Modeling Musical Context With Word2Vec

NASA Astrophysics Data System (ADS)

Herremans, Dorien; Chuan, Ching-Hua

2017-05-01

We present a semantic vector space model for capturing complex polyphonic musical context. A word2vec model based on a skip-gram representation with negative sampling was used to model slices of music from a dataset of Beethoven's piano sonatas. A visualization of the reduced vector space using t-distributed stochastic neighbor embedding shows that the resulting embedded vector space captures tonal relationships, even without any explicit information about the musical contents of the slices. Secondly, an excerpt of the Moonlight Sonata from Beethoven was altered by replacing slices based on context similarity. The resulting music shows that the selected slice based on similar word2vec context also has a relatively short tonal distance from the original slice.

Parametric and non-parametric modeling of short-term synaptic plasticity. Part I: computational study

PubMed Central

Marmarelis, Vasilis Z.; Berger, Theodore W.

2009-01-01

Parametric and non-parametric modeling methods are combined to study the short-term plasticity (STP) of synapses in the central nervous system (CNS). The nonlinear dynamics of STP are modeled by means: (1) previously proposed parametric models based on mechanistic hypotheses and/or specific dynamical processes, and (2) non-parametric models (in the form of Volterra kernels) that transforms the presynaptic signals into postsynaptic signals. In order to synergistically use the two approaches, we estimate the Volterra kernels of the parametric models of STP for four types of synapses using synthetic broadband input–output data. Results show that the non-parametric models accurately and efficiently replicate the input–output transformations of the parametric models. Volterra kernels provide a general and quantitative representation of the STP. PMID:18506609

Lesion detection performance of cone beam CT images with anatomical background noise: single-slice vs. multi-slice human and model observer study

NASA Astrophysics Data System (ADS)

Han, Minah; Jang, Hanjoo; Baek, Jongduk

2018-03-01

We investigate lesion detectability and its trends for different noise structures in single-slice and multislice CBCT images with anatomical background noise. Anatomical background noise is modeled using a power law spectrum of breast anatomy. Spherical signal with a 2 mm diameter is used for modeling a lesion. CT projection data are acquired by the forward projection and reconstructed by the Feldkamp-Davis-Kress algorithm. To generate different noise structures, two types of reconstruction filters (Hanning and Ram-Lak weighted ramp filters) are used in the reconstruction, and the transverse and longitudinal planes of reconstructed volume are used for detectability evaluation. To evaluate single-slice images, the central slice, which contains the maximum signal energy, is used. To evaluate multislice images, central nine slices are used. Detectability is evaluated using human and model observer studies. For model observer, channelized Hotelling observer (CHO) with dense difference-of-Gaussian (D-DOG) channels are used. For all noise structures, detectability by a human observer is higher for multislice images than single-slice images, and the degree of detectability increase in multislice images depends on the noise structure. Variation in detectability for different noise structures is reduced in multislice images, but detectability trends are not much different between single-slice and multislice images. The CHO with D-DOG channels predicts detectability by a human observer well for both single-slice and multislice images.

Improved biochemical preservation of lung slices during cold storage.

PubMed

Bull, D A; Connors, R C; Reid, B B; Albanil, A; Stringham, J C; Karwande, S V

2000-05-15

Development of lung preservation solutions typically requires whole-organ models which are animal and labor intensive. These models rely on physiologic rather than biochemical endpoints, making accurate comparison of the relative efficacy of individual solution components difficult. We hypothesized that lung slices could be used to assess preservation of biochemical function during cold storage. Whole rat lungs were precision cut into slices with a thickness of 500 microm and preserved at 4 degrees C in the following solutions: University of Wisconsin (UW), Euro-Collins (EC), low-potassium-dextran (LPD), Kyoto (K), normal saline (NS), or a novel lung preservation solution (NPS) developed using this model. Lung biochemical function was assessed by ATP content (etamol ATP/mg wet wt) and capacity for protein synthesis (cpm/mg protein) immediately following slicing (0 h) and at 6, 12, 18, and 24 h of cold storage. Six slices were assayed at each time point for each solution. The data were analyzed using analysis of variance and are presented as means +/- SD. ATP content was significantly higher in the lung slices stored in NPS compared with all other solutions at each time point (P < 0.0001). Protein synthesis was significantly higher in the lung slices stored in NPS compared with all other solutions at 6, 12, and 18 h of preservation (P < 0.05). This lung slice model allows the rapid and efficient screening of lung preservation solutions and their components using quantifiable biochemical endpoints. Using this model, we have developed a novel solution that improves the biochemical preservation of lung slices during cold storage. Copyright 2000 Academic Press.

White matter atlas of the human spinal cord with estimation of partial volume effect.

PubMed

Lévy, S; Benhamou, M; Naaman, C; Rainville, P; Callot, V; Cohen-Adad, J

2015-10-01

Template-based analysis has proven to be an efficient, objective and reproducible way of extracting relevant information from multi-parametric MRI data. Using common atlases, it is possible to quantify MRI metrics within specific regions without the need for manual segmentation. This method is therefore free from user-bias and amenable to group studies. While template-based analysis is common procedure for the brain, there is currently no atlas of the white matter (WM) spinal pathways. The goals of this study were: (i) to create an atlas of the white matter tracts compatible with the MNI-Poly-AMU template and (ii) to propose methods to quantify metrics within the atlas that account for partial volume effect. The WM atlas was generated by: (i) digitalizing an existing WM atlas from a well-known source (Gray's Anatomy), (ii) registering this atlas to the MNI-Poly-AMU template at the corresponding slice (C4 vertebral level), (iii) propagating the atlas throughout all slices of the template (C1 to T6) using regularized diffeomorphic transformations and (iv) computing partial volume values for each voxel and each tract. Several approaches were implemented and validated to quantify metrics within the atlas, including weighted-average and Gaussian mixture models. Proof-of-concept application was done in five subjects for quantifying magnetization transfer ratio (MTR) in each tract of the atlas. The resulting WM atlas showed consistent topological organization and smooth transitions along the rostro-caudal axis. The median MTR across tracts was 26.2. Significant differences were detected across tracts, vertebral levels and subjects, but not across laterality (right-left). Among the different tested approaches to extract metrics, the maximum a posteriori showed highest performance with respect to noise, inter-tract variability, tract size and partial volume effect. This new WM atlas of the human spinal cord overcomes the biases associated with manual delineation and partial volume effect. Combined with multi-parametric data, the atlas can be applied to study demyelination and degeneration in diseases such as multiple sclerosis and will facilitate the conduction of longitudinal and multi-center studies. Copyright © 2015 Elsevier Inc. All rights reserved.

Development and characterization of an ex-vivo brain slice culture model of chronic wasting disease

USDA-ARS?s Scientific Manuscript database

Prion diseases have long incubation times in vivo, therefore, modeling the diseases ex-vivo will advance the development of rationale-based therapeutic strategies. An organotypic slice culture assay (POSCA) was recently developed for scrapie prions by inoculating mouse cerebellar brain slices with R...

Slice sampling technique in Bayesian extreme of gold price modelling

NASA Astrophysics Data System (ADS)

Rostami, Mohammad; Adam, Mohd Bakri; Ibrahim, Noor Akma; Yahya, Mohamed Hisham

2013-09-01

In this paper, a simulation study of Bayesian extreme values by using Markov Chain Monte Carlo via slice sampling algorithm is implemented. We compared the accuracy of slice sampling with other methods for a Gumbel model. This study revealed that slice sampling algorithm offers more accurate and closer estimates with less RMSE than other methods . Finally we successfully employed this procedure to estimate the parameters of Malaysia extreme gold price from 2000 to 2011.

Improved biochemical preservation of heart slices during cold storage.

PubMed

Bull, D A; Reid, B B; Connors, R C; Albanil, A; Stringham, J C; Karwande, S V

2000-01-01

Development of myocardial preservation solutions requires the use of whole organ models which are animal and labor intensive. These models rely on physiologic rather than biochemical endpoints, making accurate comparison of the relative efficacy of individual solution components difficult. We hypothesized that myocardial slices could be used to assess preservation of biochemical function during cold storage. Whole rat hearts were precision cut into slices with a thickness of 200 microm and preserved at 4 degrees C in one of the following solutions: Columbia University (CU), University of Wisconsin (UW), D5 0.2% normal saline with 20 meq/l KCL (QNS), normal saline (NS), or a novel cardiac preservation solution (NPS) developed using this model. Myocardial biochemical function was assessed by ATP content (etamoles ATP/mg wet weight) and capacity for protein synthesis (counts per minute (cpm)/mg protein) immediately following slicing (0 hours), and at 6, 12, 18, and 24 hours of cold storage. Six slices were assayed at each time point for each solution. The data were analyzed using analysis of variance and are presented as the mean +/- standard deviation. ATP content was higher in the heart slices stored in the NPS compared to all other solutions at 6, 12, 18 and 24 hours of cold storage (p < 0.05). Capacity for protein synthesis was higher in the heart slices stored in the NPS compared to all other solutions at 6, 12, and 18 hours of cold storage (p < 0.05). CONCLUSIONS This myocardial slice model allows the rapid and efficient screening of cardiac preservation solutions and their components using quantifiable biochemical endpoints. Using this model, we have developed a novel preservation solution which improves the biochemical function of myocardial slices during cold storage.

Effect of Carboxylmethyl Cellulose Coating and Osmotic Dehydration on Freeze Drying Kinetics of Apple Slices

PubMed Central

Rahimi, Jamshid; Singh, Ashutosh; Adewale, Peter Olusola; Adedeji, Akinbode A.; Ngadi, Michael O.; Raghavan, Vijaya

2013-01-01

The effect of different concentrations of sugar solution (hypertonic) (30%, 45% and 60% w/v) and carboxyl methyl cellulose (CMC) (0%, 1% and 2% w/v) coating on freeze drying of apple slices was studied. In total, nine treatments with respect to concentrations of hypertonic solution and coating layer were prepared to analyze their influence on the physical and chemical properties of freeze dried apple slices. It was observed that increase in the sugar solution concentration, decreased the moisture content of the apple slices significantly impacting its water activity, texture and sugar gain. Application of different concentrations of CMC coating had no significant effect on the properties of dried apple slices. A significant change was observed for color of CMC coated freeze dried apple slices pretreated with 60% sugar solution. Drying kinetics of pretreated apple slices were fitted by using two drying models, Newton’s and Page’s. Page’s model showed higher R-square and lower root mean square error (RSME) compared to Newton’s model. PMID:28239107

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

NASA Astrophysics Data System (ADS)

Chen, Weilin; Yang, Tao; Yang, Ruixin

2017-07-01

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

Real-time slicing algorithm for Stereolithography (STL) CAD model applied in additive manufacturing industry

NASA Astrophysics Data System (ADS)

Adnan, F. A.; Romlay, F. R. M.; Shafiq, M.

2018-04-01

Owing to the advent of the industrial revolution 4.0, the need for further evaluating processes applied in the additive manufacturing application particularly the computational process for slicing is non-trivial. This paper evaluates a real-time slicing algorithm for slicing an STL formatted computer-aided design (CAD). A line-plane intersection equation was applied to perform the slicing procedure at any given height. The application of this algorithm has found to provide a better computational time regardless the number of facet in the STL model. The performance of this algorithm is evaluated by comparing the results of the computational time for different geometry.

TU-EF-204-11: Impact of Using Multi-Slice Training Sets On the Performance of a Channelized Hotelling Observer in a Low-Contrast Detection Task in CT

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

Favazza, C; Yu, L; Leng, S

2015-06-15

Purpose: To investigate using multiple CT image slices from a single acquisition as independent training images for a channelized Hotelling observer (CHO) model to reduce the number of repeated scans for CHO-based CT image quality assessment. Methods: We applied a previously validated CHO model to detect low contrast disk objects formed from cross-sectional images of three epoxy-resin-based rods (diameters: 3, 5, and 9 mm; length: ∼5cm). The rods were submerged in a 35x 25 cm2 iodine-doped water filled phantom, yielding-15 HU object contrast. The phantom was scanned 100 times with and without the rods present. Scan and reconstruction parameters include:more » 5 mm slice thickness at 0.5 mm intervals, 120 kV, 480 Quality Reference mAs, and a 128-slice scanner. The CHO’s detectability index was evaluated as a function of factors related to incorporating multi-slice image data: object misalignment along the z-axis, inter-slice pixel correlation, and number of unique slice locations. In each case, the CHO training set was fixed to 100 images. Results: Artificially shifting the object’s center position by as much as 3 pixels in any direction relative to the Gabor channel filters had insignificant impact on object detectability. An inter-slice pixel correlation of >∼0.2 yielded positive bias in the model’s performance. Incorporating multi-slice image data yielded slight negative bias in detectability with increasing number of slices, likely due to physical variations in the objects. However, inclusion of image data from up to 5 slice locations yielded detectability indices within measurement error of the single slice value. Conclusion: For the investigated model and task, incorporating image data from 5 different slice locations of at least 5 mm intervals into the CHO model yielded detectability indices within measurement error of the single slice value. Consequently, this methodology would Result in a 5-fold reduction in number of image acquisitions. This project was supported by National Institutes of Health grants R01 EB017095 and U01 EB017185 from the National Institute of Biomedical Imaging and Bioengineering.« less

Fluidized bed drying characteristics and modeling of ginger ( zingiber officinale) slices

NASA Astrophysics Data System (ADS)

Parlak, Nezaket

2015-08-01

In this study fluidized bed drying characteristics of ginger have been investigated. The effects of the fluidizing air temperature, velocity, humidity and bed height on the drying performance of ginger slices have been found. The experimental moisture loss data of ginger slices has been fitted to the eight thin layer drying models. Two-term model drying model has shown a better fit to the experimental data with R2 of 0.998 as compared to others.

The mouse cerebellar cortex in organotypic slice cultures: an in vitro model to analyze the consequences of mutations and pathologies on neuronal survival, development, and function.

PubMed

Lonchamp, Etienne; Dupont, Jean-Luc; Beekenkamp, Huguette; Poulain, Bernard; Bossu, Jean-Louis

2006-01-01

Thin acute slices and dissociated cell cultures taken from different parts of the brain have been widely used to examine the function of the nervous system, neuron-specific interactions, and neuronal development (specifically, neurobiology, neuropharmacology, and neurotoxicology studies). Here, we focus on an alternative in vitro model: brain-slice cultures in roller tubes, initially introduced by Beat Gähwiler for studies with rats, that we have recently adapted for studies of mouse cerebellum. Cultured cerebellar slices afford many of the advantages of dissociated cultures of neurons and thin acute slices. Organotypic slice cultures were established from newborn or 10-15-day-old mice. After 3-4 weeks in culture, the slices flattened to form a cell monolayer. The main types of cerebellar neurons could be identified with immunostaining techniques, while their electrophysiological properties could be easily characterized with the patch-clamp recording technique. When slices were taken from newborn mice and cultured for 3 weeks, aspects of the cerebellar development were displayed. A functional neuronal network was established despite the absence of mossy and climbing fibers, which are the two excitatory afferent projections to the cerebellum. When slices were made from 10-15-day-old mice, which are at a developmental stage when cerebellum organization is almost established, the structure and neuronal pathways were intact after 3-4 weeks in culture. These unique characteristics make organotypic slice cultures of mouse cerebellar cortex a valuable model for analyzing the consequences of gene mutations that profoundly alter neuronal function and compromise postnatal survival.

Rat brain sagittal organotypic slice cultures as an ex vivo dopamine cell loss system.

PubMed

McCaughey-Chapman, Amy; Connor, Bronwen

2017-02-01

Organotypic brain slice cultures are a useful tool to study neurological function as they provide a more complex, 3-dimensional system than standard 2-dimensional in vitro cell cultures. Building on a previously developed mouse brain slice culture protocol, we have developed a rat sagittal brain slice culture system as an ex vivo model of dopamine cell loss. We show that rat brain organotypic slice cultures remain viable for up to 6 weeks in culture. Using Fluoro-Gold axonal tracing, we demonstrate that the slice 3-dimensional cytoarchitecture is maintained over a 4 week culturing period, with particular focus on the nigrostriatal pathway. Treatment of the cultures with 6-hydroxydopamine and desipramine induces a progressive loss of Fluoro-Gold-positive nigral cells with a sustained loss of tyrosine hydroxylase-positive nigral cells. This recapitulates the pattern of dopaminergic degeneration observed in the rat partial 6-hydroxydopamine lesion model and, most importantly, the progressive pathology of Parkinson's disease. Our slice culture platform provides an advance over other systems, as we demonstrate for the first time 3-dimensional cytoarchitecture maintenance of rat nigrostriatal sagittal slices for up to 6 weeks. Our ex vivo organotypic slice culture system provides a long term cellular platform to model Parkinson's disease, allowing for the elucidation of mechanisms involved in dopaminergic neuron degeneration and the capability to study cellular integration and plasticity ex vivo. Copyright © 2017 Elsevier B.V. All rights reserved.

Neural network classification technique and machine vision for bread crumb grain evaluation

NASA Astrophysics Data System (ADS)

Zayas, Inna Y.; Chung, O. K.; Caley, M.

1995-10-01

Bread crumb grain was studied to develop a model for pattern recognition of bread baked at Hard Winter Wheat Quality Laboratory (HWWQL), Grain Marketing and Production Research Center (GMPRC). Images of bread slices were acquired with a scanner in a 512 multiplied by 512 format. Subimages in the central part of the slices were evaluated by several features such as mean, determinant, eigen values, shape of a slice and other crumb features. Derived features were used to describe slices and loaves. Neural network programs of MATLAB package were used for data analysis. Learning vector quantization method and multivariate discriminant analysis were applied to bread slices from what of different sources. A training and test sets of different bread crumb texture classes were obtained. The ranking of subimages was well correlated with visual judgement. The performance of different models on slice recognition rate was studied to choose the best model. The recognition of classes created according to human judgement with image features was low. Recognition of arbitrarily created classes, according to porosity patterns, with several feature patterns was approximately 90%. Correlation coefficient was approximately 0.7 between slice shape features and loaf volume.

Hyperbolic and semi-parametric models in finance

NASA Astrophysics Data System (ADS)

Bingham, N. H.; Kiesel, Rüdiger

2001-02-01

The benchmark Black-Scholes-Merton model of mathematical finance is parametric, based on the normal/Gaussian distribution. Its principal parametric competitor, the hyperbolic model of Barndorff-Nielsen, Eberlein and others, is briefly discussed. Our main theme is the use of semi-parametric models, incorporating the mean vector and covariance matrix as in the Markowitz approach, plus a non-parametric part, a scalar function incorporating features such as tail-decay. Implementation is also briefly discussed.

Drying characteristics of pumpkin ( Cucurbita moschata) slices in convective and freeze dryer

NASA Astrophysics Data System (ADS)

Caliskan, Gulsah; Dirim, Safiye Nur

2017-06-01

This study was intended to determine the drying and rehydration kinetics of convective and freeze dried pumpkin slices (0.5 × 3.5 × 0.5 cm). A pilot scale tray drier (at 80 ± 2 °C inlet temperature, 1 m s-1 air velocity) and freeze drier (13.33 kPa absolute pressure, condenser temperature of -48 ± 2 °C) were used for the drying experiments. Drying curves were fitted to six well-known thin layer drying models. Nonlinear regression analysis was used to evaluate the parameters of the selected models by using statistical software SPSS 16.0 (SPSS Inc., USA). For the convective and freeze drying processes of pumpkin slices, the highest R2 values, and the lowest RMSE as well as χ2 values were obtained from Page model. The effective moisture diffusivity (Deff) of the convective and freeze dried pumpkin slices were obtained from the Fick's diffusion model, and they were found to be 2.233 × 10-7 and 3.040 × 10-9 m2s-1, respectively. Specific moisture extraction rate, moisture extraction rate, and specific energy consumption values were almost twice in freeze drying process. Depending on the results, moisture contents and water activity values of pumpkin slices were in acceptable limits for safe storage of products. The rehydration behaviour of [at 18 ± 2 and 100 ± 2 °C for 1:25, 1:50, 1:75, 1:100, and 1:125 solid:liquid ratios (w:w)] dried pumpkin slices was determined by Peleg's model with the highest R2. The highest total soluble solid loss of pumpkin slices was observed for the rehydration experiment which performed at 1:25 solid: liquid ratio (w:w). Rehydration ratio of freeze dried slices was found 2-3 times higher than convective dried slices.

Correlation between a 2D Channelized Hotelling Observer and Human Observers in a Low-contrast Detection Task with Multi-slice Reading in CT

PubMed Central

Yu, Lifeng; Chen, Baiyu; Kofler, James M.; Favazza, Christopher P.; Leng, Shuai; Kupinski, Matthew A.; McCollough, Cynthia H.

2017-01-01

Purpose Model observers have been successfully developed and used to assess the quality of static 2D CT images. However, radiologists typically read images by paging through multiple 2D slices (i.e. multi-slice reading). The purpose of this study was to correlate human and model observer performance in a low-contrast detection task performed using both 2D and multi-slice reading, and to determine if the 2D model observer still correlate well with human observer performance in multi-slice reading. Methods A phantom containing 18 low-contrast spheres (6 sizes × 3 contrast levels) was scanned on a 192-slice CT scanner at 5 dose levels (CTDIvol = 27, 13.5, 6.8, 3.4, and 1.7 mGy), each repeated 100 times. Images were reconstructed using both filtered-backprojection (FBP) and an iterative reconstruction (IR) method (ADMIRE, Siemens). A 3D volume of interest (VOI) around each sphere was extracted and placed side-by-side with a signal-absent VOI to create a 2-alternative forced choice (2AFC) trial. Sixteen 2AFC studies were generated, each with 100 trials, to evaluate the impact of radiation dose, lesion size and contrast, and reconstruction methods on object detection. In total, 1600 trials were presented to both model and human observers. Three medical physicists acted as human observers and were allowed to page through the 3D volumes to make a decision for each 2AFC trial. The human observer performance was compared with the performance of a multi-slice channelized Hotelling observer (CHO_MS), which integrates multi-slice image data, and with the performance of previously validated CHO, which operates on static 2D images (CHO_2D). For comparison, the same 16 2AFC studies were also performed in a 2D viewing mode by the human observers and compared with the multi-slice viewing performance and the two CHO models. Results Human observer performance was well correlated with the CHO_2D performance in the 2D viewing mode (Pearson product-moment correlation coefficient R=0.972, 95% confidence interval (CI): 0.919 to 0.990) and with the CHO_MS performance in the multi-slice viewing mode (R=0.952, 95% CI: 0.865 to 0.984). The CHO_2D performance, calculated from the 2D viewing mode, also had a strong correlation with human observer performance in the multi-slice viewing mode (R=0.957, 95% CI: 879 to 0.985). Human observer performance varied between the multi-slice and 2D modes. One reader performed better in the multi-slice mode (p=0.013); whereas the other two readers showed no significant difference between the two viewing modes (p=0.057 and p=0.38). Conclusions A 2D CHO model is highly correlated with human observer performance in detecting spherical low contrast objects in multi-slice viewing of CT images. This finding provides some evidence for the use of a simpler, 2D CHO to assess image quality in clinically relevant CT tasks where multi-slice viewing is used. PMID:28555878

Ammonia-induced brain swelling and neurotoxicity in an organotypic slice model

PubMed Central

Back, Adam; Tupper, Kelsey Y.; Bai, Tao; Chiranand, Paulpoj; Goldenberg, Fernando D.; Frank, Jeffrey I.; Brorson, James R.

2013-01-01

Objectives Acute liver failure produces cerebral dysfunction and edema, mediated in part by elevated ammonia concentrations, often leading to coma and death. The pathophysiology of cerebral edema in acute liver failure is incompletely understood. In vitro models of the cerebral effects of acute liver failure have predominately consisted of dissociated astrocyte cultures or acute brain slices. We describe a stable long-term culture model incorporating both neural and glial elements in a three-dimensional tissue structure offering significant advantages to the study of astrocytic-neuronal interactions in the pathophysiology of cerebral edema and dysfunction in acute liver failure. Methods We utilized chronic organotypic slice cultures from mouse forebrain, applying ammonium acetate in iso-osmolar fashion for 72 hours. Imaging of slice thickness to assess for tissue swelling was accomplished in living slices with optical coherence tomography, and confocal microscopy of fluorescence immunochemical and histochemical staining served to assess astrocyte and neuronal numbers, morphology, and volume in the fixed brain slices. Results Ammonia exposure at 1–10 mM produced swelling of immunochemically-identified astrocytes, and at 10 mM resulted in macroscopic tissue swelling, with slice thickness increasing by about 30%. Astrocytes were unchanged in number. In contrast, 10 mM ammonia treatment severely disrupted neuronal morphology and reduced neuronal survival at 72 hours by one-half. Discussion Elevated ammonia produces astrocytic swelling, tissue swelling, and neuronal toxicity in cerebral tissues. Ammonia-treated organotypic brain slice cultures provide an in vitro model of cerebral effects of conditions relevant to acute liver failure, applicable to pathophysiological investigations. PMID:22196764

Influence of image slice thickness on rectal dose-response relationships following radiotherapy of prostate cancer

NASA Astrophysics Data System (ADS)

Olsson, C.; Thor, M.; Liu, M.; Moissenko, V.; Petersen, S. E.; Høyer, M.; Apte, A.; Deasy, J. O.

2014-07-01

When pooling retrospective data from different cohorts, slice thicknesses of acquired computed tomography (CT) images used for treatment planning may vary between cohorts. It is, however, not known if varying slice thickness influences derived dose-response relationships. We investigated this for rectal bleeding using dose-volume histograms (DVHs) of the rectum and rectal wall for dose distributions superimposed on images with varying CT slice thicknesses. We used dose and endpoint data from two prostate cancer cohorts treated with three-dimensional conformal radiotherapy to either 74 Gy (N = 159) or 78 Gy (N = 159) at 2 Gy per fraction. The rectum was defined as the whole organ with content, and the morbidity cut-off was Grade ≥2 late rectal bleeding. Rectal walls were defined as 3 mm inner margins added to the rectum. DVHs for simulated slice thicknesses from 3 to 13 mm were compared to DVHs for the originally acquired slice thicknesses at 3 and 5 mm. Volumes, mean, and maximum doses were assessed from the DVHs, and generalized equivalent uniform dose (gEUD) values were calculated. For each organ and each of the simulated slice thicknesses, we performed predictive modeling of late rectal bleeding using the Lyman-Kutcher-Burman (LKB) model. For the most coarse slice thickness, rectal volumes increased (≤18%), whereas maximum and mean doses decreased (≤0.8 and ≤4.2 Gy, respectively). For all a values, the gEUD for the simulated DVHs were ≤1.9 Gy different than the gEUD for the original DVHs. The best-fitting LKB model parameter values with 95% CIs were consistent between all DVHs. In conclusion, we found that the investigated slice thickness variations had minimal impact on rectal dose-response estimations. From the perspective of predictive modeling, our results suggest that variations within 10 mm in slice thickness between cohorts are unlikely to be a limiting factor when pooling multi-institutional rectal dose data that include slice thickness variations within this range. Presented in part at the European Society for Therapeutic Radiotherapy and Oncology Annual Meeting, April 5-8, 2014, Vienna, Austria.

On the identification of a Pliocene time slice for data–model comparison

USGS Publications Warehouse

Haywood, Alan M.; Dolan, Aisling M.; Pickering, Steven J.; Dowsett, Harry J.; McClymont, Erin L.; Prescott, Caroline L.; Salzmann, Ulrich; Hill, Daniel J.; Hunter, Stephen J.; Lunt, Daniel J.; Pope, James O.; Valdes, Paul J.

2013-01-01

The characteristics of the mid-Pliocene warm period (mPWP: 3.264–3.025 Ma BP) have been examined using geological proxies and climate models. While there is agreement between models and data, details of regional climate differ. Uncertainties in prescribed forcings and in proxy data limit the utility of the interval to understand the dynamics of a warmer than present climate or evaluate models. This uncertainty comes, in part, from the reconstruction of a time slab rather than a time slice, where forcings required by climate models can be more adequately constrained. Here, we describe the rationale and approach for identifying a time slice(s) for Pliocene environmental reconstruction. A time slice centred on 3.205 Ma BP (3.204–3.207 Ma BP) has been identified as a priority for investigation. It is a warm interval characterized by a negative benthic oxygen isotope excursion (0.21–0.23‰) centred on marine isotope stage KM5c (KM5.3). It occurred during a period of orbital forcing that was very similar to present day. Climate model simulations indicate that proxy temperature estimates are unlikely to be significantly affected by orbital forcing for at least a precession cycle centred on the time slice, with the North Atlantic potentially being an important exception.

Accurate reconstruction of 3D cardiac geometry from coarsely-sliced MRI.

PubMed

Ringenberg, Jordan; Deo, Makarand; Devabhaktuni, Vijay; Berenfeld, Omer; Snyder, Brett; Boyers, Pamela; Gold, Jeffrey

2014-02-01

We present a comprehensive validation analysis to assess the geometric impact of using coarsely-sliced short-axis images to reconstruct patient-specific cardiac geometry. The methods utilize high-resolution diffusion tensor MRI (DTMRI) datasets as reference geometries from which synthesized coarsely-sliced datasets simulating in vivo MRI were produced. 3D models are reconstructed from the coarse data using variational implicit surfaces through a commonly used modeling tool, CardioViz3D. The resulting geometries were then compared to the reference DTMRI models from which they were derived to analyze how well the synthesized geometries approximate the reference anatomy. Averaged over seven hearts, 95% spatial overlap, less than 3% volume variability, and normal-to-surface distance of 0.32 mm was observed between the synthesized myocardial geometries reconstructed from 8 mm sliced images and the reference data. The results provide strong supportive evidence to validate the hypothesis that coarsely-sliced MRI may be used to accurately reconstruct geometric ventricular models. Furthermore, the use of DTMRI for validation of in vivo MRI presents a novel benchmark procedure for studies which aim to substantiate their modeling and simulation methods using coarsely-sliced cardiac data. In addition, the paper outlines a suggested original procedure for deriving image-based ventricular models using the CardioViz3D software. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

On the identification of a Pliocene time slice for data–model comparison

PubMed Central

Haywood, Alan M.; Dolan, Aisling M.; Pickering, Steven J.; Dowsett, Harry J.; McClymont, Erin L.; Prescott, Caroline L.; Salzmann, Ulrich; Hill, Daniel J.; Hunter, Stephen J.; Lunt, Daniel J.; Pope, James O.; Valdes, Paul J.

2013-01-01

The characteristics of the mid-Pliocene warm period (mPWP: 3.264–3.025 Ma BP) have been examined using geological proxies and climate models. While there is agreement between models and data, details of regional climate differ. Uncertainties in prescribed forcings and in proxy data limit the utility of the interval to understand the dynamics of a warmer than present climate or evaluate models. This uncertainty comes, in part, from the reconstruction of a time slab rather than a time slice, where forcings required by climate models can be more adequately constrained. Here, we describe the rationale and approach for identifying a time slice(s) for Pliocene environmental reconstruction. A time slice centred on 3.205 Ma BP (3.204–3.207 Ma BP) has been identified as a priority for investigation. It is a warm interval characterized by a negative benthic oxygen isotope excursion (0.21–0.23‰) centred on marine isotope stage KM5c (KM5.3). It occurred during a period of orbital forcing that was very similar to present day. Climate model simulations indicate that proxy temperature estimates are unlikely to be significantly affected by orbital forcing for at least a precession cycle centred on the time slice, with the North Atlantic potentially being an important exception. PMID:24043865

Free-floating adult human brain-derived slice cultures as a model to study the neuronal impact of Alzheimer's disease-associated Aβ oligomers.

PubMed

Mendes, Niele D; Fernandes, Artur; Almeida, Glaucia M; Santos, Luis E; Selles, Maria Clara; Lyra-Silva, Natalia; Machado, Carla M; Horta-Júnior, José A C; Louzada, Paulo R; De Felice, Fernanda G; Alvez-Leon, Soniza; Marcondes, Jorge; Assirati, João Alberto; Matias, Caio M; Klein, William L; Garcia-Cairasco, Norberto; Ferreira, Sergio T; Neder, Luciano; Sebollela, Adriano

2018-05-31

Slice cultures have been prepared from several organs. With respect to the brain, advantages of slice cultures over dissociated cell cultures include maintenance of the cytoarchitecture and neuronal connectivity. Slice cultures from adult human brain have been reported and constitute a promising method to study neurological diseases. Despite this potential, few studies have characterized in detail cell survival and function along time in short-term, free-floating cultures. We used tissue from adult human brain cortex from patients undergoing temporal lobectomy to prepare 200 μm-thick slices. Along the period in culture, we evaluated neuronal survival, histological modifications, and neurotransmitter release. The toxicity of Alzheimer's-associated Aβ oligomers (AβOs) to cultured slices was also analyzed. Neurons in human brain slices remain viable and neurochemically active for at least four days in vitro, which allowed detection of binding of AβOs. We further found that slices exposed to AβOs presented elevated levels of hyperphosphorylated Tau, a hallmark of Alzheimer's disease. Although slice cultures from adult human brain have been previously prepared, this is the first report to analyze cell viability and neuronal activity in short-term free-floating cultures as a function of days in vitro. Once surgical tissue is available, the current protocol is easy to perform and produces functional slices from adult human brain. These slice cultures may represent a preferred model for translational studies of neurodegenerative disorders when long term culturing in not required, as in investigations on AβO neurotoxicity. Copyright © 2018 Elsevier B.V. All rights reserved.

Separation of parallel encoded complex-valued slices (SPECS) from a single complex-valued aliased coil image.

PubMed

Rowe, Daniel B; Bruce, Iain P; Nencka, Andrew S; Hyde, James S; Kociuba, Mary C

2016-04-01

Achieving a reduction in scan time with minimal inter-slice signal leakage is one of the significant obstacles in parallel MR imaging. In fMRI, multiband-imaging techniques accelerate data acquisition by simultaneously magnetizing the spatial frequency spectrum of multiple slices. The SPECS model eliminates the consequential inter-slice signal leakage from the slice unaliasing, while maintaining an optimal reduction in scan time and activation statistics in fMRI studies. When the combined k-space array is inverse Fourier reconstructed, the resulting aliased image is separated into the un-aliased slices through a least squares estimator. Without the additional spatial information from a phased array of receiver coils, slice separation in SPECS is accomplished with acquired aliased images in shifted FOV aliasing pattern, and a bootstrapping approach of incorporating reference calibration images in an orthogonal Hadamard pattern. The aliased slices are effectively separated with minimal expense to the spatial and temporal resolution. Functional activation is observed in the motor cortex, as the number of aliased slices is increased, in a bilateral finger tapping fMRI experiment. The SPECS model incorporates calibration reference images together with coefficients of orthogonal polynomials into an un-aliasing estimator to achieve separated images, with virtually no residual artifacts and functional activation detection in separated images. Copyright © 2015 Elsevier Inc. All rights reserved.

Bayesian deconvolution of [corrected] fMRI data using bilinear dynamical systems.

PubMed

Makni, Salima; Beckmann, Christian; Smith, Steve; Woolrich, Mark

2008-10-01

In Penny et al. [Penny, W., Ghahramani, Z., Friston, K.J. 2005. Bilinear dynamical systems. Philos. Trans. R. Soc. Lond. B Biol. Sci. 360(1457) 983-993], a particular case of the Linear Dynamical Systems (LDSs) was used to model the dynamic behavior of the BOLD response in functional MRI. This state-space model, called bilinear dynamical system (BDS), is used to deconvolve the fMRI time series in order to estimate the neuronal response induced by the different stimuli of the experimental paradigm. The BDS model parameters are estimated using an expectation-maximization (EM) algorithm proposed by Ghahramani and Hinton [Ghahramani, Z., Hinton, G.E. 1996. Parameter Estimation for Linear Dynamical Systems. Technical Report, Department of Computer Science, University of Toronto]. In this paper we introduce modifications to the BDS model in order to explicitly model the spatial variations of the haemodynamic response function (HRF) in the brain using a non-parametric approach. While in Penny et al. [Penny, W., Ghahramani, Z., Friston, K.J. 2005. Bilinear dynamical systems. Philos. Trans. R. Soc. Lond. B Biol. Sci. 360(1457) 983-993] the relationship between neuronal activation and fMRI signals is formulated as a first-order convolution with a kernel expansion using basis functions (typically two or three), in this paper, we argue in favor of a spatially adaptive GLM in which a local non-parametric estimation of the HRF is performed. Furthermore, in order to overcome the overfitting problem typically associated with simple EM estimates, we propose a full Variational Bayes (VB) solution to infer the BDS model parameters. We demonstrate the usefulness of our model which is able to estimate both the neuronal activity and the haemodynamic response function in every voxel of the brain. We first examine the behavior of this approach when applied to simulated data with different temporal and noise features. As an example we will show how this method can be used to improve interpretability of estimates from an independent component analysis (ICA) analysis of fMRI data. We finally demonstrate its use on real fMRI data in one slice of the brain.

Parametric Modelling of As-Built Beam Framed Structure in Bim Environment

NASA Astrophysics Data System (ADS)

Yang, X.; Koehl, M.; Grussenmeyer, P.

2017-02-01

A complete documentation and conservation of a historic timber roof requires the integration of geometry modelling, attributional and dynamic information management and results of structural analysis. Recently developed as-built Building Information Modelling (BIM) technique has the potential to provide a uniform platform, which provides possibility to integrate the traditional geometry modelling, parametric elements management and structural analysis together. The main objective of the project presented in this paper is to develop a parametric modelling tool for a timber roof structure whose elements are leaning and crossing beam frame. Since Autodesk Revit, as the typical BIM software, provides the platform for parametric modelling and information management, an API plugin, able to automatically create the parametric beam elements and link them together with strict relationship, was developed. The plugin under development is introduced in the paper, which can obtain the parametric beam model via Autodesk Revit API from total station points and terrestrial laser scanning data. The results show the potential of automatizing the parametric modelling by interactive API development in BIM environment. It also integrates the separate data processing and different platforms into the uniform Revit software.

Reconstructing liver shape and position from MR image slices using an active shape model

NASA Astrophysics Data System (ADS)

Fenchel, Matthias; Thesen, Stefan; Schilling, Andreas

2008-03-01

We present an algorithm for fully automatic reconstruction of 3D position, orientation and shape of the human liver from a sparsely covering set of n 2D MR slice images. Reconstructing the shape of an organ from slice images can be used for scan planning, for surgical planning or other purposes where 3D anatomical knowledge has to be inferred from sparse slices. The algorithm is based on adapting an active shape model of the liver surface to a given set of slice images. The active shape model is created from a training set of liver segmentations from a group of volunteers. The training set is set up with semi-manual segmentations of T1-weighted volumetric MR images. Searching for the optimal shape model that best fits to the image data is done by maximizing a similarity measure based on local appearance at the surface. Two different algorithms for the active shape model search are proposed and compared: both algorithms seek to maximize the a-posteriori probability of the grey level appearance around the surface while constraining the surface to the space of valid shapes. The first algorithm works by using grey value profile statistics in normal direction. The second algorithm uses average and variance images to calculate the local surface appearance on the fly. Both algorithms are validated by fitting the active shape model to abdominal 2D slice images and comparing the shapes, which have been reconstructed, to the manual segmentations and to the results of active shape model searches from 3D image data. The results turn out to be promising and competitive to active shape model segmentations from 3D data.

Evaluation of a pulmonary strain model by registration of dynamic CT scans

NASA Astrophysics Data System (ADS)

Pomeroy, Marc; Liang, Zhengrong; Brehm, Anthony

2017-03-01

Idiopathic pulmonary fibrosis (IPF) is a chronic fibrotic lung disease that develops in adults without any known cause. It is an interstitial lung disease in which the lung tissue becomes scarred and stiffens, ultimately leading to respiratory failure. This disease currently has no cure with limited treatment options, leading to an average survival time of 3-5 years after diagnosis. In this paper we employ a mathematical model simulating the lung parenchyma as hexagons with elastic forces applied to connecting vertices and opposing vertices. Using an image registration algorithm, we obtain trajectories of 4D-CT scans of a healthy patient, and one suffering from IPF. Converting the image trajectories into a hexagonal lattice, we fit the model parameters to match the respiratory motion seen for both patients across multiple image slices. We found the model could decently describe the healthy lung slices, with a minimum average error between corresponding vertices to be 1.66 mm. For the fibrotic lung slices the model was less accurate, maintaining a higher average error across all slices. Using the optimized parameters, we apply the forces predicted from the model using the image trajectory positions for each phase. Although the error is large, the spring constant values determined for the fibrotic patient were not as high as we expected, and more often than not determined to be lower than corresponding healthy lung slices. However, the net force distribution for some of those slices was still found to be greater than the healthy lung counterparts. Other modifications to the model, including additional directional components and which vertices were receiving with the limited sample size available, a clear distinction between the healthy and fibrotic lung cannot yet be made by this model.

Polychromatic wave-optics models for image-plane speckle. 2. Unresolved objects.

PubMed

Van Zandt, Noah R; Spencer, Mark F; Steinbock, Michael J; Anderson, Brian M; Hyde, Milo W; Fiorino, Steven T

2018-05-20

Polychromatic laser light can reduce speckle noise in many wavefront-sensing and imaging applications. To help quantify the achievable reduction in speckle noise, this study investigates the accuracy of three polychromatic wave-optics models under the specific conditions of an unresolved object. Because existing theory assumes a well-resolved object, laboratory experiments are used to evaluate model accuracy. The three models use Monte-Carlo averaging, depth slicing, and spectral slicing, respectively, to simulate the laser-object interaction. The experiments involve spoiling the temporal coherence of laser light via a fiber-based, electro-optic modulator. After the light scatters off of the rough object, speckle statistics are measured. The Monte-Carlo method is found to be highly inaccurate, while depth-slicing error peaks at 7.8% but is generally much lower in comparison. The spectral-slicing method is the most accurate, always producing results within the error bounds of the experiment.

Tectonic slicing of subducting oceanic crust along plate interfaces: Numerical modeling

NASA Astrophysics Data System (ADS)

Ruh, J. B.; Le Pourhiet, L.; Agard, Ph.; Burov, E.; Gerya, T.

2015-10-01

Multikilometer-sized slivers of high-pressure low-temperature metamorphic oceanic crust and mantle are observed in many mountain belts. These blueschist and eclogite units were detached from the descending plate during subduction. Large-scale thermo-mechanical numerical models based on finite difference marker-in-cell staggered grid technique are implemented to investigate slicing processes that lead to the detachment of oceanic slivers and their exhumation before the onset of the continental collision phase. In particular, we investigate the role of the serpentinized subcrustal slab mantle in the mechanisms of shallow and deep crustal slicing. Results show that spatially homogeneous serpentinization of the sub-Moho slab mantle leads to complete accretion of oceanic crust within the accretionary wedge. Spatially discontinuous serpentinization of the slab mantle in form of unconnected patches can lead to shallow slicing of the oceanic crust below the accretionary wedge and to its deep slicing at mantle depths depending on the patch length, slab angle, convergence velocity and continental geothermal gradient. P-T paths obtained in this study are compared to natural examples of shallow slicing of the Crescent Terrane below Vancouver Island and deeply sliced crust of the Lago Superiore and Saas-Zermatt units in the Western Alps.

Research on simplified parametric finite element model of automobile frontal crash

NASA Astrophysics Data System (ADS)

Wu, Linan; Zhang, Xin; Yang, Changhai

2018-05-01

The modeling method and key technologies of the automobile frontal crash simplified parametric finite element model is studied in this paper. By establishing the auto body topological structure, extracting and parameterizing the stiffness properties of substructures, choosing appropriate material models for substructures, the simplified parametric FE model of M6 car is built. The comparison of the results indicates that the simplified parametric FE model can accurately calculate the automobile crash responses and the deformation of the key substructures, and the simulation time is reduced from 6 hours to 2 minutes.

Modeling of Helicopter Pilot Misperception During Overland Navigation

DTIC Science & Technology

2012-03-01

into obstacles in the terrain. The Navy Safety Center has adopted James Reason’s Swiss cheese model for understanding the underlying process that...results in mishaps (Reason, 2000). The Swiss cheese model relates a system to a stack of slices of Swiss cheese . Each slice of cheese is a layer of

Why preferring parametric forecasting to nonparametric methods?

PubMed

Jabot, Franck

2015-05-07

A recent series of papers by Charles T. Perretti and collaborators have shown that nonparametric forecasting methods can outperform parametric methods in noisy nonlinear systems. Such a situation can arise because of two main reasons: the instability of parametric inference procedures in chaotic systems which can lead to biased parameter estimates, and the discrepancy between the real system dynamics and the modeled one, a problem that Perretti and collaborators call "the true model myth". Should ecologists go on using the demanding parametric machinery when trying to forecast the dynamics of complex ecosystems? Or should they rely on the elegant nonparametric approach that appears so promising? It will be here argued that ecological forecasting based on parametric models presents two key comparative advantages over nonparametric approaches. First, the likelihood of parametric forecasting failure can be diagnosed thanks to simple Bayesian model checking procedures. Second, when parametric forecasting is diagnosed to be reliable, forecasting uncertainty can be estimated on virtual data generated with the fitted to data parametric model. In contrast, nonparametric techniques provide forecasts with unknown reliability. This argumentation is illustrated with the simple theta-logistic model that was previously used by Perretti and collaborators to make their point. It should convince ecologists to stick to standard parametric approaches, until methods have been developed to assess the reliability of nonparametric forecasting. Copyright © 2015 Elsevier Ltd. All rights reserved.

Magnetohydrodynamics of unsteady viscous fluid on boundary layer past a sliced sphere

NASA Astrophysics Data System (ADS)

Nursalim, Rahmat; Widodo, Basuki; Imron, Chairul

2017-10-01

Magnetohydrodynamics (MHD) is important study in engineering and industrial fields. By study on MHD, we can reach the fluid flow characteristics that can be used to minimize its negative effect to an object. In decades, MHD has been widely studied in various geometry forms and fluid types. The sliced sphere is a geometry form that has not been investigated. In this paper we study magnetohydrodynamics of unsteady viscous fluid on boundary layer past a sliced sphere. Assumed that the fluid is incompressible, there is no magnetic field, there is no electrical voltage, the sliced sphere is fix and there is no barrier around the object. In this paper we focus on velocity profile at stagnation point (x = 0°). Mathematical model is governed by continuity and momentum equation. It is converted to non-dimensional, stream function, and similarity equation. Solution of the mathematical model is obtained by using Keller-Box numerical method. By giving various of slicing angle and various of magnetic parameter we get the simulation results. The simulation results show that increasing the slicing angle causes the velocity profile be steeper. Also, increasing the value of magnetic parameter causes the velocity profile be steeper. On the large slicing angle there is no significant effect of magnetic parameter to velocity profile, and on the high the value of magnetic parameter there is no significant effect of slicing angle to velocity profile.

A survey of program slicing for software engineering

NASA Technical Reports Server (NTRS)

Beck, Jon

1993-01-01

This research concerns program slicing which is used as a tool for program maintainence of software systems. Program slicing decreases the level of effort required to understand and maintain complex software systems. It was first designed as a debugging aid, but it has since been generalized into various tools and extended to include program comprehension, module cohesion estimation, requirements verification, dead code elimination, and maintainence of several software systems, including reverse engineering, parallelization, portability, and reuse component generation. This paper seeks to address and define terminology, theoretical concepts, program representation, different program graphs, developments in static slicing, dynamic slicing, and semantics and mathematical models. Applications for conventional slicing are presented, along with a prognosis of future work in this field.

Modelling of nectarine drying under near infrared - Vacuum conditions.

PubMed

Alaei, Behnam; Chayjan, Reza Amiri

2015-01-01

Drying of nectarine slices was performed to determine the thermal and physical properties in order to reduce product deterioration due to chemical reactions, facilitate storage and lower transportation costs. Because nectarine slices are sensitive to heat with long drying period, the selection of a suitable drying approach is a challenging task. Infrared-vacuum drying can be used as an appropriate method for susceptible materials with high moisture content such as nectarine slices. Modelling of nectarine slices drying was carried out in a thin layer near infraredvacuum conditions. Drying of the samples was implemented at the absolute pressures of 20, 40 and 60 kPa and drying temperatures of 50, 60 and 70°C. Drying behaviour of nectarine slices, as well as the effect of drying conditions on moisture loss trend, drying rate, effective diffusion coefficient, activation energy, shrinkage, colour and energy consumption of nectarine slices, dried in near infrared-vacuum dryer are discussed in this study. Six mathematical models were used to predict the moisture ratio of the samples in thin layer drying. The Midilli model had supremacy in prediction of nectarine slices drying behaviour. The maximum drying rates of the samples were between 0.014-0.047 gwater/gdry material·min. Effective moisture diffusivity of the samples was estimated in the ranges of 2.46·10-10 to 6.48·10-10 m2/s. Activation energy were computed between 31.28 and 35.23 kJ/mol. Minimum shrinkage (48.4%) and total colour difference (15.1) were achieved at temperature of 50°C and absolute pressure of 20 kPa. Energy consumption of the tests was estimated in the ranges of 0.129 to 0.247 kWh. Effective moisture diffusivity was increased with decrease of vacuum pressure and increase of drying temperature but effect of drying temperature on effective moisture diffusivity of nectarine slices was more than vacuum pressure. Activation energy was decreased with decrease in absolute pressure. Total colour difference and shrinkage of nectarine slices on near infrared-vacuum drying was decreased with decrease of vacuum pressure and decrease of drying temperature.

Acceleration of the direct reconstruction of linear parametric images using nested algorithms.

PubMed

Wang, Guobao; Qi, Jinyi

2010-03-07

Parametric imaging using dynamic positron emission tomography (PET) provides important information for biological research and clinical diagnosis. Indirect and direct methods have been developed for reconstructing linear parametric images from dynamic PET data. Indirect methods are relatively simple and easy to implement because the image reconstruction and kinetic modeling are performed in two separate steps. Direct methods estimate parametric images directly from raw PET data and are statistically more efficient. However, the convergence rate of direct algorithms can be slow due to the coupling between the reconstruction and kinetic modeling. Here we present two fast gradient-type algorithms for direct reconstruction of linear parametric images. The new algorithms decouple the reconstruction and linear parametric modeling at each iteration by employing the principle of optimization transfer. Convergence speed is accelerated by running more sub-iterations of linear parametric estimation because the computation cost of the linear parametric modeling is much less than that of the image reconstruction. Computer simulation studies demonstrated that the new algorithms converge much faster than the traditional expectation maximization (EM) and the preconditioned conjugate gradient algorithms for dynamic PET.

Free-form geometric modeling by integrating parametric and implicit PDEs.

PubMed

Du, Haixia; Qin, Hong

2007-01-01

Parametric PDE techniques, which use partial differential equations (PDEs) defined over a 2D or 3D parametric domain to model graphical objects and processes, can unify geometric attributes and functional constraints of the models. PDEs can also model implicit shapes defined by level sets of scalar intensity fields. In this paper, we present an approach that integrates parametric and implicit trivariate PDEs to define geometric solid models containing both geometric information and intensity distribution subject to flexible boundary conditions. The integrated formulation of second-order or fourth-order elliptic PDEs permits designers to manipulate PDE objects of complex geometry and/or arbitrary topology through direct sculpting and free-form modeling. We developed a PDE-based geometric modeling system for shape design and manipulation of PDE objects. The integration of implicit PDEs with parametric geometry offers more general and arbitrary shape blending and free-form modeling for objects with intensity attributes than pure geometric models.

Geometry Processing of Conventionally Produced Mouse Brain Slice Images.

PubMed

Agarwal, Nitin; Xu, Xiangmin; Gopi, M

2018-04-21

Brain mapping research in most neuroanatomical laboratories relies on conventional processing techniques, which often introduce histological artifacts such as tissue tears and tissue loss. In this paper we present techniques and algorithms for automatic registration and 3D reconstruction of conventionally produced mouse brain slices in a standardized atlas space. This is achieved first by constructing a virtual 3D mouse brain model from annotated slices of Allen Reference Atlas (ARA). Virtual re-slicing of the reconstructed model generates ARA-based slice images corresponding to the microscopic images of histological brain sections. These image pairs are aligned using a geometric approach through contour images. Histological artifacts in the microscopic images are detected and removed using Constrained Delaunay Triangulation before performing global alignment. Finally, non-linear registration is performed by solving Laplace's equation with Dirichlet boundary conditions. Our methods provide significant improvements over previously reported registration techniques for the tested slices in 3D space, especially on slices with significant histological artifacts. Further, as one of the application we count the number of neurons in various anatomical regions using a dataset of 51 microscopic slices from a single mouse brain. To the best of our knowledge the presented work is the first that automatically registers both clean as well as highly damaged high-resolutions histological slices of mouse brain to a 3D annotated reference atlas space. This work represents a significant contribution to this subfield of neuroscience as it provides tools to neuroanatomist for analyzing and processing histological data. Copyright © 2018 Elsevier B.V. All rights reserved.

Detection of MRI artifacts produced by intrinsic heart motion using a saliency model

NASA Astrophysics Data System (ADS)

Salguero, Jennifer; Velasco, Nelson; Romero, Eduardo

2017-11-01

Cardiac Magnetic Resonance (CMR) requires synchronization with the ECG to correct many types of noise. However, the complex heart motion frequently produces displaced slices that have to be either ignored or manually corrected since the ECG correction is useless in this case. This work presents a novel methodology that detects the motion artifacts in CMR using a saliency method that highlights the region where the heart chambers are located. Once the Region of Interest (RoI) is set, its center of gravity is determined for the set of slices composing the volume. The deviation of the gravity center is an estimation of the coherence between the slices and is used to find out slices with certain displacement. Validation was performed with distorted real images where a slice is artificially misaligned with respect to set of slices. The displaced slice is found with a Recall of 84% and F Score of 68%.

A deep learning model integrating FCNNs and CRFs for brain tumor segmentation.

PubMed

Zhao, Xiaomei; Wu, Yihong; Song, Guidong; Li, Zhenye; Zhang, Yazhuo; Fan, Yong

2018-01-01

Accurate and reliable brain tumor segmentation is a critical component in cancer diagnosis, treatment planning, and treatment outcome evaluation. Build upon successful deep learning techniques, a novel brain tumor segmentation method is developed by integrating fully convolutional neural networks (FCNNs) and Conditional Random Fields (CRFs) in a unified framework to obtain segmentation results with appearance and spatial consistency. We train a deep learning based segmentation model using 2D image patches and image slices in following steps: 1) training FCNNs using image patches; 2) training CRFs as Recurrent Neural Networks (CRF-RNN) using image slices with parameters of FCNNs fixed; and 3) fine-tuning the FCNNs and the CRF-RNN using image slices. Particularly, we train 3 segmentation models using 2D image patches and slices obtained in axial, coronal and sagittal views respectively, and combine them to segment brain tumors using a voting based fusion strategy. Our method could segment brain images slice-by-slice, much faster than those based on image patches. We have evaluated our method based on imaging data provided by the Multimodal Brain Tumor Image Segmentation Challenge (BRATS) 2013, BRATS 2015 and BRATS 2016. The experimental results have demonstrated that our method could build a segmentation model with Flair, T1c, and T2 scans and achieve competitive performance as those built with Flair, T1, T1c, and T2 scans. Copyright © 2017 Elsevier B.V. All rights reserved.

Multi-slice ultrasound image calibration of an intelligent skin-marker for soft tissue artefact compensation.

PubMed

Masum, M A; Pickering, M R; Lambert, A J; Scarvell, J M; Smith, P N

2017-09-06

In this paper, a novel multi-slice ultrasound (US) image calibration of an intelligent skin-marker used for soft tissue artefact compensation is proposed to align and orient image slices in an exact H-shaped pattern. Multi-slice calibration is complex, however, in the proposed method, a phantom based visual alignment followed by transform parameters estimation greatly reduces the complexity and provides sufficient accuracy. In this approach, the Hough Transform (HT) is used to further enhance the image features which originate from the image feature enhancing elements integrated into the physical phantom model, thus reducing feature detection uncertainty. In this framework, slice by slice image alignment and calibration are carried out and this provides manual ease and convenience. Copyright © 2016 Elsevier Ltd. All rights reserved.

Establishment and Characterization of a Tumor Stem Cell-Based Glioblastoma Invasion Model.

PubMed

Jensen, Stine Skov; Meyer, Morten; Petterson, Stine Asferg; Halle, Bo; Rosager, Ann Mari; Aaberg-Jessen, Charlotte; Thomassen, Mads; Burton, Mark; Kruse, Torben A; Kristensen, Bjarne Winther

2016-01-01

Glioblastoma is the most frequent and malignant brain tumor. Recurrence is inevitable and most likely connected to tumor invasion and presence of therapy resistant stem-like tumor cells. The aim was therefore to establish and characterize a three-dimensional in vivo-like in vitro model taking invasion and tumor stemness into account. Glioblastoma stem cell-like containing spheroid (GSS) cultures derived from three different patients were established and characterized. The spheroids were implanted in vitro into rat brain slice cultures grown in stem cell medium and in vivo into brains of immuno-compromised mice. Invasion was followed in the slice cultures by confocal time-lapse microscopy. Using immunohistochemistry, we compared tumor cell invasion as well as expression of proliferation and stem cell markers between the models. We observed a pronounced invasion into brain slice cultures both by confocal time-lapse microscopy and immunohistochemistry. This invasion closely resembled the invasion in vivo. The Ki-67 proliferation indexes in spheroids implanted into brain slices were lower than in free-floating spheroids. The expression of stem cell markers varied between free-floating spheroids, spheroids implanted into brain slices and tumors in vivo. The established invasion model kept in stem cell medium closely mimics tumor cell invasion into the brain in vivo preserving also to some extent the expression of stem cell markers. The model is feasible and robust and we suggest the model as an in vivo-like model with a great potential in glioma studies and drug discovery.

Further Empirical Results on Parametric Versus Non-Parametric IRT Modeling of Likert-Type Personality Data

ERIC Educational Resources Information Center

Maydeu-Olivares, Albert

2005-01-01

Chernyshenko, Stark, Chan, Drasgow, and Williams (2001) investigated the fit of Samejima's logistic graded model and Levine's non-parametric MFS model to the scales of two personality questionnaires and found that the graded model did not fit well. We attribute the poor fit of the graded model to small amounts of multidimensionality present in…

The linear transformation model with frailties for the analysis of item response times.

PubMed

Wang, Chun; Chang, Hua-Hua; Douglas, Jeffrey A

2013-02-01

The item response times (RTs) collected from computerized testing represent an underutilized source of information about items and examinees. In addition to knowing the examinees' responses to each item, we can investigate the amount of time examinees spend on each item. In this paper, we propose a semi-parametric model for RTs, the linear transformation model with a latent speed covariate, which combines the flexibility of non-parametric modelling and the brevity as well as interpretability of parametric modelling. In this new model, the RTs, after some non-parametric monotone transformation, become a linear model with latent speed as covariate plus an error term. The distribution of the error term implicitly defines the relationship between the RT and examinees' latent speeds; whereas the non-parametric transformation is able to describe various shapes of RT distributions. The linear transformation model represents a rich family of models that includes the Cox proportional hazards model, the Box-Cox normal model, and many other models as special cases. This new model is embedded in a hierarchical framework so that both RTs and responses are modelled simultaneously. A two-stage estimation method is proposed. In the first stage, the Markov chain Monte Carlo method is employed to estimate the parametric part of the model. In the second stage, an estimating equation method with a recursive algorithm is adopted to estimate the non-parametric transformation. Applicability of the new model is demonstrated with a simulation study and a real data application. Finally, methods to evaluate the model fit are suggested. © 2012 The British Psychological Society.

Slicing Method for curved façade and window extraction from point clouds

NASA Astrophysics Data System (ADS)

Iman Zolanvari, S. M.; Laefer, Debra F.

2016-09-01

Laser scanning technology is a fast and reliable method to survey structures. However, the automatic conversion of such data into solid models for computation remains a major challenge, especially where non-rectilinear features are present. Since, openings and the overall dimensions of the buildings are the most critical elements in computational models for structural analysis, this article introduces the Slicing Method as a new, computationally-efficient method for extracting overall façade and window boundary points for reconstructing a façade into a geometry compatible for computational modelling. After finding a principal plane, the technique slices a façade into limited portions, with each slice representing a unique, imaginary section passing through a building. This is done along a façade's principal axes to segregate window and door openings from structural portions of the load-bearing masonry walls. The method detects each opening area's boundaries, as well as the overall boundary of the façade, in part, by using a one-dimensional projection to accelerate processing. Slices were optimised as 14.3 slices per vertical metre of building and 25 slices per horizontal metre of building, irrespective of building configuration or complexity. The proposed procedure was validated by its application to three highly decorative, historic brick buildings. Accuracy in excess of 93% was achieved with no manual intervention on highly complex buildings and nearly 100% on simple ones. Furthermore, computational times were less than 3 sec for data sets up to 2.6 million points, while similar existing approaches required more than 16 hr for such datasets.

Preparation of organotypic brain slice cultures for the study of Alzheimer’s disease

PubMed Central

Croft, Cara L.; Noble, Wendy

2018-01-01

Alzheimer's disease, the most common cause of dementia, is a progressive neurodegenerative disorder characterised by amyloid-beta deposits in extracellular plaques, intracellular neurofibrillary tangles of aggregated tau, synaptic dysfunction and neuronal death. There are no cures for AD and current medications only alleviate some disease symptoms. Transgenic rodent models to study Alzheimer’s mimic features of human disease such as age-dependent accumulation of abnormal beta-amyloid and tau, synaptic dysfunction, cognitive deficits and neurodegeneration. These models have proven vital for improving our understanding of the molecular mechanisms underlying AD and for identifying promising therapeutic approaches. However, modelling neurodegenerative disease in animals commonly involves aging animals until they develop harmful phenotypes, often coupled with invasive procedures. In vivo studies are also resource, labour, time and cost intensive. We have developed a novel organotypic brain slice culture model to study Alzheimer’ disease which brings the potential of substantially reducing the number of rodents used in dementia research from an estimated 20,000 per year. We obtain 36 brain slices from each mouse pup, considerably reducing the numbers of animals required to investigate multiple stages of disease. This tractable model also allows the opportunity to modulate multiple pathways in tissues from a single animal. We believe that this model will most benefit dementia researchers in the academic and drug discovery sectors. We validated the slice culture model against aged mice, showing that the molecular phenotype closely mimics that displayed in vivo, albeit in an accelerated timescale. We showed beneficial outcomes following treatment of slices with agents previously shown to have therapeutic effects in vivo, and we also identified new mechanisms of action of other compounds. Thus, organotypic brain slice cultures from transgenic mouse models expressing Alzheimer’s disease-related genes may provide a valid and sensitive replacement for in vivo studies that do not involve behavioural analysis. PMID:29904599

3D acquisition and modeling for flint artefacts analysis

NASA Astrophysics Data System (ADS)

Loriot, B.; Fougerolle, Y.; Sestier, C.; Seulin, R.

2007-07-01

In this paper, we are interested in accurate acquisition and modeling of flint artefacts. Archaeologists needs accurate geometry measurements to refine their understanding of the flint artefacts manufacturing process. Current techniques require several operations. First, a copy of a flint artefact is reproduced. The copy is then sliced. A picture is taken for each slice. Eventually, geometric information is manually determined from the pictures. Such a technique is very time consuming, and the processing applied to the original, as well as the reproduced object, induces several measurement errors (prototyping approximations, slicing, image acquisition, and measurement). By using 3D scanners, we significantly reduce the number of operations related to data acquisition and completely suppress the prototyping step to obtain an accurate 3D model. The 3D models are segmented into sliced parts that are then analyzed. Each slice is then automatically fitted by mathematical representation. Such a representation offers several interesting properties: geometric features can be characterized (e.g. shapes, curvature, sharp edges, etc), and a shape of the original piece of stone can be extrapolated. The contributions of this paper are an acquisition technique using 3D scanners that strongly reduces human intervention, acquisition time and measurement errors, and the representation of flint artefacts as mathematical 2D sections that enable accurate analysis.

On the validation of cloud parametrization schemes in numerical atmospheric models with satellite data from ISCCP

NASA Astrophysics Data System (ADS)

Meinke, I.

2003-04-01

A new method is presented to validate cloud parametrization schemes in numerical atmospheric models with satellite data of scanning radiometers. This method is applied to the regional atmospheric model HRM (High Resolution Regional Model) using satellite data from ISCCP (International Satellite Cloud Climatology Project). Due to the limited reliability of former validations there has been a need for developing a new validation method: Up to now differences between simulated and measured cloud properties are mostly declared as deficiencies of the cloud parametrization scheme without further investigation. Other uncertainties connected with the model or with the measurements have not been taken into account. Therefore changes in the cloud parametrization scheme based on such kind of validations might not be realistic. The new method estimates uncertainties of the model and the measurements. Criteria for comparisons of simulated and measured data are derived to localize deficiencies in the model. For a better specification of these deficiencies simulated clouds are classified regarding their parametrization. With this classification the localized model deficiencies are allocated to a certain parametrization scheme. Applying this method to the regional model HRM the quality of forecasting cloud properties is estimated in detail. The overestimation of simulated clouds in low emissivity heights especially during the night is localized as model deficiency. This is caused by subscale cloudiness. As the simulation of subscale clouds in the regional model HRM is described by a relative humidity parametrization these deficiencies are connected with this parameterization.

A review of parametric approaches specific to aerodynamic design process

NASA Astrophysics Data System (ADS)

Zhang, Tian-tian; Wang, Zhen-guo; Huang, Wei; Yan, Li

2018-04-01

Parametric modeling of aircrafts plays a crucial role in the aerodynamic design process. Effective parametric approaches have large design space with a few variables. Parametric methods that commonly used nowadays are summarized in this paper, and their principles have been introduced briefly. Two-dimensional parametric methods include B-Spline method, Class/Shape function transformation method, Parametric Section method, Hicks-Henne method and Singular Value Decomposition method, and all of them have wide application in the design of the airfoil. This survey made a comparison among them to find out their abilities in the design of the airfoil, and the results show that the Singular Value Decomposition method has the best parametric accuracy. The development of three-dimensional parametric methods is limited, and the most popular one is the Free-form deformation method. Those methods extended from two-dimensional parametric methods have promising prospect in aircraft modeling. Since different parametric methods differ in their characteristics, real design process needs flexible choice among them to adapt to subsequent optimization procedure.

Novel active contour model based on multi-variate local Gaussian distribution for local segmentation of MR brain images

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.

High Velocity Jet Noise Source Location and Reduction. Task 6. Supplement. Computer Programs: Engineering Correlation (M*S) Jet Noise Prediction Method and Unified Aeroacoustic Prediction Model (M*G*B) for Nozzles of Arbitary Shape.

DTIC Science & Technology

1979-03-01

LSPFIT 112 4.3.5 SLICE 112 4.3.6 CRD 113 4.3.7 OUTPUT 113 4.3.8 SHOCK 115 4.3.9 ATMOS 115 4.3.10 PNLC 115 4.4 Program Usage and Logic 116 4.5 Description...number MAIN, SLICE, OUTPUT F Intermediate variable LSPFIT FAC Intermediate variable PNLC FC Center frequency SLICE FIRSTU Flight velocity Ua MAIN, SLICE...Index CRD J211 Index CRD K Index, also wave number MAIN, SLICE, PNLC KN Surrounding boundary index MAIN KNCAS Case counter MAIN KNK Surrounding

Low contrast detection in abdominal CT: comparing single-slice and multi-slice tasks

NASA Astrophysics Data System (ADS)

Ba, Alexandre; Racine, Damien; Viry, Anaïs.; Verdun, Francis R.; Schmidt, Sabine; Bochud, François O.

2017-03-01

Image quality assessment is crucial for the optimization of computed tomography (CT) protocols. Human and mathematical model observers are increasingly used for the detection of low contrast signal in abdominal CT, but are frequently limited to the use of a single image slice. Another limitation is that most of them only consider the detection of a signal embedded in a uniform background phantom. The purpose of this paper was to test if human observer performance is significantly different in CT images read in single or multiple slice modes and if these differences are the same for anatomical and uniform clinical images. We investigated detection performance and scrolling trends of human observers of a simulated liver lesion embedded in anatomical and uniform CT backgrounds. Results show that observers don't take significantly benefit of additional information provided in multi-slice reading mode. Regarding the background, performances are moderately higher for uniform than for anatomical images. Our results suggest that for low contrast detection in abdominal CT, the use of multi-slice model observers would probably only add a marginal benefit. On the other hand, the quality of a CT image is more accurately estimated with clinical anatomical backgrounds.

Prevalence Incidence Mixture Models

Cancer.gov

The R package and webtool fits Prevalence Incidence Mixture models to left-censored and irregularly interval-censored time to event data that is commonly found in screening cohorts assembled from electronic health records. Absolute and relative risk can be estimated for simple random sampling, and stratified sampling (the two approaches of superpopulation and a finite population are supported for target populations). Non-parametric (absolute risks only), semi-parametric, weakly-parametric (using B-splines), and some fully parametric (such as the logistic-Weibull) models are supported.

Correlation between in vivo and in vitro pulmonary responses to jet propulsion fuel-8 using precision-cut lung slices and a dynamic organ culture system.

PubMed

Hays, Allison M; Lantz, R Clark; Witten, Mark L

2003-01-01

In tissue slice models, interactions between the heterogeneous cell types comprising the lung parenchyma are maintained thus providing a controlled system for the study of pulmonary toxicology in vitro. However, validation of the model in vitro system must be affirmed. Previous reports, in in vivo systems, have demonstrated that Clara cells and alveolar type II cells are the targets following inhalation of JP-8 jet fuel. We have utilized the lung slice model to determine if cellular targets are similar following in vitro exposure to JP-8. Agar-filled adult rat lung explants were cored and precision cut, using the Brende/Vitron tissue slicer. Slices were cultured on titanium screens located as half-cylinders in cylindrical Teflon cradles that were loaded into standard scintillation vials and incubated at 37 degrees C. Slices were exposed to JP-8 jet fuel (0.5 mg/ml, 1.0 mg/ml, and 1.5 mg/ml in medium) for up to 24 hours. We determined ATP content using a luciferin-luciferase bioluminescent assay. No significant difference was found between the JP-8 jet fuel doses or time points, when compared to controls. Results were correlated with structural alterations following aerosol inhalation of JP-8. As a general observation, ultrastructural evaluation of alveolar type cells revealed an apparent increase in the number and size of surfactant secreting lamellar bodies that was JP-8 jet fuel-dose dependent. These results are similar to those observed following aerosol inhalation exposure. Thus, the lung tissue slice model appears to mimic in vivo effects of JP-8 and therefore is a useful model system for studying the mechanisms of lunginjury following JP-8 exposure.

Estimating and modelling cure in population-based cancer studies within the framework of flexible parametric survival models.

PubMed

Andersson, Therese M L; Dickman, Paul W; Eloranta, Sandra; Lambert, Paul C

2011-06-22

When the mortality among a cancer patient group returns to the same level as in the general population, that is, the patients no longer experience excess mortality, the patients still alive are considered "statistically cured". Cure models can be used to estimate the cure proportion as well as the survival function of the "uncured". One limitation of parametric cure models is that the functional form of the survival of the "uncured" has to be specified. It can sometimes be hard to find a survival function flexible enough to fit the observed data, for example, when there is high excess hazard within a few months from diagnosis, which is common among older age groups. This has led to the exclusion of older age groups in population-based cancer studies using cure models. Here we have extended the flexible parametric survival model to incorporate cure as a special case to estimate the cure proportion and the survival of the "uncured". Flexible parametric survival models use splines to model the underlying hazard function, and therefore no parametric distribution has to be specified. We have compared the fit from standard cure models to our flexible cure model, using data on colon cancer patients in Finland. This new method gives similar results to a standard cure model, when it is reliable, and better fit when the standard cure model gives biased estimates. Cure models within the framework of flexible parametric models enables cure modelling when standard models give biased estimates. These flexible cure models enable inclusion of older age groups and can give stage-specific estimates, which is not always possible from parametric cure models. © 2011 Andersson et al; licensee BioMed Central Ltd.

