pollutants calculated with chemical and air-quality models. In addition, this scheme was also compared with a commonly used, local, eddy-diffusivity scheme. Simulated concentrations of NO2 by the COM scheme and new parameterization of the in-canopy resistance are closer to the observations when compared to those obtained from using the local eddy-diffusivity scheme. Concentrations calculated with the COM scheme and new parameterization of in-canopy resistance, are in general higher and closer to the observations than those obtained by the local, eddy-diffusivity scheme (on the order of 15-22%). To examine the performance of the scheme, simulated and measured concentrations of a pollutant (NO2) were compared for the years 1999 and 2002. The comparison was made for the entire domain used in simulations performed by the chemical European Monitoring and Evaluation Program Unified model (version UNI-ACID, rv2.0) where schemes were incorporated.
-
Models, Measurements, and Local Decisions: Assessing and ...
This presentation includes a combination of modeling and measurement results to characterize near-source air quality in Newark, New Jersey with consideration of how this information could be used to inform decision making to reduce risk of health impacts. Decisions could include either exposure or emissions reduction, and a host of stakeholders, including residents, academics, NGOs, local and federal agencies. This presentation includes results from the C-PORT modeling system, and from a citizen science project from the local area. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.
-
Locality of the Thomas-Fermi-von Weizsäcker Equations
NASA Astrophysics Data System (ADS)
Nazar, F. Q.; Ortner, C.
2017-06-01
We establish a pointwise stability estimate for the Thomas-Fermi-von Weiz-säcker (TFW) model, which demonstrates that a local perturbation of a nuclear arrangement results also in a local response in the electron density and electrostatic potential. The proof adapts the arguments for existence and uniqueness of solutions to the TFW equations in the thermodynamic limit by Catto et al. (The mathematical theory of thermodynamic limits: Thomas-Fermi type models. Oxford mathematical monographs. The Clarendon Press, Oxford University Press, New York, 1998). To demonstrate the utility of this combined locality and stability result we derive several consequences, including an exponential convergence rate for the thermodynamic limit, partition of total energy into exponentially localised site energies (and consequently, exponential locality of forces), and generalised and strengthened results on the charge neutrality of local defects.
-
Wu, Tsung-Meng; Lin, Ke-Chun; Liau, Wei-Shiang; Chao, Yun-Yang; Yang, Ling-Hung; Chen, Szu-Yun; Lu, Chung-An; Hong, Chwan-Yang
2016-01-01
In the post-genomic era, many useful tools have been developed to accelerate the investigation of gene functions. Fluorescent proteins have been widely used as protein tags for studying the subcellular localization of proteins in plants. Several fluorescent organelle marker lines have been generated in dicot plants; however, useful and reliable fluorescent organelle marker lines are lacking in the monocot model rice. Here, we developed eight different GFP-based organelle markers in transgenic rice and created a set of DsRed-based gateway vectors for combining with the marker lines. Two mitochondrial-localized rice ascorbate peroxidase genes fused to DsRed and successfully co-localized with mitochondrial-targeted marker lines verified the practical use of this system. The co-localization of GFP-fusion marker lines and DsRed-fusion proteins provide a convenient platform for in vivo or in vitro analysis of subcellular localization of rice proteins.
-
Laarne, P H; Tenhunen-Eskelinen, M L; Hyttinen, J K; Eskola, H J
2000-01-01
The effect of number of EEG electrodes on the dipole localization was studied by comparing the results obtained using the 10-20 and 10-10 electrode systems. Two anatomically detailed models with resistivity values of 177.6 omega m and 67.0 omega m for the skull were applied. Simulated potential values generated by current dipoles were applied to different combinations of the volume conductors and electrode systems. High and low resistivity models differed slightly in favour of the lower skull resistivity model when dipole localization was based on noiseless data. The localization errors were approximately three times larger using low resistivity model for generating the potentials, but applying high resistivity model for the inverse solution. The difference between the two electrode systems was minor in favour of the 10-10 electrode system when simulated, noiseless potentials were used. In the presence of noise the dipole localization algorithm operated more accurately using the denser electrode system. In conclusion, increasing the number of recording electrodes seems to improve the localization accuracy in the presence of noise. The absolute skull resistivity value also affects the accuracy, but using an incorrect value in modelling calculations seems to be the most serious source of error.
-
NASA Astrophysics Data System (ADS)
Barretta, Raffaele; Fabbrocino, Francesco; Luciano, Raimondo; Sciarra, Francesco Marotti de
2018-03-01
Strain-driven and stress-driven integral elasticity models are formulated for the analysis of the structural behaviour of fuctionally graded nano-beams. An innovative stress-driven two-phases constitutive mixture defined by a convex combination of local and nonlocal phases is presented. The analysis reveals that the Eringen strain-driven fully nonlocal model cannot be used in Structural Mechanics since it is ill-posed and the local-nonlocal mixtures based on the Eringen integral model partially resolve the ill-posedeness of the model. In fact, a singular behaviour of continuous nano-structures appears if the local fraction tends to vanish so that the ill-posedness of the Eringen integral model is not eliminated. On the contrary, local-nonlocal mixtures based on the stress-driven theory are mathematically and mechanically appropriate for nanosystems. Exact solutions of inflected functionally graded nanobeams of technical interest are established by adopting the new local-nonlocal mixture stress-driven integral relation. Effectiveness of the new nonlocal approach is tested by comparing the contributed results with the ones corresponding to the mixture Eringen theory.
-
Medial-based deformable models in nonconvex shape-spaces for medical image segmentation.
McIntosh, Chris; Hamarneh, Ghassan
2012-01-01
We explore the application of genetic algorithms (GA) to deformable models through the proposition of a novel method for medical image segmentation that combines GA with nonconvex, localized, medial-based shape statistics. We replace the more typical gradient descent optimizer used in deformable models with GA, and the convex, implicit, global shape statistics with nonconvex, explicit, localized ones. Specifically, we propose GA to reduce typical deformable model weaknesses pertaining to model initialization, pose estimation and local minima, through the simultaneous evolution of a large number of models. Furthermore, we constrain the evolution, and thus reduce the size of the search-space, by using statistically-based deformable models whose deformations are intuitive (stretch, bulge, bend) and are driven in terms of localized principal modes of variation, instead of modes of variation across the entire shape that often fail to capture localized shape changes. Although GA are not guaranteed to achieve the global optima, our method compares favorably to the prevalent optimization techniques, convex/nonconvex gradient-based optimizers and to globally optimal graph-theoretic combinatorial optimization techniques, when applied to the task of corpus callosum segmentation in 50 mid-sagittal brain magnetic resonance images.
-
Hematopoiesis Primer Modeling Combined Injury
2012-05-01
wall (Nachman and Rafii 2008). With thrombocytopenia, vascular permeability increases allowing local movement of erythrocytes into the tissue which...Gottingen minipigs, humans, and other large animal models. PLoS One. 2011; 6(9):e25210. Epub 2011 Sep 28. Nachman R.L., S. Rafii . Platelets, petechiae
-
Directional Hearing and Sound Source Localization in Fishes.
Sisneros, Joseph A; Rogers, Peter H
2016-01-01
Evidence suggests that the capacity for sound source localization is common to mammals, birds, reptiles, and amphibians, but surprisingly it is not known whether fish locate sound sources in the same manner (e.g., combining binaural and monaural cues) or what computational strategies they use for successful source localization. Directional hearing and sound source localization in fishes continues to be important topics in neuroethology and in the hearing sciences, but the empirical and theoretical work on these topics have been contradictory and obscure for decades. This chapter reviews the previous behavioral work on directional hearing and sound source localization in fishes including the most recent experiments on sound source localization by the plainfin midshipman fish (Porichthys notatus), which has proven to be an exceptional species for fish studies of sound localization. In addition, the theoretical models of directional hearing and sound source localization for fishes are reviewed including a new model that uses a time-averaged intensity approach for source localization that has wide applicability with regard to source type, acoustic environment, and time waveform.
-
Hybrid epidemics--a case study on computer worm conficker.
Zhang, Changwang; Zhou, Shi; Chain, Benjamin M
2015-01-01
Conficker is a computer worm that erupted on the Internet in 2008. It is unique in combining three different spreading strategies: local probing, neighbourhood probing, and global probing. We propose a mathematical model that combines three modes of spreading: local, neighbourhood, and global, to capture the worm's spreading behaviour. The parameters of the model are inferred directly from network data obtained during the first day of the Conficker epidemic. The model is then used to explore the tradeoff between spreading modes in determining the worm's effectiveness. Our results show that the Conficker epidemic is an example of a critically hybrid epidemic, in which the different modes of spreading in isolation do not lead to successful epidemics. Such hybrid spreading strategies may be used beneficially to provide the most effective strategies for promulgating information across a large population. When used maliciously, however, they can present a dangerous challenge to current internet security protocols.
-
Hybrid Epidemics—A Case Study on Computer Worm Conficker
Zhang, Changwang; Zhou, Shi; Chain, Benjamin M.
2015-01-01
Conficker is a computer worm that erupted on the Internet in 2008. It is unique in combining three different spreading strategies: local probing, neighbourhood probing, and global probing. We propose a mathematical model that combines three modes of spreading: local, neighbourhood, and global, to capture the worm’s spreading behaviour. The parameters of the model are inferred directly from network data obtained during the first day of the Conficker epidemic. The model is then used to explore the tradeoff between spreading modes in determining the worm’s effectiveness. Our results show that the Conficker epidemic is an example of a critically hybrid epidemic, in which the different modes of spreading in isolation do not lead to successful epidemics. Such hybrid spreading strategies may be used beneficially to provide the most effective strategies for promulgating information across a large population. When used maliciously, however, they can present a dangerous challenge to current internet security protocols. PMID:25978309
-
Prediction of high-energy radiation belt electron fluxes using a combined VERB-NARMAX model
NASA Astrophysics Data System (ADS)
Pakhotin, I. P.; Balikhin, M. A.; Shprits, Y.; Subbotin, D.; Boynton, R.
2013-12-01
This study is concerned with the modelling and forecasting of energetic electron fluxes that endanger satellites in space. By combining data-driven predictions from the NARMAX methodology with the physics-based VERB code, it becomes possible to predict electron fluxes with a high level of accuracy and across a radial distance from inside the local acceleration region to out beyond geosynchronous orbit. The model coupling also makes is possible to avoid accounting for seed electron variations at the outer boundary. Conversely, combining a convection code with the VERB and NARMAX models has the potential to provide even greater accuracy in forecasting that is not limited to geostationary orbit but makes predictions across the entire outer radiation belt region.
-
NASA Astrophysics Data System (ADS)
Sun, Xiao; Chai, Guobei; Liu, Wei; Bao, Wenzhuo; Zhao, Xiaoning; Ming, Delie
2018-02-01
Simple cells in primary visual cortex are believed to extract local edge information from a visual scene. In this paper, inspired by different receptive field properties and visual information flow paths of neurons, an improved Combination of Receptive Fields (CORF) model combined with non-classical receptive fields was proposed to simulate the responses of simple cell's receptive fields. Compared to the classical model, the proposed model is able to better imitate simple cell's physiologic structure with consideration of facilitation and suppression of non-classical receptive fields. And on this base, an edge detection algorithm as an application of the improved CORF model was proposed. Experimental results validate the robustness of the proposed algorithm to noise and background interference.
-
Kulkarni, Yogesh M.; Chambers, Emily; McGray, A. J. Robert; Ware, Jason S.; Bramson, Jonathan L.
2012-01-01
Interleukin-12 (IL12) enhances anti-tumor immunity when delivered to the tumor microenvironment. However, local immunoregulatory elements dampen the efficacy of IL12. The identity of these local mechanisms used by tumors to suppress immunosurveillance represents a key knowledge gap for improving tumor immunotherapy. From a systems perspective, local suppression of anti-tumor immunity is a closed-loop system - where system response is determined by an unknown combination of external inputs and local cellular cross-talk. Here, we recreated this closed-loop system in vitro and combined quantitative high content assays, in silico model-based inference, and a proteomic workflow to identify the biochemical cues responsible for immunosuppression. Following an induction period, the B16 melanoma cell model, a transplantable model for spontaneous malignant melanoma, inhibited the response of a T helper cell model to IL12. This paracrine effect was not explained by induction of apoptosis or creation of a cytokine sink, despite both mechanisms present within the co-culture assay. Tumor-derived Wnt-inducible signaling protein-1 (WISP-1) was identified to exert paracrine action on immune cells by inhibiting their response to IL12. Moreover, WISP-1 was expressed in vivo following intradermal challenge with B16F10 cells and was inferred to be expressed at the tumor periphery. Collectively, the data suggest that (1) biochemical cues associated with epithelial-to-mesenchymal transition can shape anti-tumor immunity through paracrine action and (2) remnants of the immunoselective pressure associated with evolution in cancer include both sculpting of tumor antigens and expression of proteins that proactively shape anti-tumor immunity. PMID:22777646
-
A design for a dynamic biomimetic sonarhead inspired by horseshoe bats.
Caspers, Philip; Mueller, Rolf
2018-05-24
The noseleaf and pinnae of horseshoe bats (Rhinolophus ferrumequinum) have both been shown to actively deform during biosonar operation. Since these baffle structures directly affect the properties of the animal's biosonar system, this work mimics horseshoe bat sonar system with the goal of developing a platform to study the dynamic sensing principles horseshoe bats employ. Consequently, two robotic devices were developed to mimic the dynamic emission and reception characteristics of horseshoe bats. The noseleaf and pinnae shapes were modeled as smooth blanks matched to digital representations of a horseshoe bat specimen's noseleaf and pinnae. Local shape features mimicking structures on the pinnae and noseleaf were added digitally. Flexible baffles with local shape feature combinations were manufactured and paired with actuation mechanisms to mimic pinnae and noseleaf deformations in-vivo. Two noseleaves with and without local shape features were considered. Each noseleaf baffle was mounted to a platform called the dynamic emission head to actuate three surface elements of the baffle. Similarly, 12 pinna realizations composed of combinations of three local shape features were mounted to a platform called the dynamic reception head to deform the left and right pinnae independently. Motion of the noseleaf and pinnae were synchronized to the incoming and outgoing sonar waveform, and the joint time-frequency properties of the noseleaf and pinnae local feature combinations and combinations of the pinnae and noseleaf thereof were characterized across spatial direction. Amplitude modulations to the outgoing and incoming sonar pulse information across spatial direction were observed for all pinnae and noseleaf local shape feature combinations. Peak modulation variance generated by motion of the pinnae and combinations of the noseleaf and pinnae approached a white Gaussian noise variance bound. However, it was found the dynamic emitter generated less modulation than either the combined or reception scenarios. © 2018 IOP Publishing Ltd.
-
Efficient Actor-Critic Algorithm with Hierarchical Model Learning and Planning
Fu, QiMing
2016-01-01
To improve the convergence rate and the sample efficiency, two efficient learning methods AC-HMLP and RAC-HMLP (AC-HMLP with ℓ 2-regularization) are proposed by combining actor-critic algorithm with hierarchical model learning and planning. The hierarchical models consisting of the local and the global models, which are learned at the same time during learning of the value function and the policy, are approximated by local linear regression (LLR) and linear function approximation (LFA), respectively. Both the local model and the global model are applied to generate samples for planning; the former is used only if the state-prediction error does not surpass the threshold at each time step, while the latter is utilized at the end of each episode. The purpose of taking both models is to improve the sample efficiency and accelerate the convergence rate of the whole algorithm through fully utilizing the local and global information. Experimentally, AC-HMLP and RAC-HMLP are compared with three representative algorithms on two Reinforcement Learning (RL) benchmark problems. The results demonstrate that they perform best in terms of convergence rate and sample efficiency. PMID:27795704
-
Efficient Actor-Critic Algorithm with Hierarchical Model Learning and Planning.
Zhong, Shan; Liu, Quan; Fu, QiMing
2016-01-01
To improve the convergence rate and the sample efficiency, two efficient learning methods AC-HMLP and RAC-HMLP (AC-HMLP with ℓ 2 -regularization) are proposed by combining actor-critic algorithm with hierarchical model learning and planning. The hierarchical models consisting of the local and the global models, which are learned at the same time during learning of the value function and the policy, are approximated by local linear regression (LLR) and linear function approximation (LFA), respectively. Both the local model and the global model are applied to generate samples for planning; the former is used only if the state-prediction error does not surpass the threshold at each time step, while the latter is utilized at the end of each episode. The purpose of taking both models is to improve the sample efficiency and accelerate the convergence rate of the whole algorithm through fully utilizing the local and global information. Experimentally, AC-HMLP and RAC-HMLP are compared with three representative algorithms on two Reinforcement Learning (RL) benchmark problems. The results demonstrate that they perform best in terms of convergence rate and sample efficiency.
-
Assimilation of SMOS (and SMAP) Retrieved Soil Moisture into the Land Information System
NASA Technical Reports Server (NTRS)
Blankenship, Clay; Zavodsky, Bradley; Case, Jonathan; Stano, Geoffrey
2016-01-01
Goal: Accurate, high-resolution (approx.3 km) soil moisture in near-real time. Situational awareness (drought assessment, flood and fire threat). Local modeling applications (to improve sfc-PBL exchanges) Method: Assimilate satellite soil moisture retrievals into a land surface model. Combines high-resolution geophysical model data with latest satellite observations.
-
This presentation explains the importance of the fine-scale features for air toxics exposure modeling. The paper presents a new approach to combine local-scale and regional model results for the National Air Toxic Assessment. The technique has been evaluated with a chemical tra...
-
Modeling of grain boundary stresses in Alloy 600
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kozaczek, K.J.; Sinharoy, A.; Ruud, C.O.
1995-04-01
Corrosive environments combined with high stress levels and susceptible microstructures can cause intergranular stress corrosion cracking (IGSCC) of Alloy 600 components on both primary and secondary sides of pressurized water reactors. One factor affecting the IGSCC is intergranular carbide precipitation controlled by heat treatment of Alloy 600. This study is concerned with analysis of elastic stress fields in vicinity of M{sub 7}C{sub 3} and M{sub 23}C{sub 6} carbides precipitated in the matrix and at a grain boundary triple point. The local stress concentration which can lead to IGSCC initiation was studied using a two-dimensional finite element model. The intergranular precipitatesmore » are more effective stress raisers than the intragranular precipitates. The combination of the elastic property mismatch and the precipitate shape can result in a local stress field substantially different than the macroscopic stress. The maximum local stresses in the vicinity of the intergranular precipitate were almost twice as high as the applied stress.« less
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Krishnamoorthy, Sriram; Daily, Jeffrey A.; Vishnu, Abhinav
2015-11-01
Global Arrays (GA) is a distributed-memory programming model that allows for shared-memory-style programming combined with one-sided communication, to create a set of tools that combine high performance with ease-of-use. GA exposes a relatively straightforward programming abstraction, while supporting fully-distributed data structures, locality of reference, and high-performance communication. GA was originally formulated in the early 1990’s to provide a communication layer for the Northwest Chemistry (NWChem) suite of chemistry modeling codes that was being developed concurrently.
-
Improving IMES Localization Accuracy by Integrating Dead Reckoning Information
Fujii, Kenjiro; Arie, Hiroaki; Wang, Wei; Kaneko, Yuto; Sakamoto, Yoshihiro; Schmitz, Alexander; Sugano, Shigeki
2016-01-01
Indoor positioning remains an open problem, because it is difficult to achieve satisfactory accuracy within an indoor environment using current radio-based localization technology. In this study, we investigate the use of Indoor Messaging System (IMES) radio for high-accuracy indoor positioning. A hybrid positioning method combining IMES radio strength information and pedestrian dead reckoning information is proposed in order to improve IMES localization accuracy. For understanding the carrier noise ratio versus distance relation for IMES radio, the signal propagation of IMES radio is modeled and identified. Then, trilateration and extended Kalman filtering methods using the radio propagation model are developed for position estimation. These methods are evaluated through robot localization and pedestrian localization experiments. The experimental results show that the proposed hybrid positioning method achieved average estimation errors of 217 and 1846 mm in robot localization and pedestrian localization, respectively. In addition, in order to examine the reason for the positioning accuracy of pedestrian localization being much lower than that of robot localization, the influence of the human body on the radio propagation is experimentally evaluated. The result suggests that the influence of the human body can be modeled. PMID:26828492
-
Jarnevich, Catherine S.; Young, Nicholas E.; Talbert, Marian; Talbert, Colin
2018-01-01
Understanding invasive species distributions and potential invasions often requires broad‐scale information on the environmental tolerances of the species. Further, resource managers are often faced with knowing these broad‐scale relationships as well as nuanced environmental factors related to their landscape that influence where an invasive species occurs and potentially could occur. Using invasive buffelgrass (Cenchrus ciliaris), we developed global models and local models for Saguaro National Park, Arizona, USA, based on location records and literature on physiological tolerances to environmental factors to investigate whether environmental relationships of a species at a global scale are also important at local scales. In addition to correlative models with five commonly used algorithms, we also developed a model using a priori user‐defined relationships between occurrence and environmental characteristics based on a literature review. All correlative models at both scales performed well based on statistical evaluations. The user‐defined curves closely matched those produced by the correlative models, indicating that the correlative models may be capturing mechanisms driving the distribution of buffelgrass. Given climate projections for the region, both global and local models indicate that conditions at Saguaro National Park may become more suitable for buffelgrass. Combining global and local data with correlative models and physiological information provided a holistic approach to forecasting invasive species distributions.
-
Structurally Dynamic Spin Market Networks
NASA Astrophysics Data System (ADS)
Horváth, Denis; Kuscsik, Zoltán
The agent-based model of stock price dynamics on a directed evolving complex network is suggested and studied by direct simulation. The stationary regime is maintained as a result of the balance between the extremal dynamics, adaptivity of strategic variables and reconnection rules. The inherent structure of node agent "brain" is modeled by a recursive neural network with local and global inputs and feedback connections. For specific parametric combination the complex network displays small-world phenomenon combined with scale-free behavior. The identification of a local leader (network hub, agent whose strategies are frequently adapted by its neighbors) is carried out by repeated random walk process through network. The simulations show empirically relevant dynamics of price returns and volatility clustering. The additional emerging aspects of stylized market statistics are Zipfian distributions of fitness.
-
NASA Astrophysics Data System (ADS)
Tommasino, F.
2016-03-01
This review will summarize results obtained in the recent years applying the Local Effect Model (LEM) approach to the study of basic radiobiological aspects, as for instance DNA damage induction and repair, and charged particle track structure. The promising results obtained using different experimental techniques and looking at different biological end points, support the relevance of the LEM approach for the description of radiation effects induced by both low- and high-LET radiation. Furthermore, they suggest that nowadays the appropriate combination of experimental and modelling tools can lead to advances in the understanding of several open issues in the field of radiation biology.
-
NASA Astrophysics Data System (ADS)
Tironi, Antonio; Marin, Víctor H.; Campuzano, Francisco J.
2010-05-01
This article introduces a management tool for salmon farming, with a scope in the local sustainability of salmon aquaculture of the Aysen Fjord, Chilean Patagonia. Based on Integrated Coastal Zone Management (ICZM) principles, the tool combines a large 3-level nested hydrodynamic model, a particle tracking module and a GIS application into an assessment tool for particulate waste dispersal of salmon farming activities. The model offers an open source alternative to particulate waste modeling and evaluation, contributing with valuable information for local decision makers in the process of locating new facilities and monitoring stations.
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gu, Z.; Ching, W.Y.
Based on the Sterne-Inkson model for the self-energy correction to the single-particle energy in the local-density approximation (LDA), we have implemented an approximate energy-dependent and [bold k]-dependent [ital GW] correction scheme to the orthogonalized linear combination of atomic orbital-based local-density calculation for insulators. In contrast to the approach of Jenkins, Srivastava, and Inkson, we evaluate the on-site exchange integrals using the LDA Bloch functions throughout the Brillouin zone. By using a [bold k]-weighted band gap [ital E][sub [ital g
-
NASA Astrophysics Data System (ADS)
Jiang, Jingtao; Sui, Rendong; Shi, Yan; Li, Furong; Hu, Caiqi
In this paper 3-D models of combined fixture elements are designed, classified by their functions, and saved in computer as supporting elements library, jointing elements library, basic elements library, localization elements library, clamping elements library, and adjusting elements library etc. Then automatic assembly of 3-D combined checking fixture for auto-body part is presented based on modularization theory. And in virtual auto-body assembly space, Locating constraint mapping technique and assembly rule-based reasoning technique are used to calculate the position of modular elements according to localization points and clamp points of auto-body part. Auto-body part model is transformed from itself coordinate system space to virtual assembly space by homogeneous transformation matrix. Automatic assembly of different functional fixture elements and auto-body part is implemented with API function based on the second development of UG. It is proven in practice that the method in this paper is feasible and high efficiency.
-
Tellado, Matias; Olaiz, Nahuel; Michinski, Sebastian; Marshall, Guillermo
2016-01-01
Background Electrochemotherapy (ECT), a medical treatment widely used in human patients for tumor treatment, increases bleomycin toxicity by 1000 fold in the treated area with an objective response rate of around 80%. Despite its high response rate, there are still 20% of cases in which the patients are not responding. This could be ascribed to the fact that bleomycin, when administered systemically, is not reaching the whole tumor mass properly because of the characteristics of tumor vascularization, in which case local administration could cover areas that are unreachable by systemic administration. Patients and methods We propose combined bleomycin administration, both systemic and local, using companion animals as models. We selected 22 canine patients which failed to achieve a complete response after an ECT treatment session. Eleven underwent another standard ECT session (control group), while 11 received a combined local and systemic administration of bleomycin in the second treatment session. Results According to the WHO criteria, the response rates in the combined administration group were: complete response (CR) 54% (6), partial response (PR) 36% (4), stable disease (SD) 10% (1). In the control group, these were: CR 0% (0), PR 19% (2), SD 63% (7), progressive disease (PD) 18% (2). In the combined group 91% objective responses (CR+PR) were obtained. In the control group 19% objective responses were obtained. The difference in the response rate between the treatment groups was significant (p < 0.01). Conclusions Combined local and systemic bleomycin administration was effective in previously to ECT non responding canine patients. The results indicate that this approach could be useful and effective in specific population of patients and reduce the number of treatment sessions needed to obtain an objective response. PMID:27069450
-
Liu, Dan; Liu, Xuejun; Wu, Yiguang
2018-04-24
This paper presents an effective approach for depth reconstruction from a single image through the incorporation of semantic information and local details from the image. A unified framework for depth acquisition is constructed by joining a deep Convolutional Neural Network (CNN) and a continuous pairwise Conditional Random Field (CRF) model. Semantic information and relative depth trends of local regions inside the image are integrated into the framework. A deep CNN network is firstly used to automatically learn a hierarchical feature representation of the image. To get more local details in the image, the relative depth trends of local regions are incorporated into the network. Combined with semantic information of the image, a continuous pairwise CRF is then established and is used as the loss function of the unified model. Experiments on real scenes demonstrate that the proposed approach is effective and that the approach obtains satisfactory results.
-
Wu, Bitao; Lu, Huaxi; Chen, Bo; Gao, Zhicheng
2017-01-01
A finite model updating method that combines dynamic-static long-gauge strain responses is proposed for highway bridge static loading tests. For this method, the objective function consisting of static long-gauge stains and the first order modal macro-strain parameter (frequency) is established, wherein the local bending stiffness, density and boundary conditions of the structures are selected as the design variables. The relationship between the macro-strain and local element stiffness was studied first. It is revealed that the macro-strain is inversely proportional to the local stiffness covered by the long-gauge strain sensor. This corresponding relation is important for the modification of the local stiffness based on the macro-strain. The local and global parameters can be simultaneously updated. Then, a series of numerical simulation and experiments were conducted to verify the effectiveness of the proposed method. The results show that the static deformation, macro-strain and macro-strain modal can be predicted well by using the proposed updating model. PMID:28753912
-
Wu, Bitao; Lu, Huaxi; Chen, Bo; Gao, Zhicheng
2017-07-19
A finite model updating method that combines dynamic-static long-gauge strain responses is proposed for highway bridge static loading tests. For this method, the objective function consisting of static long-gauge stains and the first order modal macro-strain parameter (frequency) is established, wherein the local bending stiffness, density and boundary conditions of the structures are selected as the design variables. The relationship between the macro-strain and local element stiffness was studied first. It is revealed that the macro-strain is inversely proportional to the local stiffness covered by the long-gauge strain sensor. This corresponding relation is important for the modification of the local stiffness based on the macro-strain. The local and global parameters can be simultaneously updated. Then, a series of numerical simulation and experiments were conducted to verify the effectiveness of the proposed method. The results show that the static deformation, macro-strain and macro-strain modal can be predicted well by using the proposed updating model.
-
Hierarchical extreme learning machine based reinforcement learning for goal localization
NASA Astrophysics Data System (ADS)
AlDahoul, Nouar; Zaw Htike, Zaw; Akmeliawati, Rini
2017-03-01
The objective of goal localization is to find the location of goals in noisy environments. Simple actions are performed to move the agent towards the goal. The goal detector should be capable of minimizing the error between the predicted locations and the true ones. Few regions need to be processed by the agent to reduce the computational effort and increase the speed of convergence. In this paper, reinforcement learning (RL) method was utilized to find optimal series of actions to localize the goal region. The visual data, a set of images, is high dimensional unstructured data and needs to be represented efficiently to get a robust detector. Different deep Reinforcement models have already been used to localize a goal but most of them take long time to learn the model. This long learning time results from the weights fine tuning stage that is applied iteratively to find an accurate model. Hierarchical Extreme Learning Machine (H-ELM) was used as a fast deep model that doesn’t fine tune the weights. In other words, hidden weights are generated randomly and output weights are calculated analytically. H-ELM algorithm was used in this work to find good features for effective representation. This paper proposes a combination of Hierarchical Extreme learning machine and Reinforcement learning to find an optimal policy directly from visual input. This combination outperforms other methods in terms of accuracy and learning speed. The simulations and results were analysed by using MATLAB.
-
A fingerprint classification algorithm based on combination of local and global information
NASA Astrophysics Data System (ADS)
Liu, Chongjin; Fu, Xiang; Bian, Junjie; Feng, Jufu
2011-12-01
Fingerprint recognition is one of the most important technologies in biometric identification and has been wildly applied in commercial and forensic areas. Fingerprint classification, as the fundamental procedure in fingerprint recognition, can sharply decrease the quantity for fingerprint matching and improve the efficiency of fingerprint recognition. Most fingerprint classification algorithms are based on the number and position of singular points. Because the singular points detecting method only considers the local information commonly, the classification algorithms are sensitive to noise. In this paper, we propose a novel fingerprint classification algorithm combining the local and global information of fingerprint. Firstly we use local information to detect singular points and measure their quality considering orientation structure and image texture in adjacent areas. Furthermore the global orientation model is adopted to measure the reliability of singular points group. Finally the local quality and global reliability is weighted to classify fingerprint. Experiments demonstrate the accuracy and effectivity of our algorithm especially for the poor quality fingerprint images.
-
Liu, Zhiquan; Ma, Jianfeng; Jiang, Zhongyuan; Miao, Yinbin; Gao, Cong
2016-01-01
With the prevalence of Social Networks (SNs) and services, plenty of trust models for Trustworthy Service Recommendation (TSR) in Service-oriented SNs (S-SNs) have been proposed. The reputation-based schemes usually do not contain user preferences and are vulnerable to unfair rating attacks. Meanwhile, the local trust-based schemes generally have low reliability or even fail to work when the trust path is too long or does not exist. Thus it is beneficial to integrate them for TSR in S-SNs. This work improves the state-of-the-art Combining Global and Local Trust (CGLT) scheme and proposes a novel Integrating Reputation and Local Trust (IRLT) model which mainly includes four modules, namely Service Recommendation Interface (SRI) module, Local Trust-based Trust Evaluation (LTTE) module, Reputation-based Trust Evaluation (RTE) module and Aggregation Trust Evaluation (ATE) module. Besides, a synthetic S-SN based on the famous Advogato dataset is deployed and the well-known Discount Cumulative Gain (DCG) metric is employed to measure the service recommendation performance of our IRLT model with comparing to that of the excellent CGLT model. The results illustrate that our IRLT model is slightly superior to the CGLT model in honest environment and significantly outperforms the CGLT model in terms of the robustness against unfair rating attacks. PMID:26963089
-
Liu, Zhiquan; Ma, Jianfeng; Jiang, Zhongyuan; Miao, Yinbin; Gao, Cong
2016-01-01
With the prevalence of Social Networks (SNs) and services, plenty of trust models for Trustworthy Service Recommendation (TSR) in Service-oriented SNs (S-SNs) have been proposed. The reputation-based schemes usually do not contain user preferences and are vulnerable to unfair rating attacks. Meanwhile, the local trust-based schemes generally have low reliability or even fail to work when the trust path is too long or does not exist. Thus it is beneficial to integrate them for TSR in S-SNs. This work improves the state-of-the-art Combining Global and Local Trust (CGLT) scheme and proposes a novel Integrating Reputation and Local Trust (IRLT) model which mainly includes four modules, namely Service Recommendation Interface (SRI) module, Local Trust-based Trust Evaluation (LTTE) module, Reputation-based Trust Evaluation (RTE) module and Aggregation Trust Evaluation (ATE) module. Besides, a synthetic S-SN based on the famous Advogato dataset is deployed and the well-known Discount Cumulative Gain (DCG) metric is employed to measure the service recommendation performance of our IRLT model with comparing to that of the excellent CGLT model. The results illustrate that our IRLT model is slightly superior to the CGLT model in honest environment and significantly outperforms the CGLT model in terms of the robustness against unfair rating attacks.
-
This presentation includes a combination of modeling and measurement results to characterize near-source air quality in Newark, New Jersey with consideration of how this information could be used to inform decision making to reduce risk of health impacts. Decisions could include ...
-
System theoretic models for high density VLSI structures
NASA Astrophysics Data System (ADS)
Dickinson, Bradley W.; Hopkins, William E., Jr.
This research project involved the development of mathematical models for analysis, synthesis, and simulation of large systems of interacting devices. The work was motivated by problems that may become important in high density VLSI chips with characteristic feature sizes less than 1 micron: it is anticipated that interactions of neighboring devices will play an important role in the determination of circuit properties. It is hoped that the combination of high device densities and such local interactions can somehow be exploited to increase circuit speed and to reduce power consumption. To address these issues from the point of view of system theory, research was pursued in the areas of nonlinear and stochastic systems and into neural network models. Statistical models were developed to characterize various features of the dynamic behavior of interacting systems. Random process models for studying the resulting asynchronous modes of operation were investigated. The local interactions themselves may be modeled as stochastic effects. The resulting behavior was investigated through the use of various scaling limits, and by a combination of other analytical and simulation techniques. Techniques arising in a variety of disciplines where models of interaction were formulated and explored were considered and adapted for use.
-
Three-dimensional deformable-model-based localization and recognition of road vehicles.
Zhang, Zhaoxiang; Tan, Tieniu; Huang, Kaiqi; Wang, Yunhong
2012-01-01
We address the problem of model-based object recognition. Our aim is to localize and recognize road vehicles from monocular images or videos in calibrated traffic scenes. A 3-D deformable vehicle model with 12 shape parameters is set up as prior information, and its pose is determined by three parameters, which are its position on the ground plane and its orientation about the vertical axis under ground-plane constraints. An efficient local gradient-based method is proposed to evaluate the fitness between the projection of the vehicle model and image data, which is combined into a novel evolutionary computing framework to estimate the 12 shape parameters and three pose parameters by iterative evolution. The recovery of pose parameters achieves vehicle localization, whereas the shape parameters are used for vehicle recognition. Numerous experiments are conducted in this paper to demonstrate the performance of our approach. It is shown that the local gradient-based method can evaluate accurately and efficiently the fitness between the projection of the vehicle model and the image data. The evolutionary computing framework is effective for vehicles of different types and poses is robust to all kinds of occlusion.
-
Ko, Junsu; Park, Hahnbeom; Seok, Chaok
2012-08-10
Protein structures can be reliably predicted by template-based modeling (TBM) when experimental structures of homologous proteins are available. However, it is challenging to obtain structures more accurate than the single best templates by either combining information from multiple templates or by modeling regions that vary among templates or are not covered by any templates. We introduce GalaxyTBM, a new TBM method in which the more reliable core region is modeled first from multiple templates and less reliable, variable local regions, such as loops or termini, are then detected and re-modeled by an ab initio method. This TBM method is based on "Seok-server," which was tested in CASP9 and assessed to be amongst the top TBM servers. The accuracy of the initial core modeling is enhanced by focusing on more conserved regions in the multiple-template selection and multiple sequence alignment stages. Additional improvement is achieved by ab initio modeling of up to 3 unreliable local regions in the fixed framework of the core structure. Overall, GalaxyTBM reproduced the performance of Seok-server, with GalaxyTBM and Seok-server resulting in average GDT-TS of 68.1 and 68.4, respectively, when tested on 68 single-domain CASP9 TBM targets. For application to multi-domain proteins, GalaxyTBM must be combined with domain-splitting methods. Application of GalaxyTBM to CASP9 targets demonstrates that accurate protein structure prediction is possible by use of a multiple-template-based approach, and ab initio modeling of variable regions can further enhance the model quality.
-
NASA Astrophysics Data System (ADS)
Sandvig Mariegaard, Jesper; Huiban, Méven Robin; Tornfeldt Sørensen, Jacob; Andersson, Henrik
2017-04-01
Determining the optimal domain size and associated position of open boundaries in local high-resolution downscaling ocean models is often difficult. As an important input data set for downscaling ocean modelling, the European Copernicus Marine Environment Monitoring Service (CMEMS) provides baroclinic initial and boundary conditions for local ocean models. Tidal dynamics is often neglected in CMEMS services at large scale but tides are generally crucial for coastal ocean dynamics. To address this need, tides can be superposed via Flather (1976) boundary conditions and the combined flow downscaled using unstructured mesh. The surge component is also only partially represented in selected CMEMS products and must be modelled inside the domain and modelled independently and superposed if the domain becomes too small to model the effect in the downscaling model. The tide and surge components can generally be improved by assimilating water level from tide gauge and altimetry data. An intrinsic part of the problem is to find the limitations of local scale data assimilation and the requirement for consistency between the larger scale ocean models and the local scale assimilation methodologies. This contribution investigates the impact of domain size and associated positions of open boundaries with and without data assimilation of water level. We have used the baroclinic ocean model, MIKE 3 FM, and its newly re-factored built-in data assimilation package. We consider boundary conditions of salinity, temperature, water level and depth varying currents from the Global CMEMS 1/4 degree resolution model from 2011, where in situ ADCP velocity data is available for validation. We apply data assimilation of in-situ tide gauge water levels and along track altimetry surface elevation data from selected satellites. The MIKE 3 FM data assimilation model which use the Ensemble Kalman filter have recently been parallelized with MPI allowing for much larger applications running on HPC. The success of the downscaling is to a large degree determined by the ability to realistically describe and dynamically model the errors on the open boundaries. Three different sizes of downscaling model domains in the Northern North Sea have been examined and two different strategies for modelling the uncertainties on the open Flather boundaries are investigated. The combined downscaling and local data assimilation skill is assessed and the impact on recommended domain size is compared to pure downscaling.
-
Local facet approximation for image stitching
NASA Astrophysics Data System (ADS)
Li, Jing; Lai, Shiming; Liu, Yu; Wang, Zhengming; Zhang, Maojun
2018-01-01
Image stitching aims at eliminating multiview parallax and generating a seamless panorama given a set of input images. This paper proposes a local adaptive stitching method, which could achieve both accurate and robust image alignments across the whole panorama. A transformation estimation model is introduced by approximating the scene as a combination of neighboring facets. Then, the local adaptive stitching field is constructed using a series of linear systems of the facet parameters, which enables the parallax handling in three-dimensional space. We also provide a concise but effective global projectivity preserving technique that smoothly varies the transformations from local adaptive to global planar. The proposed model is capable of stitching both normal images and fisheye images. The efficiency of our method is quantitatively demonstrated in the comparative experiments on several challenging cases.
-
Gao, Xueping; Liu, Yinzhu; Sun, Bowen
2018-06-05
The risk of water shortage caused by uncertainties, such as frequent drought, varied precipitation, multiple water resources, and different water demands, brings new challenges to the water transfer projects. Uncertainties exist for transferring water and local surface water; therefore, the relationship between them should be thoroughly studied to prevent water shortage. For more effective water management, an uncertainty-based water shortage risk assessment model (UWSRAM) is developed to study the combined effect of multiple water resources and analyze the shortage degree under uncertainty. The UWSRAM combines copula-based Monte Carlo stochastic simulation and the chance-constrained programming-stochastic multiobjective optimization model, using the Lunan water-receiving area in China as an example. Statistical copula functions are employed to estimate the joint probability of available transferring water and local surface water and sampling from the multivariate probability distribution, which are used as inputs for the optimization model. The approach reveals the distribution of water shortage and is able to emphasize the importance of improving and updating transferring water and local surface water management, and examine their combined influence on water shortage risk assessment. The possible available water and shortages can be calculated applying the UWSRAM, also with the corresponding allocation measures under different water availability levels and violating probabilities. The UWSRAM is valuable for mastering the overall multi-water resource and water shortage degree, adapting to the uncertainty surrounding water resources, establishing effective water resource planning policies for managers and achieving sustainable development.
-
Population-based human exposure models predict the distribution of personal exposures to pollutants of outdoor origin using a variety of inputs, including air pollution concentrations; human activity patterns, such as the amount of time spent outdoors versus indoors, commuting, w...
-
Ensemble averaging and stacking of ARIMA and GSTAR model for rainfall forecasting
NASA Astrophysics Data System (ADS)
Anggraeni, D.; Kurnia, I. F.; Hadi, A. F.
2018-04-01
Unpredictable rainfall changes can affect human activities, such as in agriculture, aviation, shipping which depend on weather forecasts. Therefore, we need forecasting tools with high accuracy in predicting the rainfall in the future. This research focus on local forcasting of the rainfall at Jember in 2005 until 2016, from 77 rainfall stations. The rainfall here was not only related to the occurrence of the previous of its stations, but also related to others, it’s called the spatial effect. The aim of this research is to apply the GSTAR model, to determine whether there are some correlations of spatial effect between one to another stations. The GSTAR model is an expansion of the space-time model that combines the time-related effects, the locations (stations) in a time series effects, and also the location it self. The GSTAR model will also be compared to the ARIMA model that completely ignores the independent variables. The forcested value of the ARIMA and of the GSTAR models then being combined using the ensemble forecasting technique. The averaging and stacking method of ensemble forecasting method here provide us the best model with higher acuracy model that has the smaller RMSE (Root Mean Square Error) value. Finally, with the best model we can offer a better local rainfall forecasting in Jember for the future.
-
NASA Astrophysics Data System (ADS)
Delgado, Francisco
2017-12-01
Quantum information is an emergent area merging physics, mathematics, computer science and engineering. To reach its technological goals, it is requiring adequate approaches to understand how to combine physical restrictions, computational approaches and technological requirements to get functional universal quantum information processing. This work presents the modeling and the analysis of certain general type of Hamiltonian representing several physical systems used in quantum information and establishing a dynamics reduction in a natural grammar for bipartite processing based on entangled states.
-
NASA Astrophysics Data System (ADS)
Dias, R. G.; Gouveia, J. D.
2015-11-01
We present a method of construction of exact localized many-body eigenstates of the Hubbard model in decorated lattices, both for U = 0 and U → ∞. These states are localized in what concerns both hole and particle movement. The starting point of the method is the construction of a plaquette or a set of plaquettes with a higher symmetry than that of the whole lattice. Using a simple set of rules, the tight-binding localized state in such a plaquette can be divided, folded and unfolded to new plaquette geometries. This set of rules is also valid for the construction of a localized state for one hole in the U → ∞ limit of the same plaquette, assuming a spin configuration which is a uniform linear combination of all possible permutations of the set of spins in the plaquette.
-
Efficient QoS-aware Service Composition
NASA Astrophysics Data System (ADS)
Alrifai, Mohammad; Risse, Thomas
Web service composition requests are usually combined with endto-end QoS requirements, which are specified in terms of non-functional properties (e.g. response time, throughput and price). The goal of QoS-aware service composition is to find the best combination of services such that their aggregated QoS values meet these end-to-end requirements. Local selection techniques are very efficient but fail short in handling global QoS constraints. Global optimization techniques, on the other hand, can handle global constraints, but their poor performance render them inappropriate for applications with dynamic and real-time requirements. In this paper we address this problem and propose a solution that combines global optimization with local selection techniques for achieving a better performance. The proposed solution consists of two steps: first we use mixed integer linear programming (MILP) to find the optimal decomposition of global QoS constraints into local constraints. Second, we use local search to find the best web services that satisfy these local constraints. Unlike existing MILP-based global planning solutions, the size of the MILP model in our case is much smaller and independent on the number of available services, yields faster computation and more scalability. Preliminary experiments have been conducted to evaluate the performance of the proposed solution.
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wada, Satoshi; Harris, Timothy J.; Tryggestad, Erik
2013-11-15
Purpose: To optimize the combination of ionizing radiation and cellular immunotherapy using a preclinical autochthonous model of prostate cancer. Methods and Materials: Transgenic mice expressing a model antigen under a prostate-specific promoter were treated using a platform that integrates cone-beam CT imaging with 3-dimensional conformal therapy. Using this technology we investigated the immunologic and therapeutic effects of combining ionizing radiation with granulocyte/macrophage colony-stimulating factor-secreting cellular immunotherapy for prostate cancer in mice bearing autochthonous prostate tumors. Results: The combination of ionizing radiation and immunotherapy resulted in a significant decrease in pathologic tumor grade and gross tumor bulk that was not evidentmore » with either single-modality therapy. Furthermore, combinatorial therapy resulted in improved overall survival in a preventive metastasis model and in the setting of established micrometastases. Mechanistically, combined therapy resulted in an increase of the ratio of effector-to-regulatory T cells for both CD4 and CD8 tumor-infiltrating lymphocytes. Conclusions: Our preclinical model establishes a potential role for the use of combined radiation-immunotherapy in locally advanced prostate cancer, which warrants further exploration in a clinical setting.« less
-
Ghorbani Moghaddam, Masoud; Achuthan, Ajit; Bednarcyk, Brett A; Arnold, Steven M; Pineda, Evan J
2016-05-04
A multiscale computational model is developed for determining the elasto-plastic behavior of polycrystal metals by employing a single crystal plasticity constitutive model that can capture the microstructural scale stress field on a finite element analysis (FEA) framework. The generalized method of cells (GMC) micromechanics model is used for homogenizing the local field quantities. At first, the stand-alone GMC is applied for studying simple material microstructures such as a repeating unit cell (RUC) containing single grain or two grains under uniaxial loading conditions. For verification, the results obtained by the stand-alone GMC are compared to those from an analogous FEA model incorporating the same single crystal plasticity constitutive model. This verification is then extended to samples containing tens to hundreds of grains. The results demonstrate that the GMC homogenization combined with the crystal plasticity constitutive framework is a promising approach for failure analysis of structures as it allows for properly predicting the von Mises stress in the entire RUC, in an average sense, as well as in the local microstructural level, i.e. , each individual grain. Two-three orders of saving in computational cost, at the expense of some accuracy in prediction, especially in the prediction of the components of local tensor field quantities and the quantities near the grain boundaries, was obtained with GMC. Finally, the capability of the developed multiscale model linking FEA and GMC to solve real-life-sized structures is demonstrated by successfully analyzing an engine disc component and determining the microstructural scale details of the field quantities.
-
Ghorbani Moghaddam, Masoud; Achuthan, Ajit; Bednarcyk, Brett A.; Arnold, Steven M.; Pineda, Evan J.
2016-01-01
A multiscale computational model is developed for determining the elasto-plastic behavior of polycrystal metals by employing a single crystal plasticity constitutive model that can capture the microstructural scale stress field on a finite element analysis (FEA) framework. The generalized method of cells (GMC) micromechanics model is used for homogenizing the local field quantities. At first, the stand-alone GMC is applied for studying simple material microstructures such as a repeating unit cell (RUC) containing single grain or two grains under uniaxial loading conditions. For verification, the results obtained by the stand-alone GMC are compared to those from an analogous FEA model incorporating the same single crystal plasticity constitutive model. This verification is then extended to samples containing tens to hundreds of grains. The results demonstrate that the GMC homogenization combined with the crystal plasticity constitutive framework is a promising approach for failure analysis of structures as it allows for properly predicting the von Mises stress in the entire RUC, in an average sense, as well as in the local microstructural level, i.e., each individual grain. Two–three orders of saving in computational cost, at the expense of some accuracy in prediction, especially in the prediction of the components of local tensor field quantities and the quantities near the grain boundaries, was obtained with GMC. Finally, the capability of the developed multiscale model linking FEA and GMC to solve real-life-sized structures is demonstrated by successfully analyzing an engine disc component and determining the microstructural scale details of the field quantities. PMID:28773458
-
Fatigue crack growth with single overload - Measurement and modeling
NASA Technical Reports Server (NTRS)
Davidson, D. L.; Hudak, S. J., Jr.; Dexter, R. J.
1987-01-01
This paper compares experiments with an analytical model of fatigue crack growth under variable amplitude. The stereoimaging technique was used to measure displacements near the tips of fatigue cracks undergoing simple variations in load amplitude-single overloads and overload/underload combinations. Measured displacements were used to compute strains, and stresses were determined from the strains. Local values of crack driving force (Delta-K effective) were determined using both locally measured opening loads and crack tip opening displacements. Experimental results were compared with simulations made for the same load variation conditions using Newman's FAST-2 model. Residual stresses caused by overloads, crack opening loads, and growth retardation periods were compared.
-
NASA Astrophysics Data System (ADS)
Yang, Weizhu; Yue, Zhufeng; Li, Lei; Wang, Peiyan
2016-01-01
An optimization procedure combining an automated finite element modelling (AFEM) technique with a ground structure approach (GSA) is proposed for structural layout and sizing design of aircraft wings. The AFEM technique, based on CATIA VBA scripting and PCL programming, is used to generate models automatically considering the arrangement of inner systems. GSA is used for local structural topology optimization. The design procedure is applied to a high-aspect-ratio wing. The arrangement of the integral fuel tank, landing gear and control surfaces is considered. For the landing gear region, a non-conventional initial structural layout is adopted. The positions of components, the number of ribs and local topology in the wing box and landing gear region are optimized to obtain a minimum structural weight. Constraints include tank volume, strength, buckling and aeroelastic parameters. The results show that the combined approach leads to a greater weight saving, i.e. 26.5%, compared with three additional optimizations based on individual design approaches.
-
Management Models and Cost Analysis for Regional Special Education Programs.
ERIC Educational Resources Information Center
Connors, Eugene T.
The implementation of the Education for All Handicapped Children Act (PL 94-142) has placed an enormous financial burden on local districts. In order to create special education programs that combine cost effectiveness and high quality, a regional model has been developed. The Therapeutic Residential Experience for Emotional Stability (TREES) in…
-
Balancing building and maintenance costs in growing transport networks
NASA Astrophysics Data System (ADS)
Bottinelli, Arianna; Louf, Rémi; Gherardi, Marco
2017-09-01
The costs associated to the length of links impose unavoidable constraints to the growth of natural and artificial transport networks. When future network developments cannot be predicted, the costs of building and maintaining connections cannot be minimized simultaneously, requiring competing optimization mechanisms. Here, we study a one-parameter nonequilibrium model driven by an optimization functional, defined as the convex combination of building cost and maintenance cost. By varying the coefficient of the combination, the model interpolates between global and local length minimization, i.e., between minimum spanning trees and a local version known as dynamical minimum spanning trees. We show that cost balance within this ensemble of dynamical networks is a sufficient ingredient for the emergence of tradeoffs between the network's total length and transport efficiency, and of optimal strategies of construction. At the transition between two qualitatively different regimes, the dynamics builds up power-law distributed waiting times between global rearrangements, indicating a point of nonoptimality. Finally, we use our model as a framework to analyze empirical ant trail networks, showing its relevance as a null model for cost-constrained network formation.
-
ERIC Educational Resources Information Center
Cao, Yi; Lu, Ru; Tao, Wei
2014-01-01
The local item independence assumption underlying traditional item response theory (IRT) models is often not met for tests composed of testlets. There are 3 major approaches to addressing this issue: (a) ignore the violation and use a dichotomous IRT model (e.g., the 2-parameter logistic [2PL] model), (b) combine the interdependent items to form a…
-
Hybrid Air Quality Modeling Approach For Use in the Near ...
The Near-road EXposures to Urban air pollutant Study (NEXUS) investigated whether children with asthma living in close proximity to major roadways in Detroit, MI, (particularly near roadways with high diesel traffic) have greater health impacts associated with exposure to air pollutants than those living farther away. A major challenge in such health and exposure studies is the lack of information regarding pollutant exposure characterization. Air quality modeling can provide spatially and temporally varying exposure estimates for examining relationships between traffic-related air pollutants and adverse health outcomes. This paper presents a hybrid air quality modeling approach and its application in NEXUS in order to provide spatial and temporally varying exposure estimates and identification of the mobile source contribution to the total pollutant exposure. Model-based exposure metrics, associated with local variations of emissions and meteorology, were estimated using a combination of the AERMOD and R-LINE dispersion models, local emission source information from the National Emissions Inventory, detailed road network locations and traffic activity, and meteorological data from the Detroit City Airport. The regional background contribution was estimated using a combination of the Community Multiscale Air Quality (CMAQ) model and the Space/Time Ordinary Kriging (STOK) model. To capture the near-road pollutant gradients, refined “mini-grids” of model recep
-
Tschechne, Stephan; Neumann, Heiko
2014-01-01
Visual structures in the environment are segmented into image regions and those combined to a representation of surfaces and prototypical objects. Such a perceptual organization is performed by complex neural mechanisms in the visual cortex of primates. Multiple mutually connected areas in the ventral cortical pathway receive visual input and extract local form features that are subsequently grouped into increasingly complex, more meaningful image elements. Such a distributed network of processing must be capable to make accessible highly articulated changes in shape boundary as well as very subtle curvature changes that contribute to the perception of an object. We propose a recurrent computational network architecture that utilizes hierarchical distributed representations of shape features to encode surface and object boundary over different scales of resolution. Our model makes use of neural mechanisms that model the processing capabilities of early and intermediate stages in visual cortex, namely areas V1–V4 and IT. We suggest that multiple specialized component representations interact by feedforward hierarchical processing that is combined with feedback signals driven by representations generated at higher stages. Based on this, global configurational as well as local information is made available to distinguish changes in the object's contour. Once the outline of a shape has been established, contextual contour configurations are used to assign border ownership directions and thus achieve segregation of figure and ground. The model, thus, proposes how separate mechanisms contribute to distributed hierarchical cortical shape representation and combine with processes of figure-ground segregation. Our model is probed with a selection of stimuli to illustrate processing results at different processing stages. We especially highlight how modulatory feedback connections contribute to the processing of visual input at various stages in the processing hierarchy. PMID:25157228
-
Tschechne, Stephan; Neumann, Heiko
2014-01-01
Visual structures in the environment are segmented into image regions and those combined to a representation of surfaces and prototypical objects. Such a perceptual organization is performed by complex neural mechanisms in the visual cortex of primates. Multiple mutually connected areas in the ventral cortical pathway receive visual input and extract local form features that are subsequently grouped into increasingly complex, more meaningful image elements. Such a distributed network of processing must be capable to make accessible highly articulated changes in shape boundary as well as very subtle curvature changes that contribute to the perception of an object. We propose a recurrent computational network architecture that utilizes hierarchical distributed representations of shape features to encode surface and object boundary over different scales of resolution. Our model makes use of neural mechanisms that model the processing capabilities of early and intermediate stages in visual cortex, namely areas V1-V4 and IT. We suggest that multiple specialized component representations interact by feedforward hierarchical processing that is combined with feedback signals driven by representations generated at higher stages. Based on this, global configurational as well as local information is made available to distinguish changes in the object's contour. Once the outline of a shape has been established, contextual contour configurations are used to assign border ownership directions and thus achieve segregation of figure and ground. The model, thus, proposes how separate mechanisms contribute to distributed hierarchical cortical shape representation and combine with processes of figure-ground segregation. Our model is probed with a selection of stimuli to illustrate processing results at different processing stages. We especially highlight how modulatory feedback connections contribute to the processing of visual input at various stages in the processing hierarchy.
-
Combining Distributed and Shared Memory Models: Approach and Evolution of the Global Arrays Toolkit
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nieplocha, Jarek; Harrison, Robert J.; Kumar, Mukul
2002-07-29
Both shared memory and distributed memory models have advantages and shortcomings. Shared memory model is much easier to use but it ignores data locality/placement. Given the hierarchical nature of the memory subsystems in the modern computers this characteristic might have a negative impact on performance and scalability. Various techniques, such as code restructuring to increase data reuse and introducing blocking in data accesses, can address the problem and yield performance competitive with message passing[Singh], however at the cost of compromising the ease of use feature. Distributed memory models such as message passing or one-sided communication offer performance and scalability butmore » they compromise the ease-of-use. In this context, the message-passing model is sometimes referred to as?assembly programming for the scientific computing?. The Global Arrays toolkit[GA1, GA2] attempts to offer the best features of both models. It implements a shared-memory programming model in which data locality is managed explicitly by the programmer. This management is achieved by explicit calls to functions that transfer data between a global address space (a distributed array) and local storage. In this respect, the GA model has similarities to the distributed shared-memory models that provide an explicit acquire/release protocol. However, the GA model acknowledges that remote data is slower to access than local data and allows data locality to be explicitly specified and hence managed. The GA model exposes to the programmer the hierarchical memory of modern high-performance computer systems, and by recognizing the communication overhead for remote data transfer, it promotes data reuse and locality of reference. This paper describes the characteristics of the Global Arrays programming model, capabilities of the toolkit, and discusses its evolution.« less
-
Locally adaptive MR intensity models and MRF-based segmentation of multiple sclerosis lesions
NASA Astrophysics Data System (ADS)
Galimzianova, Alfiia; Lesjak, Žiga; Likar, Boštjan; Pernuš, Franjo; Špiclin, Žiga
2015-03-01
Neuroimaging biomarkers are an important paraclinical tool used to characterize a number of neurological diseases, however, their extraction requires accurate and reliable segmentation of normal and pathological brain structures. For MR images of healthy brains the intensity models of normal-appearing brain tissue (NABT) in combination with Markov random field (MRF) models are known to give reliable and smooth NABT segmentation. However, the presence of pathology, MR intensity bias and natural tissue-dependent intensity variability altogether represent difficult challenges for a reliable estimation of NABT intensity model based on MR images. In this paper, we propose a novel method for segmentation of normal and pathological structures in brain MR images of multiple sclerosis (MS) patients that is based on locally-adaptive NABT model, a robust method for the estimation of model parameters and a MRF-based segmentation framework. Experiments on multi-sequence brain MR images of 27 MS patients show that, compared to whole-brain model and compared to the widely used Expectation-Maximization Segmentation (EMS) method, the locally-adaptive NABT model increases the accuracy of MS lesion segmentation.