Estimating and modelling cure in population-based cancer studies within the framework of flexible parametric survival models

PubMed Central

2011-01-01

Background When the mortality among a cancer patient group returns to the same level as in the general population, that is, the patients no longer experience excess mortality, the patients still alive are considered "statistically cured". Cure models can be used to estimate the cure proportion as well as the survival function of the "uncured". One limitation of parametric cure models is that the functional form of the survival of the "uncured" has to be specified. It can sometimes be hard to find a survival function flexible enough to fit the observed data, for example, when there is high excess hazard within a few months from diagnosis, which is common among older age groups. This has led to the exclusion of older age groups in population-based cancer studies using cure models. Methods Here we have extended the flexible parametric survival model to incorporate cure as a special case to estimate the cure proportion and the survival of the "uncured". Flexible parametric survival models use splines to model the underlying hazard function, and therefore no parametric distribution has to be specified. Results We have compared the fit from standard cure models to our flexible cure model, using data on colon cancer patients in Finland. This new method gives similar results to a standard cure model, when it is reliable, and better fit when the standard cure model gives biased estimates. Conclusions Cure models within the framework of flexible parametric models enables cure modelling when standard models give biased estimates. These flexible cure models enable inclusion of older age groups and can give stage-specific estimates, which is not always possible from parametric cure models. PMID:21696598

Recent advances in parametric neuroreceptor mapping with dynamic PET: basic concepts and graphical analyses.

PubMed

Seo, Seongho; Kim, Su Jin; Lee, Dong Soo; Lee, Jae Sung

2014-10-01

Tracer kinetic modeling in dynamic positron emission tomography (PET) has been widely used to investigate the characteristic distribution patterns or dysfunctions of neuroreceptors in brain diseases. Its practical goal has progressed from regional data quantification to parametric mapping that produces images of kinetic-model parameters by fully exploiting the spatiotemporal information in dynamic PET data. Graphical analysis (GA) is a major parametric mapping technique that is independent on any compartmental model configuration, robust to noise, and computationally efficient. In this paper, we provide an overview of recent advances in the parametric mapping of neuroreceptor binding based on GA methods. The associated basic concepts in tracer kinetic modeling are presented, including commonly-used compartment models and major parameters of interest. Technical details of GA approaches for reversible and irreversible radioligands are described, considering both plasma input and reference tissue input models. Their statistical properties are discussed in view of parametric imaging.

Ruminant organotypic brain-slice cultures as a model for the investigation of CNS listeriosis

PubMed Central

Guldimann, Claudia; Lejeune, Beatrice; Hofer, Sandra; Leib, Stephen L; Frey, Joachim; Zurbriggen, Andreas; Seuberlich, Torsten; Oevermann, Anna

2012-01-01

Central nervous system (CNS) infections in ruminant livestock, such as listeriosis, are of major concern for veterinary and public health. To date, no host-specific in vitro models for ruminant CNS infections are available. Here, we established and evaluated the suitability of organotypic brain-slices of ruminant origin as in vitro model to study mechanisms of Listeria monocytogenes CNS infection. Ruminants are frequently affected by fatal listeric rhombencephalitis that closely resembles the same condition occurring in humans. Better insight into host–pathogen interactions in ruminants is therefore of interest, not only from a veterinary but also from a public health perspective. Brains were obtained at the slaughterhouse, and hippocampal and cerebellar brain-slices were cultured up to 49 days. Viability as well as the composition of cell populations was assessed weekly. Viable neurons, astrocytes, microglia and oligodendrocytes were observed up to 49 days in vitro. Slice cultures were infected with L. monocytogenes, and infection kinetics were monitored. Infected brain cells were identified by double immunofluorescence, and results were compared to natural cases of listeric rhombencephalitis. Similar to the natural infection, infected brain-slices showed focal replication of L. monocytogenes and bacteria were predominantly observed in microglia, but also in astrocytes, and associated with axons. These results demonstrate that organotypic brain-slice cultures of bovine origin survive for extended periods and can be infected easily with L. monocytogenes. Therefore, they are a suitable model to study aspects of host–pathogen interaction in listeric encephalitis and potentially in other neuroinfectious diseases. PMID:22804762

TH-EF-BRA-08: A Novel Technique for Estimating Volumetric Cine MRI (VC-MRI) From Multi-Slice Sparsely Sampled Cine Images Using Motion Modeling and Free Form Deformation

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

Harris, W; Yin, F; Wang, C

Purpose: To develop a technique to estimate on-board VC-MRI using multi-slice sparsely-sampled cine images, patient prior 4D-MRI, motion-modeling and free-form deformation for real-time 3D target verification of lung radiotherapy. Methods: A previous method has been developed to generate on-board VC-MRI by deforming prior MRI images based on a motion model(MM) extracted from prior 4D-MRI and a single-slice on-board 2D-cine image. In this study, free-form deformation(FD) was introduced to correct for errors in the MM when large anatomical changes exist. Multiple-slice sparsely-sampled on-board 2D-cine images located within the target are used to improve both the estimation accuracy and temporal resolution ofmore » VC-MRI. The on-board 2D-cine MRIs are acquired at 20–30frames/s by sampling only 10% of the k-space on Cartesian grid, with 85% of that taken at the central k-space. The method was evaluated using XCAT(computerized patient model) simulation of lung cancer patients with various anatomical and respirational changes from prior 4D-MRI to onboard volume. The accuracy was evaluated using Volume-Percent-Difference(VPD) and Center-of-Mass-Shift(COMS) of the estimated tumor volume. Effects of region-of-interest(ROI) selection, 2D-cine slice orientation, slice number and slice location on the estimation accuracy were evaluated. Results: VCMRI estimated using 10 sparsely-sampled sagittal 2D-cine MRIs achieved VPD/COMS of 9.07±3.54%/0.45±0.53mm among all scenarios based on estimation with ROI-MM-ROI-FD. The FD optimization improved estimation significantly for scenarios with anatomical changes. Using ROI-FD achieved better estimation than global-FD. Changing the multi-slice orientation to axial, coronal, and axial/sagittal orthogonal reduced the accuracy of VCMRI to VPD/COMS of 19.47±15.74%/1.57±2.54mm, 20.70±9.97%/2.34±0.92mm, and 16.02±13.79%/0.60±0.82mm, respectively. Reducing the number of cines to 8 enhanced temporal resolution of VC-MRI by 25% while maintaining the estimation accuracy. Estimation using slices sampled uniformly through the tumor achieved better accuracy than slices sampled non-uniformly. Conclusions: Preliminary studies showed that it is feasible to generate VC-MRI from multi-slice sparsely-sampled 2D-cine images for real-time 3D-target verification. This work was supported by the National Institutes of Health under Grant No. R01-CA184173 and a research grant from Varian Medical Systems.« less

Photon Entanglement Through Brain Tissue.

PubMed

Shi, Lingyan; Galvez, Enrique J; Alfano, Robert R

2016-12-20

Photon entanglement, the cornerstone of quantum correlations, provides a level of coherence that is not present in classical correlations. Harnessing it by study of its passage through organic matter may offer new possibilities for medical diagnosis technique. In this work, we study the preservation of photon entanglement in polarization, created by spontaneous parametric down-conversion, after one entangled photon propagates through multiphoton-scattering brain tissue slices with different thickness. The Tangle-Entropy (TS) plots show the strong preservation of entanglement of photons propagating in brain tissue. By spatially filtering the ballistic scattering of an entangled photon, we find that its polarization entanglement is preserved and non-locally correlated with its twin in the TS plots. The degree of entanglement correlates better with structure and water content than with sample thickness.

Photon Entanglement Through Brain Tissue

NASA Astrophysics Data System (ADS)

Shi, Lingyan; Galvez, Enrique J.; Alfano, Robert R.

2016-12-01

Photon entanglement, the cornerstone of quantum correlations, provides a level of coherence that is not present in classical correlations. Harnessing it by study of its passage through organic matter may offer new possibilities for medical diagnosis technique. In this work, we study the preservation of photon entanglement in polarization, created by spontaneous parametric down-conversion, after one entangled photon propagates through multiphoton-scattering brain tissue slices with different thickness. The Tangle-Entropy (TS) plots show the strong preservation of entanglement of photons propagating in brain tissue. By spatially filtering the ballistic scattering of an entangled photon, we find that its polarization entanglement is preserved and non-locally correlated with its twin in the TS plots. The degree of entanglement correlates better with structure and water content than with sample thickness.

First-Order Parametric Model of Reflectance Spectra for Dyed Fabrics

DTIC Science & Technology

2016-02-19

Unclassified Unlimited 31 Daniel Aiken (202) 279-5293 Parametric modeling Inverse /direct analysis This report describes a first-order parametric model of...Appendix: Dielectric Response Functions for Dyes Obtained by Inverse Analysis ……………………………...…………………………………………………….19 1 First-Order Parametric...which provides for both their inverse and direct modeling1. The dyes considered contain spectral features that are of interest to the U.S. Navy for

An EM-based semi-parametric mixture model approach to the regression analysis of competing-risks data.

PubMed

Ng, S K; McLachlan, G J

2003-04-15

We consider a mixture model approach to the regression analysis of competing-risks data. Attention is focused on inference concerning the effects of factors on both the probability of occurrence and the hazard rate conditional on each of the failure types. These two quantities are specified in the mixture model using the logistic model and the proportional hazards model, respectively. We propose a semi-parametric mixture method to estimate the logistic and regression coefficients jointly, whereby the component-baseline hazard functions are completely unspecified. Estimation is based on maximum likelihood on the basis of the full likelihood, implemented via an expectation-conditional maximization (ECM) algorithm. Simulation studies are performed to compare the performance of the proposed semi-parametric method with a fully parametric mixture approach. The results show that when the component-baseline hazard is monotonic increasing, the semi-parametric and fully parametric mixture approaches are comparable for mildly and moderately censored samples. When the component-baseline hazard is not monotonic increasing, the semi-parametric method consistently provides less biased estimates than a fully parametric approach and is comparable in efficiency in the estimation of the parameters for all levels of censoring. The methods are illustrated using a real data set of prostate cancer patients treated with different dosages of the drug diethylstilbestrol. Copyright 2003 John Wiley & Sons, Ltd.

A Unified Approach to Diffusion Direction Sensitive Slice Registration and 3-D DTI Reconstruction From Moving Fetal Brain Anatomy

PubMed Central

Fogtmann, Mads; Seshamani, Sharmishtaa; Kroenke, Christopher; Cheng, Xi; Chapman, Teresa; Wilm, Jakob; Rousseau, François

2014-01-01

This paper presents an approach to 3-D diffusion tensor image (DTI) reconstruction from multi-slice diffusion weighted (DW) magnetic resonance imaging acquisitions of the moving fetal brain. Motion scatters the slice measurements in the spatial and spherical diffusion domain with respect to the underlying anatomy. Previous image registration techniques have been described to estimate the between slice fetal head motion, allowing the reconstruction of 3-D a diffusion estimate on a regular grid using interpolation. We propose Approach to Unified Diffusion Sensitive Slice Alignment and Reconstruction (AUDiSSAR) that explicitly formulates a process for diffusion direction sensitive DW-slice-to-DTI-volume alignment. This also incorporates image resolution modeling to iteratively deconvolve the effects of the imaging point spread function using the multiple views provided by thick slices acquired in different anatomical planes. The algorithm is implemented using a multi-resolution iterative scheme and multiple real and synthetic data are used to evaluate the performance of the technique. An accuracy experiment using synthetically created motion data of an adult head and a experiment using synthetic motion added to sedated fetal monkey dataset show a significant improvement in motion-trajectory estimation compared to a state-of-the-art approaches. The performance of the method is then evaluated on challenging but clinically typical in utero fetal scans of four different human cases, showing improved rendition of cortical anatomy and extraction of white matter tracts. While the experimental work focuses on DTI reconstruction (second-order tensor model), the proposed reconstruction framework can employ any 5-D diffusion volume model that can be represented by the spatial parameterizations of an orientation distribution function. PMID:24108711

Non-parametric identification of multivariable systems: A local rational modeling approach with application to a vibration isolation benchmark

NASA Astrophysics Data System (ADS)

Voorhoeve, Robbert; van der Maas, Annemiek; Oomen, Tom

2018-05-01

Frequency response function (FRF) identification is often used as a basis for control systems design and as a starting point for subsequent parametric system identification. The aim of this paper is to develop a multiple-input multiple-output (MIMO) local parametric modeling approach for FRF identification of lightly damped mechanical systems with improved speed and accuracy. The proposed method is based on local rational models, which can efficiently handle the lightly-damped resonant dynamics. A key aspect herein is the freedom in the multivariable rational model parametrizations. Several choices for such multivariable rational model parametrizations are proposed and investigated. For systems with many inputs and outputs the required number of model parameters can rapidly increase, adversely affecting the performance of the local modeling approach. Therefore, low-order model structures are investigated. The structure of these low-order parametrizations leads to an undesired directionality in the identification problem. To address this, an iterative local rational modeling algorithm is proposed. As a special case recently developed SISO algorithms are recovered. The proposed approach is successfully demonstrated on simulations and on an active vibration isolation system benchmark, confirming good performance of the method using significantly less parameters compared with alternative approaches.

Drying characteristics and modeling of yam slices under different relative humidity conditions

USDA-ARS?s Scientific Manuscript database

The drying characteristics of yam slices under different 23 constant relative humidity (RH) and step-down RH levels were studied. A mass transfer model was developed based on Bi-Di correlations containing a drying coefficient and a lag factor to describe the drying process. It was validated using ex...

Stabilization of a finite slice in miscible displacement in homogeneous porous media

NASA Astrophysics Data System (ADS)

Pramanik, Satyajit; Mishra, Manoranjan

2016-11-01

We numerically studied the miscible displacement of a finite slice of variable viscosity and density. The stability of the finite slice depends on different flow parameters, such as displacement velocity U, mobility ratio R , and the density contrast. Series of numerical simulations corresponding to different ordered pair (R, U) in the parameter space, and a given density contrast reveal six different instability regions. We have shown that independent of the width of the slice, there always exists a region of stable displacement, and below a critical value of the slice width, this stable region increases with decreasing slice width. Further we observe that the viscous fingering (buoyancy-induced instability) at the upper interface induces buoyancy-induced instability (viscous fingering) at the lower interface. Besides the fundamental fluid dynamics understanding, our results can be helpful to model CO2 sequestration and chromatographic separation.

Estimation of cauliflower mass transfer parameters during convective drying

NASA Astrophysics Data System (ADS)

Sahin, Medine; Doymaz, İbrahim

2017-02-01

The study was conducted to evaluate the effect of pre-treatments such as citric acid and hot water blanching and air temperature on drying and rehydration characteristics of cauliflower slices. Experiments were carried out at four different drying air temperatures of 50, 60, 70 and 80 °C with the air velocity of 2.0 m/s. It was observed that drying and rehydration characteristics of cauliflower slices were greatly influenced by air temperature and pre-treatment. Six commonly used mathematical models were evaluated to predict the drying kinetics of cauliflower slices. The Midilli et al. model described the drying behaviour of cauliflower slices at all temperatures better than other models. The values of effective moisture diffusivities ( D eff ) were determined using Fick's law of diffusion and were between 4.09 × 10-9 and 1.88 × 10-8 m2/s. Activation energy was estimated by an Arrhenius type equation and was 23.40, 29.09 and 26.39 kJ/mol for citric acid, blanch and control samples, respectively.

An overview of 5G network slicing architecture

NASA Astrophysics Data System (ADS)

Chen, Qiang; Wang, Xiaolei; Lv, Yingying

2018-05-01

With the development of mobile communication technology, the traditional single network model has been unable to meet the needs of users, and the demand for differentiated services is increasing. In order to solve this problem, the fifth generation of mobile communication technology came into being, and as one of the key technologies of 5G, network slice is the core technology of network virtualization and software defined network, enabling network slices to flexibly provide one or more network services according to users' needs[1]. Each slice can independently tailor the network functions according to the requirements of the business scene and the traffic model and manage the layout of the corresponding network resources, to improve the flexibility of network services and the utilization of resources, and enhance the robustness and reliability of the whole network [2].

Parametric versus Cox's model: an illustrative analysis of divorce in Canada.

PubMed

Balakrishnan, T R; Rao, K V; Krotki, K J; Lapierre-adamcyk, E

1988-06-01

Recent demographic literature clearly recognizes the importance of survival modes in the analysis of cross-sectional event histories. Of the various survival models, Cox's (1972) partial parametric model has been very popular due to its simplicity, and readily available computer software for estimation, sometimes at the cost of precision and parsimony of the model. This paper focuses on parametric failure time models for event history analysis such as Weibell, lognormal, loglogistic, and exponential models. The authors also test the goodness of fit of these parametric models versus the Cox's proportional hazards model taking Kaplan-Meier estimate as base. As an illustration, the authors reanalyze the Canadian Fertility Survey data on 1st marriage dissolution with parametric models. Though these parametric model estimates were not very different from each other, there seemed to be a slightly better fit with loglogistic. When 8 covariates were used in the analysis, it was found that the coefficients were similar in the models, and the overall conclusions about the relative risks would not have been different. The findings reveal that in marriage dissolution, the differences according to demographic and socioeconomic characteristics may be far more important than is generally found in many studies. Therefore, one should not treat the population as homogeneous in analyzing survival probabilities of marriages, other than for cursory analysis of overall trends.

Analysis of acetabular orientation and femoral anteversion using images of three-dimensional reconstructed bone models.

PubMed

Park, Jaeyeong; Kim, Jun-Young; Kim, Hyun Deok; Kim, Young Cheol; Seo, Anna; Je, Minkyu; Mun, Jong Uk; Kim, Bia; Park, Il Hyung; Kim, Shin-Yoon

2017-05-01

Radiographic measurements using two-dimensional (2D) plain radiographs or planes from computed tomography (CT) scans have several drawbacks, while measurements using images of three-dimensional (3D) reconstructed bone models can provide more consistent anthropometric information. We compared the consistency of results using measurements based on images of 3D reconstructed bone models (3D measurements) with those using planes from CT scans (measurements using 2D slice images). Ninety-six of 561 patients who had undergone deep vein thrombosis-CT between January 2013 and November 2014 were randomly selected. We evaluated measurements using 2D slice images and 3D measurements. The images used for 3D reconstruction of bone models were obtained and measured using [Formula: see text] and [Formula: see text] (Materialize, Leuven, Belgium). The mean acetabular inclination, acetabular anteversion and femoral anteversion values on 2D slice images were 42.01[Formula: see text], 18.64[Formula: see text] and 14.44[Formula: see text], respectively, while those using images of 3D reconstructed bone models were 52.80[Formula: see text], 14.98[Formula: see text] and 17.26[Formula: see text]. Intra-rater reliabilities for acetabular inclination, acetabular anteversion, and femoral anteversion on 2D slice images were 0.55, 0.81, and 0.85, respectively, while those for 3D measurements were 0.98, 0.99, and 0.98. Inter-rater reliabilities for acetabular inclination, acetabular anteversion and femoral anteversion on 2D slice images were 0.48, 0.86, and 0.84, respectively, while those for 3D measurements were 0.97, 0.99, and 0.97. The differences between the two measurements are explained by the use of different tools. However, more consistent measurements were possible using the images of 3D reconstructed bone models. Therefore, 3D measurement can be a good alternative to measurement using 2D slice images.

Towards an Empirically Based Parametric Explosion Spectral Model

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

Ford, S R; Walter, W R; Ruppert, S

2009-08-31

Small underground nuclear explosions need to be confidently detected, identified, and characterized in regions of the world where they have never before been tested. The focus of our work is on the local and regional distances (< 2000 km) and phases (Pn, Pg, Sn, Lg) necessary to see small explosions. We are developing a parametric model of the nuclear explosion seismic source spectrum that is compatible with the earthquake-based geometrical spreading and attenuation models developed using the Magnitude Distance Amplitude Correction (MDAC) techniques (Walter and Taylor, 2002). The explosion parametric model will be particularly important in regions without any priormore » explosion data for calibration. The model is being developed using the available body of seismic data at local and regional distances for past nuclear explosions at foreign and domestic test sites. Parametric modeling is a simple and practical approach for widespread monitoring applications, prior to the capability to carry out fully deterministic modeling. The achievable goal of our parametric model development is to be able to predict observed local and regional distance seismic amplitudes for event identification and yield determination in regions with incomplete or no prior history of underground nuclear testing. The relationship between the parametric equations and the geologic and containment conditions will assist in our physical understanding of the nuclear explosion source.« less

An MR-based Model for Cardio-Respiratory Motion Compensation of Overlays in X-Ray Fluoroscopy

PubMed Central

Fischer, Peter; Faranesh, Anthony; Pohl, Thomas; Maier, Andreas; Rogers, Toby; Ratnayaka, Kanishka; Lederman, Robert; Hornegger, Joachim

2017-01-01

In X-ray fluoroscopy, static overlays are used to visualize soft tissue. We propose a system for cardiac and respiratory motion compensation of these overlays. It consists of a 3-D motion model created from real-time MR imaging. Multiple sagittal slices are acquired and retrospectively stacked to consistent 3-D volumes. Slice stacking considers cardiac information derived from the ECG and respiratory information extracted from the images. Additionally, temporal smoothness of the stacking is enhanced. Motion is estimated from the MR volumes using deformable 3-D/3-D registration. The motion model itself is a linear direct correspondence model using the same surrogate signals as slice stacking. In X-ray fluoroscopy, only the surrogate signals need to be extracted to apply the motion model and animate the overlay in real time. For evaluation, points are manually annotated in oblique MR slices and in contrast-enhanced X-ray images. The 2-D Euclidean distance of these points is reduced from 3.85 mm to 2.75 mm in MR and from 3.0 mm to 1.8 mm in X-ray compared to the static baseline. Furthermore, the motion-compensated overlays are shown qualitatively as images and videos. PMID:28692969

Combined non-parametric and parametric approach for identification of time-variant systems

NASA Astrophysics Data System (ADS)

Dziedziech, Kajetan; Czop, Piotr; Staszewski, Wieslaw J.; Uhl, Tadeusz

2018-03-01

Identification of systems, structures and machines with variable physical parameters is a challenging task especially when time-varying vibration modes are involved. The paper proposes a new combined, two-step - i.e. non-parametric and parametric - modelling approach in order to determine time-varying vibration modes based on input-output measurements. Single-degree-of-freedom (SDOF) vibration modes from multi-degree-of-freedom (MDOF) non-parametric system representation are extracted in the first step with the use of time-frequency wavelet-based filters. The second step involves time-varying parametric representation of extracted modes with the use of recursive linear autoregressive-moving-average with exogenous inputs (ARMAX) models. The combined approach is demonstrated using system identification analysis based on the experimental mass-varying MDOF frame-like structure subjected to random excitation. The results show that the proposed combined method correctly captures the dynamics of the analysed structure, using minimum a priori information on the model.

Incorporating parametric uncertainty into population viability analysis models

USGS Publications Warehouse

McGowan, Conor P.; Runge, Michael C.; Larson, Michael A.

2011-01-01

Uncertainty in parameter estimates from sampling variation or expert judgment can introduce substantial uncertainty into ecological predictions based on those estimates. However, in standard population viability analyses, one of the most widely used tools for managing plant, fish and wildlife populations, parametric uncertainty is often ignored in or discarded from model projections. We present a method for explicitly incorporating this source of uncertainty into population models to fully account for risk in management and decision contexts. Our method involves a two-step simulation process where parametric uncertainty is incorporated into the replication loop of the model and temporal variance is incorporated into the loop for time steps in the model. Using the piping plover, a federally threatened shorebird in the USA and Canada, as an example, we compare abundance projections and extinction probabilities from simulations that exclude and include parametric uncertainty. Although final abundance was very low for all sets of simulations, estimated extinction risk was much greater for the simulation that incorporated parametric uncertainty in the replication loop. Decisions about species conservation (e.g., listing, delisting, and jeopardy) might differ greatly depending on the treatment of parametric uncertainty in population models.

Direct Estimation of Kinetic Parametric Images for Dynamic PET

PubMed Central

Wang, Guobao; Qi, Jinyi

2013-01-01

Dynamic positron emission tomography (PET) can monitor spatiotemporal distribution of radiotracer in vivo. The spatiotemporal information can be used to estimate parametric images of radiotracer kinetics that are of physiological and biochemical interests. Direct estimation of parametric images from raw projection data allows accurate noise modeling and has been shown to offer better image quality than conventional indirect methods, which reconstruct a sequence of PET images first and then perform tracer kinetic modeling pixel-by-pixel. Direct reconstruction of parametric images has gained increasing interests with the advances in computing hardware. Many direct reconstruction algorithms have been developed for different kinetic models. In this paper we review the recent progress in the development of direct reconstruction algorithms for parametric image estimation. Algorithms for linear and nonlinear kinetic models are described and their properties are discussed. PMID:24396500

NTP and PCr responses to hypoxia by hypothermic and normothermic respiring, superfused, neonatal rat cerebrocortical slices: an NMR spectroscopy study at 14.1 Tesla.

PubMed

Litt, L; Hirai, K; Basus, V J; James, T L

2003-01-01

Although mechanisms of hypothermic neuroprotection during oxygen deprivation have long been investigated, further characterizations of various molecular mechanisms are appropriate. Anticipating future studies of hypothermia and hypoxia/ischemia, we investigated the extent to which our ex vivo, NMR-based, superfused brain slice model might be helpful. (Slices are approximately 350 microm thick, with 18 slices per 8 mm NMR tube.) 31P NMR spectroscopic measurements were made of hypothermia-induced changes in high energy phosphates, while simultaneously monitoring and controlling tissue temperature, using 1H NMR, the high spectroscopic resolution available at 14.1 Tesla (600 MHz for protons), and a recently published protocol. NTP and PCr concentrations in healthy, well-oxygenated slices decreased to (55 +/- 15)% and (66 +/- 30)% of their respective values at 28.0 degrees C when warmed to 38.0 degrees C, in approximate agreement with earlier in vivo studies by others. During 30 min hypoxia NTP and PCr decreased to non-observable values, regardless of temperature. After reoxygenation, NTP and PCr recoveries as percentages of respective prehypoxia values were (63% +/- 16%; 70%) +/- 5%) for hypothermic slices (28.0 degrees C), and (46% +/- 13%; 41% +/- hypothermic neuroprotection during oxygen deprivation in this model, which appears suitable for use in further studies.

Using Multivariate Adaptive Regression Spline and Artificial Neural Network to Simulate Urbanization in Mumbai, India

NASA Astrophysics Data System (ADS)

Ahmadlou, M.; Delavar, M. R.; Tayyebi, A.; Shafizadeh-Moghadam, H.

2015-12-01

Land use change (LUC) models used for modelling urban growth are different in structure and performance. Local models divide the data into separate subsets and fit distinct models on each of the subsets. Non-parametric models are data driven and usually do not have a fixed model structure or model structure is unknown before the modelling process. On the other hand, global models perform modelling using all the available data. In addition, parametric models have a fixed structure before the modelling process and they are model driven. Since few studies have compared local non-parametric models with global parametric models, this study compares a local non-parametric model called multivariate adaptive regression spline (MARS), and a global parametric model called artificial neural network (ANN) to simulate urbanization in Mumbai, India. Both models determine the relationship between a dependent variable and multiple independent variables. We used receiver operating characteristic (ROC) to compare the power of the both models for simulating urbanization. Landsat images of 1991 (TM) and 2010 (ETM+) were used for modelling the urbanization process. The drivers considered for urbanization in this area were distance to urban areas, urban density, distance to roads, distance to water, distance to forest, distance to railway, distance to central business district, number of agricultural cells in a 7 by 7 neighbourhoods, and slope in 1991. The results showed that the area under the ROC curve for MARS and ANN was 94.77% and 95.36%, respectively. Thus, ANN performed slightly better than MARS to simulate urban areas in Mumbai, India.

Grading of Chinese Cantonese Sausage Using Hyperspectral Imaging Combined with Chemometric Methods

PubMed Central

Gong, Aiping; Zhu, Susu; He, Yong; Zhang, Chu

2017-01-01

Fast and accurate grading of Chinese Cantonese sausage is an important concern for customers, organizations, and the industry. Hyperspectral imaging in the spectral range of 874–1734 nm, combined with chemometric methods, was applied to grade Chinese Cantonese sausage. Three grades of intact and sliced Cantonese sausages were studied, including the top, first, and second grades. Support vector machine (SVM) and random forests (RF) techniques were used to build two different models. Second derivative spectra and RF were applied to select optimal wavelengths. The optimal wavelengths were the same for intact and sliced sausages when selected from second derivative spectra, while the optimal wavelengths for intact and sliced sausages selected using RF were quite similar. The SVM and RF models, using full spectra and the optimal wavelengths, obtained acceptable results for intact and sliced sausages. Both models for intact sausages performed better than those for sliced sausages, with a classification accuracy of the calibration and prediction set of over 90%. The overall results indicated that hyperspectral imaging combined with chemometric methods could be used to grade Chinese Cantonese sausages, with intact sausages being better suited for grading. This study will help to develop fast and accurate online grading of Cantonese sausages, as well as other sausages. PMID:28757578

Precision-cut vibratome slices allow functional live cell imaging of the pulmonary neuroepithelial body microenvironment in fetal mice.

PubMed

Schnorbusch, Kathy; Lembrechts, Robrecht; Brouns, Inge; Pintelon, Isabel; Timmermans, Jean-Pierre; Adriaensen, Dirk

2012-01-01

We recently developed an ex vivo lung slice model that allows for confocal live cell imaging (LCI) of neuroepithelial bodies (NEBs) in postnatal mouse lungs (postnatal days 1-21 and adult). NEBs are morphologically well-characterized, extensively innervated groups of neuroendocrine cells in the airway epithelium, which are shielded from the airway lumen by 'Clara-like' cells. The prominent presence of differentiated NEBs from early embryonic development onwards, strongly suggests that NEBs may exert important functions during late fetal and neonatal life. The main goal of the present study was to adapt the current postnatal LCI lung slice model to enable functional studies of fetal mouse lungs (gestational days 17-20).In vibratome lung slices of prenatal mice, NEBs could be unequivocally identified with the fluorescent stryryl pyridinium dye 4-Di-2-ASP. Changes in the intracellular free calcium concentration and in mitochondrial membrane potential could be monitored using appropriate functional fluorescent indicators (e.g. Fluo-4).It is clear that the described fetal mouse lung slice model is suited for LCI studies of Clara cells, ciliated cells, and the NEB microenvironment, and offers excellent possibilities to further unravel the significance of NEBs during the prenatal and perinatal period.

The impact of parametrized convection on cloud feedback.

PubMed

Webb, Mark J; Lock, Adrian P; Bretherton, Christopher S; Bony, Sandrine; Cole, Jason N S; Idelkadi, Abderrahmane; Kang, Sarah M; Koshiro, Tsuyoshi; Kawai, Hideaki; Ogura, Tomoo; Roehrig, Romain; Shin, Yechul; Mauritsen, Thorsten; Sherwood, Steven C; Vial, Jessica; Watanabe, Masahiro; Woelfle, Matthew D; Zhao, Ming

2015-11-13

We investigate the sensitivity of cloud feedbacks to the use of convective parametrizations by repeating the CMIP5/CFMIP-2 AMIP/AMIP + 4K uniform sea surface temperature perturbation experiments with 10 climate models which have had their convective parametrizations turned off. Previous studies have suggested that differences between parametrized convection schemes are a leading source of inter-model spread in cloud feedbacks. We find however that 'ConvOff' models with convection switched off have a similar overall range of cloud feedbacks compared with the standard configurations. Furthermore, applying a simple bias correction method to allow for differences in present-day global cloud radiative effects substantially reduces the differences between the cloud feedbacks with and without parametrized convection in the individual models. We conclude that, while parametrized convection influences the strength of the cloud feedbacks substantially in some models, other processes must also contribute substantially to the overall inter-model spread. The positive shortwave cloud feedbacks seen in the models in subtropical regimes associated with shallow clouds are still present in the ConvOff experiments. Inter-model spread in shortwave cloud feedback increases slightly in regimes associated with trade cumulus in the ConvOff experiments but is quite similar in the most stable subtropical regimes associated with stratocumulus clouds. Inter-model spread in longwave cloud feedbacks in strongly precipitating regions of the tropics is substantially reduced in the ConvOff experiments however, indicating a considerable local contribution from differences in the details of convective parametrizations. In both standard and ConvOff experiments, models with less mid-level cloud and less moist static energy near the top of the boundary layer tend to have more positive tropical cloud feedbacks. The role of non-convective processes in contributing to inter-model spread in cloud feedback is discussed. © 2015 The Authors.

The impact of parametrized convection on cloud feedback

PubMed Central

Webb, Mark J.; Lock, Adrian P.; Bretherton, Christopher S.; Bony, Sandrine; Cole, Jason N. S.; Idelkadi, Abderrahmane; Kang, Sarah M.; Koshiro, Tsuyoshi; Kawai, Hideaki; Ogura, Tomoo; Roehrig, Romain; Shin, Yechul; Mauritsen, Thorsten; Sherwood, Steven C.; Vial, Jessica; Watanabe, Masahiro; Woelfle, Matthew D.; Zhao, Ming

2015-01-01

We investigate the sensitivity of cloud feedbacks to the use of convective parametrizations by repeating the CMIP5/CFMIP-2 AMIP/AMIP + 4K uniform sea surface temperature perturbation experiments with 10 climate models which have had their convective parametrizations turned off. Previous studies have suggested that differences between parametrized convection schemes are a leading source of inter-model spread in cloud feedbacks. We find however that ‘ConvOff’ models with convection switched off have a similar overall range of cloud feedbacks compared with the standard configurations. Furthermore, applying a simple bias correction method to allow for differences in present-day global cloud radiative effects substantially reduces the differences between the cloud feedbacks with and without parametrized convection in the individual models. We conclude that, while parametrized convection influences the strength of the cloud feedbacks substantially in some models, other processes must also contribute substantially to the overall inter-model spread. The positive shortwave cloud feedbacks seen in the models in subtropical regimes associated with shallow clouds are still present in the ConvOff experiments. Inter-model spread in shortwave cloud feedback increases slightly in regimes associated with trade cumulus in the ConvOff experiments but is quite similar in the most stable subtropical regimes associated with stratocumulus clouds. Inter-model spread in longwave cloud feedbacks in strongly precipitating regions of the tropics is substantially reduced in the ConvOff experiments however, indicating a considerable local contribution from differences in the details of convective parametrizations. In both standard and ConvOff experiments, models with less mid-level cloud and less moist static energy near the top of the boundary layer tend to have more positive tropical cloud feedbacks. The role of non-convective processes in contributing to inter-model spread in cloud feedback is discussed. PMID:26438278

Preparation and fabrication of a full-scale, sagittal-sliced, 3D-printed, patient-specific radiotherapy phantom.

PubMed

Craft, Daniel F; Howell, Rebecca M

2017-09-01

Patient-specific 3D-printed phantoms have many potential applications, both research and clinical. However, they have been limited in size and complexity because of the small size of most commercially available 3D printers as well as material warping concerns. We aimed to overcome these limitations by developing and testing an effective 3D printing workflow to fabricate a large patient-specific radiotherapy phantom with minimal warping errors. In doing so, we produced a full-scale phantom of a real postmastectomy patient. We converted a patient's clinical CT DICOM data into a 3D model and then sliced the model into eleven 2.5-cm-thick sagittal slices. The slices were printed with a readily available thermoplastic material representing all body tissues at 100% infill, but with air cavities left open. Each slice was printed on an inexpensive and commercially available 3D printer. Once the printing was completed, the slices were placed together for imaging and verification. The original patient CT scan and the assembled phantom CT scan were registered together to assess overall accuracy. The materials for the completed phantom cost $524. The printed phantom agreed well with both its design and the actual patient. Individual slices differed from their designs by approximately 2%. Registered CT images of the assembled phantom and original patient showed excellent agreement. Three-dimensional printing the patient-specific phantom in sagittal slices allowed a large phantom to be fabricated with high accuracy. Our results demonstrate that our 3D printing workflow can be used to make large, accurate, patient-specific phantoms at 100% infill with minimal material warping error. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Using pancreas tissue slices for in situ studies of islet of Langerhans and acinar cell biology.

PubMed

Marciniak, Anja; Cohrs, Christian M; Tsata, Vasiliki; Chouinard, Julie A; Selck, Claudia; Stertmann, Julia; Reichelt, Saskia; Rose, Tobias; Ehehalt, Florian; Weitz, Jürgen; Solimena, Michele; Slak Rupnik, Marjan; Speier, Stephan

2014-12-01

Studies on the cellular function of the pancreas are typically performed in vitro on its isolated functional units, the endocrine islets of Langerhans and the exocrine acini. However, these approaches are hampered by preparation-induced changes of cell physiology and the lack of an intact surrounding. We present here a detailed protocol for the preparation of pancreas tissue slices. This procedure is less damaging to the tissue and faster than alternative approaches, and it enables the in situ study of pancreatic endocrine and exocrine cell physiology in a conserved environment. Pancreas tissue slices facilitate the investigation of cellular mechanisms underlying the function, pathology and interaction of the endocrine and exocrine components of the pancreas. We provide examples for several experimental applications of pancreas tissue slices to study various aspects of pancreas cell biology. Furthermore, we describe the preparation of human and porcine pancreas tissue slices for the validation and translation of research findings obtained in the mouse model. Preparation of pancreas tissue slices according to the protocol described here takes less than 45 min from tissue preparation to receipt of the first slices.

Parametric Mass Modeling for Mars Entry, Descent and Landing System Analysis Study

NASA Technical Reports Server (NTRS)

Samareh, Jamshid A.; Komar, D. R.

2011-01-01

This paper provides an overview of the parametric mass models used for the Entry, Descent, and Landing Systems Analysis study conducted by NASA in FY2009-2010. The study examined eight unique exploration class architectures that included elements such as a rigid mid-L/D aeroshell, a lifting hypersonic inflatable decelerator, a drag supersonic inflatable decelerator, a lifting supersonic inflatable decelerator implemented with a skirt, and subsonic/supersonic retro-propulsion. Parametric models used in this study relate the component mass to vehicle dimensions and mission key environmental parameters such as maximum deceleration and total heat load. The use of a parametric mass model allows the simultaneous optimization of trajectory and mass sizing parameters.

Parametric Cost Models for Space Telescopes

NASA Technical Reports Server (NTRS)

Stahl, H. Philip

2010-01-01

A study is in-process to develop a multivariable parametric cost model for space telescopes. Cost and engineering parametric data has been collected on 30 different space telescopes. Statistical correlations have been developed between 19 variables of 59 variables sampled. Single Variable and Multi-Variable Cost Estimating Relationships have been developed. Results are being published.

N-methyl-D-aspartate neurotoxicity in hippocampal slices: protection by aniracetam.

PubMed

Pizzi, M; Consolandi, O; Memo, M; Spano, P

1995-03-14

Aniracetam, a drug known to elicit cognition enhancing properties in both animals and humans, was found to counteract the neurotoxicity induced by excitatory amino acids in primary cultures of cerebellar neurons. We report here that aniracetam prevents the neurotoxic effect induced by N-methyl-D-aspartate (NMDA) in rat hippocampal slices. Time-course experiments showed that the aniracetam-induced neuroprotection does not require preincubation of the slices with the drug. Maximal effective concentration of aniracetam was 10 microM. Since the NMDA-mediated cell death in hippocampal slices is considered a valuable experimental model of ischemia, these results suggest a possible novel therapeutic application for aniracetam.

High-quality low-dose cardiovascular computed tomography (CCT) in pediatric patients using a 64-slice scanner.

PubMed

Cannaò, Paola Maria; Secchi, Francesco; Alì, Marco; D'Angelo, Ida Daniela; Scarabello, Marco; Di Leo, Giovanni; Sardanelli, Francesco

2018-01-01

Background Cardiovascular computed tomography (CCT) technology is rapidly advancing allowing to perform good quality examinations with a radiation dose as low as 1.2 mSv. However, latest generation scanners are not available in all centers. Purpose To estimate radiation dose and image quality in pediatric CCT using a standard 64-slice scanner. Material and Methods A total of 100 patients aged 6.9 ± 5.4 years (mean ± standard deviation) who underwent a 64-slice CCT scan using 80, 100, or 120 kVp, were retrospectively evaluated. Radiation effective dose was calculated on the basis of the dose length product. Two independent readers assessed the image quality through signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and a qualitative score (3 = very good, 2 = good, 1 = poor). Non-parametric tests were used. Results Fifty-five exams were not electrocardiographically (ECG) triggered, 20 had a prospective ECG triggering, and 25 had retrospective ECG triggering. The median effective dose was 1.3 mSv (interquartile range [IQR] = 0.8-2.7 mSv). Median SNR was 30.6 (IQR = 23.4-33.6) at 120 kVp, 29.4 (IQR = 23.7-34.8) at 100 kVp, and 24.7 (IQR = 19.4-34.3) at 80 kVp. Median CNR was 21.0 (IQR = 14.8-24.4), 19.1 (IQR = 15.6-23.9), and 25.3 (IQR = 19.4-33.4), respectively. Image quality was very good, good, and poor in 56, 39, and 5 patients, respectively. No significant differences were found among voltage groups for SNR ( P = 0.486), CNR ( P = 0.336), and subjective image quality ( P = 0.296). The inter-observer reproducibility was almost perfect (κ = 0.880). Conclusion High-quality pediatric CCT can be performed using a 64-slice scanner, with a radiation effective dose close to 2 mSv in about 50% of the cases.

Probing the dynamics of dark energy with divergence-free parametrizations: A global fit study

NASA Astrophysics Data System (ADS)

Li, Hong; Zhang, Xin

2011-09-01

The CPL parametrization is very important for investigating the property of dark energy with observational data. However, the CPL parametrization only respects the past evolution of dark energy but does not care about the future evolution of dark energy, since w ( z ) diverges in the distant future. In a recent paper [J.Z. Ma, X. Zhang, Phys. Lett. B 699 (2011) 233], a robust, novel parametrization for dark energy, w ( z ) = w + w ( l n ( 2 + z ) 1 + z - l n 2 ) , has been proposed, successfully avoiding the future divergence problem in the CPL parametrization. On the other hand, an oscillating parametrization (motivated by an oscillating quintom model) can also avoid the future divergence problem. In this Letter, we use the two divergence-free parametrizations to probe the dynamics of dark energy in the whole evolutionary history. In light of the data from 7-year WMAP temperature and polarization power spectra, matter power spectrum of SDSS DR7, and SN Ia Union2 sample, we perform a full Markov Chain Monte Carlo exploration for the two dynamical dark energy models. We find that the best-fit dark energy model is a quintom model with the EOS across -1 during the evolution. However, though the quintom model is more favored, we find that the cosmological constant still cannot be excluded.

Modeling personnel turnover in the parametric organization

NASA Technical Reports Server (NTRS)

Dean, Edwin B.

1991-01-01

A model is developed for simulating the dynamics of a newly formed organization, credible during all phases of organizational development. The model development process is broken down into the activities of determining the tasks required for parametric cost analysis (PCA), determining the skills required for each PCA task, determining the skills available in the applicant marketplace, determining the structure of the model, implementing the model, and testing it. The model, parameterized by the likelihood of job function transition, has demonstrated by the capability to represent the transition of personnel across functional boundaries within a parametric organization using a linear dynamical system, and the ability to predict required staffing profiles to meet functional needs at the desired time. The model can be extended by revisions of the state and transition structure to provide refinements in functional definition for the parametric and extended organization.

From 2D to 3D: Construction of a 3D Parametric Model for Detection of Dental Roots Shape and Position from a Panoramic Radiograph—A Preliminary Report

PubMed Central

Mazzotta, Laura; Cozzani, Mauro; Mutinelli, Sabrina; Castaldo, Attilio; Silvestrini-Biavati, Armando

2013-01-01

Objectives. To build a 3D parametric model to detect shape and volume of dental roots, from a panoramic radiograph (PAN) of the patient. Materials and Methods. A PAN and a cone beam computed tomography (CBCT) of a patient were acquired. For each tooth, various parameters were considered (coronal and root lengths and widths): these were measured from the CBCT and from the PAN. Measures were compared to evaluate the accuracy level of PAN measurements. By using a CAD software, parametric models of an incisor and of a molar were constructed employing B-spline curves and free-form surfaces. PAN measures of teeth 2.1 and 3.6 were assigned to the parametric models; the same two teeth were segmented from CBCT. The two models were superimposed to assess the accuracy of the parametric model. Results. PAN measures resulted to be accurate and comparable with all other measurements. From model superimposition the maximum error resulted was 1.1 mm on the incisor crown and 2 mm on the molar furcation. Conclusion. This study shows that it is possible to build a 3D parametric model starting from 2D information with a clinically valid accuracy level. This can ultimately lead to a crown-root movement simulation. PMID:23554814

Comparison of thawing and freezing dark energy parametrizations

NASA Astrophysics Data System (ADS)

Pantazis, G.; Nesseris, S.; Perivolaropoulos, L.

2016-05-01

Dark energy equation of state w (z ) parametrizations with two parameters and given monotonicity are generically either convex or concave functions. This makes them suitable for fitting either freezing or thawing quintessence models but not both simultaneously. Fitting a data set based on a freezing model with an unsuitable (concave when increasing) w (z ) parametrization [like Chevallier-Polarski-Linder (CPL)] can lead to significant misleading features like crossing of the phantom divide line, incorrect w (z =0 ), incorrect slope, etc., that are not present in the underlying cosmological model. To demonstrate this fact we generate scattered cosmological data at both the level of w (z ) and the luminosity distance DL(z ) based on either thawing or freezing quintessence models and fit them using parametrizations of convex and of concave type. We then compare statistically significant features of the best fit w (z ) with actual features of the underlying model. We thus verify that the use of unsuitable parametrizations can lead to misleading conclusions. In order to avoid these problems it is important to either use both convex and concave parametrizations and select the one with the best χ2 or use principal component analysis thus splitting the redshift range into independent bins. In the latter case, however, significant information about the slope of w (z ) at high redshifts is lost. Finally, we propose a new family of parametrizations w (z )=w0+wa(z/1 +z )n which generalizes the CPL and interpolates between thawing and freezing parametrizations as the parameter n increases to values larger than 1.

You Can Touch This! Bringing HST images to life as 3-D models

NASA Astrophysics Data System (ADS)

Christian, Carol A.; Nota, A.; Grice, N. A.; Sabbi, E.; Shaheen, N.; Greenfield, P.; Hurst, A.; Kane, S.; Rao, R.; Dutterer, J.; de Mink, S. E.

2014-01-01

We present the very first results of an innovative process to transform Hubble images into tactile 3-D models of astronomical objects. We have created a very new, unique tool for understanding astronomical phenomena, especially designed to make astronomy accessible to visually impaired children and adults. From the multicolor images of stellar clusters, we construct 3-D computer models that are digitally sliced into layers, each featuring touchable patterning and Braille characters, and are printed on a 3-D printer. The slices are then fitted together, so that the user can explore the structure of the cluster environment with their fingertips, slice-by-slice, analogous to a visual fly-through. Students will be able to identify and spatially locate the different components of these complex astronomical objects, namely gas, dust and stars, and will learn about the formation and composition of stellar clusters. The primary audiences for the 3D models are middle school and high school blind students and, secondarily, blind adults. However, we believe that the final materials will address a broad range of individuals with varied and multi-sensory learning styles, and will be interesting and visually appealing to the public at large.

Use of a thin-section archive and enterprise 3D software for long-term storage of thin-slice CT data sets.

PubMed

Meenan, Christopher; Daly, Barry; Toland, Christopher; Nagy, Paul

2006-01-01

Rapid advances are changing the technology and applications of multidetector computed tomography (CT) scanners. The major increase in data associated with this new technology, however, breaks most commercial picture archiving and communication system (PACS) architectures by preventing them from delivering data in real time to radiologists and outside clinicians. We proposed a phased model for 3D workflow, installed a thin-slice archive and measured thin-slice data storage over a period of 5 months. A mean of 1,869 CT studies were stored per month, with an average of 643 images per study and a mean total volume of 588 GB/month. We also surveyed 48 radiologists to determine diagnostic use, impressions of thin-slice value, and requirements for retention times. The majority of radiologists thought thin slice was helpful for diagnosis and regularly used the application. Permanent storage of thin slice CT is likely to become best practice and a mission-critical pursuit for the health care enterprise.

Healthy food consumption in young women. The influence of others' eating behavior and body weight appearance.

PubMed

Stel, Mariëlle; van Koningsbruggen, Guido M

2015-07-01

People's eating behaviors tend to be influenced by the behaviors of others. In the present studies, we investigated the effect of another person's eating behavior and body weight appearance on healthy food consumption of young women. In Study 1, participants watched a short film fragment together with a confederate who appeared normal weight or overweight and consumed either 3 or 10 cucumber slices. In Study 2, a confederate who appeared underweight, normal weight, or overweight consumed no or 4 cucumber slices. The number of cucumber slices eaten by participants was registered. Results showed that participants' healthy eating behavior was influenced by the confederate's eating behavior when the confederate was underweight, normal weight, and overweight. Participants ate more cucumber slices when the confederate ate a higher amount of cucumber slices compared with a lower (or no) amount of cucumber slices (Studies 1 and 2). The food intake effect was stronger for the underweight compared with the overweight model (Study 2). Copyright © 2015 Elsevier Ltd. All rights reserved.

Effects of RF profile on precision of quantitative T2 mapping using dual-echo steady-state acquisition.

PubMed

Wu, Pei-Hsin; Cheng, Cheng-Chieh; Wu, Ming-Long; Chao, Tzu-Cheng; Chung, Hsiao-Wen; Huang, Teng-Yi

2014-01-01

The dual echo steady-state (DESS) sequence has been shown successful in achieving fast T2 mapping with good precision. Under-estimation of T2, however, becomes increasingly prominent as the flip angle decreases. In 3D DESS imaging, therefore, the derived T2 values would become a function of the slice location in the presence of non-ideal slice profile of the excitation RF pulse. Furthermore, the pattern of slice-dependent variation in T2 estimates is dependent on the RF pulse waveform. Multi-slice 2D DESS imaging provides better inter-slice consistency, but the signal intensity is subject to integrated effects of within-slice distribution of the actual flip angle. Consequently, T2 measured using 2D DESS is prone to inaccuracy even at the designated flip angle of 90°. In this study, both phantom and human experiments demonstrate the above phenomena in good agreement with model prediction. © 2013.

A novel dehydration technique for carrot slices implementing ultrasound and vacuum drying methods.

PubMed

Chen, Zhi-Gang; Guo, Xiao-Yu; Wu, Tao

2016-05-01

A novel drying technique using a combination of ultrasound and vacuum dehydration was developed to shorten the drying time and improve the quality of carrot slices. Carrot slices were dried with ultrasonic vacuum (USV) drying and vacuum drying at 65 °C and 75 °C. The drying rate was significantly influenced by the drying techniques and temperatures. Compared with vacuum drying, USV drying resulted in a 41-53% decrease in the drying time. The drying time for the USV and vacuum drying techniques at 75 °C was determined to be 140 and 340 min for carrot slices, respectively. The rehydration potential, nutritional value (retention of β-carotene and ascorbic acid), color, and textural properties of USV-dried carrot slices are predominately better compared to vacuum-dried carrot slices. Moreover, lower energy consumption was used in the USV technique. The drying data (time versus moisture ratio) were successfully fitted to Wang and Singh model. Copyright © 2015. Published by Elsevier B.V.

Photon Entanglement Through Brain Tissue

PubMed Central

Shi, Lingyan; Galvez, Enrique J.; Alfano, Robert R.

2016-01-01

Photon entanglement, the cornerstone of quantum correlations, provides a level of coherence that is not present in classical correlations. Harnessing it by study of its passage through organic matter may offer new possibilities for medical diagnosis technique. In this work, we study the preservation of photon entanglement in polarization, created by spontaneous parametric down-conversion, after one entangled photon propagates through multiphoton-scattering brain tissue slices with different thickness. The Tangle-Entropy (TS) plots show the strong preservation of entanglement of photons propagating in brain tissue. By spatially filtering the ballistic scattering of an entangled photon, we find that its polarization entanglement is preserved and non-locally correlated with its twin in the TS plots. The degree of entanglement correlates better with structure and water content than with sample thickness. PMID:27995952

Pulmonary parenchyma segmentation in thin CT image sequences with spectral clustering and geodesic active contour model based on similarity

NASA Astrophysics Data System (ADS)

He, Nana; Zhang, Xiaolong; Zhao, Juanjuan; Zhao, Huilan; Qiang, Yan

2017-07-01

While the popular thin layer scanning technology of spiral CT has helped to improve diagnoses of lung diseases, the large volumes of scanning images produced by the technology also dramatically increase the load of physicians in lesion detection. Computer-aided diagnosis techniques like lesions segmentation in thin CT sequences have been developed to address this issue, but it remains a challenge to achieve high segmentation efficiency and accuracy without much involvement of human manual intervention. In this paper, we present our research on automated segmentation of lung parenchyma with an improved geodesic active contour model that is geodesic active contour model based on similarity (GACBS). Combining spectral clustering algorithm based on Nystrom (SCN) with GACBS, this algorithm first extracts key image slices, then uses these slices to generate an initial contour of pulmonary parenchyma of un-segmented slices with an interpolation algorithm, and finally segments lung parenchyma of un-segmented slices. Experimental results show that the segmentation results generated by our method are close to what manual segmentation can produce, with an average volume overlap ratio of 91.48%.

Finite slice analysis (FINA) of sliced and velocity mapped images on a Cartesian grid

NASA Astrophysics Data System (ADS)

Thompson, J. O. F.; Amarasinghe, C.; Foley, C. D.; Rombes, N.; Gao, Z.; Vogels, S. N.; van de Meerakker, S. Y. T.; Suits, A. G.

2017-08-01

Although time-sliced imaging yields improved signal-to-noise and resolution compared with unsliced velocity mapped ion images, for finite slice widths as encountered in real experiments there is a loss of resolution and recovered intensities for the slow fragments. Recently, we reported a new approach that permits correction of these effects for an arbitrarily sliced distribution of a 3D charged particle cloud. This finite slice analysis (FinA) method utilizes basis functions that model the out-of-plane contribution of a given velocity component to the image for sequential subtraction in a spherical polar coordinate system. However, the original approach suffers from a slow processing time due to the weighting procedure needed to accurately model the out-of-plane projection of an anisotropic angular distribution. To overcome this issue we present a variant of the method in which the FinA approach is performed in a cylindrical coordinate system (Cartesian in the image plane) rather than a spherical polar coordinate system. Dubbed C-FinA, we show how this method is applied in much the same manner. We compare this variant to the polar FinA method and find that the processing time (of a 510 × 510 pixel image) in its most extreme case improves by a factor of 100. We also show that although the resulting velocity resolution is not quite as high as the polar version, this new approach shows superior resolution for fine structure in the differential cross sections. We demonstrate the method on a range of experimental and synthetic data at different effective slice widths.

Fast parallel algorithm for slicing STL based on pipeline

NASA Astrophysics Data System (ADS)

Ma, Xulong; Lin, Feng; Yao, Bo

2016-05-01

In Additive Manufacturing field, the current researches of data processing mainly focus on a slicing process of large STL files or complicated CAD models. To improve the efficiency and reduce the slicing time, a parallel algorithm has great advantages. However, traditional algorithms can't make full use of multi-core CPU hardware resources. In the paper, a fast parallel algorithm is presented to speed up data processing. A pipeline mode is adopted to design the parallel algorithm. And the complexity of the pipeline algorithm is analyzed theoretically. To evaluate the performance of the new algorithm, effects of threads number and layers number are investigated by a serial of experiments. The experimental results show that the threads number and layers number are two remarkable factors to the speedup ratio. The tendency of speedup versus threads number reveals a positive relationship which greatly agrees with the Amdahl's law, and the tendency of speedup versus layers number also keeps a positive relationship agreeing with Gustafson's law. The new algorithm uses topological information to compute contours with a parallel method of speedup. Another parallel algorithm based on data parallel is used in experiments to show that pipeline parallel mode is more efficient. A case study at last shows a suspending performance of the new parallel algorithm. Compared with the serial slicing algorithm, the new pipeline parallel algorithm can make full use of the multi-core CPU hardware, accelerate the slicing process, and compared with the data parallel slicing algorithm, the new slicing algorithm in this paper adopts a pipeline parallel model, and a much higher speedup ratio and efficiency is achieved.

Pharmacological Modulation of Three Modalities of CA1 Hippocampal Long-Term Potentiation in the Ts65Dn Mouse Model of Down Syndrome

PubMed Central

Scott-McKean, Jonah J.; Roque, Adriano L.; Surewicz, Krystyna; Johnson, Mark W.; Surewicz, Witold K.

2018-01-01

The Ts65Dn mouse is the most studied animal model of Down syndrome. Past research has shown a significant reduction in CA1 hippocampal long-term potentiation (LTP) induced by theta-burst stimulation (TBS), but not in LTP induced by high-frequency stimulation (HFS), in slices from Ts65Dn mice compared with euploid mouse-derived slices. Additionally, therapeutically relevant doses of the drug memantine were shown to rescue learning and memory deficits in Ts65Dn mice. Here, we observed that 1 μM memantine had no detectable effect on HFS-induced LTP in either Ts65Dn- or control-derived slices, but it rescued TBS-induced LTP in Ts65Dn-derived slices to control euploid levels. Then, we assessed LTP induced by four HFS (4xHFS) and found that this form of LTP was significantly depressed in Ts65Dn slices when compared with LTP in euploid control slices. Memantine, however, did not rescue this phenotype. Because 4xHFS-induced LTP had not yet been characterized in Ts65Dn mice, we also investigated the effects of picrotoxin, amyloid beta oligomers, and soluble recombinant human prion protein (rPrP) on this form of LTP. Whereas ≥10 μM picrotoxin increased LTP to control levels, it also caused seizure-like oscillations. Neither amyloid beta oligomers nor rPrP had any effect on 4xHFS-induced LTP in Ts65Dn-derived slices. PMID:29849573

Parametric models of reflectance spectra for dyed fabrics

NASA Astrophysics Data System (ADS)

Aiken, Daniel C.; Ramsey, Scott; Mayo, Troy; Lambrakos, Samuel G.; Peak, Joseph

2016-05-01

This study examines parametric modeling of NIR reflectivity spectra for dyed fabrics, which provides for both their inverse and direct modeling. The dye considered for prototype analysis is triarylamine dye. The fabrics considered are camouflage textiles characterized by color variations. The results of this study provide validation of the constructed parametric models, within reasonable error tolerances for practical applications, including NIR spectral characteristics in camouflage textiles, for purposes of simulating NIR spectra corresponding to various dye concentrations in host fabrics, and potentially to mixtures of dyes.

METHOXYCHLOR METABOLISM AND VITELLOGENINESIS IN MALE RAINBOW TROUT LIVER SLICES

EPA Science Inventory

Induction of vitellogenesis (VTG) in male fish has become an accepted biomarker for xenoestrogenicity. This study utilized the male rainbow trout liver slice model to determine the estrogenicity of parent compound, methoxychlor (MXC) and metabolites, di-hydroxy methoxychlor (HPTE...

Mapping the Chevallier-Polarski-Linder parametrization onto physical dark energy Models

NASA Astrophysics Data System (ADS)

Scherrer, Robert J.

2015-08-01

We examine the Chevallier-Polarski-Linder (CPL) parametrization, in the context of quintessence and barotropic dark energy models, to determine the subset of such models to which it can provide a good fit. The CPL parametrization gives the equation of state parameter w for the dark energy as a linear function of the scale factor a , namely w =w0+wa(1 -a ). In the case of quintessence models, we find that over most of the w0, wa parameter space the CPL parametrization maps onto a fairly narrow form of behavior for the potential V (ϕ ), while a one-dimensional subset of parameter space, for which wa=κ (1 +w0) , with κ constant, corresponds to a wide range of functional forms for V (ϕ ). For barotropic models, we show that the functional dependence of the pressure on the density, up to a multiplicative constant, depends only on wi=wa+w0 and not on w0 and wa separately. Our results suggest that the CPL parametrization may not be optimal for testing either type of model.

A general framework for parametric survival analysis.

PubMed

Crowther, Michael J; Lambert, Paul C

2014-12-30

Parametric survival models are being increasingly used as an alternative to the Cox model in biomedical research. Through direct modelling of the baseline hazard function, we can gain greater understanding of the risk profile of patients over time, obtaining absolute measures of risk. Commonly used parametric survival models, such as the Weibull, make restrictive assumptions of the baseline hazard function, such as monotonicity, which is often violated in clinical datasets. In this article, we extend the general framework of parametric survival models proposed by Crowther and Lambert (Journal of Statistical Software 53:12, 2013), to incorporate relative survival, and robust and cluster robust standard errors. We describe the general framework through three applications to clinical datasets, in particular, illustrating the use of restricted cubic splines, modelled on the log hazard scale, to provide a highly flexible survival modelling framework. Through the use of restricted cubic splines, we can derive the cumulative hazard function analytically beyond the boundary knots, resulting in a combined analytic/numerical approach, which substantially improves the estimation process compared with only using numerical integration. User-friendly Stata software is provided, which significantly extends parametric survival models available in standard software. Copyright © 2014 John Wiley & Sons, Ltd.

flexsurv: A Platform for Parametric Survival Modeling in R

PubMed Central

Jackson, Christopher H.

2018-01-01

flexsurv is an R package for fully-parametric modeling of survival data. Any parametric time-to-event distribution may be fitted if the user supplies a probability density or hazard function, and ideally also their cumulative versions. Standard survival distributions are built in, including the three and four-parameter generalized gamma and F distributions. Any parameter of any distribution can be modeled as a linear or log-linear function of covariates. The package also includes the spline model of Royston and Parmar (2002), in which both baseline survival and covariate effects can be arbitrarily flexible parametric functions of time. The main model-fitting function, flexsurvreg, uses the familiar syntax of survreg from the standard survival package (Therneau 2016). Censoring or left-truncation are specified in ‘Surv’ objects. The models are fitted by maximizing the full log-likelihood, and estimates and confidence intervals for any function of the model parameters can be printed or plotted. flexsurv also provides functions for fitting and predicting from fully-parametric multi-state models, and connects with the mstate package (de Wreede, Fiocco, and Putter 2011). This article explains the methods and design principles of the package, giving several worked examples of its use. PMID:29593450

Three-dimensional slice cultures from murine fetal gut for investigations of the enteric nervous system.

PubMed

Metzger, Marco; Bareiss, Petra M; Nikolov, Ivan; Skutella, Thomas; Just, Lothar

2007-01-01

Three-dimensional intestinal cultures offer new possibilities for the examination of growth potential, analysis of time specific gene expression, and spatial cellular arrangement of enteric nervous system in an organotypical environment. We present an easy to produce in vitro model of the enteric nervous system for analysis and manipulation of cellular differentiation processes. Slice cultures of murine fetal colon were cultured on membrane inserts for up to 2 weeks without loss of autonomous contractility. After slice preparation, cultured tissue reorganized within the first days in vitro. Afterward, the culture possessed more than 35 cell layers, including high prismatic epithelial cells, smooth muscle cells, glial cells, and neurons analyzed by immunohistochemistry. The contraction frequency of intestinal slice culture could be modulated by the neurotransmitter serotonin and the sodium channel blocker tetrodotoxin. Coculture experiments with cultured neurospheres isolated from enhanced green fluorescent protein (eGFP) transgenic mice demonstrated that differentiating eGFP-positive neurons were integrated into the intestinal tissue culture. This slice culture model of enteric nervous system proved to be useful for studying cell-cell interactions, cellular signaling, and cell differentiation processes in a three-dimensional cell arrangement.

Model risk for European-style stock index options.

PubMed

Gençay, Ramazan; Gibson, Rajna

2007-01-01

In empirical modeling, there have been two strands for pricing in the options literature, namely the parametric and nonparametric models. Often, the support for the nonparametric methods is based on a benchmark such as the Black-Scholes (BS) model with constant volatility. In this paper, we study the stochastic volatility (SV) and stochastic volatility random jump (SVJ) models as parametric benchmarks against feedforward neural network (FNN) models, a class of neural network models. Our choice for FNN models is due to their well-studied universal approximation properties of an unknown function and its partial derivatives. Since the partial derivatives of an option pricing formula are risk pricing tools, an accurate estimation of the unknown option pricing function is essential for pricing and hedging. Our findings indicate that FNN models offer themselves as robust option pricing tools, over their sophisticated parametric counterparts in predictive settings. There are two routes to explain the superiority of FNN models over the parametric models in forecast settings. These are nonnormality of return distributions and adaptive learning.

Model Comparison of Bayesian Semiparametric and Parametric Structural Equation Models

ERIC Educational Resources Information Center

Song, Xin-Yuan; Xia, Ye-Mao; Pan, Jun-Hao; Lee, Sik-Yum

2011-01-01

Structural equation models have wide applications. One of the most important issues in analyzing structural equation models is model comparison. This article proposes a Bayesian model comparison statistic, namely the "L[subscript nu]"-measure for both semiparametric and parametric structural equation models. For illustration purposes, we consider…

[Simulation and data analysis of stereological modeling based on virtual slices].

PubMed

Wang, Hao; Shen, Hong; Bai, Xiao-yan

2008-05-01

To establish a computer-assisted stereological model for simulating the process of slice section and evaluate the relationship between section surface and estimated three-dimensional structure. The model was designed by mathematic method as a win32 software based on the MFC using Microsoft visual studio as IDE for simulating the infinite process of sections and analysis of the data derived from the model. The linearity of the fitting of the model was evaluated by comparison with the traditional formula. The win32 software based on this algorithm allowed random sectioning of the particles distributed randomly in an ideal virtual cube. The stereological parameters showed very high throughput (>94.5% and 92%) in homogeneity and independence tests. The data of density, shape and size of the section were tested to conform to normal distribution. The output of the model and that from the image analysis system showed statistical correlation and consistency. The algorithm we described can be used for evaluating the stereologic parameters of the structure of tissue slices.

Comparing of Cox model and parametric models in analysis of effective factors on event time of neuropathy in patients with type 2 diabetes.

PubMed

Kargarian-Marvasti, Sadegh; Rimaz, Shahnaz; Abolghasemi, Jamileh; Heydari, Iraj

2017-01-01

Cox proportional hazard model is the most common method for analyzing the effects of several variables on survival time. However, under certain circumstances, parametric models give more precise estimates to analyze survival data than Cox. The purpose of this study was to investigate the comparative performance of Cox and parametric models in a survival analysis of factors affecting the event time of neuropathy in patients with type 2 diabetes. This study included 371 patients with type 2 diabetes without neuropathy who were registered at Fereydunshahr diabetes clinic. Subjects were followed up for the development of neuropathy between 2006 to March 2016. To investigate the factors influencing the event time of neuropathy, significant variables in univariate model ( P < 0.20) were entered into the multivariate Cox and parametric models ( P < 0.05). In addition, Akaike information criterion (AIC) and area under ROC curves were used to evaluate the relative goodness of fitted model and the efficiency of each procedure, respectively. Statistical computing was performed using R software version 3.2.3 (UNIX platforms, Windows and MacOS). Using Kaplan-Meier, survival time of neuropathy was computed 76.6 ± 5 months after initial diagnosis of diabetes. After multivariate analysis of Cox and parametric models, ethnicity, high-density lipoprotein and family history of diabetes were identified as predictors of event time of neuropathy ( P < 0.05). According to AIC, "log-normal" model with the lowest Akaike's was the best-fitted model among Cox and parametric models. According to the results of comparison of survival receiver operating characteristics curves, log-normal model was considered as the most efficient and fitted model.

METHOXYCHLOR METABOLISM AND VITELLOGENESIS IN MALE RAINBOW TROUT LIVER SLICES

EPA Science Inventory

Induction of vitellogenin (VTG) in male fish has become an accepted biomarker to xenoestrogenicity. This study utilized the male rainbow trout liver slice model to determine the estrogenicity of parent compound, methoxychlor (MXC) and metabolites, di-hydroxy methoxychlor (HPTE) a...

Modelling the mid-infrared drying of sweet potato: kinetics, mass and heat transfer parameters, and energy consumption

NASA Astrophysics Data System (ADS)

Onwude, Daniel I.; Hashim, Norhashila; Abdan, Khalina; Janius, Rimfiel; Chen, Guangnan

2018-04-01

This study investigated the drying kinetics, mass and heat transfer characteristics of sweet potato slices (0.4-0.6 cm thickness) during drying based on mid-infrared experimental set-up (intensity of 1100-1400 W/m2). Thin layer drying models were used to evaluate the drying kinetics of sweet potato slices. Two analytical models (Fick's diffusion model, and Dincer and Dost model) were used to study the mass transfer behaviour of sweet potato slices with and without shrinkage during mid-infrared drying. The heat transfer flux between the emitter and sweet potato slices was also investigated. Results demonstrated that an increase in infrared intensity from 1100 W/m2 to 1400 W/m2 resulted in increased in average radiation heat flux by 3.4 times and a 15% reduction in the overall drying time. The two-term exponential model was found to be the best in predicting the drying kinetics of sweet potato slices during mid-infrared drying. The specific heat consumption varied from 0.91-4.82 kWh/kg. The effective moisture diffusivity with and without shrinkage using the Fick's diffusion model varied from 2.632 × 10-9 to 1.596 × 10-8 m2/s, and 1.24 × 10-8 to 2.4 × 10-8 m2/s using Dincer and Dost model, respectively. The obtained values of mass transfer coefficient, Biot number and activation energy varied from 5.99 × 10-6 to 1.17 × 10-5 m/s, 0.53 to 2.62, and 12.83 kJ/mol to 34.64 kJ/mol, respectively. The values obtained for Biot number implied the existence of simultaneous internal and external resistances. The findings further explained that mid-infrared intensity of 1100 W/m2 did not significantly affect the quality of sweet potato during drying, demonstrating a great potential of applying low intensity mid-infrared radiation in the drying of agricultural crops.

Parametrically Guided Generalized Additive Models with Application to Mergers and Acquisitions Data

PubMed Central

Fan, Jianqing; Maity, Arnab; Wang, Yihui; Wu, Yichao

2012-01-01

Generalized nonparametric additive models present a flexible way to evaluate the effects of several covariates on a general outcome of interest via a link function. In this modeling framework, one assumes that the effect of each of the covariates is nonparametric and additive. However, in practice, often there is prior information available about the shape of the regression functions, possibly from pilot studies or exploratory analysis. In this paper, we consider such situations and propose an estimation procedure where the prior information is used as a parametric guide to fit the additive model. Specifically, we first posit a parametric family for each of the regression functions using the prior information (parametric guides). After removing these parametric trends, we then estimate the remainder of the nonparametric functions using a nonparametric generalized additive model, and form the final estimates by adding back the parametric trend. We investigate the asymptotic properties of the estimates and show that when a good guide is chosen, the asymptotic variance of the estimates can be reduced significantly while keeping the asymptotic variance same as the unguided estimator. We observe the performance of our method via a simulation study and demonstrate our method by applying to a real data set on mergers and acquisitions. PMID:23645976

Parametrically Guided Generalized Additive Models with Application to Mergers and Acquisitions Data.