-
Comprehensive analytical model for locally contacted rear surface passivated solar cells
NASA Astrophysics Data System (ADS)
Wolf, Andreas; Biro, Daniel; Nekarda, Jan; Stumpp, Stefan; Kimmerle, Achim; Mack, Sebastian; Preu, Ralf
2010-12-01
For optimum performance of solar cells featuring a locally contacted rear surface, the metallization fraction as well as the size and distribution of the local contacts are crucial, since Ohmic and recombination losses have to be balanced. In this work we present a set of equations which enable to calculate this trade off without the need of numerical simulations. Our model combines established analytical and empirical equations to predict the energy conversion efficiency of a locally contacted device. For experimental verification, we fabricate devices from float zone silicon wafers of different resistivity using the laser fired contact technology for forming the local rear contacts. The detailed characterization of test structures enables the determination of important physical parameters, such as the surface recombination velocity at the contacted area and the spreading resistance of the contacts. Our analytical model reproduces the experimental results very well and correctly predicts the optimum contact spacing without the use of free fitting parameters. We use our model to estimate the optimum bulk resistivity for locally contacted devices fabricated from conventional Czochralski-grown silicon material. These calculations use literature values for the stable minority carrier lifetime to account for the bulk recombination caused by the formation of boron-oxygen complexes under carrier injection.
-
Combining Targeted Agents With Modern Radiotherapy in Soft Tissue Sarcomas
Wong, Philip; Houghton, Peter; Kirsch, David G.; Finkelstein, Steven E.; Monjazeb, Arta M.; Xu-Welliver, Meng; Dicker, Adam P.; Ahmed, Mansoor; Vikram, Bhadrasain; Teicher, Beverly A.; Coleman, C. Norman; Machtay, Mitchell; Curran, Walter J.
2014-01-01
Improved understanding of soft-tissue sarcoma (STS) biology has led to better distinction and subtyping of these diseases with the hope of exploiting the molecular characteristics of each subtype to develop appropriately targeted treatment regimens. In the care of patients with extremity STS, adjunctive radiation therapy (RT) is used to facilitate limb and function, preserving surgeries while maintaining five-year local control above 85%. In contrast, for STS originating from nonextremity anatomical sites, the rate of local recurrence is much higher (five-year local control is approximately 50%) and a major cause of death and morbidity in these patients. Incorporating novel technological advancements to administer accurate RT in combination with novel radiosensitizing agents could potentially improve local control and overall survival. RT efficacy in STS can be increased by modulating biological pathways such as angiogenesis, cell cycle regulation, cell survival signaling, and cancer-host immune interactions. Previous experiences, advancements, ongoing research, and current clinical trials combining RT with agents modulating one or more of the above pathways are reviewed. The standard clinical management of patients with STS with pretreatment biopsy, neoadjuvant treatment, and primary surgery provides an opportune disease model for interrogating translational hypotheses. The purpose of this review is to outline a strategic vision for clinical translation of preclinical findings and to identify appropriate targeted agents to combine with radiotherapy in the treatment of STS from different sites and/or different histology subtypes. PMID:25326640
-
Combined effects of prevention and quarantine on a breakout in SIR model.
Kato, Fuminori; Tainaka, Kei-Ichi; Sone, Shogo; Morita, Satoru; Iida, Hiroyuki; Yoshimura, Jin
2011-01-01
Recent breakouts of several epidemics, such as flu pandemics, are serious threats to human health. The measures of protection against these epidemics are urgent issues in epidemiological studies. Prevention and quarantine are two major approaches against disease spreads. We here investigate the combined effects of these two measures of protection using the SIR model. We use site percolation for prevention and bond percolation for quarantine applying on a lattice model. We find a strong synergistic effect of prevention and quarantine under local interactions. A slight increase in protection measures is extremely effective in the initial disease spreads. Combination of the two measures is more effective than a single protection measure. Our results suggest that the protection policy against epidemics should account for both prevention and quarantine measures simultaneously.
-
Ahlfeld, David P.; Baker, Kristine M.; Barlow, Paul M.
2009-01-01
This report describes the Groundwater-Management (GWM) Process for MODFLOW-2005, the 2005 version of the U.S. Geological Survey modular three-dimensional groundwater model. GWM can solve a broad range of groundwater-management problems by combined use of simulation- and optimization-modeling techniques. These problems include limiting groundwater-level declines or streamflow depletions, managing groundwater withdrawals, and conjunctively using groundwater and surface-water resources. GWM was initially released for the 2000 version of MODFLOW. Several modifications and enhancements have been made to GWM since its initial release to increase the scope of the program's capabilities and to improve its operation and reporting of results. The new code, which is called GWM-2005, also was designed to support the local grid refinement capability of MODFLOW-2005. Local grid refinement allows for the simulation of one or more higher resolution local grids (referred to as child models) within a coarser grid parent model. Local grid refinement is often needed to improve simulation accuracy in regions where hydraulic gradients change substantially over short distances or in areas requiring detailed representation of aquifer heterogeneity. GWM-2005 can be used to formulate and solve groundwater-management problems that include components in both parent and child models. Although local grid refinement increases simulation accuracy, it can also substantially increase simulation run times.
-
NASA Astrophysics Data System (ADS)
Rittgers, J. B.; Revil, A.; Planes, T.; Mooney, M. A.; Koelewijn, A. R.
2015-02-01
New methods are required to combine the information contained in the passive electrical and seismic signals to detect, localize and monitor hydromechanical disturbances in porous media. We propose a field experiment showing how passive seismic and electrical data can be combined together to detect a preferential flow path associated with internal erosion in a Earth dam. Continuous passive seismic and electrical (self-potential) monitoring data were recorded during a 7-d full-scale levee (earthen embankment) failure test, conducted in Booneschans, Netherlands in 2012. Spatially coherent acoustic emissions events and the development of a self-potential anomaly, associated with induced concentrated seepage and internal erosion phenomena, were identified and imaged near the downstream toe of the embankment, in an area that subsequently developed a series of concentrated water flows and sand boils, and where liquefaction of the embankment toe eventually developed. We present a new 4-D grid-search algorithm for acoustic emissions localization in both time and space, and the application of the localization results to add spatially varying constraints to time-lapse 3-D modelling of self-potential data in the terms of source current localization. Seismic signal localization results are utilized to build a set of time-invariant yet spatially varying model weights used for the inversion of the self-potential data. Results from the combination of these two passive techniques show results that are more consistent in terms of focused ground water flow with respect to visual observation on the embankment. This approach to geophysical monitoring of earthen embankments provides an improved approach for early detection and imaging of the development of embankment defects associated with concentrated seepage and internal erosion phenomena. The same approach can be used to detect various types of hydromechanical disturbances at larger scales.
-
Wavepacket dynamics in one-dimensional system with long-range correlated disorder
NASA Astrophysics Data System (ADS)
Yamada, Hiroaki S.
2018-03-01
We numerically investigate dynamical property in the one-dimensional tight-binding model with long-range correlated disorder having power spectrum 1 /fα (α: spectrum exponent) generated by Fourier filtering method. For relatively small α <αc (=2) time-dependence of mean square displacement (MSD) of the initially localized wavepacket shows ballistic spread and localizes as time elapses. It is shown that α-dependence of the dynamical localization length determined by the MSD exhibits a simple scaling law in the localization regime for the relatively weak disorder strength W. Furthermore, scaled MSD by the dynamical localization length almost obeys an universal function from the ballistic to the localization regime in the various combinations of the parameters α and W.
-
NASA Technical Reports Server (NTRS)
Starnes, James H., Jr.; Rose, Cheryl A.; Rankin, Charles C.
1996-01-01
The results of an analytical study of the nonlinear response of stiffened fuselage shells with long cracks are presented. The shells are modeled with a hierarchical modeling strategy and analyzed with a nonlinear shell analysis code that maintains the shell in a nonlinear equilibrium state while the crack is grown. The analysis accurately accounts for global and local structural response phenomena. Results are presented for various combinations of internal pressure and mechanical loads, and the effects of crack orientation on the shell response are described. The effects of combined loading conditions and the effects of varying structural parameters on the stress-intensity factors associated with a crack are presented.
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Subotnik, Joseph E.; Vura-Weis, Josh; Sodt, Alex J.
We model the triplet-triplet energy-transfer experiments from the Closs group [Closs, G. L.; et al. J. Am. Chem. Soc. 1988, 110, 2652.] using a combination of Marcus theory and either Boys or Edmiston-Ruedenberg localized diabatization, and we show that relative and absolute rates of electronic excitation transfer may be computed successfully. For the case where both the donor and acceptor occupy equatorial positions on a rigid cyclohexane bridge, we find βcalc = 2.8 per C-C bond, compared with the experimental value βexp = 2.6. This work highlights the power of using localized diabatization methods as a tool for modeling nonequilibriummore » processes.« less
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Subotnik, Joseph E.; Vura-Weis, Josh; Sodt, Alex J.
We model the triplet-triplet energy-transfer experiments from the Closs group [Closs, G. L.; et al. J. Am. Chem. Soc. 1988, 110, 2652.] using a combination of Marcus theory and either Boys or Edmiston-Ruedenberg localized diabatization, and we show that relative and absolute rates of electronic excitation transfer may be computed successfully. For the case where both the donor and acceptor occupy equatorial positions on a rigid cyclohexane bridge, we find β calc = 2.8 per C-C bond, compared with the experimental value β exp = 2.6. This work highlights the power of using localized diabatization methods as a tool formore » modeling nonequilibrium processes.« less
-
NASA Astrophysics Data System (ADS)
Guegan, Loic; Murad, Nour Mohammad; Bonhommeau, Sylvain
2018-03-01
This paper deals with the modeling of the over sea radio channel and aims to establish sea turtles localization off the coast of Reunion Island, and also on Europa Island in the Mozambique Channel. In order to model this radio channel, a framework measurement protocol is proposed. The over sea measured channel is integrated to the localization algorithm to estimate the turtle trajectory based on Power of Arrival (PoA) technique compared to GPS localization. Moreover, cross correlation tool is used to characterize the over sea propagation channel. First measurement of the radio channel on the Reunion Island coast combine to the POA algorithm show an error of 18 m for 45% of the approximated points.
-
Congested traffic states in empirical observations and microscopic simulations
NASA Astrophysics Data System (ADS)
Treiber, Martin; Hennecke, Ansgar; Helbing, Dirk
2000-08-01
We present data from several German freeways showing different kinds of congested traffic forming near road inhomogeneities, specifically lane closings, intersections, or uphill gradients. The states are localized or extended, homogeneous or oscillating. Combined states are observed as well, like the coexistence of moving localized clusters and clusters pinned at road inhomogeneities, or regions of oscillating congested traffic upstream of nearly homogeneous congested traffic. The experimental findings are consistent with a recently proposed theoretical phase diagram for traffic near on-ramps [D. Helbing, A. Hennecke, and M. Treiber, Phys. Rev. Lett. 82, 4360 (1999)]. We simulate these situations with a continuous microscopic single-lane model, the ``intelligent driver model,'' using empirical boundary conditions. All observations, including the coexistence of states, are qualitatively reproduced by describing inhomogeneities with local variations of one model parameter. We show that the results of the microscopic model can be understood by formulating the theoretical phase diagram for bottlenecks in a more general way. In particular, a local drop of the road capacity induced by parameter variations has essentially the same effect as an on-ramp.
-
Matched field localization based on CS-MUSIC algorithm
NASA Astrophysics Data System (ADS)
Guo, Shuangle; Tang, Ruichun; Peng, Linhui; Ji, Xiaopeng
2016-04-01
The problem caused by shortness or excessiveness of snapshots and by coherent sources in underwater acoustic positioning is considered. A matched field localization algorithm based on CS-MUSIC (Compressive Sensing Multiple Signal Classification) is proposed based on the sparse mathematical model of the underwater positioning. The signal matrix is calculated through the SVD (Singular Value Decomposition) of the observation matrix. The observation matrix in the sparse mathematical model is replaced by the signal matrix, and a new concise sparse mathematical model is obtained, which means not only the scale of the localization problem but also the noise level is reduced; then the new sparse mathematical model is solved by the CS-MUSIC algorithm which is a combination of CS (Compressive Sensing) method and MUSIC (Multiple Signal Classification) method. The algorithm proposed in this paper can overcome effectively the difficulties caused by correlated sources and shortness of snapshots, and it can also reduce the time complexity and noise level of the localization problem by using the SVD of the observation matrix when the number of snapshots is large, which will be proved in this paper.
-
An ear punch model for studying the effect of radiation on wound healing.
Deoliveira, Divino; Jiao, Yiqun; Ross, Joel R; Corbin, Kayla; Xiao, Qizhen; Toncheva, Greta; Anderson-Evans, Colin; Yoshizumi, Terry T; Chen, Benny J; Chao, Nelson J
2011-08-01
Radiation and wound combined injury represents a major clinical challenge because of the synergistic interactions that lead to higher morbidity and mortality than either insult would produce singly. The purpose of this study was to develop a mouse ear punch model to study the physiological mechanisms underlying radiation effects on healing wounds. Surgical wounds were induced by a 2 mm surgical punch in the ear pinnae of MRL/MpJ mice. Photographs of the wounds were taken and the sizes of the ear punch wounds were quantified by image analysis. Local radiation to the ear was delivered by orthovoltage X-ray irradiator using a specially constructed jig that shields the other parts of body. Using this model, we demonstrated that local radiation to the wound area significantly delayed the healing of ear punch wounds in a dose-dependent fashion. The addition of sublethal whole body irradiation (7 Gy) further delayed the healing of ear punch wounds. These results were replicated in C57BL/6 mice; however, wound healing in MRL/MpJ mice was accelerated. These data indicate that the mouse ear punch model is a valuable model to study radiation and wound combined injury.
-
Dong, Yadong; Sun, Yongqi; Qin, Chao
2018-01-01
The existing protein complex detection methods can be broadly divided into two categories: unsupervised and supervised learning methods. Most of the unsupervised learning methods assume that protein complexes are in dense regions of protein-protein interaction (PPI) networks even though many true complexes are not dense subgraphs. Supervised learning methods utilize the informative properties of known complexes; they often extract features from existing complexes and then use the features to train a classification model. The trained model is used to guide the search process for new complexes. However, insufficient extracted features, noise in the PPI data and the incompleteness of complex data make the classification model imprecise. Consequently, the classification model is not sufficient for guiding the detection of complexes. Therefore, we propose a new robust score function that combines the classification model with local structural information. Based on the score function, we provide a search method that works both forwards and backwards. The results from experiments on six benchmark PPI datasets and three protein complex datasets show that our approach can achieve better performance compared with the state-of-the-art supervised, semi-supervised and unsupervised methods for protein complex detection, occasionally significantly outperforming such methods.
-
Imaging and radiation effects of gold nanoparticles in tumour cells
McQuaid, Harold N.; Muir, Mark F.; Taggart, Laura E.; McMahon, Stephen J.; Coulter, Jonathan A.; Hyland, Wendy B.; Jain, Suneil; Butterworth, Karl T.; Schettino, Giuseppe; Prise, Kevin M.; Hirst, David G.; Botchway, Stanley W.; Currell, Fred J.
2016-01-01
Gold nanoparticle radiosensitization represents a novel technique in enhancement of ionising radiation dose and its effect on biological systems. Variation between theoretical predictions and experimental measurement is significant enough that the mechanism leading to an increase in cell killing and DNA damage is still not clear. We present the first experimental results that take into account both the measured biodistribution of gold nanoparticles at the cellular level and the range of the product electrons responsible for energy deposition. Combining synchrotron-generated monoenergetic X-rays, intracellular gold particle imaging and DNA damage assays, has enabled a DNA damage model to be generated that includes the production of intermediate electrons. We can therefore show for the first time good agreement between the prediction of biological outcomes from both the Local Effect Model and a DNA damage model with experimentally observed cell killing and DNA damage induction via the combination of X-rays and GNPs. However, the requirement of two distinct models as indicated by this mechanistic study, one for short-term DNA damage and another for cell survival, indicates that, at least for nanoparticle enhancement, it is not safe to equate the lethal lesions invoked in the local effect model with DNA damage events. PMID:26787230
-
Flooding dynamics on the lower Amazon floodplain
NASA Astrophysics Data System (ADS)
Rudorff, C.; Melack, J. M.; Bates, P. D.
2013-05-01
We analyzed flooding dynamics of a large floodplain lake in the lower reach of the Amazon River for the period between 1995 through 2010. Floodplain inundation was simulated using the LISFLOOD-FP model, which combines one-dimensional river routing with two-dimensional overland flow, and a local hydrological model. Accurate representation of floodplain flows and inundation extent depends on the quality of the digital elevation model (DEM). We combined digital topography (derived from the Shuttle Radar Topography Mission) with extensive floodplain echo-sounding data to generate a hydraulically sound DEM. Analysis of daily water balances revealed that the dominant source of inflow alternated seasonally among direct rain and local runoff (October through January), Amazon River (March through August), and seepage (September). As inflows from the Amazon River increase during the rising limb of the hydrograph, regional floodwaters encounter the floodplain partially inundated from local hydrological inputs. At peak flow the floodplain routes, on average, 2.5% of the total discharge for this reach. The falling limb of the hydrograph coincides with the locally dry period, allowing seepage of water stored in sediments to become a dominant source. The average annual inflow from the Amazon River was 58.8 km3 (SD = 33.5), representing more than three thirds (80%) of inputs from all sources, with substantial inter-annual variability. The average annual net export of water from the floodplain to the Amazon River was 7.9 km3 (SD = 2.7).
-
Bourne, Amanda; Holness, Stephen; Holden, Petra; Scorgie, Sarshen; Donatti, Camila I.; Midgley, Guy
2016-01-01
Climate change adds an additional layer of complexity to existing sustainable development and biodiversity conservation challenges. The impacts of global climate change are felt locally, and thus local governance structures will increasingly be responsible for preparedness and local responses. Ecosystem-based adaptation (EbA) options are gaining prominence as relevant climate change solutions. Local government officials seldom have an appropriate understanding of the role of ecosystem functioning in sustainable development goals, or access to relevant climate information. Thus the use of ecosystems in helping people adapt to climate change is limited partially by the lack of information on where ecosystems have the highest potential to do so. To begin overcoming this barrier, Conservation South Africa in partnership with local government developed a socio-ecological approach for identifying spatial EbA priorities at the sub-national level. Using GIS-based multi-criteria analysis and vegetation distribution models, the authors have spatially integrated relevant ecological and social information at a scale appropriate to inform local level political, administrative, and operational decision makers. This is the first systematic approach of which we are aware that highlights spatial priority areas for EbA implementation. Nodes of socio-ecological vulnerability are identified, and the inclusion of areas that provide ecosystem services and ecological resilience to future climate change is innovative. The purpose of this paper is to present and demonstrate a methodology for combining complex information into user-friendly spatial products for local level decision making on EbA. The authors focus on illustrating the kinds of products that can be generated from combining information in the suggested ways, and do not discuss the nuance of climate models nor present specific technical details of the model outputs here. Two representative case studies from rural South Africa demonstrate the replicability of this approach in rural and peri-urban areas of other developing and least developed countries around the world. PMID:27227671
-
Bourne, Amanda; Holness, Stephen; Holden, Petra; Scorgie, Sarshen; Donatti, Camila I; Midgley, Guy
2016-01-01
Climate change adds an additional layer of complexity to existing sustainable development and biodiversity conservation challenges. The impacts of global climate change are felt locally, and thus local governance structures will increasingly be responsible for preparedness and local responses. Ecosystem-based adaptation (EbA) options are gaining prominence as relevant climate change solutions. Local government officials seldom have an appropriate understanding of the role of ecosystem functioning in sustainable development goals, or access to relevant climate information. Thus the use of ecosystems in helping people adapt to climate change is limited partially by the lack of information on where ecosystems have the highest potential to do so. To begin overcoming this barrier, Conservation South Africa in partnership with local government developed a socio-ecological approach for identifying spatial EbA priorities at the sub-national level. Using GIS-based multi-criteria analysis and vegetation distribution models, the authors have spatially integrated relevant ecological and social information at a scale appropriate to inform local level political, administrative, and operational decision makers. This is the first systematic approach of which we are aware that highlights spatial priority areas for EbA implementation. Nodes of socio-ecological vulnerability are identified, and the inclusion of areas that provide ecosystem services and ecological resilience to future climate change is innovative. The purpose of this paper is to present and demonstrate a methodology for combining complex information into user-friendly spatial products for local level decision making on EbA. The authors focus on illustrating the kinds of products that can be generated from combining information in the suggested ways, and do not discuss the nuance of climate models nor present specific technical details of the model outputs here. Two representative case studies from rural South Africa demonstrate the replicability of this approach in rural and peri-urban areas of other developing and least developed countries around the world.
-
Aydin, Ümit; Vorwerk, Johannes; Küpper, Philipp; Heers, Marcel; Kugel, Harald; Galka, Andreas; Hamid, Laith; Wellmer, Jörg; Kellinghaus, Christoph; Rampp, Stefan; Wolters, Carsten Hermann
2014-01-01
To increase the reliability for the non-invasive determination of the irritative zone in presurgical epilepsy diagnosis, we introduce here a new experimental and methodological source analysis pipeline that combines the complementary information in EEG and MEG, and apply it to data from a patient, suffering from refractory focal epilepsy. Skull conductivity parameters in a six compartment finite element head model with brain anisotropy, constructed from individual MRI data, are estimated in a calibration procedure using somatosensory evoked potential (SEP) and field (SEF) data. These data are measured in a single run before acquisition of further runs of spontaneous epileptic activity. Our results show that even for single interictal spikes, volume conduction effects dominate over noise and need to be taken into account for accurate source analysis. While cerebrospinal fluid and brain anisotropy influence both modalities, only EEG is sensitive to skull conductivity and conductivity calibration significantly reduces the difference in especially depth localization of both modalities, emphasizing its importance for combining EEG and MEG source analysis. On the other hand, localization differences which are due to the distinct sensitivity profiles of EEG and MEG persist. In case of a moderate error in skull conductivity, combined source analysis results can still profit from the different sensitivity profiles of EEG and MEG to accurately determine location, orientation and strength of the underlying sources. On the other side, significant errors in skull modeling are reflected in EEG reconstruction errors and could reduce the goodness of fit to combined datasets. For combined EEG and MEG source analysis, we therefore recommend calibrating skull conductivity using additionally acquired SEP/SEF data. PMID:24671208
-
Combined dendritic cell cryotherapy of tumor induces systemic antimetastatic immunity.
Machlenkin, Arthur; Goldberger, Ofir; Tirosh, Boaz; Paz, Adrian; Volovitz, Ilan; Bar-Haim, Erez; Lee, Sung-Hyung; Vadai, Ezra; Tzehoval, Esther; Eisenbach, Lea
2005-07-01
Cryotherapy of localized prostate, renal, and hepatic primary tumors and metastases is considered a minimally invasive treatment demonstrating a low complication rate in comparison with conventional surgery. The main drawback of cryotherapy is that it has no systemic effect on distant metastases. We investigated whether intratumoral injections of dendritic cells following cryotherapy of local tumors (cryoimmunotherapy) provides an improved approach to cancer treatment, combining local tumor destruction and systemic anticancer immunity. The 3LL murine Lewis lung carcinoma clone D122 and the ovalbumin-transfected B16 melanoma clone MO5 served as models for spontaneous metastasis. The antimetastatic effect of cryoimmunotherapy was assessed in the lung carcinoma model by monitoring mouse survival, lung weight, and induction of tumor-specific CTLs. The mechanism of cryoimmunotherapy was elucidated in the melanoma model using adoptive transfer of T cell receptor transgenic OT-I CTLs into the tumor-bearing mice, and analysis of Th1/Th2 responses by intracellular cytokine staining in CD4 and CD8 cells. Cryoimmunotherapy caused robust and tumor-specific CTL responses, increased Th1 responses, significantly prolonged survival and dramatically reduced lung metastasis. Although intratumor administration of dendritic cells alone increased the proliferation rate of CD8 cells, only cryoimmunotherapy resulted in the generation of effector memory cells. Furthermore, cryoimmunotherapyprotected mice that had survived primary MO5 tumors from rechallenge with parental tumors. These results present cryoimmunotherapy as a novel approach for systemic treatment of cancer. We envisage that cryotherapy of tumors combined with subsequent in situ immunotherapy by autologous unmodified immature dendritic cells can be applied in practice.
-
NASA Astrophysics Data System (ADS)
Förner, K.; Polifke, W.
2017-10-01
The nonlinear acoustic behavior of Helmholtz resonators is characterized by a data-based reduced-order model, which is obtained by a combination of high-resolution CFD simulation and system identification. It is shown that even in the nonlinear regime, a linear model is capable of describing the reflection behavior at a particular amplitude with quantitative accuracy. This observation motivates to choose a local-linear model structure for this study, which consists of a network of parallel linear submodels. A so-called fuzzy-neuron layer distributes the input signal over the linear submodels, depending on the root mean square of the particle velocity at the resonator surface. The resulting model structure is referred to as an local-linear neuro-fuzzy network. System identification techniques are used to estimate the free parameters of this model from training data. The training data are generated by CFD simulations of the resonator, with persistent acoustic excitation over a wide range of frequencies and sound pressure levels. The estimated nonlinear, reduced-order models show good agreement with CFD and experimental data over a wide range of amplitudes for several test cases.
-
NASA Astrophysics Data System (ADS)
Pearle, Philip
2007-03-01
In this volume in honour of GianCarlo Ghirardi, I discuss my involvement with ideas of dynamical collapse of the state vector. Ten problems are introduced, nine of which were seen following my initial work. Four of these problems had a resolution in GianCarlo Ghirardi, Alberto Rimini and Tullio Weber's spontaneous localization (SL) model (which added one more problem). This stimulated a (somewhat different) resolution of these five problems in the continuous spontaneous localization (CSL) model, in which I combined my initial work with SL. In an upcoming volume in honour of Abner Shimony, I shall discuss the status of the remaining five post-CSL problems.
-
State-to-State Internal Energy Relaxation Following the Quantum-Kinetic Model in DSMC
NASA Technical Reports Server (NTRS)
Liechty, Derek S.
2014-01-01
A new model for chemical reactions, the Quantum-Kinetic (Q-K) model of Bird, has recently been introduced that does not depend on macroscopic rate equations or values of local flow field data. Subsequently, the Q-K model has been extended to include reactions involving charged species and electronic energy level transitions. Although this is a phenomenological model, it has been shown to accurately reproduce both equilibrium and non-equilibrium reaction rates. The usefulness of this model becomes clear as local flow conditions either exceed the conditions used to build previous models or when they depart from an equilibrium distribution. Presently, the applicability of the relaxation technique is investigated for the vibrational internal energy mode. The Forced Harmonic Oscillator (FHO) theory for vibrational energy level transitions is combined with the Q-K energy level transition model to accurately reproduce energy level transitions at a reduced computational cost compared to the older FHO models.
-
Document page structure learning for fixed-layout e-books using conditional random fields
NASA Astrophysics Data System (ADS)
Tao, Xin; Tang, Zhi; Xu, Canhui
2013-12-01
In this paper, a model is proposed to learn logical structure of fixed-layout document pages by combining support vector machine (SVM) and conditional random fields (CRF). Features related to each logical label and their dependencies are extracted from various original Portable Document Format (PDF) attributes. Both local evidence and contextual dependencies are integrated in the proposed model so as to achieve better logical labeling performance. With the merits of SVM as local discriminative classifier and CRF modeling contextual correlations of adjacent fragments, it is capable of resolving the ambiguities of semantic labels. The experimental results show that CRF based models with both tree and chain graph structures outperform the SVM model with an increase of macro-averaged F1 by about 10%.
-
Predictions of Poisson's ratio in cross-ply laminates containing matrix cracks and delaminations
NASA Technical Reports Server (NTRS)
Harris, Charles E.; Allen, David H.; Nottorf, Eric W.
1989-01-01
A damage-dependent constitutive model for laminated composites has been developed for the combined damage modes of matrix cracks and delaminations. The model is based on the concept of continuum damage mechanics and uses second-order tensor valued internal state variables to represent each mode of damage. The internal state variables are defined as the local volume average of the relative crack face displacements. Since the local volume for delaminations is specified at the laminate level, the constitutive model takes the form of laminate analysis equations modified by the internal state variables. Model implementation is demonstrated for the laminate engineering modulus E(x) and Poisson's ratio nu(xy) of quasi-isotropic and cross-ply laminates. The model predictions are in close agreement to experimental results obtained for graphite/epoxy laminates.
-
Revisiting Gaussian Process Regression Modeling for Localization in Wireless Sensor Networks
Richter, Philipp; Toledano-Ayala, Manuel
2015-01-01
Signal strength-based positioning in wireless sensor networks is a key technology for seamless, ubiquitous localization, especially in areas where Global Navigation Satellite System (GNSS) signals propagate poorly. To enable wireless local area network (WLAN) location fingerprinting in larger areas while maintaining accuracy, methods to reduce the effort of radio map creation must be consolidated and automatized. Gaussian process regression has been applied to overcome this issue, also with auspicious results, but the fit of the model was never thoroughly assessed. Instead, most studies trained a readily available model, relying on the zero mean and squared exponential covariance function, without further scrutinization. This paper studies the Gaussian process regression model selection for WLAN fingerprinting in indoor and outdoor environments. We train several models for indoor/outdoor- and combined areas; we evaluate them quantitatively and compare them by means of adequate model measures, hence assessing the fit of these models directly. To illuminate the quality of the model fit, the residuals of the proposed model are investigated, as well. Comparative experiments on the positioning performance verify and conclude the model selection. In this way, we show that the standard model is not the most appropriate, discuss alternatives and present our best candidate. PMID:26370996
-
Gille, Laure-Anne; Marquis-Favre, Catherine; Morel, Julien
2016-09-01
An in situ survey was performed in 8 French cities in 2012 to study the annoyance due to combined transportation noises. As the European Commission recommends to use the exposure-response relationships suggested by Miedema and Oudshoorn [Environmental Health Perspective, 2001] to predict annoyance due to single transportation noise, these exposure-response relationships were tested using the annoyance due to each transportation noise measured during the French survey. These relationships only enabled a good prediction in terms of the percentages of people highly annoyed by road traffic noise. For the percentages of people annoyed and a little annoyed by road traffic noise, the quality of prediction is weak. For aircraft and railway noises, prediction of annoyance is not satisfactory either. As a consequence, the annoyance equivalents model of Miedema [The Journal of the Acoustical Society of America, 2004], based on these exposure-response relationships did not enable a good prediction of annoyance due to combined transportation noises. Local exposure-response relationships were derived, following the whole computation suggested by Miedema and Oudshoorn [Environmental Health Perspective, 2001]. They led to a better calculation of annoyance due to each transportation noise in the French cities. A new version of the annoyance equivalents model was proposed using these new exposure-response relationships. This model enabled a better prediction of the total annoyance due to the combined transportation noises. These results encourage therefore to improve the annoyance prediction for noise in isolation with local or revised exposure-response relationships, which will also contribute to improve annoyance modeling for combined noises. With this aim in mind, a methodology is proposed to consider noise sensitivity in exposure-response relationships and in the annoyance equivalents model. The results showed that taking into account such variable did not enable to enhance both exposure-response relationships and the annoyance equivalents model. Copyright © 2016 Elsevier Ltd. All rights reserved.
-
NASA Astrophysics Data System (ADS)
Li, Lili; Liu, Yihong; Wang, Yunpeng
2017-07-01
Urban air pollution is influenced not only by local emission sources including industry and vehicles, but also greatly by regional atmospheric pollutant transportation from the surrounding areas, especially in developed city clusters, like the Pearl River Delta (PRD). Taking an air pollution episode in Shenzhen as an example, this paper investigates the occurrence and evolution of the pollution episode and identifies the transport pathways of air pollutants in Shenzhen by combining MODIS satellite images and HYSPLIT back trajectory analysis. Results show that this pollution episode is mainly caused by the local emission of pollutants in PRD and oceanic air masses under specific weather conditions.
-
Cloherty, Shaun L; Hietanen, Markus A; Suaning, Gregg J; Ibbotson, Michael R
2010-01-01
We performed optical intrinsic signal imaging of cat primary visual cortex (Area 17 and 18) while delivering bipolar electrical stimulation to the retina by way of a supra-choroidal electrode array. Using a general linear model (GLM) analysis we identified statistically significant (p < 0.01) activation in a localized region of cortex following supra-threshold electrical stimulation at a single retinal locus. (1) demonstrate that intrinsic signal imaging combined with linear model analysis provides a powerful tool for assessing cortical responses to prosthetic stimulation, and (2) confirm that supra-choroidal electrical stimulation can achieve localized activation of the cortex consistent with focal activation of the retina.
-
Synergistic interaction between fentanyl and bupivacaine given intrathecally for labor analgesia.
Ngan Kee, Warwick D; Khaw, Kim S; Ng, Floria F; Ng, Karman K L; So, Rita; Lee, Anna
2014-05-01
Lipophilic opioids and local anesthetics are often given intrathecally in combination for labor analgesia. However, the nature of the pharmacologic interaction between these drugs has not been clearly elucidated in humans. Three hundred nulliparous women randomly received 1 of 30 different combinations of fentanyl and bupivacaine intrathecally using a combined spinal-epidural technique for analgesia in the first stage of labor. Visual analogue scale pain scores were recorded for 30 min. Response was defined by percentage decrease in pain score from baseline at 15 and 30 min. Dose-response curves for individual drugs were fitted to a hyperbolic dose-response model using nonlinear regression. The nature of the drug interaction was determined using dose equivalence methodology to compare observed effects of drug combinations with effects predicted by additivity. The derived dose-response models for individual drugs (doses in micrograms) at 15 min were: Effect = 100 × dose / (13.82 + dose) for fentanyl, and Effect = 100 × dose / (1,590 + dose) for bupivacaine. Combinations of fentanyl and bupivacaine produced greater effects than those predicted by additivity at 15 min (P < 0.001) and 30 min (P = 0.015) (mean differences, 9.1 [95% CI, 4.1-14.1] and 6.4 [95% CI, 1.2-11.5] units of the normalized response, respectively), indicating a synergistic interaction. The pharmacologic interaction between intrathecal fentanyl and bupivacaine is synergistic. Characterization and quantification of this interaction provide a theoretical basis and support for the clinical practice of combining intrathecal opioids and local anesthetics.
-
Kubas, Adam; Noak, Johannes; Trunschke, Annette; Schlögl, Robert; Neese, Frank; Maganas, Dimitrios
2017-09-01
Absorption and multiwavelength resonance Raman spectroscopy are widely used to investigate the electronic structure of transition metal centers in coordination compounds and extended solid systems. In combination with computational methodologies that have predictive accuracy, they define powerful protocols to study the spectroscopic response of catalytic materials. In this work, we study the absorption and resonance Raman spectra of the M1 MoVO x catalyst. The spectra were calculated by time-dependent density functional theory (TD-DFT) in conjunction with the independent mode displaced harmonic oscillator model (IMDHO), which allows for detailed bandshape predictions. For this purpose cluster models with up to 9 Mo and V metallic centers are considered to represent the bulk structure of MoVO x . Capping hydrogens were used to achieve valence saturation at the edges of the cluster models. The construction of model structures was based on a thorough bonding analysis which involved conventional DFT and local coupled cluster (DLPNO-CCSD(T)) methods. Furthermore the relationship of cluster topology to the computed spectral features is discussed in detail. It is shown that due to the local nature of the involved electronic transitions, band assignment protocols developed for molecular systems can be applied to describe the calculated spectral features of the cluster models as well. The present study serves as a reference for future applications of combined experimental and computational protocols in the field of solid-state heterogeneous catalysis.
-
NASA Astrophysics Data System (ADS)
Shaman, J.; Stieglitz, M.; Zebiak, S.; Cane, M.; Day, J. F.
2002-12-01
We present an ensemble local hydrologic forecast derived from the seasonal forecasts of the International Research Institute (IRI) for Climate Prediction. Three- month seasonal forecasts were used to resample historical meteorological conditions and generate ensemble forcing datasets for a TOPMODEL-based hydrology model. Eleven retrospective forecasts were run at a Florida and New York site. Forecast skill was assessed for mean area modeled water table depth (WTD), i.e. near surface soil wetness conditions, and compared with WTD simulated with observed data. Hydrology model forecast skill was evident at the Florida site but not at the New York site. At the Florida site, persistence of hydrologic conditions and local skill of the IRI seasonal forecast contributed to the local hydrologic forecast skill. This forecast will permit probabilistic prediction of future hydrologic conditions. At the Florida site, we have also quantified the link between modeled WTD (i.e. drought) and the amplification and transmission of St. Louis Encephalitis virus (SLEV). We derive an empirical relationship between modeled land surface wetness and levels of SLEV transmission associated with human clinical cases. We then combine the seasonal forecasts of local, modeled WTD with this empirical relationship and produce retrospective probabilistic seasonal forecasts of epidemic SLEV transmission in Florida. Epidemic SLEV transmission forecast skill is demonstrated. These findings will permit real-time forecast of drought and resultant SLEV transmission in Florida.
-
Two-dimensional analytical modeling of a linear variable filter for spectral order sorting.
Ko, Cheng-Hao; Wu, Yueh-Hsun; Tsai, Jih-Run; Wang, Bang-Ji; Chakraborty, Symphony
2016-06-10
A two-dimensional thin film thickness model based on the geometry of a commercial coater which can calculate more effectively the profiles of linear variable filters (LVFs) has been developed. This is done by isolating the substrate plane as an independent coordinate (local coordinate), while the rotation and translation matrices are used to establish the coordinate transformation and combine the characteristic vector with the step function to build a borderline which can conclude whether the local mask will block the deposition or not. The height of the local mask has been increased up to 40 mm in the proposed model, and two-dimensional simulations are developed to obtain a thin film profile deposition on the substrate inside the evaporation chamber to achieve the specific request of producing a LVF zone width in a more economical way than previously reported [Opt. Express23, 5102 (2015)OPEXFF1094-408710.1364/OE.23.005102].
-
Bounded Linear Stability Analysis - A Time Delay Margin Estimation Approach for Adaptive Control
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.; Ishihara, Abraham K.; Krishnakumar, Kalmanje Srinlvas; Bakhtiari-Nejad, Maryam
2009-01-01
This paper presents a method for estimating time delay margin for model-reference adaptive control of systems with almost linear structured uncertainty. The bounded linear stability analysis method seeks to represent the conventional model-reference adaptive law by a locally bounded linear approximation within a small time window using the comparison lemma. The locally bounded linear approximation of the combined adaptive system is cast in a form of an input-time-delay differential equation over a small time window. The time delay margin of this system represents a local stability measure and is computed analytically by a matrix measure method, which provides a simple analytical technique for estimating an upper bound of time delay margin. Based on simulation results for a scalar model-reference adaptive control system, both the bounded linear stability method and the matrix measure method are seen to provide a reasonably accurate and yet not too conservative time delay margin estimation.
-
Structural-change localization and monitoring through a perturbation-based inverse problem.
Roux, Philippe; Guéguen, Philippe; Baillet, Laurent; Hamze, Alaa
2014-11-01
Structural-change detection and characterization, or structural-health monitoring, is generally based on modal analysis, for detection, localization, and quantification of changes in structure. Classical methods combine both variations in frequencies and mode shapes, which require accurate and spatially distributed measurements. In this study, the detection and localization of a local perturbation are assessed by analysis of frequency changes (in the fundamental mode and overtones) that are combined with a perturbation-based linear inverse method and a deconvolution process. This perturbation method is applied first to a bending beam with the change considered as a local perturbation of the Young's modulus, using a one-dimensional finite-element model for modal analysis. Localization is successful, even for extended and multiple changes. In a second step, the method is numerically tested under ambient-noise vibration from the beam support with local changes that are shifted step by step along the beam. The frequency values are revealed using the random decrement technique that is applied to the time-evolving vibrations recorded by one sensor at the free extremity of the beam. Finally, the inversion method is experimentally demonstrated at the laboratory scale with data recorded at the free end of a Plexiglas beam attached to a metallic support.
-
2-Point microstructure archetypes for improved elastic properties
NASA Astrophysics Data System (ADS)
Adams, Brent L.; Gao, Xiang
2004-01-01
Rectangular models of material microstructure are described by their 1- and 2-point (spatial) correlation statistics of placement of local state. In the procedure described here the local state space is described in discrete form; and the focus is on placement of local state within a finite number of cells comprising rectangular models. It is illustrated that effective elastic properties (generalized Hashin Shtrikman bounds) can be obtained that are linear in components of the correlation statistics. Within this framework the concept of an eigen-microstructure within the microstructure hull is useful. Given the practical innumerability of the microstructure hull, however, we introduce a method for generating a sequence of archetypes of eigen-microstructure, from the 2-point correlation statistics of local state, assuming that the 1-point statistics are stationary. The method is illustrated by obtaining an archetype for an imaginary two-phase material where the objective is to maximize the combination C_{xxxx}^{*} + C_{xyxy}^{*}
-
Baudin, Pablo; Kristensen, Kasper
2016-06-14
We present a local framework for the calculation of coupled cluster excitation energies of large molecules (LoFEx). The method utilizes time-dependent Hartree-Fock information about the transitions of interest through the concept of natural transition orbitals (NTOs). The NTOs are used in combination with localized occupied and virtual Hartree-Fock orbitals to generate a reduced excitation orbital space (XOS) specific to each transition where a standard coupled cluster calculation is carried out. Each XOS is optimized to ensure that the excitation energies are determined to a predefined precision. We apply LoFEx in combination with the RI-CC2 model to calculate the lowest excitation energies of a set of medium-sized organic molecules. The results demonstrate the black-box nature of the LoFEx approach and show that significant computational savings can be gained without affecting the accuracy of CC2 excitation energies.
-
Perlroth, Daniella J; Bhattacharya, Jay; Goldman, Dana P; Garber, Alan M
2012-12-01
Comparative effectiveness research suggests that conservative management (CM) strategies are no less effective than active initial treatment for many men with localized prostate cancer. We estimate longer-term costs of initial management strategies and potential US health expenditure savings by increased use of conservative management for men with localized prostate cancer. Five-year total health expenditures attributed to initial management strategies for localized prostate cancer were calculated using commercial claims data from 1998 to 2006, and savings were estimated from a US population health-care expenditure model. Our analysis finds that patients receiving combinations of active treatments have the highest additional costs over conservative management at $63 500, followed by $48 550 for intensity-modulated radiation therapy, $37 500 for primary androgen deprivation therapy, and $28 600 for brachytherapy. Radical prostatectomy ($15 200) and external beam radiation therapy ($18 900) were associated with the lowest costs. The population model estimated that US health expenditures could be lowered by 1) use of initial CM over all active treatment ($2.9-3.25 billion annual savings), 2) shifting patients receiving intensity-modulated radiation therapy to CM ($680-930 million), 3) foregoing primary androgen deprivation therapy($555 million), 4) reducing the use of adjuvant androgen deprivation in addition to local therapies ($630 million), and 5) using single treatments rather than combination local treatment ($620-655 million). In conclusion, we find that all active treatments are associated with higher longer-term costs than CM. Substantial savings, representing up to 30% of total costs, could be realized by adopting CM strategies, including active surveillance, for initial management of men with localized prostate cancer.
-
Han, Xujun; Li, Xin; Rigon, Riccardo; Jin, Rui; Endrizzi, Stefano
2015-01-01
The observation could be used to reduce the model uncertainties with data assimilation. If the observation cannot cover the whole model area due to spatial availability or instrument ability, how to do data assimilation at locations not covered by observation? Two commonly used strategies were firstly described: One is covariance localization (CL); the other is observation localization (OL). Compared with CL, OL is easy to parallelize and more efficient for large-scale analysis. This paper evaluated OL in soil moisture profile characterizations, in which the geostatistical semivariogram was used to fit the spatial correlated characteristics of synthetic L-Band microwave brightness temperature measurement. The fitted semivariogram model and the local ensemble transform Kalman filter algorithm are combined together to weight and assimilate the observations within a local region surrounding the grid cell of land surface model to be analyzed. Six scenarios were compared: 1_Obs with one nearest observation assimilated, 5_Obs with no more than five nearest local observations assimilated, and 9_Obs with no more than nine nearest local observations assimilated. The scenarios with no more than 16, 25, and 36 local observations were also compared. From the results we can conclude that more local observations involved in assimilation will improve estimations with an upper bound of 9 observations in this case. This study demonstrates the potentials of geostatistical correlation representation in OL to improve data assimilation of catchment scale soil moisture using synthetic L-band microwave brightness temperature, which cannot cover the study area fully in space due to vegetation effects.
-
Han, Xujun; Li, Xin; Rigon, Riccardo; Jin, Rui; Endrizzi, Stefano
2015-01-01
The observation could be used to reduce the model uncertainties with data assimilation. If the observation cannot cover the whole model area due to spatial availability or instrument ability, how to do data assimilation at locations not covered by observation? Two commonly used strategies were firstly described: One is covariance localization (CL); the other is observation localization (OL). Compared with CL, OL is easy to parallelize and more efficient for large-scale analysis. This paper evaluated OL in soil moisture profile characterizations, in which the geostatistical semivariogram was used to fit the spatial correlated characteristics of synthetic L-Band microwave brightness temperature measurement. The fitted semivariogram model and the local ensemble transform Kalman filter algorithm are combined together to weight and assimilate the observations within a local region surrounding the grid cell of land surface model to be analyzed. Six scenarios were compared: 1_Obs with one nearest observation assimilated, 5_Obs with no more than five nearest local observations assimilated, and 9_Obs with no more than nine nearest local observations assimilated. The scenarios with no more than 16, 25, and 36 local observations were also compared. From the results we can conclude that more local observations involved in assimilation will improve estimations with an upper bound of 9 observations in this case. This study demonstrates the potentials of geostatistical correlation representation in OL to improve data assimilation of catchment scale soil moisture using synthetic L-band microwave brightness temperature, which cannot cover the study area fully in space due to vegetation effects. PMID:25635771
-
Li, Bin; Chen, Kan; Tian, Lianfang; Yeboah, Yao; Ou, Shanxing
2013-01-01
The segmentation and detection of various types of nodules in a Computer-aided detection (CAD) system present various challenges, especially when (1) the nodule is connected to a vessel and they have very similar intensities; (2) the nodule with ground-glass opacity (GGO) characteristic possesses typical weak edges and intensity inhomogeneity, and hence it is difficult to define the boundaries. Traditional segmentation methods may cause problems of boundary leakage and "weak" local minima. This paper deals with the above mentioned problems. An improved detection method which combines a fuzzy integrated active contour model (FIACM)-based segmentation method, a segmentation refinement method based on Parametric Mixture Model (PMM) of juxta-vascular nodules, and a knowledge-based C-SVM (Cost-sensitive Support Vector Machines) classifier, is proposed for detecting various types of pulmonary nodules in computerized tomography (CT) images. Our approach has several novel aspects: (1) In the proposed FIACM model, edge and local region information is incorporated. The fuzzy energy is used as the motivation power for the evolution of the active contour. (2) A hybrid PMM Model of juxta-vascular nodules combining appearance and geometric information is constructed for segmentation refinement of juxta-vascular nodules. Experimental results of detection for pulmonary nodules show desirable performances of the proposed method.
-
NASA Astrophysics Data System (ADS)
Zheng, Qiang; Li, Honglun; Fan, Baode; Wu, Shuanhu; Xu, Jindong
2017-12-01
Active contour model (ACM) has been one of the most widely utilized methods in magnetic resonance (MR) brain image segmentation because of its ability of capturing topology changes. However, most of the existing ACMs only consider single-slice information in MR brain image data, i.e., the information used in ACMs based segmentation method is extracted only from one slice of MR brain image, which cannot take full advantage of the adjacent slice images' information, and cannot satisfy the local segmentation of MR brain images. In this paper, a novel ACM is proposed to solve the problem discussed above, which is based on multi-variate local Gaussian distribution and combines the adjacent slice images' information in MR brain image data to satisfy segmentation. The segmentation is finally achieved through maximizing the likelihood estimation. Experiments demonstrate the advantages of the proposed ACM over the single-slice ACM in local segmentation of MR brain image series.
-
MODFLOW-LGR: Practical application to a large regional dataset
NASA Astrophysics Data System (ADS)
Barnes, D.; Coulibaly, K. M.
2011-12-01
In many areas of the US, including southwest Florida, large regional-scale groundwater models have been developed to aid in decision making and water resources management. These models are subsequently used as a basis for site-specific investigations. Because the large scale of these regional models is not appropriate for local application, refinement is necessary to analyze the local effects of pumping wells and groundwater related projects at specific sites. The most commonly used approach to date is Telescopic Mesh Refinement or TMR. It allows the extraction of a subset of the large regional model with boundary conditions derived from the regional model results. The extracted model is then updated and refined for local use using a variable sized grid focused on the area of interest. MODFLOW-LGR, local grid refinement, is an alternative approach which allows model discretization at a finer resolution in areas of interest and provides coupling between the larger "parent" model and the locally refined "child." In the present work, these two approaches are tested on a mining impact assessment case in southwest Florida using a large regional dataset (The Lower West Coast Surficial Aquifer System Model). Various metrics for performance are considered. They include: computation time, water balance (as compared to the variable sized grid), calibration, implementation effort, and application advantages and limitations. The results indicate that MODFLOW-LGR is a useful tool to improve local resolution of regional scale models. While performance metrics, such as computation time, are case-dependent (model size, refinement level, stresses involved), implementation effort, particularly when regional models of suitable scale are available, can be minimized. The creation of multiple child models within a larger scale parent model makes it possible to reuse the same calibrated regional dataset with minimal modification. In cases similar to the Lower West Coast model, where a model is larger than optimal for direct application as a parent grid, a combination of TMR and LGR approaches should be used to develop a suitable parent grid.
-
On radiating baroclinic instability of zonally varying flow
NASA Technical Reports Server (NTRS)
Finley, Catherine A.; Nathan, Terrence R.
1993-01-01
A quasi-geostrophic, two-layer, beta-plane model is used to study the baroclinic instability characteristics of a zonally inhomogeneous flow. It is assumed that the disturbance varied slowly in the cross-stream direction, and the stability problem was formulated as a 1D initial value problem. Emphasis is placed on determining how the vertically averaged wind, local maximum in vertical wind shear, and length of the locally supercritical region combine to yield local instabilities. Analysis of the local disturbance energetics reveals that, for slowly varying basic states, the baroclinic energy conversion predominates within the locally unstable region. Using calculations of the basic state tendencies, it is shown that the net effect of the local instabilities is to redistribute energy from the baroclinic to the barotropic component of the basic state flow.
-
Brain tumor segmentation in 3D MRIs using an improved Markov random field model
NASA Astrophysics Data System (ADS)
Yousefi, Sahar; Azmi, Reza; Zahedi, Morteza
2011-10-01
Markov Random Field (MRF) models have been recently suggested for MRI brain segmentation by a large number of researchers. By employing Markovianity, which represents the local property, MRF models are able to solve a global optimization problem locally. But they still have a heavy computation burden, especially when they use stochastic relaxation schemes such as Simulated Annealing (SA). In this paper, a new 3D-MRF model is put forward to raise the speed of the convergence. Although, search procedure of SA is fairly localized and prevents from exploring the same diversity of solutions, it suffers from several limitations. In comparison, Genetic Algorithm (GA) has a good capability of global researching but it is weak in hill climbing. Our proposed algorithm combines SA and an improved GA (IGA) to optimize the solution which speeds up the computation time. What is more, this proposed algorithm outperforms the traditional 2D-MRF in quality of the solution.
-
Impact of cosmic inhomogeneities on SNe observations
NASA Astrophysics Data System (ADS)
Kainulainen, Kimmo; Marra, Valerio
2010-06-01
We study the impact of cosmic inhomogeneities on the interpretation of SNe observations. We build an inhomogeneous universe model that can confront supernova data and yet is reasonably well compatible with the Copernican Principle. Our model combines a relatively small local void, that gives apparent acceleration at low redshifts, with a meatball model that gives sizeable lensing (dimming) at high redshifts. Together these two elements, which focus on different effects of voids on the data, allow the model to mimic the concordance model.
-
Haplotype-Based Genome-Wide Prediction Models Exploit Local Epistatic Interactions Among Markers
Jiang, Yong; Schmidt, Renate H.; Reif, Jochen C.
2018-01-01
Genome-wide prediction approaches represent versatile tools for the analysis and prediction of complex traits. Mostly they rely on marker-based information, but scenarios have been reported in which models capitalizing on closely-linked markers that were combined into haplotypes outperformed marker-based models. Detailed comparisons were undertaken to reveal under which circumstances haplotype-based genome-wide prediction models are superior to marker-based models. Specifically, it was of interest to analyze whether and how haplotype-based models may take local epistatic effects between markers into account. Assuming that populations consisted of fully homozygous individuals, a marker-based model in which local epistatic effects inside haplotype blocks were exploited (LEGBLUP) was linearly transformable into a haplotype-based model (HGBLUP). This theoretical derivation formally revealed that haplotype-based genome-wide prediction models capitalize on local epistatic effects among markers. Simulation studies corroborated this finding. Due to its computational efficiency the HGBLUP model promises to be an interesting tool for studies in which ultra-high-density SNP data sets are studied. Applying the HGBLUP model to empirical data sets revealed higher prediction accuracies than for marker-based models for both traits studied using a mouse panel. In contrast, only a small subset of the traits analyzed in crop populations showed such a benefit. Cases in which higher prediction accuracies are observed for HGBLUP than for marker-based models are expected to be of immediate relevance for breeders, due to the tight linkage a beneficial haplotype will be preserved for many generations. In this respect the inheritance of local epistatic effects very much resembles the one of additive effects. PMID:29549092
-
Haplotype-Based Genome-Wide Prediction Models Exploit Local Epistatic Interactions Among Markers.
Jiang, Yong; Schmidt, Renate H; Reif, Jochen C
2018-05-04
Genome-wide prediction approaches represent versatile tools for the analysis and prediction of complex traits. Mostly they rely on marker-based information, but scenarios have been reported in which models capitalizing on closely-linked markers that were combined into haplotypes outperformed marker-based models. Detailed comparisons were undertaken to reveal under which circumstances haplotype-based genome-wide prediction models are superior to marker-based models. Specifically, it was of interest to analyze whether and how haplotype-based models may take local epistatic effects between markers into account. Assuming that populations consisted of fully homozygous individuals, a marker-based model in which local epistatic effects inside haplotype blocks were exploited (LEGBLUP) was linearly transformable into a haplotype-based model (HGBLUP). This theoretical derivation formally revealed that haplotype-based genome-wide prediction models capitalize on local epistatic effects among markers. Simulation studies corroborated this finding. Due to its computational efficiency the HGBLUP model promises to be an interesting tool for studies in which ultra-high-density SNP data sets are studied. Applying the HGBLUP model to empirical data sets revealed higher prediction accuracies than for marker-based models for both traits studied using a mouse panel. In contrast, only a small subset of the traits analyzed in crop populations showed such a benefit. Cases in which higher prediction accuracies are observed for HGBLUP than for marker-based models are expected to be of immediate relevance for breeders, due to the tight linkage a beneficial haplotype will be preserved for many generations. In this respect the inheritance of local epistatic effects very much resembles the one of additive effects. Copyright © 2018 Jiang et al.
-
NASA Technical Reports Server (NTRS)
Backes, Paul G. (Inventor); Tso, Kam S. (Inventor)
1993-01-01
This invention relates to an operator interface for controlling a telerobot to perform tasks in a poorly modeled environment and/or within unplanned scenarios. The telerobot control system includes a remote robot manipulator linked to an operator interface. The operator interface includes a setup terminal, simulation terminal, and execution terminal for the control of the graphics simulator and local robot actuator as well as the remote robot actuator. These terminals may be combined in a single terminal. Complex tasks are developed from sequential combinations of parameterized task primitives and recorded teleoperations, and are tested by execution on a graphics simulator and/or local robot actuator, together with adjustable time delays. The novel features of this invention include the shared and supervisory control of the remote robot manipulator via operator interface by pretested complex tasks sequences based on sequences of parameterized task primitives combined with further teleoperation and run-time binding of parameters based on task context.
-
Foam flow and liquid films motion: role of the surfactants properties
NASA Astrophysics Data System (ADS)
Cantat, Isabelle
2011-11-01
Liquid foams absorb energy in a much more efficient way than each of its constituents, taken separately. However, the local process at the origin of the energy dissipation is not entirely elucidated yet, and several models may apply, thus making worth local studies on simpler systems. We investigate the motion through a wet tube of transverse soap films, or lamellae, combining local thickness and velocity measurements in the wetting film. For foaming solution with a high dilatational surface modulus, we reveal a zone of several centimeters in length, the dynamic wetting film, which is significantly influenced by a moving lamella. The dependence of this influence length on lamella velocity and wetting film thickness provides an accurate discrimination among several possible surfactants models. In collaboration with B. Dollet.
-
Integrating sensorimotor systems in a robot model of cricket behavior
NASA Astrophysics Data System (ADS)
Webb, Barbara H.; Harrison, Reid R.
2000-10-01
The mechanisms by which animals manage sensorimotor integration and coordination of different behaviors can be investigated in robot models. In previous work the first author has build a robot that localizes sound based on close modeling of the auditory and neural system in the cricket. It is known that the cricket combines its response to sound with other sensorimotor activities such as an optomotor reflex and reactions to mechanical stimulation for the antennae and cerci. Behavioral evidence suggests some ways these behaviors may be integrated. We have tested the addition of an optomotor response, using an analog VLSI circuit developed by the second author, to the sound localizing behavior and have shown that it can, as in the cricket, improve the directness of the robot's path to sound. In particular it substantially improves behavior when the robot is subject to a motor disturbance. Our aim is to better understand how the insect brain functions in controlling complex combinations of behavior, with the hope that this will also suggest novel mechanisms for sensory integration on robots.
-
Hester, Nathan; Li, Ke; Schramski, John R; Crittenden, John
2012-04-30
Globally, residential energy consumption continues to rise due to a variety of trends such as increasing access to modern appliances, overall population growth, and the overall increase of electricity distribution. Currently, residential energy consumption accounts for approximately one-fifth of total U.S. energy consumption. This research analyzes the effectiveness of a range of energy-saving measures for residential houses in semi-arid climates. These energy-saving measures include: structural insulated panels (SIP) for exterior wall construction, daylight control, increased window area, efficient window glass suitable for the local weather, and several combinations of these. Our model determined that energy consumption is reduced by up to 6.1% when multiple energy savings technologies are combined. In addition, pre-construction technologies (structural insulated panels (SIPs), daylight control, and increased window area) provide roughly 4 times the energy savings when compared to post-construction technologies (window blinds and efficient window glass). The model also illuminated the importance variations in local climate and building configuration; highlighting the site-specific nature of this type of energy consumption quantification for policy and building code considerations. Published by Elsevier Ltd.
-
NASA Technical Reports Server (NTRS)
Kidd, Chris; Chapman, Lee
2012-01-01
Meteorological measurements within urban areas are becoming increasingly important due to the accentuating effects of climate change upon the Urban Heat Island (UHI). However, ensuring that such measurements are representative of the local area is often difficult due to the diversity of the urban environment. The evaluation of sites is important for both new sites and for the relocation of established sites to ensure that long term changes in the meteorological and climatological conditions continue to be faithfully recorded. Site selection is traditionally carried out in the field using both local knowledge and visual inspection. This paper exploits and assesses the use of lidar-derived digital surface models (DSMs) to quantitatively aid the site selection process. This is acheived by combining the DSM with a solar model, first to generate spatial maps of sky view factors and sun-hour potential and second, to generate site-specific views of the horizon. The results show that such a technique is a useful first-step approach to identify key sites that may be further evaluated for the location of meteorological stations within urban areas.
-
Svenning, J.-C.; Engelbrecht, B.M.J.; Kinner, D.A.; Kursar, T.A.; Stallard, R.F.; Wright, S.J.