PubMed

Fan, Jianqing; Maity, Arnab; Wang, Yihui; Wu, Yichao

2013-01-01

Generalized nonparametric additive models present a flexible way to evaluate the effects of several covariates on a general outcome of interest via a link function. In this modeling framework, one assumes that the effect of each of the covariates is nonparametric and additive. However, in practice, often there is prior information available about the shape of the regression functions, possibly from pilot studies or exploratory analysis. In this paper, we consider such situations and propose an estimation procedure where the prior information is used as a parametric guide to fit the additive model. Specifically, we first posit a parametric family for each of the regression functions using the prior information (parametric guides). After removing these parametric trends, we then estimate the remainder of the nonparametric functions using a nonparametric generalized additive model, and form the final estimates by adding back the parametric trend. We investigate the asymptotic properties of the estimates and show that when a good guide is chosen, the asymptotic variance of the estimates can be reduced significantly while keeping the asymptotic variance same as the unguided estimator. We observe the performance of our method via a simulation study and demonstrate our method by applying to a real data set on mergers and acquisitions.

Resource allocation for error resilient video coding over AWGN using optimization approach.

PubMed

An, Cheolhong; Nguyen, Truong Q

2008-12-01

The number of slices for error resilient video coding is jointly optimized with 802.11a-like media access control and the physical layers with automatic repeat request and rate compatible punctured convolutional code over additive white gaussian noise channel as well as channel times allocation for time division multiple access. For error resilient video coding, the relation between the number of slices and coding efficiency is analyzed and formulated as a mathematical model. It is applied for the joint optimization problem, and the problem is solved by a convex optimization method such as the primal-dual decomposition method. We compare the performance of a video communication system which uses the optimal number of slices with one that codes a picture as one slice. From numerical examples, end-to-end distortion of utility functions can be significantly reduced with the optimal slices of a picture especially at low signal-to-noise ratio.

Mathematical modelling of temperature effect on growth kinetics of Pseudomonas spp. on sliced mushroom (Agaricus bisporus).

PubMed

Tarlak, Fatih; Ozdemir, Murat; Melikoglu, Mehmet

2018-02-02

The growth data of Pseudomonas spp. on sliced mushrooms (Agaricus bisporus) stored between 4 and 28°C were obtained and fitted to three different primary models, known as the modified Gompertz, logistic and Baranyi models. The goodness of fit of these models was compared by considering the mean squared error (MSE) and the coefficient of determination for nonlinear regression (pseudo-R 2 ). The Baranyi model yielded the lowest MSE and highest pseudo-R 2 values. Therefore, the Baranyi model was selected as the best primary model. Maximum specific growth rate (r max ) and lag phase duration (λ) obtained from the Baranyi model were fitted to secondary models namely, the Ratkowsky and Arrhenius models. High pseudo-R 2 and low MSE values indicated that the Arrhenius model has a high goodness of fit to determine the effect of temperature on r max . Observed number of Pseudomonas spp. on sliced mushrooms from independent experiments was compared with the predicted number of Pseudomonas spp. with the models used by considering the B f and A f values. The B f and A f values were found to be 0.974 and 1.036, respectively. The correlation between the observed and predicted number of Pseudomonas spp. was high. Mushroom spoilage was simulated as a function of temperature with the models used. The models used for Pseudomonas spp. growth can provide a fast and cost-effective alternative to traditional microbiological techniques to determine the effect of storage temperature on product shelf-life. The models can be used to evaluate the growth behaviour of Pseudomonas spp. on sliced mushroom, set limits for the quantitative detection of the microbial spoilage and assess product shelf-life. Copyright © 2017 Elsevier B.V. All rights reserved.

Microarray analysis in rat liver slices correctly predicts in vivo hepatotoxicity.

PubMed

Elferink, M G L; Olinga, P; Draaisma, A L; Merema, M T; Bauerschmidt, S; Polman, J; Schoonen, W G; Groothuis, G M M

2008-06-15

The microarray technology, developed for the simultaneous analysis of a large number of genes, may be useful for the detection of toxicity in an early stage of the development of new drugs. The effect of different hepatotoxins was analyzed at the gene expression level in the rat liver both in vivo and in vitro. As in vitro model system the precision-cut liver slice model was used, in which all liver cell types are present in their natural architecture. This is important since drug-induced toxicity often is a multi-cellular process involving not only hepatocytes but also other cell types such as Kupffer and stellate cells. As model toxic compounds lipopolysaccharide (LPS, inducing inflammation), paracetamol (necrosis), carbon tetrachloride (CCl(4), fibrosis and necrosis) and gliotoxin (apoptosis) were used. The aim of this study was to validate the rat liver slice system as in vitro model system for drug-induced toxicity studies. The results of the microarray studies show that the in vitro profiles of gene expression cluster per compound and incubation time, and when analyzed in a commercial gene expression database, can predict the toxicity and pathology observed in vivo. Each toxic compound induces a specific pattern of gene expression changes. In addition, some common genes were up- or down-regulated with all toxic compounds. These data show that the rat liver slice system can be an appropriate tool for the prediction of multi-cellular liver toxicity. The same experiments and analyses are currently performed for the prediction of human specific toxicity using human liver slices.

Using channelized Hotelling observers to quantify temporal effects of medical liquid crystal displays on detection performance

NASA Astrophysics Data System (ADS)

Platiša, Ljiljana; Goossens, Bart; Vansteenkiste, Ewout; Badano, Aldo; Philips, Wilfried

2010-02-01

Clinical practice is rapidly moving in the direction of volumetric imaging. Often, radiologists interpret these images in liquid crystal displays at browsing rates of 30 frames per second or higher. However, recent studies suggest that the slow response of the display can compromise image quality. In order to quantify the temporal effect of medical displays on detection performance, we investigate two designs of a multi-slice channelized Hotelling observer (msCHO) model in the task of detecting a single-slice signal in multi-slice simulated images. The design of msCHO models is inspired by simplifying assumptions about how humans observe while viewing in the stack-browsing mode. For comparison, we consider a standard CHO applied only on the slice where the signal is located, recently used in a similar study. We refer to it as a single-slice CHO (ssCHO). Overall, our results confirm previous findings that the slow response of displays degrades the detection performance of the observers. More specifically, the observed performance range of msCHO designs is higher compared to the ssCHO suggesting that the extent and rate of degradation, though significant, may be less drastic than previously estimated by the ssCHO. Especially, the difference between msCHO and ssCHO is more significant for higher browsing speeds than for slow image sequences or static images. This, together with their design criteria driven by the assumptions about humans, makes the msCHO models promising candidates for further studies aimed at building anthropomorphic observer models for the stack-mode image presentation.

Microarray analysis in rat liver slices correctly predicts in vivo hepatotoxicity

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

Elferink, M.G.L.; Olinga, P.; Draaisma, A.L.

2008-06-15

The microarray technology, developed for the simultaneous analysis of a large number of genes, may be useful for the detection of toxicity in an early stage of the development of new drugs. The effect of different hepatotoxins was analyzed at the gene expression level in the rat liver both in vivo and in vitro. As in vitro model system the precision-cut liver slice model was used, in which all liver cell types are present in their natural architecture. This is important since drug-induced toxicity often is a multi-cellular process involving not only hepatocytes but also other cell types such asmore » Kupffer and stellate cells. As model toxic compounds lipopolysaccharide (LPS, inducing inflammation), paracetamol (necrosis), carbon tetrachloride (CCl{sub 4}, fibrosis and necrosis) and gliotoxin (apoptosis) were used. The aim of this study was to validate the rat liver slice system as in vitro model system for drug-induced toxicity studies. The results of the microarray studies show that the in vitro profiles of gene expression cluster per compound and incubation time, and when analyzed in a commercial gene expression database, can predict the toxicity and pathology observed in vivo. Each toxic compound induces a specific pattern of gene expression changes. In addition, some common genes were up- or down-regulated with all toxic compounds. These data show that the rat liver slice system can be an appropriate tool for the prediction of multi-cellular liver toxicity. The same experiments and analyses are currently performed for the prediction of human specific toxicity using human liver slices.« less

Reduction of irregular breathing artifacts in respiration-correlated CT images using a respiratory motion model.

PubMed

Hertanto, Agung; Zhang, Qinghui; Hu, Yu-Chi; Dzyubak, Oleksandr; Rimner, Andreas; Mageras, Gig S

2012-06-01

Respiration-correlated CT (RCCT) images produced with commonly used phase-based sorting of CT slices often exhibit discontinuity artifacts between CT slices, caused by cycle-to-cycle amplitude variations in respiration. Sorting based on the displacement of the respiratory signal yields slices at more consistent respiratory motion states and hence reduces artifacts, but missing image data (gaps) may occur. The authors report on the application of a respiratory motion model to produce an RCCT image set with reduced artifacts and without missing data. Input data consist of CT slices from a cine CT scan acquired while recording respiration by monitoring abdominal displacement. The model-based generation of RCCT images consists of four processing steps: (1) displacement-based sorting of CT slices to form volume images at 10 motion states over the cycle; (2) selection of a reference image without gaps and deformable registration between the reference image and each of the remaining images; (3) generation of the motion model by applying a principal component analysis to establish a relationship between displacement field and respiration signal at each motion state; (4) application of the motion model to deform the reference image into images at the 9 other motion states. Deformable image registration uses a modified fast free-form algorithm that excludes zero-intensity voxels, caused by missing data, from the image similarity term in the minimization function. In each iteration of the minimization, the displacement field in the gap regions is linearly interpolated from nearest neighbor nonzero intensity slices. Evaluation of the model-based RCCT examines three types of image sets: cine scans of a physical phantom programmed to move according to a patient respiratory signal, NURBS-based cardiac torso (NCAT) software phantom, and patient thoracic scans. Comparison in physical motion phantom shows that object distortion caused by variable motion amplitude in phase-based sorting is visibly reduced with model-based RCCT. Comparison of model-based RCCT to original NCAT images as ground truth shows best agreement at motion states whose displacement-sorted images have no missing slices, with mean and maximum discrepancies in lung of 1 and 3 mm, respectively. Larger discrepancies correlate with motion states having a larger number of missing slices in the displacement-sorted images. Artifacts in patient images at different motion states are also reduced. Comparison with displacement-sorted patient images as a ground truth shows that the model-based images closely reproduce the ground truth geometry at different motion states. Results in phantom and patient images indicate that the proposed method can produce RCCT image sets with reduced artifacts relative to phase-sorted images, without the gaps inherent in displacement-sorted images. The method requires a reference image at one motion state that has no missing data. Highly irregular breathing patterns can affect the method's performance, by introducing artifacts in the reference image (although reduced relative to phase-sorted images), or in decreased accuracy in the image prediction of motion states containing large regions of missing data. © 2012 American Association of Physicists in Medicine.

Vis-NIR hyperspectral imaging in visualizing moisture distribution of mango slices during microwave-vacuum drying.

PubMed

Pu, Yuan-Yuan; Sun, Da-Wen

2015-12-01

Mango slices were dried by microwave-vacuum drying using a domestic microwave oven equipped with a vacuum desiccator inside. Two lab-scale hyperspectral imaging (HSI) systems were employed for moisture prediction. The Page and the Two-term thin-layer drying models were suitable to describe the current drying process with a fitting goodness of R(2)=0.978. Partial least square (PLS) was applied to correlate the mean spectrum of each slice and reference moisture content. With three waveband selection strategies, optimal wavebands corresponding to moisture prediction were identified. The best model RC-PLS-2 (Rp(2)=0.972 and RMSEP=4.611%) was implemented into the moisture visualization procedure. Moisture distribution map clearly showed that the moisture content in the central part of the mango slices was lower than that of other parts. The present study demonstrated that hyperspectral imaging was a useful tool for non-destructively and rapidly measuring and visualizing the moisture content during drying process. Copyright © 2015 Elsevier Ltd. All rights reserved.

PRESS-based EFOR algorithm for the dynamic parametrical modeling of nonlinear MDOF systems

NASA Astrophysics Data System (ADS)

Liu, Haopeng; Zhu, Yunpeng; Luo, Zhong; Han, Qingkai

2017-09-01

In response to the identification problem concerning multi-degree of freedom (MDOF) nonlinear systems, this study presents the extended forward orthogonal regression (EFOR) based on predicted residual sums of squares (PRESS) to construct a nonlinear dynamic parametrical model. The proposed parametrical model is based on the non-linear autoregressive with exogenous inputs (NARX) model and aims to explicitly reveal the physical design parameters of the system. The PRESS-based EFOR algorithm is proposed to identify such a model for MDOF systems. By using the algorithm, we built a common-structured model based on the fundamental concept of evaluating its generalization capability through cross-validation. The resulting model aims to prevent over-fitting with poor generalization performance caused by the average error reduction ratio (AERR)-based EFOR algorithm. Then, a functional relationship is established between the coefficients of the terms and the design parameters of the unified model. Moreover, a 5-DOF nonlinear system is taken as a case to illustrate the modeling of the proposed algorithm. Finally, a dynamic parametrical model of a cantilever beam is constructed from experimental data. Results indicate that the dynamic parametrical model of nonlinear systems, which depends on the PRESS-based EFOR, can accurately predict the output response, thus providing a theoretical basis for the optimal design of modeling methods for MDOF nonlinear systems.

Semi-Automatic Modelling of Building FAÇADES with Shape Grammars Using Historic Building Information Modelling

NASA Astrophysics Data System (ADS)

Dore, C.; Murphy, M.

2013-02-01

This paper outlines a new approach for generating digital heritage models from laser scan or photogrammetric data using Historic Building Information Modelling (HBIM). HBIM is a plug-in for Building Information Modelling (BIM) software that uses parametric library objects and procedural modelling techniques to automate the modelling stage. The HBIM process involves a reverse engineering solution whereby parametric interactive objects representing architectural elements are mapped onto laser scan or photogrammetric survey data. A library of parametric architectural objects has been designed from historic manuscripts and architectural pattern books. These parametric objects were built using an embedded programming language within the ArchiCAD BIM software called Geometric Description Language (GDL). Procedural modelling techniques have been implemented with the same language to create a parametric building façade which automatically combines library objects based on architectural rules and proportions. Different configurations of the façade are controlled by user parameter adjustment. The automatically positioned elements of the façade can be subsequently refined using graphical editing while overlaying the model with orthographic imagery. Along with this semi-automatic method for generating façade models, manual plotting of library objects can also be used to generate a BIM model from survey data. After the 3D model has been completed conservation documents such as plans, sections, elevations and 3D views can be automatically generated for conservation projects.

Z/sub n/ Baxter model: symmetries and the Belavin parametrization

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

Richey, M.P.; Tracy, C.A.

1986-02-01

The Z/sub n/ Baxter model is an exactly solvable lattice model in the special case of the Belavin parametrization. For this parametrization the authors calculate the partition function in an antiferromagnetic region and the order parameter in a ferromagnetic region. They find that the order parameter is expressible in terms of a modular function of level n which for n=2 is the Onsager-Yang-Baxter result. In addition they determine the symmetry group of the finite lattice partition function for the general Z/sub n/ Baxter model.

Multi-parametric centrality method for graph network models

NASA Astrophysics Data System (ADS)

Ivanov, Sergei Evgenievich; Gorlushkina, Natalia Nikolaevna; Ivanova, Lubov Nikolaevna

2018-04-01

The graph model networks are investigated to determine centrality, weights and the significance of vertices. For centrality analysis appliesa typical method that includesany one of the properties of graph vertices. In graph theory, methods of analyzing centrality are used: in terms by degree, closeness, betweenness, radiality, eccentricity, page-rank, status, Katz and eigenvector. We have proposed a new method of multi-parametric centrality, which includes a number of basic properties of the network member. The mathematical model of multi-parametric centrality method is developed. Comparison of results for the presented method with the centrality methods is carried out. For evaluate the results for the multi-parametric centrality methodthe graph model with hundreds of vertices is analyzed. The comparative analysis showed the accuracy of presented method, includes simultaneously a number of basic properties of vertices.

Applying Statistical Models and Parametric Distance Measures for Music Similarity Search

NASA Astrophysics Data System (ADS)

Lukashevich, Hanna; Dittmar, Christian; Bastuck, Christoph

Automatic deriving of similarity relations between music pieces is an inherent field of music information retrieval research. Due to the nearly unrestricted amount of musical data, the real-world similarity search algorithms have to be highly efficient and scalable. The possible solution is to represent each music excerpt with a statistical model (ex. Gaussian mixture model) and thus to reduce the computational costs by applying the parametric distance measures between the models. In this paper we discuss the combinations of applying different parametric modelling techniques and distance measures and weigh the benefits of each one against the others.

Parametric Modeling for Fluid Systems

NASA Technical Reports Server (NTRS)

Pizarro, Yaritzmar Rosario; Martinez, Jonathan

2013-01-01

Fluid Systems involves different projects that require parametric modeling, which is a model that maintains consistent relationships between elements as is manipulated. One of these projects is the Neo Liquid Propellant Testbed, which is part of Rocket U. As part of Rocket U (Rocket University), engineers at NASA's Kennedy Space Center in Florida have the opportunity to develop critical flight skills as they design, build and launch high-powered rockets. To build the Neo testbed; hardware from the Space Shuttle Program was repurposed. Modeling for Neo, included: fittings, valves, frames and tubing, between others. These models help in the review process, to make sure regulations are being followed. Another fluid systems project that required modeling is Plant Habitat's TCUI test project. Plant Habitat is a plan to develop a large growth chamber to learn the effects of long-duration microgravity exposure to plants in space. Work for this project included the design and modeling of a duct vent for flow test. Parametric Modeling for these projects was done using Creo Parametric 2.0.

Housing price prediction: parametric versus semi-parametric spatial hedonic models

NASA Astrophysics Data System (ADS)

Montero, José-María; Mínguez, Román; Fernández-Avilés, Gema

2018-01-01

House price prediction is a hot topic in the economic literature. House price prediction has traditionally been approached using a-spatial linear (or intrinsically linear) hedonic models. It has been shown, however, that spatial effects are inherent in house pricing. This article considers parametric and semi-parametric spatial hedonic model variants that account for spatial autocorrelation, spatial heterogeneity and (smooth and nonparametrically specified) nonlinearities using penalized splines methodology. The models are represented as a mixed model that allow for the estimation of the smoothing parameters along with the other parameters of the model. To assess the out-of-sample performance of the models, the paper uses a database containing the price and characteristics of 10,512 homes in Madrid, Spain (Q1 2010). The results obtained suggest that the nonlinear models accounting for spatial heterogeneity and flexible nonlinear relationships between some of the individual or areal characteristics of the houses and their prices are the best strategies for house price prediction.

Brayton Power Conversion System Parametric Design Modelling for Nuclear Electric Propulsion

NASA Technical Reports Server (NTRS)

Ashe, Thomas L.; Otting, William D.

1993-01-01

The parametrically based closed Brayton cycle (CBC) computer design model was developed for inclusion into the NASA LeRC overall Nuclear Electric Propulsion (NEP) end-to-end systems model. The code is intended to provide greater depth to the NEP system modeling which is required to more accurately predict the impact of specific technology on system performance. The CBC model is parametrically based to allow for conducting detailed optimization studies and to provide for easy integration into an overall optimizer driver routine. The power conversion model includes the modeling of the turbines, alternators, compressors, ducting, and heat exchangers (hot-side heat exchanger and recuperator). The code predicts performance to significant detail. The system characteristics determined include estimates of mass, efficiency, and the characteristic dimensions of the major power conversion system components. These characteristics are parametrically modeled as a function of input parameters such as the aerodynamic configuration (axial or radial), turbine inlet temperature, cycle temperature ratio, power level, lifetime, materials, and redundancy.

Comparison Between Linear and Non-parametric Regression Models for Genome-Enabled Prediction in Wheat

PubMed Central

Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne

2012-01-01

In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models. PMID:23275882

Comparison between linear and non-parametric regression models for genome-enabled prediction in wheat.

PubMed

Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne

2012-12-01

In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models.

Bidirectional reflectance distribution function measurements and analysis of retroreflective materials.

PubMed

Belcour, Laurent; Pacanowski, Romain; Delahaie, Marion; Laville-Geay, Aude; Eupherte, Laure

2014-12-01

We compare the performance of various analytical retroreflecting bidirectional reflectance distribution function (BRDF) models to assess how they reproduce accurately measured data of retroreflecting materials. We introduce a new parametrization, the back vector parametrization, to analyze retroreflecting data, and we show that this parametrization better preserves the isotropy of data. Furthermore, we update existing BRDF models to improve the representation of retroreflective data.

Analysis and classification of commercial ham slice images using directional fractal dimension features.

PubMed

Mendoza, Fernando; Valous, Nektarios A; Allen, Paul; Kenny, Tony A; Ward, Paddy; Sun, Da-Wen

2009-02-01

This paper presents a novel and non-destructive approach to the appearance characterization and classification of commercial pork, turkey and chicken ham slices. Ham slice images were modelled using directional fractal (DF(0°;45°;90°;135°)) dimensions and a minimum distance classifier was adopted to perform the classification task. Also, the role of different colour spaces and the resolution level of the images on DF analysis were investigated. This approach was applied to 480 wafer thin ham slices from four types of hams (120 slices per type): i.e., pork (cooked and smoked), turkey (smoked) and chicken (roasted). DF features were extracted from digitalized intensity images in greyscale, and R, G, B, L(∗), a(∗), b(∗), H, S, and V colour components for three image resolution levels (100%, 50%, and 25%). Simulation results show that in spite of the complexity and high variability in colour and texture appearance, the modelling of ham slice images with DF dimensions allows the capture of differentiating textural features between the four commercial ham types. Independent DF features entail better discrimination than that using the average of four directions. However, DF dimensions reveal a high sensitivity to colour channel, orientation and image resolution for the fractal analysis. The classification accuracy using six DF dimension features (a(90°)(∗),a(135°)(∗),H(0°),H(45°),S(0°),H(90°)) was 93.9% for training data and 82.2% for testing data.

Validation of a Parametric Approach for 3d Fortification Modelling: Application to Scale Models

NASA Astrophysics Data System (ADS)

Jacquot, K.; Chevrier, C.; Halin, G.

2013-02-01

Parametric modelling approach applied to cultural heritage virtual representation is a field of research explored for years since it can address many limitations of digitising tools. For example, essential historical sources for fortification virtual reconstructions like plans-reliefs have several shortcomings when they are scanned. To overcome those problems, knowledge based-modelling can be used: knowledge models based on the analysis of theoretical literature of a specific domain such as bastioned fortification treatises can be the cornerstone of the creation of a parametric library of fortification components. Implemented in Grasshopper, these components are manually adjusted on the data available (i.e. 3D surveys of plans-reliefs or scanned maps). Most of the fortification area is now modelled and the question of accuracy assessment is raised. A specific method is used to evaluate the accuracy of the parametric components. The results of the assessment process will allow us to validate the parametric approach. The automation of the adjustment process can finally be planned. The virtual model of fortification is part of a larger project aimed at valorising and diffusing a very unique cultural heritage item: the collection of plans-reliefs. As such, knowledge models are precious assets when automation and semantic enhancements will be considered.

A Parametric Approach to Numerical Modeling of TKR Contact Forces

PubMed Central

Lundberg, Hannah J.; Foucher, Kharma C.; Wimmer, Markus A.

2009-01-01

In vivo knee contact forces are difficult to determine using numerical methods because there are more unknown forces than equilibrium equations available. We developed parametric methods for computing contact forces across the knee joint during the stance phase of level walking. Three-dimensional contact forces were calculated at two points of contact between the tibia and the femur, one on the lateral aspect of the tibial plateau, and one on the medial side. Muscle activations were parametrically varied over their physiologic range resulting in a solution space of contact forces. The obtained solution space was reasonably small and the resulting force pattern compared well to a previous model from the literature for kinematics and external kinetics from the same patient. Peak forces of the parametric model and the previous model were similar for the first half of the stance phase, but differed for the second half. The previous model did not take into account the transverse external moment about the knee and could not calculate muscle activation levels. Ultimately, the parametric model will result in more accurate contact force inputs for total knee simulators, as current inputs are not generally based on kinematics and kinetics inputs from TKR patients. PMID:19155015

Stock price forecasting for companies listed on Tehran stock exchange using multivariate adaptive regression splines model and semi-parametric splines technique

NASA Astrophysics Data System (ADS)

Rounaghi, Mohammad Mahdi; Abbaszadeh, Mohammad Reza; Arashi, Mohammad

2015-11-01

One of the most important topics of interest to investors is stock price changes. Investors whose goals are long term are sensitive to stock price and its changes and react to them. In this regard, we used multivariate adaptive regression splines (MARS) model and semi-parametric splines technique for predicting stock price in this study. The MARS model as a nonparametric method is an adaptive method for regression and it fits for problems with high dimensions and several variables. semi-parametric splines technique was used in this study. Smoothing splines is a nonparametric regression method. In this study, we used 40 variables (30 accounting variables and 10 economic variables) for predicting stock price using the MARS model and using semi-parametric splines technique. After investigating the models, we select 4 accounting variables (book value per share, predicted earnings per share, P/E ratio and risk) as influencing variables on predicting stock price using the MARS model. After fitting the semi-parametric splines technique, only 4 accounting variables (dividends, net EPS, EPS Forecast and P/E Ratio) were selected as variables effective in forecasting stock prices.

A Semi-parametric Transformation Frailty Model for Semi-competing Risks Survival Data

PubMed Central

Jiang, Fei; Haneuse, Sebastien

2016-01-01

In the analysis of semi-competing risks data interest lies in estimation and inference with respect to a so-called non-terminal event, the observation of which is subject to a terminal event. Multi-state models are commonly used to analyse such data, with covariate effects on the transition/intensity functions typically specified via the Cox model and dependence between the non-terminal and terminal events specified, in part, by a unit-specific shared frailty term. To ensure identifiability, the frailties are typically assumed to arise from a parametric distribution, specifically a Gamma distribution with mean 1.0 and variance, say, σ2. When the frailty distribution is misspecified, however, the resulting estimator is not guaranteed to be consistent, with the extent of asymptotic bias depending on the discrepancy between the assumed and true frailty distributions. In this paper, we propose a novel class of transformation models for semi-competing risks analysis that permit the non-parametric specification of the frailty distribution. To ensure identifiability, the class restricts to parametric specifications of the transformation and the error distribution; the latter are flexible, however, and cover a broad range of possible specifications. We also derive the semi-parametric efficient score under the complete data setting and propose a non-parametric score imputation method to handle right censoring; consistency and asymptotic normality of the resulting estimators is derived and small-sample operating characteristics evaluated via simulation. Although the proposed semi-parametric transformation model and non-parametric score imputation method are motivated by the analysis of semi-competing risks data, they are broadly applicable to any analysis of multivariate time-to-event outcomes in which a unit-specific shared frailty is used to account for correlation. Finally, the proposed model and estimation procedures are applied to a study of hospital readmission among patients diagnosed with pancreatic cancer. PMID:28439147

Gradient-free MCMC methods for dynamic causal modelling

DOE PAGES

Sengupta, Biswa; Friston, Karl J.; Penny, Will D.

2015-03-14

Here, we compare the performance of four gradient-free MCMC samplers (random walk Metropolis sampling, slice-sampling, adaptive MCMC sampling and population-based MCMC sampling with tempering) in terms of the number of independent samples they can produce per unit computational time. For the Bayesian inversion of a single-node neural mass model, both adaptive and population-based samplers are more efficient compared with random walk Metropolis sampler or slice-sampling; yet adaptive MCMC sampling is more promising in terms of compute time. Slice-sampling yields the highest number of independent samples from the target density -- albeit at almost 1000% increase in computational time, in comparisonmore » to the most efficient algorithm (i.e., the adaptive MCMC sampler).« less

Multislice spiral CT simulator for dynamic cardiopulmonary studies

NASA Astrophysics Data System (ADS)

De Francesco, Silvia; Ferreira da Silva, Augusto M.

2002-04-01

We've developed a Multi-slice Spiral CT Simulator modeling the acquisition process of a real tomograph over a 4-dimensional phantom (4D MCAT) of the human thorax. The simulator allows us to visually characterize artifacts due to insufficient temporal sampling and a priori evaluate the quality of the images obtained in cardio-pulmonary studies (both with single-/multi-slice and ECG gated acquisition processes). The simulating environment allows both for conventional and spiral scanning modes and includes a model of noise in the acquisition process. In case of spiral scanning, reconstruction facilities include longitudinal interpolation methods (360LI and 180LI both for single and multi-slice). Then, the reconstruction of the section is performed through FBP. The reconstructed images/volumes are affected by distortion due to insufficient temporal sampling of the moving object. The developed simulating environment allows us to investigate the nature of the distortion characterizing it qualitatively and quantitatively (using, for example, Herman's measures). Much of our work is focused on the determination of adequate temporal sampling and sinogram regularization techniques. At the moment, the simulator model is limited to the case of multi-slice tomograph, being planned as a next step of development the extension to cone beam or area detectors.

Formation of parametric images using mixed-effects models: a feasibility study.

PubMed

Huang, Husan-Ming; Shih, Yi-Yu; Lin, Chieh

2016-03-01

Mixed-effects models have been widely used in the analysis of longitudinal data. By presenting the parameters as a combination of fixed effects and random effects, mixed-effects models incorporating both within- and between-subject variations are capable of improving parameter estimation. In this work, we demonstrate the feasibility of using a non-linear mixed-effects (NLME) approach for generating parametric images from medical imaging data of a single study. By assuming that all voxels in the image are independent, we used simulation and animal data to evaluate whether NLME can improve the voxel-wise parameter estimation. For testing purposes, intravoxel incoherent motion (IVIM) diffusion parameters including perfusion fraction, pseudo-diffusion coefficient and true diffusion coefficient were estimated using diffusion-weighted MR images and NLME through fitting the IVIM model. The conventional method of non-linear least squares (NLLS) was used as the standard approach for comparison of the resulted parametric images. In the simulated data, NLME provides more accurate and precise estimates of diffusion parameters compared with NLLS. Similarly, we found that NLME has the ability to improve the signal-to-noise ratio of parametric images obtained from rat brain data. These data have shown that it is feasible to apply NLME in parametric image generation, and the parametric image quality can be accordingly improved with the use of NLME. With the flexibility to be adapted to other models or modalities, NLME may become a useful tool to improve the parametric image quality in the future. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

High resolution wind measurements for offshore wind energy development

NASA Technical Reports Server (NTRS)

Nghiem, Son Van (Inventor); Neumann, Gregory (Inventor)

2013-01-01

A method, apparatus, system, article of manufacture, and computer readable storage medium provide the ability to measure wind. Data at a first resolution (i.e., low resolution data) is collected by a satellite scatterometer. Thin slices of the data are determined. A collocation of the data slices are determined at each grid cell center to obtain ensembles of collocated data slices. Each ensemble of collocated data slices is decomposed into a mean part and a fluctuating part. The data is reconstructed at a second resolution from the mean part and a residue of the fluctuating part. A wind measurement is determined from the data at the second resolution using a wind model function. A description of the wind measurement is output.

Parametric modelling of cost data in medical studies.

PubMed

Nixon, R M; Thompson, S G

2004-04-30

The cost of medical resources used is often recorded for each patient in clinical studies in order to inform decision-making. Although cost data are generally skewed to the right, interest is in making inferences about the population mean cost. Common methods for non-normal data, such as data transformation, assuming asymptotic normality of the sample mean or non-parametric bootstrapping, are not ideal. This paper describes possible parametric models for analysing cost data. Four example data sets are considered, which have different sample sizes and degrees of skewness. Normal, gamma, log-normal, and log-logistic distributions are fitted, together with three-parameter versions of the latter three distributions. Maximum likelihood estimates of the population mean are found; confidence intervals are derived by a parametric BC(a) bootstrap and checked by MCMC methods. Differences between model fits and inferences are explored.Skewed parametric distributions fit cost data better than the normal distribution, and should in principle be preferred for estimating the population mean cost. However for some data sets, we find that models that fit badly can give similar inferences to those that fit well. Conversely, particularly when sample sizes are not large, different parametric models that fit the data equally well can lead to substantially different inferences. We conclude that inferences are sensitive to choice of statistical model, which itself can remain uncertain unless there is enough data to model the tail of the distribution accurately. Investigating the sensitivity of conclusions to choice of model should thus be an essential component of analysing cost data in practice. Copyright 2004 John Wiley & Sons, Ltd.

Coupled oscillators in identification of nonlinear damping of a real parametric pendulum

NASA Astrophysics Data System (ADS)

Olejnik, Paweł; Awrejcewicz, Jan

2018-01-01

A damped parametric pendulum with friction is identified twice by means of its precise and imprecise mathematical model. A laboratory test stand designed for experimental investigations of nonlinear effects determined by a viscous resistance and the stick-slip phenomenon serves as the model mechanical system. An influence of accurateness of mathematical modeling on the time variability of the nonlinear damping coefficient of the oscillator is proved. A free decay response of a precisely and imprecisely modeled physical pendulum is dependent on two different time-varying coefficients of damping. The coefficients of the analyzed parametric oscillator are identified with the use of a new semi-empirical method based on a coupled oscillators approach, utilizing the fractional order derivative of the discrete measurement series treated as an input to the numerical model. Results of application of the proposed method of identification of the nonlinear coefficients of the damped parametric oscillator have been illustrated and extensively discussed.

Modeling the directivity of parametric loudspeaker

NASA Astrophysics Data System (ADS)

Shi, Chuang; Gan, Woon-Seng

2012-09-01

The emerging applications of the parametric loudspeaker, such as 3D audio, demands accurate directivity control at the audible frequency (i.e. the difference frequency). Though the delay-and-sum beamforming has been proven adequate to adjust the steering angles of the parametric loudspeaker, accurate prediction of the mainlobe and sidelobes remains a challenging problem. It is mainly because of the approximations that are used to derive the directivity of the difference frequency from the directivity of the primary frequency, and the mismatches between the theoretical directivity and the measured directivity caused by system errors incurred at different stages of the implementation. In this paper, we propose a directivity model of the parametric loudspeaker. The directivity model consists of two tuning vectors corresponding to the spacing error and the weight error for the primary frequency. The directivity model adopts a modified form of the product directivity principle for the difference frequency to further improve the modeling accuracy.

Simultaneous application of microwave energy and hot air to whole drying process of apple slices: drying kinetics, modeling, temperature profile and energy aspect

NASA Astrophysics Data System (ADS)

Horuz, Erhan; Bozkurt, Hüseyin; Karataş, Haluk; Maskan, Medeni

2018-02-01

Drying kinetics, modeling, temperature profile and energy indices were investigated in apple slices during drying by a specially designed microwave-hot air domestic hybrid oven at the following conditions: 120, 150 and 180 W microwave powers coupled with 50, 60 and 70 °C air temperatures. Both sources of energy were applied simultaneously during the whole drying processes. The drying process continued until the moisture content of apple slices reached to 20% from 86.3% (wet basis, w.b). Drying times ranged from 330 to 800 min and decreased with increasing microwave power and air temperatures. The constant rate period was only observed at low microwave powers and air temperatures. Two falling rate periods were observed. Temperature of apple slices sharply increased within the first 60 min, then reached equilibrium with drying medium and finally increased at the end of the drying process. In order to describe drying behavior of apple slices nine empirical models were applied. The Modified Logistic Model fitted the best our experimental data ( R 2 = 0.9955-0.9998; χ 2 = 3.46 × 10-5-7.85 × 10-4 and RMSE = 0.0052-0.0221). The effective moisture and thermal diffusivities were calculated by Fick's second law and ranged from 1.42 × 10-9 to 3.31 × 10-9 m2/s and 7.70 × 10-9 to 12.54 × 10-9 m2/s, respectively. The activation energy ( Ea) values were calculated from effective moisture diffusivity ( Deff), thermal diffusivity ( α) and the rate constant of the best model ( k). The Ea values found from these three terms were similar and varied from 13.04 to 33.52 kJ/mol. Energy consumption and specific energy requirement of the hybrid drying of apple slices decreased and energy efficiency of the drying system increased with increasing microwave power and air temperature. Apples can be dried rapidly and effectively by use of the hybrid technique.

Cardiac tissue slices: preparation, handling, and successful optical mapping.

PubMed

Wang, Ken; Lee, Peter; Mirams, Gary R; Sarathchandra, Padmini; Borg, Thomas K; Gavaghan, David J; Kohl, Peter; Bollensdorff, Christian

2015-05-01

Cardiac tissue slices are becoming increasingly popular as a model system for cardiac electrophysiology and pharmacology research and development. Here, we describe in detail the preparation, handling, and optical mapping of transmembrane potential and intracellular free calcium concentration transients (CaT) in ventricular tissue slices from guinea pigs and rabbits. Slices cut in the epicardium-tangential plane contained well-aligned in-slice myocardial cell strands ("fibers") in subepicardial and midmyocardial sections. Cut with a high-precision slow-advancing microtome at a thickness of 350 to 400 μm, tissue slices preserved essential action potential (AP) properties of the precutting Langendorff-perfused heart. We identified the need for a postcutting recovery period of 36 min (guinea pig) and 63 min (rabbit) to reach 97.5% of final steady-state values for AP duration (APD) (identified by exponential fitting). There was no significant difference between the postcutting recovery dynamics in slices obtained using 2,3-butanedione 2-monoxime or blebistatin as electromechanical uncouplers during the cutting process. A rapid increase in APD, seen after cutting, was caused by exposure to ice-cold solution during the slicing procedure, not by tissue injury, differences in uncouplers, or pH-buffers (bicarbonate; HEPES). To characterize intrinsic patterns of CaT, AP, and conduction, a combination of multipoint and field stimulation should be used to avoid misinterpretation based on source-sink effects. In summary, we describe in detail the preparation, mapping, and data analysis approaches for reproducible cardiac tissue slice-based investigations into AP and CaT dynamics. Copyright © 2015 the American Physiological Society.

Correlation between model observers in uniform background and human observers in patient liver background for a low-contrast detection task in CT

NASA Astrophysics Data System (ADS)

Gong, Hao; Yu, Lifeng; Leng, Shuai; Dilger, Samantha; Zhou, Wei; Ren, Liqiang; McCollough, Cynthia H.

2018-03-01

Channelized Hotelling observer (CHO) has demonstrated strong correlation with human observer (HO) in both single-slice viewing mode and multi-slice viewing mode in low-contrast detection tasks with uniform background. However, it remains unknown if the simplest single-slice CHO in uniform background can be used to predict human observer performance in more realistic tasks that involve patient anatomical background and multi-slice viewing mode. In this study, we aim to investigate the correlation between CHO in a uniform water background and human observer performance at a multi-slice viewing mode on patient liver background for a low-contrast lesion detection task. The human observer study was performed on CT images from 7 abdominal CT exams. A noise insertion tool was employed to synthesize CT scans at two additional dose levels. A validated lesion insertion tool was used to numerically insert metastatic liver lesions of various sizes and contrasts into both phantom and patient images. We selected 12 conditions out of 72 possible experimental conditions to evaluate the correlation at various radiation doses, lesion sizes, lesion contrasts and reconstruction algorithms. CHO with both single and multi-slice viewing modes were strongly correlated with HO. The corresponding Pearson's correlation coefficient was 0.982 (with 95% confidence interval (CI) [0.936, 0.995]) and 0.989 (with 95% CI of [0.960, 0.997]) in multi-slice and single-slice viewing modes, respectively. Therefore, this study demonstrated the potential to use the simplest single-slice CHO to assess image quality for more realistic clinically relevant CT detection tasks.

Cardiac tissue slices: preparation, handling, and successful optical mapping

PubMed Central

Wang, Ken; Lee, Peter; Mirams, Gary R.; Sarathchandra, Padmini; Borg, Thomas K.; Gavaghan, David J.; Kohl, Peter

2015-01-01

Cardiac tissue slices are becoming increasingly popular as a model system for cardiac electrophysiology and pharmacology research and development. Here, we describe in detail the preparation, handling, and optical mapping of transmembrane potential and intracellular free calcium concentration transients (CaT) in ventricular tissue slices from guinea pigs and rabbits. Slices cut in the epicardium-tangential plane contained well-aligned in-slice myocardial cell strands (“fibers”) in subepicardial and midmyocardial sections. Cut with a high-precision slow-advancing microtome at a thickness of 350 to 400 μm, tissue slices preserved essential action potential (AP) properties of the precutting Langendorff-perfused heart. We identified the need for a postcutting recovery period of 36 min (guinea pig) and 63 min (rabbit) to reach 97.5% of final steady-state values for AP duration (APD) (identified by exponential fitting). There was no significant difference between the postcutting recovery dynamics in slices obtained using 2,3-butanedione 2-monoxime or blebistatin as electromechanical uncouplers during the cutting process. A rapid increase in APD, seen after cutting, was caused by exposure to ice-cold solution during the slicing procedure, not by tissue injury, differences in uncouplers, or pH-buffers (bicarbonate; HEPES). To characterize intrinsic patterns of CaT, AP, and conduction, a combination of multipoint and field stimulation should be used to avoid misinterpretation based on source-sink effects. In summary, we describe in detail the preparation, mapping, and data analysis approaches for reproducible cardiac tissue slice-based investigations into AP and CaT dynamics. PMID:25595366

Parametric Cost Models for Space Telescopes

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Henrichs, Todd; Dollinger, Courtney

2010-01-01

Multivariable parametric cost models for space telescopes provide several benefits to designers and space system project managers. They identify major architectural cost drivers and allow high-level design trades. They enable cost-benefit analysis for technology development investment. And, they provide a basis for estimating total project cost. A survey of historical models found that there is no definitive space telescope cost model. In fact, published models vary greatly [1]. Thus, there is a need for parametric space telescopes cost models. An effort is underway to develop single variable [2] and multi-variable [3] parametric space telescope cost models based on the latest available data and applying rigorous analytical techniques. Specific cost estimating relationships (CERs) have been developed which show that aperture diameter is the primary cost driver for large space telescopes; technology development as a function of time reduces cost at the rate of 50% per 17 years; it costs less per square meter of collecting aperture to build a large telescope than a small telescope; and increasing mass reduces cost.

Enhancement of drying and rehydration characteristics of okra by ultrasound pre-treatment application

NASA Astrophysics Data System (ADS)

Tüfekçi, Senem; Özkal, Sami Gökhan

2017-07-01

Effect of ultrasound application prior to hot air drying on drying and rehydration kinetics, rehydration ratio and microstructure of okra slices were investigated. For this purpose, the selected parameters are ultrasound pre-treatment time (10, 20 and 30 min), ultrasound amplitude (55 and 100%) and the temperature of drying air (60 and 70 °C). 5 mm thick cylindrical shaped okra slices were used in the experiments. The samples were immersed in water and ultrasonic pre-treatments were done in water with ultrasonic probe connected to an ultrasonic generator with 20 kHz frequency. Pre-treated samples were dried in a tray drier with a 0.3 m/s air velocity. Ultrasound pre-treatment affected the drying rate of the okra slices significantly. Drying time of okra slices was decreased by the application of ultrasound pre-treatment. Modified Page model found to be the most suitable model for describing the drying characteristics of okra slices. Improvements in rehydration properties of the dried samples were observed due to the ultrasound pre-treatment. The influence of the ultrasound pre-treatment on microstructure was clearly observed through scanning electron microscopy images of the dried samples. As the amplitude of ultrasound increased the changes in structure of the okra tissue increased.

Development of Multi-slice Analytical Tool to Support BIM-based Design Process

NASA Astrophysics Data System (ADS)

Atmodiwirjo, P.; Johanes, M.; Yatmo, Y. A.

2017-03-01

This paper describes the on-going development of computational tool to analyse architecture and interior space based on multi-slice representation approach that is integrated with Building Information Modelling (BIM). Architecture and interior space is experienced as a dynamic entity, which have the spatial properties that might be variable from one part of space to another, therefore the representation of space through standard architectural drawings is sometimes not sufficient. The representation of space as a series of slices with certain properties in each slice becomes important, so that the different characteristics in each part of space could inform the design process. The analytical tool is developed for use as a stand-alone application that utilises the data exported from generic BIM modelling tool. The tool would be useful to assist design development process that applies BIM, particularly for the design of architecture and interior spaces that are experienced as continuous spaces. The tool allows the identification of how the spatial properties change dynamically throughout the space and allows the prediction of the potential design problems. Integrating the multi-slice analytical tool in BIM-based design process thereby could assist the architects to generate better design and to avoid unnecessary costs that are often caused by failure to identify problems during design development stages.

Spatial assessment of soluble solid contents on apple slices using hyperspectral imaging

USDA-ARS?s Scientific Manuscript database

A partial least squares regression (PLSR) model to map internal soluble solids content (SSC) of apples using visible/near-infrared (VNIR) hyperspectral imaging was developed. The reflectance spectra of sliced apples were extracted from hyperspectral absorbance images obtained in the 400e1000 nm rang...

Multiresponse semiparametric regression for modelling the effect of regional socio-economic variables on the use of information technology

NASA Astrophysics Data System (ADS)

Wibowo, Wahyu; Wene, Chatrien; Budiantara, I. Nyoman; Permatasari, Erma Oktania

2017-03-01

Multiresponse semiparametric regression is simultaneous equation regression model and fusion of parametric and nonparametric model. The regression model comprise several models and each model has two components, parametric and nonparametric. The used model has linear function as parametric and polynomial truncated spline as nonparametric component. The model can handle both linearity and nonlinearity relationship between response and the sets of predictor variables. The aim of this paper is to demonstrate the application of the regression model for modeling of effect of regional socio-economic on use of information technology. More specific, the response variables are percentage of households has access to internet and percentage of households has personal computer. Then, predictor variables are percentage of literacy people, percentage of electrification and percentage of economic growth. Based on identification of the relationship between response and predictor variable, economic growth is treated as nonparametric predictor and the others are parametric predictors. The result shows that the multiresponse semiparametric regression can be applied well as indicate by the high coefficient determination, 90 percent.

Non-parametric directionality analysis - Extension for removal of a single common predictor and application to time series.

PubMed

Halliday, David M; Senik, Mohd Harizal; Stevenson, Carl W; Mason, Rob

2016-08-01

The ability to infer network structure from multivariate neuronal signals is central to computational neuroscience. Directed network analyses typically use parametric approaches based on auto-regressive (AR) models, where networks are constructed from estimates of AR model parameters. However, the validity of using low order AR models for neurophysiological signals has been questioned. A recent article introduced a non-parametric approach to estimate directionality in bivariate data, non-parametric approaches are free from concerns over model validity. We extend the non-parametric framework to include measures of directed conditional independence, using scalar measures that decompose the overall partial correlation coefficient summatively by direction, and a set of functions that decompose the partial coherence summatively by direction. A time domain partial correlation function allows both time and frequency views of the data to be constructed. The conditional independence estimates are conditioned on a single predictor. The framework is applied to simulated cortical neuron networks and mixtures of Gaussian time series data with known interactions. It is applied to experimental data consisting of local field potential recordings from bilateral hippocampus in anaesthetised rats. The framework offers a non-parametric approach to estimation of directed interactions in multivariate neuronal recordings, and increased flexibility in dealing with both spike train and time series data. The framework offers a novel alternative non-parametric approach to estimate directed interactions in multivariate neuronal recordings, and is applicable to spike train and time series data. Copyright © 2016 Elsevier B.V. All rights reserved.

Improvements in Sensible Heat-Flux Parametrization in the High-Resolution Regional Model (HRM) Through the Modified Treatment of the Roughness Length for Heat

NASA Astrophysics Data System (ADS)

Anurose, T. J.; Subrahamanyam, D. Bala

2013-06-01

We discuss the impact of the differential treatment of the roughness lengths for momentum and heat (z_{0m} and z_{0h}) in the flux parametrization scheme of the high-resolution regional model (HRM) for a heterogeneous terrain centred around Thiruvananthapuram, India (8.5°N, 76.9°E). The magnitudes of sensible heat flux ( H) obtained from HRM simulations using the original parametrization scheme differed drastically from the concurrent in situ observations. With a view to improving the performance of this parametrization scheme, two distinct modifications are incorporated: (1) In the first method, a constant value of 100 is assigned to the z_{0m}/z_{0h} ratio; (2) and in the second approach, this ratio is treated as a function of time. Both these modifications in the HRM model showed significant improvements in the H simulations for Thiruvananthapuram and its adjoining regions. Results obtained from the present study provide a first-ever comparison of H simulations using the modified parametrization scheme in the HRM model with in situ observations for the Indian coastal region, and suggest a differential treatment of z_{0m} and z_{0h} in the flux parametrization scheme.

Estimating technical efficiency in the hospital sector with panel data: a comparison of parametric and non-parametric techniques.

PubMed

Siciliani, Luigi

2006-01-01

Policy makers are increasingly interested in developing performance indicators that measure hospital efficiency. These indicators may give the purchasers of health services an additional regulatory tool to contain health expenditure. Using panel data, this study compares different parametric (econometric) and non-parametric (linear programming) techniques for the measurement of a hospital's technical efficiency. This comparison was made using a sample of 17 Italian hospitals in the years 1996-9. Highest correlations are found in the efficiency scores between the non-parametric data envelopment analysis under the constant returns to scale assumption (DEA-CRS) and several parametric models. Correlation reduces markedly when using more flexible non-parametric specifications such as data envelopment analysis under the variable returns to scale assumption (DEA-VRS) and the free disposal hull (FDH) model. Correlation also generally reduces when moving from one output to two-output specifications. This analysis suggests that there is scope for developing performance indicators at hospital level using panel data, but it is important that extensive sensitivity analysis is carried out if purchasers wish to make use of these indicators in practice.

A numerical study on piezoelectric energy harvesting by combining transverse galloping and parametric instability phenomena

NASA Astrophysics Data System (ADS)

Franzini, Guilherme Rosa; Santos, Rebeca Caramêz Saraiva; Pesce, Celso Pupo

2017-12-01

This paper aims to numerically investigate the effects of parametric instability on piezoelectric energy harvesting from the transverse galloping of a square prism. A two degrees-of-freedom reduced-order model for this problem is proposed and numerically integrated. A usual quasi-steady galloping model is applied, where the transverse force coefficient is adopted as a cubic polynomial function with respect to the angle of attack. Time-histories of nondimensional prism displacement, electric voltage and power dissipated at both the dashpot and the electrical resistance are obtained as functions of the reduced velocity. Both, oscillation amplitude and electric voltage, increased with the reduced velocity for all parametric excitation conditions tested. For low values of reduced velocity, 2:1 parametric excitation enhances the electric voltage. On the other hand, for higher reduced velocities, a 1:1 parametric excitation (i.e., the same as the natural frequency) enhances both oscillation amplitude and electric voltage. It has been also found that, depending on the parametric excitation frequency, the harvested electrical power can be amplified in 70% when compared to the case under no parametric excitation.

Genetic Algorithm Based Framework for Automation of Stochastic Modeling of Multi-Season Streamflows

NASA Astrophysics Data System (ADS)

Srivastav, R. K.; Srinivasan, K.; Sudheer, K.

2009-05-01

Synthetic streamflow data generation involves the synthesis of likely streamflow patterns that are statistically indistinguishable from the observed streamflow data. The various kinds of stochastic models adopted for multi-season streamflow generation in hydrology are: i) parametric models which hypothesize the form of the periodic dependence structure and the distributional form a priori (examples are PAR, PARMA); disaggregation models that aim to preserve the correlation structure at the periodic level and the aggregated annual level; ii) Nonparametric models (examples are bootstrap/kernel based methods), which characterize the laws of chance, describing the stream flow process, without recourse to prior assumptions as to the form or structure of these laws; (k-nearest neighbor (k-NN), matched block bootstrap (MABB)); non-parametric disaggregation model. iii) Hybrid models which blend both parametric and non-parametric models advantageously to model the streamflows effectively. Despite many of these developments that have taken place in the field of stochastic modeling of streamflows over the last four decades, accurate prediction of the storage and the critical drought characteristics has been posing a persistent challenge to the stochastic modeler. This is partly because, usually, the stochastic streamflow model parameters are estimated by minimizing a statistically based objective function (such as maximum likelihood (MLE) or least squares (LS) estimation) and subsequently the efficacy of the models is being validated based on the accuracy of prediction of the estimates of the water-use characteristics, which requires large number of trial simulations and inspection of many plots and tables. Still accurate prediction of the storage and the critical drought characteristics may not be ensured. In this study a multi-objective optimization framework is proposed to find the optimal hybrid model (blend of a simple parametric model, PAR(1) model and matched block bootstrap (MABB) ) based on the explicit objective functions of minimizing the relative bias and relative root mean square error in estimating the storage capacity of the reservoir. The optimal parameter set of the hybrid model is obtained based on the search over a multi- dimensional parameter space (involving simultaneous exploration of the parametric (PAR(1)) as well as the non-parametric (MABB) components). This is achieved using the efficient evolutionary search based optimization tool namely, non-dominated sorting genetic algorithm - II (NSGA-II). This approach helps in reducing the drudgery involved in the process of manual selection of the hybrid model, in addition to predicting the basic summary statistics dependence structure, marginal distribution and water-use characteristics accurately. The proposed optimization framework is used to model the multi-season streamflows of River Beaver and River Weber of USA. In case of both the rivers, the proposed GA-based hybrid model yields a much better prediction of the storage capacity (where simultaneous exploration of both parametric and non-parametric components is done) when compared with the MLE-based hybrid models (where the hybrid model selection is done in two stages, thus probably resulting in a sub-optimal model). This framework can be further extended to include different linear/non-linear hybrid stochastic models at other temporal and spatial scales as well.

Protocols and characterization data for 2D, 3D, and slice-based tumor models from the PREDECT project.

PubMed

de Hoogt, Ronald; Estrada, Marta F; Vidic, Suzana; Davies, Emma J; Osswald, Annika; Barbier, Michael; Santo, Vítor E; Gjerde, Kjersti; van Zoggel, Hanneke J A A; Blom, Sami; Dong, Meng; Närhi, Katja; Boghaert, Erwin; Brito, Catarina; Chong, Yolanda; Sommergruber, Wolfgang; van der Kuip, Heiko; van Weerden, Wytske M; Verschuren, Emmy W; Hickman, John; Graeser, Ralph

2017-11-21

Two-dimensional (2D) culture of cancer cells in vitro does not recapitulate the three-dimensional (3D) architecture, heterogeneity and complexity of human tumors. More representative models are required that better reflect key aspects of tumor biology. These are essential studies of cancer biology and immunology as well as for target validation and drug discovery. The Innovative Medicines Initiative (IMI) consortium PREDECT (www.predect.eu) characterized in vitro models of three solid tumor types with the goal to capture elements of tumor complexity and heterogeneity. 2D culture and 3D mono- and stromal co-cultures of increasing complexity, and precision-cut tumor slice models were established. Robust protocols for the generation of these platforms are described. Tissue microarrays were prepared from all the models, permitting immunohistochemical analysis of individual cells, capturing heterogeneity. 3D cultures were also characterized using image analysis. Detailed step-by-step protocols, exemplary datasets from the 2D, 3D, and slice models, and refined analytical methods were established and are presented.

Protocols and characterization data for 2D, 3D, and slice-based tumor models from the PREDECT project

PubMed Central

de Hoogt, Ronald; Estrada, Marta F.; Vidic, Suzana; Davies, Emma J.; Osswald, Annika; Barbier, Michael; Santo, Vítor E.; Gjerde, Kjersti; van Zoggel, Hanneke J. A. A.; Blom, Sami; Dong, Meng; Närhi, Katja; Boghaert, Erwin; Brito, Catarina; Chong, Yolanda; Sommergruber, Wolfgang; van der Kuip, Heiko; van Weerden, Wytske M.; Verschuren, Emmy W.; Hickman, John; Graeser, Ralph

2017-01-01

Two-dimensional (2D) culture of cancer cells in vitro does not recapitulate the three-dimensional (3D) architecture, heterogeneity and complexity of human tumors. More representative models are required that better reflect key aspects of tumor biology. These are essential studies of cancer biology and immunology as well as for target validation and drug discovery. The Innovative Medicines Initiative (IMI) consortium PREDECT (www.predect.eu) characterized in vitro models of three solid tumor types with the goal to capture elements of tumor complexity and heterogeneity. 2D culture and 3D mono- and stromal co-cultures of increasing complexity, and precision-cut tumor slice models were established. Robust protocols for the generation of these platforms are described. Tissue microarrays were prepared from all the models, permitting immunohistochemical analysis of individual cells, capturing heterogeneity. 3D cultures were also characterized using image analysis. Detailed step-by-step protocols, exemplary datasets from the 2D, 3D, and slice models, and refined analytical methods were established and are presented. PMID:29160867

Probing kinematics and fate of the Universe with linearly time-varying deceleration parameter

NASA Astrophysics Data System (ADS)

Akarsu, Özgür; Dereli, Tekin; Kumar, Suresh; Xu, Lixin

2014-02-01

The parametrizations q = q 0+ q 1 z and q = q 0+ q 1(1 - a/ a 0) (Chevallier-Polarski-Linder parametrization) of the deceleration parameter, which are linear in cosmic redshift z and scale factor a , have been frequently utilized in the literature to study the kinematics of the Universe. In this paper, we follow a strategy that leads to these two well-known parametrizations of the deceleration parameter as well as an additional new parametrization, q = q 0+ q 1(1 - t/ t 0), which is linear in cosmic time t. We study the features of this linearly time-varying deceleration parameter in contrast with the other two linear parametrizations. We investigate in detail the kinematics of the Universe by confronting the three models with the latest observational data. We further study the dynamics of the Universe by considering the linearly time-varying deceleration parameter model in comparison with the standard ΛCDM model. We also discuss the future of the Universe in the context of the models under consideration.

Latent component-based gear tooth fault detection filter using advanced parametric modeling

NASA Astrophysics Data System (ADS)

Ettefagh, M. M.; Sadeghi, M. H.; Rezaee, M.; Chitsaz, S.

2009-10-01

In this paper, a new parametric model-based filter is proposed for gear tooth fault detection. The designing of the filter consists of identifying the most proper latent component (LC) of the undamaged gearbox signal by analyzing the instant modules (IMs) and instant frequencies (IFs) and then using the component with lowest IM as the proposed filter output for detecting fault of the gearbox. The filter parameters are estimated by using the LC theory in which an advanced parametric modeling method has been implemented. The proposed method is applied on the signals, extracted from simulated gearbox for detection of the simulated gear faults. In addition, the method is used for quality inspection of the produced Nissan-Junior vehicle gearbox by gear profile error detection in an industrial test bed. For evaluation purpose, the proposed method is compared with the previous parametric TAR/AR-based filters in which the parametric model residual is considered as the filter output and also Yule-Walker and Kalman filter are implemented for estimating the parameters. The results confirm the high performance of the new proposed fault detection method.

Single-arm phase II trial design under parametric cure models.

PubMed

Wu, Jianrong

2015-01-01

The current practice of designing single-arm phase II survival trials is limited under the exponential model. Trial design under the exponential model may not be appropriate when a portion of patients are cured. There is no literature available for designing single-arm phase II trials under the parametric cure model. In this paper, a test statistic is proposed, and a sample size formula is derived for designing single-arm phase II trials under a class of parametric cure models. Extensive simulations showed that the proposed test and sample size formula perform very well under different scenarios. Copyright © 2015 John Wiley & Sons, Ltd.

Impact of state updating and multi-parametric ensemble for streamflow hindcasting in European river basins

NASA Astrophysics Data System (ADS)

Noh, S. J.; Rakovec, O.; Kumar, R.; Samaniego, L. E.

2015-12-01

Accurate and reliable streamflow prediction is essential to mitigate social and economic damage coming from water-related disasters such as flood and drought. Sequential data assimilation (DA) may facilitate improved streamflow prediction using real-time observations to correct internal model states. In conventional DA methods such as state updating, parametric uncertainty is often ignored mainly due to practical limitations of methodology to specify modeling uncertainty with limited ensemble members. However, if parametric uncertainty related with routing and runoff components is not incorporated properly, predictive uncertainty by model ensemble may be insufficient to capture dynamics of observations, which may deteriorate predictability. Recently, a multi-scale parameter regionalization (MPR) method was proposed to make hydrologic predictions at different scales using a same set of model parameters without losing much of the model performance. The MPR method incorporated within the mesoscale hydrologic model (mHM, http://www.ufz.de/mhm) could effectively represent and control uncertainty of high-dimensional parameters in a distributed model using global parameters. In this study, we evaluate impacts of streamflow data assimilation over European river basins. Especially, a multi-parametric ensemble approach is tested to consider the effects of parametric uncertainty in DA. Because augmentation of parameters is not required within an assimilation window, the approach could be more stable with limited ensemble members and have potential for operational uses. To consider the response times and non-Gaussian characteristics of internal hydrologic processes, lagged particle filtering is utilized. The presentation will be focused on gains and limitations of streamflow data assimilation and multi-parametric ensemble method over large-scale basins.

Elastic full-waveform inversion and parametrization analysis applied to walk-away vertical seismic profile data for unconventional (heavy oil) reservoir characterization

NASA Astrophysics Data System (ADS)

Pan, Wenyong; Innanen, Kristopher A.; Geng, Yu

2018-06-01

Seismic full-waveform inversion (FWI) methods hold strong potential to recover multiple subsurface elastic properties for hydrocarbon reservoir characterization. Simultaneously updating multiple physical parameters introduces the problem of interparameter trade-off, arising from the simultaneous variations of different physical parameters, which increase the nonlinearity and uncertainty of multiparameter FWI. The coupling effects of different physical parameters are significantly influenced by model parametrization and acquisition arrangement. An appropriate choice of model parametrization is important to successful field data applications of multiparameter FWI. The objective of this paper is to examine the performance of various model parametrizations in isotropic-elastic FWI with walk-away vertical seismic profile (W-VSP) data for unconventional heavy oil reservoir characterization. Six model parametrizations are considered: velocity-density (α, β and ρ΄), modulus-density (κ, μ and ρ), Lamé-density (λ, μ΄ and ρ‴), impedance-density (IP, IS and ρ″), velocity-impedance-I (α΄, β΄ and I_P^' }) and velocity-impedance-II (α″, β″ and I_S^' }). We begin analysing the interparameter trade-off by making use of scattering radiation patterns, which is a common strategy for qualitative parameter resolution analysis. We discuss the advantages and limitations of the scattering radiation patterns and recommend that interparameter trade-offs be evaluated using interparameter contamination kernels, which provide quantitative, second-order measurements of the interparameter contaminations and can be constructed efficiently with an adjoint-state approach. Synthetic W-VSP isotropic-elastic FWI experiments in the time domain verify our conclusions about interparameter trade-offs for various model parametrizations. Density profiles are most strongly influenced by the interparameter contaminations; depending on model parametrization, the inverted density profile can be overestimated, underestimated or spatially distorted. Among the six cases, only the velocity-density parametrization provides stable and informative density features not included in the starting model. Field data applications of multicomponent W-VSP isotropic-elastic FWI in the time domain were also carried out. The heavy oil reservoir target zone, characterized by low α-to-β ratios and low Poisson's ratios, can be identified clearly with the inverted isotropic-elastic parameters.

Modelling and multi-parametric control for delivery of anaesthetic agents.

PubMed

Dua, Pinky; Dua, Vivek; Pistikopoulos, Efstratios N

2010-06-01

This article presents model predictive controllers (MPCs) and multi-parametric model-based controllers for delivery of anaesthetic agents. The MPC can take into account constraints on drug delivery rates and state of the patient but requires solving an optimization problem at regular time intervals. The multi-parametric controller has all the advantages of the MPC and does not require repetitive solution of optimization problem for its implementation. This is achieved by obtaining the optimal drug delivery rates as a set of explicit functions of the state of the patient. The derivation of the controllers relies on using detailed models of the system. A compartmental model for the delivery of three drugs for anaesthesia is developed. The key feature of this model is that mean arterial pressure, cardiac output and unconsciousness of the patient can be simultaneously regulated. This is achieved by using three drugs: dopamine (DP), sodium nitroprusside (SNP) and isoflurane. A number of dynamic simulation experiments are carried out for the validation of the model. The model is then used for the design of model predictive and multi-parametric controllers, and the performance of the controllers is analyzed.

MPTP-induced changes in hippocampal synaptic plasticity and memory are prevented by memantine through the BDNF-TrkB pathway

PubMed Central

Zhu, Guoqi; Li, Junyao; He, Ling; Wang, Xuncui; Hong, Xiaoqi

2015-01-01

Background and Purpose Mild cognitive deficit in early Parkinson's disease (PD) has been widely studied. Here we have examined the effects of memantine in preventing memory deficit in experimental PD models and elucidated some of the underlying mechanisms. Experimental Approaches I.p. injection of 1-methyl-4- phenyl-1,2,3,6-tetrahydro pyridine (MPTP) in C57BL/6 mice was used to produce models of PD. We used behavioural tasks to test memory. In vitro, we used slices of hippocampus, with electrophysiological, Western blotting, real time PCR, elisa and immunochemical techniques. Key Results Following MPTP injection, long-term memory was impaired and these changes were prevented by pre-treatment with memantine. In hippocampal slices from MPTP treated mice, long-term potentiation (LTP) –induced by θ burst stimulation (10 bursts, 4 pulses) was decreased, while long-term depression (LTD) induced by low-frequency stimulation (1 Hz, 900 pulses) was enhanced, compared with control values. A single dose of memantine (i.p., 10 mg·kg−1) reversed the decreased LTP and the increased LTD in this PD model. Activity-dependent changes in tyrosine kinase receptor B (TrkB), ERK and brain-derived neurotrophic factor (BDNF) expression were decreased in slices from mice after MPTP treatment. These effects were reversed by pretreatment with memantine. Incubation of slices in vitro with 1-methyl-4-phenylpyridinium (MPP+) decreased depolarization-induced expression of BDNF. This effect was prevented by pretreatment of slices with memantine or with calpain inhibitor III, suggesting the involvement of an overactivated calcium signalling pathway. Conclusions and Implications Memantine should be useful in preventing loss of memory and hippocampal synaptic plasticity in PD models. PMID:25560396

Software Reliability 2002

NASA Technical Reports Server (NTRS)

Wallace, Dolores R.

2003-01-01

In FY01 we learned that hardware reliability models need substantial changes to account for differences in software, thus making software reliability measurements more effective, accurate, and easier to apply. These reliability models are generally based on familiar distributions or parametric methods. An obvious question is 'What new statistical and probability models can be developed using non-parametric and distribution-free methods instead of the traditional parametric method?" Two approaches to software reliability engineering appear somewhat promising. The first study, begin in FY01, is based in hardware reliability, a very well established science that has many aspects that can be applied to software. This research effort has investigated mathematical aspects of hardware reliability and has identified those applicable to software. Currently the research effort is applying and testing these approaches to software reliability measurement, These parametric models require much project data that may be difficult to apply and interpret. Projects at GSFC are often complex in both technology and schedules. Assessing and estimating reliability of the final system is extremely difficult when various subsystems are tested and completed long before others. Parametric and distribution free techniques may offer a new and accurate way of modeling failure time and other project data to provide earlier and more accurate estimates of system reliability.

Quantifying parametric uncertainty in the Rothermel model

Treesearch

S. Goodrick

2008-01-01

The purpose of the present work is to quantify parametric uncertainty in the Rothermel wildland fire spreadmodel (implemented in software such as fire spread models in the United States. This model consists of a non-linear system of equations that relates environmentalvariables (input parameter groups...

Simulation of parametric model towards the fixed covariate of right censored lung cancer data

NASA Astrophysics Data System (ADS)

Afiqah Muhamad Jamil, Siti; Asrul Affendi Abdullah, M.; Kek, Sie Long; Ridwan Olaniran, Oyebayo; Enera Amran, Syahila

2017-09-01

In this study, simulation procedure was applied to measure the fixed covariate of right censored data by using parametric survival model. The scale and shape parameter were modified to differentiate the analysis of parametric regression survival model. Statistically, the biases, mean biases and the coverage probability were used in this analysis. Consequently, different sample sizes were employed to distinguish the impact of parametric regression model towards right censored data with 50, 100, 150 and 200 number of sample. R-statistical software was utilised to develop the coding simulation with right censored data. Besides, the final model of right censored simulation was compared with the right censored lung cancer data in Malaysia. It was found that different values of shape and scale parameter with different sample size, help to improve the simulation strategy for right censored data and Weibull regression survival model is suitable fit towards the simulation of survival of lung cancer patients data in Malaysia.

Parametric modeling studies of turbulent non-premixed jet flames with thin reaction zones

NASA Astrophysics Data System (ADS)

Wang, Haifeng

2013-11-01

The Sydney piloted jet flame series (Flames L, B, and M) feature thinner reaction zones and hence impose greater challenges to modeling than the Sanida Piloted jet flames (Flames D, E, and F). Recently, the Sydney flames received renewed interest due to these challenges. Several new modeling efforts have emerged. However, no systematic parametric modeling studies have been reported for the Sydney flames. A large set of modeling computations of the Sydney flames is presented here by using the coupled large eddy simulation (LES)/probability density function (PDF) method. Parametric studies are performed to gain insight into the model performance, its sensitivity and the effect of numerics.

Parametric estimation for reinforced concrete relief shelter for Aceh cases

NASA Astrophysics Data System (ADS)

Atthaillah; Saputra, Eri; Iqbal, Muhammad

2018-05-01

This paper was a work in progress (WIP) to discover a rapid parametric framework for post-disaster permanent shelter’s materials estimation. The intended shelters were reinforced concrete construction with bricks as its wall. Inevitably, in post-disaster cases, design variations were needed to help suited victims condition. It seemed impossible to satisfy a beneficiary with a satisfactory design utilizing the conventional method. This study offered a parametric framework to overcome slow construction-materials estimation issue against design variations. Further, this work integrated parametric tool, which was Grasshopper to establish algorithms that simultaneously model, visualize, calculate and write the calculated data to a spreadsheet in a real-time. Some customized Grasshopper components were created using GHPython scripting for a more optimized algorithm. The result from this study was a partial framework that successfully performed modeling, visualization, calculation and writing the calculated data simultaneously. It meant design alterations did not escalate time needed for modeling, visualization, and material estimation. Further, the future development of the parametric framework will be made open source.

Data-driven sampling method for building 3D anatomical models from serial histology

NASA Astrophysics Data System (ADS)

Salunke, Snehal Ulhas; Ablove, Tova; Danforth, Theresa; Tomaszewski, John; Doyle, Scott

2017-03-01

In this work, we investigate the effect of slice sampling on 3D models of tissue architecture using serial histopathology. We present a method for using a single fully-sectioned tissue block as pilot data, whereby we build a fully-realized 3D model and then determine the optimal set of slices needed to reconstruct the salient features of the model objects under biological investigation. In our work, we are interested in the 3D reconstruction of microvessel architecture in the trigone region between the vagina and the bladder. This region serves as a potential avenue for drug delivery to treat bladder infection. We collect and co-register 23 serial sections of CD31-stained tissue images (6 μm thick sections), from which four microvessels are selected for analysis. To build each model, we perform semi-automatic segmentation of the microvessels. Subsampled meshes are then created by removing slices from the stack, interpolating the missing data, and re-constructing the mesh. We calculate the Hausdorff distance between the full and subsampled meshes to determine the optimal sampling rate for the modeled structures. In our application, we found that a sampling rate of 50% (corresponding to just 12 slices) was sufficient to recreate the structure of the microvessels without significant deviation from the fullyrendered mesh. This pipeline effectively minimizes the number of histopathology slides required for 3D model reconstruction, and can be utilized to either (1) reduce the overall costs of a project, or (2) enable additional analysis on the intermediate slides.