2006-01-01
We used regression models and information-theoretic model selection to assess the relative importance of environment, local dispersal and historical contingency as controls of the distributions of 26 common plant species in tropical forest on Barro Colorado Island (BCI), Panama. We censused eighty-eight 0.09-ha plots scattered across the landscape. Environmental control, local dispersal and historical contingency were represented by environmental variables (soil moisture, slope, soil type, distance to shore, old-forest presence), a spatial autoregressive parameter (??), and four spatial trend variables, respectively. We built regression models, representing all combinations of the three hypotheses, for each species. The probability that the best model included the environmental variables, spatial trend variables and ?? averaged 33%, 64% and 50% across the study species, respectively. The environmental variables, spatial trend variables, ??, and a simple intercept model received the strongest support for 4, 15, 5 and 2 species, respectively. Comparing the model results to information on species traits showed that species with strong spatial trends produced few and heavy diaspores, while species with strong soil moisture relationships were particularly drought-sensitive. In conclusion, history and local dispersal appeared to be the dominant controls of the distributions of common plant species on BCI. Copyright ?? 2006 Cambridge University Press.
-
Flipo, Nicolas; Jeannée, Nicolas; Poulin, Michel; Even, Stéphanie; Ledoux, Emmanuel
2007-03-01
The objective of this work is to combine several approaches to better understand nitrate fate in the Grand Morin aquifers (2700 km(2)), part of the Seine basin. cawaqs results from the coupling of the hydrogeological model newsam with the hydrodynamic and biogeochemical model of river ProSe. cawaqs is coupled with the agronomic model Stics in order to simulate nitrate migration in basins. First, kriging provides a satisfactory representation of aquifer nitrate contamination from local observations, to set initial conditions for the physically based model. Then associated confidence intervals, derived from data using geostatistics, are used to validate cawaqs results. Results and evaluation obtained from the combination of these approaches are given (period 1977-1988). Then cawaqs is used to simulate nitrate fate for a 20-year period (1977-1996). The mean nitrate concentrations increase in aquifers is 0.09 mgN L(-1)yr(-1), resulting from an average infiltration flux of 3500 kgN.km(-2)yr(-1).
-
Efficacy of two lion conservation programs in Maasailand, Kenya.
Hazzah, Leela; Dolrenry, Stephanie; Naughton-Treves, Lisa; Naughton, Lisa; Edwards, Charles T T; Mwebi, Ogeto; Kearney, Fiachra; Frank, Laurence
2014-06-01
Lion (Panthera leo) populations are in decline throughout most of Africa. The problem is particularly acute in southern Kenya, where Maasai pastoralists have been spearing and poisoning lions at a rate that will ensure near term local extinction. We investigated 2 approaches for improving local tolerance of lions: compensation payments for livestock lost to predators and Lion Guardians, which draws on local cultural values and knowledge to mitigate livestock-carnivore conflict and monitor carnivores. To gauge the overall influence of conservation intervention, we combined both programs into a single conservation treatment variable. Using 8 years of lion killing data, we applied Manski's partial identification approach with bounded assumptions to investigate the effect of conservation treatment on lion killing in 4 contiguous areas. In 3 of the areas, conservation treatment was positively associated with a reduction in lion killing. We then applied a generalized linear model to assess the relative efficacy of the 2 interventions. The model estimated that compensation resulted in an 87-91% drop in the number of lions killed, whereas Lion Guardians (operating in combination with compensation and alone) resulted in a 99% drop in lion killing. © 2014 Society for Conservation Biology.
-
Influence of spatial resolution on precipitation simulations for the central Andes Mountains
NASA Astrophysics Data System (ADS)
Trachte, Katja; Bendix, Jörg
2013-04-01
The climate of South America is highly influenced by the north-south oriented Andes Mountains. Their complex structure causes modifications of large-scale atmospheric circulations resulting in various mesoscale phenomena as well as a high variability in the local conditions. Due to their height and length the terrain generates distinctly climate conditions between the western and the eastern slopes. While in the tropical regions along the western flanks the conditions are cold and arid, the eastern slopes are dominated by warm-moist and rainy air coming from the Amazon basin. Below 35° S the situation reverses with rather semiarid conditions in the eastern part and temperate rainy climate along southern Chile. Generally, global circulation models (GCMs) describe the state of the global climate and its changes, but are disabled to capture regional or even local features due to their coarse resolution. This is particularly true in heterogeneous regions such as the Andes Mountains, where local driving features, e. g. local circulation systems, highly varies on small scales and thus, lead to a high variability of rainfall distributions. An appropriate technique to overcome this problem and to gain regional and local scale rainfall information is the dynamical downscaling of the global data using a regional climate model (RCM). The poster presents results of the evaluation of the performance of the Weather Research and Forecasting (WRF) model over South America with special focus on the central Andes Mountains of Ecuador. A sensitivity study regarding the cumulus parametrization, microphysics, boundary layer processes and the radiation budget is conducted. With 17 simulations consisting of 16 parametrization scheme combinations and 1 default run a suitable model set-up for climate research in this region is supposed to be evaluated. The simulations were conducted in a two-way nested mode i) to examine the best physics scheme combination for the target and ii) to analyze the impact of spatial resolution and thus, the representation of the terrain on the result.
-
Human motion tracking by temporal-spatial local gaussian process experts.
Zhao, Xu; Fu, Yun; Liu, Yuncai
2011-04-01
Human pose estimation via motion tracking systems can be considered as a regression problem within a discriminative framework. It is always a challenging task to model the mapping from observation space to state space because of the high-dimensional characteristic in the multimodal conditional distribution. In order to build the mapping, existing techniques usually involve a large set of training samples in the learning process which are limited in their capability to deal with multimodality. We propose, in this work, a novel online sparse Gaussian Process (GP) regression model to recover 3-D human motion in monocular videos. Particularly, we investigate the fact that for a given test input, its output is mainly determined by the training samples potentially residing in its local neighborhood and defined in the unified input-output space. This leads to a local mixture GP experts system composed of different local GP experts, each of which dominates a mapping behavior with the specific covariance function adapting to a local region. To handle the multimodality, we combine both temporal and spatial information therefore to obtain two categories of local experts. The temporal and spatial experts are integrated into a seamless hybrid system, which is automatically self-initialized and robust for visual tracking of nonlinear human motion. Learning and inference are extremely efficient as all the local experts are defined online within very small neighborhoods. Extensive experiments on two real-world databases, HumanEva and PEAR, demonstrate the effectiveness of our proposed model, which significantly improve the performance of existing models.
-
High level cognitive information processing in neural networks
NASA Technical Reports Server (NTRS)
Barnden, John A.; Fields, Christopher A.
1992-01-01
Two related research efforts were addressed: (1) high-level connectionist cognitive modeling; and (2) local neural circuit modeling. The goals of the first effort were to develop connectionist models of high-level cognitive processes such as problem solving or natural language understanding, and to understand the computational requirements of such models. The goals of the second effort were to develop biologically-realistic model of local neural circuits, and to understand the computational behavior of such models. In keeping with the nature of NASA's Innovative Research Program, all the work conducted under the grant was highly innovative. For instance, the following ideas, all summarized, are contributions to the study of connectionist/neural networks: (1) the temporal-winner-take-all, relative-position encoding, and pattern-similarity association techniques; (2) the importation of logical combinators into connection; (3) the use of analogy-based reasoning as a bridge across the gap between the traditional symbolic paradigm and the connectionist paradigm; and (4) the application of connectionism to the domain of belief representation/reasoning. The work on local neural circuit modeling also departs significantly from the work of related researchers. In particular, its concentration on low-level neural phenomena that could support high-level cognitive processing is unusual within the area of biological local circuit modeling, and also serves to expand the horizons of the artificial neural net field.
-
Ghosh, Ranadhir; Yearwood, John; Ghosh, Moumita; Bagirov, Adil
2006-06-01
In this paper we investigate a hybrid model based on the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. Also we discuss different variants for hybrid models using the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. The Discrete Gradient method has the advantage of being able to jump over many local minima and find very deep local minima. However, earlier research has shown that a good starting point for the discrete gradient method can improve the quality of the solution point. Evolutionary algorithms are best suited for global optimisation problems. Nevertheless they are cursed with longer training times and often unsuitable for real world application. For optimisation problems such as weight optimisation for ANNs in real world applications the dimensions are large and time complexity is critical. Hence the idea of a hybrid model can be a suitable option. In this paper we propose different fusion strategies for hybrid models combining the evolutionary strategy with the discrete gradient method to obtain an optimal solution much quicker. Three different fusion strategies are discussed: a linear hybrid model, an iterative hybrid model and a restricted local search hybrid model. Comparative results on a range of standard datasets are provided for different fusion hybrid models.
-
NASA Astrophysics Data System (ADS)
Astuti, H. N.; Saputro, D. R. S.; Susanti, Y.
2017-06-01
MGWR model is combination of linear regression model and geographically weighted regression (GWR) model, therefore, MGWR model could produce parameter estimation that had global parameter estimation, and other parameter that had local parameter in accordance with its observation location. The linkage between locations of the observations expressed in specific weighting that is adaptive bi-square. In this research, we applied MGWR model with weighted adaptive bi-square for case of DHF in Surakarta based on 10 factors (variables) that is supposed to influence the number of people with DHF. The observation unit in the research is 51 urban villages and the variables are number of inhabitants, number of houses, house index, many public places, number of healthy homes, number of Posyandu, area width, level population density, welfare of the family, and high-region. Based on this research, we obtained 51 MGWR models. The MGWR model were divided into 4 groups with significant variable is house index as a global variable, an area width as a local variable and the remaining variables vary in each. Global variables are variables that significantly affect all locations, while local variables are variables that significantly affect a specific location.
-
Adaptive non-local smoothing-based weberface for illumination-insensitive face recognition
NASA Astrophysics Data System (ADS)
Yao, Min; Zhu, Changming
2017-07-01
Compensating the illumination of a face image is an important process to achieve effective face recognition under severe illumination conditions. This paper present a novel illumination normalization method which specifically considers removing the illumination boundaries as well as reducing the regional illumination. We begin with the analysis of the commonly used reflectance model and then expatiate the hybrid usage of adaptive non-local smoothing and the local information coding based on Weber's law. The effectiveness and advantages of this combination are evidenced visually and experimentally. Results on Extended YaleB database show its better performance than several other famous methods.
-
Localized Multi-Model Extremes Metrics for the Fourth National Climate Assessment
NASA Astrophysics Data System (ADS)
Thompson, T. R.; Kunkel, K.; Stevens, L. E.; Easterling, D. R.; Biard, J.; Sun, L.
2017-12-01
We have performed localized analysis of scenario-based datasets for the Fourth National Climate Assessment (NCA4). These datasets include CMIP5-based Localized Constructed Analogs (LOCA) downscaled simulations at daily temporal resolution and 1/16th-degree spatial resolution. Over 45 temperature and precipitation extremes metrics have been processed using LOCA data, including threshold, percentile, and degree-days calculations. The localized analysis calculates trends in the temperature and precipitation extremes metrics for relatively small regions such as counties, metropolitan areas, climate zones, administrative areas, or economic zones. For NCA4, we are currently addressing metropolitan areas as defined by U.S. Census Bureau Metropolitan Statistical Areas. Such localized analysis provides essential information for adaptation planning at scales relevant to local planning agencies and businesses. Nearly 30 such regions have been analyzed to date. Each locale is defined by a closed polygon that is used to extract LOCA-based extremes metrics specific to the area. For each metric, single-model data at each LOCA grid location are first averaged over several 30-year historical and future periods. Then, for each metric, the spatial average across the region is calculated using model weights based on both model independence and reproducibility of current climate conditions. The range of single-model results is also captured on the same localized basis, and then combined with the weighted ensemble average for each region and each metric. For example, Boston-area cooling degree days and maximum daily temperature is shown below for RCP8.5 (red) and RCP4.5 (blue) scenarios. We also discuss inter-regional comparison of these metrics, as well as their relevance to risk analysis for adaptation planning.
-
NASA Astrophysics Data System (ADS)
Wilson, R. I.; Barberopoulou, A.; Miller, K. M.; Goltz, J. D.; Synolakis, C. E.
2008-12-01
A consortium of tsunami hydrodynamic modelers, geologic hazard mapping specialists, and emergency planning managers is producing maximum tsunami inundation maps for California, covering most residential and transient populated areas along the state's coastline. The new tsunami inundation maps will be an upgrade from the existing maps for the state, improving on the resolution, accuracy, and coverage of the maximum anticipated tsunami inundation line. Thirty-five separate map areas covering nearly one-half of California's coastline were selected for tsunami modeling using the MOST (Method of Splitting Tsunami) model. From preliminary evaluations of nearly fifty local and distant tsunami source scenarios, those with the maximum expected hazard for a particular area were input to MOST. The MOST model was run with a near-shore bathymetric grid resolution varying from three arc-seconds (90m) to one arc-second (30m), depending on availability. Maximum tsunami "flow depth" and inundation layers were created by combining all modeled scenarios for each area. A method was developed to better define the location of the maximum inland penetration line using higher resolution digital onshore topographic data from interferometric radar sources. The final inundation line for each map area was validated using a combination of digital stereo photography and fieldwork. Further verification of the final inundation line will include ongoing evaluation of tsunami sources (seismic and submarine landslide) as well as comparison to the location of recorded paleotsunami deposits. Local governmental agencies can use these new maximum tsunami inundation lines to assist in the development of their evacuation routes and emergency response plans.
-
NASA Astrophysics Data System (ADS)
Zavattoni, Simone A.; Geissbühler, Lukas; Barbato, Maurizio C.; Zanganeh, Giw; Haselbacher, Andreas; Steinfeld, Aldo
2017-06-01
The concept of combined sensible/latent heat thermal energy storage (TES) has been exploited to mitigate an intrinsic thermocline TES systems drawback of heat transfer fluid outflow temperature reduction during discharging. In this study, the combined sensible/latent TES prototype under investigation is constituted by a packed bed of rocks and a small amount of encapsulated phase change material (AlSi12) as sensible heat and latent heat sections respectively. The thermo-fluid dynamics behavior of the combined TES prototype was analyzed by means of a computational fluid dynamics approach. Due to the small value of the characteristic vessel-to-particles diameter ratio, the effect of radial void-fraction variation, also known as channeling, was accounted for. Both the sensible and the latent heat sections of the storage were modeled as porous media under the assumption of local thermal non-equilibrium (LTNE). The commercial code ANSYS Fluent 15.0 was used to solve the model's constitutive conservation and transport equations obtaining a fairly good agreement with reference experimental measurements.
-
Florea, Cristina; Tanska, Petri; Mononen, Mika E; Qu, Chengjuan; Lammi, Mikko J; Laasanen, Mikko S; Korhonen, Rami K
2017-02-01
Cellular responses to mechanical stimuli are influenced by the mechanical properties of cells and the surrounding tissue matrix. Cells exhibit viscoelastic behavior in response to an applied stress. This has been attributed to fluid flow-dependent and flow-independent mechanisms. However, the particular mechanism that controls the local time-dependent behavior of cells is unknown. Here, a combined approach of experimental AFM nanoindentation with computational modeling is proposed, taking into account complex material behavior. Three constitutive models (porohyperelastic, viscohyperelastic, poroviscohyperelastic) in tandem with optimization algorithms were employed to capture the experimental stress relaxation data of chondrocytes at 5 % strain. The poroviscohyperelastic models with and without fluid flow allowed through the cell membrane provided excellent description of the experimental time-dependent cell responses (normalized mean squared error (NMSE) of 0.003 between the model and experiments). The viscohyperelastic model without fluid could not follow the entire experimental data that well (NMSE = 0.005), while the porohyperelastic model could not capture it at all (NMSE = 0.383). We also show by parametric analysis that the fluid flow has a small, but essential effect on the loading phase and short-term cell relaxation response, while the solid viscoelasticity controls the longer-term responses. We suggest that the local time-dependent cell mechanical response is determined by the combined effects of intrinsic viscoelasticity of the cytoskeleton and fluid flow redistribution in the cells, although the contribution of fluid flow is smaller when using a nanosized probe and moderate indentation rate. The present approach provides new insights into viscoelastic responses of chondrocytes, important for further understanding cell mechanobiological mechanisms in health and disease.
-
Optimal Combining Data for Improving Ocean Modeling
2008-09-30
hyperbolic or elliptic) and on the Hurst exponent characterizing the dynamics type (local or non-local). 3. Fusion data for estimating RD. Theoretical...1) RD vs time and different values of Hurst exponent h = 0.1 (black), h = 1 (red), h = 2 (blue) γ = 0.1,Ω = 0, 2) Same for γ = 0.1,Ω = 2 ). 3...accurate estimating the upper ocean velocity field and mixing characteristics such as relative dispersion and finite size Lyapunov exponent , (2
-
Real-time prediction of respiratory motion based on a local dynamic model in an augmented space
NASA Astrophysics Data System (ADS)
Hong, S.-M.; Jung, B.-H.; Ruan, D.
2011-03-01
Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively low observation rate. Sensitivity analysis indicates its robustness toward the choice of parameters. Its simplicity, robustness and low computation cost makes the proposed local dynamic model an attractive tool for real-time prediction with system latencies below 0.4 s.
-
Real-time prediction of respiratory motion based on a local dynamic model in an augmented space.
Hong, S-M; Jung, B-H; Ruan, D
2011-03-21
Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively low observation rate. Sensitivity analysis indicates its robustness toward the choice of parameters. Its simplicity, robustness and low computation cost makes the proposed local dynamic model an attractive tool for real-time prediction with system latencies below 0.4 s.
-
Mohammadi, Amrollah; Ahmadian, Alireza; Rabbani, Shahram; Fattahi, Ehsan; Shirani, Shapour
2017-12-01
Finite element models for estimation of intraoperative brain shift suffer from huge computational cost. In these models, image registration and finite element analysis are two time-consuming processes. The proposed method is an improved version of our previously developed Finite Element Drift (FED) registration algorithm. In this work the registration process is combined with the finite element analysis. In the Combined FED (CFED), the deformation of whole brain mesh is iteratively calculated by geometrical extension of a local load vector which is computed by FED. While the processing time of the FED-based method including registration and finite element analysis was about 70 s, the computation time of the CFED was about 3.2 s. The computational cost of CFED is almost 50% less than similar state of the art brain shift estimators based on finite element models. The proposed combination of registration and structural analysis can make the calculation of brain deformation much faster. Copyright © 2016 John Wiley & Sons, Ltd.
-
Combination of image descriptors for the exploration of cultural photographic collections
NASA Astrophysics Data System (ADS)
Bhowmik, Neelanjan; Gouet-Brunet, Valérie; Bloch, Gabriel; Besson, Sylvain
2017-01-01
The rapid growth of image digitization and collections in recent years makes it challenging and burdensome to organize, categorize, and retrieve similar images from voluminous collections. Content-based image retrieval (CBIR) is immensely convenient in this context. A considerable number of local feature detectors and descriptors are present in the literature of CBIR. We propose a model to anticipate the best feature combinations for image retrieval-related applications. Several spatial complementarity criteria of local feature detectors are analyzed and then engaged in a regression framework to find the optimal combination of detectors for a given dataset and are better adapted for each given image; the proposed model is also useful to optimally fix some other parameters, such as the k in k-nearest neighbor retrieval. Three public datasets of various contents and sizes are employed to evaluate the proposal, which is legitimized by improving the quality of retrieval notably facing classical approaches. Finally, the proposed image search engine is applied to the cultural photographic collections of a French museum, where it demonstrates its added value for the exploration and promotion of these contents at different levels from their archiving up to their exhibition in or ex situ.
-
BATTLE: Biomarker-Based Approaches of Targeted Therapy for Lung Cancer Elimination
2007-04-01
localization, which • The combination of erlotinib and Ad-dnIGF-1R synergistically inhibits the growth of tumors in xenograft mouse models . able outcomes...of erlotinib and Ad-dnIGF-1R synergistically inhibits the growth of tumors in xenograft mouse models . Specific Aim 2.3: To investigate the...biomarkers and adaptive randomization via hierarchical Bayes modeling . 2) To study the molecular mechanisms of response and resistance to targeted
-
Developing Local Scale, High Resolution, Data to Interface with Numerical Storm Models
NASA Astrophysics Data System (ADS)
Witkop, R.; Becker, A.; Stempel, P.
2017-12-01
High resolution, physical storm models that can rapidly predict storm surge, inundation, rainfall, wind velocity and wave height at the intra-facility scale for any storm affecting Rhode Island have been developed by Researchers at the University of Rhode Island's (URI's) Graduate School of Oceanography (GSO) (Ginis et al., 2017). At the same time, URI's Marine Affairs Department has developed methods that inhere individual geographic points into GSO's models and enable the models to accurately incorporate local scale, high resolution data (Stempel et al., 2017). This combination allows URI's storm models to predict any storm's impacts on individual Rhode Island facilities in near real time. The research presented here determines how a coastal Rhode Island town's critical facility managers (FMs) perceive their assets as being vulnerable to quantifiable hurricane-related forces at the individual facility scale and explores methods to elicit this information from FMs in a format usable for incorporation into URI's storm models.
-
Development of a recursion RNG-based turbulence model
NASA Technical Reports Server (NTRS)
Zhou, YE; Vahala, George; Thangam, S.
1993-01-01
Reynolds stress closure models based on the recursion renormalization group theory are developed for the prediction of turbulent separated flows. The proposed model uses a finite wavenumber truncation scheme to account for the spectral distribution of energy. In particular, the model incorporates effects of both local and nonlocal interactions. The nonlocal interactions are shown to yield a contribution identical to that from the epsilon-renormalization group (RNG), while the local interactions introduce higher order dispersive effects. A formal analysis of the model is presented and its ability to accurately predict separated flows is analyzed from a combined theoretical and computational stand point. Turbulent flow past a backward facing step is chosen as a test case and the results obtained based on detailed computations demonstrate that the proposed recursion -RNG model with finite cut-off wavenumber can yield very good predictions for the backstep problem.
-
NASA Astrophysics Data System (ADS)
Siami, Mohammad; Gholamian, Mohammad Reza; Basiri, Javad
2014-10-01
Nowadays, credit scoring is one of the most important topics in the banking sector. Credit scoring models have been widely used to facilitate the process of credit assessing. In this paper, an application of the locally linear model tree algorithm (LOLIMOT) was experimented to evaluate the superiority of its performance to predict the customer's credit status. The algorithm is improved with an aim of adjustment by credit scoring domain by means of data fusion and feature selection techniques. Two real world credit data sets - Australian and German - from UCI machine learning database were selected to demonstrate the performance of our new classifier. The analytical results indicate that the improved LOLIMOT significantly increase the prediction accuracy.
-
Vibration band gaps for elastic metamaterial rods using wave finite element method
NASA Astrophysics Data System (ADS)
Nobrega, E. D.; Gautier, F.; Pelat, A.; Dos Santos, J. M. C.
2016-10-01
Band gaps in elastic metamaterial rods with spatial periodic distribution and periodically attached local resonators are investigated. New techniques to analyze metamaterial systems are using a combination of analytical or numerical method with wave propagation. One of them, called here wave spectral element method (WSEM), consists of combining the spectral element method (SEM) with Floquet-Bloch's theorem. A modern methodology called wave finite element method (WFEM), developed to calculate dynamic behavior in periodic acoustic and structural systems, utilizes a similar approach where SEM is substituted by the conventional finite element method (FEM). In this paper, it is proposed to use WFEM to calculate band gaps in elastic metamaterial rods with spatial periodic distribution and periodically attached local resonators of multi-degree-of-freedom (M-DOF). Simulated examples with band gaps generated by Bragg scattering and local resonators are calculated by WFEM and verified with WSEM, which is used as a reference method. Results are presented in the form of attenuation constant, vibration transmittance and frequency response function (FRF). For all cases, WFEM and WSEM results are in agreement, provided that the number of elements used in WFEM is sufficient to convergence. An experimental test was conducted with a real elastic metamaterial rod, manufactured with plastic in a 3D printer, without local resonance-type effect. The experimental results for the metamaterial rod with band gaps generated by Bragg scattering are compared with the simulated ones. Both numerical methods (WSEM and WFEM) can localize the band gap position and width very close to the experimental results. A hybrid approach combining WFEM with the commercial finite element software ANSYS is proposed to model complex metamaterial systems. Two examples illustrating its efficiency and accuracy to model an elastic metamaterial rod unit-cell using 1D simple rod element and 3D solid element are demonstrated and the results present good approximation to the experimental data.
-
Zheng, Qingshan; Yang, Xiaolin; Lv, Rong; Ma, Longxiang; Liu, Jin; Zhu, Tao; Zhang, Wensheng
2017-01-01
Objective The quaternary lidocaine derivative (QX-314) in combination with bupivacaine can produce long-lasting nerve blocks in vivo, indicating potential clinical application. The aim of the study was to investigate the efficacy, safety, and the optimal formulation of this combination. Methods QX-314 and bupivacaine at different concentration ratios were injected in the vicinity of the sciatic nerve in rats; bupivacaine and saline served as controls (n = 6~10). Rats were inspected for durations of effective sensory and motor nerve blocks, systemic adverse effects, and histological changes of local tissues. Mathematical models were established to reveal drug-interaction, concentration-effect relationships, and the optimal ratio of QX-314 to bupivacaine. Results 0.2~1.5% QX-314 with 0.03~0.5% bupivacaine produced 5.8~23.8 h of effective nerve block; while 0.5% bupivacaine alone was effective for 4 h. No systemic side effects were observed; local tissue reactions were similar to those caused by 0.5% bupivacaine if QX-314 were used < 1.2%. The weighted modification model was successfully established, which revealed that QX-314 was the main active ingredient while bupivacaine was the synergist. The formulation, 0.9% QX-314 plus 0.5% bupivacaine, resulted in 10.1 ± 0.8 h of effective sensory and motor nerve blocks. Conclusion The combination of QX-314 and bupivacaine facilitated prolonged sciatic nerve block in rats with a satisfactory safety profile, maximizing the duration of nerve block without clinically important systemic and local tissue toxicity. It may emerge as an alternative approach to post-operative pain treatment. PMID:28334014
-
Yin, Qinqin; Li, Jun; Zheng, Qingshan; Yang, Xiaolin; Lv, Rong; Ma, Longxiang; Liu, Jin; Zhu, Tao; Zhang, Wensheng
2017-01-01
The quaternary lidocaine derivative (QX-314) in combination with bupivacaine can produce long-lasting nerve blocks in vivo, indicating potential clinical application. The aim of the study was to investigate the efficacy, safety, and the optimal formulation of this combination. QX-314 and bupivacaine at different concentration ratios were injected in the vicinity of the sciatic nerve in rats; bupivacaine and saline served as controls (n = 6~10). Rats were inspected for durations of effective sensory and motor nerve blocks, systemic adverse effects, and histological changes of local tissues. Mathematical models were established to reveal drug-interaction, concentration-effect relationships, and the optimal ratio of QX-314 to bupivacaine. 0.2~1.5% QX-314 with 0.03~0.5% bupivacaine produced 5.8~23.8 h of effective nerve block; while 0.5% bupivacaine alone was effective for 4 h. No systemic side effects were observed; local tissue reactions were similar to those caused by 0.5% bupivacaine if QX-314 were used < 1.2%. The weighted modification model was successfully established, which revealed that QX-314 was the main active ingredient while bupivacaine was the synergist. The formulation, 0.9% QX-314 plus 0.5% bupivacaine, resulted in 10.1 ± 0.8 h of effective sensory and motor nerve blocks. The combination of QX-314 and bupivacaine facilitated prolonged sciatic nerve block in rats with a satisfactory safety profile, maximizing the duration of nerve block without clinically important systemic and local tissue toxicity. It may emerge as an alternative approach to post-operative pain treatment.
-
An ear punch model for studying the effect of radiation on wound healing
DeOLIVEIRA, DIVINO; JIAO, YIQUN; ROSS, JOEL R.; CORBIN, KAYLA; XIAO, QIZHEN; TONCHEVA, GRETA; ANDERSON-EVANS, COLIN; YOSHIZUMI, TERRY T.; CHEN, BENNY J.; CHAO, NELSON J.
2011-01-01
Purpose Radiation and wound combined injury represents a major clinical challenge because of the synergistic interactions that lead to higher morbidity and mortality than either insult would produce singly. The purpose of this study was to develop a mouse ear punch model to study the physiological mechanisms underlying radiation effects on healing wounds. Materials and methods Surgical wounds were induced by a 2 mm surgical punch in the ear pinnae of MRL/MpJ mice. Photographs of the wounds were taken and the sizes of the ear punch wounds were quantified by image analysis. Local radiation to the ear was delivered by orthovoltage X-ray irradiator using a specially constructed jig that shields the other parts of body. Results Using this model, we demonstrated that local radiation to the wound area significantly delayed the healing of ear punch wounds in a dose-dependent fashion. The addition of sublethal whole body irradiation (7 Gy) further delayed the healing of ear punch wounds. These results were replicated in C57BL/6 mice; however, wound healing in MRL/MpJ mice was accelerated. Conclusions These data indicate that the mouse ear punch model is a valuable model to study radiation and wound combined injury. PMID:21480768
-
CALIBRATION OF SEMI-ANALYTIC MODELS OF GALAXY FORMATION USING PARTICLE SWARM OPTIMIZATION
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ruiz, Andrés N.; Domínguez, Mariano J.; Yaryura, Yamila
2015-03-10
We present a fast and accurate method to select an optimal set of parameters in semi-analytic models of galaxy formation and evolution (SAMs). Our approach compares the results of a model against a set of observables applying a stochastic technique called Particle Swarm Optimization (PSO), a self-learning algorithm for localizing regions of maximum likelihood in multidimensional spaces that outperforms traditional sampling methods in terms of computational cost. We apply the PSO technique to the SAG semi-analytic model combined with merger trees extracted from a standard Lambda Cold Dark Matter N-body simulation. The calibration is performed using a combination of observedmore » galaxy properties as constraints, including the local stellar mass function and the black hole to bulge mass relation. We test the ability of the PSO algorithm to find the best set of free parameters of the model by comparing the results with those obtained using a MCMC exploration. Both methods find the same maximum likelihood region, however, the PSO method requires one order of magnitude fewer evaluations. This new approach allows a fast estimation of the best-fitting parameter set in multidimensional spaces, providing a practical tool to test the consequences of including other astrophysical processes in SAMs.« less
-
NASA Astrophysics Data System (ADS)
Ntziachristos, Vasilis; Yodh, Arjun G.; Schnall, Mitchell D.; Ma, XuHui; Chance, Britton
1998-12-01
A single photon counting NIR imager designed to work simultaneously with an MRI scanner for concurrent NIR-MR mammography has recently been developed. The combination of imaging modalities aims in effectively investigating the competence of optical imaging as a stand along modality and as an MRI add-on in order to increase the sensitivity and specificity of the mammoraphic examination. In this work we focus on the second aim. We present the methodology developed to employ the MR anatomical information in order to simplify the forward problem and accurately calculate local tissue optical properties, by fitting the NIR data to this model. Derivation of local optical properties due to intrinsic or extrinsic may identify the existence of malignant and benign breast tissue NIR signatures. We have evaluated the performance of the solver with experimental measurements, also presented here, from models with known absorption perturbations. The average quantification error of absolute absorption of local lesions has been found to be less than 10% in simple models and algorithm convergence is always ensured.
-
Budach, W; Paulsen, F; Welz, S; Classen, J; Scheithauer, H; Marini, P; Belka, C; Bamberg, M
2002-01-01
The potential of Mitomycin C in combination with fractionated irradiation to inhibit tumour cell repopulation of a fast growing squamous cell carcinoma after fractionated radiotherapy was investigated in vivo. A rapidly growing human squamous cell carcinoma (FaDudd) was used for the study. For experiments, NMRI (nu/nu) mice with subcutaneously growing tumours were randomly allocated to no treatment, Mitomycin C, fractionated irradiation (ambient: 11x4.5 Gy in 15 days), or fractionated irradiation combined with Mitomycin C. Graded top up doses (clamped blood flow: 0–57 Gy) were given at day 16, 23, 30 or 37. End point of the study was the time to local tumour progression. Data were examined by multiple regression analysis (Cox). Mitomycin C alone resulted in a median time to local tumour progression of 23 (95% confidence limits: 17–43) days, fractionated irradiation in 31 (25–35) days and combined Mitomycin C plus fractionated irradiation in 65 (58–73) days (P=0.02). Mitomycin C decreased the relative risk of local recurrence by 94% (P<<0.001) equivalent to 31.7 Gy top up dose. Repopulation accounted for 1.33 (0.95–1.72) Gy per day top up dose after fractionated irradiation alone and for 0.68 (0.13–1.22) Gy per day after fractionated irradiation+Mitomycin C (P=0.018). Mitomycin C significantly reduces the risk of local recurrence and inhibits tumour cell repopulation in combination with fractionated irradiation in vivo in the tested tumour model. British Journal of Cancer (2002) 86, 470–476. DOI: 10.1038/sj/bjc/6600081 www.bjcancer.com © 2002 The Cancer Research Campaign PMID:11875717
-
A stacking ensemble learning framework for annual river ice breakup dates
NASA Astrophysics Data System (ADS)
Sun, Wei; Trevor, Bernard
2018-06-01
River ice breakup dates (BDs) are not merely a proxy indicator of climate variability and change, but a direct concern in the management of local ice-caused flooding. A framework of stacking ensemble learning for annual river ice BDs was developed, which included two-level components: member and combining models. The member models described the relations between BD and their affecting indicators; the combining models linked the predicted BD by each member models with the observed BD. Especially, Bayesian regularization back-propagation artificial neural network (BRANN), and adaptive neuro fuzzy inference systems (ANFIS) were employed as both member and combining models. The candidate combining models also included the simple average methods (SAM). The input variables for member models were selected by a hybrid filter and wrapper method. The performances of these models were examined using the leave-one-out cross validation. As the largest unregulated river in Alberta, Canada with ice jams frequently occurring in the vicinity of Fort McMurray, the Athabasca River at Fort McMurray was selected as the study area. The breakup dates and candidate affecting indicators in 1980-2015 were collected. The results showed that, the BRANN member models generally outperformed the ANFIS member models in terms of better performances and simpler structures. The difference between the R and MI rankings of inputs in the optimal member models may imply that the linear correlation based filter method would be feasible to generate a range of candidate inputs for further screening through other wrapper or embedded IVS methods. The SAM and BRANN combining models generally outperformed all member models. The optimal SAM combining model combined two BRANN member models and improved upon them in terms of average squared errors by 14.6% and 18.1% respectively. In this study, for the first time, the stacking ensemble learning was applied to forecasting of river ice breakup dates, which appeared promising for other river ice forecasting problems.
-
A model-based approach to wildland fire reconstruction using sediment charcoal records
Itter, Malcolm S.; Finley, Andrew O.; Hooten, Mevin B.; Higuera, Philip E.; Marlon, Jennifer R.; Kelly, Ryan; McLachlan, Jason S.
2017-01-01
Lake sediment charcoal records are used in paleoecological analyses to reconstruct fire history, including the identification of past wildland fires. One challenge of applying sediment charcoal records to infer fire history is the separation of charcoal associated with local fire occurrence and charcoal originating from regional fire activity. Despite a variety of methods to identify local fires from sediment charcoal records, an integrated statistical framework for fire reconstruction is lacking. We develop a Bayesian point process model to estimate the probability of fire associated with charcoal counts from individual-lake sediments and estimate mean fire return intervals. A multivariate extension of the model combines records from multiple lakes to reduce uncertainty in local fire identification and estimate a regional mean fire return interval. The univariate and multivariate models are applied to 13 lakes in the Yukon Flats region of Alaska. Both models resulted in similar mean fire return intervals (100–350 years) with reduced uncertainty under the multivariate model due to improved estimation of regional charcoal deposition. The point process model offers an integrated statistical framework for paleofire reconstruction and extends existing methods to infer regional fire history from multiple lake records with uncertainty following directly from posterior distributions.
-
Strong Local-Nonlocal Coupling for Integrated Fracture Modeling
DOE Office of Scientific and Technical Information (OSTI.GOV)
Littlewood, David John; Silling, Stewart A.; Mitchell, John A.
Peridynamics, a nonlocal extension of continuum mechanics, is unique in its ability to capture pervasive material failure. Its use in the majority of system-level analyses carried out at Sandia, however, is severely limited, due in large part to computational expense and the challenge posed by the imposition of nonlocal boundary conditions. Combined analyses in which peridynamics is em- ployed only in regions susceptible to material failure are therefore highly desirable, yet available coupling strategies have remained severely limited. This report is a summary of the Laboratory Directed Research and Development (LDRD) project "Strong Local-Nonlocal Coupling for Inte- grated Fracture Modeling,"more » completed within the Computing and Information Sciences (CIS) In- vestment Area at Sandia National Laboratories. A number of challenges inherent to coupling local and nonlocal models are addressed. A primary result is the extension of peridynamics to facilitate a variable nonlocal length scale. This approach, termed the peridynamic partial stress, can greatly reduce the mathematical incompatibility between local and nonlocal equations through reduction of the peridynamic horizon in the vicinity of a model interface. A second result is the formulation of a blending-based coupling approach that may be applied either as the primary coupling strategy, or in combination with the peridynamic partial stress. This blending-based approach is distinct from general blending methods, such as the Arlequin approach, in that it is specific to the coupling of peridynamics and classical continuum mechanics. Facilitating the coupling of peridynamics and classical continuum mechanics has also required innovations aimed directly at peridynamic models. Specifically, the properties of peridynamic constitutive models near domain boundaries and shortcomings in available discretization strategies have been addressed. The results are a class of position-aware peridynamic constitutive laws for dramatically improved consistency at domain boundaries, and an enhancement to the meshfree discretization applied to peridynamic models that removes irregularities at the limit of the nonlocal length scale and dramatically improves conver- gence behavior. Finally, a novel approach for modeling ductile failure has been developed, moti- vated by the desire to apply coupled local-nonlocal models to a wide variety of materials, including ductile metals, which have received minimal attention in the peridynamic literature. Software im- plementation of the partial-stress coupling strategy, the position-aware peridynamic constitutive models, and the strategies for improving the convergence behavior of peridynamic models was completed within the Peridigm and Albany codes, developed at Sandia National Laboratories and made publicly available under the open-source 3-clause BSD license.« less
-
Progressive Failure Analysis of Composite Stiffened Panels
NASA Technical Reports Server (NTRS)
Bednarcyk, Brett A.; Yarrington, Phillip W.; Collier, Craig S.; Arnold, Steven M.
2006-01-01
A new progressive failure analysis capability for stiffened composite panels has been developed based on the combination of the HyperSizer stiffened panel design/analysis/optimization software with the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC). MAC/GMC discretizes a composite material s microstructure into a number of subvolumes and solves for the stress and strain state in each while providing the homogenized composite properties as well. As a result, local failure criteria may be employed to predict local subvolume failure and the effects of these local failures on the overall composite response. When combined with HyperSizer, MAC/GMC is employed to represent the ply level composite material response within the laminates that constitute a stiffened panel. The effects of local subvolume failures can then be tracked as loading on the stiffened panel progresses. Sample progressive failure results are presented at both the composite laminate and the composite stiffened panel levels. Deformation and failure model predictions are compared with experimental data from the World Wide Failure Exercise for AS4/3501-6 graphite/epoxy laminates.
-
Cheung, Y M; Leung, W M; Xu, L
1997-01-01
We propose a prediction model called Rival Penalized Competitive Learning (RPCL) and Combined Linear Predictor method (CLP), which involves a set of local linear predictors such that a prediction is made by the combination of some activated predictors through a gating network (Xu et al., 1994). Furthermore, we present its improved variant named Adaptive RPCL-CLP that includes an adaptive learning mechanism as well as a data pre-and-post processing scheme. We compare them with some existing models by demonstrating their performance on two real-world financial time series--a China stock price and an exchange-rate series of US Dollar (USD) versus Deutschmark (DEM). Experiments have shown that Adaptive RPCL-CLP not only outperforms the other approaches with the smallest prediction error and training costs, but also brings in considerable high profits in the trading simulation of foreign exchange market.
-
Ontology Design Patterns as Interfaces (invited)
NASA Astrophysics Data System (ADS)
Janowicz, K.
2015-12-01
In recent years ontology design patterns (ODP) have gained popularity among knowledge engineers. ODPs are modular but self-contained building blocks that are reusable and extendible. They minimize the amount of ontological commitments and thereby are easier to integrate than large monolithic ontologies. Typically, patterns are not directly used to annotate data or to model certain domain problems but are combined and extended to form data and purpose-driven local ontologies that serve the needs of specific applications or communities. By relying on a common set of patterns these local ontologies can be aligned to improve interoperability and enable federated queries without enforcing a top-down model of the domain. In previous work, we introduced ontological views as layer on top of ontology design patterns to ease the reuse, combination, and integration of patterns. While the literature distinguishes multiple types of patterns, e.g., content patterns or logical patterns, we propose to use them as interfaces here to guide the development of ontology-driven systems.
-
NASA Technical Reports Server (NTRS)
Mixson, J. S.; Roussos, L. A.
1986-01-01
Possible reasons for disagreement between measured and predicted trends of sidewall noise transmission at low frequency are investigated using simplified analysis methods. An analytical model combining incident plane acoustic waves with an infinite flat panel is used to study the effects of sound incidence angle, plate structural properties, frequency, absorption, and the difference between noise reduction and transmission loss. Analysis shows that these factors have significant effects on noise transmission but they do not account for the differences between measured and predicted trends at low frequencies. An analytical model combining an infinite flat plate with a normally incident acoustic wave having exponentially decaying magnitude along one coordinate is used to study the effect of a localized source distribution such as is associated with propeller noise. Results show that the localization brings the predicted low-frequency trend of noise transmission into better agreement with measured propeller results. This effect is independent of low-frequency stiffness effects that have been previously reported to be associated with boundary conditions.
-
Alessandrini, Francesca; Fuchs, Helmut; Gailus-Durner, Valerie; Hrabě de Angelis, Martin; Russkamp, Dennis; Chaker, Adam; Ollert, Markus; Gutermuth, Jan; Schmidt-Weber, Carsten B.
2017-01-01
Background Allergen-specific immunotherapy (AIT) is the only curative treatment for type-1 allergies, but sometimes shows limited therapeutic response as well as local and systemic side effects. Limited control of local inflammation and patient symptoms hampers its widespread use in severe allergic asthma. Objective Our aim was to evaluate whether AIT is more effective in suppression of local inflammation if performed under the umbrella of short-term non-specific immunomodulation using a small molecule inhibitor of JAK pathways. Methods In C57BL/6J mice, a model of ovalbumin (OVA)-induced allergic airway inflammation and allergen-specific immunotherapy was combined with the administration of Tofacitinib (TOFA, a FDA-approved JAK inhibitor) from 48 hours prior to 48 hours after therapeutic OVA-injection. The effect of TOFA on human FOXP3+CD4+ T cells was studied in vitro. Results AIT combined with short-term TOFA administration was significantly more effective in suppressing total cell and eosinophil infiltration into the lung, local cytokine production including IL-1β and CXCL1 and showed a trend for the reduction of IL-4, IL-13, TNF-α and IL-6 compared to AIT alone. Furthermore, TOFA co-administration significantly reduced systemic IL-6, IL-1β and OVA-specific IgE levels and induced IgG1 to the same extent as AIT alone. Additionally, TOFA enhanced the induction of human FOXP3+CD4+ T cells. Conclusions This proof of concept study shows that JAK inhibition did not inhibit tolerance induction, but improved experimental AIT at the level of local inflammation. The improved control of local inflammation might extend the use of AIT in more severe conditions such as polyallergy, asthma and high-risk patients suffering from mastocytosis or anaphylaxis. PMID:28570653
-
Aguilar-Pimentel, Antonio; Graessel, Anke; Alessandrini, Francesca; Fuchs, Helmut; Gailus-Durner, Valerie; Hrabě de Angelis, Martin; Russkamp, Dennis; Chaker, Adam; Ollert, Markus; Blank, Simon; Gutermuth, Jan; Schmidt-Weber, Carsten B
2017-01-01
Allergen-specific immunotherapy (AIT) is the only curative treatment for type-1 allergies, but sometimes shows limited therapeutic response as well as local and systemic side effects. Limited control of local inflammation and patient symptoms hampers its widespread use in severe allergic asthma. Our aim was to evaluate whether AIT is more effective in suppression of local inflammation if performed under the umbrella of short-term non-specific immunomodulation using a small molecule inhibitor of JAK pathways. In C57BL/6J mice, a model of ovalbumin (OVA)-induced allergic airway inflammation and allergen-specific immunotherapy was combined with the administration of Tofacitinib (TOFA, a FDA-approved JAK inhibitor) from 48 hours prior to 48 hours after therapeutic OVA-injection. The effect of TOFA on human FOXP3+CD4+ T cells was studied in vitro. AIT combined with short-term TOFA administration was significantly more effective in suppressing total cell and eosinophil infiltration into the lung, local cytokine production including IL-1β and CXCL1 and showed a trend for the reduction of IL-4, IL-13, TNF-α and IL-6 compared to AIT alone. Furthermore, TOFA co-administration significantly reduced systemic IL-6, IL-1β and OVA-specific IgE levels and induced IgG1 to the same extent as AIT alone. Additionally, TOFA enhanced the induction of human FOXP3+CD4+ T cells. This proof of concept study shows that JAK inhibition did not inhibit tolerance induction, but improved experimental AIT at the level of local inflammation. The improved control of local inflammation might extend the use of AIT in more severe conditions such as polyallergy, asthma and high-risk patients suffering from mastocytosis or anaphylaxis.
-
Processes governing phytoplankton blooms in estuaries. II: The role of horizontal transport
Lucas, L.V.; Koseff, Jeffrey R.; Monismith, Stephen G.; Cloern, J.E.; Thompson, J.K.
1999-01-01
The development and distribution of phytoplankton blooms in estuaries are functions of both local conditions (i.e. the production-loss balance for a water column at a particular spatial location) and large-scale horizontal transport. In this study, the second of a 2-paper series, we use a depth-averaged hydrodynamic-biological model to identify transport-related mechanisms impacting phytoplankton biomass accumulation and distribution on a system level. We chose South San Francisco Bay as a model domain, since its combination of a deep channel surrounded by broad shoals is typical of drowned-river estuaries. Five general mechanisms involving interaction of horizontal transport with variability in local conditions are discussed. Residual (on the order of days to weeks) transport mechanisms affecting bloom development and location include residence time/export, import, and the role of deep channel regions as conduits for mass transport. Interactions occurring on tidal time scales, i.e. on the order of hours) include the phasing of lateral oscillatory tidal flow relative to temporal changes in local net phytoplankton growth rates, as well as lateral sloshing of shoal-derived biomass into deep channel regions during ebb and back into shallow regions during flood tide. Based on these results, we conclude that: (1) while local conditions control whether a bloom is possible, the combination of transport and spatial-temporal variability in local conditions determines if and where a bloom will actually occur; (2) tidal-time-scale physical-biological interactions provide important mechanisms for bloom development and evolution. As a result of both subtidal and tidal-time-scale transport processes, peak biomass may not be observed where local conditions are most favorable to phytoplankton production, and inherently unproductive areas may be regions of high biomass accumulation.
-
A complex speciation–richness relationship in a simple neutral model
Desjardins-Proulx, Philippe; Gravel, Dominique
2012-01-01
Speciation is the “elephant in the room” of community ecology. As the ultimate source of biodiversity, its integration in ecology's theoretical corpus is necessary to understand community assembly. Yet, speciation is often completely ignored or stripped of its spatial dimension. Recent approaches based on network theory have allowed ecologists to effectively model complex landscapes. In this study, we use this framework to model allopatric and parapatric speciation in networks of communities. We focus on the relationship between speciation, richness, and the spatial structure of communities. We find a strong opposition between speciation and local richness, with speciation being more common in isolated communities and local richness being higher in more connected communities. Unlike previous models, we also find a transition to a positive relationship between speciation and local richness when dispersal is low and the number of communities is small. We use several measures of centrality to characterize the effect of network structure on diversity. The degree, the simplest measure of centrality, is the best predictor of local richness and speciation, although it loses some of its predictive power as connectivity grows. Our framework shows how a simple neutral model can be combined with network theory to reveal complex relationships between speciation, richness, and the spatial organization of populations. PMID:22957181
-
A malaria transmission-directed model of mosquito life cycle and ecology
2011-01-01
Background Malaria is a major public health issue in much of the world, and the mosquito vectors which drive transmission are key targets for interventions. Mathematical models for planning malaria eradication benefit from detailed representations of local mosquito populations, their natural dynamics and their response to campaign pressures. Methods A new model is presented for mosquito population dynamics, effects of weather, and impacts of multiple simultaneous interventions. This model is then embedded in a large-scale individual-based simulation and results for local elimination of malaria are discussed. Mosquito population behaviours, such as anthropophily and indoor feeding, are included to study their effect upon the efficacy of vector control-based elimination campaigns. Results Results for vector control tools, such as bed nets, indoor spraying, larval control and space spraying, both alone and in combination, are displayed for a single-location simulation with vector species and seasonality characteristic of central Tanzania, varying baseline transmission intensity and vector bionomics. The sensitivities to habitat type, anthropophily, indoor feeding, and baseline transmission intensity are explored. Conclusions The ability to model a spectrum of local vector species with different ecologies and behaviours allows local customization of packages of interventions and exploration of the effect of proposed new tools. PMID:21999664
-
Zhang, Xuanwei; Niedermann, Gabriele
2018-05-01
Hypofractionated radiation therapy (hRT) combined with immune checkpoint blockade can induce T-cell-mediated local and abscopal antitumor effects. We had previously observed peak levels of tumor-infiltrating lymphocytes (TILs) between days 5 and 8 after hRT. Because TILs are regarded as radiosensitive, hRT schedules extending into this period might be less immunogenic, prompting us to compare clinically relevant, short and extended schedules with equivalent biologically effective doses combined with anti-programmed cell death 1 (PD1) antibody treatment. In mice bearing 2 B16-CD133 melanoma tumors, the primary tumor was irradiated with 3 × 9.18 Gy in 3 or 5 days or with 5 × 6.43 Gy in 10 days; an anti-PD1 antibody was given weekly. The mice were monitored for tumor growth and survival. T-cell responses were determined on days 8 and 15 of treatment. The role of regional lymph nodes was studied by administering FTY720, which blocks lymph node egress of activated T cells. Tumor growth measurements after combination treatment using short or extended hRT and control treatment were also performed in the wild-type B16 melanoma and 4T1 breast carcinoma models. In the B16-CD133 model, growth inhibition of irradiated primary and nonirradiated secondary tumors and overall survival were similar with all 3 hRT/anti-PD1 combinations, superior to hRT and anti-PD1 monotherapy, and was strongly dependent on CD8 + T cells. TIL infiltration and local and systemic tumor-specific CD8 + T-cell responses were also similar, regardless of whether short or extended hRT was used. Administration of FTY720 accelerated growth of both primary and secondary tumors, strongly reduced their TIL infiltration, and increased tumor-specific CD8 + T cells in the lymph nodes draining the irradiated tumor. In the 4T1 model, local and abscopal tumor control was also similar, regardless of whether short or extended hRT was used, although the synergy between hRT and anti-PD1 was weaker. No synergies were found in the B16 wild-type model lacking an exogenous antigen. Our data suggest that combination therapy with hRT schedules extending into the period during which treatment-induced T cells infiltrate the irradiated tumor can provoke local and systemic antitumor effects similar to those with therapy using shorter schedules, if the regional lymph nodes supply sufficient tumor-specific T cells. This has implications for planning clinical RT/immune checkpoint blockade trials. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.
-
The numerical modelling of MHD astrophysical flows with chemistry
NASA Astrophysics Data System (ADS)
Kulikov, I.; Chernykh, I.; Protasov, V.
2017-10-01
The new code for numerical simulation of magnetic hydrodynamical astrophysical flows with consideration of chemical reactions is given in the paper. At the heart of the code - the new original low-dissipation numerical method based on a combination of operator splitting approach and piecewise-parabolic method on the local stencil. The chemodynamics of the hydrogen while the turbulent formation of molecular clouds is modeled.
-
Improving and Evaluating Nested Sampling Algorithm for Marginal Likelihood Estimation
NASA Astrophysics Data System (ADS)
Ye, M.; Zeng, X.; Wu, J.; Wang, D.; Liu, J.
2016-12-01
With the growing impacts of climate change and human activities on the cycle of water resources, an increasing number of researches focus on the quantification of modeling uncertainty. Bayesian model averaging (BMA) provides a popular framework for quantifying conceptual model and parameter uncertainty. The ensemble prediction is generated by combining each plausible model's prediction, and each model is attached with a model weight which is determined by model's prior weight and marginal likelihood. Thus, the estimation of model's marginal likelihood is crucial for reliable and accurate BMA prediction. Nested sampling estimator (NSE) is a new proposed method for marginal likelihood estimation. The process of NSE is accomplished by searching the parameters' space from low likelihood area to high likelihood area gradually, and this evolution is finished iteratively via local sampling procedure. Thus, the efficiency of NSE is dominated by the strength of local sampling procedure. Currently, Metropolis-Hasting (M-H) algorithm is often used for local sampling. However, M-H is not an efficient sampling algorithm for high-dimensional or complicated parameter space. For improving the efficiency of NSE, it could be ideal to incorporate the robust and efficient sampling algorithm - DREAMzs into the local sampling of NSE. The comparison results demonstrated that the improved NSE could improve the efficiency of marginal likelihood estimation significantly. However, both improved and original NSEs suffer from heavy instability. In addition, the heavy computation cost of huge number of model executions is overcome by using an adaptive sparse grid surrogates.
-
Compressor Performance Scaling in the Presence of Non-Uniform Flow
NASA Astrophysics Data System (ADS)
Hill, David Jarrod
Fuselage-embedded engines in future aircraft will see increased flow distortions due to the ingestion of airframe boundary layers. This reduces the required propulsive power compared to podded engines. Inlet flow distortions mean that localized regions of flow within the fan and first stage compressor are operating at off-design conditions. It is important to weigh the benefit of increased vehicle propulsive efficiency against the resultant reduction in engine efficiency. High computational cost has limited most past research to single distortion studies. The objective of this thesis is to extract scaling laws for transonic compressor performance in the presence of various distortion patterns and intensities. The machine studied is the NASA R67 transonic compressor. Volumetric source terms are used to model rotor and stator blade rows. The modelling approach is an innovative combination of existing flow turning and loss models, combined with a compressible flow correction. This approach allows for a steady calculation to capture distortion transfer; as a result, the computational cost is reduced by two orders of magnitude. At peak efficiency, the rotor work coefficient and isentropic efficiency are matched within 1.4% of previously published experimental results. A key finding of this thesis is that, in non-uniform flow, the state-of-the-art loss model employed is unable to capture the impact of variations in local flow coefficient, limiting the analysis of local entropy generation. New insight explains the mechanism governing the interaction between a total temperature distortion and a compressor rotor. A parametric study comprising 16 inlet distortions reveals that for total temperature distortions, upstream flow redistribution and rotor diffusion factor changes are shown to scale linearly with distortion severity. Linear diffusion factor scaling does not hold true for total pressure distortions. For combined total temperature and total pressure distortions, the changes in rotor diffusion factor are predicted by the summation of the individual distortions, within 3.65%.
-
Fundamental resource-allocating model in colleges and universities based on Immune Clone Algorithms
NASA Astrophysics Data System (ADS)
Ye, Mengdie
2017-05-01
In this thesis we will seek the combination of antibodies and antigens converted from the optimal course arrangement and make an analogy with Immune Clone Algorithms. According to the character of the Algorithms, we apply clone, clone gene and clone selection to arrange courses. Clone operator can combine evolutionary search and random search, global search and local search. By cloning and clone mutating candidate solutions, we can find the global optimal solution quickly.
-
The Survey of Vision-based 3D Modeling Techniques
NASA Astrophysics Data System (ADS)
Ruan, Mingzhe
2017-10-01
This paper reviews the vision-based localization and map construction methods from the perspectives of VSLAM, SFM, 3DMax and Unity3D. It focuses on the key technologies and the latest research progress on each aspect, analyzes the advantages and disadvantages of each method, illustrates their implementation process and system framework, and further discusses the way to promote the combination for their complementary strength. Finally, the future opportunity of the combination of the four techniques is expected.
-
McKim, James M.; Hartung, Thomas; Kleensang, Andre; Sá-Rocha, Vanessa
2016-01-01
Supervised learning methods promise to improve integrated testing strategies (ITS), but must be adjusted to handle high dimensionality and dose–response data. ITS approaches are currently fueled by the increasing mechanistic understanding of adverse outcome pathways (AOP) and the development of tests reflecting these mechanisms. Simple approaches to combine skin sensitization data sets, such as weight of evidence, fail due to problems in information redundancy and high dimension-ality. The problem is further amplified when potency information (dose/response) of hazards would be estimated. Skin sensitization currently serves as the foster child for AOP and ITS development, as legislative pressures combined with a very good mechanistic understanding of contact dermatitis have led to test development and relatively large high-quality data sets. We curated such a data set and combined a recursive variable selection algorithm to evaluate the information available through in silico, in chemico and in vitro assays. Chemical similarity alone could not cluster chemicals’ potency, and in vitro models consistently ranked high in recursive feature elimination. This allows reducing the number of tests included in an ITS. Next, we analyzed with a hidden Markov model that takes advantage of an intrinsic inter-relationship among the local lymph node assay classes, i.e. the monotonous connection between local lymph node assay and dose. The dose-informed random forest/hidden Markov model was superior to the dose-naive random forest model on all data sets. Although balanced accuracy improvement may seem small, this obscures the actual improvement in misclassifications as the dose-informed hidden Markov model strongly reduced "false-negatives" (i.e. extreme sensitizers as non-sensitizer) on all data sets. PMID:26046447
-
Forman, Jason L.; Kent, Richard W.; Mroz, Krystoffer; Pipkorn, Bengt; Bostrom, Ola; Segui-Gomez, Maria
2012-01-01
This study sought to develop a strain-based probabilistic method to predict rib fracture risk with whole-body finite element (FE) models, and to describe a method to combine the results with collision exposure information to predict injury risk and potential intervention effectiveness in the field. An age-adjusted ultimate strain distribution was used to estimate local rib fracture probabilities within an FE model. These local probabilities were combined to predict injury risk and severity within the whole ribcage. The ultimate strain distribution was developed from a literature dataset of 133 tests. Frontal collision simulations were performed with the THUMS (Total HUman Model for Safety) model with four levels of delta-V and two restraints: a standard 3-point belt and a progressive 3.5–7 kN force-limited, pretensioned (FL+PT) belt. The results of three simulations (29 km/h standard, 48 km/h standard, and 48 km/h FL+PT) were compared to matched cadaver sled tests. The numbers of fractures predicted for the comparison cases were consistent with those observed experimentally. Combining these results with field exposure informantion (ΔV, NASS-CDS 1992–2002) suggests a 8.9% probability of incurring AIS3+ rib fractures for a 60 year-old restrained by a standard belt in a tow-away frontal collision with this restraint, vehicle, and occupant configuration, compared to 4.6% for the FL+PT belt. This is the first study to describe a probabilistic framework to predict rib fracture risk based on strains observed in human-body FE models. Using this analytical framework, future efforts may incorporate additional subject or collision factors for multi-variable probabilistic injury prediction. PMID:23169122
-
Luechtefeld, Thomas; Maertens, Alexandra; McKim, James M; Hartung, Thomas; Kleensang, Andre; Sá-Rocha, Vanessa
2015-11-01
Supervised learning methods promise to improve integrated testing strategies (ITS), but must be adjusted to handle high dimensionality and dose-response data. ITS approaches are currently fueled by the increasing mechanistic understanding of adverse outcome pathways (AOP) and the development of tests reflecting these mechanisms. Simple approaches to combine skin sensitization data sets, such as weight of evidence, fail due to problems in information redundancy and high dimensionality. The problem is further amplified when potency information (dose/response) of hazards would be estimated. Skin sensitization currently serves as the foster child for AOP and ITS development, as legislative pressures combined with a very good mechanistic understanding of contact dermatitis have led to test development and relatively large high-quality data sets. We curated such a data set and combined a recursive variable selection algorithm to evaluate the information available through in silico, in chemico and in vitro assays. Chemical similarity alone could not cluster chemicals' potency, and in vitro models consistently ranked high in recursive feature elimination. This allows reducing the number of tests included in an ITS. Next, we analyzed with a hidden Markov model that takes advantage of an intrinsic inter-relationship among the local lymph node assay classes, i.e. the monotonous connection between local lymph node assay and dose. The dose-informed random forest/hidden Markov model was superior to the dose-naive random forest model on all data sets. Although balanced accuracy improvement may seem small, this obscures the actual improvement in misclassifications as the dose-informed hidden Markov model strongly reduced " false-negatives" (i.e. extreme sensitizers as non-sensitizer) on all data sets. Copyright © 2015 John Wiley & Sons, Ltd.