Regional vertical total electron content (VTEC) modeling together with satellite and receiver differential code biases (DCBs) using semi-parametric multivariate adaptive regression B-splines (SP-BMARS)

NASA Astrophysics Data System (ADS)

Durmaz, Murat; Karslioglu, Mahmut Onur

2015-04-01

There are various global and regional methods that have been proposed for the modeling of ionospheric vertical total electron content (VTEC). Global distribution of VTEC is usually modeled by spherical harmonic expansions, while tensor products of compactly supported univariate B-splines can be used for regional modeling. In these empirical parametric models, the coefficients of the basis functions as well as differential code biases (DCBs) of satellites and receivers can be treated as unknown parameters which can be estimated from geometry-free linear combinations of global positioning system observables. In this work we propose a new semi-parametric multivariate adaptive regression B-splines (SP-BMARS) method for the regional modeling of VTEC together with satellite and receiver DCBs, where the parametric part of the model is related to the DCBs as fixed parameters and the non-parametric part adaptively models the spatio-temporal distribution of VTEC. The latter is based on multivariate adaptive regression B-splines which is a non-parametric modeling technique making use of compactly supported B-spline basis functions that are generated from the observations automatically. This algorithm takes advantage of an adaptive scale-by-scale model building strategy that searches for best-fitting B-splines to the data at each scale. The VTEC maps generated from the proposed method are compared numerically and visually with the global ionosphere maps (GIMs) which are provided by the Center for Orbit Determination in Europe (CODE). The VTEC values from SP-BMARS and CODE GIMs are also compared with VTEC values obtained through calibration using local ionospheric model. The estimated satellite and receiver DCBs from the SP-BMARS model are compared with the CODE distributed DCBs. The results show that the SP-BMARS algorithm can be used to estimate satellite and receiver DCBs while adaptively and flexibly modeling the daily regional VTEC.

Weighed scalar averaging in LTB dust models: part II. A formalism of exact perturbations

NASA Astrophysics Data System (ADS)

Sussman, Roberto A.

2013-03-01

We examine the exact perturbations that arise from the q-average formalism that was applied in the preceding article (part I) to Lemaître-Tolman-Bondi (LTB) models. By introducing an initial value parametrization, we show that all LTB scalars that take an FLRW ‘look-alike’ form (frequently used in the literature dealing with LTB models) follow as q-averages of covariant scalars that are common to FLRW models. These q-scalars determine for every averaging domain a unique FLRW background state through Darmois matching conditions at the domain boundary, though the definition of this background does not require an actual matching with an FLRW region (Swiss cheese-type models). Local perturbations describe the deviation from the FLRW background state through the local gradients of covariant scalars at the boundary of every comoving domain, while non-local perturbations do so in terms of the intuitive notion of a ‘contrast’ of local scalars with respect to FLRW reference values that emerge from q-averages assigned to the whole domain or the whole time slice in the asymptotic limit. We derive fluid flow evolution equations that completely determine the dynamics of the models in terms of the q-scalars and both types of perturbations. A rigorous formalism of exact spherical nonlinear perturbations is defined over the FLRW background state associated with the q-scalars, recovering the standard results of linear perturbation theory in the appropriate limit. We examine the notion of the amplitude and illustrate the differences between local and non-local perturbations by qualitative diagrams and through an example of a cosmic density void that follows from the numeric solution of the evolution equations.

Quality optimization of H.264/AVC video transmission over noisy environments using a sparse regression framework

NASA Astrophysics Data System (ADS)

Pandremmenou, K.; Tziortziotis, N.; Paluri, S.; Zhang, W.; Blekas, K.; Kondi, L. P.; Kumar, S.

2015-03-01

We propose the use of the Least Absolute Shrinkage and Selection Operator (LASSO) regression method in order to predict the Cumulative Mean Squared Error (CMSE), incurred by the loss of individual slices in video transmission. We extract a number of quality-relevant features from the H.264/AVC video sequences, which are given as input to the LASSO. This method has the benefit of not only keeping a subset of the features that have the strongest effects towards video quality, but also produces accurate CMSE predictions. Particularly, we study the LASSO regression through two different architectures; the Global LASSO (G.LASSO) and Local LASSO (L.LASSO). In G.LASSO, a single regression model is trained for all slice types together, while in L.LASSO, motivated by the fact that the values for some features are closely dependent on the considered slice type, each slice type has its own regression model, in an e ort to improve LASSO's prediction capability. Based on the predicted CMSE values, we group the video slices into four priority classes. Additionally, we consider a video transmission scenario over a noisy channel, where Unequal Error Protection (UEP) is applied to all prioritized slices. The provided results demonstrate the efficiency of LASSO in estimating CMSE with high accuracy, using only a few features. les that typically contain high-entropy data, producing a footprint that is far less conspicuous than existing methods. The system uses a local web server to provide a le system, user interface and applications through an web architecture.

Gradient-free MCMC methods for dynamic causal modelling.

PubMed

Sengupta, Biswa; Friston, Karl J; Penny, Will D

2015-05-15

In this technical note we compare the performance of four gradient-free MCMC samplers (random walk Metropolis sampling, slice-sampling, adaptive MCMC sampling and population-based MCMC sampling with tempering) in terms of the number of independent samples they can produce per unit computational time. For the Bayesian inversion of a single-node neural mass model, both adaptive and population-based samplers are more efficient compared with random walk Metropolis sampler or slice-sampling; yet adaptive MCMC sampling is more promising in terms of compute time. Slice-sampling yields the highest number of independent samples from the target density - albeit at almost 1000% increase in computational time, in comparison to the most efficient algorithm (i.e., the adaptive MCMC sampler). Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Geometric Model for a Parametric Study of the Blended-Wing-Body Airplane

NASA Technical Reports Server (NTRS)

Mastin, C. Wayne; Smith, Robert E.; Sadrehaghighi, Ideen; Wiese, Micharl R.

1996-01-01

A parametric model is presented for the blended-wing-body airplane, one concept being proposed for the next generation of large subsonic transports. The model is defined in terms of a small set of parameters which facilitates analysis and optimization during the conceptual design process. The model is generated from a preliminary CAD geometry. From this geometry, airfoil cross sections are cut at selected locations and fitted with analytic curves. The airfoils are then used as boundaries for surfaces defined as the solution of partial differential equations. Both the airfoil curves and the surfaces are generated with free parameters selected to give a good representation of the original geometry. The original surface is compared with the parametric model, and solutions of the Euler equations for compressible flow are computed for both geometries. The parametric model is a good approximation of the CAD model and the computed solutions are qualitatively similar. An optimal NURBS approximation is constructed and can be used by a CAD model for further refinement or modification of the original geometry.

The effects of drying on physical properties of bilimbi slices (Averrhoa bilimbi l.)

NASA Astrophysics Data System (ADS)

Shahari, N.; Nursabrina, M.; Suhairah, A. Zai

2015-05-01

Physical appearance analyses of fruits are used to maintain food quality throughout and at the end of processing. However, control variables have to be designed to obtained the desired food quality. In the present study, the effects of pretreatment and drying air temperatures of 50°C, 60°C and 70°C on the drying kinetics of belimbi slices were investigated using a hot-air dryer. In order to investigate and select the appropriate drying model, seven experiment based mathematical drying models were fitted to the experimental data. According to the statistical criteria (R2, SSE and RMSE), a Logarithmic model was found to be the best model to describe the drying behaviour of belimbi slices at 40°C for control; The Page/modified Page model was the best model to describe drying behaviour at 40°C, 60°C pre-treatment and 50°C for the control and the Wang and Singh model fitted well for 50°C pre-treatment and 60°C for the control. Comparison between experiment based mathematical modelling with a single phase mathematical model shows that close agreement was produced. The qualities of belimbi slices in terms of colour, texture and shrinkage with different air temperature and pre-treatment were also investigated. Higher drying temperatures gives less drying time, a lighter colour but greater product shrinkage, whilst pre-treatment can reduce product shrinkage and drying time and can also give good texture properties. The results show that pre-treatment and the drying temperature are important to improve mass and heat transfer as well as the product characteristics such as colour, shrinkage and texture.

Non-parametric wall model and methods of identifying boundary conditions for moments in gas flow equations

NASA Astrophysics Data System (ADS)

Liao, Meng; To, Quy-Dong; Léonard, Céline; Monchiet, Vincent

2018-03-01

In this paper, we use the molecular dynamics simulation method to study gas-wall boundary conditions. Discrete scattering information of gas molecules at the wall surface is obtained from collision simulations. The collision data can be used to identify the accommodation coefficients for parametric wall models such as Maxwell and Cercignani-Lampis scattering kernels. Since these scattering kernels are based on a limited number of accommodation coefficients, we adopt non-parametric statistical methods to construct the kernel to overcome these issues. Different from parametric kernels, the non-parametric kernels require no parameter (i.e. accommodation coefficients) and no predefined distribution. We also propose approaches to derive directly the Navier friction and Kapitza thermal resistance coefficients as well as other interface coefficients associated with moment equations from the non-parametric kernels. The methods are applied successfully to systems composed of CH4 or CO2 and graphite, which are of interest to the petroleum industry.

Maximum Marginal Likelihood Estimation of a Monotonic Polynomial Generalized Partial Credit Model with Applications to Multiple Group Analysis.

PubMed

Falk, Carl F; Cai, Li

2016-06-01

We present a semi-parametric approach to estimating item response functions (IRF) useful when the true IRF does not strictly follow commonly used functions. Our approach replaces the linear predictor of the generalized partial credit model with a monotonic polynomial. The model includes the regular generalized partial credit model at the lowest order polynomial. Our approach extends Liang's (A semi-parametric approach to estimate IRFs, Unpublished doctoral dissertation, 2007) method for dichotomous item responses to the case of polytomous data. Furthermore, item parameter estimation is implemented with maximum marginal likelihood using the Bock-Aitkin EM algorithm, thereby facilitating multiple group analyses useful in operational settings. Our approach is demonstrated on both educational and psychological data. We present simulation results comparing our approach to more standard IRF estimation approaches and other non-parametric and semi-parametric alternatives.

The influence of a time-varying least squares parametric model when estimating SFOAEs evoked with swept-frequency tones

NASA Astrophysics Data System (ADS)

Hajicek, Joshua J.; Selesnick, Ivan W.; Henin, Simon; Talmadge, Carrick L.; Long, Glenis R.

2018-05-01

Stimulus frequency otoacoustic emissions (SFOAEs) were evoked and estimated using swept-frequency tones with and without the use of swept suppressor tones. SFOAEs were estimated using a least-squares fitting procedure. The estimated SFOAEs for the two paradigms (with- and without-suppression) were similar in amplitude and phase. The fitting procedure minimizes the square error between a parametric model of total ear-canal pressure (with unknown amplitudes and phases) and ear-canal pressure acquired during each paradigm. Modifying the parametric model to allow SFOAE amplitude and phase to vary over time revealed additional amplitude and phase fine structure in the without-suppressor, but not the with-suppressor paradigm. The use of a time-varying parametric model to estimate SFOAEs without-suppression may provide additional information about cochlear mechanics not available when using a with-suppressor paradigm.

Parametrization of Stillinger-Weber potential based on valence force field model: application to single-layer MoS2 and black phosphorus

NASA Astrophysics Data System (ADS)

Jiang, Jin-Wu

2015-08-01

We propose parametrizing the Stillinger-Weber potential for covalent materials starting from the valence force-field model. All geometrical parameters in the Stillinger-Weber potential are determined analytically according to the equilibrium condition for each individual potential term, while the energy parameters are derived from the valence force-field model. This parametrization approach transfers the accuracy of the valence force field model to the Stillinger-Weber potential. Furthermore, the resulting Stilliinger-Weber potential supports stable molecular dynamics simulations, as each potential term is at an energy-minimum state separately at the equilibrium configuration. We employ this procedure to parametrize Stillinger-Weber potentials for single-layer MoS2 and black phosphorous. The obtained Stillinger-Weber potentials predict an accurate phonon spectrum and mechanical behaviors. We also provide input scripts of these Stillinger-Weber potentials used by publicly available simulation packages including GULP and LAMMPS.

Parametrization of Stillinger-Weber potential based on valence force field model: application to single-layer MoS2 and black phosphorus.

PubMed

Jiang, Jin-Wu

2015-08-07

We propose parametrizing the Stillinger-Weber potential for covalent materials starting from the valence force-field model. All geometrical parameters in the Stillinger-Weber potential are determined analytically according to the equilibrium condition for each individual potential term, while the energy parameters are derived from the valence force-field model. This parametrization approach transfers the accuracy of the valence force field model to the Stillinger-Weber potential. Furthermore, the resulting Stilliinger-Weber potential supports stable molecular dynamics simulations, as each potential term is at an energy-minimum state separately at the equilibrium configuration. We employ this procedure to parametrize Stillinger-Weber potentials for single-layer MoS2 and black phosphorous. The obtained Stillinger-Weber potentials predict an accurate phonon spectrum and mechanical behaviors. We also provide input scripts of these Stillinger-Weber potentials used by publicly available simulation packages including GULP and LAMMPS.

Modeling Surface Cross-contamination of Salmonella spp. on Ready-to-Eat Meat via Slicing Operation

USDA-ARS?s Scientific Manuscript database

Food pathogen cross-contamination occurring at home, retail food service or production site is one of the major factors causing foodborne illness. Studies on Salmonella Typhimurium surface transfer on ready-to-eat (RTE) deli meat and the slicer used for slicing RTE products are needed to ensure RTE...

Drying kinetics and characteristics of combined infrared-vacuum drying of button mushroom slices

NASA Astrophysics Data System (ADS)

Salehi, Fakhreddin; Kashaninejad, Mahdi; Jafarianlari, Ali

2017-05-01

Infrared-vacuum drying characteristics of button mushroom ( Agaricus bisporus) were evaluated in a combined dryer system. The effects of drying parameters, including infrared radiation power (150-375 W), system pressure (5-15 kPa) and time (0-160 min) on the drying kinetics and characteristics of button mushroom slices were investigated. Both the infrared lamp power and vacuum pressure influenced the drying time of button mushroom slices. The rate constants of the nine different kinetic's models for thin layer drying were established by nonlinear regression analysis of the experimental data which were found to be affected mainly by the infrared power level while system pressure had a little effect on the moisture ratios. The regression results showed that the Page model satisfactorily described the drying behavior of button mushroom slices with highest R value and lowest SE values. The effective moisture diffusivity increases as power increases and range between 0.83 and 2.33 × 10-9 m2/s. The rise in infrared power has a negative effect on the ΔE and with increasing in infrared radiation power it was increased.

MRI-based patient-specific human carotid atherosclerotic vessel material property variations in patients, vessel location and long-term follow up

PubMed Central

Wang, Qingyu; Canton, Gador; Guo, Jian; Guo, Xiaoya; Hatsukami, Thomas S.; Billiar, Kristen L.; Yuan, Chun; Wu, Zheyang

2017-01-01

Background Image-based computational models are widely used to determine atherosclerotic plaque stress/strain conditions and investigate their association with plaque progression and rupture. However, patient-specific vessel material properties are in general lacking in those models, limiting the accuracy of their stress/strain measurements. A noninvasive approach of combining in vivo 3D multi-contrast and Cine magnetic resonance imaging (MRI) and computational modeling was introduced to quantify patient-specific carotid plaque material properties for potential plaque model improvements. Vessel material property variation in patients, along vessel segment, and between baseline and follow up were investigated. Methods In vivo 3D multi-contrast and Cine MRI carotid plaque data were acquired from 8 patients with follow-up (18 months) with written informed consent obtained. 3D thin-layer models and an established iterative procedure were used to determine parameter values of the Mooney-Rivlin models for the 81slices from 16 plaque samples. Effective Young’s Modulus (YM) values were calculated for comparison and analysis. Results Average Effective Young’s Modulus (YM) and circumferential shrinkage rate (C-Shrink) value of the 81 slices was 411kPa and 5.62%, respectively. Slice YM value varied from 70 kPa (softest) to 1284 kPa (stiffest), a 1734% difference. Average slice YM values by vessel varied from 109 kPa (softest) to 922 kPa (stiffest), a 746% difference. Location-wise, the maximum slice YM variation rate within a vessel was 311% (149 kPa vs. 613 kPa). The average slice YM variation rate for the 16 vessels was 134%. The average variation of YM values for all patients from baseline to follow up was 61.0%. The range of the variation of YM values was [-28.4%, 215%]. For plaque progression study, YM at follow-up showed negative correlation with plaque progression measured by wall thickness increase (WTI) (r = -0.7764, p = 0.0235). Wall thickness at baseline correlated with WTI negatively, with r = -0.5253 (p = 0.1813). Plaque burden at baseline correlated with YM change between baseline and follow-up, with r = 0.5939 (p = 0.1205). Conclusion In vivo carotid vessel material properties have large variations from patient to patient, along the diseased segment within a patient, and with time. The use of patient-specific, location specific and time-specific material properties in plaque models could potentially improve the accuracy of model stress/strain calculations. PMID:28715441

A generalized framework unifying image registration and respiratory motion models and incorporating image reconstruction, for partial image data or full images

NASA Astrophysics Data System (ADS)

McClelland, Jamie R.; Modat, Marc; Arridge, Simon; Grimes, Helen; D'Souza, Derek; Thomas, David; O' Connell, Dylan; Low, Daniel A.; Kaza, Evangelia; Collins, David J.; Leach, Martin O.; Hawkes, David J.

2017-06-01

Surrogate-driven respiratory motion models relate the motion of the internal anatomy to easily acquired respiratory surrogate signals, such as the motion of the skin surface. They are usually built by first using image registration to determine the motion from a number of dynamic images, and then fitting a correspondence model relating the motion to the surrogate signals. In this paper we present a generalized framework that unifies the image registration and correspondence model fitting into a single optimization. This allows the use of ‘partial’ imaging data, such as individual slices, projections, or k-space data, where it would not be possible to determine the motion from an individual frame of data. Motion compensated image reconstruction can also be incorporated using an iterative approach, so that both the motion and a motion-free image can be estimated from the partial image data. The framework has been applied to real 4DCT, Cine CT, multi-slice CT, and multi-slice MR data, as well as simulated datasets from a computer phantom. This includes the use of a super-resolution reconstruction method for the multi-slice MR data. Good results were obtained for all datasets, including quantitative results for the 4DCT and phantom datasets where the ground truth motion was known or could be estimated.

A generalized framework unifying image registration and respiratory motion models and incorporating image reconstruction, for partial image data or full images.

PubMed

McClelland, Jamie R; Modat, Marc; Arridge, Simon; Grimes, Helen; D'Souza, Derek; Thomas, David; Connell, Dylan O'; Low, Daniel A; Kaza, Evangelia; Collins, David J; Leach, Martin O; Hawkes, David J

2017-06-07

Surrogate-driven respiratory motion models relate the motion of the internal anatomy to easily acquired respiratory surrogate signals, such as the motion of the skin surface. They are usually built by first using image registration to determine the motion from a number of dynamic images, and then fitting a correspondence model relating the motion to the surrogate signals. In this paper we present a generalized framework that unifies the image registration and correspondence model fitting into a single optimization. This allows the use of 'partial' imaging data, such as individual slices, projections, or k-space data, where it would not be possible to determine the motion from an individual frame of data. Motion compensated image reconstruction can also be incorporated using an iterative approach, so that both the motion and a motion-free image can be estimated from the partial image data. The framework has been applied to real 4DCT, Cine CT, multi-slice CT, and multi-slice MR data, as well as simulated datasets from a computer phantom. This includes the use of a super-resolution reconstruction method for the multi-slice MR data. Good results were obtained for all datasets, including quantitative results for the 4DCT and phantom datasets where the ground truth motion was known or could be estimated.

A generalized framework unifying image registration and respiratory motion models and incorporating image reconstruction, for partial image data or full images

PubMed Central

McClelland, Jamie R; Modat, Marc; Arridge, Simon; Grimes, Helen; D’Souza, Derek; Thomas, David; Connell, Dylan O’; Low, Daniel A; Kaza, Evangelia; Collins, David J; Leach, Martin O; Hawkes, David J

2017-01-01

Abstract Surrogate-driven respiratory motion models relate the motion of the internal anatomy to easily acquired respiratory surrogate signals, such as the motion of the skin surface. They are usually built by first using image registration to determine the motion from a number of dynamic images, and then fitting a correspondence model relating the motion to the surrogate signals. In this paper we present a generalized framework that unifies the image registration and correspondence model fitting into a single optimization. This allows the use of ‘partial’ imaging data, such as individual slices, projections, or k-space data, where it would not be possible to determine the motion from an individual frame of data. Motion compensated image reconstruction can also be incorporated using an iterative approach, so that both the motion and a motion-free image can be estimated from the partial image data. The framework has been applied to real 4DCT, Cine CT, multi-slice CT, and multi-slice MR data, as well as simulated datasets from a computer phantom. This includes the use of a super-resolution reconstruction method for the multi-slice MR data. Good results were obtained for all datasets, including quantitative results for the 4DCT and phantom datasets where the ground truth motion was known or could be estimated. PMID:28195833

Significant glial alterations in response to iron loading in a novel organotypic hippocampal slice culture model

PubMed Central

Healy, Sinead; McMahon, Jill; Owens, Peter; FitzGerald, Una

2016-01-01

Aberrant iron deposition in the brain is associated with neurodegenerative disorders including Multiple Sclerosis, Alzheimer’s disease and Parkinson’s disease. To study the collective response to iron loading, we have used hippocampal organotypic slices as a platform to develop a novel ex vivo model of iron accumulation. We demonstrated differential uptake and toxicity of iron after 12 h exposure to 10 μM ferrous ammonium sulphate, ferric citrate or ferrocene. Having established the supremacy of ferrocene in this model, the cultures were then loaded with 0.1–100 μM ferrocene for 12 h. One μM ferrocene exposure produced the maximal 1.6-fold increase in iron compared with vehicle. This was accompanied by a 1.4-fold increase in ferritin transcripts and mild toxicity. Using dual-immunohistochemistry, we detected ferritin in oligodendrocytes, microglia, but rarely in astrocytes and never in neurons in iron-loaded slice cultures. Moreover, iron loading led to a 15% loss of olig2-positive cells and a 16% increase in number and greater activation of microglia compared with vehicle. However, there was no appreciable effect of iron loading on astrocytes. In what we believe is a significant advance on traditional mono- or dual-cultures, our novel ex vivo slice-culture model allows characterization of the collective response of brain cells to iron-loading. PMID:27808258

The impact of slice-reduced computed tomography on histogram-based densitometry assessment of lung fibrosis in patients with systemic sclerosis.

PubMed

Nguyen-Kim, Thi Dan Linh; Maurer, Britta; Suliman, Yossra A; Morsbach, Fabian; Distler, Oliver; Frauenfelder, Thomas

2018-04-01

To evaluate usability of slice-reduced sequential computed tomography (CT) compared to standard high-resolution CT (HRCT) in patients with systemic sclerosis (SSc) for qualitative and quantitative assessment of interstitial lung disease (ILD) with respect to (I) detection of lung parenchymal abnormalities, (II) qualitative and semiquantitative visual assessment, (III) quantification of ILD by histograms and (IV) accuracy for the 20%-cut off discrimination. From standard chest HRCT of 60 SSc patients sequential 9-slice-computed tomography (reduced HRCT) was retrospectively reconstructed. ILD was assessed by visual scoring and quantitative histogram parameters. Results from standard and reduced HRCT were compared using non-parametric tests and analysed by univariate linear regression analyses. With respect to the detection of parenchymal abnormalities, only the detection of intrapulmonary bronchiectasis was significantly lower in reduced HRCT compared to standard HRCT (P=0.039). No differences were found comparing visual scores for fibrosis severity and extension from standard and reduced HRCT (P=0.051-0.073). All scores correlated significantly (P<0.001) to histogram parameters derived from both, standard and reduced HRCT. Significant higher values of kurtosis and skewness for reduced HRCT were found (both P<0.001). In contrast to standard HRCT histogram parameters from reduced HRCT showed significant discrimination at cut-off 20% fibrosis (sensitivity 88% kurtosis and skewness; specificity 81% kurtosis and 86% skewness; cut-off kurtosis ≤26, cut-off skewness ≤4; both P<0.001). Reduced HRCT is a robust method to assess lung fibrosis in SSc with minimal radiation dose with no difference in scoring assessment of lung fibrosis severity and extension in comparison to standard HRCT. In contrast to standard HRCT histogram parameters derived from the approach of reduced HRCT could discriminate at a threshold of 20% lung fibrosis with high sensitivity and specificity. Hence it might be used to detect early disease progression of lung fibrosis in context of monitoring and treatment of SSc patients.

Parametric instabilities of rotor-support systems with application to industrial ventilators

NASA Technical Reports Server (NTRS)

Parszewski, Z.; Krodkiemski, T.; Marynowski, K.

1980-01-01

Rotor support systems interaction with parametric excitation is considered for both unequal principal shaft stiffness (generators) and offset disc rotors (ventilators). Instability regions and types of instability are computed in the first case, and parametric resonances in the second case. Computed and experimental results are compared for laboratory machine models. A field case study of parametric vibrations in industrial ventilators is reported. Computed parametric resonances are confirmed in field measurements, and some industrial failures are explained. Also the dynamic influence and gyroscopic effect of supporting structures are shown and computed.

Parametric robust control and system identification: Unified approach

NASA Technical Reports Server (NTRS)

Keel, Leehyun

1994-01-01

Despite significant advancement in the area of robust parametric control, the problem of synthesizing such a controller is still a wide open problem. Thus, we attempt to give a solution to this important problem. Our approach captures the parametric uncertainty as an H(sub infinity) unstructured uncertainty so that H(sub infinity) synthesis techniques are applicable. Although the techniques cannot cope with the exact parametric uncertainty, they give a reasonable guideline to model the unstructured uncertainty that contains the parametric uncertainty. An additional loop shaping technique is also introduced to relax its conservatism.

Cardiac-gated parametric images from 82 Rb PET from dynamic frames and direct 4D reconstruction.

PubMed

Germino, Mary; Carson, Richard E

2018-02-01

Cardiac perfusion PET data can be reconstructed as a dynamic sequence and kinetic modeling performed to quantify myocardial blood flow, or reconstructed as static gated images to quantify function. Parametric images from dynamic PET are conventionally not gated, to allow use of all events with lower noise. An alternative method for dynamic PET is to incorporate the kinetic model into the reconstruction algorithm itself, bypassing the generation of a time series of emission images and directly producing parametric images. So-called "direct reconstruction" can produce parametric images with lower noise than the conventional method because the noise distribution is more easily modeled in projection space than in image space. In this work, we develop direct reconstruction of cardiac-gated parametric images for 82 Rb PET with an extension of the Parametric Motion compensation OSEM List mode Algorithm for Resolution-recovery reconstruction for the one tissue model (PMOLAR-1T). PMOLAR-1T was extended to accommodate model terms to account for spillover from the left and right ventricles into the myocardium. The algorithm was evaluated on a 4D simulated 82 Rb dataset, including a perfusion defect, as well as a human 82 Rb list mode acquisition. The simulated list mode was subsampled into replicates, each with counts comparable to one gate of a gated acquisition. Parametric images were produced by the indirect (separate reconstructions and modeling) and direct methods for each of eight low-count and eight normal-count replicates of the simulated data, and each of eight cardiac gates for the human data. For the direct method, two initialization schemes were tested: uniform initialization, and initialization with the filtered iteration 1 result of the indirect method. For the human dataset, event-by-event respiratory motion compensation was included. The indirect and direct methods were compared for the simulated dataset in terms of bias and coefficient of variation as a function of iteration. Convergence of direct reconstruction was slow with uniform initialization; lower bias was achieved in fewer iterations by initializing with the filtered indirect iteration 1 images. For most parameters and regions evaluated, the direct method achieved the same or lower absolute bias at matched iteration as the indirect method, with 23%-65% lower noise. Additionally, the direct method gave better contrast between the perfusion defect and surrounding normal tissue than the indirect method. Gated parametric images from the human dataset had comparable relative performance of indirect and direct, in terms of mean parameter values per iteration. Changes in myocardial wall thickness and blood pool size across gates were readily visible in the gated parametric images, with higher contrast between myocardium and left ventricle blood pool in parametric images than gated SUV images. Direct reconstruction can produce parametric images with less noise than the indirect method, opening the potential utility of gated parametric imaging for perfusion PET. © 2017 American Association of Physicists in Medicine.

The influence of vegetation height heterogeneity on forest and woodland bird species richness across the United States.

PubMed

Huang, Qiongyu; Swatantran, Anu; Dubayah, Ralph; Goetz, Scott J

2014-01-01

Avian diversity is under increasing pressures. It is thus critical to understand the ecological variables that contribute to large scale spatial distribution of avian species diversity. Traditionally, studies have relied primarily on two-dimensional habitat structure to model broad scale species richness. Vegetation vertical structure is increasingly used at local scales. However, the spatial arrangement of vegetation height has never been taken into consideration. Our goal was to examine the efficacies of three-dimensional forest structure, particularly the spatial heterogeneity of vegetation height in improving avian richness models across forested ecoregions in the U.S. We developed novel habitat metrics to characterize the spatial arrangement of vegetation height using the National Biomass and Carbon Dataset for the year 2000 (NBCD). The height-structured metrics were compared with other habitat metrics for statistical association with richness of three forest breeding bird guilds across Breeding Bird Survey (BBS) routes: a broadly grouped woodland guild, and two forest breeding guilds with preferences for forest edge and for interior forest. Parametric and non-parametric models were built to examine the improvement of predictability. Height-structured metrics had the strongest associations with species richness, yielding improved predictive ability for the woodland guild richness models (r(2) = ∼ 0.53 for the parametric models, 0.63 the non-parametric models) and the forest edge guild models (r(2) = ∼ 0.34 for the parametric models, 0.47 the non-parametric models). All but one of the linear models incorporating height-structured metrics showed significantly higher adjusted-r2 values than their counterparts without additional metrics. The interior forest guild richness showed a consistent low association with height-structured metrics. Our results suggest that height heterogeneity, beyond canopy height alone, supplements habitat characterization and richness models of forest bird species. The metrics and models derived in this study demonstrate practical examples of utilizing three-dimensional vegetation data for improved characterization of spatial patterns in species richness.

The Influence of Vegetation Height Heterogeneity on Forest and Woodland Bird Species Richness across the United States

PubMed Central

Huang, Qiongyu; Swatantran, Anu; Dubayah, Ralph; Goetz, Scott J.

2014-01-01

Avian diversity is under increasing pressures. It is thus critical to understand the ecological variables that contribute to large scale spatial distribution of avian species diversity. Traditionally, studies have relied primarily on two-dimensional habitat structure to model broad scale species richness. Vegetation vertical structure is increasingly used at local scales. However, the spatial arrangement of vegetation height has never been taken into consideration. Our goal was to examine the efficacies of three-dimensional forest structure, particularly the spatial heterogeneity of vegetation height in improving avian richness models across forested ecoregions in the U.S. We developed novel habitat metrics to characterize the spatial arrangement of vegetation height using the National Biomass and Carbon Dataset for the year 2000 (NBCD). The height-structured metrics were compared with other habitat metrics for statistical association with richness of three forest breeding bird guilds across Breeding Bird Survey (BBS) routes: a broadly grouped woodland guild, and two forest breeding guilds with preferences for forest edge and for interior forest. Parametric and non-parametric models were built to examine the improvement of predictability. Height-structured metrics had the strongest associations with species richness, yielding improved predictive ability for the woodland guild richness models (r2 = ∼0.53 for the parametric models, 0.63 the non-parametric models) and the forest edge guild models (r2 = ∼0.34 for the parametric models, 0.47 the non-parametric models). All but one of the linear models incorporating height-structured metrics showed significantly higher adjusted-r2 values than their counterparts without additional metrics. The interior forest guild richness showed a consistent low association with height-structured metrics. Our results suggest that height heterogeneity, beyond canopy height alone, supplements habitat characterization and richness models of forest bird species. The metrics and models derived in this study demonstrate practical examples of utilizing three-dimensional vegetation data for improved characterization of spatial patterns in species richness. PMID:25101782

The Impact of Three-Dimensional Effects on the Simulation of Turbulence Kinetic Energy in a Major Alpine Valley

NASA Astrophysics Data System (ADS)

Goger, Brigitta; Rotach, Mathias W.; Gohm, Alexander; Fuhrer, Oliver; Stiperski, Ivana; Holtslag, Albert A. M.

2018-02-01

The correct simulation of the atmospheric boundary layer (ABL) is crucial for reliable weather forecasts in truly complex terrain. However, common assumptions for model parametrizations are only valid for horizontally homogeneous and flat terrain. Here, we evaluate the turbulence parametrization of the numerical weather prediction model COSMO with a horizontal grid spacing of Δ x = 1.1 km for the Inn Valley, Austria. The long-term, high-resolution turbulence measurements of the i-Box measurement sites provide a useful data pool of the ABL structure in the valley and on slopes. We focus on days and nights when ABL processes dominate and a thermally-driven circulation is present. Simulations are performed for case studies with both a one-dimensional turbulence parametrization, which only considers the vertical turbulent exchange, and a hybrid turbulence parametrization, also including horizontal shear production and advection in the budget of turbulence kinetic energy (TKE). We find a general underestimation of TKE by the model with the one-dimensional turbulence parametrization. In the simulations with the hybrid turbulence parametrization, the modelled TKE has a more realistic structure, especially in situations when the TKE production is dominated by shear related to the afternoon up-valley flow, and during nights, when a stable ABL is present. The model performance also improves for stations on the slopes. An estimation of the horizontal shear production from the observation network suggests that three-dimensional effects are a relevant part of TKE production in the valley.

The Impact of Three-Dimensional Effects on the Simulation of Turbulence Kinetic Energy in a Major Alpine Valley

NASA Astrophysics Data System (ADS)

Goger, Brigitta; Rotach, Mathias W.; Gohm, Alexander; Fuhrer, Oliver; Stiperski, Ivana; Holtslag, Albert A. M.

2018-07-01

The correct simulation of the atmospheric boundary layer (ABL) is crucial for reliable weather forecasts in truly complex terrain. However, common assumptions for model parametrizations are only valid for horizontally homogeneous and flat terrain. Here, we evaluate the turbulence parametrization of the numerical weather prediction model COSMO with a horizontal grid spacing of Δ x = 1.1 km for the Inn Valley, Austria. The long-term, high-resolution turbulence measurements of the i-Box measurement sites provide a useful data pool of the ABL structure in the valley and on slopes. We focus on days and nights when ABL processes dominate and a thermally-driven circulation is present. Simulations are performed for case studies with both a one-dimensional turbulence parametrization, which only considers the vertical turbulent exchange, and a hybrid turbulence parametrization, also including horizontal shear production and advection in the budget of turbulence kinetic energy (TKE). We find a general underestimation of TKE by the model with the one-dimensional turbulence parametrization. In the simulations with the hybrid turbulence parametrization, the modelled TKE has a more realistic structure, especially in situations when the TKE production is dominated by shear related to the afternoon up-valley flow, and during nights, when a stable ABL is present. The model performance also improves for stations on the slopes. An estimation of the horizontal shear production from the observation network suggests that three-dimensional effects are a relevant part of TKE production in the valley.

Investigating Functional Regeneration in Organotypic Spinal Cord Co-cultures Grown on Multi-electrode Arrays.

PubMed

Heidemann, Martina; Streit, Jürg; Tscherter, Anne

2015-09-23

Adult higher vertebrates have a limited potential to recover from spinal cord injury. Recently, evidence emerged that propriospinal connections are a promising target for intervention to improve functional regeneration. So far, no in vitro model exists that grants the possibility to examine functional recovery of propriospinal fibers. Therefore, a representative model that is based on two organotypic spinal cord sections of embryonic rat, cultured next to each other on multi-electrode arrays (MEAs) was developed. These slices grow and, within a few days in vitro, fuse along the sides facing each other. The design of the used MEAs permits the performance of lesions with a scalpel blade through this fusion site without inflicting damage on the MEAs. The slices show spontaneous activity, usually organized in network activity bursts, and spatial and temporal activity parameters such as the location of burst origins, speed and direction of their propagation and latencies between bursts can be characterized. Using these features, it is also possible to assess functional connection of the slices by calculating the amount of synchronized bursts between the two sides. Furthermore, the slices can be morphologically analyzed by performing immunohistochemical stainings after the recordings. Several advantages of the used techniques are combined in this model: the slices largely preserve the original tissue architecture with intact local synaptic circuitry, the tissue is easily and repeatedly accessible and neuronal activity can be detected simultaneously and non-invasively in a large number of spots at high temporal resolution. These features allow the investigation of functional regeneration of intraspinal connections in isolation in vitro in a sophisticated and efficient way.

Model Robust Calibration: Method and Application to Electronically-Scanned Pressure Transducers

NASA Technical Reports Server (NTRS)

Walker, Eric L.; Starnes, B. Alden; Birch, Jeffery B.; Mays, James E.

2010-01-01

This article presents the application of a recently developed statistical regression method to the controlled instrument calibration problem. The statistical method of Model Robust Regression (MRR), developed by Mays, Birch, and Starnes, is shown to improve instrument calibration by reducing the reliance of the calibration on a predetermined parametric (e.g. polynomial, exponential, logarithmic) model. This is accomplished by allowing fits from the predetermined parametric model to be augmented by a certain portion of a fit to the residuals from the initial regression using a nonparametric (locally parametric) regression technique. The method is demonstrated for the absolute scale calibration of silicon-based pressure transducers.

Choice Inconsistencies among the Elderly: Evidence from Plan Choice in the Medicare Part D Program: Reply

PubMed Central

ABALUCK, JASON

2017-01-01

We explore the in- and out- of sample robustness of tests for choice inconsistencies based on parameter restrictions in parametric models, focusing on tests proposed by Ketcham, Kuminoff and Powers (KKP). We argue that their non-parametric alternatives are inherently conservative with respect to detecting mistakes. We then show that our parametric model is robust to KKP’s suggested specification checks, and that comprehensive goodness of fit measures perform better with our model than the expected utility model. Finally, we explore the robustness of our 2011 results to alternative normative assumptions highlighting the role of brand fixed effects and unobservable characteristics. PMID:29170561

Nonrelativistic approaches derived from point-coupling relativistic models

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

Lourenco, O.; Dutra, M.; Delfino, A.

2010-03-15

We construct nonrelativistic versions of relativistic nonlinear hadronic point-coupling models, based on new normalized spinor wave functions after small component reduction. These expansions give us energy density functionals that can be compared to their relativistic counterparts. We show that the agreement between the nonrelativistic limit approach and the Skyrme parametrizations becomes strongly dependent on the incompressibility of each model. We also show that the particular case A=B=0 (Walecka model) leads to the same energy density functional of the Skyrme parametrizations SV and ZR2, while the truncation scheme, up to order {rho}{sup 3}, leads to parametrizations for which {sigma}=1.

The Impact of Sources of Variability on Parametric Response Mapping of Lung CT Scans

PubMed Central

Boes, Jennifer L.; Bule, Maria; Hoff, Benjamin A.; Chamberlain, Ryan; Lynch, David A.; Stojanovska, Jadranka; Martinez, Fernando J.; Han, Meilan K.; Kazerooni, Ella A.; Ross, Brian D.; Galbán, Craig J.

2015-01-01

Parametric response mapping (PRM) of inspiration and expiration computed tomography (CT) images improves the radiological phenotyping of chronic obstructive pulmonary disease (COPD). PRM classifies individual voxels of lung parenchyma as normal, emphysematous, or nonemphysematous air trapping. In this study, bias and noise characteristics of the PRM methodology to CT and clinical procedures were evaluated to determine best practices for this quantitative technique. Twenty patients of varying COPD status with paired volumetric inspiration and expiration CT scans of the lungs were identified from the baseline COPD-Gene cohort. The impact of CT scanner manufacturer and reconstruction kernels were evaluated as potential sources of variability in PRM measurements along with simulations to quantify the impact of inspiration/expiration lung volume levels, misregistration, and image spacing on PRM measurements. Negligible variation in PRM metrics was observed when CT scanner type and reconstruction were consistent and inspiration/expiration lung volume levels were near target volumes. CT scanner Hounsfield unit drift occurred but remained difficult to ameliorate. Increasing levels of image misregistration and CT slice spacing were found to have a minor effect on PRM measurements. PRM-derived values were found to be most sensitive to lung volume levels and mismatched reconstruction kernels. As with other quantitative imaging techniques, reliable PRM measurements are attainable when consistent clinical and CT protocols are implemented. PMID:26568983

CuBe: parametric modeling of 3D foveal shape using cubic Bézier

PubMed Central

Yadav, Sunil Kumar; Motamedi, Seyedamirhosein; Oberwahrenbrock, Timm; Oertel, Frederike Cosima; Polthier, Konrad; Paul, Friedemann; Kadas, Ella Maria; Brandt, Alexander U.

2017-01-01

Optical coherence tomography (OCT) allows three-dimensional (3D) imaging of the retina, and is commonly used for assessing pathological changes of fovea and macula in many diseases. Many neuroinflammatory conditions are known to cause modifications to the fovea shape. In this paper, we propose a method for parametric modeling of the foveal shape. Our method exploits invariant features of the macula from OCT data and applies a cubic Bézier polynomial along with a least square optimization to produce a best fit parametric model of the fovea. Additionally, we provide several parameters of the foveal shape based on the proposed 3D parametric modeling. Our quantitative and visual results show that the proposed model is not only able to reconstruct important features from the foveal shape, but also produces less error compared to the state-of-the-art methods. Finally, we apply the model in a comparison of healthy control eyes and eyes from patients with neuroinflammatory central nervous system disorders and optic neuritis, and show that several derived model parameters show significant differences between the two groups. PMID:28966857

Model Adaptation in Parametric Space for POD-Galerkin Models

NASA Astrophysics Data System (ADS)

Gao, Haotian; Wei, Mingjun

2017-11-01

The development of low-order POD-Galerkin models is largely motivated by the expectation to use the model developed with a set of parameters at their native values to predict the dynamic behaviors of the same system under different parametric values, in other words, a successful model adaptation in parametric space. However, most of time, even small deviation of parameters from their original value may lead to large deviation or unstable results. It has been shown that adding more information (e.g. a steady state, mean value of a different unsteady state, or an entire different set of POD modes) may improve the prediction of flow with other parametric states. For a simple case of the flow passing a fixed cylinder, an orthogonal mean mode at a different Reynolds number may stabilize the POD-Galerkin model when Reynolds number is changed. For a more complicated case of the flow passing an oscillatory cylinder, a global POD-Galerkin model is first applied to handle the moving boundaries, then more information (e.g. more POD modes) is required to predicate the flow under different oscillatory frequencies. Supported by ARL.

Isoproterenol effects evaluated in heart slices of human and rat in comparison to rat heart in vivo

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

Herrmann, Julia E.; Heale, Jason; Bieraugel, Mike

Human response to isoproterenol induced cardiac injury was evaluated by gene and protein pathway changes in human heart slices, and compared to rat heart slices and rat heart in vivo. Isoproterenol (10 and 100 μM) altered human and rat heart slice markers of oxidative stress (ATP and GSH) at 24 h. In this in vivo rat study (0.5 mg/kg), serum troponin concentrations increased with lesion severity, minimal to mild necrosis at 24 and 48 h. In the rat and the human heart, isoproterenol altered pathways for apoptosis/necrosis, stress/energy, inflammation, and remodeling/fibrosis. The rat and human heart slices were in anmore » apoptotic phase, while the in vivo rat heart exhibited necrosis histologically and further progression of tissue remodeling. In human heart slices genes for several heat shock 70 kD members were altered, indicative of stress to mitigate apoptosis. The stress response included alterations in energy utilization, fatty acid processing, and the up-regulation of inducible nitric oxide synthase, a marker of increased oxidative stress in both species. Inflammation markers linked with remodeling included IL-1α, Il-1β, IL-6 and TNFα in both species. Tissue remodeling changes in both species included increases in the TIMP proteins, inhibitors of matrix degradation, the gene/protein of IL-4 linked with cardiac fibrosis, and the gene Ccl7 a chemokine that induces collagen synthesis, and Reg3b a growth factor for cardiac repair. This study demonstrates that the initial human heart slice response to isoproterenol cardiac injury results in apoptosis, stress/energy status, inflammation and tissue remodeling at concentrations similar to that in rat heart slices. - Highlights: • Human response to isoproterenol induced cardiac injury evaluated in heart slices. • Isoproterenol altered apoptosis, energy, inflammation and remodeling pathways. • Human model verified by comparison to rat heart slices and rat heart in vivo. • Human and rat respond to isoproterenol at similar concentrations in vitro.« less

Simulation of the hot rolling of steel with direct iteration

NASA Astrophysics Data System (ADS)

Hanoglu, Umut; Šarler, Božidar

2017-10-01

In this study a simulation system based on the meshless Local Radial Basis Function Collocation Method (LRBFCM) is applied for the hot rolling of steel. Rolling is a complex, 3D, thermo-mechanical problem; however, 2D cross-sectional slices are used as computational domains that are aligned with the rolling direction and no heat flow or strain is considered in the direction that is orthogonal to the slices. For each predefined position with respect to the rolling direction, the solution procedure is repeated until the slice reaches the final rolling position. Collocation nodes are initially distributed over the domain and boundaries of the initial slice. A local solution is achieved by considering the overlapping influence domains with either 5 or 7 nodes. Radial Basis Functions (RBFs) are used for the temperature discretization in the thermal model and displacement discretization in the mechanical model. The meshless solution procedure does not require a mesh-generation algorithm in the classic sense. Strong-form mechanical and thermal models are run for each slice regarding the contact with the roll's surface. Ideal plastic material behavior is considered for the mechanical results, where the nonlinear stress-strain relation is solved with a direct iteration. The majority of the Finite Element Model (FEM) simulations, including commercial software, use a conventional Newton-Raphson algorithm. However, direct iteration is chosen here due to its better compatibility with meshless methods. In order to overcome any unforeseen stability issues, the redistribution of the nodes by Elliptic Node Generation (ENG) is applied to one or more slices throughout the simulation. The rolling simulation presented here helps the user to design, test and optimize different rolling schedules. The results can be seen minutes after the simulation's start in terms of temperature, displacement, stress and strain fields as well as important technological parameters, like the roll-separating forces, roll toque, etc. An example of a rolling simulation, in which an initial size of 110x110 mm steel is rolled to a round bar with 80 mm diameter, is shown in Fig. 3. A user-friendly computer application for industrial use is created by using the C# and .NET frameworks.

Parametric, nonparametric and parametric modelling of a chaotic circuit time series

NASA Astrophysics Data System (ADS)

Timmer, J.; Rust, H.; Horbelt, W.; Voss, H. U.

2000-09-01

The determination of a differential equation underlying a measured time series is a frequently arising task in nonlinear time series analysis. In the validation of a proposed model one often faces the dilemma that it is hard to decide whether possible discrepancies between the time series and model output are caused by an inappropriate model or by bad estimates of parameters in a correct type of model, or both. We propose a combination of parametric modelling based on Bock's multiple shooting algorithm and nonparametric modelling based on optimal transformations as a strategy to test proposed models and if rejected suggest and test new ones. We exemplify this strategy on an experimental time series from a chaotic circuit where we obtain an extremely accurate reconstruction of the observed attractor.

Kidney segmentation in CT sequences using graph cuts based active contours model and contextual continuity.

PubMed

Zhang, Pin; Liang, Yanmei; Chang, Shengjiang; Fan, Hailun

2013-08-01

Accurate segmentation of renal tissues in abdominal computed tomography (CT) image sequences is an indispensable step for computer-aided diagnosis and pathology detection in clinical applications. In this study, the goal is to develop a radiology tool to extract renal tissues in CT sequences for the management of renal diagnosis and treatments. In this paper, the authors propose a new graph-cuts-based active contours model with an adaptive width of narrow band for kidney extraction in CT image sequences. Based on graph cuts and contextual continuity, the segmentation is carried out slice-by-slice. In the first stage, the middle two adjacent slices in a CT sequence are segmented interactively based on the graph cuts approach. Subsequently, the deformable contour evolves toward the renal boundaries by the proposed model for the kidney extraction of the remaining slices. In this model, the energy function combining boundary with regional information is optimized in the constructed graph and the adaptive search range is determined by contextual continuity and the object size. In addition, in order to reduce the complexity of the min-cut computation, the nodes in the graph only have n-links for fewer edges. The total 30 CT images sequences with normal and pathological renal tissues are used to evaluate the accuracy and effectiveness of our method. The experimental results reveal that the average dice similarity coefficient of these image sequences is from 92.37% to 95.71% and the corresponding standard deviation for each dataset is from 2.18% to 3.87%. In addition, the average automatic segmentation time for one kidney in each slice is about 0.36 s. Integrating the graph-cuts-based active contours model with contextual continuity, the algorithm takes advantages of energy minimization and the characteristics of image sequences. The proposed method achieves effective results for kidney segmentation in CT sequences.

AN ORGANOTYPIC UNIAXIAL STRAIN MODEL USING MICROFLUIDICS

PubMed Central

Dollé, Jean-Pierre; Morrison, Barclay; Schloss, Rene R.; Yarmush, Martin L.

2012-01-01

Traumatic brain injuries are the leading cause of disability each year in the US. The most common and devastating consequence is the stretching of axons caused by shear deformation that occurs during rotational acceleration of the brain during injury. The injury effects on axonal molecular and functional events are not fully characterized. We have developed a strain injury model that maintains the three dimensional cell architecture and neuronal networks found in vivo with the ability to visualize individual axons and their response to a mechanical injury. The advantage of this model is that it can apply uniaxial strains to axons that make functional connections between two organotypic slices and injury responses can be observed in real-time and over long term. This uniaxial strain model was designed to be capable of applying an array of mechanical strains at various rates of strain, thus replicating a range of modes of axonal injury. Long term culture, preservation of slice and cell orientation, and slice-slice connection on the device was demonstrated. The device has the ability to strain either individual axons or bundles of axons through the control of microchannel dimensions. The fidelity of the model was verified by observing characteristic responses to various strain injuries which included axonal beading, delayed elastic effects and breakdown in microtubules. Microtubule breakdown was shown to be dependent on the degree of the applied strain field, where maximal breakdown was observed at peak strain and minimal breakdown is observed at low strain. This strain injury model could be a powerful tool in assessing strain injury effects on functional axonal connections. PMID:23233120

Analysis of Parametric Adaptive Signal Detection with Applications to Radars and Hyperspectral Imaging

DTIC Science & Technology

2010-02-01

98 8.4.5 Training Screening ............................. .................................................................99 8.5 Experimental...associated with the proposed parametric model. Several im- portant issues are discussed, including model order selection, training screening , and time...parameters associated with the NS-AR model. In addition, we develop model order selection, training screening , and time-series based whitening and

Influence of spatial beam inhomogeneities on the parameters of a petawatt laser system based on multi-stage parametric amplification

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

Frolov, S A; Trunov, V I; Pestryakov, Efim V

2013-05-31

We have developed a technique for investigating the evolution of spatial inhomogeneities in high-power laser systems based on multi-stage parametric amplification. A linearised model of the inhomogeneity development is first devised for parametric amplification with the small-scale self-focusing taken into account. It is shown that the application of this model gives the results consistent (with high accuracy and in a wide range of inhomogeneity parameters) with the calculation without approximations. Using the linearised model, we have analysed the development of spatial inhomogeneities in a petawatt laser system based on multi-stage parametric amplification, developed at the Institute of Laser Physics, Siberianmore » Branch of the Russian Academy of Sciences (ILP SB RAS). (control of laser radiation parameters)« less

Drying characteristics of garlic ( Allium sativum L) slices in a convective hot air dryer

NASA Astrophysics Data System (ADS)

Demiray, Engin; Tulek, Yahya

2014-06-01

The effects of drying temperatures on the drying kinetics of garlic slices were investigated using a cabinet-type dryer. The experimental drying data were fitted best to the Page and Modified Page models apart from other theoretical models to predict the drying kinetics. The effective moisture diffusivities varied from 4.214 × 10-10 to 2.221 × 10-10 m2 s-1 over the temperature range studied, and activation energy was 30.582 kJ mol-1.

Modeling the survival of Salmonella on slice cooked ham as a function of apple skin polyphenols, acetic acid, oregano essential oil and carvacrol

USDA-ARS?s Scientific Manuscript database

Response surface methodology was applied to investigate the combined effect of apple skin polyphenols (ASP), acetic acid (AA), oregano essential oil (O) and carvacrol (C) on the inactivation of Salmonella on sliced cooked ham. A full factorial experimental design was employed with control variables ...

Mathematical modeling the cross-contamination of food pathogens on the surface of ready-to-eat meats while slicing

USDA-ARS?s Scientific Manuscript database

The knowledge regarding food pathogens (Listeria monocytogenes, Escherichia coli O157:H7 and Salmonella spp.) surface transfer on ready-to-eat (RTE) deli meat and the slicer used for slicing different RTE products are needed to ensure RTE food safety. The objectives of this study were to investigat...

Computation of the intensities of parametric holographic scattering patterns in photorefractive crystals.

PubMed

Schwalenberg, Simon

2005-06-01

The present work represents a first attempt to perform computations of output intensity distributions for different parametric holographic scattering patterns. Based on the model for parametric four-wave mixing processes in photorefractive crystals and taking into account realistic material properties, we present computed images of selected scattering patterns. We compare these calculated light distributions to the corresponding experimental observations. Our analysis is especially devoted to dark scattering patterns as they make high demands on the underlying model.

A convolution model for computing the far-field directivity of a parametric loudspeaker array.

PubMed

Shi, Chuang; Kajikawa, Yoshinobu

2015-02-01

This paper describes a method to compute the far-field directivity of a parametric loudspeaker array (PLA), whereby the steerable parametric loudspeaker can be implemented when phased array techniques are applied. The convolution of the product directivity and the Westervelt's directivity is suggested, substituting for the past practice of using the product directivity only. Computed directivity of a PLA using the proposed convolution model achieves significant improvement in agreement to measured directivity at a negligible computational cost.

Computer aided three-dimensional reconstruction and modeling of the pelvis, by using plastinated cross sections, as a powerful tool for morphological investigations.

PubMed

Sora, Mircea-Constantin; Jilavu, Radu; Matusz, Petru

2012-10-01

The aim of this study was to describe a method of developing a computerized model of the human female pelvis using plastinated slices. Computerized reconstruction of anatomical structures is becoming very useful for developing anatomical teaching, research modules and animations. Although databases consisting of serial sections derived from frozen cadaver material exist, plastination represents an alternative method for developing anatomical data useful for computerized reconstruction. A slice anatomy study, using plastinated transparent pelvis cross sections, was performed to obtain a 3D reconstruction. One female human pelvis used for this study, first plastinated as a block, then sliced into thin slices and in the end subjected to 3D computerized reconstruction using WinSURF modeling system (SURFdriver Software). To facilitate the understanding of the complex pelvic floor anatomy on sectional images obtained through MR imaging, and to make the representation more vivid, a female pelvis computer-aided 3D model was created. Qualitative observations revealed that the morphological features of the model were consistent with those displayed by typical cadaveric specimens. The quality of the reconstructed images appeared distinct, especially the spatial positions and complicated relationships of contiguous structures of the female pelvis. All reconstructed structures can be displayed in groups or as a whole and interactively rotated in 3D space. The utilization of plastinates for generating tissue sections is useful for 3D computerized modeling. The 3D model of the female pelvis presented in this paper provides a stereoscopic view to study the adjacent relationship and arrangement of respective pelvis sections. A better understanding of the pelvic floor anatomy is relevant to gynaecologists, radiologists, surgeons, urologists, physical therapists and all professionals who take care of women with pelvic floor dysfunction.

Rosiglitazone Suppresses In Vitro Seizures in Hippocampal Slice by Inhibiting Presynaptic Glutamate Release in a Model of Temporal Lobe Epilepsy.

PubMed

Wong, Shi-Bing; Cheng, Sin-Jhong; Hung, Wei-Chen; Lee, Wang-Tso; Min, Ming-Yuan

2015-01-01

Peroxisomal proliferator-activated receptor gamma (PPARγ) is a nuclear hormone receptor whose agonist, rosiglitazone has a neuroprotective effect to hippocampal neurons in pilocarpine-induced seizures. Hippocampal slice preparations treated in Mg2+ free medium can induce ictal and interictal-like epileptiform discharges, which is regarded as an in vitro model of N-methyl-D-aspartate (NMDA) receptor-mediated temporal lobe epilepsy (TLE). We applied rosiglitazone in hippocampal slices treated in Mg2+ free medium. The effects of rosiglitazone on hippocampal CA1-Schaffer collateral synaptic transmission were tested. We also examined the neuroprotective effect of rosiglitazone toward NMDA excitotoxicity on cultured hippocampal slices. Application of 10 μM rosiglitazone significantly suppressed amplitude and frequency of epileptiform discharges in CA1 neurons. Pretreatment with the PPARγ antagonist GW9662 did not block the effect of rosiglitazone on suppressing discharge frequency, but reverse the effect on suppressing discharge amplitude. Application of rosiglitazone suppressed synaptic transmission in the CA1-Schaffer collateral pathway. By miniature excitatory-potential synaptic current (mEPSC) analysis, rosiglitazone significantly suppressed presynaptic neurotransmitter release. This phenomenon can be reversed by pretreating PPARγ antagonist GW9662. Also, rosiglitazone protected cultured hippocampal slices from NMDA-induced excitotoxicity. The protective effect of 10 μM rosiglitazone was partially antagonized by concomitant high dose GW9662 treatment, indicating that this effect is partially mediated by PPARγ receptors. In conclusion, rosiglitazone suppressed NMDA receptor-mediated epileptiform discharges by inhibition of presynaptic neurotransmitter release. Rosiglitazone protected hippocampal slice from NMDA excitotoxicity partially by PPARγ activation. We suggest that rosiglitazone could be a potential agent to treat patients with TLE.

Immature rat brain slices exposed to oxygen-glucose deprivation as an in vitro model of neonatal hypoxic-ischemic encephalopathy.

PubMed

Fernández-López, David; Martínez-Orgado, José; Casanova, Ignacio; Bonet, Bartolomé; Leza, Juan Carlos; Lorenzo, Pedro; Moro, Maria Angeles; Lizasoain, Ignacio

2005-06-30

To analyze whether exposure to oxygen-glucose deprivation (OGD) of immature rat brain slices might reproduce the main pathophysiologic events leading to neuronal death in neonatal hypoxic-ischemic encephalopathy (NHIE), 500 microm-thick brain slices were obtained from 7-day-old Wistar rats, and incubated in oxygenated physiological solution. In OGD group, oxygen and glucose were removed from the medium for 10-30 min (n = 25); then, slices were re-incubated in normal medium. In control group the medium composition remained unchanged (CG, n = 30). Medium samples were obtained every 30 min for 3 h. To analyze neuronal damage, slices were stained with Nissl and CA1 area of hippocampus and cortex were observed under microscopy. In addition, neuronal death was quantified as LDH released to the medium determined by spectrophotometry. Additionally, medium glutamate (Glu) levels were determined by HPLC and those of TNFalpha by ELISA, whereas inducible nitric oxide synthase expression was determined by Western blot performed on slices homogenate. Optimal OGD time was established in 20 min. After OGD, a significant decrease in the number of neurones in hippocampus and cortex was observed. LDH release was maximal at 30 min, when it was five-fold greater than in CG. Furthermore, medium Glu concentrations were 200 times greater than CG levels at the end of OGD period. A linear relationship between Glu and LDH release was demonstrated. Finally, 3 h after OGD a significant induction of iNOS as well as an increase in TNFalpha release were observed. In conclusion, OGD appears as a feasible and reproducible in vitro model, leading to a neuronal damage, which is physiopathologically similar to that found in NHIE.

Revisiting dark energy models using differential ages of galaxies

NASA Astrophysics Data System (ADS)

Rani, Nisha; Jain, Deepak; Mahajan, Shobhit; Mukherjee, Amitabha; Biesiada, Marek

2017-03-01

In this work, we use a test based on the differential ages of galaxies for distinguishing the dark energy models. As proposed by Jimenez and Loeb in [1], relative ages of galaxies can be used to put constraints on various cosmological parameters. In the same vein, we reconstruct H0dt/dz and its derivative (H0d2t/dz2) using a model independent technique called non-parametric smoothing. Basically, dt/dz is the change in the age of the object as a function of redshift which is directly linked with the Hubble parameter. Hence for reconstruction of this quantity, we use the most recent H(z) data. Further, we calculate H0dt/dz and its derivative for several models like Phantom, Einstein de Sitter (EdS), ΛCDM, Chevallier-Polarski-Linder (CPL) parametrization, Jassal-Bagla-Padmanabhan (JBP) parametrization and Feng-Shen-Li-Li (FSLL) parametrization. We check the consistency of these models with the results of reconstruction obtained in a model independent way from the data. It is observed that H0dt/dz as a tool is not able to distinguish between the ΛCDM, CPL, JBP and FSLL parametrizations but, as expected, EdS and Phantom models show noticeable deviation from the reconstructed results. Further, the derivative of H0dt/dz for various dark energy models is more sensitive at low redshift. It is found that the FSLL model is not consistent with the reconstructed results, however, the ΛCDM model is in concordance with the 3σ region of the reconstruction at redshift z>= 0.3.

40 CFR Appendix C to Part 75 - Missing Data Estimation Procedures

Code of Federal Regulations, 2010 CFR

2010-07-01

... certification of a parametric, empirical, or process simulation method or model for calculating substitute data... available process simulation methods and models. 1.2Petition Requirements Continuously monitor, determine... desulfurization, a corresponding empirical correlation or process simulation parametric method using appropriate...

Comparison of Two Methods of Noise Power Spectrum Determinations of Medical Radiography Systems

NASA Astrophysics Data System (ADS)

Hassan, Wan Muhamad Saridan Wan; Ahmed Darwish, Zeki

2011-03-01

Noise in medical images is recognized as an important factor that determines the image quality. Image noise is characterized by noise power spectrum (NPS). We compared two methods of NPS determination namely the methods of Wagner and Dobbins on Lanex Regular TMG screen-film system and Hologic Lorad Selenia full field digital mammography system, with the aim of choosing the better method to use. The methods differ in terms of various parametric choices and algorithm implementations. These parameters include the low pass filtering, low frequency filtering, windowing, smoothing, aperture correction, overlapping of region of interest (ROI), length of fast Fourier transform, ROI size, method of ROI normalization, and slice selection of the NPS. Overall, the two methods agreed to the practical value of noise power spectrum between 10-3-10-6 mm2 over spatial frequency range 0-10 mm-1.

Theoretical frameworks for testing relativistic gravity. IV - A compendium of metric theories of gravity and their post-Newtonian limits.

NASA Technical Reports Server (NTRS)

Ni, W.-T.

1972-01-01

Metric theories of gravity are compiled and classified according to the types of gravitational fields they contain, and the modes of interaction among those fields. The gravitation theories considered are classified as (1) general relativity, (2) scalar-tensor theories, (3) conformally flat theories, and (4) stratified theories with conformally flat space slices. The post-Newtonian limit of each theory is constructed and its Parametrized Post-Newtonian (PPN) values are obtained by comparing it with Will's version of the formalism. Results obtained here, when combined with experimental data and with recent work by Nordtvedt and Will and by Ni, show that, of all theories thus far examined by our group, the only currently viable ones are general relativity, the Bergmann-Wagoner scalar-tensor theory and its special cases (Nordtvedt; Brans-Dicke-Jordan), and a recent, new vector-tensor theory by Nordtvedt, Hellings, and Will.

Modeling and Visualization Process of the Curve of Pen Point by GeoGebra

ERIC Educational Resources Information Center

Aktümen, Muharem; Horzum, Tugba; Ceylan, Tuba

2013-01-01

This study describes the mathematical construction of a real-life model by means of parametric equations, as well as the two- and three-dimensional visualization of the model using the software GeoGebra. The model was initially considered as "determining the parametric equation of the curve formed on a plane by the point of a pen, positioned…

Developmental models for estimating ecological responses to environmental variability: structural, parametric, and experimental issues.

PubMed

Moore, Julia L; Remais, Justin V

2014-03-01

Developmental models that account for the metabolic effect of temperature variability on poikilotherms, such as degree-day models, have been widely used to study organism emergence, range and development, particularly in agricultural and vector-borne disease contexts. Though simple and easy to use, structural and parametric issues can influence the outputs of such models, often substantially. Because the underlying assumptions and limitations of these models have rarely been considered, this paper reviews the structural, parametric, and experimental issues that arise when using degree-day models, including the implications of particular structural or parametric choices, as well as assumptions that underlie commonly used models. Linear and non-linear developmental functions are compared, as are common methods used to incorporate temperature thresholds and calculate daily degree-days. Substantial differences in predicted emergence time arose when using linear versus non-linear developmental functions to model the emergence time in a model organism. The optimal method for calculating degree-days depends upon where key temperature threshold parameters fall relative to the daily minimum and maximum temperatures, as well as the shape of the daily temperature curve. No method is shown to be universally superior, though one commonly used method, the daily average method, consistently provides accurate results. The sensitivity of model projections to these methodological issues highlights the need to make structural and parametric selections based on a careful consideration of the specific biological response of the organism under study, and the specific temperature conditions of the geographic regions of interest. When degree-day model limitations are considered and model assumptions met, the models can be a powerful tool for studying temperature-dependent development.

Influence of drying air parameters on mass transfer characteristics of apple slices

NASA Astrophysics Data System (ADS)

Beigi, Mohsen

2016-10-01

To efficiently design both new drying process and equipment and/or to improve the existing systems, accurate values of mass transfer characteristics are necessary. The present study aimed to investigate the influence of drying air parameters (i.e. temperature, velocity and relative humidity) on effective diffusivity and convective mass transfer coefficient of apple slices. The Dincer and Dost model was used to determine the mass transfer characteristics. The obtained Biot number indicated that the moisture transfer in the apple slices was controlled by both internal and external resistance. The effective diffusivity and mass transfer coefficient values obtained to be in the ranges of 7.13 × 10-11-7.66 × 10-10 and 1.46 × 10-7-3.39 × 10-7 m s-1, respectively and the both of them increased with increasing drying air temperature and velocity, and decreasing relative humidity. The validation of the model showed that the model predicted the experimental drying curves of the samples with a good accuracy.

Chaos Control of Epileptiform Bursting in the Brain

NASA Astrophysics Data System (ADS)

Slutzky, M. W.; Cvitanovic, P.; Mogul, D. J.

Epilepsy, defined as recurrent seizures, is a pathological state of the brain that afflicts over one percent of the world's population. Seizures occur as populations of neurons in the brain become overly synchronized. Although pharmacological agents are the primary treatment for preventing or reducing the incidence of these seizures, over 30% of epilepsy cases are not adequately helped by standard medical therapies. Several groups are exploring the use of electrical stimulation to terminate or prevent epileptic seizures. One experimental model used to test these algorithms is the brain slice where a select region of the brain is cut and kept viable in a well-oxygenated artificial cerebrospinal fluid. Under certain conditions, such slices may be made to spontaneously and repetitively burst, thereby providing an in vitro model of epilepsy. In this chapter, we discuss our efforts at applying chaos analysis and chaos control algorithms for manipulating this seizure-like behavior in a brain slice model. These techniques may provide a nonlinear control pathway for terminating or potentially preventing epileptic seizures in the whole brain.

AMBER: a PIC slice code for DARHT

NASA Astrophysics Data System (ADS)

Vay, Jean-Luc; Fawley, William

1999-11-01

The accelerator for the second axis of the Dual Axis Radiographic Hydrodynamic Test (DARHT) facility will produce a 4-kA, 20-MeV, 2-μ s output electron beam with a design goal of less than 1000 π mm-mrad normalized transverse emittance and less than 0.5-mm beam centroid motion. In order to study the beam dynamics throughout the accelerator, we have developed a slice Particle-In-Cell code named AMBER, in which the beam is modeled as a time-steady flow, subject to self, as well as external, electrostatic and magnetostatic fields. The code follows the evolution of a slice of the beam as it propagates through the DARHT accelerator lattice, modeled as an assembly of pipes, solenoids and gaps. In particular, we have paid careful attention to non-paraxial phenomena that can contribute to nonlinear forces and possible emittance growth. We will present the model and the numerical techniques implemented, as well as some test cases and some preliminary results obtained when studying emittance growth during the beam propagation.

SPM analysis of parametric (R)-[11C]PK11195 binding images: plasma input versus reference tissue parametric methods.

PubMed

Schuitemaker, Alie; van Berckel, Bart N M; Kropholler, Marc A; Veltman, Dick J; Scheltens, Philip; Jonker, Cees; Lammertsma, Adriaan A; Boellaard, Ronald

2007-05-01

(R)-[11C]PK11195 has been used for quantifying cerebral microglial activation in vivo. In previous studies, both plasma input and reference tissue methods have been used, usually in combination with a region of interest (ROI) approach. Definition of ROIs, however, can be labourious and prone to interobserver variation. In addition, results are only obtained for predefined areas and (unexpected) signals in undefined areas may be missed. On the other hand, standard pharmacokinetic models are too sensitive to noise to calculate (R)-[11C]PK11195 binding on a voxel-by-voxel basis. Linearised versions of both plasma input and reference tissue models have been described, and these are more suitable for parametric imaging. The purpose of this study was to compare the performance of these plasma input and reference tissue parametric methods on the outcome of statistical parametric mapping (SPM) analysis of (R)-[11C]PK11195 binding. Dynamic (R)-[11C]PK11195 PET scans with arterial blood sampling were performed in 7 younger and 11 elderly healthy subjects. Parametric images of volume of distribution (Vd) and binding potential (BP) were generated using linearised versions of plasma input (Logan) and reference tissue (Reference Parametric Mapping) models. Images were compared at the group level using SPM with a two-sample t-test per voxel, both with and without proportional scaling. Parametric BP images without scaling provided the most sensitive framework for determining differences in (R)-[11C]PK11195 binding between younger and elderly subjects. Vd images could only demonstrate differences in (R)-[11C]PK11195 binding when analysed with proportional scaling due to intersubject variation in K1/k2 (blood-brain barrier transport and non-specific binding).

Marginally specified priors for non-parametric Bayesian estimation

PubMed Central

Kessler, David C.; Hoff, Peter D.; Dunson, David B.

2014-01-01

Summary Prior specification for non-parametric Bayesian inference involves the difficult task of quantifying prior knowledge about a parameter of high, often infinite, dimension. A statistician is unlikely to have informed opinions about all aspects of such a parameter but will have real information about functionals of the parameter, such as the population mean or variance. The paper proposes a new framework for non-parametric Bayes inference in which the prior distribution for a possibly infinite dimensional parameter is decomposed into two parts: an informative prior on a finite set of functionals, and a non-parametric conditional prior for the parameter given the functionals. Such priors can be easily constructed from standard non-parametric prior distributions in common use and inherit the large support of the standard priors on which they are based. Additionally, posterior approximations under these informative priors can generally be made via minor adjustments to existing Markov chain approximation algorithms for standard non-parametric prior distributions. We illustrate the use of such priors in the context of multivariate density estimation using Dirichlet process mixture models, and in the modelling of high dimensional sparse contingency tables. PMID:25663813

Redefining the stormwater first flush phenomenon.

PubMed

Bach, Peter M; McCarthy, David T; Deletic, Ana

2010-04-01

The first flush in urban runoff has been an important, yet disputed phenomenon amongst many researchers. The vast differences in the evidence could be solely due to limitations of the first flush current definition and the approach used for its assessment. There is a need for revisiting the first flush theory in the light of its practical applications to urban drainage management practices. We propose that a catchment's first flush behaviour is to be quantified by the runoff volume required to reduce a catchment's stormwater pollutant concentrations to background levels. The proposed method for assessment of this runoff volume starts by finding the average catchment pollutant concentrations for a given increment of discharged volume using a number of event pollutographs. Non-parametric statistics are then used to establish the characteristic pollutograph by pooling statistically indifferent runoff increments (known as slices) together. This allows the identification of the catchment's initial and background pollutant concentrations and for quantification of the first flush volume and its strength. The novel technique was used on seven catchments around Melbourne, Australia, with promising results. Sensitivity to the chosen increment of runoff (for which mean concentrations are calculated) indicated that when dealing with discrete flow-weighted water quality data, a suitable slice size should closely match the flow-weighting of samples. The overall sensitivity to runoff increment and level of significance was found to be negligible. Further research is needed to fully develop this method. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Reproducibility Between Brain Uptake Ratio Using Anatomic Standardization and Patlak-Plot Methods.

PubMed

Shibutani, Takayuki; Onoguchi, Masahisa; Noguchi, Atsushi; Yamada, Tomoki; Tsuchihashi, Hiroko; Nakajima, Tadashi; Kinuya, Seigo

2015-12-01

The Patlak-plot and conventional methods of determining brain uptake ratio (BUR) have some problems with reproducibility. We formulated a method of determining BUR using anatomic standardization (BUR-AS) in a statistical parametric mapping algorithm to improve reproducibility. The objective of this study was to demonstrate the inter- and intraoperator reproducibility of mean cerebral blood flow as determined using BUR-AS in comparison to the conventional-BUR (BUR-C) and Patlak-plot methods. The images of 30 patients who underwent brain perfusion SPECT were retrospectively used in this study. The images were reconstructed using ordered-subset expectation maximization and processed using an automatic quantitative analysis for cerebral blood flow of ECD tool. The mean SPECT count was calculated from axial basal ganglia slices of the normal side (slices 31-40) drawn using a 3-dimensional stereotactic region-of-interest template after anatomic standardization. The mean cerebral blood flow was calculated from the mean SPECT count. Reproducibility was evaluated using coefficient of variation and Bland-Altman plotting. For both inter- and intraoperator reproducibility, the BUR-AS method had the lowest coefficient of variation and smallest error range about the Bland-Altman plot. Mean CBF obtained using the BUR-AS method had the highest reproducibility. Compared with the Patlak-plot and BUR-C methods, the BUR-AS method provides greater inter- and intraoperator reproducibility of cerebral blood flow measurement. © 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

The virtual slice setup.

PubMed

Lytton, William W; Neymotin, Samuel A; Hines, Michael L

2008-06-30

In an effort to design a simulation environment that is more similar to that of neurophysiology, we introduce a virtual slice setup in the NEURON simulator. The virtual slice setup runs continuously and permits parameter changes, including changes to synaptic weights and time course and to intrinsic cell properties. The virtual slice setup permits shocks to be applied at chosen locations and activity to be sampled intra- or extracellularly from chosen locations. By default, a summed population display is shown during a run to indicate the level of activity and no states are saved. Simulations can run for hours of model time, therefore it is not practical to save all of the state variables. These, in any case, are primarily of interest at discrete times when experiments are being run: the simulation can be stopped momentarily at such times to save activity patterns. The virtual slice setup maintains an automated notebook showing shocks and parameter changes as well as user comments. We demonstrate how interaction with a continuously running simulation encourages experimental prototyping and can suggest additional dynamical features such as ligand wash-in and wash-out-alternatives to typical instantaneous parameter change. The virtual slice setup currently uses event-driven cells and runs at approximately 2 min/h on a laptop.

Computed Tomography Scanner Productivity and Entry-Level Models in the Global Market

PubMed Central

Almeida, R. M. V. R.

2017-01-01

Objective This study evaluated the productivity of computed tomography (CT) models and characterized their simplest (entry-level) models' supply in the world market. Methods CT exam times were measured in eight health facilities in the state of Rio de Janeiro, Brazil. Exams were divided into six stages: (1) arrival of patient records to the examination room; (2) patient arrival; (3) patient positioning; (4) data input prior to exam; (5) image acquisition; and (6) patient departure. CT exam productivity was calculated by dividing the total weekly working time by the total exam time for each model. Additionally, an internet search identified full-body CT manufacturers and their offered entry-level models. Results The time durations of 111 CT exams were obtained. Differences among average exam times were not large, and they were mainly due to stages not directly related to data acquisition or image reconstruction. The survey identified that most manufacturers offer 2- to 4-slice models for Asia, South America, and Africa, and one offers single-slice models (Asia). In the USA, two manufacturers offer models below 16-slice. Conclusion Productivity gains are not linearly related to “slice” number. It is suggested that the use of “shareable platforms” could make CTs cheaper, increasing their availability. PMID:29093804

Regulation of Axolotl (Ambystoma mexicanum) Limb Blastema Cell Proliferation by Nerves and BMP2 in Organotypic Slice Culture.

PubMed

Lehrberg, Jeffrey; Gardiner, David M

2015-01-01

We have modified and optimized the technique of organotypic slice culture in order to study the mechanisms regulating growth and pattern formation in regenerating axolotl limb blastemas. Blastema cells maintain many of the behaviors that are characteristic of blastemas in vivo when cultured as slices in vitro, including rates of proliferation that are comparable to what has been reported in vivo. Because the blastema slices can be cultured in basal medium without fetal bovine serum, it was possible to test the response of blastema cells to signaling molecules present in serum, as well as those produced by nerves. We also were able to investigate the response of blastema cells to experimentally regulated changes in BMP signaling. Blastema cells responded to all of these signals by increasing the rate of proliferation and the level of expression of the blastema marker gene, Prrx-1. The organotypic slice culture model provides the opportunity to identify and characterize the spatial and temporal co-regulation of pathways in order to induce and enhance a regenerative response.

Regulation of Axolotl (Ambystoma mexicanum) Limb Blastema Cell Proliferation by Nerves and BMP2 in Organotypic Slice Culture

PubMed Central

Lehrberg, Jeffrey; Gardiner, David M.

2015-01-01

We have modified and optimized the technique of organotypic slice culture in order to study the mechanisms regulating growth and pattern formation in regenerating axolotl limb blastemas. Blastema cells maintain many of the behaviors that are characteristic of blastemas in vivo when cultured as slices in vitro, including rates of proliferation that are comparable to what has been reported in vivo. Because the blastema slices can be cultured in basal medium without fetal bovine serum, it was possible to test the response of blastema cells to signaling molecules present in serum, as well as those produced by nerves. We also were able to investigate the response of blastema cells to experimentally regulated changes in BMP signaling. Blastema cells responded to all of these signals by increasing the rate of proliferation and the level of expression of the blastema marker gene, Prrx-1. The organotypic slice culture model provides the opportunity to identify and characterize the spatial and temporal co-regulation of pathways in order to induce and enhance a regenerative response. PMID:25923915

Evaluating the morphological completeness of a training image.

PubMed

Gao, Mingliang; Teng, Qizhi; He, Xiaohai; Feng, Junxi; Han, Xue

2017-05-01

Understanding the three-dimensional (3D) stochastic structure of a porous medium is helpful for studying its physical properties. A 3D stochastic structure can be reconstructed from a two-dimensional (2D) training image (TI) using mathematical modeling. In order to predict what specific morphology belonging to a TI can be reconstructed at the 3D orthogonal slices by the method of 3D reconstruction, this paper begins by introducing the concept of orthogonal chords. After analyzing the relationship among TI morphology, orthogonal chords, and the 3D morphology of orthogonal slices, a theory for evaluating the morphological completeness of a TI is proposed for the cases of three orthogonal slices and of two orthogonal slices. The proposed theory is evaluated using four TIs of porous media that represent typical but distinct morphological types. The significance of this theoretical evaluation lies in two aspects: It allows special morphologies, for which the attributes of a TI can be reconstructed at a special orthogonal slice of a 3D structure, to be located and quantified, and it can guide the selection of an appropriate reconstruction method for a special TI.

Rating knowledge sharing in cross-domain collaborative filtering.

PubMed

Li, Bin; Zhu, Xingquan; Li, Ruijiang; Zhang, Chengqi

2015-05-01

Cross-domain collaborative filtering (CF) aims to share common rating knowledge across multiple related CF domains to boost the CF performance. In this paper, we view CF domains as a 2-D site-time coordinate system, on which multiple related domains, such as similar recommender sites or successive time-slices, can share group-level rating patterns. We propose a unified framework for cross-domain CF over the site-time coordinate system by sharing group-level rating patterns and imposing user/item dependence across domains. A generative model, say ratings over site-time (ROST), which can generate and predict ratings for multiple related CF domains, is developed as the basic model for the framework. We further introduce cross-domain user/item dependence into ROST and extend it to two real-world cross-domain CF scenarios: 1) ROST (sites) for alleviating rating sparsity in the target domain, where multiple similar sites are viewed as related CF domains and some items in the target domain depend on their correspondences in the related ones; and 2) ROST (time) for modeling user-interest drift over time, where a series of time-slices are viewed as related CF domains and a user at current time-slice depends on herself in the previous time-slice. All these ROST models are instances of the proposed unified framework. The experimental results show that ROST (sites) can effectively alleviate the sparsity problem to improve rating prediction performance and ROST (time) can clearly track and visualize user-interest drift over time.

Kynurenine 3-mono-oxygenase inhibitors attenuate post-ischemic neuronal death in organotypic hippocampal slice cultures.

PubMed

Carpenedo, Raffaella; Meli, Elena; Peruginelli, Fiamma; Pellegrini-Giampietro, Domenico E; Moroni, Flavio

2002-09-01

Kynurenine 3-mono-oxygenase (KMO) inhibitors reduce 3-hydroxykynurenine (3-HK) and quinolinic acid (QUIN) neosynthesis and facilitate kynurenine metabolism towards kynurenic acid (KYNA) formation. They also reduce tissue damage in models of focal or transient global cerebral ischemia in vivo. We used organotypic hippocampal slice cultures exposed to oxygen and glucose deprivation (OGD) to investigate KMO mechanism(s) of neuroprotective activity. Exposure of the slices to 30 min of OGD caused CA1 pyramidal cell death and significantly decreased the amount of KYNA released in the incubation medium. The KMO inhibitors (m-nitrobenzoyl)-alanine (30-100 micro m) or 3,4-dimethoxy-[-N-4-(nitrophenyl)thiazol-2yl]-benzenesulfonamide (1-10 micro m) reduced post-ischemic neuronal death and increased KYNA concentrations in slice incubation media. The maximal concentration of KYNA detected in the incubation media of slices treated with KMO inhibitors was approximately 50 nm and was too low to efficiently interact with alpha7 nicotinic acetylcholine receptors or with the glycineb site of N-methyl-d-aspartate (NMDA) receptors. On the other hand, the addition of either 3-HK or QUIN (1-10 micro m) to OGD-exposed hippocampal slices prevented the neuroprotective activity of KMO inhibitors. Our results suggest that KMO inhibitors reduce the neuronal death found in the CA1 region of organotypic hippocampal slices exposed to 30 min of OGD by decreasing the local synthesis of 3-HK and QUIN.

Decreased GABA-A binding on FMZ-PET in succinic semialdehyde dehydrogenase deficiency.

PubMed

Pearl, P L; Gibson, K M; Quezado, Z; Dustin, I; Taylor, J; Trzcinski, S; Schreiber, J; Forester, K; Reeves-Tyer, P; Liew, C; Shamim, S; Herscovitch, P; Carson, R; Butman, J; Jakobs, C; Theodore, W

2009-08-11

Succinic semialdehyde dehydrogenase (SSADH) deficiency is an autosomal recessive disorder of GABA metabolism characterized by elevated levels of GABA and gamma-hydroxybutyric acid. Clinical findings include intellectual impairment, hypotonia, hyporeflexia, hallucinations, autistic behaviors, and seizures. Autoradiographic labeling and slice electrophysiology studies in the murine model demonstrate use-dependent downregulation of GABA(A) receptors. We studied GABA(A) receptor activity in human SSADH deficiency utilizing [(11)C]-flumazenil (FMZ)-PET. FMZ binding was measured in 7 patients, 10 unaffected parents, and 8 healthy controls. Data analysis was performed using a reference region compartmental model, with time-activity curve from pons as the input function. Relative parametric binding potential (BP(ND)) was derived, with MRI-based pixel by pixel partial volume correction, in regions of interest drawn on coregistered MRI. In amygdala, hippocampus, cerebellar vermis, frontal, parietal, and occipital cortex, patients with SSADH deficiency had significant reductions in FMZ BP(ND) compared to parents and controls. Mean cortical values were 6.96 +/- 0.79 (controls), 6.89 +/- 0.71 (parents), and 4.88 +/- 0.77 (patients) (F ratio 16.1; p < 0.001). There were no differences between controls and parents in any cortical region. Succinic semialdehyde dehydrogenase (SSADH) deficient patients show widespread reduction in BZPR binding on [(11)C]-flumazenil-PET. Our results suggest that high endogenous brain GABA levels in SSADH deficiency downregulate GABA(A)-BZPR binding site availability. This finding suggests a potential mechanism for neurologic dysfunction in a serious neurodevelopmental disorder, and suggests that PET may be useful to translate studies in animal models to human disease.

Automatic 3D segmentation of spinal cord MRI using propagated deformable models

NASA Astrophysics Data System (ADS)

De Leener, B.; Cohen-Adad, J.; Kadoury, S.

2014-03-01

Spinal cord diseases or injuries can cause dysfunction of the sensory and locomotor systems. Segmentation of the spinal cord provides measures of atrophy and allows group analysis of multi-parametric MRI via inter-subject registration to a template. All these measures were shown to improve diagnostic and surgical intervention. We developed a framework to automatically segment the spinal cord on T2-weighted MR images, based on the propagation of a deformable model. The algorithm is divided into three parts: first, an initialization step detects the spinal cord position and orientation by using the elliptical Hough transform on multiple adjacent axial slices to produce an initial tubular mesh. Second, a low-resolution deformable model is iteratively propagated along the spinal cord. To deal with highly variable contrast levels between the spinal cord and the cerebrospinal fluid, the deformation is coupled with a contrast adaptation at each iteration. Third, a refinement process and a global deformation are applied on the low-resolution mesh to provide an accurate segmentation of the spinal cord. Our method was evaluated against a semi-automatic edge-based snake method implemented in ITK-SNAP (with heavy manual adjustment) by computing the 3D Dice coefficient, mean and maximum distance errors. Accuracy and robustness were assessed from 8 healthy subjects. Each subject had two volumes: one at the cervical and one at the thoracolumbar region. Results show a precision of 0.30 +/- 0.05 mm (mean absolute distance error) in the cervical region and 0.27 +/- 0.06 mm in the thoracolumbar region. The 3D Dice coefficient was of 0.93 for both regions.

Parametric analysis of ATM solar array.

NASA Technical Reports Server (NTRS)

Singh, B. K.; Adkisson, W. B.

1973-01-01

The paper discusses the methods used for the calculation of ATM solar array performance characteristics and provides the parametric analysis of solar panels used in SKYLAB. To predict the solar array performance under conditions other than test conditions, a mathematical model has been developed. Four computer programs have been used to convert the solar simulator test data to the parametric curves. The first performs module summations, the second determines average solar cell characteristics which will cause a mathematical model to generate a curve matching the test data, the third is a polynomial fit program which determines the polynomial equations for the solar cell characteristics versus temperature, and the fourth program uses the polynomial coefficients generated by the polynomial curve fit program to generate the parametric data.

Time-space modal logic for verification of bit-slice circuits

NASA Astrophysics Data System (ADS)

Hiraishi, Hiromi

1996-03-01

The major goal of this paper is to propose a new modal logic aiming at formal verification of bit-slice circuits. The new logic is called as time-space modal logic and its major feature is that it can handle two transition relations: one for time transition and the other for space transition. As for a verification algorithm, a symbolic model checking algorithm of the new logic is shown. This could be applicable to verification of bit-slice microprocessor of infinite bit width and 1D systolic array of infinite length. A simple benchmark result shows the effectiveness of the proposed approach.

Toward A Fail-Safe Air Force Culture: Creating a Resilient Future While Avoiding Past Mistakes

DTIC Science & Technology

2012-10-01

process often uses the “ Swiss cheese ” model to evaluate accidents. The image of holes in the protective cheese layers (proactive and reactive measures...minimize the number and size of holes in each slice of cheese . More importantly, however, a HRO’s 16 focus is on “the process of the slices lining up as

Modeling the surface cross-contamination of Salmonella spp. on ready-to-eat meat via a slicing operation

USDA-ARS?s Scientific Manuscript database

Food pathogen cross-contamination occurring in the home or at retail food service or the production site is a major factor contributing to food-borne illness. Studies on Salmonella spp. surface transfer on ready-to-eat (RTE) deli meat and the slicer used for slicing RTE products are needed to ensur...

Ophthalmologic diagnostic tool using MR images for biomechanically-based muscle volume deformation

NASA Astrophysics Data System (ADS)

Buchberger, Michael; Kaltofen, Thomas

2003-05-01

We would like to give a work-in-progress report on our ophthalmologic diagnostic software system which performs biomechanically-based muscle volume deformations using MR images. For reconstructing a three-dimensional representation of an extraocular eye muscle, a sufficient amount of high resolution MR images is used, each representing a slice of the muscle. In addition, threshold values are given, which restrict the amount of data used from the MR images. The Marching Cube algorithm is applied to the polygons, resulting in a 3D representation of the muscle, which can efficiently be rendered. A transformation to a dynamic, deformable model is applied by calculating the center of gravity of each muscle slice, approximating the muscle path and subsequently adding Hermite splines through the centers of gravity of all slices. Then, a radius function is defined for each slice, completing the transformation of the static 3D polygon model. Finally, this paper describes future extensions to our system. One of these extensions is the support for additional calculations and measurements within the reconstructed 3D muscle representation. Globe translation, localization of muscle pulleys by analyzing the 3D reconstruction in two different gaze positions and other diagnostic measurements will be available.

A novel method for air drying aloe leaf slices by covering with filter papers as a shrink-proof layer.

PubMed

Kim, S A; Baek, J H; Lee, S J; Choi, S Y; Hur, W; Lee, S Y

2009-01-01

To prevent the shrinkage of aloe vera slices during air drying, a method utilizing a shrink-proof layer was developed. The sample was configured of whole leaf aloe slices, where 1 side or both sides were covered with filter papers as shrink-proof layers. After air drying by varying the air temperature and the slice thickness, the drying characteristics, as well as several quality factors of the dried aloe vera leaf slices, were analyzed. In the simulation of the drying curves, the modified Page model showed the best fitness, representing a diffusion-controlled drying mechanism. Nonetheless, there was a trace of a constant-rate drying period in the samples dried by the method. Shrinkage was greatly reduced, and the rehydration ratios increased by approximately 50%. Scanning electron microscopic analysis revealed that the surface structure of original fibrous form was well sustained. FT-IR characteristics showed that the dried samples could sustain aloe polysaccharide acetylation. Furthermore, the functional properties of the dried slices including water holding capacity, swelling, and fat absorption capability were improved, and polysaccharide retention levels increased by 20% to 30%. Therefore, we concluded that application of shrink-proof layers on aloe slices provides a novel way to overcome the shrinkage problems commonly found in air drying, thereby improving their functional properties with less cost. Practical Application: This research article demonstrates a novel air drying method using shrink-proof layers to prevent the shrinkage of aloe slices. We analyzed extensively the characteristics of shrinkage mechanism and physical properties of aloe flesh gels in this drying system. We concluded that this method can be a beneficial means to retain the functional properties of dried aloe, and a potential alternative to freeze drying, which is still costly.

Sgr A* Emission Parametrizations from GRMHD Simulations

NASA Astrophysics Data System (ADS)

Anantua, Richard; Ressler, Sean; Quataert, Eliot

2018-06-01

Galactic Center emission near the vicinity of the central black hole, Sagittarius (Sgr) A*, is modeled using parametrizations involving the electron temperature, which is found from general relativistic magnetohydrodynamic (GRMHD) simulations to be highest in the disk-outflow corona. Jet-motivated prescriptions generalizing equipartition of particle and magnetic energies, e.g., by scaling relativistic electron energy density to powers of the magnetic field strength, are also introduced. GRMHD jet (or outflow)/accretion disk/black hole (JAB) simulation postprocessing codes IBOTHROS and GRMONTY are employed in the calculation of images and spectra. Various parametric models reproduce spectral and morphological features, such as the sub-mm spectral bump in electron temperature models and asymmetric photon rings in equipartition-based models. The Event Horizon Telescope (EHT) will provide unprecedentedly high-resolution 230+ GHz observations of the "shadow" around Sgr A*'s supermassive black hole, which the synthetic models presented here will reverse-engineer. Both electron temperature and equipartition-based models can be constructed to be compatible with EHT size constraints for the emitting region of Sgr A*. This program sets the groundwork for devising a unified emission parametrization flexible enough to model disk, corona and outflow/jet regions with a small set of parameters including electron heating fraction and plasma beta.

A Parametric Computational Model of the Action Potential of Pacemaker Cells.

PubMed

Ai, Weiwei; Patel, Nitish D; Roop, Partha S; Malik, Avinash; Andalam, Sidharta; Yip, Eugene; Allen, Nathan; Trew, Mark L

2018-01-01

A flexible, efficient, and verifiable pacemaker cell model is essential to the design of real-time virtual hearts that can be used for closed-loop validation of cardiac devices. A new parametric model of pacemaker action potential is developed to address this need. The action potential phases are modeled using hybrid automaton with one piecewise-linear continuous variable. The model can capture rate-dependent dynamics, such as action potential duration restitution, conduction velocity restitution, and overdrive suppression by incorporating nonlinear update functions. Simulated dynamics of the model compared well with previous models and clinical data. The results show that the parametric model can reproduce the electrophysiological dynamics of a variety of pacemaker cells, such as sinoatrial node, atrioventricular node, and the His-Purkinje system, under varying cardiac conditions. This is an important contribution toward closed-loop validation of cardiac devices using real-time heart models.

Quantitative transfer of Salmonella Typhimurium LT2 during mechanical slicing of tomatoes as impacted by multiple processing variables.

PubMed

Wang, Haiqiang; Ryser, Elliot T

2016-10-03

Slicing of fresh produce can readily lead to pathogen cross-contamination with pre-sliced tomatoes having been linked to multistate outbreaks of salmonellosis in the United States. This study aimed to assess the impact of multiple processing variables on quantitative transfer of Salmonella during simulated commercial slicing of tomatoes. One red round tomato was inoculated with Salmonella Typhimurium LT2 at ~5logCFU/g and sliced using a manual or electric slicer, followed by 20 uninoculated tomatoes. Thereafter, the distribution of Salmonella on inoculated and uninoculated tomato slices was evaluated along with the transfer of Salmonella from different parts of the slicer. The impact of multiple processing variables including post-contamination hold time (0 and 30min), tomato wetness (dry and wet), processing room temperature (23, 10 and 4°C), slice thickness (0.48, 0.64, and 0.95cm), tomato variety (Torero, Rebelski, and Bigdena) and pre-wash treatment (no wash, tap water, and chlorine) was also investigated. The data were fitted to a two-parameter exponential decay model (Y=A⋅exp(BX)) with the percentage of Salmonella transferred to 20 uninoculated tomatoes then calculated. Salmonella populations on nine inoculated tomato slices ranged from 4.6±0.2 to 5.5±0.3logCFU/g, with higher populations on slices from the blossom and stem scar ends. However, Salmonella transfer to the previously uninoculated slices was similar (P>0.05), ranging from 2.1±0.2 to 3.4±0.2logCFU/g. Significantly fewer salmonellae transferred from the blade (3.4±0.4 log CFU, P≤0.05) than from the back and bottom plates (4.7±0.3 log CFU) or the whole manual slicer (5.2±0.2 log CFU) to the 20 uninoculated tomatoes. However, the blade was the primary contributor to Salmonella transfer for the electric slicer. Post-contamination hold time, processing temperature and tomato slice thickness did not significantly impact (P>0.05) the Salmonella transfer rate (parameter B) or the overall percentage of cells transferred. A significantly lower (P≤0.05) transfer rate (-0.028±0.002) was observed for wet as compared to dry tomatoes (-0.051±0.002), with a significantly higher (P≤0.05) percentage (12.2±2.4%) of Salmonella transferred to wet as opposed to dry tomatoes (1.1±0.5%). Tomato variety also impacted Salmonella transfer with significantly lower (P≤0.05) transfer rates and Salmonella transfer percentages seen for Rebelski and Bigdena than Torero. These findings will provide practical guidelines for the fresh-cut tomato industry and will also be useful in developing science-based transfer models for risk assessments. Copyright © 2016 Elsevier B.V. All rights reserved.

Fitting C 2 Continuous Parametric Surfaces to Frontiers Delimiting Physiologic Structures

PubMed Central

Bayer, Jason D.

2014-01-01

We present a technique to fit C 2 continuous parametric surfaces to scattered geometric data points forming frontiers delimiting physiologic structures in segmented images. Such mathematical representation is interesting because it facilitates a large number of operations in modeling. While the fitting of C 2 continuous parametric curves to scattered geometric data points is quite trivial, the fitting of C 2 continuous parametric surfaces is not. The difficulty comes from the fact that each scattered data point should be assigned a unique parametric coordinate, and the fit is quite sensitive to their distribution on the parametric plane. We present a new approach where a polygonal (quadrilateral or triangular) surface is extracted from the segmented image. This surface is subsequently projected onto a parametric plane in a manner to ensure a one-to-one mapping. The resulting polygonal mesh is then regularized for area and edge length. Finally, from this point, surface fitting is relatively trivial. The novelty of our approach lies in the regularization of the polygonal mesh. Process performance is assessed with the reconstruction of a geometric model of mouse heart ventricles from a computerized tomography scan. Our results show an excellent reproduction of the geometric data with surfaces that are C 2 continuous. PMID:24782911

Slicing, sampling, and distance-dependent effects affect network measures in simulated cortical circuit structures.

PubMed

Miner, Daniel C; Triesch, Jochen

2014-01-01

The neuroanatomical connectivity of cortical circuits is believed to follow certain rules, the exact origins of which are still poorly understood. In particular, numerous nonrandom features, such as common neighbor clustering, overrepresentation of reciprocal connectivity, and overrepresentation of certain triadic graph motifs have been experimentally observed in cortical slice data. Some of these data, particularly regarding bidirectional connectivity are seemingly contradictory, and the reasons for this are unclear. Here we present a simple static geometric network model with distance-dependent connectivity on a realistic scale that naturally gives rise to certain elements of these observed behaviors, and may provide plausible explanations for some of the conflicting findings. Specifically, investigation of the model shows that experimentally measured nonrandom effects, especially bidirectional connectivity, may depend sensitively on experimental parameters such as slice thickness and sampling area, suggesting potential explanations for the seemingly conflicting experimental results.

Slicing, sampling, and distance-dependent effects affect network measures in simulated cortical circuit structures

PubMed Central

Miner, Daniel C.; Triesch, Jochen

2014-01-01

The neuroanatomical connectivity of cortical circuits is believed to follow certain rules, the exact origins of which are still poorly understood. In particular, numerous nonrandom features, such as common neighbor clustering, overrepresentation of reciprocal connectivity, and overrepresentation of certain triadic graph motifs have been experimentally observed in cortical slice data. Some of these data, particularly regarding bidirectional connectivity are seemingly contradictory, and the reasons for this are unclear. Here we present a simple static geometric network model with distance-dependent connectivity on a realistic scale that naturally gives rise to certain elements of these observed behaviors, and may provide plausible explanations for some of the conflicting findings. Specifically, investigation of the model shows that experimentally measured nonrandom effects, especially bidirectional connectivity, may depend sensitively on experimental parameters such as slice thickness and sampling area, suggesting potential explanations for the seemingly conflicting experimental results. PMID:25414647

Thin-slice vision: inference of confidence measure from perceptual video quality

NASA Astrophysics Data System (ADS)

Hameed, Abdul; Balas, Benjamin; Dai, Rui

2016-11-01

There has been considerable research on thin-slice judgments, but no study has demonstrated the predictive validity of confidence measures when assessors watch videos acquired from communication systems, in which the perceptual quality of videos could be degraded by limited bandwidth and unreliable network conditions. This paper studies the relationship between high-level thin-slice judgments of human behavior and factors that contribute to perceptual video quality. Based on a large number of subjective test results, it has been found that the confidence of a single individual present in all the videos, called speaker's confidence (SC), could be predicted by a list of features that contribute to perceptual video quality. Two prediction models, one based on artificial neural network and the other based on a decision tree, were built to predict SC. Experimental results have shown that both prediction models can result in high correlation measures.

Directional Multi-scale Modeling of High-Resolution Computed Tomography (HRCT) Lung Images for Diffuse Lung Disease Classification

NASA Astrophysics Data System (ADS)

Vo, Kiet T.; Sowmya, Arcot

A directional multi-scale modeling scheme based on wavelet and contourlet transforms is employed to describe HRCT lung image textures for classifying four diffuse lung disease patterns: normal, emphysema, ground glass opacity (GGO) and honey-combing. Generalized Gaussian density parameters are used to represent the detail sub-band features obtained by wavelet and contourlet transforms. In addition, support vector machines (SVMs) with excellent performance in a variety of pattern classification problems are used as classifier. The method is tested on a collection of 89 slices from 38 patients, each slice of size 512x512, 16 bits/pixel in DICOM format. The dataset contains 70,000 ROIs of those slices marked by experienced radiologists. We employ this technique at different wavelet and contourlet transform scales for diffuse lung disease classification. The technique presented here has best overall sensitivity 93.40% and specificity 98.40%.

Multi-parametric variational data assimilation for hydrological forecasting

NASA Astrophysics Data System (ADS)

Alvarado-Montero, R.; Schwanenberg, D.; Krahe, P.; Helmke, P.; Klein, B.

2017-12-01

Ensemble forecasting is increasingly applied in flow forecasting systems to provide users with a better understanding of forecast uncertainty and consequently to take better-informed decisions. A common practice in probabilistic streamflow forecasting is to force deterministic hydrological model with an ensemble of numerical weather predictions. This approach aims at the representation of meteorological uncertainty but neglects uncertainty of the hydrological model as well as its initial conditions. Complementary approaches use probabilistic data assimilation techniques to receive a variety of initial states or represent model uncertainty by model pools instead of single deterministic models. This paper introduces a novel approach that extends a variational data assimilation based on Moving Horizon Estimation to enable the assimilation of observations into multi-parametric model pools. It results in a probabilistic estimate of initial model states that takes into account the parametric model uncertainty in the data assimilation. The assimilation technique is applied to the uppermost area of River Main in Germany. We use different parametric pools, each of them with five parameter sets, to assimilate streamflow data, as well as remotely sensed data from the H-SAF project. We assess the impact of the assimilation in the lead time performance of perfect forecasts (i.e. observed data as forcing variables) as well as deterministic and probabilistic forecasts from ECMWF. The multi-parametric assimilation shows an improvement of up to 23% for CRPS performance and approximately 20% in Brier Skill Scores with respect to the deterministic approach. It also improves the skill of the forecast in terms of rank histogram and produces a narrower ensemble spread.

Self-tuning bistable parametric feedback oscillator: Near-optimal amplitude maximization without model information

NASA Astrophysics Data System (ADS)

Braun, David J.; Sutas, Andrius; Vijayakumar, Sethu

2017-01-01

Theory predicts that parametrically excited oscillators, tuned to operate under resonant condition, are capable of large-amplitude oscillation useful in diverse applications, such as signal amplification, communication, and analog computation. However, due to amplitude saturation caused by nonlinearity, lack of robustness to model uncertainty, and limited sensitivity to parameter modulation, these oscillators require fine-tuning and strong modulation to generate robust large-amplitude oscillation. Here we present a principle of self-tuning parametric feedback excitation that alleviates the above-mentioned limitations. This is achieved using a minimalistic control implementation that performs (i) self-tuning (slow parameter adaptation) and (ii) feedback pumping (fast parameter modulation), without sophisticated signal processing past observations. The proposed approach provides near-optimal amplitude maximization without requiring model-based control computation, previously perceived inevitable to implement optimal control principles in practical application. Experimental implementation of the theory shows that the oscillator self-tunes itself near to the onset of dynamic bifurcation to achieve extreme sensitivity to small resonant parametric perturbations. As a result, it achieves large-amplitude oscillations by capitalizing on the effect of nonlinearity, despite substantial model uncertainties and strong unforeseen external perturbations. We envision the present finding to provide an effective and robust approach to parametric excitation when it comes to real-world application.

Influence of stochastic sea ice parametrization on climate and the role of atmosphere–sea ice–ocean interaction

PubMed Central

Juricke, Stephan; Jung, Thomas

2014-01-01

The influence of a stochastic sea ice strength parametrization on the mean climate is investigated in a coupled atmosphere–sea ice–ocean model. The results are compared with an uncoupled simulation with a prescribed atmosphere. It is found that the stochastic sea ice parametrization causes an effective weakening of the sea ice. In the uncoupled model this leads to an Arctic sea ice volume increase of about 10–20% after an accumulation period of approximately 20–30 years. In the coupled model, no such increase is found. Rather, the stochastic perturbations lead to a spatial redistribution of the Arctic sea ice thickness field. A mechanism involving a slightly negative atmospheric feedback is proposed that can explain the different responses in the coupled and uncoupled system. Changes in integrated Antarctic sea ice quantities caused by the stochastic parametrization are generally small, as memory is lost during the melting season because of an almost complete loss of sea ice. However, stochastic sea ice perturbations affect regional sea ice characteristics in the Southern Hemisphere, both in the uncoupled and coupled model. Remote impacts of the stochastic sea ice parametrization on the mean climate of non-polar regions were found to be small. PMID:24842027

Implicit Priors in Galaxy Cluster Mass and Scaling Relation Determinations

NASA Technical Reports Server (NTRS)

Mantz, A.; Allen, S. W.

2011-01-01

Deriving the total masses of galaxy clusters from observations of the intracluster medium (ICM) generally requires some prior information, in addition to the assumptions of hydrostatic equilibrium and spherical symmetry. Often, this information takes the form of particular parametrized functions used to describe the cluster gas density and temperature profiles. In this paper, we investigate the implicit priors on hydrostatic masses that result from this fully parametric approach, and the implications of such priors for scaling relations formed from those masses. We show that the application of such fully parametric models of the ICM naturally imposes a prior on the slopes of the derived scaling relations, favoring the self-similar model, and argue that this prior may be influential in practice. In contrast, this bias does not exist for techniques which adopt an explicit prior on the form of the mass profile but describe the ICM non-parametrically. Constraints on the slope of the cluster mass-temperature relation in the literature show a separation based the approach employed, with the results from fully parametric ICM modeling clustering nearer the self-similar value. Given that a primary goal of scaling relation analyses is to test the self-similar model, the application of methods subject to strong, implicit priors should be avoided. Alternative methods and best practices are discussed.

Bounded Parametric Model Checking for Elementary Net Systems

NASA Astrophysics Data System (ADS)

Knapik, Michał; Szreter, Maciej; Penczek, Wojciech

Bounded Model Checking (BMC) is an efficient verification method for reactive systems. BMC has been applied so far to verification of properties expressed in (timed) modal logics, but never to their parametric extensions. In this paper we show, for the first time that BMC can be extended to PRTECTL - a parametric extension of the existential version of CTL. To this aim we define a bounded semantics and a translation from PRTECTL to SAT. The implementation of the algorithm for Elementary Net Systems is presented, together with some experimental results.

Parametric nanomechanical amplification at very high frequency.

PubMed

Karabalin, R B; Feng, X L; Roukes, M L

2009-09-01

Parametric resonance and amplification are important in both fundamental physics and technological applications. Here we report very high frequency (VHF) parametric resonators and mechanical-domain amplifiers based on nanoelectromechanical systems (NEMS). Compound mechanical nanostructures patterned by multilayer, top-down nanofabrication are read out by a novel scheme that parametrically modulates longitudinal stress in doubly clamped beam NEMS resonators. Parametric pumping and signal amplification are demonstrated for VHF resonators up to approximately 130 MHz and provide useful enhancement of both resonance signal amplitude and quality factor. We find that Joule heating and reduced thermal conductance in these nanostructures ultimately impose an upper limit to device performance. We develop a theoretical model to account for both the parametric response and nonequilibrium thermal transport in these composite nanostructures. The results closely conform to our experimental observations, elucidate the frequency and threshold-voltage scaling in parametric VHF NEMS resonators and sensors, and establish the ultimate sensitivity limits of this approach.

Multilevel mixed effects parametric survival models using adaptive Gauss-Hermite quadrature with application to recurrent events and individual participant data meta-analysis.

PubMed

Crowther, Michael J; Look, Maxime P; Riley, Richard D

2014-09-28

Multilevel mixed effects survival models are used in the analysis of clustered survival data, such as repeated events, multicenter clinical trials, and individual participant data (IPD) meta-analyses, to investigate heterogeneity in baseline risk and covariate effects. In this paper, we extend parametric frailty models including the exponential, Weibull and Gompertz proportional hazards (PH) models and the log logistic, log normal, and generalized gamma accelerated failure time models to allow any number of normally distributed random effects. Furthermore, we extend the flexible parametric survival model of Royston and Parmar, modeled on the log-cumulative hazard scale using restricted cubic splines, to include random effects while also allowing for non-PH (time-dependent effects). Maximum likelihood is used to estimate the models utilizing adaptive or nonadaptive Gauss-Hermite quadrature. The methods are evaluated through simulation studies representing clinically plausible scenarios of a multicenter trial and IPD meta-analysis, showing good performance of the estimation method. The flexible parametric mixed effects model is illustrated using a dataset of patients with kidney disease and repeated times to infection and an IPD meta-analysis of prognostic factor studies in patients with breast cancer. User-friendly Stata software is provided to implement the methods. Copyright © 2014 John Wiley & Sons, Ltd.

Revisiting dark energy models using differential ages of galaxies

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

Rani, Nisha; Mahajan, Shobhit; Mukherjee, Amitabha

In this work, we use a test based on the differential ages of galaxies for distinguishing the dark energy models. As proposed by Jimenez and Loeb in [1], relative ages of galaxies can be used to put constraints on various cosmological parameters. In the same vein, we reconstruct H {sub 0} {sub dt} / dz and its derivative ( H {sub 0} {sub d} {sup 2} {sup t} / dz {sup 2}) using a model independent technique called non-parametric smoothing . Basically, dt / dz is the change in the age of the object as a function of redshift whichmore » is directly linked with the Hubble parameter. Hence for reconstruction of this quantity, we use the most recent H ( z ) data. Further, we calculate H {sub 0} {sub dt} / dz and its derivative for several models like Phantom, Einstein de Sitter (EdS), ΛCDM, Chevallier-Polarski-Linder (CPL) parametrization, Jassal-Bagla-Padmanabhan (JBP) parametrization and Feng-Shen-Li-Li (FSLL) parametrization. We check the consistency of these models with the results of reconstruction obtained in a model independent way from the data. It is observed that H {sub 0} {sub dt} / dz as a tool is not able to distinguish between the ΛCDM, CPL, JBP and FSLL parametrizations but, as expected, EdS and Phantom models show noticeable deviation from the reconstructed results. Further, the derivative of H {sub 0} {sub dt} / dz for various dark energy models is more sensitive at low redshift. It is found that the FSLL model is not consistent with the reconstructed results, however, the ΛCDM model is in concordance with the 3σ region of the reconstruction at redshift z ≥ 0.3.« less

Parametric reduced models for the nonlinear Schrödinger equation

NASA Astrophysics Data System (ADS)

Harlim, John; Li, Xiantao

2015-05-01

Reduced models for the (defocusing) nonlinear Schrödinger equation are developed. In particular, we develop reduced models that only involve the low-frequency modes given noisy observations of these modes. The ansatz of the reduced parametric models are obtained by employing a rational approximation and a colored-noise approximation, respectively, on the memory terms and the random noise of a generalized Langevin equation that is derived from the standard Mori-Zwanzig formalism. The parameters in the resulting reduced models are inferred from noisy observations with a recently developed ensemble Kalman filter-based parametrization method. The forecasting skill across different temperature regimes are verified by comparing the moments up to order four, a two-time correlation function statistics, and marginal densities of the coarse-grained variables.

Parametric reduced models for the nonlinear Schrödinger equation.

PubMed

Harlim, John; Li, Xiantao

2015-05-01

Reduced models for the (defocusing) nonlinear Schrödinger equation are developed. In particular, we develop reduced models that only involve the low-frequency modes given noisy observations of these modes. The ansatz of the reduced parametric models are obtained by employing a rational approximation and a colored-noise approximation, respectively, on the memory terms and the random noise of a generalized Langevin equation that is derived from the standard Mori-Zwanzig formalism. The parameters in the resulting reduced models are inferred from noisy observations with a recently developed ensemble Kalman filter-based parametrization method. The forecasting skill across different temperature regimes are verified by comparing the moments up to order four, a two-time correlation function statistics, and marginal densities of the coarse-grained variables.

Benchmark dose analysis via nonparametric regression modeling

PubMed Central

Piegorsch, Walter W.; Xiong, Hui; Bhattacharya, Rabi N.; Lin, Lizhen

2013-01-01

Estimation of benchmark doses (BMDs) in quantitative risk assessment traditionally is based upon parametric dose-response modeling. It is a well-known concern, however, that if the chosen parametric model is uncertain and/or misspecified, inaccurate and possibly unsafe low-dose inferences can result. We describe a nonparametric approach for estimating BMDs with quantal-response data based on an isotonic regression method, and also study use of corresponding, nonparametric, bootstrap-based confidence limits for the BMD. We explore the confidence limits’ small-sample properties via a simulation study, and illustrate the calculations with an example from cancer risk assessment. It is seen that this nonparametric approach can provide a useful alternative for BMD estimation when faced with the problem of parametric model uncertainty. PMID:23683057

MRI segmentation by active contours model, 3D reconstruction, and visualization

NASA Astrophysics Data System (ADS)

Lopez-Hernandez, Juan M.; Velasquez-Aguilar, J. Guadalupe

2005-02-01

The advances in 3D data modelling methods are becoming increasingly popular in the areas of biology, chemistry and medical applications. The Nuclear Magnetic Resonance Imaging (NMRI) technique has progressed at a spectacular rate over the past few years, its uses have been spread over many applications throughout the body in both anatomical and functional investigations. In this paper we present the application of Zernike polynomials for 3D mesh model of the head using the contour acquired of cross-sectional slices by active contour model extraction and we propose the visualization with OpenGL 3D Graphics of the 2D-3D (slice-surface) information for the diagnostic aid in medical applications.

Update on Parametric Cost Models for Space Telescopes

NASA Technical Reports Server (NTRS)

Stahl. H. Philip; Henrichs, Todd; Luedtke, Alexander; West, Miranda

2011-01-01

Since the June 2010 Astronomy Conference, an independent review of our cost data base discovered some inaccuracies and inconsistencies which can modify our previously reported results. This paper will review changes to the data base, our confidence in those changes and their effect on various parametric cost models

Bim Automation: Advanced Modeling Generative Process for Complex Structures

NASA Astrophysics Data System (ADS)

Banfi, F.; Fai, S.; Brumana, R.

2017-08-01

The new paradigm of the complexity of modern and historic structures, which are characterised by complex forms, morphological and typological variables, is one of the greatest challenges for building information modelling (BIM). Generation of complex parametric models needs new scientific knowledge concerning new digital technologies. These elements are helpful to store a vast quantity of information during the life cycle of buildings (LCB). The latest developments of parametric applications do not provide advanced tools, resulting in time-consuming work for the generation of models. This paper presents a method capable of processing and creating complex parametric Building Information Models (BIM) with Non-Uniform to NURBS) with multiple levels of details (Mixed and ReverseLoD) based on accurate 3D photogrammetric and laser scanning surveys. Complex 3D elements are converted into parametric BIM software and finite element applications (BIM to FEA) using specific exchange formats and new modelling tools. The proposed approach has been applied to different case studies: the BIM of modern structure for the courtyard of West Block on Parliament Hill in Ottawa (Ontario) and the BIM of Masegra Castel in Sondrio (Italy), encouraging the dissemination and interaction of scientific results without losing information during the generative process.

Elastase-Induced Parenchymal Disruption and Airway Hyper Responsiveness in Mouse Precision Cut Lung Slices: Toward an Ex vivo COPD Model.

PubMed

Van Dijk, Eline M; Culha, Sule; Menzen, Mark H; Bidan, Cécile M; Gosens, Reinoud

2016-01-01

Background: COPD is a progressive lung disease characterized by emphysema and enhanced bronchoconstriction. Current treatments focused on bronchodilation can delay disease progression to some extent, but recovery or normalization of loss of lung function is impossible. Therefore, novel therapeutic targets are needed. The importance of the parenchyma in airway narrowing is increasingly recognized. In COPD, the parenchyma and extracellular matrix are altered, possibly affecting airway mechanics and enhancing bronchoconstriction. Our aim was to set up a comprehensive ex vivo Precision Cut Lung Slice (PCLS) model with a pathophysiology resembling that of COPD and integrate multiple readouts in order to study the relationship between parenchyma, airway functionality, and lung repair processes. Methods: Lungs of C57Bl/6J mice were sliced and treated ex vivo with elastase (2.5 μg/ml) or H 2 O 2 (200 μM) for 16 h. Following treatment, parenchymal structure, airway narrowing, and gene expression levels of alveolar Type I and II cell repair were assessed. Results: Following elastase, but not H 2 O 2 treatment, slices showed a significant increase in mean linear intercept (Lmi), reflective of emphysema. Only elastase-treated slices showed disorganization of elastin and collagen fibers. In addition, elastase treatment lowered both alveolar Type I and II marker expression, whereas H 2 O 2 stimulation lowered alveolar Type I marker expression only. Furthermore, elastase-treated slices showed enhanced methacholine-induced airway narrowing as reflected by increased pEC50 (5.87 at basal vs. 6.50 after elastase treatment) and Emax values (47.96 vs. 67.30%), and impaired chloroquine-induced airway opening. The increase in pEC50 correlated with an increase in mean Lmi. Conclusion: Using this model, we show that structural disruption of elastin fibers leads to impaired alveolar repair, disruption of the parenchymal compartment, and altered airway biomechanics, enhancing airway contraction. This finding may have implications for COPD, as the amount of elastin fiber and parenchymal tissue disruption is associated with disease severity. Therefore, we suggest that PCLS can be used to model certain aspects of COPD pathophysiology and that the parenchymal tissue damage observed in COPD contributes to lung function decline by disrupting airway biomechanics. Targeting the parenchymal compartment may therefore be a promising therapeutic target in the treatment of COPD.

Mathematical modeling the cross-contamination of Escherichia coli O157:H7 on the surface of ready-to-eat meat product while slicing

USDA-ARS?s Scientific Manuscript database

Microbial cross-contamination either at home or production site is one of the major factors of causing contamination of foods and leading to the foodborne illness. The knowledge regarding Escherichia coli O157:H7 surface transfer on ready-to-eat (RTE) deli meat and the slicer used for slicing diffe...

A parametric ribcage geometry model accounting for variations among the adult population.

PubMed

Wang, Yulong; Cao, Libo; Bai, Zhonghao; Reed, Matthew P; Rupp, Jonathan D; Hoff, Carrie N; Hu, Jingwen

2016-09-06

The objective of this study is to develop a parametric ribcage model that can account for morphological variations among the adult population. Ribcage geometries, including 12 pair of ribs, sternum, and thoracic spine, were collected from CT scans of 101 adult subjects through image segmentation, landmark identification (1016 for each subject), symmetry adjustment, and template mesh mapping (26,180 elements for each subject). Generalized procrustes analysis (GPA), principal component analysis (PCA), and regression analysis were used to develop a parametric ribcage model, which can predict nodal locations of the template mesh according to age, sex, height, and body mass index (BMI). Two regression models, a quadratic model for estimating the ribcage size and a linear model for estimating the ribcage shape, were developed. The results showed that the ribcage size was dominated by the height (p=0.000) and age-sex-interaction (p=0.007) and the ribcage shape was significantly affected by the age (p=0.0005), sex (p=0.0002), height (p=0.0064) and BMI (p=0.0000). Along with proper assignment of cortical bone thickness, material properties and failure properties, this parametric ribcage model can directly serve as the mesh of finite element ribcage models for quantifying effects of human characteristics on thoracic injury risks. Copyright © 2016 Elsevier Ltd. All rights reserved.

Nonparametric autocovariance estimation from censored time series by Gaussian imputation.

PubMed

Park, Jung Wook; Genton, Marc G; Ghosh, Sujit K

2009-02-01

One of the most frequently used methods to model the autocovariance function of a second-order stationary time series is to use the parametric framework of autoregressive and moving average models developed by Box and Jenkins. However, such parametric models, though very flexible, may not always be adequate to model autocovariance functions with sharp changes. Furthermore, if the data do not follow the parametric model and are censored at a certain value, the estimation results may not be reliable. We develop a Gaussian imputation method to estimate an autocovariance structure via nonparametric estimation of the autocovariance function in order to address both censoring and incorrect model specification. We demonstrate the effectiveness of the technique in terms of bias and efficiency with simulations under various rates of censoring and underlying models. We describe its application to a time series of silicon concentrations in the Arctic.

Joint analysis of input and parametric uncertainties in watershed water quality modeling: A formal Bayesian approach

NASA Astrophysics Data System (ADS)

Han, Feng; Zheng, Yi

2018-06-01

Significant Input uncertainty is a major source of error in watershed water quality (WWQ) modeling. It remains challenging to address the input uncertainty in a rigorous Bayesian framework. This study develops the Bayesian Analysis of Input and Parametric Uncertainties (BAIPU), an approach for the joint analysis of input and parametric uncertainties through a tight coupling of Markov Chain Monte Carlo (MCMC) analysis and Bayesian Model Averaging (BMA). The formal likelihood function for this approach is derived considering a lag-1 autocorrelated, heteroscedastic, and Skew Exponential Power (SEP) distributed error model. A series of numerical experiments were performed based on a synthetic nitrate pollution case and on a real study case in the Newport Bay Watershed, California. The Soil and Water Assessment Tool (SWAT) and Differential Evolution Adaptive Metropolis (DREAM(ZS)) were used as the representative WWQ model and MCMC algorithm, respectively. The major findings include the following: (1) the BAIPU can be implemented and used to appropriately identify the uncertain parameters and characterize the predictive uncertainty; (2) the compensation effect between the input and parametric uncertainties can seriously mislead the modeling based management decisions, if the input uncertainty is not explicitly accounted for; (3) the BAIPU accounts for the interaction between the input and parametric uncertainties and therefore provides more accurate calibration and uncertainty results than a sequential analysis of the uncertainties; and (4) the BAIPU quantifies the credibility of different input assumptions on a statistical basis and can be implemented as an effective inverse modeling approach to the joint inference of parameters and inputs.

Comparison of Survival Models for Analyzing Prognostic Factors in Gastric Cancer Patients

PubMed

Habibi, Danial; Rafiei, Mohammad; Chehrei, Ali; Shayan, Zahra; Tafaqodi, Soheil

2018-03-27

Objective: There are a number of models for determining risk factors for survival of patients with gastric cancer. This study was conducted to select the model showing the best fit with available data. Methods: Cox regression and parametric models (Exponential, Weibull, Gompertz, Log normal, Log logistic and Generalized Gamma) were utilized in unadjusted and adjusted forms to detect factors influencing mortality of patients. Comparisons were made with Akaike Information Criterion (AIC) by using STATA 13 and R 3.1.3 softwares. Results: The results of this study indicated that all parametric models outperform the Cox regression model. The Log normal, Log logistic and Generalized Gamma provided the best performance in terms of AIC values (179.2, 179.4 and 181.1, respectively). On unadjusted analysis, the results of the Cox regression and parametric models indicated stage, grade, largest diameter of metastatic nest, largest diameter of LM, number of involved lymph nodes and the largest ratio of metastatic nests to lymph nodes, to be variables influencing the survival of patients with gastric cancer. On adjusted analysis, according to the best model (log normal), grade was found as the significant variable. Conclusion: The results suggested that all parametric models outperform the Cox model. The log normal model provides the best fit and is a good substitute for Cox regression. Creative Commons Attribution License

Efficient model reduction of parametrized systems by matrix discrete empirical interpolation

NASA Astrophysics Data System (ADS)

Negri, Federico; Manzoni, Andrea; Amsallem, David

2015-12-01

In this work, we apply a Matrix version of the so-called Discrete Empirical Interpolation (MDEIM) for the efficient reduction of nonaffine parametrized systems arising from the discretization of linear partial differential equations. Dealing with affinely parametrized operators is crucial in order to enhance the online solution of reduced-order models (ROMs). However, in many cases such an affine decomposition is not readily available, and must be recovered through (often) intrusive procedures, such as the empirical interpolation method (EIM) and its discrete variant DEIM. In this paper we show that MDEIM represents a very efficient approach to deal with complex physical and geometrical parametrizations in a non-intrusive, efficient and purely algebraic way. We propose different strategies to combine MDEIM with a state approximation resulting either from a reduced basis greedy approach or Proper Orthogonal Decomposition. A posteriori error estimates accounting for the MDEIM error are also developed in the case of parametrized elliptic and parabolic equations. Finally, the capability of MDEIM to generate accurate and efficient ROMs is demonstrated on the solution of two computationally-intensive classes of problems occurring in engineering contexts, namely PDE-constrained shape optimization and parametrized coupled problems.

Dynamic 2D self-phase-map Nyquist ghost correction for simultaneous multi-slice echo planar imaging.

PubMed

Yarach, Uten; Tung, Yi-Hang; Setsompop, Kawin; In, Myung-Ho; Chatnuntawech, Itthi; Yakupov, Renat; Godenschweger, Frank; Speck, Oliver

2018-02-09

To develop a reconstruction pipeline that intrinsically accounts for both simultaneous multislice echo planar imaging (SMS-EPI) reconstruction and dynamic slice-specific Nyquist ghosting correction in time-series data. After 1D slice-group average phase correction, the separate polarity (i.e., even and odd echoes) SMS-EPI data were unaliased by slice GeneRalized Autocalibrating Partial Parallel Acquisition. Both the slice-unaliased even and odd echoes were jointly reconstructed using a model-based framework, extended for SMS-EPI reconstruction that estimates a 2D self-phase map, corrects dynamic slice-specific phase errors, and combines data from all coils and echoes to obtain the final images. The percentage ghost-to-signal ratios (%GSRs) and its temporal variations for MB3R y 2 with a field of view/4 shift in a human brain obtained by the proposed dynamic 2D and standard 1D phase corrections were 1.37 ± 0.11 and 2.66 ± 0.16, respectively. Even with a large regularization parameter λ applied in the proposed reconstruction, the smoothing effect in fMRI activation maps was comparable to a very small Gaussian kernel size 1 × 1 × 1 mm 3 . The proposed reconstruction pipeline reduced slice-specific phase errors in SMS-EPI, resulting in reduction of GSR. It is applicable for functional MRI studies because the smoothing effect caused by the regularization parameter selection can be minimal in a blood-oxygen-level-dependent activation map. © 2018 International Society for Magnetic Resonance in Medicine.

Simple Estimation of the Endolymphatic Volume Ratio after Intravenous Administration of a Single-dose of Gadolinium Contrast

PubMed Central

NAGANAWA, Shinji; KANOU, Mai; OHASHI, Toshio; KUNO, Kayao; SONE, Michihiko

2016-01-01

Purpose: To evaluate the feasibility of a simple estimation for the endolymphatic volume ratio (endolymph volume/total lymph volume = %ELvolume) from an area ratio obtained from only one slice (%EL1slice) or from three slices (%EL3slices). The %ELvolume, calculated from a time-consuming measurement on all magnetic resonance (MR) slices, was compared to the %EL1slice and the %EL3slices. Methods: In 40 ears of 20 patients with a clinical suspicion of endolymphatic hydrops, MR imaging was performed 4 hours after intravenous administration of a single dose of gadolinium-based contrast material (IV-SD-GBCM). Using previously reported HYDROPS2-Mi2 MR imaging, the %ELvolume values in the cochlea and the vestibule were measured separately by two observers. The correlations between the %EL1slice or the %EL3slices and the %ELvolume values were evaluated. Results: A strong linear correlation was observed between the %ELvolume and the %EL3slices or the %EL1slice in the cochlea. The Pearson correlation coefficient (r) was 0.968 (3 slices) and 0.965 (1 slice) for observer A, and 0.968 (3 slices) and 0.964 (1 slice) for observer B (P < 0.001, for all). A strong linear correlation was also observed between the %ELvolume and the %EL3slices or the %EL1slice in the vestibule. The Pearson correlation coefficient (r) was 0.980 (3 slices) and 0.953 (1 slice) for observer A, and 0.979 (3 slices) and 0.952 (1 slice) for observer B (P < 0.001, for all). The high intra-class correlation coefficients (0.991–0.997) between the endolymph volume ratios by two observers were observed in both the cochlea and the vestibule for values of the %ELvolume, the %EL3slices and the %EL1slice. Conclusion: The %ELvolume might be easily estimated from the %EL3slices or the %EL1slice. PMID:27001396

Simple Estimation of the Endolymphatic Volume Ratio after Intravenous Administration of a Single-dose of Gadolinium Contrast.

PubMed

Naganawa, Shinji; Kanou, Mai; Ohashi, Toshio; Kuno, Kayao; Sone, Michihiko

2016-10-11

To evaluate the feasibility of a simple estimation for the endolymphatic volume ratio (endolymph volume/total lymph volume = %EL volume ) from an area ratio obtained from only one slice (%EL 1slice ) or from three slices (%EL 3slices ). The %EL volume, calculated from a time-consuming measurement on all magnetic resonance (MR) slices, was compared to the %EL 1slice and the %EL 3slices . In 40 ears of 20 patients with a clinical suspicion of endolymphatic hydrops, MR imaging was performed 4 hours after intravenous administration of a single dose of gadolinium-based contrast material (IV-SD-GBCM). Using previously reported HYDROPS2-Mi2 MR imaging, the %EL volume values in the cochlea and the vestibule were measured separately by two observers. The correlations between the %EL 1slice or the %EL 3slices and the %EL volume values were evaluated. A strong linear correlation was observed between the %EL volume and the %EL 3slices or the %EL 1slice in the cochlea. The Pearson correlation coefficient (r) was 0.968 (3 slices) and 0.965 (1 slice) for observer A, and 0.968 (3 slices) and 0.964 (1 slice) for observer B (P < 0.001, for all). A strong linear correlation was also observed between the %EL volume and the %EL 3slices or the %EL 1slice in the vestibule. The Pearson correlation coefficient (r) was 0.980 (3 slices) and 0.953 (1 slice) for observer A, and 0.979 (3 slices) and 0.952 (1 slice) for observer B (P < 0.001, for all). The high intra-class correlation coefficients (0.991-0.997) between the endolymph volume ratios by two observers were observed in both the cochlea and the vestibule for values of the %EL volume , the %EL 3slices and the %EL 1slice . The %EL volume might be easily estimated from the %EL 3slices or the %EL 1slice .

Parametric study of extended end-plate connection using finite element modeling

NASA Astrophysics Data System (ADS)

Mureşan, Ioana Cristina; Bâlc, Roxana

2017-07-01

End-plate connections with preloaded high strength bolts represent a convenient, fast and accurate solution for beam-to-column joints. The behavior of framework joints build up with this type of connection are sensitive dependent on geometrical and material characteristics of the elements connected. This paper presents results of parametric analyses on the behavior of a bolted extended end-plate connection using finite element modeling program Abaqus. This connection was experimentally tested in the Laboratory of Faculty of Civil Engineering from Cluj-Napoca and the results are briefly reviewed in this paper. The numerical model of the studied connection was described in detail in [1] and provides data for this parametric study.

Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir bimolecular adsorption model

NASA Astrophysics Data System (ADS)

Feng, Jinchao; Lansford, Joshua; Mironenko, Alexander; Pourkargar, Davood Babaei; Vlachos, Dionisios G.; Katsoulakis, Markos A.

2018-03-01

We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data). The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.

Bayesian non-parametric inference for stochastic epidemic models using Gaussian Processes.

PubMed

Xu, Xiaoguang; Kypraios, Theodore; O'Neill, Philip D

2016-10-01

This paper considers novel Bayesian non-parametric methods for stochastic epidemic models. Many standard modeling and data analysis methods use underlying assumptions (e.g. concerning the rate at which new cases of disease will occur) which are rarely challenged or tested in practice. To relax these assumptions, we develop a Bayesian non-parametric approach using Gaussian Processes, specifically to estimate the infection process. The methods are illustrated with both simulated and real data sets, the former illustrating that the methods can recover the true infection process quite well in practice, and the latter illustrating that the methods can be successfully applied in different settings. © The Author 2016. Published by Oxford University Press.

Parametric Study of a YAV-8B Harrier in Ground Effect Using Time-Dependent Navier-Stokes Computations

NASA Technical Reports Server (NTRS)

Shishir, Pandya; Chaderjian, Neal; Ahmad, Jsaim; Kwak, Dochan (Technical Monitor)

2001-01-01

Flow simulations using the time-dependent Navier-Stokes equations remain a challenge for several reasons. Principal among them are the difficulty to accurately model complex flows, and the time needed to perform the computations. A parametric study of such complex problems is not considered practical due to the large cost associated with computing many time-dependent solutions. The computation time for each solution must be reduced in order to make a parametric study possible. With successful reduction of computation time, the issue of accuracy, and appropriateness of turbulence models will become more tractable.

Optical properties of the Einstein-de Sitter-Kasner universe

NASA Astrophysics Data System (ADS)

Landry, Sylvie; Dyer, Charles C.

1997-09-01

Most studies of gravitational lensing and their impact on observations concentrate on lensing structures which are bounded, that is, of some finite size in an otherwise reasonably smooth background universe. In this paper, we consider a model of the universe, the ``cheese slice'' universe, where the lensing is caused by very large scale structures: large slabs of alternating pure vacuum and Friedmann-Lemaı⁁tre-Robertson-Walker (FLRW) dust. The ray tracing problem is solved and shows that only the Kasner regions will introduce a bending in the beam as it propagates. The Kasner slices also introduce anisotropic redshift effects. The optical scalar equations are used as a tool to obtain the cross-sectional area and shape of the beam. All physical properties of a bundle of rays traveling through the cheese slice model are obtained analytically. The only nonanalytical result is the evaluation, in Kasner regions, of the time variable along the beam as a function of the affine parameter. Practical model results are obtained from a computer code. Multislice models are studied and the resulting impact on astronomical observations, which includes the introduction of shear and amplification, is demonstrated.

A generalized Jaynes-Cummings model: The relativistic parametric amplifier and a single trapped ion

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

Ojeda-Guillén, D., E-mail: dojedag@ipn.mx; Mota, R. D.; Granados, V. D.

2016-06-15

We introduce a generalization of the Jaynes-Cummings model and study some of its properties. We obtain the energy spectrum and eigenfunctions of this model by using the tilting transformation and the squeezed number states of the one-dimensional harmonic oscillator. As physical applications, we connect this new model to two important and novelty problems: the relativistic parametric amplifier and the quantum simulation of a single trapped ion.

Parametrization of Drag and Turbulence for Urban Neighbourhoods with Trees

NASA Astrophysics Data System (ADS)

Krayenhoff, E. S.; Santiago, J.-L.; Martilli, A.; Christen, A.; Oke, T. R.

2015-08-01

Urban canopy parametrizations designed to be coupled with mesoscale models must predict the integrated effect of urban obstacles on the flow at each height in the canopy. To assess these neighbourhood-scale effects, results of microscale simulations may be horizontally-averaged. Obstacle-resolving computational fluid dynamics (CFD) simulations of neutrally-stratified flow through canopies of blocks (buildings) with varying distributions and densities of porous media (tree foliage) are conducted, and the spatially-averaged impacts on the flow of these building-tree combinations are assessed. The accuracy with which a one-dimensional (column) model with a one-equation (-) turbulence scheme represents spatially-averaged CFD results is evaluated. Individual physical mechanisms by which trees and buildings affect flow in the column model are evaluated in terms of relative importance. For the treed urban configurations considered, effects of buildings and trees may be considered independently. Building drag coefficients and length scale effects need not be altered due to the presence of tree foliage; therefore, parametrization of spatially-averaged flow through urban neighbourhoods with trees is greatly simplified. The new parametrization includes only source and sink terms significant for the prediction of spatially-averaged flow profiles: momentum drag due to buildings and trees (and the associated wake production of turbulent kinetic energy), modification of length scales by buildings, and enhanced dissipation of turbulent kinetic energy due to the small scale of tree foliage elements. Coefficients for the Santiago and Martilli (Boundary-Layer Meteorol 137: 417-439, 2010) parametrization of building drag coefficients and length scales are revised. Inclusion of foliage terms from the new parametrization in addition to the Santiago and Martilli building terms reduces root-mean-square difference (RMSD) of the column model streamwise velocity component and turbulent kinetic energy relative to the CFD model by 89 % in the canopy and 71 % above the canopy on average for the highest leaf area density scenarios tested: . RMSD values with the new parametrization are less than 20 % of mean layer magnitude for the streamwise velocity component within and above the canopy, and for above-canopy turbulent kinetic energy; RMSD values for within-canopy turbulent kinetic energy are negligible for most scenarios. The foliage-related portion of the new parametrization is required for scenarios with tree foliage of equal or greater height than the buildings, and for scenarios with foliage below roof height for building plan area densities less than approximately 0.25.

Bim and Gis: when Parametric Modeling Meets Geospatial Data

NASA Astrophysics Data System (ADS)

Barazzetti, L.; Banfi, F.

2017-12-01

Geospatial data have a crucial role in several projects related to infrastructures and land management. GIS software are able to perform advanced geospatial analyses, but they lack several instruments and tools for parametric modelling typically available in BIM. At the same time, BIM software designed for buildings have limited tools to handle geospatial data. As things stand at the moment, BIM and GIS could appear as complementary solutions, notwithstanding research work is currently under development to ensure a better level of interoperability, especially at the scale of the building. On the other hand, the transition from the local (building) scale to the infrastructure (where geospatial data cannot be neglected) has already demonstrated that parametric modelling integrated with geoinformation is a powerful tool to simplify and speed up some phases of the design workflow. This paper reviews such mixed approaches with both simulated and real examples, demonstrating that integration is already a reality at specific scales, which are not dominated by "pure" GIS or BIM. The paper will also demonstrate that some traditional operations carried out with GIS software are also available in parametric modelling software for BIM, such as transformation between reference systems, DEM generation, feature extraction, and geospatial queries. A real case study is illustrated and discussed to show the advantage of a combined use of both technologies. BIM and GIS integration can generate greater usage of geospatial data in the AECOO (Architecture, Engineering, Construction, Owner and Operator) industry, as well as new solutions for parametric modelling with additional geoinformation.

Parametric excitation of tire-wheel assemblies by a stiffness non-uniformity

NASA Astrophysics Data System (ADS)

Stutts, D. S.; Krousgrill, C. M.; Soedel, W.

1995-01-01

A simple model of the effect of a concentrated radial stiffness non-uniformity in a passenger car tire is presented. The model treats the tread band of the tire as a rigid ring supported on a viscoelastic foundation. The distributed radial stiffness is lumped into equivalent horizontal (fore-and-aft) and vertical stiffnesses. The concentrated radial stiffness non-uniformity is modeled by treating the tread band as fixed, and the stiffness non-uniformity as rotating around it at the nominal angular velocity of the wheel. Due to loading, the center of mass of the tread band ring model is displaced upward with respect to the wheel spindle and, therefore, the rotating stiffness non-uniformity is alternately compressed and stretched through one complete rotation. This stretching and compressing of the stiffness non-uniformity results in force transmission to the wheel spindle at twice the nominal angular velocity in frequency, and therefore, would excite a given resonance at one-half the nominal angular wheel velocity that a mass unbalance would. The forcing produced by the stiffness non-uniformity is parametric in nature, thus creating the possibility of parametric resonance. The basic theory of the parametric resonance is explained, and a parameter study using derived lumped parameters based on a typical passenger car tire is performed. This study revealed that parametric resonance in passenger car tires, although possible, is unlikely at normal highway speeds as predicted by this model unless the tire is partially deflated.

Parametrically excited oscillation of stay cable and its control in cable-stayed bridges.

PubMed

Sun, Bing-nan; Wang, Zhi-gang; Ko, J M; Ni, Y Q

2003-01-01

This paper presents a nonlinear dynamic model for simulation and analysis of a kind of parametrically excited vibration of stay cable caused by support motion in cable-stayed bridges. The sag, inclination angle of the stay cable are considered in the model, based on which, the oscillation mechanism and dynamic response characteristics of this kind of vibration are analyzed through numerical calculation. It is noted that parametrically excited oscillation of a stay cable with certain sag, inclination angle and initial static tension force may occur in cable-stayed bridges due to deck vibration under the condition that the natural frequency of a cable approaches to about half of the first model frequency of the bridge deck system. A new vibration control system installed on the cable anchorage is proposed as a possible damping system to suppress the cable parametric oscillation. The numerical calculation results showed that with the use of this damping system, the cable oscillation due to the vibration of the deck and/or towers will be considerably reduced.

Changing space and sound: Parametric design and variable acoustics

NASA Astrophysics Data System (ADS)

Norton, Christopher William

This thesis examines the potential for parametric design software to create performance based design using acoustic metrics as the design criteria. A former soundstage at the University of Southern California used by the Thornton School of Music is used as a case study for a multiuse space for orchestral, percussion, master class and recital use. The criteria used for each programmatic use include reverberation time, bass ratio, and the early energy ratios of the clarity index and objective support. Using a panelized ceiling as a design element to vary the parameters of volume, panel orientation and type of absorptive material, the relationships between these parameters and the design criteria are explored. These relationships and subsequently derived equations are applied to Grasshopper parametric modeling software for Rhino 3D (a NURBS modeling software). Using the target reverberation time and bass ratio for each programmatic use as input for the parametric model, the genomic optimization function of Grasshopper - Galapagos - is run to identify the optimum ceiling geometry and material distribution.

Definition of NASTRAN sets by use of parametric geometry

NASA Technical Reports Server (NTRS)

Baughn, Terry V.; Tiv, Mehran

1989-01-01

Many finite element preprocessors describe finite element model geometry with points, lines, surfaces and volumes. One method for describing these basic geometric entities is by use of parametric cubics which are useful for representing complex shapes. The lines, surfaces and volumes may be discretized for follow on finite element analysis. The ability to limit or selectively recover results from the finite element model is extremely important to the analyst. Equally important is the ability to easily apply boundary conditions. Although graphical preprocessors have made these tasks easier, model complexity may not lend itself to easily identify a group of grid points desired for data recovery or application of constraints. A methodology is presented which makes use of the assignment of grid point locations in parametric coordinates. The parametric coordinates provide a convenient ordering of the grid point locations and a method for retrieving the grid point ID's from the parent geometry. The selected grid points may then be used for the generation of the appropriate set and constraint cards.

Modelling present-day basal melt rates for Antarctic ice shelves using a parametrization of buoyant meltwater plumes

NASA Astrophysics Data System (ADS)

Lazeroms, Werner M. J.; Jenkins, Adrian; Hilmar Gudmundsson, G.; van de Wal, Roderik S. W.