-
A Localized Ensemble Kalman Smoother
NASA Technical Reports Server (NTRS)
Butala, Mark D.
2012-01-01
Numerous geophysical inverse problems prove difficult because the available measurements are indirectly related to the underlying unknown dynamic state and the physics governing the system may involve imperfect models or unobserved parameters. Data assimilation addresses these difficulties by combining the measurements and physical knowledge. The main challenge in such problems usually involves their high dimensionality and the standard statistical methods prove computationally intractable. This paper develops and addresses the theoretical convergence of a new high-dimensional Monte-Carlo approach called the localized ensemble Kalman smoother.
-
Breathers in systems with intrinsic and extrinsic nonlinearities
NASA Astrophysics Data System (ADS)
Cruzeiro-Hansson, L.; Eilbeck, J. C.; Marín, J. L.; Russell, F. M.
2000-08-01
We study the interplay between nonlinearity and localization in a model consisting of a quantum quasiparticle interacting with a nonlinear extended lattice. The isolated lattice can support discrete breathers, and the coupling of the quasiparticle to the lattice leads to localized quasiparticle states. Minimum energy states of the full system can have both a breather and a solitonic character. Excited states lead to interesting new phenomena, such as full breather states, which arise from the combination of intrinsic and extrinsic nonlinearity.
-
Ménard, Richard; Deshaies-Jacques, Martin; Gasset, Nicolas
2016-09-01
An objective analysis is one of the main components of data assimilation. By combining observations with the output of a predictive model we combine the best features of each source of information: the complete spatial and temporal coverage provided by models, with a close representation of the truth provided by observations. The process of combining observations with a model output is called an analysis. To produce an analysis requires the knowledge of observation and model errors, as well as its spatial correlation. This paper is devoted to the development of methods of estimation of these error variances and the characteristic length-scale of the model error correlation for its operational use in the Canadian objective analysis system. We first argue in favor of using compact support correlation functions, and then introduce three estimation methods: the Hollingsworth-Lönnberg (HL) method in local and global form, the maximum likelihood method (ML), and the [Formula: see text] diagnostic method. We perform one-dimensional (1D) simulation studies where the error variance and true correlation length are known, and perform an estimation of both error variances and correlation length where both are non-uniform. We show that a local version of the HL method can capture accurately the error variances and correlation length at each observation site, provided that spatial variability is not too strong. However, the operational objective analysis requires only a single and globally valid correlation length. We examine whether any statistics of the local HL correlation lengths could be a useful estimate, or whether other global estimation methods such as by the global HL, ML, or [Formula: see text] should be used. We found in both 1D simulation and using real data that the ML method is able to capture physically significant aspects of the correlation length, while most other estimates give unphysical and larger length-scale values. This paper describes a proposed improvement of the objective analysis of surface pollutants at Environment and Climate Change Canada (formerly known as Environment Canada). Objective analyses are essentially surface maps of air pollutants that are obtained by combining observations with an air quality model output, and are thought to provide a complete and more accurate representation of the air quality. The highlight of this study is an analysis of methods to estimate the model (or background) error correlation length-scale. The error statistics are an important and critical component to the analysis scheme.
-
Pollutant Dilution and Diffusion in Urban Street Canyon Neighboring Streets
NASA Astrophysics Data System (ADS)
Sun, Z.; Fu, Zh. M.
2011-09-01
In the present study we investigated the airflow patterns and air quality of a series of typical street canyon combinations, developed a mass balance model to determine the local pollutant dilution rate, and discuss the impact of upstream canyon on the air quality of downstream canyon. The results indicated that the geometrical size of upstream and downstream buildings have significant impacts on the ambient airflow patterns. The pollution distribution within the canyons varies with different building combinations and flow patterns. Within the upstream canyon, pollution always accumulates to the low building side for non-symmetrical canyon, and for symmetrical canyon high level of pollution occurs at the leeward side. The height of the middle and downstream buildings can evidently change the pollutant dispersion direction during the transport process. Within the polluted canyon, the pollutant dilution rate (PDR) also varies with different street canyon combinations. The highest PDR is observed when the upstream buildings are both low buildings no matter the height of downstream building. However, the two cases are likely to contribution pollution to the downstream canyon. The H-L-H combination is mostly against local pollution remove, while the L-H-L case is considered the best optimistic building combination with both the ability of diluting local pollution and not remarkably decreasing air quality of downstream canyon. The current work is expected instructive for city designers to optimize traffic patterns under typical existing geometry or in the development of urban geometry modification for air quality control.
-
NASA Astrophysics Data System (ADS)
Wilkinson, Mark; Beven, Keith; Brewer, Paul; El-khatib, Yehia; Gemmell, Alastair; Haygarth, Phil; Mackay, Ellie; Macklin, Mark; Marshall, Keith; Quinn, Paul; Stutter, Marc; Thomas, Nicola; Vitolo, Claudia
2013-04-01
Today's world is dominated by a wide range of informatics tools that are readily available to a wide range of stakeholders. There is growing recognition that the appropriate involvement of local communities in land and water management decisions can result in multiple environmental, economic and social benefits. Therefore, local stakeholder groups are increasingly being asked to participate in decision making alongside policy makers, government agencies and scientists. As such, addressing flooding issues requires new ways of engaging with the catchment and its inhabitants at a local level. To support this, new tools and approaches are required. The growth of cloud based technologies offers new novel ways to facilitate this process of exchange of information in earth sciences. The Environmental Virtual Observatory Pilot project (EVOp) is a new initiative from the UK Natural Environment Research Council (NERC) designed to deliver proof of concept for new tools and approaches to support the challenges as outlined above (http://www.evo-uk.org/). The long term vision of the Environmental Virtual Observatory is to: • Make environmental data more visible and accessible to a wide range of potential users including public good applications; • Provide tools to facilitate the integrated analysis of data, greater access to added knowledge and expert analysis and visualisation of the results; • Develop new, added-value knowledge from public and private sector data assets to help tackle environmental challenges. As part of the EVO pilot, an interactive cloud based tool has been developed with local stakeholders. The Local Landscape Visualisation Tool attempts to communicate flood risk in local impacted communities. The tool has been developed iteratively to reflect the needs, interests and capabilities of a wide range of stakeholders. This tool (assessable via a web portal) combines numerous cloud based tools and services, local catchment datasets, hydrological models and novel visualisation techniques. This pilot tool has been developed by engaging with different stakeholder groups in three catchments in the UK; the Afon Dyfi (Wales), the River Tarland (Scotland) and the River Eden (England). Stakeholders were interested in accessing live data in their catchments and looking at different land use change scenarios on flood peaks. Visualisation tools have been created which offer access to real time data (such as river level, rainfall and webcam images). Other tools allow land owners to use cloud based models (example presented here uses Topmodel, a rainfall-runoff model, on a custom virtual machine image on Amazon web services) and local datasets to explore future land use scenarios, allowing them to understand the associated flood risk. Different ways to communicate model uncertainty are currently being investigated and discussed with stakeholders. In summary the pilot project has had positive feedback and has evolved into two unique parts; a web based map tool and a model interface tool. Users can view live data from different sources, combine different data types together (data mash-up), develop local scenarios for land use and flood risk and exploit the dynamic, elastic cloud modelling capability. This local toolkit will reside within a wider EVO platform that will include national and global datasets, models and state of the art cloud computer systems.
-
Contaminant dispersal in bounded turbulent shear flow
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wallace, J.M.; Bernard, P.S.; Chiang, K.F.
The dispersion of smoke downstream of a line source at the wall and at y{sup +} = 30 in a turbulent boundary layer has been predicted with a non-local model of the scalar fluxes {bar u}c and {bar v}c. The predicted plume from the wall source has been compared to high Schmidt number experimental measurements using a combination of hot-wire anemometry to obtain velocity component data synchronously with concentration data obtained optically. The predicted plumes from the source at y{sup +} = 30 and at the wall also have been compared to a low Schmidt number direct numerical simulation. Nearmore » the source, the non-local flux models give considerably better predictions than models which account solely for mean gradient transport. At a sufficient distance downstream the gradient models gives reasonably good predictions.« less
-
Liu, Tao; Zhu, Guanghu; Lin, Hualiang; Zhang, Yonghui; He, Jianfeng; Deng, Aiping; Peng, Zhiqiang; Xiao, Jianpeng; Rutherford, Shannon; Xie, Runsheng; Zeng, Weilin; Li, Xing; Ma, Wenjun
2017-01-01
Background Dengue fever (DF) in Guangzhou, Guangdong province in China is an important public health issue. The problem was highlighted in 2014 by a large, unprecedented outbreak. In order to respond in a more timely manner and hence better control such potential outbreaks in the future, this study develops an early warning model that integrates internet-based query data into traditional surveillance data. Methodology and principal findings A Dengue Baidu Search Index (DBSI) was collected from the Baidu website for developing a predictive model of dengue fever in combination with meteorological and demographic factors. Generalized additive models (GAM) with or without DBSI were established. The generalized cross validation (GCV) score and deviance explained indexes, intraclass correlation coefficient (ICC) and root mean squared error (RMSE), were respectively applied to measure the fitness and the prediction capability of the models. Our results show that the DBSI with one-week lag has a positive linear relationship with the local DF occurrence, and the model with DBSI (ICC:0.94 and RMSE:59.86) has a better prediction capability than the model without DBSI (ICC:0.72 and RMSE:203.29). Conclusions Our study suggests that a DSBI combined with traditional disease surveillance and meteorological data can improve the dengue early warning system in Guangzhou. PMID:28263988
-
Modeling donor/acceptor interactions: Combined roles of theory and computation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Newton, M.D.
2000-03-05
An extended superexchange model for electron transfer (ET) matrix elements (H{sub DA}) has been formulated as a superposition of McConnell-type pathways and implemented by combined use of configuration interaction wave functions (obtained using the INDO/s model of Zerner and co-workers) and the generalized Muliken-Hush formulation of charge-localized diabatic states. Applications are made for et (and hold transfer) in several donor/bridge/acceptor radical anion (and cation) systems, (DBA){sup {+-}}, allowing detailed comparison with experimental H{sub DA} estimates. For the case of oligo phenylene ethynylene (OPE) bridges, the role of {pi} and {sigma} electronic manifolds for different distributions of phenylene torsion angles ismore » analyzed in detail.« less
-
Burks, Tyesha N; Marx, Ruth; Powell, Laura; Rucker, Jasma; Bedja, Djahida; Heacock, Elisa; Smith, Barbara J; Foster, D Brian; Kass, David; O'Rourke, Brian; Walston, Jeremy D; Abadir, Peter M
2015-05-20
Although the effects of aging and inflammation on the health of the cardiac muscle are well documented, the combined effects of aging and chronic inflammation on cardiac muscle are largely unknown. The renin-angiotensin system (RAS) has been linked independently to both aging and inflammation, but is understudied in the context of their collective effect. Thus, we investigated localized cardiac angiotensin II type I and type II receptors (AT(1)R, AT(2)R), downstream effectors, and phenotypic outcomes using mouse models of the combination of aging and inflammation and compared it to a model of aging and a model of inflammation. We show molecular distinction in the combined effect of aging and inflammation as compared to each independently. The combination maintained an increased AT(1)R:AT(2)R and expression of Nox2 and exhibited the lowest activity of antioxidants. Despite signaling pathway differences, the combined effect shared phenotypic similarities with aging including oxidative damage, fibrosis, and hypertrophy. These phenotypic similarities have dubbed inflammatory conditions as premature aging, but they are, in fact, molecularly distinct. Moreover, treatment with an AT(1)R blocker, losartan, selectively reversed the signaling changes and ameliorated adverse phenotypic effects in the combination of aging and inflammation as well as each independently.
-
Burks, Tyesha N.; Marx, Ruth; Powell, Laura; Rucker, Jasma; Bedja, Djahida; Heacock, Elisa; Smith, Barbara J.; Foster, D. Brian; Kass, David; O'Rourke, Brian; Walston, Jeremy D.; Abadir, Peter M.
2015-01-01
Although the effects of aging and inflammation on the health of the cardiac muscle are well documented, the combined effects of aging and chronic inflammation on cardiac muscle are largely unknown. The renin-angiotensin system (RAS) has been linked independently to both aging and inflammation, but is understudied in the context of their collective effect. Thus, we investigated localized cardiac angiotensin II type I and type II receptors (AT1R, AT2R), downstream effectors, and phenotypic outcomes using mouse models of the combination of aging and inflammation and compared it to a model of aging and a model of inflammation. We show molecular distinction in the combined effect of aging and inflammation as compared to each independently. The combination maintained an increased AT1R:AT2R and expression of Nox2 and exhibited the lowest activity of antioxidants. Despite signaling pathway differences, the combined effect shared phenotypic similarities with aging including oxidative damage, fibrosis, and hypertrophy. These phenotypic similarities have dubbed inflammatory conditions as premature aging, but they are, in fact, molecularly distinct. Moreover, treatment with an AT1R blocker, losartan, selectively reversed the signaling changes and ameliorated adverse phenotypic effects in the combination of aging and inflammation as well as each independently. PMID:26221650
-
Generalized estimators of avian abundance from count survey data
Royle, J. Andrew
2004-01-01
I consider modeling avian abundance from spatially referenced bird count data collected according to common protocols such as capture?recapture, multiple observer, removal sampling and simple point counts. Small sample sizes and large numbers of parameters have motivated many analyses that disregard the spatial indexing of the data, and thus do not provide an adequate treatment of spatial structure. I describe a general framework for modeling spatially replicated data that regards local abundance as a random process, motivated by the view that the set of spatially referenced local populations (at the sample locations) constitute a metapopulation. Under this view, attention can be focused on developing a model for the variation in local abundance independent of the sampling protocol being considered. The metapopulation model structure, when combined with the data generating model, define a simple hierarchical model that can be analyzed using conventional methods. The proposed modeling framework is completely general in the sense that broad classes of metapopulation models may be considered, site level covariates on detection and abundance may be considered, and estimates of abundance and related quantities may be obtained for sample locations, groups of locations, unsampled locations. Two brief examples are given, the first involving simple point counts, and the second based on temporary removal counts. Extension of these models to open systems is briefly discussed.
-
Mattsson, Brady J.; Zipkin, Elise F.; Gardner, Beth; Blank, Peter J.; Sauer, John R.; Royle, J. Andrew
2013-01-01
Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition.
-
Mattsson, Brady J; Zipkin, Elise F; Gardner, Beth; Blank, Peter J; Sauer, John R; Royle, J Andrew
2013-01-01
Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition.
-
Mattsson, Brady J.; Zipkin, Elise F.; Gardner, Beth; Blank, Peter J.; Sauer, John R.; Royle, J. Andrew
2013-01-01
Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition. PMID:23393564
-
A model-adaptivity method for the solution of Lennard-Jones based adhesive contact problems
NASA Astrophysics Data System (ADS)
Ben Dhia, Hachmi; Du, Shuimiao
2018-05-01
The surface micro-interaction model of Lennard-Jones (LJ) is used for adhesive contact problems (ACP). To address theoretical and numerical pitfalls of this model, a sequence of partitions of contact models is adaptively constructed to both extend and approximate the LJ model. It is formed by a combination of the LJ model with a sequence of shifted-Signorini (or, alternatively, -Linearized-LJ) models, indexed by a shift parameter field. For each model of this sequence, a weak formulation of the associated local ACP is developed. To track critical localized adhesive areas, a two-step strategy is developed: firstly, a macroscopic frictionless (as first approach) linear-elastic contact problem is solved once to detect contact separation zones. Secondly, at each shift-adaptive iteration, a micro-macro ACP is re-formulated and solved within the multiscale Arlequin framework, with significant reduction of computational costs. Comparison of our results with available analytical and numerical solutions shows the effectiveness of our global strategy.
-
Network inoculation: Heteroclinics and phase transitions in an epidemic model
NASA Astrophysics Data System (ADS)
Yang, Hui; Rogers, Tim; Gross, Thilo
2016-08-01
In epidemiological modelling, dynamics on networks, and, in particular, adaptive and heterogeneous networks have recently received much interest. Here, we present a detailed analysis of a previously proposed model that combines heterogeneity in the individuals with adaptive rewiring of the network structure in response to a disease. We show that in this model, qualitative changes in the dynamics occur in two phase transitions. In a macroscopic description, one of these corresponds to a local bifurcation, whereas the other one corresponds to a non-local heteroclinic bifurcation. This model thus provides a rare example of a system where a phase transition is caused by a non-local bifurcation, while both micro- and macro-level dynamics are accessible to mathematical analysis. The bifurcation points mark the onset of a behaviour that we call network inoculation. In the respective parameter region, exposure of the system to a pathogen will lead to an outbreak that collapses but leaves the network in a configuration where the disease cannot reinvade, despite every agent returning to the susceptible class. We argue that this behaviour and the associated phase transitions can be expected to occur in a wide class of models of sufficient complexity.
-
Interactive graphic editing tools in bioluminescent imaging simulation
NASA Astrophysics Data System (ADS)
Li, Hui; Tian, Jie; Luo, Jie; Wang, Ge; Cong, Wenxiang
2005-04-01
It is a challenging task to accurately describe complicated biological tissues and bioluminescent sources in bioluminescent imaging simulation. Several graphic editing tools have been developed to efficiently model each part of the bioluminescent simulation environment and to interactively correct or improve the initial models of anatomical structures or bioluminescent sources. There are two major types of graphic editing tools: non-interactive tools and interactive tools. Geometric building blocks (i.e. regular geometric graphics and superquadrics) are applied as non-interactive tools. To a certain extent, complicated anatomical structures and bioluminescent sources can be approximately modeled by combining a sufficient large number of geometric building blocks with Boolean operators. However, those models are too simple to describe the local features and fine changes in 2D/3D irregular contours. Therefore, interactive graphic editing tools have been developed to facilitate the local modifications of any initial surface model. With initial models composed of geometric building blocks, interactive spline mode is applied to conveniently perform dragging and compressing operations on 2D/3D local surface of biological tissues and bioluminescent sources inside the region/volume of interest. Several applications of the interactive graphic editing tools will be presented in this article.
-
The CLAIR model: Extension of Brodmann areas based on brain oscillations and connectivity.
Başar, Erol; Düzgün, Aysel
2016-05-01
Since the beginning of the last century, the localization of brain function has been represented by Brodmann areas, maps of the anatomic organization of the brain. They are used to broadly represent cortical structures with their given sensory-cognitive functions. In recent decades, the analysis of brain oscillations has become important in the correlation of brain functions. Moreover, spectral connectivity can provide further information on the dynamic connectivity between various structures. In addition, brain responses are dynamic in nature and structural localization is almost impossible, according to Luria (1966). Therefore, brain functions are very difficult to localize; hence, a combined analysis of oscillation and event-related coherences is required. In this study, a model termed as "CLAIR" is described to enrich and possibly replace the concept of the Brodmann areas. A CLAIR model with optimum function may take several years to develop, but this study sets out to lay its foundation. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
-
3D-Simulation Of Concentration Distributions Inside Large-Scale Circulating Fluidized Bed Combustors
NASA Astrophysics Data System (ADS)
Wischnewski, R.; Ratschow, L.; Hartge, E. U.; Werthe, J.
With increasing size of modern CFB combustors the lateral mixing of fuels and secondary air gains more and more importance. Strong concentration gradients, which result from improper lateral mixing, can lead to operational problems, high flue gas emissions and lower boiler efficiencies. A 3D-model for the simulation of local gas and solids concentrations inside industrial-sized CFB boilers has been developed. The model is based on a macroscopic approach and considers all major mechanisms during fuel spreading and subsequent combustion of char and volatiles. Typical characteristics of modern boilers like staged combustion, a smaller cross-sectional area in the lower section of the combustion chamber and the co-combustion of additional fuels with coal can be considered. The 252 MWth combustor of Stadtwerke Duisburg AG is used for the validation of the model. A comprehensive picture of the local conditions inside the combustion chamber is achieved by the combination of local gas measurements and the three-dimensional simulation of concentration distributions.
-
Probing density and spin correlations in two-dimensional Hubbard model with ultracold fermions
NASA Astrophysics Data System (ADS)
Chan, Chun Fai; Drewes, Jan Henning; Gall, Marcell; Wurz, Nicola; Cocchi, Eugenio; Miller, Luke; Pertot, Daniel; Brennecke, Ferdinand; Koehl, Michael
2017-04-01
Quantum gases of interacting fermionic atoms in optical lattices is a promising candidate to study strongly correlated quantum phases of the Hubbard model such as the Mott-insulator, spin-ordered phases, or in particular d-wave superconductivity. We experimentally realise the two-dimensional Hubbard model by loading a quantum degenerate Fermi gas of 40 K atoms into a three-dimensional optical lattice geometry. High-resolution absorption imaging in combination with radiofrequency spectroscopy is applied to spatially resolve the atomic distribution in a single 2D layer. We investigate in local measurements of spatial correlations in both the density and spin sector as a function of filling, temperature and interaction strength. In the density sector, we compare the local density fluctuations and the global thermodynamic quantities, and in the spin sector, we observe the onset of non-local spin correlation, signalling the emergence of the anti-ferromagnetic phase. We would report our recent experimental endeavours to investigate further down in temperature in the spin sector.
-
Probing the Dusty Stellar Populations of the Local Volume Galaxies with JWST/MIRI
NASA Astrophysics Data System (ADS)
Jones, Olivia C.; Meixner, Margaret; Justtanont, Kay; Glasse, Alistair
2017-05-01
The Mid-Infrared Instrument (MIRI) for the James Webb Space Telescope (JWST) will revolutionize our understanding of infrared stellar populations in the Local Volume. Using the rich Spitzer-IRS spectroscopic data set and spectral classifications from the Surveying the Agents of Galaxy Evolution (SAGE)-Spectroscopic survey of more than 1000 objects in the Magellanic Clouds, the Grid of Red Supergiant and Asymptotic Giant Branch Star Model (grams), and the grid of YSO models by Robitaille et al., we calculate the expected flux densities and colors in the MIRI broadband filters for prominent infrared stellar populations. We use these fluxes to explore the JWST/MIRI colors and magnitudes for composite stellar population studies of Local Volume galaxies. MIRI color classification schemes are presented; these diagrams provide a powerful means of identifying young stellar objects, evolved stars, and extragalactic background galaxies in Local Volume galaxies with a high degree of confidence. Finally, we examine which filter combinations are best for selecting populations of sources based on their JWST colors.
-
Controlling the Local Electronic Properties of Si(553)-Au through Hydrogen Doping
NASA Astrophysics Data System (ADS)
Hogan, C.; Speiser, E.; Chandola, S.; Suchkova, S.; Aulbach, J.; Schäfer, J.; Meyer, S.; Claessen, R.; Esser, N.
2018-04-01
We propose a quantitative and reversible method for tuning the charge localization of Au-stabilized stepped Si surfaces by site-specific hydrogenation. This is demonstrated for Si(553)-Au as a model system by combining density functional theory simulations and reflectance anisotropy spectroscopy experiments. We find that controlled H passivation is a two-step process: step-edge adsorption drives excess charge into the conducting metal chain "reservoir" and renders it insulating, while surplus H recovers metallic behavior. Our approach illustrates a route towards microscopic manipulation of the local surface charge distribution and establishes a reversible switch of site-specific chemical reactivity and magnetic properties on vicinal surfaces.
-
Budy, Phaedra; Conner, Mary M; Salant, Nira L; Macfarlane, William W
2015-08-01
Desert fishes are some of the most imperiled vertebrates worldwide due to their low economic worth and because they compete with humans for water. An ecological complex of fishes, 2 suckers (Catostomus latipinnis, Catostomus discobolus) and a chub (Gila robusta) (collectively managed as the so-called three species) are endemic to the U.S. Colorado River Basin, are affected by multiple stressors, and have allegedly declined dramatically. We built a series of occupancy models to determine relationships between trends in occupancy, local extinction, and local colonization rates, identify potential limiting factors, and evaluate the suitability of managing the 3 species collectively. For a historical period (1889-2011), top performing models (AICc) included a positive time trend in local extinction probability and a negative trend in local colonization probability. As flood frequency decreased post-development local extinction probability increased. By the end of the time series, 47% (95% CI 34-61) and 15% (95% CI 6-33) of sites remained occupied by the suckers and the chub, respectively, and models with the 2 species of sucker as one group and the chub as the other performed best. For a contemporary period (2001-2011), top performing (based on AICc ) models included peak annual discharge. As peak discharge increased, local extinction probability decreased and local colonization probability increased. For the contemporary period, results of models that split all 3 species into separate groups were similar to results of models that combined the 2 suckers but not the chub. Collectively, these results confirmed that declines in these fishes were strongly associated with water development and that relative to their historic distribution all 3 species have declined dramatically. Further, the chub was distinct in that it declined the most dramatically and therefore may need to be managed separately. Our modeling approach may be useful in other situations in which targeted data are sparse and conservation status and best management approach for multiple species are uncertain. © 2015 Society for Conservation Biology.
-
3D Thermal/Mechanical Evolution Of The Plate Boundary Corner In SE Alaska
NASA Astrophysics Data System (ADS)
Barker, A.; Koons, P.; Upton, P.; Pavlis, T.; Chapman, J.
2007-12-01
The St Elias orogen of southeast Alaska forms part of an actively deforming plate boundary corner. The corner accommodates the transition from a strike-slip lateral boundary to a convergent normal boundary. Oblique convergence of the Yakutat microplate into the corner generates early stage tectonic characteristics associated with other corner systems (e.g. Himalayan Eastern Syntaxis). In combination with the high relief, the extreme erosive processes of the region redistribute crustal material, partition tectonic strain, and influence the advection of deep crustal material. The evolution of the convergent corner is investigated using 3D numerical models and sandbox analog models. Preliminary model results indicate the deformation partitions into a narrow two-sided orogen along the lateral boundary. The pattern transitions into a wider zone of shortening bounded by inboard and outboard directed thrusts along the frontal boundary. The inclusion of erosion boundary conditions leads to nascent tectonic aneurysm behavior, involving increased strain localization and focused vertical advection of deep crustal material. Thermal models, using the 3D velocity field from these mechanical solutions, show a vertical deflection (towards the surface) of isotherms beneath the eroding region. Sensitivity of the aneurysm behavior is related to the efficiency of the imposed erosion rate (i.e. greater erosion rates led to greater bedrock uplift rates). Higher erosion rates are localized within zones containing major glacier systems in SE Alaska: Bering Glacier, Bagley Icefield, Malaspina Glacier, and Seward Glacier. Combined thermal/mechanical solutions identify the glacier valleys as rheological weakspots, defined by localized strain and differential advection of deep crustal material.
-
Moderate MAS enhances local (1)H spin exchange and spin diffusion.
Roos, Matthias; Micke, Peter; Saalwächter, Kay; Hempel, Günter
2015-11-01
Proton NMR spin-diffusion experiments are often combined with magic-angle spinning (MAS) to achieve higher spectral resolution of solid samples. Here we show that local proton spin diffusion can indeed become faster at low (<10 kHz) spinning rates as compared to static conditions. Spin diffusion under static conditions can thus be slower than the often referred value of 0.8 nm(2)/ms, which was determined using slow MAS (Clauss et al., 1993). The enhancement of spin diffusion by slow MAS relies on the modulation of the orientation-dependent dipolar couplings during sample rotation and goes along with transient level crossings in combination with dipolar truncation. The experimental finding and its explanation is supported by density matrix simulations, and also emphasizes the sensitivity of spin diffusion to the local coupling topology. The amplification of spin diffusion by slow MAS cannot be explained by any model based on independent spin pairs; at least three spins have to be considered. Copyright © 2015 Elsevier Inc. All rights reserved.
-
Energy recovery from solid waste. [production engineering model
NASA Technical Reports Server (NTRS)
Dalton, C.; Huang, C. J.
1974-01-01
A recent group study on the problem of solid waste disposal provided a decision making model for a community to use in determining the future for its solid waste. The model is a combination of the following factors: technology, legal, social, political, economic and environmental. An assessment of local or community needs determines what form of energy recovery is desirable. A market for low pressure steam or hot water would direct a community to recover energy from solid waste by incineration to generate steam. A fuel gas could be produced by a process known as pyrolysis if there is a local market for a low heating value gaseous fuel. Solid waste can also be used directly as a fuel supplemental to coal in a steam generator. An evaluation of these various processes is made.
-
NASA Astrophysics Data System (ADS)
Zhu, Aichun; Wang, Tian; Snoussi, Hichem
2018-03-01
This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN). Firstly, a Relative Mixture Deformable Model (RMDM) is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN) is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.
-
Dérive à la surface de l'océan sous l'effet des vagues
NASA Astrophysics Data System (ADS)
Ardhuin, Fabrice; Martin-Lauzer, François-Régis; Chapron, Bertrand; Craneguy, Philippe; Girard-Ardhuin, Fanny; Elfouhaily, Tanos
2004-09-01
We model the drift velocity near the ocean surface separating the motion induced by the local current, itself influenced by winds and waves, and the motion induced by the waves, which are generated by local and remote winds. Application to the drift of 'tar balls', following the sinking of the oil tanker Prestige-Nassau in November 2002, shows that waves contribute at least one third of the drift for pollutants floating 1 m below the surface, with a mean direction about 30° to the right of the wind-sea direction. Although not new, this result was previously obtained with specific models, whereas the formalism used here combines classical wave and circulation forecasting models. To cite this article: F. Ardhuin et al., C. R. Geoscience 336 (2004).
-
An approach of traffic signal control based on NLRSQP algorithm
NASA Astrophysics Data System (ADS)
Zou, Yuan-Yang; Hu, Yu
2017-11-01
This paper presents a linear program model with linear complementarity constraints (LPLCC) to solve traffic signal optimization problem. The objective function of the model is to obtain the minimization of total queue length with weight factors at the end of each cycle. Then, a combination algorithm based on the nonlinear least regression and sequence quadratic program (NLRSQP) is proposed, by which the local optimal solution can be obtained. Furthermore, four numerical experiments are proposed to study how to set the initial solution of the algorithm that can get a better local optimal solution more quickly. In particular, the results of numerical experiments show that: The model is effective for different arrival rates and weight factors; and the lower bound of the initial solution is, the better optimal solution can be obtained.
-
Stenroos, Matti; Hauk, Olaf
2013-01-01
The conductivity profile of the head has a major effect on EEG signals, but unfortunately the conductivity for the most important compartment, skull, is only poorly known. In dipole modeling studies, errors in modeled skull conductivity have been considered to have a detrimental effect on EEG source estimation. However, as dipole models are very restrictive, those results cannot be generalized to other source estimation methods. In this work, we studied the sensitivity of EEG and combined MEG + EEG source estimation to errors in skull conductivity using a distributed source model and minimum-norm (MN) estimation. We used a MEG/EEG modeling set-up that reflected state-of-the-art practices of experimental research. Cortical surfaces were segmented and realistically-shaped three-layer anatomical head models were constructed, and forward models were built with Galerkin boundary element method while varying the skull conductivity. Lead-field topographies and MN spatial filter vectors were compared across conductivities, and the localization and spatial spread of the MN estimators were assessed using intuitive resolution metrics. The results showed that the MN estimator is robust against errors in skull conductivity: the conductivity had a moderate effect on amplitudes of lead fields and spatial filter vectors, but the effect on corresponding morphologies was small. The localization performance of the EEG or combined MEG + EEG MN estimator was only minimally affected by the conductivity error, while the spread of the estimate varied slightly. Thus, the uncertainty with respect to skull conductivity should not prevent researchers from applying minimum norm estimation to EEG or combined MEG + EEG data. Comparing our results to those obtained earlier with dipole models shows that general judgment on the performance of an imaging modality should not be based on analysis with one source estimation method only. PMID:23639259
-
Dao, Trung-Kien; Nguyen, Hung-Long; Pham, Thanh-Thuy; Castelli, Eric; Nguyen, Viet-Tung; Nguyen, Dinh-Van
2014-01-01
Many user localization technologies and methods have been proposed for either indoor or outdoor environments. However, each technology has its own drawbacks. Recently, many researches and designs have been proposed to build a combination of multiple localization technologies system which can provide higher precision results and solve the limitation in each localization technology alone. In this paper, a conceptual design of a general localization platform using combination of multiple localization technologies is introduced. The combination is realized by dividing spaces into grid points. To demonstrate this platform, a system with GPS, RFID, WiFi, and pedometer technologies is established. Experiment results show that the accuracy and availability are improved in comparison with each technology individually.
-
Dao, Trung-Kien; Nguyen, Hung-Long; Pham, Thanh-Thuy; Nguyen, Viet-Tung; Nguyen, Dinh-Van
2014-01-01
Many user localization technologies and methods have been proposed for either indoor or outdoor environments. However, each technology has its own drawbacks. Recently, many researches and designs have been proposed to build a combination of multiple localization technologies system which can provide higher precision results and solve the limitation in each localization technology alone. In this paper, a conceptual design of a general localization platform using combination of multiple localization technologies is introduced. The combination is realized by dividing spaces into grid points. To demonstrate this platform, a system with GPS, RFID, WiFi, and pedometer technologies is established. Experiment results show that the accuracy and availability are improved in comparison with each technology individually. PMID:25147866
-
Analytical modeling and tolerance analysis of a linear variable filter for spectral order sorting.
Ko, Cheng-Hao; Chang, Kuei-Ying; Huang, You-Min
2015-02-23
This paper proposes an innovative method to overcome the low production rate of current linear variable filter (LVF) fabrication. During the fabrication process, a commercial coater is combined with a local mask on a substrate. The proposed analytical thin film thickness model, which is based on the geometry of the commercial coater, is developed to more effectively calculate the profiles of LVFs. Thickness tolerance, LVF zone width, thin film layer structure, transmission spectrum and the effects of variations in critical parameters of the coater are analyzed. Profile measurements demonstrate the efficacy of local mask theory in the prediction of evaporation profiles with a high degree of accuracy.
-
Yang, Wanan; Li, Yan; Qin, Fengqing
2015-01-01
To actively maneuver a robotic capsule for interactive diagnosis in the gastrointestinal tract, visualizing accurate position and orientation of the capsule when it moves in the gastrointestinal tract is essential. A possible method that encloses the circuits, batteries, imaging device, etc into the capsule looped by an axially magnetized permanent-magnet ring is proposed. Based on expression of the axially magnetized permanent-magnet ring's magnetic fields, a localization and orientation model was established. An improved hybrid strategy that combines the advantages of particle-swarm optimization, clone algorithm, and the Levenberg-Marquardt algorithm was found to solve the model. Experiments showed that the hybrid strategy has good accuracy, convergence, and real time performance.
-
A hybrid linear/nonlinear training algorithm for feedforward neural networks.
McLoone, S; Brown, M D; Irwin, G; Lightbody, A
1998-01-01
This paper presents a new hybrid optimization strategy for training feedforward neural networks. The algorithm combines gradient-based optimization of nonlinear weights with singular value decomposition (SVD) computation of linear weights in one integrated routine. It is described for the multilayer perceptron (MLP) and radial basis function (RBF) networks and then extended to the local model network (LMN), a new feedforward structure in which a global nonlinear model is constructed from a set of locally valid submodels. Simulation results are presented demonstrating the superiority of the new hybrid training scheme compared to second-order gradient methods. It is particularly effective for the LMN architecture where the linear to nonlinear parameter ratio is large.
-
Sensitivity analysis of a wing aeroelastic response
NASA Technical Reports Server (NTRS)
Kapania, Rakesh K.; Eldred, Lloyd B.; Barthelemy, Jean-Francois M.
1991-01-01
A variation of Sobieski's Global Sensitivity Equations (GSE) approach is implemented to obtain the sensitivity of the static aeroelastic response of a three-dimensional wing model. The formulation is quite general and accepts any aerodynamics and structural analysis capability. An interface code is written to convert one analysis's output to the other's input, and visa versa. Local sensitivity derivatives are calculated by either analytic methods or finite difference techniques. A program to combine the local sensitivities, such as the sensitivity of the stiffness matrix or the aerodynamic kernel matrix, into global sensitivity derivatives is developed. The aerodynamic analysis package FAST, using a lifting surface theory, and a structural package, ELAPS, implementing Giles' equivalent plate model are used.
-
Local numerical modelling of ultrasonic guided waves in linear and nonlinear media
NASA Astrophysics Data System (ADS)
Packo, Pawel; Radecki, Rafal; Kijanka, Piotr; Staszewski, Wieslaw J.; Uhl, Tadeusz; Leamy, Michael J.
2017-04-01
Nonlinear ultrasonic techniques provide improved damage sensitivity compared to linear approaches. The combination of attractive properties of guided waves, such as Lamb waves, with unique features of higher harmonic generation provides great potential for characterization of incipient damage, particularly in plate-like structures. Nonlinear ultrasonic structural health monitoring techniques use interrogation signals at frequencies other than the excitation frequency to detect changes in structural integrity. Signal processing techniques used in non-destructive evaluation are frequently supported by modeling and numerical simulations in order to facilitate problem solution. This paper discusses known and newly-developed local computational strategies for simulating elastic waves, and attempts characterization of their numerical properties in the context of linear and nonlinear media. A hybrid numerical approach combining advantages of the Local Interaction Simulation Approach (LISA) and Cellular Automata for Elastodynamics (CAFE) is proposed for unique treatment of arbitrary strain-stress relations. The iteration equations of the method are derived directly from physical principles employing stress and displacement continuity, leading to an accurate description of the propagation in arbitrarily complex media. Numerical analysis of guided wave propagation, based on the newly developed hybrid approach, is presented and discussed in the paper for linear and nonlinear media. Comparisons to Finite Elements (FE) are also discussed.
-
Local Variability Mediates Vulnerability of Trout Populations to Land Use and Climate Change
Penaluna, Brooke E.; Dunham, Jason B.; Railsback, Steve F.; Arismendi, Ivan; Johnson, Sherri L.; Bilby, Robert E.; Safeeq, Mohammad; Skaugset, Arne E.
2015-01-01
Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of Coastal Cutthroat Trout (Oncorhynchus clarkii clarkii) to scenarios simulating identical changes in temperature and stream flows linked to forest harvest, climate change, and their combined effects over six decades. We parameterized the model for four neighboring streams located in a forested headwater catchment in northwestern Oregon, USA with multi-year, daily measurements of stream temperature, flow, and turbidity (2007–2011), and field measurements of both instream habitat structure and three years of annual trout population estimates. Model simulations revealed that variability in habitat conditions among streams (depth, available habitat) mediated the effects of forest harvest and climate change. Net effects for most simulated trout responses were different from or less than the sum of their separate scenarios. In some cases, forest harvest countered the effects of climate change through increased summer flow. Climate change most strongly influenced trout (earlier fry emergence, reductions in biomass of older trout, increased biomass of young-of-year), but these changes did not consistently translate into reductions in biomass over time. Forest harvest, in contrast, produced fewer and less consistent responses in trout. Earlier fry emergence driven by climate change was the most consistent simulated response, whereas survival, growth, and biomass were inconsistent. Overall our findings indicate a host of local processes can strongly influence how populations respond to broad scale effects of land use and climate change. PMID:26295478
-
Local variability mediates vulnerability of trout populations to land use and climate change
Penaluna, Brooke E.; Dunham, Jason B.; Railsback, Steve F.; Arismendi, Ivan; Johnson, Sherri L.; Bilby, Robert E; Safeeq, Mohammad; Skaugset, Arne E.
2015-01-01
Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of Coastal Cutthroat Trout (Oncorhynchus clarkii clarkii) to scenarios simulating identical changes in temperature and stream flows linked to forest harvest, climate change, and their combined effects over six decades. We parameterized the model for four neighboring streams located in a forested headwater catchment in northwestern Oregon, USA with multi-year, daily measurements of stream temperature, flow, and turbidity (2007–2011), and field measurements of both instream habitat structure and three years of annual trout population estimates. Model simulations revealed that variability in habitat conditions among streams (depth, available habitat) mediated the effects of forest harvest and climate change. Net effects for most simulated trout responses were different from or less than the sum of their separate scenarios. In some cases, forest harvest countered the effects of climate change through increased summer flow. Climate change most strongly influenced trout (earlier fry emergence, reductions in biomass of older trout, increased biomass of young-of-year), but these changes did not consistently translate into reductions in biomass over time. Forest harvest, in contrast, produced fewer and less consistent responses in trout. Earlier fry emergence driven by climate change was the most consistent simulated response, whereas survival, growth, and biomass were inconsistent. Overall our findings indicate a host of local processes can strongly influence how populations respond to broad scale effects of land use and climate change.
-
Local Variability Mediates Vulnerability of Trout Populations to Land Use and Climate Change.
Penaluna, Brooke E; Dunham, Jason B; Railsback, Steve F; Arismendi, Ivan; Johnson, Sherri L; Bilby, Robert E; Safeeq, Mohammad; Skaugset, Arne E
2015-01-01
Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of Coastal Cutthroat Trout (Oncorhynchus clarkii clarkii) to scenarios simulating identical changes in temperature and stream flows linked to forest harvest, climate change, and their combined effects over six decades. We parameterized the model for four neighboring streams located in a forested headwater catchment in northwestern Oregon, USA with multi-year, daily measurements of stream temperature, flow, and turbidity (2007-2011), and field measurements of both instream habitat structure and three years of annual trout population estimates. Model simulations revealed that variability in habitat conditions among streams (depth, available habitat) mediated the effects of forest harvest and climate change. Net effects for most simulated trout responses were different from or less than the sum of their separate scenarios. In some cases, forest harvest countered the effects of climate change through increased summer flow. Climate change most strongly influenced trout (earlier fry emergence, reductions in biomass of older trout, increased biomass of young-of-year), but these changes did not consistently translate into reductions in biomass over time. Forest harvest, in contrast, produced fewer and less consistent responses in trout. Earlier fry emergence driven by climate change was the most consistent simulated response, whereas survival, growth, and biomass were inconsistent. Overall our findings indicate a host of local processes can strongly influence how populations respond to broad scale effects of land use and climate change.
-
Fitzpatrick, Matthew C; Keller, Stephen R
2015-01-01
Local adaptation is a central feature of most species occupying spatially heterogeneous environments, and may factor critically in responses to environmental change. However, most efforts to model the response of species to climate change ignore intraspecific variation due to local adaptation. Here, we present a new perspective on spatial modelling of organism-environment relationships that combines genomic data and community-level modelling to develop scenarios regarding the geographic distribution of genomic variation in response to environmental change. Rather than modelling species within communities, we use these techniques to model large numbers of loci across genomes. Using balsam poplar (Populus balsamifera) as a case study, we demonstrate how our framework can accommodate nonlinear responses of loci to environmental gradients. We identify a threshold response to temperature in the circadian clock gene GIGANTEA-5 (GI5), suggesting that this gene has experienced strong local adaptation to temperature. We also demonstrate how these methods can map ecological adaptation from genomic data, including the identification of predicted differences in the genetic composition of populations under current and future climates. Community-level modelling of genomic variation represents an important advance in landscape genomics and spatial modelling of biodiversity that moves beyond species-level assessments of climate change vulnerability. © 2014 John Wiley & Sons Ltd/CNRS.
-
Kulinkina, Alexandra V; Walz, Yvonne; Koch, Magaly; Biritwum, Nana-Kwadwo; Utzinger, Jürg; Naumova, Elena N
2018-06-04
Schistosomiasis is a water-related neglected tropical disease. In many endemic low- and middle-income countries, insufficient surveillance and reporting lead to poor characterization of the demographic and geographic distribution of schistosomiasis cases. Hence, modeling is relied upon to predict areas of high transmission and to inform control strategies. We hypothesized that utilizing remotely sensed (RS) environmental data in combination with water, sanitation, and hygiene (WASH) variables could improve on the current predictive modeling approaches. Schistosoma haematobium prevalence data, collected from 73 rural Ghanaian schools, were used in a random forest model to investigate the predictive capacity of 15 environmental variables derived from RS data (Landsat 8, Sentinel-2, and Global Digital Elevation Model) with fine spatial resolution (10-30 m). Five methods of variable extraction were tested to determine the spatial linkage between school-based prevalence and the environmental conditions of potential transmission sites, including applying the models to known human water contact locations. Lastly, measures of local water access and groundwater quality were incorporated into RS-based models to assess the relative importance of environmental and WASH variables. Predictive models based on environmental characterization of specific locations where people contact surface water bodies offered some improvement as compared to the traditional approach based on environmental characterization of locations where prevalence is measured. A water index (MNDWI) and topographic variables (elevation and slope) were important environmental risk factors, while overall, groundwater iron concentration predominated in the combined model that included WASH variables. The study helps to understand localized drivers of schistosomiasis transmission. Specifically, unsatisfactory water quality in boreholes perpetuates reliance of surface water bodies, indirectly increasing schistosomiasis risk and resulting in rapid reinfection (up to 40% prevalence six months following preventive chemotherapy). Considering WASH-related risk factors in schistosomiasis prediction can help shift the focus of control strategies from treating symptoms to reducing exposure.
-
Digital Geogames to Foster Local Biodiversity
ERIC Educational Resources Information Center
Schaal, Sonja; Schaal, Steffen; Lude, Armin
2015-01-01
The valuing of biodiversity is considered to be a first step towards its conservation. Therefore, the aim of the BioDiv2Go project is to combine sensuous experiences discovering biodiversity with mobile technology and a game-based learning approach. Following the competence model for environmental education (Roczen et al, 2014), Geogames (location…
-
Feature Modeling in Underwater Environments Using Sparse Linear Combinations
2010-01-01
nose of the tor- pedo obviously has a different optical depth than the tail and points in between. Our chosen PSF does not consider this, but it...IEEE Transactions on Information Theory, 52(4), 2006. 4 [6] R. Hess and A. Fern. Improved video registration using non-distinctive local image
-
Developing an Interdisciplinary, Distributed Graduate Course for Twenty-First Century Scientists
ERIC Educational Resources Information Center
Wagner, Helene H.; Murphy, Melanie A.; Holderegger, Rolf; Waits, Lisette
2012-01-01
Graduate programs have placed an increasing emphasis on the importance of interdisciplinary education, but barriers to interdisciplinary training still remain. We present a new model for interdisciplinary, cross-institution graduate teaching that combines the best of local teaching, distance learning, and experiential learning to provide students…
-
Gary L. Achtemeier
2005-01-01
Smoke from both prescribed fires and wildfires can, under certain meteorological conditions, become entrapped within shallow layers of air near the ground at night and get carried to unexpected destinations as a combination of weather systems push air through interlocking ridge-valley terrain typical of the Piedmont of the Soutthern United States. Entrapped smoke...
-
NASA Astrophysics Data System (ADS)
Cotterman, K. A.; Follum, M. L.; Pradhan, N. R.; Niemann, J. D.
2017-12-01
Flooding impacts numerous aspects of society, from localized flash floods to continental-scale flood events. Many numerical flood models focus solely on riverine flooding, with some capable of capturing both localized and continental-scale flood events. However, these models neglect flooding away from channels that are related to excessive ponding, typically found in areas with flat terrain and poorly draining soils. In order to obtain a holistic view of flooding, we combine flood results from the Streamflow Prediction Tool (SPT), a riverine flood model, with soil moisture downscaling techniques to determine if a better representation of flooding is obtained. This allows for a more holistic understanding of potential flood prone areas, increasing the opportunity for more accurate warnings and evacuations during flooding conditions. Thirty-five years of near-global historical streamflow is reconstructed with continental-scale flow routing of runoff from global land surface models. Elevation data was also obtained worldwide, to establish a relationship between topographic attributes and soil moisture patterns. Derived soil moisture data is validated against observed soil moisture, increasing confidence in the ability to accurately capture soil moisture patterns. Potential flooding situations can be examined worldwide, with this study focusing on the United States, Central America, and the Philippines.
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Emül, Y.; Department of Software Engineering, Cumhuriyet University, 58140 Sivas; Erbahar, D.
2015-08-14
Analyses of the local crystal and electronic structure in the vicinity of Fe{sup 3+} centers in perovskite KMgF{sub 3} crystal have been carried out in a comprehensive manner. A combination of density functional theory (DFT) and a semi-empirical superposition model (SPM) is used for a complete analysis of all Fe{sup 3+} centers in this study for the first time. Some quantitative information has been derived from the DFT calculations on both the electronic structure and the local geometry around Fe{sup 3+} centers. All of the trigonal (K-vacancy case, K-Li substitution case, and normal trigonal Fe{sup 3+} center case), FeF{sub 5}Omore » cluster, and tetragonal (Mg-vacancy and Mg-Li substitution cases) centers have been taken into account based on the previously suggested experimental and theoretical inferences. The collaboration between the experimental data and the results of both DFT and SPM calculations provides us to understand most probable structural model for Fe{sup 3+} centers in KMgF{sub 3}.« less
-
Reflections in computer modeling of rooms: Current approaches and possible extensions
NASA Astrophysics Data System (ADS)
Svensson, U. Peter
2005-09-01
Computer modeling of rooms is most commonly done by some calculation technique that is based on decomposing the sound field into separate reflection components. In a first step, a list of possible reflection paths is found and in a second step, an impulse response is constructed from the list of reflections. Alternatively, the list of reflections is used for generating a simpler echogram, the energy decay as function of time. A number of geometrical acoustics-based methods can handle specular reflections, diffuse reflections, edge diffraction, curved surfaces, and locally/non-locally reacting surfaces to various degrees. This presentation gives an overview of how reflections are handled in the image source method and variants of the ray-tracing methods, which are dominating today in commercial software, as well as in the radiosity method and edge diffraction methods. The use of the recently standardized scattering and diffusion coefficients of surfaces is discussed. Possibilities for combining edge diffraction, surface scattering, and impedance boundaries are demonstrated for an example surface. Finally, the number of reflection paths becomes prohibitively high when all such combinations are included as demonstrated for a simple concert hall model. [Work supported by the Acoustic Research Centre through NFR, Norway.
-
Local and average structure of Mn- and La-substituted BiFeO3
NASA Astrophysics Data System (ADS)
Jiang, Bo; Selbach, Sverre M.
2017-06-01
The local and average structure of solid solutions of the multiferroic perovskite BiFeO3 is investigated by synchrotron X-ray diffraction (XRD) and electron density functional theory (DFT) calculations. The average experimental structure is determined by Rietveld refinement and the local structure by total scattering data analyzed in real space with the pair distribution function (PDF) method. With equal concentrations of La on the Bi site or Mn on the Fe site, La causes larger structural distortions than Mn. Structural models based on DFT relaxed geometry give an improved fit to experimental PDFs compared to models constrained by the space group symmetry. Berry phase calculations predict a higher ferroelectric polarization than the experimental literature values, reflecting that structural disorder is not captured in either average structure space group models or DFT calculations with artificial long range order imposed by periodic boundary conditions. Only by including point defects in a supercell, here Bi vacancies, can DFT calculations reproduce the literature results on the structure and ferroelectric polarization of Mn-substituted BiFeO3. The combination of local and average structure sensitive experimental methods with DFT calculations is useful for illuminating the structure-property-composition relationships in complex functional oxides with local structural distortions.
-
Local and average structure of Mn- and La-substituted BiFeO 3
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jiang, Bo; Selbach, Sverre M.
2017-06-01
The local and average structure of solid solutions of the multiferroic perovskite BiFeO 3 is investigated by synchrotron X-ray diffraction (XRD) and electron density functional theory (DFT) calculations. The average experimental structure is determined by Rietveld refinement and the local structure by total scattering data analyzed in real space with the pair distribution function (PDF) method. With equal concentrations of La on the Bi site or Mn on the Fe site, La causes larger structural distortions than Mn. Structural models based on DFT relaxed geometry give an improved fit to experimental PDFs compared to models constrained by the space groupmore » symmetry. Berry phase calculations predict a higher ferroelectric polarization than the experimental literature values, reflecting that structural disorder is not captured in either average structure space group models or DFT calculations with artificial long range order imposed by periodic boundary conditions. Only by including point defects in a supercell, here Bi vacancies, can DFT calculations reproduce the literature results on the structure and ferroelectric polarization of Mn-substituted BiFeO 3. The combination of local and average structure sensitive experimental methods with DFT calculations is useful for illuminating the structure-property-composition relationships in complex functional oxides with local structural distortions.« less
-
NASA Astrophysics Data System (ADS)
Hodgson, Murray; Wareing, Andrew
2008-01-01
A combined beam-tracing and transfer-matrix model for predicting steady-state sound-pressure levels in rooms with multilayer bounding surfaces was used to compare the effect of extended- and local-reaction surfaces, and the accuracy of the local-reaction approximation. Three rooms—an office, a corridor and a workshop—with one or more multilayer test surfaces were considered. The test surfaces were a single-glass panel, a double-drywall panel, a carpeted floor, a suspended-acoustical ceiling, a double-steel panel, and glass fibre on a hard backing. Each test surface was modeled as of extended or of local reaction. Sound-pressure levels were predicted and compared to determine the significance of the surface-reaction assumption. The main conclusions were that the difference between modeling a room surface as of extended or of local reaction is not significant when the surface is a single plate or a single layer of material (solid or porous) with a hard backing. The difference is significant when the surface consists of multilayers of solid or porous material and includes a layer of fluid with a large thickness relative to the other layers. The results are partially explained by considering the surface-reflection coefficients at the first-reflection angles.
-
NASA Astrophysics Data System (ADS)
Abid, Najmul; Mirkhalaf, Mohammad; Barthelat, Francois
2018-03-01
Natural materials such as nacre, collagen, and spider silk are composed of staggered stiff and strong inclusions in a softer matrix. This type of hybrid microstructure results in remarkable combinations of stiffness, strength, and toughness and it now inspires novel classes of high-performance composites. However, the analytical and numerical approaches used to predict and optimize the mechanics of staggered composites often neglect statistical variations and inhomogeneities, which may have significant impacts on modulus, strength, and toughness. Here we present an analysis of localization using small representative volume elements (RVEs) and large scale statistical volume elements (SVEs) based on the discrete element method (DEM). DEM is an efficient numerical method which enabled the evaluation of more than 10,000 microstructures in this study, each including about 5,000 inclusions. The models explore the combined effects of statistics, inclusion arrangement, and interface properties. We find that statistical variations have a negative effect on all properties, in particular on the ductility and energy absorption because randomness precipitates the localization of deformations. However, the results also show that the negative effects of random microstructures can be offset by interfaces with large strain at failure accompanied by strain hardening. More specifically, this quantitative study reveals an optimal range of interface properties where the interfaces are the most effective at delaying localization. These findings show how carefully designed interfaces in bioinspired staggered composites can offset the negative effects of microstructural randomness, which is inherent to most current fabrication methods.
-
Shiels, Stefanie M; Tennent, David J; Wenke, Joseph C
2018-05-21
Open fractures become infected despite meticulous debridement and care. Locally applied antibiotics, commonly embedded in polymethylmethacrylate, deliver high doses of drug directly to the fracture site. Direct application of antibiotic powder, which is being applied prophylactically in spine surgery, is a recent interest in the trauma sector, where bacterial biofilms are more prevalent. Traditional antibiotics, such as vancomycin, are poor performers against bacterial biofilms thus are ineffective in delayed treatment. Rifampin is an effective eradicator of Staphylococcal biofilms. Here, a rat model of musculoskeletal trauma was used to evaluate the utility of locally applied rifampin powder for reducing established orthopaedic Staphylococcal infections in a delayed treatment scenario that previously indicated the limited use of local vancomycin. By applying rifampin powder directly to the contaminated segmental defect, the number of bacteria, as well as clinical indications of infection, were significantly reduced compared to vancomycin and daptomycin. Considering the Infectious Disease Society of America's recommendation to use rifampin in combination with another antibiotic to reduce the onset of rifampin resistance, rifampin powder was also applied in combination with vancomycin or daptomycin with insignificant changes in eradication performance. No indications of rifampin resistance were identified. Statement of Clinical Significance: The use of locally applied rifampin is a promising therapy for mature and tolerant musculoskeletal infections. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
-
Sound source localization method in an environment with flow based on Amiet-IMACS
NASA Astrophysics Data System (ADS)
Wei, Long; Li, Min; Qin, Sheng; Fu, Qiang; Yang, Debin
2017-05-01
A sound source localization method is proposed to localize and analyze the sound source in an environment with airflow. It combines the improved mapping of acoustic correlated sources (IMACS) method and Amiet's method, and is called Amiet-IMACS. It can localize uncorrelated and correlated sound sources with airflow. To implement this approach, Amiet's method is used to correct the sound propagation path in 3D, which improves the accuracy of the array manifold matrix and decreases the position error of the localized source. Then, the mapping of acoustic correlated sources (MACS) method, which is as a high-resolution sound source localization algorithm, is improved by self-adjusting the constraint parameter at each irritation process to increase convergence speed. A sound source localization experiment using a pair of loud speakers in an anechoic wind tunnel under different flow speeds is conducted. The experiment exhibits the advantage of Amiet-IMACS in localizing a more accurate sound source position compared with implementing IMACS alone in an environment with flow. Moreover, the aerodynamic noise produced by a NASA EPPLER 862 STRUT airfoil model in airflow with a velocity of 80 m/s is localized using the proposed method, which further proves its effectiveness in a flow environment. Finally, the relationship between the source position of this airfoil model and its frequency, along with its generation mechanism, is determined and interpreted.
-
Jackowski, Konrad; Krawczyk, Bartosz; Woźniak, Michał
2014-05-01
Currently, methods of combined classification are the focus of intense research. A properly designed group of combined classifiers exploiting knowledge gathered in a pool of elementary classifiers can successfully outperform a single classifier. There are two essential issues to consider when creating combined classifiers: how to establish the most comprehensive pool and how to design a fusion model that allows for taking full advantage of the collected knowledge. In this work, we address the issues and propose an AdaSS+, training algorithm dedicated for the compound classifier system that effectively exploits local specialization of the elementary classifiers. An effective training procedure consists of two phases. The first phase detects the classifier competencies and adjusts the respective fusion parameters. The second phase boosts classification accuracy by elevating the degree of local specialization. The quality of the proposed algorithms are evaluated on the basis of a wide range of computer experiments that show that AdaSS+ can outperform the original method and several reference classifiers.
-
Ahm, Malte; Thorndahl, Søren; Nielsen, Jesper E; Rasmussen, Michael R
2016-12-01
Combined sewer overflow (CSO) structures are constructed to effectively discharge excess water during heavy rainfall, to protect the urban drainage system from hydraulic overload. Consequently, most CSO structures are not constructed according to basic hydraulic principles for ideal measurement weirs. It can, therefore, be a challenge to quantify the discharges from CSOs. Quantification of CSO discharges are important in relation to the increased environmental awareness of the receiving water bodies. Furthermore, CSO discharge quantification is essential for closing the rainfall-runoff mass-balance in combined sewer catchments. A closed mass-balance is an advantage for calibration of all urban drainage models based on mass-balance principles. This study presents three different software sensor concepts based on local water level sensors, which can be used to estimate CSO discharge volumes from hydraulic complex CSO structures. The three concepts were tested and verified under real practical conditions. All three concepts were accurate when compared to electromagnetic flow measurements.