2018-01-01

Basal melting below ice shelves is a major factor in mass loss from the Antarctic Ice Sheet, which can contribute significantly to possible future sea-level rise. Therefore, it is important to have an adequate description of the basal melt rates for use in ice-dynamical models. Most current ice models use rather simple parametrizations based on the local balance of heat between ice and ocean. In this work, however, we use a recently derived parametrization of the melt rates based on a buoyant meltwater plume travelling upward beneath an ice shelf. This plume parametrization combines a non-linear ocean temperature sensitivity with an inherent geometry dependence, which is mainly described by the grounding-line depth and the local slope of the ice-shelf base. For the first time, this type of parametrization is evaluated on a two-dimensional grid covering the entire Antarctic continent. In order to apply the essentially one-dimensional parametrization to realistic ice-shelf geometries, we present an algorithm that determines effective values for the grounding-line depth and basal slope in any point beneath an ice shelf. Furthermore, since detailed knowledge of temperatures and circulation patterns in the ice-shelf cavities is sparse or absent, we construct an effective ocean temperature field from observational data with the purpose of matching (area-averaged) melt rates from the model with observed present-day melt rates. Our results qualitatively replicate large-scale observed features in basal melt rates around Antarctica, not only in terms of average values, but also in terms of the spatial pattern, with high melt rates typically occurring near the grounding line. The plume parametrization and the effective temperature field presented here are therefore promising tools for future simulations of the Antarctic Ice Sheet requiring a more realistic oceanic forcing.

Image Quality of 3rd Generation Spiral Cranial Dual-Source CT in Combination with an Advanced Model Iterative Reconstruction Technique: A Prospective Intra-Individual Comparison Study to Standard Sequential Cranial CT Using Identical Radiation Dose

PubMed Central

Wenz, Holger; Maros, Máté E.; Meyer, Mathias; Förster, Alex; Haubenreisser, Holger; Kurth, Stefan; Schoenberg, Stefan O.; Flohr, Thomas; Leidecker, Christianne; Groden, Christoph; Scharf, Johann; Henzler, Thomas

2015-01-01

Objectives To prospectively intra-individually compare image quality of a 3rd generation Dual-Source-CT (DSCT) spiral cranial CT (cCT) to a sequential 4-slice Multi-Slice-CT (MSCT) while maintaining identical intra-individual radiation dose levels. Methods 35 patients, who had a non-contrast enhanced sequential cCT examination on a 4-slice MDCT within the past 12 months, underwent a spiral cCT scan on a 3rd generation DSCT. CTDIvol identical to initial 4-slice MDCT was applied. Data was reconstructed using filtered backward projection (FBP) and 3rd-generation iterative reconstruction (IR) algorithm at 5 different IR strength levels. Two neuroradiologists independently evaluated subjective image quality using a 4-point Likert-scale and objective image quality was assessed in white matter and nucleus caudatus with signal-to-noise ratios (SNR) being subsequently calculated. Results Subjective image quality of all spiral cCT datasets was rated significantly higher compared to the 4-slice MDCT sequential acquisitions (p<0.05). Mean SNR was significantly higher in all spiral compared to sequential cCT datasets with mean SNR improvement of 61.65% (p*Bonferroni0.05<0.0024). Subjective image quality improved with increasing IR levels. Conclusion Combination of 3rd-generation DSCT spiral cCT with an advanced model IR technique significantly improves subjective and objective image quality compared to a standard sequential cCT acquisition acquired at identical dose levels. PMID:26288186

Image Quality of 3rd Generation Spiral Cranial Dual-Source CT in Combination with an Advanced Model Iterative Reconstruction Technique: A Prospective Intra-Individual Comparison Study to Standard Sequential Cranial CT Using Identical Radiation Dose.

PubMed

Wenz, Holger; Maros, Máté E; Meyer, Mathias; Förster, Alex; Haubenreisser, Holger; Kurth, Stefan; Schoenberg, Stefan O; Flohr, Thomas; Leidecker, Christianne; Groden, Christoph; Scharf, Johann; Henzler, Thomas

2015-01-01

To prospectively intra-individually compare image quality of a 3rd generation Dual-Source-CT (DSCT) spiral cranial CT (cCT) to a sequential 4-slice Multi-Slice-CT (MSCT) while maintaining identical intra-individual radiation dose levels. 35 patients, who had a non-contrast enhanced sequential cCT examination on a 4-slice MDCT within the past 12 months, underwent a spiral cCT scan on a 3rd generation DSCT. CTDIvol identical to initial 4-slice MDCT was applied. Data was reconstructed using filtered backward projection (FBP) and 3rd-generation iterative reconstruction (IR) algorithm at 5 different IR strength levels. Two neuroradiologists independently evaluated subjective image quality using a 4-point Likert-scale and objective image quality was assessed in white matter and nucleus caudatus with signal-to-noise ratios (SNR) being subsequently calculated. Subjective image quality of all spiral cCT datasets was rated significantly higher compared to the 4-slice MDCT sequential acquisitions (p<0.05). Mean SNR was significantly higher in all spiral compared to sequential cCT datasets with mean SNR improvement of 61.65% (p*Bonferroni0.05<0.0024). Subjective image quality improved with increasing IR levels. Combination of 3rd-generation DSCT spiral cCT with an advanced model IR technique significantly improves subjective and objective image quality compared to a standard sequential cCT acquisition acquired at identical dose levels.

TEXCAD: Textile Composite Analysis for Design. Version 1.0: User's manual

NASA Technical Reports Server (NTRS)

Naik, Rajiv A.

1994-01-01

The Textile Composite Analysis for Design (TEXCAD) code provides the materials/design engineer with a user-friendly desktop computer (IBM PC compatible or Apple Macintosh) tool for the analysis of a wide variety of fabric reinforced woven and braided composites. It can be used to calculate overall thermal and mechanical properties along with engineering estimates of damage progression and strength. TEXCAD also calculates laminate properties for stacked, oriented fabric constructions. It discretely models the yarn centerline paths within the textile repeating unit cell (RUC) by assuming sinusoidal undulations at yarn cross-over points and uses a yarn discretization scheme (which subdivides each yarn not smaller, piecewise straight yarn slices) together with a 3-D stress averaging procedure to compute overall stiffness properties. In the calculations for strength, it uses a curved beam-on-elastic foundation model for yarn undulating regions together with an incremental approach in which stiffness properties for the failed yarn slices are reduced based on the predicted yarn slice failure mode. Nonlinear shear effects and nonlinear geometric effects can be simulated. Input to TEXCAD consists of: (1) materials parameters like impregnated yarn and resin properties such moduli, Poisson's ratios, coefficients of thermal expansion, nonlinear parameters, axial failure strains and in-plane failure stresses; and (2) fabric parameters like yarn sizes, braid angle, yarn packing density, filament diameter and overall fiber volume fraction. Output consists of overall thermoelastic constants, yarn slice strains/stresses, yarn slice failure history, in-plane stress-strain response and ultimate failure strength. Strength can be computed under the combined action of thermal and mechanical loading (tension, compression and shear).

Effect of acute and repeated restraint stress on glucose oxidation to CO2 in hippocampal and cerebral cortex slices.

PubMed

Torres, I L; Gamaro, G D; Silveira-Cucco, S N; Michalowski, M B; Corrêa, J B; Perry, M L; Dalmaz, C

2001-01-01

It has been suggested that glucocorticoids released during stress might impair neuronal function by decreasing glucose uptake by hippocampal neurons. Previous work has demonstrated that glucose uptake is reduced in hippocampal and cerebral cortex slices 24 h after exposure to acute stress, while no effect was observed after repeated stress. Here, we report the effect of acute and repeated restraint stress on glucose oxidation to CO2 in hippocampal and cerebral cortex slices and on plasma glucose and corticosterone levels. Male adult Wistar rats were exposed to restraint 1 h/day for 50 days in the chronic model. In the acute model there was a single exposure. Immediately or 24 h after stress, the animals were sacrificed and the hippocampus and cerebral cortex were dissected, sliced, and incubated with Krebs buffer, pH 7.4, containing 5 mM glucose and 0.2 microCi D-[U-14C] glucose. CO2 production from glucose was estimated. Trunk blood was also collected, and both corticosterone and glucose were measured. The results showed that corticosterone levels after exposure to acute restraint were increased, but the increase was smaller when the animals were submitted to repeated stress. Blood glucose levels increased after both acute and repeated stress. However, glucose utilization, measured as CO2 production in hippocampal and cerebral cortex slices, was the same in stressed and control groups under conditions of both acute and chronic stress. We conclude that, although stress may induce a decrease in glucose uptake, this effect is not sufficient to affect the energy metabolism of these cells.

An Efficient Non-iterative Bulk Parametrization of Surface Fluxes for Stable Atmospheric Conditions Over Polar Sea-Ice

NASA Astrophysics Data System (ADS)

Gryanik, Vladimir M.; Lüpkes, Christof

2018-02-01

In climate and weather prediction models the near-surface turbulent fluxes of heat and momentum and related transfer coefficients are usually parametrized on the basis of Monin-Obukhov similarity theory (MOST). To avoid iteration, required for the numerical solution of the MOST equations, many models apply parametrizations of the transfer coefficients based on an approach relating these coefficients to the bulk Richardson number Rib. However, the parametrizations that are presently used in most climate models are valid only for weaker stability and larger surface roughnesses than those documented during the Surface Heat Budget of the Arctic Ocean campaign (SHEBA). The latter delivered a well-accepted set of turbulence data in the stable surface layer over polar sea-ice. Using stability functions based on the SHEBA data, we solve the MOST equations applying a new semi-analytic approach that results in transfer coefficients as a function of Rib and roughness lengths for momentum and heat. It is shown that the new coefficients reproduce the coefficients obtained by the numerical iterative method with a good accuracy in the most relevant range of stability and roughness lengths. For small Rib, the new bulk transfer coefficients are similar to the traditional coefficients, but for large Rib they are much smaller than currently used coefficients. Finally, a possible adjustment of the latter and the implementation of the new proposed parametrizations in models are discussed.

Prepositioning emergency supplies under uncertainty: a parametric optimization method

NASA Astrophysics Data System (ADS)

Bai, Xuejie; Gao, Jinwu; Liu, Yankui

2018-07-01

Prepositioning of emergency supplies is an effective method for increasing preparedness for disasters and has received much attention in recent years. In this article, the prepositioning problem is studied by a robust parametric optimization method. The transportation cost, supply, demand and capacity are unknown prior to the extraordinary event, which are represented as fuzzy parameters with variable possibility distributions. The variable possibility distributions are obtained through the credibility critical value reduction method for type-2 fuzzy variables. The prepositioning problem is formulated as a fuzzy value-at-risk model to achieve a minimum total cost incurred in the whole process. The key difficulty in solving the proposed optimization model is to evaluate the quantile of the fuzzy function in the objective and the credibility in the constraints. The objective function and constraints can be turned into their equivalent parametric forms through chance constrained programming under the different confidence levels. Taking advantage of the structural characteristics of the equivalent optimization model, a parameter-based domain decomposition method is developed to divide the original optimization problem into six mixed-integer parametric submodels, which can be solved by standard optimization solvers. Finally, to explore the viability of the developed model and the solution approach, some computational experiments are performed on realistic scale case problems. The computational results reported in the numerical example show the credibility and superiority of the proposed parametric optimization method.

Towards the generation of a parametric foot model using principal component analysis: A pilot study.

PubMed

Scarton, Alessandra; Sawacha, Zimi; Cobelli, Claudio; Li, Xinshan

2016-06-01

There have been many recent developments in patient-specific models with their potential to provide more information on the human pathophysiology and the increase in computational power. However they are not yet successfully applied in a clinical setting. One of the main challenges is the time required for mesh creation, which is difficult to automate. The development of parametric models by means of the Principle Component Analysis (PCA) represents an appealing solution. In this study PCA has been applied to the feet of a small cohort of diabetic and healthy subjects, in order to evaluate the possibility of developing parametric foot models, and to use them to identify variations and similarities between the two populations. Both the skin and the first metatarsal bones have been examined. Besides the reduced sample of subjects considered in the analysis, results demonstrated that the method adopted herein constitutes a first step towards the realization of a parametric foot models for biomechanical analysis. Furthermore the study showed that the methodology can successfully describe features in the foot, and evaluate differences in the shape of healthy and diabetic subjects. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

ACCELERATING MR PARAMETER MAPPING USING SPARSITY-PROMOTING REGULARIZATION IN PARAMETRIC DIMENSION

PubMed Central

Velikina, Julia V.; Alexander, Andrew L.; Samsonov, Alexey

2013-01-01

MR parameter mapping requires sampling along additional (parametric) dimension, which often limits its clinical appeal due to a several-fold increase in scan times compared to conventional anatomic imaging. Data undersampling combined with parallel imaging is an attractive way to reduce scan time in such applications. However, inherent SNR penalties of parallel MRI due to noise amplification often limit its utility even at moderate acceleration factors, requiring regularization by prior knowledge. In this work, we propose a novel regularization strategy, which utilizes smoothness of signal evolution in the parametric dimension within compressed sensing framework (p-CS) to provide accurate and precise estimation of parametric maps from undersampled data. The performance of the method was demonstrated with variable flip angle T1 mapping and compared favorably to two representative reconstruction approaches, image space-based total variation regularization and an analytical model-based reconstruction. The proposed p-CS regularization was found to provide efficient suppression of noise amplification and preservation of parameter mapping accuracy without explicit utilization of analytical signal models. The developed method may facilitate acceleration of quantitative MRI techniques that are not suitable to model-based reconstruction because of complex signal models or when signal deviations from the expected analytical model exist. PMID:23213053

A physiology-based parametric imaging method for FDG-PET data

NASA Astrophysics Data System (ADS)

Scussolini, Mara; Garbarino, Sara; Sambuceti, Gianmario; Caviglia, Giacomo; Piana, Michele

2017-12-01

Parametric imaging is a compartmental approach that processes nuclear imaging data to estimate the spatial distribution of the kinetic parameters governing tracer flow. The present paper proposes a novel and efficient computational method for parametric imaging which is potentially applicable to several compartmental models of diverse complexity and which is effective in the determination of the parametric maps of all kinetic coefficients. We consider applications to [18 F]-fluorodeoxyglucose positron emission tomography (FDG-PET) data and analyze the two-compartment catenary model describing the standard FDG metabolization by an homogeneous tissue and the three-compartment non-catenary model representing the renal physiology. We show uniqueness theorems for both models. The proposed imaging method starts from the reconstructed FDG-PET images of tracer concentration and preliminarily applies image processing algorithms for noise reduction and image segmentation. The optimization procedure solves pixel-wise the non-linear inverse problem of determining the kinetic parameters from dynamic concentration data through a regularized Gauss-Newton iterative algorithm. The reliability of the method is validated against synthetic data, for the two-compartment system, and experimental real data of murine models, for the renal three-compartment system.

A parametric model order reduction technique for poroelastic finite element models.

PubMed

Lappano, Ettore; Polanz, Markus; Desmet, Wim; Mundo, Domenico

2017-10-01

This research presents a parametric model order reduction approach for vibro-acoustic problems in the frequency domain of systems containing poroelastic materials (PEM). The method is applied to the Finite Element (FE) discretization of the weak u-p integral formulation based on the Biot-Allard theory and makes use of reduced basis (RB) methods typically employed for parametric problems. The parametric reduction is obtained rewriting the Biot-Allard FE equations for poroelastic materials using an affine representation of the frequency (therefore allowing for RB methods) and projecting the frequency-dependent PEM system on a global reduced order basis generated with the proper orthogonal decomposition instead of standard modal approaches. This has proven to be better suited to describe the nonlinear frequency dependence and the strong coupling introduced by damping. The methodology presented is tested on two three-dimensional systems: in the first experiment, the surface impedance of a PEM layer sample is calculated and compared with results of the literature; in the second, the reduced order model of a multilayer system coupled to an air cavity is assessed and the results are compared to those of the reference FE model.

A Hybrid Wind-Farm Parametrization for Mesoscale and Climate Models

NASA Astrophysics Data System (ADS)

Pan, Yang; Archer, Cristina L.

2018-04-01

To better understand the potential impact of wind farms on weather and climate at the regional to global scales, a new hybrid wind-farm parametrization is proposed for mesoscale and climate models. The proposed parametrization is a hybrid model because it is not based on physical processes or conservation laws, but on the multiple linear regression of the results of large-eddy simulations (LES) with the geometric properties of the wind-farm layout (e.g., the blockage ratio and blockage distance). The innovative aspect is that each wind turbine is treated individually based on its position in the farm and on the wind direction by predicting the velocity upstream of each turbine. The turbine-induced forces and added turbulence kinetic energy (TKE) are first derived analytically and then implemented in the Weather Research and Forecasting model. Idealized simulations of the offshore Lillgrund wind farm are conducted. The wind-speed deficit and TKE predicted with the hybrid model are in excellent agreement with those from the LES results, while the wind-power production estimated with the hybrid model is within 10% of that observed. Three additional wind farms with larger inter-turbine spacing than at Lillgrund are also considered, and a similar agreement with LES results is found, proving that the hybrid parametrization works well with any wind farm regardless of the spacing between turbines. These results indicate the wind-turbine position, wind direction, and added TKE are essential in accounting for the wind-farm effects on the surroundings, for which the hybrid wind-farm parametrization is a promising tool.

Robust outer synchronization between two nonlinear complex networks with parametric disturbances and mixed time-varying delays

NASA Astrophysics Data System (ADS)

Zhang, Chuan; Wang, Xingyuan; Luo, Chao; Li, Junqiu; Wang, Chunpeng

2018-03-01

In this paper, we focus on the robust outer synchronization problem between two nonlinear complex networks with parametric disturbances and mixed time-varying delays. Firstly, a general complex network model is proposed. Besides the nonlinear couplings, the network model in this paper can possess parametric disturbances, internal time-varying delay, discrete time-varying delay and distributed time-varying delay. Then, according to the robust control strategy, linear matrix inequality and Lyapunov stability theory, several outer synchronization protocols are strictly derived. Simple linear matrix controllers are designed to driver the response network synchronize to the drive network. Additionally, our results can be applied on the complex networks without parametric disturbances. Finally, by utilizing the delayed Lorenz chaotic system as the dynamics of all nodes, simulation examples are given to demonstrate the effectiveness of our theoretical results.

Mass transfer characteristics of bisporus mushroom ( Agaricus bisporus) slices during convective hot air drying

NASA Astrophysics Data System (ADS)

Ghanbarian, Davoud; Baraani Dastjerdi, Mojtaba; Torki-Harchegani, Mehdi

2016-05-01

An accurate understanding of moisture transfer parameters, including moisture diffusivity and moisture transfer coefficient, is essential for efficient mass transfer analysis and to design new dryers or improve existing drying equipments. The main objective of the present study was to carry out an experimental and theoretical investigation of mushroom slices drying and determine the mass transfer characteristics of the samples dried under different conditions. The mushroom slices with two thicknesses of 3 and 5 mm were dried at air temperatures of 40, 50 and 60 °C and air flow rates of 1 and 1.5 m s-1. The Dincer and Dost model was used to determine the moisture transfer parameters and predict the drying curves. It was observed that the entire drying process took place in the falling drying rate period. The obtained lag factor and Biot number indicated that the moisture transfer in the samples was controlled by both internal and external resistance. The effective moisture diffusivity and the moisture transfer coefficient increased with increasing air temperature, air flow rate and samples thickness and varied in the ranges of 6.5175 × 10-10 to 1.6726 × 10-9 m2 s-1 and 2.7715 × 10-7 to 3.5512 × 10-7 m s-1, respectively. The validation of the Dincer and Dost model indicated a good capability of the model to describe the drying curves of the mushroom slices.

3D prostate histology image reconstruction: Quantifying the impact of tissue deformation and histology section location

PubMed Central

Gibson, Eli; Gaed, Mena; Gómez, José A.; Moussa, Madeleine; Pautler, Stephen; Chin, Joseph L.; Crukley, Cathie; Bauman, Glenn S.; Fenster, Aaron; Ward, Aaron D.

2013-01-01

Background: Guidelines for localizing prostate cancer on imaging are ideally informed by registered post-prostatectomy histology. 3D histology reconstruction methods can support this by reintroducing 3D spatial information lost during histology processing. The need to register small, high-grade foci drives a need for high accuracy. Accurate 3D reconstruction method design is impacted by the answers to the following central questions of this work. (1) How does prostate tissue deform during histology processing? (2) What spatial misalignment of the tissue sections is induced by microtome cutting? (3) How does the choice of reconstruction model affect histology reconstruction accuracy? Materials and Methods: Histology, paraffin block face and magnetic resonance images were acquired for 18 whole mid-gland tissue slices from six prostates. 7-15 homologous landmarks were identified on each image. Tissue deformation due to histology processing was characterized using the target registration error (TRE) after landmark-based registration under four deformation models (rigid, similarity, affine and thin-plate-spline [TPS]). The misalignment of histology sections from the front faces of tissue slices was quantified using manually identified landmarks. The impact of reconstruction models on the TRE after landmark-based reconstruction was measured under eight reconstruction models comprising one of four deformation models with and without constraining histology images to the tissue slice front faces. Results: Isotropic scaling improved the mean TRE by 0.8-1.0 mm (all results reported as 95% confidence intervals), while skew or TPS deformation improved the mean TRE by <0.1 mm. The mean misalignment was 1.1-1.9° (angle) and 0.9-1.3 mm (depth). Using isotropic scaling, the front face constraint raised the mean TRE by 0.6-0.8 mm. Conclusions: For sub-millimeter accuracy, 3D reconstruction models should not constrain histology images to the tissue slice front faces and should be flexible enough to model isotropic scaling. PMID:24392245

Cone beam computed tomography of plastinated hearts for instruction of radiological anatomy.

PubMed

Chang, Chih-Wei; Atkinson, Gregory; Gandhi, Niket; Farrell, Michael L; Labrash, Steven; Smith, Alice B; Norton, Neil S; Matsui, Takashi; Lozanoff, Scott

2016-09-01

Radiological anatomy education is an important aspect of the medical curriculum. The purpose of this study was to establish and demonstrate the use of plastinated anatomical specimens, specifically human hearts, for use in radiological anatomy education. Four human hearts were processed with routine plastination procedures at room temperature. Specimens were subjected to cone beam computed tomography and a graphics program (ER3D) was applied to generate 3D cardiac models. A comparison was conducted between plastinated hearts and their corresponding computer models based on a list of morphological cardiac features commonly studied in the gross anatomy laboratory. Results showed significant correspondence between plastinations and CBCT-generated 3D models (98 %; p < .01) for external structures and 100 % for internal cardiac features, while 85 % correspondence was achieved between plastinations and 2D CBCT slices. Complete correspondence (100 %) was achieved between key observations on the plastinations and internal radiological findings typically required of medical student. All pathologic features seen on the plastinated hearts were also visualized internally with the CBCT-generated models and 2D slices. These results suggest that CBCT-derived slices and models can be successfully generated from plastinated material and provide accurate representations for radiological anatomy education.

Parametric Modeling as a Technology of Rapid Prototyping in Light Industry

NASA Astrophysics Data System (ADS)

Tomilov, I. N.; Grudinin, S. N.; Frolovsky, V. D.; Alexandrov, A. A.

2016-04-01

The paper deals with the parametric modeling method of virtual mannequins for the purposes of design automation in clothing industry. The described approach includes the steps of generation of the basic model on the ground of the initial one (obtained in 3D-scanning process), its parameterization and deformation. The complex surfaces are presented by the wireframe model. The modeling results are evaluated with the set of similarity factors. Deformed models are compared with their virtual prototypes. The results of modeling are estimated by the standard deviation factor.

Investigation of drying kinetics of tomato slices dried by using a closed loop heat pump dryer

NASA Astrophysics Data System (ADS)

Coşkun, Salih; Doymaz, İbrahim; Tunçkal, Cüneyt; Erdoğan, Seçil

2017-06-01

In this study, tomato slices were dried at three different drying air temperatures (35, 40 and 45 °C) and at 1 m/s air velocities by using a closed loop heat pump dryer (HPD). To explain the drying characteristics of tomato slices, ten thin-layer drying models were applied. The drying of tomato slices at each temperature occurred in falling-rate period; no constant-rate period of drying was observed. The drying rate was significantly influenced by drying temperature. The effective moisture diffusivity varied between 8.28 × 10-11 and 1.41 × 10-10 m2/s, the activation energy was found to be 43.12 kJ/mol. Besides, at the end of drying process, the highest mean specific moisture extraction ratio and coefficient of performance of HPD system were obtained as 0.324 kg/kWh and 2.71, respectively, at the highest drying air temperature (45 °C).

Visual Literacy and the Integration of Parametric Modeling in the Problem-Based Curriculum

ERIC Educational Resources Information Center

Assenmacher, Matthew Benedict

2013-01-01

This quasi-experimental study investigated the application of visual literacy skills in the form of parametric modeling software in relation to traditional forms of sketching. The study included two groups of high school technical design students. The control and experimental groups involved in the study consisted of two randomly selected groups…

Multivariable Parametric Cost Model for Ground Optical Telescope Assembly

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes; Reese, Gayle; Byberg, Alicia

2005-01-01

A parametric cost model for ground-based telescopes is developed using multivariable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction-limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature are examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e., multi-telescope phased-array systems). Additionally, single variable models Based on aperture diameter are derived.

In vitro determination of biomechanical properties of human articular cartilage in osteoarthritis using multi-parametric MRI

NASA Astrophysics Data System (ADS)

Juras, Vladimir; Bittsansky, Michal; Majdisova, Zuzana; Szomolanyi, Pavol; Sulzbacher, Irene; Gäbler, Stefan; Stampfl, Jürgen; Schüller, Georg; Trattnig, Siegfried

2009-03-01

The objective of this study was to evaluate the correlations between MR parameters and the biomechanical properties of naturally degenerated human articular cartilage. Human cartilage explants from the femoral condyles of patients who underwent total knee replacement were evaluated on a micro-imaging system at 3 T. To quantify glycosaminoglycan (GAG) content, delayed gadolinium-enhanced MRI of the cartilage (dGEMRIC) was used. T2 maps were created by using multi-echo, multi-slice spin echo sequences with six echoes: 15, 30, 45, 60, 75, and 90 ms. Data for apparent diffusion constant (ADC) maps were obtained from pulsed gradient spin echo (PGSE) sequences with five b-values: 10.472, 220.0, 627.0, 452.8, 724.5, and 957.7. MR parameters were correlated with mechanical parameters (instantaneous ( I) and equilibrium ( Eq) modulus and relaxation time ( τ)), and the OA stage of each cartilage specimen was determined by histological evaluation of hematoxylin-eosin stained slices. For some parameters, a high correlation was found: the correlation of T1Gd vs Eq ( r = 0.8095), T1Gd vs I/ Eq ( r = -0.8441) and T1Gd vs τ ( r = 0.8469). The correlation of T2 and ADC with selected biomechanical parameters was not statistically significant. In conclusion, GAG content measured by dGEMRIC is highly related to the selected biomechanical properties of naturally degenerated articular cartilage. In contrast, T2 and ADC were unable to estimate these properties. The results of the study imply that some MR parameters can non-invasively predict the biomechanical properties of degenerated articular cartilage.

Stochastic Modelling, Analysis, and Simulations of the Solar Cycle Dynamic Process

NASA Astrophysics Data System (ADS)

Turner, Douglas C.; Ladde, Gangaram S.

2018-03-01

Analytical solutions, discretization schemes and simulation results are presented for the time delay deterministic differential equation model of the solar dynamo presented by Wilmot-Smith et al. In addition, this model is extended under stochastic Gaussian white noise parametric fluctuations. The introduction of stochastic fluctuations incorporates variables affecting the dynamo process in the solar interior, estimation error of parameters, and uncertainty of the α-effect mechanism. Simulation results are presented and analyzed to exhibit the effects of stochastic parametric volatility-dependent perturbations. The results generalize and extend the work of Hazra et al. In fact, some of these results exhibit the oscillatory dynamic behavior generated by the stochastic parametric additative perturbations in the absence of time delay. In addition, the simulation results of the modified stochastic models influence the change in behavior of the very recently developed stochastic model of Hazra et al.

Comparison of radiation parametrizations within the HARMONIE-AROME NWP model

NASA Astrophysics Data System (ADS)

Rontu, Laura; Lindfors, Anders V.

2018-05-01

Downwelling shortwave radiation at the surface (SWDS, global solar radiation flux), given by three different parametrization schemes, was compared to observations in the HARMONIE-AROME numerical weather prediction (NWP) model experiments over Finland in spring 2017. Simulated fluxes agreed well with each other and with the observations in the clear-sky cases. In the cloudy-sky conditions, all schemes tended to underestimate SWDS at the daily level, as compared to the measurements. Large local and temporal differences between the model results and observations were seen, related to the variations and uncertainty of the predicted cloud properties. The results suggest a possibility to benefit from the use of different radiative transfer parametrizations in a NWP model to obtain perturbations for the fine-resolution ensemble prediction systems. In addition, we recommend usage of the global radiation observations for the standard validation of the NWP models.

Latest astronomical constraints on some non-linear parametric dark energy models

NASA Astrophysics Data System (ADS)

Yang, Weiqiang; Pan, Supriya; Paliathanasis, Andronikos

2018-04-01

We consider non-linear redshift-dependent equation of state parameters as dark energy models in a spatially flat Friedmann-Lemaître-Robertson-Walker universe. To depict the expansion history of the universe in such cosmological scenarios, we take into account the large-scale behaviour of such parametric models and fit them using a set of latest observational data with distinct origin that includes cosmic microwave background radiation, Supernove Type Ia, baryon acoustic oscillations, redshift space distortion, weak gravitational lensing, Hubble parameter measurements from cosmic chronometers, and finally the local Hubble constant from Hubble space telescope. The fitting technique avails the publicly available code Cosmological Monte Carlo (COSMOMC), to extract the cosmological information out of these parametric dark energy models. From our analysis, it follows that those models could describe the late time accelerating phase of the universe, while they are distinguished from the Λ-cosmology.

Extended parametric representation of compressor fans and turbines. Volume 2: Part user's manual (parametric turbine)

NASA Technical Reports Server (NTRS)

Coverse, G. L.

1984-01-01

A turbine modeling technique has been developed which will enable the user to obtain consistent and rapid off-design performance from design point input. This technique is applicable to both axial and radial flow turbine with flow sizes ranging from about one pound per second to several hundred pounds per second. The axial flow turbines may or may not include variable geometry in the first stage nozzle. A user-specified option will also permit the calculation of design point cooling flow levels and corresponding changes in efficiency for the axial flow turbines. The modeling technique has been incorporated into a time-sharing program in order to facilitate its use. Because this report contains a description of the input output data, values of typical inputs, and example cases, it is suitable as a user's manual. This report is the second of a three volume set. The titles of the three volumes are as follows: (1) Volume 1 CMGEN USER's Manual (Parametric Compressor Generator); (2) Volume 2 PART USER's Manual (Parametric Turbine); (3) Volume 3 MODFAN USER's Manual (Parametric Modulation Flow Fan).

Numerical approach to describe complementary drying of banana slices osmotically dehydrated

NASA Astrophysics Data System (ADS)

da Silva Júnior, Aluízio Freire; da Silva, Wilton Pereira; de Farias Aires, Juarez Everton; Farias Aires, Kalina Lígia C. A.

2018-02-01

In this work, diffusion model was used to describe the water loss in the complementary drying process of cylindrical slices of banana pretreated by osmotic dehydration. A numerical solution has been proposed for the diffusion equation in cylindrical coordinates, which was obtained through the Finite Volume Method. The diffusion equation was discretized assuming that the effective water diffusivity and the dimensions of a finite cylinder may vary; also considering the boundary condition of the third kind. The banana slices were cut in length of about 1.00 cm and average radius 1.70 cm before osmotic pretreatment, and completed the pretreatment with length of about 0.74 cm and average radius 1.40 cm. The complementary drying was carried out in a kiln with circulation and air exchange. Drying temperatures were the same as used in the osmotic pretreatment (40 to 70 °C). The proposed model described well the water loss, with good statistical indicators for all fits.

The impact of slice-reduced computed tomography on histogram-based densitometry assessment of lung fibrosis in patients with systemic sclerosis

PubMed Central

Maurer, Britta; Suliman, Yossra A.; Morsbach, Fabian; Distler, Oliver; Frauenfelder, Thomas

2018-01-01

Background To evaluate usability of slice-reduced sequential computed tomography (CT) compared to standard high-resolution CT (HRCT) in patients with systemic sclerosis (SSc) for qualitative and quantitative assessment of interstitial lung disease (ILD) with respect to (I) detection of lung parenchymal abnormalities, (II) qualitative and semiquantitative visual assessment, (III) quantification of ILD by histograms and (IV) accuracy for the 20%-cut off discrimination. Methods From standard chest HRCT of 60 SSc patients sequential 9-slice-computed tomography (reduced HRCT) was retrospectively reconstructed. ILD was assessed by visual scoring and quantitative histogram parameters. Results from standard and reduced HRCT were compared using non-parametric tests and analysed by univariate linear regression analyses. Results With respect to the detection of parenchymal abnormalities, only the detection of intrapulmonary bronchiectasis was significantly lower in reduced HRCT compared to standard HRCT (P=0.039). No differences were found comparing visual scores for fibrosis severity and extension from standard and reduced HRCT (P=0.051–0.073). All scores correlated significantly (P<0.001) to histogram parameters derived from both, standard and reduced HRCT. Significant higher values of kurtosis and skewness for reduced HRCT were found (both P<0.001). In contrast to standard HRCT histogram parameters from reduced HRCT showed significant discrimination at cut-off 20% fibrosis (sensitivity 88% kurtosis and skewness; specificity 81% kurtosis and 86% skewness; cut-off kurtosis ≤26, cut-off skewness ≤4; both P<0.001). Conclusions Reduced HRCT is a robust method to assess lung fibrosis in SSc with minimal radiation dose with no difference in scoring assessment of lung fibrosis severity and extension in comparison to standard HRCT. In contrast to standard HRCT histogram parameters derived from the approach of reduced HRCT could discriminate at a threshold of 20% lung fibrosis with high sensitivity and specificity. Hence it might be used to detect early disease progression of lung fibrosis in context of monitoring and treatment of SSc patients. PMID:29850118

Distributing coil elements in three dimensions enhances parallel transmission multiband RF performance: A simulation study in the human brain at 7 Tesla.

PubMed

Wu, Xiaoping; Tian, Jinfeng; Schmitter, Sebastian; Vaughan, J Tommy; Uğurbil, Kâmil; Van de Moortele, Pierre-François

2016-06-01

We explore the advantages of using a double-ring radiofrequency (RF) array and slice orientation to design parallel transmission (pTx) multiband (MB) pulses for simultaneous multislice (SMS) imaging with whole-brain coverage at 7 Tesla (T). A double-ring head array with 16 elements split evenly in two rings stacked in the z-direction was modeled and compared with two single-ring arrays consisting of 8 or 16 elements. The array performance was evaluated by designing band-specific pTx MB pulses with local specific absorption rate (SAR) control. The impact of slice orientations was also investigated. The double-ring array consistently and significantly outperformed the other two single-ring arrays, with peak local SAR reduced by up to 40% at a fixed excitation error of 0.024. For all three arrays, exciting sagittal or coronal slices yielded better RF performance than exciting axial or oblique slices. A double-ring RF array can be used to drastically improve SAR versus excitation fidelity tradeoff for pTx MB pulse design for brain imaging at 7 T; therefore, it is preferable against single-ring RF array designs when pursuing various biomedical applications of pTx SMS imaging. In comparing the stripline arrays, coronal and sagittal slices are more advantageous than axial and oblique slices for pTx MB pulses. Magn Reson Med 75:2464-2472, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Metabolomics of Therapy Response in Preclinical Glioblastoma: A Multi-Slice MRSI-Based Volumetric Analysis for Noninvasive Assessment of Temozolomide Treatment

PubMed Central

Arias-Ramos, Nuria; Ferrer-Font, Laura; Lope-Piedrafita, Silvia; Mocioiu, Victor; Julià-Sapé, Margarida; Pumarola, Martí; Arús, Carles; Candiota, Ana Paula

2017-01-01

Glioblastoma (GBM) is the most common aggressive primary brain tumor in adults, with a short survival time even after aggressive therapy. Non-invasive surrogate biomarkers of therapy response may be relevant for improving patient survival. Previous work produced such biomarkers in preclinical GBM using semi-supervised source extraction and single-slice Magnetic Resonance Spectroscopic Imaging (MRSI). Nevertheless, GBMs are heterogeneous and single-slice studies could prevent obtaining relevant information. The purpose of this work was to evaluate whether a multi-slice MRSI approach, acquiring consecutive grids across the tumor, is feasible for preclinical models and may produce additional insight into therapy response. Nosological images were analyzed pixel-by-pixel and a relative responding volume, the Tumor Responding Index (TRI), was defined to quantify response. Heterogeneous response levels were observed and treated animals were ascribed to three arbitrary predefined groups: high response (HR, n = 2), TRI = 68.2 ± 2.8%, intermediate response (IR, n = 6), TRI = 41.1 ± 4.2% and low response (LR, n = 2), TRI = 13.4 ± 14.3%, producing therapy response categorization which had not been fully registered in single-slice studies. Results agreed with the multi-slice approach being feasible and producing an inverse correlation between TRI and Ki67 immunostaining. Additionally, ca. 7-day oscillations of TRI were observed, suggesting that host immune system activation in response to treatment could contribute to the responding patterns detected. PMID:28524099

Parametric Sensitivity Analysis of Oscillatory Delay Systems with an Application to Gene Regulation.

PubMed

Ingalls, Brian; Mincheva, Maya; Roussel, Marc R

2017-07-01

A parametric sensitivity analysis for periodic solutions of delay-differential equations is developed. Because phase shifts cause the sensitivity coefficients of a periodic orbit to diverge, we focus on sensitivities of the extrema, from which amplitude sensitivities are computed, and of the period. Delay-differential equations are often used to model gene expression networks. In these models, the parametric sensitivities of a particular genotype define the local geometry of the evolutionary landscape. Thus, sensitivities can be used to investigate directions of gradual evolutionary change. An oscillatory protein synthesis model whose properties are modulated by RNA interference is used as an example. This model consists of a set of coupled delay-differential equations involving three delays. Sensitivity analyses are carried out at several operating points. Comments on the evolutionary implications of the results are offered.

A strategy for improved computational efficiency of the method of anchored distributions

NASA Astrophysics Data System (ADS)

Over, Matthew William; Yang, Yarong; Chen, Xingyuan; Rubin, Yoram

2013-06-01

This paper proposes a strategy for improving the computational efficiency of model inversion using the method of anchored distributions (MAD) by "bundling" similar model parametrizations in the likelihood function. Inferring the likelihood function typically requires a large number of forward model (FM) simulations for each possible model parametrization; as a result, the process is quite expensive. To ease this prohibitive cost, we present an approximation for the likelihood function called bundling that relaxes the requirement for high quantities of FM simulations. This approximation redefines the conditional statement of the likelihood function as the probability of a set of similar model parametrizations "bundle" replicating field measurements, which we show is neither a model reduction nor a sampling approach to improving the computational efficiency of model inversion. To evaluate the effectiveness of these modifications, we compare the quality of predictions and computational cost of bundling relative to a baseline MAD inversion of 3-D flow and transport model parameters. Additionally, to aid understanding of the implementation we provide a tutorial for bundling in the form of a sample data set and script for the R statistical computing language. For our synthetic experiment, bundling achieved a 35% reduction in overall computational cost and had a limited negative impact on predicted probability distributions of the model parameters. Strategies for minimizing error in the bundling approximation, for enforcing similarity among the sets of model parametrizations, and for identifying convergence of the likelihood function are also presented.

Critical evaluation of climate syntheses to benchmark CMIP6/PMIP4 127 ka Last Interglacial simulations in the high-latitude regions

NASA Astrophysics Data System (ADS)

Capron, E.; Govin, A.; Feng, R.; Otto-Bliesner, B. L.; Wolff, E. W.

2017-07-01

The Last Interglacial (LIG, ∼129-116 thousand years ago, ka) represents an excellent case study to investigate the response of sensitive components of the Earth System and mechanisms of high-latitude amplification to a climate warmer than present-day. The Paleoclimate Model Intercomparison Project (Phase 4, hereafter referred as PMIP4) and the Coupled Model Intercomparison Project (Phase 6, hereafter referred as CMIP6) are coordinating the design of (1) a LIG Tier 1 equilibrium simulation to simulate the climate response at 127 ka, a time interval associated with a strong orbital forcing and greenhouse gas concentrations close to preindustrial levels and (2) associated Tier 2 sensitivity experiments to examine the role of the ocean, vegetation and dust feedbacks in modulating the response to this orbital forcing. Evaluating the capability of the CMIP6/PMIP4 models to reproduce the 127 ka polar and sub-polar climate will require appropriate data-based benchmarks which are currently missing. Based on a recent data synthesis that offers the first spatio-temporal representation of high-latitude (i.e. poleward of 40°N and 40°S) surface temperature evolution during the LIG, we produce a new 126-128 ka time slab, hereafter named 127 ka time slice. This 127 ka time slice represents surface temperature anomalies relative to preindustrial and is associated with quantitative estimates of the uncertainties related to relative dating and surface temperature reconstruction methods. It illustrates warmer-than-preindustrial conditions in the high-latitude regions of both hemispheres. In particular, summer sea surface temperatures (SST) in the North Atlantic region were on average 1.1 °C (with a standard error of the mean of 0.7 °C) warmer relative to preindustrial and 1.8 °C (with a standard error of the mean of 0.8 °C) in the Southern Ocean. In Antarctica, average 127 ka annual surface air temperature was 2.2 °C (with a standard error of the mean of 1.4 °C) warmer compared to preindustrial. We provide a critical evaluation of the latest LIG surface climate compilations that are available for evaluating LIG climate model experiments. We discuss in particular our new 127 ka time-slice in the context of existing LIG surface temperature time-slices. We also compare the 127 ka time slice with the ones published for the 125 and 130 ka time intervals and we discuss the potential and limits of a data-based time slice at 127 ka in the context of the upcoming coordinated modeling exercise. Finally we provide guidance on the use of the available LIG climate compilations for future model-data comparison exercises in the framework of the upcoming CMIP6/PMIP4 127 ka experiments. We do not recommend the use of LIG peak warmth-centered syntheses. Instead we promote the use of the most recent syntheses that are based on coherent chronologies between paleoclimatic records and provide spatio-temporal reconstruction of the LIG climate. In particular, we recommend using our new 127 ka data-based time slice in model-data comparison studies with a focus on the high-latitude climate.

Rapid calculation of accurate atomic charges for proteins via the electronegativity equalization method.

PubMed

Ionescu, Crina-Maria; Geidl, Stanislav; Svobodová Vařeková, Radka; Koča, Jaroslav

2013-10-28

We focused on the parametrization and evaluation of empirical models for fast and accurate calculation of conformationally dependent atomic charges in proteins. The models were based on the electronegativity equalization method (EEM), and the parametrization procedure was tailored to proteins. We used large protein fragments as reference structures and fitted the EEM model parameters using atomic charges computed by three population analyses (Mulliken, Natural, iterative Hirshfeld), at the Hartree-Fock level with two basis sets (6-31G*, 6-31G**) and in two environments (gas phase, implicit solvation). We parametrized and successfully validated 24 EEM models. When tested on insulin and ubiquitin, all models reproduced quantum mechanics level charges well and were consistent with respect to population analysis and basis set. Specifically, the models showed on average a correlation of 0.961, RMSD 0.097 e, and average absolute error per atom 0.072 e. The EEM models can be used with the freely available EEM implementation EEM_SOLVER.

A derivation of the Cramer-Rao lower bound of euclidean parameters under equality constraints via score function

NASA Astrophysics Data System (ADS)

Susyanto, Nanang

2017-12-01

We propose a simple derivation of the Cramer-Rao Lower Bound (CRLB) of parameters under equality constraints from the CRLB without constraints in regular parametric models. When a regular parametric model and an equality constraint of the parameter are given, a parametric submodel can be defined by restricting the parameter under that constraint. The tangent space of this submodel is then computed with the help of the implicit function theorem. Finally, the score function of the restricted parameter is obtained by projecting the efficient influence function of the unrestricted parameter on the appropriate inner product spaces.

Advancements in automated tissue segmentation pipeline for contrast-enhanced CT scans of adult and pediatric patients

NASA Astrophysics Data System (ADS)

Somasundaram, Elanchezhian; Kaufman, Robert; Brady, Samuel

2017-03-01

The development of a random forests machine learning technique is presented for fully-automated neck, chest, abdomen, and pelvis tissue segmentation of CT images using Trainable WEKA (Waikato Environment for Knowledge Analysis) Segmentation (TWS) plugin of FIJI (ImageJ, NIH). The use of a single classifier model to segment six tissue classes (lung, fat, muscle, solid organ, blood/contrast agent, bone) in the CT images is studied. An automated unbiased scheme to sample pixels from the training images and generate a balanced training dataset over the seven classes is also developed. Two independent training datasets are generated from a pool of 4 adult (>55 kg) and 3 pediatric patients (<=55 kg) with 7 manually contoured slices for each patient. Classifier training investigated 28 image filters comprising a total of 272 features. Highly correlated and insignificant features are eliminated using Correlated Feature Subset (CFS) selection with Best First Search (BFS) algorithms in WEKA. The 2 training models (from the 2 training datasets) had 74 and 71 input training features, respectively. The study also investigated the effect of varying the number of trees (25, 50, 100, and 200) in the random forest algorithm. The performance of the 2 classifier models are evaluated on inter-patient intra-slice, intrapatient inter-slice and inter-patient inter-slice test datasets. The Dice similarity coefficients (DSC) and confusion matrices are used to understand the performance of the classifiers across the tissue segments. The effect of number of features in the training input on the performance of the classifiers for tissue classes with less than optimal DSC values is also studied. The average DSC values for the two training models on the inter-patient intra-slice test data are: 0.98, 0.89, 0.87, 0.79, 0.68, and 0.84, for lung, fat, muscle, solid organ, blood/contrast agent, and bone, respectively. The study demonstrated that a robust segmentation accuracy for lung, muscle and fat tissue classes. For solid-organ, blood/contrast and bone, the performance of the segmentation pipeline improved significantly by using the advanced capabilities of WEKA. However, further improvements are needed to reduce the noise in the segmentation.

A gradient-based model parametrization using Bernstein polynomials in Bayesian inversion of surface wave dispersion

NASA Astrophysics Data System (ADS)

Gosselin, Jeremy M.; Dosso, Stan E.; Cassidy, John F.; Quijano, Jorge E.; Molnar, Sheri; Dettmer, Jan

2017-10-01

This paper develops and applies a Bernstein-polynomial parametrization to efficiently represent general, gradient-based profiles in nonlinear geophysical inversion, with application to ambient-noise Rayleigh-wave dispersion data. Bernstein polynomials provide a stable parametrization in that small perturbations to the model parameters (basis-function coefficients) result in only small perturbations to the geophysical parameter profile. A fully nonlinear Bayesian inversion methodology is applied to estimate shear wave velocity (VS) profiles and uncertainties from surface wave dispersion data extracted from ambient seismic noise. The Bayesian information criterion is used to determine the appropriate polynomial order consistent with the resolving power of the data. Data error correlations are accounted for in the inversion using a parametric autoregressive model. The inversion solution is defined in terms of marginal posterior probability profiles for VS as a function of depth, estimated using Metropolis-Hastings sampling with parallel tempering. This methodology is applied to synthetic dispersion data as well as data processed from passive array recordings collected on the Fraser River Delta in British Columbia, Canada. Results from this work are in good agreement with previous studies, as well as with co-located invasive measurements. The approach considered here is better suited than `layered' modelling approaches in applications where smooth gradients in geophysical parameters are expected, such as soil/sediment profiles. Further, the Bernstein polynomial representation is more general than smooth models based on a fixed choice of gradient type (e.g. power-law gradient) because the form of the gradient is determined objectively by the data, rather than by a subjective parametrization choice.

Parametric model of the scala tympani for haptic-rendered cochlear implantation.

PubMed

Todd, Catherine; Naghdy, Fazel

2005-01-01

A parametric model of the human scala tympani has been designed for use in a haptic-rendered computer simulation of cochlear implant surgery. It will be the first surgical simulator of this kind. A geometric model of the Scala Tympani has been derived from measured data for this purpose. The model is compared with two existing descriptions of the cochlear spiral. A first approximation of the basilar membrane is also produced. The structures are imported into a force-rendering software application for system development.

Approximation Model Building for Reliability & Maintainability Characteristics of Reusable Launch Vehicles

NASA Technical Reports Server (NTRS)

Unal, Resit; Morris, W. Douglas; White, Nancy H.; Lepsch, Roger A.; Brown, Richard W.

2000-01-01

This paper describes the development of parametric models for estimating operational reliability and maintainability (R&M) characteristics for reusable vehicle concepts, based on vehicle size and technology support level. A R&M analysis tool (RMAT) and response surface methods are utilized to build parametric approximation models for rapidly estimating operational R&M characteristics such as mission completion reliability. These models that approximate RMAT, can then be utilized for fast analysis of operational requirements, for lifecycle cost estimating and for multidisciplinary sign optimization.

Multivariable Parametric Cost Model for Ground Optical: Telescope Assembly

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes; Reese, Gayle; Byberg, Alicia

2004-01-01

A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature were examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter were derived.

Parametric Modeling in the CAE Process: Creating a Family of Models

NASA Technical Reports Server (NTRS)

Brown, Christopher J.

2011-01-01

This Presentation meant as an example - Give ideas of approaches to use - The significant benefit of PARAMETRIC geometry based modeling The importance of planning before you build Showcase some NX capabilities - Mesh Controls - Associativity - Divide Face - Offset Surface Reminder - This only had to be done once! - Can be used for any cabinet in that "family" Saves a lot of time if pre-planned Allows re-use in the future

GEE-Smoothing Spline in Semiparametric Model with Correlated Nominal Data

NASA Astrophysics Data System (ADS)

Ibrahim, Noor Akma; Suliadi

2010-11-01

In this paper we propose GEE-Smoothing spline in the estimation of semiparametric models with correlated nominal data. The method can be seen as an extension of parametric generalized estimating equation to semiparametric models. The nonparametric component is estimated using smoothing spline specifically the natural cubic spline. We use profile algorithm in the estimation of both parametric and nonparametric components. The properties of the estimators are evaluated using simulation studies.

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models.

PubMed

Bignardi, A B; El Faro, L; Cardoso, V L; Machado, P F; Albuquerque, L G

2009-09-01

The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

Correlation between a Student's Performance on the Mental Cutting Test and Their 3D Parametric Modeling Ability

ERIC Educational Resources Information Center

Steinhauer, H. M.

2012-01-01

Engineering graphics has historically been viewed as a challenging course to teach as students struggle to grasp and understand the fundamental concepts and then to master their proper application. The emergence of stable, fast, affordable 3D parametric modeling platforms such as CATIA, Pro-E, and AutoCAD while providing several pedagogical…

Quantum Treatment of Two Coupled Oscillators in Interaction with a Two-Level Atom:

NASA Astrophysics Data System (ADS)

Khalil, E. M.; Abdalla, M. Sebawe; Obada, A. S.-F.

In this communication we handle a modified model representing the interaction between a two-level atom and two modes of the electromagnetic field in a cavity. The interaction between the modes is assumed to be of a parametric amplifier type. The model consists of two different systems, one represents the Jaynes-Cummings model (atom-field interaction) and the other represents the two mode parametric amplifier model (field-field interaction). After some canonical transformations the constants of the motion have been obtained and used to derive the time evolution operator. The wave function in the Schrödinger picture is constructed and employed to discuss some statistical properties related to the system. Further discussion related to the statistical properties of some physical quantities is given where we have taken into account an initial correlated pair-coherent state for the modes. We concentrate in our examination on the system behavior that occurred as a result of the variation of the parametric amplifier coupling parameter as well as the detuning parameter. It has been shown that the interaction of the parametric amplifier term increases the revival period and consequently longer period of strong interaction between the atom and the fields.

Processes controlling surface, bottom and lateral melt of Arctic sea ice in a state of the art sea ice model.

PubMed

Tsamados, Michel; Feltham, Daniel; Petty, Alek; Schroeder, David; Flocco, Daniela

2015-10-13

We present a modelling study of processes controlling the summer melt of the Arctic sea ice cover. We perform a sensitivity study and focus our interest on the thermodynamics at the ice-atmosphere and ice-ocean interfaces. We use the Los Alamos community sea ice model CICE, and additionally implement and test three new parametrization schemes: (i) a prognostic mixed layer; (ii) a three equation boundary condition for the salt and heat flux at the ice-ocean interface; and (iii) a new lateral melt parametrization. Recent additions to the CICE model are also tested, including explicit melt ponds, a form drag parametrization and a halodynamic brine drainage scheme. The various sea ice parametrizations tested in this sensitivity study introduce a wide spread in the simulated sea ice characteristics. For each simulation, the total melt is decomposed into its surface, bottom and lateral melt components to assess the processes driving melt and how this varies regionally and temporally. Because this study quantifies the relative importance of several processes in driving the summer melt of sea ice, this work can serve as a guide for future research priorities. © 2015 The Author(s).

Electrophysiology of Hypothalamic Magnocellular Neurons In vitro: A Rhythmic Drive in Organotypic Cultures and Acute Slices.

PubMed

Israel, Jean-Marc; Oliet, Stéphane H; Ciofi, Philippe

2016-01-01

Hypothalamic neurohormones are released in a pulsatile manner. The mechanisms of this pulsatility remain poorly understood and several hypotheses are available, depending upon the neuroendocrine system considered. Among these systems, hypothalamo-neurohypophyseal magnocellular neurons have been early-considered models, as they typically display an electrical activity consisting of bursts of action potentials that is optimal for the release of boluses of the neurohormones oxytocin and vasopressin. The cellular mechanisms underlying this bursting behavior have been studied in vitro, using either acute slices of the adult hypothalamus, or organotypic cultures of neonatal hypothalamic tissue. We have recently proposed, from experiments in organotypic cultures, that specific central pattern generator networks, upstream of magnocellular neurons, determine their bursting activity. Here, we have tested whether a similar hypothesis can be derived from in vitro experiments in acute slices of the adult hypothalamus. To this aim we have screened our electrophysiological recordings of the magnocellular neurons, previously obtained from acute slices, with an analysis of autocorrelation of action potentials to detect a rhythmic drive as we recently did for organotypic cultures. This confirmed that the bursting behavior of magnocellular neurons is governed by central pattern generator networks whose rhythmic drive, and thus probably integrity, is however less satisfactorily preserved in the acute slices from adult brains.

Increased glutamate-stimulated norepinephrine release from prefrontal cortex slices of spontaneously hypertensive rats.

PubMed

Russell, V A; Wiggins, T M

2000-12-01

Spontaneously hypertensive rats (SHR) have behavioral characteristics (hyperactivity, impulsiveness, poorly sustained attention) similar to the behavioral disturbances of children with attention-deficit hyperactivity disorder (ADHD). We have previously shown that dopaminergic and noradrenergic systems are disturbed in the prefrontal cortex of SHR compared to their normotensive Wistar-Kyoto (WKY) control rats. It was of interest to determine whether the underlying neural circuits that use glutamate as a neurotransmitter function normally in the prefrontal cortex of SHR. An in vitro superfusion technique was used to demonstrate that glutamate caused a concentration-dependent stimulation of [3H]norepinephrine release from rat prefrontal cortex slices. Glutamate (100 microM and 1 mM) caused significantly greater release of norepinephrine from prefrontal cortex slices of SHR than from control slices. The effect of glutamate was not mediated by NMDA receptors, since NMDA (10 and 100 microM) did not exert any effect on norepinephrine release and MK-801 (10 microM) did not antagonize the effect of 100 microM glutamate. These results demonstrate that glutamate stimulates norepinephrine release from rat prefrontal cortex slices and that this increase is enhanced in SHR. The results are consistent with the suggestion that the noradrenergic system is overactive in prefrontal cortex of SHR, the animal model for ADHD.

Effect of Monovalent Ion Parameters on Molecular Dynamics Simulations of G-Quadruplexes.

PubMed

Havrila, Marek; Stadlbauer, Petr; Islam, Barira; Otyepka, Michal; Šponer, Jiří

2017-08-08

G-quadruplexes (GQs) are key noncanonical DNA and RNA architectures stabilized by desolvated monovalent cations present in their central channels. We analyze extended atomistic molecular dynamics simulations (∼580 μs in total) of GQs with 11 monovalent cation parametrizations, assessing GQ overall structural stability, dynamics of internal cations, and distortions of the G-tetrad geometries. Majority of simulations were executed with the SPC/E water model; however, test simulations with TIP3P and OPC water models are also reported. The identity and parametrization of ions strongly affect behavior of a tetramolecular d[GGG] 4 GQ, which is unstable with several ion parametrizations. The remaining studied RNA and DNA GQs are structurally stable, though the G-tetrad geometries are always deformed by bifurcated H-bonding in a parametrization-specific manner. Thus, basic 10-μs-scale simulations of fully folded GQs can be safely done with a number of cation parametrizations. However, there are parametrization-specific differences and basic force-field errors affecting the quantitative description of ion-tetrad interactions, which may significantly affect studies of the ion-binding processes and description of the GQ folding landscape. Our d[GGG] 4 simulations indirectly suggest that such studies will also be sensitive to the water models. During exchanges with bulk water, the Na + ions move inside the GQs in a concerted manner, while larger relocations of the K + ions are typically separated. We suggest that the Joung-Cheatham SPC/E K + parameters represent a safe choice in simulation studies of GQs, though variation of ion parameters can be used for specific simulation goals.

Ex vivo human pancreatic slice preparations offer a valuable model for studying pancreatic exocrine biology.

PubMed

Liang, Tao; Dolai, Subhankar; Xie, Li; Winter, Erin; Orabi, Abrahim I; Karimian, Negar; Cosen-Binker, Laura I; Huang, Ya-Chi; Thorn, Peter; Cattral, Mark S; Gaisano, Herbert Y

2017-04-07

A genuine understanding of human exocrine pancreas biology and pathobiology has been hampered by a lack of suitable preparations and reliance on rodent models employing dispersed acini preparations. We have developed an organotypic slice preparation of the normal portions of human pancreas obtained from cancer resections. The preparation was assessed for physiologic and pathologic responses to the cholinergic agonist carbachol (Cch) and cholecystokinin (CCK-8), including 1) amylase secretion, 2) exocytosis, 3) intracellular Ca 2+ responses, 4) cytoplasmic autophagic vacuole formation, and 5) protease activation. Cch and CCK-8 both dose-dependently stimulated secretory responses from human pancreas slices similar to those previously observed in dispersed rodent acini. Confocal microscopy imaging showed that these responses were accounted for by efficient apical exocytosis at physiologic doses of both agonists and by apical blockade and redirection of exocytosis to the basolateral plasma membrane at supramaximal doses. The secretory responses and exocytotic events evoked by CCK-8 were mediated by CCK-A and not CCK-B receptors. Physiologic agonist doses evoked oscillatory Ca 2+ increases across the acini. Supraphysiologic doses induced formation of cytoplasmic autophagic vacuoles and activation of proteases (trypsin, chymotrypsin). Maximal atropine pretreatment that completely blocked all the Cch-evoked responses did not affect any of the CCK-8-evoked responses, indicating that rather than acting on the nerves within the pancreas slice, CCK cellular actions directly affected human acinar cells. Human pancreas slices represent excellent preparations to examine pancreatic cell biology and pathobiology and could help screen for potential treatments for human pancreatitis. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Streamflow hindcasting in European river basins via multi-parametric ensemble of the mesoscale hydrologic model (mHM)

NASA Astrophysics Data System (ADS)

Noh, Seong Jin; Rakovec, Oldrich; Kumar, Rohini; Samaniego, Luis

2016-04-01

There have been tremendous improvements in distributed hydrologic modeling (DHM) which made a process-based simulation with a high spatiotemporal resolution applicable on a large spatial scale. Despite of increasing information on heterogeneous property of a catchment, DHM is still subject to uncertainties inherently coming from model structure, parameters and input forcing. Sequential data assimilation (DA) may facilitate improved streamflow prediction via DHM using real-time observations to correct internal model states. In conventional DA methods such as state updating, parametric uncertainty is, however, often ignored mainly due to practical limitations of methodology to specify modeling uncertainty with limited ensemble members. If parametric uncertainty related with routing and runoff components is not incorporated properly, predictive uncertainty by DHM may be insufficient to capture dynamics of observations, which may deteriorate predictability. Recently, a multi-scale parameter regionalization (MPR) method was proposed to make hydrologic predictions at different scales using a same set of model parameters without losing much of the model performance. The MPR method incorporated within the mesoscale hydrologic model (mHM, http://www.ufz.de/mhm) could effectively represent and control uncertainty of high-dimensional parameters in a distributed model using global parameters. In this study, we present a global multi-parametric ensemble approach to incorporate parametric uncertainty of DHM in DA to improve streamflow predictions. To effectively represent and control uncertainty of high-dimensional parameters with limited number of ensemble, MPR method is incorporated with DA. Lagged particle filtering is utilized to consider the response times and non-Gaussian characteristics of internal hydrologic processes. The hindcasting experiments are implemented to evaluate impacts of the proposed DA method on streamflow predictions in multiple European river basins having different climate and catchment characteristics. Because augmentation of parameters is not required within an assimilation window, the approach could be stable with limited ensemble members and viable for practical uses.

Slicing AADL Specifications for Model Checking

NASA Technical Reports Server (NTRS)

Odenbrett, Maximilian; Nguyen, Viet Yen; Noll, Thomas

2010-01-01

To combat the state-space explosion problem in model checking larger systems, abstraction techniques can be employed. Here, methods that operate on the system specification before constructing its state space are preferable to those that try to minimize the resulting transition system as they generally reduce peak memory requirements. We sketch a slicing algorithm for system specifications written in (a variant of) the Architecture Analysis and Design Language (AADL). Given a specification and a property to be verified, it automatically removes those parts of the specification that are irrelevant for model checking the property, thus reducing the size of the corresponding transition system. The applicability and effectiveness of our approach is demonstrated by analyzing the state-space reduction for an example, employing a translator from AADL to Promela, the input language of the SPIN model checker.

The analysis of incontinence episodes and other count data in patients with overactive bladder by Poisson and negative binomial regression.

PubMed

Martina, R; Kay, R; van Maanen, R; Ridder, A

2015-01-01

Clinical studies in overactive bladder have traditionally used analysis of covariance or nonparametric methods to analyse the number of incontinence episodes and other count data. It is known that if the underlying distributional assumptions of a particular parametric method do not hold, an alternative parametric method may be more efficient than a nonparametric one, which makes no assumptions regarding the underlying distribution of the data. Therefore, there are advantages in using methods based on the Poisson distribution or extensions of that method, which incorporate specific features that provide a modelling framework for count data. One challenge with count data is overdispersion, but methods are available that can account for this through the introduction of random effect terms in the modelling, and it is this modelling framework that leads to the negative binomial distribution. These models can also provide clinicians with a clearer and more appropriate interpretation of treatment effects in terms of rate ratios. In this paper, the previously used parametric and non-parametric approaches are contrasted with those based on Poisson regression and various extensions in trials evaluating solifenacin and mirabegron in patients with overactive bladder. In these applications, negative binomial models are seen to fit the data well. Copyright © 2014 John Wiley & Sons, Ltd.

Parametric regression model for survival data: Weibull regression model as an example

PubMed Central

2016-01-01

Weibull regression model is one of the most popular forms of parametric regression model that it provides estimate of baseline hazard function, as well as coefficients for covariates. Because of technical difficulties, Weibull regression model is seldom used in medical literature as compared to the semi-parametric proportional hazard model. To make clinical investigators familiar with Weibull regression model, this article introduces some basic knowledge on Weibull regression model and then illustrates how to fit the model with R software. The SurvRegCensCov package is useful in converting estimated coefficients to clinical relevant statistics such as hazard ratio (HR) and event time ratio (ETR). Model adequacy can be assessed by inspecting Kaplan-Meier curves stratified by categorical variable. The eha package provides an alternative method to model Weibull regression model. The check.dist() function helps to assess goodness-of-fit of the model. Variable selection is based on the importance of a covariate, which can be tested using anova() function. Alternatively, backward elimination starting from a full model is an efficient way for model development. Visualization of Weibull regression model after model development is interesting that it provides another way to report your findings. PMID:28149846

Active appearance pyramids for object parametrisation and fitting.

PubMed

Zhang, Qiang; Bhalerao, Abhir; Dickenson, Edward; Hutchinson, Charles

2016-08-01

Object class representation is one of the key problems in various medical image analysis tasks. We propose a part-based parametric appearance model we refer to as an Active Appearance Pyramid (AAP). The parts are delineated by multi-scale Local Feature Pyramids (LFPs) for superior spatial specificity and distinctiveness. An AAP models the variability within a population with local translations of multi-scale parts and linear appearance variations of the assembly of the parts. It can fit and represent new instances by adjusting the shape and appearance parameters. The fitting process uses a two-step iterative strategy: local landmark searching followed by shape regularisation. We present a simultaneous local feature searching and appearance fitting algorithm based on the weighted Lucas and Kanade method. A shape regulariser is derived to calculate the maximum likelihood shape with respect to the prior and multiple landmark candidates from multi-scale LFPs, with a compact closed-form solution. We apply the 2D AAP on the modelling of variability in patients with lumbar spinal stenosis (LSS) and validate its performance on 200 studies consisting of routine axial and sagittal MRI scans. Intervertebral sagittal and parasagittal cross-sections are typically used for the diagnosis of LSS, we therefore build three AAPs on L3/4, L4/5 and L5/S1 axial cross-sections and three on parasagittal slices. Experiments show significant improvement in convergence range, robustness to local minima and segmentation precision compared with Constrained Local Models (CLMs), Active Shape Models (ASMs) and Active Appearance Models (AAMs), as well as superior performance in appearance reconstruction compared with AAMs. We also validate the performance on 3D CT volumes of hip joints from 38 studies. Compared to AAMs, AAPs achieve a higher segmentation and reconstruction precision. Moreover, AAPs have a significant improvement in efficiency, consuming about half the memory and less than 10% of the training time and 15% of the testing time. Copyright © 2016 Elsevier B.V. All rights reserved.

Volterra model of the parametric array loudspeaker operating at ultrasonic frequencies.

PubMed

Shi, Chuang; Kajikawa, Yoshinobu

2016-11-01

The parametric array loudspeaker (PAL) is an application of the parametric acoustic array in air, which can be applied to transmit a narrow audio beam from an ultrasonic emitter. However, nonlinear distortion is very perceptible in the audio beam. Modulation methods to reduce the nonlinear distortion are available for on-axis far-field applications. For other applications, preprocessing techniques are wanting. In order to develop a preprocessing technique with general applicability to a wide range of operating conditions, the Volterra filter is investigated as a nonlinear model of the PAL in this paper. Limitations of the standard audio-to-audio Volterra filter are elaborated. An improved ultrasound-to-ultrasound Volterra filter is proposed and empirically demonstrated to be a more generic Volterra model of the PAL.

Ground-Based Telescope Parametric Cost Model

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes

2004-01-01

A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis, The model includes both engineering and performance parameters. While diameter continues to be the dominant cost driver, other significant factors include primary mirror radius of curvature and diffraction limited wavelength. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e.. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter are derived. This analysis indicates that recent mirror technology advances have indeed reduced the historical telescope cost curve.

TOWARD HIGH-PRECISION SEISMIC STUDIES OF WHITE DWARF STARS: PARAMETRIZATION OF THE CORE AND TESTS OF ACCURACY

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

Giammichele, N.; Fontaine, G.; Brassard, P.

We present a prescription for parametrizing the chemical profile in the core of white dwarfs in light of the recent discovery that pulsation modes may sometimes be deeply confined in some cool pulsating white dwarfs. Such modes may be used as unique probes of the complicated chemical stratification that results from several processes that occurred in previous evolutionary phases of intermediate-mass stars. This effort is part of our ongoing quest for more credible and realistic seismic models of white dwarfs using static, parametrized equilibrium structures. Inspired by successful techniques developed in design optimization fields (such as aerodynamics), we exploit Akimamore » splines for the tracing of the chemical profile of oxygen (carbon) in the core of a white dwarf model. A series of tests are then presented to better seize the precision and significance of the results that can be obtained in an asteroseismological context. We also show that the new parametrization passes an essential basic test, as it successfully reproduces the chemical stratification of a full evolutionary model.« less

Real-time solution of linear computational problems using databases of parametric reduced-order models with arbitrary underlying meshes

NASA Astrophysics Data System (ADS)

Amsallem, David; Tezaur, Radek; Farhat, Charbel

2016-12-01

A comprehensive approach for real-time computations using a database of parametric, linear, projection-based reduced-order models (ROMs) based on arbitrary underlying meshes is proposed. In the offline phase of this approach, the parameter space is sampled and linear ROMs defined by linear reduced operators are pre-computed at the sampled parameter points and stored. Then, these operators and associated ROMs are transformed into counterparts that satisfy a certain notion of consistency. In the online phase of this approach, a linear ROM is constructed in real-time at a queried but unsampled parameter point by interpolating the pre-computed linear reduced operators on matrix manifolds and therefore computing an interpolated linear ROM. The proposed overall model reduction framework is illustrated with two applications: a parametric inverse acoustic scattering problem associated with a mockup submarine, and a parametric flutter prediction problem associated with a wing-tank system. The second application is implemented on a mobile device, illustrating the capability of the proposed computational framework to operate in real-time.

Toward High-precision Seismic Studies of White Dwarf Stars: Parametrization of the Core and Tests of Accuracy

NASA Astrophysics Data System (ADS)

Giammichele, N.; Charpinet, S.; Fontaine, G.; Brassard, P.

2017-01-01

We present a prescription for parametrizing the chemical profile in the core of white dwarfs in light of the recent discovery that pulsation modes may sometimes be deeply confined in some cool pulsating white dwarfs. Such modes may be used as unique probes of the complicated chemical stratification that results from several processes that occurred in previous evolutionary phases of intermediate-mass stars. This effort is part of our ongoing quest for more credible and realistic seismic models of white dwarfs using static, parametrized equilibrium structures. Inspired by successful techniques developed in design optimization fields (such as aerodynamics), we exploit Akima splines for the tracing of the chemical profile of oxygen (carbon) in the core of a white dwarf model. A series of tests are then presented to better seize the precision and significance of the results that can be obtained in an asteroseismological context. We also show that the new parametrization passes an essential basic test, as it successfully reproduces the chemical stratification of a full evolutionary model.

TH-C-18A-11: Investigating the Minimum Scan Parameters Required to Generate Free-Breathing Fast-Helical CT Scans Without Motion-Artifacts

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

Thomas, D; Neylon, J; Dou, T

Purpose: A recently proposed 4D-CT protocol uses deformable registration of free-breathing fast-helical CT scans to generate a breathing motion model. In order to allow accurate registration, free-breathing images are required to be free of doubling-artifacts, which arise when tissue motion is greater than scan speed. This work identifies the minimum scanner parameters required to successfully generate free-breathing fast-helical scans without doubling-artifacts. Methods: 10 patients were imaged under free breathing conditions 25 times in alternating directions with a 64-slice CT scanner using a low dose fast helical protocol. A high temporal resolution (0.1s) 4D-CT was generated using a patient specific motionmore » model and patient breathing waveforms, and used as the input for a scanner simulation. Forward projections were calculated using helical cone-beam geometry (800 projections per rotation) and a GPU accelerated reconstruction algorithm was implemented. Various CT scanner detector widths and rotation times were simulated, and verified using a motion phantom. Doubling-artifacts were quantified in patient images using structural similarity maps to determine the similarity between axial slices. Results: Increasing amounts of doubling-artifacts were observed with increasing rotation times > 0.2s for 16×1mm slice scan geometry. No significant increase in doubling artifacts was observed for 64×1mm slice scan geometry up to 1.0s rotation time although blurring artifacts were observed >0.6s. Using a 16×1mm slice scan geometry, a rotation time of less than 0.3s (53mm/s scan speed) would be required to produce images of similar quality to a 64×1mm slice scan geometry. Conclusion: The current generation of 16 slice CT scanners, which are present in most Radiation Oncology departments, are not capable of generating free-breathing sorting-artifact-free images in the majority of patients. The next generation of CT scanners should be capable of at least 53mm/s scan speed in order to use a fast-helical 4D-CT protocol to generate a motion-artifact free 4D-CT. NIH R01CA096679.« less

An Application of Semi-parametric Estimator with Weighted Matrix of Data Depth in Variance Component Estimation

NASA Astrophysics Data System (ADS)

Pan, X. G.; Wang, J. Q.; Zhou, H. Y.

2013-05-01

The variance component estimation (VCE) based on semi-parametric estimator with weighted matrix of data depth has been proposed, because the coupling system model error and gross error exist in the multi-source heterogeneous measurement data of space and ground combined TT&C (Telemetry, Tracking and Command) technology. The uncertain model error has been estimated with the semi-parametric estimator model, and the outlier has been restrained with the weighted matrix of data depth. On the basis of the restriction of the model error and outlier, the VCE can be improved and used to estimate weighted matrix for the observation data with uncertain model error or outlier. Simulation experiment has been carried out under the circumstance of space and ground combined TT&C. The results show that the new VCE based on the model error compensation can determine the rational weight of the multi-source heterogeneous data, and restrain the outlier data.

Hybrid pathwise sensitivity methods for discrete stochastic models of chemical reaction systems.

PubMed

Wolf, Elizabeth Skubak; Anderson, David F

2015-01-21

Stochastic models are often used to help understand the behavior of intracellular biochemical processes. The most common such models are continuous time Markov chains (CTMCs). Parametric sensitivities, which are derivatives of expectations of model output quantities with respect to model parameters, are useful in this setting for a variety of applications. In this paper, we introduce a class of hybrid pathwise differentiation methods for the numerical estimation of parametric sensitivities. The new hybrid methods combine elements from the three main classes of procedures for sensitivity estimation and have a number of desirable qualities. First, the new methods are unbiased for a broad class of problems. Second, the methods are applicable to nearly any physically relevant biochemical CTMC model. Third, and as we demonstrate on several numerical examples, the new methods are quite efficient, particularly if one wishes to estimate the full gradient of parametric sensitivities. The methods are rather intuitive and utilize the multilevel Monte Carlo philosophy of splitting an expectation into separate parts and handling each in an efficient manner.

Cosmological implications of quantum mechanics parametrization of dark energy

NASA Astrophysics Data System (ADS)

Szydłowski, Marek; Stachowski, Aleksander; Urbanowski, Krzysztof

2017-08-01

We consider the cosmology with the running dark energy. The parametrization of dark energy is derived from the quantum process of transition from the false vacuum state to the true vacuum state. This model is the generalized interacting CDM model. We consider the energy density of dark energy parametrization, which is given by the Breit-Wigner energy distribution function. The idea of the process of the quantum mechanical decay of unstable states was formulated by Krauss and Dent. We used this idea in our considerations. In this model is an energy transfer in the dark sector. In this evolutional scenario the universe starts from the false vacuum state and goes to the true vacuum state of the present day universe. The intermediate regime during the passage from false to true vacuum states takes place. In this way the cosmological constant problem can be tried to solve. We estimate the cosmological parameters for this model. This model is in a good agreement with the astronomical data and is practically indistinguishable from CDM model.

In vitro 6-hydroxydopamine-induced toxicity in striatal, cerebrocortical and hippocampal slices is attenuated by atorvastatin and MK-801.

PubMed

Massari, Caio M; Castro, Adalberto A; Dal-Cim, Tharine; Lanznaster, Débora; Tasca, Carla I

2016-12-01

Parkinson's disease (PD) involves the loss of striatal dopaminergic neurons, although other neurotransmitters and brain areas are also involved in its pathophysiology. In rodent models to PD it has been shown statins improve cognitive and motor deficits and attenuate inflammatory responses evoked by PD-related toxins. Statins are the drugs most prescribed to hypercholesterolemia, but neuroprotective effects have also been attributed to statins treatment in humans and in animal models. This study aimed to establish an in vitro model of 6-hydroxydopamine (6-OHDA)-induced toxicity, used as an initial screening test to identify effective drugs against neural degeneration related to PD. The putative neuroprotective effect of atorvastatin against 6-OHDA-induced toxicity in rat striatal, cerebrocortical and hippocampal slices was also evaluated. 6-OHDA (100μM) decreased cellular viability in slices obtained from rat cerebral cortex, hippocampus and striatum. 6-OHDA also induced an increased reactive oxygen species (ROS) production and mitochondrial dysfunction. Co-incubation of 6-OHDA with atorvastatin (10μM) or MK-801 (50μM) an N-methyl-d-aspartate (NMDA) receptor antagonist, partially attenuated the cellular damage evoked by 6-OHDA in the three brain areas. Atorvastatin partially reduced ROS production in the hippocampus and striatum and disturbances of mitochondria membrane potential in cortex and striatum. 6-OHDA-induced toxicity in vitro displays differences among the brain structures, but it is also observed in cerebrocortical and hippocampal slices, besides striatum. Copyright © 2016 Elsevier B.V. All rights reserved.

Wavelength dependence of nanosecond laser induced surface damage in fused silica from 260 to 1550 nm

NASA Astrophysics Data System (ADS)

Cao, Ming; Cao, Jianjun; Liu, Mian; Sun, Yuan; Wu, Meng; Guo, Shiming; Gao, Shumei

2018-04-01

The wavelength dependence of laser induced surface damage in fused silica is experimentally studied in a wide wavelength range from 260 to 1550 nm. An optical parametric oscillator system is used to provide the tunable laser pulses with a duration of 5 ns. In the experiments, the exit surface of the silica slice is observed to be damaged prior to the entrance surface. The damage threshold decreases gradually as the wavelength decreases from 1550 to 324 nm and drops suddenly at 324 nm, which corresponds to a half of 7.66 eV. This wavelength dependence can be explained by a defect assisted multiphoton absorption mechanism. By fitting the experimental data with a power law equation, the damage threshold is found to be proportional to the 3.47-th power of wavelength in the range of 325-685 nm and 1.1-th power of wavelength in the range of 260-1550 nm.

Proceedings of the Solid Freeform Fabrication Symposium (3rd) Held in Austin, Texas on 3-5 August 1992

DTIC Science & Technology

1992-09-01

to accept; Manufacturing the desk could be only a very small facility for manufacturing Instant In every manufacturing process Manufacturing will be...produced " instant " parts Layer Characterized most, but not all Manufacturing of the new principles Material Deposit Includes the geometrical...using the NOODLES CAD environment [4]. Next, the CAD model is sliced, and the slices are used to generate files that control the laser mask cutting

A testbed to explore the optimal electrical stimulation parameters for suppressing inter-ictal spikes in human hippocampal slices.

PubMed

Min-Chi Hsiao; Pen-Ning Yu; Dong Song; Liu, Charles Y; Heck, Christi N; Millett, David; Berger, Theodore W

2014-01-01

New interventions using neuromodulatory devices such as vagus nerve stimulation, deep brain stimulation and responsive neurostimulation are available or under study for the treatment of refractory epilepsy. Since the actual mechanisms of the onset and termination of the seizure are still unclear, most researchers or clinicians determine the optimal stimulation parameters through trial-and-error procedures. It is necessary to further explore what types of electrical stimulation parameters (these may include stimulation frequency, amplitude, duration, interval pattern, and location) constitute a set of optimal stimulation paradigms to suppress seizures. In a previous study, we developed an in vitro epilepsy model using hippocampal slices from patients suffering from mesial temporal lobe epilepsy. Using a planar multi-electrode array system, inter-ictal activity from human hippocampal slices was consistently recorded. In this study, we have further transferred this in vitro seizure model to a testbed for exploring the possible neurostimulation paradigms to inhibit inter-ictal spikes. The methodology used to collect the electrophysiological data, the approach to apply different electrical stimulation parameters to the slices are provided in this paper. The results show that this experimental testbed will provide a platform for testing the optimal stimulation parameters of seizure cessation. We expect this testbed will expedite the process for identifying the most effective parameters, and may ultimately be used to guide programming of new stimulating paradigms for neuromodulatory devices.

Freezing effect on bread appearance evaluated by digital imaging

NASA Astrophysics Data System (ADS)

Zayas, Inna Y.

1999-01-01

In marketing channels, bread is sometimes delivered in a frozen sate for distribution. Changes occur in physical dimensions, crumb grain and appearance of slices. Ten loaves, twelve bread slices per loaf were scanned for digital image analysis and then frozen in a commercial refrigerator. The bread slices were stored for four weeks scanned again, permitted to thaw and scanned a third time. Image features were extracted, to determine shape, size and image texture of the slices. Different thresholds of grey levels were set to detect changes that occurred in crumb, images were binarized at these settings. The number of pixels falling into these gray level settings were determined for each slice. Image texture features of subimages of each slice were calculated to quantify slice crumb grain. The image features of the slice size showed shrinking of bread slices, as a results of freezing and storage, although shape of slices did not change markedly. Visible crumb texture changes occurred and these changes were depicted by changes in image texture features. Image texture features showed that slice crumb changed differently at the center of a slice compared to a peripheral area close to the crust. Image texture and slice features were sufficient for discrimination of slices before and after freezing and after thawing.

Classification of Company Performance using Weighted Probabilistic Neural Network

NASA Astrophysics Data System (ADS)

Yasin, Hasbi; Waridi Basyiruddin Arifin, Adi; Warsito, Budi

2018-05-01

Classification of company performance can be judged by looking at its financial status, whether good or bad state. Classification of company performance can be achieved by some approach, either parametric or non-parametric. Neural Network is one of non-parametric methods. One of Artificial Neural Network (ANN) models is Probabilistic Neural Network (PNN). PNN consists of four layers, i.e. input layer, pattern layer, addition layer, and output layer. The distance function used is the euclidean distance and each class share the same values as their weights. In this study used PNN that has been modified on the weighting process between the pattern layer and the addition layer by involving the calculation of the mahalanobis distance. This model is called the Weighted Probabilistic Neural Network (WPNN). The results show that the company's performance modeling with the WPNN model has a very high accuracy that reaches 100%.

Parameterization models for pesticide exposure via crop consumption.

PubMed

Fantke, Peter; Wieland, Peter; Juraske, Ronnie; Shaddick, Gavin; Itoiz, Eva Sevigné; Friedrich, Rainer; Jolliet, Olivier

2012-12-04

An approach for estimating human exposure to pesticides via consumption of six important food crops is presented that can be used to extend multimedia models applied in health risk and life cycle impact assessment. We first assessed the variation of model output (pesticide residues per kg applied) as a function of model input variables (substance, crop, and environmental properties) including their possible correlations using matrix algebra. We identified five key parameters responsible for between 80% and 93% of the variation in pesticide residues, namely time between substance application and crop harvest, degradation half-lives in crops and on crop surfaces, overall residence times in soil, and substance molecular weight. Partition coefficients also play an important role for fruit trees and tomato (Kow), potato (Koc), and lettuce (Kaw, Kow). Focusing on these parameters, we develop crop-specific models by parametrizing a complex fate and exposure assessment framework. The parametric models thereby reflect the framework's physical and chemical mechanisms and predict pesticide residues in harvest using linear combinations of crop, crop surface, and soil compartments. Parametric model results correspond well with results from the complex framework for 1540 substance-crop combinations with total deviations between a factor 4 (potato) and a factor 66 (lettuce). Predicted residues also correspond well with experimental data previously used to evaluate the complex framework. Pesticide mass in harvest can finally be combined with reduction factors accounting for food processing to estimate human exposure from crop consumption. All parametric models can be easily implemented into existing assessment frameworks.

Efficient Parallel Levenberg-Marquardt Model Fitting towards Real-Time Automated Parametric Imaging Microscopy

PubMed Central

Zhu, Xiang; Zhang, Dianwen

2013-01-01

We present a fast, accurate and robust parallel Levenberg-Marquardt minimization optimizer, GPU-LMFit, which is implemented on graphics processing unit for high performance scalable parallel model fitting processing. GPU-LMFit can provide a dramatic speed-up in massive model fitting analyses to enable real-time automated pixel-wise parametric imaging microscopy. We demonstrate the performance of GPU-LMFit for the applications in superresolution localization microscopy and fluorescence lifetime imaging microscopy. PMID:24130785

A parametric model of muscle moment arm as a function of joint angle: application to the dorsiflexor muscle group in mice.

PubMed

Miller, S W; Dennis, R G

1996-12-01

A parametric model was developed to describe the relationship between muscle moment arm and joint angle. The model was applied to the dorsiflexor muscle group in mice, for which the moment arm was determined as a function of ankle angle. The moment arm was calculated from the torque measured about the ankle upon application of a known force along the line of action of the dorsiflexor muscle group. The dependence of the dorsiflexor moment arm on ankle angle was modeled as r = R sin(a + delta), where r is the moment arm calculated from the measured torque and a is the joint angle. A least-squares curve fit yielded values for R, the maximum moment arm, and delta, the angle at which the maximum moment arm occurs as offset from 90 degrees. Parametric models were developed for two strains of mice, and no differences were found between the moment arms determined for each strain. Values for the maximum moment arm, R, for the two different strains were 0.99 and 1.14 mm, in agreement with the limited data available from the literature. While in some cases moment arm data may be better fitted by a polynomial, use of the parametric model provides a moment arm relationship with meaningful anatomical constants, allowing for the direct comparison of moment arm characteristics between different strains and species.

Selecting a Separable Parametric Spatiotemporal Covariance Structure for Longitudinal Imaging Data

PubMed Central

George, Brandon; Aban, Inmaculada

2014-01-01

Longitudinal imaging studies allow great insight into how the structure and function of a subject’s internal anatomy changes over time. Unfortunately, the analysis of longitudinal imaging data is complicated by inherent spatial and temporal correlation: the temporal from the repeated measures, and the spatial from the outcomes of interest being observed at multiple points in a patients body. We propose the use of a linear model with a separable parametric spatiotemporal error structure for the analysis of repeated imaging data. The model makes use of spatial (exponential, spherical, and Matérn) and temporal (compound symmetric, autoregressive-1, Toeplitz, and unstructured) parametric correlation functions. A simulation study, inspired by a longitudinal cardiac imaging study on mitral regurgitation patients, compared different information criteria for selecting a particular separable parametric spatiotemporal correlation structure as well as the effects on Type I and II error rates for inference on fixed effects when the specified model is incorrect. Information criteria were found to be highly accurate at choosing between separable parametric spatiotemporal correlation structures. Misspecification of the covariance structure was found to have the ability to inflate the Type I error or have an overly conservative test size, which corresponded to decreased power. An example with clinical data is given illustrating how the covariance structure procedure can be done in practice, as well as how covariance structure choice can change inferences about fixed effects. PMID:25293361

Parametric FEM for geometric biomembranes

NASA Astrophysics Data System (ADS)

Bonito, Andrea; Nochetto, Ricardo H.; Sebastian Pauletti, M.

2010-05-01

We consider geometric biomembranes governed by an L2-gradient flow for bending energy subject to area and volume constraints (Helfrich model). We give a concise derivation of a novel vector formulation, based on shape differential calculus, and corresponding discretization via parametric FEM using quadratic isoparametric elements and a semi-implicit Euler method. We document the performance of the new parametric FEM with a number of simulations leading to dumbbell, red blood cell and toroidal equilibrium shapes while exhibiting large deformations.

Failure Time Distributions: Estimates and Asymptotic Results.

DTIC Science & Technology

1980-01-01

of the models. A parametric family of distributions is proposed for approximating life distri- butions whose hazard rate is bath-tub shaped, this...of the limiting dirtributions of the models. A parametric family of distributions is proposed for approximating life distribution~s whose hazard rate...12. always justified. But, because of this gener- ality, the possible limit laws for the maximum form a very large family . The

Application of Group-Level Item Response Models in the Evaluation of Consumer Reports about Health Plan Quality

ERIC Educational Resources Information Center

Reise, Steven P.; Meijer, Rob R.; Ainsworth, Andrew T.; Morales, Leo S.; Hays, Ron D.

2006-01-01

Group-level parametric and non-parametric item response theory models were applied to the Consumer Assessment of Healthcare Providers and Systems (CAHPS[R]) 2.0 core items in a sample of 35,572 Medicaid recipients nested within 131 health plans. Results indicated that CAHPS responses are dominated by within health plan variation, and only weakly…

Teaching Mathematics with Intelligent Support in Natural Language. Tertiary Education Students Working with Parametrized Modelling Activities

ERIC Educational Resources Information Center

Rojano, Teresa; García-Campos, Montserrat

2017-01-01

This article reports the outcomes of a study that seeks to investigate the role of feedback, by way of an intelligent support system in natural language, in parametrized modelling activities carried out by a group of tertiary education students. With such a system, it is possible to simultaneously display on a computer screen a dialogue window and…

Large-scale subject-specific cerebral arterial tree modeling using automated parametric mesh generation for blood flow simulation.

PubMed

Ghaffari, Mahsa; Tangen, Kevin; Alaraj, Ali; Du, Xinjian; Charbel, Fady T; Linninger, Andreas A

2017-12-01

In this paper, we present a novel technique for automatic parametric mesh generation of subject-specific cerebral arterial trees. This technique generates high-quality and anatomically accurate computational meshes for fast blood flow simulations extending the scope of 3D vascular modeling to a large portion of cerebral arterial trees. For this purpose, a parametric meshing procedure was developed to automatically decompose the vascular skeleton, extract geometric features and generate hexahedral meshes using a body-fitted coordinate system that optimally follows the vascular network topology. To validate the anatomical accuracy of the reconstructed vasculature, we performed statistical analysis to quantify the alignment between parametric meshes and raw vascular images using receiver operating characteristic curve. Geometric accuracy evaluation showed an agreement with area under the curves value of 0.87 between the constructed mesh and raw MRA data sets. Parametric meshing yielded on-average, 36.6% and 21.7% orthogonal and equiangular skew quality improvement over the unstructured tetrahedral meshes. The parametric meshing and processing pipeline constitutes an automated technique to reconstruct and simulate blood flow throughout a large portion of the cerebral arterial tree down to the level of pial vessels. This study is the first step towards fast large-scale subject-specific hemodynamic analysis for clinical applications. Copyright © 2017 Elsevier Ltd. All rights reserved.

Wave Attenuation and Gas Exchange Velocity in Marginal Sea Ice Zone

NASA Astrophysics Data System (ADS)

Bigdeli, A.; Hara, T.; Loose, B.; Nguyen, A. T.

2018-03-01

The gas transfer velocity in marginal sea ice zones exerts a strong control on the input of anthropogenic gases into the ocean interior. In this study, a sea state-dependent gas exchange parametric model is developed based on the turbulent kinetic energy dissipation rate. The model is tuned to match the conventional gas exchange parametrization in fetch-unlimited, fully developed seas. Next, fetch limitation is introduced in the model and results are compared to fetch limited experiments in lakes, showing that the model captures the effects of finite fetch on gas exchange with good fidelity. Having validated the results in fetch limited waters such as lakes, the model is next applied in sea ice zones using an empirical relation between the sea ice cover and the effective fetch, while accounting for the sea ice motion effect that is unique to sea ice zones. The model results compare favorably with the available field measurements. Applying this parametric model to a regional Arctic numerical model, it is shown that, under the present conditions, gas flux into the Arctic Ocean may be overestimated by 10% if a conventional parameterization is used.

Metabolic Therapy for Temporal Lobe Epilepsy in a Dish: Investigating Mechanisms of Ketogenic Diet using Electrophysiological Recordings in Hippocampal Slices

PubMed Central

Kawamura, Masahito Jr.; Ruskin, David N.; Masino, Susan A.

2016-01-01

The hippocampus is prone to epileptic seizures and is a key brain region and experimental platform for investigating mechanisms associated with the abnormal neuronal excitability that characterizes a seizure. Accordingly, the hippocampal slice is a common in vitro model to study treatments that may prevent or reduce seizure activity. The ketogenic diet is a metabolic therapy used to treat epilepsy in adults and children for nearly 100 years; it can reduce or eliminate even severe or refractory seizures. New insights into its underlying mechanisms have been revealed by diverse types of electrophysiological recordings in hippocampal slices. Here we review these reports and their relevant mechanistic findings. We acknowledge that a major difficulty in using hippocampal slices is the inability to reproduce precisely the in vivo condition of ketogenic diet feeding in any in vitro preparation, and progress has been made in this in vivo/in vitro transition. Thus far at least three different approaches are reported to reproduce relevant diet effects in the hippocampal slices: (1) direct application of ketone bodies; (2) mimicking the ketogenic diet condition during a whole-cell patch-clamp technique; and (3) reduced glucose incubation of hippocampal slices from ketogenic diet–fed animals. Significant results have been found with each of these methods and provide options for further study into short- and long-term mechanisms including Adenosine triphosphate (ATP)-sensitive potassium (KATP) channels, vesicular glutamate transporter (VGLUT), pannexin channels and adenosine receptors underlying ketogenic diet and other forms of metabolic therapy. PMID:27847463

Solenoid transport of beams with current-dependent initial conditions

DOE PAGES

Harris, J. R.; Poole, B. R.; Lewellen, J. W.

2017-09-06

We present that intense charged particle beams will generally be formed with an initial correlation between their longitudinal properties, including longitudinal variations in current, and their transverse properties, including their radius and divergence. This is due to the competition between the transverse focusing fields in the beam source and the time-varying space charge forces in the beam. In DC electron guns where the current modulation is slow compared to the electron transit time, the nature of these correlations was previously shown to depend on the gun geometry, exhibiting a linear dependence of the beam radius and divergence on the beammore » current at the gun exit. Here, we extend the previous work to study the transport of beams with such correlation in uniform and periodic solenoid channels. For each transport channel configuration studied, the transverse envelope equation is used to calculate the envelope of 101 beam slices differing in their slice currents, as well as initial radius and divergence (due to their dependence on slice current). For each channel configuration, these calculations are performed 546 times, with each of these iterations considering a different degree of correlation between the radius and divergence, and the slice current. It is found that some degree of correlation between the initial radius and slice current actually aids in beam transport, and the required strength of correlation can be estimated with simple models. Finally, increasing the degree of correlation between the initial divergence and slice current is generally counterproductive, and the degree of sensitivity to such correlations depends on the design of the transport channel.« less

Solenoid transport of beams with current-dependent initial conditions

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

Harris, J. R.; Poole, B. R.; Lewellen, J. W.

We present that intense charged particle beams will generally be formed with an initial correlation between their longitudinal properties, including longitudinal variations in current, and their transverse properties, including their radius and divergence. This is due to the competition between the transverse focusing fields in the beam source and the time-varying space charge forces in the beam. In DC electron guns where the current modulation is slow compared to the electron transit time, the nature of these correlations was previously shown to depend on the gun geometry, exhibiting a linear dependence of the beam radius and divergence on the beammore » current at the gun exit. Here, we extend the previous work to study the transport of beams with such correlation in uniform and periodic solenoid channels. For each transport channel configuration studied, the transverse envelope equation is used to calculate the envelope of 101 beam slices differing in their slice currents, as well as initial radius and divergence (due to their dependence on slice current). For each channel configuration, these calculations are performed 546 times, with each of these iterations considering a different degree of correlation between the radius and divergence, and the slice current. It is found that some degree of correlation between the initial radius and slice current actually aids in beam transport, and the required strength of correlation can be estimated with simple models. Finally, increasing the degree of correlation between the initial divergence and slice current is generally counterproductive, and the degree of sensitivity to such correlations depends on the design of the transport channel.« less

Analysis of survival in breast cancer patients by using different parametric models

NASA Astrophysics Data System (ADS)

Enera Amran, Syahila; Asrul Afendi Abdullah, M.; Kek, Sie Long; Afiqah Muhamad Jamil, Siti

2017-09-01

In biomedical applications or clinical trials, right censoring was often arising when studying the time to event data. In this case, some individuals are still alive at the end of the study or lost to follow up at a certain time. It is an important issue to handle the censoring data in order to prevent any bias information in the analysis. Therefore, this study was carried out to analyze the right censoring data with three different parametric models; exponential model, Weibull model and log-logistic models. Data of breast cancer patients from Hospital Sultan Ismail, Johor Bahru from 30 December 2008 until 15 February 2017 was used in this study to illustrate the right censoring data. Besides, the covariates included in this study are the time of breast cancer infection patients survive t, age of each patients X1 and treatment given to the patients X2 . In order to determine the best parametric models in analysing survival of breast cancer patients, the performance of each model was compare based on Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and log-likelihood value using statistical software R. When analysing the breast cancer data, all three distributions were shown consistency of data with the line graph of cumulative hazard function resembles a straight line going through the origin. As the result, log-logistic model was the best fitted parametric model compared with exponential and Weibull model since it has the smallest value in AIC and BIC, also the biggest value in log-likelihood.

Development and Validation of a Statistical Shape Modeling-Based Finite Element Model of the Cervical Spine Under Low-Level Multiple Direction Loading Conditions

PubMed Central

Bredbenner, Todd L.; Eliason, Travis D.; Francis, W. Loren; McFarland, John M.; Merkle, Andrew C.; Nicolella, Daniel P.

2014-01-01

Cervical spinal injuries are a significant concern in all trauma injuries. Recent military conflicts have demonstrated the substantial risk of spinal injury for the modern warfighter. Finite element models used to investigate injury mechanisms often fail to examine the effects of variation in geometry or material properties on mechanical behavior. The goals of this study were to model geometric variation for a set of cervical spines, to extend this model to a parametric finite element model, and, as a first step, to validate the parametric model against experimental data for low-loading conditions. Individual finite element models were created using cervical spine (C3–T1) computed tomography data for five male cadavers. Statistical shape modeling (SSM) was used to generate a parametric finite element model incorporating variability of spine geometry, and soft-tissue material property variation was also included. The probabilistic loading response of the parametric model was determined under flexion-extension, axial rotation, and lateral bending and validated by comparison to experimental data. Based on qualitative and quantitative comparison of the experimental loading response and model simulations, we suggest that the model performs adequately under relatively low-level loading conditions in multiple loading directions. In conclusion, SSM methods coupled with finite element analyses within a probabilistic framework, along with the ability to statistically validate the overall model performance, provide innovative and important steps toward describing the differences in vertebral morphology, spinal curvature, and variation in material properties. We suggest that these methods, with additional investigation and validation under injurious loading conditions, will lead to understanding and mitigating the risks of injury in the spine and other musculoskeletal structures. PMID:25506051

Empirical study of the dependence of the results of multivariable flexible survival analyses on model selection strategy.

PubMed

Binquet, C; Abrahamowicz, M; Mahboubi, A; Jooste, V; Faivre, J; Bonithon-Kopp, C; Quantin, C

2008-12-30

Flexible survival models, which avoid assumptions about hazards proportionality (PH) or linearity of continuous covariates effects, bring the issues of model selection to a new level of complexity. Each 'candidate covariate' requires inter-dependent decisions regarding (i) its inclusion in the model, and representation of its effects on the log hazard as (ii) either constant over time or time-dependent (TD) and, for continuous covariates, (iii) either loglinear or non-loglinear (NL). Moreover, 'optimal' decisions for one covariate depend on the decisions regarding others. Thus, some efficient model-building strategy is necessary.We carried out an empirical study of the impact of the model selection strategy on the estimates obtained in flexible multivariable survival analyses of prognostic factors for mortality in 273 gastric cancer patients. We used 10 different strategies to select alternative multivariable parametric as well as spline-based models, allowing flexible modeling of non-parametric (TD and/or NL) effects. We employed 5-fold cross-validation to compare the predictive ability of alternative models.All flexible models indicated significant non-linearity and changes over time in the effect of age at diagnosis. Conventional 'parametric' models suggested the lack of period effect, whereas more flexible strategies indicated a significant NL effect. Cross-validation confirmed that flexible models predicted better mortality. The resulting differences in the 'final model' selected by various strategies had also impact on the risk prediction for individual subjects.Overall, our analyses underline (a) the importance of accounting for significant non-parametric effects of covariates and (b) the need for developing accurate model selection strategies for flexible survival analyses. Copyright 2008 John Wiley & Sons, Ltd.

Long-range parametric amplification of THz wave with absorption loss exceeding parametric gain.

PubMed

Wang, Tsong-Dong; Huang, Yen-Chieh; Chuang, Ming-Yun; Lin, Yen-Hou; Lee, Ching-Han; Lin, Yen-Yin; Lin, Fan-Yi; Kitaeva, Galiya Kh

2013-01-28

Optical parametric mixing is a popular scheme to generate an idler wave at THz frequencies, although the THz wave is often absorbing in the nonlinear optical material. It is widely suggested that the useful material length for co-directional parametric mixing with strong THz-wave absorption is comparable to the THz-wave absorption length in the material. Here we show that, even in the limit of the absorption loss exceeding parametric gain, the THz idler wave can grows monotonically from optical parametric amplification over a much longer distance in a nonlinear optical material until pump depletion. The coherent production of the non-absorbing signal wave can assist the growth of the highly absorbing idler wave. We also show that, for the case of an equal input pump and signal in difference frequency generation, the quick saturation of the THz idler wave predicted from a much simplified and yet popular plane-wave model fails when fast diffraction of the THz wave from the co-propagating optical mixing waves is considered.

Grating lobe elimination in steerable parametric loudspeaker.

PubMed

Shi, Chuang; Gan, Woon-Seng

2011-02-01

In the past two decades, the majority of research on the parametric loudspeaker has concentrated on the nonlinear modeling of acoustic propagation and pre-processing techniques to reduce nonlinear distortion in sound reproduction. There are, however, very few studies on directivity control of the parametric loudspeaker. In this paper, we propose an equivalent circular Gaussian source array that approximates the directivity characteristics of the linear ultrasonic transducer array. By using this approximation, the directivity of the sound beam from the parametric loudspeaker can be predicted by the product directivity principle. New theoretical results, which are verified through measurements, are presented to show the effectiveness of the delay-and-sum beamsteering structure for the parametric loudspeaker. Unlike the conventional loudspeaker array, where the spacing between array elements must be less than half the wavelength to avoid spatial aliasing, the parametric loudspeaker can take advantage of grating lobe elimination to extend the spacing of ultrasonic transducer array to more than 1.5 wavelengths in a typical application.

Current economic and sensitivity analysis for ID slicing of 4 inch and 6 inch diameter silicon ingots for photovoltaic applications

NASA Technical Reports Server (NTRS)

Roberts, E. G.; Johnson, C. M.

1982-01-01

The economics and sensitivities of slicing large diameter silicon ingots for photovoltaic applications were examined. Current economics and slicing add on cost sensitivities are calculated using variable parameters for blade life, slicing yield, and slice cutting speed. It is indicated that cutting speed has the biggest impact on slicing add on cost, followed by slicing yield, and by blade life as the blade life increases.

Differentiation of dried sea cucumber products from different geographical areas by surface desorption atmospheric pressure chemical ionization mass spectrometry.

PubMed

Wu, Zhongchen; Chen, Huanwen; Wang, Weiling; Jia, Bin; Yang, Tianlin; Zhao, Zhanfeng; Ding, Jianhua; Xiao, Xuxian

2009-10-28

Without any sample pretreatment, mass spectral fingerprints of 486 dried sea cucumber slices were rapidly recorded in the mass range of m/z 50-800 by using surface desorption atmospheric pressure chemical ionization mass spectrometry (DAPCI-MS). A set of 162 individual sea cucumbers (Apostichopus japonicus Selenka) grown up in 3 different geographical regions (Weihai: 59 individuals, 177 slices; Yantai: 53 individuals, 159 slices; Dalian: 50 individuals, 150 slices;) in north China sea were successfully differentiated according to their habitats both by Principal Components Analysis (PCA) and Soft Independent Modeling of Class Analogy (SIMCA) of the mass spectral raw data, demonstrating that DAPCI-MS is a practically convenient tool for high-throughput differentiation of sea cucumber products. It has been found that the difference between the body wall tissue and the epidermal tissue is heavily dependent on the habitats. The experimental data also show that the roughness of the sample surface contributes to the variance of the signal levels in a certain extent, but such variance does not fail the differentiation of the dried sea cucumber samples.

Automatic segmentation of left ventricle in cardiac cine MRI images based on deep learning

NASA Astrophysics Data System (ADS)

Zhou, Tian; Icke, Ilknur; Dogdas, Belma; Parimal, Sarayu; Sampath, Smita; Forbes, Joseph; Bagchi, Ansuman; Chin, Chih-Liang; Chen, Antong

2017-02-01

In developing treatment of cardiovascular diseases, short axis cine MRI has been used as a standard technique for understanding the global structural and functional characteristics of the heart, e.g. ventricle dimensions, stroke volume and ejection fraction. To conduct an accurate assessment, heart structures need to be segmented from the cine MRI images with high precision, which could be a laborious task when performed manually. Herein a fully automatic framework is proposed for the segmentation of the left ventricle from the slices of short axis cine MRI scans of porcine subjects using a deep learning approach. For training the deep learning models, which generally requires a large set of data, a public database of human cine MRI scans is used. Experiments on the 3150 cine slices of 7 porcine subjects have shown that when comparing the automatic and manual segmentations the mean slice-wise Dice coefficient is about 0.930, the point-to-curve error is 1.07 mm, and the mean slice-wise Hausdorff distance is around 3.70 mm, which demonstrates the accuracy and robustness of the proposed inter-species translational approach.

Multi-state modelling of repeated hospitalisation and death in patients with heart failure: The use of large administrative databases in clinical epidemiology.

PubMed

Ieva, Francesca; Jackson, Christopher H; Sharples, Linda D

2017-06-01

In chronic diseases like heart failure (HF), the disease course and associated clinical event histories for the patient population vary widely. To improve understanding of the prognosis of patients and enable health care providers to assess and manage resources, we wish to jointly model disease progression, mortality and their relation with patient characteristics. We show how episodes of hospitalisation for disease-related events, obtained from administrative data, can be used as a surrogate for disease status. We propose flexible multi-state models for serial hospital admissions and death in HF patients, that are able to accommodate important features of disease progression, such as multiple ordered events and competing risks. Fully parametric and semi-parametric semi-Markov models are implemented using freely available software in R. The models were applied to a dataset from the administrative data bank of the Lombardia region in Northern Italy, which included 15,298 patients who had a first hospitalisation ending in 2006 and 4 years of follow-up thereafter. This provided estimates of the associations of age and gender with rates of hospital admission and length of stay in hospital, and estimates of the expected total time spent in hospital over five years. For example, older patients and men were readmitted more frequently, though the total time in hospital was roughly constant with age. We also discuss the relative merits of parametric and semi-parametric multi-state models, and model assessment and comparison.

Model selection criterion in survival analysis

NASA Astrophysics Data System (ADS)

Karabey, Uǧur; Tutkun, Nihal Ata

2017-07-01

Survival analysis deals with time until occurrence of an event of interest such as death, recurrence of an illness, the failure of an equipment or divorce. There are various survival models with semi-parametric or parametric approaches used in medical, natural or social sciences. The decision on the most appropriate model for the data is an important point of the analysis. In literature Akaike information criteria or Bayesian information criteria are used to select among nested models. In this study,the behavior of these information criterion is discussed for a real data set.

Scalability of the muscular action in a parametric 3D model of the index finger.

PubMed

Sancho-Bru, Joaquín L; Vergara, Margarita; Rodríguez-Cervantes, Pablo-Jesús; Giurintano, David J; Pérez-González, Antonio

2008-01-01

A method for scaling the muscle action is proposed and used to achieve a 3D inverse dynamic model of the human finger with all its components scalable. This method is based on scaling the physiological cross-sectional area (PCSA) in a Hill muscle model. Different anthropometric parameters and maximal grip force data have been measured and their correlations have been analyzed and used for scaling the PCSA of each muscle. A linear relationship between the normalized PCSA and the product of the length and breadth of the hand has been finally used for scaling, with a slope of 0.01315 cm(-2), with the length and breadth of the hand expressed in centimeters. The parametric muscle model has been included in a parametric finger model previously developed by the authors, and it has been validated reproducing the results of an experiment in which subjects from different population groups exerted maximal voluntary forces with their index finger in a controlled posture.

A New Program Structuring Mechanism Based on Layered Graphs.

DTIC Science & Technology

1984-12-01

which is a single-page diagram. Diagrams are constructed from some 40 symbols , chiefly A- boxes, arrows and annotations. A single model specifies a...are identified and used in describing it. 20The symbol "G" derives from the original use of the term "group" for "object slice". Since Ŕ" is already an...overloaded mathematical symbol , retaining "G" seems as good as any alternative. 21The names object slices and views reflect the interpretation placed

Model for nucleon valence structure functions at all x, all p ⊥ and all Q 2 from the correspondence between QCD and DTU

NASA Astrophysics Data System (ADS)

Cohen-Tannoudji, G.; El Hassouni, A.; Mantrach, A.; Oudrhiri-Safiani, E. G.

1982-09-01

We propose a simple parametrization of the nucleon valence structure functions at all x, all p ⊥ and all Q 2. We use the DTU parton model to fix the parametrization at a reference point ( Q {0/2}=3 GeV2) and we mimic the QCD evolution by replacing the dimensioned parameters of the DTU parton model by functions depending on Q 2. Excellent agreement is obtained with existing data.

Spectacle and SpecViz: New Spectral Analysis and Visualization Tools

NASA Astrophysics Data System (ADS)

Earl, Nicholas; Peeples, Molly; JDADF Developers

2018-01-01

A new era of spectroscopic exploration of our universe is being ushered in with advances in instrumentation and next-generation space telescopes. The advent of new spectroscopic instruments has highlighted a pressing need for tools scientists can use to analyze and explore these new data. We have developed Spectacle, a software package for analyzing both synthetic spectra from hydrodynamic simulations as well as real COS data with an aim of characterizing the behavior of the circumgalactic medium. It allows easy reduction of spectral data and analytic line generation capabilities. Currently, the package is focused on automatic determination of absorption regions and line identification with custom line list support, simultaneous line fitting using Voigt profiles via least-squares or MCMC methods, and multi-component modeling of blended features. Non-parametric measurements, such as equivalent widths, delta v90, and full-width half-max are available. Spectacle also provides the ability to compose compound models used to generate synthetic spectra allowing the user to define various LSF kernels, uncertainties, and to specify sampling.We also present updates to the visualization tool SpecViz, developed in conjunction with the JWST data analysis tools development team, to aid in the exploration of spectral data. SpecViz is an open source, Python-based spectral 1-D interactive visualization and analysis application built around high-performance interactive plotting. It supports handling general and instrument-specific data and includes advanced tool-sets for filtering and detrending one-dimensional data, along with the ability to isolate absorption regions using slicing and manipulate spectral features via spectral arithmetic. Multi-component modeling is also possible using a flexible model fitting tool-set that supports custom models to be used with various fitting routines. It also features robust user extensions such as custom data loaders and support for user-created plugins that add new functionality.This work was supported in part by HST AR #13919, HST GO #14268, and HST AR #14560.

Light-weight Parallel Python Tools for Earth System Modeling Workflows

NASA Astrophysics Data System (ADS)

Mickelson, S. A.; Paul, K.; Xu, H.; Dennis, J.; Brown, D. I.

2015-12-01

With the growth in computing power over the last 30 years, earth system modeling codes have become increasingly data-intensive. As an example, it is expected that the data required for the next Intergovernmental Panel on Climate Change (IPCC) Assessment Report (AR6) will increase by more than 10x to an expected 25PB per climate model. Faced with this daunting challenge, developers of the Community Earth System Model (CESM) have chosen to change the format of their data for long-term storage from time-slice to time-series, in order to reduce the required download bandwidth needed for later analysis and post-processing by climate scientists. Hence, efficient tools are required to (1) perform the transformation of the data from time-slice to time-series format and to (2) compute climatology statistics, needed for many diagnostic computations, on the resulting time-series data. To address the first of these two challenges, we have developed a parallel Python tool for converting time-slice model output to time-series format. To address the second of these challenges, we have developed a parallel Python tool to perform fast time-averaging of time-series data. These tools are designed to be light-weight, be easy to install, have very few dependencies, and can be easily inserted into the Earth system modeling workflow with negligible disruption. In this work, we present the motivation, approach, and testing results of these two light-weight parallel Python tools, as well as our plans for future research and development.

The Efficiency of UVC Radiation in the Inactivation of
Listeria monocytogenes on Beef-Agar Food Models.

PubMed

Hamidi-Oskouei, Amir M; James, Christian; James, Stephen

2015-06-01

The aim of this study is to evaluate the effect of meat content and surface smoothness on the deactivation of Listeria monocytogenes in beef-agar food models achieved by shortwave ultraviolet (UVC) light. Food models with various meat contents were made using chopped beef slices and agar solution. Prepared models together with a Listeria selective agar (LSA) plate and a slice of cooked beef were inoculated with L. monocytogenes and then exposed to UVC light. Population of Listeria reduced to below the level of detection on the LSA plates. As the content of beef in the beef-agar models increased, more L. monocytogenes cells survived. Survival was greatest on the treated cooked slice of beef. To better understand the effect of surface irregularities, a white light interferometer was used to analyse the surface smoothness of beef-agar media and LSA plates. No correlation was observed between the surface roughness of seven out of nine types of produced beef-agar media and the degree of inactivation resulting from UVC radiation at the given dose, whereas, less bacterial cells were killed as beef content of the food models increased. The findings of the current study show that the chemical composition of the treated sample also plays an important role in pathogen resistance and survival, meaning that two samples with similar surface irregularities but different chemical composition might produce very different inactivation results when exposed to UVC light.

The Efficiency of UVC Radiation in the Inactivation of
Listeria monocytogenes on Beef-Agar Food Models

PubMed Central

James, Christian; James, Stephen

2015-01-01

Summary The aim of this study is to evaluate the effect of meat content and surface smoothness on the deactivation of Listeria monocytogenes in beef-agar food models achieved by shortwave ultraviolet (UVC) light. Food models with various meat contents were made using chopped beef slices and agar solution. Prepared models together with a Listeria selective agar (LSA) plate and a slice of cooked beef were inoculated with L. monocytogenes and then exposed to UVC light. Population of Listeria reduced to below the level of detection on the LSA plates. As the content of beef in the beef-agar models increased, more L. monocytogenes cells survived. Survival was greatest on the treated cooked slice of beef. To better understand the effect of surface irregularities, a white light interferometer was used to analyse the surface smoothness of beef-agar media and LSA plates. No correlation was observed between the surface roughness of seven out of nine types of produced beef-agar media and the degree of inactivation resulting from UVC radiation at the given dose, whereas, less bacterial cells were killed as beef content of the food models increased. The findings of the current study show that the chemical composition of the treated sample also plays an important role in pathogen resistance and survival, meaning that two samples with similar surface irregularities but different chemical composition might produce very different inactivation results when exposed to UVC light. PMID:27904353

Model-free estimation of the psychometric function

PubMed Central

Żychaluk, Kamila; Foster, David H.

2009-01-01

A subject's response to the strength of a stimulus is described by the psychometric function, from which summary measures, such as a threshold or slope, may be derived. Traditionally, this function is estimated by fitting a parametric model to the experimental data, usually the proportion of successful trials at each stimulus level. Common models include the Gaussian and Weibull cumulative distribution functions. This approach works well if the model is correct, but it can mislead if not. In practice, the correct model is rarely known. Here, a nonparametric approach based on local linear fitting is advocated. No assumption is made about the true model underlying the data, except that the function is smooth. The critical role of the bandwidth is identified, and its optimum value estimated by a cross-validation procedure. As a demonstration, seven vision and hearing data sets were fitted by the local linear method and by several parametric models. The local linear method frequently performed better and never worse than the parametric ones. Supplemental materials for this article can be downloaded from app.psychonomic-journals.org/content/supplemental. PMID:19633355

Parametric laws to model urban pollutant dispersion with a street network approach

NASA Astrophysics Data System (ADS)

Soulhac, L.; Salizzoni, P.; Mejean, P.; Perkins, R. J.

2013-03-01

This study discusses the reliability of the street network approach for pollutant dispersion modelling in urban areas. This is essentially based on a box model, with parametric relations that explicitly model the main phenomena that contribute to the street canyon ventilation: the mass exchanges between the street and the atmosphere, the pollutant advection along the street axes and the pollutant transfer at street intersections. In the first part of the paper the focus is on the development of a model for the bulk transfer street/atmosphere, which represents the main ventilation mechanisms for wind direction that are almost perpendicular to the axis of the street. We then discuss the role of the advective transfer along the street axis on its ventilation, depending on the length of the street and the direction of the external wind. Finally we evaluate the performances of a box model integrating parametric exchange laws for these transfer phenomena. To that purpose we compare the prediction of the model to wind tunnel experiments of pollutant dispersion within a street canyon placed in an idealised urban district.

Parametric Model Based On Imputations Techniques for Partly Interval Censored Data

NASA Astrophysics Data System (ADS)

Zyoud, Abdallah; Elfaki, F. A. M.; Hrairi, Meftah

2017-12-01

The term ‘survival analysis’ has been used in a broad sense to describe collection of statistical procedures for data analysis. In this case, outcome variable of interest is time until an event occurs where the time to failure of a specific experimental unit might be censored which can be right, left, interval, and Partly Interval Censored data (PIC). In this paper, analysis of this model was conducted based on parametric Cox model via PIC data. Moreover, several imputation techniques were used, which are: midpoint, left & right point, random, mean, and median. Maximum likelihood estimate was considered to obtain the estimated survival function. These estimations were then compared with the existing model, such as: Turnbull and Cox model based on clinical trial data (breast cancer data), for which it showed the validity of the proposed model. Result of data set indicated that the parametric of Cox model proved to be more superior in terms of estimation of survival functions, likelihood ratio tests, and their P-values. Moreover, based on imputation techniques; the midpoint, random, mean, and median showed better results with respect to the estimation of survival function.

Blind identification of nonlinear models with non-Gaussian inputs

NASA Astrophysics Data System (ADS)

Prakriya, Shankar; Pasupathy, Subbarayan; Hatzinakos, Dimitrios

1995-12-01

Some methods are proposed for the blind identification of finite-order discrete-time nonlinear models with non-Gaussian circular inputs. The nonlinear models consist of two finite memory linear time invariant (LTI) filters separated by a zero-memory nonlinearity (ZMNL) of the polynomial type (the LTI-ZMNL-LTI models). The linear subsystems are allowed to be of non-minimum phase (NMP). The methods base their estimates of the impulse responses on slices of the N plus 1th order polyspectra of the output sequence. It is shown that the identification of LTI-ZMNL systems requires only a 1-D moment or polyspectral slice. The coefficients of the ZMNL are not estimated, and need not be known. The order of the nonlinearity can, in theory, be estimated from the received signal. These methods possess several noise and interference suppression characteristics, and have applications in modeling nonlinearly amplified QAM/QPSK signals in digital satellite and microwave communications.

Resolution of a Rank-Deficient Adjustment Model Via an Isomorphic Geometrical Setup with Tensor Structure.

DTIC Science & Technology

1987-03-01

would be transcribed as L =AX - V where L, X, and V are the vectors of constant terms, parametric corrections , and b_o bresiduals, respectively. The...tensor. a Just as du’ represents the parametric corrections in tensor notations, the necessary associated metric tensor a’ corresponds to the variance...observations, n residuals, and 0 n- parametric corrections to X (an initial set of parameters), respectively. b 0 b The vctor L is formed as 1. L where

Predicting ecosystem dynamics at regional scales: an evaluation of a terrestrial biosphere model for the forests of northeastern North America.

PubMed

Medvigy, David; Moorcroft, Paul R

2012-01-19

Terrestrial biosphere models are important tools for diagnosing both the current state of the terrestrial carbon cycle and forecasting terrestrial ecosystem responses to global change. While there are a number of ongoing assessments of the short-term predictive capabilities of terrestrial biosphere models using flux-tower measurements, to date there have been relatively few assessments of their ability to predict longer term, decadal-scale biomass dynamics. Here, we present the results of a regional-scale evaluation of the Ecosystem Demography version 2 (ED2)-structured terrestrial biosphere model, evaluating the model's predictions against forest inventory measurements for the northeast USA and Quebec from 1985 to 1995. Simulations were conducted using a default parametrization, which used parameter values from the literature, and a constrained model parametrization, which had been developed by constraining the model's predictions against 2 years of measurements from a single site, Harvard Forest (42.5° N, 72.1° W). The analysis shows that the constrained model parametrization offered marked improvements over the default model formulation, capturing large-scale variation in patterns of biomass dynamics despite marked differences in climate forcing, land-use history and species-composition across the region. These results imply that data-constrained parametrizations of structured biosphere models such as ED2 can be successfully used for regional-scale ecosystem prediction and forecasting. We also assess the model's ability to capture sub-grid scale heterogeneity in the dynamics of biomass growth and mortality of different sizes and types of trees, and then discuss the implications of these analyses for further reducing the remaining biases in the model's predictions.

Zero- vs. one-dimensional, parametric vs. non-parametric, and confidence interval vs. hypothesis testing procedures in one-dimensional biomechanical trajectory analysis.

PubMed

Pataky, Todd C; Vanrenterghem, Jos; Robinson, Mark A

2015-05-01

Biomechanical processes are often manifested as one-dimensional (1D) trajectories. It has been shown that 1D confidence intervals (CIs) are biased when based on 0D statistical procedures, and the non-parametric 1D bootstrap CI has emerged in the Biomechanics literature as a viable solution. The primary purpose of this paper was to clarify that, for 1D biomechanics datasets, the distinction between 0D and 1D methods is much more important than the distinction between parametric and non-parametric procedures. A secondary purpose was to demonstrate that a parametric equivalent to the 1D bootstrap exists in the form of a random field theory (RFT) correction for multiple comparisons. To emphasize these points we analyzed six datasets consisting of force and kinematic trajectories in one-sample, paired, two-sample and regression designs. Results showed, first, that the 1D bootstrap and other 1D non-parametric CIs were qualitatively identical to RFT CIs, and all were very different from 0D CIs. Second, 1D parametric and 1D non-parametric hypothesis testing results were qualitatively identical for all six datasets. Last, we highlight the limitations of 1D CIs by demonstrating that they are complex, design-dependent, and thus non-generalizable. These results suggest that (i) analyses of 1D data based on 0D models of randomness are generally biased unless one explicitly identifies 0D variables before the experiment, and (ii) parametric and non-parametric 1D hypothesis testing provide an unambiguous framework for analysis when one׳s hypothesis explicitly or implicitly pertains to whole 1D trajectories. Copyright © 2015 Elsevier Ltd. All rights reserved.

Developing Parametric Models for the Assembly of Machine Fixtures for Virtual Multiaxial CNC Machining Centers

NASA Astrophysics Data System (ADS)

Balaykin, A. V.; Bezsonov, K. A.; Nekhoroshev, M. V.; Shulepov, A. P.

2018-01-01

This paper dwells upon a variance parameterization method. Variance or dimensional parameterization is based on sketching, with various parametric links superimposed on the sketch objects and user-imposed constraints in the form of an equation system that determines the parametric dependencies. This method is fully integrated in a top-down design methodology to enable the creation of multi-variant and flexible fixture assembly models, as all the modeling operations are hierarchically linked in the built tree. In this research the authors consider a parameterization method of machine tooling used for manufacturing parts using multiaxial CNC machining centers in the real manufacturing process. The developed method allows to significantly reduce tooling design time when making changes of a part’s geometric parameters. The method can also reduce time for designing and engineering preproduction, in particular, for development of control programs for CNC equipment and control and measuring machines, automate the release of design and engineering documentation. Variance parameterization helps to optimize construction of parts as well as machine tooling using integrated CAE systems. In the framework of this study, the authors demonstrate a comprehensive approach to parametric modeling of machine tooling in the CAD package used in the real manufacturing process of aircraft engines.

Super learning to hedge against incorrect inference from arbitrary parametric assumptions in marginal structural modeling.

PubMed

Neugebauer, Romain; Fireman, Bruce; Roy, Jason A; Raebel, Marsha A; Nichols, Gregory A; O'Connor, Patrick J

2013-08-01

Clinical trials are unlikely to ever be launched for many comparative effectiveness research (CER) questions. Inferences from hypothetical randomized trials may however be emulated with marginal structural modeling (MSM) using observational data, but success in adjusting for time-dependent confounding and selection bias typically relies on parametric modeling assumptions. If these assumptions are violated, inferences from MSM may be inaccurate. In this article, we motivate the application of a data-adaptive estimation approach called super learning (SL) to avoid reliance on arbitrary parametric assumptions in CER. Using the electronic health records data from adults with new-onset type 2 diabetes, we implemented MSM with inverse probability weighting (IPW) estimation to evaluate the effect of three oral antidiabetic therapies on the worsening of glomerular filtration rate. Inferences from IPW estimation were noticeably sensitive to the parametric assumptions about the associations between both the exposure and censoring processes and the main suspected source of confounding, that is, time-dependent measurements of hemoglobin A1c. SL was successfully implemented to harness flexible confounding and selection bias adjustment from existing machine learning algorithms. Erroneous IPW inference about clinical effectiveness because of arbitrary and incorrect modeling decisions may be avoided with SL. Copyright © 2013 Elsevier Inc. All rights reserved.

Estimating the number and size of phloem sieve plate pores using longitudinal views and geometric reconstruction.

PubMed

Bussières, Philippe

2014-05-12

Because it is difficult to obtain transverse views of the plant phloem sieve plate pores, which are short tubes, to estimate their number and diameters, a method based on longitudinal views is proposed. This method uses recent methods to estimate the number and the sizes of approximately circular objects from their images, given by slices perpendicular to the objects. Moreover, because such longitudinal views are obtained from slices that are rather close to the plate centres whereas the pore size may vary with the pore distance from the plate edge, a sieve plate reconstruction model was developed and incorporated in the method to consider this bias. The method was successfully tested with published longitudinal views of phloem of Soybean and an exceptional entire transverse view from the same tissue. The method was also validated with simulated slices in two sieve plates from Cucurbita and Phaseolus. This method will likely be useful to estimate and to model the hydraulic conductivity and the architecture of the plant phloem, and it could have applications for other materials with approximately cylindrical structures.

PARAMETRIC DISTANCE WEIGHTING OF LANDSCAPE INFLUENCE ON STREAMS

EPA Science Inventory

We present a parametric model for estimating the areas within watersheds whose land use best predicts indicators of stream ecological condition. We regress a stream response variable on the distance-weighted proportion of watershed area that has a specific land use, such as agric...

More than the sum of its parts: Coarse-grained peptide-lipid interactions from a simple cross-parametrization

NASA Astrophysics Data System (ADS)

Bereau, Tristan; Wang, Zun-Jing; Deserno, Markus

2014-03-01

Interfacial systems are at the core of fascinating phenomena in many disciplines, such as biochemistry, soft-matter physics, and food science. However, the parametrization of accurate, reliable, and consistent coarse-grained (CG) models for systems at interfaces remains a challenging endeavor. In the present work, we explore to what extent two independently developed solvent-free CG models of peptides and lipids—of different mapping schemes, parametrization methods, target functions, and validation criteria—can be combined by only tuning the cross-interactions. Our results show that the cross-parametrization can reproduce a number of structural properties of membrane peptides (for example, tilt and hydrophobic mismatch), in agreement with existing peptide-lipid CG force fields. We find encouraging results for two challenging biophysical problems: (i) membrane pore formation mediated by the cooperative action of several antimicrobial peptides, and (ii) the insertion and folding of the helix-forming peptide WALP23 in the membrane.

Plastome-wide comparison reveals new SNV resources for the authentication of Dendrobium huoshanense and its corresponding medicinal slice (Huoshan Fengdou).

PubMed

Niu, Zhitao; Pan, Jiajia; Xue, Qingyun; Zhu, Shuying; Liu, Wei; Ding, Xiaoyu

2018-05-01

Dendrobium species and their corresponding medicinal slices have been extensively used as traditional Chinese medicine (TCM) in many Asian countries. However, it is extremely difficult to identify Dendrobium species based on their morphological and chemical features. In this study, the plastomes of D. huoshanense were used as a model system to investigate the hypothesis that plastomic mutational hotspot regions could provide a useful single nucleotide variants (SNVs) resource for authentication studies. We surveyed the plastomes of 17 Dendrobium species, including the newly sequenced plastome of D. huoshanense . A total of 19 SNVs that could be used for the authentication of D. huoshanense were detected. On the basis of this comprehensive comparison, we identified the four most informative hotspot regions in the Dendrobium plastome that encompass ccsA to ndhF , matK to 3'trnG , rpoB to psbD, and trnT to rbcL . Furthermore, to established a simple and accurate method for the authentication of D. huoshanense and its medicinal slices, a total of 127 samples from 20 Dendrobium species including their corresponding medicinal slices (Fengdous) were used in this study. Our results suggest that D. huoshanense and its medicinal slices can be rapidly and unequivocally identified using this method that combines real-time PCR with the amplification refractory mutation system (ARMS).

Hexose transport by brain slices: further studies on energy dependence

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

Kyle-Lillegard, J.; Gold, B.I.

1983-04-01

We studied the uptake of (/sup 3/H)2-deoxyglucose ((/sup 3/H)2DG) by slices of rat cerebral cortex in vitro as a model of glucose transport by brain. Slices were incubated with (/sup 3/H)2DG, or with L-(/sup 3/H)glucose as a marker for diffusion; the difference between (/sup 3/H)2DG uptake and L-(/sup 3/H)glucose uptake was defined as net (/sup 3/H)2DG transport. Net (/sup 3/H)2DG transport was a function of incubation temperature, with an estimated temperature coefficient of 1.87 from 15 degrees C to 25 degrees C. The net uptake of (/sup 3/H)2DG was not inhibited by phlorizin or phloretin in concentrations well above themore » reported Ki of these inhibitors for hexose uptake in other systems. To examine the hypothesis that (/sup 3/H)2DG transport by brain slices is dependent on mitochondrial energy, we studied net (/sup 3/H)2DG uptake by slices which had been preincubated in media designed to alter intracellular ATP stores. The transport process was very sensitive to inhibition by DNP, but the correlation between (/sup 3/H)2DG transport and ATP levels was unclear. In contrast to our published hypothesis that the transport process required mitochondrial energy, these data indicate that dependence on energy is not absolute.« less

Parametric instability of shaft with discs

NASA Astrophysics Data System (ADS)

Wahab, A. M. Abdul; Rasid, Z. A.; Abu, A.; Rudin, N. F. Mohd Noor

2017-12-01

The occurrence of resonance is a major criterion to be considered in the design of shaft. While force resonance occurs merely when the natural frequency of the rotor system equals speed of the shaft, parametric resonance or parametric instability can occur at excitation speed that is integral or sub-multiple of the frequency of the rotor. This makes the study on parametric resonance crucial. Parametric instability of a shaft system consisting of a shaft and disks has been investigated in this study. The finite element formulation of the Mathieu-Hill equation that represents the parametric instability problem of the shaft is developed based on Timoshenko’s beam theory and Nelson’s finite element method (FEM) model that considers the effect of torsional motion on such problem. The Bolotin’s method is used to determine the regions of instability and the Strut-Ince diagram. The validation works show that the results of this study are in close agreement to past results. It is found that a larger radius of disk will cause the shaft to become more unstable compared to smaller radius although both weights are similar. Furthermore, the effect of torsional motion on the parametric instability of the shaft is significant at higher rotating speed.

Direct adaptive robust tracking control for 6 DOF industrial robot with enhanced accuracy.

PubMed

Yin, Xiuxing; Pan, Li

2018-01-01

A direct adaptive robust tracking control is proposed for trajectory tracking of 6 DOF industrial robot in the presence of parametric uncertainties, external disturbances and uncertain nonlinearities. The controller is designed based on the dynamic characteristics in the working space of the end-effector of the 6 DOF robot. The controller includes robust control term and model compensation term that is developed directly based on the input reference or desired motion trajectory. A projection-type parametric adaptation law is also designed to compensate for parametric estimation errors for the adaptive robust control. The feasibility and effectiveness of the proposed direct adaptive robust control law and the associated projection-type parametric adaptation law have been comparatively evaluated based on two 6 DOF industrial robots. The test results demonstrate that the proposed control can be employed to better maintain the desired trajectory tracking even in the presence of large parametric uncertainties and external disturbances as compared with PD controller and nonlinear controller. The parametric estimates also eventually converge to the real values along with the convergence of tracking errors, which further validate the effectiveness of the proposed parametric adaption law. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

An organotypic slice culture model of chronic white matter injury with maturation arrest of oligodendrocyte progenitors.

PubMed

Dean, Justin M; Riddle, Art; Maire, Jennifer; Hansen, Kelly D; Preston, Marnie; Barnes, Anthony P; Sherman, Larry S; Back, Stephen A

2011-07-05

CNS myelination disturbances commonly occur in chronic white matter lesions in neurodevelopmental and adult neurological disorders. Recent studies support that myelination failure can involve a disrupted cellular repair mechanism where oligodendrocyte (OL) progenitor cells (OPCs) proliferate in lesions with diffuse astrogliosis, but fail to fully differentiate to mature myelinating OLs. There are no in vitro models that reproduce these features of myelination failure. Forebrain coronal slices from postnatal day (P) 0.5/1 rat pups were cultured for 1, 5, or 9 days in vitro (DIV). Slices rapidly exhibited diffuse astrogliosis and accumulation of the extracellular matrix glycosaminoglycan hyaluronan (HA), an inhibitor of OPC differentiation and re-myelination. At 1 DIV ~1.5% of Olig2+ OLs displayed caspase-3 activation, which increased to ~11.5% by 9 DIV. At 1 DIV the density of PDGFRα+ and PDGFRα+/Ki67+ OPCs were significantly elevated compared to 0 DIV (P < 0.01). Despite this proliferative response, at 9 DIV ~60% of white matter OLs were late progenitors (preOLs), compared to ~7% in the postnatal day 10 rat (P < 0.0001), consistent with preOL maturation arrest. Addition of HA to slices significantly decreased the density of MBP+ OLs at 9 DIV compared to controls (217 ± 16 vs. 328 ± 17 cells/mm2, respectively; P = 0.0003), supporting an inhibitory role of HA in OL lineage progression in chronic lesions. Diffuse white matter astrogliosis and early OPC proliferation with impaired OL maturation were reproduced in this model of myelination failure. This system may be used to define mechanisms of OPC maturation arrest and myelination failure related to astrogliosis and HA accumulation.

Neuroprotective effect of the new thiadiazolidinone NP00111 against oxygen-glucose deprivation in rat hippocampal slices: implication of ERK1/2 and PPARgamma receptors.

PubMed

Rosa, Angelo O; Egea, Javier; Martínez, Ana; García, Antonio G; López, Manuela G

2008-07-01

Thiadiazolidinones (TDZDs) are small molecules that inhibit glycogen synthase kinase 3-beta (GSK3-beta) activity in a non competitive manner to ATP. NP00111, a new TDZD, besides causing inhibition of GSK-3beta, has also shown to be an agonist of PPARgamma . Since phosphorylation and consequent inhibition of GSK-3beta by PI-3K/Akt and agonism of PPARgamma have shown to afford neuroprotection in several in vitro and in vivo models, we have studied the potential neuroprotective effect of NP00111 in an "in vitro" model of ischemia-reperfusion. NP00111, at the concentration of 10 microM, significantly protected adult rat hippocampal slices subjected to oxygen and glucose deprivation (OGD) for 1 h followed by 3 h re-oxygenation, measured as lactic dehydrogenase (LDH) released to the extracellular media. The protective effects of NP00111 were more pronounced during the re-oxygenation period in comparison to the OGD period. Other GSK-3beta inhibitors like lithium or AR-A014418 did not afford protection in this model. However, the PPARgamma agonist rosiglitazone was protective at 3 microM. Protection afforded by NP00111 and rosiglitazone were prevented by the PPARgamma antagonist GW9662, suggesting that both NP00111 and rosiglitazone were preventing cell death caused by oxygen-glucose deprivation via activation of PPARgamma. NP00111 increased by two fold phosphorylation of ERK1/2 and its protective effects were lost when the hippocampal slices were co-incubated with the mitogen-activated protein kinase (MAPK) inhibitor PD98059. In conclusion, the novel TDZD NP00111 was protective against OGD in rat hippocampal slices by a mechanism related to phosphorylation of ERK1/2 via activation of PPARgamma.

Anal sphincter trauma and anal incontinence in urogynecological patients.

PubMed

Guzmán Rojas, R A; Kamisan Atan, I; Shek, K L; Dietz, H P

2015-09-01

To determine the prevalence of evidence of residual obstetric anal sphincter injury, to evaluate its association with anal incontinence (AI) and to establish minimal diagnostic criteria for significant (residual) external anal sphincter (EAS) trauma. This was a retrospective analysis of ultrasound volume datasets of 501 patients attending a tertiary urogynecological unit. All patients underwent a standardized interview including determination of St Mark's score for those presenting with AI. Tomographic ultrasound imaging (TUI) was used to evaluate the EAS and the internal anal sphincter (IAS). Among a total of 501 women, significant EAS and IAS defects were found in 88 and 59, respectively, and AI was reported by 69 (14%). Optimal prediction of AI was achieved using a model that included four abnormal slices of the EAS on TUI. IAS defects were found to be less likely to be associated with AI. In a multivariable model controlling for age and IAS trauma, the presence of at least four abnormal slices gave an 18-fold (95% CI, 9-36; P < 0.0001) increase in the likelihood of AI, compared with those with fewer than four abnormal slices. Using receiver-operating characteristics curve statistics, this model yielded an area under the curve of 0.86 (95% CI, 0.80-0.92). Both AI and significant EAS trauma are common in patients attending urogynecological units, and are strongly associated with each other. Abnormalities of the IAS seem to be less important in predicting AI. Our data support the practice of using, as a minimal criterion, defects present in four of the six slices on TUI for the diagnosis of significant EAS trauma. Copyright © 2015 ISUOG. Published by John Wiley & Sons Ltd.

Convergence optimization of parametric MLEM reconstruction for estimation of Patlak plot parameters.

PubMed

Angelis, Georgios I; Thielemans, Kris; Tziortzi, Andri C; Turkheimer, Federico E; Tsoumpas, Charalampos

2011-07-01

In dynamic positron emission tomography data many researchers have attempted to exploit kinetic models within reconstruction such that parametric images are estimated directly from measurements. This work studies a direct parametric maximum likelihood expectation maximization algorithm applied to [(18)F]DOPA data using reference-tissue input function. We use a modified version for direct reconstruction with a gradually descending scheme of subsets (i.e. 18-6-1) initialized with the FBP parametric image for faster convergence and higher accuracy. The results compared with analytic reconstructions show quantitative robustness (i.e. minimal bias) and clinical reproducibility within six human acquisitions in the region of clinical interest. Bland-Altman plots for all the studies showed sufficient quantitative agreement between the direct reconstructed parametric maps and the indirect FBP (--0.035x+0.48E--5). Copyright © 2011 Elsevier Ltd. All rights reserved.

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

Murphy, L.T.; Hickey, M.

This paper summarizes the progress to date by CH2M HILL and the UKAEA in development of a parametric modelling capability for estimating the costs of large nuclear decommissioning projects in the United Kingdom (UK) and Europe. The ability to successfully apply parametric cost estimating techniques will be a key factor to commercial success in the UK and European multi-billion dollar waste management, decommissioning and environmental restoration markets. The most useful parametric models will be those that incorporate individual components representing major elements of work: reactor decommissioning, fuel cycle facility decommissioning, waste management facility decommissioning and environmental restoration. Models must bemore » sufficiently robust to estimate indirect costs and overheads, permit pricing analysis and adjustment, and accommodate the intricacies of international monetary exchange, currency fluctuations and contingency. The development of a parametric cost estimating capability is also a key component in building a forward estimating strategy. The forward estimating strategy will enable the preparation of accurate and cost-effective out-year estimates, even when work scope is poorly defined or as yet indeterminate. Preparation of cost estimates for work outside the organizations current sites, for which detailed measurement is not possible and historical cost data does not exist, will also be facilitated. (authors)« less

Frustration of resonant preheating by exotic kinetic terms

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

Rahmati, Shohreh; Seahra, Sanjeev S., E-mail: srahmati@unb.ca, E-mail: sseahra@unb.ca

2014-10-01

We study the effects of exotic kinetic terms on parametric resonance during the preheating epoch of the early universe. Specifically, we consider modifications to the action of ordinary matter fields motivated by generalized uncertainty principles, polymer quantization, as well as Dirac-Born-Infeld and k-essence models. To leading order in an ''exotic physics'' scale, the equations of motion derived from each of these models have the same algebraic form involving a nonlinear self-interaction in the matter sector. Neglecting spatial dependence, we show that the nonlinearity effectively shuts down the parametric resonance after a finite time period. We find numeric evidence that themore » frustration of parametric resonance persists to spatially inhomogenous matter in (1+1)-dimensions.« less

Parametric Model of an Aerospike Rocket Engine

NASA Technical Reports Server (NTRS)

Korte, J. J.

2000-01-01

A suite of computer codes was assembled to simulate the performance of an aerospike engine and to generate the engine input for the Program to Optimize Simulated Trajectories. First an engine simulator module was developed that predicts the aerospike engine performance for a given mixture ratio, power level, thrust vectoring level, and altitude. This module was then used to rapidly generate the aerospike engine performance tables for axial thrust, normal thrust, pitching moment, and specific thrust. Parametric engine geometry was defined for use with the engine simulator module. The parametric model was also integrated into the iSIGHTI multidisciplinary framework so that alternate designs could be determined. The computer codes were used to support in-house conceptual studies of reusable launch vehicle designs.

Parametric Model of an Aerospike Rocket Engine

NASA Technical Reports Server (NTRS)

Korte, J. J.

2000-01-01

A suite of computer codes was assembled to simulate the performance of an aerospike engine and to generate the engine input for the Program to Optimize Simulated Trajectories. First an engine simulator module was developed that predicts the aerospike engine performance for a given mixture ratio, power level, thrust vectoring level, and altitude. This module was then used to rapidly generate the aerospike engine performance tables for axial thrust, normal thrust, pitching moment, and specific thrust. Parametric engine geometry was defined for use with the engine simulator module. The parametric model was also integrated into the iSIGHT multidisciplinary framework so that alternate designs could be determined. The computer codes were used to support in-house conceptual studies of reusable launch vehicle designs.

[Preparation of simulate craniocerebral models via three dimensional printing technique].

PubMed

Lan, Q; Chen, A L; Zhang, T; Zhu, Q; Xu, T

2016-08-09

Three dimensional (3D) printing technique was used to prepare the simulate craniocerebral models, which were applied to preoperative planning and surgical simulation. The image data was collected from PACS system. Image data of skull bone, brain tissue and tumors, cerebral arteries and aneurysms, and functional regions and relative neural tracts of the brain were extracted from thin slice scan (slice thickness 0.5 mm) of computed tomography (CT), magnetic resonance imaging (MRI, slice thickness 1mm), computed tomography angiography (CTA), and functional magnetic resonance imaging (fMRI) data, respectively. MIMICS software was applied to reconstruct colored virtual models by identifying and differentiating tissues according to their gray scales. Then the colored virtual models were submitted to 3D printer which produced life-sized craniocerebral models for surgical planning and surgical simulation. 3D printing craniocerebral models allowed neurosurgeons to perform complex procedures in specific clinical cases though detailed surgical planning. It offered great convenience for evaluating the size of spatial fissure of sellar region before surgery, which helped to optimize surgical approach planning. These 3D models also provided detailed information about the location of aneurysms and their parent arteries, which helped surgeons to choose appropriate aneurismal clips, as well as perform surgical simulation. The models further gave clear indications of depth and extent of tumors and their relationship to eloquent cortical areas and adjacent neural tracts, which were able to avoid surgical damaging of important neural structures. As a novel and promising technique, the application of 3D printing craniocerebral models could improve the surgical planning by converting virtual visualization into real life-sized models.It also contributes to functional anatomy study.