-
NASA Astrophysics Data System (ADS)
Palumbo, G.; Piccininni, A.; Guglielmi, P.; Sorgente, D.; Tricarico, L.
2016-08-01
The present work deals with the advantages in the Hydromechanical Deep Drawing (HDD) when AA5754 Tailored Heat Treated Blanks (THTBs) are adopted. It is well known that the creation of a suitable distribution of material properties increases the process performance. When non heat-treatable alloys are considered, the THTB approach can be successfully applied to increase the Limit Drawing Ratio (LDR) by changing the peripheral zone into the annealed state starting from a cold-worked blank. If this approach is combined with the advantages of a counterpressure, even more remarkable improvements can be achieved. Due to the large number of involved parameters, the optimized design of both the local treatment and the pressure profile were investigated coupling an axial symmetric Finite Element model with the integration platform modeFRONTIER. Results confirmed the possibility of increasing the LDR from 2.0 (Deep Drawing using a blank in the annealed state) up to about 3.0 if combining the adoption of a THTB with the optimal pressure profile.
-
Parikh, Nidhi; Hayatnagarkar, Harshal G; Beckman, Richard J; Marathe, Madhav V; Swarup, Samarth
2016-11-01
We describe a large-scale simulation of the aftermath of a hypothetical 10kT improvised nuclear detonation at ground level, near the White House in Washington DC. We take a synthetic information approach, where multiple data sets are combined to construct a synthesized representation of the population of the region with accurate demographics, as well as four infrastructures: transportation, healthcare, communication, and power. In this article, we focus on the model of agents and their behavior, which is represented using the options framework. Six different behavioral options are modeled: household reconstitution, evacuation, healthcare-seeking, worry, shelter-seeking, and aiding & assisting others. Agent decision-making takes into account their health status, information about family members, information about the event, and their local environment. We combine these behavioral options into five different behavior models of increasing complexity and do a number of simulations to compare the models.
-
Parikh, Nidhi; Hayatnagarkar, Harshal G.; Beckman, Richard J.; Marathe, Madhav V.; Swarup, Samarth
2016-01-01
We describe a large-scale simulation of the aftermath of a hypothetical 10kT improvised nuclear detonation at ground level, near the White House in Washington DC. We take a synthetic information approach, where multiple data sets are combined to construct a synthesized representation of the population of the region with accurate demographics, as well as four infrastructures: transportation, healthcare, communication, and power. In this article, we focus on the model of agents and their behavior, which is represented using the options framework. Six different behavioral options are modeled: household reconstitution, evacuation, healthcare-seeking, worry, shelter-seeking, and aiding & assisting others. Agent decision-making takes into account their health status, information about family members, information about the event, and their local environment. We combine these behavioral options into five different behavior models of increasing complexity and do a number of simulations to compare the models. PMID:27909393
-
NASA Astrophysics Data System (ADS)
Kirschner, Matthias; Wesarg, Stefan
2011-03-01
Active Shape Models (ASMs) are a popular family of segmentation algorithms which combine local appearance models for boundary detection with a statistical shape model (SSM). They are especially popular in medical imaging due to their ability for fast and accurate segmentation of anatomical structures even in large and noisy 3D images. A well-known limitation of ASMs is that the shape constraints are over-restrictive, because the segmentations are bounded by the Principal Component Analysis (PCA) subspace learned from the training data. To overcome this limitation, we propose a new energy minimization approach which combines an external image energy with an internal shape model energy. Our shape energy uses the Distance From Feature Space (DFFS) concept to allow deviations from the PCA subspace in a theoretically sound and computationally fast way. In contrast to previous approaches, our model does not rely on post-processing with constrained free-form deformation or additional complex local energy models. In addition to the energy minimization approach, we propose a new method for liver detection, a new method for initializing an SSM and an improved k-Nearest Neighbour (kNN)-classifier for boundary detection. Our ASM is evaluated with leave-one-out tests on a data set with 34 tomographic CT scans of the liver and is compared to an ASM with standard shape constraints. The quantitative results of our experiments show that we achieve higher segmentation accuracy with our energy minimization approach than with standard shape constraints.nym
-
NASA Astrophysics Data System (ADS)
Wada, Y.
2017-12-01
Humanity has already reached or even exceeded the Earth's carrying capacity. Growing needs for food, energy and water will only exacerbate existing challenges over the next decades. Consequently, the acceptance of "business as usual" is eroding and we are being challenged to adopt new, more integrated, and more inclusive development pathways that avoid dangerous interference with the local environment and global planetary boundaries. This challenge is embodied in the United Nation's Sustainable Development Goals (SDGs), which endeavor to set a global agenda for moving towards more sustainable development strategies. To improve and sustain human welfare, it is critical that access to modern, reliable, and affordable water, energy, and food is expanded and maintained. The Integrated Solutions for Water, Energy, and Land (IS-WEL) project has been launched by IIASA, together with the Global Environment Facility (GEF) and the United Nations Industrial Development Organization (UNIDO). This project focuses on the water-energy-land nexus in the context of other major global challenges such as urbanization, environmental degradation, and equitable and sustainable futures. It develops a consistent framework for looking at the water-energy-land nexus and identify strategies for achieving the needed transformational outcomes through an advanced assessment framework. A multi-scalar approach are being developed that aims to combine global and regional integrated assessment tools with local stakeholder knowledge in order to identify robust solutions to energy, water, food, and ecosystem security in selected regions of the world. These are regions facing multiple energy, water and land use challenges and rapid demographic and economic changes, and are hardest hit by increasing climate variability and change. This project combines the global integrated assessment model (MESSAGE) with the global land (GLOBIOM) and water (Community Water Model) model respectively, and the integrated modeling framework are then combined with detailed regional decision support tools for water-energy-land nexus analysis in case study regions. A number of stakeholder meetings are used to engage local communities in the definition of important nexus drivers, scenario development and definition of performance metrics.
-
Lorz, Alexander; Lorenzi, Tommaso; Clairambault, Jean; Escargueil, Alexandre; Perthame, Benoît
2015-01-01
Histopathological evidence supports the idea that the emergence of phenotypic heterogeneity and resistance to cytotoxic drugs can be considered as a process of selection in tumor cell populations. In this framework, can we explain intra-tumor heterogeneity in terms of selection driven by the local cell environment? Can we overcome the emergence of resistance and favor the eradication of cancer cells by using combination therapies? Bearing these questions in mind, we develop a model describing cell dynamics inside a tumor spheroid under the effects of cytotoxic and cytostatic drugs. Cancer cells are assumed to be structured as a population by two real variables standing for space position and the expression level of a phenotype of resistance to cytotoxic drugs. The model takes explicitly into account the dynamics of resources and anticancer drugs as well as their interactions with the cell population under treatment. We analyze the effects of space structure and combination therapies on phenotypic heterogeneity and chemotherapeutic resistance. Furthermore, we study the efficacy of combined therapy protocols based on constant infusion and bang-bang delivery of cytotoxic and cytostatic drugs.
-
Antibiotic effects against periodontal bacteria in organ cultured tissue.
Takeshita, Masaaki; Haraguchi, Akira; Miura, Mayumi; Hamachi, Takafumi; Fukuda, Takao; Sanui, Terukazu; Takano, Aiko; Nishimura, Fusanori
2017-02-01
Mechanical reduction of infectious bacteria by using physical instruments is considered the principal therapeutic strategy for periodontal disease; addition of antibiotics is adjunctive. However, local antibiotic treatment, combined with conventional mechanical debridement, has recently been shown to be more effective in periodontitis subjects with type 2 diabetes. This suggests that some bacteria may invade the inflamed inner gingival epithelium, and mechanical debridement alone will be unable to reduce these bacteria completely. Therefore, we tried to establish infected organ culture models that mimic the inner gingival epithelium and aimed to see the effects of antibiotics in these established models. Mouse dorsal skin epithelia were isolated, and periodontal bacteria were injected into the epithelia. Infected epithelia were incubated with test antibiotics, and colony-forming ability was evaluated. Results indicated that effective antibiotics differed according to injected bacteria and the bacterial combinations tested. Overall, in organ culture model, the combination of amoxicillin or cefdinir and metronidazole compensate for the effects of less effective bacterial combinations on each other. This in vitro study would suggest effective periodontal treatment regimens, especially for severe periodontitis.
-
Kubas, Adam; Noak, Johannes
2017-01-01
Absorption and multiwavelength resonance Raman spectroscopy are widely used to investigate the electronic structure of transition metal centers in coordination compounds and extended solid systems. In combination with computational methodologies that have predictive accuracy, they define powerful protocols to study the spectroscopic response of catalytic materials. In this work, we study the absorption and resonance Raman spectra of the M1 MoVOx catalyst. The spectra were calculated by time-dependent density functional theory (TD-DFT) in conjunction with the independent mode displaced harmonic oscillator model (IMDHO), which allows for detailed bandshape predictions. For this purpose cluster models with up to 9 Mo and V metallic centers are considered to represent the bulk structure of MoVOx. Capping hydrogens were used to achieve valence saturation at the edges of the cluster models. The construction of model structures was based on a thorough bonding analysis which involved conventional DFT and local coupled cluster (DLPNO-CCSD(T)) methods. Furthermore the relationship of cluster topology to the computed spectral features is discussed in detail. It is shown that due to the local nature of the involved electronic transitions, band assignment protocols developed for molecular systems can be applied to describe the calculated spectral features of the cluster models as well. The present study serves as a reference for future applications of combined experimental and computational protocols in the field of solid-state heterogeneous catalysis. PMID:28989667
-
Zosel, Franziska; Haenni, Dominik; Soranno, Andrea; Nettels, Daniel; Schuler, Benjamin
2017-10-21
Intrinsically disordered proteins (IDPs) are increasingly recognized as a class of molecules that can exert essential biological functions even in the absence of a well-defined three-dimensional structure. Understanding the conformational distributions and dynamics of these highly flexible proteins is thus essential for explaining the molecular mechanisms underlying their function. Single-molecule fluorescence spectroscopy in combination with Förster resonance energy transfer (FRET) is a powerful tool for probing intramolecular distances and the rapid long-range distance dynamics in IDPs. To complement the information from FRET, we combine it with photoinduced electron transfer (PET) quenching to monitor local loop-closure kinetics at the same time and in the same molecule. Here we employed this combination to investigate the intrinsically disordered N-terminal domain of HIV-1 integrase. The results show that both long-range dynamics and loop closure kinetics on the sub-microsecond time scale can be obtained reliably from a single set of measurements by the analysis with a comprehensive model of the underlying photon statistics including both FRET and PET. A more detailed molecular interpretation of the results is enabled by direct comparison with a recent extensive atomistic molecular dynamics simulation of integrase. The simulations are in good agreement with experiment and can explain the deviation from simple models of chain dynamics by the formation of persistent local secondary structure. The results illustrate the power of a close combination of single-molecule spectroscopy and simulations for advancing our understanding of the dynamics and detailed mechanisms in unfolded and intrinsically disordered proteins.
-
NASA Astrophysics Data System (ADS)
Zosel, Franziska; Haenni, Dominik; Soranno, Andrea; Nettels, Daniel; Schuler, Benjamin
2017-10-01
Intrinsically disordered proteins (IDPs) are increasingly recognized as a class of molecules that can exert essential biological functions even in the absence of a well-defined three-dimensional structure. Understanding the conformational distributions and dynamics of these highly flexible proteins is thus essential for explaining the molecular mechanisms underlying their function. Single-molecule fluorescence spectroscopy in combination with Förster resonance energy transfer (FRET) is a powerful tool for probing intramolecular distances and the rapid long-range distance dynamics in IDPs. To complement the information from FRET, we combine it with photoinduced electron transfer (PET) quenching to monitor local loop-closure kinetics at the same time and in the same molecule. Here we employed this combination to investigate the intrinsically disordered N-terminal domain of HIV-1 integrase. The results show that both long-range dynamics and loop closure kinetics on the sub-microsecond time scale can be obtained reliably from a single set of measurements by the analysis with a comprehensive model of the underlying photon statistics including both FRET and PET. A more detailed molecular interpretation of the results is enabled by direct comparison with a recent extensive atomistic molecular dynamics simulation of integrase. The simulations are in good agreement with experiment and can explain the deviation from simple models of chain dynamics by the formation of persistent local secondary structure. The results illustrate the power of a close combination of single-molecule spectroscopy and simulations for advancing our understanding of the dynamics and detailed mechanisms in unfolded and intrinsically disordered proteins.
-
COSMOLOGY OF CHAMELEONS WITH POWER-LAW COUPLINGS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mota, David F.; Winther, Hans A.
2011-05-20
In chameleon field theories, a scalar field can couple to matter with gravitational strength and still evade local gravity constraints due to a combination of self-interactions and the couplings to matter. Originally, these theories were proposed with a constant coupling to matter; however, the chameleon mechanism also extends to the case where the coupling becomes field dependent. We study the cosmology of chameleon models with power-law couplings and power-law potentials. It is found that these generalized chameleons, when viable, have a background expansion very close to {Lambda}CDM, but can in some special cases enhance the growth of the linear perturbationsmore » at low redshifts. For the models we consider, it is found that this region of the parameter space is ruled out by local gravity constraints. Imposing a coupling to dark matter only, the local constraints are avoided, and it is possible to have observable signatures on the linear matter perturbations.« less
-
An integrated approach to model strain localization bands in magnesium alloys
NASA Astrophysics Data System (ADS)
Baxevanakis, K. P.; Mo, C.; Cabal, M.; Kontsos, A.
2018-02-01
Strain localization bands (SLBs) that appear at early stages of deformation of magnesium alloys have been recently associated with heterogeneous activation of deformation twinning. Experimental evidence has demonstrated that such "Lüders-type" band formations dominate the overall mechanical behavior of these alloys resulting in sigmoidal type stress-strain curves with a distinct plateau followed by pronounced anisotropic hardening. To evaluate the role of SLB formation on the local and global mechanical behavior of magnesium alloys, an integrated experimental/computational approach is presented. The computational part is developed based on custom subroutines implemented in a finite element method that combine a plasticity model with a stiffness degradation approach. Specific inputs from the characterization and testing measurements to the computational approach are discussed while the numerical results are validated against such available experimental information, confirming the existence of load drops and the intensification of strain accumulation at the time of SLB initiation.
-
Localized states in the conserved Swift-Hohenberg equation with cubic nonlinearity
NASA Astrophysics Data System (ADS)
Thiele, Uwe; Archer, Andrew J.; Robbins, Mark J.; Gomez, Hector; Knobloch, Edgar
2013-04-01
The conserved Swift-Hohenberg equation with cubic nonlinearity provides the simplest microscopic description of the thermodynamic transition from a fluid state to a crystalline state. The resulting phase field crystal model describes a variety of spatially localized structures, in addition to different spatially extended periodic structures. The location of these structures in the temperature versus mean order parameter plane is determined using a combination of numerical continuation in one dimension and direct numerical simulation in two and three dimensions. Localized states are found in the region of thermodynamic coexistence between the homogeneous and structured phases, and may lie outside of the binodal for these states. The results are related to the phenomenon of slanted snaking but take the form of standard homoclinic snaking when the mean order parameter is plotted as a function of the chemical potential, and are expected to carry over to related models with a conserved order parameter.
-
Two Back Stress Hardening Models in Rate Independent Rigid Plastic Deformation
NASA Astrophysics Data System (ADS)
Yun, Su-Jin
In the present work, the constitutive relations based on the combination of two back stresses are developed using the Armstrong-Frederick, Phillips and Ziegler’s type hardening rules. Various evolutions of the kinematic hardening parameter can be obtained by means of a simple combination of back stress rate using the rule of mixtures. Thus, a wide range of plastic deformation behavior can be depicted depending on the dominant back stress evolution. The ultimate back stress is also determined for the present combined kinematic hardening models. Since a kinematic hardening rule is assumed in the finite deformation regime, the stress rate is co-rotated with respect to the spin of substructure obtained by incorporating the plastic spin concept. A comparison of the various co-rotational rates is also included. Assuming rigid plasticity, the continuum body consists of the elastic deformation zone and the plastic deformation zone to form a hybrid finite element formulation. Then, the plastic deformation behavior is investigated under various loading conditions with an assumption of the J2 deformation theory. The plastic deformation localization turns out to be strongly dependent on the description of back stress evolution and its associated hardening parameters. The analysis for the shear deformation with fixed boundaries is carried out to examine the deformation localization behavior and the evolution of state variables.
-
Quantitative determination of wool in textile by near-infrared spectroscopy and multivariate models.
Chen, Hui; Tan, Chao; Lin, Zan
2018-08-05
The wool content in textiles is a key quality index and the corresponding quantitative analysis takes an important position due to common adulterations in both raw and finished textiles. Conventional methods are maybe complicated, destructive, time-consuming, environment-unfriendly. Developing a quick, easy-to-use and green alternative method is interesting. The work focuses on exploring the feasibility of combining near-infrared (NIR) spectroscopy and several partial least squares (PLS)-based algorithms and elastic component regression (ECR) algorithms for measuring wool content in textile. A total of 108 cloth samples with wool content ranging from 0% to 100% (w/w) were collected and all the compositions are really existent in the market. The dataset was divided equally into the training and test sets for developing and validating calibration models. When using local PLS, the original spectrum axis was split into 20 sub-intervals. No obvious difference of performance can be seen for the local PLS models. The ECR model is comparable or superior to the other models due its flexibility, i.e., being transition state from PCR to PLS. It seems that ECR combined with NIR technique may be a potential method for determining wool content in textile products. In addition, it might have regulatory advantages to avoid time-consuming and environmental-unfriendly chemical analysis. Copyright © 2018 Elsevier B.V. All rights reserved.
-
3-D Localization Method for a Magnetically Actuated Soft Capsule Endoscope and Its Applications
Yim, Sehyuk; Sitti, Metin
2014-01-01
In this paper, we present a 3-D localization method for a magnetically actuated soft capsule endoscope (MASCE). The proposed localization scheme consists of three steps. First, MASCE is oriented to be coaxially aligned with an external permanent magnet (EPM). Second, MASCE is axially contracted by the enhanced magnetic attraction of the approaching EPM. Third, MASCE recovers its initial shape by the retracting EPM as the magnetic attraction weakens. The combination of the estimated direction in the coaxial alignment step and the estimated distance in the shape deformation (recovery) step provides the position of MASCE in 3-D. It is experimentally shown that the proposed localization method could provide 2.0–3.7 mm of distance error in 3-D. This study also introduces two new applications of the proposed localization method. First, based on the trace of contact points between the MASCE and the surface of the stomach, the 3-D geometrical model of a synthetic stomach was reconstructed. Next, the relative tissue compliance at each local contact point in the stomach was characterized by measuring the local tissue deformation at each point due to the preloading force. Finally, the characterized relative tissue compliance parameter was mapped onto the geometrical model of the stomach toward future use in disease diagnosis. PMID:25383064
-
New developments in tribomechanical modeling of automotive sheet steel forming
NASA Astrophysics Data System (ADS)
Khandeparkar, Tushar; Chezan, Toni; van Beeck, Jeroen
2018-05-01
Forming of automotive sheet metal body panels is a complex process influenced by both the material properties and contact conditions in the forming tooling. Material properties are described by the material constitutive behavior and the material flow into the forming die can be described by the tribological system. This paper investigates the prediction accuracy of the forming process using the Tata Steel state of the art description of the material constitutive behavior in combination with different friction models. A cross-die experiment is used to investigate the accuracy of local deformation modes typically seen in automotive sheet metal forming operations. Results of advanced friction models as well as the classical Coulomb friction description are compared to the experimentally measured strain distribution and material draw-in. Two hot-dip galvanized coated steel forming grades were used for the investigations. The results show that the accuracy of the simulation is not guaranteed by the advanced friction models for the entire investigated blank holder force range, both globally and locally. A measurable difference between the calculated and measured local strains is seen for both studied models even in the case where the global indicator, i.e. the draw-in, is well predicted.
-
Empirical Modeling of the Plasmasphere Dynamics Using Neural Networks
NASA Astrophysics Data System (ADS)
Zhelavskaya, I. S.; Shprits, Y.; Spasojevic, M.
2017-12-01
We present a new empirical model for reconstructing the global dynamics of the cold plasma density distribution based only on solar wind data and geomagnetic indices. Utilizing the density database obtained using the NURD (Neural-network-based Upper hybrid Resonance Determination) algorithm for the period of October 1, 2012 - July 1, 2016, in conjunction with solar wind data and geomagnetic indices, we develop a neural network model that is capable of globally reconstructing the dynamics of the cold plasma density distribution for 2 ≤ L ≤ 6 and all local times. We validate and test the model by measuring its performance on independent datasets withheld from the training set and by comparing the model predicted global evolution with global images of He+ distribution in the Earth's plasmasphere from the IMAGE Extreme UltraViolet (EUV) instrument. We identify the parameters that best quantify the plasmasphere dynamics by training and comparing multiple neural networks with different combinations of input parameters (geomagnetic indices, solar wind data, and different durations of their time history). We demonstrate results of both local and global plasma density reconstruction. This study illustrates how global dynamics can be reconstructed from local in-situ observations by using machine learning techniques.
-
Altszyler, Edgar; Ventura, Alejandra C; Colman-Lerner, Alejandro; Chernomoretz, Ariel
2017-01-01
Ultrasensitive response motifs, capable of converting graded stimuli into binary responses, are well-conserved in signal transduction networks. Although it has been shown that a cascade arrangement of multiple ultrasensitive modules can enhance the system's ultrasensitivity, how a given combination of layers affects a cascade's ultrasensitivity remains an open question for the general case. Here, we introduce a methodology that allows us to determine the presence of sequestration effects and to quantify the relative contribution of each module to the overall cascade's ultrasensitivity. The proposed analysis framework provides a natural link between global and local ultrasensitivity descriptors and it is particularly well-suited to characterize and understand mathematical models used to study real biological systems. As a case study, we have considered three mathematical models introduced by O'Shaughnessy et al. to study a tunable synthetic MAPK cascade, and we show how our methodology can help modelers better understand alternative models.
-
NASA Astrophysics Data System (ADS)
Kan-Dapaah, Kwabena; Rahbar, Nima; Theriault, Christian; Soboyejo, Wole
2015-04-01
This paper presents an implantable polymer/metal alloy thin film structure for localized post-operative treatment of breast cancer. A combination of experiments and models is used to study the temperature changes due to Joule heating by patterned metallic thin films embedded in poly-dimethylsiloxane. The heat conduction within the device and the surrounding normal/cancerous breast tissue is modeled with three-dimensional finite element method (FEM). The FEM simulations are used to explore the potential effects of device geometry and Joule heating on the temperature distribution and lesion (thermal dose). The FEM model is validated using a gel model that mimics biological media. The predictions are also compared to prior results from in vitro studies and relevant in vivo studies in the literature. The implications of the results are discussed for the potential application of polymer/metal thin film structures in hyperthermic treatment of cancer.
-
Incorporating evolutionary processes into population viability models.
Pierson, Jennifer C; Beissinger, Steven R; Bragg, Jason G; Coates, David J; Oostermeijer, J Gerard B; Sunnucks, Paul; Schumaker, Nathan H; Trotter, Meredith V; Young, Andrew G
2015-06-01
We examined how ecological and evolutionary (eco-evo) processes in population dynamics could be better integrated into population viability analysis (PVA). Complementary advances in computation and population genomics can be combined into an eco-evo PVA to offer powerful new approaches to understand the influence of evolutionary processes on population persistence. We developed the mechanistic basis of an eco-evo PVA using individual-based models with individual-level genotype tracking and dynamic genotype-phenotype mapping to model emergent population-level effects, such as local adaptation and genetic rescue. We then outline how genomics can allow or improve parameter estimation for PVA models by providing genotypic information at large numbers of loci for neutral and functional genome regions. As climate change and other threatening processes increase in rate and scale, eco-evo PVAs will become essential research tools to evaluate the effects of adaptive potential, evolutionary rescue, and locally adapted traits on persistence. © 2014 Society for Conservation Biology.
-
Altszyler, Edgar; Ventura, Alejandra C.; Colman-Lerner, Alejandro; Chernomoretz, Ariel
2017-01-01
Ultrasensitive response motifs, capable of converting graded stimuli into binary responses, are well-conserved in signal transduction networks. Although it has been shown that a cascade arrangement of multiple ultrasensitive modules can enhance the system’s ultrasensitivity, how a given combination of layers affects a cascade’s ultrasensitivity remains an open question for the general case. Here, we introduce a methodology that allows us to determine the presence of sequestration effects and to quantify the relative contribution of each module to the overall cascade’s ultrasensitivity. The proposed analysis framework provides a natural link between global and local ultrasensitivity descriptors and it is particularly well-suited to characterize and understand mathematical models used to study real biological systems. As a case study, we have considered three mathematical models introduced by O’Shaughnessy et al. to study a tunable synthetic MAPK cascade, and we show how our methodology can help modelers better understand alternative models. PMID:28662096
-
CreativeDrought: An interdisciplinary approach to building resilience to drought
NASA Astrophysics Data System (ADS)
Rangecroft, Sally; Van Loon, Anne; Rohse, Melanie; Day, Rosie; Birkinshaw, Stephen; Makaya, Eugine
2017-04-01
Drought events cause severe water and food insecurities in many developing countries where resilience to natural hazards and change is low due to a number of reasons (including poverty, social and political inequality, and limited access to information). Furthermore, with climate change and increasing pressures from population and societal change, populations are expected to experience future droughts outside of their historic range. Integrated water resources management is an established tool combining natural science, engineering and management to help address drought and associated impacts. However, it often lacks a strong social and cultural aspect, leading to poor implementation on the ground. For a more holistic approach to building resilience to future drought, a stronger interdisciplinary approach is required which can incorporate the local cultural context and perspectives into drought and water management, and communicate information effectively to communities. In this pilot project 'CreativeDrought', we use a novel interdisciplinary approach aimed at building resilience to future drought in rural Africa by combining hydrological modelling with rich local information and engaging communicative approaches from social sciences. The work is conducted through a series of steps in which we i) engage with local rural communities to collect narratives on drought experiences; ii) generate hydrological modelling scenarios based on IPCC projections, existing data and the collected narratives; iii) feed these back to the local community to gather their responses to these scenarios; iv) iteratively adapt them to obtain hypothetical future drought scenarios; v) engage the community with the scenarios to formulate new future drought narratives; and vi) use this new data to enhance local water resource management. Here we present some of the indigenous knowledge gathered through narratives and the hydrological modelling scenarios for a rural community in Southern Africa. We use this local knowledge to develop the hypothetical future scenarios with a hydrological model (SHETRAN), with an iterative process to build trust in the tool. Through workshops, the communities can then use their own experiences, the modelling scenarios and climate analogies to experiment with stories about future drought events and possible effective ways of responding to them. This interdisciplinary approach allows the local community to extrapolate their narrated, experienced droughts from outside their historic range and into their projected range. These workshops will find innovative and effective ways to communicate science and information to the rural population. In this co-creation process of using creative experimentation based on narratives and scenario hydrological modelling, we develop new ways of adapting to drought and building resilience. This approach to increasing resilience is regarded as robust because it uses scientific methods, but is also culturally embedded and bottom-up.
-
Eroglu, Duygu Yilmaz; Ozmutlu, H Cenk
2014-01-01
We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms.
-
The effect of local parameters on gas turbine emissions
NASA Technical Reports Server (NTRS)
Kauffman, C. W.; Correa, S. M.; Orozco, N. J.
1980-01-01
Gas turbine engine inlet parameters reflect changes in local atmospheric conditions. The pollutant emissions for the engine reflects these changes. In attempting to model the effect of the changing ambient conditions on the emissions it was found that these emissions exhibit an extreme sensitivity to some of the details of the combustion process such as the local fuel-air ratio and the size of the drops in the fuel spray. Fuel-air ratios have been mapped under nonburning conditions using a single JT8D-17 combustion can at simulated idle conditions, and significant variations in the local values have been found. Modelling of the combustor employs a combination of perfectly stirred and plug flow reactors including a finite rate vaporization treatment of the fuel spray. Results show that a small increase in the mean drop size can lead to a large increase in hydrocarbon emissions and decreasing the value of the CO-OH rate constant can lead to large increases in the carbon monoxide emissions. These emissions may also be affected by the spray characteristics with larger drops retarding the combustion process. Hydrocarbon, carbon monoxide, and oxides of nitrogen emissions calculated using the model accurately reflect measured emission variations caused by changing engine inlet conditions.
-
Meteorological Controls on Local and Regional Volcanic Ash Dispersal.
Poulidis, Alexandros P; Phillips, Jeremy C; Renfrew, Ian A; Barclay, Jenni; Hogg, Andrew; Jenkins, Susanna F; Robertson, Richard; Pyle, David M
2018-05-02
Volcanic ash has the capacity to impact human health, livestock, crops and infrastructure, including international air traffic. For recent major eruptions, information on the volcanic ash plume has been combined with relatively coarse-resolution meteorological model output to provide simulations of regional ash dispersal, with reasonable success on the scale of hundreds of kilometres. However, to predict and mitigate these impacts locally, significant improvements in modelling capability are required. Here, we present results from a dynamic meteorological-ash-dispersion model configured with sufficient resolution to represent local topographic and convectively-forced flows. We focus on an archetypal volcanic setting, Soufrière, St Vincent, and use the exceptional historical records of the 1902 and 1979 eruptions to challenge our simulations. We find that the evolution and characteristics of ash deposition on St Vincent and nearby islands can be accurately simulated when the wind shear associated with the trade wind inversion and topographically-forced flows are represented. The wind shear plays a primary role and topographic flows a secondary role on ash distribution on local to regional scales. We propose a new explanation for the downwind ash deposition maxima, commonly observed in volcanic eruptions, as resulting from the detailed forcing of mesoscale meteorology on the ash plume.
-
21 CFR 346.22 - Permitted combinations of anorectal active ingredients.
Code of Federal Regulations, 2010 CFR
2010-04-01
...) of this section. (c) Any single local anesthetic identified in § 346.10 may be combined with any single vasoconstrictor identified in § 346.12. (d) Any single local anesthetic identified in § 346.10 may be combined with any single astringent identified in § 346.18. (e) Any single local anesthetic...
-
21 CFR 346.22 - Permitted combinations of anorectal active ingredients.
Code of Federal Regulations, 2011 CFR
2011-04-01
...) of this section. (c) Any single local anesthetic identified in § 346.10 may be combined with any single vasoconstrictor identified in § 346.12. (d) Any single local anesthetic identified in § 346.10 may be combined with any single astringent identified in § 346.18. (e) Any single local anesthetic...
-
Architecture for reactive planning of robot actions
NASA Astrophysics Data System (ADS)
Riekki, Jukka P.; Roening, Juha
1995-01-01
In this article, a reactive system for planning robot actions is described. The described hierarchical control system architecture consists of planning-executing-monitoring-modelling elements (PEMM elements). A PEMM element is a goal-oriented, combined processing and data element. It includes a planner, an executor, a monitor, a modeler, and a local model. The elements form a tree-like structure. An element receives tasks from its ancestor and sends subtasks to its descendants. The model knowledge is distributed into the local models, which are connected to each other. The elements can be synchronized. The PEMM architecture is strictly hierarchical. It integrated planning, sensing, and modelling into a single framework. A PEMM-based control system is reactive, as it can cope with asynchronous events and operate under time constraints. The control system is intended to be used primarily to control mobile robots and robot manipulators in dynamic and partially unknown environments. It is suitable especially for applications consisting of physically separated devices and computing resources.
-
Efficient implicit LES method for the simulation of turbulent cavitating flows
DOE Office of Scientific and Technical Information (OSTI.GOV)
Egerer, Christian P., E-mail: christian.egerer@aer.mw.tum.de; Schmidt, Steffen J.; Hickel, Stefan
2016-07-01
We present a numerical method for efficient large-eddy simulation of compressible liquid flows with cavitation based on an implicit subgrid-scale model. Phase change and subgrid-scale interface structures are modeled by a homogeneous mixture model that assumes local thermodynamic equilibrium. Unlike previous approaches, emphasis is placed on operating on a small stencil (at most four cells). The truncation error of the discretization is designed to function as a physically consistent subgrid-scale model for turbulence. We formulate a sensor functional that detects shock waves or pseudo-phase boundaries within the homogeneous mixture model for localizing numerical dissipation. In smooth regions of the flowmore » field, a formally non-dissipative central discretization scheme is used in combination with a regularization term to model the effect of unresolved subgrid scales. The new method is validated by computing standard single- and two-phase test-cases. Comparison of results for a turbulent cavitating mixing layer obtained with the new method demonstrates its suitability for the target applications.« less
-
Elastic Response and Failure Studies of Multi-Wall Carbon Nanotube Twisted Yarns
NASA Technical Reports Server (NTRS)
Gates, Thomas S.; Jefferson, Gail D.; Frankland, Sarah-Jane V.
2007-01-01
Experimental data on the stress-strain behavior of a polymer multiwall carbon nanotube (MWCNT) yarn composite are used to motivate an initial study in multi-scale modeling of strength and stiffness. Atomistic and continuum length scale modeling methods are outlined to illustrate the range of parameters required to accurately model behavior. The carbon nanotubes yarns are four-ply, twisted, and combined with an elastomer to form a single-layer, unidirectional composite. Due to this textile structure, the yarn is a complicated system of unique geometric relationships subjected to combined loads. Experimental data illustrate the local failure modes induced by static, tensile tests. Key structure-property relationships are highlighted at each length scale indicating opportunities for parametric studies to assist the selection of advantageous material development and manufacturing methods.
-
Self-organising mixture autoregressive model for non-stationary time series modelling.
Ni, He; Yin, Hujun
2008-12-01
Modelling non-stationary time series has been a difficult task for both parametric and nonparametric methods. One promising solution is to combine the flexibility of nonparametric models with the simplicity of parametric models. In this paper, the self-organising mixture autoregressive (SOMAR) network is adopted as a such mixture model. It breaks time series into underlying segments and at the same time fits local linear regressive models to the clusters of segments. In such a way, a global non-stationary time series is represented by a dynamic set of local linear regressive models. Neural gas is used for a more flexible structure of the mixture model. Furthermore, a new similarity measure has been introduced in the self-organising network to better quantify the similarity of time series segments. The network can be used naturally in modelling and forecasting non-stationary time series. Experiments on artificial, benchmark time series (e.g. Mackey-Glass) and real-world data (e.g. numbers of sunspots and Forex rates) are presented and the results show that the proposed SOMAR network is effective and superior to other similar approaches.
-
NASA Astrophysics Data System (ADS)
Girard, Corentin; Rinaudo, Jean-Daniel; Pulido-Velazquez, Manuel
2016-04-01
Adaptation to the multiple facets of global change challenges the conventional means of sustainably planning and managing water resources at the river basin scale. Numerous demand or supply management options are available, from which adaptation measures need to be selected in a context of high uncertainty of future conditions. Given the interdependency of water users, agreements need to be found at the local level to implement the most effective adaptation measures. Therefore, this work develops an approach combining economics and water resources engineering to select a cost-effective programme of adaptation measures in the context of climate change uncertainty, and to define an equitable allocation of the cost of the adaptation plan between the stakeholders involved. A framework is developed to integrate inputs from the two main approaches commonly used to plan for adaptation. The first, referred to as "top-down", consists of a modelling chain going from global greenhouse gases emission scenarios to local hydrological models used to assess the impact of climate change on water resources. Conversely, the second approach, called "bottom-up", starts from assessing vulnerability at the local level to then identify adaptation measures used to face an uncertain future. The methodological framework presented in this contribution relies on a combination of these two approaches to support the selection of adaptation measures at the local level. Outcomes from these two approaches are integrated to select a cost-effective combination of adaptation measures through a least-cost optimization model developed at the river basin scale. The performances of a programme of measures are assessed under different climate projections to identify cost-effective and least-regret adaptation measures. The issue of allocating the cost of the adaptation plan is considered through two complementary perspectives. The outcome of a negotiation process between the stakeholders is modelled through the implementation of cooperative game theory to define cost allocation scenarios. These results are compared with cost allocation rules based on social justice principles to provide contrasted insights into a negotiation process. The interdisciplinary framework developed in this research combines economics and water resources engineering methods, establishing a promising means of bridging the gap between bottom-up and top-down approaches and supporting the creation of cost-effective and equitable adaptation plans at the local level. The approach has been applied to the Orb river basin in Southern France. Acknowledgements The study has been partially supported by the IMPADAPT project /CGL2013-48424-C2-1-R) from the Spanish ministry MINECO (Ministerio de Economía y Competitividad) and European FEDER funds. Corentin Girard is supported by a grant from the University Lecturer Training Program (FPU12/03803) of the Ministry of Education, Culture and Sports of Spain.
-
Local-global classifier fusion for screening chest radiographs
NASA Astrophysics Data System (ADS)
Ding, Meng; Antani, Sameer; Jaeger, Stefan; Xue, Zhiyun; Candemir, Sema; Kohli, Marc; Thoma, George
2017-03-01
Tuberculosis (TB) is a severe comorbidity of HIV and chest x-ray (CXR) analysis is a necessary step in screening for the infective disease. Automatic analysis of digital CXR images for detecting pulmonary abnormalities is critical for population screening, especially in medical resource constrained developing regions. In this article, we describe steps that improve previously reported performance of NLM's CXR screening algorithms and help advance the state of the art in the field. We propose a local-global classifier fusion method where two complementary classification systems are combined. The local classifier focuses on subtle and partial presentation of the disease leveraging information in radiology reports that roughly indicates locations of the abnormalities. In addition, the global classifier models the dominant spatial structure in the gestalt image using GIST descriptor for the semantic differentiation. Finally, the two complementary classifiers are combined using linear fusion, where the weight of each decision is calculated by the confidence probabilities from the two classifiers. We evaluated our method on three datasets in terms of the area under the Receiver Operating Characteristic (ROC) curve, sensitivity, specificity and accuracy. The evaluation demonstrates the superiority of our proposed local-global fusion method over any single classifier.
-
Thorogood, Rose; Davies, Nicholas B.
2016-01-01
Individuals often vary defences in response to local predation or parasitism risk. But how should they assess threat levels when it pays their enemies to hide? For common cuckoo hosts, assessing parasitism risk is challenging: cuckoo eggs are mimetic and adult cuckoos are secretive and resemble hawks. Here, we show that egg rejection by reed warblers depends on combining personal and social information of local risk. We presented model cuckoos or controls at a pair’s own nest (personal information of an intruder) and/or on a neighbouring territory, to which they were attracted by broadcasts of alarm calls (social information). Rejection of an experimental egg was stimulated only when hosts were alerted by both social and personal information of cuckoos. However, pairs that rejected eggs were not more likely to mob a cuckoo. Therefore, while hosts can assess risk from the sight of a cuckoo, a cuckoo cannot gauge if her egg will be accepted from host mobbing. Our results reveal how hosts respond rapidly to local variation in parasitism, and why it pays cuckoos to be secretive, both to avoid alerting their targets and to limit the spread of social information in the local host neighbourhood. PMID:26794435
-
Redjal, Navid; Zhu, Yanni; Shah, Khalid
2015-01-01
Despite advances in standard therapies, the survival of glioblastoma multiforme (GBM) patients has not improved. Limitations to successful translation of new therapies include poor delivery of systemic therapies and use of simplified preclinical models which fail to reflect the clinical complexity of GBMs. Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) induces apoptosis specifically in tumor cells and we have tested its efficacy by on-site delivery via engineered stem cells (SC) in mouse models of GBM that mimic the clinical scenario of tumor aggressiveness and resection. However, about half of tumor lines are resistant to TRAIL and overcoming TRAIL-resistance in GBM by combining therapeutic agents that are currently in clinical trials with SC-TRAIL and understanding the molecular dynamics of these combination therapies are critical to the broad use of TRAIL as a therapeutic agent in clinics. In this study, we screened clinically relevant chemotherapeutic agents for their ability to sensitize resistant GBM cell lines to TRAIL induced apoptosis. We show that low dose cisplatin increases surface receptor expression of death receptor 4/5 post G2 cycle arrest and sensitizes GBM cells to TRAIL induced apoptosis. In vivo, using an intracranial resection model of resistant primary human-derived GBM and real-time optical imaging, we show that a low dose of cisplatin in combination with synthetic extracellular matrix encapsulated SC-TRAIL significantly decreases tumor regrowth and increases survival in mice bearing GBM. This study has the potential to help expedite effective translation of local stem cell-based delivery of TRAIL into the clinical setting to target a broad spectrum of GBMs. © 2014 AlphaMed Press.
-
Residue-level global and local ensemble-ensemble comparisons of protein domains.
Clark, Sarah A; Tronrud, Dale E; Karplus, P Andrew
2015-09-01
Many methods of protein structure generation such as NMR-based solution structure determination and template-based modeling do not produce a single model, but an ensemble of models consistent with the available information. Current strategies for comparing ensembles lose information because they use only a single representative structure. Here, we describe the ENSEMBLATOR and its novel strategy to directly compare two ensembles containing the same atoms to identify significant global and local backbone differences between them on per-atom and per-residue levels, respectively. The ENSEMBLATOR has four components: eePREP (ee for ensemble-ensemble), which selects atoms common to all models; eeCORE, which identifies atoms belonging to a cutoff-distance dependent common core; eeGLOBAL, which globally superimposes all models using the defined core atoms and calculates for each atom the two intraensemble variations, the interensemble variation, and the closest approach of members of the two ensembles; and eeLOCAL, which performs a local overlay of each dipeptide and, using a novel measure of local backbone similarity, reports the same four variations as eeGLOBAL. The combination of eeGLOBAL and eeLOCAL analyses identifies the most significant differences between ensembles. We illustrate the ENSEMBLATOR's capabilities by showing how using it to analyze NMR ensembles and to compare NMR ensembles with crystal structures provides novel insights compared to published studies. One of these studies leads us to suggest that a "consistency check" of NMR-derived ensembles may be a useful analysis step for NMR-based structure determinations in general. The ENSEMBLATOR 1.0 is available as a first generation tool to carry out ensemble-ensemble comparisons. © 2015 The Protein Society.
-
Residue-level global and local ensemble-ensemble comparisons of protein domains
Clark, Sarah A; Tronrud, Dale E; Andrew Karplus, P
2015-01-01
Many methods of protein structure generation such as NMR-based solution structure determination and template-based modeling do not produce a single model, but an ensemble of models consistent with the available information. Current strategies for comparing ensembles lose information because they use only a single representative structure. Here, we describe the ENSEMBLATOR and its novel strategy to directly compare two ensembles containing the same atoms to identify significant global and local backbone differences between them on per-atom and per-residue levels, respectively. The ENSEMBLATOR has four components: eePREP (ee for ensemble-ensemble), which selects atoms common to all models; eeCORE, which identifies atoms belonging to a cutoff-distance dependent common core; eeGLOBAL, which globally superimposes all models using the defined core atoms and calculates for each atom the two intraensemble variations, the interensemble variation, and the closest approach of members of the two ensembles; and eeLOCAL, which performs a local overlay of each dipeptide and, using a novel measure of local backbone similarity, reports the same four variations as eeGLOBAL. The combination of eeGLOBAL and eeLOCAL analyses identifies the most significant differences between ensembles. We illustrate the ENSEMBLATOR's capabilities by showing how using it to analyze NMR ensembles and to compare NMR ensembles with crystal structures provides novel insights compared to published studies. One of these studies leads us to suggest that a “consistency check” of NMR-derived ensembles may be a useful analysis step for NMR-based structure determinations in general. The ENSEMBLATOR 1.0 is available as a first generation tool to carry out ensemble-ensemble comparisons. PMID:26032515
-
Kirilenko, M Yu; Tikunova, E V; Sirotina, S S; Polonikov, A V; Bushueva, O Yu; Churnosov, M I
Primary open-angle glaucoma (POAG) is a multifactorial disease, etiopathogenesis of which largely depends on growth factors. Possessing a variety of medical and biological effects, these cytokines may influence the development and progression of POAG. to reveal the role of genetic polymorphisms of growth factors in predisposition to developing POAG that is refractory to local hypotensive therapy. The object of the study were 162 patients with stage II-III POAG, in whom local hypotensive therapy was inefficient, 90 patients with stage II-III POAG well controlled on local hypotensive therapy, and 191 controls. The material for the study was venous blood taken from the cubital vein of a proband. Isolation of genomic DNA was performed by phenol-chloroform extraction. Analysis of genetic polymorphisms of growth factors was performed through allelic discrimination. For that, synthesis of DNA was carried out via polymerase chain reaction (PCR). It is found that the T IGFR-1 genetic variant (OR=1.34) and a combination of the C VEGF-A and T IGFR-1 genetic variants (OR=1.90) are risk factors of developing POAG that is refractory to local hypotensive therapy. A statistical model for predicting such a risk has been proposed that includes: VEGF-A с.-958C>T genetic marker (rs 833,061), age, concomitant non-inflammatory ocular diseases, microvascular changes in the conjunctiva, the degree of pigmentation of the angle of the anterior chamber, and pseudoexfoliative syndrome. Recognition accuracy of the model is 90.42%. The T IGFR-1 genetic variant and a combination of the C VEGF-A and T IGFR-1 genetic variants increase the risk of developing POAG that is refractory to local hypotensive therapy.
-
Chapiro, Julius; Geschwind, Jean-François
2015-08-01
In this issue, Rozenblum et al ( 1 ) were able to demonstrate that radiofrequency (RF) ablation-induced liver regeneration promotes "off-target" tumorigenesis in a MDR2 knock-out mouse model of hepatocellular carcinoma (HCC) in the setting of chronic liver inflammation. In addition, the authors demonstrated that blocking liver regeneration with a c-met inhibitor might attenuate or eliminate potential tumorigenic effects. These results provide the rationale for combined therapeutic approaches of RF ablation followed by a systemic application of immunomodulatory drugs.
-
Jaber, Abobaker M; Ismail, Mohd Tahir; Altaher, Alsaidi M
2014-01-01
This paper mainly forecasts the daily closing price of stock markets. We propose a two-stage technique that combines the empirical mode decomposition (EMD) with nonparametric methods of local linear quantile (LLQ). We use the proposed technique, EMD-LLQ, to forecast two stock index time series. Detailed experiments are implemented for the proposed method, in which EMD-LPQ, EMD, and Holt-Winter methods are compared. The proposed EMD-LPQ model is determined to be superior to the EMD and Holt-Winter methods in predicting the stock closing prices.
-
Wang, Ranran; Eckelman, Matthew J; Zimmerman, Julie B
2013-10-01
A consequential life cycle assessment (LCA) is conducted to evaluate the trade-offs between water quality improvements and the incremental climate, resource, and economic costs of implementing green (bioretention basin, green roof, and permeable pavement) versus gray (municipal separate stormwater sewer systems, MS4) alternatives of stormwater infrastructure expansions against a baseline combined sewer system with combined sewer overflows in a typical Northeast US watershed for typical, dry, and wet years. Results show that bioretention basins can achieve water quality improvement goals (e.g., mitigating freshwater eutrophication) for the least climate and economic costs of 61 kg CO2 eq. and $98 per kg P eq. reduction, respectively. MS4 demonstrates the minimum life cycle fossil energy use of 42 kg oil eq. per kg P eq. reduction. When integrated with the expansion in stormwater infrastructure, implementation of advanced wastewater treatment processes can further reduce the impact of stormwater runoff on aquatic environment at a minimal environmental cost (77 kg CO2 eq. per kg P eq. reduction), which provides support and valuable insights for the further development of integrated management of stormwater and wastewater. The consideration of critical model parameters (i.e., precipitation intensity, land imperviousness, and infrastructure life expectancy) highlighted the importance and implications of varying local conditions and infrastructure characteristics on the costs and benefits of stormwater management. Of particular note is that the impact of MS4 on the local aquatic environment is highly dependent on local runoff quality indicating that a combined system of green infrastructure prior to MS4 potentially provides a more cost-effective improvement to local water quality.
-
Local lattice distortion in high-entropy alloys
NASA Astrophysics Data System (ADS)
Song, Hongquan; Tian, Fuyang; Hu, Qing-Miao; Vitos, Levente; Wang, Yandong; Shen, Jiang; Chen, Nanxian
2017-07-01
The severe local lattice distortion, induced mainly by the large atomic size mismatch of the alloy components, is one of the four core effects responsible for the unprecedented mechanical behaviors of high-entropy alloys (HEAs). In this work, we propose a supercell model, in which every lattice site has similar local atomic environment, to describe the random distributions of the atomic species in HEAs. Using these supercells in combination with ab initio calculations, we investigate the local lattice distortion of refractory HEAs with body-centered-cubic structure and 3 d HEAs with face-centered-cubic structure. Our results demonstrate that the local lattice distortion of the refractory HEAs is much more significant than that of the 3 d HEAs. We show that the atomic size mismatch evaluated with the empirical atomic radii is not accurate enough to describe the local lattice distortion. Both the lattice distortion energy and the mixing entropy contribute significantly to the thermodynamic stability of HEAs. However the local lattice distortion has negligible effect on the equilibrium lattice parameter and bulk modulus.
-
Models of Sector Flows Under Local, Regional and Airport Weather Constraints
NASA Technical Reports Server (NTRS)
Kulkarni, Deepak
2017-01-01
Recently, the ATM community has made important progress in collaborative trajectory management through the introduction of a new FAA traffic management initiative called a Collaborative Trajectory Options Program (CTOP). FAA can use CTOPs to manage air traffic under multiple constraints (manifested as flow constrained areas or FCAs) in the system, and it allows flight operators to indicate their preferences for routing and delay options. CTOPs also permits better management of the overall trajectory of flights by considering both routing and departure delay options simultaneously. However, adoption of CTOPs in airspace has been hampered by many factors that include challenges in how to identify constrained areas and how to set rates for the FCAs. Decision support tools providing assistance would be particularly helpful in effective use of CTOPs. Such DSTs tools would need models of demand and capacity in the presence of multiple constraints. This study examines different approaches to using historical data to create and validate models of maximum flows in sectors and other airspace regions in the presence of multiple constraints. A challenge in creating an empirical model of flows under multiple constraints is a lack of sufficient historical data that captures diverse situations involving combinations of multiple constraints especially those with severe weather. The approach taken here to deal with this is two-fold. First, we create a generalized sector model encompassing multiple sectors rather than individual sectors in order to increase the amount of data used for creating the model by an order of magnitude. Secondly, we decompose the problem so that the amount of data needed is reduced. This involves creating a baseline demand model plus a separate weather constrained flow reduction model and then composing these into a single integrated model. A nominal demand model is a flow model (gdem) in the presence of clear local weather. This defines the flow as a function of weather constraints in neighboring regions, airport constraints and weather in locations that can cause re-routes to the location of interest. A weather constrained flow reduction model (fwx-red) is a model of reduction in baseline counts as a function of local weather. Because the number of independent variables associated with each of the two decomposed models is smaller than that with a single model, need for amount of data is reduced. Finally, a composite model that combines these two can be represented as fwx-red (gdem(e), l) where e represents non-local constraints and l represents local weather. The approaches studied to developing these models are divided into three categories: (1) Point estimation models (2) Empirical models (3) Theoretical models. Errors in predictions of these different types of models have been estimated. In situations when there is abundant data, point estimation models tend to be very accurate. In contrast, empirical models do better than theoretical models when there is some data available. The biggest benefit of theoretical models is their general applicability in wider range situations once the degree of accuracy of these has been established.
-
Models of Sector Aircraft Counts in the Presence of Local, Regional and Airport Constraints
NASA Technical Reports Server (NTRS)
Kulkarni, Deepak
2017-01-01
Recently, the ATM community has made important progress in collaborative trajectory management through the introduction of a new FAA traffic management initiative called a Collaborative Trajectory Options Program (CTOP). FAA can use CTOPs to manage air traffic under multiple constraints (manifested as flow constrained areas or FCAs) in the system, and it allows flight operators to indicate their preferences for routing and delay options. CTOPs also permits better management of the overall trajectory of flights by considering both routing and departure delay options simultaneously. However, adoption of CTOPs in airspace has been hampered by many factors that include challenges in how to identify constrained areas and how to set rates for the FCAs. Decision support tools providing assistance would be particularly helpful in effective use of CTOPs. Such DSTs tools would need models of demand and capacity in the presence of multiple constraints. This study examines different approaches to using historical data to create and validate models of maximum flows in sectors and other airspace regions in the presence of multiple constraints. A challenge in creating an empirical model of flows under multiple constraints is a lack of sufficient historical data that captures diverse situations involving combinations of multiple constraints especially those with severe weather. The approach taken here to deal with this is two-fold. First, we create a generalized sector model encompassing multiple sectors rather than individual sectors in order to increase the amount of data used for creating the model by an order of magnitude. Secondly, we decompose the problem so that the amount of data needed is reduced. This involves creating a baseline demand model plus a separate weather constrained flow reduction model and then composing these into a single integrated model. A nominal demand model is a flow model (gdem) in the presence of clear local weather. This defines the flow as a function of weather constraints in neighboring regions, airport constraints and weather in locations that can cause re-routes to the location of interest. A weather constrained flow reduction model (fwx-red) is a model of reduction in baseline counts as a function of local weather. Because the number of independent variables associated with each of the two decomposed models is smaller than that with a single model, need for amount of data is reduced. Finally, a composite model that combines these two can be represented as fwx-red (gdem(e), l) where e represents non-local constraints and l represents local weather. The approaches studied to developing these models are divided into three categories: (1) Point estimation models (2) Empirical models (3) Theoretical models. Errors in predictions of these different types of models have been estimated. In situations when there is abundant data, point estimation models tend to be very accurate. In contrast, empirical models do better than theoretical models when there is some data available. The biggest benefit of theoretical models is their general applicability in wider range situations once the degree of accuracy of these has been established.
-
Rapid Processing of a Global Feature in the ON Visual Pathways of Behaving Monkeys.
Huang, Jun; Yang, Yan; Zhou, Ke; Zhao, Xudong; Zhou, Quan; Zhu, Hong; Yang, Yingshan; Zhang, Chunming; Zhou, Yifeng; Zhou, Wu
2017-01-01
Visual objects are recognized by their features. Whereas, some features are based on simple components (i.e., local features, such as orientation of line segments), some features are based on the whole object (i.e., global features, such as an object having a hole in it). Over the past five decades, behavioral, physiological, anatomical, and computational studies have established a general model of vision, which starts from extracting local features in the lower visual pathways followed by a feature integration process that extracts global features in the higher visual pathways. This local-to-global model is successful in providing a unified account for a vast sets of perception experiments, but it fails to account for a set of experiments showing human visual systems' superior sensitivity to global features. Understanding the neural mechanisms underlying the "global-first" process will offer critical insights into new models of vision. The goal of the present study was to establish a non-human primate model of rapid processing of global features for elucidating the neural mechanisms underlying differential processing of global and local features. Monkeys were trained to make a saccade to a target in the black background, which was different from the distractors (white circle) in color (e.g., red circle target), local features (e.g., white square target), a global feature (e.g., white ring with a hole target) or their combinations (e.g., red square target). Contrary to the predictions of the prevailing local-to-global model, we found that (1) detecting a distinction or a change in the global feature was faster than detecting a distinction or a change in color or local features; (2) detecting a distinction in color was facilitated by a distinction in the global feature, but not in the local features; and (3) detecting the hole was interfered by the local features of the hole (e.g., white ring with a squared hole). These results suggest that monkey ON visual systems have a subsystem that is more sensitive to distinctions in the global feature than local features. They also provide the behavioral constraints for identifying the underlying neural substrates.
-
Modelling of Fiber/Matrix Debonding of Composites Under Cyclic Loading
NASA Technical Reports Server (NTRS)
Naghipour, Paria; Pineda, Evan J.; Bednarcyk, Brett A.; Arnold, Steven M.
2013-01-01
The micromechanics theory, generalized method of cells (GMC), was employed to simulate the debonding of fiber/matrix interfaces, within a repeating unit cell subjected to global, cyclic loading, utilizing a cyclic crack growth law. Cycle dependent, interfacial debonding was implemented as a new module to the available GMC formulation. The degradation of interfacial stresses, with applied load cycles, was achieved via progressive evolution of the interfacial compliance. A periodic repeating unit cell, representing the fiber/matrix architecture of a composite, was subjected to combined normal and shear loadings, and degradation of the global transverse stress in successive cycles was monitored. The obtained results were compared to values from a corresponding finite element model. Reasonable agreement was achieved for combined normal and shear loading conditions, with minimal variation for pure loading cases. The local effects of interfacial debonding, and fatigue damage will later be combined as sub-models to predict the experimentally obtained fatigue life of Ti-15-3/Sic composites at the laminate level.
-
ERIC Educational Resources Information Center
Chambers, Jay G.; Parrish, Thomas B.
The Resource Cost Model (RCM) is a resource management system that combines the technical advantages of sophisticated computer simulation software with the practical benefits of group decision making to provide detailed information about educational program costs. The first section of this document introduces the conceptual framework underlying…
-
Combination Therapy Improves Survival in Prostate Cancer Model | Center for Cancer Research
Surgery and radiotherapy are the recommended treatments for localized prostate cancer. Recurrent prostate cancer, however, is often treated with androgen-deprivation therapy. Most patients who undergo this type of therapy eventually develop castration-resistant prostate cancer (CRPC). Though initially androgen-related therapies for CRPC had been thought to be ineffective,
-
The Prenatal Care at School Program
ERIC Educational Resources Information Center
Griswold, Carol H.; Nasso, Jacqueline T.; Swider, Susan; Ellison, Brenda R.; Griswold, Daniel L.; Brooks, Marilyn
2013-01-01
School absenteeism and poor compliance with prenatal appointments are concerns for pregnant teens. The Prenatal Care at School (PAS) program is a new model of prenatal care involving local health care providers and school personnel to reduce the need for students to leave school for prenatal care. The program combines prenatal care and education…
-
Integrating Science and Management to Assess Forest Ecosystem Vulnerability to Climate Change
Leslie A. Brandt; Patricia R. Butler; Stephen D. Handler; Maria K. Janowiak; P. Danielle Shannon; Christopher W. Swanston
2017-01-01
We developed the ecosystem vulnerability assessment approach (EVAA) to help inform potential adaptation actions in response to a changing climate. EVAA combines multiple quantitative models and expert elicitation from scientists and land managers. In each of eight assessment areas, a panel of local experts determined potential vulnerability of forest ecosystems to...
-
Combining Research, Outreach and Student Learning: A New Model in Rhode Island
ERIC Educational Resources Information Center
Grossman-Garber, Deborah; Gold, Arthur; Husband, Thomas
2001-01-01
American research universities are renowned for applying cutting-edge science to the improvement of the world's health and environmental systems. Indeed, as a society, people have come to expect this type of intellectual leadership from their great universities. Less appreciated is the robust opportunity for state and local governments to harness…
-
An, Ji-Yong; Meng, Fan-Rong; You, Zhu-Hong; Fang, Yu-Hong; Zhao, Yu-Jun; Zhang, Ming
2016-01-01
We propose a novel computational method known as RVM-LPQ that combines the Relevance Vector Machine (RVM) model and Local Phase Quantization (LPQ) to predict PPIs from protein sequences. The main improvements are the results of representing protein sequences using the LPQ feature representation on a Position Specific Scoring Matrix (PSSM), reducing the influence of noise using a Principal Component Analysis (PCA), and using a Relevance Vector Machine (RVM) based classifier. We perform 5-fold cross-validation experiments on Yeast and Human datasets, and we achieve very high accuracies of 92.65% and 97.62%, respectively, which is significantly better than previous works. To further evaluate the proposed method, we compare it with the state-of-the-art support vector machine (SVM) classifier on the Yeast dataset. The experimental results demonstrate that our RVM-LPQ method is obviously better than the SVM-based method. The promising experimental results show the efficiency and simplicity of the proposed method, which can be an automatic decision support tool for future proteomics research.