Predictive power of theoretical modelling of the nuclear mean field: examples of improving predictive capacities

NASA Astrophysics Data System (ADS)

Dedes, I.; Dudek, J.

2018-03-01

We examine the effects of the parametric correlations on the predictive capacities of the theoretical modelling keeping in mind the nuclear structure applications. The main purpose of this work is to illustrate the method of establishing the presence and determining the form of parametric correlations within a model as well as an algorithm of elimination by substitution (see text) of parametric correlations. We examine the effects of the elimination of the parametric correlations on the stabilisation of the model predictions further and further away from the fitting zone. It follows that the choice of the physics case and the selection of the associated model are of secondary importance in this case. Under these circumstances we give priority to the relative simplicity of the underlying mathematical algorithm, provided the model is realistic. Following such criteria, we focus specifically on an important but relatively simple case of doubly magic spherical nuclei. To profit from the algorithmic simplicity we chose working with the phenomenological spherically symmetric Woods–Saxon mean-field. We employ two variants of the underlying Hamiltonian, the traditional one involving both the central and the spin orbit potential in the Woods–Saxon form and the more advanced version with the self-consistent density-dependent spin–orbit interaction. We compare the effects of eliminating of various types of correlations and discuss the improvement of the quality of predictions (‘predictive power’) under realistic parameter adjustment conditions.

Modelling road accident blackspots data with the discrete generalized Pareto distribution.

PubMed

Prieto, Faustino; Gómez-Déniz, Emilio; Sarabia, José María

2014-10-01

This study shows how road traffic networks events, in particular road accidents on blackspots, can be modelled with simple probabilistic distributions. We considered the number of crashes and the number of fatalities on Spanish blackspots in the period 2003-2007, from Spanish General Directorate of Traffic (DGT). We modelled those datasets, respectively, with the discrete generalized Pareto distribution (a discrete parametric model with three parameters) and with the discrete Lomax distribution (a discrete parametric model with two parameters, and particular case of the previous model). For that, we analyzed the basic properties of both parametric models: cumulative distribution, survival, probability mass, quantile and hazard functions, genesis and rth-order moments; applied two estimation methods of their parameters: the μ and (μ+1) frequency method and the maximum likelihood method; used two goodness-of-fit tests: Chi-square test and discrete Kolmogorov-Smirnov test based on bootstrap resampling; and compared them with the classical negative binomial distribution in terms of absolute probabilities and in models including covariates. We found that those probabilistic models can be useful to describe the road accident blackspots datasets analyzed. Copyright © 2014 Elsevier Ltd. All rights reserved.

A shape-based statistical method to retrieve 2D TRUS-MR slice correspondence for prostate biopsy

NASA Astrophysics Data System (ADS)

Mitra, Jhimli; Srikantha, Abhilash; Sidibé, Désiré; Martí, Robert; Oliver, Arnau; Lladó, Xavier; Ghose, Soumya; Vilanova, Joan C.; Comet, Josep; Meriaudeau, Fabrice

2012-02-01

This paper presents a method based on shape-context and statistical measures to match interventional 2D Trans Rectal Ultrasound (TRUS) slice during prostate biopsy to a 2D Magnetic Resonance (MR) slice of a pre-acquired prostate volume. Accurate biopsy tissue sampling requires translation of the MR slice information on the TRUS guided biopsy slice. However, this translation or fusion requires the knowledge of the spatial position of the TRUS slice and this is only possible with the use of an electro-magnetic (EM) tracker attached to the TRUS probe. Since, the use of EM tracker is not common in clinical practice and 3D TRUS is not used during biopsy, we propose to perform an analysis based on shape and information theory to reach close enough to the actual MR slice as validated by experts. The Bhattacharyya distance is used to find point correspondences between shape-context representations of the prostate contours. Thereafter, Chi-square distance is used to find out those MR slices where the prostates closely match with that of the TRUS slice. Normalized Mutual Information (NMI) values of the TRUS slice with each of the axial MR slices are computed after rigid alignment and consecutively a strategic elimination based on a set of rules between the Chi-square distances and the NMI leads to the required MR slice. We validated our method for TRUS axial slices of 15 patients, of which 11 results matched at least one experts validation and the remaining 4 are at most one slice away from the expert validations.

Hybrid pathwise sensitivity methods for discrete stochastic models of chemical reaction systems

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

Wolf, Elizabeth Skubak, E-mail: ewolf@saintmarys.edu; Anderson, David F., E-mail: anderson@math.wisc.edu

2015-01-21

Stochastic models are often used to help understand the behavior of intracellular biochemical processes. The most common such models are continuous time Markov chains (CTMCs). Parametric sensitivities, which are derivatives of expectations of model output quantities with respect to model parameters, are useful in this setting for a variety of applications. In this paper, we introduce a class of hybrid pathwise differentiation methods for the numerical estimation of parametric sensitivities. The new hybrid methods combine elements from the three main classes of procedures for sensitivity estimation and have a number of desirable qualities. First, the new methods are unbiased formore » a broad class of problems. Second, the methods are applicable to nearly any physically relevant biochemical CTMC model. Third, and as we demonstrate on several numerical examples, the new methods are quite efficient, particularly if one wishes to estimate the full gradient of parametric sensitivities. The methods are rather intuitive and utilize the multilevel Monte Carlo philosophy of splitting an expectation into separate parts and handling each in an efficient manner.« less

Selecting a separable parametric spatiotemporal covariance structure for longitudinal imaging data.

PubMed

George, Brandon; Aban, Inmaculada

2015-01-15

Longitudinal imaging studies allow great insight into how the structure and function of a subject's internal anatomy changes over time. Unfortunately, the analysis of longitudinal imaging data is complicated by inherent spatial and temporal correlation: the temporal from the repeated measures and the spatial from the outcomes of interest being observed at multiple points in a patient's body. We propose the use of a linear model with a separable parametric spatiotemporal error structure for the analysis of repeated imaging data. The model makes use of spatial (exponential, spherical, and Matérn) and temporal (compound symmetric, autoregressive-1, Toeplitz, and unstructured) parametric correlation functions. A simulation study, inspired by a longitudinal cardiac imaging study on mitral regurgitation patients, compared different information criteria for selecting a particular separable parametric spatiotemporal correlation structure as well as the effects on types I and II error rates for inference on fixed effects when the specified model is incorrect. Information criteria were found to be highly accurate at choosing between separable parametric spatiotemporal correlation structures. Misspecification of the covariance structure was found to have the ability to inflate the type I error or have an overly conservative test size, which corresponded to decreased power. An example with clinical data is given illustrating how the covariance structure procedure can be performed in practice, as well as how covariance structure choice can change inferences about fixed effects. Copyright © 2014 John Wiley & Sons, Ltd.

Establishment of Biological Reference Intervals and Reference Curve for Urea by Exploratory Parametric and Non-Parametric Quantile Regression Models.

PubMed

Sarkar, Rajarshi

2013-07-01

The validity of the entire renal function tests as a diagnostic tool depends substantially on the Biological Reference Interval (BRI) of urea. Establishment of BRI of urea is difficult partly because exclusion criteria for selection of reference data are quite rigid and partly due to the compartmentalization considerations regarding age and sex of the reference individuals. Moreover, construction of Biological Reference Curve (BRC) of urea is imperative to highlight the partitioning requirements. This a priori study examines the data collected by measuring serum urea of 3202 age and sex matched individuals, aged between 1 and 80 years, by a kinetic UV Urease/GLDH method on a Roche Cobas 6000 auto-analyzer. Mann-Whitney U test of the reference data confirmed the partitioning requirement by both age and sex. Further statistical analysis revealed the incompatibility of the data for a proposed parametric model. Hence the data was non-parametrically analysed. BRI was found to be identical for both sexes till the 2(nd) decade, and the BRI for males increased progressively 6(th) decade onwards. Four non-parametric models were postulated for construction of BRC: Gaussian kernel, double kernel, local mean and local constant, of which the last one generated the best-fitting curves. Clinical decision making should become easier and diagnostic implications of renal function tests should become more meaningful if this BRI is followed and the BRC is used as a desktop tool in conjunction with similar data for serum creatinine.

A Device for Long-Term Perfusion, Imaging, and Electrical Interfacing of Brain Tissue In vitro

PubMed Central

Killian, Nathaniel J.; Vernekar, Varadraj N.; Potter, Steve M.; Vukasinovic, Jelena

2016-01-01

Distributed microelectrode array (MEA) recordings from consistent, viable, ≥500 μm thick tissue preparations over time periods from days to weeks may aid in studying a wide range of problems in neurobiology that require in vivo-like organotypic morphology. Existing tools for electrically interfacing with organotypic slices do not address necrosis that inevitably occurs within thick slices with limited diffusion of nutrients and gas, and limited removal of waste. We developed an integrated device that enables long-term maintenance of thick, functionally active, brain tissue models using interstitial perfusion and distributed recordings from thick sections of explanted tissue on a perforated multi-electrode array. This novel device allows for automated culturing, in situ imaging, and extracellular multi-electrode interfacing with brain slices, 3-D cell cultures, and potentially other tissue culture models. The device is economical, easy to assemble, and integrable with standard electrophysiology tools. We found that convective perfusion through the culture thickness provided a functional benefit to the preparations as firing rates were generally higher in perfused cultures compared to their respective unperfused controls. This work is a step toward the development of integrated tools for days-long experiments with more consistent, healthier, thicker, and functionally more active tissue cultures with built-in distributed electrophysiological recording and stimulation functionality. The results may be useful for the study of normal processes, pathological conditions, and drug screening strategies currently hindered by the limitations of acute (a few hours long) brain slice preparations. PMID:27065793

Mortalin inhibition in experimental Parkinson's disease.

PubMed

Chiasserini, Davide; Tozzi, Alessandro; de Iure, Antonio; Tantucci, Michela; Susta, Federica; Orvietani, Pier Luigi; Koya, Keizo; Binaglia, Luciano; Calabresi, Paolo

2011-08-01

Among heat shock proteins, mortalin has been linked to the pathogenesis of Parkinson's disease. In the present work a rat model of Parkinson's disease was used to analyze the expression of striatal proteins and, more specifically, mortalin expression. The possible involvement of mortalin in Parkinson's disease pathogenesis was further investigated by utilizing an electrophysiological approach and pharmacological inhibition of mortalin in both the physiological and the parkinsonian states. Proteomic analysis was used to investigate changes in striatal protein expression in the 6-hydroxydopamine rat model of Parkinson's disease. The electrophysiological effects of MKT-077, a rhodamine-123 analogue acting as an inhibitor of mortalin, were measured by field potential recordings from corticostriatal brain slices obtained from control, sham-operated, and 6-hydroxydopamine-denervated animals. Slices in the presence of rotenone, an inhibitor of mitochondrial complex I, were also analyzed. Proteomic analysis revealed downregulation of mortalin in the striata of 6-hydroxydopamine-treated rats in comparison with sham-operated animals. MKT-077 reduced corticostriatal field potential amplitude in physiological conditions, inducing membrane depolarization and inward current in striatal medium spiny neurons. In addition, we observed that concentrations of MKT-077 not inducing any electrophysiological effect in physiological conditions caused significant changes in striatal slices from parkinsonian animals as well as in slices treated with a submaximal concentration of rotenone. These findings suggest a critical link between mortalin function and mitochondrial activity in both physiological and pathological conditions mimicking Parkinson's disease. Copyright © 2011 Movement Disorder Society.

Postharvest monitoring of organic potato (cv. Anuschka) during hot-air drying using visible-NIR hyperspectral imaging.

PubMed

Moscetti, Roberto; Sturm, Barbara; Crichton, Stuart Oj; Amjad, Waseem; Massantini, Riccardo

2018-05-01

The potential of hyperspectral imaging (500-1010 nm) was evaluated for monitoring of the quality of potato slices (var. Anuschka) of 5, 7 and 9 mm thickness subjected to air drying at 50 °C. The study investigated three different feature selection methods for the prediction of dry basis moisture content and colour of potato slices using partial least squares regression (PLS). The feature selection strategies tested include interval PLS regression (iPLS), and differences and ratios between raw reflectance values for each possible pair of wavelengths (R[λ 1 ]-R[λ 2 ] and R[λ 1 ]:R[λ 2 ], respectively). Moreover, the combination of spectral and spatial domains was tested. Excellent results were obtained using the iPLS algorithm. However, features from both datasets of raw reflectance differences and ratios represent suitable alternatives for development of low-complex prediction models. Finally, the dry basis moisture content was high accurately predicted by combining spectral data (i.e. R[511 nm]-R[994 nm]) and spatial domain (i.e. relative area shrinkage of slice). Modelling the data acquired during drying through hyperspectral imaging can provide useful information concerning the chemical and physicochemical changes of the product. With all this information, the proposed approach lays the foundations for a more efficient smart dryer that can be designed and its process optimized for drying of potato slices. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Sparkle model for AM1 calculation of lanthanide complexes: improved parameters for europium.

PubMed

Rocha, Gerd B; Freire, Ricardo O; Da Costa, Nivan B; De Sá, Gilberto F; Simas, Alfredo M

2004-04-05

In the present work, we sought to improve our sparkle model for the calculation of lanthanide complexes, SMLC,in various ways: (i) inclusion of the europium atomic mass, (ii) reparametrization of the model within AM1 from a new response function including all distances of the coordination polyhedron for tris(acetylacetonate)(1,10-phenanthroline) europium(III), (iii) implementation of the model in the software package MOPAC93r2, and (iv) inclusion of spherical Gaussian functions in the expression which computes the core-core repulsion energy. The parametrization results indicate that SMLC II is superior to the previous version of the model because Gaussian functions proved essential if one requires a better description of the geometries of the complexes. In order to validate our parametrization, we carried out calculations on 96 europium(III) complexes, selected from Cambridge Structural Database 2003, and compared our predicted ground state geometries with the experimental ones. Our results show that this new parametrization of the SMLC model, with the inclusion of spherical Gaussian functions in the core-core repulsion energy, is better capable of predicting the Eu-ligand distances than the previous version. The unsigned mean error for all interatomic distances Eu-L, in all 96 complexes, which, for the original SMLC is 0.3564 A, is lowered to 0.1993 A when the model was parametrized with the inclusion of two Gaussian functions. Our results also indicate that this model is more applicable to europium complexes with beta-diketone ligands. As such, we conclude that this improved model can be considered a powerful tool for the study of lanthanide complexes and their applications, such as the modeling of light conversion molecular devices.

Rate distortion optimal bit allocation methods for volumetric data using JPEG 2000.

PubMed

Kosheleva, Olga M; Usevitch, Bryan E; Cabrera, Sergio D; Vidal, Edward

2006-08-01

Computer modeling programs that generate three-dimensional (3-D) data on fine grids are capable of generating very large amounts of information. These data sets, as well as 3-D sensor/measured data sets, are prime candidates for the application of data compression algorithms. A very flexible and powerful compression algorithm for imagery data is the newly released JPEG 2000 standard. JPEG 2000 also has the capability to compress volumetric data, as described in Part 2 of the standard, by treating the 3-D data as separate slices. As a decoder standard, JPEG 2000 does not describe any specific method to allocate bits among the separate slices. This paper proposes two new bit allocation algorithms for accomplishing this task. The first procedure is rate distortion optimal (for mean squared error), and is conceptually similar to postcompression rate distortion optimization used for coding codeblocks within JPEG 2000. The disadvantage of this approach is its high computational complexity. The second bit allocation algorithm, here called the mixed model (MM) approach, mathematically models each slice's rate distortion curve using two distinct regions to get more accurate modeling at low bit rates. These two bit allocation algorithms are applied to a 3-D Meteorological data set. Test results show that the MM approach gives distortion results that are nearly identical to the optimal approach, while significantly reducing computational complexity.

Precision-cut liver slices of Atlantic cod (Gadus morhua): an in vitro system for studying the effects of environmental contaminants.

PubMed

Eide, M; Karlsen, O A; Kryvi, H; Olsvik, P A; Goksøyr, A

2014-08-01

The Atlantic cod (Gadus morhua) is an economically important species commonly consumed by humans. The widespread distribution of cod in the North Atlantic Ocean makes it vulnerable to effluents from human activities, such as coastal industries and offshore petroleum exploration. It has been demonstrated that many effluents have adverse effects on cod reproduction and health, e.g. by disrupting endocrine signaling pathways. The liver, expressing important components of the biotransformation and the endocrine system, is one of the main target organs. Thus, reliable and reproducible in vitro systems of the liver are important for studying effects of environmental contaminants. The aim of this study was to investigate precision-cut liver slices (PCLS) as an alternative in vitro system for toxicological studies of the Atlantic cod liver. Slices of 8 mm in diameter and 250 μm thickness were prepared and cultivated from immature cod. Several analyses to measure the liver slice viability were performed: enzyme assays, histology, and morphometric analysis, all confirming cell viability for up to 72 h in culture. The liver slices were also exposed to two well-known model environmental contaminants, β-naphthoflavone (BNF) and 17α-ethynylestradiol (EE2), representing established agonists for the aryl hydrocarbon receptor (AHR) and the estrogen receptor (ER), respectively. The results showed increased transcription of the target genes cytochrome P450 1A (CYP1A) and vitellogenin (VTG), both well-established biomarkers for exposure of fish to the selected compounds. In conclusion, PCLS is a promising in vitro system for toxicological studies of cod liver cells. The liver slices are viable in culture for several days and respond to environmental contaminants in a dose- and time-specific manner. Copyright © 2013 Elsevier B.V. All rights reserved.

Fructose-1,6-Bisphospate does not preserve ATP in hypoxic-ischemic neonatal cerebrocortical slices

PubMed Central

Liu, Jia; Hirai, Kiyoshi; Litt, Lawrence

2008-01-01

Fructose-1,6-bisphosphate (FBP), an endogenous intracellular metabolite in glycolysis, was found in many preclinical studies to be neuroprotective during hypoxia-ischemia (HI) when administered exogenously. We looked for HI neuroprotection from FBP in a neonatal rat brain slice model, using 14.1 Tesla 1H /31P/13C NMR spectroscopy of perchloric acid slice extracts to ask: 1) if FBP preserves high energy phosphates during HI; and 2) if exogenous [1-13C]FBP enters cells and is glycolytically metabolized to [3-13C]lactate. We also asked: 3) if substantial superoxide production occurs during and after HI, thinking such might be treatable by exogenous FBP's antioxidant effects. Superfused P7 rat cerebrocortical slices (350μm) were treated with 2 mM FBP before and during 30 min of HI, and then given four hours of recovery with an FBP-free oxygenated superfusate. Slices were removed before HI, at the end of HI, and at 1 and 4 hours after HI. FBP did not improve high energy phosphate levels or change 1H metabolite profiles. Large increases in [3-13C]lactate were seen with 13C NMR, but the lactate fractional enrichment was always (1.1±0.5)%, implying that all of lactate's 13C was natural abundance 13C, that none was from metabolism of 13C-FBP. FBP had no effect on the fluorescence of ethidium produced from superoxide oxidation of hydroethidine. Compared to control slices, ethidium fluorescence was 25% higher during HI and 50% higher at the end of recovery. Exogenous FBP did not provide protection or enter glycolysis. Its use as an antioxidant might be worth studying at higher FBP concentrations. PMID:18725216

Apixaban decreases brain thrombin activity in a male mouse model of acute ischemic stroke.

PubMed

Bushi, Doron; Chapman, Joab; Wohl, Anton; Stein, Efrat Shavit; Feingold, Ekaterina; Tanne, David

2018-05-14

Factor Xa (FXa) plays a critical role in the coagulation cascade by generation of thrombin. During focal ischemia thrombin levels increase in the brain tissue and cause neural damage. This study examined the hypothesis that administration of the FXa inhibitor, apixaban, following focal ischemic stroke may have therapeutic potential by decreasing brain thrombin activity and infarct volume. Male mice were divided into a treated groups that received different doses of apixaban (2, 20, 100 mg/kg administered I.P.) or saline (controls) immediately after blocking the middle cerebral artery (MCA). Thrombin activity was measured by a fluorescence assay on fresh coronal slices taken from the mice brains 24 hr following the MCA occlusion. Infarct volume was assessed using triphenyltetrazolium chloride staining. A high dose of apixaban (100 mg/kg) significantly decreased thrombin activity levels in the ipsilateral hemisphere compared to the control group (Slice#5, p = .016; Slice#6, p = .016; Slice#7, p = .016; Slice#8, p = .036; by the nonparametric Mann-Whitney test). In addition, treatment with apixaban doses of both 100 mg/kg (32 ± 8% vs. 76 ± 7% in the treatment vs. control groups respectively; p = .005 by the nonparametric Mann-Whitney test) and 20 mg/kg (43 ± 7% vs. 76 ± 7% in the treatment vs. control groups respectively; p = .019 by the nonparametric Mann-Whitney test) decreased infarct volumes in areas surrounding the ischemic core (Slices #3 and #8). No brain hemorrhages were observed either in the treated or control groups. In summary, I.P. administration of high dose of apixaban immediately after MCA occlusion decreases brain thrombin activity and reduces infarct size. © 2018 Wiley Periodicals, Inc.

Toward accurate tooth segmentation from computed tomography images using a hybrid level set model

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

Gan, Yangzhou; Zhao, Qunfei; Xia, Zeyang, E-mail: zy.xia@siat.ac.cn, E-mail: jing.xiong@siat.ac.cn

Purpose: A three-dimensional (3D) model of the teeth provides important information for orthodontic diagnosis and treatment planning. Tooth segmentation is an essential step in generating the 3D digital model from computed tomography (CT) images. The aim of this study is to develop an accurate and efficient tooth segmentation method from CT images. Methods: The 3D dental CT volumetric images are segmented slice by slice in a two-dimensional (2D) transverse plane. The 2D segmentation is composed of a manual initialization step and an automatic slice by slice segmentation step. In the manual initialization step, the user manually picks a starting slicemore » and selects a seed point for each tooth in this slice. In the automatic slice segmentation step, a developed hybrid level set model is applied to segment tooth contours from each slice. Tooth contour propagation strategy is employed to initialize the level set function automatically. Cone beam CT (CBCT) images of two subjects were used to tune the parameters. Images of 16 additional subjects were used to validate the performance of the method. Volume overlap metrics and surface distance metrics were adopted to assess the segmentation accuracy quantitatively. The volume overlap metrics were volume difference (VD, mm{sup 3}) and Dice similarity coefficient (DSC, %). The surface distance metrics were average symmetric surface distance (ASSD, mm), RMS (root mean square) symmetric surface distance (RMSSSD, mm), and maximum symmetric surface distance (MSSD, mm). Computation time was recorded to assess the efficiency. The performance of the proposed method has been compared with two state-of-the-art methods. Results: For the tested CBCT images, the VD, DSC, ASSD, RMSSSD, and MSSD for the incisor were 38.16 ± 12.94 mm{sup 3}, 88.82 ± 2.14%, 0.29 ± 0.03 mm, 0.32 ± 0.08 mm, and 1.25 ± 0.58 mm, respectively; the VD, DSC, ASSD, RMSSSD, and MSSD for the canine were 49.12 ± 9.33 mm{sup 3}, 91.57 ± 0.82%, 0.27 ± 0.02 mm, 0.28 ± 0.03 mm, and 1.06 ± 0.40 mm, respectively; the VD, DSC, ASSD, RMSSSD, and MSSD for the premolar were 37.95 ± 10.13 mm{sup 3}, 92.45 ± 2.29%, 0.29 ± 0.06 mm, 0.33 ± 0.10 mm, and 1.28 ± 0.72 mm, respectively; the VD, DSC, ASSD, RMSSSD, and MSSD for the molar were 52.38 ± 17.27 mm{sup 3}, 94.12 ± 1.38%, 0.30 ± 0.08 mm, 0.35 ± 0.17 mm, and 1.52 ± 0.75 mm, respectively. The computation time of the proposed method for segmenting CBCT images of one subject was 7.25 ± 0.73 min. Compared with two other methods, the proposed method achieves significant improvement in terms of accuracy. Conclusions: The presented tooth segmentation method can be used to segment tooth contours from CT images accurately and efficiently.« less

Estimating solar ultraviolet irradiance (290-385 nm) by means of the spectral parametric models: SPCTRAL2 and SMARTS2

NASA Astrophysics Data System (ADS)

Foyo-Moreno, I.; Vida, J.; Olmo, F. J.; Alados-Arboledas, L.

2000-11-01

Since the discovery of the ozone depletion in Antarctic and the globally declining trend of stratospheric ozone concentration, public and scientific concern has been raised in the last decades. A very important consequence of this fact is the increased broadband and spectral UV radiation in the environment and the biological effects and heath risks that may take place in the near future. The absence of widespread measurements of this radiometric flux has lead to the development and use of alternative estimation procedures such as the parametric approaches. Parametric models compute the radiant energy using available atmospheric parameters. Some parametric models compute the global solar irradiance at surface level by addition of its direct beam and diffuse components. In the present work, we have developed a comparison between two cloudless sky parametrization schemes. Both methods provide an estimation of the solar spectral irradiance that can be integrated spectrally within the limits of interest. For this test we have used data recorded in a radiometric station located at Granada (37.180°N, 3.580°W, 660 m a.m.s.l.), an inland location. The database includes hourly values of the relevant variables covering the years 1994-95. The performance of the models has been tested in relation to their predictive capability of global solar irradiance in the UV range (290-385 nm). After our study, it appears that information concerning the aerosol radiative effects is fundamental in order to obtain a good estimation. The original version of SPCTRAL2 provides estimates of the experimental values with negligible mean bias deviation. This suggests not only the appropriateness of the model but also the convenience of the aerosol features fixed in it to Granada conditions. SMARTS2 model offers increased flexibility concerning the selection of different aerosol models included in the code and provides the best results when the selected models are those considered as urban. Although SMARTS2 provide slightly worse results, both models give estimates of solar ultraviolet irradiance with mean bias deviation below 5%, and root mean square deviation close to experimental errors.

Analytic modeling of aerosol size distributions

NASA Technical Reports Server (NTRS)

Deepack, A.; Box, G. P.

1979-01-01

Mathematical functions commonly used for representing aerosol size distributions are studied parametrically. Methods for obtaining best fit estimates of the parameters are described. A catalog of graphical plots depicting the parametric behavior of the functions is presented along with procedures for obtaining analytical representations of size distribution data by visual matching of the data with one of the plots. Examples of fitting the same data with equal accuracy by more than one analytic model are also given.

Parametric Adjustments to the Rankine Vortex Wind Model for Gulf of Mexico Hurricanes

DTIC Science & Technology

2012-11-01

2012 4. TITLE AND SUBTITLE Parametric Adjustments to the Rankine Vortex Wind Model for Gulf of Mexico Hurricanes 5a. CONTRACT NUMBER 5b. GRANT ...may be used to construct spatially varying wind fields for the GOM region (e.g., Thompson and Cardone [12]), but this requires using a complicated...Storm Damage Reduc- tion, and Dredging Operations and Environmental Research (DOER). The USACE Headquarters granted permission to publish this paper

Parametric study of laser photovoltaic energy converters

NASA Technical Reports Server (NTRS)

Walker, G. H.; Heinbockel, J. H.

1987-01-01

Photovoltaic converters are of interest for converting laser power to electrical power in a space-based laser power system. This paper describes a model for photovoltaic laser converters and the application of this model to a neodymium laser silicon photovoltaic converter system. A parametric study which defines the sensitivity of the photovoltaic parameters is described. An optimized silicon photovoltaic converter has an efficiency greater than 50 percent for 1000 W/sq cm of neodymium laser radiation.

Four photon parametric amplification. [in unbiased Josephson junction

NASA Technical Reports Server (NTRS)

Parrish, P. T.; Feldman, M. J.; Ohta, H.; Chiao, R. Y.

1974-01-01

An analysis is presented describing four-photon parametric amplification in an unbiased Josephson junction. Central to the theory is the model of the Josephson effect as a nonlinear inductance. Linear, small signal analysis is applied to the two-fluid model of the Josephson junction. The gain, gain-bandwidth product, high frequency limit, and effective noise temperature are calculated for a cavity reflection amplifier. The analysis is extended to multiple (series-connected) junctions and subharmonic pumping.

Scalable Learning for Geostatistics and Speaker Recognition

DTIC Science & Technology

2011-01-01

of prior knowledge of the model or due to improved robustness requirements). Both these methods have their own advantages and disadvantages. The use...application. If the data is well-correlated and low-dimensional, any prior knowledge available on the data can be used to build a parametric model. In the...absence of prior knowledge , non-parametric methods can be used. If the data is high-dimensional, PCA based dimensionality reduction is often the first

Model independent constraints on transition redshift

NASA Astrophysics Data System (ADS)

Jesus, J. F.; Holanda, R. F. L.; Pereira, S. H.

2018-05-01

This paper aims to put constraints on the transition redshift zt, which determines the onset of cosmic acceleration, in cosmological-model independent frameworks. In order to perform our analyses, we consider a flat universe and assume a parametrization for the comoving distance DC(z) up to third degree on z, a second degree parametrization for the Hubble parameter H(z) and a linear parametrization for the deceleration parameter q(z). For each case, we show that type Ia supernovae and H(z) data complement each other on the parameter space and tighter constrains for the transition redshift are obtained. By combining the type Ia supernovae observations and Hubble parameter measurements it is possible to constrain the values of zt, for each approach, as 0.806± 0.094, 0.870± 0.063 and 0.973± 0.058 at 1σ c.l., respectively. Then, such approaches provide cosmological-model independent estimates for this parameter.

Component isolation for multi-component signal analysis using a non-parametric gaussian latent feature model

NASA Astrophysics Data System (ADS)

Yang, Yang; Peng, Zhike; Dong, Xingjian; Zhang, Wenming; Clifton, David A.

2018-03-01

A challenge in analysing non-stationary multi-component signals is to isolate nonlinearly time-varying signals especially when they are overlapped in time and frequency plane. In this paper, a framework integrating time-frequency analysis-based demodulation and a non-parametric Gaussian latent feature model is proposed to isolate and recover components of such signals. The former aims to remove high-order frequency modulation (FM) such that the latter is able to infer demodulated components while simultaneously discovering the number of the target components. The proposed method is effective in isolating multiple components that have the same FM behavior. In addition, the results show that the proposed method is superior to generalised demodulation with singular-value decomposition-based method, parametric time-frequency analysis with filter-based method and empirical model decomposition base method, in recovering the amplitude and phase of superimposed components.

Slice regular functions of several Clifford variables

NASA Astrophysics Data System (ADS)

Ghiloni, R.; Perotti, A.

2012-11-01

We introduce a class of slice regular functions of several Clifford variables. Our approach to the definition of slice functions is based on the concept of stem functions of several variables and on the introduction on real Clifford algebras of a family of commuting complex structures. The class of slice regular functions include, in particular, the family of (ordered) polynomials in several Clifford variables. We prove some basic properties of slice and slice regular functions and give examples to illustrate this function theory. In particular, we give integral representation formulas for slice regular functions and a Hartogs type extension result.

Modular electronics packaging system

NASA Technical Reports Server (NTRS)

Hunter, Don J. (Inventor)

2001-01-01

A modular electronics packaging system includes multiple packaging slices that are mounted horizontally to a base structure. The slices interlock to provide added structural support. Each packaging slice includes a rigid and thermally conductive housing having four side walls that together form a cavity to house an electronic circuit. The chamber is enclosed on one end by an end wall, or web, that isolates the electronic circuit from a circuit in an adjacent packaging slice. The web also provides a thermal path between the electronic circuit and the base structure. Each slice also includes a mounting bracket that connects the packaging slice to the base structure. Four guide pins protrude from the slice into four corresponding receptacles in an adjacent slice. A locking element, such as a set screw, protrudes into each receptacle and interlocks with the corresponding guide pin. A conduit is formed in the slice to allow electrical connection to the electronic circuit.

Time-slice analysis of the Australian summer monsoon during the late Quaternary using the Fast Ocean Atmosphere Model

NASA Astrophysics Data System (ADS)

Marshall, A. G.; Lynch, A. H.

2006-10-01

We use the Fast Ocean Atmosphere Model (FOAM) to investigate the variation in the Australian summer monsoon over the last 55 000 years. A synthesis of palaeoenvironmental observations is used to constrain the model for six time slices: 55, 35, 21, 11, 6 and 0 ka. Both inter-hemispheric forcing and the seasonal timing of local insolation changes play key, and interacting, roles on the evolution and intensity of the monsoon.During the onset to the monsoon, a heat low develops to the west of Australia over the Indian Ocean in all time slices, but with varying strengths. Divergent outflow from Asia converges with the cyclonic flow to bring increased rainfall to northern Australia and the maritime continent. The relative importance of a low pressure pull and the high pressure push varies according to the strength of the pressure anomalies. Only in the middle Holocene is the low pressure pull the dominant forcing mechanism. At 21 ka, the climate shift to colder mean temperatures determines the large-scale dynamics of the monsoon.The general picture that emerges from these results is consistent with available palaeodata but highlights the importance of a broad regional perspective to ascribe the driving mechanisms at different times. Copyright

Modeling the growth of Lactobacillus viridescens under non-isothermal conditions in vacuum-packed sliced ham.

PubMed

Silva, Nathália Buss da; Longhi, Daniel Angelo; Martins, Wiaslan Figueiredo; Laurindo, João Borges; Aragão, Gláucia Maria Falcão de; Carciofi, Bruno Augusto Mattar

2017-01-02

Lactic acid bacteria (LAB) are responsible for spoiling vacuum-packed meat products, such as ham. Since the temperature is the main factor affecting the microbial dynamic, the use of mathematical models describing the microbial behavior into a non-isothermal environment can be very useful for predicting food shelf life. In this study, the growth of Lactobacillus viridescens was measured in vacuum-packed sliced ham under non-isothermal conditions, and the predictive ability of primary (Baranyi and Roberts, 1994) and secondary (Square Root) models were assessed using parameters estimated in MRS culture medium under isothermal conditions (between 4 and 30°C). Fresh ham piece was sterilized, sliced, inoculated, vacuum-packed, and stored in a temperature-controlled incubator at five different non-isothermal conditions (between 4 and 25°C) and one isothermal condition (8°C). The mathematical models obtained in MRS medium were assessed by comparing predicted values with L. viridescens growth data in vacuum-packed ham. Its predictive ability was assessed through statistical indexes, with good results (bias factor between 0.95 and 1.03; accuracy factor between 1.04 and 1.07, and RMSE between 0.76 and 1.33), especially in increasing temperature, which predictions were safe. The model parameters obtained from isothermal growth data in MRS medium enabled to estimate the shelf life of a commercial ham under non-isothermal conditions in the temperature range analyzed. Copyright © 2016 Elsevier B.V. All rights reserved.

Illiquidity premium and expected stock returns in the UK: A new approach

NASA Astrophysics Data System (ADS)

Chen, Jiaqi; Sherif, Mohamed

2016-09-01

This study examines the relative importance of liquidity risk for the time-series and cross-section of stock returns in the UK. We propose a simple way to capture the multidimensionality of illiquidity. Our analysis indicates that existing illiquidity measures have considerable asset specific components, which justifies our new approach. Further, we use an alternative test of the Amihud (2002) measure and parametric and non-parametric methods to investigate whether liquidity risk is priced in the UK. We find that the inclusion of the illiquidity factor in the capital asset pricing model plays a significant role in explaining the cross-sectional variation in stock returns, in particular with the Fama-French three-factor model. Further, using Hansen-Jagannathan non-parametric bounds, we find that the illiquidity-augmented capital asset pricing models yield a small distance error, other non-liquidity based models fail to yield economically plausible distance values. Our findings have important implications for managing the liquidity risk of equity portfolios.

Automated, Parametric Geometry Modeling and Grid Generation for Turbomachinery Applications

NASA Technical Reports Server (NTRS)

Harrand, Vincent J.; Uchitel, Vadim G.; Whitmire, John B.

2000-01-01

The objective of this Phase I project is to develop a highly automated software system for rapid geometry modeling and grid generation for turbomachinery applications. The proposed system features a graphical user interface for interactive control, a direct interface to commercial CAD/PDM systems, support for IGES geometry output, and a scripting capability for obtaining a high level of automation and end-user customization of the tool. The developed system is fully parametric and highly automated, and, therefore, significantly reduces the turnaround time for 3D geometry modeling, grid generation and model setup. This facilitates design environments in which a large number of cases need to be generated, such as for parametric analysis and design optimization of turbomachinery equipment. In Phase I we have successfully demonstrated the feasibility of the approach. The system has been tested on a wide variety of turbomachinery geometries, including several impellers and a multi stage rotor-stator combination. In Phase II, we plan to integrate the developed system with turbomachinery design software and with commercial CAD/PDM software.

A semi-parametric within-subject mixture approach to the analyses of responses and response times.

PubMed

Molenaar, Dylan; Bolsinova, Maria; Vermunt, Jeroen K

2018-05-01

In item response theory, modelling the item response times in addition to the item responses may improve the detection of possible between- and within-subject differences in the process that resulted in the responses. For instance, if respondents rely on rapid guessing on some items but not on all, the joint distribution of the responses and response times will be a multivariate within-subject mixture distribution. Suitable parametric methods to detect these within-subject differences have been proposed. In these approaches, a distribution needs to be assumed for the within-class response times. In this paper, it is demonstrated that these parametric within-subject approaches may produce false positives and biased parameter estimates if the assumption concerning the response time distribution is violated. A semi-parametric approach is proposed which resorts to categorized response times. This approach is shown to hardly produce false positives and parameter bias. In addition, the semi-parametric approach results in approximately the same power as the parametric approach. © 2017 The British Psychological Society.

Development of suspended core soft glass fibers for far-detuned parametric conversion

NASA Astrophysics Data System (ADS)

Rampur, Anupamaa; Ciąćka, Piotr; Cimek, Jarosław; Kasztelanic, Rafał; Buczyński, Ryszard; Klimczak, Mariusz

2018-04-01

Light sources utilizing χ (2) parametric conversion combine high brightness with attractive operation wavelengths in the near and mid-infrared. In optical fibers, it is possible to use χ (3) degenerate four-wave mixing in order to obtain signal-to-idler frequency detuning of over 100 THz. We report on a test series of nonlinear soft glass suspended core fibers intended for parametric conversion of 1000-1100 nm signal wavelengths available from an array of mature lasers into the near-to-mid-infrared range of 2700-3500 nm under pumping with an erbium sub-picosecond laser system. The presented discussion includes modelling of the fiber properties, details of their physical development and characterization, and experimental tests of parametric conversion.

Parametric Method Performance for Dynamic 3'-Deoxy-3'-18F-Fluorothymidine PET/CT in Epidermal Growth Factor Receptor-Mutated Non-Small Cell Lung Carcinoma Patients Before and During Therapy.

PubMed

Kramer, Gerbrand Maria; Frings, Virginie; Heijtel, Dennis; Smit, E F; Hoekstra, Otto S; Boellaard, Ronald

2017-06-01

The objective of this study was to validate several parametric methods for quantification of 3'-deoxy-3'- 18 F-fluorothymidine ( 18 F-FLT) PET in advanced-stage non-small cell lung carcinoma (NSCLC) patients with an activating epidermal growth factor receptor mutation who were treated with gefitinib or erlotinib. Furthermore, we evaluated the impact of noise on accuracy and precision of the parametric analyses of dynamic 18 F-FLT PET/CT to assess the robustness of these methods. Methods : Ten NSCLC patients underwent dynamic 18 F-FLT PET/CT at baseline and 7 and 28 d after the start of treatment. Parametric images were generated using plasma input Logan graphic analysis and 2 basis functions-based methods: a 2-tissue-compartment basis function model (BFM) and spectral analysis (SA). Whole-tumor-averaged parametric pharmacokinetic parameters were compared with those obtained by nonlinear regression of the tumor time-activity curve using a reversible 2-tissue-compartment model with blood volume fraction. In addition, 2 statistically equivalent datasets were generated by countwise splitting the original list-mode data, each containing 50% of the total counts. Both new datasets were reconstructed, and parametric pharmacokinetic parameters were compared between the 2 replicates and the original data. Results: After the settings of each parametric method were optimized, distribution volumes (V T ) obtained with Logan graphic analysis, BFM, and SA all correlated well with those derived using nonlinear regression at baseline and during therapy ( R 2 ≥ 0.94; intraclass correlation coefficient > 0.97). SA-based V T images were most robust to increased noise on a voxel-level (repeatability coefficient, 16% vs. >26%). Yet BFM generated the most accurate K 1 values ( R 2 = 0.94; intraclass correlation coefficient, 0.96). Parametric K 1 data showed a larger variability in general; however, no differences were found in robustness between methods (repeatability coefficient, 80%-84%). Conclusion: Both BFM and SA can generate quantitatively accurate parametric 18 F-FLT V T images in NSCLC patients before and during therapy. SA was more robust to noise, yet BFM provided more accurate parametric K 1 data. We therefore recommend BFM as the preferred parametric method for analysis of dynamic 18 F-FLT PET/CT studies; however, SA can also be used. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

A discrete epidemic model for bovine Babesiosis disease and tick populations

NASA Astrophysics Data System (ADS)

Aranda, Diego F.; Trejos, Deccy Y.; Valverde, Jose C.

2017-06-01

In this paper, we provide and study a discrete model for the transmission of Babesiosis disease in bovine and tick populations. This model supposes a discretization of the continuous-time model developed by us previously. The results, here obtained by discrete methods as opposed to continuous ones, show that similar conclusions can be obtained for the discrete model subject to the assumption of some parametric constraints which were not necessary in the continuous case. We prove that these parametric constraints are not artificial and, in fact, they can be deduced from the biological significance of the model. Finally, some numerical simulations are given to validate the model and verify our theoretical study.

Slice profile effects in 2D slice-selective MRI of hyperpolarized nuclei.

PubMed

Deppe, Martin H; Teh, Kevin; Parra-Robles, Juan; Lee, Kuan J; Wild, Jim M

2010-02-01

This work explores slice profile effects in 2D slice-selective gradient-echo MRI of hyperpolarized nuclei. Two different sequences were investigated: a Spoiled Gradient Echo sequence with variable flip angle (SPGR-VFA) and a balanced Steady-State Free Precession (SSFP) sequence. It is shown that in SPGR-VFA the distribution of flip angles across the slice present in any realistically shaped radiofrequency (RF) pulse leads to large excess signal from the slice edges in later RF views, which results in an undesired non-constant total transverse magnetization, potentially exceeding the initial value by almost 300% for the last RF pulse. A method to reduce this unwanted effect is demonstrated, based on dynamic scaling of the slice selection gradient. SSFP sequences with small to moderate flip angles (<40 degrees ) are also shown to preserve the slice profile better than the most commonly used SPGR sequence with constant flip angle (SPGR-CFA). For higher flip angles, the slice profile in SSFP evolves in a manner similar to SPGR-CFA, with depletion of polarization in the center of the slice. Copyright 2009 Elsevier Inc. All rights reserved.

X-1 to X-Wings: Developing a Parametric Cost Model

NASA Technical Reports Server (NTRS)

Sterk, Steve; McAtee, Aaron

2015-01-01

In todays cost-constrained environment, NASA needs an X-Plane database and parametric cost model that can quickly provide rough order of magnitude predictions of cost from initial concept to first fight of potential X-Plane aircraft. This paper takes a look at the steps taken in developing such a model and reports the results. The challenges encountered in the collection of historical data and recommendations for future database management are discussed. A step-by-step discussion of the development of Cost Estimating Relationships (CERs) is then covered.

Technical Topic 3.2.2.d Bayesian and Non-Parametric Statistics: Integration of Neural Networks with Bayesian Networks for Data Fusion and Predictive Modeling

DTIC Science & Technology

2016-05-31

and included explosives such as TATP, HMTD, RDX, RDX, ammonium nitrate , potassium perchlorate, potassium nitrate , sugar, and TNT. The approach...Distribution Unlimited UU UU UU UU 31-05-2016 15-Apr-2014 14-Jan-2015 Final Report: Technical Topic 3.2.2. d Bayesian and Non- parametric Statistics...of Papers published in non peer-reviewed journals: Final Report: Technical Topic 3.2.2. d Bayesian and Non-parametric Statistics: Integration of Neural

Parametrized modified gravity and the CMB bispectrum

NASA Astrophysics Data System (ADS)

Di Valentino, Eleonora; Melchiorri, Alessandro; Salvatelli, Valentina; Silvestri, Alessandra

2012-09-01

We forecast the constraints on modified theories of gravity from the cosmic microwave background (CMB) anisotropies bispectrum that arises from correlations between lensing and the Integrated Sachs-Wolfe effect. In models of modified gravity the evolution of the metric potentials is generally altered and the contribution to the CMB bispectrum signal can differ significantly from the one expected in the standard cosmological model. We adopt a parametrized approach and focus on three different classes of models: Linder’s growth index, Chameleon-type models, and f(R) theories. We show that the constraints on the parameters of the models will significantly improve with future CMB bispectrum measurements.

Three-dimensional echocardiography: rational mode of component images for left ventricular volume quantitation.

PubMed

Nixdorff, Uwe; Feddersen, Isa; Voigt, Jens-Uwe; Flachskampf, Frank A

2005-01-01

Three-dimensional echocardiography (3DE) improves the accuracy of left ventricle (LV) volumetry compared with the two-dimensional echocardiography (2DE) approach because geometric assumptions in the algorithms may be eliminated. The relationship between accuracy of mode (short- versus long-axis planimetry) and the number of component images versus time required for analysis remains to be determined. Sixteen latex models simulating heterogeneously distorted (aneurysmatic) human LVs (56-303 ml; mean 182+/-82 ml) were scanned from an 'apical' position (simultaneous 2DE and 3DE). For 3DE volumetry, the slice thickness was varied for the short (C-scan) and long axes (B-scan) in 5-mm steps between 1 and 25 mm. The mean differences (true-echocardiographic volumes) were 16.5+/-44.3 ml in the 2DE approach (95% confidence intervals -27.8 to +60.8) and 0.6+/-4.0 ml (short axis; 95% confidence intervals -3.4 to +4.6) as well as 2.1+/-9.9 ml (long axis; 95% confidence intervals -7.8 to +12.0) in the 3DE approach (in both cases, the slice thickness was 1 mm). Above a slice thickness of 15 mm, the 95% confidence intervals increased steeply; in the short versus long axes, these were -6.5 to +8.5 versus -7.0 to +10.6 at 15 mm and -10.1 to +15.7 versus -11.3 to +10.9 at 20 mm. The intra-observer variance differed significantly (p<0.001) only above 15 mm (short axis). Time required for analysis derived by measuring short-axis slice thicknesses of 1, 15, and 25 mm was 58+/-16, 7+/-2 and 3+/-1 min, respectively. The most rational component image analysis for 3DE volumetry in the in vitro model uses short-axis slices with a thickness of 15 mm. Copyright (c) 2005 S. Karger AG, Basel.

Prostate contouring in MRI guided biopsy.

PubMed

Vikal, Siddharth; Haker, Steven; Tempany, Clare; Fichtinger, Gabor

2009-03-27

With MRI possibly becoming a modality of choice for detection and staging of prostate cancer, fast and accurate outlining of the prostate is required in the volume of clinical interest. We present a semi-automatic algorithm that uses a priori knowledge of prostate shape to arrive at the final prostate contour. The contour of one slice is then used as initial estimate in the neighboring slices. Thus we propagate the contour in 3D through steps of refinement in each slice. The algorithm makes only minimum assumptions about the prostate shape. A statistical shape model of prostate contour in polar transform space is employed to narrow search space. Further, shape guidance is implicitly imposed by allowing only plausible edge orientations using template matching. The algorithm does not require region-homogeneity, discriminative edge force, or any particular edge profile. Likewise, it makes no assumption on the imaging coils and pulse sequences used and it is robust to the patient's pose (supine, prone, etc.). The contour method was validated using expert segmentation on clinical MRI data. We recorded a mean absolute distance of 2.0 ± 0.6 mm and dice similarity coefficient of 0.93 ± 0.3 in midsection. The algorithm takes about 1 second per slice.

Prostate contouring in MRI guided biopsy

PubMed Central

Vikal, Siddharth; Haker, Steven; Tempany, Clare; Fichtinger, Gabor

2010-01-01

With MRI possibly becoming a modality of choice for detection and staging of prostate cancer, fast and accurate outlining of the prostate is required in the volume of clinical interest. We present a semi-automatic algorithm that uses a priori knowledge of prostate shape to arrive at the final prostate contour. The contour of one slice is then used as initial estimate in the neighboring slices. Thus we propagate the contour in 3D through steps of refinement in each slice. The algorithm makes only minimum assumptions about the prostate shape. A statistical shape model of prostate contour in polar transform space is employed to narrow search space. Further, shape guidance is implicitly imposed by allowing only plausible edge orientations using template matching. The algorithm does not require region-homogeneity, discriminative edge force, or any particular edge profile. Likewise, it makes no assumption on the imaging coils and pulse sequences used and it is robust to the patient's pose (supine, prone, etc.). The contour method was validated using expert segmentation on clinical MRI data. We recorded a mean absolute distance of 2.0 ± 0.6 mm and dice similarity coefficient of 0.93 ± 0.3 in midsection. The algorithm takes about 1 second per slice. PMID:21132083

Jini service to reconstruct tomographic data

NASA Astrophysics Data System (ADS)

Knoll, Peter; Mirzaei, S.; Koriska, K.; Koehn, H.

2002-06-01

A number of imaging systems rely on the reconstruction of a 3- dimensional model from its projections through the process of computed tomography (CT). In medical imaging, for example magnetic resonance imaging (MRI), positron emission tomography (PET), and Single Computer Tomography (SPECT) acquire two-dimensional projections of a three dimensional projections of a three dimensional object. In order to calculate the 3-dimensional representation of the object, i.e. its voxel distribution, several reconstruction algorithms have been developed. Currently, mainly two reconstruct use: the filtered back projection(FBP) and iterative methods. Although the quality of iterative reconstructed SPECT slices is better than that of FBP slices, such iterative algorithms are rarely used for clinical routine studies because of their low availability and increased reconstruction time. We used Jini and a self-developed iterative reconstructions algorithm to design and implement a Jini reconstruction service. With this service, the physician selects the patient study from a database and a Jini client automatically discovers the registered Jini reconstruction services in the department's Intranet. After downloading the proxy object the this Jini service, the SPECT acquisition data are reconstructed. The resulting transaxial slices are visualized using a Jini slice viewer, which can be used for various imaging modalities.

Discovery of Hyperpolarized Molecular Imaging Biomarkers in a Novel Prostate Tissue Slice Culture Model

DTIC Science & Technology

2013-06-01

start of tissue 2D culture , and 3 and 20 hours post culturing of the TSC’s in the 3D bioreactor (left) and corresponding representative tissue... culture tissue slice 13P spectrum obtained after 20 hours in the 5mm 3D MR compatible tissue culture bioreactor . 5 TSC’s with ≈ 90% viability...hours (≈98%) of being in 3D culture within the MR compatible bioreactor . • We demonstrated that the increased flux from pyruvate to lactate in the

A probabilistic strategy for parametric catastrophe insurance

NASA Astrophysics Data System (ADS)

Figueiredo, Rui; Martina, Mario; Stephenson, David; Youngman, Benjamin

2017-04-01

Economic losses due to natural hazards have shown an upward trend since 1980, which is expected to continue. Recent years have seen a growing worldwide commitment towards the reduction of disaster losses. This requires effective management of disaster risk at all levels, a part of which involves reducing financial vulnerability to disasters ex-ante, ensuring that necessary resources will be available following such events. One way to achieve this is through risk transfer instruments. These can be based on different types of triggers, which determine the conditions under which payouts are made after an event. This study focuses on parametric triggers, where payouts are determined by the occurrence of an event exceeding specified physical parameters at a given location, or at multiple locations, or over a region. This type of product offers a number of important advantages, and its adoption is increasing. The main drawback of parametric triggers is their susceptibility to basis risk, which arises when there is a mismatch between triggered payouts and the occurrence of loss events. This is unavoidable in said programmes, as their calibration is based on models containing a number of different sources of uncertainty. Thus, a deterministic definition of the loss event triggering parameters appears flawed. However, often for simplicity, this is the way in which most parametric models tend to be developed. This study therefore presents an innovative probabilistic strategy for parametric catastrophe insurance. It is advantageous as it recognizes uncertainties and minimizes basis risk while maintaining a simple and transparent procedure. A logistic regression model is constructed here to represent the occurrence of loss events based on certain loss index variables, obtained through the transformation of input environmental variables. Flood-related losses due to rainfall are studied. The resulting model is able, for any given day, to issue probabilities of occurrence of loss events. Due to the nature of parametric programmes, it is still necessary to clearly define when a payout is due or not, and so a decision threshold probability above which a loss event is considered to occur must be set, effectively converting the issued probabilities into deterministic binary outcomes. Model skill and value are evaluated over the range of possible threshold probabilities, with the objective of defining the optimal one. The predictive ability of the model is assessed. In terms of value assessment, a decision model is proposed, allowing users to quantify monetarily their expected expenses when different combinations of model event triggering and actual event occurrence take place, directly tackling the problem of basis risk.

A new process sensitivity index to identify important system processes under process model and parametric uncertainty

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

Dai, Heng; Ye, Ming; Walker, Anthony P.

Hydrological models are always composed of multiple components that represent processes key to intended model applications. When a process can be simulated by multiple conceptual-mathematical models (process models), model uncertainty in representing the process arises. While global sensitivity analysis methods have been widely used for identifying important processes in hydrologic modeling, the existing methods consider only parametric uncertainty but ignore the model uncertainty for process representation. To address this problem, this study develops a new method to probe multimodel process sensitivity by integrating the model averaging methods into the framework of variance-based global sensitivity analysis, given that the model averagingmore » methods quantify both parametric and model uncertainty. A new process sensitivity index is derived as a metric of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and model parameters. For demonstration, the new index is used to evaluate the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that converting precipitation to recharge, and the geology process is also simulated by two models of different parameterizations of hydraulic conductivity; each process model has its own random parameters. The new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less

Model-free aftershock forecasts constructed from similar sequences in the past

NASA Astrophysics Data System (ADS)

van der Elst, N.; Page, M. T.

2017-12-01

The basic premise behind aftershock forecasting is that sequences in the future will be similar to those in the past. Forecast models typically use empirically tuned parametric distributions to approximate past sequences, and project those distributions into the future to make a forecast. While parametric models do a good job of describing average outcomes, they are not explicitly designed to capture the full range of variability between sequences, and can suffer from over-tuning of the parameters. In particular, parametric forecasts may produce a high rate of "surprises" - sequences that land outside the forecast range. Here we present a non-parametric forecast method that cuts out the parametric "middleman" between training data and forecast. The method is based on finding past sequences that are similar to the target sequence, and evaluating their outcomes. We quantify similarity as the Poisson probability that the observed event count in a past sequence reflects the same underlying intensity as the observed event count in the target sequence. Event counts are defined in terms of differential magnitude relative to the mainshock. The forecast is then constructed from the distribution of past sequences outcomes, weighted by their similarity. We compare the similarity forecast with the Reasenberg and Jones (RJ95) method, for a set of 2807 global aftershock sequences of M≥6 mainshocks. We implement a sequence-specific RJ95 forecast using a global average prior and Bayesian updating, but do not propagate epistemic uncertainty. The RJ95 forecast is somewhat more precise than the similarity forecast: 90% of observed sequences fall within a factor of two of the median RJ95 forecast value, whereas the fraction is 85% for the similarity forecast. However, the surprise rate is much higher for the RJ95 forecast; 10% of observed sequences fall in the upper 2.5% of the (Poissonian) forecast range. The surprise rate is less than 3% for the similarity forecast. The similarity forecast may be useful to emergency managers and non-specialists when confidence or expertise in parametric forecasting may be lacking. The method makes over-tuning impossible, and minimizes the rate of surprises. At the least, this forecast constitutes a useful benchmark for more precisely tuned parametric forecasts.

True Density Prediction of Garlic Slices Dehydrated by Convection.

PubMed

López-Ortiz, Anabel; Rodríguez-Ramírez, Juan; Méndez-Lagunas, Lilia

2016-01-01

Physiochemical parameters with constant values are employed for the mass-heat transfer modeling of the air drying process. However, structural properties are not constant under drying conditions. Empirical, semi-theoretical, and theoretical models have been proposed to describe true density (ρp). These models only consider the ideal behavior and assume a linear relationship between ρp and moisture content (X); nevertheless, some materials exhibit a nonlinear behavior of ρp as a function of X with a tendency toward being concave-down. This comportment, which can be observed in garlic and carrots, has been difficult to model mathematically. This work proposes a semi-theoretical model for predicting ρp values, taking into account the concave-down comportment that occurs at the end of the drying process. The model includes the ρs dependency on external conditions (air drying temperature (Ta)), the inside temperature of the garlic slices (Ti ), and the moisture content (X) obtained from experimental data on the drying process. Calculations show that the dry solid density (ρs ) is not a linear function of Ta, X, and Ti . An empirical correlation for ρs is proposed as a function of Ti and X. The adjustment equation for Ti is proposed as a function of Ta and X. The proposed model for ρp was validated using experimental data on the sliced garlic and was compared with theoretical and empirical models that are available in the scientific literature. Deviation between the experimental and predicted data was determined. An explanation of the nonlinear behavior of ρs and ρp in the function of X, taking into account second-order phase changes, are then presented. © 2015 Institute of Food Technologists®

Uncertainty importance analysis using parametric moment ratio functions.

PubMed

Wei, Pengfei; Lu, Zhenzhou; Song, Jingwen

2014-02-01

This article presents a new importance analysis framework, called parametric moment ratio function, for measuring the reduction of model output uncertainty when the distribution parameters of inputs are changed, and the emphasis is put on the mean and variance ratio functions with respect to the variances of model inputs. The proposed concepts efficiently guide the analyst to achieve a targeted reduction on the model output mean and variance by operating on the variances of model inputs. The unbiased and progressive unbiased Monte Carlo estimators are also derived for the parametric mean and variance ratio functions, respectively. Only a set of samples is needed for implementing the proposed importance analysis by the proposed estimators, thus the computational cost is free of input dimensionality. An analytical test example with highly nonlinear behavior is introduced for illustrating the engineering significance of the proposed importance analysis technique and verifying the efficiency and convergence of the derived Monte Carlo estimators. Finally, the moment ratio function is applied to a planar 10-bar structure for achieving a targeted 50% reduction of the model output variance. © 2013 Society for Risk Analysis.

A Backward-Lagrangian-Stochastic Footprint Model for the Urban Environment

NASA Astrophysics Data System (ADS)

Wang, Chenghao; Wang, Zhi-Hua; Yang, Jiachuan; Li, Qi

2018-02-01

Built terrains, with their complexity in morphology, high heterogeneity, and anthropogenic impact, impose substantial challenges in Earth-system modelling. In particular, estimation of the source areas and footprints of atmospheric measurements in cities requires realistic representation of the landscape characteristics and flow physics in urban areas, but has hitherto been heavily reliant on large-eddy simulations. In this study, we developed physical parametrization schemes for estimating urban footprints based on the backward-Lagrangian-stochastic algorithm, with the built environment represented by street canyons. The vertical profile of mean streamwise velocity is parametrized for the urban canopy and boundary layer. Flux footprints estimated by the proposed model show reasonable agreement with analytical predictions over flat surfaces without roughness elements, and with experimental observations over sparse plant canopies. Furthermore, comparisons of canyon flow and turbulence profiles and the subsequent footprints were made between the proposed model and large-eddy simulation data. The results suggest that the parametrized canyon wind and turbulence statistics, based on the simple similarity theory used, need to be further improved to yield more realistic urban footprint modelling.

Synthesis and Analysis of Custom Bi-directional Reflectivity Distribution Functions in DIRSIG

NASA Astrophysics Data System (ADS)

Dank, J.; Allen, D.

2016-09-01

The bi-directional reflectivity distribution (BRDF) function is a fundamental optical property of materials, characterizing important properties of light scattered by a surface. For accurate radiance calculations using synthetic targets and numerical simulations such as the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model, fidelity of the target BRDFs is critical. While fits to measured BRDF data can be used in DIRSIG, obtaining high-quality data over a large spectral continuum can be time-consuming and expensive, requiring significant investment in illumination sources, sensors, and other specialized hardware. As a consequence, numerous parametric BRDF models are available to approximate actual behavior; but these all have shortcomings. Further, DIRSIG doesn't allow direct visualization of BRDFs, making it difficult for the user to understand the numerical impact of various models. Here, we discuss the innovative use of "mixture maps" to synthesize custom BRDFs as linear combinations of parametric models and measured data. We also show how DIRSIG's interactive mode can be used to visualize and analyze both available parametric models currently used in DIRSIG and custom BRDFs developed using our methods.

Trial-dependent psychometric functions accounting for perceptual learning in 2-AFC discrimination tasks.

PubMed

Kattner, Florian; Cochrane, Aaron; Green, C Shawn

2017-09-01

The majority of theoretical models of learning consider learning to be a continuous function of experience. However, most perceptual learning studies use thresholds estimated by fitting psychometric functions to independent blocks, sometimes then fitting a parametric function to these block-wise estimated thresholds. Critically, such approaches tend to violate the basic principle that learning is continuous through time (e.g., by aggregating trials into large "blocks" for analysis that each assume stationarity, then fitting learning functions to these aggregated blocks). To address this discrepancy between base theory and analysis practice, here we instead propose fitting a parametric function to thresholds from each individual trial. In particular, we implemented a dynamic psychometric function whose parameters were allowed to change continuously with each trial, thus parameterizing nonstationarity. We fit the resulting continuous time parametric model to data from two different perceptual learning tasks. In nearly every case, the quality of the fits derived from the continuous time parametric model outperformed the fits derived from a nonparametric approach wherein separate psychometric functions were fit to blocks of trials. Because such a continuous trial-dependent model of perceptual learning also offers a number of additional advantages (e.g., the ability to extrapolate beyond the observed data; the ability to estimate performance on individual critical trials), we suggest that this technique would be a useful addition to each psychophysicist's analysis toolkit.

Hbim to VR. Semantic Awareness and Data Enrichment Interoperability for Parametric Libraries of Historical Architecture

NASA Astrophysics Data System (ADS)

Quattrini, R.; Battini, C.; Mammoli, R.

2018-05-01

Recently we assist to an increasing availability of HBIM models rich in geometric and informative terms. Instead, there is still a lack of researches implementing dedicated libraries, based on parametric intelligence and semantically aware, related to the architectural heritage. Additional challenges became from their portability in non-desktop environment (such as VR). The research article demonstrates the validity of a workflow applied to the architectural heritage, which starting from the semantic modeling reaches the visualization in a virtual reality environment, passing through the necessary phases of export, data migration and management. The three-dimensional modeling of the classical Doric order takes place in the BIM work environment and is configured as a necessary starting point for the implementation of data, parametric intelligences and definition of ontologies that exclusively qualify the model. The study also enables an effective method for data migration from the BIM model to databases integrated into VR technologies for AH. Furthermore, the process intends to propose a methodology, applicable in a return path, suited to the achievement of an appropriate data enrichment of each model and to the possibility of interaction in VR environment with the model.

The mitochondrial toxin, 3-nitropropionic acid, induces extracellular Zn2+ accumulation in rat hippocampus slices.

PubMed

Wei, Guo; Hough, Christopher J; Sarvey, John M

2004-11-11

3-nitropropionic acid (3-NPA), a suicide inhibitor of succinate dehydrogenase (SDH; complex II), has been used to provide useful experimental models of Huntington's disease (HD) and "chemical hypoxia" in rodents. The trace ion Zn2+ has been shown to cause neurodegeneration. Employing real-time Newport Green fluorescence imaging of extracellular Zn2+, we found that 3-NPA (10-100 microM) caused a concentration-dependent increase in the concentration of extracellular Zn2+ ([Zn2+]o) in acute rat hippocampus slices. This increase in [Zn2+]o was abolished by 10 mM CaEDTA. The increase of [Zn2+]o was also accompanied by a rapid increase of cytoplasmic-free Zn2+ concentration ([Zn2+]i). The induction of Zn2+ release by 3-MPA in hippocampus slices points to a potential mechanism by which 3-NPA might induce neurodegeneration.

Targeting neurotransmitter receptors with nanoparticles in vivo allows single-molecule tracking in acute brain slices

NASA Astrophysics Data System (ADS)

Varela, Juan A.; Dupuis, Julien P.; Etchepare, Laetitia; Espana, Agnès; Cognet, Laurent; Groc, Laurent

2016-03-01

Single-molecule imaging has changed the way we understand many biological mechanisms, particularly in neurobiology, by shedding light on intricate molecular events down to the nanoscale. However, current single-molecule studies in neuroscience have been limited to cultured neurons or organotypic slices, leaving as an open question the existence of fast receptor diffusion in intact brain tissue. Here, for the first time, we targeted dopamine receptors in vivo with functionalized quantum dots and were able to perform single-molecule tracking in acute rat brain slices. We propose a novel delocalized and non-inflammatory way of delivering nanoparticles (NPs) in vivo to the brain, which allowed us to label and track genetically engineered surface dopamine receptors in neocortical neurons, revealing inherent behaviour and receptor activity regulations. We thus propose a NP-based platform for single-molecule studies in the living brain, opening new avenues of research in physiological and pathological animal models.

Test of the Chevallier-Polarski-Linder parametrization for rapid dark energy equation of state transitions

NASA Astrophysics Data System (ADS)

Linden, Sebastian; Virey, Jean-Marc

2008-07-01

We test the robustness and flexibility of the Chevallier-Polarski-Linder (CPL) parametrization of the dark energy equation of state w(z)=w0+wa(z)/(1+z) in recovering a four-parameter steplike fiducial model. We constrain the parameter space region of the underlying fiducial model where the CPL parametrization offers a reliable reconstruction. It turns out that non-negligible biases leak into the results for recent (z<2.5) rapid transitions, but that CPL yields a good reconstruction in all other cases. The presented analysis is performed with supernova Ia data as forecasted for a space mission like SNAP/JDEM, combined with future expectations for the cosmic microwave background shift parameter R and the baryonic acoustic oscillation parameter A.

Parametric spatiotemporal oscillation in reaction-diffusion systems.

PubMed

Ghosh, Shyamolina; Ray, Deb Shankar

2016-03-01

We consider a reaction-diffusion system in a homogeneous stable steady state. On perturbation by a time-dependent sinusoidal forcing of a suitable scaling parameter the system exhibits parametric spatiotemporal instability beyond a critical threshold frequency. We have formulated a general scheme to calculate the threshold condition for oscillation and the range of unstable spatial modes lying within a V-shaped region reminiscent of Arnold's tongue. Full numerical simulations show that depending on the specificity of nonlinearity of the models, the instability may result in time-periodic stationary patterns in the form of standing clusters or spatially localized breathing patterns with characteristic wavelengths. Our theoretical analysis of the parametric oscillation in reaction-diffusion system is corroborated by full numerical simulation of two well-known chemical dynamical models: chlorite-iodine-malonic acid and Briggs-Rauscher reactions.

Parametric spatiotemporal oscillation in reaction-diffusion systems

NASA Astrophysics Data System (ADS)

Ghosh, Shyamolina; Ray, Deb Shankar

2016-03-01

We consider a reaction-diffusion system in a homogeneous stable steady state. On perturbation by a time-dependent sinusoidal forcing of a suitable scaling parameter the system exhibits parametric spatiotemporal instability beyond a critical threshold frequency. We have formulated a general scheme to calculate the threshold condition for oscillation and the range of unstable spatial modes lying within a V-shaped region reminiscent of Arnold's tongue. Full numerical simulations show that depending on the specificity of nonlinearity of the models, the instability may result in time-periodic stationary patterns in the form of standing clusters or spatially localized breathing patterns with characteristic wavelengths. Our theoretical analysis of the parametric oscillation in reaction-diffusion system is corroborated by full numerical simulation of two well-known chemical dynamical models: chlorite-iodine-malonic acid and Briggs-Rauscher reactions.

Augmented Reality Robot-assisted Radical Prostatectomy: Preliminary Experience.

PubMed

Porpiglia, Francesco; Fiori, Cristian; Checcucci, Enrico; Amparore, Daniele; Bertolo, Riccardo

2018-05-01

To present our preliminary experience with augmented reality robot-assisted radical prostatectomy (AR-RARP). From June to August 2017, patients candidate to RARP were enrolled and underwent high-resolution multi-parametric magnetic resonance imaging (1-mm slices) according to dedicated protocol. The obtained three-dimensional (3D) reconstruction was integrated in the robotic console to perform AR-RARP. According to the staging at magnetic resonance imaging or reconstruction, in case of cT2 prostate cancer, intrafascial nerve sparing (NS) was performed: a mark was placed on the prostate capsule to indicate the virtual underlying intraprostatic lesion; in case of cT3, standard NS AR-RARP was scheduled with AR-guided biopsy at the level of suspected extracapsular extension (ECE). Prostate specimens were scanned to assess the 3D model concordance. Sixteen patients underwent intrafascial NS technique (cT2), whereas 14 underwent standard NS+ selective biopsy of suspected ECE (cT3). Final pathology confirmed clinical staging. Positive surgical margins' rate was 30% (no positive surgical margins in pT2). In patients whose intraprostatic lesions were marked, final pathology confirmed lesion location. In patients with suspected ECE, AR-guided selective biopsies confirmed the ECE location, with 11 of 14 biopsies (78%) positive for prostate cancer. Prostate specimens were scanned with finding of a good overlap. The mismatch between 3D reconstruction and scanning ranged from 1 to 5 mm. In 85% of the entire surface, the mismatch was <3 mm. In our preliminary experience, AR-RARP seems to be safe and effective. The accuracy of 3D reconstruction seemed to be promising. This technology has still limitations: the virtual models are manually oriented and rigid. Future collaborations with bioengineers will allow overcoming these limitations. Copyright © 2018 Elsevier Inc. All rights reserved.

Representation of deformable motion for compression of dynamic cardiac image data

NASA Astrophysics Data System (ADS)

Weinlich, Andreas; Amon, Peter; Hutter, Andreas; Kaup, André

2012-02-01

We present a new approach for efficient estimation and storage of tissue deformation in dynamic medical image data like 3-D+t computed tomography reconstructions of human heart acquisitions. Tissue deformation between two points in time can be described by means of a displacement vector field indicating for each voxel of a slice, from which position in the previous slice at a fixed position in the third dimension it has moved to this position. Our deformation model represents the motion in a compact manner using a down-sampled potential function of the displacement vector field. This function is obtained by a Gauss-Newton minimization of the estimation error image, i. e., the difference between the current and the deformed previous slice. For lossless or lossy compression of volume slices, the potential function and the error image can afterwards be coded separately. By assuming deformations instead of translational motion, a subsequent coding algorithm using this method will achieve better compression ratios for medical volume data than with conventional block-based motion compensation known from video coding. Due to the smooth prediction without block artifacts, particularly whole-image transforms like wavelet decomposition as well as intra-slice prediction methods can benefit from this approach. We show that with discrete cosine as well as with Karhunen-Lo`eve transform the method can achieve a better energy compaction of the error image than block-based motion compensation while reaching approximately the same prediction error energy.