-
Measured and Modeled Hydroxyl (OH) and Hydroperoxyl (HO2) During KORUS-AQ
NASA Astrophysics Data System (ADS)
Brosius, A. L.; Brune, W. H.; Thames, A. B.; Miller, D. O.
2017-12-01
In the troposphere, hydroxyl (OH) reacts with most atmospheric pollutants, initiating their removal from the atmosphere and in some cases creating other atmospheric pollutants, such as ozone and small particles. Hydroperoxyl (HO2) also plays a role in oxidation chemistry by producing tropospheric ozone (O3). Air pollution in Korea is a combination of locally generated pollution, aged pollution from China, and the interaction of local pollution with forest emissions. Thus, OH and HO2 interact with a complex soup of chemical species over Korea, providing a stringent test for the understanding of atmospheric oxidation chemistry. During KORUS-AQ, we measured OH and HO2 using the Airborne Tropospheric Hydrogen Oxides Sensor (ATHOS) as part of a large instrument suite installed on the NASA DC-8 aircraft. We use the Master Chemical Mechanism (MCM), constrained by the simultaneous measurement of many of chemical species to calculate OH and HO2. While the measured and modeled OH and HO2 generally agree within combined uncertainties, there are substantial discrepancies. We will discuss possible reasons for the discrepancies and the implications for air quality regulatory policy.
-
Liu, Haorui; Yi, Fengyan; Yang, Heli
2016-01-01
The shuffled frog leaping algorithm (SFLA) easily falls into local optimum when it solves multioptimum function optimization problem, which impacts the accuracy and convergence speed. Therefore this paper presents grouped SFLA for solving continuous optimization problems combined with the excellent characteristics of cloud model transformation between qualitative and quantitative research. The algorithm divides the definition domain into several groups and gives each group a set of frogs. Frogs of each region search in their memeplex, and in the search process the algorithm uses the “elite strategy” to update the location information of existing elite frogs through cloud model algorithm. This method narrows the searching space and it can effectively improve the situation of a local optimum; thus convergence speed and accuracy can be significantly improved. The results of computer simulation confirm this conclusion. PMID:26819584
-
How vision and movement combine in the hippocampal place code.
Chen, Guifen; King, John A; Burgess, Neil; O'Keefe, John
2013-01-02
How do external environmental and internal movement-related information combine to tell us where we are? We examined the neural representation of environmental location provided by hippocampal place cells while mice navigated a virtual reality environment in which both types of information could be manipulated. Extracellular recordings were made from region CA1 of head-fixed mice navigating a virtual linear track and running in a similar real environment. Despite the absence of vestibular motion signals, normal place cell firing and theta rhythmicity were found. Visual information alone was sufficient for localized firing in 25% of place cells and to maintain a local field potential theta rhythm (but with significantly reduced power). Additional movement-related information was required for normally localized firing by the remaining 75% of place cells. Trials in which movement and visual information were put into conflict showed that they combined nonlinearly to control firing location, and that the relative influence of movement versus visual information varied widely across place cells. However, within this heterogeneity, the behavior of fully half of the place cells conformed to a model of path integration in which the presence of visual cues at the start of each run together with subsequent movement-related updating of position was sufficient to maintain normal fields.
-
Depeursinge, Adrien; Kurtz, Camille; Beaulieu, Christopher F.; Napel, Sandy; Rubin, Daniel L.
2014-01-01
We describe a framework to model visual semantics of liver lesions in CT images in order to predict the visual semantic terms (VST) reported by radiologists in describing these lesions. Computational models of VST are learned from image data using high–order steerable Riesz wavelets and support vector machines (SVM). The organization of scales and directions that are specific to every VST are modeled as linear combinations of directional Riesz wavelets. The models obtained are steerable, which means that any orientation of the model can be synthesized from linear combinations of the basis filters. The latter property is leveraged to model VST independently from their local orientation. In a first step, these models are used to predict the presence of each semantic term that describes liver lesions. In a second step, the distances between all VST models are calculated to establish a non–hierarchical computationally–derived ontology of VST containing inter–term synonymy and complementarity. A preliminary evaluation of the proposed framework was carried out using 74 liver lesions annotated with a set of 18 VSTs from the RadLex ontology. A leave–one–patient–out cross–validation resulted in an average area under the ROC curve of 0.853 for predicting the presence of each VST when using SVMs in a feature space combining the magnitudes of the steered models with CT intensities. Likelihood maps are created for each VST, which enables high transparency of the information modeled. The computationally–derived ontology obtained from the VST models was found to be consistent with the underlying semantics of the visual terms. It was found to be complementary to the RadLex ontology, and constitutes a potential method to link the image content to visual semantics. The proposed framework is expected to foster human–computer synergies for the interpretation of radiological images while using rotation–covariant computational models of VSTs to (1) quantify their local likelihood and (2) explicitly link them with pixel–based image content in the context of a given imaging domain. PMID:24808406
-
NASA Technical Reports Server (NTRS)
Creamean, J. M.; Ault, A. P.; White, A. B.; Neiman, P. J.; Ralph, F. M.; Minnis, Patrick; Prather, K. A.
2014-01-01
Aerosols that serve as cloud condensation nuclei (CCN) and ice nuclei (IN) have the potential to profoundly influence precipitation processes. Furthermore, changes in orographic precipitation have broad implications for reservoir storage and flood risks. As part of the CalWater I field campaign (2009-2011), the impacts of aerosol sources on precipitation were investigated in the California Sierra Nevada. In 2009, the precipitation collected on the ground was influenced by both local biomass burning (up to 79% of the insoluble residues found in precipitation) and long-range transported dust and biological particles (up to 80% combined), while in 2010, by mostly local sources of biomass burning and pollution (30-79% combined), and in 2011 by mostly long-range transport from distant sources (up to 100% dust and biological). Although vast differences in the source of residues was observed from year-to-year, dust and biological residues were omnipresent (on average, 55% of the total residues combined) and were associated with storms consisting of deep convective cloud systems and larger quantities of precipitation initiated in the ice phase. Further, biological residues were dominant during storms with relatively warm cloud temperatures (up to -15 C), suggesting these particles were more efficient IN compared to mineral dust. On the other hand, lower percentages of residues from local biomass burning and pollution were observed (on average 31% and 9%, respectively), yet these residues potentially served as CCN at the base of shallow cloud systems when precipitation quantities were low. The direct connection of the source of aerosols within clouds and precipitation type and quantity can be used in models to better assess how local emissions versus long-range transported dust and biological aerosols play a role in impacting regional weather and climate, ultimately with the goal of more accurate predictive weather forecast models and water resource management.
-
Seismic tomography of the southern California crust based on spectral-element and adjoint methods
NASA Astrophysics Data System (ADS)
Tape, Carl; Liu, Qinya; Maggi, Alessia; Tromp, Jeroen
2010-01-01
We iteratively improve a 3-D tomographic model of the southern California crust using numerical simulations of seismic wave propagation based on a spectral-element method (SEM) in combination with an adjoint method. The initial 3-D model is provided by the Southern California Earthquake Center. The data set comprises three-component seismic waveforms (i.e. both body and surface waves), filtered over the period range 2-30 s, from 143 local earthquakes recorded by a network of 203 stations. Time windows for measurements are automatically selected by the FLEXWIN algorithm. The misfit function in the tomographic inversion is based on frequency-dependent multitaper traveltime differences. The gradient of the misfit function and related finite-frequency sensitivity kernels for each earthquake are computed using an adjoint technique. The kernels are combined using a source subspace projection method to compute a model update at each iteration of a gradient-based minimization algorithm. The inversion involved 16 iterations, which required 6800 wavefield simulations. The new crustal model, m16, is described in terms of independent shear (VS) and bulk-sound (VB) wave speed variations. It exhibits strong heterogeneity, including local changes of +/-30 per cent with respect to the initial 3-D model. The model reveals several features that relate to geological observations, such as sedimentary basins, exhumed batholiths, and contrasting lithologies across faults. The quality of the new model is validated by quantifying waveform misfits of full-length seismograms from 91 earthquakes that were not used in the tomographic inversion. The new model provides more accurate synthetic seismograms that will benefit seismic hazard assessment.
-
Adjoint Tomography of the Southern California Crust (Invited) (Invited)
NASA Astrophysics Data System (ADS)
Tape, C.; Liu, Q.; Maggi, A.; Tromp, J.
2009-12-01
We iteratively improve a three-dimensional tomographic model of the southern California crust using numerical simulations of seismic wave propagation based on a spectral-element method (SEM) in combination with an adjoint method. The initial 3D model is provided by the Southern California Earthquake Center. The dataset comprises three-component seismic waveforms (i.e. both body and surface waves), filtered over the period range 2-30 s, from 143 local earthquakes recorded by a network of 203 stations. Time windows for measurements are automatically selected by the FLEXWIN algorithm. The misfit function in the tomographic inversion is based on frequency-dependent multitaper traveltime differences. The gradient of the misfit function and related finite-frequency sensitivity kernels for each earthquake are computed using an adjoint technique. The kernels are combined using a source subspace projection method to compute a model update at each iteration of a gradient-based minimization algorithm. The inversion involved 16 iterations, which required 6800 wavefield simulations and a total of 0.8 million CPU hours. The new crustal model, m16, is described in terms of independent shear (Vs) and bulk-sound (Vb) wavespeed variations. It exhibits strong heterogeneity, including local changes of ±30% with respect to the initial 3D model. The model reveals several features that relate to geologic observations, such as sedimentary basins, exhumed batholiths, and contrasting lithologies across faults. The quality of the new model is validated by quantifying waveform misfits of full-length seismograms from 91 earthquakes that were not used in the tomographic inversion. The new model provides more accurate synthetic seismograms that will benefit seismic hazard assessment.
-
Combining local scaling and global methods to detect soil pore space
NASA Astrophysics Data System (ADS)
Martin-Sotoca, Juan Jose; Saa-Requejo, Antonio; Grau, Juan B.; Tarquis, Ana M.
2017-04-01
The characterization of the spatial distribution of soil pore structures is essential to obtain different parameters that will influence in several models related to water flow and/or microbial growth processes. The first step in pore structure characterization is obtaining soil images that best approximate reality. Over the last decade, major technological advances in X-ray computed tomography (CT) have allowed for the investigation and reconstruction of natural porous media architectures at very fine scales. The subsequent step is delimiting the pore structure (pore space) from the CT soil images applying a thresholding. Many times we could find CT-scan images that show low contrast at the solid-void interface that difficult this step. Different delimitation methods can result in different spatial distributions of pores influencing the parameters used in the models. Recently, new local segmentation method using local greyscale value (GV) concentration variabilities, based on fractal concepts, has been presented. This method creates singularity maps to measure the GV concentration at each point. The C-A method was combined with the singularity map approach (Singularity-CA method) to define local thresholds that can be applied to binarize CT images. Comparing this method with classical methods, such as Otsu and Maximum Entropy, we observed that more pores can be detected mainly due to its ability to amplify anomalous concentrations. However, it delineated many small pores that were incorrect. In this work, we present an improve version of Singularity-CA method that avoid this problem basically combining it with the global classical methods. References Martín-Sotoca, J.J., A. Saa-Requejo, J.B. Grau, A.M. Tarquis. New segmentation method based on fractal properties using singularity maps. Geoderma, 287, 40-53, 2017. Martín-Sotoca, J.J, A. Saa-Requejo, J.B. Grau, A.M. Tarquis. Local 3D segmentation of soil pore space based on fractal properties using singularity maps. Geoderma, http://dx.doi.org/10.1016/j.geoderma.2016.11.029. Torre, Iván G., Juan C. Losada and A.M. Tarquis. Multiscaling properties of soil images. Biosystems Engineering, http://dx.doi.org/10.1016/j.biosystemseng.2016.11.006.
-
NASA Astrophysics Data System (ADS)
Itter, M.; Finley, A. O.; Hooten, M.; Higuera, P. E.; Marlon, J. R.; McLachlan, J. S.; Kelly, R.
2016-12-01
Sediment charcoal records are used in paleoecological analyses to identify individual local fire events and to estimate fire frequency and regional biomass burned at centennial to millenial time scales. Methods to identify local fire events based on sediment charcoal records have been well developed over the past 30 years, however, an integrated statistical framework for fire identification is still lacking. We build upon existing paleoecological methods to develop a hierarchical Bayesian point process model for local fire identification and estimation of fire return intervals. The model is unique in that it combines sediment charcoal records from multiple lakes across a region in a spatially-explicit fashion leading to estimation of a joint, regional fire return interval in addition to lake-specific local fire frequencies. Further, the model estimates a joint regional charcoal deposition rate free from the effects of local fires that can be used as a measure of regional biomass burned over time. Finally, the hierarchical Bayesian approach allows for tractable error propagation such that estimates of fire return intervals reflect the full range of uncertainty in sediment charcoal records. Specific sources of uncertainty addressed include sediment age models, the separation of local versus regional charcoal sources, and generation of a composite charcoal record The model is applied to sediment charcoal records from a dense network of lakes in the Yukon Flats region of Alaska. The multivariate joint modeling approach results in improved estimates of regional charcoal deposition with reduced uncertainty in the identification of individual fire events and local fire return intervals compared to individual lake approaches. Modeled individual-lake fire return intervals range from 100 to 500 years with a regional interval of roughly 200 years. Regional charcoal deposition to the network of lakes is correlated up to 50 kilometers. Finally, the joint regional charcoal deposition rate exhibits changes over time coincident with major climatic and vegetation shifts over the past 10,000 years. Ongoing work will use the regional charcoal deposition rate to estimate changes in biomass burned as a function of climate variability and regional vegetation pattern.
-
Zwolak, Pawel; Farei-Campagna, Jan; Jentzsch, Thorsten; von Rechenberg, Brigitte; Werner, Clément M
2018-01-01
Posterolateral spinal fusion is a common orthopaedic surgery performed to treat degenerative and traumatic deformities of the spinal column. In posteriolateral spinal fusion, different osteoinductive demineralized bone matrix products have been previously investigated. We evaluated the effect of locally applied zoledronic acid in combination with commercially available demineralized bone matrix putty on new bone formation in posterolateral spinal fusion in a murine in vivo model. A posterolateral sacral spine fusion in murine model was used to evaluate the new bone formation. We used the sacral spine fusion model to model the clinical situation in which a bone graft or demineralized bone matrix is applied after dorsal instrumentation of the spine. In our study, group 1 received decortications only (n = 10), group 2 received decortication, and absorbable collagen sponge carrier, group 3 received decortication and absorbable collagen sponge carrier with zoledronic acid in dose 10 µg, group 4 received demineralized bone matrix putty (DBM putty) plus decortication (n = 10), and group 5 received DBM putty, decortication and locally applied zoledronic acid in dose 10 µg. Imaging was performed using MicroCT for new bone formation assessment. Also, murine spines were harvested for histopathological analysis 10 weeks after surgery. The surgery performed through midline posterior approach was reproducible. In group with decortication alone there was no new bone formation. Application of demineralized bone matrix putty alone produced new bone formation which bridged the S1-S4 laminae. Local application of zoledronic acid to demineralized bone matrix putty resulted in significant increase of new bone formation as compared to demineralized bone matrix putty group alone. A single local application of zoledronic acid with DBM putty during posterolateral fusion in sacral murine spine model increased significantly new bone formation in situ in our model. Therefore, our results justify further investigations to potentially use local application of zoledronic acid in future clinical studies.
-
NASA Astrophysics Data System (ADS)
Babaci-Wilhite, Zehlia
2017-06-01
This article addresses the importance of teaching and learning science in local languages. The author argues that acknowledging local knowledge and using local languages in science education while emphasising inquiry-based learning improve teaching and learning science. She frames her arguments with the theory of inquiry, which draws on perspectives of both dominant and non-dominant cultures with a focus on science literacy as a human right. She first examines key assumptions about knowledge which inform mainstream educational research and practice. She then argues for an emphasis on contextualised learning as a right in education. This means accounting for contextualised knowledge and resisting the current trend towards de-contextualisation of curricula. This trend is reflected in Zanzibar's recent curriculum reform, in which English replaced Kiswahili as the language of instruction (LOI) in the last two years of primary school. The author's own research during the initial stage of the change (2010-2015) revealed that the effect has in fact proven to be counterproductive, with educational quality deteriorating further rather than improving. Arguing that language is essential to inquiry-based learning, she introduces a new didactic model which integrates alternative assumptions about the value of local knowledge and local languages in the teaching and learning of science subjects. In practical terms, the model is designed to address key science concepts through multiple modalities - "do it, say it, read it, write it" - a "hands-on" experiential combination which, she posits, may form a new platform for innovation based on a unique mix of local and global knowledge, and facilitate genuine science literacy. She provides examples from cutting-edge educational research and practice that illustrate this new model of teaching and learning science. This model has the potential to improve learning while supporting local languages and culture, giving local languages their rightful place in all aspects of education.
-
Another convex combination of product states for the separable Werner state
DOE Office of Scientific and Technical Information (OSTI.GOV)
Azuma, Hiroo; Ban, Masashi; CREST, Japan Science and Technology Agency, 1-1-9 Yaesu, Chuo-ku, Tokyo 103-0028
2006-03-15
In this paper, we write down the separable Werner state in a two-qubit system explicitly as a convex combination of product states, which is different from the convex combination obtained by Wootters' method. The Werner state in a two-qubit system has a single real parameter and varies from inseparable to separable according to the value of its parameter. We derive a hidden variable model that is induced by our decomposed form for the separable Werner state. From our explicit form of the convex combination of product states, we understand the following: The critical point of the parameter for separability ofmore » the Werner state comes from positivity of local density operators of the qubits.« less
-
NASA Astrophysics Data System (ADS)
Stige, Leif Chr.; Langangen, Øystein; Yaragina, Natalia A.; Vikebø, Frode B.; Bogstad, Bjarte; Ottersen, Geir; Stenseth, Nils Chr.; Hjermann, Dag Ø.
2015-05-01
Understanding the causes of the large interannual fluctuations in the recruitment to many marine fishes is a key challenge in fisheries ecology. We here propose that the combination of mechanistic and statistical modelling of the pelagic early life stages (ELS) prior to recruitment can be a powerful approach for improving our understanding of local-scale and population-scale dynamics. Specifically, this approach allows separating effects of ocean transport and survival, and thereby enhances the knowledge of the processes that regulate recruitment. We analyse data on the pelagic eggs, larvae and post-larvae of Northeast Arctic cod and on copepod nauplii, the main prey of the cod larvae. The data originate from two surveys, one in spring and one in summer, for 30 years. A coupled physical-biological model is used to simulate the transport, ambient temperature and development of cod ELS from spawning through spring and summer. The predictions from this model are used as input in a statistical analysis of the summer data, to investigate effects of covariates thought to be linked to growth and survival. We find significant associations between the local-scale ambient copepod nauplii concentration and temperature in spring and the local-scale occurrence of cod (post)larvae in summer, consistent with effects on survival. Moreover, years with low copepod nauplii concentrations and low temperature in spring are significantly associated with lower mean length of the cod (post)larvae in summer, likely caused in part by higher mortality leading to increased dominance of young and hence small individuals. Finally, we find that the recruitment at age 3 is strongly associated with the mean body length of the cod ELS, highlighting the biological significance of the findings.
-
NASA Technical Reports Server (NTRS)
VandeVen, C.; Weiss, S. B.
2001-01-01
Our challenge is to model plant species distributions in complex montane environments using disparate sources of data, including topography, geology, and hyperspectral data. From an ecologist's point of view, species distributions are determined by local environment and disturbance history, while spectral data are 'ancillary.' However, a remote sensor's perspective says that spectral data provide picture of what vegetation is there, topographic and geologic data are ancillary. In order to bridge the gap, all available data should be used to get the best possible prediction of species distributions using complex multivariate techniques implemented on a GIS. Vegetation reflects local climatic and nutrient conditions, both of which can be modeled, allowing predictive mapping of vegetation distributions. Geologic substrate strongly affects chemical, thermal, and physical properties of soils, while climatic conditions are determined by local topography. As elevation increases, precipitation increases and temperature decreases. Aspect, slope, and surrounding topography determine potential insolation, so that south-facing slopes are warmer and north-facing slopes cooler at a given elevation. Topographic position (ridge, slope, canyon, or meadow) and slope angle affect sediment accumulation and soil depth. These factors combine as complex environmental gradients, and underlie many features of plant distributions. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data, digital elevation models, digitized geologic maps, and 378 ground control points were used to predictively map species distributions in the central and southern White Mountains, along the western boundary of the Basin and Range province. Minimum Noise Fraction (MNF) bands were calculated from the visible and near-infrared AVIRIS bands, and combined with digitized geologic maps and topographic variables using Canonical Correspondence Analysis (CCA). CCA allows for modeling species 'envelopes' in multidimensional environmental space, which can then be projected across entire landscapes.
-
NASA Astrophysics Data System (ADS)
Vacquie, Laure; Houet, Thomas
2016-04-01
In the last century, European mountain landscapes have experienced significant transformations. Natural and anthropogenic changes, climate changes, touristic and industrial development, socio-economic interactions, and their implications in terms of LUCC (land use and land cover changes) have directly influenced the spatial organization and vulnerability of mountain landscapes. This study is conducted as part of the SAMCO project founded by the French National Science Agency (ANR). It aims at developing a methodological approach, combining various tools, modelling platforms and methods, to identify vulnerable regions to landslide hazards accounting for futures LUCC. It presents an integrated approach combining participative scenarios and a LULC changes simulation models to assess the combined effects of LUCC and climate change on landslide risks in the Cauterets valley (French Pyrenees Mountains) up to 2100. Through vulnerability and risk mapping, the objective is to gather information to support landscape planning and implement land use strategies with local stakeholders for risk management. Four contrasting scenarios are developed and exhibit contrasting trajectories of socio-economic development. Prospective scenarios are based on national and international socio-economic contexts relying on existing assessment reports. The methodological approach integrates knowledge from local stakeholders to refine each scenario during their construction and to reinforce their plausibility and relevance by accounting for local specificities, e.g. logging and pastoral activities, touristic development, urban planning, etc. A process-based model, the Forecasting Scenarios for Mountains (ForeSceM) model, developed on the Dinamica Ego modelling platform is used to spatially allocate futures LUCC for each prospective scenario. Concurrently, a spatial decision support tool, i.e. the SYLVACCESS model, is used to identify accessible areas for forestry in scenario projecting logging activities. The method results in the development of LULC maps providing insights into a range of alternative futures using a scope of socio-economic and environmental conditions. A landslides assessment model, the ALICE model is then used as a final tool to analyze the potential impacts of simulated LUCC on landslide risks and the consequences in terms of vulnerability, e.g. changes in disaster risk allocation or characterization, degree of perturbation. This assessment intends to provide insights onto the potential future development of the valley to help identify areas at stake and to guide decision makers to help the risk management. Preliminary results show strong differences of futures land use and land cover maps that have significant influence on landslides hazards.
-
He, Bo; Zhang, Shujing; Yan, Tianhong; Zhang, Tao; Liang, Yan; Zhang, Hongjin
2011-01-01
Mobile autonomous systems are very important for marine scientific investigation and military applications. Many algorithms have been studied to deal with the computational efficiency problem required for large scale simultaneous localization and mapping (SLAM) and its related accuracy and consistency. Among these methods, submap-based SLAM is a more effective one. By combining the strength of two popular mapping algorithms, the Rao-Blackwellised particle filter (RBPF) and extended information filter (EIF), this paper presents a combined SLAM-an efficient submap-based solution to the SLAM problem in a large scale environment. RBPF-SLAM is used to produce local maps, which are periodically fused into an EIF-SLAM algorithm. RBPF-SLAM can avoid linearization of the robot model during operating and provide a robust data association, while EIF-SLAM can improve the whole computational speed, and avoid the tendency of RBPF-SLAM to be over-confident. In order to further improve the computational speed in a real time environment, a binary-tree-based decision-making strategy is introduced. Simulation experiments show that the proposed combined SLAM algorithm significantly outperforms currently existing algorithms in terms of accuracy and consistency, as well as the computing efficiency. Finally, the combined SLAM algorithm is experimentally validated in a real environment by using the Victoria Park dataset.
-
NASA Astrophysics Data System (ADS)
Apel, H.; Trepat, O. M.; Hung, N. N.; Chinh, D. T.; Merz, B.; Dung, N. V.
2015-08-01
Many urban areas experience both fluvial and pluvial floods, because locations next to rivers are preferred settlement areas, and the predominantly sealed urban surface prevents infiltration and facilitates surface inundation. The latter problem is enhanced in cities with insufficient or non-existent sewer systems. While there are a number of approaches to analyse either fluvial or pluvial flood hazard, studies of combined fluvial and pluvial flood hazard are hardly available. Thus this study aims at the analysis of fluvial and pluvial flood hazard individually, but also at developing a method for the analysis of combined pluvial and fluvial flood hazard. This combined fluvial-pluvial flood hazard analysis is performed taking Can Tho city, the largest city in the Vietnamese part of the Mekong Delta, as example. In this tropical environment the annual monsoon triggered floods of the Mekong River can coincide with heavy local convective precipitation events causing both fluvial and pluvial flooding at the same time. Fluvial flood hazard was estimated with a copula based bivariate extreme value statistic for the gauge Kratie at the upper boundary of the Mekong Delta and a large-scale hydrodynamic model of the Mekong Delta. This provided the boundaries for 2-dimensional hydrodynamic inundation simulation for Can Tho city. Pluvial hazard was estimated by a peak-over-threshold frequency estimation based on local rain gauge data, and a stochastic rain storm generator. Inundation was simulated by a 2-dimensional hydrodynamic model implemented on a Graphical Processor Unit (GPU) for time-efficient flood propagation modelling. All hazards - fluvial, pluvial and combined - were accompanied by an uncertainty estimation considering the natural variability of the flood events. This resulted in probabilistic flood hazard maps showing the maximum inundation depths for a selected set of probabilities of occurrence, with maps showing the expectation (median) and the uncertainty by percentile maps. The results are critically discussed and ways for their usage in flood risk management are outlined.
-
Rajeshkumar, N V; Yabuuchi, Shinichi; Pai, Shweta G; Tong, Zeen; Hou, Shihe; Bateman, Scott; Pierce, Daniel W; Heise, Carla; Von Hoff, Daniel D; Maitra, Anirban; Hidalgo, Manuel
2016-08-09
Albumin-bound paclitaxel (nab-paclitaxel, nab-PTX) plus gemcitabine (GEM) combination has demonstrated efficient antitumour activity and statistically significant overall survival of patients with metastatic pancreatic ductal adenocarcinoma (PDAC) compared with GEM monotherapy. This regimen is currently approved as a standard of care treatment option for patients with metastatic PDAC. It is unclear whether cremophor-based PTX combined with GEM provide a similar level of therapeutic efficacy in PDAC. We comprehensively explored the antitumour efficacy, effect on metastatic dissemination, tumour stroma and survival advantage following GEM, PTX and nab-PTX as monotherapy or in combination with GEM in a locally advanced, and a highly metastatic orthotopic model of human PDAC. Nab-PTX treatment resulted in significantly higher paclitaxel tumour plasma ratio (1.98-fold), robust stromal depletion, antitumour efficacy (3.79-fold) and survival benefit compared with PTX treatment. PTX plus GEM treatment showed no survival gain over GEM monotherapy. However, nab-PTX in combination with GEM decreased primary tumour burden, metastatic dissemination and significantly increased median survival of animals compared with either agents alone. These therapeutic effects were accompanied by depletion of dense fibrotic tumour stroma and decreased proliferation of carcinoma cells. Notably, nab-PTX monotherapy was equivalent to nab-PTX plus GEM in providing survival advantage to mice in a highly aggressive metastatic PDAC model, indicating that nab-PTX could potentially stop the progression of late-stage pancreatic cancer. Our data confirmed that therapeutic efficacy of PTX and nab-PTX vary widely, and the contention that these agents elicit similar antitumour response was not supported. The addition of PTX to GEM showed no survival advantage, concluding that a clinical combination of PTX and GEM may unlikely to provide significant survival advantage over GEM monotherapy and may not be a viable alternative to the current standard-of-care nab-PTX plus GEM regimen for the treatment of PDAC patients.
-
Robust active contour via additive local and global intensity information based on local entropy
NASA Astrophysics Data System (ADS)
Yuan, Shuai; Monkam, Patrice; Zhang, Feng; Luan, Fangjun; Koomson, Ben Alfred
2018-01-01
Active contour-based image segmentation can be a very challenging task due to many factors such as high intensity inhomogeneity, presence of noise, complex shape, weak boundaries objects, and dependence on the position of the initial contour. We propose a level set-based active contour method to segment complex shape objects from images corrupted by noise and high intensity inhomogeneity. The energy function of the proposed method results from combining the global intensity information and local intensity information with some regularization factors. First, the global intensity term is proposed based on a scheme formulation that considers two intensity values for each region instead of one, which outperforms the well-known Chan-Vese model in delineating the image information. Second, the local intensity term is formulated based on local entropy computed considering the distribution of the image brightness and using the generalized Gaussian distribution as the kernel function. Therefore, it can accurately handle high intensity inhomogeneity and noise. Moreover, our model is not dependent on the position occupied by the initial curve. Finally, extensive experiments using various images have been carried out to illustrate the performance of the proposed method.
-
NASA Astrophysics Data System (ADS)
Magnani, Federico; Dewar, Roderick C.; Borghetti, Marco
2009-04-01
Leakage (spillover) refers to the unintended negative (positive) consequences of forest carbon (C) management in one area on C storage elsewhere. For example, the local C storage benefit of less intensive harvesting in one area may be offset, partly or completely, by intensified harvesting elsewhere in order to meet global timber demand. We present the results of a theoretical study aimed at identifying the key factors determining leakage and spillover, as a prerequisite for more realistic numerical studies. We use a simple model of C storage in managed forest ecosystems and their wood products to derive approximate analytical expressions for the leakage induced by decreasing the harvesting frequency of existing forest, and the spillover induced by establishing new plantations, assuming a fixed total wood production from local and remote (non-local) forests combined. We find that leakage and spillover depend crucially on the growth rates, wood product lifetimes and woody litter decomposition rates of local and remote forests. In particular, our results reveal critical thresholds for leakage and spillover, beyond which effects of forest management on remote C storage exceed local effects. Order of magnitude estimates of leakage indicate its potential importance at global scales.
-
Action detection by double hierarchical multi-structure space-time statistical matching model
NASA Astrophysics Data System (ADS)
Han, Jing; Zhu, Junwei; Cui, Yiyin; Bai, Lianfa; Yue, Jiang
2018-03-01
Aimed at the complex information in videos and low detection efficiency, an actions detection model based on neighboring Gaussian structure and 3D LARK features is put forward. We exploit a double hierarchical multi-structure space-time statistical matching model (DMSM) in temporal action localization. First, a neighboring Gaussian structure is presented to describe the multi-scale structural relationship. Then, a space-time statistical matching method is proposed to achieve two similarity matrices on both large and small scales, which combines double hierarchical structural constraints in model by both the neighboring Gaussian structure and the 3D LARK local structure. Finally, the double hierarchical similarity is fused and analyzed to detect actions. Besides, the multi-scale composite template extends the model application into multi-view. Experimental results of DMSM on the complex visual tracker benchmark data sets and THUMOS 2014 data sets show the promising performance. Compared with other state-of-the-art algorithm, DMSM achieves superior performances.
-
Dynamic behavior of the interaction between epidemics and cascades on heterogeneous networks
NASA Astrophysics Data System (ADS)
Jiang, Lurong; Jin, Xinyu; Xia, Yongxiang; Ouyang, Bo; Wu, Duanpo
2014-12-01
Epidemic spreading and cascading failure are two important dynamical processes on complex networks. They have been investigated separately for a long time. But in the real world, these two dynamics sometimes may interact with each other. In this paper, we explore a model combined with the SIR epidemic spreading model and a local load sharing cascading failure model. There exists a critical value of the tolerance parameter for which the epidemic with high infection probability can spread out and infect a fraction of the network in this model. When the tolerance parameter is smaller than the critical value, the cascading failure cuts off the abundance of paths and blocks the spreading of the epidemic locally. While the tolerance parameter is larger than the critical value, the epidemic spreads out and infects a fraction of the network. A method for estimating the critical value is proposed. In simulations, we verify the effectiveness of this method in the uncorrelated configuration model (UCM) scale-free networks.
-
Tests of local Lorentz invariance violation of gravity in the standard model extension with pulsars.
Shao, Lijing
2014-03-21
The standard model extension is an effective field theory introducing all possible Lorentz-violating (LV) operators to the standard model and general relativity (GR). In the pure-gravity sector of minimal standard model extension, nine coefficients describe dominant observable deviations from GR. We systematically implemented 27 tests from 13 pulsar systems to tightly constrain eight linear combinations of these coefficients with extensive Monte Carlo simulations. It constitutes the first detailed and systematic test of the pure-gravity sector of minimal standard model extension with the state-of-the-art pulsar observations. No deviation from GR was detected. The limits of LV coefficients are expressed in the canonical Sun-centered celestial-equatorial frame for the convenience of further studies. They are all improved by significant factors of tens to hundreds with existing ones. As a consequence, Einstein's equivalence principle is verified substantially further by pulsar experiments in terms of local Lorentz invariance in gravity.
-
NASA Astrophysics Data System (ADS)
Young, S. L.; Kress, B. T.; Rodriguez, J. V.; McCollough, J. P.
2013-12-01
Operational specifications of space environmental hazards can be an important input used by decision makers. Ideally the specification would come from on-board sensors, but for satellites where that capability is not available another option is to map data from remote observations to the location of the satellite. This requires a model of the physical environment and an understanding of its accuracy for mapping applications. We present a statistical comparison between magnetic field model mappings of solar energetic particle observations made by NOAA's Geostationary Operational Environmental Satellites (GOES) to the location of the Combined Release and Radiation Effects Satellite (CRRES). Because CRRES followed a geosynchronous transfer orbit which precessed in local time this allows us to examine the model accuracy between LEO and GEO orbits across a range of local times. We examine the accuracy of multiple magnetic field models using a variety of statistics and examine their utility for operational purposes.
-
Action detection by double hierarchical multi-structure space–time statistical matching model
NASA Astrophysics Data System (ADS)
Han, Jing; Zhu, Junwei; Cui, Yiyin; Bai, Lianfa; Yue, Jiang
2018-06-01
Aimed at the complex information in videos and low detection efficiency, an actions detection model based on neighboring Gaussian structure and 3D LARK features is put forward. We exploit a double hierarchical multi-structure space-time statistical matching model (DMSM) in temporal action localization. First, a neighboring Gaussian structure is presented to describe the multi-scale structural relationship. Then, a space-time statistical matching method is proposed to achieve two similarity matrices on both large and small scales, which combines double hierarchical structural constraints in model by both the neighboring Gaussian structure and the 3D LARK local structure. Finally, the double hierarchical similarity is fused and analyzed to detect actions. Besides, the multi-scale composite template extends the model application into multi-view. Experimental results of DMSM on the complex visual tracker benchmark data sets and THUMOS 2014 data sets show the promising performance. Compared with other state-of-the-art algorithm, DMSM achieves superior performances.
-
Local effects of redundant terrestrial and GPS-based tie vectors in ITRF-like combinations
NASA Astrophysics Data System (ADS)
Abbondanza, Claudio; Altamimi, Zuheir; Sarti, Pierguido; Negusini, Monia; Vittuari, Luca
2009-11-01
Tie vectors (TVs) between co-located space geodetic instruments are essential for combining terrestrial reference frames (TRFs) realised using different techniques. They provide relative positioning between instrumental reference points (RPs) which are part of a global geodetic network such as the international terrestrial reference frame (ITRF). This paper gathers the set of very long baseline interferometry (VLBI)-global positioning system (GPS) local ties performed at the observatory of Medicina (Northern Italy) during the years 2001-2006 and discusses some important aspects related to the usage of co-location ties in the combinations of TRFs. Two measurement approaches of local survey are considered here: a GPS-based approach and a classical approach based on terrestrial observations (i.e. angles, distances and height differences). The behaviour of terrestrial local ties, which routinely join combinations of space geodetic solutions, is compared to that of GPS-based local ties. In particular, we have performed and analysed different combinations of satellite laser ranging (SLR), VLBI and GPS long term solutions in order to (i) evaluate the local effects of the insertion of the series of TVs computed at Medicina, (ii) investigate the consistency of GPS-based TVs with respect to space geodetic solutions, (iii) discuss the effects of an imprecise alignment of TVs from a local to a global reference frame. Results of ITRF-like combinations show that terrestrial TVs originate the smallest residuals in all the three components. In most cases, GPS-based TVs fit space geodetic solutions very well, especially in the horizontal components (N, E). On the contrary, the estimation of the VLBI RP Up component through GPS technique appears to be awkward, since the corresponding post fit residuals are considerably larger. Besides, combination tests including multi-temporal TVs display local effects of residual redistribution, when compared to those solutions where Medicina TVs are added one at a time. Finally, the combination of TRFs turns out to be sensitive to the orientation of the local tie into the global frame.
-
Analysis of typical fault-tolerant architectures using HARP
NASA Technical Reports Server (NTRS)
Bavuso, Salvatore J.; Bechta Dugan, Joanne; Trivedi, Kishor S.; Rothmann, Elizabeth M.; Smith, W. Earl
1987-01-01
Difficulties encountered in the modeling of fault-tolerant systems are discussed. The Hybrid Automated Reliability Predictor (HARP) approach to modeling fault-tolerant systems is described. The HARP is written in FORTRAN, consists of nearly 30,000 lines of codes and comments, and is based on behavioral decomposition. Using the behavioral decomposition, the dependability model is divided into fault-occurrence/repair and fault/error-handling models; the characteristics and combining of these two models are examined. Examples in which the HARP is applied to the modeling of some typical fault-tolerant systems, including a local-area network, two fault-tolerant computer systems, and a flight control system, are presented.
-
Cho, Byungchul; Poulsen, Per; Ruan, Dan; Sawant, Amit; Keall, Paul J
2012-11-21
The goal of this work was to experimentally quantify the geometric accuracy of a novel real-time 3D target localization method using sequential kV imaging combined with respiratory monitoring for clinically realistic arc and static field treatment delivery and target motion conditions. A general method for real-time target localization using kV imaging and respiratory monitoring was developed. Each dimension of internal target motion T(x, y, z; t) was estimated from the external respiratory signal R(t) through the correlation between R(t(i)) and the projected marker positions p(x(p), y(p); t(i)) on kV images by a state-augmented linear model: T(x, y, z; t) = aR(t) + bR(t - τ) + c. The model parameters, a, b, c, were determined by minimizing the squared fitting error ∑‖p(x(p), y(p); t(i)) - P(θ(i)) · (aR(t(i)) + bR(t(i) - τ) + c)‖(2) with the projection operator P(θ(i)). The model parameters were first initialized based on acquired kV arc images prior to MV beam delivery. This method was implemented on a trilogy linear accelerator consisting of an OBI x-ray imager (operating at 1 Hz) and real-time position monitoring (RPM) system (30 Hz). Arc and static field plans were delivered to a moving phantom programmed with measured lung tumour motion from ten patients. During delivery, the localization method determined the target position and the beam was adjusted in real time via dynamic multileaf collimator (DMLC) adaptation. The beam-target alignment error was quantified by segmenting the beam aperture and a phantom-embedded fiducial marker on MV images and analysing their relative position. With the localization method, the root-mean-squared errors of the ten lung tumour traces ranged from 0.7-1.3 mm and 0.8-1.4 mm during the single arc and five-field static beam delivery, respectively. Without the localization method, these errors ranged from 3.1-7.3 mm. In summary, a general method for real-time target localization using kV imaging and respiratory monitoring has been experimentally investigated for arc and static field delivery. The average beam-target error was 1 mm.
-
NASA Astrophysics Data System (ADS)
Cho, Byungchul; Poulsen, Per; Ruan, Dan; Sawant, Amit; Keall, Paul J.
2012-11-01
The goal of this work was to experimentally quantify the geometric accuracy of a novel real-time 3D target localization method using sequential kV imaging combined with respiratory monitoring for clinically realistic arc and static field treatment delivery and target motion conditions. A general method for real-time target localization using kV imaging and respiratory monitoring was developed. Each dimension of internal target motion T(x, y, z; t) was estimated from the external respiratory signal R(t) through the correlation between R(ti) and the projected marker positions p(xp, yp; ti) on kV images by a state-augmented linear model: T(x, y, z; t) = aR(t) + bR(t - τ) + c. The model parameters, a, b, c, were determined by minimizing the squared fitting error ∑‖p(xp, yp; ti) - P(θi) · (aR(ti) + bR(ti - τ) + c)‖2 with the projection operator P(θi). The model parameters were first initialized based on acquired kV arc images prior to MV beam delivery. This method was implemented on a trilogy linear accelerator consisting of an OBI x-ray imager (operating at 1 Hz) and real-time position monitoring (RPM) system (30 Hz). Arc and static field plans were delivered to a moving phantom programmed with measured lung tumour motion from ten patients. During delivery, the localization method determined the target position and the beam was adjusted in real time via dynamic multileaf collimator (DMLC) adaptation. The beam-target alignment error was quantified by segmenting the beam aperture and a phantom-embedded fiducial marker on MV images and analysing their relative position. With the localization method, the root-mean-squared errors of the ten lung tumour traces ranged from 0.7-1.3 mm and 0.8-1.4 mm during the single arc and five-field static beam delivery, respectively. Without the localization method, these errors ranged from 3.1-7.3 mm. In summary, a general method for real-time target localization using kV imaging and respiratory monitoring has been experimentally investigated for arc and static field delivery. The average beam-target error was 1 mm.
-
Area-to-point regression kriging for pan-sharpening
NASA Astrophysics Data System (ADS)
Wang, Qunming; Shi, Wenzhong; Atkinson, Peter M.
2016-04-01
Pan-sharpening is a technique to combine the fine spatial resolution panchromatic (PAN) band with the coarse spatial resolution multispectral bands of the same satellite to create a fine spatial resolution multispectral image. In this paper, area-to-point regression kriging (ATPRK) is proposed for pan-sharpening. ATPRK considers the PAN band as the covariate. Moreover, ATPRK is extended with a local approach, called adaptive ATPRK (AATPRK), which fits a regression model using a local, non-stationary scheme such that the regression coefficients change across the image. The two geostatistical approaches, ATPRK and AATPRK, were compared to the 13 state-of-the-art pan-sharpening approaches summarized in Vivone et al. (2015) in experiments on three separate datasets. ATPRK and AATPRK produced more accurate pan-sharpened images than the 13 benchmark algorithms in all three experiments. Unlike the benchmark algorithms, the two geostatistical solutions precisely preserved the spectral properties of the original coarse data. Furthermore, ATPRK can be enhanced by a local scheme in AATRPK, in cases where the residuals from a global regression model are such that their spatial character varies locally.
-
Probing the Dusty Stellar Populations of the Local Volume Galaxies with JWST /MIRI
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jones, Olivia C.; Meixner, Margaret; Justtanont, Kay
The Mid-Infrared Instrument (MIRI) for the James Webb Space Telescope ( JWST ) will revolutionize our understanding of infrared stellar populations in the Local Volume. Using the rich Spitzer -IRS spectroscopic data set and spectral classifications from the Surveying the Agents of Galaxy Evolution (SAGE)–Spectroscopic survey of more than 1000 objects in the Magellanic Clouds, the Grid of Red Supergiant and Asymptotic Giant Branch Star Model (grams), and the grid of YSO models by Robitaille et al., we calculate the expected flux densities and colors in the MIRI broadband filters for prominent infrared stellar populations. We use these fluxes tomore » explore the JWST /MIRI colors and magnitudes for composite stellar population studies of Local Volume galaxies. MIRI color classification schemes are presented; these diagrams provide a powerful means of identifying young stellar objects, evolved stars, and extragalactic background galaxies in Local Volume galaxies with a high degree of confidence. Finally, we examine which filter combinations are best for selecting populations of sources based on their JWST colors.« less
-
Fritscher, Karl; Grunerbl, Agnes; Hanni, Markus; Suhm, Norbert; Hengg, Clemens; Schubert, Rainer
2009-10-01
Currently, conventional X-ray and CT images as well as invasive methods performed during the surgical intervention are used to judge the local quality of a fractured proximal femur. However, these approaches are either dependent on the surgeon's experience or cannot assist diagnostic and planning tasks preoperatively. Therefore, in this work a method for the individual analysis of local bone quality in the proximal femur based on model-based analysis of CT- and X-ray images of femur specimen will be proposed. A combined representation of shape and spatial intensity distribution of an object and different statistical approaches for dimensionality reduction are used to create a statistical appearance model in order to assess the local bone quality in CT and X-ray images. The developed algorithms are tested and evaluated on 28 femur specimen. It will be shown that the tools and algorithms presented herein are highly adequate to automatically and objectively predict bone mineral density values as well as a biomechanical parameter of the bone that can be measured intraoperatively.
-
Average structure and local configuration of excess oxygen in UO(2+x).
Wang, Jianwei; Ewing, Rodney C; Becker, Udo
2014-03-19
Determination of the local configuration of interacting defects in a crystalline, periodic solid is problematic because defects typically do not have a long-range periodicity. Uranium dioxide, the primary fuel for fission reactors, exists in hyperstoichiometric form, UO(2+x). Those excess oxygen atoms occur as interstitial defects, and these defects are not random but rather partially ordered. The widely-accepted model to date, the Willis cluster based on neutron diffraction, cannot be reconciled with the first-principles molecular dynamics simulations present here. We demonstrate that the Willis cluster is a fair representation of the numerical ratio of different interstitial O atoms; however, the model does not represent the actual local configuration. The simulations show that the average structure of UO(2+x) involves a combination of defect structures including split di-interstitial, di-interstitial, mono-interstitial, and the Willis cluster, and the latter is a transition state that provides for the fast diffusion of the defect cluster. The results provide new insights in differentiating the average structure from the local configuration of defects in a solid and the transport properties of UO(2+x).
-
Choice vs. voice? PPI policies and the re-positioning of the state in England and Wales.
Hughes, David; Mullen, Caroline; Vincent-Jones, Peter
2009-09-01
CONTEXT AND THESIS: Changing patient and public involvement (PPI) policies in England and Wales are analysed against the background of wider National Health Service (NHS) reforms and regulatory frameworks. We argue that the growing divergence of health policies is accompanied by a re-positioning of the state vis-à-vis PPI, characterized by different mixes of centralized and decentralized regulatory instruments. Analysis of legislation and official documents, and interviews with policy makers. In England, continued hierarchical control is combined with the delegation of responsibilities for the oversight and organization of PPI to external institutions such as the Care Quality Commission and local involvement networks, in support of the government's policy agenda of increasing marketization. In Wales, which has rejected market reforms and economic regulation, decentralization is occurring through the use of mixed regulatory approaches and networks suited to the small-country governance model, and seeks to benefit from the close proximity of central and local actors by creating new forms of engagement while maintaining central steering of service planning. Whereas English PPI policies have emerged in tandem with a pluralistic supply-side market and combine new institutional arrangements for patient 'choice' with other forms of involvement, the Welsh policies focus on 'voice' within a largely publicly-delivered service. While the English reforms draw on theories of economic regulation and the experience of independent regulation in the utilities sector, the Welsh model of local service integration has been more influenced by reforms in local government. Such transfers of governance instruments from other public service sectors to the NHS may be problematic.
-
NASA Astrophysics Data System (ADS)
Behafarid, Farhad; Brasseur, James G.
2017-11-01
Following tablet disintegration, clouds of drug particles 5-200 μm in diameter pass through the intestines where drug molecules are absorbed into the blood. Release rate depends on particle size, drug solubility, local drug concentration and the hydrodynamic environment driven by patterned gut contractions. To analyze the dynamics underlying drug release and absorption, we use a 3D lattice Boltzmann model of the velocity and concentration fields driven by peristaltic contractions in vivo, combined with a mathematical model of dissolution-rate from each drug particle transported through the grid. The model is empirically extended for hydrodynamic enhancements to release rate by local convection and shear-rate, and incorporates heterogeneity in bulk concentration. Drug dosage and solubility are systematically varied along with peristaltic wave speed and volume. We predict large hydrodynamic enhancements (35-65%) from local shear-rate with minimal enhancement from convection. With high permeability boundary conditions, a quasi-equilibrium balance between release and absorption is established with volume and wave-speed dependent transport time scale, after an initial transient and before a final period of dissolution/absorption. Supported by FDA.
-
NASA Astrophysics Data System (ADS)
Hansen, A. L.; Donnelly, C.; Refsgaard, J. C.; Karlsson, I. B.
2018-01-01
This paper describes a modeling approach proposed to simulate the impact of local-scale, spatially targeted N-mitigation measures for the Baltic Sea Basin. Spatially targeted N-regulations aim at exploiting the considerable spatial differences in the natural N-reduction taking place in groundwater and surface water. While such measures can be simulated using local-scale physically-based catchment models, use of such detailed models for the 1.8 million km2 Baltic Sea basin is not feasible due to constraints on input data and computing power. Large-scale models that are able to simulate the Baltic Sea basin, on the other hand, do not have adequate spatial resolution to simulate some of the field-scale measures. Our methodology combines knowledge and results from two local-scale physically-based MIKE SHE catchment models, the large-scale and more conceptual E-HYPE model, and auxiliary data in order to enable E-HYPE to simulate how spatially targeted regulation of agricultural practices may affect N-loads to the Baltic Sea. We conclude that the use of E-HYPE with this upscaling methodology enables the simulation of the impact on N-loads of applying a spatially targeted regulation at the Baltic Sea basin scale to the correct order-of-magnitude. The E-HYPE model together with the upscaling methodology therefore provides a sound basis for large-scale policy analysis; however, we do not expect it to be sufficiently accurate to be useful for the detailed design of local-scale measures.
-
NASA Astrophysics Data System (ADS)
Sun, Alexander Y.; Morris, Alan P.; Mohanty, Sitakanta
2009-07-01
Estimated parameter distributions in groundwater models may contain significant uncertainties because of data insufficiency. Therefore, adaptive uncertainty reduction strategies are needed to continuously improve model accuracy by fusing new observations. In recent years, various ensemble Kalman filters have been introduced as viable tools for updating high-dimensional model parameters. However, their usefulness is largely limited by the inherent assumption of Gaussian error statistics. Hydraulic conductivity distributions in alluvial aquifers, for example, are usually non-Gaussian as a result of complex depositional and diagenetic processes. In this study, we combine an ensemble Kalman filter with grid-based localization and a Gaussian mixture model (GMM) clustering techniques for updating high-dimensional, multimodal parameter distributions via dynamic data assimilation. We introduce innovative strategies (e.g., block updating and dimension reduction) to effectively reduce the computational costs associated with these modified ensemble Kalman filter schemes. The developed data assimilation schemes are demonstrated numerically for identifying the multimodal heterogeneous hydraulic conductivity distributions in a binary facies alluvial aquifer. Our results show that localization and GMM clustering are very promising techniques for assimilating high-dimensional, multimodal parameter distributions, and they outperform the corresponding global ensemble Kalman filter analysis scheme in all scenarios considered.
-
Global D-brane models with stabilised moduli and light axions
NASA Astrophysics Data System (ADS)
Cicoli, Michele
2014-03-01
We review recent attempts to try to combine global issues of string compactifications, like moduli stabilisation, with local issues, like semi-realistic D-brane constructions. We list the main problems encountered, and outline a possible solution which allows globally consistent embeddings of chiral models. We also argue that this stabilisation mechanism leads to an axiverse. We finally illustrate our general claims in a concrete example where the Calabi-Yau manifold is explicitly described by toric geometry.
-
NASA Astrophysics Data System (ADS)
Naidoo, L.; Cho, M. A.; Mathieu, R.; Asner, G.
2012-04-01
The accurate classification and mapping of individual trees at species level in the savanna ecosystem can provide numerous benefits for the managerial authorities. Such benefits include the mapping of economically useful tree species, which are a key source of food production and fuel wood for the local communities, and of problematic alien invasive and bush encroaching species, which can threaten the integrity of the environment and livelihoods of the local communities. Species level mapping is particularly challenging in African savannas which are complex, heterogeneous, and open environments with high intra-species spectral variability due to differences in geology, topography, rainfall, herbivory and human impacts within relatively short distances. Savanna vegetation are also highly irregular in canopy and crown shape, height and other structural dimensions with a combination of open grassland patches and dense woody thicket - a stark contrast to the more homogeneous forest vegetation. This study classified eight common savanna tree species in the Greater Kruger National Park region, South Africa, using a combination of hyperspectral and Light Detection and Ranging (LiDAR)-derived structural parameters, in the form of seven predictor datasets, in an automated Random Forest modelling approach. The most important predictors, which were found to play an important role in the different classification models and contributed to the success of the hybrid dataset model when combined, were species tree height; NDVI; the chlorophyll b wavelength (466 nm) and a selection of raw, continuum removed and Spectral Angle Mapper (SAM) bands. It was also concluded that the hybrid predictor dataset Random Forest model yielded the highest classification accuracy and prediction success for the eight savanna tree species with an overall classification accuracy of 87.68% and KHAT value of 0.843.
-
Moulatlet, Gabriel Massaine; Zuquim, Gabriela; Figueiredo, Fernando Oliveira Gouvêa; Lehtonen, Samuli; Emilio, Thaise; Ruokolainen, Kalle; Tuomisto, Hanna
2017-10-01
Amazonia combines semi-continental size with difficult access, so both current ranges of species and their ability to cope with environmental change have to be inferred from sparse field data. Although efficient techniques for modeling species distributions on the basis of a small number of species occurrences exist, their success depends on the availability of relevant environmental data layers. Soil data are important in this context, because soil properties have been found to determine plant occurrence patterns in Amazonian lowlands at all spatial scales. Here we evaluate the potential for this purpose of three digital soil maps that are freely available online: SOTERLAC, HWSD, and SoilGrids. We first tested how well they reflect local soil cation concentration as documented with 1,500 widely distributed soil samples. We found that measured soil cation concentration differed by up to two orders of magnitude between sites mapped into the same soil class. The best map-based predictor of local soil cation concentration was obtained with a regression model combining soil classes from HWSD with cation exchange capacity (CEC) from SoilGrids. Next, we evaluated to what degree the known edaphic affinities of thirteen plant species (as documented with field data from 1,200 of the soil sample sites) can be inferred from the soil maps. The species segregated clearly along the soil cation concentration gradient in the field, but only partially along the model-estimated cation concentration gradient, and hardly at all along the mapped CEC gradient. The main problems reducing the predictive ability of the soil maps were insufficient spatial resolution and/or georeferencing errors combined with thematic inaccuracy and absence of the most relevant edaphic variables. Addressing these problems would provide better models of the edaphic environment for ecological studies in Amazonia.
-
Blyton, Michaela D J; Banks, Sam C; Peakall, Rod; Lindenmayer, David B
2012-02-01
The formal testing of mating system theories with empirical data is important for evaluating the relative importance of different processes in shaping mating systems in wild populations. Here, we present a generally applicable probability modelling framework to test the role of local mate availability in determining a population's level of genetic monogamy. We provide a significance test for detecting departures in observed mating patterns from model expectations based on mate availability alone, allowing the presence and direction of behavioural effects to be inferred. The assessment of mate availability can be flexible and in this study it was based on population density, sex ratio and spatial arrangement. This approach provides a useful tool for (1) isolating the effect of mate availability in variable mating systems and (2) in combination with genetic parentage analyses, gaining insights into the nature of mating behaviours in elusive species. To illustrate this modelling approach, we have applied it to investigate the variable mating system of the mountain brushtail possum (Trichosurus cunninghami) and compared the model expectations with the outcomes of genetic parentage analysis over an 18-year study. The observed level of monogamy was higher than predicted under the model. Thus, behavioural traits, such as mate guarding or selective mate choice, may increase the population level of monogamy. We show that combining genetic parentage data with probability modelling can facilitate an improved understanding of the complex interactions between behavioural adaptations and demographic dynamics in driving mating system variation. © 2011 Blackwell Publishing Ltd.
-
Mapping Dependence Between Extreme Rainfall and Storm Surge
NASA Astrophysics Data System (ADS)
Wu, Wenyan; McInnes, Kathleen; O'Grady, Julian; Hoeke, Ron; Leonard, Michael; Westra, Seth
2018-04-01
Dependence between extreme storm surge and rainfall can have significant implications for flood risk in coastal and estuarine regions. To supplement limited observational records, we use reanalysis surge data from a hydrodynamic model as the basis for dependence mapping, providing information at a resolution of approximately 30 km along the Australian coastline. We evaluated this approach by comparing the dependence estimates from modeled surge to that calculated using historical surge records from 79 tide gauges around Australia. The results show reasonable agreement between the two sets of dependence values, with the exception of lower seasonal variation in the modeled dependence values compared to the observed data, especially at locations where there are multiple processes driving extreme storm surge. This is due to the combined impact of local bathymetry as well as the resolution of the hydrodynamic model and its meteorological inputs. Meteorological drivers were also investigated for different combinations of extreme rainfall and surge—namely rain-only, surge-only, and coincident extremes—finding that different synoptic patterns are responsible for each combination. The ability to supplement observational records with high-resolution modeled surge data enables a much more precise quantification of dependence along the coastline, strengthening the physical basis for assessments of flood risk in coastal regions.
-
Zhang, Yu; Zhu, Xiaofei; Liu, Ri; Wang, Xianglian; Sun, Gaofeng; Song, Jiaqi; Lu, Jianping; Zhang, Huojun
2018-04-01
To identify whether the combination of pre-treatment radiological and clinical factors can predict the overall survival (OS) in patients with locally advanced pancreatic cancer (LAPC) treated with stereotactic body radiation and sequential S-1 (a prodrug of 5-FU combined with two modulators) therapy with improved accuracy compared with that of established clinical and radiologic risk models. Patients admitted with LAPC underwent diffusion weighted imaging (DWI) scan at 3.0-T (b = 600 s/mm 2 ). The mean signal intensity (SI b = 600) of region-of-interest (ROI) was measured. The Log-rank test was done for tumor location, biliary stent, S-1, and other treatments and the Cox regression analysis was done to identify independent prognostic factors for OS. Prediction error curves (PEC) were used to assess potential errors in prediction of survival. The accuracy of prediction was evaluated by Integrated Brier Score (IBS) and C index. 41 patients were included in this study. The median OS was 11.7 months (2.8-23.23 months). The 1-year OS was 46%. Multivariate analysis showed that pre-treatment SI b = 600 value and administration of S-1 were independent predictors for OS. The performance of pre-treatment SI b = 600 and S-1 treatment in combination was better than that of SI b = 600 or S-1 treatment alone. The combination of pre-treatment SI b = 600 and S-1 treatment could predict the OS in patients with LAPC undergoing SBRT and sequential S-1 therapy with improved accuracy compared with that of established clinical and radiologic risk models. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
-
Chebouba, Lokmane; Boughaci, Dalila; Guziolowski, Carito
2018-06-04
The use of data issued from high throughput technologies in drug target problems is widely widespread during the last decades. This study proposes a meta-heuristic framework using stochastic local search (SLS) combined with random forest (RF) where the aim is to specify the most important genes and proteins leading to the best classification of Acute Myeloid Leukemia (AML) patients. First we use a stochastic local search meta-heuristic as a feature selection technique to select the most significant proteins to be used in the classification task step. Then we apply RF to classify new patients into their corresponding classes. The evaluation technique is to run the RF classifier on the training data to get a model. Then, we apply this model on the test data to find the appropriate class. We use as metrics the balanced accuracy (BAC) and the area under the receiver operating characteristic curve (AUROC) to measure the performance of our model. The proposed method is evaluated on the dataset issued from DREAM 9 challenge. The comparison is done with a pure random forest (without feature selection), and with the two best ranked results of the DREAM 9 challenge. We used three types of data: only clinical data, only proteomics data, and finally clinical and proteomics data combined. The numerical results show that the highest scores are obtained when using clinical data alone, and the lowest is obtained when using proteomics data alone. Further, our method succeeds in finding promising results compared to the methods presented in the DREAM challenge.
-
Approximate Dynamic Programming: Combining Regional and Local State Following Approximations.
Deptula, Patryk; Rosenfeld, Joel A; Kamalapurkar, Rushikesh; Dixon, Warren E
2018-06-01
An infinite-horizon optimal regulation problem for a control-affine deterministic system is solved online using a local state following (StaF) kernel and a regional model-based reinforcement learning (R-MBRL) method to approximate the value function. Unlike traditional methods such as R-MBRL that aim to approximate the value function over a large compact set, the StaF kernel approach aims to approximate the value function in a local neighborhood of the state that travels within a compact set. In this paper, the value function is approximated using a state-dependent convex combination of the StaF-based and the R-MBRL-based approximations. As the state enters a neighborhood containing the origin, the value function transitions from being approximated by the StaF approach to the R-MBRL approach. Semiglobal uniformly ultimately bounded (SGUUB) convergence of the system states to the origin is established using a Lyapunov-based analysis. Simulation results are provided for two, three, six, and ten-state dynamical systems to demonstrate the scalability and performance of the developed method.
-
Deciphering the Local Interstellar Spectra of Primary Cosmic-Ray Species with HELMOD
NASA Astrophysics Data System (ADS)
Boschini, M. J.; Della Torre, S.; Gervasi, M.; Grandi, D.; Jóhannesson, G.; La Vacca, G.; Masi, N.; Moskalenko, I. V.; Pensotti, S.; Porter, T. A.; Quadrani, L.; Rancoita, P. G.; Rozza, D.; Tacconi, M.
2018-05-01
Local interstellar spectra (LIS) of primary cosmic ray (CR) nuclei, such as helium, oxygen, and mostly primary carbon are derived for the rigidity range from 10 MV to ∼200 TV using the most recent experimental results combined with the state-of-the-art models for CR propagation in the Galaxy and in the heliosphere. Two propagation packages, GALPROP and HELMOD, are combined into a single framework that is used to reproduce direct measurements of CR species at different modulation levels, and at both polarities of the solar magnetic field. The developed iterative maximum-likelihood method uses GALPROP-predicted LIS as input to HELMOD, which provides the modulated spectra for specific time periods of the selected experiments for model–data comparison. The interstellar and heliospheric propagation parameters derived in this study are consistent with our prior analyses using the same methodology for propagation of CR protons, helium, antiprotons, and electrons. The resulting LIS accommodate a variety of measurements made in the local interstellar space (Voyager 1) and deep inside the heliosphere at low (ACE/CRIS, HEAO-3) and high energies (PAMELA, AMS-02).
-
NASA Astrophysics Data System (ADS)
Sherajul Islam, Md.; Anindya, Khalid N.; Bhuiyan, Ashraful G.; Tanaka, Satoru; Makino, Takayuki; Hashimoto, Akihiro
2018-02-01
We report the details of the effects of the 10B isotope and those of B and N vacancies combined with the isotope on the phonon modes of two-dimensional hexagonal boron nitride (h-BN). The phonon density of states and localization problems are solved using the forced vibrational method, which is suitable for an intricate and disordered system. We observe an upward shift of Raman-active E2g-mode optical phonons (32 cm-1) for a 100% 10B isotope, which matches well with the experiment and simple harmonic oscillator model. However, a downward shift of E2g-mode phonons is observed for B or N vacancies and the combination of the isotope and vacancy-type disordered BN. Strong localized eigenmodes are found for all types of defects, and a typical localization length is on the order of ˜7 nm for naturally occurring BN samples. These results are very important for understanding the heat dissipation and electron transport properties of BN-based nanoelectronics.
-
Sun, Deshun; Liu, Fei
2018-06-01
In this paper, a hepatitis B virus (HBV) model with an incubation period and delayed state and control variables is firstly proposed. Furthermore, the combination treatment is adopted to have a longer-lasting effect than mono-therapy. The equilibrium points and basic reproduction number are calculated, and then the local stability is analyzed on this model. We then present optimal control strategies based on the Pontryagin's minimum principle with an objective function not only to reduce the levels of exposed cells, infected cells and free viruses nearly to zero at the end of therapy, but also to minimize the drug side-effect and the cost of treatment. What's more, we develop a numerical simulation algorithm for solving our HBV model based on the combination of forward and backward difference approximations. The state dynamics of uninfected cells, exposed cells, infected cells, free viruses, CTL and ALT are simulated with or without optimal control, which show that HBV is reduced nearly to zero based on the time-varying optimal control strategies whereas the disease would break out without control. At last, by the simulations, we prove that strategy A is the best among the three kinds of strategies we adopt and further comparisons have been done between model (1) and model (2).
-
Elissen, Arianne M J; Struijs, Jeroen N; Baan, Caroline A; Ruwaard, Dirk
2015-05-01
To support providers and commissioners in accurately assessing their local populations' health needs, this study produces an overview of Dutch predictive risk models for health care, focusing specifically on the type, combination and relevance of included determinants for achieving the Triple Aim (improved health, better care experience, and lower costs). We conducted a mixed-methods study combining document analyses, interviews and a Delphi study. Predictive risk models were identified based on a web search and expert input. Participating in the study were Dutch experts in predictive risk modelling (interviews; n=11) and experts in healthcare delivery, insurance and/or funding methodology (Delphi panel; n=15). Ten predictive risk models were analysed, comprising 17 unique determinants. Twelve were considered relevant by experts for estimating community health needs. Although some compositional similarities were identified between models, the combination and operationalisation of determinants varied considerably. Existing predictive risk models provide a good starting point, but optimally balancing resources and targeting interventions on the community level will likely require a more holistic approach to health needs assessment. Development of additional determinants, such as measures of people's lifestyle and social network, may require policies pushing the integration of routine data from different (healthcare) sources. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
-
Lam, King-Yeung; Lou, Yuan
2014-02-01
We consider a mathematical model of two competing species for the evolution of conditional dispersal in a spatially varying, but temporally constant environment. Two species are different only in their dispersal strategies, which are a combination of random dispersal and biased movement upward along the resource gradient. In the absence of biased movement or advection, Hastings showed that the mutant can invade when rare if and only if it has smaller random dispersal rate than the resident. When there is a small amount of biased movement or advection, we show that there is a positive random dispersal rate that is both locally evolutionarily stable and convergent stable. Our analysis of the model suggests that a balanced combination of random and biased movement might be a better habitat selection strategy for populations.
-
Ultrasound for Drug and Gene Delivery to the Brain
Hynynen, Kullervo
2008-01-01
Noninvasive, transient, and local image-guided blood-brain barrier disruption (BBBD) has been demonstrated with focused ultrasound exposure in animal models. Most studies have combined low pressure amplitude and low time average acoustic power burst sonications with intra-vascular injection of pre-formed micro-bubbles to produce BBBD without damage to the neurons. The BBB has been shown to be healed within a few hours after the exposure. The combination of focused ultrasound beams with MR image guidance allows precise anatomical targeting as demonstrated by the delivery of several marker molecules in different animal models. This method may in the future have a significant impact on the diagnosis and treatment of central nervous system (CNS) disorders. Most notably, the delivery of the chemotherapy agents liposomal Doxorubicin and Herceptin has been shown in a rat model. PMID:18486271
-
Atmospheric deposition maps for the Rocky Mountains
Nanus, L.; Campbell, D.H.; Ingersoll, G.P.; Clow, D.W.; Mast, M.A.
2003-01-01
Variability in atmospheric deposition across the Rocky Mountains is influenced by elevation, slope, aspect, and precipitation amount and by regional and local sources of air pollution. To improve estimates of deposition in mountainous regions, maps of average annual atmospheric deposition loadings of nitrate, sulfate, and acidity were developed for the Rocky Mountains by using spatial statistics. A parameter-elevation regressions on independent slopes model (PRISM) was incorporated to account for variations in precipitation amount over mountainous regions. Chemical data were obtained from the National Atmospheric Deposition Program/National Trends Network and from annual snowpack surveys conducted by the US Geological Survey and National Park Service, in cooperation with other Federal, State and local agencies. Surface concentration maps were created by ordinary kriging in a geographic information system, using a local trend and mathematical model to estimate the spatial variance. Atmospheric-deposition maps were constructed at 1-km resolution by multiplying surface concentrations from the kriged grid and estimates of precipitation amount from the PRISM model. Maps indicate an increasing spatial trend in concentration and deposition of the modeled constituents, particularly nitrate and sulfate, from north to south throughout the Rocky Mountains and identify hot-spots of atmospheric deposition that result from combined local and regional sources of air pollution. Highest nitrate (2.5-3.0kg/ha N) and sulfate (10.0-12.0kg/ha SO4) deposition is found in northern Colorado.
-
Local and Regional Determinants of an Uncommon Functional Group in Freshwater Lakes and Ponds
McCann, Michael James
2015-01-01
A combination of local and regional factors and stochastic forces is expected to determine the occurrence of species and the structure of communities. However, in most cases, our understanding is incomplete, with large amounts of unexplained variation. Using functional groups rather than individual species may help explain the relationship between community composition and conditions. In this study, I used survey data from freshwater lakes and ponds to understand factors that determine the presence of the floating plant functional group in the northeast United States. Of the 176 water bodies surveyed, 104 (59.1%) did not contain any floating plant species. The occurrence of this functional group was largely determined by local abiotic conditions, which were spatially autocorrelated across the region. A model predicting the presence of the floating plant functional group performed similarly to the best species-specific models. Using a permutation test, I also found that the observed prevalence of floating plants is no different than expected by random assembly from a species pool of its size. These results suggest that the size of the species pool interacts with local conditions in determining the presence of a functional group. Nevertheless, a large amount of unexplained variation remains, attributable to either stochastic species occurrence or incomplete predictive models. The simple permutation approach in this study can be extended to test alternative models of community assembly. PMID:26121636
-
Fault Gauge Numerical Simulation : Dynamic Rupture Propagation and Local Energy Partitioning
NASA Astrophysics Data System (ADS)
Mollon, G.
2017-12-01
In this communication, we present dynamic simulations of the local (centimetric) behaviour of a fault filled with a granular gauge submitted to dynamic rupture. The numerical tool (Fig. 1) combines classical Discrete Element Modelling (albeit with the ability to deal with arbitrary grain shapes) for the simualtion of the gauge, and continuous modelling for the simulation of the acoustic waves emission and propagation. In a first part, the model is applied to the simulation of steady-state shearing of the fault under remote displacement boudary conditions, in order to observe the shear accomodation at the interface (R1 cracks, localization, wear, etc.). It also makes it possible to fit to desired values the Rate and State Friction properties of the granular gauge by adapting the contact laws between grains. Such simulations provide quantitative insight in the steady-state energy partitionning between fracture, friction and acoustic emissions as a function of the shear rate. In a second part, the model is submitted to dynamic rupture. For that purpose, the fault is elastically preloaded just below rupture, and a displacement pulse is applied at one end of the sample (and on only one side of the fault). This allows to observe the propagation of the instability along the fault and the interplay between this propagation and the local granular phenomena. Energy partitionning is then observed both in space and time.
-
ICF target 2D modeling using Monte Carlo SNB electron thermal transport in DRACO
NASA Astrophysics Data System (ADS)
Chenhall, Jeffrey; Cao, Duc; Moses, Gregory
2016-10-01
The iSNB (implicit Schurtz Nicolai Busquet multigroup diffusion electron thermal transport method is adapted into a Monte Carlo (MC) transport method to better model angular and long mean free path non-local effects. The MC model was first implemented in the 1D LILAC code to verify consistency with the iSNB model. Implementation of the MC SNB model in the 2D DRACO code enables higher fidelity non-local thermal transport modeling in 2D implosions such as polar drive experiments on NIF. The final step is to optimize the MC model by hybridizing it with a MC version of the iSNB diffusion method. The hybrid method will combine the efficiency of a diffusion method in intermediate mean free path regions with the accuracy of a transport method in long mean free path regions allowing for improved computational efficiency while maintaining accuracy. Work to date on the method will be presented. This work was supported by Sandia National Laboratories and the Univ. of Rochester Laboratory for Laser Energetics.
-
Progress in building a cognitive vision system
NASA Astrophysics Data System (ADS)
Benjamin, D. Paul; Lyons, Damian; Yue, Hong
2016-05-01
We are building a cognitive vision system for mobile robots that works in a manner similar to the human vision system, using saccadic, vergence and pursuit movements to extract information from visual input. At each fixation, the system builds a 3D model of a small region, combining information about distance, shape, texture and motion to create a local dynamic spatial model. These local 3D models are composed to create an overall 3D model of the robot and its environment. This approach turns the computer vision problem into a search problem whose goal is the acquisition of sufficient spatial understanding for the robot to succeed at its tasks. The research hypothesis of this work is that the movements of the robot's cameras are only those that are necessary to build a sufficiently accurate world model for the robot's current goals. For example, if the goal is to navigate through a room, the model needs to contain any obstacles that would be encountered, giving their approximate positions and sizes. Other information does not need to be rendered into the virtual world, so this approach trades model accuracy for speed.
-
Optimal frame-by-frame result combination strategy for OCR in video stream
NASA Astrophysics Data System (ADS)
Bulatov, Konstantin; Lynchenko, Aleksander; Krivtsov, Valeriy
2018-04-01
This paper describes the problem of combining classification results of multiple observations of one object. This task can be regarded as a particular case of a decision-making using a combination of experts votes with calculated weights. The accuracy of various methods of combining the classification results depending on different models of input data is investigated on the example of frame-by-frame character recognition in a video stream. Experimentally it is shown that the strategy of choosing a single most competent expert in case of input data without irrelevant observations has an advantage (in this case irrelevant means with character localization and segmentation errors). At the same time this work demonstrates the advantage of combining several most competent experts according to multiplication rule or voting if irrelevant samples are present in the input data.
-
Procedures for adjusting regional regression models of urban-runoff quality using local data
Hoos, A.B.; Sisolak, J.K.
1993-01-01
Statistical operations termed model-adjustment procedures (MAP?s) can be used to incorporate local data into existing regression models to improve the prediction of urban-runoff quality. Each MAP is a form of regression analysis in which the local data base is used as a calibration data set. Regression coefficients are determined from the local data base, and the resulting `adjusted? regression models can then be used to predict storm-runoff quality at unmonitored sites. The response variable in the regression analyses is the observed load or mean concentration of a constituent in storm runoff for a single storm. The set of explanatory variables used in the regression analyses is different for each MAP, but always includes the predicted value of load or mean concentration from a regional regression model. The four MAP?s examined in this study were: single-factor regression against the regional model prediction, P, (termed MAP-lF-P), regression against P,, (termed MAP-R-P), regression against P, and additional local variables (termed MAP-R-P+nV), and a weighted combination of P, and a local-regression prediction (termed MAP-W). The procedures were tested by means of split-sample analysis, using data from three cities included in the Nationwide Urban Runoff Program: Denver, Colorado; Bellevue, Washington; and Knoxville, Tennessee. The MAP that provided the greatest predictive accuracy for the verification data set differed among the three test data bases and among model types (MAP-W for Denver and Knoxville, MAP-lF-P and MAP-R-P for Bellevue load models, and MAP-R-P+nV for Bellevue concentration models) and, in many cases, was not clearly indicated by the values of standard error of estimate for the calibration data set. A scheme to guide MAP selection, based on exploratory data analysis of the calibration data set, is presented and tested. The MAP?s were tested for sensitivity to the size of a calibration data set. As expected, predictive accuracy of all MAP?s for the verification data set decreased as the calibration data-set size decreased, but predictive accuracy was not as sensitive for the MAP?s as it was for the local regression models.
-
NASA Astrophysics Data System (ADS)
Choudhury, Anustup; Farrell, Suzanne; Atkins, Robin; Daly, Scott
2017-09-01
We present an approach to predict overall HDR display quality as a function of key HDR display parameters. We first performed subjective experiments on a high quality HDR display that explored five key HDR display parameters: maximum luminance, minimum luminance, color gamut, bit-depth and local contrast. Subjects rated overall quality for different combinations of these display parameters. We explored two models | a physical model solely based on physically measured display characteristics and a perceptual model that transforms physical parameters using human vision system models. For the perceptual model, we use a family of metrics based on a recently published color volume model (ICT-CP), which consists of the PQ luminance non-linearity (ST2084) and LMS-based opponent color, as well as an estimate of the display point spread function. To predict overall visual quality, we apply linear regression and machine learning techniques such as Multilayer Perceptron, RBF and SVM networks. We use RMSE and Pearson/Spearman correlation coefficients to quantify performance. We found that the perceptual model is better at predicting subjective quality than the physical model and that SVM is better at prediction than linear regression. The significance and contribution of each display parameter was investigated. In addition, we found that combined parameters such as contrast do not improve prediction. Traditional perceptual models were also evaluated and we found that models based on the PQ non-linearity performed better.
-
NREL's EVI-Pro Lite Tool Paves the Way for Future Electric Vehicle
Electric Vehicle Infrastructure Planning NREL's EVI-Pro Lite Tool Paves the Way for Future Electric Vehicle electric vehicle charging station To assist state and local governments anticipating this type of growth in simplified version of the Electric Vehicle Infrastructure Projection Tool (EVI-Pro) model. Combining a sleek
-
NASA Astrophysics Data System (ADS)
Shi, J.; Donahue, N. M.; Klima, K.; Blackhurst, M.
2016-12-01
In order to tradeoff global impacts of greenhouse gases with highly local impacts of conventional air pollution, researchers require a method to compare global and regional impacts. Unfortunately, we are not aware of a method that allows these to be compared, "apples-to-apples". In this research we propose a three-step model to compare possible city-wide actions to reduce greenhouse gases and conventional air pollutants. We focus on Pittsburgh, PA, a city with consistently poor air quality that is interested in reducing both greenhouse gases and conventional air pollutants. First, we use the 2013 Pittsburgh Greenhouse Gas Inventory to update the Blackhurst et al. model and conduct a greenhouse gas abatement potentials and implementation costs of proposed greenhouse gas reduction efforts. Second, we use field tests for PM2.5, NOx, SOx, organic carbon (OC) and elemental carbon (EC) data to inform a Land-use Regression Model for local air pollution at a 100m x 100m spatial level, which combined with a social cost of air pollution model (EASIUR) allows us to calculate economic social damages. Third, we combine these two models into a three-dimensional greenhouse gas cost abatement curve to understand the implementation costs and social benefits in terms of air quality improvement and greenhouse gas abatement for each potential intervention. We anticipated such results could provide policy-maker insights in green city development.
-
Semantic wireless localization of WiFi terminals in smart buildings
NASA Astrophysics Data System (ADS)
Ahmadi, H.; Polo, A.; Moriyama, T.; Salucci, M.; Viani, F.
2016-06-01
The wireless localization of mobile terminals in indoor scenarios by means of a semantic interpretation of the environment is addressed in this work. A training-less approach based on the real-time calibration of a simple path loss model is proposed which combines (i) the received signal strength information measured by the wireless terminal and (ii) the topological features of the localization domain. A customized evolutionary optimization technique has been designed to estimate the optimal target position that fits the complex wireless indoor propagation and the semantic target-environment relation, as well. The proposed approach is experimentally validated in a real building area where the available WiFi network is opportunistically exploited for data collection. The presented results point out a reduction of the localization error obtained with the introduction of a very simple semantic interpretation of the considered scenario.
-
NASA Astrophysics Data System (ADS)
Liu, Yong-Kui; Li, Zhi; Chen, Xiao-Jie; Wang, Long
2009-08-01
We investigate the evolutionary Prisoner's Dilemma and the Snowdrift Game on small-world networks in a realistic social context where individuals consider their local contributions to their group and update their strategies by self-questioning. An individual with introspection can determine whether its current strategy is superior by playing a virtual round of the game and its local contribution is defined as the sum of all the payoffs its neighbors collect against it. In our model, the performance of an individual is determined by both its payoff and local contribution through a linear combination. We demonstrate that the present mechanism can produce very robust cooperative behavior in both games. Furthermore, we provide theoretical analysis based on mean-field approximation, and find that the analytical predictions are qualitatively consistent with the simulation results.
-
Gurney, Georgina G.; Melbourne-Thomas, Jessica; Geronimo, Rollan C.; Aliño, Perry M.; Johnson, Craig R.
2013-01-01
Climate change has emerged as a principal threat to coral reefs, and is expected to exacerbate coral reef degradation caused by more localised stressors. Management of local stressors is widely advocated to bolster coral reef resilience, but the extent to which management of local stressors might affect future trajectories of reef state remains unclear. This is in part because of limited understanding of the cumulative impact of multiple stressors. Models are ideal tools to aid understanding of future reef state under alternative management and climatic scenarios, but to date few have been sufficiently developed to be useful as decision support tools for local management of coral reefs subject to multiple stressors. We used a simulation model of coral reefs to investigate the extent to which the management of local stressors (namely poor water quality and fishing) might influence future reef state under varying climatic scenarios relating to coral bleaching. We parameterised the model for Bolinao, the Philippines, and explored how simulation modelling can be used to provide decision support for local management. We found that management of water quality, and to a lesser extent fishing, can have a significant impact on future reef state, including coral recovery following bleaching-induced mortality. The stressors we examined interacted antagonistically to affect reef state, highlighting the importance of considering the combined impact of multiple stressors rather than considering them individually. Further, by providing explicit guidance for management of Bolinao's reef system, such as which course of management action will most likely to be effective over what time scales and at which sites, we demonstrated the utility of simulation models for supporting management. Aside from providing explicit guidance for management of Bolinao's reef system, our study offers insights which could inform reef management more broadly, as well as general understanding of reef systems. PMID:24260347
-
Gurney, Georgina G; Melbourne-Thomas, Jessica; Geronimo, Rollan C; Aliño, Perry M; Johnson, Craig R
2013-01-01
Climate change has emerged as a principal threat to coral reefs, and is expected to exacerbate coral reef degradation caused by more localised stressors. Management of local stressors is widely advocated to bolster coral reef resilience, but the extent to which management of local stressors might affect future trajectories of reef state remains unclear. This is in part because of limited understanding of the cumulative impact of multiple stressors. Models are ideal tools to aid understanding of future reef state under alternative management and climatic scenarios, but to date few have been sufficiently developed to be useful as decision support tools for local management of coral reefs subject to multiple stressors. We used a simulation model of coral reefs to investigate the extent to which the management of local stressors (namely poor water quality and fishing) might influence future reef state under varying climatic scenarios relating to coral bleaching. We parameterised the model for Bolinao, the Philippines, and explored how simulation modelling can be used to provide decision support for local management. We found that management of water quality, and to a lesser extent fishing, can have a significant impact on future reef state, including coral recovery following bleaching-induced mortality. The stressors we examined interacted antagonistically to affect reef state, highlighting the importance of considering the combined impact of multiple stressors rather than considering them individually. Further, by providing explicit guidance for management of Bolinao's reef system, such as which course of management action will most likely to be effective over what time scales and at which sites, we demonstrated the utility of simulation models for supporting management. Aside from providing explicit guidance for management of Bolinao's reef system, our study offers insights which could inform reef management more broadly, as well as general understanding of reef systems.
-
NASA Astrophysics Data System (ADS)
Karl, Thomas R.; Wang, Wei-Chyung; Schlesinger, Michael E.; Knight, Richard W.; Portman, David
1990-10-01
Important surface observations such as the daily maximum and minimum temperature, daily precipitation, and cloud ceilings often have localized characteristics that are difficult to reproduce with the current resolution and the physical parameterizations in state-of-the-art General Circulation climate Models (GCMs). Many of the difficulties can be partially attributed to mismatches in scale, local topography. regional geography and boundary conditions between models and surface-based observations. Here, we present a method, called climatological projection by model statistics (CPMS), to relate GCM grid-point flee-atmosphere statistics, the predictors, to these important local surface observations. The method can be viewed as a generalization of the model output statistics (MOS) and perfect prog (PP) procedures used in numerical weather prediction (NWP) models. It consists of the application of three statistical methods: 1) principle component analysis (FICA), 2) canonical correlation, and 3) inflated regression analysis. The PCA reduces the redundancy of the predictors The canonical correlation is used to develop simultaneous relationships between linear combinations of the predictors, the canonical variables, and the surface-based observations. Finally, inflated regression is used to relate the important canonical variables to each of the surface-based observed variables.We demonstrate that even an early version of the Oregon State University two-level atmospheric GCM (with prescribed sea surface temperature) produces free-atmosphere statistics than can, when standardized using the model's internal means and variances (the MOS-like version of CPMS), closely approximate the observed local climate. When the model data are standardized by the observed free-atmosphere means and variances (the PP version of CPMS), however, the model does not reproduce the observed surface climate as well. Our results indicate that in the MOS-like version of CPMS the differences between the output of a ten-year GCM control run and the surface-based observations are often smaller than the differences between the observations of two ten-year periods. Such positive results suggest that GCMs may already contain important climatological information that can be used to infer the local climate.
-
Condensation Front Migration in a Protoplanetary Nebula
NASA Technical Reports Server (NTRS)
Davis, Sanford S.
2004-01-01
Condensation front dynamics are investigated in the mid-solar nebula region. A quasi-steady model of the evolving nebula is combined with equilibrium vapor pressure curves to determine evolutionary condensation fronts for selected species. These fronts are found to migrate inwards from the far-nebula to final positions during a period of 10(exp 7) years. The physical process governing this movement is a combination of local viscous heating and luminescent heating from the central star. Two luminescent heating models are used and their effects on the ultimate radial position of the condensation front are discussed. At first the fronts move much faster than the nebular accretion velocity, but after a time the accreting gas and dust overtakes the slowing condensation front.
-
Modelling daily PM2.5 concentrations at high spatio-temporal resolution across Switzerland.
de Hoogh, Kees; Héritier, Harris; Stafoggia, Massimo; Künzli, Nino; Kloog, Itai
2018-02-01
Spatiotemporal resolved models were developed predicting daily fine particulate matter (PM 2.5 ) concentrations across Switzerland from 2003 to 2013. Relatively sparse PM 2.5 monitoring data was supplemented by imputing PM 2.5 concentrations at PM 10 sites, using PM 2.5 /PM 10 ratios at co-located sites. Daily PM 2.5 concentrations were first estimated at a 1 × 1km resolution across Switzerland, using Multiangle Implementation of Atmospheric Correction (MAIAC) spectral aerosol optical depth (AOD) data in combination with spatiotemporal predictor data in a four stage approach. Mixed effect models (1) were used to predict PM 2.5 in cells with AOD but without PM 2.5 measurements (2). A generalized additive mixed model with spatial smoothing was applied to generate grid cell predictions for those grid cells where AOD was missing (3). Finally, local PM 2.5 predictions were estimated at each monitoring site by regressing the residuals from the 1 × 1km estimate against local spatial and temporal variables using machine learning techniques (4) and adding them to the stage 3 global estimates. The global (1 km) and local (100 m) models explained on average 73% of the total,71% of the spatial and 75% of the temporal variation (all cross validated) globally and on average 89% (total) 95% (spatial) and 88% (temporal) of the variation locally in measured PM 2.5 concentrations. Copyright © 2017 Elsevier Ltd. All rights reserved.
-
Lipid emulsion improves survival in animal models of local anesthetic toxicity: a meta-analysis.
Fettiplace, Michael R; McCabe, Daniel J
2017-08-01
The Lipid Emulsion Therapy workgroup, organized by the American Academy of Clinical Toxicology, recently conducted a systematic review, which subjectively evaluated lipid emulsion as a treatment for local anesthetic toxicity. We re-extracted data and conducted a meta-analysis of survival in animal models. We extracted survival data from 26 publications and conducted a random-effect meta-analysis based on odds ratio weighted by inverse variance. We assessed the benefit of lipid emulsion as an independent variable in resuscitative models (16 studies). We measured Cochran's Q for heterogeneity and I 2 to determine variance contributed by heterogeneity. Finally, we conducted a funnel plot analysis and Egger's test to assess for publication bias in studies. Lipid emulsion reduced the odds of death in resuscitative models (OR =0.24; 95%CI: 0.1-0.56, p = .0012). Heterogeneity analysis indicated a homogenous distribution. Funnel plot analysis did not indicate publication bias in experimental models. Meta-analysis of animal data supports the use of lipid emulsion (in combination with other resuscitative measures) for the treatment of local anesthetic toxicity, specifically from bupivacaine. Our conclusion differed from the original review. Analysis of outliers reinforced the need for good life support measures (securement of airway and chest compressions) along with prompt treatment with lipid.
-
The Martian crustal magnetic field as seen from MGS and MAVEN
NASA Astrophysics Data System (ADS)
Langlais, B.; Thebault, E.
2017-12-01
We present a new model of the Martian crustal magnetic field. This model combines constraints from all available measurements made by Mars Global Surveyor (1997-2006) and MAVEN (2014-). This is the first time a planet (besides the Earth) is flown twice with spacecraft providing high quality vector magnetic field measurements over its entire surface. Both missions have pros and cons which are fully taken into account and exploited. The constant altitude and local time of MGS during its (high altitude) mapping orbit phases allows to separate static, internal fields from transient, external fields. Low altitude measurements (below 250 km) by MAVEN allow to a posteriori validate MGS magnetic field measurements both on the day and night sides. The indirect estimates of the field intensity by the Electron Reflectometer experiment completes the dataset. The new model in constructed with carefully selected measurements, using local and extrapolated proxies to estimate the level of the external field activity. Tracks are individually checked to remove spurious or noisy measurements. The final model has a horizontal resolution close to 100 km. At a local scale, anomalies are better defined, which should ease their interpretation in terms of magnetization properties and processes. During this presentation we will compare this model to previous ones and discuss its new findings.
-
Ghouzam, Yassine; Postic, Guillaume; Guerin, Pierre-Edouard; de Brevern, Alexandre G.; Gelly, Jean-Christophe
2016-01-01
Protein structure prediction based on comparative modeling is the most efficient way to produce structural models when it can be performed. ORION is a dedicated webserver based on a new strategy that performs this task. The identification by ORION of suitable templates is performed using an original profile-profile approach that combines sequence and structure evolution information. Structure evolution information is encoded into profiles using structural features, such as solvent accessibility and local conformation —with Protein Blocks—, which give an accurate description of the local protein structure. ORION has recently been improved, increasing by 5% the quality of its results. The ORION web server accepts a single protein sequence as input and searches homologous protein structures within minutes. Various databases such as PDB, SCOP and HOMSTRAD can be mined to find an appropriate structural template. For the modeling step, a protein 3D structure can be directly obtained from the selected template by MODELLER and displayed with global and local quality model estimation measures. The sequence and the predicted structure of 4 examples from the CAMEO server and a recent CASP11 target from the ‘Hard’ category (T0818-D1) are shown as pertinent examples. Our web server is accessible at http://www.dsimb.inserm.fr/ORION/. PMID:27319297
-
Ghouzam, Yassine; Postic, Guillaume; Guerin, Pierre-Edouard; de Brevern, Alexandre G; Gelly, Jean-Christophe
2016-06-20
Protein structure prediction based on comparative modeling is the most efficient way to produce structural models when it can be performed. ORION is a dedicated webserver based on a new strategy that performs this task. The identification by ORION of suitable templates is performed using an original profile-profile approach that combines sequence and structure evolution information. Structure evolution information is encoded into profiles using structural features, such as solvent accessibility and local conformation -with Protein Blocks-, which give an accurate description of the local protein structure. ORION has recently been improved, increasing by 5% the quality of its results. The ORION web server accepts a single protein sequence as input and searches homologous protein structures within minutes. Various databases such as PDB, SCOP and HOMSTRAD can be mined to find an appropriate structural template. For the modeling step, a protein 3D structure can be directly obtained from the selected template by MODELLER and displayed with global and local quality model estimation measures. The sequence and the predicted structure of 4 examples from the CAMEO server and a recent CASP11 target from the 'Hard' category (T0818-D1) are shown as pertinent examples. Our web server is accessible at http://www.dsimb.inserm.fr/ORION/.
-
Testing for new physics: neutrinos and the primordial power spectrum
DOE Office of Scientific and Technical Information (OSTI.GOV)
Canac, Nicolas; Abazajian, Kevork N.; Aslanyan, Grigor
2016-09-01
We test the sensitivity of neutrino parameter constraints from combinations of CMB and LSS data sets to the assumed form of the primordial power spectrum (PPS) using Bayesian model selection. Significantly, none of the tested combinations, including recent high-precision local measurements of H{sub 0} and cluster abundances, indicate a signal for massive neutrinos or extra relativistic degrees of freedom. For PPS models with a large, but fixed number of degrees of freedom, neutrino parameter constraints do not change significantly if the location of any features in the PPS are allowed to vary, although neutrino constraints are more sensitive to PPSmore » features if they are known a priori to exist at fixed intervals in log k . Although there is no support for a non-standard neutrino sector from constraints on both neutrino mass and relativistic energy density, we see surprisingly strong evidence for features in the PPS when it is constrained with data from Planck 2015, SZ cluster counts, and recent high-precision local measurements of H{sub 0}. Conversely combining Planck with matter power spectrum and BAO measurements yields a much weaker constraint. Given that this result is sensitive to the choice of data this tension between SZ cluster counts, Planck and H{sub 0} measurements is likely an indication of unmodeled systematic bias that mimics PPS features, rather than new physics in the PPS or neutrino sector.« less
-
Post-modelling of images from a laser-induced wavy boiling front
NASA Astrophysics Data System (ADS)
Matti, R. S.; Kaplan, A. F. H.
2015-12-01
Processes like laser keyhole welding, remote fusion laser cutting or laser drilling are governed by a highly dynamic wavy boiling front that was recently recorded by ultra-high speed imaging. A new approach has now been established by post-modelling of the high speed images. Based on the image greyscale and on a cavity model the three-dimensional front topology is reconstructed. As a second step the Fresnel absorptivity modulation across the wavy front is calculated, combined with the local projection of the laser beam. Frequency polygons enable additional analysis of the statistical variations of the properties across the front. Trends like shadow formation and time dependency can be studied, locally and for the whole front. Despite strong topology modulation in space and time, for lasers with 1 μm wavelength and steel the absorptivity is bounded to a narrow range of 35-43%, owing to its Fresnel characteristics.
-
Disjunctive Normal Shape and Appearance Priors with Applications to Image Segmentation.
Mesadi, Fitsum; Cetin, Mujdat; Tasdizen, Tolga
2015-10-01
The use of appearance and shape priors in image segmentation is known to improve accuracy; however, existing techniques have several drawbacks. Active shape and appearance models require landmark points and assume unimodal shape and appearance distributions. Level set based shape priors are limited to global shape similarity. In this paper, we present a novel shape and appearance priors for image segmentation based on an implicit parametric shape representation called disjunctive normal shape model (DNSM). DNSM is formed by disjunction of conjunctions of half-spaces defined by discriminants. We learn shape and appearance statistics at varying spatial scales using nonparametric density estimation. Our method can generate a rich set of shape variations by locally combining training shapes. Additionally, by studying the intensity and texture statistics around each discriminant of our shape model, we construct a local appearance probability map. Experiments carried out on both medical and natural image datasets show the potential of the proposed method.
-
Deformation, Failure, and Fatigue Life of SiC/Ti-15-3 Laminates Accurately Predicted by MAC/GMC
NASA Technical Reports Server (NTRS)
Bednarcyk, Brett A.; Arnold, Steven M.
2002-01-01
NASA Glenn Research Center's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) (ref.1) has been extended to enable fully coupled macro-micro deformation, failure, and fatigue life predictions for advanced metal matrix, ceramic matrix, and polymer matrix composites. Because of the multiaxial nature of the code's underlying micromechanics model, GMC--which allows the incorporation of complex local inelastic constitutive models--MAC/GMC finds its most important application in metal matrix composites, like the SiC/Ti-15-3 composite examined here. Furthermore, since GMC predicts the microscale fields within each constituent of the composite material, submodels for local effects such as fiber breakage, interfacial debonding, and matrix fatigue damage can and have been built into MAC/GMC. The present application of MAC/GMC highlights the combination of these features, which has enabled the accurate modeling of the deformation, failure, and life of titanium matrix composites.
-
NASA Technical Reports Server (NTRS)
Phillips, T. J.
1984-01-01
The heating associated with equatorial, subtropical, and midlatitude ocean temperature anamolies in the Held-Suarez climate model is analyzed. The local and downstream response to the anomalies is analyzed, first by examining the seasonal variation in heating associated with each ocean temperature anomaly, and then by combining knowledge of the heating with linear dynamical theory in order to develop a more comprehensive explanation of the seasonal variation in local and downstream atmospheric response to each anomaly. The extent to which the linear theory of propagating waves can assist the interpretation of the remote cross-latitudinal response of the model to the ocean temperature anomalies is considered. Alternative hypotheses that attempt to avoid the contradictions inherent in a strict application of linear theory are investigated, and the impact of sampling errors on the assessment of statistical significance is also examined.
-
Automated feature extraction in color retinal images by a model based approach.
Li, Huiqi; Chutatape, Opas
2004-02-01
Color retinal photography is an important tool to detect the evidence of various eye diseases. Novel methods to extract the main features in color retinal images have been developed in this paper. Principal component analysis is employed to locate optic disk; A modified active shape model is proposed in the shape detection of optic disk; A fundus coordinate system is established to provide a better description of the features in the retinal images; An approach to detect exudates by the combined region growing and edge detection is proposed. The success rates of disk localization, disk boundary detection, and fovea localization are 99%, 94%, and 100%, respectively. The sensitivity and specificity of exudate detection are 100% and 71%, correspondingly. The success of the proposed algorithms can be attributed to the utilization of the model-based methods. The detection and analysis could be applied to automatic mass screening and diagnosis of the retinal diseases.
-
Role of weakest links and system-size scaling in multiscale modeling of stochastic plasticity
NASA Astrophysics Data System (ADS)
Ispánovity, Péter Dusán; Tüzes, Dániel; Szabó, Péter; Zaiser, Michael; Groma, István
2017-02-01
Plastic deformation of crystalline and amorphous matter often involves intermittent local strain burst events. To understand the physical background of the phenomenon a minimal stochastic mesoscopic model was introduced, where details of the microstructure evolution are statistically represented in terms of a fluctuating local yield threshold. In the present paper we propose a method for determining the corresponding yield stress distribution for the case of crystal plasticity from lower scale discrete dislocation dynamics simulations which we combine with weakest link arguments. The success of scale linking is demonstrated by comparing stress-strain curves obtained from the resulting mesoscopic and the underlying discrete dislocation models in the microplastic regime. As shown by various scaling relations they are statistically equivalent and behave identically in the thermodynamic limit. The proposed technique is expected to be applicable to different microstructures and also to amorphous materials.
-
Breaking barriers to care: a community of solution for chronic disease management.
Sanders, Jim; Solberg, Bill; Gauger, Michael
2013-01-01
For 10 years the Medical College of Wisconsin and Columbia St. Mary's Hospital have joined together in a partnership to work within some of Milwaukee's most impoverished neighborhoods. Beginning simply by providing health care through a free clinic, the partnership soon was confronted with numerous examples of barriers to care being experienced by patients. A community-based participatory action process allowed the local population to give voice to the local realities of barriers to care. Here we combine our anecdotal clinical experience, the neighborhood's input, and an example of a successful program from a low-resource international setting to create a novel approach to treating chronic disease in uninsured populations. This model of care has been successful for 2 reasons. First, the model shows good health outcomes at low cost. Second, solid community partnerships with care providers, churches, and other groups have been formed in support of the model, ensuring its credibility and sustainability.
-
Double symbolic joint entropy in nonlinear dynamic complexity analysis
NASA Astrophysics Data System (ADS)
Yao, Wenpo; Wang, Jun
2017-07-01
Symbolizations, the base of symbolic dynamic analysis, are classified as global static and local dynamic approaches which are combined by joint entropy in our works for nonlinear dynamic complexity analysis. Two global static methods, symbolic transformations of Wessel N. symbolic entropy and base-scale entropy, and two local ones, namely symbolizations of permutation and differential entropy, constitute four double symbolic joint entropies that have accurate complexity detections in chaotic models, logistic and Henon map series. In nonlinear dynamical analysis of different kinds of heart rate variability, heartbeats of healthy young have higher complexity than those of the healthy elderly, and congestive heart failure (CHF) patients are lowest in heartbeats' joint entropy values. Each individual symbolic entropy is improved by double symbolic joint entropy among which the combination of base-scale and differential symbolizations have best complexity analysis. Test results prove that double symbolic joint entropy is feasible in nonlinear dynamic complexity analysis.
-
Stress-based control of magnetic nanowire domain walls in artificial multiferroic systems
NASA Astrophysics Data System (ADS)
Dean, J.; Bryan, M. T.; Schrefl, T.; Allwood, D. A.
2011-01-01
Artificial multiferroic systems, which combine piezoelectric and piezomagnetic materials, offer novel methods of controlling material properties. Here, we use combined structural and magnetic finite element models to show how localized strains in a piezoelectric film coupled to a piezomagnetic nanowire can attract and pin magnetic domain walls. Synchronous switching of addressable contacts enables the controlled movement of pinning sites, and hence domain walls, in the nanowire without applied magnetic field or spin-polarized current, irrespective of domain wall structure. Conversely, domain wall-induced strain in the piezomagnetic material induces a local potential difference in the piezoelectric, providing a mechanism for sensing domain walls. This approach overcomes the problems in magnetic nanowire memories of domain wall structure-dependent behavior and high power consumption. Nonvolatile random access or shift register memories based on these effects can achieve storage densities >1 Gbit/In2, sub-10 ns switching times, and power consumption <100 keV per operation.
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Anderson, R W; Pember, R B; Elliott, N S
2001-10-22
A new method that combines staggered grid Arbitrary Lagrangian-Eulerian (ALE) techniques with structured local adaptive mesh refinement (AMR) has been developed for solution of the Euler equations. This method facilitates the solution of problems currently at and beyond the boundary of soluble problems by traditional ALE methods by focusing computational resources where they are required through dynamic adaption. Many of the core issues involved in the development of the combined ALEAMR method hinge upon the integration of AMR with a staggered grid Lagrangian integration method. The novel components of the method are mainly driven by the need to reconcile traditionalmore » AMR techniques, which are typically employed on stationary meshes with cell-centered quantities, with the staggered grids and grid motion employed by Lagrangian methods. Numerical examples are presented which demonstrate the accuracy and efficiency of the method.« less
-
Cancer treatment by photodynamic therapy combined with NK-cell-line-based adoptive immunotherapy
NASA Astrophysics Data System (ADS)
Korbelik, Mladen; Sun, Jinghai
1998-05-01
Treatment of solid cancers by photodynamic therapy (PDT) triggers a strong acute inflammatory reaction localized to the illuminated malignant tissue. This event is regulated by a massive release of various potent mediators which have a profound effect not only on local host cell populations, but also attract different types of immune cells to the treated tumor. Phagocytosis of PDT-damaged cancerous cells by antigen presenting cells, such as activated tumor associated macrophages, enables the recognition of even poorly immunogenic tumors by specific immune effector cells and the generation of immune memory populations. Because of its inflammatory/immune character, PDT is exceptionally responsive to adjuvant treatments with various types of immunotherapy. Combining PDT with immuneactivators, such as cytokines or other specific or non-specific immune agents, rendered marked improvements in tumor cures with various cancer models. Another clinically attractive strategy is adoptive immunotherapy, and the prospects of its use in conjunction with PDT are outlined.
-
Dynamics of correlations in long-range quantum systems follwing a quantum quench
NASA Astrophysics Data System (ADS)
Cevolani, Lorenzo; Carleo, Giuseppe; Sanchez-Palencia, Laurent
We study how and how fast correlations can spread in a quantum system abruptly driven out of equilibrium by a quantum quench. This protocol can be experimentally realized and it allow to address fundamental questions concerning the quasi-locality principle in isolated quantum systems with both short- and long-range interactions. We focus on two different models describing, respectively, lattice bosons, and spins. Our study is based on a combined approach, based on one hand on accurate many-body numerical calculations and on the other hand on a quasi-particle microscopic theory. We find that, for sufficiently fast decaying interaction potential the propagation is ballistic and the Lieb-Robinson bounds for long-range interactions are never attained. When the interactions are really long-range, the scenario is completely different in the two cases. In the bosonic system the locality is preserved and a ballistic propagation is still present while in the spin system an instantaneous propagation of correlations completely destroys locality. Using the microscopic point of view we can quantitatively describe all the different regimes, from instantaneous to ballistic, found in the spin model and we explain how locality is protected in the bosonic model leading to a ballistic propagation. ERC (FP7/2007-2013 No. 256294), QUIC (H2020 No. 641122).
-
Ozmutlu, H. Cenk
2014-01-01
We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms. PMID:24977204
-
NASA Astrophysics Data System (ADS)
Nishiura, Takanobu; Nakamura, Satoshi
2002-11-01
It is very important to capture distant-talking speech for a hands-free speech interface with high quality. A microphone array is an ideal candidate for this purpose. However, this approach requires localizing the target talker. Conventional talker localization algorithms in multiple sound source environments not only have difficulty localizing the multiple sound sources accurately, but also have difficulty localizing the target talker among known multiple sound source positions. To cope with these problems, we propose a new talker localization algorithm consisting of two algorithms. One is DOA (direction of arrival) estimation algorithm for multiple sound source localization based on CSP (cross-power spectrum phase) coefficient addition method. The other is statistical sound source identification algorithm based on GMM (Gaussian mixture model) for localizing the target talker position among localized multiple sound sources. In this paper, we particularly focus on the talker localization performance based on the combination of these two algorithms with a microphone array. We conducted evaluation experiments in real noisy reverberant environments. As a result, we confirmed that multiple sound signals can be identified accurately between ''speech'' or ''non-speech'' by the proposed algorithm. [Work supported by ATR, and MEXT of Japan.
-
Numerical Modeling of Nonlinear Thermodynamics in SMA Wires
DOE Office of Scientific and Technical Information (OSTI.GOV)
Reynolds, D R; Kloucek, P
We present a mathematical model describing the thermodynamic behavior of shape memory alloy wires, as well as a computational technique to solve the resulting system of partial differential equations. The model consists of conservation equations based on a new Helmholtz free energy potential. The computational technique introduces a viscosity-based continuation method, which allows the model to handle dynamic applications where the temporally local behavior of solutions is desired. Computational experiments document that this combination of modeling and solution techniques appropriately predicts the thermally- and stress-induced martensitic phase transitions, as well as the hysteretic behavior and production of latent heat associatedmore » with such materials.« less
-
Muñoz-Antoli, C; Marín, A; Trelis, M; Toledo, R; Esteban, J-G
2010-12-01
An experimental infection with echinostomatid miracidia in sympatric or 'local' vs. allopatric or 'away' snail combinations, as a model to examine parasite compatibility, was carried out. We employed Euparyphium albuferensis miracidia to infect Gyraulus chinensis snails, from three different natural parks: Albufera (Valencia, Spain); the Ebro Delta (Tarragona, Spain) and Coto de Doñana (Huelva, Spain). Insignificant differences between the three snail strains were noted for the infection rate and the rhythm of daily cercarial production. However, a significantly higher total cercarial production per snail, patent period and life span were observed in local snails. The different infection characteristics in the three G. chinensis strains considered reveal that E. albuferensis miracidia demonstrate local adaptation.
-
Estimation of TOA based MUSIC algorithm and cross correlation algorithm of appropriate interval
NASA Astrophysics Data System (ADS)
Lin, Wei; Liu, Jun; Zhou, Yineng; Huang, Jiyan
2017-03-01
Localization of mobile station (MS) has now gained considerable attention due to its wide applications in military, environmental, health and commercial systems. Phrase angle and encode data of MSK system model are two critical parameters in time-of-arrival (TOA) localization technique; nevertheless, precise value of phrase angle and encode data are not easy to achieved in general. In order to meet the actual situation, we should consider the condition that phase angle and encode data is unknown. In this paper, a novel TOA localization method, which combine MUSIC algorithm and cross correlation algorithm in an appropriate interval, is proposed. Simulations show that the proposed method has better performance than music algorithm and cross correlation algorithm of the whole interval.
-
Locally linear embedding: dimension reduction of massive protostellar spectra
NASA Astrophysics Data System (ADS)
Ward, J. L.; Lumsden, S. L.
2016-09-01
We present the results of the application of locally linear embedding (LLE) to reduce the dimensionality of dereddened and continuum subtracted near-infrared spectra using a combination of models and real spectra of massive protostars selected from the Red MSX Source survey data base. A brief comparison is also made with two other dimension reduction techniques; principal component analysis (PCA) and Isomap using the same set of spectra as well as a more advanced form of LLE, Hessian locally linear embedding. We find that whilst LLE certainly has its limitations, it significantly outperforms both PCA and Isomap in classification of spectra based on the presence/absence of emission lines and provides a valuable tool for classification and analysis of large spectral data sets.
-
Crossed Ga2O3/SnO2 multiwire architecture: a local structure study with nanometer resolution.
Martínez-Criado, Gema; Segura-Ruiz, Jaime; Chu, Manh-Hung; Tucoulou, Remi; López, Iñaki; Nogales, Emilio; Mendez, Bianchi; Piqueras, Javier
2014-10-08
Crossed nanowire structures are the basis for high-density integration of a variety of nanodevices. Owing to the critical role of nanowires intersections in creating hybrid architectures, it has become a challenge to investigate the local structure in crossing points in metal oxide nanowires. Thus, if intentionally grown crossed nanowires are well-patterned, an ideal model to study the junction is formed. By combining electron and synchrotron beam nanoprobes, we show here experimental evidence of the role of impurities in the coupling formation, structural modifications, and atomic site configuration based on crossed Ga2O3/SnO2 nanowires. Our experiment opens new avenues for further local structure studies with both nanometer resolution and elemental sensitivity.
-
NASA Technical Reports Server (NTRS)
Hochhalter, Jake D.; Littlewood, David J.; Christ, Robert J., Jr.; Veilleux, M. G.; Bozek, J. E.; Ingraffea, A. R.; Maniatty, Antionette M.
2010-01-01
The objective of this paper is to develop further a framework for computationally modeling microstructurally small fatigue crack growth in AA 7075-T651 [1]. The focus is on the nucleation event, when a crack extends from within a second-phase particle into a surrounding grain, since this has been observed to be an initiating mechanism for fatigue crack growth in this alloy. It is hypothesized that nucleation can be predicted by computing a non-local nucleation metric near the crack front. The hypothesis is tested by employing a combination of experimentation and nite element modeling in which various slip-based and energy-based nucleation metrics are tested for validity, where each metric is derived from a continuum crystal plasticity formulation. To investigate each metric, a non-local procedure is developed for the calculation of nucleation metrics in the neighborhood of a crack front. Initially, an idealized baseline model consisting of a single grain containing a semi-ellipsoidal surface particle is studied to investigate the dependence of each nucleation metric on lattice orientation, number of load cycles, and non-local regularization method. This is followed by a comparison of experimental observations and computational results for microstructural models constructed by replicating the observed microstructural geometry near second-phase particles in fatigue specimens. It is found that orientation strongly influences the direction of slip localization and, as a result, in uences the nucleation mechanism. Also, the baseline models, replication models, and past experimental observation consistently suggest that a set of particular grain orientations is most likely to nucleate fatigue cracks. It is found that a continuum crystal plasticity model and a non-local nucleation metric can be used to predict the nucleation event in AA 7075-T651. However, nucleation metric threshold values that correspond to various nucleation governing mechanisms must be calibrated.
-
Accurate modeling of switched reluctance machine based on hybrid trained WNN
DOE Office of Scientific and Technical Information (OSTI.GOV)
Song, Shoujun, E-mail: sunnyway@nwpu.edu.cn; Ge, Lefei; Ma, Shaojie
2014-04-15
According to the strong nonlinear electromagnetic characteristics of switched reluctance machine (SRM), a novel accurate modeling method is proposed based on hybrid trained wavelet neural network (WNN) which combines improved genetic algorithm (GA) with gradient descent (GD) method to train the network. In the novel method, WNN is trained by GD method based on the initial weights obtained per improved GA optimization, and the global parallel searching capability of stochastic algorithm and local convergence speed of deterministic algorithm are combined to enhance the training accuracy, stability and speed. Based on the measured electromagnetic characteristics of a 3-phase 12/8-pole SRM, themore » nonlinear simulation model is built by hybrid trained WNN in Matlab. The phase current and mechanical characteristics from simulation under different working conditions meet well with those from experiments, which indicates the accuracy of the model for dynamic and static performance evaluation of SRM and verifies the effectiveness of the proposed modeling method.« less
-
Full waveform inversion of combined towed streamer and limited OBS seismic data: a theoretical study
NASA Astrophysics Data System (ADS)
Yang, Huachen; Zhang, Jianzhong
2018-06-01
In marine seismic oil exploration, full waveform inversion (FWI) of towed-streamer data is used to reconstruct velocity models. However, the FWI of towed-streamer data easily converges to a local minimum solution due to the lack of low-frequency content. In this paper, we propose a new FWI technique using towed-streamer data, its integrated data sets and limited OBS data. Both integrated towed-streamer seismic data and OBS data have low-frequency components. Therefore, at early iterations in the new FWI technique, the OBS data combined with the integrated towed-streamer data sets reconstruct an appropriate background model. And the towed-streamer seismic data play a major role in later iterations to improve the resolution of the model. The new FWI technique is tested on numerical examples. The results show that when starting models are not accurate enough, the models inverted using the new FWI technique are superior to those inverted using conventional FWI.
-
NASA Astrophysics Data System (ADS)
Phillips, C.; Holz, R.; Eloranta, E. W.; Reid, J. S.; Kim, S. W.; Kuehn, R.; Marais, W.
2017-12-01
The University of Wisconsin High Spectral Resolution Lidar (HSRL) has been continuously operating at Seoul National University as part of the Korea-United States Air Quality Study (KORUS-AQ). The instrument was installed in March of 2016 and continues to operate as of August 2017, providing a truly unique data set to monitor aerosol and cloud properties. With its capability to separate the molecular and particulate scattering, the HSRL is able to detect extremely thin aerosol layers with sub-molecular scattering sensitivity. The system deployed in Seoul has depolarization measurements at 532 nm as well as a near IR channel at 1064 nm providing discrimination between dust, smoke, pollution, water clouds, and ice clouds. As will be presented, these capabilities can be used to produce three channel combined RGB images that provide visualization of small changes in the aerosol properties. A primary motivation of KORUS-AQ was to determine the relative effects of transported pollution and local pollution on air quality in Seoul. We hypothesize that HSRL-based image analysis algorithms combined with satellite and model re-analysis has the potential to identify cases when remote sources of aerosols and pollution are advected into the boundary layer with impacts to the surface air quality. To facilitate this research we have developed the capability to combine ten-minute geostationary imagery from Himawari-8, nearby radiosondes, model output, surface PM measurements, and AERONET data over the HSRL site. On a case-by-case basis, it is possible to separate layers of aerosols with different scattering properties using these tools. Additionally, a preliminary year-long aerosol climatology with integrated geo-stationary retrievals and modeling data will be presented. The focus is on investigating correlations between the HSRL aerosol measurements (depolarization, color ratio, extinction, and lidar ratio) with the model output and aerosol sources. This analysis will use recently developed algorithms that automate the HSRL cloud and aerosol masking, providing the capability to characterize the seasonal changes in aerosol radiative properties and supplement the month-long field campaign with almost two years of continuous HSRL observations.
-
Terrestrial Ecosystems - Land Surface Forms of the Conterminous United States
Cress, Jill J.; Sayre, Roger G.; Comer, Patrick; Warner, Harumi
2009-01-01
As part of an effort to map terrestrial ecosystems, the U.S. Geological Survey has generated land surface form classes to be used in creating maps depicting standardized, terrestrial ecosystem models for the conterminous United States, using an ecosystems classification developed by NatureServe . A biophysical stratification approach, developed for South America and now being implemented globally, was used to model the ecosystem distributions. Since land surface forms strongly influence the differentiation and distribution of terrestrial ecosystems, they are one of the key input layers in this biophysical stratification. After extensive investigation into various land surface form mapping methodologies, the decision was made to use the methodology developed by the Missouri Resource Assessment Partnership (MoRAP). MoRAP made modifications to Hammond's land surface form classification, which allowed the use of 30-meter source data and a 1-km2 window for analyzing the data cell and its surrounding cells (neighborhood analysis). While Hammond's methodology was based on three topographic variables, slope, local relief, and profile type, MoRAP's methodology uses only slope and local relief. Using the MoRAP method, slope is classified as gently sloping when more than 50 percent of the area in a 1-km2 neighborhood has slope less than 8 percent, otherwise the area is considered moderately sloping. Local relief, which is the difference between the maximum and minimum elevation in a neighborhood, is classified into five groups: 0-15 m, 16-30 m, 31-90 m, 91-150 m, and >150 m. The land surface form classes are derived by combining slope and local relief to create eight landform classes: flat plains (gently sloping and local relief = 90 m), low hills (not gently sloping and local relief = 150 m). However, in the USGS application of the MoRAP methodology, an additional local relief group was used (> 400 m) to capture additional local topographic variation. As a result, low mountains were redefined as not gently sloping and 151 m 400 m. The final application of the MoRAP methodology was implemented using the USGS 30-meter National Elevation Dataset and an existing USGS slope dataset that had been derived by calculating the slope from the NED in Universal Transverse Mercator (UTM) coordinates in each UTM zone, and then combining all of the zones into a national dataset. This map shows a smoothed image of the nine land surface form classes based on MoRAP's methodology. Additional information about this map and any data developed for the ecosystems modeling of the conterminous United States is available online at http://rmgsc.cr.usgs.gov/ecosystems/.
-
Modelling malaria incidence by an autoregressive distributed lag model with spatial component.
Laguna, Francisco; Grillet, María Eugenia; León, José R; Ludeña, Carenne
2017-08-01
The influence of climatic variables on the dynamics of human malaria has been widely highlighted. Also, it is known that this mosquito-borne infection varies in space and time. However, when the data is spatially incomplete most popular spatio-temporal methods of analysis cannot be applied directly. In this paper, we develop a two step methodology to model the spatio-temporal dependence of malaria incidence on local rainfall, temperature, and humidity as well as the regional sea surface temperatures (SST) in the northern coast of Venezuela. First, we fit an autoregressive distributed lag model (ARDL) to the weekly data, and then, we adjust a linear separable spacial vectorial autoregressive model (VAR) to the residuals of the ARDL. Finally, the model parameters are tuned using a Markov Chain Monte Carlo (MCMC) procedure derived from the Metropolis-Hastings algorithm. Our results show that the best model to account for the variations of malaria incidence from 2001 to 2008 in 10 endemic Municipalities in North-Eastern Venezuela is a logit model that included the accumulated local precipitation in combination with the local maximum temperature of the preceding month as positive regressors. Additionally, we show that although malaria dynamics is highly heterogeneous in space, a detailed analysis of the estimated spatial parameters in our model yield important insights regarding the joint behavior of the disease incidence across the different counties in our study. Copyright © 2017 Elsevier Ltd. All rights reserved.
-
Knee cartilage segmentation using active shape models and local binary patterns
NASA Astrophysics Data System (ADS)
González, Germán.; Escalante-Ramírez, Boris
2014-05-01
Segmentation of knee cartilage has been useful for opportune diagnosis and treatment of osteoarthritis (OA). This paper presents a semiautomatic segmentation technique based on Active Shape Models (ASM) combined with Local Binary Patterns (LBP) and its approaches to describe the surrounding texture of femoral cartilage. The proposed technique is tested on a 16-image database of different patients and it is validated through Leave- One-Out method. We compare different segmentation techniques: ASM-LBP, ASM-medianLBP, and ASM proposed by Cootes. The ASM-LBP approaches are tested with different ratios to decide which of them describes the cartilage texture better. The results show that ASM-medianLBP has better performance than ASM-LBP and ASM. Furthermore, we add a routine which improves the robustness versus two principal problems: oversegmentation and initialization.
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Collins, L.; Tselev, A.; Jesse, S.
The correlation between local mechanical (elasto-plastic) and structural (composition) properties of coal presents significant fundamental and practical interest for coal processing and the development of rheological models of coal to coke transformations and for advancing novel approaches. Here, we explore the relationship between the local structural, chemical composition and mechanical properties of coal using a combination of confocal micro-Raman imaging and band excitation atomic force acoustic microscopy (BE-AFAM) for a bituminous coal. This allows high resolution imaging (10s of nm) of mechanical properties of the heterogeneous (banded) architecture of coal and correlating them to the optical gap, average crystallite size,more » the bond-bending disorder of sp2 aromatic double bonds and the defect density. This methodology hence allows the structural and mechanical properties of coal components (lithotypes, microlithotypes, and macerals) to be understood, and related to local chemical structure, potentially allowing for knowledge-based modelling and optimization of coal utilization processes.« less
-
NASA Astrophysics Data System (ADS)
Abazajian, Kevork N.; Keeley, Ryan E.
2016-04-01
We incorporate Milky Way dark matter halo profile uncertainties, as well as an accounting of diffuse gamma-ray emission uncertainties in dark matter annihilation models for the Galactic Center Extended gamma-ray excess (GCE) detected by the Fermi Gamma Ray Space Telescope. The range of particle annihilation rate and masses expand when including these unknowns. However, two of the most precise empirical determinations of the Milky Way halo's local density and density profile leave the signal region to be in considerable tension with dark matter annihilation searches from combined dwarf galaxy analyses for single-channel dark matter annihilation models. The GCE and dwarf tension can be alleviated if: one, the halo is very highly concentrated or strongly contracted; two, the dark matter annihilation signal differentiates between dwarfs and the GC; or, three, local stellar density measures are found to be significantly lower, like that from recent stellar counts, increasing the local dark matter density.
-
Li, Xingang; Sun, Shusen; Wang, Qiang; Zhao, Zhigang
2018-02-01
For patients with intracranial infection, local intrathecal administration of meropenem may be a useful method to obtain a sufficient drug concentration in the cerebral spinal fluid (CSF). However, a large inter-individual variability may pose treatment efficacy at risk. This study aimed to identify factors affecting drug concentration in the CSF using population pharmacokinetics method. After craniotomy, aneurysm patients with an indwelling lumbar cistern drainage tube who received a combined intravenous and intrathecal administration of meropenem for the treatment of suspected intracranial infection were enrolled. Venous blood and CSF specimens were collected for determining meropenem concentrations. Nonlinear mixed-effects modeling method was used to fit blood and CSF concentrations simultaneously and to develop the population pharmacokinetic model. The proposed model was applied to simulate dosage regimens. A three-compartmental model was established to describe meropenem in vivo behavior. Lumbar CSF drainage resulted in a drug loss, and drug clearance in CSF (CL CSF ) was employed to describe this. The covariate analysis found that the drainage volume (mL/day) was strongly associated with CL CSF , and the effect of creatinine clearance was significant on the clearance of meropenem in blood (CL). Visual predictive check suggested that the proposed pharmacokinetic model agreed well with the observations. Simulation showed that both intravenous and intrathecal doses should be increased with the increases of minimum inhibitory concentration and daily CSF drainage volume. This model incorporates covariates of the creatinine clearance and the drainage volume, and a simple to use dosage regimen table was created to guide clinicians with meropenem dosing.
-
Electronic structure studies of La2CuO4
NASA Astrophysics Data System (ADS)
Wachs, A. L.; Turchi, P. E. A.; Jean, Y. C.; Wetzler, K. H.; Howell, R. H.; Fluss, M. J.; Harshman, D. R.; Remeika, J. P.; Cooper, A. S.; Fleming, R. M.
1988-07-01
We report results of positron-electron momentum-distribution measurements of single-crystal La2CuO4 using two-dimensional angular correlation of positron-annihilation-radiation techniques. The data contain two components: a large (~85%), isotropic corelike electron contribution and a remaining, anisotropic valence-electron contribution modeled using a linear combination of atomic orbitals-molecular orbital method and a localized ion scheme, within the independent-particle model approximation. This work suggests a ligand-field Hamiltonian to be justified for describing the electronic properties of perovskite materials.
-
Ercan, Nilufer; Uludag, Mecit Orhan; Agis, Erol Rauf; Demirel-Yilmaz, Emine
2013-12-01
Nonsteroidal anti-inflammatory drugs (NSAIDs) are the most used drugs in musculoskeletal disorders, but their systemic adverse effects limit their therapeutic benefit in local inflammation. On the other hand, topical preparations of capsaicinoids are widely used for musculoskeletal disorders as a complementary therapy. In this study, the effects of both topical capsaicinoids-containing patch and local subcutaneous capsaicin application on the anti-inflammatory action of NSAID were examined. Carrageenan-induced paw oedema of rats was used as the inflammation model. The volume and weight of the paw oedema and plasma extravasation in the paw were determined after carrageenan injection. The systemic application of diclofenac (3 mg/kg), which is an NSAID, significantly decreased the volume and weight of the paw oedema. Topical capsaicinoids-containing patch application or local capsaicin injection (2, 10, 20 μg/paw) alone did not cause any effect on oedema volume and weight. However, the combination of diclofenac with topical capsaicinoids-containing patch significantly increased the effectiveness of diclofenac on inflammation. Evans blue content of the paws that represents plasma extravasation was decreased by capsaicinoids-containing patch with and without diclofenac and diclofenac combination with the lowest dose of capsaicin injection. The results of this study indicate that topical application of capsaicinoids-containing patch enhances the anti-inflammatory effect of diclofenac and its beneficial effect may not purely relate to its capsaicin content. In the treatment of local inflammatory disorders, the combination of NSAID with topical capsaicinoids-containing patch could increase the anti-inflammatory efficiency of drug without systemic side effects.
-
Dmitrieva, Olga; Michalakidis, Georgios; Mason, Aaron; Jones, Simon; Chan, Tom; de Lusignan, Simon
2012-01-01
A new distributed model of health care management is being introduced in England. Family practitioners have new responsibilities for the management of health care budgets and commissioning of services. There are national datasets available about health care providers and the geographical areas they serve. These data could be better used to assist the family practitioner turned health service commissioners. Unfortunately these data are not in a form that is readily usable by these fledgling family commissioning groups. We therefore Web enabled all the national hospital dermatology treatment data in England combining it with locality data to provide a smart commissioning tool for local communities. We used open-source software including the Ruby on Rails Web framework and MySQL. The system has a Web front-end, which uses hypertext markup language cascading style sheets (HTML/CSS) and JavaScript to deliver and present data provided by the database. A combination of advanced caching and schema structures allows for faster data retrieval on every execution. The system provides an intuitive environment for data analysis and processing across a large health system dataset. Web-enablement has enabled data about in patients, day cases and outpatients to be readily grouped, viewed, and linked to other data. The combination of web-enablement, consistent data collection from all providers; readily available locality data; and a registration based primary system enables the creation of data, which can be used to commission dermatology services in small areas. Standardized datasets collected across large health enterprises when web enabled can readily benchmark local services and inform commissioning decisions.
-
Pioz, Maryline; Guis, Hélène; Calavas, Didier; Durand, Benoît; Abrial, David; Ducrot, Christian
2011-04-20
Understanding the spatial dynamics of an infectious disease is critical when attempting to predict where and how fast the disease will spread. We illustrate an approach using a trend-surface analysis (TSA) model combined with a spatial error simultaneous autoregressive model (SAR(err) model) to estimate the speed of diffusion of bluetongue (BT), an infectious disease of ruminants caused by bluetongue virus (BTV) and transmitted by Culicoides. In a first step to gain further insight into the spatial transmission characteristics of BTV serotype 8, we used 2007-2008 clinical case reports in France and TSA modelling to identify the major directions and speed of disease diffusion. We accounted for spatial autocorrelation by combining TSA with a SAR(err) model, which led to a trend SAR(err) model. Overall, BT spread from north-eastern to south-western France. The average trend SAR(err)-estimated velocity across the country was 5.6 km/day. However, velocities differed between areas and time periods, varying between 2.1 and 9.3 km/day. For more than 83% of the contaminated municipalities, the trend SAR(err)-estimated velocity was less than 7 km/day. Our study was a first step in describing the diffusion process for BT in France. To our knowledge, it is the first to show that BT spread in France was primarily local and consistent with the active flight of Culicoides and local movements of farm animals. Models such as the trend SAR(err) models are powerful tools to provide information on direction and speed of disease diffusion when the only data available are date and location of cases.
-
NASA Astrophysics Data System (ADS)
Lo, Joseph Y.; Gavrielides, Marios A.; Markey, Mia K.; Jesneck, Jonathan L.
2003-05-01
We developed an ensemble classifier for the task of computer-aided diagnosis of breast microcalcification clusters,which are very challenging to characterize for radiologists and computer models alike. The purpose of this study is to help radiologists identify whether suspicious calcification clusters are benign vs. malignant, such that they may potentially recommend fewer unnecessary biopsies for actually benign lesions. The data consists of mammographic features extracted by automated image processing algorithms as well as manually interpreted by radiologists according to a standardized lexicon. We used 292 cases from a publicly available mammography database. From each cases, we extracted 22 image processing features pertaining to lesion morphology, 5 radiologist features also pertaining to morphology, and the patient age. Linear discriminant analysis (LDA) models were designed using each of the three data types. Each local model performed poorly; the best was one based upon image processing features which yielded ROC area index AZ of 0.59 +/- 0.03 and partial AZ above 90% sensitivity of 0.08 +/- 0.03. We then developed ensemble models using different combinations of those data types, and these models all improved performance compared to the local models. The final ensemble model was based upon 5 features selected by stepwise LDA from all 28 available features. This ensemble performed with AZ of 0.69 +/- 0.03 and partial AZ of 0.21 +/- 0.04, which was statistically significantly better than the model based on the image processing features alone (p<0.001 and p=0.01 for full and partial AZ respectively). This demonstrated the value of the radiologist-extracted features as a source of information for this task. It also suggested there is potential for improved performance using this ensemble classifier approach to combine different sources of currently available data.
-
Data Mining for Efficient and Accurate Large Scale Retrieval of Geophysical Parameters
NASA Astrophysics Data System (ADS)
Obradovic, Z.; Vucetic, S.; Peng, K.; Han, B.
2004-12-01
Our effort is devoted to developing data mining technology for improving efficiency and accuracy of the geophysical parameter retrievals by learning a mapping from observation attributes to the corresponding parameters within the framework of classification and regression. We will describe a method for efficient learning of neural network-based classification and regression models from high-volume data streams. The proposed procedure automatically learns a series of neural networks of different complexities on smaller data stream chunks and then properly combines them into an ensemble predictor through averaging. Based on the idea of progressive sampling the proposed approach starts with a very simple network trained on a very small chunk and then gradually increases the model complexity and the chunk size until the learning performance no longer improves. Our empirical study on aerosol retrievals from data obtained with the MISR instrument mounted at Terra satellite suggests that the proposed method is successful in learning complex concepts from large data streams with near-optimal computational effort. We will also report on a method that complements deterministic retrievals by constructing accurate predictive algorithms and applying them on appropriately selected subsets of observed data. The method is based on developing more accurate predictors aimed to catch global and local properties synthesized in a region. The procedure starts by learning the global properties of data sampled over the entire space, and continues by constructing specialized models on selected localized regions. The global and local models are integrated through an automated procedure that determines the optimal trade-off between the two components with the objective of minimizing the overall mean square errors over a specific region. Our experimental results on MISR data showed that the combined model can increase the retrieval accuracy significantly. The preliminary results on various large heterogeneous spatial-temporal datasets provide evidence that the benefits of the proposed methodology for efficient and accurate learning exist beyond the area of retrieval of geophysical parameters.
-
NASA Astrophysics Data System (ADS)
Maussion, F.; Kropacek, J.; Finkelnburg, R.; Scherer, D.
2012-04-01
Large lakes and inland water bodies have a significant influence on their local climate. The hydrometeorological effect of inland water bodies is varying greatly between seasons, years and contrasting climatic conditions. It is generally hypothesised that the cool air above the lake will inhibit convection in summer; conversely, the relatively warm lake in late-autumn will initiate convective instability that may generate strong snowfalls. In this study we focus on the lake Nam Co (2'000 sq.km, 4700 m a.s.l). Located in a transition zone between the continental climate of Central Asia and the Indian Monsoon system, the Nam Co lake is covered by ice from mid-January to end of April and reaches surface temperatures of 13 °C in summer. We address three main research questions: (i) what is the influence of the Nam Co lake on local meteorological variables over the course of the year, (ii) what is the impact of the timing of the lake freezing on late-autumn and winter precipitation fields and (iii) how will the influence of the lake evolve in the context of a changing climate? In order to answer these questions, we combine satellite observations of lake surface temperatures from the ARC-Lake product and atmospheric modelling using the WRF model. The spatio-temporal variability of temperature, wind and precipitation fields during the last decade are analyzed using high-resolution (up to 2 km) simulations. The positive impact of the assimilation of the lake surface temperatures for the initialization of the model is analysed and discussed, as well as the combined influences of the large scale (westerlies, monsoon) and local (orographic) forcings. Our results are of relevance for any regional climate or hydrological modelling study and bring new insights in our understanding of the complex hydrometeorological processes taking place on the Tibetan Plateau.
-
Centeno, Maria; Tierney, Tim M; Perani, Suejen; Shamshiri, Elhum A; St Pier, Kelly; Wilkinson, Charlotte; Konn, Daniel; Vulliemoz, Serge; Grouiller, Frédéric; Lemieux, Louis; Pressler, Ronit M; Clark, Christopher A; Cross, J Helen; Carmichael, David W
2017-08-01
Surgical treatment in epilepsy is effective if the epileptogenic zone (EZ) can be correctly localized and characterized. Here we use simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) data to derive EEG-fMRI and electrical source imaging (ESI) maps. Their yield and their individual and combined ability to (1) localize the EZ and (2) predict seizure outcome were then evaluated. Fifty-three children with drug-resistant epilepsy underwent EEG-fMRI. Interictal discharges were mapped using both EEG-fMRI hemodynamic responses and ESI. A single localization was derived from each individual test (EEG-fMRI global maxima [GM]/ESI maximum) and from the combination of both maps (EEG-fMRI/ESI spatial intersection). To determine the localization accuracy and its predictive performance, the individual and combined test localizations were compared to the presumed EZ and to the postsurgical outcome. Fifty-two of 53 patients had significant maps: 47 of 53 for EEG-fMRI, 44 of 53 for ESI, and 34 of 53 for both. The EZ was well characterized in 29 patients; 26 had an EEG-fMRI GM localization that was correct in 11, 22 patients had ESI localization that was correct in 17, and 12 patients had combined EEG-fMRI and ESI that was correct in 11. Seizure outcome following resection was correctly predicted by EEG-fMRI GM in 8 of 20 patients, and by the ESI maximum in 13 of 16. The combined EEG-fMRI/ESI region entirely predicted outcome in 9 of 9 patients, including 3 with no lesion visible on MRI. EEG-fMRI combined with ESI provides a simple unbiased localization that may predict surgery better than each individual test, including in MRI-negative patients. Ann Neurol 2017;82:278-287. © 2017 American Neurological Association.
-
Rixen, M.; Ferreira-Coelho, E.; Signell, R.
2008-01-01
Despite numerous and regular improvements in underlying models, surface drift prediction in the ocean remains a challenging task because of our yet limited understanding of all processes involved. Hence, deterministic approaches to the problem are often limited by empirical assumptions on underlying physics. Multi-model hyper-ensemble forecasts, which exploit the power of an optimal local combination of available information including ocean, atmospheric and wave models, may show superior forecasting skills when compared to individual models because they allow for local correction and/or bias removal. In this work, we explore in greater detail the potential and limitations of the hyper-ensemble method in the Adriatic Sea, using a comprehensive surface drifter database. The performance of the hyper-ensembles and the individual models are discussed by analyzing associated uncertainties and probability distribution maps. Results suggest that the stochastic method may reduce position errors significantly for 12 to 72??h forecasts and hence compete with pure deterministic approaches. ?? 2007 NATO Undersea Research Centre (NURC).
-
Engin, Ozge; Sayar, Mehmet; Erman, Burak
2009-01-13
Relative contributions of local and non-local interactions to the unfolded conformations of peptides are examined by using the rotational isomeric states model which is a Markov model based on pairwise interactions of torsion angles. The isomeric states of a residue are well described by the Ramachandran map of backbone torsion angles. The statistical weight matrices for the states are determined by molecular dynamics simulations applied to monopeptides and dipeptides. Conformational properties of tripeptides formed from combinations of alanine, valine, tyrosine and tryptophan are investigated based on the Markov model. Comparison with molecular dynamics simulation results on these tripeptides identifies the sequence-distant long-range interactions that are missing in the Markov model. These are essentially the hydrogen bond and hydrophobic interactions that are obtained between the first and the third residue of a tripeptide. A systematic correction is proposed for incorporating these long-range interactions into the rotational isomeric states model. Preliminary results suggest that the Markov assumption can be improved significantly by renormalizing the statistical weight matrices to include the effects of the long-range correlations.
-
NASA Astrophysics Data System (ADS)
Engin, Ozge; Sayar, Mehmet; Erman, Burak
2009-03-01
Relative contributions of local and non-local interactions to the unfolded conformations of peptides are examined by using the rotational isomeric states model which is a Markov model based on pairwise interactions of torsion angles. The isomeric states of a residue are well described by the Ramachandran map of backbone torsion angles. The statistical weight matrices for the states are determined by molecular dynamics simulations applied to monopeptides and dipeptides. Conformational properties of tripeptides formed from combinations of alanine, valine, tyrosine and tryptophan are investigated based on the Markov model. Comparison with molecular dynamics simulation results on these tripeptides identifies the sequence-distant long-range interactions that are missing in the Markov model. These are essentially the hydrogen bond and hydrophobic interactions that are obtained between the first and the third residue of a tripeptide. A systematic correction is proposed for incorporating these long-range interactions into the rotational isomeric states model. Preliminary results suggest that the Markov assumption can be improved significantly by renormalizing the statistical weight matrices to include the effects of the long-range correlations.
-
Assal, Timothy J.; Anderson, Patrick J.; Sibold, Jason
2015-01-01
The availability of land cover data at local scales is an important component in forest management and monitoring efforts. Regional land cover data seldom provide detailed information needed to support local management needs. Here we present a transferable framework to model forest cover by major plant functional type using aerial photos, multi-date Système Pour l’Observation de la Terre (SPOT) imagery, and topographic variables. We developed probability of occurrence models for deciduous broad-leaved forest and needle-leaved evergreen forest using logistic regression in the southern portion of the Wyoming Basin Ecoregion. The model outputs were combined into a synthesis map depicting deciduous and coniferous forest cover type. We evaluated the models and synthesis map using a field-validated, independent data source. Results showed strong relationships between forest cover and model variables, and the synthesis map was accurate with an overall correct classification rate of 0.87 and Cohen’s kappa value of 0.81. The results suggest our method adequately captures the functional type, size, and distribution pattern of forest cover in a spatially heterogeneous landscape.
-
NASA Astrophysics Data System (ADS)
Chavare, Kushal; Bhatt, Nilesh; Prizomwala, Siddharth
2017-04-01
The boulder deposits on the coasts are interpreted and evaluated as high energy marine wave events like tsunami. Several numerical models are now available to estimate wave height and/or run up of the tsunami wave. The coast of Saurashtra, facing the Arabian Sea on its west hosts such deposits in younger ( 1 and 6 ka) and older ( 35 ka) coastal records. The dimensions, characteristics and morphology of these boulders were studied with different numeric models and were applied with reference to submerged, sub-aerial and joint bounded boulder scenarios which were combined with the local control variables like roughness coefficient, slope of platforms, fractures, shoaling effect, etc. The application of these models indicated a significant role of local control variables in boulder dislodgment, transport and final emplacement on shore platform. Examples from three different sites from the coast of Saurashtra, western India are reported and discussed in detail.
-
TRILEX and G W +EDMFT approach to d -wave superconductivity in the Hubbard model
NASA Astrophysics Data System (ADS)
Vučičević, J.; Ayral, T.; Parcollet, O.
2017-09-01
We generalize the recently introduced TRILEX approach (TRiply irreducible local EXpansion) to superconducting phases. The method treats simultaneously Mott and spin-fluctuation physics using an Eliashberg theory supplemented by local vertex corrections determined by a self-consistent quantum impurity model. We show that, in the two-dimensional Hubbard model, at strong coupling, TRILEX yields a d -wave superconducting dome as a function of doping. Contrary to the standard cluster dynamical mean field theory (DMFT) approaches, TRILEX can capture d -wave pairing using only a single-site effective impurity model. We also systematically explore the dependence of the superconducting temperature on the bare dispersion at weak coupling, which shows a clear link between strong antiferromagnetic (AF) correlations and the onset of superconductivity. We identify a combination of hopping amplitudes particularly favorable to superconductivity at intermediate doping. Finally, we study within G W +EDMFT the low-temperature d -wave superconducting phase at strong coupling in a region of parameter space with reduced AF fluctuations.
-
ChainMail based neural dynamics modeling of soft tissue deformation for surgical simulation.
Zhang, Jinao; Zhong, Yongmin; Smith, Julian; Gu, Chengfan
2017-07-20
Realistic and real-time modeling and simulation of soft tissue deformation is a fundamental research issue in the field of surgical simulation. In this paper, a novel cellular neural network approach is presented for modeling and simulation of soft tissue deformation by combining neural dynamics of cellular neural network with ChainMail mechanism. The proposed method formulates the problem of elastic deformation into cellular neural network activities to avoid the complex computation of elasticity. The local position adjustments of ChainMail are incorporated into the cellular neural network as the local connectivity of cells, through which the dynamic behaviors of soft tissue deformation are transformed into the neural dynamics of cellular neural network. Experiments demonstrate that the proposed neural network approach is capable of modeling the soft tissues' nonlinear deformation and typical mechanical behaviors. The proposed method not only improves ChainMail's linear deformation with the nonlinear characteristics of neural dynamics but also enables the cellular neural network to follow the principle of continuum mechanics to simulate soft tissue deformation.
-
Well logging interpretation of production profile in horizontal oil-water two phase flow pipes
NASA Astrophysics Data System (ADS)
Zhai, Lu-Sheng; Jin, Ning-De; Gao, Zhong-Ke; Zheng, Xi-Ke
2012-03-01
Due to the complicated distribution of local velocity and local phase hold up along the radial direction of pipe in horizontal oil-water two phase flow, it is difficult to measure the total flow rate and phase volume fraction. In this study, we carried out dynamic experiment in horizontal oil-water two phases flow simulation well by using combination measurement system including turbine flowmeter with petal type concentrating diverter, conductance sensor and flowpassing capacitance sensor. According to the response resolution ability of the conductance and capacitance sensor in different range of total flow rate and water-cut, we use drift flux model and statistical model to predict the partial phase flow rate, respectively. The results indicate that the variable coefficient drift flux model can self-adaptively tone the model parameter according to the oil-water two phase flow characteristic, and the prediction result of partial phase flow rate of oil-water two phase flow is of high accuracy.
-
Processing Motion Signals in Complex Environments
NASA Technical Reports Server (NTRS)
Verghese, Preeti
2000-01-01
Motion information is critical for human locomotion and scene segmentation. Currently we have excellent neurophysiological models that are able to predict human detection and discrimination of local signals. Local motion signals are insufficient by themselves to guide human locomotion and to provide information about depth, object boundaries and surface structure. My research is aimed at understanding the mechanisms underlying the combination of motion signals across space and time. A target moving on an extended trajectory amidst noise dots in Brownian motion is much more detectable than the sum of signals generated by independent motion energy units responding to the trajectory segments. This result suggests that facilitation occurs between motion units tuned to similar directions, lying along the trajectory path. We investigated whether the interaction between local motion units along the motion direction is mediated by contrast. One possibility is that contrast-driven signals from motion units early in the trajectory sequence are added to signals in subsequent units. If this were the case, then units later in the sequence would have a larger signal than those earlier in the sequence. To test this possibility, we compared contrast discrimination thresholds for the first and third patches of a triplet of sequentially presented Gabor patches, aligned along the motion direction. According to this simple additive model, contrast increment thresholds for the third patch should be higher than thresholds for the first patch.The lack of a measurable effect on contrast thresholds for these various manipulations suggests that the pooling of signals along a trajectory is not mediated by contrast-driven signals. Instead, these results are consistent with models that propose that the facilitation of trajectory signals is achieved by a second-level network that chooses the strongest local motion signals and combines them if they occur in a spatio-temporal sequence consistent with a trajectory. These results parallel the lack of increased apparent contrast along a static contour made up of similarly oriented elements.
-
Combined hybrid functional and DFT+U calculations for metal chalcogenides
DOE Office of Scientific and Technical Information (OSTI.GOV)
Aras, Mehmet; Kılıç, Çetin, E-mail: cetin-kilic@gyte.edu.tr
2014-07-28
In the density-functional studies of materials with localized electronic states, the local/semilocal exchange-correlation functionals are often either combined with a Hubbard parameter U as in the LDA+U method or mixed with a fraction of exactly computed (Fock) exchange energy yielding a hybrid functional. Although some inaccuracies of the semilocal density approximations are thus fixed to a certain extent, the improvements are not sufficient to make the predictions agree with the experimental data. Here, we put forward the perspective that the hybrid functional scheme and the LDA+U method should be treated as complementary, and propose to combine the range-separated Heyd-Scuseria-Ernzerhof (HSE)more » hybrid functional with the Hubbard U. We thus present a variety of HSE+U calculations for a set of II-VI semiconductors, consisting of zinc and cadmium monochalcogenides, along with comparison to the experimental data. Our findings imply that an optimal value U{sup *} of the Hubbard parameter could be determined, which ensures that the HSE+U{sup *} calculation reproduces the experimental band gap. It is shown that an improved description not only of the electronic structure but also of the crystal structure and energetics is obtained by adding the U{sup *} term to the HSE functional, proving the utility of HSE+U{sup *} approach in modeling semiconductors with localized electronic states.« less
-
Benkert, Pascal; Schwede, Torsten; Tosatto, Silvio Ce
2009-05-20
The selection of the most accurate protein model from a set of alternatives is a crucial step in protein structure prediction both in template-based and ab initio approaches. Scoring functions have been developed which can either return a quality estimate for a single model or derive a score from the information contained in the ensemble of models for a given sequence. Local structural features occurring more frequently in the ensemble have a greater probability of being correct. Within the context of the CASP experiment, these so called consensus methods have been shown to perform considerably better in selecting good candidate models, but tend to fail if the best models are far from the dominant structural cluster. In this paper we show that model selection can be improved if both approaches are combined by pre-filtering the models used during the calculation of the structural consensus. Our recently published QMEAN composite scoring function has been improved by including an all-atom interaction potential term. The preliminary model ranking based on the new QMEAN score is used to select a subset of reliable models against which the structural consensus score is calculated. This scoring function called QMEANclust achieves a correlation coefficient of predicted quality score and GDT_TS of 0.9 averaged over the 98 CASP7 targets and perform significantly better in selecting good models from the ensemble of server models than any other groups participating in the quality estimation category of CASP7. Both scoring functions are also benchmarked on the MOULDER test set consisting of 20 target proteins each with 300 alternatives models generated by MODELLER. QMEAN outperforms all other tested scoring functions operating on individual models, while the consensus method QMEANclust only works properly on decoy sets containing a certain fraction of near-native conformations. We also present a local version of QMEAN for the per-residue estimation of model quality (QMEANlocal) and compare it to a new local consensus-based approach. Improved model selection is obtained by using a composite scoring function operating on single models in order to enrich higher quality models which are subsequently used to calculate the structural consensus. The performance of consensus-based methods such as QMEANclust highly depends on the composition and quality of the model ensemble to be analysed. Therefore, performance estimates for consensus methods based on large meta-datasets (e.g. CASP) might overrate their applicability in more realistic modelling situations with smaller sets of models based on individual methods.
-
Leurer, Klaus C; Brown, Colin
2008-04-01
This paper presents a model of acoustic wave propagation in unconsolidated marine sediment, including compaction, using a concept of a simplified sediment structure, modeled as a binary grain-size sphere pack. Compressional- and shear-wave velocities and attenuation follow from a combination of Biot's model, used as the general framework, and two viscoelastic extensions resulting in complex grain and frame moduli, respectively. An effective-grain model accounts for the viscoelasticity arising from local fluid flow in expandable clay minerals in clay-bearing sediments. A viscoelastic-contact model describes local fluid flow at the grain contacts. Porosity, density, and the structural Biot parameters (permeability, pore size, structure factor) as a function of pressure follow from the binary model, so that the remaining input parameters to the acoustic model consist solely of the mass fractions and the known mechanical properties of each constituent (e.g., carbonates, sand, clay, and expandable clay) of the sediment, effective pressure, or depth, and the environmental parameters (water depth, salinity, temperature). Velocity and attenuation as a function of pressure from the model are in good agreement with data on coarse- and fine-grained unconsolidated marine sediments.
-
Wang, Bao-Zhen; Chen, Zhi
2013-01-01
This article presents a GIS-based multi-source and multi-box modeling approach (GMSMB) to predict the spatial concentration distributions of airborne pollutant on local and regional scales. In this method, an extended multi-box model combined with a multi-source and multi-grid Gaussian model are developed within the GIS framework to examine the contributions from both point- and area-source emissions. By using GIS, a large amount of data including emission sources, air quality monitoring, meteorological data, and spatial location information required for air quality modeling are brought into an integrated modeling environment. It helps more details of spatial variation in source distribution and meteorological condition to be quantitatively analyzed. The developed modeling approach has been examined to predict the spatial concentration distribution of four air pollutants (CO, NO(2), SO(2) and PM(2.5)) for the State of California. The modeling results are compared with the monitoring data. Good agreement is acquired which demonstrated that the developed modeling approach could deliver an effective air pollution assessment on both regional and local scales to support air pollution control and management planning.
-
Sazonovas, A; Japertas, P; Didziapetris, R
2010-01-01
This study presents a new type of acute toxicity (LD(50)) prediction that enables automated assessment of the reliability of predictions (which is synonymous with the assessment of the Model Applicability Domain as defined by the Organization for Economic Cooperation and Development). Analysis involved nearly 75,000 compounds from six animal systems (acute rat toxicity after oral and intraperitoneal administration; acute mouse toxicity after oral, intraperitoneal, intravenous, and subcutaneous administration). Fragmental Partial Least Squares (PLS) with 100 bootstraps yielded baseline predictions that were automatically corrected for non-linear effects in local chemical spaces--a combination called Global, Adjusted Locally According to Similarity (GALAS) modelling methodology. Each prediction obtained in this manner is provided with a reliability index value that depends on both compound's similarity to the training set (that accounts for similar trends in LD(50) variations within multiple bootstraps) and consistency of experimental results with regard to the baseline model in the local chemical environment. The actual performance of the Reliability Index (RI) was proven by its good (and uniform) correlations with Root Mean Square Error (RMSE) in all validation sets, thus providing quantitative assessment of the Model Applicability Domain. The obtained models can be used for compound screening in the early stages of drug development and prioritization for experimental in vitro testing or later in vivo animal acute toxicity studies.
-
Wang, Gui-Bin; Long, Wei; Li, Xiao-Dong; Xu, Guang-Yin; Lu, Ji-Xiang
2017-01-01
BACKGROUND To investigate the effect that dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has on surgical decision making relative to video-electroencephalography (VEEG) and positron emission tomography-computed tomography (PET-CT), and if the differences in these variables translates to differences in surgical outcomes. MATERIAL AND METHODS A total of 166 children with epilepsy undergoing preoperative DCE-MRI, VEEG, and PET-CT examinations, surgical resection of epileptic foci, and intraoperative electrocorticography (ECoG) monitoring were enrolled. All children were followed up for 12 months and grouped by Engles prognostic classification for epilepsy. Based on intraoperative ECoG as gold standard, the diagnostic values of DCE-MRI, VEEG, PET-CT, DCE-MRI combined with VEEG, DCE-MRI combined with PET-CT, and combined application of DCE-MRI, VEEG, and PET-CT in preoperative localization for epileptic foci were evaluated. RESULTS The sensitivity of DCE-MRI, VEEG, and PET-CT was 59.64%, 76.51%, and 93.98%, respectively; the accuracy of DCE-MRI, VEEG, PET-CT, DCE-MRI combined with VEEG, and DCE-MRI combined with PET-CT was 57.58%, 67.72%, 91.03%, 91.23%, and 96.49%, respectively. Localization accuracy rate of the combination of DCE-MRI, VEEG, and PET-CT was 98.25% (56/57), which was higher than that of DCE-MRI combined with VEEG and of DCE-MRI combined with PET-CT. No statistical difference was found in the accuracy rate of localization between these three combined techniques. During the 12-month follow-up, children were grouped into Engles grade I (n=106), II (n=31), III (n=21), and IV (n=8) according to postoperative conditions. CONCLUSIONS All DCE-MRI combined with VEEG, DCE-MRI combined with PET-CT, and DCE-MRI combined with VEEG and PET-CT examinations have excellent accuracy in preoperative localization of epileptic foci and present excellent postoperative efficiency, suggesting that these combined imaging methods are suitable for serving as the reference basis in preoperative localization of epileptic foci in children with epilepsy.
-
Using a NIATx based local learning collaborative for performance improvement
Roosa, Mathew; Scripa, Joseph S.; Zastowny, Thomas R.; Ford, James H.
2012-01-01
Local governments play an important role in improving substance abuse and mental health services. The structure of the local learning collaborative requires careful attention to old relationships and challenges local governmental leaders to help move participants from a competitive to collaborative environment. This study describes one county’s experience applying the NIATx process improvement model via a local learning collaborative. Local substance abuse and mental health agencies participated in two local learning collaboratives designed to improve client retention in substance abuse treatment and client access to mental health services. Results of changes implemented at the provider level on access and retention are outlined. The process of implementing evidence-based practices by using the Plan-Do-Study-Act rapid-cycle change is a powerful combination for change at the local level. Key lessons include: creating a clear plan and shared vision, recognizing that one size does not fit all, using data can help fuel participant engagement, a long collaborative may benefit from breaking it into smaller segments, and paying providers to offset costs of participation enhances their engagement. The experience gained in Onondaga County, New York, offers insights that serve as a foundation for using the local learning collaborative in other community-based organizations. PMID:21371751
-
Local dark matter and dark energy as estimated on a scale of ~1 Mpc in a self-consistent way
NASA Astrophysics Data System (ADS)
Chernin, A. D.; Teerikorpi, P.; Valtonen, M. J.; Dolgachev, V. P.; Domozhilova, L. M.; Byrd, G. G.
2009-12-01
Context: Dark energy was first detected from large distances on gigaparsec scales. If it is vacuum energy (or Einstein's Λ), it should also exist in very local space. Here we discuss its measurement on megaparsec scales of the Local Group. Aims: We combine the modified Kahn-Woltjer method for the Milky Way-M 31 binary and the HST observations of the expansion flow around the Local Group in order to study in a self-consistent way and simultaneously the local density of dark energy and the dark matter mass contained within the Local Group. Methods: A theoretical model is used that accounts for the dynamical effects of dark energy on a scale of ~1 Mpc. Results: The local dark energy density is put into the range 0.8-3.7ρv (ρv is the globally measured density), and the Local Group mass lies within 3.1-5.8×1012 M⊙. The lower limit of the local dark energy density, about 4/5× the global value, is determined by the natural binding condition for the group binary and the maximal zero-gravity radius. The near coincidence of two values measured with independent methods on scales differing by ~1000 times is remarkable. The mass ~4×1012 M⊙ and the local dark energy density ~ρv are also consistent with the expansion flow close to the Local Group, within the standard cosmological model. Conclusions: One should take into account the dark energy in dynamical mass estimation methods for galaxy groups, including the virial theorem. Our analysis gives new strong evidence in favor of Einstein's idea of the universal antigravity described by the cosmological constant.
-
Meirovitch, Eva; Shapiro, Yury E.; Polimeno, Antonino; Freed, Jack H.
2009-01-01
15N-1H spin relaxation is a powerful method for deriving information on protein dynamics. The traditional method of data analysis is model-free (MF), where the global and local N-H motions are independent and the local geometry is simplified. The common MF analysis consists of fitting single-field data. The results are typically field-dependent, and multi-field data cannot be fit with standard fitting schemes. Cases where known functional dynamics has not been detected by MF were identified by us and others. Recently we applied to spin relaxation in proteins the Slowly Relaxing Local Structure (SRLS) approach which accounts rigorously for mode-mixing and general features of local geometry. SRLS was shown to yield MF in appropriate asymptotic limits. We found that the experimental spectral density corresponds quite well to the SRLS spectral density. The MF formulae are often used outside of their validity ranges, allowing small data sets to be force-fitted with good statistics but inaccurate best-fit parameters. This paper focuses on the mechanism of force-fitting and its implications. It is shown that MF force-fits the experimental data because mode-mixing, the rhombic symmetry of the local ordering and general features of local geometry are not accounted for. Combined multi-field multi-temperature data analyzed by MF may lead to the detection of incorrect phenomena, while conformational entropy derived from MF order parameters may be highly inaccurate. On the other hand, fitting to more appropriate models can yield consistent physically insightful information. This requires that the complexity of the theoretical spectral densities matches the integrity of the experimental data. As shown herein, the SRLS densities comply with this requirement. PMID:16821820
-
Wang, Xian; Xu, Shiqin; Qin, Xiang; Li, Xiaohong; Feng, Shan-Wu; Liu, Yusheng; Wang, Wei; Guo, Xirong; Shen, Rong; Shen, Xiaofeng; Wang, Fuzhou
2015-01-01
Abstract To compare the analgesic efficacy and safety of the sole local anesthetic ropivacaine with the combination of both local anesthetic ropivacaine and opioidergic analgesic sufentanil given epidurally on the labor pain control. After institutional review board approval and patient consent, a total of 500 nulliparas requesting epidural labor analgesia were enrolled and 481 eventually were randomized into 2 groups: a sole local anesthetic group (ropivacaine 0.125%) and a combination of local anesthetic and opioidergic analgesic group (0.125% ropivacaine + 0.3 μg/mL sufentanil). After the test dose, a 10-mL epidural analgesic solution was given in a single bolus, followed by intermittent bolus injection of 10 to 15 mL of the solution. The primary outcome was the analgesic efficacy measured using Numerical Rating Scale (NRS) of pain. Other maternal and infant variables were evaluated as secondary outcomes. A total of 346 participants completed the study. The median NRS pain score during the 1st stage of labor was significantly lower in the combination group 2.2 (interquartile range [IQR]: 1.8–2.7) comparing to the sole local analgesic group 2.4 (IQR: 2.0–2.8) (P < 0.0001). No significant difference was observed in NRS pain score prior epidural analgesia and during the 2nd stage of labor. Patients in both groups rated same satisfaction of analgesia. Patients in the sole local analgesic group experienced fewer side effects than those in the combination group (37.7% vs 47.2%, P = 0.082). The individual analgesia-related cost in the sole local analgesic group was less ($5.7 ± 2.06) than that in the combination group ($9.76 ± 3.54) (P < 0.0001). The incidence of 1-minute Apgar ≤ 7 was lower in the sole local analgesic group 2 (1.2%) than the combination group 10 (5.5%) (P = 0.038). No difference was found between other secondary outcomes. The sole local anesthetic ropivacaine produces a comparable labor analgesic effect as the combination of both local anesthetic ropivacaine and opioidergic analgesic sufentanil at different stages of labor (ΔNRS = 0.2) but the former has less side effects, lower cost, and less incidence of lower 1-minute Apgar scoring. These results imply the necessity of a systematic reevaluation of epidural labor analgesia with sole local anesthetics against combination regimens of local anesthetics and other opioids. PMID:26512604
-
Wang, Xian; Xu, Shiqin; Qin, Xiang; Li, Xiaohong; Feng, Shan-Wu; Liu, Yusheng; Wang, Wei; Guo, Xirong; Shen, Rong; Shen, Xiaofeng; Wang, Fuzhou
2015-10-01
To compare the analgesic efficacy and safety of the sole local anesthetic ropivacaine with the combination of both local anesthetic ropivacaine and opioidergic analgesic sufentanil given epidurally on the labor pain control.After institutional review board approval and patient consent, a total of 500 nulliparas requesting epidural labor analgesia were enrolled and 481 eventually were randomized into 2 groups: a sole local anesthetic group (ropivacaine 0.125%) and a combination of local anesthetic and opioidergic analgesic group (0.125% ropivacaine + 0.3 μg/mL sufentanil). After the test dose, a 10-mL epidural analgesic solution was given in a single bolus, followed by intermittent bolus injection of 10 to 15 mL of the solution. The primary outcome was the analgesic efficacy measured using Numerical Rating Scale (NRS) of pain. Other maternal and infant variables were evaluated as secondary outcomes.A total of 346 participants completed the study. The median NRS pain score during the 1st stage of labor was significantly lower in the combination group 2.2 (interquartile range [IQR]: 1.8-2.7) comparing to the sole local analgesic group 2.4 (IQR: 2.0-2.8) (P < 0.0001). No significant difference was observed in NRS pain score prior epidural analgesia and during the 2nd stage of labor. Patients in both groups rated same satisfaction of analgesia. Patients in the sole local analgesic group experienced fewer side effects than those in the combination group (37.7% vs 47.2%, P = 0.082). The individual analgesia-related cost in the sole local analgesic group was less ($5.7 ± 2.06) than that in the combination group ($9.76 ± 3.54) (P < 0.0001). The incidence of 1-minute Apgar ≤ 7 was lower in the sole local analgesic group 2 (1.2%) than the combination group 10 (5.5%) (P = 0.038). No difference was found between other secondary outcomes.The sole local anesthetic ropivacaine produces a comparable labor analgesic effect as the combination of both local anesthetic ropivacaine and opioidergic analgesic sufentanil at different stages of labor (ΔNRS = 0.2) but the former has less side effects, lower cost, and less incidence of lower 1-minute Apgar scoring. These results imply the necessity of a systematic reevaluation of epidural labor analgesia with sole local anesthetics against combination regimens of local anesthetics and other opioids.
-
NASA Astrophysics Data System (ADS)
Djuwendah, E.; Priyatna, T.; Kusno, K.; Deliana, Y.; Wulandari, E.
2018-03-01
Building agribusiness model of LEISA is needed as a prototype of sustainable regional and economic development (SRRED) in the watersheds (DAS) of West Java Province. Agribusiness model of LEISA is a sustainable agribusiness system applying low external input. The system was developed in the framework of optimizing local-based productive resources including soil, water, vegetation, microclimate, renewable energy, appropriate technology, social capital, environment and human resources by combining various subsystems including integrated production subsystems of crops, livestock and fish to provide a maximum synergy effect, post-harvest subsystem and processing of results, marketing subsystems and supporting subsystems. In this study, the ecological boundary of Cipunegara sub-watershed ecosystem, administrative boundaries are Surian Subdistricts in Sumedang. The purpose of this study are to identify the potency of natural resources and local agricultural technologies that could support the LEISA model in Surian and to identify the potency of internal and external inputs in the LEISA model. The research used qualitative descriptive method and technical action research. Data were obtained through interviews, documentation, and observation. The results showed that natural resources in the form of agricultural land, water resources, livestock resources, and human labor are sufficient to support agribusiness model of LEISA. LEISA agribusiness model that has been applied in the research location is the integration of beef cattle, agroforestry, and agrosilvopasture. By building LEISA model, agribusiness can optimize the utilization of locally based productive resources, reduce dependence on external resources, and support sustainable food security.
-
Combining multiple earthquake models in real time for earthquake early warning
Minson, Sarah E.; Wu, Stephen; Beck, James L; Heaton, Thomas H.
2017-01-01
The ultimate goal of earthquake early warning (EEW) is to provide local shaking information to users before the strong shaking from an earthquake reaches their location. This is accomplished by operating one or more real‐time analyses that attempt to predict shaking intensity, often by estimating the earthquake’s location and magnitude and then predicting the ground motion from that point source. Other EEW algorithms use finite rupture models or may directly estimate ground motion without first solving for an earthquake source. EEW performance could be improved if the information from these diverse and independent prediction models could be combined into one unified, ground‐motion prediction. In this article, we set the forecast shaking at each location as the common ground to combine all these predictions and introduce a Bayesian approach to creating better ground‐motion predictions. We also describe how this methodology could be used to build a new generation of EEW systems that provide optimal decisions customized for each user based on the user’s individual false‐alarm tolerance and the time necessary for that user to react.
-
Model-based analysis of pattern motion processing in mouse primary visual cortex
Muir, Dylan R.; Roth, Morgane M.; Helmchen, Fritjof; Kampa, Björn M.
2015-01-01
Neurons in sensory areas of neocortex exhibit responses tuned to specific features of the environment. In visual cortex, information about features such as edges or textures with particular orientations must be integrated to recognize a visual scene or object. Connectivity studies in rodent cortex have revealed that neurons make specific connections within sub-networks sharing common input tuning. In principle, this sub-network architecture enables local cortical circuits to integrate sensory information. However, whether feature integration indeed occurs locally in rodent primary sensory areas has not been examined directly. We studied local integration of sensory features in primary visual cortex (V1) of the mouse by presenting drifting grating and plaid stimuli, while recording the activity of neuronal populations with two-photon calcium imaging. Using a Bayesian model-based analysis framework, we classified single-cell responses as being selective for either individual grating components or for moving plaid patterns. Rather than relying on trial-averaged responses, our model-based framework takes into account single-trial responses and can easily be extended to consider any number of arbitrary predictive models. Our analysis method was able to successfully classify significantly more responses than traditional partial correlation (PC) analysis, and provides a rigorous statistical framework to rank any number of models and reject poorly performing models. We also found a large proportion of cells that respond strongly to only one stimulus class. In addition, a quarter of selectively responding neurons had more complex responses that could not be explained by any simple integration model. Our results show that a broad range of pattern integration processes already take place at the level of V1. This diversity of integration is consistent with processing of visual inputs by local sub-networks within V1 that are tuned to combinations of sensory features. PMID:26300738
-
Implementation of a WRF-CMAQ Air Quality Modeling System in Bogotá, Colombia
NASA Astrophysics Data System (ADS)
Nedbor-Gross, R.; Henderson, B. H.; Pachon, J. E.; Davis, J. R.; Baublitz, C. B.; Rincón, A.
2014-12-01
Due to a continuous economic growth Bogotá, Colombia has experienced air pollution issues in recent years. The local environmental authority has implemented several strategies to curb air pollution that have resulted in the decrease of PM10 concentrations since 2010. However, more activities are necessary in order to meet international air quality standards in the city. The University of Florida Air Quality and Climate group is collaborating with the Universidad de La Salle to prioritize regulatory strategies for Bogotá using air pollution simulations. To simulate pollution, we developed a modeling platform that combines the Weather Research and Forecasting Model (WRF), local emissions, and the Community Multi-scale Air Quality model (CMAQ). This platform is the first of its kind to be implemented in the megacity of Bogota, Colombia. The presentation will discuss development and evaluation of the air quality modeling system, highlight initial results characterizing photochemical conditions in Bogotá, and characterize air pollution under proposed regulatory strategies. The WRF model has been configured and applied to Bogotá, which resides in a tropical climate with complex mountainous topography. Developing the configuration included incorporation of local topography and land-use data, a physics sensitivity analysis, review, and systematic evaluation. The threshold, however, was set based on synthesis of model performance under less mountainous conditions. We will evaluate the impact that differences in autocorrelation contribute to the non-ideal performance. Air pollution predictions are currently under way. CMAQ has been configured with WRF meteorology, global boundary conditions from GEOS-Chem, and a locally produced emission inventory. Preliminary results from simulations show promising performance of CMAQ in Bogota. Anticipated results include a systematic performance evaluation of ozone and PM10, characterization of photochemical sensitivity, and air quality predictions under proposed regulatory scenarios.
-
There Are No Subways in Lickingville: Metropolitan Models Don't Work for Rural People.
ERIC Educational Resources Information Center
Hillman, Arnold
This book presents an overview of the problems facing rural America and offers solutions at the national, state, and local levels. The combination of public lack of awareness and metropolitan-centered authority has created a view of rural America and its people that is contrary to both the data and actual living conditions. Rural education has…
-
Zhang, Xuming; Ren, Jinxia; Huang, Zhiwen; Zhu, Fei
2016-01-01
Multimodal medical image fusion (MIF) plays an important role in clinical diagnosis and therapy. Existing MIF methods tend to introduce artifacts, lead to loss of image details or produce low-contrast fused images. To address these problems, a novel spiking cortical model (SCM) based MIF method has been proposed in this paper. The proposed method can generate high-quality fused images using the weighting fusion strategy based on the firing times of the SCM. In the weighting fusion scheme, the weight is determined by combining the entropy information of pulse outputs of the SCM with the Weber local descriptor operating on the firing mapping images produced from the pulse outputs. The extensive experiments on multimodal medical images show that compared with the numerous state-of-the-art MIF methods, the proposed method can preserve image details very well and avoid the introduction of artifacts effectively, and thus it significantly improves the quality of fused images in terms of human vision and objective evaluation criteria such as mutual information, edge preservation index, structural similarity based metric, fusion quality index, fusion similarity metric and standard deviation. PMID:27649190
-
Zhang, Xuming; Ren, Jinxia; Huang, Zhiwen; Zhu, Fei
2016-09-15
Multimodal medical image fusion (MIF) plays an important role in clinical diagnosis and therapy. Existing MIF methods tend to introduce artifacts, lead to loss of image details or produce low-contrast fused images. To address these problems, a novel spiking cortical model (SCM) based MIF method has been proposed in this paper. The proposed method can generate high-quality fused images using the weighting fusion strategy based on the firing times of the SCM. In the weighting fusion scheme, the weight is determined by combining the entropy information of pulse outputs of the SCM with the Weber local descriptor operating on the firing mapping images produced from the pulse outputs. The extensive experiments on multimodal medical images show that compared with the numerous state-of-the-art MIF methods, the proposed method can preserve image details very well and avoid the introduction of artifacts effectively, and thus it significantly improves the quality of fused images in terms of human vision and objective evaluation criteria such as mutual information, edge preservation index, structural similarity based metric, fusion quality index, fusion similarity metric and standard deviation.
-
A simple Lagrangian forecast system with aviation forecast potential
NASA Technical Reports Server (NTRS)
Petersen, R. A.; Homan, J. H.
1983-01-01
A trajectory forecast procedure is developed which uses geopotential tendency fields obtained from a simple, multiple layer, potential vorticity conservative isentropic model. This model can objectively account for short-term advective changes in the mass field when combined with fine-scale initial analyses. This procedure for producing short-term, upper-tropospheric trajectory forecasts employs a combination of a detailed objective analysis technique, an efficient mass advection model, and a diagnostically proven trajectory algorithm, none of which require extensive computer resources. Results of initial tests are presented, which indicate an exceptionally good agreement for trajectory paths entering the jet stream and passing through an intensifying trough. It is concluded that this technique not only has potential for aiding in route determination, fuel use estimation, and clear air turbulence detection, but also provides an example of the types of short range forecasting procedures which can be applied at local forecast centers using simple algorithms and a minimum of computer resources.
-
NASA Astrophysics Data System (ADS)
Apel, Heiko; Martínez Trepat, Oriol; Nghia Hung, Nguyen; Thi Chinh, Do; Merz, Bruno; Viet Dung, Nguyen
2016-04-01
Many urban areas experience both fluvial and pluvial floods, because locations next to rivers are preferred settlement areas and the predominantly sealed urban surface prevents infiltration and facilitates surface inundation. The latter problem is enhanced in cities with insufficient or non-existent sewer systems. While there are a number of approaches to analyse either a fluvial or pluvial flood hazard, studies of a combined fluvial and pluvial flood hazard are hardly available. Thus this study aims to analyse a fluvial and a pluvial flood hazard individually, but also to develop a method for the analysis of a combined pluvial and fluvial flood hazard. This combined fluvial-pluvial flood hazard analysis is performed taking Can Tho city, the largest city in the Vietnamese part of the Mekong Delta, as an example. In this tropical environment the annual monsoon triggered floods of the Mekong River, which can coincide with heavy local convective precipitation events, causing both fluvial and pluvial flooding at the same time. The fluvial flood hazard was estimated with a copula-based bivariate extreme value statistic for the gauge Kratie at the upper boundary of the Mekong Delta and a large-scale hydrodynamic model of the Mekong Delta. This provided the boundaries for 2-dimensional hydrodynamic inundation simulation for Can Tho city. The pluvial hazard was estimated by a peak-over-threshold frequency estimation based on local rain gauge data and a stochastic rainstorm generator. Inundation for all flood scenarios was simulated by a 2-dimensional hydrodynamic model implemented on a Graphics Processing Unit (GPU) for time-efficient flood propagation modelling. The combined fluvial-pluvial flood scenarios were derived by adding rainstorms to the fluvial flood events during the highest fluvial water levels. The probabilities of occurrence of the combined events were determined assuming independence of the two flood types and taking the seasonality and probability of coincidence into account. All hazards - fluvial, pluvial and combined - were accompanied by an uncertainty estimation taking into account the natural variability of the flood events. This resulted in probabilistic flood hazard maps showing the maximum inundation depths for a selected set of probabilities of occurrence, with maps showing the expectation (median) and the uncertainty by percentile maps. The results are critically discussed and their usage in flood risk management are outlined.
-
Azmi, Asfar S.; Banerjee, Sanjeev; Ali, Shadan; Wang, Zhiwei; Bao, Bin; Beck, Frances W.J.; Maitah, Main; Choi, Minsig; Shields, Tony F.; Philip, Philip A.; Sarkar, Fazlul H.; Mohammad, Ramzi M.
2011-01-01
Earlier we had shown that the MDM2 inhibitor (MI-219) belonging to the spiro-oxindole family can synergistically enhance the efficacy of platinum chemotherapeutics leading to 50% tumor free survival in a genetically complex pancreatic ductal adenocarcinoma (PDAC) xenograft model. In this report, we have taken a systems and network modeling approach in order to understand central mechanisms behind MI219-oxaliplatin synergy with validation in PDAC, colon and breast cancer cell lines. Microarray profiling of drug treatments (MI-219, oxaliplatin or their combination) in capan-2 cells reveal a similar unique set of gene alterations that is duplicated in other solid tumor cells. As single agent, MI-219 or oxaliplatin induced alterations in 48 and 761 genes respectively. The combination treatment resulted in 767 gene alterations with emergence of 286 synergy unique genes. Ingenuity network modeling of combination and synergy unique genes showed the crucial role of five key local networks CREB, CARF, EGR1, NF-kB and E Cadherin. The network signatures were validated at the protein level in all three cell lines. Individually silencing central nodes in these five hubs resulted in abrogation of MI-219-oxaliplatin activity confirming their critical role in aiding p53 mediated apoptotic response. We anticipate that our MI219-oxaliplatin network blueprints can be clinically translated in the rationale design and application of this unique therapeutic combination in a genetically pre-defined subset of patients. PMID:21623005
-
Choice vs. voice? PPI policies and the re‐positioning of the state in England and Wales
Hughes, David; Mullen, Caroline; Vincent‐Jones, Peter
2009-01-01
Abstract Context and Thesis Changing patient and public involvement (PPI) policies in England and Wales are analysed against the background of wider National Health Service (NHS) reforms and regulatory frameworks. We argue that the growing divergence of health policies is accompanied by a re‐positioning of the state vis‐à‐vis PPI, characterized by different mixes of centralized and decentralized regulatory instruments. Method Analysis of legislation and official documents, and interviews with policy makers. Findings In England, continued hierarchical control is combined with the delegation of responsibilities for the oversight and organization of PPI to external institutions such as the Care Quality Commission and local involvement networks, in support of the government’s policy agenda of increasing marketization. In Wales, which has rejected market reforms and economic regulation, decentralization is occurring through the use of mixed regulatory approaches and networks suited to the small‐country governance model, and seeks to benefit from the close proximity of central and local actors by creating new forms of engagement while maintaining central steering of service planning. Whereas English PPI policies have emerged in tandem with a pluralistic supply‐side market and combine new institutional arrangements for patient ‘choice’ with other forms of involvement, the Welsh policies focus on ‘voice’ within a largely publicly‐delivered service. Discussion While the English reforms draw on theories of economic regulation and the experience of independent regulation in the utilities sector, the Welsh model of local service integration has been more influenced by reforms in local government. Such transfers of governance instruments from other public service sectors to the NHS may be problematic. PMID:19754688
-
Local richness along gradients in the Siskiyou herb flora: R.H. Whittaker revisited
Grace, James B.; Harrison, Susan; Damschen, Ellen Ingman
2011-01-01
In his classic study in the Siskiyou Mountains (Oregon, USA), one of the most botanically rich forested regions in North America, R. H. Whittaker (1960) foreshadowed many modern ideas on the multivariate control of local species richness along environmental gradients related to productivity. Using a structural equation model to analyze his data, which were never previously statistically analyzed, we demonstrate that Whittaker was remarkably accurate in concluding that local herb richness in these late-seral forests is explained to a large extent by three major abiotic gradients (soils, topography, and elevation), and in turn, by the effects of these gradients on tree densities and the numbers of individual herbs. However, while Whittaker also clearly appreciated the significance of large-scale evolutionary and biogeographic influences on community composition, he did not fully articulate the more recent concept that variation in the species richness of local communities could be explained in part by variation in the sizes of regional species pools. Our model of his data is among the first to use estimates of regional species pool size to explain variation in local community richness along productivity-related gradients. We find that regional pool size, combined with a modest number of other interacting abiotic and biotic factors, explains most of the variation in local herb richness in the Siskiyou biodiversity hotspot.
-
Event-Ready Bell Test Using Entangled Atoms Simultaneously Closing Detection and Locality Loopholes
NASA Astrophysics Data System (ADS)
Rosenfeld, Wenjamin; Burchardt, Daniel; Garthoff, Robert; Redeker, Kai; Ortegel, Norbert; Rau, Markus; Weinfurter, Harald
2017-07-01
An experimental test of Bell's inequality allows ruling out any local-realistic description of nature by measuring correlations between distant systems. While such tests are conceptually simple, there are strict requirements concerning the detection efficiency of the involved measurements, as well as the enforcement of spacelike separation between the measurement events. Only very recently could both loopholes be closed simultaneously. Here we present a statistically significant, event-ready Bell test based on combining heralded entanglement of atoms separated by 398 m with fast and efficient measurements of the atomic spin states closing essential loopholes. We obtain a violation with S =2.221 ±0.033 (compared to the maximal value of 2 achievable with models based on local hidden variables) which allows us to refute the hypothesis of local realism with a significance level P <2.57 ×10-9.